Multiple causes of nonstationarity in the Weihe annual low-flow series

摘要: Abstract. Under the background of global climate change and local anthropogenic activities, multiple driving forces have introduced various nonstationary components into low-flow series. This has led to a high demand on frequency analysis that considers nonstationary conditions for modeling. In this study, through framework with generalized linear model (GLM) consider time-varying distribution parameters, explanatory variables were incorporated explain the variation in distribution parameters. These are comprised three indices human activities (HAs; i.e., population, POP; irrigation area, IAR; gross domestic product, GDP) and eight measuring catchment conditions (i.e., total precipitation P , mean events λ temperature T potential evapotranspiration (EP), climate aridity index AI EP base-flow (BFI), recession constant K and recession-related aridity K) . framework was applied annual minimum flow series both Huaxian Xianyang gauging stations Weihe River, China (also known as Wei He River). The results from stepwise regression for optimal show variables related irrigation, recession, play an important role modeling. Specifically, minimum 30-day shows distribution model with any one all is better than one without variables, gamma model with four best the highest relative importance among these followed by IAR, BFI We conclude incorporation indices related generation permits tracing various forces. The established link will be beneficial analyze future occurrences extremes similar areas.