Multi-scale flow regimes and driving forces analysis based on different models: a case study of the Wu river basin

Abstract

Quantitatively separating the influence of climate change and human activities on runoff is crucial to achieving sustainable water resource management in watersheds. This study presents a framework for quantitative assessment by integrating the indicators of hydrologic alteration, the whale optimization algorithm and random forest (WOA-RF), and the water erosion prediction (WEP-L) model. This framework aims to reconstruct natural runoff and quantify the differences in hydrological conditions and their driving forces at multi-timescales (annual, season, and month). The results indicate that the runoff of the Wu River has decreased since 2005, with a change degree of 46%. Climate factors were found to influence the interannual variation of runoff mainly. Meanwhile, human activities had a more significant impact in autumn, with a relative contribution rate of 59.0% (WOA-RF model) and 70.8% (WEP-L model). Monthly, the picture is more complex, with the results of the WOA-RF model indicating that climate change has a significant impact in July, August, and September (88.8, 92.7, and 79.3%, respectively). However, the WEP-L model results showed that the relative contribution of land use was significant in April, May, June, October, and November (51.24, 64.23, 63.63, 53.16, and 50.63%, respectively). The results of the study can be helpful for regional water allocation.