Remote sensing–based soil water balance for irrigation water accounting at plot and water user association management scale

Abstract Irrigation water accounting (IWA) plays a key role in irrigation management in arid or semi-arid environments. Currently, water managers perform IWA through indirect or direct measurements such as statistical methods or flow meters. However, they have a high maintenance cost and great efforts must be done when large irrigated areas must be covered. The presented framework based on the dual crop coefficient FAO56 methodology introduces an operative application of a Remote Sensing-based Soil Water Balance (RS-SWB) to obtain a Remote Sensing-based Irrigation Water Accounting (RS-IWA). A basic input of the model is the time series of basal crop coefficient and fractional vegetation cover. It has been implemented in a large water user association (100,000 ha) along three years (2010−2012). The results are analysed from the perspective of two water management scales: the plot and the water user association. At plot scale, the RS-IWA of maize and wheat, as primary crops irrigated on demand, show a root square mean error (RMSE) of about 12 % compared with the records from local farmers. At water user association management scale, the results from RS-IWA show an RMSE of about 15 % for a comprehensive range of irrigated crops group such as spring crops, summer crops, double harvest, alfalfa, and vineyards. Hence, RS-IWA based on RS-SWB offers reproducible and reliable mapped estimations that can be used for different water managers, as they are being required from actual agro-environmental laws that are pushing these actors to better knowledge in time and space of those water resources applied.