Quantifying Soil Water and Root Dynamics Using a Coupled Hydrogeophysical Inversion

Plot- to field-scale root distribution data are relatively rare and difficult to measure with traditional methods. Nevertheless, these data are needed to accurately model root water uptake (RWU) processes within agronomic, hydrologic, and terrestrial biosphere models. New tools are needed to effecti...

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Bibliographic Details
Main Authors: Alexandria S. Kuhl, Anthony D. Kendall, Remke L. Van Dam, David W. Hyndman
Format: Article
Language:English
Published: Wiley 2018-03-01
Series:Vadose Zone Journal
Online Access:https://dl.sciencesocieties.org/publications/vzj/articles/17/1/170154
Description
Summary:Plot- to field-scale root distribution data are relatively rare and difficult to measure with traditional methods. Nevertheless, these data are needed to accurately model root water uptake (RWU) processes within agronomic, hydrologic, and terrestrial biosphere models. New tools are needed to effectively observe root distributions and model dynamic root growth processes. In the past decade, geophysical tools have increasingly been used to study the vadose zone, and hydrogeophysical inversions have shown promise to noninvasively characterize water dynamics. In such an approach, the hydrology is modeled and hydrological data are inverted with the geophysical data, constraining the geophysical inversion results and decreasing uncertainty and the number of nonunique solutions. In this study, we developed and tested a coupled hydrogeophysical inversion approach that uses electrical resistivity data to estimate soil hydraulic, petrophysical, and root dynamic parameters. This builds on prior research that used either a coupled hydrogeophysical inversion to estimate soil hydraulic parameters only, or a hydrological inversion to estimate root distribution or root water uptake parameters. Our results indicate that under the conditions tested, this approach accurately captures root water dynamics and soil hydraulic parameters. This opens up opportunities to noninvasively image a variety of root distributions and soil systems, better understand the dynamics of RWU processes, and improve estimates of transpiration for systems models.
ISSN:1539-1663