Influence of remotely-sensed vegetation conditions as an input parameter on the VIC hydrologic model

The Variable Infiltration Capacity (VIC) hydrologic model currently uses climatological leaf area index (LAI) to represent vegetation growth. This does not account for interannual variability in the timing and health of vegetation. The purpose of this study is to evaluate how using observed vegetation as an input model parameter influences VIC-derived soil moisture and energy flux. Normalized Difference Vegetation Index (NDVI) from 250-m Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance imagery was used to derive Leaf Area Index (LAI). The LAI product was averaged over each two-year period between 2000 and 2010 at 48 points in the United States Great Plains. Nine sets of two-year LAI averages were parameterized in the Variable Infiltration Capacity (VIC) hydrologic model to represent vegetation conditions. VIC was run at a daily time step over each two year period under both the custom vegetation conditions and the model default vegetation parameters. The first year of the model run was used as spin up time, and model-derived soil moisture from the second year was analyzed. The influence of remotely-sensed vegetation condition parameterization on VIC-derived soil moisture was examined by comparing model-derived soil moisture under two-year LAI averages with soil moisture derived under VIC default vegetation condition parameters. Both output soil moisture datasets were also compared to in situ soil moisture observations at each site, providing an accuracy assessment. Results indicate that the use of satellite-derived vegetation can have a significant influence on land surface model output.