Pub Date : 2024-07-02DOI: 10.1016/j.agwat.2024.108941
Pan Huo, Pengcheng Gao
The degassing potential of supersaturated dissolved greenhouse gases (N2O, CO2, and CH4) in groundwater has often been overlooked as a source of emissions in irrigated agriculture. Quantifying the degassing potential and investigating measures are essential for agricultural carbon mitigation. This study estimated for the first time the direct greenhouse gas degassing potential from groundwater under different irrigation methods and explored mitigation strategies in the Guanzhong Basin, Northwest China. The results revealed that while short-term degassing potential from groundwater irrigation exceeds that reported for global inland waters and fertilized soils, the interannual degassing potential (13,819–52,163 t CO2-eq year−1) represents only 0.3–1.1 % of annual emissions from regional agricultural soils. The degassing potential exhibited a trend of over-surface drip irrigation (ODI) > surface drip irrigation (DI) > subsurface drip irrigation (SDI) > flood irrigation (FI) under equivalent irrigation volumes. Notably, SDI emerges as a promising strategy for concurrent water conservation and greenhouse gas mitigation. Switching from over-surface and surface drip irrigation to subsurface drip irrigation yields a reduction of 60.8 % and 46.3 % in carbon emissions per cubic meter of water saved, respectively. This study provides valuable insights for the development of sustainable irrigation practices and emphasizes the importance of integrating groundwater degassing potential into agricultural carbon budgets and emission mitigation strategies.
{"title":"Degassing of greenhouse gases from groundwater under different irrigation methods: A neglected carbon source in agriculture","authors":"Pan Huo, Pengcheng Gao","doi":"10.1016/j.agwat.2024.108941","DOIUrl":"https://doi.org/10.1016/j.agwat.2024.108941","url":null,"abstract":"<div><p>The degassing potential of supersaturated dissolved greenhouse gases (N<sub>2</sub>O, CO<sub>2</sub>, and CH<sub>4</sub>) in groundwater has often been overlooked as a source of emissions in irrigated agriculture. Quantifying the degassing potential and investigating measures are essential for agricultural carbon mitigation. This study estimated for the first time the direct greenhouse gas degassing potential from groundwater under different irrigation methods and explored mitigation strategies in the Guanzhong Basin, Northwest China. The results revealed that while short-term degassing potential from groundwater irrigation exceeds that reported for global inland waters and fertilized soils, the interannual degassing potential (13,819–52,163 t CO<sub>2</sub>-eq year<sup>−1</sup>) represents only 0.3–1.1 % of annual emissions from regional agricultural soils. The degassing potential exhibited a trend of over-surface drip irrigation (ODI) > surface drip irrigation (DI) > subsurface drip irrigation (SDI) > flood irrigation (FI) under equivalent irrigation volumes. Notably, SDI emerges as a promising strategy for concurrent water conservation and greenhouse gas mitigation. Switching from over-surface and surface drip irrigation to subsurface drip irrigation yields a reduction of 60.8 % and 46.3 % in carbon emissions per cubic meter of water saved, respectively. This study provides valuable insights for the development of sustainable irrigation practices and emphasizes the importance of integrating groundwater degassing potential into agricultural carbon budgets and emission mitigation strategies.</p></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":null,"pages":null},"PeriodicalIF":5.9,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0378377424002762/pdfft?md5=46576d9294a03b85a4acef4606e416db&pid=1-s2.0-S0378377424002762-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141486424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-01DOI: 10.1016/j.agwat.2024.108930
Qiang Xu , Hongguang Liu , Mingsi Li , Ping Gong , Pengfei Li , Yibin Xu
Cultivating Suaeda salsa (S. salsa) is a promising strategy for the improvement and development of saline wastelands. However, the absence of a scientifically reasonable water and fertilizer management system has long hindered the large-scale improvement and utilization of saline wastelands. Therefore, we performed field experiments for two consecutive years to investigate the effects of water-nitrogen coupling on biomass, forage quality, salt absorption capacity, soil improvement effect, and economic benefits of S. salsa. The optimal water and nitrogen dosages for multi-objective optimization were determined using multiple regression and spatial analysis methods. Three irrigation levels were established for the experiment based on 0.35 (W1), 0.50 (W2), and 0.65 (W3) of the local ETo (Where ETo denotes the reference evapotranspiration calculated based on the FAO-56 recommended by the Food and Agriculture Organization). The three nitrogen application levels were 150 (F1), 250 (F2), and 350 (F3) kg ha−1 in the complete combination design. At the same nitrogen application level, the biomass and economic benefits of the W3 irrigation level were the highest. However, the forage quality, salt absorption capacity, salt reduction, and water productivity at the W3 irrigation level were lower than those at the W2 irrigation level, and the water productivity at the W1 irrigation level was the highest. At the same irrigation level, when the nitrogen application level was F2, the biomass, forage quality, salt absorption, salt reduction, and net profit, all reached their maximum values, and water productivity was the highest at the F3 level. The optimal amount of water and nitrogen applied for each parameter was different, so it was impossible to obtain the highest biomass, forage quality, salt absorption, salt reduction, water productivity, and net profit at the same time. Therefore, multi-objective optimization was needed, the optimal irrigation volume range was 3350.11–3485.97 m3 ha−1, and the nitrogen application rate range was 273.49–326.66 kg ha−1. These findings provide a scientific basis for the large-scale cultivation of S. salsa in extreme arid region, which is helpful for the improvement and utilization of saline-alkali land.
