Development of the Spatial Rainfall Generator (SRGEN) for the Agricultural Policy/Environmental Extender Model1. (3rd September 2014)

• Record Type: Journal Article
• Authors: Jeong, Jaehak; Williams, Jimmy R.; Rossi, Colleen G.; Taylor, Robin A.; Wang, Xiuying; Fox, William E.
• Is Part Of: Journal of the American Water Resources Association. Volume 51:Number 1(2015:Feb.)
• Page Start: 154
• Page End: 167
• Publication Date: 2014-09-03
• Subjects: Water-supply -- Periodicals; Hydrology -- Periodicals; Water resources development -- Periodicals; Water resources development -- Environmental aspects -- Periodicals; 333.9100973
• DOI: 10.1111/jawr.12239
• Languages: English
• ISSNs: 1093-474X

Abstract

<abstract abstract-type="main" id="jawr12239-abs-0001"> <title>Abstract</title> <p>Accurate spatial representation of climatic patterns is often a challenge in modeling biophysical processes at the watershed scale, especially where the representation of a spatial gradient in rainfall is not sufficiently captured by the number of weather stations. The spatial rainfall generator (SRGEN) is developed as an extension of the "weather generator" (WXGEN), a component of the Agricultural Policy/Environmental eXtender (APEX) model. SRGEN generates spatially distributed daily rainfall using monthly weather statistics available at multiple locations in a watershed. The spatial rainfall generator as incorporated in APEX is tested on the Cowhouse watershed (1, 178 km<sup>2</sup>) in central Texas. The watershed presented a significant spatial rainfall gradient of 2.9 mm/km in the lateral (north‐south) directions based on four rainfall gages. A comparative analysis between SRGEN and WXGEN indicates that SRGEN performs well (PBIAS = 2.40%). Good results were obtained from APEX for streamflow (NSE = 0.99, PBIAS = 8.34%) and NO<sub>3</sub>‐N and soluble P loads (PBIAS ≈ 6.00% for each, respectively). However, APEX underpredicted sediment yield and organic N and P loads (PBIAS: 24.75‐27.90%) with SRGEN, although its uncertainty in output was lower than WXGEN results (PBIAS: −13.02 to −46.13%). The overall improvement achieved in rainfall generation by SRGEN is demonstrated to be effective in the improving model performance on flow and water quality output.</p> </abstract>