Effects of drought and flood on crop production in China across 1949–2015: spatial heterogeneity analysis with Bayesian hierarchical modeling

Chen, Huili; Liang, Zhongyao; Liu, Yong; Jiang, Qingsong; Xie, Shuguang

doi:10.1007/s11069-018-3216-0

Cited by 44 publications

(18 citation statements)

References 64 publications

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“…In contrast, states in the southern US still showed positive yield even under extreme rainfall conditions. The similar mixture of negative and positive yield responses was reported in China (Chen, Liang, Liang, Liu, & Xie, ; Chen, Liang, Liu, Jiang, & Xie, ), suggesting the complexity of excessive rainfall whose impact on crop yield varies in sign.…”

Section: Resultssupporting

confidence: 72%

Excessive rainfall leads to maize yield loss of a comparable magnitude to extreme drought in the United States

Guan

Schnitkey

et al. 2019

Global Change Biology

383

251

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Increasing drought and extreme rainfall are major threats to maize production in the United States. However, compared to drought impact, the impact of excessive rainfall on crop yield remains unresolved. Here, we present observational evidence from crop yield and insurance data that excessive rainfall can reduce maize yield up to −34% (−17 ± 3% on average) in the United States relative to the expected yield from the long‐term trend, comparable to the up to −37% loss by extreme drought (−32 ± 2% on average) from 1981 to 2016. Drought consistently decreases maize yield due to water deficiency and concurrent heat, with greater yield loss for rainfed maize in wetter areas. Excessive rainfall can have either negative or positive impact on crop yield, and its sign varies regionally. Excessive rainfall decreases maize yield significantly in cooler areas in conjunction with poorly drained soils, and such yield loss gets exacerbated under the condition of high preseason soil water storage. Current process‐based crop models cannot capture the yield loss from excessive rainfall and overestimate yield under wet conditions. Our results highlight the need for improved understanding and modeling of the excessive rainfall impact on crop yield.

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Section: Resultssupporting

confidence: 72%

Excessive rainfall leads to maize yield loss of a comparable magnitude to extreme drought in the United States

Guan

Schnitkey

et al. 2019

Global Change Biology

383

251

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show abstract

“…In addition, the comparison of influence patterns between lower vulnerability (low and moderate vulnerabilities) and higher vulnerability in the above synergistic method shows that their difference is that the lower vulnerability arises with the higher attribute value strength of A * . This is because the indexes reflecting irrigation capacity, water-saving technology and economic level are conducive to reducing the sensitivity of agricultural system and increasing the adaptability to drought (Pei et al, 2016;Chen et al, 2018).…”

Section: Note(s)mentioning

confidence: 99%

Identifying influence patterns of regional agricultural drought vulnerability using a two-phased grey rough combined model

Sun

Fang

Dang

et al. 2020

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PurposeA core challenge of assessing regional agricultural drought vulnerability (RADV) is to reveal what vulnerability factors, under which kinds of synergistic combinations and at what strengths, will lead to higher vulnerability: namely, the influence patterns of RADV.Design/methodology/approachA two-phased grey rough combined model is proposed to identify influence patterns of RADV from a new perspective of learning and mining historical cases. The grey entropy weight clustering with double base points is proposed to assess degrees of RADV. The simplest decision rules that reflect the complex synergistic relationships between RADV and its influencing factors are extracted using the rough set approach.FindingsThe results exemplified by China's Henan Province in the years 2008–2016 show higher degrees of RADV in the north and west regions of the province, in comparison with the south and east. In the patterns with higher RADV, the higher proportion of agricultural population appears in all decision rules as a core feature. A smaller quantity of water resources per unit of cultivated land area and a lower adaptive capacity, involving levels of irrigation technology and economic development, present a significant synergistic influence relationship that distinguishes the features of higher vulnerability from those of the lower.Originality/valueThe proposed grey rough combined model not only evaluates temporal dynamics and spatial differences of RADV but also extracts the decision rules between RADV and its influencing factors. The identified influence patterns inspire managerial implications for preventing and reducing agricultural drought through its historical evolution and formation mechanism.

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“…Optimal water resource and risk management that mitigates drought and flood impacts, e.g. on navigation or crop production, is often only possible when considering both extremes (Chen et al 2018, Duviella et al 2018). In addition, research on floods and droughts has largely been done separately, while both research fields could benefit from each other with regard to monitoring and forecasting approaches, assessment methods and analytical tools.…”

Section: Introductionmentioning

confidence: 99%

“…For instance, Duviella et al (2018) proposed an adaptive allocation planning of water resources under consideration of droughts and floods to effectively mitigate negative impacts on navigation. Also, for effective risk management in the agricultural sector, it is important to understand and quantify the influence of drought and floods on crop production (Chen et al 2018). With the aim of creating water-sensitive and resilient cities, Rodriguez et al (2014) developed a framework and specific guidance for maximizing the value and use of water in urban areas and considering drought and flood resilience.…”

Section: Introductionmentioning

confidence: 99%

How to improve attribution of changes in drought and flood impacts

Kreibich

Blauhut

Aerts

et al. 2019

Hydrological Sciences Journal

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For the development of sustainable, efficient risk management strategies for the hydrological extremes of droughts and floods, it is essential to understand the temporal changes of impacts, and their respective causes and interactions. In particular, little is known about changes in vulnerability and their influence on drought and flood impacts. We present a fictitious dialogue between two experts, one in droughts and the other in floods, showing that the main obstacles to scientific advancement in this area are both a lack of data and a lack of commonly accepted approaches. The drought and flood experts "discuss" available data and methods and we suggest a complementary approach. This approach consists of collecting a large number of single or multiple paired-event case studies from catchments around the world, undertaking detailed analyses of changes in impacts and drivers, and carrying out a comparative analysis. The advantages of this approach are that it allows detailed context-and location-specific assessments based on the paired-event analyses, and reveals general, transferable conclusions based on the comparative analysis of various case studies. Additionally, it is quite flexible in terms of data and can accommodate differences between floods and droughts.

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Effects of drought and flood on crop production in China across 1949–2015: spatial heterogeneity analysis with Bayesian hierarchical modeling

Cited by 44 publications

References 64 publications

Excessive rainfall leads to maize yield loss of a comparable magnitude to extreme drought in the United States

Excessive rainfall leads to maize yield loss of a comparable magnitude to extreme drought in the United States

Identifying influence patterns of regional agricultural drought vulnerability using a two-phased grey rough combined model

How to improve attribution of changes in drought and flood impacts

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