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| Titel |
Efficient GIS-based model-driven method for flood risk management and its application in central China |
| VerfasserIn |
Y. Liu, J. Zhou, L. Song, Q. Zou, J. Guo, Y. Wang |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1561-8633
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| Digitales Dokument |
URL |
| Erschienen |
In: Natural Hazards and Earth System Sciences ; 14, no. 2 ; Nr. 14, no. 2 (2014-02-21), S.331-346 |
| Datensatznummer |
250118278
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| Publikation (Nr.) |
 copernicus.org/nhess-14-331-2014.pdf |
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| Zusammenfassung |
| 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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