SWAT Literature Database for Peer-Reviewed Journal Articles

Title:Effects of different spatial and temporal weather data resolutions on the streamflow modeling of a semi-arid basin, Northeast Brazil 
Authors:Bressiani, D. de A., R. Srinivasan, C.A. Jones and E.M. Mendiondo 
Journal:International Journal of Agricultural and Biological Engineering 
Volume (Issue):8(3) 
Article ID: 
URL (non-DOI journals): 
Broad Application Category:hydrologic only 
Primary Application Category:climate data effects 
Secondary Application Category:weather generator effects/processes 
Watershed Description:73,000 km^2 Jaguaribe River, located in the state of Ceará in northeast Brazil. 
Calibration Summary: 
Validation Summary: 
General Comments:This article is part of a set of 11 articles that comprise a SWAT special issue published in IJABE volume 8(3) in June, 2015. 
Abstract:One major difficulty in the application of distributed hydrological models is the availability of data with sufficient quantity and quality to perform an adequate evaluation of a watershed and to capture its dynamics. The Soil & Water Assessment Tool (SWAT) was used in this study to analyze the hydrologic responses to different sources, spatial scales, and temporal resolutions of weather inputs for the semi-arid Jaguaribe watershed (73,000 km2) in northeastern Brazil. Four different simulations were conducted, based on four groups of weather and precipitation inputs:Group 1- SWAT Weather Generator based on monthly data from four airport weather stations and daily data based on 124 local rain gauges; Group 2- daily local data from 14 weather stations and 124 precipitation gauges; Group 3- Daily values from a global coupled forecast model (NOAA’s Climate Forecast System Reanalysis - CFSR); and Group 4- CFSR data with 124 local precipitation gauges. The four simulations were evaluated using multiple statistical efficiency metrics for four streamflow gauges, using: Nash-Sutcliffe coefficient (NSE), determination coefficient (R2), the ratio of the root mean square to the standard deviation of the observed data (RSR), and the percent bias (PBIAS). The Group 4 simulation performed best overall (provided the best statistical values) with results ranked as “good” or “very good” on all four efficiency metrics suggesting that using CFSR data for weather parameters other than precipitation, coupled with precipitation data from local rain gauges, can provide reasonable hydrologic responses. The second best results were obtained with Group 1, which provided “good” results in three of four efficiency metrics. Group 2 performed worse overall than Groups 1 and 4, probably due to uncertainty related to daily measures and a large percentage of missing data. Groups 2 and 3 were “unsatisfactory” according to three or four of the efficiency metrics, indicating that the choice of weather data is very important. 
Keywords:climate data resolution, hydrology, SWAT model, Brazil, semi-arid