HR: 1330h
AN: H22B-0916    [PDF]
TI: Combined Analysis Using River Flow and Leaf Area Index in an Evaluation of a Spatially-Distributed Hydro-Ecologic Model for Semi-Arid Shrubland Watersheds
AU: * Choate, J
EM: jchoate@rohan.sdsu.edu
AF: San Diego State University, 5500 Campanile Dr, San Diego, Ca 92182-4493 United States
AU: Tague, C
EM: ctague@mail.sdsu.edu
AF: San Diego State University, 5500 Campanile Dr, San Diego, Ca 92182-4493 United States
AU: Hope, A
EM: hope1@mail.sdsu.edu
AF: San Diego State University, 5500 Campanile Dr, San Diego, Ca 92182-4493 United States
AU: Bruce, R
EM: abruce@rohan.sdsu.edu
AF: San Diego State University, 5500 Campanile Dr, San Diego, Ca 92182-4493 United States
AU: Ploessel, L
EM: ploessel@rohan.sdsu.edu
AF: San Diego State University, 5500 Campanile Dr, San Diego, Ca 92182-4493 United States
AU: Anaya, M
EM: manaya@rohan.sdsu.edu
AF: San Diego State University, 5500 Campanile Dr, San Diego, Ca 92182-4493 United States
AB: Distributed hydro-ecologic models which link seasonal streamflow, soil moisture and evapotranspiration patterns with spatial patterns of vegetation are important tools for understanding the sensitivity of Mediterranean shrubland ecosystems to future climate and land use change. Applying spatially distributed process based models to investigate these interactions, however, must address issues of parameter uncertainty and calibration. Monte-carlo based approaches that evaluate metrics of observed and modeled streamflow correspondence are commonly used to constrain parameter space. In these ecosystems, however, the strong coupling between vegetation biomass and soil moisture patterns can be used to provide an additional constraint on hydrologic model parameters and further data for model evaluation. In particular, examining the sensitivity of modeled spatial patterns of LAI (leaf area index) across parameter space and comparison between modeled and observed patterns of LAI derived from remote sensing data can provide important information about the ability of a model to predict spatial patterns in addition to aggregate responses such as streamflow. We examine these issues using RHESSys (Regional hydro-ecologic simulation system) for several small watersheds near Santa Barbara, California. Results indicate model parameter space can be more tightly constrained by examining the sensitivity of LAI to parameters that control hydraulic conductivity and soil depth. However, significant deviation between modeled and remote sensing derived LAI across parameter space indicate the limitations of current model assumptions about the key process that control the spatial distribution of soil moisture in these watersheds. Implications for examining the sensitivity of these semi-arid ecosystems to climate change are discussed.
DE: 1640 Remote sensing
DE: 1851 Plant ecology
DE: 1860 Runoff and streamflow
DE: 1866 Soil moisture
SC: Hydrology [H]
MN: 2003 Fall Meeting