Agricultural Water Management最新文献

{"title":"Towards sustainability for water-agriculture-energy-ecosystems nexus with interconnected uncertainty: A vine copula-based fixed-mix stochastic programming method","authors":"Yanxiao Zhou ,&nbsp;Yongping Li ,&nbsp;Guohe Huang ,&nbsp;Yufei Zhang","doi":"10.1016/j.agwat.2025.109892","DOIUrl":"10.1016/j.agwat.2025.109892","url":null,"abstract":"<div><div>The collaborative management of the water-agriculture-energy-ecosystems (WAEE) nexus is of great significance for promoting sustainable development; however, some parameters associated with interconnected uncertainty (i.e., joint-random uncertainty) existing in the WAEE nexus can introduce additional complexity and intensify the conflict-laden issue of water allocation among agriculture, energy and ecosystems. This study develops a vine copula-based fixed-mix stochastic programming (VCFSP) method that can capture joint violation risks among multiple random variables and handle uncertainties represented as probability distributions in the WAEE nexus. A VCFSP-WAEE model is then formulated for synergistically managing the WAEE nexus of the Kaidu-Kongque River Basin in northwest China, where 96 scenarios involving different utilization rates of brackish water and joint violation probabilities are examined. Results reveal that, with the increase of brackish water utilization rate: (i) the total amount of water (allocated to agriculture, energy and ecosystems) would rise from 13.5 × 10⁹ m³ to 16.0 × 10⁹ m³ during 2046–2050, while the amount of conventional water resources would decrease by 209.4 × 10⁶ m³; (ii) the agricultural cultivated area would increase by 0.4 × 10⁶ ha, and the food yield would increase by 4.7 × 10⁹ kg at the end of planning period. In order to alleviate the pressure of local surface water and groundwater shortages, it is suggested to enhance the utilization efficiency of unconventional water resources and develop low-cost desalination technologies. Compared with the current situation, during the planning period, the proportion of agricultural water allocation would show a general decrease trend (from 73.2 % to 55.9 %), while the proportion of ecological water allocation would present an increase trend (from 6.5 % to 17.7 %). This discloses that increasing the utilization of unconventional water (especially brackish water) is beneficial for increasing ecological water supply, thereby improving the eco-environment in arid regions.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"321 ","pages":"Article 109892"},"PeriodicalIF":6.5,"publicationDate":"2025-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145323445","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":"Recycling nutrients: The promise and perils of wastewater use in global and Brazilian agriculture","authors":"Fernando Rodrigues-Silva ,&nbsp;Daniel A.S. Rodrigues ,&nbsp;Pâmela B. Vilela ,&nbsp;Rafael Kopschitz Xavier Bastos ,&nbsp;Niels O.G. Jørgensen ,&nbsp;Jeppe Lund Nielsen ,&nbsp;Louise Schlüter ,&nbsp;Maria Clara V.M. Starling ,&nbsp;Camila C. Amorim","doi":"10.1016/j.agwat.2025.109901","DOIUrl":"10.1016/j.agwat.2025.109901","url":null,"abstract":"<div><div>As global water demand rises – driven by climate change, population growth, and agricultural expansion – treated wastewater irrigation (WWI) offers a promising strategy for water conservation and nutrient recycling. Agriculture consumes nearly 70 % of global freshwater<strong>,</strong> while only 50.8 % of wastewater is treated in Brazil, where WWI represents less than 0.1 % of total irrigation. This review critically assesses the potential and challenges of WWI in Brazilian agriculture by comparing global practices, regulatory frameworks, and treatment technologies. WWI can significantly reduce freshwater withdrawals and dependence on chemical fertilizers, enhancing soil fertility through the recycling of nitrogen, phosphorus, and potassium. However, persistent contaminants of emerging concern (CECs) – including antibiotic-resistant bacteria (ARB)<strong>,</strong> resistance genes (ARGs)<strong>,</strong> microplastics, and heavy metals – pose environmental and health risks, as conventional systems such as UASB reactors and stabilization ponds, which are vastly implemented in Brazil, were not designed to remove them efficiently. Despite successful examples in high-income countries, regulatory gaps persist in low- and middle-income countries like Brazil, where only 9 of 27 states have local guidelines for wastewater reuse. The adoption of advanced technologies (e.g., membrane filtration, ozonation, UV disinfection) and the development of risk-based regulatory approaches are essential to ensure safety and public acceptance. Educational initiatives and participatory governance can further promote informed decision-making. By investing in technological innovation, harmonized regulation, and interdisciplinary research, WWI could evolve from a niche practice to a mainstream solution for sustainable agriculture, food security, and water resource management in Brazil and globally.