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A Watershed Analysis & Treatment Evaluation Routine Spreadsheet WATERS)
Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.orgCitation: Pp. 490-495 in Total Maximum Daily Load (TMDL) Environmental Regulations: Proceedings of the March 11-13, 2002 Conference, (Fort Worth, Texas, USA) 701P0102.(doi:10.13031/2013.7601)
Authors: D.M. Amatya, G.M. Chescheir, R.W. Skaggs, G.P. Fernandez and J.W. Gilliam
Keywords: Watershed Model, Export Coefficient, Delivery Ratio, GIS, @RISK, TMDL
Procedures for development of a Watershed Analysis and Treatment Evaluation Routine Spreadsheet (WATERS) are presented as a potential tool for TMDL allocation. The spreadsheet watershed model, applied on a subwatershed basis to characterize spatial inputs, is divided into four worksheets: hydrology, subwatershed load, transport, and watershed load. The annual flows are calculated using available methods in the hydrology worksheet. Various options of calculating subwatershed load using literature and measured data, regressions, and modeling are used in the second worksheet. The third worksheet calculates the pollutant delivery ratios (DR) using the first order kinetics of pollutant decay as a function of travel time and decay rate. Both of these parameters are based on litera-ture. Pollutant delivered at the watershed outlet is calculated as a product of DR and subwatershed load. Annual watershed load, calculated as the sum of all subwatershed loads, may have uncertainty associated with various input parameters. Uncertain model parameters then can be input as a probabilistic distribution in WATERS when embedded in @RISK decision analysis tool (Palisade Corporation), which can run several Monte Carlo simulations using these input distributions. The output of watershed pollutant load can then be described using a probability distribution that can be used further for confidence limits on load estimates, exceedence loads or standard violations in TMDL analysis. The spreadsheet model in @RISK is also capable of conducting sensitivity analyses of input parameters and what-if scenarios for management decis ions. The model, which is flexible and easy to apply, uses an adaptive approach to alter equations as more accurate method becomes available. The spreadsheet model, with a potential for linking with GIS tools, is being tested on the coastal plain watersheds in eastern North Carolina.(Download PDF) (Export to EndNotes)