The Journal of Hydrology features a publication by members of the project team InoCottonGROW. The article "Spatially distributed model calibration of a highly managed hydrological system using remote-sensing-derived ET data" deals with the challenge of calibrating a spatially distributed hydrological model that meets the local specifics of a heavily used agricultural region.
The special feature of the study region is that the majority of the hydrological system is determined by anthropogenic influences, for example in the form of irrigated agriculture with man-made canals. The researchers have therefore calibrated a Soil and Water Assessment Tool (SWAT) for the entire meso scale of the irrigation system. Both the global Dynamically Dimensioned Search Algorithm (DDS) and the Kling-Gupta Efficiency (KGE) were used as objective functions. To account for spatio-temporal heterogeneity in local water flows, evapotranspiration estimates (ET) generated by remote sensing were used.
However, the results thus obtained were still unsatisfactory with regard to the spatial distribution in the study area, since the area is mainly characterized by small-scale and diverse agricultural structures. The ET product was therefore modified to include land-use type-dependent ET characteristics, ultimately enabling better calibration.
The accepted manuscript of the authors Rike Becker, Akash Koppa, Stephan Schulz, Muhammad Usman, Tim from the Beek and Christoph Schüth is already available online here and is currently in print.