资源环境科技发展态势分析平台

Many studies have examined how runoff (Q) responds to long‐term changes in precipitation (P) and temperature (T), but the effects of potential evapotranspiration (PET) have received less attention. We examine observational data sets for P, T, and Q; along with PET estimated from observations, to determine the extent to which derived P and PET runoff elasticities (𝜀_𝑃 and 𝜀_{𝑃𝐸𝑇,} the fractional changes in runoff associated with given fractional changes in precipitation and PET, respectively) meet Dooge’s complementary relationship (under certain conditions, 𝜀_𝑃 +𝜀_𝑃𝐸𝑇 = 1). We apply three statistical methods and two hydrologic models to estimate 𝜀_𝑃 and 𝜀_𝑃𝐸𝑇 in 84 headwater river basins in California, Oregon, and Washington. We find that while the estimates of 𝜀_𝑃 are generally consistent across two statistical estimators and one model‐based estimator, the estimates of 𝜀_𝑃𝐸𝑇 using the statistical methods differ considerably (generally they are much more negative) from the model‐based estimates and some appear to be implausible. The model‐based estimates show better conformance to the complementary relationship (and in the median across sites, they sum to close to 1.0). We explore several factors that might explain the failure of the observation‐based estimators, including interaction between P and PET and non‐closure of the water budget at annual time scales.