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"321 ","pages":"Article 109901"},"PeriodicalIF":6.5,"publicationDate":"2025-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145323434","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 of a CNN classifier with XAI to detect interpretable water stress in sweet potato using RGB images","authors":"Soo Been Cho ,&nbsp;Ji Won Choi ,&nbsp;Mohamad Soleh Hidayat ,&nbsp;Jung-Il Cho ,&nbsp;Hoonsoo Lee ,&nbsp;Byoung-Kwan Cho ,&nbsp;Geonwoo Kim","doi":"10.1016/j.agwat.2025.109899","DOIUrl":"10.1016/j.agwat.2025.109899","url":null,"abstract":"<div><div>Recent abnormal climate conditions have resulted in a decline in both the yield and quality of sweet potatoes (Ipomoea batatas L.). To overcome this, various deep-learning-driven monitoring techniques have been developed. High-cost hyper- or multispectral imagery integrated with done applications is intensively used with large-scale datasets to accomplish this. While high-cost hyperspectral or multispectral imagery integrated with drone applications is commonly used with large-scale datasets, these methods can be limited by their high costs and operational and maintenance challenges. Therefore, the current study developed a cost-effective monitoring system for evaluating water stress levels using RGB imagery and deep-learning models. A Convolutional Neural Network (CNN) model was served as the base model, and its several hybrid models were produced by combining the CNN with Random Forest (RF), Support Vector Machine (SVM), and Vision Transformer (ViT) were developed. As a result, the CNN-ViT hybrid model has achieved the highest accuracy of 0.99. In addition, to address the low-dimensional input issue, the feature maps extracted by the CNN were utilized for the ViT model. This approach enabled feature visualization of the water stress levels in the RGB imagery of sweet potatoes. Consequently the developed cost-effective RGB imagery monitoring system has demonstrated potential as a practical diagnostic tool for agricultural field monitoring</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"321 ","pages":"Article 109899"},"PeriodicalIF":6.5,"publicationDate":"2025-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145324034","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":"Research on the reciprocal feedback relationship and influencing factors between meteorological and agricultural drought in Northeast China","authors":"Tianchi Yu ,&nbsp;Tianxiao Li ,&nbsp;Qiang Fu ,&nbsp;Zhaoqiang Zhou ,&nbsp;Mo Li ,&nbsp;Dong Liu ,&nbsp;Renjie Hou ,&nbsp;Xuechen Yang","doi":"10.1016/j.agwat.2025.109893","DOIUrl":"10.1016/j.agwat.2025.109893","url":null,"abstract":"<div><div>Global climate change exacerbates drought-induced agricultural and ecological degradation. Understanding complex meteorological–agricultural drought feedback is crucial for the development of effective mitigation strategies and sustainable agriculture. In this study, meteorological drought is quantified using the Standardized Precipitation Index (SPI), while agricultural drought is assessed via the Standardized Soil Moisture Index (SSI). By combining the Copula function, with the Random Forest method and SHAP value theory, this research provides a comprehensive analysis of drought interconnections, assessing both meteorological and agricultural drought dynamics and their influencing factors in Northeast China for the 2000–2023 period. The research results indicate that the following: (1) The monthly scale correlation between the SPI and the SSI in Northeast China shows significant seasonal differences. Summer has the strongest positive correlation, whereas winter has the weakest association. During the summer months, the highest positive correlation rate is 92.18 % in August, with that in July reaching a peak PCC value of 0.872. (2) The meteorological–agricultural drought reciprocal feedback relationship in Northeast China shows significant spatiotemporal differences. Spatially, positive feedback dominates in the southwestern part of the Songnen Plain, whereas negative feedback prevails in the Liaodong hills region. Temporally, the proportion within the reciprocal feedback threshold range of [0.5–2] reaches its peak in August at 37.11 %, indicating the establishment of a stable positive feedback mechanism during this month. (3) Low precipitation, high temperature, low soil moisture and high ET_p significantly strengthen the negative feedback effect of agricultural drought on meteorological drought, with the synergistic effect of low precipitation and high temperature being the most prominent. These findings elucidate spatiotemporal drought interactions, surpassing static correlation limitations while establishing methodological references for cross-regional drought feedback analysis.