Agricultural Water Management最新文献

{"title":"Deficit irrigation and biostimulation preconditioning to improve drought resistance in melon","authors":"Susana Zapata-García, Abdelmalek Temnani, Pablo Berríos, Pedro J. Espinosa, Claudia Monllor, Alejandro Pérez-Pastor","doi":"10.1016/j.agwat.2025.109311","DOIUrl":"https://doi.org/10.1016/j.agwat.2025.109311","url":null,"abstract":"The need to increase crop water productivity under low water availability conditions, leads not only to the use of technology for real-time soil water monitoring, but also to test the response of certain products, such as algae-based biostimulants, on the agronomy and physiology response of the plants. The aim of this study was to assess the effect of different sustainable strategies to maximize water productivity on melon plants, by monitoring the soil water status using sensors, reduce water inputs in a non-critical period of the melon growth and by preconditioning plants to cope with water stress by the application of a commercial biostimulant based on <ce:italic>Ascophyllum nodosum</ce:italic> extract, Seamac Rhizo®. With special emphasis on understanding the physiological response that these plants develop to respond to water stress. Four treatments were evaluated: (i) a farmer treatment, irrigated at 100 % ET<ce:inf loc=\"post\">c</ce:inf>, (ii) a precision irrigation (PI) treatment, irrigated with a threshold of 20 % soil water depletion in the active root uptake zone, between flowering and ripening, otherwise irrigated as FARM; (iii) an irrigation suppression (IS) treatment, irrigated as PI for the most of the cycle, except between 42 and 55 days after transplant (swelling of the first fruits), when irrigation was totally suppressed; (iv) a biostimulated irrigation suppression treatment (ISb), irrigated as IS with two applications of biostimulant during vegetative development. Our results indicate that under the severe water deficit applied, melon plants did not reduce their marketable yield with respect to the PI treatment due to leaf osmotic adjustment. Moreover, biostimulated plants (ISb) exhibited an enhanced water root absorption, which enabled them to increase their yield by a 44 % compared to IS treatment. This fact increased the irrigation water productivity by 53 % and 44 % with respect to the PI and IS treatments, respectively. Furthermore, harvested fruits from the biostimulated treatment showed a higher concentration of phenolics compounds compared to PI. Therefore, the incorporation of plant biostimulation is proposed as a sustainable strategy to increase water productivity and enhance functional fruit quality.","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"32 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143020015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of combined nitrogen and phosphorus fertilization on summer maize yield and soil fertility in coastal saline-alkali land","authors":"Changjian Ma, Wu Wenbiao, Peng Hou, Yue Wang, Bowen Li, Huabin Yuan, Lining Liu, Xuejun Wang, Zeqiang Sun, Yan Li","doi":"10.1016/j.agwat.2024.109277","DOIUrl":"https://doi.org/10.1016/j.agwat.2024.109277","url":null,"abstract":"Soil salinization limits food production and land use efficiency. Proper nitrogen and phosphate fertilizer application can improve saline soils, but the optimal ratio under saline-alkali conditions is unclear. This experiment set different nitrogen fertilizer application rates (60 kg/hm<ce:sup loc=\"post\">2</ce:sup>, 120 kg/hm<ce:sup loc=\"post\">2</ce:sup>) and phosphate fertilizer application rates (40 kg/hm<ce:sup loc=\"post\">2</ce:sup>, 80 kg/hm<ce:sup loc=\"post\">2</ce:sup>, 120 kg/hm<ce:sup loc=\"post\">2</ce:sup>). The results showed that various nitrogen and phosphate fertilizer treatments had significant effects on grain yield, biomass yield, and soil nutrients. The T3 treatment (nitrogen fertilizer: 120 kg/hm², phosphate fertilizer: 120 kg/hm²) resulted in the highest yields, with the average grain yield and biomass yield of maize over three growing seasons being 6.70 × 10 ³ kg/hm² and 17.53 × 10 ³ kg/hm², respectively. For the three-year average, the alkaline hydrolyzable nitrogen content (228.70 mg/kg), nitrogen uptake (199.75 mg/kg) and average phosphorus uptake (239.89 mg/kg) was highest under the T3 treatment. The yield of summer maize is directly influenced by factors such as alkaline hydrolysable nitrogen, available phosphorus, readily available potassium in the soil, nitrogen uptake, phosphorus uptake, potassium uptake, soil moisture content at 0–20 cm and 20–40 cm depths. Among these, phosphorus uptake (Standardized Path Coefficient (SPC) = 0.65) and potassium uptake (SPC=0.57) have the greatest impact on the increase in grain yield (GY). The optimal