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SECTION 5. CHESAPEAKE BAY MONITORING AND 

MODELING FRAMEWORKS

For purposes of developing the Chesapeake Bay TMDL, data and scenario results from extensive 

monitoring networks and a series of linked environmental models simulating the nutrient and 

sediment pollutant load sources and the associated water quality and biological responses have 

been applied to support decision making by EPA and its partner Bay watershed jurisdictions. The 

suite of models was developed, calibrated and verified using long-term Bay, watershed, airshed, 

and land-cover monitoring observations and published technical and scientific findings.

The suite of monitoring and modeling frameworks provide accurate and reliable representation 

of the complex Bay water quality processes. The models are valuable tools in synthesizing an 

enormous amount of data, predicting outcomes, providing allocation scenarios and tracking 

progress toward restoration of the Bay. Models have some inherent uncertainty. Because of the 

amount of data and resources taken to develop, calibrate, and verify the accuracy of the Bay 

models, the uncertainly of the suite of models is minimized.

5.1 Technical Monitoring and Modeling Requirements

The combined Chesapeake Bay monitoring and modeling frameworks effectively address all the 

factors necessary for developing a scientifically sound and reliable TMDL that meets the TMDL 

regulatory requirements. The factors addressed in and through the various models are the 

following:

Regulated point sources and non-regulated nonpoint sources of nitrogen, phosphorus, and 

sediment are fully considered and evaluated separately in terms of their relative 

contributions to water quality impairment of the Chesapeake Bay’s tidal waters.

Water quality impairments in the Bay are temporally and spatially variable and are directly 

limited to nutrient and sediment pollutant loadings.

Time-variable aspects of land practices that have a large effect on nutrient and sediment 

loadings and resulting water quality in the Bay are fully simulated.

All sources of data are gathered using methodologies fully consistent across the Bay 

watershed helping ensure equitable allocation of the resultant load reduction responsibility 

across the seven watershed jurisdictions and multiple pollutant source sectors.

The modeling framework takes advantage of decades of atmospheric deposition, 

streamflow, precipitation, water quality, biological resource and land cover monitoring data 

generated through the Bay-wide tidal and basinwide watershed monitoring networks as 

well as tracking and reporting of the implementation of pollution load reduction practices 

and technologies for model calibration and verification.

A wide variety of hydrological conditions have been characterized through decades of 

monitoring to provide reliable simulations in support of management decision making 

across the decadal-scale model hydrologic periods.

The combined monitoring and modeling frameworks provide the ability to simulate and 

assess the critical spatial and temporal variability of the Bay water quality criteria—DO, 
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water clarity, underwater Bay grass acreage, and chlorophyll a—as adopted into the 

jurisdictions’ WQS regulations.

The primary regulatory factor that must be addressed by the combined monitoring and modeling 

frameworks is whether the TMDL allocation scenario will attain and maintain the applicable 

WQS. To make that assessment, the models must be able to relate the pollutant loading from all 

sources to achievement of the Bay jurisdictions’ Chesapeake Bay WQS across all tidal waters. A 

determination that a particular scenario achieves compliance with the applicable water quality 

criteria within each segment for each of the jurisdictions’ WQS requires evaluating the water 

quality impacts of pollutant loadings on multiple parameters across all seasons over a minimum 

of 3 years (USEPA 2003a, 2007a). As a result, the models must provide a time-variable analysis. 

In addition, the modeling framework should also be useful in developing and evaluating action 

plans for implementation, and confirming those combined implementation actions will yield 

achievement of Chesapeake Bay WQS (USEPA 2008b, 2009c, 2010d).

5.2 Bay Monitoring Framework Overview

In August 1984, the original Chesapeake Bay tidal monitoring program was created to achieve

three objectives: characterize the baseline water quality conditions; detect trends in water quality 

indicators; and increase the understanding of ecosystem process and factors affecting Bay water 

quality and living resources (MD OEP 1987). The long-term Chesapeake Bay and watershed 

monitoring networks have accomplished many more objectives in the past 26 years, including 

the following:

Classifying status and tracking trends in water quality and living resources response to 

management actions

Supporting a scientific basis for targeting a dual nutrient strategy to water quality and 

habitat health recovery

Identifying eutrophication as the primary cause of SAV decline

Providing sufficient and diverse data supporting scientifically based and peer-reviewed 

estuarine water quality criteria development to guide restoration targeting and water quality 

assessments (e.g., CWA section 303(d) listing/delisting decisions)

Supporting decision makers’ needs for the Bay TMDL process with high-quality data 

underlying Chesapeake Bay water quality model development, calibration and verification

5.2.1 Partnership’s Chesapeake Bay Tidal Monitoring Network

Undergoing adaptive changes over the almost three decades as management needs and requests 

have significantly evolved over time (CBP 1989a, 1989b; USEPA 2003a; MRAT 2009), the 

Chesapeake Bay tidal monitoring network includes the following:

Tidal water quality monitoring for 26 parameters at over 150 stations distributed over the 

92 Chesapeake Bay tidal segments

Shallow-water monitoring addressing a select set of segments on a rotational basis

Benthic infaunal community monitoring at fixed and random stations across the tidal 

waters

Annual aerial and ground surveys of underwater Bay grasses
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Each component of the tidal monitoring network has been designed to support the Bay 

jurisdictions’ tidal water Bay section 303(d) listing decision makings, addressing DO, water 

clarity, SAV, and chlorophyll a criteria attainment assessments and benthic infaunal communitybased impairment decisions (USEPA 2003a, 2004a, 2007a, 2007b, 2008a, 2010a).

The Bay tidal monitoring network is funded, operated, and maintained through a longstanding 

state-federal-university partnership that produces fundamental data supporting Bay TMDL 

development. This data is utilized in public reporting on the health of the Bay, its tidal rivers,

and supporting ecosystem; assessment of achieving the Bay jurisdictions’ Chesapeake Bay WQS 

regulations; evaluation of the effectiveness of actions to reduce nutrient and sediment pollution 

from the surrounding watershed; developing, calibrating, and verifying models; and generating 

water quality and living resource indicators.

Chesapeake Bay Water Quality Monitoring

The long-term Chesapeake Bay water quality monitoring program uses a fixed station strategy 

with sites distributed along the mid-channel waters of the Bay and its tidal tributaries and 

embayments. The exact number of stations has varied over the 26-year history of the program. A 

set of 162 stations that have been sampled consistently for the majority of those years is 

illustrated in Figure 5-1. One or more stations are in each of the 92 Bay segments. Over the 26-

year history of the program, sampling frequency has ranged from 20 times per year to the present 

14 cruises annually. Synoptic sampling of all the tidal waters takes 1–2 weeks with available 

resources.

At each station, vertical profiles of in-situ water quality measurements are made using 

instrumentation and standard operating procedures approved by the Chesapeake Bay Program’s 

Analytical and Methods Workgroup (see Section 5.2.3). Measurements are collected at 0.5 m, 

1.0 m, 2.0 m and 3.0 m and at a maximum of 2-meter intervals from 1.0 m below the surface to 

1.0 m above the bottom. Water temperature, DO, conductivity, and pH are recorded at each 

depth. Photosynthetic Active Radiation measurements are made, and Secchi depth measurements 

are recorded using a Secchi disc.

At stations where stratification provides a pycnocline, grab samples are collected at 0.5 m below 

the surface, at 1.5 m above the upper pycnocline, at 1.5 m below the lower pycnocline and at 1.0 

m above the bottom. At stations with no identifiable pycnocline as determined by the protocol, 

grab samples are collected at 0.5 m below the surface and 1.0 m above the bottom, and at the 

physical profiling depths which are above one-third and two-thirds the distance between the 

surface- and bottom-sampling depths. Each of the grab sample depths again corresponds to an insitu water quality measured profiling depth.
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Figure 5-1. Tidal monitoring network stations.
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Shallow-Water Monitoring

For shallow water habitat, monitoring consists of high-speed, spatially detailed water quality 

mapping (data collected every 4 seconds) called DATAFLOW, and high-frequency (15-minute 

measurement intervals) continuous monitoring at fixed sites (CONMON) (USEPA 2007a). The 

high-resolution measurements record water temperature, DO concentration, DO saturation, pH, 

salinity (derived from conductivity), turbidity, and fluorescence (used to estimate chlorophyll a).

CONMON measurements are collected March to November. All sondes (i.e. data measurement 

devices) are either at constant depth of approximately 1 m below the surface or at a fixed depth 

from the bottom (0.3 m–0.5 m) depending on depth conditions. In addition to the suite of 

measurements collected by the CONMON meter, LI-COR sensors measure the light penetration 

at the site on each visit. A Secchi measurement is also collected. As a part of standardized 

operating procedures to ensure data quality, each CONMON site is serviced biweekly unless 

water quality readings demonstrate that weekly intervals should be maintained. During each site 

visit, instruments in the water are calibrated against replacement instruments and a third 

instrument. Discrete grab water samples are collected for chlorophyll a, turbidity, and TSS 

calibration. A nutrient suite is further conducted on the discrete water sample. Upon swapping 

out instruments, the instrument removed from the field is returned to the lab for cleaning and lab 

calibration before being redeployed.

DATAFLOW is conducted on a subset of Bay segments each year with monthly measurements 

from April to October. Measurements are made while traveling in a boat at speeds up to 25 

knots. The DATAFLOW system is compact, can fit on a small boat, and allows sampling in 

shallow water with the ability to map an entire small tidal tributary in a day or less. This program 

complements the long term fixed station monitoring by providing data in nearshore shallow 

water habitats critical to SAV where water quality behaves differently from the mid-channel 

measures.

