Spatial Quantification of Crop Water Stresses using Remote Sensing

Around 70% of all water used for agriculture in Australia is consumed by irrigation withinthe Murray Darling Basin (MDB) and these water resources are under considerable pressure due to over allocation of irrigation and land degradation over the past years. Issues of soil salinization i.e. closely associated with the rise of groundwater tables arerisking the sustainability of irrigated food production before the recent drought. Enhanced water use efficiency and refined water use practices are needed for irrigation to sustain inthe future.The main objective of this study is to explore the possibility of spatially quantifying crop stresses by applying remote sensing. Our aim is to assess the impact of groundwater depth and salinity and soil salinity on crop productivity in the Coleambally irrigation Area (CIA) located in the MDB. Remote sensing provides representative measurements of several relevant physicalparameters at various spatial scales.SEBAL remote sensing model was applied toestimate actual evapotranspiration (ET) using MODIS and Landsat data for year 2004 -2005. Regression analysis was applied to develop two different models that can test the significance of groundwater depth and salinity, and soil salinity on actual ET. Both linear and non-linear structural forms of the regression models were applied.The empirical findings using both MODIS and Landsat data consistently validated the previous findings i.e. groundwater depth had a highly significant impact on ET.The impact of soil and groundwater salinities on ET was not found significant using satellite data. This may be due to data limitation as the soil and groundwater salinity survey in the CIA is done every 3 years. Nevertheless, a consistent relationship was found between groundwater depth and ET. The results showed that this relationship can be represented by using Landsat since the spatially distributed data hasthe potential to capture more variability.