Movement ofHypophthalmichthysDNA in the Illinois River Watershed by the Double-Crested Cormorant (Phalacrocorax auritus)

Waterbirds ◽  
2017 ◽  
Vol 40 (1) ◽  
pp. 63-68 ◽  
Author(s):  
Michael P. Guilfoyle ◽  
Heather L. Farrington ◽  
Richard F. Lance ◽  
Katie C. Hanson-Dorr ◽  
Brian S. Dorr ◽  
...  
Keyword(s):  
Illinois River ◽  
Phalacrocorax Auritus ◽  
River Watershed

scholarly journals Phosphorus Mass Balance of the Illinois River Watershed in Arkansas and Oklahoma

2013 ◽  
Vol 05 (06) ◽  
pp. 591-603 ◽  
Author(s):  
Bernard Engel ◽  
Meagan Smith ◽  
John Berton Fisher ◽  
Roger Olsen ◽  
Laurent Ahiablame
Keyword(s):  
Mass Balance ◽  
Illinois River ◽  
River Watershed ◽  
Phosphorus Mass Balance

scholarly journals Enhanced streamflow prediction with SWAT using support vector regression for spatial calibration: A case study in the Illinois River watershed, U.S.

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0248489
Author(s):  
Lifeng Yuan ◽  
Kenneth J. Forshay
Keyword(s):  
Support Vector Regression ◽  
Assessment Tool ◽  
Swat Model ◽  
Illinois River ◽  
Support Vector ◽  
Streamflow Prediction ◽  
River Watershed ◽  
Monthly Streamflow ◽  
Non Linear ◽  
Spatial Calibration

Accurate streamflow prediction plays a pivotal role in hydraulic project design, nonpoint source pollution estimation, and water resources planning and management. However, the highly non-linear relationship between rainfall and runoff makes prediction difficult with desirable accuracy. To improve the accuracy of monthly streamflow prediction, a seasonal Support Vector Regression (SVR) model coupled to the Soil and Water Assessment Tool (SWAT) model was developed for 13 subwatersheds in the Illinois River watershed (IRW), U.S. Terrain, precipitation, soil, land use and land cover, and monthly streamflow data were used to build the SWAT model. SWAT Streamflow output and the upstream drainage area were used as two input variables into SVR to build the hybrid SWAT-SVR model. The Calibration Uncertainty Procedure (SWAT-CUP) and Sequential Uncertainty Fitting-2 (SUFI-2) algorithms were applied to compare the model performance against SWAT-SVR. The spatial calibration and leave-one-out sampling methods were used to calibrate and validate the hybrid SWAT-SVR model. The results showed that the SWAT-SVR model had less deviation and better performance than SWAT-CUP simulations. SWAT-SVR predicted streamflow more accurately during the wet season than the dry season. The model worked well when it was applied to simulate medium flows with discharge between 5 m3 s-1 and 30 m3 s-1, and its applicable spatial scale fell between 500 to 3000 km2. The overall performance of the model on yearly time series is “Satisfactory”. This new SWAT-SVR model has not only the ability to capture intrinsic non-linear behaviors between rainfall and runoff while considering the mechanism of runoff generation but also can serve as a reliable regional tool for an ungauged or limited data watershed that has similar hydrologic characteristics with the IRW.

Sign in / Sign up

Export Citation Format

Share Document