Changes in Climate and Land Cover Affect Seasonal Streamflow Forecasts in the Rio Grande Headwaters. (9th June 2020)

• Record Type: Journal Article
• Authors: Penn, Colin A.; Clow, David W.; Sexstone, Graham A.; Murphy, Sheila F.
• Is Part Of: Journal of the American Water Resources Association. Volume 56:Number 5(2020)
• Page Start: 882
• Page End: 902
• Publication Date: 2020-06-09
• Subjects: Rio Grande -- hydrologic modeling -- snow hydrology -- streamflow forecasting; Water-supply -- Periodicals; Hydrology -- Periodicals; Water resources development -- Periodicals; Water resources development -- Environmental aspects -- Periodicals; 333.9100973
• DOI: 10.1111/1752-1688.12863
• Languages: English
• ISSNs: 1093-474X

Abstract

Abstract: Seasonal streamflow forecast bias, changes in climate, snowpack, and land cover, and the effects of these changes on relations between basin‐wide snowpack, SNOw TELemetry (SNOTEL) station snowpack, and seasonal streamflow were evaluated in the headwaters of the Rio Grande, Colorado. Results indicate that shifts in the seasonality of precipitation and changing climatology are consistent with periods of overprediction and underprediction in streamflow forecasts. Multiple linear regression of SNOTEL data, postcedent precipitation, and land‐cover changes explained 2%–18% more variability in streamflow prediction than using SNOTEL station data alone. Simulated basin‐wide snowpack from a physically based model had significant negative trends in snow water equivalent (−4.33 mm/yr) and snow‐covered area (−0.05%/yr) during the melt period April–June. Simulated streamflow from a precipitation‐runoff model increased an average 5% when the effects of bark beetle‐induced tree mortality were compared to a baseline simulation with static vegetation. The effects of a 2013 wildfire increased simulated seasonal streamflow an average 35% for 1–4 years postfire. The combined effects of climate and land‐cover changes on snowpack‐streamflow relations highlight the difficulty in seasonal streamflow forecasting, which has important implications for water‐resource management. Abstract : Research Impact Statement : Changing relations between snow, precipitation, and seasonal runoff were evaluated in the Rio Grande Headwaters basin using statistical and physical modeling techniques.