vvEPA
United States
Environmental Protection
Agency
Online Source Water Quality Monitoring
For Water Quality Surveillance and Response Systems
Office of Water (MC 140)
EPA 817-B-16-003
September 2016
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Disclaimer
The Water Security Division of the Office of Ground Water and Drinking Water of the EPA has reviewed
and approved this document for publication. This document does not impose legally binding requirements
on any party. The information in this document is intended solely to recommend or suggest and does not
imply any requirements. Neither the United States Government nor any of its employees, contractors or
their employees make any warranty, expressed or implied, or assumes any legal liability or responsibility
for any third party's use of any information, product, or process discussed in this document, or represents
that its use by such party would not infringe on privately owned rights. Mention of trade names or
commercial products does not constitute endorsement or recommendation for use.
Questions concerning this document should be addressed to WQ SRS@epa.gov or the following
contacts:
Steve Allgeier
EPA Water Security Division
26 West Martin Luther King Drive
Mail Code 140
Cincinnati, OH 45268
(513) 569-7131
Allgeier. Steve@epa. gov
or
Matt Umberg
EPA Water Security Division
26 West Martin Luther King Drive
Mail Code 140
Cincinnati, OH 45268
(513) 569-7357
Umberg .Matt@epa. gov
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Acknowledgements
The document was developed by the EPA Water Security Division, with additional support provided
under EPA contract EP-C-15-012. The following individuals contributed to the development of this
document:
Joel Allen, EPA, Office of Research and Development
Steve Allgeier, EPA, Water Security Division
Erin Cummings, CH2M
Jennifer Liggett, CH2M
Alan Lindquist, EPA, Office of Research and Development
Christopher Macintosh, CH2M
Kenneth Thompson, CH2M
Matt Umberg, EPA, Water Security Division
Peer review of this document was provided by the following individuals:
Alison Aminto, Philadelphia Water Department
Kelly Anderson, Philadelphia Water Department
Kevin R. Gertig, City of Fort Collins Utilities
Terra Haxton, EPA, National Homeland Security Research Center
Richard Lieberman, EPA, Standards and Risk Management Division
Kevin Linder, Aurora Water
Howard Rubin, EPA, Drinking Water Protection Division
Debabrata Sahoo, Woolpert Inc.
Rick Scott, Seattle Public Utilities
David Travers, EPA, Water Security Division
Tom Waters, EPA, Standards and Risk Management Division
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Table of Contents
List of Figures iv
List of Tables v
Abbreviations vi
Section 1: Introduction 1
1.1 Overview of Source Water Monitoring 3
1.2 Purpose and Overview of this Document 5
Section 2: Framework for Designing a Source Water Monitoring System 6
2.1 Establish Design Goals 6
2.2 Establish Performance Objectives 8
2.3 Conduct a Risk Assessment 10
2.4 Design the SWM System 14
Section 3: Source Water Monitoring Locations 17
3.1 SWM Locations to Support Treatment Process Optimization 18
3.2 SWM Locations to Detect Contamination Incidents 19
3.3 SWM Locations to Monitor Threats to Long-Term Water Quality 22
Section 4: Source Water Monitoring Parameters 23
4.1 Useful SWM Parameters 23
4.2 Parameter Selection 25
Section 5: Source Water Monitoring Stations 32
5.1 Instrumentation 33
5.2 Sampling 33
5.3 Power Supply and Distribution 34
5.4 Communications 35
5.5 Packaging 35
Section 6: Information Management and Analysis 36
6.1 Analysis and Visualization Techniques 36
6.2 SWM Information Management System Architecture 44
6.3 SWM Information Management System Requirements 47
Section 7: Investigation and Response Procedures 50
7.1 Procedures for Investigation of and Response to SWM Alerts 50
7.2 Procedures for Investigation of and Response to Long-Term Source Water Quality Changes ...62
7.3 Implementation of SWM Procedures 65
Section 8: Example of SWM Design 67
8.1 Design Approach 67
8.2 SWM Location Selection 71
8.3 SWMParameter Selection 72
8.4 SWM Station Design 74
8.5 Information Management and Analysis 76
8.6 Investigation and Response Procedures 76
Section 9: Case Studies 78
9.1 Greenville Water 78
9.2 City of Fort Collins Utilities 79
9.3 Clermont County Water Resources Division 81
9.4 West Virginia American Water 83
9.5 Bratislava Water Company 84
9.6 Susquehanna River Basin Commission Early Warning System 86
9.7 River Alert Information Network 88
9.8 Philadelphia Water Department 90
Resources 95
Glossary 102
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List of Figures
Figure 1-1. Incorporation of Source Water Monitoring into an SRS 2
Figure 1-2. Example Schematic of Source Water Monitoring 3
Figure 1-3. SWM Location vs. SWM Station 4
Figure 2-1. Source Water Monitoring Implementation Framework 6
Figure 2-2. Source Water Monitoring Design Elements 14
Figure 3-1. SWM Location Selected to Support Treatment Process Optimization 18
Figure 3-2. A Single Upstream SWM Location to Monitor Multiple SW Threats 20
Figure 3 -3. Multiple Upstream SWM Locations to Monitor Multiple SW Threats 21
Figure 3-4. SWM Locations to Monitor Threats to Long-Term Water Quality 22
Figure 5-1. Functional Block Diagram of an SWM Station 32
Figure 6-1. Time-Series Plots and Thresholds for Treatment Process Optimization 37
Figure 6-2. Time-Series Plots and Thresholds for Detection of Contamination Incidents 39
Figure 6-3. SWM Display showing Alert Status and Time-Series Data for an SWM Location 40
Figure 6-4. Text Message and Dashboard Alert Notifications 41
Figure 6-5. Example Plots of Monthly Average and Yearly Average for Source Water TOC 43
Figure 6-6. Geospatial Presentation Showing the Change in TOC over a 10-Year Period 44
Figure 6-7. SWM Information Management as an Extension of an Existing SCADA Architecture 45
Figure 6-8. Example of a Dedicated SWM Information Management System 46
Figure 7-1. Example of an SWM Alert Investigation Process Flow Diagram 51
Figure 7-2. Example Treatment Optimization Procedure Flow Diagram 55
Figure 7-3. Example Source Water Contamination Incident Response Decision Tree 58
Figure 8-1. Location of High-Priority SW Threats for Anytown Water 68
Figure 8-2. SWM Locations for Anytown Water 71
Figure 9-1. Greenville Water SWM Locations 78
Figure 9-2. Example of Greenville Water SCADA System Screen for SWM Data 79
Figure 9-3. West Virginia American Water Source Water Monitoring Station 83
Figure 9-4. Screenshot of West Virginia American Water Source Water Monitoring Data 84
Figure 9-5. Bratislava Water Company SWM Station 85
Figure 9-6. Bratislava Water Company SWM Alert Notification 85
Figure 9-7. Susquehanna River Basin Region 86
Figure 9-8. Susquehanna River Basin Commission SWM Station 87
Figure 9-9. RAIN SWM Station 88
Figure 9-10. Overview of RAIN SWM Locations 89
Figure 9-11. RAIN Interactive Display 90
Figure 9-12. Overview of PWD's Source Watersheds and Drinking Water Intakes 91
Figure 9-13. Example of SWM Data Visualization on EWS Homepage 93
Figure 9-14. Philadelphia Water Resources Monitoring Program Website User Interface 94
iv
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List of Tables
Table 2-1. Scoring Considerations for Risk Assessment Parameters by Design Goal 13
Table 4-1. Overview of SWMParameters 23
Table 4-2. SWMParameters that Support Treatment Process Optimization 26
Table 4-3. SWM Parameters that Support Detection of Contamination Incidents 27
Table 4-4. SWM Parameters that Support Monitoring of Long-Term Water Quality 29
Table 5-1. Comparison of Key Attributes of Two Sample Measurement Options 34
Table 6-1. Statistical Analysis Techniques for Characterizing Long-Term Water Quality 42
Table 6-2. Examples of SWM Information Management Functional Requirements 48
Table 6-3. Examples of SWM Information Management System Technical Requirements 49
Table 7-1. Example SWM Alert Investigation Process Description 52
Table 7-2. Typical Information Resources Useful during the Investigation of an SWM Alert 53
Table 7-3. Common Causes of Invalid and Valid SWM Alerts 54
Table 7-4. Example Treatment Process Optimization Procedure Description 56
Table 7-5. Example Source Water Contamination Incident Response Decision Tree Description 59
Table 7-6. Example Roles and Responsibilities during SWM Alert Investigations
and Treatment Optimization 61
Table 7-7. Example Roles and Responsibilities during Response to Source Water Contamination 62
Table 7-8. Typical Information Resources Useful to the Investigation of Sustained Change
in Source Water Quality 63
Table 7-9. Example Roles and Responsibilities for Monitoring Threats to Long-Term Water Quality 65
Table 8-1. High-Priority SW Threats of Source Water Contamination for Anytown Water 68
Table 8-2. High-Priority SW Threats to Long-Term Source Water Quality for Anytown Water 70
Table 8-3. Parameters Selected to Support Treatment Process Optimization for Anytown Water 72
Table 8-4. Parameter Selected to Detect Contamination Incidents and Monitor Threats
to Long-Term Water Quality for Anytown Water 73
Table 8-5. Final SWM Station Designs for Anytown Water 75
Table 9-1. Fort Collins Utilities SWM Stations 80
Table 9-2. Clermont County Water Resources Division SWM Stations 82
v
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Abbreviations
ADS Anomaly Detection System
ANSI American National Standards Institute
ASME-ITI American Society of Mechanical Engineers Innovative Technologies Institute
AWWA American Water Works Association
CERCLIS Comprehensive Environmental Response, Compensation, and Liability Information
System
CH2M CH2M Hill, Inc.
CIO Chief Information Officer
CM Consequence Management
CREAT Climate Resilience Evaluation and Awareness Tool
DBP Disinfection Byproduct
DO Dissolved Oxygen
DOC Dissolved Organic Carbon
DWMAPS Drinking Water Mapping Application to Protect Source Waters
ECHO Enforcement and Compliance History Online
EPA United States Environmental Protection Agency
ERP Emergency Response Plan
EWS Early Warning System
GAC Granular Activated Carbon
GIS Geographic Information System
HAB Harmful Algal Bloom
HMI Human Machine Interface
IT Information Technology
LIMS Laboratory Information Management System
NEMA National Electrical Manufacturers Association
NH3 Ammonia
NH/ Ammonium
N03 Nitrate
N02 Nitrite
NPDES National Pollutant Discharge Elimination System
NTU Nephelometric turbidity units
NWIS National Water Information System
ORP Oxidation-Reduction Potential
OWQM Online Water Quality Monitoring
PAC Powdered Activated Carbon
PLC Programmable Logic Controller
PWD Philadelphia Water Department
RAIN River Alert Information Network
RCRAInfo Resource Conservation and Recovery Act Information
vi
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S&A
Sampling and Analysis
SCADA
Supervisory Control and Data Acquisition
SDWA
Safe Water Drinking Act
SRBC
Susquehanna River Basin Commission
SRS
Water Quality Surveillance and Response System
SW Threat
Source Water Threat
swc
Source Water Collaborative
SWM
Source Water Monitoring
TOC
Total Organic Carbon
TRI
Toxic Release Inventory
TSCA
Toxic Substances Control Act
USGS
United States Geological Survey
uv
Ultra-violet
VSAT
Vulnerability Self-Assessment Tool
WVAW
West Virginia American Water
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Online Source Water Quality Monitoring
Section 1: Introduction
Source water1 is water from natural resources (e.g., aquifers, lakes, rivers, and streams) that is treated to
produce drinking water for a community. Source water monitoring (SWM) involves the use of online
water quality instruments for real-time measurement of water quality in a source water. The
understanding gained through SWM enables drinking water utilities to more efficiently treat the source
water, identify significant changes in water quality, implement appropriate treatment strategies, and take
actions to protect the source water for its intended use.
SWM can be implemented as a stand-alone monitoring program, or it can be incorporated into a Water
Quality Surveillance and Response System (SRS). An SRS is a framework developed by the United
States Environmental Protection Agency (EPA) to support monitoring and management of water quality
from source to tap. The system consists of one or more components that provide information to guide
drinking water utility operations and enhance a utility's ability to quickly detect and respond to water
quality changes. An SRS overview can be found in the SRS Primer (EPA. 2015a). Figure 1-1 illustrates
the manner in which SWM can be integrated into an SRS.
1 Words in bold italic font are terms defined in the Glossary at the end of this document.
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Online Source Water Quality Monitoring
SURVEILLANCE
Online Water Quality Monitoring
s \
Distribution
System Monitoring
/ \
Source Water
Monitoring
4
Treatment
Adjustment
Source Water
Management
Real-Time Data Access,
Visualization, and Analysis
_
Enhanced
Security
Monitoring
Public Health
Surveillance
Customer
Complaint
Surveillance
WATER
QUALITY
CHANGES
;?
M
V V ^
SB
Sampling &
Analysis
Traditional SRS components are shown in boxes
with a black border, and SWM surveillance and
response activities are shown with a red border.
Figure 1-1. Incorporation of Source Water Monitoring into an SRS
The design of an SRS is flexible and can include any combination of components shown in Figure 1-1.
However, it is recommended that all SRS designs include at least one surveillance component and basic
capabilities for Sampling and Analysis (S&A) and Consequence Management (CM). S&A is important
because the surveillance components of an SRS, including SWM, typically provide only a general
indication of a potential water quality problem; S&A establishes capabilities for confirming or ruling out
specific contaminants or contaminant classes. CM establishes procedures and relationships with response
partners for responding to serious water quality problems such as contamination.
The guidance provided in this document treats SWM as an application of the Online Water Quality
Monitoring (OWQM) component within an SRS. This allows many of the elements of an SRS, such as
information management systems, visualization tools, S&A capabilities, and contamination incident
response plans, to be leveraged to support SWM operations. Furthermore, there is a substantial body of
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Online Source Water Quality Monitoring
SRS guidance that can support the design of SWM. These resources are cited throughout the document,
where applicable.
1.1 Overview of Source Water Monitoring
Treatment plants are designed and operated to treat contaminants known to occur in source water, comply
with drinking water standards, and meet customer expectations. Unanticipated changes quality or the
presence of unusual contaminants in source water can
adversely impact the ability of a utility to meet these
objectives. SWM can improve a utility 's ability to detect
variations in source water quality.
SWM involves the measurement of various water quality
parameters in source water or watersheds. An SWM
location is the site in a waterbody where water is sampled
for measurement. SWM locations are selected relative to
control points, which are locations where a treatment
process can be modified (e.g., addition of pretreatment
chemicals) or a response action can be implemented (e.g.,
closing an intake). SWM stations are installed at or near
SWM locations and consist of online water quality
instruments that measure parameters and communications
equipment that transmits data to a central location, such as a
utility control center. A schematic of an example SWM
system is shown in Figure 1-2.
Reasons to Implement Source
Water Monitoring
~
Provide information to facilitate
protection of the public water supply
for all intended uses
p
Observe long-term trends in source
water quaiity to prepare for future
challenges or regulations
L o
Detect and respond to contamination
incidents
D
Optimize treatment processes to
improve finished water quality and
reduce costs
|p
Develop information that supports
regulatory compliance
~
Investigate and identify pollution
sources and potentially responsible
parties
Media
Filtration
^^ฆDisinfection
Off-Stream
Storage
Pretreatment
Control
Center
Coagulation/
Sedimentation
Distribution
System
X
iWM Location
Control Point
Monitoring
Control/Feedback
Figure 1-2. Example Schematic of Source Water Monitoring
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Online Source Water Quality Monitoring
The physical location where the SWM station is installed may not be the same as the SWM location. For
example, source water can be pumped from an SWM location to an SWM station installed at a different
site. Figure 1-3 shows an SWM station installed at the SWM location (Exhibit A) and an SWM station
installed away from the SWM location (Exhibit B).
Exhibit A
SWM Station
/iAi
o
SWM Location
Exhibit B
Sample Drawn from
Source Water
SWM Station
Piping to Flow-cell at SWM Station
SWM Location
Figure 1-3. SWM Location vs. SWM Station
The scale of an SWM system can extend from an individual drinking water utility monitoring at its
treatment plant intake to systems that monitor an entire watershed. The latter typically involve multiple
organizations to provide coverage of a large area (e.g., an entire watershed or river basin) and share the
cost required to install, operate, and maintain the system. Benefits of a watershed-scale SWM system
include the ability to achieve extensive geographic coverage and maintain more monitoring locations than
could be maintained by any single organization. However, such systems require sustained commitment by
all partners and can present challenges if partner organizations decide to end their support.
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Online Source Water Quality Monitoring
1.2 Purpose and Overview of this Document
This document provides guidance on the design of an SWM system that is based on best practices and
lessons learned from existing SWM systems. It introduces key concepts, provides examples, and directs
the reader to additional resources for guidance on specific technical elements of SWM.
This document is primarily intended for use by water sector
professionals, but might also be useful to organizations or
individuals with an interest in source water quality. These
additional stakeholders might include those responsible for
assuring the quality of water for recreational purposes, those
involved in aquaculture or other commercial ventures, those
responsible for environmental protection, and those concerned
with the quality of natural resources.
The remaining sections of this document cover the following
topics:
Section 2 describes a framework for designing an SWM system, introduces three high-level
design goals for SWM, and presents a process for identifying and prioritizing potential source
water threats.
Section 3 provides guidance on the selection of monitoring locations to support each of the three
design goals for SWM.
Section 4 provides guidance on selecting water quality parameters to achieve each of the three
design goals for SWM.
Section 5 provides guidance on the selection of monitoring equipment and the design of SWM
stations.
Section 6 provides guidance on the development of an information management system and
analysis techniques to support each of the three SWM design goals.
Section 7 provides guidance on developing investigation and response procedures to support
SWM.
Section 8 presents an example of the SWM design process described in the previous sections.
Section 9 presents SWM case studies that illustrate a variety of designs and implementation
approaches.
Resources presents a comprehensive list of documents, tools, and other sources cited in this
document, including a summary of and link to each resource.
Glossary provides definitions of terms used in this document, which are indicated by bold, italic
font at first use in the body of the document.
Applicability of Guidance
The methodology presented in
this document can be used to
design SWM systems that vary
widely in complexityfrom a
simple system monitoring a
single parameter at a single
location to a system that
monitors multiple parameters at
several locations in a watershed.
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Online Source Water Quality Monitoring
Section 2: Framework for
Designing a Source Water Monitoring System
The design process for SWM follows the principles of project management and master planning that are
described in Sections 2 and 3 of Guidance for Developing Integrated Water Quality Surveillance and
Response Systems (EPA. 2015b) (referred to throughout this document as SRS Integration Guidance).
This section presents a framework for implementing SWM, as shown in Figure 2-1. While depicted as a
linear process, in practice it is iterative. Decisions or findings in downstream steps can require that earlier
steps be revisited.
Establish
Design Goals
Optimize treatment
processes
Detect contamination
incidents
Monitor threats to
long-term water
quality
Establish
Performance
Objectives
Operational reliability
Information reliability
Sustainability
Conduct Risk
Assessment
Identify and
characterize SW
threats
Prioritize SW threats
based on their
relative risk
Design the
SWM System
Select SWM locations
Select SWM
parameters
Design SWM stations
Develop information
management and
analysis tools
Develop investigation
and response
procedures
Figure 2-1. Source Water Monitoring implementation Framework
2.1 Establish Design Goals
Design goals are the specific benefits a utility expects to achieve by implementing SWM. The
establishment of design goals is critical to ensuring that SWM will be useful to the utility.
Three common, high-level design goals for SWM are to (1) optimize treatment processes, (2) detect
contamination incidents, and (3) monitor threats to long-term water quality. These design goals are
presented and discussed in order of increasing complexity, with complexity generally defined in terms of
the number of parameters monitored, the number of SWM locations, and the area covered by SWM
locations. SWM designed for treatment process optimization is simplest in that it requires one to a few
SWM locations for specific parameters that are directly related to the performance of treatment processes.
Designing for detection of contamination incidents generally requires the addition of upstream SWM
locations and parameters capable of detecting a wider range of water quality changes along with more
sophisticated data analysis methods. Even more SWM locations may be necessary to monitor threats to
long-term water quality.
These high-level design goals cover most SWM applications. However, a utility planning to implement
SWM should first establish the overall purpose of SWM and the decisions that SWM data is intended to
support. This will inform the development of detailed design goals to guide SWM implementation.
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Online Source Water Quality Monitoring
Optimize Treatment Processes
SWM data can be used to optimize treatment processes by monitoring water quality parameter variations
that impact the performance of treatment processes, such as pH, turbidity, and total organic carbon
(TOC).
The primary decisions that guide the design of SWM to
optimize treatment processes include these:
Identify specific treatment targets. This decision
will guide the selection of parameters to monitor.
Examples might include removal of particulate
matter, removal of organic contaminants, or
removal of algal toxins.
Determine the treatment processes that support
these targets. This information will help identify
control points in the treatment plant that can be
adjusted based on the information generated by
SWM. For example, the following processes can
Factors to Consider
when Refining Design Goals
to Optimize Treatment Processes
~ Flexibility in utilization of the source,
such as withdrawal at different depths
at the intake, off-stream storage, etc.
~ Treatment process control points that
can be manipulated to handle variable
source water quality
~ Options to limit impact of poor quality
source water on treatment processes,
such as booms, pump and treat,
adsorptive barriers, diversion, etc.
be adjusted in response to a change in source water
quality: pretreatment with powdered activated carbon (PAC), pretreatment with permanganate,
coagulation/sedimentation, and disinfection.
Determine the time necessary to implement treatment process changes. This time period is
that between validation of a change in source water quality and adjustment of treatment processes
in response to that validated change. The time available will influence the selection of SWM
locations and the required frequency at which water quality instruments generate data.
Detect Contamination Incidents
SWM can be used to detect transient source water contamination incidents that may upset or pass through
a water treatment process. This includes detection of contamination resulting from accidents (e.g.,
chemical releases from spills on or near the source water), unusual discharges (e.g., untreated sewage
discharge), and natural events (e.g., seasonal algal blooms).
The primary decisions that guide the design of SWM to
detect contamination incidents include these:
Identify the specific types of contamination
incidents that SWM should be able to detect. A
risk assessment should be undertaken to develop a
prioritized list of source water threats (SW
threats) that have the potential to contaminate the
source water. This will guide the selection of both
parameters to monitor and SWM locations.
Evaluate the response options available to
mitigate the impacts of each type of
contamination incident identified. Consideration
should be given to both the efficacy of the
response actions in reducing the consequences of
contamination as well as the cost associated with
implementing the response actions. The cost of
Factors to Consider
when Refining Design Goals
to Detect Contamination Incidents
~
Characteristics of SW threats and their
associated contaminants
~
Likelihood of natural events such as
wildfires, floods, and harmful algal
blooms that could contaminate the
source water
~
Hydrologic parameters affecting
contaminant fate and transport
~
Limitations of existing treatment
processes to treat or remove identified
contaminants
~
Options for responding to various types
of contamination incidents
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Online Source Water Quality Monitoring
implementing a response action will influence the necessary reliability of the information
generated by SWM (i.e., more costly response actions will generally require a higher degree of
information reliability).
Determine the time necessary to implement response options. This is the time period between
detection and investigation of a water quality change and implementation of an effective
response. The time available from detection to response will influence the selection of SWM
locations and the necessary frequency of data generation and analysis.
Monitor Threats to Long-Term Water Quality
SWM can be used to monitor the impact of SW threats on long-term water quality in the source water and
surrounding watershed. SWM provides the information needed to assess the suitability of the source to
serve as a drinking water supply, provide recreational opportunities, and support a healthy ecosystem.
SWM can also be used to monitor the impacts of climate change on source water quality.
The primary decisions that guide the design of SWM to
support monitoring of threats to long-term water quality
include these:
Identify factors that influence long-term source
water quality. This understanding will guide the
selection of SWM parameters and locations. A risk
assessment can be conducted to identify and
prioritize SW threats to long-term water quality.
Identify stakeholders in maintaining source
water quality. Coordination with stakeholders can
provide opportunities to collect additional data and
identify other uses of the data collected.
Identify potential mitigation strategies.
Monitoring long-term trends in source water
quality can provide a better understanding of gradual changes in water quality and support
selection of strategies for maintaining acceptable source water quality.
Another factor to consider during SWM design is that a single incident can alter source water quality in a
number of ways over different time periods. As an example, consider a wildfire, which can produce a
high loading of silt and ash during runoff events immediately following the fire. This transient
contamination incident may require a utility to implement highly unusual, short-term treatment
modifications. Long-term effects of wildfires might include an increase in TOC loading for multiple
years, which would require sustained treatment plant optimization. Finally, long-term source water
quality monitoring can provide stakeholders with information that can be used to gauge the effectiveness
of watershed restoration efforts such as reseeding.
2.2 Establish Performance Objectives
Performance objectives and their associated metrics are measurable indicators of how well SWM meets
the design goals established by a utility. Throughout design, implementation, and operation of SWM, a
utility can use performance objectives determine whether the system is operating within acceptable
tolerances. While specific performance objectives should be developed by each utility in the context of its
unique design goals, common performance objectives are described as follows.
Factors to Consider
when Refining Design Goals
to Monitor Threats
to Long-Term Water Quality
~
Seasonal variations in source water
conditions such as temperature,
precipitation, and flow
~
Characteristics of SW threats and their
associated contaminants
~
Land use in the watershed
~
Projected impacts of climate change in
the region
~
Uses of the source water beyond a
drinking water supply
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Online Source Water Quality Monitoring
Operational Reliability
Operational reliability is the degree to which an SWM system is performing at a level capable of
achieving the established design goals. It depends on proper maintenance of equipment and information
management systems necessary to operate the system. Considerations for operational reliability include
accessibility of SWM stations for maintenance, suitability of water quality sensors to the chemistry and
quality of a source (e.g., turbidity, pH), environmental impact on SWM stations (e.g., source water
temperature, humidity, and ambient temperatures), and adequacy of training for personnel responsible for
maintaining the SWM equipment. Example metrics used to monitor operational reliability include the
following:
Percentage of time that the SWM system is fully operational
Average response time to correct equipment problems
Information Reliability
Information reliability is the degree to which information produced by an SWM station is of sufficient
quality to support decision-making. Specifically, utility personnel must be able to interpret the difference
between typical water quality variability and changes indicative of a water quality issue requiring a
response action or treatment process change. Considerations for information reliability include the
representativeness of the water monitored at each SWM location, compatibility of the sensors with the
water chemistry, sensor capabilities (e.g., detection limits), maintenance of sensors, and data analysis
methods.
Information reliability can be characterized through data quality objectives, which are metrics or criteria
that establish the quality and quantity of data needed to support decisions. Examples of data quality
objectives that might be considered for SWM include:
Data accuracy
Data completeness
Number of invalid alerts per month
Establishing data quality objectives is an element of quality control/quality assurance that is important for
any environmental monitoring program. Further information about quality assurance for online water
quality data can be found in Quality Assurance (ACRR) Matrix (ASW. 2010).
