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Water 2018, 10(9), 1188; https://doi.org/10.3390/w10091188

Spatial Pattern Oriented Multicriteria Sensitivity Analysis of a Distributed Hydrologic Model

1
Geological Survey of Denmark and Greenland, Øster Voldgade 10, 1350 Copenhagen, Denmark
2
Department of Civil Engineering, Istanbul Technical University, Maslak, 34469 Istanbul, Turkey
3
Department of Environmental Engineering, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark
*
Authors to whom correspondence should be addressed.
Received: 10 August 2018 / Revised: 29 August 2018 / Accepted: 1 September 2018 / Published: 4 September 2018
(This article belongs to the Special Issue Hydrologic Modelling for Water Resources and River Basin Management)
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Abstract

Hydrologic models are conventionally constrained and evaluated using point measurements of streamflow, which represent an aggregated catchment measure. As a consequence of this single objective focus, model parametrization and model parameter sensitivity typically do not reflect other aspects of catchment behavior. Specifically for distributed models, the spatial pattern aspect is often overlooked. Our paper examines the utility of multiple performance measures in a spatial sensitivity analysis framework to determine the key parameters governing the spatial variability of predicted actual evapotranspiration (AET). The Latin hypercube one-at-a-time (LHS-OAT) sampling strategy with multiple initial parameter sets was applied using the mesoscale hydrologic model (mHM) and a total of 17 model parameters were identified as sensitive. The results indicate different parameter sensitivities for different performance measures focusing on temporal hydrograph dynamics and spatial variability of actual evapotranspiration. While spatial patterns were found to be sensitive to vegetation parameters, streamflow dynamics were sensitive to pedo-transfer function (PTF) parameters. Above all, our results show that behavioral model definitions based only on streamflow metrics in the generalized likelihood uncertainty estimation (GLUE) type methods require reformulation by incorporating spatial patterns into the definition of threshold values to reveal robust hydrologic behavior in the analysis. View Full-Text
Keywords: mHM; remote sensing; spatial pattern; sensitivity analysis; GLUE; actual evapotranspiration mHM; remote sensing; spatial pattern; sensitivity analysis; GLUE; actual evapotranspiration
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Demirel, M.C.; Koch, J.; Mendiguren, G.; Stisen, S. Spatial Pattern Oriented Multicriteria Sensitivity Analysis of a Distributed Hydrologic Model. Water 2018, 10, 1188.

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