application rates for maize production in saline-alkali soil are 120 kg/hm² for nitrogen fertilizer and 120 kg/hm² for phosphate fertilizer. These results can provide a theoretical basis for fertilizer management in maize production on saline-alkali land.","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"70 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143020045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hydrothermal conditions dominated sensitivity and lag effect of grassland productivity in Yunnan Province, China: Implications for climate change","authors":"Yan Fang, Long Wan, Jing Tong, Guijing Li, Jing Pang, Enfu Chang, Linglan Chen, Zixuan Shi","doi":"10.1016/j.agwat.2025.109293","DOIUrl":"https://doi.org/10.1016/j.agwat.2025.109293","url":null,"abstract":"Net primary productivity (NPP) is an important indicator of carbon and water cycles in grassland ecosystems and is highly sensitive to climate change. This study focused on grassland and its sub-regions in Yunnan Province and analyzed the productivity of grassland ecosystems under different hydrothermal conditions from 2001 to 2021. The results indicated that grassland experienced a warming and drying trend, with an overall upward trend averaging 5.30 gC·m<ce:sup loc=\"post\">−2</ce:sup>·a<ce:sup loc=\"post\">−1</ce:sup>. Notably, the central Yunnan Plateau region boasted the highest productivity growth rate, reaching 7.67 gC·m<ce:sup loc=\"post\">−2</ce:sup>·a<ce:sup loc=\"post\">−1</ce:sup>. The response of grassland productivity to climate change under different hydrothermal conditions exhibited distinct spatial heterogeneity and complexity. Grasslands in the hot and humid zone of southwestern Yunnan presented the highest sensitivity to changes in precipitation, temperature, and solar radiation, at 3.08 (gC·m<ce:sup loc=\"post\">−2</ce:sup>·a<ce:sup loc=\"post\">−1</ce:sup>)/mm, 53.3 (gC·m<ce:sup loc=\"post\">−2</ce:sup>·a<ce:sup loc=\"post\">−1</ce:sup>)/°C, and 4.07 (gC·m<ce:sup loc=\"post\">−2</ce:sup>·a<ce:sup loc=\"post\">−1</ce:sup>)/(MJ·m<ce:sup loc=\"post\">−2</ce:sup>), respectively. In the Qinghai-Tibetan Plateau alpine region, rising temperatures contributed to productivity growth. In contrast, warmer temperatures and water stress led to a decline in grassland productivity in the hot and dry vally of the Jinsha River. In addition, grassland productivity showed variable lag effects in different hydrothermal regions. The areas where grassland productivity with a 3-month lag effects in response to temperature, precipitation, and solar radiation accounted for 25.26 %, 34.52 %, and 16.04 % of the region, respectively. The grassland productivity responses to temperature and precipitation exhibited a long lag effect, primarily observed in dry and hot areas. This study is crucial for guiding adaptive vegetation management in Yunnan grassland ecosystems under different hydrothermal conditions to better cope with climate change.","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"93 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142986280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Generating high-precision farmland irrigation pattern maps using remotely sensed ecological indices and machine learning algorithms","authors":"Yuqi Liu, Yang Wang, Yanling Liao, Renkuan Liao, Jirka Šimůnek","doi":"10.1016/j.agwat.2025.109302","DOIUrl":"https://doi.org/10.1016/j.agwat.2025.109302","url":null,"abstract":"Conducting field investigations of farmland irrigation patterns on a large scale is a time-consuming and labor-intensive task. The traditional approach of employing satellite remote sensing for large-scale visual assessments is impractical for identifying irrigation patterns due to interference caused by vegetation cover. To address this, we utilized the Google Earth Engine (GEE) platform, integrating environmental covariates and machine learning algorithms, to generate distribution maps of irrigation patterns (micro-irrigation and surface irrigation) at a 30-meter resolution for the Turpan-Hami Basin. Results demonstrate that the Classification and Regression Tree (CART) model achieved a classification accuracy of 0.81, effectively distinguishing between different irrigation patterns. The analysis of feature importance determined NDVI (<ce:italic>i.e.</ce:italic>, Normalized Difference Vegetation Index), EVI (<ce:italic>i.e.</ce:italic>, Enhanced Vegetation Index), MSI (<ce:italic>i.e.</ce:italic>, Moisture Stress Index), Ec (<ce:italic>i.e.</ce:italic>, Transpiration), and NDWI (<ce:italic>i.e.