Warming and Dimming: Interactive Impacts on Potential Summer Maize Yield in North China Plain

Hu, Qi; Ma, Xin; He, Huayun; Pan, Feifei; He, Qijin; Huang, Bing; Pan, Xuebiao

doi:10.3390/su11092588

Cited by 7 publications

(4 citation statements)

References 59 publications

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“…The different effects of air pollutants on climate factors combined with the varying requirements of crops for light, heat and water in each crop growing stage lead to distinct spatiotemporal patterns of the indirect effects of air pollutants on crop yields (figures S7-S13). Generally, crops are more vulnerable to drought and light deficiency during the reproductive stage (from tasseling to filling) with stronger transpiration and photosynthesis (Butler and Huybers 2015, Feng et al 2019, Hu et al 2019. Our results confirm this by showing that air pollutants exert a larger indirect influence on crop yields during this stage (figures S12-S13).…”

Section: Differences In the Sensitivity Of Wheat And Maize Yields To ...supporting

confidence: 81%

Quantifying the indirect effects of different air pollutants on crop yields in North China Plain

Lu,

Leng,

2024

Environ. Res. Lett.

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High concentrations of air pollutants could affect crop yield directly via influencing crop physiology and indirectly via regulating climate conditions. How multiple air pollutants affect crop yields directly and indirectly remains elusive in the North China Plain (NCP), which is the hotspot of air pollution and crop production. Here, we construct data-driven models to quantify the indirect effects of four major air pollutants on the yields of winter wheat and summer maize through modulating climate variations in the NCP during 2005-2020. Our results show that wheat has a greater negative sensitivity to absorbing aerosol optical thickness (AAOD), ozone concentration (O3), sulfur dioxide concentration (SO2) and nitrogen dioxide concentration (NO2) than maize. The indirect effects of AAOD, O3 and SO2 in November and O3 in April control wheat yield variation, while the indirect effects of AAOD and O3 in June, O3 and SO2 in July, O3 and NO2 in August, and O3 in September dominate maize yield variation. Our results emphasize the indirect effects of air pollutants on crop yield via regulating climate variations, which has great implications for improving our understanding of air pollution-climate-crop interactions and guiding targeted adaptation and mitigation efforts.

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Section: Differences In the Sensitivity Of Wheat And Maize Yields To ...supporting

confidence: 81%

Quantifying the indirect effects of different air pollutants on crop yields in North China Plain

Lu,

Leng,

2024

Environ. Res. Lett.

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“…This region is the main winter wheat production area of China. Abundant light, heat, and water resources are the favorable factors for crop production [33,34]. The low yield was mainly distributed in eastern Gansu, central Shanxi, southern Hebei, and eastern Sichuan, where the yield was below 4 t/ha.…”

Section: Spatio-temporal Patterns Of Winter Wheat Yields From 2000 To...mentioning

confidence: 99%

Multi-Source Data Modeling of the Spatial Distribution of Winter Wheat Yield in China from 2000 to 2015

et al. 2020

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Yield gridded datasets are essential for agricultural land management, food security and harmonious human–land relationships. Many studies have developed yield spatialization models that are based on cropland areas. However, crop planting areas, phenological dates, and net primary production (NPP) have received minimal attention. This study proposes a novel method to simulate winter wheat yields in China from 2000 to 2015 using crop phenological datasets, phenological observations, and NPP. The results showed that the NPP in the growing season and statistical yield showed a significant positive correlation (R2 = 0.93, p < 0.01). The mean prediction error of the gridded yield dataset was 12.01%. The relative errors of the gridded yield dataset for approximately half of the samples were between −10% and 10%. Furthermore, the yield distribution was high in the east and low in the west. The high yield was primarily concentrated in the North China Plain, while low yield was observed in eastern Gansu, central Shanxi, southern Hebei, and eastern Sichuan. From 2000 to 2015, the yield mainly showed an increasing trend in the study area, with the average rate of 0.17 t ha−1 yr−1, especially in the North China Plain. This study suggests that NPP is a key indicator to evaluate the yield of winter wheat. Furthermore, this method can be used to generate gridded yield maps along with providing credible and fundamental data for climate change and sustainable agricultural development.

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“…The North China Plain is a vital maize production hub in China, yet it faces chronic freshwater shortages [1,2]. The irregular spatial and temporal distribution of high temperatures and rainfall leads to seasonal drought stress during the growth of summer maize, resulting in lower rain-fed summer maize yields compared to irrigated crops [3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Simulation of Irrigation Strategy Based on Stochastic Rainfall and Evapotranspiration

Long,

Wang,

et al. 2023

Agronomy

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The North China Plain plays a pivotal role in China’s crop production, contributing to 30% of the maize yield. Nevertheless, summer maize in this region faces challenges due to climatic constraints characterized by concurrent high temperatures and rainfall during the growing season, resulting in a relatively high evapotranspiration rate. In this study, we explored eight soil moisture-based threshold irrigation strategies, consisting of two upper limits and four lower limits, along with a rainfed mode (E). The upper and lower irrigation limits are expressed as a percentage of the field’s water-holding capacity (sfc). For the four full irrigation modes (A1, A2, A3, A4), the lower limits were set at 0.6 sfc, 0.6 sfc, 0.5 sfc, and 0.5 sfc, respectively. The upper limits were defined at two levels: 0.8 sfc for A1 and A2 and sfc for A3 and A4. Similarly, for the four deficit irrigation modes (B1, B2, B3, B4), the lower limits were established at 0.4 sfc, 0.4 sfc, 0.3 sfc, and 0.3 sfc, respectively, with the upper limits set at two levels: 0.8 sfc for B1 and B2 and the full sfc for B3 and B4. To investigate the impact of rainfall and potential evapotranspiration on these irrigation modes under long-term fluctuations, we employed a stochastic framework that probabilistically linked rainfall events and irrigation applications. The Monte Carlo method was employed to simulate a long-term series (4000a) of rainfall parameters and evapotranspiration using 62 years of meteorological data from the Xinxiang region, situated in the southern part of the North China Plain. Results showed that the relative yield and net irrigation water requirement of summer maize decreased with decreasing irrigation lower limits. Additionally, the interannual variation of rainfall parameters and evapotranspiration during the growing season were remarkable, which led to the lowest relative yield of the rainfed mode (E) aligned with a larger interannual difference. According to the simulation results, mode A4 (irrigation lower limit equals 0.5 sfc, irrigation upper limit equals 0.8 sfc) could be adopted for adequate water resources. Conversely, mode B2 is more suitable for a lack of water resources.

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Warming and Dimming: Interactive Impacts on Potential Summer Maize Yield in North China Plain

Cited by 7 publications

References 59 publications

Quantifying the indirect effects of different air pollutants on crop yields in North China Plain

Quantifying the indirect effects of different air pollutants on crop yields in North China Plain

Multi-Source Data Modeling of the Spatial Distribution of Winter Wheat Yield in China from 2000 to 2015

Simulation of Irrigation Strategy Based on Stochastic Rainfall and Evapotranspiration

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