Future Water Requirements and Crop Productivity at Al-Najaf Governorate Under Different Climate Change Scenarios (2020–2080)
This study aims to predict the effect of climate change on net irrigation water requirements (NIWR) and agricultural productivity from five common crops (wheat, barley, summer maize, and sorghum) in the Al-Najaf Governorate in Iraq. GFDL-ESM2M mode was used to predict the lower and upper temp and pr...
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| Format: | Article |
| Language: | English |
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Unviversity of Technology- Iraq
2023-05-01
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| Series: | Engineering and Technology Journal |
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| Online Access: | https://etj.uotechnology.edu.iq/article_178312_2fefdcad1787ba3e42d171f820229248.pdf |
| _version_ | 1797337721048399872 |
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| author | Noor Sabah Mustafa Al-Mukhtar Khalid Shemal |
| author_facet | Noor Sabah Mustafa Al-Mukhtar Khalid Shemal |
| author_sort | Noor Sabah |
| collection | DOAJ |
| description | This study aims to predict the effect of climate change on net irrigation water requirements (NIWR) and agricultural productivity from five common crops (wheat, barley, summer maize, and sorghum) in the Al-Najaf Governorate in Iraq. GFDL-ESM2M mode was used to predict the lower and upper temp and precipitation for two time periods (2020-2080) with 30 years for two periods (P1 and P2) under representative concentrations paths (RCP 2.5, RCP6, and RCP8.5). The CROPWAT model is used to determine NIWR, and the extreme learning model was used to estimate agricultural yields using previous crop yield production and weather data, supported vectors machine (SVM) is executed as a Machines Learns algorithm. Results showed NIWR increment to consider cropping owing to climate change. Barley is the crop most affected by climate change under the (RCP2.5, RCP6, and RCP8.5) scenarios, with increasing crop water requirements (NIWR) of (22%, 23%, and 24% ) for P1 and (23%, 24%, and 29%) for P2, respectively. Summer maize is the crop least affected by climate change under all climate change scenarios, with increasing crop water requirements of (1%, 2%, and 4%) for P1 and (1%, 2%, and 5% for P2. Climate change negatively affects the crop yield of all crops under the different climate change scenarios. The findings of this study could be used as a guide to developing adaptation strategies for dealing with potential changes in water availability and agricultural water productivity due to climate change. |
| first_indexed | 2024-03-08T09:16:44Z |
| format | Article |
| id | doaj.art-0472c6dd85804866922da6a91f0693e6 |
| institution | Directory Open Access Journal |
| issn | 1681-6900 2412-0758 |
| language | English |
| last_indexed | 2024-03-08T09:16:44Z |
| publishDate | 2023-05-01 |
| publisher | Unviversity of Technology- Iraq |
| record_format | Article |
| series | Engineering and Technology Journal |
| spelling | doaj.art-0472c6dd85804866922da6a91f0693e62024-01-31T14:15:08ZengUnviversity of Technology- IraqEngineering and Technology Journal1681-69002412-07582023-05-0141568769710.30684/etj.2023.137102.1335178312Future Water Requirements and Crop Productivity at Al-Najaf Governorate Under Different Climate Change Scenarios (2020–2080)Noor Sabah0Mustafa Al-Mukhtar1Khalid Shemal2Civil Engineering Dept., University of Technology-Iraq, Alsina’a street, 10066 Baghdad, Iraq.Civil Engineering Dept., University of Technology-Iraq, Alsina’a street, 10066 Baghdad, Iraq.Civil Engineering Dept., University of Technology-Iraq, Alsina’a street, 10066 Baghdad, Iraq.This study aims to predict the effect of climate change on net irrigation water requirements (NIWR) and agricultural productivity from five common crops (wheat, barley, summer maize, and sorghum) in the Al-Najaf Governorate in Iraq. GFDL-ESM2M mode was used to predict the lower and upper temp and precipitation for two time periods (2020-2080) with 30 years for two periods (P1 and P2) under representative concentrations paths (RCP 2.5, RCP6, and RCP8.5). The CROPWAT model is used to determine NIWR, and the extreme learning model was used to estimate agricultural yields using previous crop yield production and weather data, supported vectors machine (SVM) is executed as a Machines Learns algorithm. Results showed NIWR increment to consider cropping owing to climate change. Barley is the crop most affected by climate change under the (RCP2.5, RCP6, and RCP8.5) scenarios, with increasing crop water requirements (NIWR) of (22%, 23%, and 24% ) for P1 and (23%, 24%, and 29%) for P2, respectively. Summer maize is the crop least affected by climate change under all climate change scenarios, with increasing crop water requirements of (1%, 2%, and 4%) for P1 and (1%, 2%, and 5% for P2. Climate change negatively affects the crop yield of all crops under the different climate change scenarios. The findings of this study could be used as a guide to developing adaptation strategies for dealing with potential changes in water availability and agricultural water productivity due to climate change.https://etj.uotechnology.edu.iq/article_178312_2fefdcad1787ba3e42d171f820229248.pdfal-najaf governorateclimate changecrop productivitycrop water requirementsmachine learning |
| spellingShingle | Noor Sabah Mustafa Al-Mukhtar Khalid Shemal Future Water Requirements and Crop Productivity at Al-Najaf Governorate Under Different Climate Change Scenarios (2020–2080) Engineering and Technology Journal al-najaf governorate climate change crop productivity crop water requirements machine learning |
| title | Future Water Requirements and Crop Productivity at Al-Najaf Governorate Under Different Climate Change Scenarios (2020–2080) |
| title_full | Future Water Requirements and Crop Productivity at Al-Najaf Governorate Under Different Climate Change Scenarios (2020–2080) |
| title_fullStr | Future Water Requirements and Crop Productivity at Al-Najaf Governorate Under Different Climate Change Scenarios (2020–2080) |
| title_full_unstemmed | Future Water Requirements and Crop Productivity at Al-Najaf Governorate Under Different Climate Change Scenarios (2020–2080) |
| title_short | Future Water Requirements and Crop Productivity at Al-Najaf Governorate Under Different Climate Change Scenarios (2020–2080) |
| title_sort | future water requirements and crop productivity at al najaf governorate under different climate change scenarios 2020 2080 |
| topic | al-najaf governorate climate change crop productivity crop water requirements machine learning |
| url | https://etj.uotechnology.edu.iq/article_178312_2fefdcad1787ba3e42d171f820229248.pdf |
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