Options for Identifying

1
Options for Identifying Quantifying Pollutant
Loads
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Presentation Overview

• Goals of pollutant load estimation
• Options for quantifying current loads or
  conditions
• Data-driven approaches
• Models
• Modeling, as it relates to environmental systems
• Types of models
• Models typically used for load estimation
• Data needs
• Example Application of Simple Model

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Why is Pollutant Load Estimation Necessary?

• Identify relative magnitude of contributions from
  different sources
• Determine whether locations of sources are
  critical
• Evaluate timing of source loading
• Target future management efforts
• Plan restoration strategies
• Project future loads under changing conditions
• Develop a mechanism for quantifying potential
  improvement

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Pollutant Load Estimation Approaches

• Has it already been done?
• Total Maximum Daily Loads (TMDLs)
• Clean Lakes Studies
• Other local and regional studies
• If not
• Data-driven approaches
• Best when detailed monitoring data available
• Models
• Provide greater insight into impact of sources
  (temporally and spatially)
• Readily allow for evaluation of future conditions
  

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Data-driven Approaches

• Estimate source loads using
• Monitoring data
• Periodic water quality concentrations and flow
  gauging data
• Facility discharge monitoring reports
• Literature
• Loading rates, often by landuse (e.g.,
  lbs/acre/year)
• Typical facility concentrations and flow

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Is a Data-driven Approach Appropriate?

• Monitoring data
• Does it represent most conditions that occur (low
  flow, storms, etc.)?
• Are spatial and source variability
  well-represented?
• Have all parameters of interest been monitored?
• Is there a clear path to a management strategy?

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Load Estimates Monitoring Data

• In simplest terms
• load flow x concentration
• Load duration curves
• Flow-based presentation
• Statistical techniques
• Relationships between flow and concentration to
  fill in the blanks when data arent available
• Examples include
• Regression approach
• FLUX

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Load Duration Curves

• Rank daily flow and generate flow duration curve
• Multiply water quality concentrations by
  corresponding flow values
• Flow curve represents water quality target

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Regression Approach

• Develop a regression equation by plotting flow
  vs. corresponding water quality concentration
• Use the relationship to predict water quality
  concentration for days when flow data exist
• Note limited applicability to data that is
  heavily storm-driven and spans orders of
  magnitude (e.g., sediment)
• should consider log transform regression approach
• Minimum Variance Unbiased Estimator (MVUE)
  recommended by USGS for bias correction
  (http//co.water.usgs.gov/sediment/bias.frame.html
  )

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Regression Approach - Example
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FLUX

• Interactive computer program
• Developed for U.S. Army Corps of Engineers
• Maps flow-concentration relationship from
  available data onto entire flow record
• Calculates total mass, streamflow, and error
  statistics
• Can stratify data into groups based on flow
• Six available estimation algorithms

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FLUX Data Requirements

• Constituent concentrations, ideally collected
  weekly to monthly for at least a year
• Date each sample was collected
• Corresponding flow measurements (instantaneous or
  daily mean)
• Complete flow record (daily mean) for the period
  of interest

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Load Estimates Literature

• Landuse-specific loading rates (typically annual)
• Multiply loading rate by area
• loadall (arealu1 x loading ratelu1) (arealu2 x
  loading ratelu2)
• Generally for landuse or watershed-wide analysis
• Many sources Lin (2004) Beaulac and Reckhow
  (1982), etc.
• Use with caution (need correct representation for
  your local watershed)
• Pollution sources
• Climate
• Soils

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Example Load Estimation Based on Literature Values
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Limitations of Data-driven Approaches

• Monitoring data
• Reflect current/historical conditions (limited
  use for future predictions)
• Insight limited by extent of data (usually water
  quality data)
• Often not source-specific
• May reflect a small range of flow conditions
• Literature
• Not reflective of local conditions
• Wide variation among literature
• Often a static value (e.g., annual)

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If a Data-driven Approach Isnt EnoughModels are
Available
What is a Model?

• A theoretical construct,
• together with assignment of numerical values to
  model parameters,
• incorporating some prior observations drawn from
  field and laboratory data,
• and relating external inputs or forcing functions
  to system variable responses

Definition from Thomann and Mueller, 1987
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Nuts and Bolts of a Model
Input
Model Algorithms
Output
Factor 1
Rainfall Event
System
Response
Land use
Factor 2
Soil
Pollutant Buildup
Stream
Pt. Source
Factor 3
Others
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Is a Model Necessary? It depends what you
want to know
Probably Not

• What are the loads associated with individual
  sources?
• Where and when does impairment occur?
• Is a particular source or multiple sources
  generally causing the problem?
• Will management actions result in meeting water
  quality standards?
• Which combination of management actions will most
  effectively meet load targets?
• Will future conditions make impairments worse?
• How can future growth be managed to minimize
  adverse impacts?

