Quantifying Irrigation Water Use over Regional Scales with Landsat and Climate Data

Irrigated agriculture has been identified as using approximately 72% of water globally. Australia, like many places in the world, is subject to water sharing plans that cross government boarders and are subject to a mixture of management policies. There is a pressing need to develop a method to monitor irrigation water use to aid in water resource assessments and monitoring. This paper aims to test a previously developed method which monitors irrigation water use using remotely sensed observations over the catchment scale, without the need for in-situ observations, ground data or in‑depth knowledge of crops and their planting dates. Using conservative assumptions about agricultural land management practice, irrigation is calculated as Irr=AET-P. The method tests three vegetation indices derived from Landsat 5/7/8 images to calculate crop coefficients (K_c) based on multiple published relationships. These are combined through the FAO56 methodology using gridded rainfall and two reference evapotranspiration (ET₀) products to find actual evapotranspiration as AET=ET₀xK_c, providing six ET₀-K_c combinations. Validation data is sourced from Irrigation Infrastructure Operators (IIO) from across the Murray-Darling Basin, Australia which are required to record irrigation water deliveries for billing purposes. The majority of these regions are in arid or semi-arid regions. Data periods used in this study range from 2003/04 to 2016/17. Results indicate this method can effectively assess irrigation water use over a range of catchment sizes from ~6,000 to ~600,000 ha. The best results returned a monthly irrigation RMSE ranging from 1.13 to 2.42 mm/month. Issues arise when regions have a designated low water allocation volume for that season (<40%). The allocation percentage is a function of water storage levels, demand and forecasts. Comparisons with the Standardised Precipitation Index (SPI) and Evaporative Stress Index (ESI) show that the proposed method is robust to the rapid onset and short-term droughts. However, its performance was poor during the long term droughts with low water allocation years. The study results during these years has been predominately attributed to water stress in certain crops being undetected, agricultural managers skipping annual crop commodities as well as stock and domestic water use making up larger portions of total water use. This is a limitation of this approach, although when only comparing results in years with greater than 40% allocations, the results improved significantly showing it can monitor water use effectively. When adequate water is available, this approach is able to accurately predict irrigation water use for the sites examined.