Investigating Effects of Climate Seasonality, Catchment Characteristics and Socio-economic Factors on the Budyko Curve Parameter w at Different Spatiotemporal Scales

One parameter model, Budyko-type equations have begun to be widely adopted to quantify long-term average water balance in catchment scale and, also to separate the contributions of climate change and human activities to the variation of runoff. Acknowledging that climate seasonality, landscape characteristics and socio-economic factors may multi-dimensionally affect the model parameter w. In this paper, a multivariate adaptive regression spline (MARS) model is proposed to determine statistically significant factors among the complicated factors and to identify their interactions on the model parameter w at the spatial scale. In order to investigate the impacts of climate change and human activities on the model parameter w at the temporal scale, the relationship of the parameter w in Budyko-type equation with climatic and human factors is firstly built to reveal the time-variation process of w by using an 11-year moving window, then the impacts of climate change and human activities on runoff are separated by using the sensitivity method. Quantifying the impact of climate and land use/cover change on water yield is important for catchment management planning and decision making.