| Abstract： |
Streamflow elasticity to precipitation, defined as the percent change of streamflow resulting from a 1% change in precipitation, is sometimes used as an alternative to rainfall-runoff models in climate impact analyses. Elasticity is usually estimated from long streamflow and precipitation series aggregated at annual time steps while the climate impact analyses are usually geared toward changes at decadal scales. The purpose of this paper is therefore to understand how the elasticity depends on the aggregation time scale and the process controls of such a dependence. We analyze streamflow records of 7,053 catchments around the world over the period 1950-2016, and select 5,327 with reliable elasticity estimates for aggregation time ranging from 13 to 60 months. We find a significant scaling of streamflow elasticity to precipitation with aggregation time in 66% of the catchments which is much larger than expected by chance. Positive scaling occurs much more frequently than negative scaling. More arid/less rainy catchments, less forested catchments and catchments with a large base flow contribution to streamflow are more frequently characterized by a positive scaling. A random forest classification model identifies aridity index, latitude, mean annual precipitation, the potential evapotranspiration seasonality, the base flow index and the precipitation seasonality as relevant explanatory variables of the scaling. We interpret the sign of the scaling by non-linear runoff generation in arid regions, by the effect of climate modes and snow processes, and by the regulation capacity of vegetation to transpire more water if the past years were wet. It is suggested to use decadal elasticities instead of annual elasticities in climate impact analyses in order to account for their scaling behavior. |
