| description abstract | revious studies have reported relationships between mean annual climatic variables and mean annual leaf area index (LAI), but the seasonal and spatial variability of this relationship for different vegetation cover types in different climate zones have rarely been explored in Australia. The authors developed simple models using remotely sensed LAI data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and gridded climatic data from the Australian Water Availability Project. They were able to relate seasonal and annual LAI of three different land cover types (tree, pasture, and crop) with climatic variables for the period 2000?09 in the Goulburn?Broken catchment, Australia. Strong relationships were obtained between annual LAI of crop, pasture, and tree with annual precipitation (R2 = 0.70, 0.65, and 0.82, respectively). Monthly LAI of each land cover type also showed a strong relationship (R2 = 0.92, 0.95, and 0.95) with the difference between precipitation P and reference crop evapotranspiration (PET; P ? PET) for crop, pasture, and tree. Independent model calibration and validation showed good agreement with remotely sensed MODIS LAI. The results from the application of the developed model on the future impact of climate change suggest that under all climate scenarios crop, pasture, and tree showed consistent decreases in mean annual LAI. For the future climate change scenarios considered, crop showed a decline of 7%?38%, pasture showed a decline of 5%?24%, and tree showed a decline of 2%?11% from the historical mean annual. These results can be used to assess the impacts of future climatic and land cover changes on water resources by coupling them with hydrological models. | |
