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Ecohydrological modeling studies in developing countries, such as\udsub-Saharan Africa, often face the problem of extensive parametrical\udrequirements and limited available data. Satellite remote sensing data may be\udable to fill this gap, but require novel methodologies to exploit their\udspatio-temporal information that could potentially be incorporated into model\udcalibration and validation frameworks.\ud  \udThe present study tackles this problem by suggesting an automatic calibration\udprocedure, based on the empirical orthogonal function, for\uddistributed ecohydrological daily models. The procedure is tested with the\udsupport of remote sensing data in a data-scarce environment – the upper\udEwaso Ngiro river basin in Kenya. In the present application, the TETIS-VEG model\udis calibrated using only NDVI (Normalized Difference Vegetation Index) data\udderived from MODIS. The results demonstrate that (1) satellite data of\udvegetation dynamics can be used to calibrate and validate ecohydrological\udmodels in water-controlled and data-scarce regions, (2) the model calibrated\udusing only satellite data is able to reproduce both the spatio-temporal\udvegetation dynamics and the observed discharge at the outlet and (3) the\udproposed automatic calibration methodology works satisfactorily and it allows\udfor a straightforward incorporation of spatio-temporal data into the\udcalibration and validation framework of a model

hydrology and earth system sciences

Calibration of a parsimonious distributed ecohydrological daily model in a data-scarce basin by exclusively using the spatio-temporal variation of NDVI