Simulation of Landscape Ecological Risk Change in Hanjiang River Basin under SSP-RCP Scenarios
Landscape ecological risk assessment plays a vital role in identifying vulnerable ecosystem areas for targe-ted management.While current methods primarily rely on land-use change data for ecological risk analysis,they of-ten lack a comprehensive evaluation of multiple factors,especially the prediction of landscape ecological risk dy-namics under climate change scenarios integrating climate variations and socio-economic trends.To tackle this is-sue,we constructed a predictive model for ecological landscape risk influenced by diverse factors by integrating tra-ditional landscape ecological risk assessment models with deep learning technique,and further applied this model to simulating the change in landscape ecological risks of Hanjiang River Basin.Findings reveal that:1)during the baseline period(2000-2015),higher ecological risk levels predominantly clustered in the downstream of Dan-jiangkou reservoir;2)both SSP370 and SSP585 scenarios exhibited elevated ecological risk levels,particularly concentrated in the downstream of Danjiangkou;3)the high ecological risk area in Hanjiang River basin signifi-cantly expanded under the 2042 scenario for SSP370 and SSP585,with an average increase of 14.58%per decade under the SSP370 scenario.The proposed landscape ecological risk prediction approach in consideration of multiple factors serves as a valuable reference for ecological risk assessment in the basin under changing climatic conditions and the formulation of ecological compensation policies.
climate changelandscape ecological riskdeep learningSSP-RCPHanjiang River Basin