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"321 ","pages":"Article 109893"},"PeriodicalIF":6.5,"publicationDate":"2025-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145326799","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":"Optimizing crop planting structure for balancing water, ecology, and economy in groundwater over-exploited ecologically sensitive regions","authors":"Gong Cheng ,&nbsp;Zhanling Wu ,&nbsp;Xiaonan Guo ,&nbsp;Wenshuo Dang ,&nbsp;Yanjun Shen ,&nbsp;Yongqing Qi ,&nbsp;Lijiang Qiao ,&nbsp;Jianmei Luo ,&nbsp;Yucui Zhang","doi":"10.1016/j.agwat.2025.109876","DOIUrl":"10.1016/j.agwat.2025.109876","url":null,"abstract":"<div><div>Bashang Plateau in China serves as an ecological barrier against wind-driven sand invasion and is a vital water conservation area in the Beijing-Tianjin-Hebei region. Since the 1990s, the expansion of the vegetable industry has increased irrigation demand and actual groundwater extraction, threatening regional water security and ecological stability. This study aims to quantify crop-specific water consumption and explore sustainable planting structures that reduce agricultural water use while maintaining economic and ecological viability. We analyzed the temporal dynamics of dominant crop planting areas (corn, beans, naked oats, oilseeds, coarse cereals, sugar crop, potatoes, and vegetables), and the spatial-temporal characteristics of regional precipitation, temperature, and soil moisture distribution from 2000 to 2020. Crop-specific evapotranspiration (ET) was measured through field experiments (2021–2022), and the nondominated sorting genetic algorithm II (NSGA-II) was employed to generate sustainable planting structures under 10 %, 20 %, and 30 % regional water-saving targets. Over two decades, planting structure shifted toward water-intensive crops, peaking during 2013–2016 before declining due to water scarcity and market dynamics. The 10 % water reduction scenario (S1) proved feasible by reducing the planting area of potatoes and vegetables and increasing coarse cereals (particularly in Shangyi and Kangbao, with lower precipitation), maintaining economic benefits and ecosystem service value. However, 20 % and 30 % reduction (S2, S3) caused economic losses of 6 % and 12.7 %, respectively, due to coarse cereals could not fully offset losses from reduced potato and vegetable production. Balancing groundwater sustainability with agricultural productivity requires optimizing planting structures, supported by improved irrigation technologies and policy incentives. The findings emphasize the need for a balanced crop restructuring strategy, prioritizing high-value crops while limiting water-intensive crops to ensure a sustainable agricultural system in this ecologically sensitive region.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"321 ","pages":"Article 109876"},"PeriodicalIF":6.5,"publicationDate":"2025-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145324036","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 ridge-furrow mulching system and limited supplementary irrigation on soil microbial community structure, function and carbon emissions","authors":"Yueyue Xu ,&nbsp;Xian Liu ,&nbsp;Zeyu Liu ,&nbsp;Ting Pan ,&nbsp;Fu Chen ,&nbsp;Juanling Wang ,&nbsp;Xuefang Huang","doi":"10.1016/j.agwat.2025.109897","DOIUrl":"10.1016/j.agwat.2025.109897","url":null,"abstract":"<div><div>Limited supplementary irrigation under the ridge-furrow mulching planting technology (R) is an important high-efficiency water-saving agricultural measure promoted in the dryland area. To systematically clarify the mechanism of R and supplementary irrigation on soil microorganisms and carbon emissions in farmland, this study investigated dryland farming systems under R with three irrigation amount, using traditional planting (T) as the control, the effects of different irrigation on soil microbial community structure, carbon cycle function gene diversity, carbohydrate-active enzymes and carbon emissions were explored. The results showed that R and supplementary irrigation significantly changed the carbon emission. R increased the CO₂ emission and decreased the CH₄ absorption. It increased the microbial richness but had no significant impact on species diversity, <em>Sphingomonasy</em> and <em>Nocardioides</em> were dominant bacterial groups in farmland. The functional gene diversity of carbon cycle and carbohydrate-active enzymes were studied, in the same irrigation treatment, the Ace and Shannon index of carbon cycle function genes in R increased by 0.05 %-4.85 % and 0.48 %-3.86 % compared with T. The abundance of GTs and GHs under R increased by 3.20 %-20.97 % and 0.68 %-14.00 %, while the CEs family decreased significantly by 34.72 %-36.31 %. Pearson analysis indicated that the cultivation patterns and supplementary irrigation mainly affected farmland carbon emissions by influencing shannon index of carbon cycle functional genes, bacterial <em>Lysobacter,</em> carbohydrate-active enzymes <em>GH74 and PL22</em>. The results of this study can provide a scientific basis for a deeper understanding of the microbial-mediated carbon cycle process under the R with limited supplementary irrigation in dryland farming areas.