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Improving Predictions of Water Supply in the Rio Grande under Changing Climate Conditions

Climate Variability, Snowpack and Streamflow in the Rio Grande Headwaters
Principal Investigator
David Gutzler


Start Date
End Date
Release Date


On its southbound course from Colorado to the Gulf of Mexico, the Rio Grande provides water resources for more than 13 million people. The quantity of water flowing into the northern section of the river depends on how much snowpack from the Rocky Mountains melts into runoff and on seasonal precipitation rates. Models describing the relationship between winter snowpack quantity and springtime snowmelt runoff quantities for the basin are combined with models describing long-term natural variation in precipitation to create water supply outlooks. The outlooks developed by the U.S. Natural Resources Conservation Service are currently used by stakeholders to make critical water allocation decisions in the basin. Improvements to water supply [...]

Child Items (3)


Principal Investigator :
David Gutzler
Funding Agency :
South Central CSC
CMS Group :
Climate Adaptation Science Centers (CASC) Program

Attached Files

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“Rio Grande River - Credit: Alan Cressler”
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This project will use observed historical data and climate model projections to develop statistical prediction models to relate winter snowpack to subsequent snowmelt runoff in the upper Rio Grande. Statistical models of this sort are used operationally to create water supply outlooks for the Rio Grande each year. The research proposed here will inform improvements to these outlooks in several ways. First, we will closely examine the sensitivity of these models to changes in the baseline period, to investigate whether recent climate change has affected the prediction skill of models based on historical data. Second, we will develop statistical prediction models based on climate model projections, to examine how snowpack-streamflow relationships are projected to change in ways that directly affect annual water supply outlooks. Third, we will use historical simulations of streamflow to provide a new estimate of uncertainties in water supply outlooks.

Project Extension

typeTechnical Summary
valueThis proposal describes a program of research that represents an expansion and logical continuation of a one-year pilot project currently in progress. We propose an analysis of historical observations and climate model projections to assess the processes that factor into annual water supply outlooks for the upper Rio Grande. Water supply outlooks are a hydrologic version of short-term climate predictions. They are strongly influenced by trends in snowpack associated with climate change, and by natural multidecadal fluctuations in winter and spring precipitation, both of which affect the expected value of streamflow following ablation of snowpack in the Rio Grande headwaters drainages. Large interannual fluctuations in post-snowmelt precipitation also affect flows and tend to limit streamflow predictability. On multidecadal climate change time scales, the effect of increasing temperature on snowpack and ET is projected to become the first-order process responsible for projections of diminished streamflow, subject to continued large interannual and decadal fluctuations of precipitation. In the proposed research these processes will be incorporated into statistical prediction models for Rio Grande streamflow, similar to the models used operationally by the U.S. Natural Resources Conservation Service for their current operational water supply outlooks. The sensitivity of these prediction models to historical period of record will be quantified, and if possible attributed to specific components of climate variability and change. Then the statistical models will be applied to more complex climate change projections generated by coupled dynamical models. The results of the research will place constraints on the predictability of streamflow associated with winter snowpack, identify changes to streamflow predictability over the past several decades (a period of rapid observed warming), and assess future predictability.

Budget Extension

typeAward Type
typeAward Number

Rio Grande River - Credit: Alan Cressler
Rio Grande River - Credit: Alan Cressler


Spatial Services

ScienceBase WMS


  • National and Regional Climate Adaptation Science Centers
  • South Central CASC

Associated Items



Additional Information


Type Scheme Key
RegistrationUUID NCCWSC 84d2620c-c4be-4aff-997a-1f7ca5d998d7
StampID NCCWSC SC16-PD0839

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