RZWQM2 Simulated Irrigation Strategies to Mitigate Climate Change Impacts on Cotton Production in Hyper–Arid Areas
Improving cotton (<i>Gossypium hirsutum</i> 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 (<inline-formula><math xmlns=...
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MDPI AG
2023-09-01
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| 丛编: | Agronomy |
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| 在线阅读: | https://www.mdpi.com/2073-4395/13/10/2529 |
| _version_ | 1827722044904570880 |
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| author | Xiaoping Chen Haibo Dong Shaoyuan Feng Dongwei Gui Liwang Ma Kelly R. Thorp Hao Wu Bo Liu Zhiming Qi |
| author_facet | Xiaoping Chen Haibo Dong Shaoyuan Feng Dongwei Gui Liwang Ma Kelly R. Thorp Hao Wu Bo Liu Zhiming Qi |
| author_sort | Xiaoping Chen |
| collection | DOAJ |
| description | Improving cotton (<i>Gossypium hirsutum</i> 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 (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mfenced open="[" close="]" separators="|"><mrow><msub><mrow><mi mathvariant="normal">C</mi><mi mathvariant="normal">O</mi></mrow><mrow><mn>2</mn></mrow></msub></mrow></mfenced></mrow><mrow><mi mathvariant="normal">a</mi><mi mathvariant="normal">t</mi><mi mathvariant="normal">m</mi></mrow></msub></mrow></semantics></math></inline-formula>) of 380 ppm (baseline, BL<sub>0/380</sub>), the Root Zone Water Quality Model (RZWQM2) was used to evaluate the effects of four climate change scenarios—S<sub>1.5/380</sub> (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>∆</mo><msubsup><mrow><mi mathvariant="normal">T</mi></mrow><mrow><mi mathvariant="normal">a</mi><mi mathvariant="normal">i</mi><mi mathvariant="normal">r</mi></mrow><mrow><mo>°</mo></mrow></msubsup><mo>=</mo><mn>1.5</mn><mo> </mo><mo>°</mo><mi mathvariant="normal">C</mi><mo>,</mo><mo>∆</mo><msub><mrow><mfenced open="[" close="]" separators="|"><mrow><msub><mrow><mi mathvariant="normal">C</mi><mi mathvariant="normal">O</mi></mrow><mrow><mn>2</mn></mrow></msub></mrow></mfenced></mrow><mrow><mi mathvariant="normal">a</mi><mi mathvariant="normal">t</mi><mi mathvariant="normal">m</mi></mrow></msub><mo>=</mo><mn>0</mn></mrow></semantics></math></inline-formula>), S<sub>2.0/380</sub> (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>∆</mo><msubsup><mrow><mi mathvariant="normal">T</mi></mrow><mrow><mi mathvariant="normal">a</mi><mi mathvariant="normal">i</mi><mi mathvariant="normal">r</mi></mrow><mrow><mo>°</mo></mrow></msubsup><mo>=</mo><mn>2.0</mn><mo> </mo><mo>°</mo><mi mathvariant="normal">C</mi><mo>,</mo><mo>∆</mo><msub><mrow><mfenced open="[" close="]" separators="|"><mrow><msub><mrow><mi mathvariant="normal">C</mi><mi mathvariant="normal">O</mi></mrow><mrow><mn>2</mn></mrow></msub></mrow></mfenced></mrow><mrow><mi mathvariant="normal">a</mi><mi mathvariant="normal">t</mi><mi mathvariant="normal">m</mi></mrow></msub><mo>=</mo><mn>0</mn></mrow></semantics></math></inline-formula>), S<sub>1.5/490</sub> (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>∆</mo><msubsup><mrow><mi mathvariant="normal">T</mi></mrow><mrow><mi mathvariant="normal">a</mi><mi mathvariant="normal">i</mi><mi mathvariant="normal">r</mi></mrow><mrow><mo>°</mo></mrow></msubsup><mo>=</mo><mn>1.5</mn><mo> </mo><mo>°</mo><mi mathvariant="normal">C</mi><mo>,</mo><mo>∆</mo><msub><mrow><mfenced open="[" close="]" separators="|"><mrow><msub><mrow><mi mathvariant="normal">C</mi><mi mathvariant="normal">O</mi></mrow><mrow><mn>2</mn></mrow></msub></mrow></mfenced></mrow><mrow><mi mathvariant="normal">a</mi><mi