Simulated deficit irrigation and climate change effects on sunflower production in Eastern Colorado with CSM-CROPGRO-Sunflower in RZWQM2

Zhang, Jing; Zhang, Huihui; Sima, Matthew; Trout, Thomas J.; Malone, R. W.; Wang, Li

doi:10.1016/j.agwat.2020.106672

Cited by 9 publications

(3 citation statements)

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“…Furthermore, there may be uncertainties in in optimizing irrigation scheduling under future climate scenarios based on local traditional irrigation time and amount. Using the automatic irrigation method based on RZWQM2 model may be more bene cial to nd out the optimal irrigation amount (Ma et al 2012a;Fang et al 2014;Zhang et al 2021).…”

Section: Uncertainty In Optimizing Irrigation Amount Under Changementioning

confidence: 99%

“…Based on RZWQM2, Chen et al (2019) predicted the impact of climate change on cotton yield and water requirements in northwest China in the near term (2041-2060) and for the long term (2061-2080). Zhang et al (2021) simulated the effects of de cit irrigation and climate change on sun ower (Helianthus annuus L.) yield in semi-arid Colorado under four RCP representative concentration emission pathways. However, studies investigating how to optimize de cit irrigation practices to address negative impacts of global warming on cotton yield in hyper-arid areas are rare.…”

Section: Introductionmentioning

confidence: 99%

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RZWQM2 simulated irrigation strategies to mitigate climate change impacts on cotton production in hyper–arid areas

Chen

Dong

Feng

et al. 2022

Preprint

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Improving cotton (Gossypium hirsutum L.) yield and water use efficiency (WUE) under future climate scenarios by optimizing irrigation regimes is crucial in hyper–arid areas. Assuming a current baseline atmospheric carbon dioxide concentration ( ${\left[{\text{C}\text{O}}_{2}\right]}_{\text{a}\text{t}\text{m}}$ ) of 380 ppm (baseline, BL0/380), the Root Zone Water Quality Model (RZWQM2) was used to evaluate the effects of four climate change scenarios — S1.5/380 ( $\varDelta {\text{T}}_{\text{a}\text{i}\text{r}}^{^\circ }=1.5^\circ \text{C}, \varDelta {\left[{\text{C}\text{O}}_{2}\right]}_{\text{a}\text{t}\text{m}}=0$ ), S2.0/380 ( $\varDelta {\text{T}}_{\text{a}\text{i}\text{r}}^{^\circ }=2.0^\circ \text{C}, \varDelta {\left[{\text{C}\text{O}}_{2}\right]}_{\text{a}\text{t}\text{m}}=0$ ), S1.5/490 ( $\varDelta {\text{T}}_{\text{a}\text{i}\text{r}}^{^\circ }=1.5^\circ \text{C}, \varDelta {\left[{\text{C}\text{O}}_{2}\right]}_{\text{a}\text{t}\text{m}}=+110 \text{p}\text{p}\text{m}$ ) and S2.0/650 ( $\varDelta {\text{T}}_{\text{a}\text{i}\text{r}}^{^\circ }=2.0^\circ \text{C}, \varDelta {\left[{\text{C}\text{O}}_{2}\right]}_{\text{a}\text{t}\text{m}}=+270 \text{p}\text{p}\text{m}$ ) on soil water content (θ), soil temperature ( ${\text{T}}_{\text{s}\text{o}\text{i}\text{l}}^{^\circ }$ ), aboveground biomass, cotton yield and WUE under full irrigation. Cotton yield and irrigation water use efficiency (IWUE) under ten different irrigation management strategies were analysed for economic benefits. Under the S1.5/380 and S2.0/380 scenarios, the average simulated aboveground biomass of cotton (vs. BL0/380) declined by 11% and 16%, whereas under S1.5/490 and S2.0/650 scenarios it increased by 12% and 30%, respectively. The simulated average seed cotton yield (vs. BL0/380) increased by 9.0% and 20.3% under the S1.5/490 and S2.0/650 scenarios, but decreased by 10.5% and 15.3% under the S1.5/380 and S2.0/380 scenarios, respectively. Owing to greater cotton yield and lesser transpiration, a 9.0% and 24.2% increase (vs. BL0/380) in cotton WUE occurred under the S1.5/490 and S2.0/650 scenarios, respectively. The highest net income ($3741 ha−1) and net water yield ($1.14 m−3) of cotton under climate change occurred when irrigated at 650 mm and 500 mm per growing season, respectively. These results suggested that deficit irrigation can be adopted in irrigated cotton fields to address the agricultural water crisis expected under climate change.