Sustainabilitv
Sustainability is the degree to which benefits derived from information generated by SWM justify the cost
and level of effort required for its implementation and operation. Benefits are largely determined by the
design goals that SWM data supports. For example, an annual reduction in chemical usage or sludge
production can be achieved due to more efficient chemical dosing guided by SWM data. Other benefits
may be difficult to quantify, such as increased confidence of utility managers and operators in their ability
to detect source water quality problems. However, these benefits should still be captured and described as
they are important to gauging the sustainability of the SWM system. Costs include the capital and
ongoing expenditures required to implement and operate the equipment and systems, as well as the effort
required to analyze the SWM data and investigate alerts. Example metrics for sustainability include the
following:
Improvements in finished water quality and operations due to treatment process optimization
Consequences avoided through early detection of and response to contamination incidents
Value of non-monetary benefits gained from the operation of SWM
Lifecycle cost to implement and maintain SWM
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Online Source Water Quality Monitoring
Risk Assessment Tool
EPA has developed the
Vulnerability Self-
Assessment Tool (VSAT)
(EPA. 2015c), which guides
a water utility through the
risk assessment process in
a manner consistent with
the J100 Standard.
2.3 Conduct a Risk Assessment
A risk assessment is a systematic process for analyzing and prioritizing threats to inform the selection and
implementation of risk mitigation strategies. The results of a risk
assessment can guide the design of SWM by ensuring that the resulting
system addresses the most serious threats. The most widely accepted
and broadly applicable risk assessment methodology for the water
sector is the J100 Standard (A WW A. 2010). In the context of this
guidance document, the J100 methodology is used to assign values to
the following three risk assessment parameters for each SW threat:
Likelihood is the probability that an SW threat will
contaminate the source water and can range in value from 0
(contamination will not occur) to 1 (contamination is certain to
occur). The likelihood value may be based on previous contamination incidents caused by the SW
threat (or similar SW threats) or on projections and models.
Vulnerability is the probability that a utility or its customers would be impacted by an SW threat
and can range in value from 0 (no adverse impact will occur) to 1 (adverse impact is certain to
occur). The vulnerability value is generally based on the ability of the utility to effectively
respond to an SW threat, preventing or mitigating consequences to utility infrastructure,
operations, and customers.
Consequences are the adverse effects of an incident experienced by a utility (e.g., damaged
infrastructure) or its customers (e.g., illness). Where possible, consequences are expressed in
terms of monetary damage, providing a standard measure of consequence across all threats.
However, it is not always possible to accurately monetize consequences, and values may need to
be derived from qualitative factors. In such cases consequences can be normalized such that the
SW threat with the greatest consequence has a value of 100 while the values for all other SW
threats are less than 100.
The values for these three risk parameters are used to calculate the overall risk score, as shown in
Equation 2-1.
R = L x V x C
Where:
R = Risk of a specific threat to a utility or its customers
L = Likelihood that a specific threat will occur (score range: 0 to 1)
V = Vulnerability of a utility to a specific threat (score range: 0 to 1)
C = Consequences of the specific threat (score range: 0 to 100)
Equation 2-1. Risk Equation
Identify and Characterize Potential SW Threats
To conduct a risk assessment, SW threats must first be identified and characterized. SW threats include
any facility, discharge, land use, weather event, or other feature within a watershed that has the potential
to degrade source water quality and impair its intended use. SW threats can be stationary or mobile.
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Stationary threats are present at fixed, known locations such as:
Chemical storage facilities (e.g., oil and gas storage facilities)
Industrial facilities that use chemicals (e.g., tanneries, automotive body shops, dry cleaners)
Agricultural facilities (e.g., concentrated animal feeding operations, large fertilized areas)
Urban areas (e.g., runoff over impervious contaminated surfaces)
Oil and natural gas extraction operations
Wastewater treatment plant outfalls
Stormwater outfalls
Mobile threats present a variable point of potential contaminant entry into the source water, making them
more difficult to monitor. Examples of mobile threats include:
Transportation corridors (e.g., vehicular traffic, rolling stock on railway tracks)
Watercraft (e.g., barges and other vessels)
Natural disasters (e.g., wildfires, floods, hurricanes, landslides)
A variety of resources are available to identify and characterize SW threats, some of which are described
below. Additional information about these resources, including where to find them, is available in the
Resources section.
State Primacy Agency Source Water Assessments provide an inventory of known and potential
SW threats within a state. This information can be used to identify known and potential sources
of contamination and to characterize the vulnerability of source water to these threats (EPA.
2016a).
Drinking Water Mapping Application to Protect Source Waters (DWMAPS) is a geographic
information system (GlS)-based tool developed by EPA that provides layers of spatially
referenced data using information from databases such as National Pollutant Discharge
Elimination System (NPDES); Enforcement and Compliance History Online (ECHO); Toxic
Release Inventory (TRI); Comprehensive Environmental Response, Compensation, and Liability
Information System (CERCLIS); Resource Conservation and Recovery Act Information
(RCRAInfo); and Toxic Substances Control Act (TSCA). DWMAPS provides information about
potential SW threats, including their locations and details of discharge permits (EPA. 2016b).
Land Use Maps are often developed and maintained by a city, county, or state. These maps may
be useful for identifying current and future potential SW threats, such as areas of urban or
commercial expansion.
Each SW threat identified should be characterized to the fullest extent possible, capturing information
such as the following:
Location of the SW threat and the distance from the threat to the source water
Owner or operator of the property or facility where the SW threat is located
Potential contaminants associated with the SW threat (e.g., chemicals stored on site, pesticides or
fertilizers applied to the land)
Volume or mass of potential contaminants stored at the location of an SW threat or discharge
rates from SW threats, such as outfalls
Characteristics of the potential contaminants stored at the location of an SW threat (e.g.,
solubility, toxicity), which may be available in material safety data sheets that are required to be
on file at the location where a chemical is stored or used
Estimates of contaminant dispersion and dilution in the source water during a contamination
incident from the SW threat (e.g., results from hydrology model simulations or tracer studies)
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Existing risk mitigation strategies to protect the source water from the threat (e.g., leak detection,
spill containment, runoff control)
Some of this information may not be available for all types of SW threats, but the characterization of each
SW threat should be as complete as possible. A detailed characterization of SW threats is useful not only
for the risk assessment, but also for selecting SWM parameters and locations, as well as for response
planning.
The process for identifying SW threats is the same for flowing water systems (e.g., rivers and streams),
and still water systems (e.g., ponds and lakes). Some aspects of this process also apply to groundwater
sources, which face some similar and unique risks as compared to surface water. The characteristics of the
source water will inform the identification of SW threats as well as the assignment of values to the risk
assessment parameters.
Prioritize Risk of Potential SW Threats
The risk assessment needs to provide a relative prioritization of the SW threats to ensure that SWM is
designed to focus on the highest priority SW threats within the available budget. As such, it is important
to assign values to each of the risk parameters in a consistent manner. For example, where SW threats are
identified that do not have appreciably different characteristics that would influence likelihood,
vulnerability, or consequence, the same or similar values should be assigned to the risk parameters for
these similar threats.
A risk assessment is useful for designing an SWM system to detect contamination incidents and/or
monitor threats to long-term water quality because it prioritizes the SW threats to be monitored. If the
SWM system is intended to meet both of these design goals, it may be useful to identify and prioritize
two sets of SW threats: (1) those that pose an acute risk to source water quality due to a contamination
incident and (2) those that pose a chronic risk to long-term water quality. This strategy ensures that the
SWM design will consider the highest priority SW threats to both short-term and long-term water quality.
A risk assessment is generally not used to optimize treatment processes because this design goal is
intended to meet specific treatment targets by adjusting treatment processes in response to typical source
water quality variability.
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The attributes of SW threats considered when assigning values to each risk assessment parameter will be
different when assessing risk for the design goals of detection of contamination incidents and monitoring
of threats to long-term water quality, as illustrated in Table 2-1.
Table 2-1. Scoring Considerations for Risk Assessment Parameters by Design Goal
Risk Assessment
Parameter
Scoring Considerations
Detect Contamination Incidents
(Short-Term Risks)
Monitor Threats to Long-Term Water
Quality (Long-Term Risks)
Likelihood
The probability that an SW threat will cause
a significant yet transient degradation in
source water quality. The frequency of
occurrence of previous, similar incidents can
be used to estimate a likelihood score.
Existing mitigation strategies at the SW
threat such as leak detection systems,
secondary containment, and spill response
plans can reduce likelihood.
The probability that an SW threat will cause
a sustained change in water quality (e.g.,
longer than one year). Characteristics of the
SW threat, such as discharge rates or
contaminant loading rates, can be used to
estimate a likelihood score. Existing
mitigation strategies such as runoff control
systems can reduce likelihood.
Vulnerability
The probability that a contamination incident
caused by an SW threat will adversely
impact the utility or its customers. The ability
of the utility to respond to a contamination
incident in a manner that mitigates the
consequences of the incident can be used to
estimate a vulnerability score. Availability of
treatment that can remove or neutralize a
contaminant can reduce vulnerability.
The probability that a sustained change in
water quality caused by an SW threat will
adversely impact the utility or its customers.
The ability of the utility to adapt to changing
source water quality can be used to estimate
a vulnerability score. Implementation of a
source water protection plan, which
considers threats to long-term water quality,
can reduce vulnerability.
Consequence
The damage or negative impacts to the utility
or its customers resulting from a
contamination incident caused by an SW
threat. Potential consequences include
disruption or upsets to treatment plant
operations, aesthetic changes that make the
water unacceptable to customers, or adverse
health effects in exposed customers. A
consequence score may be determined by
estimating the number of customers
impacted, the duration of a disruption in
service, or the cost of restoring a system to
normal operations following a contamination
incident.
The impact of a long-term water quality
change on treatment plant operations or
finished water quality. Potential
consequences may include difficulty in
meeting treatment targets, failure to comply
with drinking water standards, aesthetic
changes that are unacceptable to customers,
or diversion of utility resources to modify the
treatment plant in response to the water
quality change. A consequence score may
be determined through an analysis to
estimate the impact of degraded source
water quality on utility operations.
The results of a risk assessment are used to develop (1) a prioritized list of SW threats of contamination
(short-term risks) and (2) a prioritized list of SW threats to long-term water quality design goal (long-term
risks). These lists are used to identify high-priority threats that will be considered in an SWM design. It is
also important to understand that risks may change over time and
that the risk assessment may need to be updated when new potential
SW threats are identified. A Template for Conducting a Risk
Assessment for Source Water Threats can be opened and edited in
Microsoftฎ Word by clicking the icon in the callout box.
This template can guide
a risk assessment for
source water threats.
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2.4 Design the SWM System
The major design elements associated with SWM are summarized in Figure 2-2 and briefly described in
this section. Detailed guidance on each design element is presented in Sections 3 through 7.
SWM | SWM
Locations Parameters
SWM
Stations
Information
Management &
Analysis
Figure 2-2. Source Water Monitoring Design Elements
Select Source Water Monitoring Locations
SWM locations should be selected based on design goals established for SWM as well as the results from
a source water risk assessment. Typical monitoring locations include the raw water intake to a treatment
plant, various locations and depths in rivers and lakes, and strategic locations in the watershed.
Monitoring locations for groundwater sources will generally be limited to an intake structure (for
centralized groundwater treatment facilities), the wellhead, or monitoring wells. This document does not
present methods for locating monitoring wells within an aquifer. Guidance on the selection of SWM
locations is discussed in detail in Section 3.
Select Source Water Monitoring Parameters
The selection of SWM parameters is based on design goals established for SWM, as well as the results
from a source water risk assessment. In particular, the contaminants associated with specific SW threats
can inform the selection of SWM parameters. The parameters monitored determine the types of water
quality variations, incidents, or trends that can be detected. Guidance on the selection of SWM parameters
is discussed in detail in Section 4.
Design Source Water Monitoring Stations
The design of SWM stations is based on the locations and parameters selected for SWM. It includes
selection of the specific water quality instalments and ancillary equipment necessary to bring sensors into
contact with a water sample and transmit data. The station design can dramatically impact capital costs,
operating costs, data accuracy, and data completeness. Guidance on the design of SWM stations is
discussed in detail in Section 5.
Develop Information Management and Analysis Tools
Information management systems receive, process, analyze, store, and present data generated by SWM
stations. An information management system may include data analysis tools that generate alerts and send
notifications to designated personnel when water quality anomalies are detected. Information
management and analysis are discussed in detail in Section 6.
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Develop Investigation and Response Procedures
Once a water quality anomaly has been detected, an investigation should be undertaken to determine the
cause of the anomaly and guide response actions appropriate to the situation. The procedure for
responding to a water quality anomaly will depend on the design goals for the system. To optimize
treatment processes, a response procedure will guide adjustments to treatment process settings to meet
treatment targets. For detection of contamination incidents, a response procedure will guide actions that
prevent potentially contaminated water from entering a treatment plant or finished water. Investigative
activities that support monitoring long-term water quality involve the analysis of data over multiple years
to determine whether a source water quality baseline is changing. Investigation and response procedures
are discussed in detail in Section 7.
SWM designed to realize multiple design goals can be implemented
in phases to progressively expand the system to meet these goals.
An example of this approach is an initial phase with a single SWM
location at an intake for treatment process optimization, followed by
phases to provide capabilities for the detection of contamination
incidents and monitoring of threats to long-term water quality.
Subsequent phases would build on the previous installations, adding
capabilities to meet additional goals.
SRS Planning
If an SWM system will be part
of a larger SRS, it should be
incorporated into a master
plan, as described in Section
3 of Guidance for Developing
an Integrated Water Quality
Surveillance and Response
System (EPA. 2015bi. Master
planning for an SRS involves
the development of a
complete SRS design, which
is implemented in phases
based on available resources.
If multiple potential designs emerge during the design process, an
evaluation of alternatives should be conducted to consider the cost
and benefits associated with each. For example, some alternatives
may offer tradeoffs between the number of parameters monitored
and the number of monitoring locations. Each of these alternatives
will have different capabilities and a different cost for procurement, operation, and maintenance
throughout the life of the system. Framework for Comparing Alternative Water Quality Surveillance and
Response Systems (EPA. 2015d) provides a systematic process for comparing alternative designs that
considers both the capabilities and cost of each design.
Once the SWM design elements have been developed, they should
be captured in a design document. A Template for Developing an
SWM Preliminary Design Document can be opened and edited in
Microsoftฎ Word by clicking the icon in the callout box.
|wf|
This template can be
used to develop an SWM
preliminary design.
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SWM Funding Opportunities
Both financial and personnel resources are required to implement SWM. There are a variety of methods to fund
the project, a few of which are described below. This list is not intended to be comprehensive, but it provides an
indication of the types of funding options that may be available.
Pay-as-you-go. Funding SWM through a pay-as-you-go strategy involves incorporating the cost of
implementation into the annual budget. This can be done through allocating existing cash reserves or developing
new revenue sources such as capital improvement fees, increased property taxes, or tapping a portion of water
sales revenue. This funding mechanism works best for a phased SWM implementation where pieces of the
system are gradually deployed as the capital becomes available.
Bonds/Loans. Funding SWM through bonds or loans incurs debt at the beginning of the project, which is
typically paid back over a 10- or 20-year period. The debt may be serviced through implementation of new
revenue sources such as capital improvement fees, increased property taxes, or a portion of water sales revenue.
Financing SWM using bonds or loans can allow for significant expenditures at the beginning of the project,
accelerating design and implementation.
Grants/Federal Loans. Funding SWM through grants or federal loans (usually provided at or below market
interest rates) involves applying to a government agency or other organization. To improve the likelihood of an
award, the project description should meet all requirements specified in the grant/loan application. The following
organizations are potential sources of grant funding for SWM:
Bureau of Reclamation. Significant grant funding opportunities are available for systems that reduce
energy consumption, address climate-related risks, and support sustainability of water systems.
(http://watersmartapp.usbr.aov/WaterSmart)
Department of Agriculture. Districts that provide water to agricultural customers, and possibly along
with urban customers, can apply for grants related to improving water quality and water availability for
agricultural customers. To be eligible for these grants, at least 30 percent of water production should go
to agricultural use. (http://www.rd.usda.gov/)
Drinking Water State Revolving Fund. These federal loans must address a serious risk to public
health, bring the systems into compliance with the Safe Drinking Water Act, consolidate water supplies,
or replace aging infrastructure, (https://www.epa.aov/drinkinawatersrf)
Global City Teams Challenge. Provides funding for Smart Cities projects, (https://www.us-
ianite.org/alobalcitvteams/)
Public-private partnership. Funding SWM through public-private partnerships involves working with a
private entity that would benefit from financing some aspect of SWM.
Some of these funding opportunities may require development and approval of specific documentation such as a
Quality Assurance Project Plan, Data Management Plan, or Health and Safety Plan. To secure funding and
support for an SWM project, a business case should be developed that clearly articulates the benefits of SWM,
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Section 3: Source Water Monitoring Locations
An SWM location is the site in a source water where water is sampled for measurement. Selection of
SWM locations should be guided by the design goals established for the system and the time required to
implement a response action relative to the time a water quality change is detected. SWM locations are
selected relative to control points, which are locations where a treatment process can be modified (e.g.,
addition of pretreatment chemicals) or a response action can be implemented (e.g., closing of an intake).
For detection of contamination incidents and monitoring of threats to long-term water quality, SWM
location selection should also be informed by the location of high-priority SW threats.
Selection of SWM locations and SWM installation sites will also be influenced by a variety of site-
specific considerations, such as accessibility and natural hazards as discussed in Guidelines and Standard
Procedures for Continuous Water-Quality Monitors: Station Operation, Record Computation, and Data
Reporting (USGS. 2006). Performance objectives, such as operational reliability and sustainability should
also be considered when selecting these locations. The final selection of SWM locations will be a
compromise between the ideal location that meets the design goals and practical implementation
considerations.
The following sections present a series of examples demonstrating how each of the three design goals
covered in this document influence the selection of SWM locations. All of these examples are based on a
single hypothetical utility with a river source. The sequence of the examples is intended to illustrate how
an SWM system can be expanded from a single monitoring location at an intake to multiple monitoring
locations throughout the source water and watershed.
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r
a
Monitoring at the Intake
While monitoring source water
quality at the intake offers several
advantages, it may not always be
the best choice. If pretreatment
chemicals are added at the
intake, it may be preferable to
conduct monitoring upstream of
the intake to provide adequate
time between detection of a water
quality change and adjustment to
pretreatment process.
3.1 SWM Locations to Support Treatment Process Optimization
To support treatment process optimization, SWM data needs to be available to operators in sufficient time
to make process adjustments in response to changes in source water quality. Many common treatment
process adjustments, such as changes to chemical feed rates, process loading rates, and filter backwash
frequency, can be made in a matter of minutes. As such, an
SWM location selected for treatment optimization does not need
to be far from control points in a treatment plant to provide
adequate time for operators to respond. SWM locations within
the infrastructure that conveys water from the intake to the
treatment plant may provide sufficient time to make operational
changes, simplifying SWM station installation and ensuring that
the water sampled by the SWM station is representative of the
water to be treated. Where water is drawn from multiple sources,
monitoring water quality at the intake for each source can
provide information that guides decisions to switch sources or
adjust the blend ratio from different sources. Figure 3-1 shows
an SWM location at the intake structure for the plant.
Distribution
System
Off-Stream Storage
Disinfection
Fi tration
Pretreatment
ontro^
Center
Coagulation/
Sedimentation
WM Location
Control Point
Figure 3-1. SWM Location Selected to Support Treatment Process Optimization
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3.2 SWM Locations to Detect Contamination Incidents
The process of selecting SWM locations for the purpose of detecting contamination incidents, such as
chemical spills, is an iterative process consisting of the following steps:
1. Calculate the time required to investigate a water quality change and implement a response
2. Determine the critical detection point
3. Select the SWM locations based on the results of Steps 1 and 2
Calculate Investigation and Response Times
The investigation and response time should be calculated for each unique action that may be taken in
response to a source water quality change. It is the sum of the following two segments:
The time to confirm that a water quality change is real and requires a response. Once a
change in source water quality is detected, the change should be investigated to ensure that it is
not due to an equipment problem. The time required for this investigation can be estimated using
data from previous investigations or using the results from drills and exercise. The process for
investigating a source water quality change is described in detail in Section 7.
The time to implement a response action. After determining that a change in source water
quality requires a response, a specific response action is selected and implemented. A range of
response actions should be considered for different source water contamination scenarios. The
time to implement each response action can be estimated using information from previous
implementation of those actions and/or the experience of utility operators. Response actions are
described in detail in Section 7.
Determine Critical Detection Point
The critical detection point is the location on the source water
where detection of a water quality change provides enough lead
time to implement a response action. Conservatively, the critical
detection point is determined using the response action that takes
the most time to implement or the response action associated with
the control point furthest upstream. The distance from the control
point to the critical detection point is calculated by multiplying the
flow rate for the source water by the total response time. Use of a
conservative (high) source water flow rate for calculating the
distance to the critical detection point is recommended. If source
water is piped to sensors in a flow-cell, as described in Section 5,
the time for the water sample to travel from the source to the
sensors should be added to the total response time to determine the
critical detection point.
Any SWM location upstream of the critical detection point should provide adequate time to implement a
response action. SWM locations farther upstream and closer to an SW threat may be selected to increase
the likelihood of detecting a water quality change caused by the SW threat (i.e., by minimizing the
opportunities for dilution as a contaminant plume flows downstream from the SW threat).
If there is a high-priority SW threat downstream of the critical detection point, the hydraulic travel time
from the SW threat to the control point where it can be mitigated (e.g., an intake structure that can be
closed) should be calculated to develop an alternative response that, although not ideal, can still provide a
level of mitigation. It is recommended that hydraulic travel time be calculated using a conservative (high)
source water flow rate.
Still Water
In still water, such as lakes and
reservoirs, a contaminant will
generally spread slowly and
persist for an extended period
of time. Thus, it is generally not
necessary to determine a
critical detection point in lakes
and reservoirs for the purpose
of selecting SWM locations.
Monitoring at or near the intake
typically provides sufficient
time to implement a response.
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Select the SWM Locations
The process for selecting SWM locations should consider the location of the critical detection point, the
locations of SW threats, and the locations of control points associated with response actions. The
practicalities of SWM station installation, as discussed in
Section 5, will impact SWM location selection as well.
Several examples follow to illustrate the selection process. Note
that all of these examples include SWM Location 1 at the intake
(see Figure 3-1). While Location 1 was selected to support
treatment process optimization, it is also available to support
detection of contamination incidents.
Sensor Depth
When using immersed sensors,
consider the impact of sensor
depth on the ability of the sensor to
detect a water quality change. For
example, if the contaminant
associated with the SW threat
floats, select a monitoring depth
near the surface of the waterbody.
Additional guidance on these
considerations is available in other
resources (USGS. 2006).
The simplest SWM design can be implemented when all SW
threats are upstream of the critical detection point. This situation
requires only one additional SWM location (SWM Location 2)
to be selected downstream of the SW threat closest to the intake
(SW Threat A) but upstream of the critical detection point, as shown m Figure 3-2 (this figure is zoomed
out from Figure 3-1 to show a longer stretch of the river). This approach uses the minimum number of
SWM locations and provides enough hydraulic travel time between the SWM location and the control
point to implement an appropriate response. A single SWM location may also be sufficient in situations
where SW threats upstream of the critical detection point are clustered (not shown).
,41)
Control Center
a
\^*SWM Location
SW Threat
Control Point
Figure 3-2. A Single Upstream SWM Location to Monitor Multiple SW Threats
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Online Source Water Quality Monitoring
There may be situations where it is desirable to include an SWM location near each SW threat, as shown
in Figure 3-3, such as:
When the benefit of early detection outweighs the cost of additional SWM stations
When attribution of an incident, such as a spill, to a specific SW threat is important
When SW threats involve contaminant volumes or flows that can rapidly dilute to a concentration
that is difficult to detect but still high enough to present a risk to the utility or its customers
When there is a need to follow the progression of a contaminant plume and provide confirmation
of the initial detection
Control Center
\^*SWM Location
Control Point
SW Threat
Figure 3-3. Multiple Upstream SWM Locations to Monitor Multiple SW Threats
The SWM locations shown in Figures 3-2 and 3-3 were selected based on the location of stationary
threats. Mobile SW threats, such as road or rail traffic moving adjacent to a long stretch of source water
or a vessel on the source water, require a different approach to SWM location selection. One approach to
monitoring for mobile SWM threats is to locate an SWM
station at the critical detection point, which would allow
adequate time to respond to a spill from a mobile threat
that occurs upstream of this point. Also, the SWM location
at the intake (SWM Location 1 in the figures) would
provide detection capability for mobile SW threats. While
monitoring at the intake would not provide time for an
optimal response, it can still detect a water quality change
in time to implement a response that will mitigate the
consequences of the incident.
Alternative Notifications
Notifications of spills, leaks, or discharges
from an SW threat owner can provide
another means of detecting
contamination incidents. This method can
be particularly useful for SW threats
downstream of the critical detection point.
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3.3 SWM Locations to Monitor Threats to Long-Term Water Quality
SWM locations can be selected to monitor threats to long-term water quality. Figure 3-4 is a zoomed out
image of Figure 3-3 that shows areas of future industrial and agricultural expansion that could degrade
water quality in the tributaries feeding the river source. To monitor these SW threats, additional SWM
locations were selected in the tributaries, upstream of their confluence with the river, as indicated by
SWM Locations 6 and 7.
Area of Future
Industrial
Use
Area of Future
Agricultural
Use
Control Center
xV'SWM Location
Control Point
Figure 3-4. SWM Locations to Monitor Threats to Long-Term Water Quality
The examples presented in this section consider each of the three design goals separately and identify
SWM locations accordingly. However, it can be seen that careful placement can allow individual SWM
locations to support more than one design goal. SWM Location 1 is an example where a single location
supports all three design goals. Also, while SWM Locations 2 through 5 were selected for detection of
contamination incidents, they could also monitor threats to long-term water quality. The ability of a single
SWM station to support multiple design goals will improve the sustainability of the SWM system.
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Section 4: Source Water Monitoring Parameters
This section describes water quality parameters that may be useful to optimize treatment processes, detect
contamination incidents, and monitor threats to long-term water quality.
4.1 Useful SWM Parameters
Table 4-1 provides an overview of water quality parameters that are potentially useful for SWM and that
can be monitored using online instruments. Additional information about the online instruments used to
measure these parameters is available in Guidance for Selecting Online Water Quality Monitoring
Parameters and Evaluating Sensor Technologies for Source Water and Distribution System Monitoring
(EPA. 2016c).
