Measurement and simulation of diurnal variations in water use efficiency and radiation use efficiency in an irrigated wheat-maize field in the North China Plain

Wang, Jing; Zhao, Tianbao; Wang, Enli; Yu, Qiang; Yang, Xiaoguang; Feng, Liping; Pan, Xuebiao

doi:10.1080/01140671.2010.482965

Cited by 8 publications

(3 citation statements)

References 35 publications

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“…Moreover, irrigation is not used frequently during maize growing season because precipitation concentrates in maize growing season such as regions I-III and V-VI or because there is no available irrigation water resource e.g. in region IV (Wang et al 2010, Yin et al 2015. Therefore, our assumptions are close to actual production conditions although optimal sowing dates and cultivars may change with different amounts of nitrogen fertilization and irrigation.…”

Section: Discussionmentioning

confidence: 99%

Optimizing sowing window and cultivar choice can boost China’s maize yield under 1.5 °C and 2 °C global warming

Huang

Wang

et al. 2020

Environ. Res. Lett.

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Climate change, with increased temperatures and varied rainfall, poses a great challenge to food security around the world. Appropriately assessing the impacts of climate change on crop productivity and understanding the adaptation potential of agriculture to climate change are urgently needed to help develop effective strategies for future agriculture and to maintain food security. In this study, we studied future maize yield changes under 1.5°C (2018-2037) and 2°C (2044-2063) warming scenarios and investigated the adaptation potential across China's Maize Belt by optimizing the sowing date and cultivar using the APSIM-Maize model. In comparison to the baseline scenario, under the 1.5°C and 2°C warming scenarios, we found that without adaptation, maize yields would increase in the relatively cool regions with a single-cropping system but decrease in other regions. However, in comparison with the baseline scenario, under the 1.5°C and 2°C warming scenarios with adaptation, maize yields would increase by 11.1%-53.9% across the study area. Across the maize belt, compared with the baseline scenario, under warming of 1.5°C, the potential sowing window would increase by 2-17 d, and under warming of 2°C, this sowing window would increase by 4-26 d. The optimal sowing window would also be significantly extended in the regions with single-cropping systems by an average of 10 d under the 1.5°C warming scenario and 12 d under the 2°C warming scenario. Latematuring cultivar achieved higher yield than early-middle maturing cultivars in all regions except the north part of Northeast China. Adjusting the sowing date by increasing growth-period precipitation contributed more (44.5%-96.7%) to yield improvements than shifting cultivars (0%-50.8%) and climate change (−53.1% to 23.0%) across all maize planting regions except in the wet southwestern parts of the maize belt. The differences among the maize planting regions in terms of high adaptation potential provide invaluable information for policymakers and stakeholders of maize production to set out optimized agricultural strategies to safeguard the supply of maize.

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Section: Discussionmentioning

confidence: 99%

Optimizing sowing window and cultivar choice can boost China’s maize yield under 1.5 °C and 2 °C global warming

Huang

Wang

et al. 2020

Environ. Res. Lett.

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“…Although the NCP is a typical irrigated agriculture region, with relatively enough water and fertilizer, no additional data can be used to validate this in pixel scale [49,63,64]. The complicated interactions between climate warming and non-climate effects were also not considered in this study.…”

Section: Uncertainties and Limitationsmentioning

confidence: 99%

Using MODIS LAI Data to Monitor Spatio-Temporal Changes of Winter Wheat Phenology in Response to Climate Warming

Song

Wang

et al. 2020

Remote Sensing

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Understanding spatio-temporal changes in winter wheat (Triticum aestivum L) phenology and its response to temperature will be vital for adapting to climate change in the coming years. For this purpose, the heading date (HD), maturity date (MD), and length of the reproductive growth period (LRGP) were detected from the remotely sensed leaf area index (LAI) data by a threshold-based method during the harvest year 2003 to 2018 across the North China Plain. The results show that there was high spatial heterogeneity of winter wheat phenology in pixel scale across the whole area, which could not be detected in previous site-based studies. The results also verified that climate warming could explain part of the change in the HD. However, for the LRGP, the potential impact of non-climate effects should be further investigated. This study presents the spatio-temporal changes both in winter wheat phenology and corresponding mean temperature and then analyzes their relationships in pixel scale. Additionally, this study further discusses the potential impact of non-climate effects on the LRGP.

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“…No nitrogen fertilizer stress occurred during the growing period of winter wheat and summer maize. Because 70% of annual precipitation is concentrated in the growing period of summer maize, no supplemental irrigation was applied during the growing period of summer maize (Wang et al 2010b). All the simulation experiments were run continuously from 1961 to 2010, i.e., without resetting initial soil conditions at each sowing of winter wheat.…”

Section: Apsim Modelmentioning

confidence: 99%

Modeling the sensitivity of wheat yield and yield gap to temperature change with two contrasting methods in the North China Plain

et al. 2019

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Wheat productivity in the North China Plain (NCP) is highly sensitive to climate change and varies greatly in spatial-temporal scale. Contrasting responses of wheat productivity to climate change were reported with different assessment methods. In this study, the impacts of climate warming (+ 2 °C) on wheat yields and yield gaps in the NCP were compared under rainfed, irrigated, and potential conditions using climatic resource utilization model (CRUM) and APSIM. Average potential yield increased 289 kg ha −1 per decade (P < 0.01) simulated by CRUM but decreased 219 kg ha −1 per decade (P < 0.01) simulated by APSIM across the NCP during 1961-2010. Under the + 2 °C scenario compared with current climate , wheat yields under potential, two irrigations, one irrigation, and rainfed conditions increased 27%, 23%, 28%, and 13% simulated by CRUM but decreased 7%, 8%, 10%, and 17% simulated by APSIM. Simulated yield gaps between potential yield and yields under rainfed and one and two irrigations by CRUM increased 33%, 27%, and 32%, respectively. Simulated yield gap between potential and rainfed yields by APSIM increased 9% while the gaps between potential yield and yields under one and two irrigations by APSIM decreased 12% and 10%. Without cultivar change, simulated shortened growth period by APSIM due to increased temperature would decrease wheat yields. By contrast, increased temperature under a constant growth period assumed by CRUM would increase yields especially potential yield. This suggested that wheat yields could be maintained by effective utilization of crop growth duration, such as breeding new cultivars under warming climate in the NCP.

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Measurement and simulation of diurnal variations in water use efficiency and radiation use efficiency in an irrigated wheat-maize field in the North China Plain

Cited by 8 publications

References 35 publications

Optimizing sowing window and cultivar choice can boost China’s maize yield under 1.5 °C and 2 °C global warming

Optimizing sowing window and cultivar choice can boost China’s maize yield under 1.5 °C and 2 °C global warming

Using MODIS LAI Data to Monitor Spatio-Temporal Changes of Winter Wheat Phenology in Response to Climate Warming

Modeling the sensitivity of wheat yield and yield gap to temperature change with two contrasting methods in the North China Plain

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