Simulating water and energy fluxes using a coupled groundwater, surface water, land surface and regional climate model.

The land surface component of atmospheric models represents many processes that control the exchange of energy, momentum and water fluxes between soil, vegetation and the atmosphere, and has long been recognized as important for hydrometeorological forecasting and climate predictions. At present, the land surface parameterization schemes of atmospheric models usually have very crude representation of the surface and subsurface water movement. This has in turn contributed to the large uncertainty in meteorological and hydrologic predictions. The goal of this project is to develop and apply a coupled regional climate, land-surface, groundwater flow model as a means to further understand important mass and energy couplings between regional climate, land surface and groundwater. The project involves coupling three distinct submodels that have traditionally been used independently with abstracted and potentially oversimplified (inter-model) boundary conditions. This project builds on previous work at LLNL that has successfully linked a 3-D sub-surface groundwater flow model - the PARFLOW model - with the Community Land Model (CLM). This PARFLOW-CLM model will be further coupled with a regional climate model – the Advanced Regional Prediction System (ARPS). With significantly improved representation of the land surface hydrological processes, we hope to achieve (1) an improved understanding of the sensitivity and importance of coupled physical processes from the subsurface to the atmosphere; (2) a more realistic model representation of weather and climate predictions, including precipitation and temperature, at the regional scale; and (3) a new tool for predicting hydrologic conditions (rainfall, temperature, snowfall, snowmelt, runoff, infiltration, soil moisture, groundwater flow, and with upgrade capability to predict solute transport processes).

This work was conducted under the auspices of the U. S. Department of Energy by the University of California, Lawrence Livermore National Laboratory (LLNL) under contract W-7405-Eng. This work was funded by the LLNL LDRD program.