A dynamic von Mises-based model to evaluate the impact of urbanization and climate change on flood timing in Yangtze and Huaihe River Basins, China

Abstract

The combined effect of global warming and urbanization have an impact on the occurrences of floods in the Yangtze River Basin (YRB) and Huaihe River Basin (HRB), causing potential risks to the safe operation of watersheds. Therefore, this study proposed a dynamic von Mises-based (DvM) framework for detecting the impact of urbanization and climate change on flood timing (FT) across HRB and YRB from the nonstationary frequency included: (1) visualization of empirical probability of FT series to ascertain the number of mixed von Mises distributions; (2) selection of the multi-covariate-based model in consideration of the combined effect of multiple physical covariates, following the phase-wise strategy which involves the likelihood ratio test, Kolmogorov-Smirnov goodness-of-fit test, and the Akaike information criterion; (3) development of the linear regression-based comparative approach to isolate and distinguish the delaying and advancing effects of various factors (mainly climate change and urbanization-induced impact) on FT. In terms of the urbanization-induced impact on peak flow timing, HRB suffered an advanced effect by 4% and YRB suffered an advanced effect by 2%, which can be attributed to the divergence of the urbanization development level quantified by the impervious surfaces of sub-basins controlled by the stations in these two basins. In contrast to the modest advancement caused by urbanization (4% for HRB and 2% for YRB) in influencing the timing of flood peaks in the two basins, climate change factors, specifically the timing of soil moisture (TSM) and maximum rainfall (TPRE), play a more significant role in contributing to a delayed trend observed at a total of seven stations in the Huaihe River Basin and Yangtze River Basin. The main driver behind the trend towards delayed flood timing in both the Huaihe River Basin (HRB) and the Yangtze River Basin (YRB) is predominantly influenced by the timing of soil moisture. According to TSM, this factor contributes 16% in HRB and 10% in YRB. In contrast, the timing of rainfall has a lesser impact, accounting for 13% in HRB and 8% in YRB according to TPRE.