Measuring the past 20 years of urban-rural land growth in flood-prone areas in the developed Taihu Lake watershed, China

Abstract

There is growing interest in using the urban landscape for stormwater management studies, where land patterns and processes can be important controls for the sustainability of urban development and planning. This paper proposes an original index of Major Hazard Oriented Level (MHOL) and investigates the structure distribution, driving factors, and controlling suggestions of urban-rural land growth in flood-prone areas in the Taihu Lake watershed, China. The MHOL of incremental urban-rural land increased from M 31.51 during the years 1985–1995 to M 38.37 during the years 1995–2010 (M for medium structure distribution, and the number for high-hazard value). The index shows that urban-rural land was distributed uniformly in flood hazard levels and tended to move rapidly to high-hazard areas, where 72.68% of incremental urban-rural land was aggregated maximally in new urban districts along the Huning traffic line and the Yangtze River. Thus, the current accelerating growth of new urban districts could account for the ampliative exposure to high-hazard areas. New districts are driven by the powerful link between land financial benefits and political achievements for local governments and the past unsustainable process of “single objective” oriented planning. The correlation categorical analysis of the current development intensity and carrying capacity of hydrological ecosystems for sub-basins was used to determine four types of development areas and provide decision makers with indications on the future watershed-scale subdivision of Major Function Oriented Zoning implemented by the Chinese government.

Keywords

urban-rural land growth / flood-prone areas / major hazard oriented level / major function oriented zoning / Taihu Lake Watershed

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Acknowledgments

We would like to thank Guo Chen at Michigan State University for helpful comments and edits, and Yingbao Yang for advances about the use of SWMM model. This work was supported by the National Natural Science Foundation of China (Grant No. 41571511) and the Program for Frontier Research Issues in Chinese Academy Sciences (No. NIGLAS2012135022).

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2017 Higher Education Press and Springer-Verlag Berlin Heidelberg