Pub Date : 2025-12-16DOI: 10.1016/j.agwat.2025.110081
Mengyu Wang , Zhao Wang , Lifeng Wu , Congjie Hao
Improving water use efficiency in agricultural production is crucial for food security and sustainable development. This study investigates the spatiotemporal evolution and future trends of agricultural water use efficiency (AWUE) in China. A super-efficiency undesirable slacked-based model (SU-SBM) is used to measure AWUE across 31 provinces from 2013 to 2023. Kernel density estimation and the center of gravity migration model are used to analyze the spatiotemporal evolution pattern and pathway, while Moran’s index is applied to examine spatial correlations. Finally, a grey spatiotemporal model is established to predict future trends of regional AWUE under different policy scenarios. The results indicate that while overall efficiency is rising, regional disparities are widening. The distribution converges during the initial policy period but subsequently disperses along an east-west axis, ultimately polarizing into high and low efficiency regions. Multi-scenario predictions further show different regional responses to fiscal investments. Simply increasing expenditure is insufficient for universal improvement. Consequently, the study proposes differentiated strategies based on regional development and resource endowments. These findings provide a scientific basis for formulating targeted and adaptive water management policies.
{"title":"Spatiotemporal evolution and scenario prediction of agricultural water use efficiency in China","authors":"Mengyu Wang , Zhao Wang , Lifeng Wu , Congjie Hao","doi":"10.1016/j.agwat.2025.110081","DOIUrl":"10.1016/j.agwat.2025.110081","url":null,"abstract":"<div><div>Improving water use efficiency in agricultural production is crucial for food security and sustainable development. This study investigates the spatiotemporal evolution and future trends of agricultural water use efficiency (AWUE) in China. A super-efficiency undesirable slacked-based model (SU-SBM) is used to measure AWUE across 31 provinces from 2013 to 2023. Kernel density estimation and the center of gravity migration model are used to analyze the spatiotemporal evolution pattern and pathway, while Moran’s index is applied to examine spatial correlations. Finally, a grey spatiotemporal model is established to predict future trends of regional AWUE under different policy scenarios. The results indicate that while overall efficiency is rising, regional disparities are widening. The distribution converges during the initial policy period but subsequently disperses along an east-west axis, ultimately polarizing into high and low efficiency regions. Multi-scenario predictions further show different regional responses to fiscal investments. Simply increasing expenditure is insufficient for universal improvement. Consequently, the study proposes differentiated strategies based on regional development and resource endowments. These findings provide a scientific basis for formulating targeted and adaptive water management policies.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"323 ","pages":"Article 110081"},"PeriodicalIF":6.5,"publicationDate":"2025-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145784871","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}
Pub Date : 2025-12-16DOI: 10.1016/j.agwat.2025.110086
Mengtao Ci , Xingming Hao , Fan Sun , Qixiang Liang , Xue Fan , Jingjing Zhang , Haibing Xiong , Jinfan Xu , Xinran Guo
Accurate quantification of evapotranspiration (ET) is critical for improving climate models, enhancing drought early warning systems, and optimising water resource management, as ET represents the largest water flux between land and atmosphere. However, precise ET estimation is often hindered by the complexity of data sources and temporal misalignments. To overcome these challenges, we proposed AGFusionET, a multi-timescale fusion model that integrates heterogeneous ET data from various sources, including remote sensing and climate models, to enhance ET estimation accuracy. AGFusionET uses AutoML and autoencoders to fuse data from 20 distinct ET products at fine temporal and spatial resolutions. Based on 585 eddy covariance datasets, we generated a long-term, high-resolution global ET dataset (0.05°) spanning 1982–2023, ensuring strong spatiotemporal continuity. The validation results show that AGFusionET outperforms all other benchmark ET products, achieving a Kling-Gupta Efficiency (KGE) of 0.88 and a Root Mean Square Error (RMSE) of 12.12 mm/month. AGFusionET excelled at both the monthly and annual scales at independent validation sites. By incorporating Normalised difference vegetation index (NDVI), Vapour pressure deficit (VPD), and diverse ET products that encode vegetation water status and irrigation-induced surface responses, AGFusionET partially reflects agricultural influences on ET even though explicit crop- and irrigation-related inputs are not included. Our study introduces a generalisable framework for multisource ET data fusion that provides more accurate and reliable ET estimates across diverse ecosystems, particularly in arid and high-latitude regions.
