Hydrologic modelings/GIS as an aid in locating monitoring sites
With the increasing importance and awareness of non-point source pollution, critical siting of water quality monitoring stations becomes important. Within large watersheds this siting becomes difficult because of the time and expense to travel the entire watershed and evaluate the area. Previous work has shown that hydrologic models can assist in evaluating water quality in large watersheds. In this study, the hydrologic model SWAT (Soil and Water Assessment Tool) was used to simulate flows, sediment and nutrient loadings on a 9,000 km{sup 2} watershed in central Texas for the period 1970--1984. The model is a continuous, daily time step model that predicts surface runoff, percolation, lateral subsurface flow, groundwater flow, transmission losses and flood routing. The Geographic Resources Analysis Support System (GRASS) and available Natural Resources Conservation Service databases provided input into SWAT. Subwatersheds demonstrating areas of highest per acre loadings were identified from model output. Modeled output of streamflow, nitrogen, phosphorus, and sediment loadings were analyzed. For 1972--1974, the correlation coefficient between observed and simulated streamflow was 0.83, while the Nash-Sutcliffe coefficient was 0.57 indicating the model is a better predictor than using the mean. Average annual loads from the entire basin were 3.9 kg ha{sup {minus}1} NO{sub 3} and 0.03 kg ha{sup {minus}1} soluble P. Subwatersheds in the lower part of the watershed had loads which were higher than the watershed average and as a result monitoring stations have been installed. The results demonstrate that a hydrologic model and available spatial databases can be used to aid in locating sites.
- Research Organization:
- Texas Agricultural Experiment Station, Temple, TX (US)
- OSTI ID:
- 20080238
- Journal Information:
- Transactions of the ASAE, Vol. 42, Issue 6; Other Information: PBD: Nov-Dec 1999; ISSN 0001-2351
- Country of Publication:
- United States
- Language:
- English
Similar Records
Scalable deep learning for watershed model calibration
On the Use of NLDAS2 Weather Data for Hydrologic Modeling in the Upper Mississippi River Basin