Estimating hydrologic vulnerabilities to climate change using simulated historical data: A proof-of-concept for a rapid assessment algorithm in the Colorado River Basin

Study focus: Future climate impacts on streamflow are of critical concern due to its importance for water and energy supplies. However, rigorous studies of such impacts involve complicated modeling chains that can be time-consuming and costly to implement. We examine an alternative approach by devel...

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Main Authors: Kurt C. Solander, Katrina E. Bennett, Sean W. Fleming, Richard S. Middleton
Format: Article
Language:English
Published: Elsevier 2019-12-01
Series:Journal of Hydrology: Regional Studies
Online Access:http://www.sciencedirect.com/science/article/pii/S2214581819301806
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author Kurt C. Solander
Katrina E. Bennett
Sean W. Fleming
Richard S. Middleton
author_facet Kurt C. Solander
Katrina E. Bennett
Sean W. Fleming
Richard S. Middleton
author_sort Kurt C. Solander
collection DOAJ
description Study focus: Future climate impacts on streamflow are of critical concern due to its importance for water and energy supplies. However, rigorous studies of such impacts involve complicated modeling chains that can be time-consuming and costly to implement. We examine an alternative approach by developing a method to predict the 21st century peak March-May (MAM) streamflow response to warming from historical data alone, specifically, past observations of the Snow-to-Precipitation ratio divided by basin Area (SPA). Study region: Using the Colorado River Basin (CRB) as a proving ground, we test this empirical relationship over 23 basins ranging in size from 9728 to 639,806 km2 within the CRB. Data was derived from hydrology model simulations forced by a suite of climate models, run under two emissions scenarios. New hydrological insights: Our proof-of-concept study revealed useful predictive capability (r2 = 0.58) and additionally identified three response types: rain- (basin SPA < 1.2 × 10−3 km-2), snow-rain- (1.4 × 10−3 to 3 × 10−3 km-2), and snow-dominant (>3 × 10−3 km-2). The most dramatic changes occurred in snow-dominant basins where streamflow increased up to 320 % in MAM, but decreased by up to 60 % in the critical high demand months of July-September (JAS). By quantifying the relationship between historical data and future streamflow projections, our findings suggest this empirical relationship is useful to quickly and cheaply determine where and when large changes in hydrology will occur from future warming. Keywords: Streamflow forecasting, Snow, Climate variability, Modeling, Water resources management
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spelling doaj.art-3c3b96782d6d4539abdd40c93c8a011a2022-12-22T01:12:42ZengElsevierJournal of Hydrology: Regional Studies2214-58182019-12-0126Estimating hydrologic vulnerabilities to climate change using simulated historical data: A proof-of-concept for a rapid assessment algorithm in the Colorado River BasinKurt C. Solander0Katrina E. Bennett1Sean W. Fleming2Richard S. Middleton3Los Alamos National Laboratory, Los Alamos, NM, USA; Corresponding author.Los Alamos National Laboratory, Los Alamos, NM, USAWhite Rabbit R&D LLC (Fleming), Corvallis, OR, USALos Alamos National Laboratory, Los Alamos, NM, USAStudy focus: Future climate impacts on streamflow are of critical concern due to its importance for water and energy supplies. However, rigorous studies of such impacts involve complicated modeling chains that can be time-consuming and costly to implement. We examine an alternative approach by developing a method to predict the 21st century peak March-May (MAM) streamflow response to warming from historical data alone, specifically, past observations of the Snow-to-Precipitation ratio divided by basin Area (SPA). Study region: Using the Colorado River Basin (CRB) as a proving ground, we test this empirical relationship over 23 basins ranging in size from 9728 to 639,806 km2 within the CRB. Data was derived from hydrology model simulations forced by a suite of climate models, run under two emissions scenarios. New hydrological insights: Our proof-of-concept study revealed useful predictive capability (r2 = 0.58) and additionally identified three response types: rain- (basin SPA < 1.2 × 10−3 km-2), snow-rain- (1.4 × 10−3 to 3 × 10−3 km-2), and snow-dominant (>3 × 10−3 km-2). The most dramatic changes occurred in snow-dominant basins where streamflow increased up to 320 % in MAM, but decreased by up to 60 % in the critical high demand months of July-September (JAS). By quantifying the relationship between historical data and future streamflow projections, our findings suggest this empirical relationship is useful to quickly and cheaply determine where and when large changes in hydrology will occur from future warming. Keywords: Streamflow forecasting, Snow, Climate variability, Modeling, Water resources managementhttp://www.sciencedirect.com/science/article/pii/S2214581819301806
spellingShingle Kurt C. Solander
Katrina E. Bennett
Sean W. Fleming
Richard S. Middleton
Estimating hydrologic vulnerabilities to climate change using simulated historical data: A proof-of-concept for a rapid assessment algorithm in the Colorado River Basin
Journal of Hydrology: Regional Studies
title Estimating hydrologic vulnerabilities to climate change using simulated historical data: A proof-of-concept for a rapid assessment algorithm in the Colorado River Basin
title_full Estimating hydrologic vulnerabilities to climate change using simulated historical data: A proof-of-concept for a rapid assessment algorithm in the Colorado River Basin
title_fullStr Estimating hydrologic vulnerabilities to climate change using simulated historical data: A proof-of-concept for a rapid assessment algorithm in the Colorado River Basin
title_full_unstemmed Estimating hydrologic vulnerabilities to climate change using simulated historical data: A proof-of-concept for a rapid assessment algorithm in the Colorado River Basin
title_short Estimating hydrologic vulnerabilities to climate change using simulated historical data: A proof-of-concept for a rapid assessment algorithm in the Colorado River Basin
title_sort estimating hydrologic vulnerabilities to climate change using simulated historical data a proof of concept for a rapid assessment algorithm in the colorado river basin
url http://www.sciencedirect.com/science/article/pii/S2214581819301806
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