期刊
ECOLOGICAL INDICATORS
卷 113, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.ecolind.2020.106251
关键词
Climate change; Hydrology; Land use and land cover; SWAT; Human-environment systems
资金
- NSF Idaho EPSCoR Program
- National Science Foundation [OIA-1757324]
Previous studies have identified the importance of simulating and quantifying the relationship between hydrologic variation and climate change under historical scenarios at regional and continental scales. However, robust demonstration of the potential of combining consistent land use/cover change (LUCC) and climate change to simulate future hydrologic processes is still lacking. Furthermore, investigating the future connections between hydrologic characteristics and climate variables demands exploration of these phenomena at small (basin) scale. To fill this gap, this research simulates land use/cover patterns in 2030 based on the logistic Cellular Automata-Markov model. Then the Soil Water Assessment Tool (SWAT) simulates change in streamflow within the Ashuelot River basin in New England between 2002-2009 and 2032-2039. Projected climate data are obtained from two general circulation models (GCMs) under Representative Concentration Pathways (RCPs) 4.5 and 8.5. We also quantify relationships between the rates of change (RC) of streamflow, precipitation and potential evapotranspiration (PET) among 29 subbasins at a monthly scale between the two time periods under different climate scenarios by implementing a panel data approach. Results show greatest changes in forestland (-21.07 km(2)) and intensive urban land (+5.4 km(2)) by 2030. Comparisons between the two periods show a negative overall trend in runoff under RCPs 4.5 and 8.5 for both selected GCMs. Panel data analysis indicates that precipitation may contribute more to the RC of streamflow when change in streamflow is significantly influenced by both PET and precipitation over the study period. Therefore, this study provides an important insight into quantifying and comparing the relationship of basin-scale change between streamflow and future climate.
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