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NATIONAL SCIENCE FOUNDATION (NSF) 2016

Assessing controls on hydrologic connectivity, plant water availability and degradation risk in drylands with isotope tracers and Lagrangian modeling

Drylands Conductivity Hydrolic

NATIONAL SCIENCE FOUNDATION

Titre : Assessing controls on hydrologic connectivity, plant water availability and degradation risk in drylands with isotope tracers and Lagrangian modeling

Organismes NSF : EAR Division Of Earth Sciences

Durée : August 1, 2016 // July 31, 2019

Résumé
Due to the lack of vegetation associated with many dryland ecosystems, rainfall generates significant overland flow so that runoff/runon processes become important for providing flows to vegetated sites where water can infiltrate, leading to complex patterns of water resources available to plants. Predicting these flow patterns from easily observable features such as vegetation and topographic patterns, would be instrumental in evaluating landscape vulnerability to desertification. In addition, it would provide design strategies for restoration activities by optimizing vegetation selection, hillslope contouring and planting design. This research aims to develop improved techniques to enable such predictions through models that test runon-runoff process against the experimental behavior of isotopic tracers and through the development of new techniques that improve the realism of modeled vegetation and topographic surfaces. The research will support two doctoral research students (one in Israel and one in the US), and research exchange between research sites at UC Berkeley and Ben Gurion University of the Negev. It will enable outreach activities that use the research findings to inform land restoration planning and guidelines, in conjunction with partners at the UC Berkeley College of Environmental Design and the Keren Kayemeth LeIsrael-Jewish National Fund in Israel.

The project will advance predictions of dryland vulnerability to disruption of runon-runoff processes based on the spatial organization of vegetation, hillslope topography and storm characteristics. The aim of such predictions is to identify high priorities for intervention to prevent degradation, and to inform restoration designs, focusing on modification of the vegetation distribution and hillslope form. Previous modeling attempts to generalize the predictions of plant water availability based on spatial pattern were constrained in two ways : (i) The models used to make predictions are generally tested against indirect metrics of the runon-runoff process, such as net discharge from a runoff plot, rather than against observations of site-to-site source-sink transport of water during storm events ; thus their ability to constrain the source-sink behavior within a runoff site is questionable. (ii) The model experiments used to connect dryland surface features to water redistribution rely on individual realizations of idealized land surfaces. Consequently, uncertainty is poorly characterized, and the meaning of the resulting metrics for real landscapes is unclear. This proposal exploits isotopic tracer experiments to reveal patterns of connectivity and water availability to vegetation on a well-characterized dryland hillslope at the Lehavim Long Term Ecological Research site in Israel. The patterns will be used to test the predictions of runoff-runon models by adapting these models to predict Lagrangian transport of water using Coupled Eulerian-Lagrangian Modeling techniques. Model experiments with the tested model will then draw on the emerging field of multi-point statistics to enable realistic realizations of landscape surface features, allowing uncertainty in predicted water availability, degradation risk or restoration quality to be characterized. The research will provide insights into landscape-scale controls on desertification vulnerability based on the likelihood that runoff is captured on a hillslope, or is lost via export from vegetated slopes.

Partenaire (s) : Sally Thompson sally.thompson berkeley.edu (Principal Investigator)

Sponsor  : University of California-Berkeley

Financement : $282,543.00

National Science Foundation

Page publiée le 14 juillet 2018