DATAFLOW calibration data are collected at multiple sites to either coordinate with long-term 

or CONMON monitoring stations, and large signal areas to insure coverage of the data gradient 

with the calibration. Discrete grab water samples are collected for chlorophyll. In addition, 

measurements of physical parameters and Secchi depth are made, and on PAR to calculate water 

column light attenuation (Kd). There is quality assurance/quality control (QA/QC) on the data set 

upon returning from the field.

To date, 65 of the 92 Chesapeake Bay segments have 1 to 3 years of shallow-water monitoring 

data available for assessment (Figure 5-2).
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Figure 5-2. Shallow-water monitoring illustrating segment completion and latest rotation for Maryland.

Benthos

The current Bay-wide benthic monitoring program, initiated in Maryland in 1984 and in Virginia 

in 1985, now consists of fixed and random site components. The fixed site monitoring program 

has 53 stations traditionally sampled annually in spring and summer. All fixed sites in Maryland 

and Virginia are sampled using three replicate bottom grabs. The probability-based, random 

strata sampling was initiated in Maryland in 1994. Since 1996, the probability-based sampling 

program has become the standardized approach in Virginia as well, providing a Bay-wide 

regulatory assessment estimating impaired habitat conditions. The impairment assessment relies 

on approximately 200 sites sampled between July 15 and September 30 each year (Figure 5-3). 

Benthos are collected with a Young grab sampler at the probability-based sites.
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Source: R. Llanso, VERSAR, Inc.

Figure 5-3. Example of results from the probability-based sampling distribution, 1998, to estimate habitat 

impairment through benthic community condition assessment.

Submerged Aquatic Vegetation

Consistent annual SAV aerial surveys commenced in 1984 and have been completed every year 

(except 1988) to the present providing detailed mapping of SAV bed coverage, acreage, 

estimated density, and, in combination with ground survey, species identification (Figure 5-4). In 

2001 the program increased efficiency and accuracy by scanning aerial photography from digital 

negatives and orthorectifying (i.e. geometric correction of the photograph) the images using 
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image processing software. SAV beds are categorized visually according to density on the basis 

of percent cover estimates. SAV beds are generally photographed May through October—lower 

Bay SAV in May and June, and low salinity and freshwater areas August through October.

Figure 5-4. One way of illustrating SAV mapping results.

5.2.2 Partnership’s Watershed Monitoring Network

The Chesapeake Bay watershed water-quality network is a network of 85 streamflow gauges and 

water-quality sampling sites operated across the Bay watershed (Figure 5-5). The network is an 

essential component to reporting, tracking, and modeling nitrogen, phosphorus, and sediment 

concentration and loads in the Chesapeake Bay watershed as it provides the only consistent, 

coordinated monitoring effort across all seven Chesapeake Bay watershed jurisdictions. Data 

from the watershed monitoring network sites have been used to develop, calibrate and verify the 

Phase 5.3 Chesapeake Bay Watershed Model (Bay Watershed Model).
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The CBP partnership designed the watershed water-quality sampling network in 2004 and signed 

a MOU in September 2004 to implement the network (Chesapeake Bay Watershed Partners 

2004). The watershed monitoring network has undergone multiple scientific reviews since its 

inception (e.g., STAC 2005a, 2005b; MRAT 2009). After a 2009 review of the monitoring 

network, the original objectives of the network were modified to reflect a balance between the 

long-term monitoring goals of CBP partners and the increased need for tracking changes that 

could result from management actions (restoration) and other changes occurring in the 

watershed. The new objectives, as adopted by the partnership through the CBP’s Management 

Board (MRAT 2009), are as follows:

1. Measure and assess the status and trends of nutrient and sediment concentrations and 

loads in major tributaries and subwatersheds and selected tributary strategy basins

2. Provide data suitable for the assessment of factors affecting nutrient and sediment status 

and trends from major pollutant source sectors

3. Measure and assess the effects of targeted management and land-use change

4. Improve calibration and verification of partners’ watershed models

5. Support spatial and topical prioritization of pollutant reduction, restoration, and 

preservation actions

The network has 85 sites consisting of 67 sites fully implemented (primary) and another 18 sites 

partially implemented (secondary) (Figure 5-5). All primary sites have the following: (1) 

continuous USGS streamflow gauging; (2) 20 water chemistry samples collected annually over a 

range of stream flow conditions (12 base flow and 8 storm flow); (3) nitrogen, phosphorus, and 

sediment analyses; and (4) collection techniques that ensure representative samples. At 

secondary sites, all the requirements for primary sites are met except storm sampling (Figure 

5-5). More than 30 of the primary sites are in locations where monitoring has been coordinated 

for decades, allowing for trend analysis at the locations. Data analysis is just becoming possible 

on the remaining sites as they accumulate close to 5 years of data.
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Source: Chesapeake Bay Program

Figure 5-5. Watershed monitoring network.
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5.2.3 Data Quality and Access

The CBP partnership has a QA program that covers all internal and external activities that 

involve the collection, evaluation, or use of environmental data. The QA program meets the 

requirements of EPA Order CIO 2105.0 for EPA programs, i.e., the American National Standard 

ANSI/ASQC E4-1994. The QA program also satisfies the requirements of the EPA Information 

Quality Guidelines,

1 which describes how EPA organizations meet the Data Quality Act (section 

515(a) of the Treasury and General Government Appropriations Act for Fiscal Year 2001 (Public 

Law 106-554; H.R. 5658). The CBP Office Quality Assurance Program Management Plan2

describes the QA systems and is reviewed regularly and approved by EPA Region 3 (USEPA 

2010k).

The CBP partnership has maintained a research-quality monitoring program for Chesapeake Bay 

tidal waters since the late 1980s when standardized sampling, analytical, and data management 

procedures were developed and coordinated with the then Maryland Office of Environmental 

Programs and the Virginia State Water Control Board. River Input monitoring was then initiated 

at the major fall lines to measure nutrient and sediment loadings from the watershed’s nine 

largest rivers and integrated into the partnership’s QA program. The coordinated watershed 

water quality monitoring was later expanded upstream into rivers and streams across the Bay 

watershed, with seven watershed jurisdictions using comparable protocols (Chesapeake 

Watershed Partners 2004).

Each monitoring program produces a continuous record of high-quality data. As each of the 

monitoring programs is designed to detect trends in water quality constituents, trend analyses 

require very reproducible data over time collected at the lowest possible limits of detection. 

Changes in methods, laboratories, instruments, sampling sites, and such, can affect the results, so 

changes are carefully evaluated and approved to preserve the reproducibility of the data sets over 

time. Data comparability among watershed jurisdictions is reviewed every 3 months through the 

Chesapeake Bay Coordinated Split Sample Program (USEPA 1991b). The CBP Office evaluates 

the accuracy of laboratory data every 3 months by reviewing results of performance evaluation 

samples, i.e., CBP Blind Audit Samples3and UGSS Standard Reference Samples.

4

The tidal monitoring program is designed to represent the complexities of the estuary. Every 2–4 

weeks, a three-dimensional view is obtained by sampling various depths from the surface to the 

bottom of the water column at approximately 139 stations, with each Bay segment having one or 

more sampling sites. Sites are sampled at least once each month. Standardized sampling and 

analytical methods are used to detect low levels of nutrients, chlorophyll and particulates; these 

methods were approved by EPA in 1986 and are still used today (USEPA 1996).

The Chesapeake Bay watershed monitoring network is designed to measure the discharge of 

nutrient and sediment loads from 85 sites in watersheds larger than 1,000 square kilometers. 

Routine samples are collected monthly with additional storm-event samples to obtain a range of 

discharges and loadings. The six jurisdictions, the Susquehanna River Basin Commission, and 

 

1

See http://www.epa.gov/quality/informationguidelines/.

2

See http://archive.chesapeakebay.net/pubs/quality_assurance/cbpoqmp5_01.pdf.

3

See http://nasl.cbl.umces.edu/.

4

See http://bqs.usgs.gov/srs/.
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USGS all use the same set of 

standardized CBP protocols that are 

based on USGS sampling methods and 

EPA-approved analytical methods (CBP 

2008).

All federally funded organizations 

performing sampling, analysis and data 

analysis as part of the tidal and 

watershed monitoring networks have 

EPA-approved QA plans and standard 

operating procedures that conform to the 

CBP Recommended Guidelines for 

Sampling and Analysis5(USEPA 1996). 

These guidelines specify sampling and 

analytical methods, precision and 

accuracy checks and tolerances, and documentation requirements. The QA documents for 

individual partner organizations responsible for components of the larger tidal and watershed 

water quality monitoring networks are on the CBP partnership website at 

http://www.chesapeakebay.net/qualityassurance_wq.aspx.

The CBP Office conducts routine audits of field and laboratory operations to ensure that the 

procedures are carried out according to their approved QA plans. Several organizations conduct 

their own internal field audits or require the use of accredited environmental laboratories.

The Analytical Methods and Quality Assurance Workgroup6has been part of the CBP 

organizational structure since 1988. The workgroup, composed of field sampling team and 

laboratory managers provides technical peer reviews of data collection and reporting activities to 

ensure consistency among the sampling and analytical organizations (Figure 5-6). The 

Workgroup reviews blind audit and coordinated split sample results and identifies potential 

causes of observed differences. Special studies or corrective actions might be necessary to ensure 

inter-laboratory agreement. If differences are found to affect subsequent data analyses, the 

associated bias is quantified and documented in Data and Information Tracking System

(DAITS). DAITS is a registry of technical investigations regarding the quality and use of water 

quality data sets.

