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Sustainability 2018, 10(9), 3209; https://doi.org/10.3390/su10093209

Comparing the Hydrological Responses of Conceptual and Process-Based Models with Varying Rain Gauge Density and Distribution

1
State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300072, China
2
State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China
3
Science and Technology Innovation Center for Smart Water, Northeastern University, Shenyang 110819, China
4
Department of Information Management, Peking University, Beijing 100871, China
5
Institute of Ocean Research, Peking University, Beijing 100871, China
*
Author to whom correspondence should be addressed.
Received: 23 August 2018 / Revised: 3 September 2018 / Accepted: 5 September 2018 / Published: 7 September 2018
(This article belongs to the Special Issue Impacts of Climate Change on Hydrology, Water Quality and Ecology)
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Abstract

Precipitation provides the most crucial input for hydrological modeling. However, rain gauge networks, the most common precipitation measurement mechanisms, are sometimes sparse and inadequately distributed in practice, resulting in an imperfect representation of rainfall spatial variability. The objective of this study is to analyze the sensitivity of different model structures to the different density and distribution of rain gauges and evaluate their reliability and robustness. Based on a rain gauge network of 20 gauges in the Jinjiang River Basin, south-eastern China, this study compared the performance of two conceptual models (the hydrologic model (HYMOD) and Xinanjiang) and one process-based distributed model (the water and energy transfer between soil, plants and atmosphere model (WetSpa)) with different rain gauge distributions. The results show that the average accuracy for the three models is generally stable as the number of rain gauges decreases but is sensitive to changes in the network distribution. HYMOD has the highest calibration uncertainty, followed by Xinanjiang and WetSpa. Differing model responses are consistent with changes in network distribution, while calibration uncertainties are more related to model structures. View Full-Text
Keywords: rainfall-runoff modeling; rainfall; rain gauge network; sensitivity analysis rainfall-runoff modeling; rainfall; rain gauge network; sensitivity analysis
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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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Yin, Z.; Liao, W.; Lei, X.; Wang, H.; Wang, R. Comparing the Hydrological Responses of Conceptual and Process-Based Models with Varying Rain Gauge Density and Distribution. Sustainability 2018, 10, 3209.

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