Drought conditions represent unique challenges for water resource management. Water users in the Central Valley of California rely on the seasonal melt of substantial mountain snow (Figure 1 – blue line) in the Sierra Nevada to augment limited groundwater stores. This runoff is stored in reservoirs in the Sierra Nevada foothills and released in summer when demand is highest (Figure 1 – orange line). Under drought conditions, runoff volumes are significantly reduced and demand far exceeds runoff and storage, making water shortages — known as supply-demand imbalances — much more common.
Participants: Noah Molotch, David Rizzardo Chief of Water Supply Forecasting of California's Department of Water Resources, Keith Musselman, Leanne Lestak, John Berggren and Kehan Yang.
This project produces satellite-based tools to characterize agricultural water supply-demand imbalances during extreme drought conditions, provides these tools to water managers, and assesses the utility of these datasets to inform water resource decision-making during drought.
This research project uses NASA satellite-based (MODIS) snow water equivalent (SWE) and (Landsat and MODIS) ET estimates – from the NASA Satellite Irrigation Management Support project (SIMS) – for years 2000 through 2019. The primary objective of the work 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 the California Department of Water Resources (CA DWR) computational environment; and to conduct quantitative and qualitative assessments of the utility of the SIMS ET, and MODIS-based snowpack information, to inform water resource decision-making during droughts. The research focuses on ingestion of remotely sensed observations within operational models used by the CA DWR.
The Impacts: Actionable information for decision-makers and stakeholders
By linking NASA products to existing water supply forecast procedures at the CA DWR, we provide information to support water management decisions. A strong partnership with CA DWR ensures effective integration of our products into decision-making processes with an emphasis on two-way communication. Namely, the participation by David Rizzardo, California’s Chief of Water Supply Forecasting, and John Berggren (University of Colorado-Boulder), an expert in stakeholder decision support, ensure continual communication between researchers and stakeholders. The research connects improved understanding of Earth System Science to mitigation and adaptation to global change – providing actionable information to decision-makers and stakeholders.
Real-Time SWE Reports
The bi-monthly reports are an experimental research product that provides near-real-time estimates of snow-water equivalent (SWE) at a spatial resolution of 500 m for the Sierra Nevada in California from mid-winter through the melt season. The report is released within a week of the date of data acquisition. The SWE report format was co-produced by the Molotch hydrology group and the CA DWR to ensure that the reports provide actionable information.
The spatial SWE analysis method for the Sierra Nevada uses the following data as inputs:
- In-situ SWE from all operational CA snow gage sensor sites
- MODSCAG fractional snow-covered area (fSCA) data from recent cloud-free MODIS satellite images
- Physiographic information (elevation, latitude, upwind mountain barriers, slope, etc.)
- Historical daily SWE patterns (2000-2014) retrospectively generated using historical MODSCAG data and an energy-balance model that back-calculates SWE given the fSCA time-series and meltout date for each pixel
The real time SWE reports provide spatial maps of SWE at 500-m resolution as well as percent of average maps and tables showing SWE by watershed and by elevation band. Real time SWE reports for the Seirra Nevada Mountains are created by INSTAAR's Mountain Hydrology Group and are available for public use. Real Time SWE Reports
"The valuable data gathered by the CWEST and NASA Earth science teams gives the California Department of Water Resources a broader sense for how much water is being stored in our snowpack, allowing us to fine-tune vital seasonal runoff estimates, which are used by water managers and reservoir operators across the state.”
- David Rizzardo, Chief, Snow Surveys Section/Water Supply Forecasting, CA DWR
Case Studies; Oroville Flood Event and Drought Monitoring
In addition to drought management, the data products produced under this project have been used to characterize runoff during floods such as occurred in February 2017 upstream of California’s Oroville Dam. This “atmospheric river” event dropped up to 20 inches of rainfall on substantial mountain snowpack. The resulting flood wave threatened the structural integrity of the Oroville Dam, causing $870M in damages and requiring the evacuation of more than 180k downstream residents. Guided by CA DWR decision-makers, we used the satellite-based snow product to quantify the additional runoff produced by snowmelt during this large rain-on-snow flood event. The improved characterization of mountain snow distribution provided by our “real-time” snowpack maps (Figure 2) and advisory reports help to better inform forecasts and decisions. Thus, our partnership has the demonstrated potential to help the State of California prepare for and manage water supply extremes including both drought and flood.
During those same atmospheric river events CWEST calculations show that those storms may have recouped 37 percent of the state's five-year snow-water deficit (Figure 3). Two powerful storms deposited roughly 17.5-million acre feet of water on California's Sierra Nevada range in January 2017.
The scale of the problems addressed goes far beyond California. Globally, agricultural water demands are heavily reliant on seasonal snow to support over a billion people. These dependent commodities and populations are potentially vulnerable to a changing climate. Water managers across the globe will increasingly seek improved information on water supply, demand, and imbalances. This timely project uses satellite-based water supply and demand information to improve water resource management with careful attention to provide actionable decision support for agricultural producers.