Abstract
We propose a new nonparametric approach for assessing future changes in
annual stream flows in extreme drought years based on an ensemble of
climate projections. We apply the method to the Potomac River basin,
investigating whether future flows in the river may be impacted by “hot
drought”, that is, increasing severity of hydrological drought caused
by rising temperatures coupled with variability in precipitation. Long
time series representative of annual climate in time periods of interest
are constructed by pooling and concatenating shorter time series sampled
from an ensemble of bias corrected and spatially downscaled climate
projections, where the K-nearest neighbor method is used to select pool
members. The pooled time series are of sufficient length to allow
estimation of the probability distribution of a full range of future
annual flows, including 1st percentile values, indicative of flow in an
extreme drought year. An empirically derived climate response function
for annual mean flow is used as this study’s simple hydrologic model.
The resulting set of cumulative probability distributions can be used to
compute scaling factors for future annual Potomac River flow which
demonstrate the disparate impacts of climate change on high flow,
average flow, and low flow years. For most scenarios considered, results
indicate that though long-term mean precipitation and river flow will
increase modestly in future years, annual flows in an extreme drought
year will decrease. This new approach can provide multi-model consensus
inputs for water supply planning models to support decision-making
regarding new infrastructure for climate resilience.