Modeling Leaf Area Index Variation for Cropland, Pasture and Tree in Response to Climatic Variation in the Goulburn-Broken Catchment, Australia

Abstract:

Previous 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 zone have rarely been explored in Australia. We 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 (AWAP). We were able to relate seasonal and annual leaf area index of three different land cover types (tree, pasture and crop) with climatic variables for the period 2000 to 2009 in the Goulbourn-Broken catchment, Australia. Strong relationships were obtained between annual leaf area index of crop, pasture and tree with annual precipitation (R² =0.70, 0.65 and 0.82), respectively. Monthly LAI of each land cover types also showed strong (R² = 0.92, 0.95 and 0.95) relationship with the difference between precipitation and reference crop evapotranspiration (P-PET) for crop, pasture and tree respectively. Independent model calibration and validation showed good agreement with remotely sensed MODIS LAI. The results from application of the developed model on 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 scenarios considered, crop showed a decline of between 7 to 38%, pasture 5 to 24% and tree 2 to 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.