Agricultural Water Management最新文献

{"title":"Synergistic management of the water-food-energy-carbon nexus in resource-constrained megaregions: A dynamic general equilibrium assessment for Beijing–Tianjin–Hebei","authors":"Shihao Shan ,&nbsp;Xichen Lin ,&nbsp;Hongzhen Ni ,&nbsp;Chaomeng Ma ,&nbsp;Jie Wang","doi":"10.1016/j.agwat.2026.110205","DOIUrl":"10.1016/j.agwat.2026.110205","url":null,"abstract":"<div><div>The intrinsic interlinkages among water, food, energy, and carbon emissions have become a critical factor of regional sustainable development. Under the low-carbon transition, the demand for coordinated policy supply to ensure water, food, and energy security has increased substantially. However, existing general equilibrium analyses of Water–Food–Energy–Carbon (WFEC) nexus policies often lack sufficient policy specificity and systemic coverage, as they tend to overlook dynamic linkages and cross-sectoral transmission processes.To address this gap, this study extends a multi-regional dynamic Computable General Equilibrium (CGE) model by explicitly representing substitution effects among multiple types of water and energy inputs, disaggregating grain production from the agricultural sector, and incorporating a carbon emissions linkage module. Oriented toward prospective policy demands in the Beijing–Tianjin–Hebei (BTH) region, the model is used to design and evaluate water-saving, food production enhancement, energy conservation and carbon reduction, as well as integrated policy scenarios, and to assess their WFEC nexus interaction effects across the three regions.The results indicate that: (1) Single-resource policies targeted at specific objectives involve substantial trade-offs, whereas the integrated scenario (S4) achieves the most synergistic effects across water saving, food production, and energy–carbon mitigation. By 2035, S4 reduces total regional water use by 3.06 %, energy consumption by 0.55 %, and carbon emissions by 2.57 %, while increasing grain produciotn by 0.41 %, at a marginal GDP loss of only 0.02 %.(2)Hebei exhibits the strongest WFEC nexus coupling,with a Policy Comprehensive Impact(PCI) gap between the integrated scenario and single-policy scenarios averages 0.366, compared with 0.447 in Beijing and 0.373 in Tianjin, and further narrows to 0.273 by 2035.(3)Effective WFEC nexus governance in the BTH megaregions requires synergistic, region-differentiated coordination framework, in which Hebei serves as the primary adjustment area for integrated regulation, while Beijing and Tianjin play complementary and stabilizing roles within the coordinated policy portfolio.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"325 ","pages":"Article 110205"},"PeriodicalIF":6.5,"publicationDate":"2026-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146146755","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 review of artificial intelligence applications for predicting crop performance and enhancing food security under drought-induced water stress","authors":"Ali Fares,&nbsp;Anoop Valiya Veettil,&nbsp;Atikur Rahman,&nbsp;Ripendra Awal","doi":"10.1016/j.agwat.2026.110212","DOIUrl":"10.1016/j.agwat.2026.110212","url":null,"abstract":"<div><div>Artificial Intelligence (AI) has emerged as a vital tool for predicting crop performance, including crop growth, diseases, and yield, and assisting in informed decision-making, such as predicting precise water management practices for sustainable water use, thereby maximizing growers’ profits. Climate change and the increasing frequency of severe droughts have significantly affected crop yields, posing a challenge to global food security. Therefore, predicting crop performance, particularly expected yield, is crucial during water stress. AI algorithms, including Random Forest (RF), Gradient Boosting Machines (GBM), Artificial Neural Networks (ANNs), and Convolutional Neural Networks (CNNs), enable the integration of weather, soil, crop, and irrigation management data to predict crop performance under drought with higher accuracy. This review focuses on the applications of AI-based models in quantifying the impact of drought on crop performance, considering nonlinear soil–plant–atmosphere