SWAT Literature Database for Peer-Reviewed Journal Articles

Title:Enumerating the effects of climate change on water resources using GCM scenarios at the Xin'anjiang Watershed, China 
Authors:Zaman, M., M.N. Anjum, M. Usman, I. Ahmad, M. Saifullah, S. Yuan and S. Liu 
Year:2018 
Journal:Water 
Volume (Issue):10(10) 
Pages: 
Article ID:1296 
DOI:10.3390/w10101296 
URL (non-DOI journals): 
Model:SWAT 
Broad Application Category:hydrologic only 
Primary Application Category:climate change assessment 
Secondary Application Category:hydropower assessment 
Watershed Description:11,675.710 km^2 Xin'jiang river, located in southeast China. 
Calibration Summary: 
Validation Summary: 
General Comments: 
Abstract:The present study developed a novel approach to study the climate change impact on the water resources and generation of hydropower optimally using forecasted stream flows for the Xin’anjiang water shed in China. Future flows were projected using six large-scale Global circulation models (GCMs) with RCP4.5 and RCP8.5 scenarios. A newly developed mathematical modeling using particle swarm optimization was incorporated to work out the projected optimal electricity generation from the Xin’anjiang hydropower station. The results reveal that watershed will be warmer by the end of the 21st century with a maximum increase of up to 4.9 C for mean maximum, and 4.8 C for mean minimum temperature. Six GCMs under Representative Concentration pathways (RCPs) showed that future precipitation is complex to predict with certainty and significant differences were observed among the different GCMs. The overall mean monthly and seasonal precipitation increase for most scenarios with the maximum increase during the 2020s and 2080s, whereas 2050s exhibited the lesser increase. Resultantly, there would be an increase in the stream flows during these periods, which was used for electricity production up to 31.41 X 108 kWh. 
Language:English 
Keywords:water resources; climate change; particle swarm optimization; SWAT; CMIP5; optimal electricity generation; Xin’anjiang watershed