Developing a deep drainage risk map for the Border Rivers area

Deep drainage (DD) is recognised as one of the main drivers for dryland and irrigated salinity. Review of the literature on risk and hazard highlights few Australian studies on assessing DD risk and the need to develop new methods for determining DD risk. This study developed a method to map DD risk for the Northern Murray Darling Basin Catchment of the Border Rivers. Deep drainage was predicted at 85 points in the landscape using the mechanistic soil-water model SWAP, with soil hydraulic inputs created using pedotransfer functions and crop input from supervised classification of LANDSAT imagery. Uncertainty of the hydraulic property estimation was included using Monte Carlo simulations. The DD values were subsequently translated to probabilities of exceeding 5 or 100 mm/year for different land management options. The outcomes indicated that exceeding 100mm/year deep drainage had a probability of 60, 25, 1 and 5% for irrigated cotton, wheat, pasture and native vegetation, respectively. Using regression kriging based on ancillary information from the LANDSAT imagery, DD probabilities were predicted spatially over the study area to create a risk map. Soil type was less important than land use in determining the probability of exceeding a certain value, because land uses tended to be already aligned with certain soil types. Areas that require further research include incorporation of temporal variability in land-use and spatial variability in climate.