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Application of a Watershed Model (HSPF) for Evaluating Sources and Transport of (en Inglés)
Lorraine E. Flint
(Autor)
·
Clinton D. Church
(Autor)
·
Gregory O. Mendez
(Autor)
·
Createspace Independent Publishing Platform
· Tapa Blanda
Application of a Watershed Model (HSPF) for Evaluating Sources and Transport of (en Inglés) - Flint, Lorraine E. ; Church, Clinton D. ; Mendez, Gregory O.
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Ahorras: S/ 103,29
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Reseña del libro "Application of a Watershed Model (HSPF) for Evaluating Sources and Transport of (en Inglés)"
A watershed model using Hydrologic Simulation Pro- gram-FORTRAN (HSPF) was developed for the urbanized Chino Basin in southern California to simulate the transport of pathogen indicator bacteria, evaluate the flow-component and land-use contributions to bacteria contamination and water-quality degradation throughout the basin, and develop a better understanding of the potential effects of climate and land-use change on water quality. The calibration of the model for indicator bacteria was supported by historical data col- lected before this study and by samples collected by the U.S. Geological Survey from targeted land-use areas during storms in water-year 2004. The model was successfully calibrated for streamflow at 5 gage locations representing the Chino Creek and Mill Creek drainages. Although representing pathogens as dissolved constituents limits the model's ability to simulate the transport of pathogen indicator bacteria, the bacteria concen- trations measured over the period 1998-2004 were well rep- resented by the simulated concentrations for most locations. Hourly concentrations were more difficult to predict because of high variability in measured bacteria concentrations. In gen- eral, model simulations indicated that the residential and com- mercial land uses were the dominant sources for most of the pathogen indicator bacteria during low streamflows. However, simulations indicated that land used for intensive livestock (dairies and feedlots) and mixed agriculture contributed the most bacteria during storms.
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