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Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 14, issue 2 | Copyright
Nat. Hazards Earth Syst. Sci., 14, 331-346, 2014
https://doi.org/10.5194/nhess-14-331-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 21 Feb 2014

Research article | 21 Feb 2014

Efficient GIS-based model-driven method for flood risk management and its application in central China

Y. Liu1,2,3, J. Zhou1,3, L. Song4, Q. Zou1,3, J. Guo1,3, and Y. Wang5 Y. Liu et al.
  • 1School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan, 430074, China
  • 2School of Electrical and Electronic Engineering, Hubei University ofTechnology, Wuhan, 430068, China
  • 3Hubei Key Laboratory of Digital Valley Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China
  • 4Laboratory of Numerical Modeling Technique for Water Resources, Department of Water Resources and Environment, Pearl River Water Resources Research Institute, Guangzhou, 510623, China
  • 5School of Engineering and Technology, Hubei University of Technology, Wuhan, 430068, China

Abstract. In recent years, an important development in flood management has been the focal shift from flood protection towards flood risk management. This change greatly promoted the progress of flood control research in a multidisciplinary way. Moreover, given the growing complexity and uncertainty in many decision situations of flood risk management, traditional methods, e.g., tight-coupling integration of one or more quantitative models, are not enough to provide decision support for managers. Within this context, this paper presents a beneficial methodological framework to enhance the effectiveness of decision support systems, through the dynamic adaptation of support regarding the needs of the decision-maker. In addition, we illustrate a loose-coupling technical prototype for integrating heterogeneous elements, such as multi-source data, multidisciplinary models, GIS tools and existing systems. The main innovation is the application of model-driven concepts, which put the system in a state of continuous iterative optimization. We define the new system as a model-driven decision support system (MDSS ). Two characteristics that differentiate the MDSS are as follows: (1) it is made accessible to non-technical specialists; and (2) it has a higher level of adaptability and compatibility. Furthermore, the MDSS was employed to manage the flood risk in the Jingjiang flood diversion area, located in central China near the Yangtze River. Compared with traditional solutions, we believe that this model-driven method is efficient, adaptable and flexible, and thus has bright prospects of application for comprehensive flood risk management.

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