interactions and the integration of spatial data through remote sensing. However, data limitations, modeling dynamic drought responses, and addressing spatial heterogeneity in drought indices pose significant challenges for AI-based predictions. Case studies demonstrate AI's potential to predict crop yields under drought conditions, with applications ranging from traditional machine learning (ML) models to advanced deep learning (DL) frameworks. However, there is no clear consensus on the best AI model for drought-induced water stress management, although ANNs and RFs are more commonly used than others in precision-based irrigation and crop yield prediction. DL-based models, such as CNN and Long Short-Term Memory (LSTM), are less frequently applied, despite their strengths in handling complex and unstructured data, as well as modeling long-term drought impacts. Refining AI algorithms to support precision irrigation scheduling, integrating AI with conventional water management practices, and enabling data-driven decision support systems will be vital for mitigating the adverse effects of drought on crop performance.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"325 ","pages":"Article 110212"},"PeriodicalIF":6.5,"publicationDate":"2026-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146146857","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":"Spatial distributed management strategies for maize high-yield and high-efficiency under different production-demand scenarios in Northwest China","authors":"Honghang Zhang ,&nbsp;Chuanbin Liang ,&nbsp;Wenxin Zhang ,&nbsp;Manoj Shukla ,&nbsp;Yu Fang ,&nbsp;Shichao Chen ,&nbsp;Taisheng Du","doi":"10.1016/j.agwat.2026.110166","DOIUrl":"10.1016/j.agwat.2026.110166","url":null,"abstract":"<div><div>Rapid warming and increasingly stringent water allocations in arid Northwest China have exacerbated the inherent trade-offs among maize yield, water productivity (WP_c) and economic returns. This study employed a statistical modeling-optimization pipeline (PLS-GA) and a machine learning-optimization pipeline (RF-GA) to build a framework for better maize production in the Hexi Corridor of Gansu Province, an arid region in northwest China. The framework uses yield and actual evapotranspiration (ET_{c act}) prediction as well as multi-objective optimization calculations. The optimal irrigation, nitrogen application, and planting density were proposed for five production-demand scenarios and the consequent impacts on yield, WP_c, and economic returns under future climate change were systematically assessed. Results showed that random forest (RF) outperformed partial least squares (PLS) regression in capturing non-linear relationships (R²= 0.80 vs. 0.51) for yield simulation, whereas PLS provided superior explanatory power for individual factors. Findings also showed that all scenarios in the historical period could have benefited from an increase in planting density by at least 13.1 % and precision planting, leading to improvements in yield, WP_c, and economic returns of at least 20.2 %, 31.4 %, and 15.1 %, respectively, alongside reductions in nitrogen application and irrigation of at least 13.7 % and 6.3 %, respectively. During mid-century (2041–2050), planting density and irrigation were projected to decline 0.4–1.1 % and 0.1–3.5 %, respectively, while nitrogen application to increase by 4.7–9.9 %. These adaptive measures lead to enhanced yield (5.8–6.2 %) and economic returns (13.8–14.7 %), albeit with a decline in WP_c (13.1–14.5 %). This study presents an integrated maize management strategy that simultaneously optimizes grain yield, WP_c, and economic returns in the Hexi Corridor, while also contributing a scalable methodological framework for advancing climate-resilient agricultural practices in arid, irrigated agroecosystems of Northwest China and comparable regions.