5.2.4 Data Submission and Quality Assurance

Water quality data are submitted electronically to the CBP Office by the participating data 

providers (Figure 5-6) according to data submission requirements specified in the federal 

grant/cooperative agreement assistance award provisions (USEPA 2010b). Agencies collecting 

data as part of the Chesapeake Bay tidal water quality monitoring program submit data to the 

Chesapeake Information Management System (CIMS) within 60 days of the end of the month in 

which the sample was collected. Watershed water quality monitoring data are submitted once per 

year. The Data Upload and Quality Assurance Tool (DUQAT) is an automated online tool 

available to data submitters who manage the processing of their data before it is included in the 

 

5

See http://www.chesapeakebay.net/committee_analyticalmethodsworkgroup_projects.aspx?menuitem=16701.

6

See http://www.chesapeakebay.net/committee_analyticalmethodsworkgroup_info.aspx.

Online Chesapeake Bay Monitoring Networks data 

submission, data access, and quality assurance 

resources:

Chesapeake Bay Program Data Hub 

http://www.chesapeakebay.net/dataandtools.aspx?men

uitem=14872

CBP Water Quality Database

http://www.chesapeakebay.net/data_waterquality.aspx

CBP Map of Mainstem and Tributary Stations 

http://archive.chesapeakebay.net/pubs/maps/2004-

149.pdf

CBP Online Water Quality Data Dictionary 

http://archive.chesapeakebay.net/data/data_dict.cfm?D

B_CODE=CBP_WQDB
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database. DUQUAT proceeds through more than 150 format and QA checks, provides a report 

on errors and outliers and, after formal acceptance by the submitter and CBP data manager, loads 

the data into the CIMS Water Quality Database. The final report from the QA-checks is archived 

and available for future reference. The CIMS Data Upload & Quality Assurance Tool User’s 

Guide7gives directions on how to use the tool and shows the correct table formats (Lane 2004). 

The database for the Chesapeake Bay watershed monitoring network is being developed; 

however, data submittals from the participating partners will be required to pass through a 

modified version of DUQAT before acceptance into the database.

After a water quality data submission has passed through DUQAT, and within 24 hours after 

acceptance, the data are added to the Water Quality Database and made available to the public on 

the CBP Data Hub.

8

The Data Hub interface provides access to several types of data related to 

the Chesapeake Bay. It provides links to CBP water quality, living resources (benthic and 

plankton), and nutrient point source databases, and external links to partner data sets and 

databases available on the Data Hub. A data download tool is available for each CBP database 

that allows for queries based upon user-defined inputs such as geographic region and date range. 

Each query results in a downloadable, tab- or comma-delimited text file that can be imported to 

any program (e.g., SAS, Excel, and Access) for further analysis. About 12,000 sampling events 

comprising 8,000,000 data records are housed in the Water Quality Database from 1984 to 

present that are available to the public (scientists, data analysts, and private citizens).

All required data submissions from the monitoring programs described must meet the data 

requirements set forth in the Chesapeake Bay Program Guidance for Data Management, 

October 1997, Metadata Guidelines, and CBP Program Data Dictionaries developed by the 

Information Management Subcommittee of the CBP. All living resources data deliverables are 

sent in a format compliant with Appendix E of the 2000 Users Guide to Living Resources Data

when submitted to the CBP (USEPA 2000).

Database documentation and metadata links for the various sampling programs are available for 

viewing and download. A map of mainstem and tributary monitoring stations9is available and 

helps users query for data in a specific geographic region of the watershed. The 1993 Guide to 

Using CBP Water Quality Monitoring Data10 describes the Chesapeake Bay tidal water quality 

monitoring program in general and provides detailed information about the existing database. A 

2009 draft update to that document is being reviewed. The Water Quality Database Design and 

Data Dictionary11 is a resource that defines the development of the database and provides a 

detailed description of the tables and data in the database. The online version of the Water 

Quality Data Dictionary provides the up-to-date CIMS and CBP codes used in the Water Quality 

Database.

 

7

See http://archive.chesapeakebay.net/pubs/DUQATUsersGuide.pdf.

8

See http://www.chesapeakebay.net/dataandtools.aspx?menuitem=14872.

9

See http://archive.chesapeakebay.net/pubs/maps/2004-149.pdf.

10 See http://archive.chesapeakebay.net/pubs/wquser.pdf.

11 See http://archive.chesapeakebay.net/pubs/cbwqdb2004_RB.PDF.
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Source: Chesapeake Bay Program

Laboratory Abbreviations:

CBL – University of Maryland Chesapeake Biological Laboratory

DCLS – Virginia Department of Consolidated Laboratory Services

DHMH – Maryland Department of Health and Mental Hygiene

DNREC – Delaware Department of Natural Resources and Environmental Quality

DNREC ESL – Delaware Natural Resources Environmental Laboratory Services

Md. DNR – Maryland Department of Natural Resources

NWQL – National Water Quality Laboratory

NYSDEP – New York State Department of Environmental Conservation

ODU – Old Dominion University Water Quality Laboratory

PADEP – Pennsylvania Department of Environmental Protection

SRBC – Susquehanna River Basin Commission

USGS – United States Geological Survey (Md., Pa., Va. & W.Va. Water Science Centers)

Va. DEQ – Virginia Department of Environmental Quality

VIMS – Virginia Institute of Marine Science

Figure 5-6. Chesapeake Bay tidal and watershed water quality monitoring networks’ participants arrayed by 

their role in sample collection, laboratory analysis, or data reporting.
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5.2.5 Monitoring Applications in Chesapeake Bay TMDL Development

Data collected through the Chesapeake Bay tidal and watershed monitoring networks, described 

above, have been applied in numerous ways, supporting the development of the Bay TMDL:

Used to develop the original Chesapeake Bay segmentation scheme and its subsequent 

refinements (USEPA 2004b, 2005)

Used in derivation of the DO, water clarity, SAV restoration acreage and chlorophyll a 

criteria published by EPA on behalf of the partnership (USEPA 2003a)

Used in the delineation of the spatial boundaries of the five Chesapeake Bay tidal water 

designated uses (USEPA 2003c, 2004e, 2010a)

Used in the original development and ongoing refinement of the Chesapeake Bay water 

quality criteria assessment procedures (USEPA 2003a, 2004a, 2007a, 2007b, 2008a, 2010a)

Used by four Bay jurisdictions to assess achievement of their respective Chesapeake Bay 

WQS and development of their section 303(d) lists (USEPA 2007a)

Used in the development, calibration, and verification of the Phase 5.3 Chesapeake Bay 

Watershed Model and Chesapeake Bay Water Quality Model (USEPA 2010j)

5.3 Modeling Framework Overview

Since the early 1980s, the CBP has developed and applied multiple generations of linked 

environmental models to help evaluate the response of Chesapeake Bay water quality to various 

management scenarios and programmatic approaches (Figure 5-7). The fourth and fifth 

generations of some of these environmental models have been applied to support the Chesapeake 

Bay TMDL development.

The Chesapeake Bay models are state-of-the-science, but they are just one of the tools in the 

TMDL analysis that also includes monitoring and environmental research. The models produce 

estimates, not perfect forecasts. Hence, they reduce, but do not eliminate, uncertainty in 

environmental decision making. Used properly, the models provide best estimates for developing 

nutrient and sediment reductions that are most protective of the environment. Ultimately, the 

Chesapeake Bay TMDL was based on the overall corroboration of the Chesapeake Bay models, 

monitoring, and environmental research.

The two major components of the Chesapeake Bay TMDL modeling framework are the Phase 

5.3 Chesapeake Bay Watershed Model and the Chesapeake Bay Water Quality and Sediment 

Transport Model (Bay Water Quality Model). Several other models and tools were used to 

provide critical inputs or to facilitate parameterizing the Bay Watershed Model to run various 

management scenarios (Table 5-1).
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Table 5-1. Modeling tools supporting development of the Chesapeake Bay TMDL.