</ce:italic>, Normalized Difference Water Index) as the key indicators linked to irrigation patterns. Regional mapping findings reveal an increase in the proportion of micro-irrigation from 40.2 % in 2015 to 47.0 % in 2023, underscoring the successful implementation of water-saving practices in the Turpan-Hami Basin. Additionally, we developed a GEE-based interactive interface, which enables users to generate corresponding distribution maps of irrigation patterns by selecting a specific year, offering uesful data support for policymakers and farmers to better manage agricultural water resources.","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"37 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142986279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development potential of multi-cropping systems and its influence on agricultural water consumption in the Huang–Huai–Hai River Basin of China","authors":"Linghui Li, Qingming Wang, Yong Zhao, Jiaqi Zhai, Haihong Li, Shuying Han, Lichuan Wang, Yunpeng Gui","doi":"10.1016/j.agwat.2025.109298","DOIUrl":"https://doi.org/10.1016/j.agwat.2025.109298","url":null,"abstract":"The impact of global warming on the cropping system (CS) has been increasingly emphasized, and it is essential to analyze the changing pattern of the CS and the impact of agricultural water consumption (AWC) for timely adjustment of the crop and water management. This study analyzed the spatial-temporal changes of the actual and potential CS based on the remote sensing and meteorological dataset from 2001 to 2022 to explore the development potentiality of multi-cropping systems (MCS), and adapted the CS change into the Decision Support System for Agrotechnology Transfer model (DSSAT) to simulate the change of evapotranspiration. The results indicated that in the past 22 years, both of the actual and potential CS have shown a trend of transition to MCS with an area of 187.4 thousand km<ce:sup loc=\"post\">2</ce:sup> and 215.4 thousand km<ce:sup loc=\"post\">2</ce:sup>. The duration of the accumulated temperature above 10°C have prolonged at a rate of 5.2 days decade<ce:sup loc=\"post\">–1</ce:sup>, which shortened the length of growth season (LOS) of the single CS, double CS, triple CS and triple in two years CS by 1.2 days decade<ce:sup loc=\"post\">–1</ce:sup>, 0.8 days decade<ce:sup loc=\"post\">–1</ce:sup>, 2.3 days decade<ce:sup loc=\"post\">–1</ce:sup>, and 0.2 days decade<ce:sup loc=\"post\">–1</ce:sup>, respectively. Warming promoted the transformation to MCS with 64.25 % (35.3 %) potential of area distribution (growth period), and the region with the greatest potential was the mountainous area in the Yellow River Basin. The simulated average evapotranspiration was 491.2 mm per year with an increasing by 30.51 %, and would further increase by 57.28 % after the development of MCS.","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"14 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142986285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A new regional reference evapotranspiration model based on quantile approximation of meteorological variables","authors":"Guomin Huang, Jianhua Dong, Lifeng Wu, Jingwei Luo, Rangjian Qiu, Yaokui Cui, Yicheng Wang","doi":"10.1016/j.agwat.2025.109299","DOIUrl":"https://doi.org/10.1016/j.agwat.2025.109299","url":null,"abstract":"Reference evapotranspiration (ETo) is a variable that can assist in estimating agricultural water use in water-scarce regions. Estimating ETo with limited data is an important alternative to overcome the current shortage of meteorological data in many areas around the world. For this purpose, this study introduces a new method for establishing a simplified regional ETo model. The method, which creating ETo models based on temperature at meteorological stations that have the highest quantile matching with the target station's meteorological variables based on the closest meteorological data characteristics. To test the performance of the new method, we used data from 120 meteorological stations in Northwest China from 2000 to 2021 to develop XGBoost models to establish the new regional ETo model. We compared the proposed method with local models and two conventional regional ETo models to evaluate its performance. While the new method increased the Root Mean Square Error (RMSE) by an average of 13.4 % compared to local models, it demonstrated significant advantages over conventional regional models. Specifically, the RMSE decreased by 6.4–7.1 %, the Normalized RMSE (NRMSE) decreased by 5.5–7.3 %, computation time was reduced by 18.4–21.8 times, and spatial memory usage was reduced by 147–211 %. These improvements make the proposed method more efficient and scalable, particularly for regional applications in data-scarce areas.","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"53 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142986284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Responses of dry edible