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

Ecohydrological models provide a tool to investigate the mutual relationships between vegetation and the hydrological cycle. Ecohydrological modelling studies in developing countries, such as sub-saharan Africa often face the problem of extensive parametrical requirements and limited available data. Satellite remote sensing data may be able to fill 15 this gap, but require novel methodologies to exploit its spatio-temporal information that could potentially be incorporated in ecohydrological model calibration and validation. The present study aims to implement a distributed ecohydrological daily model in a data scarce environment with the support of remote sensing data. An automatic calibration procedure, based on Empirical Orthogonal Functions techniques, is proposed and applied in the Upper Ewaso river basin in Kenya. The model is calibrated only using NDVI (Normalized Difference 20 Vegetation Index) data derived from MODIS. The obtained results demonstrate that: (1) satellite data of vegetation dynamics contains an extraordinary amount of information that can be used to implement ecohydrological models in scarce data dry regions; (2) the model calibrated only using satellite data is able to reproduce both the spatio-temporal vegetation dynamics and the observed discharge at the outlet point; and (3) the proposed semi-automatic calibration methodology works satisfactorily and it allows to incorporate spatio-temporal data in the model parametrization. 25