Summary
Texas is the state that experiences frequency occurrence of extreme floods and droughts, and reservoirs are critical infrastructures for water supply and flood management. At present, reservoir operators in the state of Texas rely on HEC-HMS configured in event-base mode for predicting reservoir inflow. The major sources of error in the prediction are precipitation and loss factors. This project aims to integrate satellite-based soil moisture and precipitation products to improve the inflow prediction.
The UTA team is working closely with US Army Corps of Engineer (USACE; Figure. 1) and Lower Colorado River Authority (LCRA; Figure. 1) to i) create a blended precipitation product by combining precipitation products from Global Precipitation Mission (GPM) and ground-based weather radar units operated by National Weather Service; and ii) enhance real-time soil moisture estimates and incorporate these estimates in producing and adjusting loss factors in real-time. The products and systems will be tested using operational configurations of HEC-HMS models from USACE and LCRA before delivering to the latter for operational adoption.
End users/partners:
US Army Corps of Engineer-Fort Worth District (USACE-FWD), Lower Colorado River Authority (LCRA), Brazos River Authority, San Antonio River Authority, NASA Goddard Space Flight Center, NASA Short-term Prediction Research and Transition Center, and WEST Consultants, National Weather Service (NWS) West Gulf River Forecast Center
Data sources, models, and technologies:
The satellite data sources include IMERG precipitation product, SMAP soil moisture, ALEXI, and potentially SMAP vegetation optical depth, and potentially GOES-16 lightning mapper data. Ground-based sensor data include precipitation data from National Weather Service NEXRAD network; in situ rain gauge and soil moisture sensor product. Models include the NASA Land Information System (LIS), the HEC-HMS models maintained by USACE-FWD and LCRA. Technologies include the current Total Runoff Tool (TRT) developed by WEST Consultant for estimating loss factors from soil moisture; precipitation fusion system; and automated real-time loss estimation module (Figure. 2). The latter two systems are being developed.
Major Accomplishments in CY19, Plans/expectations for 2020:
Accomplishment 1: The team set up the USACE and LCRA HEC-HMS models, and adopted the Total Runoff Tool (TRT) developed by the WEST Consultants by Feb. 2020
Accomplishment 2: The team performed HEC-HMS simulations using the initial and constant loss factors estimated by TRT with the North America Land Data Assimilation System (NLDAS) soil moisture products as inputs (Figure. 3).
Accomplishment 3: The team set up the Land Information System and successfully assimilated SMAP Level 3 soil moisture products into the Noah-MP model; the results were validated against in situ data (Figure. 4)
For 2022, the team will focus on the following tasks:
Task 1: Adjust the loss estimates from TRT for use in HEC-HMS, and refine the loss estimation scheme to include spatially distributed soil moisture
Task 2: Complete the testing of the soil moisture-based loss estimates for LCRA basins
Task 3: Generate blended precipitation products that infuse IMERG 4-h data
Task 4: Create bias-adjusted soil moisture product through LIS for testing using the refined loss estimation scheme