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"325 ","pages":"Article 110166"},"PeriodicalIF":6.5,"publicationDate":"2026-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145995187","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":"Spatio-temporal HYDRUS-1D soil water balance simulations as support for precision irrigation in North-Eastern Germany","authors":"Jan Lukas Wenzel ,&nbsp;Christopher Conrad ,&nbsp;Talha Mahmood ,&nbsp;Matthias Kunz ,&nbsp;Martin Volk ,&nbsp;Julia Pöhlitz","doi":"10.1016/j.agwat.2026.110157","DOIUrl":"10.1016/j.agwat.2026.110157","url":null,"abstract":"<div><div>Accurate spatio-temporal information on the soil water balance is critical for an efficient and sustainable irrigation. Large effort requirements limit the applicability of complex simulations for precision irrigation. The spatially distributed application of one-dimensional models can reconcile the need for precise soil water balance simulations with the complexity of root-zone water flow processes. This study uses HYDRUS-1D to simulate the daily depth-specific (0 cm to 60 cm, in 10 cm increments) soil water balance from 1st April to 30th September 2021 (2022). Simulations at 70 m spatial resolution covered a 1600 ha farm in Mecklenburg-Western Pomerania, Germany. Results were validated against in-situ soil water content (SWC) and two remotely-sensed SWC data sets (“Soil Moisture Active Passive”, SMAP; Sentinel-1, S1-SWC). Further analysis explored crop-specific irrigation efficiencies and potential farm-scale water savings. Spatially distributed HYDRUS-1D simulations showed good accuracy compared to in-situ SWC (RMSE_mean = 0.020 m³ m⁻³; MAE_mean = 0.017 m³ m⁻³; R²_mean = 0.676; bias = −0.008 m³ m⁻³). The agreement with remotely-sensed SWC was moderate to weak (RMSE_mean = 0.059 (0.150) m³ m⁻³, MAE_mean = 0.049 (0.123) m³ m⁻³, R²_mean = 0.208 (0.141), mean bias = 0.021 (0.108) m³ m⁻³ for SMAP (S1-SWC)). Irrigation efficiencies were 65.0 % (potato), 47.3 % (wheat), 40.5 % (rye), and 58.2 % (sugar beet). Potential water savings amounted to 87,006.9 m³ (11.2 % of total irrigation water; 2021) and 71,396.6 m³ (10.4 %; 2022). The proposed approach reduces the trade-offs between accurately representing the soil water balance in the root-zone and keeping the practical effort reasonable.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"325 ","pages":"Article 110157"},"PeriodicalIF":6.5,"publicationDate":"2026-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146134109","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":"From past to future: Spatiotemporal insights into drought stress on Belgian pome fruit production for 1991–2090","authors":"Brecht Bamps ,&nbsp;Anne Gobin ,&nbsp;Ben Somers ,&nbsp;Jos Van Orshoven","doi":"10.1016/j.agwat.2026.110151","DOIUrl":"10.1016/j.agwat.2026.110151","url":null,"abstract":"<div><div>Recurring drought episodes cause significant economic losses and uncertainty in the Belgian pome fruit sector, requiring effective risk management strategies. Considering the expected increase in frequency, intensity and duration of drought episodes, our study focuses on quantifying the associated location-specific hazard for apple and pear orchards in Belgium. A spatially distributed implementation of the growth model AquaCrop was used to calculate a daily soil water balance at a 12.5 × 12.5 km spatial resolution based on nine bias corrected regional climate model projections from the EURO-CORDEX ensemble for emission scenarios RCP4.5 and RCP8.5. The spatiotemporal evolution of the precipitation deficit (mm), transpiration deficit (mm) and net irrigation requirement (mm) were used to assess current and future meteorological and agricultural drought hazards. We find a spatially averaged increase of the transpiration deficit of 61.4% (39.0%) and the net irrigation requirement of 32.3 % (18.5%) comparing a period in the far future (2061–2090) to a baseline period (1991–2020) under scenario RCP8.5 (RCP4.5). In addition, corresponding interquartile ranges of 204.2% (77.6%) and 30.8% (10.3%) show a large inter-climate model variability in the simulation results. The projected increase of the precipitation deficit during the summer months causes agricultural drought in a spatially heterogeneous manner, relating to the soil total available water content and depth to the shallow groundwater table. Despite the overall increase in drought hazard, the suitability of the current production regions is not projected to change relative to other agricultural regions in Belgium regarding agricultural drought.