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

Abstract

Ecohydrological modeling 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 this gap, but require novel methodologies to exploit their spatiotemporal information that could potentially be incorporated into model calibration and validation frameworks.The present study tackles this problem by suggesting an automatic calibration procedure, based on the empirical orthogonal function, for distributed ecohydrological daily models. The procedure is tested with the support of remote sensing data in a data-scarce environment-the upper Ewaso Ngiro river basin in Kenya. In the present application, the TETIS-VEG model is calibrated using only NDVI (Normalized Difference Vegetation Index) data derived from MODIS. The results demonstrate that (1) satellite data of vegetation dynamics can be used to calibrate and validate ecohydrological models in water-controlled and datascarce regions, (2) the model calibrated using only satellite data is able to reproduce both the spatio-temporal vegetation dynamics and the observed discharge at the outlet and (3) the proposed automatic calibration methodology works satisfactorily and it allows for a straightforward incorporation of spatio-temporal data into the calibration and validation framework of a model.

Published in

Hydrology and Earth System Sciences
2017, Volume: 21, number: 12, pages: 6235-6251 Publisher: COPERNICUS GESELLSCHAFT MBH

SLU Authors

• Ruiz-Pérez, Guiomar

  • Department of Crop Production Ecology, Swedish University of Agricultural Sciences
    
  • Polytechnic University of Valencia

Sustainable Development Goals

SDG17 Partnerships for the goals


UKÄ Subject classification

Oceanography, Hydrology, Water Resources
Ecology


Publication identifier

DOI: https://doi.org/10.5194/hess-21-6235-2017

Permanent link to this page (URI)

https://res.slu.se/id/publ/93299