Probably

• Models are used in many areas
• TMDLs, stormwater evaluation and design,
  permitting, hazardous waste remediation,
  dredging, coastal planning, watershed management
  and planning, air studies

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Types of Models

• Landscape models
• Runoff of water and materials on and through the
  land surface
• Receiving water models
• Flow of water through streams and into lakes and
  estuaries
• Transport, deposition, and transformation in
  receiving waters
• Watershed models
• Combination of landscape and receiving water
  models
• Site-scale models
• Detailed representation of local processes, for
  example Best Management Practices (BMPs)

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Types of Models

• Landscape/Site-scale models

• Landscape/Site-scale models

• Receiving water models

• Receiving water models

• Watershed models

• Watershed models

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Model Basis

• Empirical formulations
• mathematical relationship based on observed data
  rather than theoretical relationships
• Deterministic models
• mathematical models designed to produce system
  responses or outputs to temporal and spatial
  inputs (process-based)

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Review of Commonly Used Models

• Landscape and Watershed models
• Simple models
• Mid-range models
• Comprehensive watershed models
• Field-scale models

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Simple Models

• Loading Rate
• Simple Method
• USLE / MUSLE
• USGS Regression
• PLOAD
• STEPL

• Minimal data preparation
• Landuse, soil, slope, etc.
• Good for long averaging periods
• Annual or seasonal budgets
• No calibration
• Some testing/validation is preferable
• Comparison of relative magnitude
• Limitations
• Limited to waterbodies where loadings can be
  aggregated over longer averaging periods
• Limited to gross loadings

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Mid-range Models

• AGNPS
• GWLF
• P8
• SWAT ( receiving water)

• More detailed data preparation
• Meteorological data
• Good for seasonal/event issues
• Minimal or no calibration
• Testing and validation preferable
• Application objectives
• Storm events, daily loads
• Limitations
• Daily/monthly load summaries
• Limited pollutants simulated
• Limited in-stream simulation and comparison with
  standards

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Comprehensive Watershed Models

• HSPF/LSPC
• SWMM

• Accommodate more detailed data input
• Short time steps and finer configuration
• Complex algorithms need state/kinetic variables
• Ability to evaluate various averaging periods and
  frequencies
• Calibration is required
• Addresses a wide range of water and water quality
  problems
• Include both landscape and receiving water
  simulation
• Limitations
• More training and experience needed
• Time-consuming (need GIS help, output analysis
  tools, etc.)

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Source of Additional Information on Model
Selection

• EPA 1997, Compendium of Models for TMDL
  Development and Watershed Assessment.
  EPA841-B-97-007
• Review of loading and receiving water models
• Ecological assessment techniques and models
• Model selection

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Example of Simple Model Application

• Spreadsheet Tool for Estimating Pollutant Load
  (STEPL)
• Employs simple algorithms to calculate nutrient
  and sediment loads from different land uses
• Also includes estimates of load reductions that
  would result from the implementation of various
  BMPs
• Data driven and highly empirical
• A customized MS Excel spreadsheet model
• Simple and easy to use

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STEPL Users?

• Basic understanding of hydrology, erosion, and
  pollutant loading processes
• Knowledge (use and limitation) of environmental
  data (e.g., land use, agricultural statistics,
  and BMP efficiencies)
• Familiarity with MS Excel and Excel Formulas

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Process
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STEPL Web Site
Link to on-line Data server
Link to download setup program to install STEPL
program and documents
Temporary URL http//it.tetratech-ffx.com/stepl
until moved to EPA server
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(No Transcript)
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STEPL Main Program

• Run STEPL executable program to create and
  customize spreadsheet dynamically
• Go to demonstration

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Conclusions

• Many tools are available to quantify pollutant
  loads
• Approach depends on intended use of predictions
• Simplest approaches are data-driven
• Watershed modeling is more complex and
  time-consuming
• provides more insight into spatial and temporal
  characteristics
• useful for future predictions and evaluation of
  management options
• One size doesnt fit all!