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EVALUATION OF RUNOFF, EROSION, AND PHOSPHORUS MODELING SYSTEM—SIMPLE 1
Author(s) -
Kornecki Ted S.,
Sabbagh George J.,
Storm Daniel E.
Publication year - 1999
Publication title -
jawra journal of the american water resources association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.957
H-Index - 105
eISSN - 1752-1688
pISSN - 1093-474X
DOI - 10.1111/j.1752-1688.1999.tb04176.x
Subject(s) - surface runoff , watershed , environmental science , phosphorus , erosion , hydrology (agriculture) , sediment , volume (thermodynamics) , soil science , geology , geotechnical engineering , chemistry , ecology , geomorphology , physics , organic chemistry , quantum mechanics , machine learning , computer science , biology
The purpose of this study was to evaluate the performance of Spatially Integrated Models for Phosphorus Loading and Erosion (SIMPLE) in predicting runoff volume, sediment loss, and phosphorus loading from two watersheds. The modeling system was applied to the 334 ha QOD subwatershed, part of the Owl Run watershed, located in Fauquier County, Virginia, and to the 2240 ha watershed, Battle Branch, located in Delaware County, Oklahoma. Simulation runs were conducted at cell and field scales, and simulation results were compared with observed data. Runoff volume and dissolved phosphorus loading were measured at the Battle Branch watershed. Runoff volume, sediment yield, and total phosphorus loading were measured at the QOD site. SIMPLE tended to underestimate runoff volumes during the dormant period, from November to March. The comparison between observed and predicted dissolved phosphorus showed better correlation than for observed and predicted total phosphorus loading. Cell level simulations provided similar estimates of runoff volume and phosphorus loading when compared to field level simulations for both watersheds. However, observed sediment yields better compared with the values predicted from the cell level simulation when compared to field level simulation. Finally, results of model evaluation indicated that SIMPLE's predictive ability is acceptable for screening applications but not for site‐specific quantitative predictions.