{"title":"Multi-timescale evapotranspiration fusion: A novel autoencoder with automated machine learning-based approach for enhanced estimation accuracy","authors":"Mengtao Ci , Xingming Hao , Fan Sun , Qixiang Liang , Xue Fan , Jingjing Zhang , Haibing Xiong , Jinfan Xu , Xinran Guo","doi":"10.1016/j.agwat.2025.110086","DOIUrl":"10.1016/j.agwat.2025.110086","url":null,"abstract":"<div><div>Accurate quantification of evapotranspiration (ET) is critical for improving climate models, enhancing drought early warning systems, and optimising water resource management, as ET represents the largest water flux between land and atmosphere. However, precise ET estimation is often hindered by the complexity of data sources and temporal misalignments. To overcome these challenges, we proposed AGFusionET, a multi-timescale fusion model that integrates heterogeneous ET data from various sources, including remote sensing and climate models, to enhance ET estimation accuracy. AGFusionET uses AutoML and autoencoders to fuse data from 20 distinct ET products at fine temporal and spatial resolutions. Based on 585 eddy covariance datasets, we generated a long-term, high-resolution global ET dataset (0.05°) spanning 1982–2023, ensuring strong spatiotemporal continuity. The validation results show that AGFusionET outperforms all other benchmark ET products, achieving a Kling-Gupta Efficiency (KGE) of 0.88 and a Root Mean Square Error (RMSE) of 12.12 mm/month. AGFusionET excelled at both the monthly and annual scales at independent validation sites. By incorporating Normalised difference vegetation index (NDVI), Vapour pressure deficit (VPD), and diverse ET products that encode vegetation water status and irrigation-induced surface responses, AGFusionET partially reflects agricultural influences on ET even though explicit crop- and irrigation-related inputs are not included. Our study introduces a generalisable framework for multisource ET data fusion that provides more accurate and reliable ET estimates across diverse ecosystems, particularly in arid and high-latitude regions.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"323 ","pages":"Article 110086"},"PeriodicalIF":6.5,"publicationDate":"2025-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145784872","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}
Pub Date : 2025-12-15DOI: 10.1016/j.agwat.2025.110083
Zijun Tang , Zhijun Li , Youzhen Xiang , Junhua Wang , Sabeeqa Usman Malik , Tao Sun , Junsheng Lu , Wei Zhang , Shu Wang , Xueyan Zhang , Fucang Zhang
In arid and semi-arid regions, optimizing field mulching and nitrogen (N) management is crucial for winter oilseed rape production. This three-year study on the Chinese Loess Plateau investigated how mulching modes (film, straw, and no mulching) and N rates interact to influence yield and water productivity through coupled water–light–carbon processes. We developed a coupled "water–light" efficiency index to diagnose leaf physiological status and applied structural equation modeling to quantify driving mechanisms. Results showed that film mulching combined with moderate N (210 kg ha−1) achieved a robust seed yield of 3762.7 kg ha−1, comparable to the highest N rate but with 25 % less fertilizer input, while attaining superior water productivity of 10.83 kg ha−1 mm−1. Mechanistically, film mulching acted as a hydrological regulator by reducing evaporation and stabilizing root-zone soil water. This favorable environment allowed moderate N to function as a physiological activator, enhancing leaf chlorophyll content and photochemical efficiency without the excessive water depletion often caused by high N inputs. The proposed coupled index effectively captured this synergy, identifying physiological states with "low water cost and high photochemical return." Structural modeling confirmed that yield formation was driven by a cascade where stabilized soil water promoted leaf physiological function and canopy structure, ultimately maximizing carbon assimilation. Consequently, prioritizing film mulching with moderate N harmonizes water supply and physiological demand, offering a sustainable strategy for dryland agriculture.
在干旱半干旱区，优化地膜覆盖和氮素管理对冬季油菜生产至关重要。本研究以黄土高原为研究对象，研究了覆盖模式（膜覆盖、秸秆覆盖和不覆盖）和施氮量是如何通过水-光-碳耦合过程相互作用影响产量和水分生产力的。我们建立了一个耦合的“水-光”效率指数来诊断叶片的生理状态，并应用结构方程模型来量化驱动机制。结果表明，适度施氮（210 kg ha−1）配膜可获得3762.7 kg ha−1的强劲种子产量，与最高施氮量相当，但肥料投入量减少25 %，同时获得10.83 kg ha−1 mm−1的优异水分生产力。从机械上讲，覆膜通过减少蒸发和稳定根区土壤水分来调节水文。这种有利的环境允许适量的氮作为生理激活剂，提高叶片叶绿素含量和光化学效率，而不会造成高氮输入导致的过度缺水。所提出的耦合指数有效地捕获了这种协同作用，确定了具有“低水成本和高光化学回报”的生理状态。结构模型证实了产量的形成是由一个级联驱动的，稳定的土壤水分促进了叶片的生理功能和冠层结构，最终使碳吸收最大化。因此，优先覆盖适度氮的地膜可以协调水分供应和生理需求，为旱地农业提供可持续发展的策略。
{"title":"Interactive effects of field mulching and nitrogen management on leaf photochemical efficiency, water use, and yield formation in winter oilseed rape (Brassica napus L.): A three-year appraisal","authors":"Zijun Tang , Zhijun Li , Youzhen Xiang , Junhua Wang , Sabeeqa Usman Malik , Tao Sun , Junsheng Lu , Wei Zhang , Shu Wang , Xueyan Zhang , Fucang Zhang","doi":"10.1016/j.agwat.2025.110083","DOIUrl":"10.1016/j.agwat.2025.110083","url":null,"abstract":"<div><div>In arid and semi-arid regions, optimizing field mulching and nitrogen (N) management is crucial for winter oilseed rape production. This three-year study on the Chinese Loess Plateau investigated how mulching modes (film, straw, and no mulching) and N rates interact to influence yield and water productivity through coupled water–light–carbon processes. We developed a coupled \"water–light\" efficiency index to diagnose leaf physiological status and applied structural equation modeling to quantify driving mechanisms. Results showed that film mulching combined with moderate N (210 kg ha<sup>−1</sup>) achieved a robust seed yield of 3762.7 kg ha<sup>−1</sup>, comparable to the highest N rate but with 25 % less fertilizer input, while attaining superior water productivity of 10.83 kg ha<sup>−1</sup> mm<sup>−1</sup>. Mechanistically, film mulching acted as a hydrological regulator by reducing evaporation and stabilizing root-zone soil water. This favorable environment allowed moderate N to function as a physiological activator, enhancing leaf chlorophyll content and photochemical efficiency without the excessive water depletion often caused by high N inputs. The proposed coupled index effectively captured this synergy, identifying physiological states with \"low water cost and high photochemical return.\" Structural modeling confirmed that yield formation was driven by a cascade where stabilized soil water promoted leaf physiological function and canopy structure, ultimately maximizing carbon assimilation. Consequently, prioritizing film mulching with moderate N harmonizes water supply and physiological demand, offering a sustainable strategy for dryland agriculture.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"323 ","pages":"Article 110083"},"PeriodicalIF":6.5,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145797821","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}
