4.7 Article

Dynamic root distributions in ecohydrological modeling: A case study at Walnut Gulch Experimental Watershed

Journal

WATER RESOURCES RESEARCH
Volume 49, Issue 6, Pages 3292-3305

Publisher

AMER GEOPHYSICAL UNION
DOI: 10.1002/wrcr.20245

Keywords

ecohydrology; phenotypic plasticity; root distribution

Funding

  1. United States Department of Agriculture, Agricultural Research Service
  2. Kuwait-MIT Center for Natural Resources and the Environment
  3. MIT Martin Family Society of Fellows for Sustainability

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Arid regions are characterized by high variability in the arrival of rainfall, and species found in these areas have adapted mechanisms to ensure the capture of this scarce resource. In particular, the rooting strategies employed by vegetation can be critical to their survival. However, land surface models currently prescribe rooting profiles as a function of only the plant functional type of interest with no consideration for the soil texture or rainfall regime of the region being modeled. Additionally, these models do not incorporate the ability of vegetation to dynamically alter their rooting strategies in response to transient changes in environmental forcings or competition from other plant species and therefore tend to underestimate the resilience of these ecosystems. To address the simplicity of the current representation of roots in land surface models, a new dynamic rooting scheme was incorporated into the framework of the distributed ecohydrological model tRIBS+VEGGIE. The new scheme optimizes the allocation of carbon to the root zone to reduce the perceived stress of the vegetation, so that root profiles evolve based upon local climate and soil conditions. The ability of the new scheme to capture the complex dynamics of natural systems was evaluated by comparisons to hourly timescale energy flux, soil moisture, and vegetation growth observations from the Walnut Gulch Experimental Watershed, Arizona. Robust agreement was found between the model and observations, providing confidence that the improved model is able to capture the multidirectional interactions between climate, soil, and vegetation at this site.

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