Abstract
Two widely used approaches, nonparametric approach and Budyko framework approach, were used to calculate precipitation elasticity of streamflow (ε) in China’s main river basins. While the Budyko framework illustrates only the effect of climate onε, the nonparametric approach illustrates the effects of both climate and human activity onε. Both approaches showed similar spatial pattern ofε, with high values for northern arid catchments and low values for southern humid catchments, suggesting high sensitivity of streamflow to climate in the arid catchments in China’s north. Inland catchments had lowεvalues, probably because most of the annual streamflow was driven by glacial and snowmelt. While strong anthropologic activities reduce the sensitivity of streamflow to precipitation in some northern arid catchments, which was indicated by lowerεvalues produced by nonparametric approach, the combined use of the two approaches underscored the significance in identifying the effects of anthropologic factors on streamflow.
Highlights
As precipitation is a major factor of streamflow, it is important that water resources scientists and managers understand the sensitivity of streamflow to precipitation
Several studies suggest that ε is highly related to catchment climate attributes, denoted as aridity index (AI), which is the ratio of mean annual potential evapotranspiration (PET) to precipitation
Zheng et al [6] observed a positive correlation between ε and AI in a long term (1960–2000) of the headwater regions of Yellow River basin
Summary
As precipitation is a major factor of streamflow, it is important that water resources scientists and managers understand the sensitivity of streamflow to precipitation. Most studies involving streamflow sensitivity are based on conceptual catchment modeling by varying atmospheric inputs to estimate changes in streamflow [1, 2]. Sankarasubramanian et al [2] developed a nonparametric model for estimating precipitation elasticity of streamflow (ε), which is the proportional change in streamflow resulting from changes in precipitation. While ε = 2.0 indicates that 1% change in precipitation results in 2% change in streamflow, higher ε suggests higher streamflow sensitivity to precipitation. Several studies suggest that ε is highly related to catchment climate attributes, denoted as aridity index (AI), which is the ratio of mean annual potential evapotranspiration (PET) to precipitation. Sankarasubramanian and Vogel [7] noted that watershed aridity index together with watershed soil water holding capacity is more related to ε
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