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"325 ","pages":"Article 110151"},"PeriodicalIF":6.5,"publicationDate":"2026-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145969403","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":"Effects of deficit irrigation at different phenological periods on yield, quality, and water productivity of Xanthoceras sorbifolium Bunge in the Horqin Sandy Land of China","authors":"Shuqin Song ,&nbsp;Benye Xi ,&nbsp;Yang Liu ,&nbsp;Jing Zhong ,&nbsp;Xiaoxia Wang ,&nbsp;Liming Jia","doi":"10.1016/j.agwat.2026.110130","DOIUrl":"10.1016/j.agwat.2026.110130","url":null,"abstract":"<div><div>In arid and semi-arid regions, improving water efficiency is imperative for the sustainable advancement of both forestry and agriculture. The water demand period for <em>Xanthoceras sorbifolium</em> Bunge, an economically and ecologically important tree grown in the Horqin Sandy Land of China, is unknown. This knowledge gap has hindered the development of optimized deficit irrigation (DI) schemes aimed at conserving water while maintaining yield and quality. To identify this key period and better understand the water-use dynamics of this species, we conducted a two-year field experiment (2021–2022). Eight irrigation treatments were applied across three key phenological stages: flowering (F), fruit setting to expansion (S), and fruit-expansion to maturity (M). The irrigation treatments included full-stage (FSM), two-stage (FS, FM, and SM), single-stage (F, S, and M), and no irrigation (NI). The application of DI decreased fruit yields by 8.36–58.01 % (p &lt; 0.05), while two-stage irrigation significantly reduced water consumption and evapotranspiration compared with full-stage irrigation (p &lt; 0.01). FS significantly improved water productivity (<span><math><mi>WP</mi></math></span>), irrigation water productivity (<span><math><msub><mrow><mi>WP</mi></mrow><mrow><mi>I</mi></mrow></msub></math></span>), and fruit quality. All two-stage irrigation treatments demonstrated yield response factors (<span><math><msub><mrow><mi>k</mi></mrow><mrow><mi>y</mi></mrow></msub></math></span>) &lt; 1. The FS treatment reduced irrigation volume by 43.7 %, while the yield decreased by only 8.36 %, suggesting that the irrigation savings did not significantly compromise yield. In summary, the FS treatment is recommended as the most optimal irrigation schedule, followed by SM and FM, for the production of <em>X. sorbifolium</em> in drylands. This approach conserves water while minimally impacting productivity, thus representing a sustainable water management strategy.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"325 ","pages":"Article 110130"},"PeriodicalIF":6.5,"publicationDate":"2026-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145976458","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":"Impact of the soil freeze-thaw process on runoff generation and water balance in an alpine region of the northeast Qinghai-Tibet plateau","authors":"Linshan Yang ,&nbsp;Jingru Wang ,&nbsp;Tiaoxue Lu ,&nbsp;Wanghan He ,&nbsp;Xingyi Zou ,&nbsp;Honghua Xia ,&nbsp;Raffaele Albano ,&nbsp;Bogdan Ozga-Zielinski ,&nbsp;Jan Adamowski ,&nbsp;Qi Feng","doi":"10.1016/j.agwat.2026.110191","DOIUrl":"10.1016/j.agwat.2026.110191","url":null,"abstract":"<div><div>The soil freeze-thaw process profoundly influences runoff generation through complex and interconnected mechanisms, yet its quantitative impact remains poorly understood, particularly across different vegetation types and elevations. Addressing this issue is critical for improving hydrological predictions in cold regions. In this study, we established an integrated atmosphere-vegetation-soil observation system across varying elevations and vegetation types in the Qilian Mountains (QLM) and employed the Simultaneous Heat and Water (SHAW) model to quantitatively assess soil hydrothermal dynamics and runoff generation during different freeze-thaw stages from 2015 to 2023. The results demonstrate that the SHAW model could accurately simulate soil hydrothermal processes across all vegetation types (NSE &gt; 0.80 for soil temperature; NSE &gt; 0.69 for soil moisture) in