Model Function

Chesapeake Bay Airshed Model Provides estimates of wet and dry atmospheric 

deposition to the Bay watershed and water quality

models

Chesapeake Bay Land Change Model, Version 4 Provides annual time series of land uses to the Bay 

Watershed Model including projected land uses out to 

2030

Chesapeake Bay Spatially Referenced 

Regressions on Watershed Attributes 

(SPARROW) Model

Provides a general calibration check on Bay 

Watershed Model land use and riverine loads

Chesapeake Bay Scenario Builder Facilitates the creation of input decks for Bay 

Watershed Model management scenarios

Phase 5.3 Chesapeake Bay Community 

Watershed Model

Simulates loading and transport of nutrients and 

sediment from various sources in the Bay 

watershed

Provides estimates of watershed loads resulting 

from various management scenarios

Chesapeake Bay Water Quality/Sediment 

Transport Model

Simulates estuarine hydrodynamics, water quality, 

sediment transport, and key living resources such 

as underwater grasses, oysters and menhaden

Predicts Bay water quality resulting from various 

management scenarios

Ensures allocated loads under the Bay TMDL will 

meet jurisdictions’ WQS Bay criteria

Chesapeake Bay Criteria Assessment Program Assesses attainment of the jurisdictions’ WQS Bay 

criteria using a unique combination of Bay Water 

Quality Model management scenario outputs and Bay 

water quality monitoring data

Chesapeake Bay Climate Change Simulation Uses aspects of downscaled data from Global Climate 

Models, the Bay Watershed Model, and the Bay Water 

Quality Model to simulate climate change effects in 

the Chesapeake Bay and its watershed

The models used to develop the Chesapeake Bay TMDL simulate the same 10-year hydrologic 

period from 1991 to 2000. The models are linked together so that the output of one simulation 

provides input data for another model (Figure 5-7). For example, the nitrogen outputs from the 

Chesapeake Bay Airshed Model (CBAM) affect the nitrogen input from atmospheric deposition 

to the Bay Watershed Model. The Bay Watershed Model, in turn, transports the total nutrient and 

sediment loads, including the contributions from atmospheric deposition, to the Bay Water 

Quality Model. The Bay Water Quality Model, in turn, simulates the effects of the nutrient and 

sediment loads generated by the Bay Watershed Model, and the effects of direct atmospheric 

deposition to tidal surface waters on Bay water quality (e.g., DO, water clarity, chlorophyll a), 

exchange of nutrients and oxygen with bottom sediments, and living resources (e.g., underwater 

Bay grasses, algae, zooplankton, bottom-dwelling worms and clams, oysters, and menhaden).
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Figure 5-7. Chesapeake Bay TMDL modeling framework.

The following sections provide additional details about each of the Bay models and other 

decision support tools used to support development of the Chesapeake Bay TMDL and the 

linkages between the various models and tools. For each model/tool, the sections provide a 

general description of it and how the model was used in developing the Chesapeake Bay TMDL. 

Links to more detailed, online documentation are provided.

5.4 Chesapeake Bay Airshed Model

The Chesapeake Bay Airshed Model (CBAM) provides estimates of nitrogen deposition 

resulting from changes in emissions from utility, mobile, and industrial sources because of 

management actions or growth.

The CBAM was used to provide inputs of nitrogen from wet and dry deposition to the Bay 

Watershed Model and to the Bay Water Quality Model. The CBAM is linked to the Bay 

Watershed Model through atmospheric deposition to land surfaces and to the Bay Water Quality 

Model through atmospheric deposition to water surfaces of the tidal Chesapeake Bay (USEPA 

2010j).

The CBAM combines a regression model of wet deposition (Figure 5-8) (Grimm and Lynch 

2000; 2005), and a continental-scale air quality model of North America called the Community 

Multiscale Air Quality Model (CMAQ) for estimates of dry deposition (Figure 5-9) (Dennis et 

al. 2007; Hameedi et al. 2007). Wet deposition occurs during precipitation events and contributes 

to the loads only during days of rain or snow. Dry deposition occurs continuously and is input at 

a constant rate every day.
DRAFT Chesapeake Bay TMDL

5-18 September 24, 2010

Source: Grimm and Lynch, 2005.

Figure 5-8. Atmospheric deposition monitoring stations used in the airshed regression model. 
DRAFT Chesapeake Bay TMDL

5-19 September 24, 2010

Source: Dr. Robin Dennis, USEPA/ORD/NERL/AMAD/AEIB.

Figure 5-9. The CMAQ 12 km grid over the Phase 5 domain.
DRAFT Chesapeake Bay TMDL

5-20 September 24, 2010

The CMAQ scenarios include the management actions required by the Clean Air Act (CAA) in 

2010, 2020, and 2030. The future year scenarios reflect emissions reductions from national 

control programs for both stationary and mobile sources, including the Clean Air Transport Rule 

(Replacement for the Clean Air Interstate Rule), the Tier-2 Vehicle Rule, the Nonroad Engine 

Rule, the Heavy-Duty Diesel Engine Rule, and the Locomotive/Marine Engine Rule.

The CMAQ provides monthly constants for dry deposition. It requires a variety of input files that 

contain information pertaining to the entire North American continent. Those include hourly 

emissions estimates and meteorological data in every grid cell and a set of pollutant 

concentrations to initialize the model and to specify concentrations along the modeling domain 

boundaries. The initial and boundary concentrations were obtained from output of a global 

chemistry model.

The CMAQ simulation period is for one year, 2002, characterized as an average deposition year. 

The 2002 CMAQ simulation year was used to provide the monthly dry deposition estimate for 

each year of the 1985 to 2010 Bay simulation.

The wet deposition regression model provides hourly wet deposition loads to each land-segment 

on the basis of each land-segment’s rainfall. The regression model uses 29 National Atmospheric 

Deposition Program monitoring stations and 6 AirMoN stations to form a regression of wetfall 

deposition in the entire Phase 5 Model Domain over the entire simulation period (see Appendix 

M).

To account for wet deposition of nitrogen, EPA both developed a specific TMDL LA for the 

direct nitrogen atmospheric deposition onto tidal surface waters of the Chesapeake Bay and 

accounted for air deposition of nitrogen in the LAs to the watershed. The Bay TMDL air 

allocation reflects the modeled nitrogen deposition to the Bay, taking into account the reduction 

in air emissions expected from sources regulated under existing or planned federal CAA

authorized programs (see Section 6.10 and Appendix M).

Detailed information related to the CBAM and its application in the Chesapeake Bay TMDL is 

available in Section 5 of the Phase 5.3 Chesapeake Bay Watershed Model Report (USEPA 

2010i) at http://www.chesapeakebay.net/model_phase5.aspx?menuitem=26169.

5.5 Chesapeake Bay Land Change Model

The Chesapeake Bay Phase 5.3 model makes use of annually changing land use profiles derived 

from the Chesapeake Bay Land Change Model.

5.5.1 Motivations for Developing Future Land Use Estimates

A major challenge facing water resource managers today is how to maintain progress restoring 

the Chesapeake Bay in the face of continued population and urban development. The 

Chesapeake Bay Land Change Model (Land Change Model) was developed to help address this 

management challenge. In conjunction with the Bay Watershed Model, the Bay Land Change 

Model can be used to assess potential future changes in nutrient and sediment loads to the Bay.
DRAFT Chesapeake Bay TMDL

5-21 September 24, 2010

5.5.2 Scale of Chesapeake Bay Land Change Model Future Land Use 

Estimates

To meet the data requirements of Phase 5.3 Chesapeake Bay Watershed Model, the Bay Land 

Change Model forecasts change at the Bay Watershed Model segment scale. The latest version 

of the Bay Land Change Model includes more than 2,000 modeling segments (e.g., polygons) in 

the Bay watershed and intersecting counties (Figure 5-10). The segments were created on the 

basis of an intersection of county boundaries, major topographic divides, and a 1:250,000 scale 

river reach drainage area network. Because the modeling segments are within counties, all data 

generated at the modeling segment scale can also be provided at the county scale for local review 

and comment.
DRAFT Chesapeake Bay TMDL

5-22 September 24, 2010

Source: Chesapeake Bay Program Office.

Figure 5-10. The Land Change Model.
DRAFT Chesapeake Bay TMDL

5-23 September 24, 2010

5.5.3 Components of Chesapeake Bay Land Change Model Future Land 

Use Estimates

In support of the CBP management concerns, researchers from USGS, EPA, Shippensburg 

University, and a private consultant developed the Chesapeake Bay Land Change Model, which 

combines the strengths of a growth allocation model or GAMe (Reilly 2003), with those of a 

cellular automata model, SLEUTH (slope, land use, excluded land, urban extent, transportation, 

and hillshade) (Clarke et al. 1997; Jantz et al. 2003). GAMe projects future urban developed area 

at the watershed modeling segment scale by fitting total housing unit trends over the 1990s to a

Gompertz (exponential S-shaped) curve that is then used to extrapolate housing trends to the year 

2030. County population projections converted to county scale estimates of total housing 

demand are used to constrain the modeling segment scale forecasts generated using the 

Gompertz Curve. After the model segment scale forecasts of housing demand are adjusted to 

match the county scale housing demand totals, they are converted to an estimate of future urban 

developed area using segment-specific ratios of urban developed land cover area to total housing 

units.

The proportions of structural development growth occurring on farmland, forest land, sewer, 

septic, and within existing developed boundaries are determined uniquely for each watershed 

modeling segment using the SLEUTH growth model, a stochastic cellular automata model 

customized for application in the Chesapeake Bay watershed by Goetz and Jantz (2006). 

SLEUTH extrapolates historic rates and patterns of urban developed growth into the future using 

satellite derived imagery of 1990 and 2000 impervious cover. SLEUTH was calibrated 

separately in 15 different county clusters in the Bay watershed. Counties were clustered 

according to shared characteristics of urban developed growth, commuting patterns, and state 

and ecoregion boundaries. SLEUTH uses a Monte Carlo method to generate multiple simulations 

of future growth, which are combined to create a probability map of future urban development. 

The output from SLEUTH is a 30-m resolution probability raster data set that indicates the 

probability of urban developed growth in the year 2030 with values ranging from 0 to 100 

percent.

The patterns of probable growth can vary for each cluster of counties by the coefficients used to 

calibrate SLEUTH in each cluster. The patterns and levels of probable urban developed can also 

vary within a county by local factors of attraction and repulsion. The factors are represented in a 

30-m resolution raster data set referred to as an exclusion layer. Local areas off limits to 

development can include public lands, conservation easements, rurally zoned lands, steep slopes 

(greater than 21 percent grade), emergent wetlands, and open water. For the Bay watershed, an 

exclusion layer was created in a GIS using information on public and protected lands, 

generalized zoning, and land cover. Values greater than 50 are relatively repulsive to growth 

with 100 being completely excluded. Values less than 50 are relatively attractive to growth (e.g., 

areas zoned for moderate or high density growth). The midpoint, 50, is neutral.

