The overarching goal of the project is to characterize anomalies in water supply and demand using a combination of NASA satellite observations and NASA physically based land surface models. The annual water supply-demand imbalance is ingested into existing California Department of Water Resources (CA DWR) operations and the jointly-produced information is distributed to multiple stakeholders across California. This “co-production” of knowledge is accomplished by initializing dialogue between scientists and decision makers early in the research process, and continuing dialogue to jointly set research goals and iterate to achieve mutually successful outcomes. Face-to-face meetings, two workshops, webinar training, and conference calls help to define project directions. For example, decision maker input during these meeting has been invaluable in designing the most useful information content and format of our weekly snow water equivalent (SWE) reports used for forecasting. Such iteration between groups of scientists, stakeholders, and forecasters will continue to inform our research to provide satellite-based tools to evaluate agricultural water supply-demand imbalances and to serve broader NASA strategic goals.
Noah Molotch, University of Colorado at Boulder
John Berggren, University of Colorado at Boulder
Leanne Lestak, University of Colorado at Boulder
Keith Musselman, University of Colorado at Boulder
David Rizzardo, California Department of Water Resources (CA DWR)
Collaborators and Stakeholders
California Department of Water Resources, NASA-JPL, U.S. Fish and Wildlife Service, San Francisco Public Utilities Commission, Pacific Gas and Electric, Kings River Water Association, City of Bakersfield, Sacramento Municipal Utility District, Turlock Irrigation District, U.S. Bureau of Reclamation, Merced Irrigation District, Kaweah Delta Water Conservation District, J.G. Boswell Company, Southern California Edison, Los Angeles Department of Water and Power, National Oceanic and Atmospheric Administration, National Park Service, University of California at Merced, and the Desert Research Institute.
Agricultural water supplies in California are heavily dependent on natural water storage in the form of Sierra Nevada snowpack, which represents approximately 14 million acre feet (~17 km3) of water annually. Demands on these sources of water storage meet or exceed supply under normal climatic conditions. The recent California drought significantly reduced seasonal snowpack leading to significant water supply-demand imbalances that have had profound economic and societal impacts. Interestingly, both the causal factors associated with drought (e.g. abnormally low snowpack and high air temperatures) and the consequences of drought (e.g. reduced evapotranspiration (ET), land fallowing, and land surface productivity) are observable using orbiting satellites. Hence, analysis of satellite data documenting water supply-demand imbalances and the tipping points associated with land use changes may provide water managers with new tools for mitigating the impacts of long-term drought. Water allocation decisions are informed by forecasts of streamflow volume for 20 major river basins across the state issued by the California Department of Water Resources. The various statistical models used for forecasting tend to perform relatively well (errors < 5% of observed flow) during normal climatic conditions but are subject to significant error during abnormal climatic conditions and associated abnormal patterns of snow distribution; e.g. the current drought in California.
Using MODIS-based snow water equivalent (SWE) estimates and Landsat and MODIS-based ET estimates from the NASA Satellite Irrigation Management Support project (SIMS) from 2000 through the funding cycle (i.e. 2019); the primary objective of this research is to provide satellite-based tools for evaluating agricultural water supply-demand imbalances during extreme drought conditions. Related secondary and tertiary objectives aim to: migrate remotely sensed SWE and ET analyses into CA DWR computational environment; and to conduct quantitative and qualitative assessment of the utility of the SIMS ET, and MODIS-based snowpack information to inform water resource decisions during drought.
Our project characterizes anomalies in water supply and demand conditions using a combination of NASA satellite observations and NASA physically based land surface models. These efforts are directly linked to existing water supply forecast procedures at the CA DWR and the demand-relevant decisions that derive from these forecasts. Our existing partnership with CA DWR ensures the integration of the project results into the decision-making process. Moreover, the participation by John Berggren (University of Colorado), who is a specialist in stakeholder decision support, with David Rizzardo (CA DWR) and other decision makers ensures continual iteration between researchers and stakeholders. This research is also highly relevant to broader NASA strategic goals by connecting improved understanding of Earth System Science (i.e. snow distribution, and ET) to mitigation of, and adaptation to global change.
For more information and to download data and reports from this project, please see ftp://snowserver.colorado.edu/pub/fromLeanne/forCADWR/Near_Real_Time_Re…