Pub Date : 2025-12-15DOI: 10.1016/j.agwat.2025.110067
Yani Gun , Guofeng Zhu , Yinying Jiao , Longhu Chen , Xiaoyu Qi , Rui Li , Yuxin Miao , Zhijie Zheng , Wenmin Li , Jiangwei Yang , Ziwen Liu
Artificial wetlands in arid regions are characterized by high evaporation rates, artificially structured vegetation, and a higher proportion of non-drought-tolerant trees compared to natural wetlands. While these artificial wetlands play a crucial role in water resource management, ecosystem restoration, and environmental protection in arid regions, their water consumption patterns remain poorly understood. To address this knowledge gap, understanding the water use strategies of trees in artificial wetlands is critical for wetland ecosystem construction and efficient water resource utilization. In this study, we established a monitoring system to sample precipitation, groundwater, surface water, soil water, and the dominant tree species (willow) in the Zhangye artificial wetland in an arid region of China, and conducted hydrogen and oxygen stable isotope analyses. Our results reveal three key findings: (1) the dominant willow species primarily relies on soil water and groundwater as its main water sources, with their combined contribution exceeding 60 % across different seasons; (2) the artificially supplied water serves as the main source of soil water and groundwater in the Zhangye wetland; (3) water consumption of a single willow tree during the growing season reaches 432.5 mm, approximately three times the growing season precipitation, with total consumption by willows in the entire wetland system reaching 18.94 million m³ . Based on these findings, our study quantitatively assesses the dependence of trees in artificial wetlands on imported water and associated evapotranspiration losses in arid regions. We conclude that the current dominant tree species are excessively dependent on artificial water supply and have high evaporation rates. Consequently, we recommend that the current ecological forest structure should be re-evaluated, and moderately drought-resistant tree species with low evaporation rates should be selected to enhance wetland ecosystem resilience and reduce water resource consumption. This study provides quantitative quantitative evidence that willow water consumption is approximately three times the growing season precipitation and that groundwater and soil water contribute over 60 % to willow water sources in artificial wetlands of arid regions, revealing how artificial water introduction fundamentally alters tree water use strategies and offering insights for optimizing vegetation structure in water-limited ecosystems.
{"title":"Quantifying tree dependency on imported water in artificial wetlands of arid regions: Insights from isotope analysis","authors":"Yani Gun , Guofeng Zhu , Yinying Jiao , Longhu Chen , Xiaoyu Qi , Rui Li , Yuxin Miao , Zhijie Zheng , Wenmin Li , Jiangwei Yang , Ziwen Liu","doi":"10.1016/j.agwat.2025.110067","DOIUrl":"10.1016/j.agwat.2025.110067","url":null,"abstract":"<div><div>Artificial wetlands in arid regions are characterized by high evaporation rates, artificially structured vegetation, and a higher proportion of non-drought-tolerant trees compared to natural wetlands. While these artificial wetlands play a crucial role in water resource management, ecosystem restoration, and environmental protection in arid regions, their water consumption patterns remain poorly understood. To address this knowledge gap, understanding the water use strategies of trees in artificial wetlands is critical for wetland ecosystem construction and efficient water resource utilization. In this study, we established a monitoring system to sample precipitation, groundwater, surface water, soil water, and the dominant tree species (willow) in the Zhangye artificial wetland in an arid region of China, and conducted hydrogen and oxygen stable isotope analyses. Our results reveal three key findings: (1) the dominant willow species primarily relies on soil water and groundwater as its main water sources, with their combined contribution exceeding 60 % across different seasons; (2) the artificially supplied water serves as the main source of soil water and groundwater in the Zhangye wetland; (3) water consumption of a single willow tree during the growing season reaches 432.5 mm, approximately three times the growing season precipitation, with total consumption by willows in the entire wetland system reaching 18.94 million m³ . Based on these findings, our study quantitatively assesses the dependence of trees in artificial wetlands on imported water and associated evapotranspiration losses in arid regions. We conclude that the current dominant tree species are excessively dependent on artificial water supply and have high evaporation rates. Consequently, we recommend that the current ecological forest structure should be re-evaluated, and moderately drought-resistant tree species with low evaporation rates should be selected to enhance wetland ecosystem resilience and reduce water resource consumption. This study provides quantitative quantitative evidence that willow water consumption is approximately three times the growing season precipitation and that groundwater and soil water contribute over 60 % to willow water sources in artificial wetlands of arid regions, revealing how artificial water introduction fundamentally alters tree water use strategies and offering insights for optimizing vegetation structure in water-limited ecosystems.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"323 ","pages":"Article 110067"},"PeriodicalIF":6.5,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145797866","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}