{"title":"Optimizing water and nitrogen management for saline wasteland improvement: A case study on Suaeda salsa","authors":"Qiang Xu , Hongguang Liu , Mingsi Li , Ping Gong , Pengfei Li , Yibin Xu","doi":"10.1016/j.agwat.2024.108930","DOIUrl":"https://doi.org/10.1016/j.agwat.2024.108930","url":null,"abstract":"<div><p>Cultivating <em>Suaeda salsa (S. salsa)</em> is a promising strategy for the improvement and development of saline wastelands. However, the absence of a scientifically reasonable water and fertilizer management system has long hindered the large-scale improvement and utilization of saline wastelands. Therefore, we performed field experiments for two consecutive years to investigate the effects of water-nitrogen coupling on biomass, forage quality, salt absorption capacity, soil improvement effect, and economic benefits of <em>S. salsa</em>. The optimal water and nitrogen dosages for multi-objective optimization were determined using multiple regression and spatial analysis methods. Three irrigation levels were established for the experiment based on 0.35 (W1), 0.50 (W2), and 0.65 (W3) of the local ETo (Where <em>ET</em><sub><em>o</em></sub> denotes the reference evapotranspiration calculated based on the FAO-56 recommended by the Food and Agriculture Organization)<sup>.</sup> The three nitrogen application levels were 150 (F1), 250 (F2), and 350 (F3) kg ha<sup>−1</sup> in the complete combination design. At the same nitrogen application level, the biomass and economic benefits of the W3 irrigation level were the highest. However, the forage quality, salt absorption capacity, salt reduction, and water productivity at the W3 irrigation level were lower than those at the W2 irrigation level, and the water productivity at the W1 irrigation level was the highest. At the same irrigation level, when the nitrogen application level was F2, the biomass, forage quality, salt absorption, salt reduction, and net profit, all reached their maximum values, and water productivity was the highest at the F3 level. The optimal amount of water and nitrogen applied for each parameter was different, so it was impossible to obtain the highest biomass, forage quality, salt absorption, salt reduction, water productivity, and net profit at the same time. Therefore, multi-objective optimization was needed, the optimal irrigation volume range was 3350.11–3485.97 m<sup>3</sup> ha<sup>−1</sup>, and the nitrogen application rate range was 273.49–326.66 kg ha<sup>−1</sup>. These findings provide a scientific basis for the large-scale cultivation of <em>S. salsa</em> in extreme arid region, which is helpful for the improvement and utilization of saline-alkali land.</p></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":null,"pages":null},"PeriodicalIF":5.9,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0378377424002658/pdfft?md5=0ede97cf05a4bbc4af2237fc668211d9&pid=1-s2.0-S0378377424002658-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141483470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Temporal and spatial irrigation performance indicators are crucial in informing decisions for improving the efficiency and sustainability of water and land resources. However, evaluating these indicators requires reliable and cost-effective data, which is challenging to obtain, particularly for small-scale irrigation schemes. This study aimed to assess the performance of a small-scale irrigation scheme using remote sensing and ground truth data for the 2021/22 and 2022/2023 irrigation seasons employing the Shimburit irrigation scheme in Northwestern Ethiopia, predominantly cultivated with wheat, as a case study. The performance indicators, including equity, adequacy, overall consumed ratio (OCR), and productivity, were assessed. The actual evapotranspiration (ET), the main input for performance assessment, was estimated using the surface energy balance for land – improved (SEBALI) model in the Google Earth Engine (GEE) platform. The results revealed good equity within the scheme, with a coefficient of variation of ETa value per field inside the scheme are 1.90 and 1.63 for the respective seasons. The water use adequacy across the fields was assessed to be very good in the two seasons. The scheme's overall consumed ratio (OCR) was 0.54 and 0.43 during the two subsequent seasons. Water productivity of wheat is 3.03 kg/m3 and 3.06 kg/m3 in the two seasons. However, due to untimely rainfall during harvest, land productivity declined from 3.25 tons/ha in the first season to 2.08 tons/ha in the second season. The study demonstrates the potential of using remote sensing to evaluate irrigation performance indicators and water productivity in smallholder irrigated fields.
{"title":"Monitoring small-scale irrigation performance using remote sensing in the Upper Blue Nile Basin, Ethiopia","authors":"Yilkal Gebeyehu Mekonnen , Tena Alamirew , Kassahun Birhanu Tadesse , Abebe Demissie Chukalla","doi":"10.1016/j.agwat.2024.108928","DOIUrl":"10.1016/j.agwat.2024.108928","url":null,"abstract":"<div><p>Temporal and spatial irrigation performance indicators are crucial in informing decisions for improving the efficiency and sustainability of water and land resources. However, evaluating these indicators requires reliable and cost-effective data, which is challenging to obtain, particularly for small-scale irrigation schemes. This study aimed to assess the performance of a small-scale irrigation scheme using remote sensing and ground truth data for the 2021/22 and 2022/2023 irrigation seasons employing the Shimburit irrigation scheme in Northwestern Ethiopia, predominantly cultivated with wheat, as a case study. The performance indicators, including equity, adequacy, overall consumed ratio (OCR), and productivity, were assessed. The actual evapotranspiration (ET), the main input for performance assessment, was estimated using the surface energy balance for land – improved (SEBALI) model in the Google Earth Engine (GEE) platform. The results revealed good equity within the scheme, with a coefficient of variation of ETa value per field inside the scheme are 1.90 and 1.63 for the respective seasons. The water use adequacy across the fields was assessed to be very good in the two seasons. The scheme's overall consumed ratio (OCR) was 0.54 and 0.43 during the two subsequent seasons. Water productivity of wheat is 3.03 kg/m<sup>3</sup> and 3.06 kg/m<sup>3</sup> in the two seasons. However, due to untimely rainfall during harvest, land productivity declined from 3.25 tons/ha in the first season to 2.08 tons/ha in the second season. The study demonstrates the potential of using remote sensing to evaluate irrigation performance indicators and water productivity in smallholder irrigated fields.</p></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":null,"pages":null},"PeriodicalIF":5.9,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0378377424002634/pdfft?md5=f739396e04fd263af0bfa6ea00b14af2&pid=1-s2.0-S0378377424002634-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141463136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-01DOI: 10.1016/j.agwat.2024.108935
Heng Fang , Yuannong Li , Xiaobo Gu , Yadan Du , Pengpeng Chen , Hongxiang Hu