The probability output from SLEUTH is overlaid onto a raster land cover data set to determine 

the relative proportions of land cover classes and sewer areas affected by future growth. For 

example, if a cell with a 50 percent probability of becoming developed by 2030 overlays a forest 

cell in the land cover map, 50 percent of that cell is considered forest loss. For each modeling 

segment, the total acreage of all land cover classes converted to urban developed are summed 

and divided by the total of urban developed acreage forecasted in the modeling segment. That
DRAFT Chesapeake Bay TMDL

5-24 September 24, 2010

process generates relative proportions of future growth by land cover class for each modeling 

segment. Multiplying those proportions by the acreage of forecasted growth (generated by 

GAMe) determines how much acreage to subtract or add in future years to the Phase 5 

Watershed Model 2002 baseline land use classes.

The Bay Land Change Model also includes a Sewer Model to estimate the population on sewer 

and septic in the years 2000 and 2030. Where local data were not available, a population density 

raster data set derived from year 2000 Census Block Group data and detailed road vector files 

were used to represent probable sewered areas in the year 2000. The approach captures 81

percent of Maryland’s mapped residential sewered areas on the basis of a one-to-one cell 

comparison. That approach also compares favorably with survey data in Virginia representing 

households with sewer service in the 2001 to 2005 period.

Modeled sewered areas in the year 2000 were expanded along existing roads by 300 m to 2,000

m to represent possible expansion of the sewer network through the year 2030. Forecasted 

population values for each watershed modeling segment were derived by converting the housing 

demand forecasts into estimates of future population. Future populations on sewer and septic 

were estimated by overlaying the SLEUTH probability map onto the modeled sewer service 

areas for 2030 to derive proportions of growth on sewer and septic, which were then multiplied 

by the forecasted population in each modeling segment. The proportions of growth on sewer and 

septic were kept constant for all interim year forecasts between 2000 and 2030. The percent 

change in population within each sewer service area was used to estimate the percent change in 

flow for all wastewater treatment plants in or close to each service area.

More detailed information on the Chesapeake Bay Land Change Model and its application in the 

Chesapeake Bay TMDL is available in Section 4 of the Phase 5.3 Chesapeake Bay Watershed 

Model Report (USEPA 2010i) at 

http://www.chesapeakebay.net/model_phase5.aspx?menuitem=26169.

5.6 Chesapeake Bay SPARROW Model

The USGS developed a set of spatially referenced regression models to provide additional spatial 

detail on nutrient sources and transport processes in the Bay watershed. The SPARROW 

(SPAtially Referenced Regression On 

Watershed attributes) model integrates 

monitoring data with landscape 

information and uses statistical 

methods to relate water-quality 

monitoring data to upstream sources 

and watershed characteristics that 

affect the fate and transport of 

constituents to streams, estuaries, and 

other receiving waterbodies (Preston 

et al. 2009). SPARROW is watershed 

based and designed for use in 

predicting long-term average values 

such as concentrations and delivered 

loads to downstream receiving waters. 

For additional information on Chesapeake Bay 

SPARROW modeling, see the following resources:

SPARROW fact sheet

http://pubs.usgs.gov/fs/2009/3019/

National SPARROW home page

http://water.usgs.gov/nawqa/sparrow/

Chesapeake Bay Specific

http://md.water.usgs.gov/publications/wrir-99-

4054/html/index.htm

http://md.water.usgs.gov/publications/ofr-2004-1433/

http://chesapeake.usgs.gov/coast/restorationmapper.htm

l
DRAFT Chesapeake Bay TMDL

5-25 September 24, 2010

Statistical methods are used to explain in-stream measurements of water quality in relation to 

upstream sources and watershed properties (e.g., soil characteristics, precipitation, and land 

cover).

Among its outputs, the SPARROW model can be used to quantify incremental yield or edge-offield loading, which is the amount (load per area) of total nutrients or sediment generated in each 

reach basin independent of upstream load (Figure 5-11). The Chesapeake Bay SPARROW 

models provide loading information for three separate periods, the late 1980s, the early 1990s, 

and the late 1990s (Brakebill and Preston 2004). For the Chesapeake Bay watershed modeling 

and TMDL development effort, EPA used the results of the SPARROW model as a data source 

for estimating average edge-of-field targets when developing and calibrating the Phase 5.3 

Chesapeake Bay Watershed Model (USEPA 2010j).

Source: Preston and Brakebill, 1999.

Figure 5-11. An example of SPARROW Model output showing delivered yield of total nitrogen in the 

Chesapeake Bay watershed during 1987. 
DRAFT Chesapeake Bay TMDL

5-26 September 24, 2010

5.7 Scenario Builder

Scenario Builder is a standalone data pre-processor for the Phase 5.3 Chesapeake Bay Watershed 

Model. It is designed to track the land use-related nutrient processes for the multiple land userelated sources in the watershed and to facilitate parameterization of those sources for watershed 

model scenarios to be run through the Bay Watershed Model (Figure 5-12). Scenario Builder 

generates information that is used to simulate loads related to animal production areas, manure 

storage, application of manure and fertilizers, septic inputs, plant growth/uptake and BMP 

implementation. Scenario Builder can handle data at a variety of levels, including land-river 

segment, river segment, land segment, county, state and basin, tributary strategy basin, or state 

and can vary by the BMP in question. Scenario Builder is designed so that users may select an 

area of one or more counties, the livestock types and the number of animals, along with a land 

use using the 25 Watershed Model-HSPF categories and then be able to alter the crop mix that is 

nested in each of the agricultural land uses along with Best management practices (BMPs).

Source: Scenario Builder Documentation, 

http://archive.chesapeakebay.net/pubs/SB_Documentation_Final_V22_9_16_2010.pdf

Figure 5-12. Scenario Builder conceptual process.

Scenario Builder provides nutrient loads to the land and the area of soil available to be eroded. 

Loads are input to the Bay Watershed Model to generate modeled estimates of loads delivered to 

the Bay. Additional information related to Scenario Builder and its application in Bay TMDL 

development (USEPA 2010d) is at 

http://www.chesapeakebay.net/modeling.aspx?menuitem=19303.
DRAFT Chesapeake Bay TMDL

5-27 September 24, 2010

For the Bay TMDL, Scenario Builder was used to provide the land use-based scenario inputs to 

the Phase 5.3 Chesapeake Bay Watershed Model. The seven watershed jurisdictions will 

continue using it when implementing the Bay TMDL to build model scenarios of their actual and 

future implementation practices that will, in turn, be run through the Bay Watershed Model to 

track implementation status and project future implementation rates.

5.8 Phase 5 Chesapeake Bay Watershed Model

The Phase 5.3 Chesapeake Bay Watershed Model is an application of the Hydrologic Simulation 

Program-Fortran (HSPF) (Bicknell et al. 2005). The segmentation scheme divides the 

Chesapeake Bay watershed into approximately 1,000 segments/subbasins, the average size is 

about 64 square miles. About 280 monitoring stations throughout the Chesapeake Bay watershed 

were used for calibration of hydrology, while approximately 200 monitoring stations were used 

to calibrate water quality, depending on the constituent being calibrated. There are 530 riversegments with simulated reaches that drain to a simulated downstream reach. There are 62 riversegments with simulated reaches that drain directly to the Chesapeake Bay and 379 riversegments adjacent to tidal waters that are without a simulated reach (Figure 5-13).

The Bay Watershed Model simulation period covers 21 years from 1984 to 2005 to take 

advantage of more recent and expanded monitoring. The expansion of the model period to a 

21-year period required a change in the treatment of land use in model calibration. While the 

Phase 4.3 Bay Watershed Model and all previous watershed model versions had a constant land 

use, the Phase 5.3 Bay Watershed Model allows a time series of land use input data to change 

annually over the 1984 to 2005 simulation period (USEPA 2010i).

As a community model, the Phase 5.3 Bay Watershed Model has open source model code, 

pre-processors, post-processors, and input data that are freely available to the public (USEPA 

2010i). Input data include precipitation information, point sources discharges, atmospheric 

deposition, and land use (USEPA 2010i). By offering the Bay Watershed Model as a community 

model, end users—typically TMDL model developers and watershed researchers and 

implementation plan developers—can use the model independently as-is or as a starting point for 

more detailed, small-scale models (USEPA 2010i). The Phase 5.3 Bay Watershed Model can be 

downloaded from this ftp site: ftp://ftp.chesapeakebay.net/Modeling/phase5/community/ or the 

Chesapeake Community Modeling Program’s website at 

http://ches.communitymodeling.org/models/CBPhase5/datalibrary.php.

The Bay Watershed Model simulates the 21-year period (1984–2005) on a one-hour time step 

(USEPA 2010j). Nutrient inputs from manure, fertilizers, and atmospheric deposition are based 

on an annual time series using a mass balance of U.S. Census of Agriculture animal populations

and crops, records of fertilizer sales, and other data sources. BMPs are incorporated on an annual 

time step and nutrient and sediment reduction efficiencies are varied by the size of storms. Point 

source and onsite wastewater management nutrient and sediment contributions are also included 

in the model. The following sections provide additional details regarding the underlying data 

used to develop and calibrate the Phase 5.3 Bay Watershed Model.
DRAFT Chesapeake Bay TMDL

5-28 September 24, 2010

Source: Phase 5.3 Chesapeake Bay Watershed Model.