Pub Date : 2025-12-13DOI: 10.1016/j.agwat.2025.110064
Shuang Li , Yajun Geng , Huijie Li , Tao Zhou , Hongchen Li , Ruiqi Ren , Peng Li , Fangzhi Duan , Zhandong Liu , Haitao Wang , Bing Cheng Si
Mitigating reactive nitrogen loss from soil is critical for sustainable agricultural intensification. However, the combined effects of the nitrification inhibitor DMPP (3,4-dimethylpyrazole phosphate) and irrigation strategies on soil nitrogen dynamics remain unclear. A two-year experiment in the North China Plain evaluated how DMPP application, irrigation method (alternate vs. conventional drip irrigation), and irrigation quota (27 mm vs. 36 mm) affected soil NH₃ and N₂O emissions, physicochemical properties, enzyme activities, and microbial communities in summer maize systems. DMPP application, irrigation method and irrigation quota significantly affected soil urease and catalase activities, while alkaline phosphatase was mainly influenced by irrigation method (P < 0.05). Actinobacteriota and Proteobacteria dominated the microbial phyla, accounting for over 40 % of total relative abundance. Compared with treatments without DMPP, DMPP reduced N₂O emissions by 37.4–70.4 % but increased NH₃ volatilization by 13.5–18.7 % due to higher NH₄⁺-N concentrations and enhanced urease activity. Alternate drip irrigation (ADI) consistently lowered both NH₃ and N₂O emissions by 9.6–23.9 % and 17.8–37.6 %, respectively, compared with conventional drip irrigation, and when combined with DMPP under a 27 mm irrigation quota, achieved the lowest global warming potential and greenhouse gas intensity. Random forest regression analysis revealed soil water-filled pore space as the main driver of N₂O emission, while catalase and urease activities primarily controlled NH₃ volatilization. Integrating DMPP with ADI under 27 mm irrigation quota is recommended to mitigate gaseous nitrogen losses. Future research should examine microbial functional genes and long-term soil responses under integrated water-nitrogen management.
{"title":"The combination of 3,4-dimethylpyrazole phosphate and alternate drip irrigation with low irrigation quotas resulted in the lowest NH3 and N2O emissions","authors":"Shuang Li , Yajun Geng , Huijie Li , Tao Zhou , Hongchen Li , Ruiqi Ren , Peng Li , Fangzhi Duan , Zhandong Liu , Haitao Wang , Bing Cheng Si","doi":"10.1016/j.agwat.2025.110064","DOIUrl":"10.1016/j.agwat.2025.110064","url":null,"abstract":"<div><div>Mitigating reactive nitrogen loss from soil is critical for sustainable agricultural intensification. However, the combined effects of the nitrification inhibitor DMPP (3,4-dimethylpyrazole phosphate) and irrigation strategies on soil nitrogen dynamics remain unclear. A two-year experiment in the North China Plain evaluated how DMPP application, irrigation method (alternate vs. conventional drip irrigation), and irrigation quota (27 mm vs. 36 mm) affected soil NH₃ and N₂O emissions, physicochemical properties, enzyme activities, and microbial communities in summer maize systems. DMPP application, irrigation method and irrigation quota significantly affected soil urease and catalase activities, while alkaline phosphatase was mainly influenced by irrigation method (<em>P</em> < 0.05). <em>Actinobacteriota</em> and <em>Proteobacteria</em> dominated the microbial phyla, accounting for over 40 % of total relative abundance. Compared with treatments without DMPP, DMPP reduced N₂O emissions by 37.4–70.4 % but increased NH₃ volatilization by 13.5–18.7 % due to higher NH₄⁺-N concentrations and enhanced urease activity. Alternate drip irrigation (ADI) consistently lowered both NH₃ and N₂O emissions by 9.6–23.9 % and 17.8–37.6 %, respectively, compared with conventional drip irrigation, and when combined with DMPP under a 27 mm irrigation quota, achieved the lowest global warming potential and greenhouse gas intensity. Random forest regression analysis revealed soil water-filled pore space as the main driver of N₂O emission, while catalase and urease activities primarily controlled NH₃ volatilization. Integrating DMPP with ADI under 27 mm irrigation quota is recommended to mitigate gaseous nitrogen losses. Future research should examine microbial functional genes and long-term soil responses under integrated water-nitrogen management.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"323 ","pages":"Article 110064"},"PeriodicalIF":6.5,"publicationDate":"2025-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145753297","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}
Water flow, solute transport, and crop responses are essential physical and biological processes in cropland, which become more complicated under film mulched drip irrigation. To simulate these interactive processes, we developed a new model by coupling a two-dimensional water flow and solute transport model with a crop growth model (WSP-2D). The WSP-2D considered infiltration/evaporation flux through planting holes of mulched film to replace the commonly adopted no flux condition. Two-dimensional root growth was quantified with the crop growth day and coupled to the root water uptake distribution model to strengthen the interaction in depicting the soil-plant system. The developed model was calibrated and verified by measured data from a two-year field experiment under film mulched drip irrigation in Northwest China. The field soil water and salt dynamics, leaf area index, biomass, and crop yield were well captured by the coupled model, with the coefficient of determination of greater than 0.90, 0.48, 0.90, and 0.98, respectively. Scenario simulations indicate that the simulated soil water content and salt concentration matched better with measurements when evaporation and precipitation rates were considered for film mulched zone. The simulations with a fixed root distribution overestimate soil water content up to 21.8 % and underestimate salt concentration up to 43.5 % in the top layer of the root zone, while underestimate the soil water content and overestimate salt concentration in the lower layer of the root zone. Salt mainly accumulated in the upper loam layer with an underlying sand layer and in the soil beneath the plant row due to transpiration. In conclusion, the WSP-2D considers more interactive processes in the soil-plant system under film mulched drip irrigation condition and better simulate these processes.