The biodegradable film, as an ideal substitute for plastic film, has broad application prospects. However, it is uncertain in maize actual evapotranspiration () components, yield, and water use efficiency (WUE) of biodegradable and plastic films during the different rainfall seasons. Therefore, a 4-year field trial with three mulching patterns (FNM: flat planting with non-mulching, RPM: ridge-furrow with plastic film mulching, and RBM: ridge-furrow with biodegradable film mulching) and two N-fertilization levels (0 and 180 kg N ha–1) was conducted. The results showed that the machine-learning models could accurately estimate maize and its partitioning, and the random forest and artificial neural networks models had the highest accuracy and the least input variables after optimization. Compared to FNM, RBM and RPM increased by 10.8 mm, 14.0 mm in the dry season, 9.1 mm, 11.2 mm in the normal season, and 4.0 mm, 7.5 mm in the wet season, respectively, but decreased by 75.8 mm, 82.7 mm in the dry season, 48.6 mm, 56.7 mm in the normal season, 67.1 mm, and 74.9 mm in the wet season, respectively. Therefore, RBM and RPM decreased by 65.0 mm, 68.8 mm in the dry season, 39.5 mm, 45.6 mm in the normal season, and 53.1 mm, 67.5 mm in the wet season, respectively, compared to FNM. Nitrogen application had a similar effect on and but only increased by 13.3 mm in the dry season, 2 mm in the normal season, and 4.3 mm in the wet season, respectively, compared to N0. Furthermore, RBM and RPM under different nitrogen-fertilizations increased maize yield by 4.0 %, 3.6 % in the dry season, 3.0 %, 3.3 % in the normal season, and 5.3 %, 5.9 % in the wet season, respectively, also increased maize WUE by 23.3 %, 24.1 % in the dry season, 12.9 %, 15.0 % in the normal season, and 21.1 %, 23.4 % in the wet season, respectively, compared to FNM. This study proved that RPM could be replaced by RBM under 180 kg N ha–1 in the different rainfall seasons in terms of reducing , increasing maize yield, and improving WUE. The optimized machine learning models in this study also provided a low-cost method for computing regional maize
{"title":"Evapotranspiration, water use efficiency, and yield for film mulched maize under different nitrogen-fertilization rates and climate conditions","authors":"Heng Fang , Yuannong Li , Xiaobo Gu , Yadan Du , Pengpeng Chen , Hongxiang Hu","doi":"10.1016/j.agwat.2024.108935","DOIUrl":"https://doi.org/10.1016/j.agwat.2024.108935","url":null,"abstract":"<div><p>The biodegradable film, as an ideal substitute for plastic film, has broad application prospects. However, it is uncertain in maize actual evapotranspiration (<span><math><msub><mrow><mi>ET</mi></mrow><mrow><mi>ac</mi></mrow></msub></math></span>) components, yield, and water use efficiency (WUE) of biodegradable and plastic films during the different rainfall seasons. Therefore, a 4-year field trial with three mulching patterns (FNM: flat planting with non-mulching, RPM: ridge-furrow with plastic film mulching, and RBM: ridge-furrow with biodegradable film mulching) and two N-fertilization levels (0 and 180 kg N ha<sup>–1</sup>) was conducted. The results showed that the machine-learning models could accurately estimate maize <span><math><msub><mrow><mi>ET</mi></mrow><mrow><mi>ac</mi></mrow></msub></math></span> and its partitioning, and the random forest and artificial neural networks models had the highest accuracy and the least input variables after optimization. Compared to FNM, RBM and RPM increased <span><math><msub><mrow><mi>E</mi></mrow><mrow><mi>t</mi></mrow></msub></math></span> by 10.8 mm, 14.0 mm in the dry season, 9.1 mm, 11.2 mm in the normal season, and 4.0 mm, 7.5 mm in the wet season, respectively, but decreased <span><math><msub><mrow><mi>E</mi></mrow><mrow><mi>s</mi></mrow></msub></math></span> by 75.8 mm, 82.7 mm in the dry season, 48.6 mm, 56.7 mm in the normal season, 67.1 mm, and 74.9 mm in the wet season, respectively. Therefore, RBM and RPM decreased <span><math><msub><mrow><mi>ET</mi></mrow><mrow><mi>ac</mi></mrow></msub></math></span> by 65.0 mm, 68.8 mm in the dry season, 39.5 mm, 45.6 mm in the normal season, and 53.1 mm, 67.5 mm in the wet season, respectively, compared to FNM. Nitrogen application had a similar effect on <span><math><msub><mrow><mi>E</mi></mrow><mrow><mi>s</mi></mrow></msub></math></span> and <span><math><msub><mrow><mi>E</mi></mrow><mrow><mi>t</mi></mrow></msub></math></span> but only increased <span><math><msub><mrow><mi>ET</mi></mrow><mrow><mi>ac</mi></mrow></msub></math></span> by 13.3 mm in the dry season, 2 mm in the normal season, and 4.3 mm in the wet season, respectively, compared to N0. Furthermore, RBM and RPM under different nitrogen-fertilizations increased maize yield by 4.0 %, 3.6 % in the dry season, 3.0 %, 3.3 % in the normal season, and 5.3 %, 5.9 % in the wet season, respectively, also increased maize WUE by 23.3 %, 24.1 % in the dry season, 12.9 %, 15.0 % in the normal season, and 21.1 %, 23.4 % in the wet season, respectively, compared to FNM. This study proved that RPM could be replaced by RBM under 180 kg N ha<sup>–1</sup> in the different rainfall seasons in terms of reducing <span><math><msub><mrow><mi>ET</mi></mrow><mrow><mi>ac</mi></mrow></msub></math></span>, increasing maize yield, and improving WUE. The optimized machine learning models in this study also provided a low-cost method for computing regional maize <span><math><msub><mrow><mi>ET</mi></mrow><mrow><mi","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":null,"pages":null},"PeriodicalIF":5.9,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0378377424002701/pdfft?md5=57076a51047a4e127b4be6100db3a219&pid=1-s2.0-S0378377424002701-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141483468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-29DOI: 10.1016/j.agwat.2024.108937
Pilar Lorenzo , Rafael Reyes , Evangelina Medrano , Rosa Granados , Santiago Bonachela , Joaquín Hernández , Juan C. López , Juan J. Magán , Francisco M. del Amor , M. Cruz Sánchez-Guerrero
The microclimate of low-tech, unheated greenhouses in Mediterranean areas, associated with the local outdoor climate, is often outside the optimal range for most horticultural crops during both the warm and cold growing season. The use of a new hybrid system of passive cooling (evaporative screens) and heating (water-filled sleeves), in combination with an internal movable shading/thermal screen, was evaluated on a representative summer transplanted sweet pepper crop grown in perlite growing bags. The experiment was carried out in two identical greenhouses at the IFAPA La Mojonera research center in Almeria (SE Spain): one greenhouse with the hybrid passive system of cooling and heating, in combination with a shading/thermal screen, and another (reference greenhouse) using common local greenhouse climate management practices. Evaporative screens, in combination with a movable shading screen, improved the greenhouse climate, in particular the air vapour pressure deficit, and increased the leaf area index in the early stages of the crop, which, in turn, increased the early production of leaf and shoot dry matter and marketable fruit, compared to the reference greenhouse crop. In addition, the combined use of water-filled sleeves and thermal screen during the cold growth period increased greenhouse air temperatures, especially at night, and substrate temperatures. Overall, by improving the greenhouse microclimate during the warm and cold growth periods, the hybrid passive cooling/heating system, in combination with the shading/thermal screen, increased the marketable yield of a summer transplanted sweet pepper crop by 25 %, reduced the irrigation water supply by 8 %, and improved the irrigation water use efficiency by 20 % (including the potential water used to humidify the evaporative screens).
