Quantifying Subsurface Water and Heat Distribution and its Linkage with Landscape Properties in Terrestrial Environment using Hydro-Thermal-Geophysical Monitoring and Coupled Inverse Modeling

Abstract:

Quantifying water and heat fluxes in the subsurface is crucial for managing water resources and for understanding the terrestrial ecosystem where hydrological properties drive a variety of biogeochemical processes across a large range of spatial and temporal scales. Here, we present the development of an advanced monitoring strategy where hydro-thermal-geophysical datasets are continuously acquired and further involved in a novel inverse modeling framework to estimate the hydraulic and thermal parameter that control heat and water dynamics in the subsurface and further influence surface processes such as evapotranspiration and vegetation growth. The measured and estimated soil properties are also used to investigate co-interaction between subsurface and surface dynamics by using above-ground aerial imaging. The value of this approach is demonstrated at two different sites, one in the polygonal shaped Arctic tundra where water and heat dynamics have a strong impact on freeze-thaw processes, vegetation and biogeochemical processes, and one in a floodplain along the Colorado River where hydrological fluxes between compartments of the system (surface, vadose zone and groundwater) drive biogeochemical transformations.

Results show that the developed strategy using geophysical, point-scale and aerial measurements is successful to delineate the spatial distribution of hydrostratigraphic units having distinct physicochemical properties, to monitor and quantify in high resolution water and heat distribution and its linkage with vegetation, geomorphology and weather conditions, and to estimate hydraulic and thermal parameters for enhanced predictions of water and heat fluxes as well as evapotranspiration. Further, in the Colorado floodplain, results document the potential presence of only periodic infiltration pulses as a key hot moment controlling soil hydro and biogeochemical functioning. In the arctic, results show the strong linkage between soil water content, thermal parameters, thaw layer thickness and vegetation distribution. Overall, results of these efforts demonstrate the value of coupling various datasets at high spatial and temporal resolution to improve predictive understanding of subsurface and surface dynamics.