Utilizing Entropy-Based Method for Rainfall Network Design in Huaihe River Basin, China

The nonstationary characteristics caused by significant variation in hydrometeorological series the context of climate change inevitably have a certain impact on selection an optimal gauging network. This study proposes entropy-based, multi-objective, rain gauge network optimization method to facilitate design 43 stations-based Huaihe River Basin (HRB), China. first goal this is improve accuracy gauge-related information estimation through and comparison discretization methods. second quantify trend-caused nonstationarity using sliding window method. compares divergence three kinds methods, including floor function-based approach, Scott’s equal bin width histogram (EWH-Sc) Sturges’s (EWH-St) approach. matching degree variance marginal entropy observed computed select most suitable above 75% all stations HRB could definitely influence final results rain-gauge Therefore, future studies optimization, it necessary carry out uncertainty research according local conditions view human activities.