地中海地区低技术、无暖气温室的小气候与当地室外气候相关联，在温暖和寒冷的生长季节往往超出大多数园艺作物的最佳范围。在珍珠岩种植袋中种植的具有代表性的夏季移栽甜椒作物上，对使用新型被动冷却（蒸发屏）和加热（注水套管）混合系统，并结合内部可移动遮阳/隔热屏进行了评估。实验在位于阿尔梅里亚（西班牙东南部）的 IFAPA La Mojonera 研究中心的两个相同温室中进行：一个温室采用混合被动式制冷和加热系统，并结合遮阳/保温幕；另一个温室（参考温室）采用当地常见的温室气候管理方法。与参考温室作物相比，蒸发网与活动遮阳网相结合，改善了温室气候，特别是空气蒸汽压力不足，提高了作物早期阶段的叶面积指数，进而提高了叶片和嫩枝干物质的早期产量以及可上市果实的产量。此外，在寒冷生长期结合使用注水套管和保温幕还能提高温室气温（尤其是夜间）和基质温度。总之，通过改善温暖和寒冷生长期的温室小气候，混合被动降温/加热系统与遮阳/保温幕相结合，使夏季移栽甜椒作物的可上市产量提高了 25%，灌溉用水量减少了 8%，灌溉用水效率提高了 20%（包括用于蒸发幕加湿的潜在用水）。
{"title":"Hybrid passive cooling and heating system for Mediterranean greenhouses. Microclimate and sweet pepper crop response","authors":"Pilar Lorenzo , Rafael Reyes , Evangelina Medrano , Rosa Granados , Santiago Bonachela , Joaquín Hernández , Juan C. López , Juan J. Magán , Francisco M. del Amor , M. Cruz Sánchez-Guerrero","doi":"10.1016/j.agwat.2024.108937","DOIUrl":"https://doi.org/10.1016/j.agwat.2024.108937","url":null,"abstract":"<div><p>The microclimate of low-tech, unheated greenhouses in Mediterranean areas, associated with the local outdoor climate, is often outside the optimal range for most horticultural crops during both the warm and cold growing season. The use of a new hybrid system of passive cooling (evaporative screens) and heating (water-filled sleeves), in combination with an internal movable shading/thermal screen, was evaluated on a representative summer transplanted sweet pepper crop grown in perlite growing bags. The experiment was carried out in two identical greenhouses at the IFAPA La Mojonera research center in Almeria (SE Spain): one greenhouse with the hybrid passive system of cooling and heating, in combination with a shading/thermal screen, and another (reference greenhouse) using common local greenhouse climate management practices. Evaporative screens, in combination with a movable shading screen, improved the greenhouse climate, in particular the air vapour pressure deficit, and increased the leaf area index in the early stages of the crop, which, in turn, increased the early production of leaf and shoot dry matter and marketable fruit, compared to the reference greenhouse crop. In addition, the combined use of water-filled sleeves and thermal screen during the cold growth period increased greenhouse air temperatures, especially at night, and substrate temperatures. Overall, by improving the greenhouse microclimate during the warm and cold growth periods, the hybrid passive cooling/heating system, in combination with the shading/thermal screen, increased the marketable yield of a summer transplanted sweet pepper crop by 25 %, reduced the irrigation water supply by 8 %, and improved the irrigation water use efficiency by 20 % (including the potential water used to humidify the evaporative screens).</p></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":null,"pages":null},"PeriodicalIF":5.9,"publicationDate":"2024-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0378377424002725/pdfft?md5=9b04d27976199eff1f630c8ef7ff8839&pid=1-s2.0-S0378377424002725-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141483469","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-28DOI: 10.1016/j.agwat.2024.108924
Juan Dong , Yuanjun Zhu , Ningbo Cui , Xiaoxu Jia , Li Guo , Rangjian Qiu , Ming’an Shao
Accurate estimation of crop evapotranspiration (ET) is essential for the efficient utilization of agricultural water resources, crop production enhancement, and sustainable agricultural development. However, direct measurement of ET is highly expensive, intricate, and time-consuming, highlighting the imperative of establishing a novel model to accurately estimate ET in agricultural ecosystems. To address the above problems, this study proposed a novel model (GWA-CNN-BiLSTM), which incorporates Grey Wolf Algorithm (GWA), Convolutional Neural Network (CNN), and Bidirectional Long Short-Term Memory network (BiLSTM) as a hyperparameter adjuster, feature extractor, and regression component, respectively, to estimate ET built upon various input combinations comprising net solar radiation (Rn), vapor pressure deficit (VPD), average air temperature (Ta), soil water content (SWC), and leaf area index (LAI) about winter wheat-spring maize rotation system during 2012–2020 in the Loess Plateau. Besides, following a comparative assessment within GWA-CNN-BiLSTM, Convolutional Bidirectional Long Short-Term Memory network (CNN-BiLSTM), BiLSTM, Long Short-Term Memory network (LSTM), and Shuttleworth-Wallace (SW) models, the results revealed that GWA-CNN-BiLSTM under varied inputs obtained the superior performance, ranging from 0.562 to 0.957 in determination coefficient (R2), 8.4–41.5 % in relative root mean square error (RRMSE), 0.349 mm d−1 to 1.521 mm d−1 in mean absolute error (MAE), −3.26 % to 14.11 % in percent bias (PBIAS), and 0.820–1.091 in regression coefficient (b0), respectively. Moreover, while the accuracy of BiLSTM over LSTM was evident, its performance was notably improved by the incorporation of the CNN module. Additionally, LSTM-type models under complete input combination present better precision than SW by 29.7−51.4 % in R2, 44.2−76.1 % in RRMSE, and 33.6−63.4 % in MAE, respectively. Furthermore, the accuracy of all models under varied inputs exhibited excellence in winter wheat compared to spring maize, and corresponding improvements ranged 1.4−4.3 % in R2, 5.1−20.1 % in RRMSE, and 3.1−17.9 % in MAE, respectively. Besides, the meteorological factors (Rn, VPD, Ta) proved to be the most important inputs for ET estimation in winter wheat and spring maize. Wherein the importance of SWC exceeded that of LAI in winter wheat, while the opposite trend was observed in spring maize. In brief, GWA-CNN-BiLSTM is the highly recommended model to estimate ET of winter wheat-spring maize rotation system under diverse input data scenarios in the Loess Plateau, which can facilitate to offer valuable assistance in regional agriculture water management decisions.