an alpine region. Soil water content and water balance components varied significantly across both freeze-thaw stages and vegetation types. There was almost no surface runoff formed in desert steppe and mountainous steppe, and deep seepage was also low. In contrast, shrub meadow exhibited substantial deep seepage (89.29 mm) during the completely thawed stage and could be a major source of recharging to streamflow. The major water fluxes for the four vegetation types occurred during thawing and completely thawed stages, dominated by evapotranspiration. Evapotranspiration accounted for 93 %, 94 %, 81 %, and 62 % of annual precipitation in desert steppe, mountainous steppe, coniferous forest, and shrub meadow, respectively. While the component of evapotranspiration differed, it was dominated by soil evaporation in desert steppe (79 % of total ET) and mountainous steppe (92 %), and by vegetation transpiration in coniferous forest (59 %) and shrub meadow (78 %). These findings offer critical insights into water partitioning within the soil-vegetation-atmosphere continuum, enabling more accurate predictions of streamflow and water availability in alpine regions.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"325 ","pages":"Article 110191"},"PeriodicalIF":6.5,"publicationDate":"2026-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146071663","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":"Integrating water evaluation and adaptation planning with enhanced sustainable development goals impact assessment for sustainable irrigation optimization in water stressed agricultural basin","authors":"Naveed Ahmed ,&nbsp;Jiang Ming ,&nbsp;Youssef M. Youssef ,&nbsp;Shahid Ali ,&nbsp;Nassir Alarifi ,&nbsp;Waqas Ul Hussan ,&nbsp;Faten Nahas ,&nbsp;Mahmoud E. Abd-Elmaboud","doi":"10.1016/j.agwat.2026.110132","DOIUrl":"10.1016/j.agwat.2026.110132","url":null,"abstract":"<div><div>This study advances prior approaches by integrating Water Evaluation and Adaptation Planning (WEAP) modelling with a novel Enhanced Sustainable Development Goals (SDG) Impact Assessment Framework (ESIAF) to holistically evaluate irrigation scenarios in water-stressed agricultural regions such as the Indus Basin. Applied to the Chaj Doab region within Pakistan's Indus Basin, this research fills a critical gap in canal-specific, SDG-linked planning for water-stressed agricultural regions. In this integrated approach, the WEAP model simulated physical system responses, quantifying that the optimal scenario (Scenario 3) improves water-use efficiency by 32.4 % (to 67.55 kg/m³) and increases crop yields by 74 %. The ESIAF sustainability assessment reveals this scenario achieves a Final Sustainability Score (FSS) of 0.66 with a Sustainability Balance Index (SBI) of 0.86, demonstrating robust alignment with SDG 6 (Clean Water and Sanitation), SDG 2 (Zero Hunger), and SDG 8 (Decent Work and Economic Growth). Conversely, climate change projections (Scenario 5) indicate system reliability could plummet to 34–35 %, underscoring the urgency of adaptive measures. The WEAP-ESIAF coupling provides a replicable decision-support tool that offers direct insights for implementing Pakistan's National Water Policy (2018) and guiding sustainable irrigation investments in semi-arid, glacier-dependent basins.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"325 ","pages":"Article 110132"},"PeriodicalIF":6.5,"publicationDate":"2026-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146025040","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":"Response of soil water–salt distribution and maize growth to aerated subsurface drip irrigation in saline soils","authors":"Wenxiu Li ,&nbsp;Kai Chang ,&nbsp;Xiangping Wang ,&nbsp;Changcheng He ,&nbsp;Qiancheng Gao ,&nbsp;Rongjiang Yao ,&nbsp;Wenping Xie ,&nbsp;Dongxiang Ma ,&nbsp;Hai Zhu ,&nbsp;Wei Zhu","doi":"10.1016/j.agwat.2026.110173","DOIUrl":"10.1016/j.agwat.2026.110173","url":null,"abstract":"<div><div>Aerated subsurface drip irrigation (ASDI) is a promising strategy for improving crop productivity in saline soils, yet its effects on root–zone water–salt dynamics and crop adaptation remain unclear. Here, based on a two–year field experiment, we