Integrating USDA Crop Progress Data, and Remote Sensing Evapotranspiration and Leaf Area Index in Parsimonious Modeling of Hydrologic Responses in Midwestern Landscapes

A parsimonious hydrologic model, the Threshold-Exeedance-Lagrangian Model (TELM), was developed for the intensively managed watersheds in the agricultural Midwest. Crop vegetative progress was identified as a critical model input to the TELM due to its influence on evapotranspiration (ET) and land surface water budget. Crop phenology estimated using USDA crop progress data as well as RS-derived LAI data were compared as a function of spatial and temporal scales. We examined the hypotheses that 1) the integration of RS LAI with TELM enhances its ability to predict stream flow; 2) the enhancement of model predictions with RS-TELM depends on the spatial and temporal variability of LAI over the watershed. First, we developed methodologies for integrating RS data in the TELM framework. Second, we investigated the spatio-temporal variability of crop phenology over the whole state and identified three mesoscale watersheds with distinct levels of variability. Third, we applied five strategies in running the TELM: 1) statewide theoretical LAI curve based on general information of crop growing stages; 2) district-level theoretical LAI curve derived from USDA crop progress data; 3) watershed average LAI curve lumped from RS LAI; 4) distributed LAI derived from MODIS NDVI (Normalized Difference Vegetation Index) data; and 5) distributed MODIS ET data. By examining the hydrographs of watershed outlet streamflow, and the goodness-of-fit measures of model predictions, we further discussed the impacts of the spatio-temporal variability of crop phenology on model performances.