Mapping the Global-Scale Maize Drought Risk Under Climate Change Based on the GEPIC-Vulnerability-Risk Model

Yin, Yuanyuan; Gao, Yuan; Lin, Degen; Wang, Lei; Ma, Weidong; Wang, Jing’ai

doi:10.1007/s13753-021-00349-3

Cited by 12 publications

(4 citation statements)

References 56 publications

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“…In such regions, efficient irrigation management is paramount for optimizing maize production [3]. Furthermore, water scarcity is a pressing issue globally, intensified by factors such as climate change, population growth, and urbanization [4], [5]. As a result, sustainable water management practices in agriculture have become imperative to ensure food security and mitigate the consequences of water shortages.…”

Section: Introductionmentioning

confidence: 99%

Maize production at phenological stages affected by water irrigation stress in dryland conditions

Suriadi,

Syarifinnur,

Mulyati

et al. 2024

IOP Conf. Ser.: Earth Environ. Sci.

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The growth and yield of maize are significantly influenced by the adequacy of soil moisture during the growth period. Given the uncertain rainfall due to climate change, the availability of water for maize production is becoming increasingly limited, while the demand is rising due to population growth. The extent to which maize yield is affected by soil moisture stress at each phenological stage in dryland areas has not been thoroughly explored. This study aimed to determine the production and biomass of maize at various growth stages due to water stress. Watering using drip irrigation equipped with soil moisture sensors was stopped after the maize plants reached 20, 40, 60 (flowering), 80 days after sowing (DAS), and at harvest. Parameters of biomass, maize yield, and other parameters were determined when the soil’s permanent wilting point reached, and soil samples were taken to determine the moisture content. The results showed that irrigation up to 80 DAS was not significantly different in yield, although it was 30% lower than that irrigation up to harvest. However, irrigation up to 60 DAS reduced the yield by 3.9 times and 4.9 times compared to the yield at irrigation up to 80 DAS (85.897 grams/plant) and at harvest (108.57 grams/plant), respectively. Other parameters, such as dry biomass, cob weight, cob length, and cob diameter followed the yield trend, although their values varied. The dry biomass of maize at irrigation until 20 and 40 DAS were 13.68 grams/plant and 40.05 grams/plant, respectively. The experiment implies that irrigation water should be provided until 80 DAS to minimize significant yield losses of maize in dryland conditions.

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Section: Introductionmentioning

confidence: 99%

Maize production at phenological stages affected by water irrigation stress in dryland conditions

Suriadi,

Syarifinnur,

Mulyati

et al. 2024

IOP Conf. Ser.: Earth Environ. Sci.

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“…Administrative areas were generally employed as the spatial unit during drought risk assessment because socioeconomic data were customarily collected by administrative regions (Ahmadalipour et al., 2019; Kim et al., 2020), leading to a relatively coarse spatial resolution. In recent decades, the prosperous development of climate models has provided gridded projections of climate data (Lehner et al., 2017; Thilakarathne & Sridhar, 2017; Yin et al., 2021), making it possible to project future drought risk with a relatively high spatial resolution. Risk predictions can contribute to distinguishing future high‐risk regions and identifying the risk change for specific regions.…”

Section: Introductionmentioning

confidence: 99%

Projecting Global Drought Risk Under Various SSP‐RCP Scenarios

et al. 2023

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Drought risk assessment can identify high‐risk areas and bridge the gap between impacts and adaptation. It is thus vital to investigate changes in drought risk and exposed social economy under climate change. Here, the future global meteorological drought risk is projected for the 2021–2100 period under four combined scenarios of Representative Concentration Pathways and Shared Socioeconomic Pathways (SSPs), i.e., SSP1‐2.6, SSP2‐4.5, SSP3‐7.0, and SSP5‐8.5. And then the exposed population and Gross Domestic Product (GDP) under high risk are analyzed. Drought risk will further strengthen in the future under SSP2‐4.5, SSP3‐7.0, and SSP5‐8.5, with large increases distributed in South Asia, the Mediterranean, East Asia, Southeast Asia, and Central America. The strongest increasing trends in drought risk are concentrated in equatorial regions including South Asia, West Africa, and Central America. A large percentage of the population and economy are exposed to high drought risk. The exposed population under the highest risk level is the largest under SSP5‐8.5 and the smallest under SSP3‐7.0 for regions in North America, while being the largest under SSP3‐7.0 for other regions. The exposed GDP under the highest risk level is the highest under SSP5‐8.5 and the lowest under SSP3‐7.0, while the disparity among diverse scenarios is larger for the rich regions than the developing ones.

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“…The scenario simulation approach is the third kind. Agricultural models can simulate the response processes of crops under various disaster circumstances [11][12][13]. This technique can represent the feedback mechanism between the hazard system and crops; however, the model structure is complicated, and its parameters are difficult to obtain, limiting its application.…”

Section: Introductionmentioning

confidence: 99%

Risk Assessment of Maize Yield Losses in Gansu Province Based on Spatial Econometric Analysis

Fan¹,

Wang

Lin³

et al. 2023

Agriculture

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The frequent occurrence of meteorological disasters in China has caused huge losses to agriculture. Risk assessment serves as a bridge from disaster crisis management to disaster risk management. Therefore, it is necessary to carry out a refined comprehensive risk assessment of meteorological disasters in typical areas. However, several limitations remain in the disaster loss risk research, such as too coarse resolution and too single risk indicator. Additionally, less research has examined geographical information on risk clustering and barycenter migration, as well as temporal information on the sustainability of trends. Consequently, it is significant to unearth the geographical and temporal information on disaster loss and identify the refined spatial and temporal evolution pattern of crop risk. For this reason, we evaluated the risk of corn production in Gansu Province. First, based on maize yield data, a risk evaluation index system was constructed using the characteristics of variation trends, fluctuations, and extreme values of disaster losses. Then, the spatial distribution patterns and temporal evolution characteristics of maize production risks on a county scale in Gansu Province were determined using spatial analysis and climate diagnosis technology. The results show that there is a large interdecadal fluctuation in risk. In the 1980s, 1990s, 2000s, and 2010s, the average yield reduction rates of maize in Gansu Province were −11.8%, −12.6%, −8.7%, and −8.5%, and the proportions of counties with severe yield reduction were 34.8%, 44.4%, 20.8%, and 9.7%, respectively. Second, most counties belong to medium-low or low-risk areas for maize production. High-risk counties are primarily located in eastern and southern Gansu, whereas low-risk counties are mostly found along the Hexi Corridor. Third, most risk indicators exhibit some geographical aggregation. The Jiuquan region falls within the low-low-risk aggregation zone. In contrast, the Qingyang region is a high-high aggregation zone with a gradual expansion trend. Four, each risk indicator’s geographical barycenter migrates over a complicated path, but the direction and distance vary considerably. The comprehensive risk migrates along the south-northwest-southeast trajectory, albeit at a shorter distance. Five, the proportion of counties with a medium, medium-severe, severe, and total yield reduction tended to decline. In addition, the annual precipitation is significantly or very significantly correlated with most risk indicators and the comprehensive risk level. The results can guide agricultural production processes at all levels, as well as government disaster prevention.

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Mapping the Global-Scale Maize Drought Risk Under Climate Change Based on the GEPIC-Vulnerability-Risk Model

Cited by 12 publications

References 56 publications

Maize production at phenological stages affected by water irrigation stress in dryland conditions

Maize production at phenological stages affected by water irrigation stress in dryland conditions

Projecting Global Drought Risk Under Various SSP‐RCP Scenarios

Risk Assessment of Maize Yield Losses in Gansu Province Based on Spatial Econometric Analysis

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