Table 4-1. Overview of SWM Parameters
Parameter
Parameter Description
Ammonia (NH3)
Concentration of dissolved ammonia (NH3) in solution
Can occur naturally or originate from agricultural and urban runoff, wastewater
treatment plants, or sanitary sewer overflows
Can impact drinking water treatment and distribution operations (e.g., chlorine
demand, nitrification)
Can be highly toxic to aquatic organisms
Alkalinity
Measure of a water's buffering capacity (i.e., its ability to resist a change in pH
when an acid or base is added), typically measured in carbonate equivalents
Can result from pollutant loadings (e.g., metals) from transportation
Will impact the quantity of treatment chemicals (e.g., coagulant, acid, or base) that
need to be added to achieve acceptable process performance
Will influence the stability of finished water pH in distribution systems
Can affect the bioavailability of contaminants, particularly metals, in natural
systems
Dissolved Oxygen (DO)
Concentration of dissolved oxygen in solution (the location of the DO sensor can
influence DO concentration measured)
DO concentrations can be reduced by pollutants in stormwater runoff and sanitary
sewer overflows
Low DO concentrations can impact oxidation-reduction potential, adversely
impacting the performance of some treatment processes, although mixing during
pumping and flocculation can bring DO concentrations to near saturation
Low DO can be lethal to certain aquatic organisms
Dissolved Organic
Carbon (DOC)
Total Organic Carbon
(TOC)
Concentration of organic carbon (compounds that contain carbon and hydrogen)
TOC includes suspended and dissolved organic carbon
DOC is the fraction of organic carbon that passes through a filter with a
0.45 micrometer pore size
Decaying natural organic matter may increase DOC/TOC concentrations
Presence of DOC/TOC during chlorination results in disinfection byproducts
Assimilable organic carbon can support biological regrowth in distribution systems
Hydrocarbons
Concentration of long-chain, unsaturated organic compounds that include
hydrogen and carbon
Can occur due to urban runoff, transportation, or spills
Can be an indicator of source water contamination with petroleum products
Can impart an objectionable odor to water, and can be difficult to remove from
distribution system and household plumbing materials
Can be toxic to aquatic organisms
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Parameter
Parameter Description
Nitrate and Nitrite
Concentration of nitrate (NO3) and nitrite (NO2) in solution
Can occur in wastewater treatment plant discharge, agricultural runoff, or urban
runoff
Regulated contaminants that can be difficult to remove through conventional
treatment
Can promote algal and bacterial growth
Ortho-phosphates
Concentration of inorganic compounds consisting of phosphorus and oxygen
Can occur naturally or originate from agricultural and urban runoff
Used to protect drinking water distribution pipelines and household plumbing from
corrosion
Can promote algal and bacterial growth
Oxidation-Reduction
Potential (ORP)
Measure of the potential flow of electrons between reducers and oxidizers, which
characterizes the oxidizing or reducing power of a solution
Low ORP can reduce the efficacy of oxidation treatment processes
Can serve as an indicator of natural processes in source water (e.g., turnover)
PH
Negative logarithm of the concentration of hydrogen ions in an aqueous solution
Fundamental to understanding aqueous chemistry
pH variation can be caused by natural biological and chemical processes
Can affect the performance of coagulation/sedimentation treatment processes
Changes in pH can affect chemical and biological processes in source water
Significant changes in pH levels are often toxic to aquatic organisms
Photosynthetic Pigments
Amount of chemicals present that are used by photosynthetic organisms to capture
solar energy in chemical bonds
Includes chlorophyll a and phycocyanin (direct measure of cyanobacteria levels)
Can be an indicator of autotrophic biomass and algal blooms
In-vivo fluorescence can characterize the relative proportion of algal species
Specific Conductance
Measure of the ionic strength of a solution and commonly used as a surrogate for
total dissolved solids
Can increase due to sanitary sewer overflows, combined sewer overflows, and
wastewater treatment plant discharges
Can indicate salt water or brackish water intrusion
Can interfere with osmotic balance in aquatic organisms
Spectral Absorbance
Measure of wavelength absorption across the ultra-violet (UV)/visible spectrum
Spectral absorption profiles of a source water can provide a baseline spectral
fingerprint used to detect anomalous water quality
Can provide derived measurements for other water quality parameters (e.g., nitrate
and nitrite)
Spectral absorption at 254 nm (UV-254) is commonly used as a surrogate for the
concentration of natural organic matter
Streaming Current
(Zeta Potential)
Determination of the surface charge (zeta potential) by measuring particle
velocities when a potential difference is applied
Commonly used as a process monitoring tool for coagulation, sedimentation, and
filtration
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Parameter
Parameter Description
Temperature
Measure of the thermal energy in water
Influences chemical equilibrium and kinetics, which may impact treatment process
performance
Can indicate blending of water from different sources (e.g., wastewater treatment
plant effluent blending with a source water)
Integrated into water quality sensors that measure temperature-dependent
parameters (e.g., pH, specific conductance) to enable temperature compensation
to those parameter measurements
Toxicity
Aggregate measure of the adverse effects to aquatic organisms resulting from
exposure to chemicals in their environment
Indicator of the presence of chemicals or toxins in water that could harm people or
aquatic organisms
Turbidity
Measure of the cloudiness of water due to suspended particles
Can increase due to sanitary sewer overflows, combined sewer overflows, and
wastewater treatment plant discharges
High turbidity levels can overload some treatment processes due the associated
increase in suspended solids
Can serve as an indicator of bacteria and other particulate pollutants
High turbidity levels can decrease light passage, impacting the subsurface
ecosystem
4.2 Parameter Selection
This section describes the SWM parameters useful for each of the design goals presented in Section 2.1.
When selecting parameters, consider that some provide innate benefits while others may complement
other monitored parameters, providing more useful information when measured together. For example,
pH impacts ammonia speciation, with lower pH levels shifting the equilibrium toward the ammonium ion
(NH4+), which is more toxic to aquatic organisms. Thus, both ammonia and pH should be monitored if
ammonia is a known or potential source water contaminant.
The following sections list parameters that could be potentially useful for specific applications under each
of the three design goals. The parameters listed for each application are generally complementary,
meaning that monitoring multiple parameters would more effectively meet the listed design goal.
However, parameter selection should always be informed by the SWM location and other site-specific
considerations.
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Parameter Selection to Optimize Treatment Processes
The parameters useful to optimize treatment processes will depend on the processes that will be
optimized. Table 4-2 lists SWM parameters that are useful for optimizing conventional treatment
processes.
Table 4-2. SWM Parameters that Support Treatment Process Optimization
Treatment Process
Parameters
Rationale for Parameter Selection
Permanganate
Pretreatment
ORP
ORP can indicate the presence of reducing agents in the source water,
which would increase the required dose of permanganate.
DO
Low DO concentrations in the source water can indicate a reducing
environment, increasing the required dose of permanganate.
DOC/TOC
High DOC/TOC concentrations in the source water can exert an oxidant
demand, increasing the required dose of permanganate.
Spectral
Absorbance
Removal of iron and manganese is often the treatment target for pre-
oxidation using permanganate. Spectral absorbance can be used to
measure the iron and manganese concentrations in the source water,
which can be used to determine the permanganate dose needed to
achieve iron and manganese removal targets.
PH
pH can impact the efficacy of permanganate as a pre-oxidant.
PAC Pretreatment
Photosynthetic
Pigments
PAC may be added to remove harmful algal toxins and byproducts. An
increase in photosynthetic pigments can provide a direct indication of
algal activity and thus might serve as a trigger for PAC addition.
DOC/TOC
High DOC/TOC concentrations can compete for active adsorption sites
on PAC particles, thus increasing the concentration of PAC needed to
achieve other treatment targets, such as removal of harmful algal toxins
or taste & odor-causing compounds.
PH
pH can impact the efficacy of PAC in adsorbing specific contaminants.
Coagulation/
Sedimentation
Turbidity
Turbidity can be used to determine the coagulant dose necessary to
meet process effluent water quality targets.
DOC/TOC
The treatment target for enhanced coagulation is typically established
as either a percent removal of DOC/TOC during conventional treatment
or a target DOC/TOC concentration in filter effluent. DOC/TOC data can
be used to determine the coagulant dose needed to achieve optimized
coagulation.
PH
pH has a significant impact on the performance of coagulation
processes and the ability to achieve enhanced coagulation.
Spectral
Absorbance
Spectral absorbance can detect changes in the chemical composition of
a source water, which may impact the performance of coagulation
processes.
Alkalinity
Alkalinity can impact the amount of coagulant or acid/base that needs to
be dosed to reach a pH range necessary for optimized coagulation.
Filtration
N/A
Because upstream conventional treatment process alter the water
quality parameters important to filtration performance, most notably
turbidity, source water quality data has little application to optimization of
filtration.
Disinfection
Ammonia
Ammonia is generally not removed by upstream conventional treatment
processes, thus, changes in the concentration of ammonia in the source
water can impact the chlorine dose required for breakpoint chlorination
and adequate disinfection.
Note: Temperature should also be monitored for each of these treatment processes due to its impact on reaction rates and process
performance.
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Parameter Selection to Detect Contamination Incidents
Table 4-3 lists several contaminant groups, potentially useful SWM parameters, and the rationale for how
each parameter can support detection of the listed contaminant group. The information in this table is
general, and parameter selection should be guided by the specific contaminants associated with SW
threats identified during the risk assessment. Parameter selection can also be guided by studies, such as
Distribution System Water Quality Monitoring: Sensor Technology Evaluation Methodology and Results
(EPA. 2009). that have evaluated the responsiveness of various water quality parameters to different
contaminants in drinking water. The ability of any of the listed parameters to detect the presence of a
contaminant is contingent upon a contaminant concentration that is sufficiently high to change the
parameter value from the baseline. Detection capabilities are also dependent on the configuration of the
data analysis tools used to detect anomalies as described in Section 6.
Table 4-3. SWM Parameters that Support Detection of Contamination Incidents
Contaminant Group and
Associated SW Threats
Parameters
Rationale for Parameter Selection
Inorqanic Industrial
Chemicals
from SW threats, such as:
Chemical storage tanks
Pesticide and fertilizer
storage tanks
Transportation corridors
Watercraft
Spectral Absorbance
Some inorganic chemicals absorb in the UV-visible
spectrum. As such, a change in spectral absorption
may indicate contamination with an inorganic industrial
chemical. Furthermore, some spectral instruments
allow users to add spectral fingerprints to a library. If
the spectral fingerprint for a specific inorganic
chemical associated with an SW threat is produced, it
can be added to a utility's fingerprint library to facilitate
future detection of the contaminant.
Specific Conductance
Some inorganic chemicals have charged functional
groups that can dissociate and form ionic species
when dissolved in water. An increase in specific
conductance could indicate the presence of inorganic
industrial chemicals.
Toxicity
Toxicity provides a general indication of the presence
of a potentially toxic substance and thus may detect
the presence of toxic industrial chemicals. Note that
toxicity monitors vary widely in how they respond to
different chemicals.
Oraanic Industrial Chemicals
from SW threats, such as:
Chemical storage tanks
Pesticide and fertilizer
storage tanks
Transportation corridors
Watercraft
DOC/TOC
DOC/TOC can be used to determine the carbon
concentration associated with organic compounds,
including organic industrial chemicals. Thus, an
increase in DOC/TOC may indicate the presence of an
organic industrial chemical.
Spectral Absorbance
Many organic chemicals absorb in the UV-visible
spectrum. Thus, a change in spectral absorption can
indicate contamination from an organic industrial
chemical. Furthermore, some spectral instruments
allow users to add spectral fingerprints to a library. If
the spectral fingerprint for a specific organic chemical
associated with an SW threat is produced, it can be
added to a utility's fingerprint library to facilitate future
detection of the contaminant.
Specific Conductance
Some organic chemicals have charged functional
groups that can dissociate and form ionic species
when dissolved in water. An increase in specific
conductance could indicate the presence of organic
industrial chemicals.
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Contaminant Group and
Associated SW Threats
Parameters
Rationale for Parameter Selection
Oraanic Industrial Chemicals
from SW threats, such as:
Chemical storage tanks
Pesticide and fertilizer
storage tanks
Transportation corridors
Watercraft
Toxicity
Toxicity provides a general indication of the presence
of a potentially toxic substance and thus may detect
the presence of toxic industrial chemicals. Note that
toxicity monitors vary widely in how they respond to
different chemicals.
Petroleum Products
from SW threats, such as:
Petroleum storage tanks
Shale gas and oil drilling
Transportation corridors
Watercraft
DOC/TOC
DOC/TOC can be used to determine the carbon
concentration associated with petroleum products. An
increase in DOC/TOC could indicate the presence of
petroleum products.
Hydrocarbons
Hydrocarbon monitoring can provide a direct measure
of hydrocarbon concentrations in a source water.
Toxicity
Toxicity provides a general indication of the presence
of a potentially toxic substance, and thus may detect
the presence of petroleum products. Note that toxicity
monitors vary widely in how they respond to petroleum
products.
Alqal Toxins/Harmful Alqal
Blooms (HABs)
from SW threats, such as:
Agricultural runoff
Urban runoff
Wastewater treatment
plant discharges
Ammonia
Ammonia can be monitored to detect increases in
nutrient loading that can support harmful algal bloom
formation.
DO
Sharp decreases in DO concentrations can indicate
the formation of algal blooms.
Nitrate and Nitrite
Nitrate and nitrite can be monitored to detect increases
in nutrient loading that can support harmful algal
bloom formation.
Ortho-phosphates
Ortho-phosphates can be monitored to detect
increases in nutrient loading that can support harmful
algal bloom formation.
Photosynthetic Pigments
An increase in photosynthetic pigments can provide a
direct indication of algal activity.
PH
Increases in pH can occur due to photosynthetic
activity and microbial respiration, and thus may be an
indication of algal bloom formation.
Turbidity
Increased turbidity can indicate the formation of algal
blooms.
Toxicity
Toxicity provides a general indication of the presence
of a potentially toxic substance and thus may detect
the presence of toxins. Note that toxicity monitors vary
widely in how they respond to algal toxins.
Wastewater
from SW threats, such as:
Wastewater outfall
Wastewater holding ponds
Spray field runoff
Ammonia
Ammonia is typically the most prominent nitrogen
species in raw wastewater. Thus, monitoring for
ammonia can be an effective method of detecting
wastewater discharges.
DO
Sharp decreases in DO concentrations can indicate
the release of wastewater, which would elevate the
bio-chemical oxygen demand.
Nitrate and Nitrite
Nitrate and nitrite concentrations can be significant in
wastewater effluent from plants that practice
nitrification. Thus, monitoring for nitrate and nitrite can
be an effective method of detecting wastewater
discharges.
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Contaminant Group and
Associated SW Threats
Parameters
Rationale for Parameter Selection
Wastewater
from SW threats, such as:
Wastewater outfall
Ortho-phosphates
Phosphates can be present in wastewater effluent. As
such, monitoring for ortho-phosphates can be an
effective method of detecting wastewater discharges.
Wastewater holding ponds
Spray field runoff
DOC/TOC
DOC/TOC can be used to determine the carbon
concentration associated with all organic compounds.
An increase in DOC/TOC could indicate the release of
wastewater.
Specific Conductance
Some contaminants in wastewater have charged
functional groups that increase the ionic strength of a
solution. An increase in specific conductance could
indicate a higher concentration of wastewater.
Toxicity
Toxicity provides a general indication of the presence
of a potentially toxic substance and thus may detect
the presence of toxic chemicals present in wastewater.
Note that toxicity monitors vary widely in how they
respond to different chemicals.
Turbidity
An increase in turbidity can indicate an increase in the
concentration of suspended solids and
microorganisms that may be present in wastewater.
Note: It is recommended that pH and temperature be selected for all contaminant groups and SW threats as these parameters
are important for the fundamental understanding of aqueous chemistry.
Parameter Selection to Monitor Threats to Long-Term Water Quality
The parameters useful for monitoring of threats to long-term water quality will depend on the specific
contaminants associated with high-risk SW threats. Selected parameters should be capable of providing
useful information about the specific contaminants or contaminant classes identified during the risk
assessment. Table 4-4 lists several contaminant groups, potentially useful SWM parameters, and the
rationale for how parameters can be used to detect contaminant groups. For this design goal, parameter
selection should consider how the SW threats are likely to alter water quality over time.
Table 4-4. SWM Parameters that Support Monitoring of Long-Term Water Quality
Contaminant Group and
Associated SW Threats
Parameters
Rationale for Parameter Selection
Waste wate r/sto rmwate r
from SW threats, such as:
Wastewater outfalls
Wastewater holding ponds
Stormwater outfalls
Combined sewer overflows
Ammonia
Elevated concentrations of ammonia can harm
aquatic life, adversely impact beneficial uses (e.g.,
fisheries), and adversely impact treatment
processes such as disinfection.
DO
Insufficient DO can damage the aquatic ecosystem
and adversely impact beneficial uses (e.g.,
recreational activities).
Septic systems
Climate change
DOC/TOC
Elevated concentrations of DOC/TOC can indicate
higher pollutant loading, which would be harmful to
the overall health of the waterbody. In extreme
cases, a sustained increase in DOC/TOC may
require modifications to treatment processes.
Nitrate and Nitrite
Elevated concentrations of nitrate and nitrite can
indicate higher nutrient loading, with the potential to
trigger algal blooms and HABs. In extreme cases, a
sustained increase in nitrate and nitrite may require
the addition of a treatment process for nitrate
removal to meet drinking water regulations.
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Contaminant Group and
Associated SW Threats
Parameters
Rationale for Parameter Selection
Waste wate r/sto rmwate r
from SW threats, such as:
Wastewater outfalls
Ortho-phosphates
Elevated concentrations of ortho-phosphates can
indicate higher nutrient loading with the potential to
trigger algal blooms and HABs.
Wastewater holding ponds
Stormwater outfalls
Combined sewer overflows
Septic systems
Climate change
Photosynthetic Pigments
An increase in photosynthetic pigments is a direct
indicator of the level of algal activity and the
potential for HABs.
Specific Conductance
Elevated specific conductance could result in an
exceedance of secondary drinking water standards
and decreased customer acceptance of the water. If
bromide is one of the inorganic chemicals
contributing to the increase, it could result in higher
concentrations of disinfection byproducts (DBPs),
potentially requiring source water blending or
addition of advanced treatment (e.g., reverse
osmosis).
Toxicity
Can indicate the presence of toxins that are harmful
to aquatic life and degrade the overall health of the
waterbody. Specific toxins could require additional
treatment processes.
Turbidity
Increased turbidity could adversely impact the
overall health of a waterbody by reducing the depth
of sunlight penetration. A significant and sustained
increase in turbidity could require treatment process
adjustments to maintain acceptable effluent water
quality.
Inorqanic and orqanic nutrients
from SW threats, such as:
Agricultural runoff
Urban runoff
Wastewater outfalls
Wildfires
Ammonia
Elevated concentrations of ammonia can harm
aquatic life, adversely impacting beneficial uses
(e.g., fisheries), and can adversely impact treatment
processes such as disinfection.
DO
Insufficient DO can damage the aquatic ecosystem
and adversely impact beneficial uses (e.g.,
recreational activities).
Climate change
DOC/TOC
Elevated concentrations of DOC/TOC can indicate
higher pollutant loading, which would be harmful to
the overall health of the waterbody. In extreme
cases, a sustained increase in DOC/TOC may
require modifications to treatment processes.
Nitrate and Nitrite
Elevated concentrations of nitrate and nitrite can
indicate higher nutrient loading, with the potential to
trigger algal blooms and HABs. In extreme cases, a
sustained increase in nitrate and nitrite may require
the addition of a treatment process for nitrate
removal to meet drinking water regulations.
Ortho-phosphates
Elevated concentrations of ortho-phosphates can
indicate higher nutrient loading with the potential to
trigger algal blooms and HABs.
Photosynthetic Pigments
An increase in photosynthetic pigments is a direct
indicator of the level of algal activity and the
potential for HABs.
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Contaminant Group and
Associated SW Threats
Parameters
Rationale for Parameter Selection
Inoraanic and oraanic nutrients
from SW threats, such as:
Agricultural runoff
Urban runoff
Wastewater outfalls
Wildfires
Climate change
Specific Conductance
Elevated specific conductance could result in an
exceedance of secondary drinking water standards
and decreased customer acceptance of the water. If
bromide is one of the inorganic chemicals
contributing to the increase, it could result in higher
concentrations of DBPs, potentially requiring source
water blending or addition of advanced treatment
(e.g., reverse osmosis).
Pesticides and herbicides
from SW threats, such as:
Agricultural runoff
Urban runoff
Transportation runoff
DOC/TOC
An increase in DOC/TOC can indicate a higher
loading of pesticides and herbicides, which may
adversely impact the overall health of the waterbody
and require significant treatment modification.
Spectral Absorbance
An increase in spectral absorbance can indicate a
higher loading of pesticides and herbicides, which
may adversely impact the overall health of the
waterbody and require significant treatment
modification.
Toxicity
An increase in the toxicity of a waterbody could be
directly attributed to increased loading of pesticides
and herbicides.
Note: It is recommended that pH and temperature be selected for all contaminant groups and SW threats as these parameters are
important for the fundamental understanding of aqueous chemistry.
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Section 5: Source Water Monitoring Stations
Once SWM locations and SWM parameters have been selected, SWM stations can be designed. Each
SWM station will consist of the water quality instruments used to measure the selected parameters and the
ancillary equipment needed to bring a sample into contact with sensors, power the station, communicate
data to a utility control center, and protect the station from the environment, vandalism, or tampering. The
actual design of a station will depend on:
SWM location
Parameters to be monitored at the location
Practical considerations for installation and maintenance of the station at the location
A basic functional block diagram of an SWM station is shown in Figure 5-1, which delineates the SWM
station functions as follows:
Instrumentation. Providing the means to measure the selected parameters.
Sampling. Placing the sensors in contact with the source water and, as necessary, disposing of the
waste stream.
Power Supply and Distribution. Supplying sufficient power to the energized equipment in the
SWM station.
Communications. Providing the means to transfer the data collected by the SWM station to a
control center and transfer instructions from the control center to the SWM station.
Packaging. Providing a structure to mount and protect the instrumentation and ancillary
equipment both from the environment and potential tampering.
The following sections describe each of the functions identified in Figure 5-1.
Figure 5-1. Functional Block Diagram of an SWM Station
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Online Source Water Quality Monitoring
5.1 Instrumentation
In many cases, multiple sensor technologies are available to measure a given parameter, and specific
instruments will need to be selected for an SWM station. Several factors warrant consideration when
selecting an instrument, including instrument performance, sampling and analysis interval, environment at
the SWM installation site, lifecycle cost, and vendor support. An overview of SWM parameters and
related sensor technologies, as well as factors that should be considered during the selection process, are
covered in Guidance for Selecting Online Water Quality Monitoring Parameters and Evaluating Sensor
Technologies for Source Water and Distribution System Monitoring (EPA. 2016c).
5.2 Sampling
Two commonly used approaches to source water sampling for online measurement are:
Immersion of sensors directly into a waterbody
Pumping the source water to sensors housed in a flow-cell
Immersion of sensors directly into a waterbody ensures that the
sensors are measuring water quality with minimal disturbance or
change to the sample. This sampling method is useful for
parameters such as DO, which can change due to mixing and
transport to a flow-cell. Many parameters can be monitored by
sensors that can be immersed directly into a waterbody. A sensor
designed for use in this manner is usually equipped with a
protective housing and a means of cleaning the measurement
surface using wipers, brushes, or compressed air.
The second sampling approach involves pumping a water sample to
sensors inserted into a flow-cell that is not immersed in the
waterbody. This method requires installation of a pump and
associated piping to move the sample to the SWM station and a
flow-cell to ensure steady flow to all sensors. Some sensors
designed for use in a flow-cell are equipped with wipers, brushes, or compressed air to control fouling.
Flow-cells are useful in the following situations:
When using sensors that only operate correctly at specific flow rates and pressures, and cannot be
placed directly into a waterbody (e.g., many ammonia sensors).
When using instruments that require a controlled environment to operate correctly.
When instruments use reagents that cannot be discharged directly into a waterbody.
A comparison of the key attributes of the two sample measurement options (immersion and flow-cell) is
provided in Table 5-1. The attributes used for the comparison are:
Measurement Interference. The degree to which the sampling method introduces artifacts that
could interfere with measurement.
Measurement Delay. The degree to which the sampling method increases the time between
when a sample is taken from a source water and when a sensor makes a measurement.
Exposure to Environment. The degree to which the sampling method exposes instrumentation
to variable or hostile environmental conditions.
Lifecycle Cost. The degree to which the sampling method increases the cost of installing and
maintaining the instrumentation.
Representative Samples
When sampling a waterbody,
the sample represents only
the actual point where it was
taken. A waterbody is complex
in its composition in all three
dimensions, so a truly
representative view of the
waterbody would require
profiling in three dimensions,
which is impractical to do in
real time. However, sensors
placed at thoughtfully selected
positions in a waterbody can
provide information needed for
^^^^^specifi^SVVIV^pplicatioi^^^
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Online Source Water Quality Monitoring
Maintainability. The degree to which the sampling method increases the time and effort
necessary to maintain the instrumentation.
Table 5-1. Comparison of Key Attributes of Two Sample Measurement Options
Attribute
Immersion
Flow-cell
Comments
Measurement
Interference
e
Placing sensors directly in the waterbody eliminates many
sources of measurement interferences that may be
introduced when using a flow-cell, such as turbulence and
potential contamination from pumps and piping.
Measurement
Delay
o
When sensors are immersed in the source, measurement
delay is negligible. When a flow-cell is used, the sample is
pumped from the point it is extracted from the source to
the sensors in the flow-cell. The transit time to the flow-
cell is determined by the distance between the SWM
location and SWM station as well as the flow rate. This
delay can vary from minutes to hours depending on the
distance and flow.
Exposure to
Environment
O
Use of a flow-cell allows for more control over the
environment in which the instruments operate.
Lifecycle Cost
e
e
The use of a flow-cell requires additional piping and
possibly pumps, which can increase installation costs.
However, sensors installed directly into a waterbody may
be more costly to maintain.
Maintainability
o
e
Use of a flow-cell allows the sensors to be placed in a
more convenient location for maintenance. However, this
option also requires piping and pumps that must be
maintained.
Rating: = Positive; o = Neutral; o = Negative
If reagents are used during measurement, the effluent sample stream should be properly disposed. This
may require disposal into a sewer unless there is an NPDES permit to discharge the effluent sample
stream into a waterbody. In cases where reagentless sensors are used and nothing is added to the sample
stream, it may be possible to return the effluent sample stream to the source water following
measurement.
5.3 Power Supply and Distribution
The choice of power supply for an SWM station will be limited by the location where the SWM station
will be installed as well as the power requirements for the station equipment. Where it is readily available,
grid power is often the simplest and least expensive power supply. However, if grid power is not available
nearby, extending it to an SWM station may be equally or more expensive than using an alternative
supply (e.g., wind or solar supported by batteries). When using grid power, it is suggested that the SWM
stations have a dedicated circuit on the main breaker panel or a line conditioner to avoid erratic voltage or
circuit breaker trips. To ensure continued operation of an SWM station during minor power outages, an
uninterruptible power supply should also be installed. Additional guidance on power distribution is
available in Guidance for Building Online Water Quality Monitoring Stations (EPA. 2016d).