{"title":"Integrated modeling of crop growth with 2D soil water flow and solute transport considering dynamic root spatial distribution under film mulched drip irrigation","authors":"Shuai Chen , Zunqiu Xu , Chunying Wang , Songhao Shang","doi":"10.1016/j.agwat.2025.110069","DOIUrl":"10.1016/j.agwat.2025.110069","url":null,"abstract":"<div><div>Water flow, solute transport, and crop responses are essential physical and biological processes in cropland, which become more complicated under film mulched drip irrigation. To simulate these interactive processes, we developed a new model by coupling a two-dimensional water flow and solute transport model with a crop growth model (WSP-2D). The WSP-2D considered infiltration/evaporation flux through planting holes of mulched film to replace the commonly adopted no flux condition. Two-dimensional root growth was quantified with the crop growth day and coupled to the root water uptake distribution model to strengthen the interaction in depicting the soil-plant system. The developed model was calibrated and verified by measured data from a two-year field experiment under film mulched drip irrigation in Northwest China. The field soil water and salt dynamics, leaf area index, biomass, and crop yield were well captured by the coupled model, with the coefficient of determination of greater than 0.90, 0.48, 0.90, and 0.98, respectively. Scenario simulations indicate that the simulated soil water content and salt concentration matched better with measurements when evaporation and precipitation rates were considered for film mulched zone. The simulations with a fixed root distribution overestimate soil water content up to 21.8 % and underestimate salt concentration up to 43.5 % in the top layer of the root zone, while underestimate the soil water content and overestimate salt concentration in the lower layer of the root zone. Salt mainly accumulated in the upper loam layer with an underlying sand layer and in the soil beneath the plant row due to transpiration. In conclusion, the WSP-2D considers more interactive processes in the soil-plant system under film mulched drip irrigation condition and better simulate these processes.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"323 ","pages":"Article 110069"},"PeriodicalIF":6.5,"publicationDate":"2025-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145753351","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}
Pub Date : 2025-12-13DOI: 10.1016/j.agwat.2025.110077
Ling Zhang , Tao Che , Kun Zhang , Donghai Zheng , Xin Li
Accurate and spatially explicit estimates of irrigation water use (IWU) are essential for understanding the earth system dynamics in the Anthropocene. Recent advances in remote sensing have spurred growing interest in satellite-based IWU estimation. However, large-scale IWU estimates remain limited in both accuracy and spatial resolution due to inherent deficiencies in satellite observations and methodological constraints. Here, we present a novel framework for spatially explicit IWU estimation by integrating satellite-based soil moisture and evapotranspiration (ET) products with reanalysis data. Within this framework, we developed two alternative models: one based on root zone soil moisture (RSM) and the other on surface soil moisture (SSM), both grounded in soil water balance principles. The models estimate IWU by quantifying differences in soil moisture, ET, and drainage between natural and irrigated conditions. Both the RSM- and SSM-based models perform well in predicting prefecture-level IWU during the validation period, achieving coefficients of determination (R²) between 0.72 and 0.90 and root mean square errors (RMSE) of 0.55–0.66 km³ /year, depending on the spatial scale of calibration (i.e., province, prefecture, or subregion). By combining our framework with different satellite products, we produce ensemble IWU estimates at 1 km resolution across China. The resulting dataset reveals a clear increasing trend in China’s IWU from 2001 to 2020, primarily driven by the expansion of irrigated area, while its interannual variability is largely controlled by fluctuations in IWU per unit irrigated area. This dataset shows a significant advancement in both accuracy and spatial detail over existing datasets and will be useful for irrigation-related research and agricultural water management in China.