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"321 ","pages":"Article 109897"},"PeriodicalIF":6.5,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145326798","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":"Enhancement of border irrigation systems: Leveraging simulation–optimization techniques","authors":"Mahmood Akbari ,&nbsp;Saeed Farahani","doi":"10.1016/j.agwat.2025.109891","DOIUrl":"10.1016/j.agwat.2025.109891","url":null,"abstract":"<div><div>Surface irrigation systems, while widespread due to their low operational costs, often suffer from significant inefficiencies driven by inappropriate design and management practices. To address this, the current study proposes a new simulation–optimization model aimed to the design of open-end border irrigation systems, seeking to enhance hydraulic performance under field constraints. The model integrates a modified hydro-empirical SCS simulation framework with the Grey Wolf Optimizer (GWO) algorithm, using border length, slope, inflow discharge, and deficit irrigation Factor as decision variables. Performance evaluation is based on five hydraulic indicators, embedded in a weighted single-objective function. The model was applied to three real case studies representing varying soil textures and irrigation requirements. Results demonstrate that the modified SCS model could simulate all four phases of irrigation as well as determine the subsurface infiltration curve across the field. Also optimization consistently reduced the advance time, aligning infiltration opportunity times across the field, and thereby improved distribution uniformity, and requirement efficiency, while substantially reducing total applied water. The findings also highlight the critical influence of decision variables—particularly inflow discharge and field length—on system performance, and emphasize that shortening the advance phase was the most effective strategy for performance enhancement. Ultimately, the proposed model offers a computationally efficient and hydraulically robust approach to designing border irrigation systems with improved resource efficiency and operational resilience.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"321 ","pages":"Article 109891"},"PeriodicalIF":6.5,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145324033","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":"Optimizing root zone environment to enhance technology stability of “dry sowing and wet emergence” in cotton fields of southern Xinjiang, China","authors":"Shuo Wang ,&nbsp;Zhenhua Wang ,&nbsp;Yungang Bai ,&nbsp;Jianghui Zhang ,&nbsp;Zheng Fang","doi":"10.1016/j.agwat.2025.109895","DOIUrl":"10.1016/j.agwat.2025.109895","url":null,"abstract":"<div><div>In southern Xinjiang, limited precipitation and low soil moisture render the Dry Sowing and Wet Emergence (DSME) technique susceptible to instability, mainly due to uneven post-sowing irrigation and surface salinization. Thus, identifying a suitable irrigation regime for DSME is essential to regulate the root-zone environment, promote cotton germination and growth, and improve the reliability of this technique. Between 2021 and 2023, we conducted a three-year field experiment to examine DSME's impacts on soil water-heat-salt dynamics, cotton physiological characteristics, yield, and irrigation water productivity (IWP). In the third year, we implemented an enhanced irrigation strategy integrating winter drip irrigation with DSME. This included 17 seedling-stage treatments: 8, 10, and 15 mm in 2021; 5, 10, and 13 mm in 2022; and 5, 10, 13, and 15 mm in 2023. Drip frequencies varied from 1 to 4 times in 2021–2022–1–2 times in 2023. The results showed that seedling-stage irrigation amounts were significantly and positively correlated with cotton growth indices, thereby markedly increasing plant height, dry matter accumulation, and yield. Combining higher irrigation volumes with greater frequencies significantly enhanced IWP. Specifically, treatments G7, B7, and DG4 achieved 1.78, 1.81, and 1.83 kg m³ , respectively—representing increases of 16.29 %, 25.69 %, and 38.64 % over the control. In summary, integrating winter drip irrigation with DSME yielded optimal results. This approach substantially reduced agricultural water use while improving cotton yield and quality, offering a sustainable, water-efficient strategy for cultivation in southern Xinjiang's arid regions.