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5.4 Communications
The selection of a communications solution to transmit data from an SWM station to a control center is
strongly influenced by the station's location. Communications solutions may include wired and wireless
technologies. One potential advantage of using a flow-cell for sampling is that wired communication
methods may be available near an SWM station installation site. Guidance for Designing
Communications Systems for Water Quality Surveillance and Response Systems (EPA. 2016e) provides
further details for common communications options as well as a set of evaluation criteria to support the
selection process.
5.5 Packaging
Packaging for an SWM station includes the materials and devices used to mount or house sensors and
ancillary equipment. To achieve the various design goals and performance objectives, SWM stations may
need to be installed in buildings, near other equipment, or in remote areas near or directly in the source
water, all of which will influence the station packaging. SWM stations are typically constructed using one
of five primary design types:
Wall-mounted racks are assembled by securing instruments and related equipment to a mounting
panel that is attached to a wall.
Free-standing racks are constructed by securing instruments and related equipment to a mounting
panel that is attached to an open, structural frame that provides access on both sides of the panel.
Enclosed stations house instruments and related equipment inside a custom-made, prefabricated, or
National Electrical Manufacturers Association (NEMA) enclosure.
Compact stations are smaller versions of enclosed stations that can be designed around one or two
reagent-based instruments or a reagentless instrument that measures multiple parameters.
Floating platforms allow for a station to be located on the surface of a waterbody. These stations
typically consist of one or more cabinets containing instrumentation and electronics, which are
mounted on a pontoon or buoy. Only reagentless instruments are used on floating platforms to avoid
the difficulties associated with replacing reagents and properly disposing of the waste stream.
Details for each of these SWM station designs are provided in Guidance for Building Online Water
Quality Monitoring Stations (EPA. 2016d).
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Section 6: Information Management and Analysis
The data generated by the SWM stations must be converted into actionable information to achieve the
selected design goals and provide the utility with the maximum value for its investment in SWM.
Actionable information is produced by analyzing SWM data, along with supporting information, and
presenting relevant results to the end user in a manner that is easy to understand. To achieve these
objectives, an SWM information management system must
provide data storage, access, analysis, notification, and
visualization capabilities.
The development process discussed in this section is consistent
with the general principles of information management system
design presented in Section 4 of the SRS Integration Guidance
(EPA. 2015b). with additional considerations that are specific to
an SWM information management system. This section covers
the following topics:
Analysis and visualization techniques
SWM information management system architecture
SWM information management system requirements
6.1 Analysis and Visualization Techniques
SWM data is analyzed to identify changes in source water quality that require attention from utility
personnel and may prompt actions to meet the SWM design goals. Analysis of SWM data generates
information that visualization tools display in a manner that is easily interpreted and applied by utility
personnel. Analysis and visualization techniques will vary for each design goal as described below.
Preparation for SWM Data Analysis
To use SWM data effectively, it is first necessary to verify that it meets data quality objectives (e.g., accuracy and
completeness) and characterize normal variability:
1. Verify that the data being used for analysis meets data quality objectives. All available water
quality sensors produce data that exhibits an inherent level of noise and outliers on occasion. When
performing the types of analyses described in this document, it is important to have reliable data that
meets data quality objectives. Before using the data collected from SWM stations, obvious errors should
be removed or corrected, a process referred to as data validation. Data validation may be performed by
a computer at an SWM station or as part of the analytics layer of a centralized information management
system as described in Section 6.2.
2. Establish the normal variability, or baseline, for SWM water quality data. The data analysis
approaches described in this section rely on understanding the normal variability for each parameter at
each SWM location to establish a baseline.
Additional guidance on techniques for data validation and establishment of a baseline can be found in Exploratory
Analysis of Time-series Data to Prepare for Real-time Online Water Quality Monitoring (EPA. 2016f).
Analysis and Visualization to Optimize Treatment Processes
SWM for treatment process optimization involves monitoring SWM data in real-time to identify changes
in source water quality that require treatment process adjustments. It requires an understanding of the
relationships between source water quality and the process adjustments necessary to improve treatment
process performance. This knowledge can be gained through bench- or pilot-scale studies, or through
application of institutional knowledge developed through operation of the full-scale plant. Two methods
of analyzing SWM data to support treatment optimization are thresholds and treatment process models.
Information Utilization
During a forum with chief
information officers (ClOs) from
50 major utilities across the United
States, the ClOs estimated that
only 10 to 15 percent of the
information gathered by their
organizations is properly
evaluated. Automated analysis
and effective visualization of data
can help to address this
underutilization of collected data.
36
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Online Source Water Quality Monitoring
The use of thresholds to optimize treatment processes involves real-time monitoring of the parameters
that affect the treatment process performance and adjusting the process when the monitored parameters
cross previously defined thresholds. Most processes are impacted by multiple parameters, so individual
parameter thresholds should not be considered in isolation. To help operators identify potentially
significant changes in water quality, an alert can be generated based on a parameter crossing a threshold
(minimum or maximum). Threshold analysis is often visualized using time-series plots that show a
moving window of recently measured values along with the minimum and maximum thresholds, as
illustrated in Figure 6-1. The thresholds, shown as dashed orange lines, represent the range of variability
in which the current treatment process settings can achieve optimized treatment. In this example, the x-
axis displays the time of day in hours and the y-axis displays the parameter concentration in the units
specified in the legend. The information provided through these plots, along with operator knowledge
about the treatment process, can then be used to make process adjustments.
Source Water pH
Source Water Ammonia
1
1
c
o r-
5
4
0.1
1 1
0.06
0:00 2:00 4:00 6:00 8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00
pH - Treatment Process Thresholds
0:00 2:00 4:00 6:00 8:00
Ammonia (mg/L)
10:00 12:00 14:00 16:00 18:00 20:00 22:00
^Treatment Process Thresholds
Source Water TOC
Source Water Turbidity
1
20
n
n
1
1.5
1
-J
1
10
0:00 2:00 4:00 6:00 8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00
TOC (mg/L) Treatment Process Thresholds
0:00 2:00 4:00 6:00 8:00
Turbidity (NTU)
0:00 12:00 14:00 16:00 18:00 20:00 22:00
Treatment Process Thresholds
Note that this figure displays idealized data, without noise, to clearly demonstrate the concept of threshold analysis.
Figure 6-1. Time-Series Plots and Thresholds for Treatment Process Optimization
Thresholds must be defined for each monitored parameter and each treatment process. A combination of
statistical analysis of historic water quality data and knowledge of treatment process performance can be
used to establish thresholds for treatment optimization. Statistical analysis can be used to develop
thresholds based on typical variability in a water quality parameter over a relevant time period (e.g., daily
or weekly for highly variable parameters, monthly or seasonally for less variable parameters). Knowledge
of treatment process performance can help to correlate process settings with different source water quality
types. A five to ten percent factor of safety should be applied to thresholds such that a process will
continue to produce water of acceptable water quality as the parameter value begins to cross the
threshold. This provides operators with time to investigate and respond to a source water quality change.
37
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Online Source Water Quality Monitoring
The second analysis approach involves the use of treatment process models. These models codify the
relationship among influent water quality, treatment process settings, and treatment process effluent water
quality. Models for treatment processes can be categorized as mechanistic, statistical, or knowledge-based
(McEwen. 1998). Mechanistic models relate inputs and outputs to the fundamental properties of the
processes and use empirically determined coefficients to calibrate the model to a specific treatment plant.
Statistical models are used when reliable mechanistic models are unavailable; inputs are related to outputs
based on statistical analysis of historic data. Knowledge-based models use techniques such as neural
networks and expert systems to describe complex systems where there is a limited understanding of the
specific principles that drive the system. These models use knowledge of the inputs, outputs, human
experience, and past performance to predict future process performance.
Treatment process models use validated SWM data, current treatment process settings, and process
effluent water quality to determine the process adjustments necessary (e.g., chemical dosing, loading
rates) to maintain optimized treatment. If the model is connected to a supervisory control and data
acquisition (SCADA) system, it could be configured to automatically adjust treatment process settings. If
not, operators can manually adjust treatment process settings as described in Section 7.1.
Analysis and Visualization for Detection of Contamination Incidents
SWM for detection of contamination incidents involves monitoring SWM data in real-time to identify
water quality anomalies. Two methods of using SWM data to support detection of contamination
incidents are threshold analysis and automated anomaly detection systems (ADSs).
A simple approach for detecting contamination incidents uses thresholds for individual SWM parameters.
The thresholds are based on the normal variability of each parameter at each location so that a threshold
exceedance is indicative of a water quality anomaly. The use of individual parameter thresholds for the
detection of contamination incidents in drinking water distribution systems is discussed in detail in the
article Parameter Set Points: An Effective Solution for Real-Time Data Analysis (Umbcrg and Allgcicr.
2016).
Thresholds can be established using statistical analysis of historical data gathered over a representative
period, although it may be necessary to use specialized software packages to analyze the large volume of
SWM data needed to perform these analyses. Alternatively, the analytics necessary to calculate
statistically derived thresholds may be built into an information management system. Threshold values
are generally set to avoid excessive invalid alerts while maintaining sufficient sensitivity to detect
contamination incidents. If there are significant shifts in water quality, such as seasonal changes, unique
thresholds may need to be established for each time period with a significantly different water quality
baseline.
38
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Online Source Water Quality Monitoring
An example of a visualization technique to support threshold analysis is shown in Figure 6-2. In this
example, the thresholds used for treatment process optimization are shown as dashed orange lines, as
described in Figure 6-1. The red dashed lines indicate thresholds for detection of contamination incidents,
which are set at the 99.9th percentile, as calculated from a statistical analysis of six months of data. In this
figure, the thresholds for detection of contamination incidents are further from the typical parameter
values compared with the thresholds for treatment optimization. Also, with the exception of pH, only
upper thresholds were established for detection of contamination incidents because a contamination
incident would not be expected to decrease ammonia, TOC, or turbidity. The reason for the differences
between thresholds for treatment optimization and contamination incident detection is that the former are
intended to guide treatment process changes in response to typical water quality changes, whereas the
latter are intended to identify anomalies that are outside of the range of typical water quality variability.
Source Water pH
Source Water Ammonia
0.25
6
0.2
4
01 / ^
3
0.05
0
0:00 2:00 4:00 6:00 8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 0:00
pH - Treatment Process Thresholds Incident Threshold
0:00 2:00 4:00 6:00 8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 0:00
Ammonia (mg/L) -Treatment Process Thresholds
Incident Threshold
Source Water TOC
Source Water Turbidity
2.5
30
25
iฐ 1 \/~\
15 1 I M
i
5
0
0:00 2:00 4:00 6:00 8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 0:00
TOC (mg/L) -Treatment Process Thresholds Incident Threshold
0:00 2:00 4:00 6:00 8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 0:00
Turbidity (NTU) -Treatment Process Thresholds
Incident Threshold
Note that this figure displays idealized data, without noise, to clearly demonstrate the concept of threshold analysis.
Figure 6-2. Time-Series Plots and Thresholds for Detection of Contamination Incidents
More complex ADSs use software-based algorithms that are
generally able to analyze the behavior of multiple parameters
measured at a single monitoring location to identify anomalies.
Some ADSs require manual input of algorithm coefficients based on
guidelines provided by the developer and basic knowledge of the
monitored datastreams. These ADSs use an initial set of coefficients
that can then be modified as typical water quality patterns are better
characterized. Some ADSs learn normal variability using training
datasets to balance the number of invalid alerts against the
possibility of missing a true anomaly. These software tools may
include features that allow a user to assign a specific cause to alerts
and classify each as valid or invalid, which can reduce the future
occurrence of invalid alerts without compromising detection capabilities.
Anomaly Detection
Systems
ADSs that were evaluated as
part of the Event Detection
System Challenge (EPA.
2013a) under EPA's SRS
program include:
CANARY (EPA)
ana::tool (s::can)
Hach Event Monitor (Hach)
39
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Online Source Water Quality Monitoring
Prior to selecting an ADS, a utility should evaluate multiple options using representative historical data to
determine which option is able to most reliably differentiate between true water quality anomalies and
typical water quality variability at each SWM location.
A dashboard is a visually oriented user interface that integrates and displays data from multiple sources
spatially and graphically. An example of a GIS-based dashboard designed to display data from SWM
locations and United States Geological Survey (USGS) stations is shown in Figure 6-3. Additional
information resources that support the interpretation of water quality data, such as weather and
streamflow data, can be incorporated into a dashboard design. Presenting information from a variety of
resources in a spatial context can be valuable during the investigation of a water quality anomaly, as
discussed in Section 7.1. Additional information about the features and design of dashboards is available
in Dashboard Design Guidance for Water Quality Surveillance and Response Systems (EPA. 2015c).
Source Water Monitoring
Anytown, USA
*6 o
Specify Scales ~
Source Water Ammonia
INTAKE
1 Toolbar
Functions
Toolbar
Icon
SWM Location
9
SWM Location
With Alert
%
USGS Station
Q
SW Threat
&
Display Alert
Management Tool
Create
Bookmark
Annotate &
Measure
Look Up Address
On Map
V
Print
&
Display Attribute
Data
Display Legend
&
Figure 6-3. SWM Display showing Alert Status and Time-Series Data for an SWM Location
To support real-time analysis of SWM data, water quality baselines should be regularly updated to reflect
recent conditions. When there is a change in the baseline, threshold values or ADS settings will need to be
updated accordingly. The required frequency of these updates depends on the variability of the monitored
parameters at each SWM location. For example, updates to the baseline may coincide with seasonal
changes. Many ADSs can automatically adapt to a changing baseline as part of their learning algorithms.
40
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Online Source Water Quality Monitoring
When potential water quality anomalies are detected by any method, SWM information systems should
generate an alert and provide notifications to operators to inform them of water quality changes that
require attention. As operators may not have the time to frequently review new data as it is generated,
notifications should be provided using flashing icons on a screen, emails, or text messages. Where
possible, notifications should contain details about the alert (e.g., time, SWM location, alerting parameter,
current parameter value). An example of a text message notification of an SWM alert, and the associated
alert details available through the dashboard, is shown in Figure 6-4.
Messages SWM A/ert **
SWM alert generated on
2016/08/18 at 04:00.
Alert location = River Bend.
Alert parameters = TOC
and specific conductance.
See Event ID 111 in the
Alert Management Toolbox
0
Alert Management Toolbox
ID
Status
Component
Type
Pressure
Zone
Date/Time
108
Acknowledged
SWM
Turbidity
High Hollows
2016/07/05
09:45
109
Acknowledged
SWM
pH
Intake
2016/07/30
13:30
110
Acknowledged
SWM
TOC
South Flats
2016/08/03
11:15
R
Acknowledged
SWM
TOC
River Bend
2016/08/18
04:00 I
Region Code: River Bend Acknowledge: X
Status: Under Investigation
Acknowledged By; John Smith Time: 2016/08/18 04:00
Comment Thread: 2016/08/18 04:00 John Smith Acknowledgement
2016/08/18 04:08 John Smith reviewed recent
maintenance records for the SWM station at River
Bend. No issues reported
Add Comment:
Map Event Update Status
Figure 6-4. Text Message and Dashboard Alert Notifications
Analysis and Visualization for Monitoring Threats to Long-Term Water Quality
Monitoring threats to long-term water quality relies on the ongoing analysis of SWM data over the course
of multiple years to identify trends and sustained changes in the baseline. Information derived from SWM
can infonn development of strategies to respond to a deterioration in source water quality that impacts
utility operations and water quality goals.
Multiple years of data should be analyzed for a given parameter and location to distinguish statistically
significant changes in the baseline from typical seasonal patterns. After each parameter at each location
has been characterized, a systematic analysis can be performed to determine whether (1) the baseline for
multiple parameters has changed at a specific SWM location and (2) the baseline for a given parameter
has changed at multiple SWM locations. These results can help to assess whether the change is
widespread throughout the source water and watershed or isolated to a specific area.
41
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Online Source Water Quality Monitoring
A variety of visual and statistical techniques can be used to identify significant, sustained changes in the
baseline for a parameter. Examples include graphical analysis, hypothesis testing, correlations, and trend
analysis, as briefly described in Table 6-1. More detail about the types of statistical analysis appropriate
for characterizing long-term water quality are provided in Statistical Methods in Water Resources (TJSGS.
2002).
Table 6-1. Statistical Analysis Techniques for Characterizing Long-Term Water Quality
Type of Analysis
Statistical Methods
Example Applications
Graphical Data Analysis
Time Series
Display temporal trends in the data
Histograms
Display data sorted into meaningful categories
Box and Whisker Plots
Compare statistics for SWM data from different
SWM locations
Scatterplots
Explore a potential relationship between two
variables, such as flow and turbidity
Hypothesis Testing
(Nonparametric)
T-Test
Confirm that a specific parameter has changed
over a defined period of time
Rank-Sum Test
Determine whether the values of a parameter at
two different locations are similar or different
Matched Pair Testing
Determine whether a parameter has changed
from year to year
Correlation
Correlation Coefficient
Establish the strength of the relationship
between two items, e.g., recreational river
usage and source water turbidity
Linear Regression
Determine whether there is a statistically
significant relationship between two items, e.g.,
source water TOC and turbidity
Multivariate Analysis
Consider the combined impact of multiple
variables on a system or process
Trend Analysis
Mann-Kendall Test
Determine whether values either only increase
or only decrease
Seasonal Kendall Test
Determine whether parameters have changed
overtime, taking into account seasonal
variability
42
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Online Source Water Quality Monitoring
Figure 6-5 provides an example of a time-series plot used to display a long-term trend in water quality.
This figure shows a plot of monthly TOC averages as the blue line and the yearly TOC averages as the
red dotted line. The increasing trend in yearly TOC averages over a 10-year period can be clearly seen in
this chart. This is one of the simpler visualization approaches for exploring potential trends, and the
results of such simple analyses may lead to the use of more complex statistical techniques as presented in
Table 6-1.
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Figure 6-5. Example Plots of Monthly Average and Yearly Average for Source Water TOC
43
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Online Source Water Quality Monitoring
When considering multiple SWM locations in a watershed, a GIS-based presentation can provide an
overview of parameter changes across the entire monitored area. The example in Figure 6-6 shows the
GIS display of the watershed with the SWM locations color-coded to indicate the change in TOC over a
10-year period.
Source Water Monitoring
Anytown, USA
Specify Scales ~
10-Year Changes
No Change
+ 10
V
WTP
INTAKE
Figure 6-6. Geospatial Presentation Showing the Change in TOC over a 10-Year Period
6.2 SWM Information Management System Architecture
SWM information management functions can be integrated into an existing information management
system, or a dedicated SWM information system can be developed. In either case, a system will likely be
centralized (e.g., at a utility's control center), and data will be transmitted from remote monitoring
locations to this centralized system. The design of the information management system will be captured in
the architecture, which is a conceptual representation of hardware, software, and processes that are part of
the system.
Options for an SWM information management system architecture discussed in this document include:
SCADA system. Integrating SWM functions into an existing SCADA system.
Dedicated information management system. Implementing a dedicated information
management system to provide the functions required for SWM, such as analysis, notification,
and visualization.
Cloud-based solutions. Using cloud services to provide the functions required for SWM.
44
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Online Source Water Quality Monitoring
SCADA System
SWM stations can be added to an existing SCADA system, such as that used to monitor and control a
treatment plant. Familiarity with SCADA may make it relatively simple and inexpensive to incorporate
datastreams generated by SWM. An example of a SCADA architecture expanded to include SWM is
shown in Figure 6-7. This arrangement leverages existing SCADA elements, such as a historian for data
storage and a human machine interface (FIMI) for visualization of SWM data. The same type of
Programmable Logic Controllers (PLCs) used at existing monitoring locations can be used to provide
monitoring and control functions at SWM stations. However, an existing SCADA system may impose
some limitations on SWM information management, such as the functionality for visualization, the
number of users that can access the F[MI, and the types of water quality instrumentation that can be used.
Furthermore, utility information security policies may regulate connectivity outside of the utility, limiting
connections to external sources of information that may be useful for understanding the source water and
assisting with an investigation.
SWM STATION
Source
Water
|U
XP1
SWM
Instrumentation
Coagulation/
Filtration
Disinfection
Sedimentation
PLC 1
PLC 2
PLC 3
SWM PLC
I
SCADA Server
SCADA HMI
SWM: Source Water Monitoring
PLC: Programmable Logic Controller
HMI: Human Machine Interface
SCADA: Supervisory Control and
Data Acquisition
SCADA Historian
EXISTING TREATMENT PLANT SCADA
Figure 6-7, SWM Information Management as an Extension of an Existing SCADA Architecture
Dedicated Information Management System
A dedicated information management system for SWM may be useful when:
SWM produces data that is difficult to store in a SCADA historian. For example, spectral
absorbance over multiple wavelengths can generate a spectral profile as an array of 256 data
45
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Online Source Water Quality Monitoring
points for each sample. The design of some SCADA historians is not optimal for storing such
arrays, but alternate database structures can be built to store these complex datastreams
efficiently.
SWM requires access to data on networks that cannot be accessed by the SCADA system due to
security policies. For example, a requirement to display weather data or USGS flow data via an
internet connection may preclude the use of SCADA.
Remote access to SWM data is required, and security policies prohibit remote access to the
SCADA system.
The use of a dedicated SWM information management system provides greater flexibility for achieving
the required functionality, and it allows for connection with other information management systems,
within and external to the utility. Figure 6-8 illustrates a conceptual architecture for a dedicated SWM
information management system with connections to a treatment plant SCADA system, laboratory
information management system (LIMS), and external data from the National Weather Service and
USGS. This type of architecture can also incoiporate more powerful analytics and visualization tools to
assist with the investigation process.
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Online Source Water Quality Monitoring
Cloud-Based Solutions
Cloud-based solutions provide another option for SWM information management. There are three types
of cloud-based solutions:
A hosted cloud is owned and maintained by a third party where the utility pays only for the
portion of the cloud that it uses, usually on a lease-type of arrangement.
A private cloud is owned by the utility, but uses cloud technology to provide the required
services.
Proprietary clouds are provided by vendors of many water quality instruments to interact with the
instruments and collect the data generated.
Both SCADA-based and dedicated SWM information management systems can be implemented using
cloud technology.
A hosted cloud may be attractive for a utility that wants to contract development and operation of the
information management system as a third-party service rather than maintain the information technology
(IT) infrastructure in-house. This approach may also allow for expedited implementation of the SWM
information management system. The main advantage of a hosted system is that there is little capital
expenditure required as the utility does not need to purchase hardware and software for the system.
A private cloud provides the same capabilities as a hosted cloud except that the utility owns the hardware
and software. This requires capital expenditure to set up; however, the cloud would be under the utility's
control.
Proprietary clouds provided by instrumentation vendors are used to collect, store, and process data, and
provide a user interface for their specific sensors. This service often provides a low-cost and readily
available method for manually or automatically accessing the data directly for each one of the devices,
which can be useful when a small number of devices are deployed. However, this approach can present
challenges when the data in the proprietary cloud requires integration with other data that resides within
other utility information management systems. In many cases this integration may require the
development of unique software (often referred to as "listener" software) to identify that new data has
been uploaded to the cloud and transfer it to the utility system for further processing and storage.
6.3 SWM Information Management System Requirements
SWM information management systems are unique for every utility due in part to differences in existing
information management systems and capabilities, expertise of utility personnel responsible for
developing and using the information management system, and resources available to develop an
information management system to support SWM. Each utility will also establish unique design goals and
performance objectives for SWM. These factors collectively influence the manner in which the SWM
information management system is utilized by utility personnel and thus impact the requirements.
To develop an information management system that meets users" expectations and provides them with the
information they need, when they need it, and in a usable format, information management requirements
must be defined. This section references Section 4.2 of the SRS Integration Guidance (EPA. 2015b).
which describes a methodical, end-user driven process for developing requirements and selecting an
information management system.
Two categories of requirements need to be developed for an SWM information management system:
Functional requirements define key features and attributes of the system that are visible to end
users. Examples of functional requirements include the manner in which data can be accessed, the
47
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Online Source Water Quality Monitoring
types of tables and plots that can be produced through the user interface, the means by which
alerts are transmitted to utility personnel, and the ability to generate custom reports. Functional
requirements should be informed by end users.
Technical requirements are system attributes and design features that are often not readily
apparent to end users but are essential to meeting functional requirements and other design
constraints. Examples include attributes such as system availability, information security and
privacy, backup and recovery, data storage needs, and integration requirements. Technical
requirements are generally developed by IT personnel or derived from IT standards.
Functional Requirements
Before developing functional requirements, expected uses of the SWM information management system
should be defined. Expected uses are simply the manner in which users expect to interact with the system.
For example, users may want to review recent source water quality data daily to guide treatment plant
operations, be notified of anomalous water quality conditions, and access a variety of information
resources to investigate the cause of a source water quality anomaly. The expected uses of an information
management system will guide the development of detailed functional requirements, such as the examples
described in Table 6-2.
Table 6-2. Examples of SWM Information Management Functional Requirements
Title
Description
Presentation of SWM
Station Operating Status
Colored icons are used to identify the current operating status of each SWM station
on the GIS display using the following attributes:
Green - Normal operation, all systems functioning properly
Yellow - Some of the subsystems (e.g., sensors) malfunctioning
Grey - Station not communicating and assumed to be offline
Red - Station producing an ADS alert
Mouse Over and Drill Down
When users hover over an icon on the map, a pop-up box appears that displays
detailed data associated with the icon (e.g., values, time-stamps, location,
instrument status). A hyperlink is available in the pop-up box that opens a detailed
data history in the user interface (e.g., time-series plots for SWM parameters).
External Data Sources
The SWM information management system will provide a connection to and obtain
the latest information from:
USGS river flow and water quality data
National Weather Service data
Display of Overlays
Multiple overlays can be displayed at the same time. Overlays that may be
displayed concurrently include:
SWM station location and status
Current source water flow data
Recent water quality data from grab samples
Active spill reports
Generation of
SWM Station Reports
Reports can be manually generated for any time period, and a report can be
generated for a selected station that includes box-and-whisker plots for the
parameters at the station and statistics on station equipment diagnostics.
Remote Access
Notifications and summary information can be accessed remotely using mobile
devices, such as smartphones or tablets, over a secure connection.
Automated
Report Generation
The system will automatically generate customizable reports that provide validated
data, analysis output, time-series plots, and statistical summaries even when there
are no alerts produced in the reporting period.
Parameter Adjustment
The system will include a user interface that provides users with the ability to easily
adjust key parameters and display features without modifying the underlying code.
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Online Source Water Quality Monitoring
Technical Requirements
Technical requirements are often dependent on the functional requirements and should be developed after
the functional requirements have been defined. Generally, development of technical requirements is the
responsibility of IT personnel who consider the technical aspects of the SWM information management
system design that are necessary to meet the functional requirements. Technical requirements will also be
informed by IT policies, such as security protocols, and the need to adapt the system over time to
incorporate new functions, datastreams, and features. Examples of technical requirements are provided in
Table 6-3.
