Climate elasticity of streamflow in the United States

TLDR

Precipitation elasticity of streamflow, ϵP, measures streamflow sensitivity to rainfall, but watershed model‑based estimates are highly sensitive to model structure and calibration error, and the Budyko hypothesis only explains ϵP variations in very humid basins. A Monte Carlo experiment compares a nonparametric estimator of ϵP with various watershed model‑based approaches, and the estimator is then used to construct a map of ϵP for the United States. The nonparametric estimator has low bias and is as robust as or more robust than alternate model‑based approaches; comparisons with ten detailed climate change studies show that the resulting ϵP contour map provides a validation metric for past and future climate change investigations in the United States, and further investigations reveal that ϵP tends to be low for basins with significant snow accumulation and for basins whose moisture and energy inputs are seasonally in phase.

Abstract

Precipitation elasticity of streamflow, ϵ P , provides a measure of the sensitivity of streamflow to changes in rainfall. Watershed model‐based estimates of ϵ P are shown to be highly sensitive to model structure and calibration error. A Monte Carlo experiment compares a nonparametric estimator of ϵ P with various watershed model‐based approaches. The nonparametric estimator is found to have low bias and is as robust as or more robust than alternate model‐based approaches. The nonparametric estimator is used to construct a map of ϵ P for the United States. Comparisons with 10 detailed climate change studies reveal that the contour map of ϵ P introduced here provides a validation metric for past and future climate change investigations in the United States. Further investigations reveal that ϵ P tends to be low for basins with significant snow accumulation and for basins whose moisture and energy inputs are seasonally in phase with one another. The Budyko hypothesis can only explain variations in ϵ P for very humid basins.