A methodology for up-scaling irrigation losses

This paper presents a methodology for up-scaling field irrigation losses and quantifying relative losses at the irrigation area level for potential water savings. Two levels of analysis were considered: First, the field level where irrigation is applied. Second, the irrigation area level, where the field level losses are aggregated, or up-scaled, using average loss functions. In this up-scaling approach, detailed crop-soil-water modelling can capture the variability of physical parameters (such as soils, crops, water table depth, and management practices) at the field level which are then used to derive loss functions for aggregating losses at higher scales (irrigation area level). This allows potential field-level adaptations and water management changes made by individual farmers to be assessed for impact at the larger irrigation area level. The APSIM farming systems model was used for simulation of crops (wheat, rice, and soybean) and their interaction with the wider system processes at the field level. Given the climate, soil, and management information (sowing, fertilisation, irrigation, and residue management), the model simulates infiltration, the soil moisture profile, plant water uptake, soil evaporation, and deep drainage on a daily basis. Then, by placing the field level analysis in the context of the wider irrigation system or catchment, it is possible to correlate field level interventions (e.g. water savings measures) with water requirements at these higher levels. Application of this method in the Coleambally Irrigation Area in NSW, Australia, demonstrated that an exponential function can describe the relationship between deep drainage losses and the water table depth for different soil, crop, and water table depth combinations. The rate of loss increase (slope of the curve) with the water table depth is higher on lighter (higher intake rates) soils than on heavy soils and is more pronounced in areas under rice cultivation. We also demonstratethat this analysis technique can assist in identifying spatial distribution of losses in irrigation areas, considering water table depth as an additional factor, leading to targeted areas for water-saving measures.