Introduction

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The climate in southwestern North America is changing in ways that are starting to have appreciable effects on water availability and water management in the Rio Grande Basin. The quantity of water flowing into the northern section of the Rio Grande/Rio Bravo (hereinafter referred to as the Rio Grande) depends on snowpack from the Rocky Mountains as well as seasonal precipitation. Declining snowpack is one of the most widely recognized features of a warming climate in mountainous areas of western North America. To improve the accuracy of projected outlooks for water management planning, specifically an improved understanding of the changing relation between snowpack and streamflow in the upper basin, researchers at the University of New Mexico performed analysis of historical observations and climate models developed by the Bureau of Reclamation.

Key Issues Addressed

The Upper Rio Grande is largely fed by snowpack, but the relation between temperature change and snowmelt runoff is not well understood. As temperatures have risen over the past half-century, snowpack in the Rocky Mountains has declined, and the seasonal predictability of streamflow has diminished. Large fluctuations in post-snowmelt precipitation also contribute to streamflows. These factors tend to curtail the predictability of streamflow that is simulated with relatively low confidence in climate change climate change
Climate change includes both global warming driven by human-induced emissions of greenhouse gases and the resulting large-scale shifts in weather patterns. Though there have been previous periods of climatic change, since the mid-20th century humans have had an unprecedented impact on Earth's climate system and caused change on a global scale.

Learn more about climate change projections. This poses a tremendous challenge for management of river flows and annual water supply allocations that depend on seasonal forecasts. To address this challenge, this research aims to identify changes to streamflow predictability, assess future predictability, and inform the development of more reliable water supply outlooks essential for water management planning purposes in the Rio Grande Basin.

Project Goals

• Identify changes to snowpack and streamflow predictability in the Rio Grande over the past several decades
• Assess the processes that affect annual water supply and seasonal predictions of streamflow
• Increase confidence in projections of diminished streamflow in a warmer climate
• Inform the development of more reliable water supply outlooks essential for resource management planning purposes in the Rio Grande Basin

Project Highlights

Student Success: Two graduate students completed M.S. degrees with theses derived from project-based research and have gone on to fruitful next career steps.

• Measured Streamflow: Observed streamflow was analyzed at the Del Norte gage on the mainstem of the Rio Grande, located just upstream from the first of many large agricultural diversion points. Project researchers verified that measured streamflow at Del Norte was close to natural streamflow estimates made independently by the US Natural Resources Conservation Service (NRCS). This justified their interpretation of streamflows (and changes to streamflows over the years) at Del Norte as representing actual fluctuations rather than changes in upstream water management.
• Comprehensive Snowpack Analysis: This project carried out a thorough analysis of snowpack in the Rio Grande headwaters based on manual snow course observations extending back to 1958. NRCS snow course data from seven sites in the Rio Grande headwaters basin were used to identify and correlate trends between snowpack, temperature, and precipitation.
• Climate-Based Model Predictions: With observational results in hand, the project team examined the interannual variability of snowpack and streamflow of publicly available 21st-century climate projections provided by the Bureau of Reclamation. These simulations started with climate variables including snow, temperature, and precipitation generated by global climate models from the CMIP5 archive used for the 2013 IPCC climate change assessment. These simulated climate variables were used to drive a surface hydrology model that simulated streamflow in major river basins across the western U.S. including in the Rio Grande.

Lessons Learned

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The results of this study establish that measured peak snowpack has declined approximately 20 percent over the past half century coincident with well-documented increases in temperature. As snowpack declines, the previously tight coupling between snowpack and snowmelt runoff has appreciably diminished, resulting in snowpack-based seasonal predictions that exhibit declining prediction skill. With temperatures rising and snowpack declining further, results indicate seasonal streamflow in the Rio Grande will become increasingly harder to predict. The decline in seasonal forecast skill associated with snowpack measurements will likely reduce the ability of regional water managers in the southwest to effectively plan for water management in snowmelt-dominated rivers. Knowing that changes are occurring should motivate those reliant on the Rio Grande to plan for the likelihood of diminished streamflow in the years ahead and to support more sustainable use of water in the basin.

The changes in streamflow predictability were reflected in the examined ensemble of climate models. Most simulations did not reproduce changes consistent with the observational snowpack assessment. In an ensemble average, these forecasts showed declining streamflow in the Rio Grande. However, despite consistent strong evidence of increasing temperature, projections varied greatly across simulations, indicating that temperature itself is not a helpful predictor of snowmelt runoff. By assessing additional metrics derived from observational results, the group identified a subset of model simulations more consistent in projecting diminished future streamflows.  

The decreased contribution of snowpack towards runoff means other sources of precipitation become more important in streamflow predictions. In recent decades, year-to-year fluctuations in post-peak-snowpack precipitation have accounted for much of the changes seen in streamflow that are no longer related to snowpack. Results of this study indicate that the effect of temperature increase on streamflow is likely indirect and that the appropriate predictors of streamflow should be peak snowpack and spring precipitation.

Next Steps

• Improvements in snowpack estimation will be needed to improve (or just to maintain) streamflow predictability as snowpack diminishes at lower elevations, making in situ SNOTEL and snow course measurements less representative of basin-scale snowpack.
• Continue research on the effects of seasonal prediction of spring season precipitation on water supply outlooks as it applies to other major snow-fed rivers is encouraged
• Present and publish for water managers, researchers, and legislative bodies

Funding Partners 

• This research was supported by a grant to the University of New Mexico (UNM) from the U.S. Geological Survey (USGS) South Central Climate Science Center. S.B. Chavarria was additionally supported by the United States Department of Agriculture (USDA) NIFA program, and by student grants from the UNM Department of Earth and Planetary Sciences and Office of Graduate Studies

Resources

• USGS Project Page
• Downscaled CMIP3 and CMIP5 Climate and Hydrology Projections

Contacts

• David S. Gutzler, Ph.D., Principal Investigator, University of New Mexico: gutzler@unm.edu
• Shaleene B. Chavarria, Graduate Researcher (Former), Hydrologist, USGS New Mexico Water Science Center: schavar@usgs.gov
• Nels R. Bjarke, Graduate Researcher, University of Colorado: Nels.Bjarke@colorado.edu

Case Study Lead Author

• Ilana Casarez, Student Hydrologist, USGS Oklahoma - Texas Water Science Center: icasarez@usgs.gov

Suggested Citation

Casarez l., R. (2020). “Improving Predictions of Water Supply in the Rio Grande Under Changing Climate Conditions.” CART. Retrieved from https://www.fws.gov/project/predictions-water-supply-rio-grande.