Table 6-3. Examples of SWM Information Management System Technical Requirements
Title
Description
Encryption
All interactions with the SWM information management system will be encrypted
via Secure Socket Layer.
Map Service Utilization
The SWM information management system will be able to read and display map
services provided by the utility's GIS using a configurable list of map services.
Size of the Operational
Data Store
The operational data store will provide ready access to the last 90 days of data for
all source data systems used in the SWM information management system.
Parameter Data Storage
The SWM information management system will provide storage of datastreams for
spectral profiles (256 data points per sample) and toxicity monitors.
External Data Sources
National Weather Service and USGS data will be accessed via a secure
connection.
Information resources associated with specific SW threats (e.g., spill reports, leak
detection alerts from SW threats, discharge rates) will be accessed using a secure
connection.
Design Flexibility and
Ability to Accommodate
New Requirements
Because the SWM system will be implemented in phases and expanded in the
future, the system will have the flexibility to incorporate additional datastreams,
monitoring locations, and external data sources.
The Information Management Requirements Development Tool (EPA. 2015f). a software package
designed to help users define and prioritize requirements for an information management system, can be
used to develop and document the requirements for an SWM information management system. This tool
is populated with common functional and technical requirements for an information management system
designed to support OWQM operations. It also provides a feature for generating a consolidated list of
functional and technical requirements that can be used to develop design and/or bid documents as
appropriate.
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Online Source Water Quality Monitoring
Section 7: Investigation and Response Procedures
Utilization of SWM data to guide utility decisions related to treatment operations and response to water
quality anomalies requires an investigation into the cause of a change in source water quality. Procedures
should be developed to guide these activities.
Investigation and response activities will be different for transient water quality anomalies versus
sustained, long-term water quality changes. Thus, this section provides guidance on the development of
two unique procedures, as briefly described below:
Investigation of and Response to SWM Alerts. This procedure supports treatment optimization
and detection of contamination incidents. Both of these design goals rely on alerts generated
when a transient water quality anomaly is detected. The procedure involves the investigation of
an alert to determine its cause and decide on immediate response actions to address a change in
source water quality. Examples of response actions include adjusting treatment process settings to
maintain optimized treatment or closing a source water intake if the source water has been
contaminated. Guidance for developing this procedure is provided in Section 7.1.
Investigation of and Response to Long-Term Water Quality Changes. This procedure
supports monitoring of threats to long-term water quality. It involves the investigation of
sustained changes to source water quality to determine the cause and inform the development of
long-term strategies to manage significant changes in the source water quality baseline. An
example of such a strategy is the implementation of a runoff control program to reduce
contaminant loadings from non-point sources of pollution. Guidance for developing this
procedure is provided in Section 7.2.
Once investigation and response procedures for the relevant design goals have been developed, they
should be tested and refined before putting them into practice. Section 7.3 provides guidance on the steps
necessary to implement these procedures, including training, preliminary operation, and real-time
operation.
7.1 Procedures for Investigation of and Response to SWM Alerts
For SWM design goals that rely on rapid response to transient changes in source water quality, such as
treatment optimization and detection of contamination incidents, the SWM information management
system should include a means of identifying an anomaly and generating an alert in real time (see Section
6.1). This section provides guidance on developing procedures for investigating and responding to SWM
alerts. The elements of this procedure should cover the following:
Alert Investigation Process. A detailed, sequential list of steps for investigating the cause of an
alert, as well as information resources to support an investigation.
Response Actions to Optimize Treatment Processes. A process for making treatment process
adjustments in response to a change in source water quality to maintain optimal performance.
Response Actions for Detection of Contamination Incidents. A process for making decisions
in response to a possible source water contamination incident.
Roles and Responsibilities. A list of all personnel who have a role in the investigation of an alert
or a response to a verified water quality anomaly.
The Template for Developing SWM Investigation and Response Procedures includes editable process
flow diagrams, checklists, and tables that can be used to build
utility-specific SWM procedures. The template can be opened
in Microsoftฎ Word by clicking the icon in the callout box.
[jr] J
This template provides an
editable SWM Investigation and
Response Procedure.
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Examples of alert investigation tools that support these procedures (e.g., quick reference guide, alert
investigation record) can be found in Section 5 of the SRS Integration Guidance (EPA. 2015b).
SWM Alert Investigation Process
An alert investigation process can be visually represented in a diagram that shows the progression of steps
from beginning to end. This simplified representation of the process allows individuals with
responsibilities for discrete steps to see how their activities support the overall investigation. Figure 7-1
provides an example of an alert investigation process flow diagram.
I
1. SWM alert
notification received
2. Investigate the
validity of the alert
J
Start of Process
Action Performed
Decision Step
End of Decision Tree
\
3. Is the alert valid
and indicative of a
real change in
water quality?
NO
/
| YES
5. Investigate the cause
of the water quality
change
4. Close the
investigation and
correct issue that
caused the invalid
alert
\
6. Is source water
contamination
possible?
/
NO
YES
7. Evaluate the
need to modify
treatment using
a "Treatment
Roadmap"
8. Collect
samples for
laboratory
analysis
9. Evaluate
response actions
using a
"Contamination
Incident Response
Decision Tree"
Figure 7-1. Example of an SWM Alert Investigation Process Flow Diagram
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Table 7-1 describes the steps of the alert investigation process depicted in Figure 7-1 providing:
Instructions for completing the step
The individual or position assigned to complete the step
Information resources that should be consulted during the step (see Table 7-2 for descriptions)
Table 7-1. Example SWM Alert Investigation Process Description
ID
Name
Assigned To
Information Resources
1
Designated personnel receive SWM alert
notification.
On-duty
plant operator
SWM user interface
Smartphone
2
Investigate the validity of the alert.
Evaluate recent SWM station maintenance records
and compare data from the alerting station against
patterns typical of equipment malfunction. If possible,
inspect the SWM station to determine whether it is
functioning properly.
Instrument
technician
SWM station
maintenance records
Sensor diagnostic tools
Data patterns for known
instrument problems
Results of SWM station
inspection
3
Is the SWM alert valid and indicative of a real
change in source water quality?
No-Go to Step 4.
Yes - Go to Step 5.
On-duty plant
operator
Findings from Step 2 of
the investigation
4
Close the investigation.
The SWM alert is not due to a real water quality
change. Correct the issue that caused the invalid
SWM alert.
Instrument
technician
Findings documented in
alert investigation record
5
Investigate the cause of the water quality change.
Review available information resources to determine
if the following caused the SWM alert:
Change in source supplying the treatment plant
Weather (e.g., rainfall)
Natural disasters (e.g., floods, fires)
Known pollution incident (e.g., spills)
Water quality
specialist
On-duty plant operator
National Weather Service
or local weather stations
USGS online stream and
watershed data
State environmental
protection agency
Spill reporting hotline
Visual inspection of the
waterbody
6
Is source water contamination possible?
No-Go to Step 7.
Yes - Go to Steps 8 and 9.
Water quality
specialist
Findings from Step 5 of
the investigation
7
Evaluate the need to modify treatment process
settings to maintain optimal performance.
Follow separate procedure to decide if and how to
adjust treatment process settings in response to the
change in source water quality
On-duty plant
operator
Treatment Process
Optimization Procedure
Treatment Roadmap
8
Collect samples for field or laboratory analysis.
Follow separate procedure for collecting samples and
deciding the analyses to conduct.
Water quality
technician
Sampling and analysis
procedures
9
Evaluate response actions to mitigate
consequences of possible contamination.
Follow separate procedure to decide how to respond
to the possible contamination incident.
Water quality
supervisor
Source Water
Contamination Incident
Response Procedure
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Table 7-2. Typical Information Resources Useful during the Investigation of an SWM Alert
Resource
Description
SWM Station Maintenance
Records
Information about recent maintenance activities, ongoing sensor issues, and
previous sensor problems
Sensor Diagnostic Tools
Some sensors include diagnostic tools that evaluate sensor performance in
real time
USGS Monitoring Stations
Results from USGS water quality and stream gauge monitoring stations in
the watershed
Watershed Monitoring Programs
Results of watershed monitoring or surveillance programs (e.g., formal
source water monitoring collaborative) as well as informal monitoring
networks (e.g., citizen science initiatives, field observations)
National Weather Service
Current and recent weather conditions in the watershed and upstream areas
that impact water quality in the watershed
Local Weather Monitoring
Station
Data from weather monitoring stations located in the watershed can provide
greater resolution than that from the National Weather Service
State Environmental Protection
Agencies
Reports of ongoing environmental monitoring programs (e.g., for nutrient
pollution, algal blooms), environmental emergencies (e.g., flooding, fires),
and regulated discharges
Spill Reporting Hotlines
Reports of recent spills into the source water
Owner/Operator of an SW Threat
Alerts from spill detection systems, reports of recent incidents at an SW
threat, and observations of current facility operations
Other Utility Information
Management Systems
Information from operational control systems and work management
systems that may provide information about utility activities that could have
contributed to the source water quality change (e.g., a change in the source
water supplying the treatment plant)
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At the conclusion of the alert investigation process, the cause of the alert should be documented. Table
7-3 lists and describes common causes of alerts. The causes are grouped into invalid alerts (triggered by
something other than a true change in source water quality) and valid alerts (triggered by a true change in
source water quality). Invalid alerts typically occur more frequently than valid alerts, especially during the
initial phases of system startup.
Table 7-3. Common Causes of Invalid and Valid SWM Alerts
Alert Cause
Description
Invalid Alerts
Equipment Issue
Inaccurate data values caused by a sensor maintenance activity, sensor
malfunction, loss of power, or a data transmission error
Flow-cells may produce inaccurate data if there is an interruption in the supply
of water to the flow-cell
Immersed sensors may produce inaccurate data if they are not submerged or
are buried in sediment
Data Analysis Issue
An artifact of the data analysis system in which an alert is generated even
though data is accurate and within the normal range of values and variability
Valid Alerts
Change in Source Water
Supply
For treatment plants that use multiple source waters, a water quality change
caused by a change in the source supplying the plant
Weather
A water quality change caused by a weather event (e.g., rainfall, snowpack
melt)
Natural Disaster
A water quality change, and possibly a contamination incident, caused by a
natural disaster (e.g., flood, fire, landslide)
Environmental Condition
A water quality change, and possibly a contamination incident, caused by an
environmental condition (e.g., lake turnover, an algal bloom)
Discharge
A contamination incident caused by a discharge from a storm water outfall,
wastewater outfall, or other NPDES permit holder
Spill
A contamination incident caused by a spill or unauthorized discharge from an
SW threat (e.g., chemical storage facility, watercraft)
If an alert is determined to be valid but unrelated to contamination, the water quality change is evaluated
to determine whether it could impact the ability of the utility's treatment plant to meet treatment targets.
If all reasonable causes of the water quality change that triggered the alert have been considered and ruled
out, contamination is deemed possible. At this point, samples should be collected and analyzed in an
attempt to confirm and identify the contaminant, and contamination incident response procedures should
be activated.
Response Actions to Optimize Treatment Processes
If the investigation of a valid alert concludes that a source water quality change is not due to
contamination, the change may still warrant a response for the purpose of treatment optimization (Step 7
in Figure 7-1). This response will typically be guided by a treatment roadmap or a treatment process
model.
A treatment roadmap is a set of instructions for adjusting treatment processes to achieve treatment targets
based on information generated by SWM. These instructions are typically developed using historical data
from full-scale operations to establish relationships between optimal treatment process settings and a
specific source water quality type. Typically, multiple water quality parameters (e.g., turbidity, TOC,
alkalinity, pH) are used to define a source water quality type. The roadmap specifies the range of source
water quality parameter values under which a set of treatment process settings would achieve defined
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treatment targets. A treatment process optimization procedure, such as that shown in Figure 7-2, guides
the application of a treatment road map based on SWM data.
=f
I
1. Turbidity
monitored
at plant influent
Y
2. Turbidity within
/ upper and lower
\ threshholds?
| NO
3. Make initial
adjustments to the
full-scale process
4. Perform
jar testing
5. Evaluate zeta
potentials for
settled water
treatment targets
T
YES
9. Continue to
operate under
current treatment
process settings
Start of Process
Action Performed
Decision Step
End of Decision Tree
YES
6. Determine
required process
adjustments
t
7. Implement
full-scale process
adjustments
t
8. Does the NQ
process effluent meet )
Figure 7-2. Example Treatment Optimization Procedure Flow Diagram
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Online Source Water Quality Monitoring
Table 7-4 describes the steps of the treatment process optimization procedure depicted in Figure 7-2 and
lists responsibilities and information resources used during each step.
Table 7-4. Example Treatment Process Optimization Procedure Description
ID
Name
Assigned To
Information Resources
1
Real change in turbidity detected and verified.
On-duty plant
operator
SWM user interface
Smartphone
2
Is the turbidity data within the thresholds for the
current treatment process settings?
Yes - Go to Step 9.
No-Go to Step 3.
On-duty plant
operator
SWM user interface
Treatment roadmap or
standard operating
procedure
3
Make initial adjustments to the full-scale treatment
process.
Using a treatment roadmap, standard operating
procedure, or operator judgement, adjust treatment
process settings to treat the new source water quality.
On-duty plant
operator
Treatment roadmap or
standard operating
procedure
4
Perform jar testing.
Conduct jar tests with the source water using a range of
doses likely to encompass the dose required to treat the
new source water quality.
Water quality
technician
Jar testing standard
operating procedure
5
Evaluate zeta potentials for settled water.
Measure the zeta potential of the settled water from the
jar tests and compare with the zeta potential of the
settled water from the full-scale plant.
Water quality
technician
Zeta potential
measurement procedure
6
Determine required process adjustments.
Use the results from the jar tests and zeta potential
measurements, along with the treatment roadmap, to
refine the treatment process settings for the full-scale
plant.
On-duty plant
operator
Results from Steps 4 and 5
Treatment roadmap or
standard operating
procedure
7
Implement full-scale process adjustments.
Implement the process adjustments determined in Step 6
and monitor the process to determine whether the
process adjustments have brought the process back into
the range of optimized performance.
On-duty plant
operator
Treatment roadmap or
standard operating
procedure
8
Does the process effluent meet treatment targets?
Yes - Go to Step 9.
No-Go to Step 6.
On-duty plant
operator
Results from treatment
process monitoring
9
Continue to operate under the current treatment
process settings.
On-duty plant
operator
N/A
An alternative to a treatment process optimization procedure is use of a treatment process model, which
can be used to predict optimal treatment process settings. If the treatment process model is connected to
the SCADA system, it can be configured to automatically adjust treatment process settings to maintain
optimal treatment.
Treatment process monitoring can be used to confirm that the treatment process adjustments have had the
desired effect. Confirmation can be accomplished through measurement of water quality in the process
effluent using online instrumentation or grab sampling. Additionally, visual inspection of flocculation
(floe size) and sedimentation (floe carry over) can provide an operator with a sense of whether the process
is operating properly. If treatment process monitoring indicates that treatment targets are not being met,
processes can be further adjusted.
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Response Actions for Contamination Incident Detection
If the investigation of a valid alert concludes that source water contamination is possible, S&A activities
should be implemented in an attempt to confirm that contamination has taken place, identify the
contaminant, and determine its concentration as noted in Step 8 of Figure 7-1. Building Laboratory
Capabilities to Respond to Drinking Water Contamination (EPA. 2013b) provides guidance on
identifying analytical methods and laboratories to test for contaminants of concern during a possible
contamination incident.
As described in Figure 7-1, Step 9, response actions should be evaluated with respect to their ability to
mitigate the consequences of a contamination incident to a utility and its customers. Decisions regarding
an appropriate response to a source water contamination incident depend on a number of factors, such as:
Confidence in the information indicating that the source water has been contaminated
Whether the identity of the contaminant is known, and if known, the characteristics of the
contaminant
The risk that contaminated water presents to the utility and its customers
Response options available to the utility
Consequences of implementing response actions (e.g., impact on sanitation, firefighting,
businesses, the local economy)
The logic for making these response decisions can be codified in a decision tree, as shown in the example
in Figure 7-3.
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Online Source Water Quality Monitoring
1. Source water
ฆ ฆ vvunv*i
^contamination is possible JT
T
YES
3. Close the
intake and
continue the
investigation
\
4. Can the
intake remain
closed until the
contamination
incident passes?
| YES
5. Verify that the
contamination
incident has
passed, open the
intake, and
resume normal
operations
\
2. Can the intake
be closed?
/
NO
I Start of Process
Action Performed
Decision Step
End of Decision Tree
| NO
6. Is the identity of
contaminant known?
| YES
10. Can the treatment
plant remove or neutralize
the contaminant?
| YES
11. Modify treatment as
necessary and monitor
finished water quality
12. Has the
contaminant concentration
been reduced to
acceptable levels?
Iyes
NO
7. Continue the
investigation
NO
8. Is contamina- YES
\ tion still possible?/
| NO
9. Close the
3T1^
NO
13. Continue to
treat and monitor
for the contaminant
until the
contamination
incident has passed
14. Activate
"Distribution System
Figure 7-3. Example Source Water Contamination Incident Response Decision Tree
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Table 7-5 describes the steps of the contamination incident response decision tree depicted in Figure 7-3
and lists responsibilities and information resources used during each step.
Table 7-5. Example Source Water Contamination Incident Response Decision Tree Description
ID
Name
Assigned To
Information Resources
1
Source water contamination is possible.
And potentially contaminated water could enter the
intake currently in use.
Water quality
supervisor
SWM user interface
Smartphone
2
Can the intake be closed?
Yes - Go to Step 3.
No-Go to Step 6.
Treatment plant
supervisor
Current raw water
storage
Availability of an alternate
source or intake
3
Close the intake and continue the investigation.
Determine how long the intake can remain closed.
Determine how long the potentially contaminated
water will pose a risk to the treatment plant.
Treatment plant
supervisor
Water quality
supervisor
Current system storage
and demand
Information about the
contamination incident
4
Can the intake remain closed until the
contamination incident passes?
Yes - Go to Step 5.
No-Go to Step 6.
Treatment plant
supervisor
Estimate of the time
when storage will be
exhausted
Estimate of the time until
contamination incident
passes the intake
5
Verify that the contamination incident has
passed, open the intake, and resume normal
operations.
Collect samples at the intake and analyze them for
suspected contaminants or indicators.
Water quality
supervisor
Results from sampling
and analysis
Information about the
contamination incident
6
Is the identity of the contaminant known?
No-Go to Step 7.
Yes - Go to Step 10.
Water quality
supervisor
Information about the
contamination incident
7
Continue the investigation.
Gather information and collect samples for analysis in
an attempt to identify the contaminant (or rule out
potential contaminants).
Water quality
supervisor
Information about the
contamination incident
Investigation procedures
and resources
8
Is contamination still possible?
No-Go to Step 9.
Yes - Go to Step 1.
Water quality
supervisor
Information about the
contamination incident
Results from sampling
and analysis
9
Close the investigation.
Contamination has been ruled out. Close the
investigation and return to normal operations.
Water quality
supervisor
Findings documented in
alert investigation record
10
Can the treatment plant remove or neutralize the
contaminant?
Yes - Go to Step 11.
No-Go to Step 14.
Treatment plant
supervisor
Water Contamination
Information Tool
Treatability Database
11
Modify treatment as necessary and monitor
finished water quality.
Confer with stakeholders to determine an acceptable
contaminant concentration in finished water. Collect
samples from the finished water for analysis, and
arrange for rapid laboratory analysis.
On-duty plant
operator
Water quality
technician
Health advisories
Treatment process
standard operating
procedures
Sampling and analysis
procedures
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ID
Name
Assigned To
Information Resources
12
Has the contaminant concentration been reduced
to acceptable levels?
Yes - Go to Step 13.
No-Go to Step 14.
Water quality
supervisor
Results from sampling
and analysis
Input from the drinking
water primacy agency
and other stakeholders
13
Continue to treat and monitor the contaminant
until the contamination incident has passed.
Collect samples in the plant influent and finished
water and analyze for the target contaminant(s)
On-duty plant
operator
Water quality
technician
Information about the
contamination incident
Results from sampling
and analysis
14
Activate the "Distribution System Contamination
Response Plan"
If contaminated water has entered the distribution
system, or is likely to, take actions to mitigate
consequences and protect public health. These
actions are documented in a Distribution System
Contamination Response Plan.
Water quality
supervisor
Distribution System
Contamination Response
Plan
Information about the
contamination incident
Results from sampling
and analysis
The example incident response decision tree shown in Figure 7-3 considers three possible responses to
source water contamination:
Closing the intake can be the most effective response strategy by preventing contaminated water
from coming into contact with utility infrastructure and customers. The ability to close an intake
will depend on the availability of alternate raw water sources, availability of distribution system
interconnections with neighboring utilities, distribution system storage, anticipated customer
demand, and the expected duration of the contamination incident. Even if the intake can remain
closed for only a short period, this action provides additional time to collect and analyze samples
in order to identify the contaminant and determine its concentration. Ideally, the intake could
remain closed until contaminated water no longer presents a risk to the utility or its customers.
Modifying treatment to remove or neutralize the
contaminant may be effective depending on the specific
contaminant that is present and the treatment processes
that are utilized. However, this response option should
only be considered if the identity and approximate
concentration of the contaminant are known. Resources
such as the Water Contaminant Information Tool (EPA.
2016h) and the Treatability Database (EPA. 2016i) can be used to evaluate the potential of
various treatment processes to remove or neutralize specific contaminants. If this response
strategy is used, samples of finished water should be collected and analyzed to ensure that the
contaminant has been removed.
Activating a Distribution System Contamination Response Plan if there is a risk that
contaminated water has or will pass into the distribution system at concentrations above
acceptable levels. A Distribution System Contamination Response Plan is an annex or appendix
to a utility's Emergency Response Plan (ERP), which guides utility decisions for responding to
distribution system contamination. Potential response actions considered at this stage include
isolation of portions of the distribution system to minimize the spread of contaminated water,
diversion and flushing to remove contaminated water from the distribution system, and public
notification and use restrictions to prevent customers from coming into contact with contaminated
water. A template and guide for developing a Distribution System Contamination Response Plan
can be found in Guide for Developing a Distribution System Contamination Response Plan (EPA.
20160.
Harmful Algal Blooms
EPA's website for Cyanobacterial
Harmful Algal Blooms provides
information and resources useful for
treating HABs (EPA. 2016q).
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Activating a Risk Communication Plan in anticipation of the public becoming aware of the
incident, regardless of whether there is a potential risk to the public. Planning for risk
communication should begin as soon as source water contamination is considered to be possible.
Guidance for issuing public notification and communicating with customers during a drinking
water contamination incident is provided in Developing Risk Communication Plans for Drinking
Water Contamination Incidents (EPA. 2013c).
Roles and Responsibilities
Roles and responsibilities will need to be assigned for implementation of each activity during the
investigation of and response to SWM alerts.
Alert investigation and response for treatment optimization will likely occur with some regularity,
especially in surface water sources with frequent changes in water quality. As such, these procedures
should be incorporated into routine operations, and roles and responsibilities for implementing these
procedures should align with existing job functions to the extent possible. Leveraging existing expertise
in this manner will reduce the amount of new training required and can result in increased acceptance of
new responsibilities. Table 7-6 provides an example of roles and responsibilities for investigating alerts
and adjusting treatment processes for optimal performance.
Table 7-6. Example Roles and Responsibilities during SWM Alert Investigations and Treatment
Optimization
Role
Description of Responsibilities
On-duty Plant Operator
Receives notification of alerts
Assesses the validity of the alert and determines if it may be indicative of a real-
water quality change
Notifies other utility personnel with a role in the investigation
Adjusts treatment processes to maintain optimal performance
Monitors treatment process to verify performance
Water Quality Technician
Performs jar testing
Collects samples for field or laboratory analysis
Water Quality Specialist
Reviews the source water quality data that generated the alert
Reviews the results of investigations for previous alerts with similar water quality
patterns
Investigates potential causes of the alert
Instrument Technician
Provides information about recent sensor issues or equipment maintenance
Conducts an on-site inspection of the SWM station that generated the alert to
determine whether it is operating properly
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Response actions implemented following a determination that source water contamination is possible may
include significant deviations from normal operations (e.g., closing an intake) and thus will often require
a higher level of authorization than is typical for normal operations. As such, members of a utility's senior
management team will likely play a role in making decisions. Table 7-7 provides an example of roles and
responsibilities during response to source water contamination. Some of these roles and responsibilities
may be covered, at least in a general manner, in a utility's ERP.
Table 7-7. Example Roles and Responsibilities during Response to Source Water Contamination
Role
Description of Responsibilities
Utility Director
(Incident Commander)
Decides if and when to implement the Incident Command System
Reviews and approves significant response decisions
Directs and oversees implementation of the response
Public Information Officer
Implements the Risk Communication Plan
Coordinates communications among partners and stakeholders
Prepares for and implements public notification plans
Water Quality Supervisor
Coordinates sampling and analysis efforts
Investigates the characteristics of confirmed or probable contaminants
Verifies proper QA/QC on field and laboratory results
Decides if and when to implement the Distribution System Contamination
Incident Response Plan
Treatment Plant
Supervisor
Evaluates the ability of treatment processes to remove or neutralize a
contaminant
Directs and oversees implementation of operational response actions such as
closing the intake or modifying treatment
Water Quality Technician
Collects samples for field or laboratory analysis
Supports monitoring of treatment process performance
Laboratory Personnel
Conducts laboratory analyses on water samples
Because possible source water contamination incidents rarely occur, these procedures will be
implemented infrequently. To maintain familiarity with these procedures, they should be exercised at
least once per year. Resources to plan and implement exercises are described in Section 7.3.
7.2 Procedures for Investigation of and Response to Long-Term
Source Water Quality Changes
For the SWM design goal of monitoring threats to long-term water quality, the SWM information
management system should include a means of identifying statistically significant changes in the source
water quality baseline. This section provides guidance for investigating and responding to a long-term
change in source water quality. The elements of this procedure include:
Investigation Framework. A process that guides the investigation into the cause of a sustained
change in source water quality.
Response Framework. A process used to identify, evaluate, and select strategies to manage a
sustained degradation in source water quality.
Roles and Responsibilities. A list of all personnel who have a role in the investigation of or
response to a sustained change in source water quality.
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Investigation Framework
Monitoring threats to long-term water quality involves the analysis of source water quality trends over the
course of multiple years to identify sustained, and potentially irreversible, changes in the source water
quality baseline. This is accomplished through the routine analysis of SWM data using the techniques
described in Section 6.1. The purpose of the investigation framework is to attribute water quality changes
to a cause, which will inform the development of mitigation strategies.
The investigation considers the locations where a long-term change in source water quality has occurred
to determine the geographic extent of the change. Furthermore both the locations and the parameters that
have changed can be useful in identifying SW threats responsible for a degradation in water quality.
Identification of the cause(s) of a sustained change in source water quality is necessary for evaluating the
impact of the change on utility operations and developing effective mitigation strategies. This process will
require consideration of a variety of information resources, such as those listed in Table 7-8.