{"title":"Estimating crop evapotranspiration of wheat-maize rotation system using hybrid convolutional bidirectional Long Short-Term Memory network with grey wolf algorithm in Chinese Loess Plateau region","authors":"Juan Dong , Yuanjun Zhu , Ningbo Cui , Xiaoxu Jia , Li Guo , Rangjian Qiu , Ming’an Shao","doi":"10.1016/j.agwat.2024.108924","DOIUrl":"10.1016/j.agwat.2024.108924","url":null,"abstract":"<div><p>Accurate estimation of crop evapotranspiration (ET) is essential for the efficient utilization of agricultural water resources, crop production enhancement, and sustainable agricultural development. However, direct measurement of ET is highly expensive, intricate, and time-consuming, highlighting the imperative of establishing a novel model to accurately estimate ET in agricultural ecosystems. To address the above problems, this study proposed a novel model (GWA-CNN-BiLSTM), which incorporates Grey Wolf Algorithm (GWA), Convolutional Neural Network (CNN), and Bidirectional Long Short-Term Memory network (BiLSTM) as a hyperparameter adjuster, feature extractor, and regression component, respectively, to estimate ET built upon various input combinations comprising net solar radiation (R<sub>n</sub>), vapor pressure deficit (VPD), average air temperature (T<sub>a</sub>), soil water content (SWC), and leaf area index (LAI) about winter wheat-spring maize rotation system during 2012–2020 in the Loess Plateau. Besides, following a comparative assessment within GWA-CNN-BiLSTM, Convolutional Bidirectional Long Short-Term Memory network (CNN-BiLSTM), BiLSTM, Long Short-Term Memory network (LSTM), and Shuttleworth-Wallace (SW) models, the results revealed that GWA-CNN-BiLSTM under varied inputs obtained the superior performance, ranging from 0.562 to 0.957 in determination coefficient (R<sup>2</sup>), 8.4–41.5 % in relative root mean square error (RRMSE), 0.349 mm d<sup>−1</sup> to 1.521 mm d<sup>−1</sup> in mean absolute error (MAE), −3.26 % to 14.11 % in percent bias (PBIAS), and 0.820–1.091 in regression coefficient (b<sub>0</sub>), respectively. Moreover, while the accuracy of BiLSTM over LSTM was evident, its performance was notably improved by the incorporation of the CNN module. Additionally, LSTM-type models under complete input combination present better precision than SW by 29.7−51.4 % in R<sup>2</sup>, 44.2−76.1 % in RRMSE, and 33.6−63.4 % in MAE, respectively. Furthermore, the accuracy of all models under varied inputs exhibited excellence in winter wheat compared to spring maize, and corresponding improvements ranged 1.4−4.3 % in R<sup>2</sup>, 5.1−20.1 % in RRMSE, and 3.1−17.9 % in MAE, respectively. Besides, the meteorological factors (R<sub>n</sub>, VPD, T<sub>a</sub>) proved to be the most important inputs for ET estimation in winter wheat and spring maize. Wherein the importance of SWC exceeded that of LAI in winter wheat, while the opposite trend was observed in spring maize. In brief, GWA-CNN-BiLSTM is the highly recommended model to estimate ET of winter wheat-spring maize rotation system under diverse input data scenarios in the Loess Plateau, which can facilitate to offer valuable assistance in regional agriculture water management decisions.</p></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":null,"pages":null},"PeriodicalIF":5.9,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0378377424002592/pdfft?md5=df31a5a2a07aa9dd0748e63883a00935&pid=1-s2.0-S0378377424002592-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141463207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Turkestan region in the southern part of Kazakhstan is currently facing a water scarcity issue due to various factors. These factors include the declining transboundary flow of the Syr Darya River, the effects of climate change, the increasing population, and the economic growth of neighboring countries in Central Asia. The water availability of the operating irrigation systems in the region fluctuates between 75 % and 95 %, dropping to 50–60 % in dry years, leading to a significant shortage of water resources. In particular, the agro-industrial complex, the largest water consumer, is heavily affected, with over 80 % of available water resources needed for irrigation. Therefore, this research aimed to investigate the potential use of groundwater and collector-drainage water to enhance water availability in the Maktaaral district of this region. The research methodology consisted of analytical and experimental studies to examine the formation and contribution of groundwater to total water consumption based on its depth and to determine the qualitative composition of collector-drainage water for reuse in irrigation. The study results indicate substantial losses of irrigation water due to filtration in the region, leading to a significant rise in the groundwater table. Consequently, the area of irrigated lands with groundwater depths up to 1 m (hydromorphic regime) in the Maktaaral district increased from 105 ha in 1994–378 ha in 2002 and to 2562 ha in 2021, representing an 18-fold increase. Under these conditions, the contribution of groundwater to total water consumption was 74 %, with irrigation water accounting for 26 %. In areas with a semihydromorphic soil regime where the groundwater table varies within 2–3 m, the volume of groundwater consumption decreased, amounting to 51 % of the total water consumption. Moreover, under the automorphous soil regime, where the groundwater table is greater than 3 m, the total water consumption was fully supported by irrigation water. Research on the qualitative composition of collector-drainage water in the Maktaaral district revealed a predominance of toxic salts (74.3–76.6 %), indicating that their use for irrigation would lead to soil salinization and alkalinization. The reuse of these waters is feasible only through mixing them with irrigation water to reduce salinity and increase the volume of suitable water resources for irrigation. However, regular monitoring of the chemical composition of such waters is essential.
