B52C-04
Quantifying biogeochemical responses to hydrological perturbations in terrestrial systems using geophysical monitoring and inversion schemes

Friday, 18 December 2015: 11:05
2006 (Moscone West)
Susan S. Hubbard1, Baptiste Dafflon1, Anh Phuong Tran1, Jinsong Chen2 and Haruko M Wainwright1, (1)Lawrence Berkeley National Laboratory, Berkeley, CA, United States, (2)Lawrence Berkeley National Lab, Berkeley, CA, United States
Abstract:
Although recognized that terrestrial hydrological processes drive a variety of biogeochemical processes, quantifying interactions that occur across a range of scales and compartments is challenging. We describe recently developed approaches to quantify these interactions, and demonstrate the value of developed approaches in two different terrestrial systems. The first is a relatively flat Arctic tundra polygonal ground system, where snowmelt-dominated, surface water distribution significantly influences soil microbial activity and resulting production of greenhouse gasses. The second is a Colorado River floodplain-catchment, where a transient snowmelt pulse leads to hydrological and biogeochemical interactions between different compartents of the system.

Three capabilties were developed to improve understanding of hydrology influences on biogeochemistry at these sites. The first is a networked sensing system that coincidently measures below-, at- and above-ground critical properties (such as soil moisture, soil temperature, canopy greenness, surface water inundation, active layer depth, and snow thickness). The approach takes advantage of autonomous data acquisition using unmanned aerial vehicles, tram-based sensors, and surface geophysical approaches. The dense datasets enable ‘visualization’ of interactions that occur across compartments in response to freeze-thaw and runoff processes. The second advance is the development of a coupled hydro-thermal-geophysical inversion scheme that takes advantage of spatially extensive geophysical data as well as direct but sparse measurements in the quantitative estimation of terrestrial responses to hydrological perturbations. The third is the development of stochastic ‘zonation’ approaches, which use multi-type, multi-scale datasets to identify regions in the landscape that have unique distributions of properties that influence biogeochemical cycling. Together, the sensing, modeling, and integrative functional zonation approaches hold value for documenting how both press and pulse hydrological perturbations drive biogeochemical transformations - from local scales where native processes occur to landscape scales needed to improve climate model predictions.