A Decision Support System for Matching Irrigation Demand and Supply in the Near Real Time Environment

This study deals with the application of a novel decision support system (DSS) for precise matching of irrigation demand and supply in a the near real time environment for the Coleambally Irrigation area (CIA), located in the southwest of New South Wales (NSW), Australia. Forecasting of irrigation demand in the real time environment entails a complete understanding of the spatio - temporal variability of meteorological parameters and evapotranspiration (ET). For improved irrigation system management and operation, a holistic approach of integrating remote sensing derived ET from the SEBAL method with forecasted meteorological data and water use efficiency was used to forecast net irrigation demand. In order to capture the spatial variability, the CIA has been divided into 22 nodes based on direction of flow and connectivity. All hydrological data of inflow and outflow was estimated at all nodes of the CIA for the estimation of water use efficiencies. 10 Landsat 5 TM satellite images were used for mapping irrigated crops and estimation of actual ET for the summer cropping season of 2008 - 2009. This estimated actual ET and forecasted meteorological data was used for demand forecasting for 7 d. The results were compared with the data obtained for irrigation supplies. The methodology is very robust and cost effective for demand driven irrigation systems that have a good database, and daily demand can be forecast and updated by using remote sensing image analysis with minimum time input. The outcome of irrigation demand forecasting on a daily basis for three summer months (December 2009 - February 2010) has been applied within the DSS by linking crop water demand with irrigation system management in the near real time environment. The developed model has been coupled with CICL' s water ordering system and has been tested and refined for implementation across all spatial scales ranging from farm to irrigation system in the CIA. The developed DSS, featuring a web - based interface for near real time inquiry into the irrigation status from farm to system level, will enable irrigators to more closely match water application to crop water consumption within daily operational constraints in the CIA. This user friendly decision support model provides water managers with a deeper and more useful understanding about the irrigation demand and supply in the CIA.