{"title":"The possibility of using groundwater and collector-drainage water to increase water availability in the Maktaaral district of the Turkestan region of Kazakhstan","authors":"Dyuisenkhan Ayana , Zhaparkulova Yermekkul , Yerlan Issakov , Mirdadayev Mirobit , Aldiyarova Ainura , Kaipbayev Yerbolat , Kalmashova Ainur , Zhoya Kairat , Kai Zhu , Lóránt Dénes Dávid","doi":"10.1016/j.agwat.2024.108934","DOIUrl":"10.1016/j.agwat.2024.108934","url":null,"abstract":"<div><p>The Turkestan region in the southern part of Kazakhstan is currently facing a water scarcity issue due to various factors. These factors include the declining transboundary flow of the Syr Darya River, the effects of climate change, the increasing population, and the economic growth of neighboring countries in Central Asia. The water availability of the operating irrigation systems in the region fluctuates between 75 % and 95 %, dropping to 50–60 % in dry years, leading to a significant shortage of water resources. In particular, the agro-industrial complex, the largest water consumer, is heavily affected, with over 80 % of available water resources needed for irrigation. Therefore, this research aimed to investigate the potential use of groundwater and collector-drainage water to enhance water availability in the Maktaaral district of this region. The research methodology consisted of analytical and experimental studies to examine the formation and contribution of groundwater to total water consumption based on its depth and to determine the qualitative composition of collector-drainage water for reuse in irrigation. The study results indicate substantial losses of irrigation water due to filtration in the region, leading to a significant rise in the groundwater table. Consequently, the area of irrigated lands with groundwater depths up to 1 m (hydromorphic regime) in the Maktaaral district increased from 105 ha in 1994–378 ha in 2002 and to 2562 ha in 2021, representing an 18-fold increase. Under these conditions, the contribution of groundwater to total water consumption was 74 %, with irrigation water accounting for 26 %. In areas with a semihydromorphic soil regime where the groundwater table varies within 2–3 m, the volume of groundwater consumption decreased, amounting to 51 % of the total water consumption. Moreover, under the automorphous soil regime, where the groundwater table is greater than 3 m, the total water consumption was fully supported by irrigation water. Research on the qualitative composition of collector-drainage water in the Maktaaral district revealed a predominance of toxic salts (74.3–76.6 %), indicating that their use for irrigation would lead to soil salinization and alkalinization. The reuse of these waters is feasible only through mixing them with irrigation water to reduce salinity and increase the volume of suitable water resources for irrigation. However, regular monitoring of the chemical composition of such waters is essential.</p></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":null,"pages":null},"PeriodicalIF":5.9,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0378377424002695/pdfft?md5=9d63fd624a0f999944e2626e5d18f8ec&pid=1-s2.0-S0378377424002695-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141463490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-28DOI: 10.1016/j.agwat.2024.108939
Bing Yu , Songhao Shang
The increasing demand for food due to population growth and climate change poses significant challenges to achieve the Sustainable Development Goal of zero hunger by 2030. A key aspect in overcoming these challenges is to determine appropriate planting patterns for various crops, aimed at enhancing regional-scale crop water productivity despite the constraints of limited water and land resources. Remote sensing data and models provide the possibility for accurately estimating water productivity of different crops on a regional scale, but studies on remote sensing-based assessments of regional crop water productivity and its applications in agricultural management are still limited. In this study, we present a satellite-based integrated approach to assess crop planting suitability based on regional crop water productivity estimation. Focusing on the Hetao Irrigation District (HID) in the upper Yellow River basin, a representative irrigation district in arid region of Northwest China, we first use remote sensing data (HJ-1A/1B) to estimate water productivity for the two major crops, maize and sunflower, within the HID from evapotranspiration and yield estimates. Additionally, we introduce a novel crop planting suitability index based on the frequency distribution of crop water productivity, facilitating the determination of appropriate crop planting patterns. Our findings reveal that Dengkou, the periphery of Hangjinhouqi, and the southern part of Linhe are optimal for maize cultivation, while Wuyuan and the northern part of Linhe are ideal for sunflower cultivation. This is attributed to higher water productivity levels for maize in Dengkou (2.46 kg/m³) and Linhe (2.15 kg/m³), and for sunflower in Wuyuan (0.86 kg/m³). Following the optimization of crop planting distribution, the average water productivity for maize and sunflower increases by 7.6 % and 5.0 %, respectively. The proposed method can be generalized to other regions, and the results offer valuable insights for local governments in decision-making to regulate cropping pattern and maximize regional crop water productivity.
