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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 22, issue 2 | Copyright
Hydrol. Earth Syst. Sci., 22, 1299-1315, 2018
https://doi.org/10.5194/hess-22-1299-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 20 Feb 2018

Research article | 20 Feb 2018

Combining satellite data and appropriate objective functions for improved spatial pattern performance of a distributed hydrologic model

Mehmet C. Demirel et al.
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Cited articles
Allen, R. G., Pereira, L. S., Raes, D., and Smith, M.: Crop Evapotranspiration – Guidelines for Computing Crop Water Requirements, FAO Irrigation and drainage paper 56, http://www.fao.org/docrep/x0490e/x0490e00.htm (last access: 16 February 2018), 1998.
Berezowski, T., Nossent, J., Chormański, J., and Batelaan, O.: Spatial sensitivity analysis of snow cover data in a distributed rainfall-runoff model, Hydrol. Earth Syst. Sci., 19, 1887–1904, https://doi.org/10.5194/hess-19-1887-2015, 2015.
Beven, K. and Freer, J.: Equifinality, data assimilation, and uncertainty estimation in mechanistic modelling of complex environmental systems using the GLUE methodology, J. Hydrol., 249, 11–29, https://doi.org/10.1016/S0022-1694(01)00421-8, 2001.
Campolongo, F., Cariboni, J., and Saltelli, A.: An effective screening design for sensitivity analysis of large models, Environ. Model. Softw., 22, 1509–1518, https://doi.org/10.1016/j.envsoft.2006.10.004, 2007.
Chen, J. M., Chen, X., Ju, W., and Geng, X.: Distributed hydrological model for mapping evapotranspiration using remote sensing inputs, J. Hydrol., 305, 15–39, https://doi.org/10.1016/j.jhydrol.2004.08.029, 2005.
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Short summary
Satellite data offer great opportunities to improve spatial model predictions by means of spatially oriented model evaluations. In this study, satellite images are used to observe spatial patterns of evapotranspiration at the land surface. These spatial patterns are utilized in combination with streamflow observations in a model calibration framework including a novel spatial performance metric tailored to target the spatial pattern performance of a catchment-scale hydrological model.
Satellite data offer great opportunities to improve spatial model predictions by means of...
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