ParFlow-LIS: An Advanced Hydrologic Data Assimilation System for Studying Surface and Subsurface Hydrologic Processes
Abstract
The Upper Colorado River Basin (UCRB) provides water to nearly 40 million people through several sectors including agricultural and food industries, hydropower, and drinking water. Climate change and increasing water demand due to expanding population will continue to threaten the security of Food, Energy, and Water (FEW) in this region. Groundwater contributes an average of 50% of total streamflow in the UCRB and is expected to decline to as low as 29% by the 2050s as a result of a future dry and hot climate. In addition, the other energy and water fluxes, such as Evapotranspiration (ET) and Snow Water Equivalent (SWE), are expected to be significantly impacted, resulting in intensifying drought conditions and threatening security of FEW in UCRB. Despite recent progress in Earth system models and their successful applications, groundwater processes are still poorly represented within them. In this prototype study, we used a newly developed coupled hydrologic model, ParFlow-LIS (Land Information System) to study the surface and subsurface hydrologic processes and their interactions across the UCRB while accounting for multiple sources of uncertainties involved in different layers of model simulations. ParFlow-LIS is an integrated physically based hydrologic modeling framework that enables the user to benefit from assimilating the satellite observations to provide more accurate and reliable model predictions. This study discusses the preliminary results of assimilating GRACE (Gravity Recovery and Climate Experiment) groundwater signal into ParFlow-LIS and its usefulness in improving the understanding of the surface water and groundwater processes and their interactions across the UCRB.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2022
- Bibcode:
- 2022AGUFM.H25R1324A