{"title":"A novel framework for pixel-wise estimation of irrigation water use by integrating remote sensing and reanalysis data","authors":"Ling Zhang , Tao Che , Kun Zhang , Donghai Zheng , Xin Li","doi":"10.1016/j.agwat.2025.110077","DOIUrl":"10.1016/j.agwat.2025.110077","url":null,"abstract":"<div><div>Accurate and spatially explicit estimates of irrigation water use (IWU) are essential for understanding the earth system dynamics in the Anthropocene. Recent advances in remote sensing have spurred growing interest in satellite-based IWU estimation. However, large-scale IWU estimates remain limited in both accuracy and spatial resolution due to inherent deficiencies in satellite observations and methodological constraints. Here, we present a novel framework for spatially explicit IWU estimation by integrating satellite-based soil moisture and evapotranspiration (ET) products with reanalysis data. Within this framework, we developed two alternative models: one based on root zone soil moisture (RSM) and the other on surface soil moisture (SSM), both grounded in soil water balance principles. The models estimate IWU by quantifying differences in soil moisture, ET, and drainage between natural and irrigated conditions. Both the RSM- and SSM-based models perform well in predicting prefecture-level IWU during the validation period, achieving coefficients of determination (R²) between 0.72 and 0.90 and root mean square errors (RMSE) of 0.55–0.66 km³ /year, depending on the spatial scale of calibration (i.e., province, prefecture, or subregion). By combining our framework with different satellite products, we produce ensemble IWU estimates at 1 km resolution across China. The resulting dataset reveals a clear increasing trend in China’s IWU from 2001 to 2020, primarily driven by the expansion of irrigated area, while its interannual variability is largely controlled by fluctuations in IWU per unit irrigated area. This dataset shows a significant advancement in both accuracy and spatial detail over existing datasets and will be useful for irrigation-related research and agricultural water management in China.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"323 ","pages":"Article 110077"},"PeriodicalIF":6.5,"publicationDate":"2025-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145753288","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}
Pub Date : 2025-12-12DOI: 10.1016/j.agwat.2025.110066
Zaineb Bouswir , Salah Er-Raki , Jamal Ezzahar , Saïd Khabba , Abdelhakim Amazirh , Hiba Ait Ben Ahmed , Lamia Jallal , Abdelghani Chehbouni
Evapotranspiration (ET) is a fundamental component of the water and energy balance, strongly influencing crop growth and productivity. Accurate ET estimation is critical in semi-arid regions, where water scarcity requires optimized management. Among the available approaches, the Penman–Monteith (PM) model is the most widely used for this purpose, its performance strongly depends on the accurate characterization of surface resistance (), a key parameter controlling ET estimations. In this study, two approaches for estimating were evaluated for winter wheat cultivated in the Haouz plain (Morocco) under contrasting irrigation regimes (full and deficit) during the 2016–2017 and 2017–2018 growing seasons. The first is a mechanistic formulation, based on the Jarvis model, which incorporates vapor pressure deficit (VPD) and soil water content (θ) to capture stomatal responses. The second is an empirical approach, using a thermal stress index (SI) derived from land surface temperature (LST), providing a rapid indicator of crop water status.
Both approaches were integrated into the PM model and calibrated with eddy covariance data collected over a deficit-irrigated field in 2016/2017, then validated across both irrigation regimes and seasons. Results showed that the mechanistic approach reproduced ET dynamics under full irrigation (R² ≥ 0.73; RMSE < 0.6 mm·day⁻¹), but underestimated fluxes under severe stress. Conversely, the empirical approach, being more sensitive to short-term water status, outperformed under deficit irrigation (R² ≥ 0.79; RMSE < 0.6 mm·day⁻¹). Moreover, a critical SI threshold of 0.5 was identified, which could serve as a practical guideline for irrigation scheduling to reduce water losses. Overall, the results highlight the robustness and complementarity of both approaches and suggest the potential of hybrid models combining physiological realism with thermal sensitivity to improve irrigation management in water-limited areas.
{"title":"Assessment of empirical and physically-based approaches to simulate surface resistance for improved evapotranspiration modeling of winter wheat in semi-arid region, Morocco","authors":"Zaineb Bouswir , Salah Er-Raki , Jamal Ezzahar , Saïd Khabba , Abdelhakim Amazirh , Hiba Ait Ben Ahmed , Lamia Jallal , Abdelghani Chehbouni","doi":"10.1016/j.agwat.2025.110066","DOIUrl":"10.1016/j.agwat.2025.110066","url":null,"abstract":"<div><div>Evapotranspiration (ET) is a fundamental component of the water and energy balance, strongly influencing crop growth and productivity. Accurate ET estimation is critical in semi-arid regions, where water scarcity requires optimized management. Among the available approaches, the Penman–Monteith (PM) model is the most widely used for this purpose, its performance strongly depends on the accurate characterization of surface resistance (<span><math><msub><mrow><mi>r</mi></mrow><mrow><mi>c</mi></mrow></msub></math></span>), a key parameter controlling ET estimations. In this study, two approaches for estimating <span><math><msub><mrow><mi>r</mi></mrow><mrow><mi>c</mi></mrow></msub></math></span> were evaluated for winter wheat cultivated in the Haouz plain (Morocco) under contrasting irrigation regimes (full and deficit) during the 2016–2017 and 2017–2018 growing seasons. The first is a mechanistic formulation, based on the Jarvis model, which incorporates vapor pressure deficit (<em>VPD</em>) and soil water content (<em>θ</em>) to capture stomatal responses. The second is an empirical approach, using a thermal stress index (<em>SI</em>) derived from land surface temperature (<em>LST</em>), providing a rapid indicator of crop water status.