“The 20 July 2021 Major Flood Event” in Greater Zhengzhou, China: A Case Study of Flooding Severity and Landscape Characteristics

Yanbo Duan, Yu Gary Gao, Yusen Zhang, Huawei Li, Zhonghui Li, Ziying Zhou, Guohang Tian () and Yakai Lei ()
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Yanbo Duan: College of Landscape Architecture and Art, Henan Agricultural University, Zhengzhou 450002, China
Yu Gary Gao: College of Food, Agricultural, and Environmental Sciences South Centers, The Ohio State University, 1864 Shyville Road, Piketon, OH 45661, USA
Yusen Zhang: College of Landscape Architecture and Art, Henan Agricultural University, Zhengzhou 450002, China
Huawei Li: College of Landscape Architecture and Art, Henan Agricultural University, Zhengzhou 450002, China
Zhonghui Li: Henan Water & Power Engineering Consulting Co., Ltd., Zhengzhou 450017, China
Ziying Zhou: College of Landscape Architecture and Art, Henan Agricultural University, Zhengzhou 450002, China
Guohang Tian: College of Landscape Architecture and Art, Henan Agricultural University, Zhengzhou 450002, China
Yakai Lei: College of Landscape Architecture and Art, Henan Agricultural University, Zhengzhou 450002, China

Land, 2022, vol. 11, issue 11, 1-23

Abstract: Climate change and rapid urbanization are two global processes that have significantly aggravated natural disasters, such as drought and flooding. Urbanization without resilient and sustainable planning and execution could lead to undesirable changes in landscapes and stormwater regulation capacity. These changes have exacerbated the effects of extreme climatic events with disastrous consequences in many cities worldwide. Unfortunately, the major storm in Zhengzhou, China on 20 July 2021 was one of these examples. This event provided a rare opportunity to study the key roles of green infrastructures (GI) in mitigating flooding risks in a major urban center after a devasting flood event. Using the data from high-resolution images collected via two satellites, a comprehensive study of the Jialu System in Greater Zhengzhou was conducted to systematically compare how far the river water had reached before and after the 20 July 2021 major storm in order to identify the main weak links in the city’s GI and stormwater management system. A flood inundation intensity index (FI) in the Upper (UJLR), Middle (MJLR), and Lower (LJLR) Regions of the Jialu River System was generated. Bivariate Moran’s I, a correlation coefficient between FI and landscape characteristics, was calculated and used to identify problem areas for future improvements. Our results showed that the MJLR had the severest flooding impacts. LJLR had the biggest change in how far the river water reached after flooding, ranging from 4.59 m to 706.28 m. In UJLR, the percentages of mine, crop land, and green space had the highest global bivariate Moran’s I correlation coefficients. In MJLR, the percentages of vacant land, impervious surfaces, and water body had the highest global bivariate Moran’s I correlation coefficients. In LJLR, the percentages of vacant land, water body, and crop land had the highest global bivariate Moran’s I correlation coefficients. The total percentages of both high landscape characteristics indices-high flood inundation intensity indices and low landscape characteristics indices-high flood inundation intensity indices areas are 12.96%, 13.47%, and 13.80% in UJLR, MJLR, and LJLR, respectively. These land cover composition types identified for each region can be treated as areas of primary focus. However, GeoDector Model (GDM) analyses showed that our eight variables of landscape characteristics were not independent. Hence, a more comprehensive approach integrating all eight variables is still necessary in future flood mitigation efforts.

Keywords: urban climate change; flood; landscape characteristics; green infrastructure (GI); bivariate Moran’s I; remote sensing; urban stormwater management; Greater Zhengzhou (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2022
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