bean crop growth and water productivities under different irrigation scenarios in the U.S. high plains","authors":"Angie Gradiz, Xin Qiao, Saleh Taghvaeian, Wei-zhen Liang, Daran Rudnick, Abia Katimbo, Jun Wang, Swathi Palle","doi":"10.1016/j.agwat.2024.109280","DOIUrl":"https://doi.org/10.1016/j.agwat.2024.109280","url":null,"abstract":"Dry edible bean is an important crop for protein sources worldwide. As freshwater resources become increasingly constrained, understanding how dry beans respond to different irrigation regimes and identifying optimal irrigation management strategies becomes crucial for maintaining adequate yields. This three-year (2021–2023) study investigated the impacts of irrigation treatments, ranging from rainfed to over-irrigated conditions, on soil water dynamics, canopy cover, leaf area index, yield, actual evapotranspiration, and water productivities for dry edible beans grown in western Nebraska, U.S. Although dry beans are often considered a shallow-rooted crop, our results demonstrated their ability to adapt to drought stress by extracting soil water from significantly deeper depths than previously expected. Results also revealed that reducing irrigation by 25 % did not significantly decrease yields across all three growing seasons. The pooled normalized biomass water productivity (WP<ce:inf loc=\"post\">b</ce:inf>) was 16.5 g m<ce:sup loc=\"post\">−2</ce:sup> with an R<ce:sup loc=\"post\">2</ce:sup> of 0.68. This quantified WP<ce:inf loc=\"post\">b</ce:inf> can be valuable for future crop modeling simulations, such as those using FAO's AquaCrop model.","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"2 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142986286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Increasing exposure of cotton growing areas to compound drought and heat events in a warming climate","authors":"Shengli Liu, Wei Zhang, Tongtong Shi, Tong Li, Hui Li, Guanyin Zhou, Zhanbiao Wang, Xiongfeng Ma","doi":"10.1016/j.agwat.2025.109307","DOIUrl":"https://doi.org/10.1016/j.agwat.2025.109307","url":null,"abstract":"Cotton (<ce:italic>Gossypium hirsutum L.</ce:italic>) is a critical source of natural fiber and cottonseed oil for humans, yielding substantial economic benefits globally. However, the susceptibility of cotton cultivation to compound drought and heat events (CDHEs) brings significant threats to cotton productivity. Despite this, a comprehensive assessment of global CDHE occurrence over cotton-growing areas and its potential impacts on cotton yields remains unresolved, hindering efforts to implement adaptive strategies to ensure global cotton productivity. To address this gap, we analyzed changes in mean temperature and soil moisture within global cotton-growing areas during their respective growing seasons, estimated the probability of CDHEs across multiple spatial scales via copula theorems, and examined the relationship between cotton yield anomalies and CDHEs in major cotton countries. Our results indicate increasing but divergent trends in mean temperature and soil moisture. Specifically, while most regions exhibit drying trends, India and Pakistan show significant wetting trends, with soil moisture increasing during the cotton growing season. The global average probability of CDHEs between 1961–1990 and 1991–2020 showed a more than threefold increase in severity, with such an increase occurring in approximately 61 % of cotton-growing areas due to comparable contributions from drying and warming trends. Furthermore, major cotton-producing countries exhibited similar CDHE trends, leading to a heightened probability of synchronous CDHE occurrences, except in countries connected to India and Pakistan. Such occurrences of CDHEs are significantly related to cotton yield failures in major cotton-producing countries. Our findings emphasize the growing exposures of cotton-growing areas to CDHEs and highlight the urgent need for adaptive strategies to enhance the resilience of cotton production systems under changing climatic conditions.","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"24 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142986282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unraveling the interplay between NDVI, soil moisture, and snowmelt: A comprehensive analysis of the Tibetan Plateau agroecosystem","authors":"Di Wei, Lin Yan, Ziqi Zhang, Jia Yu, Xue’er Luo, Yun Zhang, Bo Wang","doi":"10.1016/j.agwat.2025.109306","DOIUrl":"https://doi.org/10.1016/j.agwat.2025.109306","url":null,"abstract":"The rapid changing climate conditions within Tibetan Plateau determine the complex interaction between vegetation succession and agricultural water resources, including soil moisture and snowmelt. While previous studies