{"title":"Integrated assessment of crop planting suitability: A case study in the Hetao Irrigation District of China using HJ-1A/1B satellite data","authors":"Bing Yu , Songhao Shang","doi":"10.1016/j.agwat.2024.108939","DOIUrl":"10.1016/j.agwat.2024.108939","url":null,"abstract":"<div><p>The increasing demand for food due to population growth and climate change poses significant challenges to achieve the Sustainable Development Goal of zero hunger by 2030. A key aspect in overcoming these challenges is to determine appropriate planting patterns for various crops, aimed at enhancing regional-scale crop water productivity despite the constraints of limited water and land resources. Remote sensing data and models provide the possibility for accurately estimating water productivity of different crops on a regional scale, but studies on remote sensing-based assessments of regional crop water productivity and its applications in agricultural management are still limited. In this study, we present a satellite-based integrated approach to assess crop planting suitability based on regional crop water productivity estimation. Focusing on the Hetao Irrigation District (HID) in the upper Yellow River basin, a representative irrigation district in arid region of Northwest China, we first use remote sensing data (HJ-1A/1B) to estimate water productivity for the two major crops, maize and sunflower, within the HID from evapotranspiration and yield estimates. Additionally, we introduce a novel crop planting suitability index based on the frequency distribution of crop water productivity, facilitating the determination of appropriate crop planting patterns. Our findings reveal that Dengkou, the periphery of Hangjinhouqi, and the southern part of Linhe are optimal for maize cultivation, while Wuyuan and the northern part of Linhe are ideal for sunflower cultivation. This is attributed to higher water productivity levels for maize in Dengkou (2.46 kg/m³) and Linhe (2.15 kg/m³), and for sunflower in Wuyuan (0.86 kg/m³). Following the optimization of crop planting distribution, the average water productivity for maize and sunflower increases by 7.6 % and 5.0 %, respectively. The proposed method can be generalized to other regions, and the results offer valuable insights for local governments in decision-making to regulate cropping pattern and maximize regional crop water productivity.</p></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":null,"pages":null},"PeriodicalIF":5.9,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0378377424002749/pdfft?md5=a44f758051b3a11ca3c7a9f5639593d4&pid=1-s2.0-S0378377424002749-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141463343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-21DOI: 10.1016/j.agwat.2024.108926
Bouthayna El Amine , Fatema Mosseddaq , Abdelhadi Ait Houssa , Ahmed Bouaziz , Lhoussaine Moughli , Abdallah Oukarroum
Water and iron are crucial elements for soybean growth and development, particularly in calcareous soils and arid climatic conditions. The aim of this study was to improve iron and water use efficiency and enhance soybean resilience to water scarcity and iron deficiency. So, the effect of 16 treatments; 4 deficit irrigation water regimes (25, 50, 75 and 100 % crop water requirements (CWR)) combined to 4 foliar iron gradual concentrations (F0=0, F1=1, F2=3 and F3=5 g/L of FeSO4) applied at 3–4 leaves, at the beginning of flowering and at the end of flowering; was investigated in this split plot experiment with 4 replicates. Our results showed that supplying iron and water to plants can improve chlorophyll florescence a, chlorophyll content, stomatal conductance, yield, iron uptake, and protein content. Determining the optimal combination of deficit irrigation treatment and gradual iron sulfate concentrations for soybean is an alternative to save water and improve growth parameters. In our manuscript, we can conclude that 75 % CWR × F2 is the best combination of the two factors that led to the same biological yield as 100 % CWR. Consequently, we can say that applying F2 as a foliar iron concentration led to an economy of 25 % of the soybean crop water requirement by ensuring an adequate supply of soluble iron, facilitating root uptake, promoting protein synthesis, enhancing chlorophyll formation, and supporting overall nutrient uptake and metabolism.
{"title":"How far can the interactive effects of continuous deficit irrigation and foliar iron fertilization improve the physiological and agronomic status of soybeans grown in calcareous soils under arid climate conditions?","authors":"Bouthayna El Amine , Fatema Mosseddaq , Abdelhadi Ait Houssa , Ahmed Bouaziz , Lhoussaine Moughli , Abdallah Oukarroum","doi":"10.1016/j.agwat.2024.108926","DOIUrl":"https://doi.org/10.1016/j.agwat.2024.108926","url":null,"abstract":"<div><p>Water and iron are crucial elements for soybean growth and development, particularly in calcareous soils and arid climatic conditions. The aim of this study was to improve iron and water use efficiency and enhance soybean resilience to water scarcity and iron deficiency. So, the effect of 16 treatments; 4 deficit irrigation water regimes (25, 50, 75 and 100 % crop water requirements (CWR)) combined to 4 foliar iron gradual concentrations (F0=0, F1=1, F2=3 and F3=5 g/L of FeSO<sub>4</sub>) applied at 3–4 leaves, at the beginning of flowering and at the end of flowering; was investigated in this split plot experiment with 4 replicates. Our results showed that supplying iron and water to plants can improve chlorophyll florescence a, chlorophyll content, stomatal conductance, yield, iron uptake, and protein content. Determining the optimal combination of deficit irrigation treatment and gradual iron sulfate concentrations for soybean is an alternative to save water and improve growth parameters. In our manuscript, we can conclude that 75 % CWR × F2 is the best combination of the two factors that led to the same biological yield as 100 % CWR. Consequently, we can say that applying F2 as a foliar iron concentration led to an economy of 25 % of the soybean crop water requirement by ensuring an adequate supply of soluble iron, facilitating root uptake, promoting protein synthesis, enhancing chlorophyll formation, and supporting overall nutrient uptake and metabolism.</p></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":null,"pages":null},"PeriodicalIF":5.9,"publicationDate":"2024-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0378377424002610/pdfft?md5=d0c3a64ca5a3daeeb8cf3b1304c5d891&pid=1-s2.0-S0378377424002610-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141433837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-20DOI: 10.1016/j.agwat.2024.108927