mathvariant="normal">t</mi><mi mathvariant="normal">m</mi></mrow></msub><mo>=</mo><mo>+</mo><mn>110</mn><mo> </mo><mi mathvariant="normal">p</mi><mi mathvariant="normal">p</mi><mi mathvariant="normal">m</mi></mrow></semantics></math></inline-formula>) and S<sub>2.0/650</sub> (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>∆</mo><msubsup><mrow><mi mathvariant="normal">T</mi></mrow><mrow><mi mathvariant="normal">a</mi><mi mathvariant="normal">i</mi><mi mathvariant="normal">r</mi></mrow><mrow><mo>°</mo></mrow></msubsup><mo>=</mo><mn>2.0</mn><mo> </mo><mo>°</mo><mi mathvariant="normal">C</mi><mo>,</mo><mo>∆</mo><msub><mrow><mfenced open="[" close="]" separators="|"><mrow><msub><mrow><mi mathvariant="normal">C</mi><mi mathvariant="normal">O</mi></mrow><mrow><mn>2</mn></mrow></msub></mrow></mfenced></mrow><mrow><mi mathvariant="normal">a</mi><mi mathvariant="normal">t</mi><mi mathvariant="normal">m</mi></mrow></msub><mo>=</mo><mo>+</mo><mn>270</mn><mo> </mo><mi mathvariant="normal">p</mi><mi mathvariant="normal">p</mi><mi mathvariant="normal">m</mi></mrow></semantics></math></inline-formula>) on soil water content (<i>θ</i>), soil temperature (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mrow><mi mathvariant="normal">T</mi></mrow><mrow><mi mathvariant="normal">s</mi><mi mathvariant="normal">o</mi><mi mathvariant="normal">i</mi><mi mathvariant="normal">l</mi></mrow><mrow><mo>°</mo></mrow></msubsup></mrow></semantics></math></inline-formula>), aboveground biomass, cotton yield and WUE under full irrigation. Cotton yield and irrigation water use efficiency (IWUE) under 10 different irrigation management strategies were analysed for economic benefits. Under the S<sub>1.5/380</sub> and S<sub>2.0/380</sub> scenarios, the average simulated aboveground biomass of cotton (vs. BL<sub>0/380</sub>) declined by 11% and 16%, whereas under S<sub>1.5/490</sub> and S<sub>2.0/650</sub> scenarios it increased by 12% and 30%, respectively. The simulated average seed cotton yield (vs. BL<sub>0/380</sub>) increased by 9.0% and 20.3% under the S<sub>1.5/490</sub> and S<sub>2.0/650</sub> scenarios, but decreased by 10.5% and 15.3% under the S<sub>1.5/380</sub> and S<sub>2.0/380</sub> scenarios, respectively. Owing to greater cotton yield and lesser transpiration, a 9.0% and 24.2% increase (vs. BL<sub>0/380</sub>) in cotton WUE occurred under the S<sub>1.5/490</sub> and S<sub>2.0/650</sub> scenarios, respectively. The highest net income ($3741 ha<sup>−1</sup>) and net water yield ($1.14 m<sup>−3</sup>) 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. |
| first_indexed | 2024-03-10T21:30:11Z |
| format | Article |
| id | doaj.art-3fea9bd6e99a4be48a5ccb6f73f0b9d8 |
| institution | Directory Open Access Journal |
| issn | 2073-4395 |
| language | English |
| last_indexed | 2024-03-10T21:30:11Z |
| publishDate | 2023-09-01 |
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| series | Agronomy |
| spelling | doaj.art-3fea9bd6e99a4be48a5ccb6f73f0b9d82023-11-19T15:21:28ZengMDPI AGAgronomy2073-43952023-09-011310252910.3390/agronomy13102529RZWQM2 Simulated Irrigation Strategies to Mitigate Climate Change Impacts on Cotton Production in Hyper–Arid AreasXiaoping Chen0Haibo Dong1Shaoyuan Feng2Dongwei Gui3Liwang Ma4Kelly R. Thorp5Hao Wu6Bo Liu7Zhiming Qi8College of Hydraulic Science and Engineering, Yangzhou University, Yangzhou 225009, ChinaCollege of Hydraulic Science and Engineering, Yangzhou University, Yangzhou 225009, ChinaCollege of Hydraulic Science and Engineering, Yangzhou University, Yangzhou 225009, ChinaCele National Station of Observation and