assessed the effects of ASDI on soil water–salt distribution, root development, crop yield, and irrigation water productivity under conventional (W₁) and 20 % water–saving (W_0.8) irrigation regimes, each combined with two dissolved oxygen concentrations (12 and 20 mg /L), using non–aerated irrigation as the control (CK). ASDI improved the soil water–salt environment by enhancing water storage, infiltration, and salt suppression, with salinity responses showing clear irrigation–dependent and temporal patterns. Under W₁, aeration consistently reduced salt accumulation over two seasons, maintaining soil salt storage below CK. The initially smaller low–salinity zone under W₁ compared with W_0.8 likely reflected feedbacks between root growth and water–salt redistribution. In contrast, under W_0.8, the low–salinity zone progressively contracted by 2024, accompanied by soil salt storage exceeding CK, indicating a potential risk of salt accumulation under sustained water–saving irrigation. Increasing the aeration mitigated this trend and enhanced soil enzyme activity. An improved root–zone environment promoted root development, increasing the maximum root density by 16 % and other root traits. These responses sustained grain yield under water–saving conditions, while increasing the harvest index by 2.5 % and irrigation water productivity by 25.0 %. Overall, aeration alleviated salt accumulation and supported crop performance, while its longer–term effectiveness under continuous water–saving requires further validation.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"325 ","pages":"Article 110173"},"PeriodicalIF":6.5,"publicationDate":"2026-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146025215","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 global meta-analysis of the effects of irrigation with water containing salts on saline-alkali soils","authors":"Xiang Qiao ,&nbsp;Zhixin Hao ,&nbsp;Haolong Liu ,&nbsp;Yang Liu","doi":"10.1016/j.agwat.2026.110202","DOIUrl":"10.1016/j.agwat.2026.110202","url":null,"abstract":"<div><div>Irrigation with water containing salts offers promise for alleviating freshwater shortages in saline-alkali regions but presents a trade-off: excessive salt accumulation may induce crop stress, risking agricultural sustainability. Achieving a sustainable balance requires a comprehensive understanding of the interactions among evapotranspiration, soil salinity, soil type, precipitation, groundwater dynamics, crop selection, and irrigation management. In this study, we synthesized data from 81 published articles (1023 paired observations) to assess the effects of irrigation with water containing salts on soil electrical conductivity (EC), soil moisture content (SMC), and crop yield in saline-alkali soils under various environmental conditions and agronomic management practices. Results showed that, compared to freshwater irrigation, irrigation with water containing salts significantly increased soil EC by 26.86 % and SMC by 8.85 %, while reducing crop yield by 21.99 %. Further analysis of categorical variables revealed that freezing saline water irrigation (FSWI) contributed to moisture retention and salt suppression, thereby mitigating yield loss (soil EC: −23.49 %, SMC: 8.64 %, crop yield: −11.59 %). Minimal yield reductions were also observed under specific conditions, including mean annual temperature (MAT) below 10°C, groundwater depth &gt; 1.5 m, irrigation water quantity ranged from 50 % to 75 % of ET₀, and salt-tolerant crop type (e.g., cotton). The Boosted Regression Tree (BRT) model analysis further identified irrigation water salinity, MAT, irrigation water quantity, soil texture and crop type as the key factors regulating crop responses to irrigation with salty water. These findings provide valuable insights into optimizing irrigation strategies for water containing salts, supporting a scientific basis for sustainable agricultural management in saline-alkali regions.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"325 ","pages":"Article 110202"},"PeriodicalIF":6.5,"publicationDate":"2026-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146110573","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}