Establishment of agricultural drought loss models: A comparison of statistical methods

Zhu, Xiufang; Hou, Chenyao; Xu, Kun; Liu, Ying

doi:10.1016/j.ecolind.2020.106084

Cited by 20 publications

(9 citation statements)

References 47 publications

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“…The yield decomposition method decomposed the crop pure yield into disaster-induced loss and trending yield. However, the trending yield resulted in a huge difference by using different methods (Zhang, 2004;Li et al, 2008;Hu, 2016;Zhang et al, 2018;Zhu et al, 2020;, while the yield reduction apportionment method calculated the disaster-induced grain yield loss according to fixed yield reduction proportions of the areas experiencing different degrees of disasters (Zhang et al, 2009;Gao et al, 2012;Wen et al, 2017;Xiao et al, 2017;Guo et al, 2019;Yu et al, 2019). Based on the harvest yield, this method eliminated differences in crop varieties and disaster resistance of crop at different growth stages (Gong and Zhang, 2010), and it is also used by the Ministry of Agriculture, the Ministry of Civil Affairs, and the National Bureau of Statistics in China.…”

Section: Literature Reviewmentioning

confidence: 99%

Spatial–Temporal Characteristics and Driving Factors of Disaster-Induced Grain Yield Loss in China

Zhao

Deng

Yang

2022

Front. Environ. Sci.

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The current article aimed to characterize the spatial–temporal characteristics and the driving factors of disaster-induced grain yield loss. Taking the world’s largest agricultural country, China, as the research object, this study evaluated China’s disaster-induced grain yield loss from 1978 to 2019 and investigated the contribution of three driving factors, using a logarithmic mean Divisia index (LMDI) approach. The results showed that drought and flood were the main disasters causing grain yield losses in China. China’s grain disaster loss peaked in 2000 and then entered a declining period. In terms of spatial distribution, disaster-induced grain yield loss mainly concentrated in the regions including the Middle-Lower Yangtze region, the Huang-Huai-Hai region, and Northeast China. The gravity center of disaster-induced grain yield loss shifted northward in China. Disaster intensity contributed the most to change in disaster-induced grain yield loss, followed by yield loss density, and the grain planting area. Thus, addressing drought and flood disasters, and enhancing disaster prevention and reduction capacity are critical to reduce disaster-induced grain yield loss, especially in the Middle-Lower Yangtze, the Huang-Huai-Hai region, and Northeast China.

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Section: Literature Reviewmentioning

confidence: 99%

Spatial–Temporal Characteristics and Driving Factors of Disaster-Induced Grain Yield Loss in China

Zhao

Deng

Yang

2022

Front. Environ. Sci.

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“…When using run theory to identify drought and flood events, first, an interception level is given according to the grading standard of drought indicators, and the discrete series changing with time is intercepted. When the disaster index is lower than a certain threshold and the duration exceeds a certain length, a disaster event is considered to have occurred [51]. When the random variable is continuously greater than the interception level one or more times, a positive run occurs, and vice versa, a negative run occurs.…”

Section: Run Theorymentioning

confidence: 99%

Three-Dimensional Vulnerability Assessment of Peanut (Arachis hypogaea) Based on Comprehensive Drought Index and Vulnerability Surface: A Case Study of Shandong Province, China

Wei

Yang

et al. 2022

Remote Sensing

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Agricultural drought is a major problem facing China’s agricultural production. In this study, the cash crop ‘peanut’ was used as an example to explore vulnerability. Through the atmosphere–plant–soil continuum system, a single index that could represent different types of droughts affecting peanuts was selected and weighted using the CRITIC weighting method to construct a multi-source data fusion drought index (MFDI). Then, Pearson correlation analysis between the comprehensive drought index and relative meteorological yield and the Mann–Kendall trend test for different growth periods of peanuts were used to verify MFDI and analyze the variation over time. A three-dimensional vulnerability assessment method of drought intensity–drought duration–yield reduction rate was established based on the run theory and trend surface analysis. The results show that the constructed multi-source data fusion drought index (MFDI) can more accurately characterize the actual drought conditions of peanuts in Shandong Province. The MFDI results showed that the drought severity in the coastal areas of the study area decreased with the growth and development of peanuts, while the drought became more severe in the western and northern parts during the late growth period of peanuts. The vulnerability surface of the drought intensity–drought duration–yield reduction rate showed that when the drought intensity was <0.8 and the duration was <3.5 months, the vulnerability of peanut crops was low, and then with the increase in drought intensity or duration, the vulnerability increased. The impact of drought duration cannot be ignored. In contrast to traditional vulnerability assessment methods, this study established a three-dimensional vulnerability surface, which provides a new approach for agricultural drought vulnerability assessment. The research results are helpful for a deeper understanding of the relationship between drought and crop vulnerability and provide scientific support for local governments in formulating disaster prevention and mitigation policies.

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“…A large number of indices have been developed to quantify and analyze drought [62][63][64]. The SPI [65] and SPEI [66] are two commonly used drought indices with multiscale characteristics that are suitable for different periods and regions [67,68].…”

Section: Drought Indices and Levelsmentioning

confidence: 99%

Impacts of Heat and Drought on Gross Primary Productivity in China

et al. 2021

Self Cite

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Heat and drought stress, which often occur together, are the main environmental factors limiting the survival and growth of vegetation. Studies on the response of gross primary production (GPP) to extreme climate events such as heat and drought are highly significant for the identification of ecologically vulnerable regions, ecological risk assessments, and ecological environmental protection. We got 1982–2017 climatic data from the University of East Anglia Climatic Research Unit, Norwich, England, and GPP data from National Earth System Science Data Sharing Service Platform, Beijing, China. Using Theil–Sen median trend analysis and the Mann–Kendall test, we analyzed trends in temperature and the standardized precipitation/standardized precipitation evapotranspiration indices in the eight vegetation regions of China. Additionally, the response of GPP to the single and combined impacts of heat and drought were analyzed using multidimensional copula functions, and GPP reduction probabilities were estimated under different drought levels and heat intensities. The results showed that the probability of a drastic GPP reduction increases with increasing drought levels and heat intensities. The combined impacts of heat and drought on vegetation productivity is greater than the impacts of either drought or heat alone and presents a nonlinear superposition of the two extremes. The impact of heat on GPP is not evident when the drought level is high. The temperate grassland and warm temperate deciduous broad-leaved forest regions are the most sensitive regions to drought and heat in China. This study provides a scientific basis for the comprehensive evaluation of the risk of GPP reduction under the single and combined impacts of heat stress and drought stress.

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Establishment of agricultural drought loss models: A comparison of statistical methods

Cited by 20 publications

References 47 publications

Spatial–Temporal Characteristics and Driving Factors of Disaster-Induced Grain Yield Loss in China

Spatial–Temporal Characteristics and Driving Factors of Disaster-Induced Grain Yield Loss in China

Three-Dimensional Vulnerability Assessment of Peanut (Arachis hypogaea) Based on Comprehensive Drought Index and Vulnerability Surface: A Case Study of Shandong Province, China

Impacts of Heat and Drought on Gross Primary Productivity in China

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