Research on meteorological thresholds of drought and flood disaster: a case study in the Huai River Basin, China

Gao, Chao; Zhang, Zhengtao; Zhai, Jun; Liu, Qing; Mengting, Yao

doi:10.1007/s00477-014-0951-y

Cited by 36 publications

(19 citation statements)

References 15 publications

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“…From 1981 to 2005, the waterlogging occurred with a frequency of about 2.5 years in Jianghuai plain area of Anhui Province and caused about 10% loss of winter wheat production. In severe waterlogging years, e.g., 1985, 1991, 1998, 2003, and 2005, more than 20% winter wheat yield losses were observed [17,18] . Therefore, it is of critical importance to gain more thorough understanding about the prone environment and risk of waterlogging in this region.…”

Section: Introductionmentioning

confidence: 99%

Waterlogging risk assessment for winter wheat using multi-source data in the middle and lower reaches of Yangtze River

Chen¹,

Huang²,

Song³

et al. 2018

International Journal of Agricultural and Biological Engineering

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Waterlogging is a serious agro-meteorological disaster caused by excessive soil water, which usually causes tremendous crop yield losses. The region of middle and lower reaches of Yangtze River in China is an important production base of winter wheat, and is an area prone to waterlogging. The risk assessment of winter wheat waterlogging can provide more thorough understanding about the risk-prone environment related with food safety in this region. This study combined a variety of environmental and agricultural factors and assessed the waterlogging risk of winter wheat from the aspects of sensitivity of hazard formative environments, hazard risk, and vulnerability of hazard-affected body using multi-source data. Furthermore, it constructed a compound waterlogging risk assessment model to classify the study area into high, relatively high, moderate, and low risky areas, respectively. The results showed that the proposed model could more comprehensively reflect the occurrence mechanism of winter wheat waterlogging by synchronizing geographical, agricultural, and meteorological factors. The waterlogging regionalization based on the model could reasonably represent the spatial distribution and differentiate regional characteristics of winter wheat waterlogging in the study area. et al. Waterlogging risk assessment for winter wheat using multi-source data in the middle and lower reaches of Yangtze River. Int J Agric & Biol Eng, 2018; 11(5): 198-205.

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Section: Introductionmentioning

confidence: 99%

Waterlogging risk assessment for winter wheat using multi-source data in the middle and lower reaches of Yangtze River

Chen¹,

Huang²,

Song³

et al. 2018

International Journal of Agricultural and Biological Engineering

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“…In this way, we could determine the optimal DDPT that is most likely to cause disaster loss from a practical point of view, namely, the threshold of disaster-triggering precipitation, i.e., the DDPT. In addition, the current research on the DDPT in China mainly focuses on a small-scale range of regions and basins [31][32][33][34][35][36][37].To improve these imperfections, there are two main aims of this study: (1) To explore the disaster-triggering threshold of extreme precipitation in the mainland of China from an economic loss perspective, and (2) to comprehensively analyze the spatial landscape and statistical characteristics of the DDPT across China at regional and provincial scales (see Figure 1). Therefore, based on the daily gridded observational precipitation dataset and rainstorm and flood disaster direct economic losses (DELs) (2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012) in the mainland of China, this study established a large number of threshold combinations by combining the fixed threshold method and percentile method, which are commonly used to determine the disaster-triggering precipitation threshold value.…”

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confidence: 99%

Daily Precipitation Threshold for Rainstorm and Flood Disaster in the Mainland of China: An Economic Loss Perspective

Liu

Tang

et al. 2020

Preprint

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Exploring precipitation threshold from an economic loss perspective is critical for rainstorm and flood disaster risk assessment under climate change. Based on the daily gridded precipitation dataset and direct economic losses (DELs) of rainstorm and flood disasters in the mainland of China, this paper first filtered a relatively reasonable disaster-triggering daily precipitation threshold (DDPT) combination according to the relationship between extreme precipitation days and direct economic loss (DEL) rates at province level and then comprehensively analyzed the spatial landscape of DDPT across China. The results show that (1) the daily precipitation determined by the combination of a 10 mm fixed threshold and 99.3th percentile is recognized as the optimal DDPT of rainstorm and flood disasters, and the correlation coefficient between annual extreme precipitation days and DEL rates reached 0.45 (p < 0.01).(2) The optimal DDPT decreases from southeast (up to 87 mm) to northwest (10 mm) across China, and the DDPTs of 7 out of 31 provinces are lower than 25 mm, while 5 provinces are higher than 50 mm on average. These results suggest that DDPTs exist with large spatial heterogeneity across China, and adopting regional differentiated DDPT is helpful for conducting effective disaster risk analysis.Sustainability 2020, 12, 407 2 of 14 (DDPT) [15]. Currently, there is no uniform threshold standard for the determination of extreme precipitation events [16]. There are various methods for determining the extreme precipitation globally, including fixed threshold method, parametric method, non-parametric method, and detrended fluctuation analysis method [14][15][16][17][18]. The fixed threshold method uses an absolute daily precipitation intensity as the critical value of the region [14]. For example, precipitation exceeding 50 mm over 24 h is usually defined as extreme precipitation in China [16,19]. This method is suitable for small-scale areas and has strong subjectivity and experience [20][21][22].The most commonly used nonparametric method is the percentile method, which ranks the amount of precipitation over a certain period of time and selects a certain percentile daily precipitation value as the extreme precipitation criterion for the region [23]. The percentiles selected varied from study to study. Zhai et al. [24] considered the 95th percentile of all rain days during 1961-1990 as the criterion for judging extreme precipitation events. Beniston et al. [25] and Pielke et al.[2] regarded 90th percentile of the observed precipitation data as a standard of extreme precipitation events. This method is suitable for the definition and comparison of extreme precipitation events in different regions [26,27]. Parametric methods include probabilistic analysis [28], the peak over threshold (POT) method [16], the generalized extreme value distribution (GEV) method [29]. These parametric methods depend on the size of the data series and the probability distribution, which could greatly affect the results [22].As a key criterion...

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“…Drought occurred for more than eight times from 1959 to 2001. 24 Therefore, the probability occurrence of the flood is greater than droughts in the River Basin. Drought is occurred due to less amount of precipitation over few months or more.…”

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confidence: 99%

“…In drought years especially agricultural lands are affected by water shortage. 24 Water resources infrastructures were built to control the frequency of flood and drought disaster. In the river basin the problem is not only the quantity of water, currently water quality also the important issue.…”

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Overview of Prominent Problems in Huai River Basin, China

Gebeyehu

Zhao

Zhou

et al. 2018

IJH

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Research on meteorological thresholds of drought and flood disaster: a case study in the Huai River Basin, China

Cited by 36 publications

References 15 publications

Waterlogging risk assessment for winter wheat using multi-source data in the middle and lower reaches of Yangtze River

Waterlogging risk assessment for winter wheat using multi-source data in the middle and lower reaches of Yangtze River

Daily Precipitation Threshold for Rainstorm and Flood Disaster in the Mainland of China: An Economic Loss Perspective

Overview of Prominent Problems in Huai River Basin, China

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