Figure 5-13. Segmentation and reach simulation of the Phase 5.3 Chesapeake Bay Watershed Model.
DRAFT Chesapeake Bay TMDL

5-29 September 24, 2010

5.8.1 Segmentation

In many HSPF applications, the river segmentation and the land segmentation is the same. Each 

river segment will have a set of land uses that drain to it and it only. In the Phase 5.3 Bay 

Watershed Model, the segmentation schemes are separate. Land segments are generally county 

based because a simulation of a representative acre of each land use type exists in each county. 

Some counties in mountainous regions where the rainfall patterns varied significantly have been 

broken out in to several land segments. The segments that result from the intersection of the two 

segmentation schemes are known as land-river segments (Martucci et al., 2006).

5.8.2 Model Setup

Detailed information related to how the Bay Watershed Model was set up to support 

development of the Bay TMDL is available in the Phase 5.3 Chesapeake Bay Watershed Model 

Report. In addition, information related to model representation of land use-related nutrient 

generating sources is available in the working documentation for the Scenario Builder 

application (USEPA 2010j). The following paragraphs provide a general description of critical 

data components underlying the Bay Watershed Model.

Meteorological Data

Meteorological data are critical inputs to the model because precipitation is a primary driver of

loading in the Bay. Approximately 500 daily data and 200 hourly data precipitation monitoring 

stations were used in the Bay Watershed Model. Precipitation is derived from an hourly output 

regression model of these stations developed by USGS. Meteorological parameters included in 

the simulation are hourly temperature, solar radiation, wind speed, daily dew point, cloud cover, 

and potential evapotranspiration. Those parameters were collected from the seven primary 

meteorological stations in the Chesapeake Bay watershed (USEPA 2010j).

Withdrawals

Water withdrawals are represented in the model as daily amounts from jurisdictions’ reported 

data of monthly or annual withdrawals. Water withdrawals include irrigation use and

thermoelectric use, among others. The model takes into account the seasonal cycle of irrigation 

use. Consumptive uses are modeled as 100 percent removal of the water from the appropriate 

stream segment, and any resulting wastewater is treated as a separately modeled point source 

discharge (USEPA 2010j).

Sediment

Soil characteristics were obtained from the Natural Resources Conservation Service 

Interpretation Records and the National Resources Institute. Sediment delivery from each land 

use is based on National Resources Institute estimates of annual edge-of-field sediment loads, as 

determined by the Revised Universal Soil Loss Equation (USEPA 2010j).

Land uses

The watershed model simulates 24 land uses, including 11 types of cropland, 2 types of 

woodland, 3 types of pasture, 5 types of developed land, and provisions for other special land 

uses such as surface mines and AFOs (Table 5-2) (USEPA 2010j). Nutrients in the major 

pervious land uses of woodland, cropland, hay, pasture, and developed pervious are simulated 
DRAFT Chesapeake Bay TMDL

5-30 September 24, 2010

using the AGCHEM modules in HSPF that fully simulate forest or crop nutrient cycling, 

including uptake by plants. The minor pervious land uses, which are harvested forest, land under 

construction, nurseries, surface mines, and degraded riparian pasture, are simulated through 

PQUAL, which represents nutrient export through concentration coefficients. Impervious land 

uses are simulated through the IQUAL modules, which use accumulation and washoff 

coefficients to simulate nutrient and sediment export. The final Phase 5.3 land use is available as 

a sub-county tabular database for the years 1985, 1987, 1992, 1997, 2002, and 2005 at 

ftp://ftp.chesapeakebay.net/Modeling/phase5/Phase%205.3%20Calibration/Model%20Input/land

_use.zip

The Phase 5.3 model input decks including the land use files above are also linked with a brief 

explanation from the Phase 5 Model page on: 

chesapeakebay.net.http://www.chesapeakebay.net/model_phase5.aspx.

The Bay Watershed Model uses a continuous time series of land use interpolated from those 

years.

The principal databases used to develop the Phase 5.3 Bay Watershed Model, 30-meter land use 

coverage are the following:

USGS Chesapeake Bay Land Cover 1984, 1992, 2001 and 2006 Data Series (CBLCD).

County level agricultural census data (USDA 1982, 1987, 1992, 1997, 2002, 2007).

2001 Impervious Surface Land Cover data developed by the University of Maryland’s 

Regional Earth Science Applications Center (RESAC) (Goetz et al. 2004).

Ancillary data from the jurisdictions were used to develop the extractive land use cover, 

including spatial and tabular permitting information.

Construction land use is a percentage of impervious change.

Table 5-2 provides a summary of the land use types modeled by the Phase 5.3 Bay Watershed 

Model, the specific land uses and a basic description of their derivation. Additional detail is 

available in Section 4 of the Phase 5.3 Chesapeake Bay Watershed Model report (USEPA 2010j) 

at http://www.chesapeakebay.net/model_phase5.aspx?menuitem=26169.

Table 5-2. Phase 5.3 Chesapeake Bay Watershed Model land uses

Land use type Land use Description Source

Agricultural Pasture Based on pastureland areas 

from the agricultural census

USDA Agricultural Census 

Degraded riparian 

pasture

Unfenced riparian areas where 

livestock have stream access; 

represents a portion of the 

pasture use

A unique area designated 

by each state as the acres 

of planned riparian 

pasture fencing in their 

Tributary Strategies

Nutrient 

management 

pasture

Pasture that is part of a farm 

plan where crop nutrient 

management is practiced. 

Nutrient management pasture is 

pasture that receives manures 

that are excess on a farm after 

all crop nutrient needs are 

satisfied.

Derived from the pasture 

land use and state nutrient 

management BMP 

tracking data
DRAFT Chesapeake Bay TMDL

5-31 September 24, 2010

Land use type Land use Description Source

Alfalfa hay Alfalfa is a separate hay 

category because it is a 

nitrogen-fixing, leguminous crop 

and receives different nutrient 

applications than other hay 

crops

USDA Agricultural Census

Hay-unfertilized (Wild hay) + (cropland idle) + 

(cropland in cultivated summer 

fallow)

USDA Agricultural Census

Hay-fertilized (Hay-alfalfa, other tame, small 

grain, wild grass, silage, green 

chop, act) – (wild hay) – (alfalfa) 

+ (cropland on which all crops 

failed)

USDA Agricultural Census

Conventional tillage

with manure

Wheat, barley, buckwheat, 

sunflower, corn, sorghum, 

soybeans and dry beans

USDA Agricultural Census

Conservation tillage 

with manure

Wheat, barley, buckwheat, 

sunflower, corn, sorghum, 

soybeans and dry beans

USDA Agricultural Census

Conventional tillage 

without manure

(Cotton) + (tobacco) + (land 

used for vegetables) + 

(potatoes, excluding sweet 

potatoes) + (sweet potatoes) + 

(berries) + (nursery acres in the 

open) + (land in orchards)

USDA Agricultural Census

Conservation tillage 

without manure 

Crops typically grown for direct 

human consumption (such as 

cotton, tobacco, vegetables, 

potatoes and berries) and field 

nurseries

USDA Agricultural Census

Nursery Container nurseries, which 

typically have a high density of 

plants (10–100 plants per 

square meter) and high rates of 

nutrient applications 

USDA Agricultural Census

Animal Feeding 

Operations

Percentage of pastureland, 

based on animal populations 

from the agricultural census

Derived from the USDA 

Agricultural Census count 

of farms and the type and 

numbers of animals

Woodland Forest, woodlots, 

and wooded 

Includes woodlands, woodlots, 

wetlands and usually any 

wooded area of 30 meters by 30 

meters remotely sensed by 

spectral analysis. Predominant 

land use in watershed.

Largely derived from the 

land area the was not 

developed, not in the 

Agricultural Census and 

not water of lakes and 

rivers

Harvested forest Estimated at 1% of forest, 

woodlots, and wooded land use

Derived from the forest, 

woodlots, and wooded 

land use

Developed High-density 

pervious

High-Intensity Pervious 

Developed (Hp) lands are 

immediately adjacent to HighIntensity Impervious Developed 

lands and include mostly small 

Derived from satellite data 

and density of road 

network
DRAFT Chesapeake Bay TMDL

5-32 September 24, 2010

Land use type Land use Description Source

landscaped areas and lands 

adjacent to developed 

structures and major roadways.

No portions of these lands are 

impervious

High-density 

impervious

High-Intensity Impervious 

Developed (Hi) lands contain 

more than 50% impervious 

surfaces per quarter-acre (on 

average) and generally 

represent impervious surfaces 

associated with large structures 

and major roads and include 

mostly commercial, industrial, 

and high-density residential land 

uses, interstates, and other 

major roads.

Derived from satellite data 

and density of road 

network

Low-density 

pervious

Low Intensity Pervious 

Developed (Lp) lands are 

generally associated with LowIntensity Impervious Developed 

lands and include residential 

lawns, golf courses, cemeteries, 

ball fields, developed parks, and 

other developed open spaces.

Any impervious surfaces 

associated with these land uses 

are captured in either the lowintensity or high-intensity 

impervious developed classes 

depending on the size of the 

structure or road.

Derived from satellite data 

and density of road 

network

Low-density 

impervious

Low-Intensity Impervious 

Developed (Li) lands contain 

less than 50% impervious 

surfaces per quarter-acre (on 

average) and generally 

represent impervious surfaces 

associated with small structures 

and minor roads and include 

mostly low to medium density 

residential areas and some 

sidewalks and driveways.

