Estimating Soil and Root Parameters using a Hydrogeophysical Inversion

Abstract:

Transpiration is the dominant pathway for water exchange to the atmosphere in temperate climates, and therefore a crucial aspect of modeling water balances at regional and local scales. Transpiration is dependent on soil water availability as well as root distribution, which in turn depends on many factors beyond just the plant species; including the climate conditions and soil texture. However, measuring both root distribution and transpiration directly remains a challenge, which limits our ability to model interactions between the hydrosphere and atmosphere with confidence.

Hydrogeophysical techniques that use electrical resistivity tomography (ERT) can visualize and quantify the dynamic movement of water that occurs via infiltration, redistribution, and root water uptake processes. Importantly, electrical resistivity approaches can be designed to be temporally and/or spatially robust, covering large areas or long time periods with relative ease, an advantage over point or in-situ methods. ERT data can be sensitive to the distribution of roots throughout the growing season, and our goal is to determine the data conditions necessary for a hydrogeophysical inversion that could model root dynamics.

Previous studies have shown the value of using hydrogeophysical inversions to estimate soil properties. Others have used hydrological inversions to estimate both soil properties and root distribution parameters (such as maximum rooting depth). In this study, we combine these two approaches to use a coupled hydrogeophysical inversion that estimates water retention curve parameters as well as parameters of a root water uptake model. After validating the model using realistic synthetic data, we apply it to a field site in Southwest Michigan where several different biofuel crops are instrumented with ERT arrays, Time Domain Reflectometry, and temperature sensors. This method shows promise for modeling the transient nature of root water uptake, transpiration, and root distributions under field conditions for a variety of vegetation types.