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"321 ","pages":"Article 109895"},"PeriodicalIF":6.5,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145326797","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":"Modeling optimal nitrogen application rate and placement for maximizing wheat yield in a semi-arid environment using APSIM","authors":"Jiade Yin ,&nbsp;Jinyu Liang ,&nbsp;Huizhi Hou ,&nbsp;Mingsheng Ma ,&nbsp;Yanjie Fang ,&nbsp;Yanlan Liu ,&nbsp;Hongli Wang ,&nbsp;Kangning Lei","doi":"10.1016/j.agwat.2025.109896","DOIUrl":"10.1016/j.agwat.2025.109896","url":null,"abstract":"<div><div>To investigate the optimal nitrogen (N) application amount and depth that can simultaneously improve both yield and nitrogen use efficiency, we employed the APSIM-Wheat model. The model was calibrated and validated using field trial data from 2012 to 2017, reflecting traditional wheat farming practices in the study area, along with supporting information on crop traits and soil properties from relevant literature. The results showed that a calibrated APSIM-Wheat model could accurately simulate the phenology, biomass, and yield of wheat in the study area, as well as the dynamic changes in soil water and nitrogen conditions. The calibrated APSIM to simulate wheat yield under different N application strategies which showed that increasing the depth of soil N application, in the range of 0–30 cm, could improve wheat yield and yield sustainability in normal and wet years, while increasing N application increased yield instability. The optimal N application depth and amount were about 20–23 cm and 120–150 kg ha⁻¹ and can be reported directly with according to the quantitative relationships between N application amount, depth, agronomic efficiency of N (AE_N) and wheat yield under different annual precipitation conditions. Under the optimal N application conditions, the potential yield, biomass, and AE_N were 16.5 %, 5.3 %, and 31.7 % higher, respectively, than those under farmers' conventional practices. These results demonstrate that optimized nitrogen management can significantly enhance wheat productivity and fertilizer use efficiency, with important implications for sustainable agricultural practices.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"321 ","pages":"Article 109896"},"PeriodicalIF":6.5,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145324031","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 series approach to estimate soil moisture over wheat fields from a single SAR image","authors":"Wentao Han ,&nbsp;Mingxu Wang ,&nbsp;Yangyang Cao ,&nbsp;Zhengdong Luo ,&nbsp;Cui Zhou ,&nbsp;Jianjun Zhu ,&nbsp;Haiqiang Fu ,&nbsp;Qinghua Xie","doi":"10.1016/j.agwat.2025.109883","DOIUrl":"10.1016/j.agwat.2025.109883","url":null,"abstract":"<div><div>The coupling of soil moisture (SM) with other factors, such as surface roughness and vegetation coverage, impedes the generation of large-scale high-precision SM products. Eliminating the effects of vegetation and roughness based on backscattering intensity ratios (BIRs) from time-series data is the primary approach for addressing this problem. However, this method is susceptible to the low temporal resolution of SAR images, leading to unstable retrieval results. In this study, we propose to decouple SM from other factors using a spatial series approach (SSA), which requires only a single synthetic aperture radar (SAR) image and utilizes the BIRs of spatial series points to retrieve SM. The core idea is to employ BIRs to implicitly compensate for vegetation and roughness effects, thereby avoiding explicit parameter estimation with inherent biases. For this purpose, spatial series points are selected based on the incidence angle, volume scattering power, canopy dominant orientation, and roughness. Then, the BIRs of these points are used for SM retrieval. Experiments are conducted using L-band UAVSAR data acquired at different times. The experimental results show that the root mean square error (RMSE) of SM retrieved by the SSA is around 10 %, and the correlation coefficient exceeds 0.7. This approach holds value by expanding the observational dimensions and enhancing SM monitoring capabilities, particularly in scenarios where time-series SAR data acquisition is unfeasible. Future integration with temporal-series methods could establish a spatiotemporal-series inversion framework, which would markedly advance large-scale SM retrieval research.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"321 ","pages":"Article 109883"},"PeriodicalIF":6.5,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145324032","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}