</div><div>Both approaches were integrated into the PM model and calibrated with eddy covariance data collected over a deficit-irrigated field in 2016/2017, then validated across both irrigation regimes and seasons. Results showed that the mechanistic approach reproduced ET dynamics under full irrigation (R² ≥ 0.73; RMSE < 0.6 mm·day⁻¹), but underestimated fluxes under severe stress. Conversely, the empirical approach, being more sensitive to short-term water status, outperformed under deficit irrigation (R² ≥ 0.79; RMSE < 0.6 mm·day⁻¹). Moreover, a critical SI threshold of 0.5 was identified, which could serve as a practical guideline for irrigation scheduling to reduce water losses. Overall, the results highlight the robustness and complementarity of both approaches and suggest the potential of hybrid models combining physiological realism with thermal sensitivity to improve irrigation management in water-limited areas.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"323 ","pages":"Article 110066"},"PeriodicalIF":6.5,"publicationDate":"2025-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145731699","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}
Pub Date : 2025-12-12DOI: 10.1016/j.agwat.2025.110046
Yikun Lu, Chang Feng, Zhonghui Guo, Liu Yang, Qing Liu
Blue water (BW) and green water (GW) are crucial elements that determine watershed water resource availability and ecosystem health; however, constrained by hydrological model uncertainties, their precise simulation and quantitative assessment remain challenging. This study integrates physically-based hydrological models with remote sensing fusion data and observed data to construct seven calibration schemes, with a focus on evaluating the effectiveness of dual-variable blue-green water calibration methods based on remote sensing data fusion in enhancing simulation accuracy, reducing uncertainty, and achieving precise quantification of blue-green water, validated through a case study in the Xiangjiang River Basin. The following main conclusions were drawn: (1) The remote sensing fusion evapotranspiration (ET) data achieved the highest accuracy (R = 0.87, Re = 37.5 %, RMSE = 56.56 mm/month), with spatiotemporal fusion processing enabling a better balance between authenticity and accuracy, outperforming individual ET products; (2) The remote sensing fusion ET data can better support the model in achieving reliable simulation accuracy for both blue-green water, whether it is used as input for single-variable GW calibration or for dual-variable blue-green water calibration. Particularly under the dual-variable calibration scheme, this data significantly improved the simultaneous simulation accuracy of blue-green water; (3) The dual-variable scheme based on remote sensing fusion data significantly outperforms the traditional single-variable BW calibration in GW simulation. This scheme effectively constrains and optimizes vertical flux parameters by utilizing ET data, thereby substantially improving the estimation accuracy of GW. This study exploratorily combined hydrological modeling with remote sensing data fusion methods, providing an effective approach for accurate simulation of blue-green water at the watershed scale. It has application potential in water resources optimal allocation, vegetation water conservation assessment, and ecosystem service function quantification, and can provide scientific support for sustainable management of watershed water resources and ecological protection decision-making.
蓝水（BW）和绿水（GW）是决定流域水资源可用性和生态系统健康的关键要素；然而，受水文模型不确定性的限制，其精确模拟和定量评估仍然具有挑战性。本研究将基于物理的水文模型与遥感融合数据和观测数据相结合，构建了7种定标方案，重点评估了基于遥感数据融合的双变量蓝绿水定标方法在提高模拟精度、降低不确定性和实现蓝绿水精确量化方面的有效性，并通过湘江流域的案例研究进行了验证。结果表明：(1)遥感融合蒸散发（ET）数据精度最高（R = 0.87, Re = 37.5% %,RMSE = 56.56 mm/月），时空融合处理能更好地平衡真实性和准确性，优于单项蒸散发产品；(2)无论是单变量GW定标还是双变量蓝绿水定标，遥感融合ET数据都能更好地支持模型实现可靠的蓝绿水模拟精度。特别是在双变量校准方案下，该数据显著提高了蓝绿水的同时模拟精度；(3)基于遥感融合数据的双变量方案在GW仿真中显著优于传统的单变量BW标定。该方案利用ET数据有效地约束和优化了垂直通量参数，从而大大提高了GW的估算精度。本研究探索性地将水文建模与遥感数据融合方法相结合，为流域尺度上蓝绿色水的精确模拟提供了有效途径。在水资源优化配置、植被涵养评价、生态系统服务功能量化等方面具有应用潜力，可为流域水资源可持续管理和生态保护决策提供科学支持。
{"title":"Blue and green water simulation in the river basin using remote sensing data fusion and dual-variable hydrological calibration","authors":"Yikun Lu, Chang Feng, Zhonghui Guo, Liu Yang, Qing Liu","doi":"10.1016/j.agwat.2025.110046","DOIUrl":"10.1016/j.agwat.2025.110046","url":null,"abstract":"<div><div>Blue water (BW) and green water (GW) are crucial elements that determine watershed water resource availability and ecosystem health; however, constrained by hydrological model uncertainties, their precise simulation and quantitative assessment remain challenging. This study integrates physically-based hydrological models with remote sensing fusion data and observed data to construct seven calibration schemes, with a focus on evaluating the effectiveness of dual-variable blue-green water calibration methods based on remote sensing data fusion in enhancing simulation accuracy, reducing uncertainty, and achieving precise quantification of blue-green water, validated through a case study in the Xiangjiang River Basin. The following main conclusions were drawn: (1) The remote sensing fusion evapotranspiration (ET) data achieved the highest accuracy (R = 0.87, Re = 37.5 %, RMSE = 56.56 mm/month), with spatiotemporal fusion processing enabling a better balance between authenticity and accuracy, outperforming individual ET products; (2) The remote sensing fusion ET data can better support the model in achieving reliable simulation accuracy for both blue-green water, whether it is used as input for single-variable GW calibration or for dual-variable blue-green water calibration. Particularly under the dual-variable calibration scheme, this data significantly improved the simultaneous simulation accuracy of blue-green water; (3) The dual-variable scheme based on remote sensing fusion data significantly outperforms the traditional single-variable BW calibration in GW simulation. This scheme effectively constrains and optimizes vertical flux parameters by utilizing ET data, thereby substantially improving the estimation accuracy of GW. This study exploratorily combined hydrological modeling with remote sensing data fusion methods, providing an effective approach for accurate simulation of blue-green water at the watershed scale. It has application potential in water resources optimal allocation, vegetation water conservation assessment, and ecosystem service function quantification, and can provide scientific support for sustainable management of watershed water resources and ecological protection decision-making.