Exploring the potential of five satellite-derived soil moisture products for simulating long-term irrigation datasets using the SM Delta approach

Abstract

Irrigation accounts for approximately 70 % of global freshwater withdrawals, significantly impacting the water cycle through reduced streamflow and groundwater tables and increased evapotranspiration. Accurate long-term estimates of irrigation water use (IWU) are essential for improving climate model simulations. However, in situ irrigation data are extremely rare on a global scale, and statistical surveys, as well as irrigation simulated by models, are too uncertain to provide reliable estimates. Satellite-derived soil moisture (SM) data offer a promising alternative approach for monitoring long-term IWU globally.This thesis builds on the Soil Moisture (SM) Delta method, which estimates IWU by calculating the differences between satellite and modeled SM data. The approach is based on the fact that satellite-based SM theoretically contains an irrigation signal, whereas model-based SM lacks such a signal if irrigation is not modeled. The methodology is used to assess the ability of five satellite-based SM products to retrieve long-term irrigation estimates. 15-year IWU datasets have been produced over the Ebro Basin (86,000 km2) and the Murray-Darling Basin (1,000,000 km2) using coarse-scale (0.25°) SM data, and validated against in situ IWU data from an irrigation district in the Ebro Basin and four irrigation districts in the Murray-Darling Basin.Validation of the IWU estimates against in situ IWU data from the irrigation district in the Ebro Basin showed a significant correlation when using the ESA CCI COMBINED product (R=0.75), which also yielded the lowest Root Mean Square Deviation (RMSD=22.84 mm/month), showing the best performance over this basin. In the Murray-Darling Basin, validation results varied among the four irrigation districts, with ESA CCI ACTIVE performing best in three irrigation districts (R=0.40, RMSD=21.84, bias=4.01 mm/month on average) and ESA CCI PASSIVE in one district (R=0.64, RMSD=19.70 mm/month, bias=0.83 mm/month). In terms of overall performance, ESA CCI COMBINED proved to be the most reliable product with a good balance between low RMSD (22.01 mm/month on average) and the highest correlation (R=0.45 on average) in the four irrigation districts.All products show an underestimation of IWU in the Ebro Basin, which could be improved by including evapotranspiration in the algorithm. Furthermore, when compared with studies obtaining high-resolution IWU estimates, our coarse-resolution method performed comparably well in the Ebro Basin. These large-scale, long-term IWU datasets are an important step towards better accounting for the impacts of irrigation in climatic and hydrological modeling and can improve water resource management.