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The Spatiotemporal Distribution of Flash Floods and Analysis of Partition Driving Forces in Yunnan Province

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  • Junnan Xiong

    (School of Civil Engineering and Architecture, Southwest Petroleum University, Chengdu 610500, China)

  • Chongchong Ye

    (School of Civil Engineering and Architecture, Southwest Petroleum University, Chengdu 610500, China)

  • Weiming Cheng

    (State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China)

  • Liang Guo

    (China Institute of Water Resources and Hydropower Research, Beijing 100038, China)

  • Chenghu Zhou

    (State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China)

  • Xiaolei Zhang

    (China Institute of Water Resources and Hydropower Research, Beijing 100038, China)

Abstract

Flash floods are one of the most serious natural disasters, and have a significant impact on economic development. In this study, we employed the spatiotemporal analysis method to measure the spatial–temporal distribution of flash floods and examined the relationship between flash floods and driving factors in different subregions of landcover. Furthermore, we analyzed the response of flash floods on the economic development by sensitivity analysis. The results indicated that the number of flash floods occurring annually increased gradually from 1949 to 2015, and regions with a high quantity of flash floods were concentrated in Zhaotong, Qujing, Kunming, Yuxi, Chuxiong, Dali, and Baoshan. Specifically, precipitation and elevation had a more significant effect on flash floods in the settlement than in other subregions, with a high r (Pearson’s correlation coefficient) value of 0.675, 0.674, 0.593, 0.519, and 0.395 for the 10 min precipitation in 20-year return period, elevation, 60 min precipitation in 20-year return period, 24 h precipitation in 20-year return period, and 6 h precipitation in 20-year return period, respectively. The sensitivity analysis showed that the Kunming had the highest sensitivity ( S = 21.86) during 2000–2005. Based on the research results, we should focus on heavy precipitation events for flash flood prevention and forecasting in the short term; but human activities and ecosystem vulnerability should be controlled over the long term.

Suggested Citation

  • Junnan Xiong & Chongchong Ye & Weiming Cheng & Liang Guo & Chenghu Zhou & Xiaolei Zhang, 2019. "The Spatiotemporal Distribution of Flash Floods and Analysis of Partition Driving Forces in Yunnan Province," Sustainability, MDPI, vol. 11(10), pages 1-18, May.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:10:p:2926-:d:233572
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    2. Junnan Xiong & Wei Li & Hao Zhang & Weiming Cheng & Chongchong Ye & Yunliang Zhao, 2019. "Selected Environmental Assessment Model and Spatial Analysis Method to Explain Correlations in Environmental and Socio-Economic Data with Possible Application for Explaining the State of the Ecosystem," Sustainability, MDPI, vol. 11(17), pages 1-26, September.
    3. Hariklia D. Skilodimou & George D. Bathrellos, 2021. "Natural and Technological Hazards in Urban Areas: Assessment, Planning and Solutions," Sustainability, MDPI, vol. 13(15), pages 1-5, July.
    4. Zhiwei Yong & Junnan Xiong & Zegen Wang & Weiming Cheng & Jiawei Yang & Quan Pang, 2021. "Relationship of extreme precipitation, surface air temperature, and dew point temperature across the Tibetan Plateau," Climatic Change, Springer, vol. 165(1), pages 1-22, March.
    5. Junnan Xiong & Chongchong Ye & Tiancai Zhou & Weiming Cheng, 2019. "Health Risk and Resilience Assessment with Respect to the Main Air Pollutants in Sichuan," IJERPH, MDPI, vol. 16(15), pages 1-19, August.

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