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"323 ","pages":"Article 110046"},"PeriodicalIF":6.5,"publicationDate":"2025-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145731698","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}
Pub Date : 2025-12-12DOI: 10.1016/j.agwat.2025.110082
Xinglong Mu , Jin Wang , Fanxiang Meng , Ennan Zheng , Gang Li , Mo Li , Tianxiao Li , Zhaoxing Xiao , Yiming Fan , Xinru Li
Northeast China's agricultural sustainability is currently confronted with dual challenges of progressive soil degradation and uneven precipitation distribution. To address water deficit during critical crop growth stages while maintaining soil conservation, this study implemented a conservation tillage system integrated with Rainwater Harvesting-Recharge Irrigation Gradients (RH-RIG) through field experimentation. A 3 × 4 factorial completely randomized design was adopted, combining three conservation tillage practices (No-till/NT, Reduced tillage/RT, No-till with Mulching/NTM) with four RH-RIG levels (75 %, 125 %, 150 % of natural precipitation, plus rain-fed control/100 %). The experiment investigated the effects of tillage practices and rainwater utilization gradients on soybean root parameters (root length, surface area, volume, mean diameter, root-to-shoot ratio) and yield components. The results showed that: (1) Conservation tillage practices significantly influenced soybean root morphological traits, particularly total root length, root surface area, and root dry matter biomass (p < 0.05), thereby enhancing overall root system development. (2) Root parameters exhibited nonlinear responses to RH-RIG. The 125 % RH-RIG treatment achieved peak root volume and length, while the 150 % treatment reduced traits due to anaerobic stress, suggesting 1 25 % as a more effective water threshold. (3) No interaction was observed between tillage practices and RH-RIG. The combination of NT and 125 % RH-RIG (Treatment A2) independently enhanced root growth through additive physiological effects. (4) Root traits were positively correlated with yield. Treatment A2 produced the highest grain yield (2.97 ± 0.02 t ha⁻¹), representing a 31.6 % increase over the control. This study provides a theoretical foundation for implementing soil conservation-priority strategies and rainwater utilization in agricultural practices within cold-region Mollisol areas, offering critical guidance for enhancing crop productivity.
{"title":"Effects of conservation tillage and rainwater harvesting-recharge irrigation on soybean root architecture and yield in cold-region mollisols","authors":"Xinglong Mu , Jin Wang , Fanxiang Meng , Ennan Zheng , Gang Li , Mo Li , Tianxiao Li , Zhaoxing Xiao , Yiming Fan , Xinru Li","doi":"10.1016/j.agwat.2025.110082","DOIUrl":"10.1016/j.agwat.2025.110082","url":null,"abstract":"<div><div>Northeast China's agricultural sustainability is currently confronted with dual challenges of progressive soil degradation and uneven precipitation distribution. To address water deficit during critical crop growth stages while maintaining soil conservation, this study implemented a conservation tillage system integrated with Rainwater Harvesting-Recharge Irrigation Gradients (RH-RIG) through field experimentation. A 3 × 4 factorial completely randomized design was adopted, combining three conservation tillage practices (No-till/NT, Reduced tillage/RT, No-till with Mulching/NTM) with four RH-RIG levels (75 %, 125 %, 150 % of natural precipitation, plus rain-fed control/100 %). The experiment investigated the effects of tillage practices and rainwater utilization gradients on soybean root parameters (root length, surface area, volume, mean diameter, root-to-shoot ratio) and yield components. The results showed that: (1) Conservation tillage practices significantly influenced soybean root morphological traits, particularly total root length, root surface area, and root dry matter biomass (p < 0.05), thereby enhancing overall root system development. (2) Root parameters exhibited nonlinear responses to RH-RIG. The 125 % RH-RIG treatment achieved peak root volume and length, while the 150 % treatment reduced traits due to anaerobic stress, suggesting 1 25 % as a more effective water threshold. (3) No interaction was observed between tillage practices and RH-RIG. The combination of NT and 125 % RH-RIG (Treatment A2) independently enhanced root growth through additive physiological effects. (4) Root traits were positively correlated with yield. Treatment A2 produced the highest grain yield (2.97 ± 0.02 t ha⁻¹), representing a 31.6 % increase over the control. This study provides a theoretical foundation for implementing soil conservation-priority strategies and rainwater utilization in agricultural practices within cold-region Mollisol areas, offering critical guidance for enhancing crop productivity.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"323 ","pages":"Article 110082"},"PeriodicalIF":6.5,"publicationDate":"2025-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145731139","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}
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