Derived from satellite data 

and density of road 

network

MS4 Developed land coincident with 

an area requiring Municipal 

Separate Storm Sewer System 

(MS4) permits.

Derived from state 

regulatory data

Minor Land 

uses

Bare-construction Based on the difference 

between the RESAC impervious 

land estimates of 1990 and 

2000. Impervious land, which 

increased over the 10-year 

period, was assumed to have 

transitioned from a bareconstruction land use

Derived from a 

combination of impervious 

area and construction 

permits
DRAFT Chesapeake Bay TMDL

5-33 September 24, 2010

Land use type Land use Description Source

Extractive-Active 

and Abandoned 

Mines

Mines, gravel pits and areas 

affected by mine-related 

activities. In Virginia, acres are 

based on permit information; all 

others are based on RESAC 

data

State permitting data

Open Water Nontidal waters, acreage 

constant throughout model 

period

Satellite-derived estimate

Source: USEPA 2010j

Agricultural Land Uses

Satellite-derived estimates of cropland and pasture have higher uncertainty in the prediction of 

the extent of these land cover classes compared to the Census of Agriculture in certain land-river 

segments, so census data were used to inform and modify the extent of these land uses. Countylevel total agricultural land use from the agricultural census data were interpolated to the base 

years of 1990 and 2000. Agricultural land use was distributed to the model segments by the ratio 

of census agricultural classes for each county, and other land uses were distributed in the 

remaining model segment area in proportion to their acreage in the county. Annual changes in 

land use were linearly extrapolated or interpolated from the 1990 and 2000 base years and years 

covered in the agricultural census (1982, 1987, 1992, 1997 and 2002), resulting in annual subcounty data sets of land use.

The total agricultural area was split into different agricultural land uses, by the average ratio of 

crops in the agricultural census. Crops were aggregated by similar surface cover characteristics 

and fertilizer application rates to yield categories with similar nutrient-loading properties.

State agricultural engineers provided fertilizer and manure application timing and rates, crop 

rotation information, and field operation timing information. Manure application is represented 

in a time-varying mass balance of manure nutrients, according to animal population and 

predominant manure handling practices (USEPA 2010j).

Animal waste areas are defined by manure acres, which allows for the simulation of high nutrient 

content runoff and are based on the population of different animal types. The manure acres in a 

given area change based on the number of animals of each type (beef and dairy cattle, swine, 

laying hens, broilers and turkeys) and the implementation of animal waste management systems. 

Nutrient export is simulated as a concentration applied to the runoff from the manure acres 

(USEPA 2010j).

Urban Land Uses

For urban land representation, high- and low-density development and the proportion of 

impervious and pervious area were mapped for 1990 and 2000 (USEPA 2010j).

Other Land Uses

Other land uses represented in the model include construction, which typically has high sediment 

loading capacity; extractive-active and abandoned mines; and open nontidal water.
DRAFT Chesapeake Bay TMDL

5-34 September 24, 2010

Future Land Use Estimations

The Chesapeake Bay Land Change Model was developed to help assess potential future changes 

in nutrient and sediment loads to the Bay resulting from land use changes (see Section 5.5 and 

Section 6).

5.8.3 Pollutant Source Representation

The Bay Watershed Model represents various sources of nutrients and sediments on the basis of 

the characteristics of the source and information available for characterizing the source. Point 

sources such as permitted wastewater and industrial dischargers that generally discharge 

continuously are represented directly in the model using locational data, flow, and discharge 

characteristics. Other sources, such as septic systems or agricultural activities, are represented in 

the model through the underlying land use coverage and assumptions related to nutrient and 

sediment production from associated land uses. Those sources can be thought of as land userelated sources because the simulation of their loading characteristics is driven by the land use 

categories with which they are associated. Several such land use-related sources are subject to 

NPDES permits. An example of such a land use-related source is an MS4 area, which is subject 

to an NPDES permit and must receive a WLA in the TMDL, but loadings are derived as a 

function of the modeled land use loading rates for associated land uses (e.g., urban pervious 

land). The following paragraphs summarize Bay Watershed Model representation of the major 

sources of nutrients and sediment to the Bay. Additional minor land use sources are also detailed 

in the Phase 5.3 Chesapeake Bay Watershed Model Report (USEPA 2010j).

Municipal and Industrial Discharges

Municipal and industrial discharges are considered direct inputs to the river reaches. In the Bay 

Watershed Model, the river segments are simulated as a completely mixed reactor, and all the 

wastewater discharged loads within a reach are summed for each of the river segments and input 

as a daily load (USEPA 2010j).

CAFOs

CAFOs are represented in the model as part of the AFO land use, which represents the 

production area of livestock operations. The loading is calculated on the basis of animal counts; 

manure nutrients production rate modified by feed considerations; time spent in pasture out of 

the production area; volatilization factors; and loss coefficients, which are dependent on storage 

facility type. The full description of the CAFO and AFO land use loads is available in the 

Scenario Builder documentation (USEPA 2010c) at 

http://www.chesapeakebay.net/modeling.aspx?menuitem=19303.

CSOs

CSO loads are not directly simulated by the Bay Watershed Model. CSO loads for the TMDL 

were developed using estimations of daily CSO flows and nutrient concentrations for the CSO 

communities in the watershed. For details related to how the loads were calculated, see Section 7 

of the Phase 5.3 Chesapeake Bay Watershed Model Report (USEPA 2010j) at 

http://www.chesapeakebay.net/model_phase5.aspx?menuitem=26169.

MS4s

The estimated MS4 areas were provided by each of the jurisdictions and represent the current 

understanding of MS4 areas. While the best and final definition of an MS4 is delineated 
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sewersheds (drainage area served by a sewer system), most jurisdictions could provide only 

municipal boundaries as an estimated MS4 area. There might be additional developed land, 

however, outside the municipal boundaries that also drains to the MS4 area, that can be shown 

by GIS data. The Phase 5.3 Bay Watershed Model uses the GIS data and topographic 

information to delineate the sewershed, which includes all land in the municipal boundaries and 

developed land outside the municipal boundaries that drains to the MS4 (USEPA 2010j).

Septic Loads

Septic system loads are calculated on the basis of U.S. Census Bureau estimates of the number of 

systems in the watershed and standard assumptions regarding nitrogen waste generation and 

attenuation. The model simulates nitrate discharges directly to stream and river reaches (USEPA 

2010j).

5.8.4 Calibration

The Phase 5.3 Bay Watershed Model segments are defined such that segment outlets are in 

proximity to in-stream flow gauging and water quality monitoring stations to increase the 

accuracy of model calibration. Calibration involved comparing available streamflow and water 

quality data for the years 1985 to 2005 to watershed model calibration output for the same 

period.

To calibrate the model output, various water quality parameters such as simulated streamflows,

(sediment) TSS, total phosphorus, organic and particulate phosphorus, phosphate, total nitrogen, 

nitrate, total ammonia, organic nitrogen concentrations and loads, temperature, and DO were 

compared to the observed data from the in-stream monitoring sites (Figure 5-14). In an 

automated calibration process, model parameters were adjusted to optimize the representation of 

observed in-stream conditions (USEPA 2010j).

The calibrated Bay Watershed Model was run for a 21-year hydrologic period (1985–2005) to 

simulate loads for various evaluation scenarios. Those loads were linked to the Bay Water 

Quality/Sediment Transport Model to test whether a given scenario met the Bay jurisdictions’ 

WQS in the Bay. Modeled loads are reported as the average annual load over the modeled

period.
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Source: USEPA 2010i.

Figure 5-14. Phase 5.3 Chesapeake Bay Watershed Model hydrology (upper panel) and water quality (lower 

panel) monitoring calibration stations overlaid on the Phase 5.3 river segments.
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5.9 Chesapeake Bay Water Quality and Sediment Transport Model

The Bay Watershed Model was linked to the Chesapeake Bay Water Quality/Sediment Transport 

Model (Bay Water Quality Model), which in turn was used to evaluate the impacts on Bay water 

quality conditions in response to changes in nutrient and sediment loading levels.

The Bay Water Quality Model combines a three-dimensional hydrologic transport model 

(CH3D) with a eutrophication model (CE-QUAL-ICM) to predict water quality conditions in the 

Bay resulting from changes in loads from the contributing area (Figure 5-15). The hydrodynamic 

model computes intra-tidal transport using a three-dimensional grid framework of 57,000 cells 

(Cerco, 2010 [in preparation]). The sediment transport model computes continuous threedimensional velocities, surface elevation, vertical viscosity and diffusivity, temperature, salinity, 

and density using time increments of 5 minutes.

The eutrophication (water quality) model computes algal biomass, nutrient cycling, and DO, as 

well as numerous additional constituents and processes using a 15-minute time step ((Cerco and 

Noel, 2004)). In addition, the eutrophication model incorporates a predictive sediment 

diagenesis12 component, which simulates the chemical and biological processes undergone at the 

sediment-water interface after sediments are deposited (Di Toro, 2001; Cerco and Cole, 1994).

The hydrodynamic model was calibrated for the period 1991–2000 and verified against the large 

amount of observed tidal elevations, currents, and densities available for the Bay.

Computed flows, surface elevations, and vertical diffusivities from the hydrodynamic model 

were output at 2-hour intervals for use in the water quality model. Boundary conditions were 

specified at all river inflows, lateral flows, and at the mouth of the Bay.