Research for Desert Grassland Ecosystem in Xinjiang, Cele 848300, ChinaUSDA-ARS, Rangeland Resources and Systems Research Unit, Fort Collins, CO 80526, USAUSDA-ARS, U.S. Arid Land Agricultural Research Center, Maricopa, AZ 85138, USACollege of Hydraulic Science and Engineering, Yangzhou University, Yangzhou 225009, ChinaCollege of Hydraulic Science and Engineering, Yangzhou University, Yangzhou 225009, ChinaDepartment of Bioresource Engineering, McGill University, Sainte-Anne-de-Bellevue, QC H9X 3V9, CanadaImproving cotton (<i>Gossypium hirsutum</i> 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 (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mfenced open="[" close="]" separators="|"><mrow><msub><mrow><mi mathvariant="normal">C</mi><mi mathvariant="normal">O</mi></mrow><mrow><mn>2</mn></mrow></msub></mrow></mfenced></mrow><mrow><mi mathvariant="normal">a</mi><mi mathvariant="normal">t</mi><mi mathvariant="normal">m</mi></mrow></msub></mrow></semantics></math></inline-formula>) of 380 ppm (baseline, BL<sub>0/380</sub>), the Root Zone Water Quality Model (RZWQM2) was used to evaluate the effects of four climate change scenarios—S<sub>1.5/380</sub> (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>∆</mo><msubsup><mrow><mi mathvariant="normal">T</mi></mrow><mrow><mi mathvariant="normal">a</mi><mi mathvariant="normal">i</mi><mi mathvariant="normal">r</mi></mrow><mrow><mo>°</mo></mrow></msubsup><mo>=</mo><mn>1.5</mn><mo> </mo><mo>°</mo><mi mathvariant="normal">C</mi><mo>,</mo><mo>∆</mo><msub><mrow><mfenced open="[" close="]" separators="|"><mrow><msub><mrow><mi mathvariant="normal">C</mi><mi mathvariant="normal">O</mi></mrow><mrow><mn>2</mn></mrow></msub></mrow></mfenced></mrow><mrow><mi mathvariant="normal">a</mi><mi mathvariant="normal">t</mi><mi mathvariant="normal">m</mi></mrow></msub><mo>=</mo><mn>0</mn></mrow></semantics></math></inline-formula>), S<sub>2.0/380</sub> (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>∆</mo><msubsup><mrow><mi mathvariant="normal">T</mi></mrow><mrow><mi mathvariant="normal">a</mi><mi mathvariant="normal">i</mi><mi mathvariant="normal">r</mi></mrow><mrow><mo>°</mo></mrow></msubsup><mo>=</mo><mn>2.0</mn><mo> </mo><mo>°</mo><mi mathvariant="normal">C</mi><mo>,</mo><mo>∆</mo><msub><mrow><mfenced open="[" close="]" separators="|"><mrow><msub><mrow><mi mathvariant="normal">C</mi><mi mathvariant="normal">O</mi></mrow><mrow><mn>2</mn></mrow></msub></mrow></mfenced></mrow><mrow><mi mathvariant="normal">a</mi><mi mathvariant="normal">t</mi><mi mathvariant="normal">m</mi></mrow></msub><mo>=</mo><mn>0</mn></mrow></semantics></math></inline-formula>), S<sub>1.5/490</sub> (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>∆</mo><msubsup><mrow><mi mathvariant="normal">T</mi></mrow><mrow><mi mathvariant="normal">a</mi><mi mathvariant="normal">i</mi><mi mathvariant="normal">r</mi></mrow><mrow><mo>°</mo></mrow></msubsup><mo>=</mo><mn>1.5</mn><mo> </mo><mo>°</mo><mi mathvariant="normal">C</mi><mo>,</mo><mo>∆</mo><msub><mrow><mfenced open="[" close="]" separators="|"><mrow><msub><mrow><mi mathvariant="normal">C</mi><mi mathvariant="normal">O</mi></mrow><mrow><mn>2</mn></mrow></msub></mrow></mfenced></mrow><mrow><mi mathvariant="normal">a</mi><mi mathvariant="normal">t</mi><mi mathvariant="normal">m</mi></mrow></msub><mo>=</mo><mo>+</mo><mn>110</mn><mo> </mo><mi mathvariant="normal">p</mi><mi mathvariant="normal">p</mi><mi mathvariant="normal">m</mi></mrow></semantics></math></inline-formula>) and S<sub>2.0/650</sub> (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>∆</mo><msubsup><mrow><mi