Table 7-8. Typical Information Resources Useful to the Investigation of Sustained Change in
Source Water Quality
Resource
Description
National Weather Service
Trends in key weather variables (e.g., temperature, precipitation, cloudy/sunny
days) over the past several years
Local Weather
Monitoring Station
If the data available from the National Weather Service or other weather
services is insufficient, data from weather monitoring stations located in the
watershed may provide the necessary level of detail.
Climate Resilience Evaluation
and Awareness Tool (CREAT)
CREAT uses climate models to predict changes in key weather variables
under various climate change scenarios. The information generated by
CREAT can be used as inputs to hydrology models, which in turn may be used
to estimate future chanaes in source water qualitv (EPA, 2012).
Facility Owner/Operators
Discharge data over the past several years, including flow and quality
Watershed Surveys
Watershed surveys (conducted by foot, vehicle, or drone), informed by data
generated through SWM, to identify potential sources of pollution.
Focused Sampling
and Analysis
Sampling programs designed to provide a full characterization of water quality
in a specific area over a limited period of time, informed by data generated
through SWM
USGS Watershed
Monitoring Data
Basic water quality parameters (e.g., pH, temperature, specific conductance)
along with flow and depth data over the past several years
Watershed Monitoring
Programs
Results of watershed monitoring or surveillance programs (e.g., formal source
water monitoring collaborative) as well as informal monitoring networks (e.g.,
citizen science initiatives, field observations)
Watershed Stakeholders
Information from watershed stakeholders and partners about the health, uses,
and features of the watershed
Land-use Maps
and Satellite Imagery
Graphical representations of land use in the watershed, viewed over the past
several years
Land-use Projections
Documentation of planned uses of land areas in the watershed over the next
several years
Physical Changes
to the Source Waterbody
Man-made or natural activities that change the physical condition of the
waterbody, such as dredging operations and rechanneling
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Response Framework
Identification of the probable cause(s) of a long-term degradation in source water quality can provide the
basis for developing a mitigation or restoration strategy. These strategies may include efforts to slow the
deterioration of the source water, reverse the deterioration, or adapt to the new source water quality
baseline. While the most effective strategy will depend on the specifics of the SW threats, the watershed,
and utility resources, a few potential strategies include:
Reducing contaminant loadings from specific point sources of pollution, either by reducing flow
or reducing contaminant concentrations prior to discharge
Reducing contaminant loadings from non-point sources of pollution through strategies such as
runoff control programs
Convincing local authorities and land owners to alter their land-use policies to reduce
contamination in the watershed
Implementing additional drinking water treatment capable of handling the projected source water
quality
Developing a new drinking water source
Approaches to mitigate a deterioration in source water quality will be strategic and may be implemented
over the course of several years. These strategies should be incorporated into existing source water
protection planning activities. A number of resources are available to support local source water
protection initiatives (EPA. 2016k; SWC. 2016).
After a mitigation strategy has been implemented, data from SWM can be used to assess the efficacy of
the strategy. If the desired change is not realized within a reasonable amount of time, the strategy may
need to be altered or discontinued.
Roles and Responsibilities
Roles and responsibilities will need to be assigned for implementation of each activity necessary to
monitor long-term water quality. Implementation of these activities will require front-line personnel to
implement investigation activities, planners to consider potential mitigation strategies, senior management
to decide which mitigation strategies to implement, and stakeholders to commit to strategies that are
outside of the utility's control. Table 7-6 provides an example of roles and responsibilities for monitoring
of threats to long-term water quality. While many of these roles are assumed by utility personnel, other
stakeholders may be engaged, such as managers of recreational uses of the waterbody, land use managers,
local regulatory authorities, and government agencies (e.g., U.S. Army Corps of Engineers).
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Table 7-9. Example Roles and Responsibilities for Monitoring Threats to Long-Term Water Quality
Role
Description of Responsibilities
Utility Director
Selects strategies to implement to mitigate the effects of a degradation in source
water quality
Ensures the availability of sufficient resources to implement the selected
strategies
Water Quality Manager
Manages the analysis of long-term trends in source water quality
Oversees the investigation into the cause of a sustained change in source water
quality
Evaluates strategies for mitigating the effects of a degradation in source water
quality
Water Quality Specialist
Performs detailed review of long-term trends in source water quality
Oversees water quality or watershed surveys to investigate the cause of a
sustained degradation in source water quality
Considers the results of climate, weather, and water quality modeling and
forecasting when assessing the cause of a sustained change in source water
quality
Plant Supervisor
Evaluates the ability of existing or modified treatment processes to adequately
treat the projected source water quality baseline
Engineers and Planners
Evaluates the ability of new, or significantly retrofitted, treatment processes to
adequately treat the projected source water quality baseline
Provides information on long-term programs and develops requirements for
protecting the source water
Community and
Stakeholders
Provides input to, and collaborate on, long-term programs to protect source water
quality.
Due to the long-term, strategic nature of these activities, implementation of this procedure will likely be
intermittent and sequential. For example, an investigation into the potential causes of a sustained change
in source water quality will occur only after analysts have confirmed the trend. Furthermore,
consideration of possible mitigation strategies will occur only after the cause of the change in source
water quality has been identified and is determined to have significant implications for utility operations.
7.3 Implementation of SWM Procedures
This section describes a suggested process for putting SWM procedures into practice. Recommended
activities include:
Training and Exercises
Preliminary Operation
Real-time Operation
Training and Exercises
Training and exercises are necessary to ensure that all utility personnel with a role in SWM investigation
and response procedures are aware of their responsibilities. It is suggested that training on these
procedures include the following:
An overview of the purpose and design of SWM
A detailed description of the investigation and response procedures
A review of checklists, quick reference guides, user interfaces, and other tools available to
support alert investigation and response activities
Instructions for documenting the results of alert investigations
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Section 6 of SRS Integration Guidance (EPA. 2015b) provides general guidance on implementing a
training and exercise program. In general, classroom training is used first to orient personnel to their
responsibilities during implementation of new procedures. Once they are comfortable with the
procedures, drills and exercises provide the opportunity to practice implementing their responsibilities in
a controlled environment. The SRS Exercise Development Toolbox (EPA. 20161) is an interactive
software program developed to assist utilities in the design and execution of exercises.
Preliminary Operation
Following initial training, a period of preliminary operation allows personnel to practice their
responsibilities before transitioning to real-time operation. For example, personnel can be asked to
investigate alerts in batches as they have time, not necessarily as alerts are generated. The duration of
preliminary operation will depend on how quickly personnel become proficient with operating the system
and implementing their responsibilities under the procedures, but a minimum duration of six months is
recommended.
One useful way to provide practice and support during this period is to hold regular meetings with all
investigators to discuss recent data and alerts. It is generally most effective if participants are asked to
perform specific analyses or alert investigations before each meeting and then discuss conclusions,
observations, insights, and challenges as a group. The frequency of these meetings would likely decrease
as the group gains more experience in conducting investigations.
Preliminary operation provides an opportunity for investigators to clarify responsibilities, streamline the
procedures, refine alert investigation tools, and better integrate SWM responsibilities into existing job
functions. Also, the rate of invalid alerts may be higher than desired during preliminary operations, but
this experience can be used to fine-tune the ADS to achieve the desired balance between detection
capabilities and occurrence of invalid alerts.
Real-Time Operation
During real-time operation, personnel are expected to fully execute their responsibilities and investigate
all alerts as they are generated. Also, SWM response procedures are implemented if an alert is determined
to be valid. The transition from preliminary to real-time operation, including timing and expectations for
how investigations are performed and documented, should be clearly communicated to all personnel with
a role in SWM. Furthermore, sufficient time in the workday must be allocated for personnel to investigate
alerts as they are generated. If the ADS is properly configured to minimize the occurrence of invalid
alerts, this time commitment will be minimal.
As part of real-time operation, investigation and response procedures may need to be updated to maintain
their usefulness. Recommendations for updating procedures include:
Designate one or more individuals with responsibility for maintaining alert investigation materials
Establish a review schedule (an annual review should suffice in most cases)
Review the record of alert investigations, conduct tabletop exercises, and solicit feedback from
investigators to identify necessary updates
Track and review the time required to complete investigations and implement response actions, and
update the procedures if times are not acceptable
Establish a protocol for submitting and tracking change requests
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Section 8: Example of SWM Design
This section presents a hypothetical example of a comprehensive SWM design process using the
principles presented in the previous sections of this document. Section 8.1 presents the overall design
approach, while Sections 8.2 to 8.6 describe each design element.
8.1 Design Approach
A hypothetical drinking water utility, Anytown Water, uses river water and a storage reservoir as its
sources. The utility uses conventional treatment processes that include pretreatment (PAC and
permanganate), coagulation/sedimentation (ferric chloride), filtration (dual media), and disinfection (free
chlorine).
As part of its commitment to producing high-quality drinking water for its customers, Anytown Water
wants to use SWM data to optimize its treatment processes. To do so, the following treatment targets
were established:
Turbidity Target. Achieve turbidity levels in the filter effluent of 0.10 Nephelometric Turbidity
Units (NTU) 95 percent of the time. This treatment target exceeds regulatory requirements and is
intended to improve barriers to Cryptosporidium and Giardict, as well as remove particles that
could shield other pathogenic organisms from free chlorine during the disinfection process.
TOC Removal Target. Achieve 50 percent TOC reduction through enhanced coagulation, which
helps the utility to meet its goal to keep total trihalomethane at or below 75 percent of the
maximum contaminant level.
Anytown Water also recognizes the potential for spills and other contamination threats in the source water
due to several industries located near the river banks upstream of the drinking water intake. Thus, the
utility is interested in using SWM data to provide timely detection of contamination incidents.
Additionally, the utility wants to monitor long-term trends in source water quality to inform the selection
of source water protection strategies and evaluate the efficacy of those strategies that are implemented.
Based on these considerations, the utility is designing SWM to support optimization of treatment
processes, detection of contamination incidents, and monitoring threats to long-term water quality.
Performance objectives were established for operational reliability, information reliability, and
sustainability, which serve as metrics for evaluating the effectiveness of SWM implementation.
To inform the design of SWM for the purposes of detecting contamination incidents and monitoring
threats to long-term water quality, the project team used DWMAPS to identify stationary threats and
consulted with the United States Coast Guard to identify potential mobile threats on the river source.
Through these resources, more than two dozen potential SW threats were identified, and the
characteristics described in Section 2.3 were gathered and documented for each threat. The project team
conducted a risk assessment that considered short-term risks due to contamination incidents and threats to
long-term water quality. The results of the risk assessment produced a list of prioritized SW threats that
could cause (1) a short-term contamination incident and (2) a long-term degradation in source water
quality. The assessment identified a total of five high-priority SW threats, three near the river and two
near the reservoir, as shown in Figure 8-1. Summaries of the risk assessment results for high-priority SW
threats of source water contamination and long-term source water quality are presented in Tables 8-1 and
8-2, respectively.
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^ Intake
Reservoir
Intake
Blending Facility
^
Distribution
System
Media Filtration
Disinfection
Pretreatment
Contror
Center
Coagulation/
Sedimentation
SW Threat ^ Control Point
Figure 8-1. Location of High-Priority SW Threats for Anytown Water
Table 8-1. High-Priority SW Threats of Source Water Contamination for Anytown Water
ID
SW Threat
Potential
Contaminants
Rationale for Risk Assessment Scoring
Risk
Score
A
Commercial
Barges
(Mobile Threat
- River)
Hydrocarbons
Unknown
Organics
Unknown
Inorganics
Large volumes of fuel and unknown cargo are stored on
commercial barges and transported along the river.
Likelihood. High: While a limited number of accidental
spills have been reported along the river upstream of the
utility intake over the past decade, commercial barge traffic
has doubled over the past two years, increasing the
probability of accidents and spills.
Vulnerability. High: The treatment plant can remove
hydrocarbons at concentrations in the sub mg/L range,
however, higher concentrations would likely overwhelm and
pass through treatment. Furthermore, the ability of the
treatment plant to remove unknown contaminants that
could be in the cargo is unknown.
Consequence. High: A high probability exists that at least
some of these contaminants could damage utility
infrastructure or pass through to the customer and create a
potential public health issue. Furthermore, hydrocarbons
would be very difficult to clean from the distribution system
and premise plumbing systems, and remediation would
likely be difficult, expensive, and lengthy.
35
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ID
SW Threat
Potential
Contaminants
Rationale for Risk Assessment Scoring
Risk
Score
B
Petrochemical
Facility
(Stationary
Threat - River)
Hydrocarbons
Unknown
Organics
Large volumes of fuel oil, diesel fuel, and smaller quantities
of unknown organic compounds are stored in tanks at the
facility.
Likelihood. Low: Effective secondary containment
surrounding the tanks should contain a spill from a leaking
tank. However, there is still a slight chance that spilled
chemicals could make their way into the river, just one mile
upstream of the intake.
Vulnerability. Moderate: The treatment plant could remove
the hydrocarbons at concentrations in the sub mg/L range;
higher concentrations would likely overwhelm and pass
through treatment.
Consequence. High: A high probability exists that at least
some of these contaminants could damage utility
infrastructure or pass through to the customer and create a
potential aesthetic problem. Furthermore, hydrocarbons
would be very difficult to clean from the distribution system
and premise plumbing systems, and remediation would
likely be difficult, expensive, and lengthy.
25
C
Wastewater
Outfall
(Stationary
Threat - River)
Pathogens
Unknown
Organics
Unknown
Inorganics
A failure at the wastewater treatment plant could result in
large volumes of untreated wastewater entering the river.
Likelihood. Low: Wastewater treatment failures are
infrequent and safeguards that prevent discharge of
untreated wastewater are in place.
Vulnerability. Moderate: The existing treatment processes
are not equipped to handle the high contaminant loads that
would result from a large discharge of untreated
wastewater.
Consequence. Moderate: While contaminant
concentrations would be reduced through treatment, it is
likely that some potentially harmful contaminants would
pass through the drinking water treatment plant and create
a potential public health issue.
20
D
Pesticide
Storage Tank
(Stationary
Threat -
Reservoir)
Pesticides
A significant volume (100-1,000 gallons) of pesticide is
stored onsite at an agricultural facility near the reservoir.
Likelihood. Low: The agricultural facility has secondary
containment around the storage tanks, and the tanks are
rarely full.
Vulnerability. Low: The treatment plant may have the
capacity to handle the increased contaminant load,
depending on the concentration of pesticide in the source
water at the intake.
Consequence. Moderate: Pesticides passing through the
drinking water treatment plant could create a potential
public health issue.
15
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Table 8-2. High-Priority SW Threats to Long-Term Source Water Quality for Anytown Water
ID
SW Threat
Potential
Contaminants
Rationale for Risk Assessment Scoring
Risk
Score
C
Wastewater
Outfall
(Stationary
Threat - River)
Pathogens
Unknown
Organics
Unknown
Inorganics
Increasing volumes of treated wastewater effluent are
projected due to increased residential and industrial growth
over the next five years.
Likelihood. High: Models project that these increased
discharge volumes will degrade water quality in the river,
leading to increased loading of pathogens, unknown
organics, and unknown inorganics.
Vulnerability. Low: The treatment plant may have the
capacity to treat the degraded source water, although some
contaminants may present a challenge. Also, the flow in the
river, and thus the potential for dilution of the treated
wastewater effluent, may change due to the effects of
climate change.
Consequence. Moderate: Failure to effectively respond to
the degraded water quality could result in Safe Drinking
Water Act (SDWA) violations and water that is
unacceptable to customers.
30
E
Agricultural
Runoff
(Stationary
Threat -
Reservoir)
Ammonia
Nitrates and
Nitrites
Phosphorous
Pesticides
The cumulative effects of agricultural runoff could
irreversibly degrade water quality in the reservoir.
Likelihood. Low: The reservoir has been engineered to
minimize runoff into the reservoir.
Vulnerability. Moderate: It would be difficult to restore the
reservoir to acceptable quality if accumulated contaminants
from runoff started eutrophication.
Consequence. Moderate: Impaired source water would
likely increase the occurrence of harmful algal blooms and
other serious water quality problems. Modifications to the
treatment plan may be necessary to maintain acceptable
finished water quality.
20
Due to constraints on available resources, both financial and personnel, Anytown Water recognized that
its SWM program would need to be implemented in phases over several years. However, the utility
wanted to realize benefits as soon as possible while building toward a long-term vision for SWM, so it
ensured that the system would be capable of supporting all three design goals, to some degree, in the first
phase. SWM stations installed in latter phases would expand the ability of SWM to support contamination
incident detection and monitoring of threats to long-term water quality.
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8.2 SWM Location Selection
The SWM locations selected to meet the design goals are shown in Figure 8-2.
Intake
Reservoir
Blending Facility
Distribution
System
Media Filtration
Disinfection
Pretreatment
Controf
Center
Coagulation/
Sedimentation
X^SWM Location
H Control Point
SW Threat
Figure 8-2. SWM Locations for Anytown Water
The utility's blending facility, shown in Figure 8-2, was evaluated as a potential SWM location to support
treatment process optimization. To ensure that this location would provide SWM data in sufficient time to
make treatment process adjustments, the project team compared the hydraulic travel time between the
blending facility and the pretreatment contact basin with the time required to change pretreatment
operations. Under typical production, the hydraulic travel time between the blending facility and the
pretreatment process basin was calculated to be 13 minutes. It was also determined that operators can
investigate and validate an SWM alert and adjust pretreatment in 10 minutes or less. Thus, monitoring at
the blending facility provides sufficient time to make a process change and was selected as SWM
Location 1 to support treatment process optimization.
The project team evaluated additional SWM locations to support detection of contamination incidents.
The critical detection point on the river was determined to be 0.25 miles upstream of the nver intake
structure, which would provide sufficient time to close the intake should a contamination incident be
detected upstream of this point. To provide additional response time, the utility placed SWM Location 2
approximately 0.75 miles upstream of the river intake, which is both upstream of the critical detection
point and downstream of SW Threats B and C (petrochemical facility and wastewater outfall). SWM
Location 3 was located inside the river intake structure to provide monitoring for SW Threat A, which
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represents mobile threats that could cause a contamination incident between SWM Location 2 and the
river intake. While a detection at Location 3 does not provide sufficient time for an optimal response,
consequences could still be mitigated if a response is implemented following a detection at this location.
The project team placed SWM Location 4 at the reservoir intake structure, as shown in Figure 8-2, to
monitor SW Threat D (pesticide storage tank). The flow from the reservoir to the intake structure is low
enough such that monitoring at SWM Location 4 provides adequate time to close the reservoir intake if a
contamination incident was detected at that location.
SWM Locations 2, 3, and 4 can also be used to monitor threats to long-term water quality. Locations 2
and 3 monitor SW Threat C (wastewater outfall), while Location 4 monitors SW Threat D (agricultural
runoff).
8.3 SWM Parameter Selection
SWM parameters were selected based on the design goals established by Anytown Water. For the
treatment optimization design goal, the project team determined it would be necessary to monitor the
parameters shown in Table 8-3 to meet the treatment targets.
Table 8-3. Parameters Selected to Support Treatment Process Optimization for Anytown Water
SWM Location 1 (Blending Facility)
SWM
Parameter
Rationale for Parameter Selection
DOC/TOC
Source water DOC/TOC concentration data is needed to determine the coagulant dose necessary
to achieve the turbidity and TOC removal targets.
Turbidity
Source water turbidity concentration data is needed to determine the coagulant dose necessary to
achieve the turbidity and TOC removal targets.
PH
Source water pH data is needed to determine the acid dose required to reach the pH necessary
to achieve the turbidity and TOC removal targets.
Temperature
Temperature impacts the equilibrium and kinetics of the chemical processes that drive
coagulation, with higher temperatures generally increasing the effectiveness of coagulation.
To detect contamination incidents and monitor threats to long-term water quality, parameter selection was
driven by the high-priority SW threats identified during the risk assessment. Parameters were selected
based on the contaminants associated with each SW threat and are listed in Table 8-4.
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Table 8-4. Parameter Selected to Detect Contamination Incidents and Monitor Threats to
Long-Term Water Quality for Anytown Water
SWM Location 2 (River)
SWM
Parameter
Threat ID
Rationale for Parameter Selection
Hydrocarbons
A, B
Hydrocarbon monitoring can provide a direct measure of hydrocarbon
concentrations in the source water.
Spectral
Absorbance
A, B, C
Many chemicals absorb in the spectral range of 250-450 nm. A change in spectral
absorbance can indicate an increase in the concentration of chemical
contaminants in the source water.
DOC/TOC
A, B, C
An increase in DOC/TOC can indicate contamination with an organic chemical.
Specific
Conductance
A, C
Some chemicals have charged functional groups that can dissociate and form
ionic species when dissolved in water. A change in specific conductance could be
an indicator of the presence of unknown chemicals in the source water.
Turbidity
C
An increase in turbidity results from an increase in the concentration of suspended
solids, which can be an indicator of potential microbiological contamination.
Ammonia
C
Ammonia can provide a direct measure of nutrients that can trigger an algal bloom
if in sufficient concentration.
Nitrates and
Nitrites
C
Nitrates and nitrites can provide a direct measure of nutrients that can trigger an
algal bloom if in sufficient concentration.
Ortho-
phosphates
C
Orthophosphates can provide a direct measure of nutrients that can trigger an
algal bloom if in sufficient concentration.
Photosynthetic
Pigments
C
Photosynthetic pigments can provide a direct indication of algal activity in the
source water.
SWM Location 3 (River Intake)
SWM
Parameter
Threat ID
Rationale for Parameter Selection
Hydrocarbons
A, B
Hydrocarbon monitoring can provide a direct measure of hydrocarbon
concentrations in the source water.
Spectral
Absorbance
A, B, C
Many chemicals absorb in the spectral range of 250-450 nm. A change in spectral
absorbance can indicate an increase in the concentration of chemical
contaminants in the source water.
DOC/TOC
A, B, C
An increase in DOC/TOC can indicate contamination with an organic chemical.
Specific
Conductance
A, C
Some chemicals have charged functional groups that can dissociate and form
ionic species when dissolved in water. A change in specific conductance could be
an indicator of the presence of unknown chemicals in the source water.
Turbidity
C
An increase in turbidity results from an increase in the concentration of suspended
solids, which can be an indicator of potential microbiological contamination.
Ammonia
C
Ammonia can provide a direct measure of nutrients that can trigger an algal bloom
if in sufficient concentration.
Nitrates and
Nitrites
C
Nitrates and nitrites can provide a direct measure of nutrients that can trigger an
algal bloom if in sufficient concentration.
Ortho-
phosphates
C
Orthophosphates can provide a direct measure of nutrients that can trigger an
algal bloom if in sufficient concentration.
Photosynthetic
Pigments
C
Photosynthetic pigments can provide a direct indication of algal activity in the
source water.
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SWM Location 4 (Reservoir)
SWM
Parameter
Threat ID
Rationale for Parameter Selection
Spectral
Absorbance
D
Many organic chemicals, including pesticides, absorb in the spectral range of 250-
450 nm. A change in spectral absorbance can indicate an increase in the
concentration of organic contaminants that could result from fuel or cargo spills in
the source water.
DOC/TOC
D
An increase in DOC/TOC can indicate contamination with an organic chemical,
including pesticides.
Ammonia
E
Ammonia can provide a direct measure of nutrients that can trigger an algal bloom
if in sufficient concentration.
Nitrates and
Nitrites
E
Nitrates and nitrites can provide a direct measure of nutrients that can trigger an
algal bloom if in sufficient concentration.
Ortho-
phosphates
E
Ortho-phosphates can provide a direct measure of nutrients that can trigger an
algal bloom if in sufficient concentration.
Photosynthetic
Pigments
E
Photosynthetic pigments can provide a direct indication of algal activity in the
source water.
8.4 SWM Station Design
SWM station design involved the selection of sensor technologies, a sampling approach, power
distribution, a communications solution, and packaging for the SWM locations. Station design was
informed by the locations and parameters selected in previous steps, as well as the performance objectives
established for SWM.
A key aspect of SWM station design is the selection of sensor technologies to measure the selected
parameters. The comparison methodology presented in Framework for Comparing Alternative Water
Quality Surveillance and Response Systems (EPA. 2015d) was used to evaluate candidate sensor
technology options for the selected parameters at each location. This comparison considered both
lifecycle costs and the capability of each alternative. The lifecycle costs included capital, maintenance,
and replacement costs over an established period of time to enable technology comparison on an equal
basis. To objectively assess the capability of each alternative, the following evaluation criteria were
developed:
Ability to measure a parameter and provide reliable data. This criterion included a review of
existing information and an evaluation of sensor performance in the installed environment. It also
considered the ability of sensors to reliably measure the expected range of parameter values.
Other performance indicators that were considered include accuracy, precision, resolution,
measurement frequency, fouling potential, and interference.
Integration within current systems. The degree to which a particular technology fits with
existing systems and within current training, quality assurance, maintenance, and procurement
programs.
Potential for future applications. This criterion includes a technology's ability to monitor
parameters that can be leveraged for future phases of SWM implementation or other water quality
monitoring applications.
The project team compared sampling, power distribution, communication, and packaging options for each
station design. The station designs for SWM Locations 2, 3, and 4 were more complex compared to SWM
Location 1 due to the number of parameters selected to support the design goals and the lack of existing
infrastructure at the installation sites (e.g., SWM Location 2 is positioned on the bank of the river where
grid power and wired communications are unavailable).
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A summary of the station designs for each SWM location is provided in Table 8-4. The summary
includes the selected parameters, instrumentation, sampling, power distribution, communication, and
packaging for each station. To facilitate procurement, fabrication, and maintenance, a common suite of
instruments was used across the four SWM stations. A local computer was also installed within each
station to manage operation of sensors and station equipment and allow operators to perform remote
diagnostics on the spectral absorbance instruments.