Loads to the system include distributed or nonpoint source loads, point source loads, atmospheric 

loads, bank loads, and wetlands loads. Nonpoint source loads enter the tidal system at tributary 

fall lines and as runoff below the fall lines. Point source loads are from industries and municipal 

wastewater treatment plants. Atmospheric loads are deposited directly to the Bay tidal surface 

waters. Atmospheric loads to the watershed are incorporated in the distributed loads. Bank loads 

originate with shoreline erosion. Wetland loads are materials created in and exported from 

wetlands and include exported wetland oxygen demand.

Detailed documentation on the Chesapeake Bay Water Quality/Sediment Transport Model is at 

http://www.chesapeakebay.net/content/publications/cbp_26167.pdf.

 

12 Predictive sediment diagenesis is a predictive model of how organic material and nutrients in sediment on the Bay 

floor are processed.
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Source: Cerco, 2010 [in preparation].

Figure 5-15. The detailed 57,000 cell grid of the Chesapeake Bay Water Quality and Sediment Transport 

Model.
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5-39 September 24, 2010

5.9.1 Nonpoint Source Loads

Nonpoint source loads to the Bay Water Quality/Sediment Transport Model are from the Phase 

5.3 Bay Watershed Model. Loads are provided daily, routed to surface cells on the model grid. 

Routing is based on local watershed characteristics and on drainage area contributing to the cell 

adjacent to the land (USEPA 2010j).

5.9.2 Point Source Loads

Wastewater discharged loads to the Bay model were based on reports provided by local 

regulatory agencies which, depending on the source, were specified annually or monthly. In the 

model, loads from individual sources were summed into loads to model surface cells and were 

provided monthly (USEPA 2010j).

5.9.3 Atmospheric Loads

The EPA CBP Office computed the daily atmospheric loads for each Water Quality and 

Sediment Transport Model surface cell (USEPA 2010j). Wet deposition loads of ammonium and 

nitrate were derived from National Atmospheric Deposition Program observations. Dry 

deposition load was derived from the CMAQ. Deposition loads of organic and inorganic 

phosphorus were specified on a uniform, constant, areal basis derived from published values.

5.9.4 Bank Loads

Bank loads are the solids, carbon, and nutrient loads contributed to the water column through 

shoreline erosion. Although erosion is episodic, bank loads can be estimated only as long-term 

averages by areal surveys. The volume of eroded material is commonly quantified from 

comparison of topographic maps or aerial photos separated by time scales of years. 

Consequently, the erosion estimates are averaged over periods of years, but bank loads are input 

into the Bay Water Quality/Sediment Transport Model as episodic events as determined by a 

wave energy submodel. Bank loads were estimated for shoreline and sub-tidal erosion for much 

of the Chesapeake Bay shoreline on a scale of about every 10 kilometers of shoreline.

5.9.5 Wetlands

Wetlands loads are the sources (or sinks) of oxygen and oxygen-demanding material, such as 

carbon, that is associated with wetlands that fringe the shore of the Bay and tributaries. These 

loads are invoked primarily as an aid in calibrating tidal tributary DO concentrations. Loads to 

each cell were computed by multiplying the amount of adjacent wetlands area by the amount of 

areal carbon export or oxygen consumption. A uniform carbon (C) export of 0.3 grams (g) C per 

meters2per day (m-2 d-1) was employed, leading to a uniform oxygen (O2) demand of 2 g O2 

m-2 d-1. Segments receiving the largest carbon loads and subject to the greatest oxygen 

consumption include the mid-portion of the Bay, Tangier Sound, several Eastern Shore 

tributaries, the middle and lower James River, the tidal fresh York River, and the York River 

mouth.

5.9.6 Model Setup

Within the Bay Water Quality Model, 90 of the 92 Chesapeake Bay segments are fully 

represented within the 57,000 model cells and fully simulated. Two segments—the Western 

Branch Patuxent and the Chesapeake and Delaware Canal—were either not included in the 
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modeled Chesapeake Bay segments or not fully simulated in the Bay Water Quality/Sediment 

Transport Model. Bay TMDLs were developed for both of these tidal segments using 

information from the Phase 5.3 Bay Watershed Model, Bay Water Quality Model results from 

adjoining tidal Bay segments, and other documented sources (see Section 9).

The Western Branch Patuxent River (WBRTF) segment in Maryland (see Table 2-1 and Figure 

2-5) was not simulated in the Bay Water Quality/Sediment Transport Model because of the lack 

of quality data on the tidal river’s bathymetry (Cerco, 2010 [in preparation]). In June 2000, the 

Maryland Department of Environment published a BOD TMDL for this tidal river segment to 

address DO impairments (MDE 2000). Therefore, WBRTF is listed on Category 4a for a BOD 

TMDL on Maryland’s 2008 Integrated Report (see Table 2-1) (MDE 2008). A TMDL for 

segment WBRTF has been developed on the basis of (1) Maryland Department of Environment’s 

original BOD TMDL and loading information from the surrounding Phase 5.3 watershed model 

segments that drain directly into the Western Branch Patuxent River segment, and (2) outputs 

from the down-tide Patuxent River segments (PAXTF, PAXOH, PAXMH), which are also listed 

as impaired (see Table 2-1) (MDE 2008).

The Delaware portion of the Chesapeake and Delaware Canal (C&DOH_DE) is simulated in the 

Bay Water Quality Model as a boundary condition13 for the Delaware Bay using constant flow 

and load (Cerco, 2010 [in preparation]). The segment is listed as impaired (see Table 2-1) (DE 

DNREC 2008). A Chesapeake Bay TMDL for segment C&DOH_DE was developed using a 

combination of loading information from the surrounding Phase 5.3 Bay Watershed Model 

segments that drain directly into this Bay segment and outputs from the down-tide Chesapeake 

Bay segments (C&DOH_MD, ELKOH, and CB1TF), which also are listed as impaired (see 

Table 2-1 and Section 9) (MDE 2008).

5.10 CHESAPEAKE BAY CRITERIA ASSESSMENT PROGRAM

Output from the Bay Water Quality Model is used to modify historical water quality monitoring 

observations from the period 1991–2000 for the purposes of determining Chesapeake Bay WQS 

attainment under various pollutant load reduction scenarios (for more details on this process, see 

Section 6.2.1). To perform the necessary procedures on the large amount of data required from 

both the Bay Water Quality Model and the Chesapeake Bay Water Quality Monitoring Program 

database, a set of Fortran modules were developed. These post-processing modules read output 

from the Bay Water Quality Model (hourly values for DO; daily values for chlorophyll a), 

perform regression analyses, and apply those regressions to the appropriate historical monitoring 

data set. Additional Fortran modules then perform the same standardized, automated criteria 

assessment procedures that are used to assess more recent monitoring data for the Bay 

jurisdictions’ section 303(d) listing reports.

The source code for this suite of Fortran modules is maintained by the EPA CBP Office’s 

Modeling and Monitoring teams on behalf of the partnership, and are at 

ftp://ftp.chesapeakebay.net/Monitoring/CriteriaAssessment/.

The process by which historical monitoring data are scenario-modified using output from the 

Bay Water Quality Model is summarized in Section 6.2.1. For a detailed description of the 

 

13 Boundary conditions refer to the definition or statement of conditions or phenomena at the boundaries of a model; 

water levels, flows, and concentrations that are specified at the boundaries of the area being modeled. 
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Chesapeake Bay water quality criteria assessment procedures used for generating 303(d) listings, 

see EPA’s 2008 Ambient Water Quality Criteria for Dissolved Oxygen, Water Clarity and 

Chlorophyll a for the Chesapeake Bay and Its Tidal Tributaries–2008 Technical Support for 

Criteria Assessment Protocols Addendum (USEPA 2008a) and EPA’s 2010 Ambient Water 

Quality Criteria for Dissolved Oxygen, Water Clarity and Chlorophyll a for the Chesapeake Bay 

and Its Tidal Tributaries: 2010 Technical Support for Criteria Assessment Protocols Addendum

(USEPA 2010a).

5.11 CLIMATE CHANGE SIMULATION

The potential effects of climate change have not been explicitly accounted for in the current Bay 

TMDL allocations beyond application of a 10-year hydrologic period because of staff resource 

and time constraints and known limitations in the current suite of Bay models to fully simulate 

the effects of climate change. A preliminary assessment of climate change impacts on the 

Chesapeake Bay was conducted, in parallel, using an earlier version of the Phase 5 Bay 

Watershed Model and tools developed for EPA’s BASINS 4 system including the Climate 

Assessment Tool. Flows and associated nutrient and sediment loads were assessed in all river 

basins of the Chesapeake Bay with three key climate change scenarios reflecting the range of 

potential changes in temperature and precipitation in the year 2030. The three key scenarios 

came from a larger set of 42 climate change scenarios that were evaluated from 7 Global Climate 

Models, 2 scenarios from the Intergovernmental Panel on Climate Change Special Report on 

Emissions Scenarios storylines, and 3 assumptions about precipitation intensity in the largest 

events. The 42 climate change scenarios were run on the Phase 5 Watershed Model of the 

Monocacy River watershed, a subbasin of the Potomac in the Piedmont region, using a 2030 

estimated land use based on a sophisticated land use model containing socioeconomic estimates 

of development throughout the watershed. The results provide an indication of likely 

precipitation and flow patterns under future potential climate conditions (Linker et al. 2007, 

2008) (see Appendix E).