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Section: Uncertainty In Optimizing Irrigation Amount Under Changementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

RZWQM2 simulated irrigation strategies to mitigate climate change impacts on cotton production in hyper–arid areas

Chen

Dong

Feng

et al. 2022

Preprint

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“…However, climate and population changes will influence food security and self-sufficient of food production in many countries. Since the industrial revolution, global climate has been significantly affected by increasing greenhouse gas emissions, with associated effects on the water cycle (Wu et al, 2012 ; Yao et al, 2020 ), river flows (Gudmundsson et al, 2021 ), agricultural irrigation (Zhang et al, 2021 ), as well as many other ecologically, sociologically and economically important processes. As crops’ growth, agricultural production is highly sensitive to climate change (Ikhuoso et al, 2020 ; Ye et al, 2020 ; Zhao et al, 2015 ).…”

Section: Introductionmentioning

confidence: 99%

Changes in per capita wheat production in China in the context of climate change and population growth

Sun

Wang

2023

Food Sec.

Self Cite

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To address challenges associated with climate change, population growth and decline in international trade linked to the COVID-19 pandemic, determining whether national crop production can meet populations’ requirements and contribute to socio-economic resilience is crucial. Three crop models and three global climate models were used in conjunction with predicted population changes. Compared with wheat production in 2000–2010, total production and per capita wheat production were significantly (P < 0.05) increase in 2020–2030, 2030–2040 and 2040–2050, respectively, under RCP4.5 and RCP8.5 due to climate change in China. However, when considering population and climate changes, the predicted per capita production values were 125.3 ± 0.3, 127.1 ± 2.3 and 128.8 ± 2.7 kg during the 2020–2030, 2030–2040, 2040–2050 periods under RCP4.5, or 126.2 ± 0.7, 128.7 ± 2.5, and 131.0 ± 4.1 kg, respectively, under RCP8.5. These values do not significantly differ (P > 0.05) from the baseline level (127.9 ± 1.3 kg). The average per capita production in Loess Plateau and Gansu-Xinjiang subregions declined. In contrast, per capita production in the Huanghuai, Southwestern China, and Middle-Lower Yangtze Valleys subregions increased. The results suggest that climate change will increase total wheat production in China, but population change will partly offset the benefits to the grain market. In addition, domestic grain trade will be influenced by both climate and population changes. Wheat supply capacity will decline in the main supply areas. Further research is required to address effects of the changes on more crops and in more countries to obtain deeper understanding of the implications of climate change and population growth for global food production and assist formulation of robust policies to enhance food security. Supplementary Information The online version contains supplementary material available at 10.1007/s12571-023-01351-x.

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Wie wirken sich die Abstände der Tropfrohre auf den Saatgutertrag und den Nettoertrag von Sonnenblumen mit Tropfbewässerung bei unterschiedlichen Bewässerungsregimes aus?

Yavuz

2022

Gesunde Pflanzen

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Simulated deficit irrigation and climate change effects on sunflower production in Eastern Colorado with CSM-CROPGRO-Sunflower in RZWQM2

Cited by 9 publications

References 50 publications

RZWQM2 simulated irrigation strategies to mitigate climate change impacts on cotton production in hyper–arid areas

RZWQM2 simulated irrigation strategies to mitigate climate change impacts on cotton production in hyper–arid areas

Changes in per capita wheat production in China in the context of climate change and population growth

Wie wirken sich die Abstände der Tropfrohre auf den Saatgutertrag und den Nettoertrag von Sonnenblumen mit Tropfbewässerung bei unterschiedlichen Bewässerungsregimes aus?

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