Table 8-5. Final SWM Station Designs for Anytown Water
SWM Station
Element
SWM Location 1
(Blending facility)
SWM Location 2
(Bank of river)
SWM Location 3
(River intake)
SWM Location 4
(Reservoir intake)
Instrumentation
Parameters
Absorption
Spectrometry
DOC/TOC
Absorption
Spectrometry
DOC/TOC
Absorption
Spectrometry
DOC/TOC
Absorption
Spectrometry
DOC/TOC
Turbidity
Turbidity
Nitrogen species
Spectral
absorbance
Hydrocarbons
Turbidity
Nitrogen species
Spectral
absorbance
Hydrocarbons
Nitrogen species
Spectral
absorbance
ISE
ISE
ISE
ISE
pH
Temperature
pH
Temperature
Ammonia
pH
Temperature
Ammonia
pH
Temperature
Ammonia
Colorimetrv
Ortho-phosphates
Colorimetrv
Ortho-phosphates
Colorimetrv
Ortho-phosphates
Fluorometrv
Photosynthetic
pigments
Fluorometrv
Photosynthetic
pigments
Fluorometrv
Photosynthetic
pigments
Conductivity Cell
Specific
conductance
Conductivity Cell
Specific
conductance
Sampling
Sample line fitted
with a pressure
regulator to carry
water from the
effluent pipe from the
blending facility to a
flow-cell at the SWM
station
Pump used to transfer
water from the river to
a flow-cell, and a drain
line to collect the
waste stream (which
contained reagents
from the colorimeter)
Sample line fitted with
a pressure regulator to
carry water from
effluent pipe from the
intake facility to a flow-
cell, and a drain line to
collect the waste
stream (which
contained reagents
from the colorimeter)
Sample line fitted with
a pressure regulator to
carry water from
effluent pipe from the
intake facility to a flow-
cell, and a drain line to
collect the waste
stream (which
contained reagents
from the colorimeter)
Power Supply
and Distribution
Existing grid power
Solar power
Existing grid power
Existing grid power
Communications
Fiber optics
Wireless
Fiber optics
Fiber optics
Packaging
Wall-mounted rack
Enclosed station
Enclosed station
Enclosed station
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8.5 Information Management and Analysis
Anytown Water decided to use a dedicated SWM information management system rather than leverage its
existing SCADA system. A key driver behind this decision was that the SCADA historian could not
provide appropriate storage for spectral array data, which will be collected by three of the four SWM
stations, as shown in Table 8-5. This dedicated system provides storage using a PostgreSQL database and
three displays: one dedicated to treatment plant optimization, one dedicated to detection of contamination
incidents, and the third for monitoring threats to long-term water quality.
For the treatment process optimization design goal, the display shows time-series plots of TOC, turbidity,
pH, and temperature data, as well as their associated treatment optimization thresholds. Threshold values
for DOC/TOC, turbidity, pH, and temperature were determined by analyzing one year of historic data to
characterize normal variability in these parameters, the results of jar tests, and full-scale experience to
determine treatment process settings necessary to achieve optimal performance for different source water
quality types. Once a threshold is exceeded, the SWM information management system generates an alert
to notify the operator that treatment process settings may need to be adjusted to maintain optimal
treatment process performance.
For detection of contamination incidents, an ADS operates on the local computer at each SWM station to
analyze the station water quality data in real time and generate alerts if an anomaly is detected. These
alerts, along with the sensor data, are transmitted to the SWM information management system for
presentation on the display and storage in the PostgreSQL database. The alerts are also transmitted to
mobile communication devices assigned to key personnel.
For monitoring of threats to long-term water quality, SWM data is pulled quarterly from the PostgreSQL
database and analyzed using statistical analysis tools available through the SWM information
management system. Each quarter, a dedicated group of utility personnel with expertise in water quality,
source water management, and statistics meet to review the data. A variety of analysis techniques, such as
those listed in Table 6-1, are used to investigate trends and correlations in the data. The analysis is
cumulative, building an understanding of long-term changes and trends over multiple years.
8.6 Investigation and Response Procedures
To support SWM operations, Anytown Water developed two procedures: (1) SWM Alert Investigation
and Response Procedure and (2) Investigation and Response Procedure for Long-Term Water Quality
Changes.
The SWM Investigation and Response Procedure supports treatment process optimization and detection
of contamination incidents, and includes the following elements:
An alert investigation process flow diagram, which presents the steps to identify the most likely
cause of an alert and decide whether response actions are necessary
An alert investigation checklist, which documents the information resources that should be
checked and actions that should be taken over the course of an alert investigation
A treatment roadmap, which prescribes adjustments to chemical dosing and loading rates to
maintain optimal performance from pretreatment through disinfection
A source water contamination incident response decision tree, that summarizes the decision logic
and criteria for implementing various response actions if source water contamination is possible
A list of key personnel and their contact information along with a description of their
responsibilities under this procedure
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The Investigation and Response Procedure for Long-Term Water Quality Changes supports monitoring of
threats to long-term water quality and development of mitigation strategies, and includes the following
elements:
A framework for investigating the cause of a long-term change in source water quality, including
the statistical methods, visualization techniques, analysis methods, and information resources
used to understand trends in source water quality by location and by parameter
A framework for making decisions and strategic plans to respond to a significant change in
source water quality, including resources to help establish the cost, feasibility, and efficacy of
various mitigation strategies
A list of key personnel and their contact information along with a description of their
responsibilities under this procedure
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Section 9: Case Studies
Various organizations across the world have implemented SWM systems in response to threats to source
water quality such as shale oil and gas drilling in watersheds, harmful algal blooms, spills, or other forms
of source water contamination. This section provides case studies of existing SWM systems that have
been implemented to address the three design goals described in Section 2. These case studies include
SWM systems designed by individual drinking water utilities as well as watershed-scale systems.
9.1 Greenville Water
Greenville Water supplies drinking water to almost 500,000 customers in the Upstate region of South
Carolina, drawing water from Table Rock Reservoir, North Saluda
Reservoir, and Lake Keowee. The design goal for Greenville's
SWM system is to detect contamination incidents.
The water quality in each of Greenville's sources is relatively
constant, which simplifies the process of identifying a potential
contamination incident. To achieve real-time monitoring of the
sources, an SWM station was installed at the treatment plant
intake located on each source water. Figure 9-1 provides an overview of Greenville's SWM locations.
Each station monitors pH, specific conductance, and turbidity.
At a Glance
Design goals: To detect
contamination incidents
Monitoring locations: 3
Parameters: pH, specific
conductance, and turbidity
Water Treatment Plant
GREENVILLE
COUNTY
Adkins Water Treatment Plant
Q SWM Location
Water Treatment Plant
Service Area
Figure 9-1. Greenville Water SWM Locations
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SWM data is sent via radio to Greenville's control room where it is stored and can be accessed by utility
personnel. The data is reviewed daily on SCADA system screens. Figure 9-2 is an example of a SCADA
screen that displays data from one of the SWM stations. The SCADA system can generate an alert if one
or more of the parameter values crosses established thresholds. However, no significant water quality
incidents have been detected in any of Greenville's source waters as of the date of publication.
50.00-1
45 00-
40.00-
6 00-
0 00"
675
0.52
Figure 9-2. Example of Greenville Water SCADA System Screen for SWM Data
9.2 City of Fort Collins Utilities
The City of Fort Collins Utilities in Colorado supplies water to a population of 161,000, treating water
from the Cache la Poudre River (Poudre River) and Horsetooth
Reservoir. The design goals for the Fort Collins' SWM system are to
optimize treatment processes and detect contamination incidents.
The Poudre River water quality is subject to large fluctuations due to
a number of different influences (e.g., spring runoff, floods, fires),
which may impact the ability to use the source. Fort Collins' SWM
system includes five stations to monitor the two sources, as shown in
Table 9-1. Emphasis is placed on monitoring the Poudre River due to
recent issues with turbidity caused by wildfires in 2012.
At a Glance
Design goals: To optimize
treatment processes and detect
contamination incidents
Monitoring locations: 3 remote,
2 in plant
Parameters: alkalinity,
hydrocarbons, pH, specific
conductance, temperature, TOC,
turbidity, and UV-254
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Table 9-1. Fort Collins Utilities SWM Stations
Location
Parameters
Role
Utilization
In Poudre River, four
miles upstream of intake
Specific conductance
Turbidity
Detection of
contamination incidents
Only March/April through
November, as the river is
otherwise too low or
frozen
In Poudre River, just
upstream of the intake
Turbidity
Detection of
contamination incidents
Monitors the river turbidity
continuously, even when
the flow to the plant is
shut off
In pipeline between the
Poudre River intake and
the treatment plant
Alkalinity
Hydrocarbons
pH
Specific conductance
Temperature
Turbidity
UV-254
Treatment process
optimization and detection
of contamination incidents
Only online when the
Poudre River intake is in
use
Poudre River raw water at
the treatment plant
Alkalinity
pH
Specific conductance
Temperature
TOC
Turbidity
Treatment process
optimization and detection
of contamination incidents
Only online when the
Poudre River intake is in
use. TOC is only online
during spring runoff
Horsetooth Reservoir raw
water at the treatment
plant
Alkalinity
Hydrocarbons
pH
Specific conductance
Temperature
Turbidity
Treatment process
optimization and detection
of contamination incidents
Only online when the
Horsetooth Reservoir
intake is in use
All monitoring stations transmit data to a SCADA system where it is stored and can be accessed. Alerts
are based on thresholds for specific parameters. Operators respond to alerts by reviewing the SWM data,
which informs decisions for treatment process operations. Operators have the ability to isolate or blend
the two sources, as necessary, in response to source water quality changes.
Example Incident
In 2012, wildfires created ash in the watershed, which caused significant turbidity in the Poudre River. Turbidity
measurement in the river just upstream of the intake provides warning of high turbidity. The Poudre River is not
used as a source when the turbidity reaches a pre-defined threshold.
Case Study References
http://www.fcgov.com/utilities/what-we-do/water/water-qualitv/source-water-monitoring
http://www.fcgov.com/utilities/what-we-do/water/water-qualitv/source-water-monitoring/upper-
poudre-qualitv-monitoring
http://www.fcgov.com/utilities/img/site specific/uploads/December 2015 Watershed Newslette
r Template.pdf
http://www.fcgov.com/utilities/img/site specific/uploads/2013HT report final.pdf
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9.3 Clermont County Water Resources Division
The Clermont County Water Resources Department supplies water to over 43,000 customers in southwest
Ohio, drawing water from Harsha Lake, the Little Miami River
Valley Aquifer, and the Ohio River Valley Aquifer. The design
goals for this SWM system are to detect contamination incidents
and monitor threats to long-term water quality.
Harsha Lake has a history of cyanotoxin producing HAB events,
which have typically occurred in early summer. The high risk of
cyanotoxin formation in the lake and the difficulty in removing it
through existing drinking water treatment processes forced
Clermont County to add advanced, expensive treatment
techniques. To control the formation of DBPs, granular activated carbon (GAC) contactors were installed,
which provide the added benefit of removing several cyanotoxins. Managing loading rates of multiple
GAC contactors has become an important tool in cyanotoxin treatment. As a result, the utility wanted to
develop empirical relationships between algal community composition, toxicity, and cyanotoxin
concentrations to better detect and respond to cyanobacterial blooms and their toxins. To accomplish this
objective, the utility established a partnership with EPA's Office of Research and Development to convert
three historical water quality sampling sites to SWM stations, as described in Table 9-2. Grab sampling
for a range of water quality parameters occurs at various frequencies to supplement data produced by
SWM stations.
At a Glance
Design goals: To detect
contamination incidents and monitor
threats to long-term water quality
Monitoring locations: 3
Parameters: DO, ORP, pH,
photosynthetic pigments, specific
conductance, spectral absorbance,
temperature, toxicity, and turbidity
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Table 9-2. Clermont County Water Resources Division SWM Stations
Location
Parameters
Role
Surface of Harsha Lake near the
intake of the Bob McEwen Water
Treatment Plant
DO
ORP
pH
Photosynthetic pigments
Specific conductance
Spectral absorbance
Temperature
Toxicity
Turbidity
Detection of contamination incidents
and monitoring of threats to long-term
water quality
Harsha Lake intake to the Bob
McEwen Water Treatment Plant
DO
ORP
pH
Photosynthetic pigments
Specific conductance
Spectral absorbance
Temperature
TOC
Toxicity
Turbidity
Detection of contamination incidents
and monitoring threats to long-term
water quality
Floating Platform on Harsha Lake
DO
ORP
pH
Photosynthetic pigments
Specific conductance
Temperature
TOC
Turbidity
Detection of contamination incidents
and monitoring of threats to long-term
water quality
Data produced by SWM stations is sent via a cellular internet connection to a central workstation. All data
is analyzed visually, using time-series plots to determine parameter relationships and identify data outliers
and instances of instrument failure. Spectral absorbance and toxicity data is also analyzed by an ADS that
is integrated with instrument software. Utility personnel can access SWM data through a central
workstation and externally, in "read-only mode," through other secured methods. The system creates
weekly reports that include QA metrics, for personnel to review on a weekly basis.
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9.4 West Virginia American Water
West Virginia American Water (WVAW) serves approximately 550,000 customers in around 300
communities across West Virginia drawing water from various
surface water sources across the state. The primary design goals of
WV AW's SWM system are to optimize treatment processes and
detect contamination incidents.
WVAW has implemented an SWM system that goes above and
beyond state regulatory requirements established in 2014 to
proactively monitor their source waters. An SWM station was
installed at each of WVAW's eight water treatment plants to
monitor water from the associated intakes. These stations
continuously monitor the following parameters: DO, DOC (via UV-254), ORP, pH. specific conductance,
temperature, and turbidity. A photograph of one of the SWM stations is shown in Figure 9-3.
Figure 9-3. West Virginia American Water Source Water Monitoring Station
SWM data is recorded every two minutes and sent, via fiber optic cable, to a server that securely transmits
data to a cloud-based web platform. Personnel with their own login credentials can view current
parameter values as well as time-series plots of historical data using a secure Internet connection. A
screenshot of a time-series plot showing a data subset generated at an SWM location is shown in Figure
9-4. SWM data is currently analyzed using visual and statistical techniques to establish baseline water
quality at each of the SWM locations. WVAW is in the process of implementing an ADS to analyze data
from multiple sensors in real-time and provide alerting based on a "rare combination" comparison to
baseline data.
At a Glance
Design goals: To optimize
treatment processes and detect
contamination incidents
Monitoring locations: 8
Parameters: DO, DOC (via
UV-254), ORP, pH, specific
conductance, temperature, and
turbidity
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*OOm
Figure 9-4, Screenshot of West Virginia American Water Source Water Monitoring Data
Case Study References
http://www.amwater.com/wvaw/water-qualitv-and-stewardship/source-water-
protection/index.html
Data Quality Management for Continuous Source Water Monitoring, Presented at NEMC,
August 2016 http://www.nemc.us/meeting/2016/load abstract.php?id=91
9.5 Bratislava Water Company
The Bratislava Water Company in Slovakia uses groundwater from a deep aquifer as its main source to
supply a population of greater than 600,000. Over 144 MGD of
drinking water is produced in seven central water treatment facilities
that extract water from 176 wells. The only treatment performed is
chlorination to prevent microbiological regrowth during distribution.
The design goal for Bratislava's SWM system is to detect
contamination incidents.
Water quality is consistently high in most of Bratislava's 176
groundwater wells. However, the utility is concerned about the
possibility of contamination with pesticides, water soluble components of oil, and chemical warfare
agents. As a result, SWM stations were installed at each of the sources to monitor N03, TOC, specific
conductance, temperature, and spectral absorbance. A photograph of an SWM station is shown in Figure
9-5.
At a Glance
Design goals: To detect
contamination incidents
Monitoring locations: 176
Parameters: NO3, specific
conductance, spectral
absorbance, temperature, and
TOC
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Online Source Water Quality Monitoring
Figure 9-5. Bratislava Water Company SWM Station
Each of the SWM stations is equipped with an ADS that sends an alert to plant operators when a potential
water quality anomaly is detected, as illustrated in Figure 9-6. When an alert is received, operators shut
down the well in which the anomaly was detected. Water samples are then collected and analyzed to
determine whether contamination has occurred before bringing the well back online.
Process Schematic
Figure 9-6, Bratislava Water Company SWM Alert Notification
Case Study References
http://www.s-can.at/medialibrarv/references/Reference Bratislava web.pdf
http://www.s-can.at/medialibrarv/pdf/bratislava publication.pdf
http://www.s-can.at/medialibrarv/pdf/bratislava poster.pdf
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Online Source Water Quality Monitoring
9.6 Susquehanna River Basin Commission Early Warning System
The Susquehanna River Basin Commission (SRBC) Early Warning System is an SWM program for the
lower Susquehanna River region which provides water to parts of
Pennsylvania, New York, and Maryland. The system provides
information to help protect public drinking water supplies serving
about 850,000 people. A stakeholder group guides implementation
of the SWM program and includes participating public water
suppliers and representatives from various environmental protection
and emergency response agencies. The design goals of SRBC's
system are to optimize treatment processes and detect contamination
incidents.
SRBC operates 55 SWM stations that monitor a minimum of pH, temperature, and turbidity at critical
locations along the major rivers of the Susquehanna Basin. The monitored area is shown in Figure 9-7.
The system was set up as an early warning system for contamination incidents and includes SWM
stations that monitor water quality downstream of oil and gas industry facilities. A photo of an SWM
station is shown in Figure 9-8.
EARLY WARNING SYSTEM (EWS)
MONITORING STATIONS
IN THE SUSQUEHANA RIVER BASIN
Corning-#!
William'sport "
Sunbuny
EWS Station
f Lancaster
JปYork
SRBC
Figure 9-7. Susquehanna River Basin Region
At a Glance
Design goals: To optimize
treatment processes and detect
contamination incidents
Monitoring locations: 55
Parameters: pH, temperature,
and turbidity
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Figure 9-8. Susquehanna River Basin Commission
SWM Station
SWM data is transmitted in real-time to water treatment plants and the SRBC. A secure database and
website interface provide access to the data and tools for investigating, or responding to, contamination
incidents. The website interface provides user-friendly access to information and tools, including a time-
of-travel tool to help estimate contaminant dispersal times that enable downstream users to respond to
adverse changes in water quality. Data associated with the stations specifically monitoring the oil and gas
industry are published to a public website even five minutes.
Case Study References
http://www.sourcewaterpa.org/7page id=l 806
http://www.srbc .net/drinkingwater/
http://www.srbc.net/pubinfo/docs/infosheets/SRB%20 Early Warning System 136411 l.pdf
http://www.srbc .net/programs/docs/09SRBCEW S. pdf
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9.7 River Alert Information Network
The River Alert Information Network (RAIN) is a regional SWM system dedicated to protecting shared
drinking water resources in western Pennsylvania and northern West
Virginia. RAIN is a collaboration of 51 water utilities, the
Pennsylvania Department of Environment Protection, the West
Virginia Department of Health and Human Resources, the California
University of Pennsylvania, Carnegie Mellon University, and the
University of Pittsburgh. The design goal for RAIN's SWM system
is to detect contamination incidents.
RAIN currently monitors water quality in the Monongahela,
Allegheny, and Ohio rivers. A total of 29 SWM stations are installed along these rivers to monitor DO,
NH3 pH, specific conductance, temperature, and turbidity. A photo of a RAIN SWM station is shown m
Figure 9-9. An overview of SWM locations is shown in Figure 9-10.
Figure 9-9, RAIN SWM Station
At a Glance
Design goals: To detect
contamination incidents
Monitoring locations: 29
Parameters: DO, NH3, pH,
specific conductance,
temperature, and turbidity
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Allegheny
River
Ohio
River
[Monongahela
River C"
TtnaS*
iMorgantowri
N
~ Drinking Water Intake Sensors
# Tributary Sensors
fa Rain Locations
A
0 5 10 20
Kilometers
30 40
Figure 9-10. Overview of RAIN SWM Locations
SWM data is transmitted from SWM stations in the field to a data center at the California University of
Pennsylvania for analysis. Electronic updates are periodically forwarded to RAIN headquarters in
Pittsburgh. If one or more parameters fall outside of established threshold values, automated notifications
are sent to impacted drinking water treatment plants. SWM data is also made available to the public via
the USGS RAIN website. A screenshot of the website, which displays an interactive map and data from
one of the RAIN SWM stations, is shown in Figure 9-11.
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Online Source Water Quality Monitoring
RIVER ALERT INFORMATION NETWORK
Green
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Louisville
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DATA DOWNLOADS: 1-Daj
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LAST SITE DATA:
3/9/2015 2:15 PM
Cond: 0.186 (mS/cm) Temp: 4 8 (C) DO: 15.80 (mg/ L)
Turbidity: 11.90 (ntu) UVAS: 10.30 (A)
Waynesburg
Monongahela
Pleasant
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Figure 9-11. RAIN Interactive Display
Example Incident
In 2010, SWM stations detected an increase of bromide levels in the Monongahela River. While a single source
for the increased levels was never identified, it was suspected that the increase was caused by wastewater
discharges from Marcellus Shale drilling or electric power plants. The combined effect of controls that were
placed on some discharges along the river as well as significantly more rainfall resulted in lower bromide
concentrations and more stable water quality in the river in 2011.
Case Study References
http ://www.rainmatters .org/
http://www.sourcewaterpa.org/wp-content/uploads/2013/04/Part-2-SWP-Coalitions-vs-DIY -
Gina-Cvprvch-RAIN-3-9-13-Schuvlkill-Watershed-Congress.pdf
http: //usgs. dailvinvention. com/rain .php
9.8 Philadelphia Water Department
Philadelphia Water Department (PWD) is a combined urban utility located in Philadelphia, Pennsylvania,
that delivers approximately 250 MGD of high-quality drinking water to 1.6 million residents in
Philadelphia and its surrounding suburbs. PWD operates three conventional drinking water treatment
plants located on two densely populated and industrialized rivers with distinct water quality
characteristics. The Schuylkill River hosts two treatment plants that supply a total of roughly 40 percent
of the city's demand. The balance of the demand is met by the utility's largest plant located on the tidal
Delaware River. Philadelphia is located at the confluence of these two rivers in a vast watershed of more
than 10,000 square miles. Figure 9-12 provides an overview of the utility's source watersheds and
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Online Source Water Quality Monitoring
drinking water intakes. Less than 1 percent of the total source watershed area is within city boundaries,
necessitating a partnership-based approach to meet source water protection objectives.
PWD has taken proactive steps towards being an industry and regional leader in source water protection
by creating mechanisms for regional coordination to implement source water protection measures.
Recognizing the many benefits of online water quality monitoring, the utility has incorporated SWM
components into regional, local, and utility-specific systems. Two SWM systems are described in this
case study: the Delaware Valley Early Warning System and the Philadelphia Water Resources Monitoring
Program.
"County
coutny
PHLADELPHIA
NEW YORK
PEhNSYLVANIA
Philadelphia
rT-X U I
Legend
T Philadelphia
Schuylkill River Watershed
ฆ Dams
Delaware River Watershed
# PWD Treatment Plants [_ n Township lines
Major Roads
I | County Lines
Roods
[ 1 State Lines
Fail mount Park
if Majoc Cities
Wildlife Refuge
Figure 9-12. Overview of PWD's Source Watersheds arid Drinking Water intakes
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Online Source Water Quality Monitoring
Delaware Valley Early Warning System
The Delaware Valley Early Warning System (EWS) is a private, web-based water quality event
communication system. The EWS is designed to monitor the
safety of the drinking water supply by providing data and analysis
tools to aid planning and response for potential source water
contamination incidents. Technological components of the EWS,
such as a sophisticated notification system, secure database portal,
user-friendly website, and comprehensive water quality and flow
monitoring network, create the advanced functionality and unique
capabilities that make the EWS an industry model for surface
water notification and monitoring systems.
The system is owned and managed by PWD, although the system covers an area well outside of the city's
boundaries. The system's user base consists of more than 300 individual users from 50 different
organizations that include water utilities, industries, and representatives from government agencies in
Pennsylvania, New Jersey, and Delaware. EWS technical and analytical capabilities cover both the
Schuylkill and Delaware Watersheds with the exception of tributaries downstream of Philadelphia and the
New York City water supply.
Water quality incidents are reported through a telephone hotline or the EWS website, and email and
telephone notifications to the entire user base are processed within minutes. Users can log in to the secure
website to see additional event details and supplemental information, including an interactive ArcGIS
map of the projected spill trajectory and time of travel estimations for tidal and non-tidal intakes. In
addition to providing a user interface, the website supports SWM system users by providing:
Secure means of accessing and analyzing information
Tools for determining appropriate incident response
Interface for updating incident reports
List of contacts for incident follow-up
Animation of modeled spill trajectory for events on tidal waters
The SWM stations are fully integrated with the EWS website and database portal. The monitoring
network consists of four SWM stations at drinking water intakes and 84 supplemental USGS water
monitoring stations on the lower Delaware River and its tributaries. These stations monitor parameters
such as DO, flow, pH, specific conductance, temperature, and turbidity. The system is designed to allow
EWS users to easily track water quality changes and potential impacts from contamination incidents
through automatically generated graphical displays and user-friendly data query tools available on the
system's secure website. An example of real-time flow and turbidity data visualization from the EWS
homepage is shown in Figure 9-13. The graph displays readings from the last 15 days from multiple
SWM stations on the main stem of the Schuylkill and Delaware Rivers.
Another objective of the system is to provide users with access to historic water quality data through
query functions. Both real-time and historic data can be queried and viewed in charts online or
downloaded to a file that can be further analyzed by the EWS subscriber using data analysis software.
Additionally, both real-time and historic flow data can be used to produce conservative time of travel
estimations for each reported event.
PWD supports ongoing system upgrades and enhancements to ensure that the EWS remains the most
advanced and robust system possible, helping to protect the drinking water supply for over 3 million
people in the watershed.
At a Glance
Design goals: To detect
contamination incidents and monitor
threats to long-term water quality
Monitoring locations: 88
Parameters: DO, pH, specific
conductance, temperature, and
turbidity
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Online Source Water Quality Monitoring
Real-Time Flow and Turbidity Charts for the last 15 days
FLOW, STREAM, INSTANTANEOUS
1700-
1360-
1420-
1280-
1 140-
1000-
/20-
USGS Schuylkill
PhtLidclphia4
(01474500)
USGS Schuylkill
Notrntown
(01473S00)
USGS Schuylkill
Readings (01471S10) I
USGS Schuylkill
Pottstown2
(01472000)
From: June 28, 2016 To July 13, 2016
Figure 9-13. Example of SWM Data Visualization on EWS Homepage
Example Incidents
Past significant contamination incidents reported to the Delaware Valley EWS include a spill of 275,000 gallons of
crude oil in the tidal Delaware River in 2004, a spill of 100 million gallons of fly ash into the Delaware River from
an industrial lagoon in 2005, a cyanide release through a wastewater treatment plant into a tributary to the
Schuylkill River in 2006, and a train derailment release of 25,000 gallons of vinyl chloride into a tributary to the
Delaware River in 2012.
At a Glance
Philadelphia Water Resources Monitoring Program
As a combined utility, PWD uses online water quality monitoring data to support both Safe Drinking
Water Act and Clean Water Act objectives. PWD works
cooperatively with USGS to maintain an extensive monitoring
network within the City of Philadelphia. The objective of the
system is to characterize the quality of the City's waterways and
detect water quality changes that may warrant further
investigation. Ten strategically positioned stream flow monitoring
stations augmented with SWM instruments characterize water
quality entering and exiting Philadelphia's sub-watersheds.
Design goals: To detect
contamination incidents and monitor
threats to long-term water quality
Monitoring locations: 10
Parameters: DO, pH, specific
conductance, temperature, and
turbidity
Monitored water quality parameters include DO, pH, specific conductance, temperature, and, at select
locations, turbidity. Hydrological parameters such as flow and gauge height are also measured.
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SWM data is automatically uploaded to databases in the USGS computer network, and a web server
transfers the data to the USGS National Water Information System (NWIS) website. A separate utility
website automatically retrieves data from the USGS NWIS at regular intervals and geospatially displays
the results on a publicly accessible website shown in Figure 9-14. A traffic light color scheme is applied
to each parameter at each station to denote good water quality (green), undesirable changes in water
quality (yellow), and poor water quality (red). Rating thresholds are based on stream use designations and
established water quality criteria. Users can select a station on the map to see the most recent
instantaneous readings.
