SWAT Literature Database for Peer-Reviewed Journal Articles

Title:Integrating landscape metrics and hydrologic modeling to assess the impact of natural disturbances on ecohydrological processes in the Chenyulan Watershed, Taiwan 
Authors:Chiang, L.-C., Y.-T. Chuang and C.-C. Han 
Year:2019 
Journal:International Journal of Environmental Research and Public Health 
Volume (Issue):16(2) 
Pages: 
Article ID:266 
DOI:10.3390/ijerph16020266 
URL (non-DOI journals): 
Model:SWAT 
Broad Application Category:hydrologic & pollutant 
Primary Application Category:land use change 
Secondary Application Category:sediment loss and transport 
Watershed Description:449 km^2 Chenyulan River, which is located in Nantou County in central Taiwan. 
Calibration Summary: 
Validation Summary: 
General Comments: 
Abstract:The Chenyulan watershed, located in the central mountain area of Taiwan, has been suffering from earthquakes, typhoons, and heavy rainfalls in recent decades. These sequential natural disturbances have a cumulative impact on the watershed, leading to more fragile and fragmented land cover and loss of capacity of soil water conservation. In this study, the Soil and Water Assessment Tool (SWAT) and a landscape metrics tool (FRAGSTATS) were used to assess the direct impact (e.g., by annual rainfall) and indirect impact (e.g., by landscape configuration and composition) of natural disturbances on the ecohydrological processes of the Chenyulan watershed. Six SPOT satellite images from 2008 to 2013 were analyzed by using the nearest feature line embedding (NFLE) approach and reclassified into six land cover types: forest, cultivated land, grassland, river, landslide, and built-up. Forest was found to have the largest patch size, indicating that it is more resilient to disturbances, while agricultural land tended to expand from the river side toward the hill. Two land cover change scenarios were compared in the SWAT model. The results showed that there was no significant difference in simulated streamflow during 2004–2015 and sediment loading during 2004–2009; however, the model performed better for sediment loading during 2010–2015 with dynamic land cover change (coefficient of determination (R2) = 0.66, Nash-Sutcliffe efficiency coefficient (NSE) = 0.62, percent bias (PBIAS) = 10.5%, root mean square error observation standard deviation ratio (RSR) = 0.62) than with constant land cover (R2 = 0.61, NSE = 0.54, PBIAS = −17.3%, RSR = 0.68), indicating that long-term land cover change should be considered in hydrologic modeling. Changes in landslides during 2008–2013 were found to significantly affect ecohydrological processes, especially after 2011. In general, annual precipitation plays a dominant role, and landscape composition had by far the strongest influence on water yield and sediment yield compared to landscape configuration. The results can be useful for understanding the effects of land cover change on ecohydrological processes in the Chenyulan watershed and the potential impact of ecohydrological changes on the environment and public health. 
Language:English 
Keywords:image classification, land cover change, landscape metrics, SWAT, watershed management