have primarily focused on the coupling relationship between NDVI and soil moisture, snowmelt, as a critical water source in plateau ecosystems, plays an equally important role in regulating the water cycle. This study integrates MODIS remote sensing images and ERA5-Land meteorological reanalysis datasets to establish a ternary system encompassing NDVI, soil moisture, and snowmelt. Using geostatistical methods such as trend analysis, cross-correlation, random forest algorithm, and Granger causality, we explore the temporal dynamics and causal relationships among these ecological variables. Results indicate an overall increase in NDVI, a consistent decrease in snowmelt, and spatially heterogeneous changes in soil moisture across the Tibetan Plateau from 2001 to 2023. NDVI and soil moisture exhibit mostly instantaneous responses, with a brief one-month time-lag effect, while NDVI demonstrates a more pronounced lagged response to snowmelt. In grassland ecosystems, soil moisture lags behind snowmelt, whereas in woodlands, snowmelt lags behind soil moisture. Transitional vegetation zones reveal a regulatory feedback loop, where snowmelt predominantly influences soil moisture, which subsequently transitions to a bidirectional feedback mechanism between soil moisture and snowmelt as vegetation succession in woodland ecosystems. This study provides new insights into the feedback processes between vegetation growth and water resources in different ecological zones of Tibetan Plateau, guiding water management and sustainable development for agroecosystem.","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"205 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142986283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of practicing water-saving irrigation on greenhouse gas emissions and crop productivity: A global meta-analysis","authors":"Mingdong Tan, Ningbo Cui, Shouzheng Jiang, Liwen Xing, Shenglin Wen, Quanshan Liu, Weikang Li, Siwei Yan, Yaosheng Wang, Haochen Jin, Zhihui Wang","doi":"10.1016/j.agwat.2025.109300","DOIUrl":"https://doi.org/10.1016/j.agwat.2025.109300","url":null,"abstract":"Water-saving irrigation (WSI) is extensively utilized worldwide to address the growing disparity between dwindling water supplies and increasing food demand. Moreover, WSI has attracted extensive attention for its potential to mitigate greenhouse gas (GHG) emissions in agriculture systems. In this study, a global meta-analysis of 1230 observations from 62 publications were conducted to investigate the global patterns and underlying drive<ce:underline>r</ce:underline>s of soil GHG emissions and crop productivity (crop yield and water use efficiency) induced by WSI, and the contributions of key factors to GHG emissions and crop productivity were further quantified. The results showed that WSI significantly alleviated the agricultural greenhouse effect by reducing carbon dioxide (CO<ce:inf loc=\"post\">2</ce:inf>) emission (ln RR = −0.084, 95 %CI: −0.139 to −0.028) and methane (CH<ce:inf loc=\"post\">4</ce:inf>) emissions (ln RR = −0.551, 95 %CI: −0.640 to −0.462). Notably, the global warming potential (GWP) and greenhouse gas intensity (GHGI) significantly decreased by −0.290 (95 %CI: −0.346 to −0.234) and −0.389 (95 %CI: −0.579 to −0.199), respectively, highlighting the effectiveness of WSI in mitigating the impacts of climate change. Furthermore, water use efficiency (WUE) significantly improved by 0.265 (95 %CI: 0.203–0327). However, WSI also led to an increase in nitrous oxide (N<ce:inf loc=\"post\">2</ce:inf>O) emissions by 0.126 (95 %CI: 0.057–0.196) while a slight decrease of crop yield by −0.048 (95 %CI: −0.071 to −0.026). Climate factors such as mean annual precipitation (MAP) and temperature (MAT) directly and indirectly influenced GHG emissions and crop productivity by altering soil properties and the efficacy of fertilization practices. MAP, pH, organic carbon (OC) and bulk density (BD) were identified as key factors responsible for the emissions of CO<ce:inf loc=\"post\">2</ce:inf> (16.37 %), CH<ce:inf loc=\"post\">4</ce:inf> (17.35 %) and N<ce:inf loc=\"post\">2</ce:inf>O (20.19 %) as well as crop yield (16.21 %), respectively. Implementing WSI alongside fertilization rates of less than 100 kg/ha can balance mitigating greenhouse effect (GWP and GHGI) and maintaining crop yields. These findings emphasize the critical role of WSI in enhancing agricultural sustainability and reducing GHG emissions, thus providing valuable insights for future management strategies.","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"74 2 Pt 1 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2025-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142986317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}