Somerton
Select a station to view the most recent
real-time data.
01465798/% Andalusia
. ^ Roxborough
J Manayunk
7
/V 01474000
Tacony
014670261
tonville
EXPLANATION
Darby/Cobbs Watershed
Frankford/Tacony Watershed
Pennypack watershed
Poquessing Watershed
Schuylkill Watershed
Wissahlckon Watershed
0147S530
01474500
01467200
ฆ Water-quality station
~ Streamflow and water-quality station
COLOR CODES FOR PARAMETERS
J good water quality
_] undesirable changes in water quality
| poor water quality
l not ranked
Philadelphia
International Airport
Figure 9-14. Philadelphia Water Resources Monitoring Program Website User Interface
The user interface and data visualization allows PWD personnel to simultaneously monitor spatial and
temporal quality and quantity trends. This information is used to assess aquatic ecosystem health, evaluate
source water quality, and inform decision-making surrounding watershed restoration initiatives.
Additionally, these stations serve as Philadelphia's long-term, wet-weather monitoring stations.
Additional quality assurance and data analysis is performed on data from each SWM station.
Case Study Reference
http://www.phila.gov/water/wuAVater%200ualitv%20Reports/2Q15WaterOualitv.pdf
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Resources
Introduction
Water Quality Surveillance and Response System Primer (EPA, 2015a)
https://www.cpa.gov/sitcs/production/filcs/2015-
06/documents/water quality sureveillance and response system primer.pdf
This document provides an overview of Water Quality Surveillance and Response Systems, and
serves as a foundation for the application of technical guidance and products used to implement
an SRS. EPA 817-B-15-002, May 2015.
Framework for Designing a Source Water Monitoring System
Guidance for Developing Integrated Water Quality Surveillance and Response Systems
(EPA, 2015b)
https://www.cpa.gov/sitcs/production/filcs/2015-
12/documents/guidance for developing integrated wq srss 110415.pdf
This document provides guidance for applying system engineering principles to the design and
implementation of an SRS to ensure that the SRS functions as an integrated whole and is
designed to effectively perform its intended function. Section 2 provides guidance on project
management and coordination. Section 3 provides guidance on master planning for a multi-
component SRS. EPA 817-B-15-006, October 2015.
Quality Assurance (ACRR) Matrix (ASW, 2010)
http://www.watersensors.org/pdfs/ASW OA Matrix web.pdf
A series of tables that provide guidance on quality control and record-keeping practices for
common water quality parameters monitored online.
J100 Standard (AWWA, 2010)
http: //www .awwa. org/store/productdetail. aspx?productid=21625
The J100 Standard was developed collaboratively by the American National Standards Institute
(ANSI), American Society of Mechanical Engineers Innovative Technologies Institute (ASME-
ITI), and American Waterworks Association (AWWA). J100 sets the requirements for all-
hazards risk and resilience analysis for the water sector, ensuring a consistent framework for
conducting risk assessments. The J100 documents a seven-step process for evaluating risks
presented by man-made threats, natural hazards, dependencies, and proximity to hazardous sites.
Vulnerability Self-Assessment Tool (EPA, 2015c)
https://vosemite.epa.gov/ow/SReg.nsf/description/VSAT
The Vulnerability Self-Assessment Tool (VSAT) is an electronic resource designed to help water
and wastewater utilities of all sizes to identify vulnerabilities to both man-made and natural
hazards, and evaluate potential improvements to enhance their security and resiliency. Version
VSAT 6.0, released in 2015, is consistent with the J100 Standard.
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State Primacy Agency Source Water Assessments (EPA, 2016a)
https://www.epa.gov/sourcewaterprotection/conducting-source-water-assessments
State drinking water primacy agencies are required to conduct source water assessments that
include an inventory of known and potential sources of contamination. Source water assessments
provide information about sources of drinking water used by public water systems. They are
developed by state primacy agencies to help local governments, water utilities, and others protect
drinking water sources. While the assessment programs are tailored to each state's specific issues,
they all generally follow these three steps: (1) delineate the source water protection area, (2)
conduct an inventory of potential sources of contamination, and (3) determine the vulnerability of
the water supply to contamination. Contact your state drinking water primacy agency for more
information.
DWMAPS (EPA, 2016b)
https://www.epa.gov/sourcewaterprotection/dwmaps
This GIS-based tool was developed by EPA to help states and utilities update their source water
assessments. It provides layers of spatially referenced data using information from databases such
as National Pollutant Discharge Elimination System (NPDES); Toxic Release Inventory (TRI);
Comprehensive Environmental Response, Compensation, and Liability Information System
(CERCLIS); Resource Conservation and Recovery Act Information (RCRAInfo); and Toxic
Substances Control Act (TSCA). DWMAPS also provides meta-data that can be useful for
characterizing potential SW threats. A secure version of DWMAPS, which shows the location of
drinking water intakes relative to the location of source water threats, is available to drinking
water utilities and state primacy agencies.
Template for Conducting a Risk Assessment for Source Water Threats (Word File)
Click this link to open the template
This Word template can be used to document a risk assessment for SW threats. It provides tables
for summarizing the attributes of SW threats and associated contaminants, example definitions of
the risk assessment parameters, and tables for documenting the results of the risk assessment.
September 2016.
Framework for Comparing Alternatives for Water Quality Surveillance and Response Systems
(EPA, 2015d)
https://www.epa.gov/sites/production/files/2015-
07/documents/framework for comparing alternatives for water quality surveillance and resp
onse svstems.pdf
This document provides guidance for selecting the most appropriate SRS design for a utility from
a set of viable alternatives. It guides the user through an objective, stepwise analysis for ranking
multiple alternatives and describes, in general terms, the types of information necessary to
compare the alternatives. EPA 817-B-15-003, June 2015.
Template for Developing an SWM Preliminary Design Document (Word File)
Click this link to open the template
This Word template can be used to document the preliminary design of an SWM system,
including: SWM implementation team, design goals, performance objectives, SW threats, SWM
locations, SWM parameters, preliminary information management requirements, initial training
plan, budget, and schedule. September 2016.
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Source Water Monitoring Locations
Guidelines and Standard Procedures for Continuous Water-Quality Monitors: Station Operation,
Record Computation, and Data Reporting (USGS, 2006)
http://pubs.usgs.gov/tm/20Q6/tmlD3/pdf/TMlD3.pdf
Provides guidelines for equipment and monitor selection, placement of online water quality
monitoring equipment in an aquatic environment, sensor inspection and calibration methods, data
evaluation, record review, and data reporting.
Source Water Monitoring Parameters
Guidance for Selecting Online Water Quality Monitoring Parameters and Evaluating Sensor
Technologies for Source Water and Distribution System Monitoring (EPA, 2016c)
https: //www .epa. gov/waterqualitvsurveillance/online -water-qualitv-monitoring-re source s
This document provides detailed information about commonly monitored water quality
parameters and guidance on selecting appropriate parameters to monitor for a given application. It
also provides a summary of available technologies for monitoring each parameter.
Distribution System Water Quality Monitoring: Sensor Technology Evaluation Methodology and
Results A Guide for Sensor Manufacturers and Water Utilities (EPA, 2009)
http: //www .epa. gov/site s/production/ files/2015 -
06/documents/distribution system water quality monitoring sensor technology evaluation me
thodology results.pdf
This document presents the methodology and findings from several studies evaluating the ability
of common water quality parameters to detect a variety of contaminants in finished drinking
water. EPA 600/R-09/076, October 2009.
Source Water Monitoring Stations
Guidance for Building Online Water Quality Monitoring Stations (EPA, 2016d)
https://www.epa.gov/waterqualitvsurveillance/online-water-qualitv-monitoring-resources
This document provides guidance for designing water quality monitoring stations for both source
water and distribution system applications. It describes different station designs and provides
detailed design schematics, describes basic station equipment and station accessories, and
provides considerations for fabricating and installing online water quality monitoring stations.
Guidance for Designing Communications Systems for Water Quality Surveillance and Response
Systems (EPA, 2016e)
https://www.epa.gov/waterqualitvsurveillance/svstem-design-resources
This document provides guidance and information to help utilities select an appropriate
communications system to support operation of a Water Quality Surveillance and Response
System. It provides rigorous criteria for evaluation communications system options, evaluates
common technologies with respect to these criteria, describes the process for establishing
requirements for a communications system, and provides guidance on selecting and implementing
a system. EPA 817-B-16-002, September 2016.
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Information Management and Analysis
Guidance for Developing Integrated Water Quality Surveillance and Response Systems
(EPA, 2015b)
https://www.epa.gov/sites/production/files/2015-
12/documcnts/guidancc for developing integrated wq srss 110415.pdf
This document provides guidance for applying system engineering principles to the design and
implementation of an SRS to ensure that the SRS functions as an integrated whole and is
designed to effectively perform its intended function. Section 4 provides guidance on developing
information management system requirements, selecting an information management system, and
IT master planning. Appendix B provides an example outline for an IT operations and
maintenance plan. EPA 817-B-15-006, October 2015.
Exploratory Analysis of Time-series Data to Prepare for Real-time Online Water Quality
Monitoring (EPA, 2016f)
https://www.epa.gov/waterqualitvsurveillance/online-water-qualitv-monitoring-resources
This document describes methods for analyzing time-series water quality data to establish normal
variability for water quality at unique monitoring locations. It also describes how the results of
this exploratory analysis can be used to develop tools and training to prepare utility personnel for
real-time analysis of online water quality data.
Treatment process selection for particle removal (McEwen, 1998)
http://www.waterrf.org/executivesummarvlibrarv/90701 423 profile.pdf
This document provides guidance on the evaluation, testing, implementation, and optimization of
drinking water treatment processes for particle removal. McEwen, J. B. (ed.). Denver, CO:
AWWA/International Water Supply Association.
Parameter set points: an effective solution for real-time data analysis (Umberg and Allgeier, 2016)
http://dx.doi.org/10.5942/iawwa.2016.108.00Q9
This paper presents the results from an evaluation of the application of thresholds to anomaly
detection in online water quality data collected from a drinking water distribution system.
Umberg, K. and Allgeier, S. JAWWA, 108, E60-E66.
Event Detection System Challenge (EPA, 2013a)
https://www.epa.gov/sites/production/files/2015-
07/documents/water quality event detection system challenge methodology and findings.pdf
This report describes the methodology and results from a study designed to evaluate five anomaly
detection systems used for the analysis of online water quality data for finished water. EPA 817-
R-13-002, April 2013.
Dashboard Design Guidance for Water Quality Surveillance and Response Systems (EPA, 2015e)
https://www.epa.gov/sites/production/files/2015-
12/documents/srs dashboard guidance 112015.pdf
This document provides information about useful features and functions that can be incorporated
into an SRS dashboard. It also provides guidance on a systematic approach that can be used by
utility managers and IT personnel to define requirements for a dashboard. EPA 817-B-15-007,
November 2015.
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Statistical Methods in Water Resources (USGS, 2002)
http://water.usgs.gov/pubs/twri/twri4a3/
This document provides a comprehensive and detailed description of statistical techniques that
can be used to analyze water quality data. It is particularly useful for evaluating correlations and
long-term trends in source water quality. Helsel, D. R. and Hirsch, R. M. In Techniques of water-
resources investigation of the United States Geological Survey, Book 4, Hydrologic analysis and
interpretation.
Information Management Requirements Development Tool (EPA, 2015f)
http://www.epa.gov/waterqualitvsurveillance/surveillance-and-response-svstem-resources
This tool is intended to help users develop requirements for an SRS information management
system, thereby preparing them to select and implement an information management solution.
Specifically, this tool (1) assists SRS component teams with development of component
functional requirements, (2) assists IT personnel with development of technical requirements, and
(3) allows the IT design team to efficiently consolidate and review all requirements. EPA 817-B-
15-004, October 2015.
Investigation and Response Procedures
Template for Developing SWM Investigation and Response Procedures (Word File)
Click this link to open the template
This Word template can be used to develop investigation and response procedures, including: an
SWM alert investigation procedure, a treatment process optimization procedure, and a source
water contamination incident response procedure. The template includes editable procedure
flowcharts with supporting tables and an editable investigation checklist. September 2016.
Guidance for Developing Integrated Water Quality Surveillance and Response Systems
(EPA, 2015b)
https://www.epa.gov/sites/production/files/2015-
12/documents/guidance for developing integrated wq srss 110415.pdf
This document provides guidance for applying system engineering principles to the design and
implementation of an SRS to ensure that the SRS functions as an integrated whole and is
designed to effectively perform its intended function. Section 5 provides guidance on developing
alert investigation procedures, and includes examples of alert investigation tools such as an alert
investigation record and quick reference guides. Section 6 provides guidance on developing a
training program to support SRS operations. EPA 817-B-15-006, October 2015.
Guidance for Building Laboratory Capabilities to Respond to Drinking Water Contamination
(EPA, 2013b)
https://www.epa.gov/sites/production/files/2015-
06/documents/guidance for building laboratory capabilities to respond to drinking water co
ntamination.pdf
This document provides guidance to assist drinking water utilities with building laboratory
capabilities for responding to water contamination incidents, including those occurring in source
waters. It presents contaminant classes of concern, lists analytical methods for those classes, and
provides information on the role of national laboratory networks in responding to drinking water
contamination incidents. EPA 817-R-13-001, March 2013.
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Cyanobacterial Harmful Algal Blooms (EPA, 2016g)
https://www.epa.gov/nutrient-policv-data/cvanohabs
This website provides information and numerous resources for understanding, preventing, and
managing harmful algal blooms in surface water. Topics covered include: causes and prevention,
detection, health and ecological effects, control and treatment, guidance and recommendations,
and a listing of stat resources.
Water Contaminant Information Tool (EPA, 2016h)
https: //www .epa. gov/waterlabnetwork/acce ss -water-contaminant-information-tool
This database provides information on over 800 drinking water and wastewater contaminants,
including pathogens, pesticides, and toxic industrial chemicals. It can serve as a useful resource
for investigating the properties of contaminants associated with SW threats during a risk
assessment. It can also be a valuable resource during response to a source water contamination
incident once the identity of the contaminant is known or suspected. Note that users must register
with EPA to obtain access to this database. EPA 817-F-15-026, November 2015.
Treatability Database (EPA, 2016i)
https://iaspub.epa.gov/tdb/pages/general/home.do
This database provides referenced information on the control of contaminants in drinking water.
It allows users to access information gathered from thousands of literature sources from a single
database. It can serve as a useful resource for investigating the treatability of contaminants when
planning a response to a source water contamination incident.
Guide for Developing a Distribution System Contamination Response Plan (EPA, 2016j)
https://www.epa.gov/waterqualitvsurveillance/consequence-management-resources
This resource provides an editable template for developing a utility-specific Distribution System
Contamination Response Plan. Elements of this plan include investigation of a possible
distribution system contamination incident, planning for site characterization, implementing
operational response actions, issuing public notification, and planning for remediation and
recovery. An accompanying guide helps the user populate the template to customize the plan to a
specific utility.
Developing Risk Communication Plans for Drinking Water Contamination Incidents (EPA, 2013c)
https://www.epa.gov/sites/production/files/2015-
07/documents/developing risk communication plans for drinking water contamination incide
nts.pdf
This resource provides guidance on developing an effective risk communication plan to guide
communications with response partners and the public during a drinking water contamination
incident. EPA 817-F-13-003, April 2013.
Climate Ready Water Utilities (EPA, 2012)
https://www.epa.gov/crwu
This EPA program provides the water sector with practical tools, training, and technical
assistance needed to adapt to climate change by promoting a clear understanding of climate
science and adaptation strategies. One tool provided through this program is the Climate
Resilience Evaluation and Awareness Tool (CREAT), which is a risk assessment tool that allows
a water utility to evaluate potential impacts of climate change under different time periods and
scenarios. CREAT complements other tools and resources, including hydrology and water quality
models.
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Source Water Protection (EPA, 2016k)
https://www.epa.gov/sourcewaterprotection
This EPA program provides guidance and links to a variety of tools and resources to support
source water protection activities.
Source Water Collaborative (SWC, 2016)
http: //sourcewatercollaborative. org/
The Source Water Collaborative (SWC) is a group consisting of 26 national organization and
state and local partners with a mission to foster protection of drinking water resources. The SWC
hosts a website with links to a number of tools and resources to support source water protection.
SRS Exercise Development Toolbox (EPA, 20161)
https://www.epa.gov/waterqualitvsurveillance/water-qualitv-surveillance-and-response-svstem-
exercise-development-toolbox
The Exercise Development Toolbox helps utilities and response partner agencies to design,
conduct, and evaluate exercises around contamination scenarios. These exercises can be used to
develop and refine investigation and response procedures, and train personnel in the proper
implementation of those procedures. The toolbox guides users through the process of developing
realistic scenarios, designing discussion-based and operations-based exercises, and creating
exercise documents. March 2016.
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Glossary
accuracy. The degree to which a measured value represents the true value.
alert. An indication from an SRS surveillance component that an anomaly has been detected in a
datastream monitored by that component. Alerts may be visual or audible, and may initiate automatic
notifications such as pager, text, or email messages.
alert investigation process. A documented process that guides the investigation of an SRS alert. A
typical procedure defines roles and responsibilities for alert investigations, includes an investigation
process diagram, and provides one or more checklists to guide investigators through their role in the
process.
anomaly. A deviation from an established baseline in a monitored datastream. Detection of an anomaly
by an SRS surveillance component generates an alert.
anomaly detection system (ADS). A data analysis tool designed to detect deviations from an established
baseline. An ADS may take a variety of forms, ranging from thresholds to complex computer algorithms.
architecture. The fundamental organization of a system embodied in its components, their relationships
to each other and the environment, and the principles guiding its design and evolution. The architecture of
an information management system is conceptualized as three tiers: source data systems, analytical
infrastructure, and presentation.
baseline. Values for a datastream that include the variability observed during typical system conditions.
completeness. The percentage of data that is of sufficient quality to support its intended use.
component. One of the primary functional areas of an SRS. There are four surveillance components:
Online Water Quality Monitoring (including source water and distribution system monitoring), Enhanced
Security Monitoring, Customer Complaint Surveillance, and Public Health Surveillance. There are two
response components: Consequence Management and Sampling and Analysis.
consequence. The adverse effects of an incident experienced by a utility (e.g., damaged infrastructure) or
its customers (e.g., illness). In the context of a source water risk assessment, consequences result when a
threat contaminates or degrades the quality of a source water. The value for consequence in the risk
assessment equation can be based on quantitative factors such as economic damage, duration of lost
services, number of illnesses, or number of fatalities. The consequence value can also be based on semi-
quantitative measures and normalized such that the SW threat that would result in the greatest
consequences has a consequence value of 100, and the values for all other SW threats being less than 100.
Consequence Management (CM). One of the response components of an SRS. This component
encompasses actions taken to plan for and respond to possible drinking water contamination incidents to
minimize the response and recovery timeframe, and ultimately minimize consequences to a utility and the
public.
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contamination incident. The presence of a contaminant in a source water or drinking water distribution
system that has the potential to cause harm to a utility or the community served by the utility.
Contamination incidents may have natural (e.g., toxins produced by a harmful algal bloom), accidental
(e.g., chemicals spilled into a source water), or intentional (e.g., purposeful injection of a contaminant into
a source water) causes.
control center. A utility facility that houses operators who monitor and control treatment plant and
system operations, as well as other personnel with monitoring or control responsibilities. Control centers
often receive system alerts related to operations, water quality, security, and some of the SRS surveillance
components.
control point. A location where a treatment process can be modified (e.g., addition of pretreatment
chemicals) or a response action can be implemented (e.g., closing an intake).
critical detection point. The location upstream of a drinking water intake from which the hydraulic travel
time to the intake equals the time required to implement a response action, such as closing an intake
structure. The location of the critical detection point is a function of the flow rate used to calculate the
hydraulic travel time.
dashboard. A visually oriented user interface that integrates data from multiple SRS components to
provide a holistic view of system water quality. The integrated display of information in a dashboard
allows for more efficient and effective management of water quality and the timely investigation of water
quality anomalies.
data analysis. The process of analyzing data to support routine system operation, rapid identification of
water quality anomalies, and generation of alert notifications.
data quality objectives. Qualitative and quantitative statements that clarify study objectives, define the
appropriate types of data, and specify the tolerable levels of potential decision errors that will be used as
the basis for establishing the quality and quantity of data needed to support decisions.
design goal. The specific benefits to be realized through deployment of an SRS and each of its
components. For source water monitoring, the following three design goals are applicable: to optimize
treatment processes, detect contamination incidents, and monitor threats to long-term water quality.
Distribution System Contamination Response Plan. A planned decision-making framework that
establishes roles and responsibilities and guides the investigative and response actions following a
determination that distribution system contamination is possible.
emergency response plan (ERP). A document that describes the actions a drinking water utility would
take in response to a variety of emergencies such as contamination incidents, natural disasters, or loss of a
critical asset.
functional requirement. A type of information management requirement that defines key features and
attributes of an information management system that are visible to the end user. Examples of functional
requirements include the manner in which data is accessed, the types of tables and plots that can be
produced through the user interface, the manner in which component alerts are transmitted to
investigators, and the ability to generate custom reports.
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geographic information system (GIS). Hardware and software used to store, manage, and display
geographically referenced information. Typical information layers used by water utilities include utility
infrastructure, hydrants, service lines, streets, and hydraulic zones. GIS can also be used to display
information generated by an SRS.
information management system. The combination of hardware, software, tools, and processes that
collectively support an SRS and provide users with information needed to monitor real-time system
conditions. The system allows users to efficiently identify, investigate, and respond to water quality
incidents.
invalid alert. An alert from an SWM system that is not due to a true water quality anomaly or a
contamination incident.
lifecycle cost. The total cost of a system, component, or asset over its useful life. Lifecycle cost includes
the cost of implementation, operation and maintenance, and renewal.
likelihood. In the context of a source water risk assessment, the probability that an SW threat will
contaminate the source water. The value for likelihood in the risk assessment equation can range from 0
(contamination won't occur) to 1 (contamination is certain to occur).
Online Water Quality Monitoring (OWQM). One of the surveillance components of an SRS. OWQM
utilizes data collected from monitoring stations that are deployed at strategic locations in a source water
or a distribution system. Monitored parameters can include common water quality parameters (e.g., pH,
specific conductance, turbidity) and advanced parameters (e.g., total organic carbon, spectral absorbance)
Data from monitoring stations is transferred to a central location and analyzed.
percentile. In statistics, a value on a scale of 100 that indicates the percent of a distribution that is equal
to or below it.
performance objectives. Measurable indicators of how well an SRS or its components meet established
design goals.
possible. In the context of the threat level determination process, water contamination is considered
possible if the cause of an alert from one of the surveillance components cannot be identified or
determined to be benign.
preliminary operation. A period of SRS component operation during which all equipment and IT
systems are operational, but data analysis and investigations are not performed in real time. The purpose
of preliminary operations is to evaluate the performance of the SRS component, address problems, and
allow personnel to become familiar with SRS component procedures.
real-time. A mode of operation in which data describing the current state of a system is available in
sufficient time for analysis and subsequent use to support assessment, control, and decision functions
related to the monitored system.
risk assessment. A method of assigning risk values to a threat based on likelihood, vulnerability, and
consequence. The current standard risk methodology for the water sector is the J100 standard.
risk communication plan. A plan developed by a utility to guide communications with the public and
coordination with response partners and the media during an emergency.
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Sampling and Analysis (S&A). One of the response components of an SRS. S&A is activated during
Consequence Management to help confirm or rule out possible water contamination through field and
laboratory analyses of water samples. In addition to laboratory analyses, S&A includes all the activities
associated with site characterization. S&A continues to be active throughout remediation and recovery if
contamination is confirmed.
source water. Water from natural resources that is generally treated in order to produce drinking water
for a community. Source water is usually classified as either groundwater (drawn from aquifers) or
surface water (drawn from rivers, streams, lakes, ponds, etc.). Prior to being removed for the purpose of
drinking water production, surface water may have other uses such as recreation (e.g., boating,
swimming, fishing), aquaculture, and transportation route.
source water threat (SW threat). A facility, land use, weather event, or environmental condition with
the potential to degrade source water quality.
spectral fingerprint. The spectral absorbance of a sample over a range of wavelengths (typically in the
visible and ultraviolet spectrum). Spectral fingerprints can be measured for specific compounds or
complex mixtures, and can be a means of identifying the presence of a specific compound or a change in
the characteristics of a complex mixture.
SWM location. The specific location in a source water or watershed where water is sampled for
measurement by an SWM station. Note that an SWM station may be installed away from the SWM
location (i.e., if the water sample is transported from the waterbody to the SWM station through piping).
SWM station. A configuration of one or more water quality instruments and associated support systems,
such as plumbing, electric, and communications that is installed to monitor water quality in real time at an
SWM location.
technical requirement. A type of information management requirement that defines system attributes
and design features that are often not readily apparent to the end user, but are essential to meeting
functional requirements or other design constraints. Examples include attributes such as system
availability, information security and privacy, backup and recovery, data storage needs, and inter-system
integration requirements.
threshold. Minimum and/or maximum acceptable values for individual datastreams that are compared
against current or recent data to determine whether conditions are anomalous or atypical of normal
operations.
treatment process model. A conceptual representation of the operation and performance of a drinking
water treatment unit process. The model typically captures the relationship among influent water quality,
treatment process settings, and effluent water quality. Treatment process models can be categorized as
mechanistic, statistical, or knowledge-based.
treatment roadmap. A set of instructions for adjusting treatment processes to achieve treatment targets
based on information from influent water quality data, process monitoring feedback, or process effluent
water quality data.
valid alert. An alert due to water contamination, a verified water quality incident, an intrusion at a utility
facility, or a public health incident.
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vulnerability. In the context of a source water risk assessment, the probability that a utility or its
customers would be impacted by an SW threat. The value for vulnerability in the risk assessment equation
can range from 0 (no adverse impact will occur) to 1 (adverse impact is certain to occur). The
vulnerability value is generally based on the ability of the utility to effectively respond to an SW threat,
preventing or mitigating consequences to utility infrastructure, operations, and customers.
water quality instrument. A unit that includes one or more sensors, electronics, internal plumbing,
displays, and software that is necessary to take a water quality measurement and generate data in a format
that can be communicated, stored, and displayed. Some instruments also includes diagnostic tools.
water quality sensor. The part of a water quality instrument that performs the physical measurement of a
water quality parameter in a sample.
Water Quality Surveillance and Response System (SRS). A system that employs one or more
surveillance components to monitor and manage source water and distribution system water quality in
real time. An SRS utilizes a variety of data analysis techniques to detect water quality anomalies and
generate alerts. Procedures guide the investigation of alerts and the response to validated water quality
incidents that might impact operations, public health, or utility infrastructure.
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