mathvariant="normal">T</mi></mrow><mrow><mi mathvariant="normal">a</mi><mi mathvariant="normal">i</mi><mi mathvariant="normal">r</mi></mrow><mrow><mo>°</mo></mrow></msubsup><mo>=</mo><mn>2.0</mn><mo> </mo><mo>°</mo><mi mathvariant="normal">C</mi><mo>,</mo><mo>∆</mo><msub><mrow><mfenced open="[" close="]" separators="|"><mrow><msub><mrow><mi mathvariant="normal">C</mi><mi mathvariant="normal">O</mi></mrow><mrow><mn>2</mn></mrow></msub></mrow></mfenced></mrow><mrow><mi mathvariant="normal">a</mi><mi mathvariant="normal">t</mi><mi mathvariant="normal">m</mi></mrow></msub><mo>=</mo><mo>+</mo><mn>270</mn><mo> </mo><mi mathvariant="normal">p</mi><mi mathvariant="normal">p</mi><mi mathvariant="normal">m</mi></mrow></semantics></math></inline-formula>) on soil water content (<i>θ</i>), soil temperature (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mrow><mi mathvariant="normal">T</mi></mrow><mrow><mi mathvariant="normal">s</mi><mi mathvariant="normal">o</mi><mi mathvariant="normal">i</mi><mi mathvariant="normal">l</mi></mrow><mrow><mo>°</mo></mrow></msubsup></mrow></semantics></math></inline-formula>), aboveground biomass, cotton yield and WUE under full irrigation. Cotton yield and irrigation water use efficiency (IWUE) under 10 different irrigation management strategies were analysed for economic benefits. Under the S<sub>1.5/380</sub> and S<sub>2.0/380</sub> scenarios, the average simulated aboveground biomass of cotton (vs. BL<sub>0/380</sub>) declined by 11% and 16%, whereas under S<sub>1.5/490</sub> and S<sub>2.0/650</sub> scenarios it increased by 12% and 30%, respectively. The simulated average seed cotton yield (vs. BL<sub>0/380</sub>) increased by 9.0% and 20.3% under the S<sub>1.5/490</sub> and S<sub>2.0/650</sub> scenarios, but decreased by 10.5% and 15.3% under the S<sub>1.5/380</sub> and S<sub>2.0/380</sub> scenarios, respectively. Owing to greater cotton yield and lesser transpiration, a 9.0% and 24.2% increase (vs. BL<sub>0/380</sub>) in cotton WUE occurred under the S<sub>1.5/490</sub> and S<sub>2.0/650</sub> scenarios, respectively. The highest net income ($3741 ha<sup>−1</sup>) and net water yield ($1.14 m<sup>−3</sup>) 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.https://www.mdpi.com/2073-4395/13/10/2529global warmingdeficit irrigationcotton yieldwater useRZWQM2 |
| spellingShingle | Xiaoping Chen Haibo Dong Shaoyuan Feng Dongwei Gui Liwang Ma Kelly R. Thorp Hao Wu Bo Liu Zhiming Qi RZWQM2 Simulated Irrigation Strategies to Mitigate Climate Change Impacts on Cotton Production in Hyper–Arid Areas Agronomy global warming deficit irrigation cotton yield water use RZWQM2 |
| title | RZWQM2 Simulated Irrigation Strategies to Mitigate Climate Change Impacts on Cotton Production in Hyper–Arid Areas |
| title_full | RZWQM2 Simulated Irrigation Strategies to Mitigate Climate Change Impacts on Cotton Production in Hyper–Arid Areas |
| title_fullStr | RZWQM2 Simulated Irrigation Strategies to Mitigate Climate Change Impacts on Cotton Production in Hyper–Arid Areas |
| title_full_unstemmed | RZWQM2 Simulated Irrigation Strategies to Mitigate Climate Change Impacts on Cotton Production in Hyper–Arid Areas |
| title_short | RZWQM2 Simulated Irrigation Strategies to Mitigate Climate Change Impacts on Cotton Production in Hyper–Arid Areas |
| title_sort | rzwqm2 simulated irrigation strategies to mitigate climate change impacts on cotton production in hyper arid areas |
| topic | global warming deficit irrigation cotton yield water use RZWQM2 |
| url | https://www.mdpi.com/2073-4395/13/10/2529 |
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