Combining remote sensing and hydrological models to enhance spatial and temporal variability

The development of water saving measures requires a thorough understanding of the water balance at a high spatial and temporal resolution. Remote sensing is strong in producing information at a high spatial scale, while simulation models are strong in producing water balance estimates at a high temporal resolution. Actual evapotranspiration for an irrigated area in western Turkey was calculated using the SEBAL remote sensing land algorithm using two Landsat images. The hydrological model SWAP was set up to simulate the water balance for the same area, assuming a certain distribution in soil properties., planting dates, and irrigation practices. A comparison between evapotranspiration determined from SEBAL and from SWAP was made, and differences were minimized by adapting the stochastic input in planting date and irrigation practice. The optimized stochastic input data for SWAP was used to simulate all terms of the water balance for the entire irrigation scheme.