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ARS Home » Southeast Area » Oxford, Mississippi » National Sedimentation Laboratory » Watershed Physical Processes Research » Research » Publications at this Location » Publication #254511
Title: Comparisons of Historical versus Synthetic Weather Inputs to Watershed Models and their Effect on Pollutant Loads

Author
item THEURER, F - Natural Resources Conservation Service (NRCS, USDA)
item MOORE, D - Natural Resources Conservation Service (NRCS, USDA)
item MERKEL, W - Natural Resources Conservation Service (NRCS, USDA)
item QUAN, Q - Natural Resources Conservation Service (NRCS, USDA)
item MOODY, H - Natural Resources Conservation Service (NRCS, USDA)
item Bingner, Ronald - Ron
item Bonta, James - Jim
item Flanagan, Dennis

Submitted to: Federal Interagency Sedimentation Conference Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 6/24/2010
Publication Date: 6/27/2010
Citation: Theurer, F.D., Moore, D.S., Merkel, W.H., Quan, Q.D., Moody, H.F., Bingner, R.L., Bonta, J.V., Flanagan, D.C. 2010. Comparisons of Historical versus Synthetic Weather Inputs to Watershed Models and their Effect on Pollutant Loads. In: Proceedings of the Federal Interagency Sedimentation Conference, June 27-July 1, 2010, Las Vegas, Nevada. 2010 CDROM.

Interpretive Summary: Synthetic weather generators are important for continuous-simulation of agricultural watersheds for risk analyses of downstream water quality. Many watersheds are sparsely or totally ungauged and daily weather must either be transposed or augmented. Since water quality models must recognize runoff, erosion, sediment transport, and pollutant loads, augmented precipitation statistics must reflect the precipitation patterns as well as the average annual precipitation of the indigenous parent’s historical climate. This paper addresses how well synthetic weather generators reproduce their original historical weather’s precipitation amounts and patterns that are to be used for subsequent simulation of watershed runoff, erosion, streamflow and pollutant loads. Synthetically generated climate can create time series of daily weather that are long enough to conduct risk analyses; i.e., frequency and probability analyses of the resulting streamflow and pollutant loads. Historical records frequently are serially incomplete and generally too short, or simply may not be available, for such purposes. Improvement in climate generation technology is needed to address the interaction of weather patterns over large watershed areas for effective evaluation of conservation practices.

Technical Abstract: Synthetic weather generators are important for continuous-simulation of agricultural watersheds for risk analyses of downstream water quality. Many watersheds are sparsely or totally ungauged and daily weather must either be transposed or augmented. Since water quality models must recognize runoff, erosion, sediment transport, and pollutant loads, augmented precipitation statistics must reflect the precipitation patterns as well as the average annual precipitation of the indigenous parent’s historical climate. This paper addresses how well synthetic weather generators reproduce their parent’s historical weather’s precipitation amounts and patterns which are to be used for subsequent simulation of watershed runoff, erosion, streamflow and pollutant loads. Synthetically generated climate can create time series of daily weather that are long enough to conduct risk analyses; i.e., frequency and probability analyses of the resulting streamflow and pollutant loads. Historical records frequently are serially incomplete and generally too short, or simply may not be available, for such purposes.