Missouri River Basin Forecast Center: Soil Moisture Data Use in a Hydrologic Forecasting System
In response to severe drought and flood events in the Upper Missouri River Basin (UMRB) between 2011 and 2019, the Infrastructure Investment and Jobs Act provided funding to improve water monitoring in the region. The UMRB Data Value Study, led by NOAA’s National Integrated Drought Information System (NIDIS), is the assessment element of this multi-component, multi-agency project.
The Soil Moisture Data Use in a Hydrologic Forecasting System project was led by the National Weather Service’s Missouri Basin River Forecast Center (MBRFC) as a component of the UMRB Data Value Study. This project explored the potential of precipitation, soil moisture, and soil temperature data from the U.S. Army Corps of Engineers’ UMRB mesonet build-out to improve hydrologic models—and, therefore, improve hydrologic forecasts, a critical tool for hydrologic operations and management.
Project Approach and Findings
The MBRFC issues timely water resource forecasts of streamflow and runoff generation to support water management and hazard warning in the UMRB. This project explored the potential of newly available precipitation, soil moisture, and soil temperature data from the expanded mesonets in the UMRB to improve runoff and streamflow forecast accuracy.
Incorporating In Situ Precipitation Data
MBRFC forecasts already use in situ precipitation data; however, not all sub-basins in the UMRB were equally well instrumented for data collection prior to the UMRB build-out. New monitoring stations in the region improved spatial coverage in the area, and findings from this project indicate incorporating precipitation data from these stations in the forecasting process will improve accuracy of hydrologic models and streamflow forecasts. The U.S. Army Corps of Engineers and U.S. Bureau of Reclamation are already putting new precipitation data to use in the UMRB in this way.
Incorporating In Situ Soil Moisture and Soil Temperature Data
In situ soil moisture and soil temperature observations are not currently incorporated into the MBRFC’s hydrologic forecasting process. To consider possible future integration of these variables, this project conducted proof-of-concept computations.
The project team found using in situ soil moisture data to set up and to train the Sacramento Soil Moisture Accounting model (SAC-SMA) improved the accuracy of computed soil moisture outputs. Similarly, they learned that researchers could use in situ soil temperature data to develop a method to to represent frozen soils across the UMRB using the Sacramento Heat Transfer (SAC-HT) model.
These calculations also demonstrated that soil temperature and soil moisture data may offer forecasters and other decision-makers additional context about the hydrologic system that can be used as a qualitative reference.
For more information, please contact Elise Osenga (elise.osenga@noaa.gov).
Research Snapshot
Gregg Schalk, NOAA's National Weather Service
John Lague, Jim Terrell, Scott Dummer, and Michael Smith, NOAA's National Weather Service
Results of This Research
- New UMRB mesonet stations improved spatial coverage of precipitation data, with the potential to increase accuracy of U.S. Army Corps of Engineers and U.S. Bureau of Reclamation runoff forecasts.
- Soil temperature data from the UMRB stations provide new context to qualitatively understand runoff conditions by providing a way to estimate frost thickness.
- As more stations and longer periods of record become available in the UMRB, in situ soil moisture readings could be used to adjust model parameters to improve forecasts of high streamflow events and flooding.