Suat Irmak
Grain yield, irrigation-yield production functions (IYPFs), evapotranspiration-yield production functions (ETYPFs), total soil water-yield production function (TSWYPF), crop evapotranspiration (ETc), and basal ET (ETb) response of subsurface drip-irrigated (SDI) maize were investigated under full irrigation treatment (FIT), 75 % FIT, 50 % FIT, and rainfed (RF). Yield response to irrigation differed significantly (P<0.05) between the treatments with FIT having the highest grain yield, followed by 75 % FIT, 50 % FIT, and RF in all growing seasons. There was a 14, 6, and 12 % yield reduction in 75 % FIT, 50 % FIT, and RF with respect to FIT, respectively. FIT had the highest ETc, followed by 75 % FIT, 50 % FIT, and RF. ETc reduction with 75 % FIT, 50 % FIT and RF with respect to FIT had similar reductions between the years. Under these experimental conditions, ETc of SDI-irrigated maize can be expected to be reduced by 5.2 % (25 mm), 13 % (65 mm), and 26 % (130 mm) with the limited irrigation (75 % FIT and 50 % FIT) and RF, respectively. The amount of irrigation water required for maximum grain yield varied between the growing seasons as a function of climatic conditions (262, 225, and 173 mm in 2004, 2005, and 2006, respectively). Based on the IYPFs, a 25.4 mm of irrigation application resulted in 0.061, 0.063, and 0.066 t/ha yield increase (beyond the intercept) in 2004, 2005, and 2006, respectively, with a 3-yr average of 0.063 t/ha. A 25.4 mm of irrigation application resulted in 15.6, 16.0, and 13.7 mm of increase in ETc (beyond the intercept) in 2004, 2005, and 2006 seasons, respectively, with a 3-yr average of 15.1 mm. On a three-year average basis, 10.7, 29.1, and 67 % yield reduction in 75 % FIT, 50 % FIT, and RF treatments with respect to FIT can be expected under these climate, soil-water, and crop management conditions with SDI-irrigated maize. A strong dependence of the ETYPF slopes on RF treatment’s yield was observed. ETb had substantial inter-annual variation as 356, 230, and 315 mm in 2004, 2005, and 2006, respectively. ETb was strongly and positively correlated (R2=0.99) with the seasonal precipitation and strongly, but negatively correlated (R2=0.89) with seasonal cumulative thermal unit (Growing Degree Days). Based on the pooled ETYPFs, a 25.4 mm of ETc resulted in 1.86, 1.72, and 2.61 t/ha grain yield (beyond the intercept) in 2004, 2005, and 2006, respectively, with a seasonal average of 2.1 t/ha. Data and information of this research can provide guidance for irrigation professionals, managers, advisors, engineers, agronomists, economists, and other professionals and can be incorporated into the planning, forecasting, allocating and managing of water resources availability-demand-actual use analyses and decisions to enhance crop production efficiency.
{"title":"Maize response to different subsurface drip irrigation management strategies: Yield, production functions, basal and crop evapotranspiration","authors":"Suat Irmak","doi":"10.1016/j.agwat.2024.108927","DOIUrl":"https://doi.org/10.1016/j.agwat.2024.108927","url":null,"abstract":"<div><p>Grain yield, irrigation-yield production functions (IYPFs), evapotranspiration-yield production functions (ETYPFs), total soil water-yield production function (TSWYPF), crop evapotranspiration (ET<sub>c</sub>), and basal ET (ET<sub>b</sub>) response of subsurface drip-irrigated (SDI) maize were investigated under full irrigation treatment (FIT), 75 % FIT, 50 % FIT, and rainfed (RF). Yield response to irrigation differed significantly (P<0.05) between the treatments with FIT having the highest grain yield, followed by 75 % FIT, 50 % FIT, and RF in all growing seasons. There was a 14, 6, and 12 % yield reduction in 75 % FIT, 50 % FIT, and RF with respect to FIT, respectively. FIT had the highest ET<sub>c</sub>, followed by 75 % FIT, 50 % FIT, and RF. ET<sub>c</sub> reduction with 75 % FIT, 50 % FIT and RF with respect to FIT had similar reductions between the years. Under these experimental conditions, ET<sub>c</sub> of SDI-irrigated maize can be expected to be reduced by 5.2 % (25 mm), 13 % (65 mm), and 26 % (130 mm) with the limited irrigation (75 % FIT and 50 % FIT) and RF, respectively. The amount of irrigation water required for maximum grain yield varied between the growing seasons as a function of climatic conditions (262, 225, and 173 mm in 2004, 2005, and 2006, respectively). Based on the IYPFs, a 25.4 mm of irrigation application resulted in 0.061, 0.063, and 0.066 t/ha yield increase (beyond the intercept) in 2004, 2005, and 2006, respectively, with a 3-yr average of 0.063 t/ha. A 25.4 mm of irrigation application resulted in 15.6, 16.0, and 13.7 mm of increase in ET<sub>c</sub> (beyond the intercept) in 2004, 2005, and 2006 seasons, respectively, with a 3-yr average of 15.1 mm. On a three-year average basis, 10.7, 29.1, and 67 % yield reduction in 75 % FIT, 50 % FIT, and RF treatments with respect to FIT can be expected under these climate, soil-water, and crop management conditions with SDI-irrigated maize. A strong dependence of the ETYPF slopes on RF treatment’s yield was observed. ET<sub>b</sub> had substantial inter-annual variation as 356, 230, and 315 mm in 2004, 2005, and 2006, respectively. ET<sub>b</sub> was strongly and positively correlated (R<sup>2</sup>=0.99) with the seasonal precipitation and strongly, but negatively correlated (R<sup>2</sup>=0.89) with seasonal cumulative thermal unit (Growing Degree Days). Based on the pooled ETYPFs, a 25.4 mm of ET<sub>c</sub> resulted in 1.86, 1.72, and 2.61 t/ha grain yield (beyond the intercept) in 2004, 2005, and 2006, respectively, with a seasonal average of 2.1 t/ha. Data and information of this research can provide guidance for irrigation professionals, managers, advisors, engineers, agronomists, economists, and other professionals and can be incorporated into the planning, forecasting, allocating and managing of water resources availability-demand-actual use analyses and decisions to enhance crop production efficiency.</p></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":null,"pages":null},"PeriodicalIF":6.7,"publicationDate":"2024-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0378377424002622/pdfft?md5=648e4518860a1d9221d4670cc623d543&pid=1-s2.0-S0378377424002622-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141429484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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