1. http://www.washingtonpost.com/blogs/capit al-weather-gang/wp/2014/10/28/hawaii- lava-flow-advances-now-less-than-100- yards-from-nearest-home-in- pahoa/?hpid=z3http://www.washingtonpost.com/blogs/capit al-weather-gang/wp/2014/10/28/hawaii- lava-flow-advances-now-less-than-100- yards-from-nearest-home-in- pahoa/?hpid=z3

4. Modeling Water Quality

5. Special reference of this work to….

6. Water 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

7. Water quality prediction tools Expected mean concentration modeling Fate transport modeling

8. Assumptions 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

9. Limitations 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)

10. Advantages 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

11. Expected mean concentration This is a landscape based type of water quality modeling that uses established loading rates for different land cover types to predict water quality

12. Expected mean concentrations For example, an acre of row crops will produce so many tons of Nitrogen a year Or a clear cut barren land acre of land will produce so many tons per year of total suspended solids

13. Expected mean concentrations Problem is that many of the loading rates were done for areas outside of our state 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

14. Expected mean concentrations Annual average cumulative runoff loads of the pollutant in kg/year.

16. EMC 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.

17. Expected 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

19. Env Settings

20. Steps Perform a crosswalk between the NLCD land cover and the six EMC fields EMC Classes: Urban/Developed Open/Brush Agriculture Woodland/forest Barren Wetlands

21. Crosswalk

22. Reclassify

23. Using a remap table in Reclassify

26. EMC values for TSS Annual average cumulative runoff loads of the pollutant in kg/year.

27. TSS

30. Estimating 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….

31. Estimating 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-m 3 )so that L is determined in kg/year

32. Cell based loading grid

33. Cell based loading grid result

34. Cumulative load Part APart B

36. Cumulative load result for TSS

37. Pollutant concentrations First add the cumu_runoff2 grid from the runoff lecture earlier to ArcMap, then….

38. Pollutant concentrations

39. TSS concentrations in mg/L

40. Relating it to thresholds

41. Standards

42. Fate transport modeling Just a fancy way to refer to a mass balance raster model 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

43. Steps Add a water quality dataset to your view display a good sample dataset is the wqsamples83.shp

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

45. Results Based on the water quality parameter chosen, streams are modeled for concentration and loading