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Constraining Conceptual Hydrological Models With Multiple Information Sources

Nijzink, R. C., Almeida, S., Pechlivanidis, I. G., Capell, R., Gustafssons, D., Arheimer, B., Parajka, J., Freer, J., Han, D., Wagener, T., van Nooijen, R. R. P., Savenije, H. H. G., and Hrachowitz, M., 2018. Constraining Conceptual Hydrological Models With Multiple Information Sources. Water Resources Research, 54(10):8332–8362, doi:10.1029/2017WR021895.

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@ARTICLE{2018WRR....54.8332N,
       author = {{Nijzink}, R.~C. and {Almeida}, S. and {Pechlivanidis}, I.~G. and {Capell}, R. and {Gustafssons}, D. and {Arheimer}, B. and {Parajka}, J. and {Freer}, J. and {Han}, D. and {Wagener}, T. and {van Nooijen}, R.~R.~P. and {Savenije}, H.~H.~G. and {Hrachowitz}, M.},
        title = "{Constraining Conceptual Hydrological Models With Multiple Information Sources}",
      journal = {Water Resources Research},
     keywords = {hydrological modeling, calibration, remote sensing, parameter estimation},
         year = 2018,
        month = oct,
       volume = {54},
       number = {10},
        pages = {8332-8362},
     abstract = "{The calibration of hydrological models without streamflow observations
        is problematic, and the simultaneous, combined use of remotely
        sensed products for this purpose has not been exhaustively
        tested thus far. Our hypothesis is that the combined use of
        products can (1) reduce the parameter search space and (2)
        improve the representation of internal model dynamics and
        hydrological signatures. Five different conceptual hydrological
        models were applied to 27 catchments across Europe. A parameter
        selection process, similar to a likelihood weighting procedure,
        was applied for 1,023 possible combinations of 10 different data
        sources, ranging from using 1 to all 10 of these products.
        Distances between the two empirical distributions of model
        performance metrics with and without using a specific product
        were determined to assess the added value of a specific product.
        In a similar way, the performance of the models to reproduce 27
        hydrological signatures was evaluated relative to the
        unconstrained model. Significant reductions in the parameter
        space were obtained when combinations included Advanced
        Microwave Scanning Radiometer - Earth Observing System and
        Advanced Scatterometer soil moisture, Gravity Recovery and
        Climate Experiment total water storage anomalies, and, in snow-
        dominated catchments, the Moderate Resolution Imaging
        Spectroradiometer snow cover products. The evaporation products
        of Land Surface Analysis - Satellite Application Facility and
        MOD16 were less effective for deriving meaningful, well-
        constrained posterior parameter distributions. The hydrological
        signature analysis indicated that most models profited from
        constraining with an increasing number of data sources.
        Concluding, constraining models with multiple data sources
        simultaneously was shown to be valuable for at least four of the
        five hydrological models to determine model parameters in
        absence of streamflow.}",
          doi = {10.1029/2017WR021895},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2018WRR....54.8332N},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

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