Modeling Water QualityModeling Water QualityModeling Water QualityModeling Water Quality

Special reference of this work to….Special reference of this work to….

Water quality prediction toolsWater quality prediction tools

• As the name states, these are prediction tools

• They tend to state the worst possible case for water quality

• Many assumptions are built into their use

Water quality prediction toolsWater quality prediction tools

• Expected mean concentration modeling

• Fate transport modeling

AssumptionsAssumptions• Streams have uniform width, depth, roughness• Same ecological rate constants (reareation

rates, pollution decay rates and sediment oxygen demand rate)

• Transport of pollutants is considered to be conservative (values get averaged over changing flow conditions only) -> no loss or decay of pollutants is considered

LimitationsLimitations• Does not consider infiltration, interflow, or

ground water flow additions• Does not include atmospheric conditions such

as temperature or evapotranspiration• Uses mean annual runoff and flow measures

with one time water quality sampling data (must match sampling to normal flow conditions or calibrate flow to time of sampling)

AdvantagesAdvantages

• Includes surface runoff from point and non-point sources

• It is a landscape (watershed) model as compared to a receiving water model

• Easy to analyze visual output and query capability from results

• A deterministic simulation model type

Expected mean concentrationExpected mean concentration

• This is a landscape based water quality modeling approach as compared to an instream water quality modeling approach

Expected mean concentrationsExpected mean concentrations

• Difficult to find and have EMC studies done in study area

• Soils, temperature, rainfall, etc are all different

• It is best used as a proxy of possible conditions to compare one area vs another based on land cover distribution

EPA PLOAD program EMC valuesEPA PLOAD program EMC values

Values in mg/L

USGS Report for MichiganUSGS Report for Michigan

EMC loading values referencesEMC loading values references

Adamus, C. L. and M. J. Bergman, 1995. Estimating Nonpoint Source Pollution Loads with a GIS Screening Model. Water Resources Bulletin, American Water Resources Association 12(4):647-655.

Donigan, A. S., B. R. Bicknell, and L. C. Linker, 1995. Regional Assessment of Nutrient Loadings from Agriculture and Resulting Water Quality in the Chesapeake Bay Area. Proceedings of the International Symposium on Water Quality Modeling, American Society of Agricultural Engineers, Orlando, FL.

Evans, B. M., R. A. White, G. W. Petersen, J. M. Hamlett, G. M. Baumer, A. J. McDonnell, 1994. Land Use and Nonpoint Pollution Study of the Delaware River Basin. Prepared for the Delaware River Basin Commission, Report Number ER9406, Environmental Resources Research Institute, The Pennsylvania State University, University Park, PA.

Haith, D. A. and L. L. Shoemaker, 1987. Generalized Watershed Loading Functions for Stream Flow Nutrients. Water Resources Bulletin 23(3):471- 478.

Nizeyimana, E, B. M. Evans, M. C. Anderson, G. W. Peterson, D. R. DeWalle, W. E. Sharpe, J. M. Hamlett, B. R. Swistock, 1997. Quantification of NPS Pollution Loads Within Pennsylvania Watersheds. Prepared for Pennsylvania Department of Environmental Protection Bureau of Water Quality Protection, Report Number ER9708,Environmental Resources Research Institute, The Pennsylvania State University, University Park, PA.

Olivera, F., R. J. Chareneau and D. R. Maidment, 1996. Spatially Distributed Modeling of Storm Runoff and Non-Point Source Pollution Using GIS. Report 96-4, Center for Watershed Research, University of Texas, Austin, TX.

Expected mean concentrationsExpected mean concentrations

• The previous table can be used with different land cover as input but all cover types must be aggregated to fit into one of the six types to be assigned a loading rate

Env SettingsEnv Settings

StepsSteps

Assign the EMC values in mg/L to cover types

Reclassify Reclassify

Using a remap table in ReclassifyUsing a remap table in Reclassify

EMC values to the land cover classesEMC values to the land cover classes

Estimating Annual Loadings Throughout WatershedEstimating Annual Loadings Throughout Watershed

• The pollutant mass contribution that each cell makes to downstream pollutant loading is calculated by taking the product of the expected mean concentration and runoff associated with the cell or

Load (mass/time) = EMC (mass/volume) * Q (volume/time)

Which becomes….

Estimating Annual Loadings Throughout WatershedEstimating Annual Loadings Throughout Watershed

L = K * Q * EMC * A

Q is units in mm/year

EMC is in mg/Liter

A is area of one grid cell

K is constant to make units consistent

(ie K = 10-6 kg-m-L/mg-mm-m3 ) so that

L is determined in kg/year

LoadingsLoadings

Cell based loading gridCell based loading grid

Cell based loading grid resultCell based loading grid result

Cumulative loadCumulative loadPart A Part B

Cumulative load result for TSSCumulative load result for TSS

Pollutant concentrationsPollutant concentrationsFirst add the cumu_runoff2 grid from the runoff lecture earlier to ArcMap, then….

TSS concentrations in mg/LTSS concentrations in mg/L

Relating it to thresholdsRelating it to thresholds

StandardsStandards

Fate transport modelingFate transport modeling

• This is different from the EMC approach in that the user can input their water quality data

• It uses sampled water quality as inputs to determine downstream effects

StepsSteps

Add a water quality dataset to your view display

NoteNote

• The water quality dataset must have concentration values in Mg/L for average flow conditions

ResultsResults

• Based on the water quality parameter chosen, streams can be modeled for concentration and loading