Agricultural Water Management最新文献

{"title":"Optimizing summer fallow management decreases oligotrophic bacterial abundance and enhances rain-fed wheat yield through water and fertilizer improvements","authors":"Bin Yang ,&nbsp;Hao-ying Wang ,&nbsp;Lian-li Zhang ,&nbsp;Li Li ,&nbsp;Ting-liang Li","doi":"10.1016/j.agwat.2025.110099","DOIUrl":"10.1016/j.agwat.2025.110099","url":null,"abstract":"<div><div>Water scarcity and low soil fertility represent significant limitations to productivity within the dryland farming systems of the Loess Plateau. Consequently, optimizing summer fallow management to improve soil water retention and fertility is critical for enhancing soil quality in this region. To assess the maximum efficiency of rainfall capture during the summer fallow period, elucidate its interactions with soil microbial communities, and clarify the mechanisms underlying yield enhancement, a two-year field experiment was conducted. This study evaluated several treatments applied during the summer fallow: organic fertilizer alone (OF); organic fertilizer combined with deep tillage (OD); organic fertilizer with deep tillage and furrow-ridging (ODR); organic fertilizer with deep tillage, furrow-ridging, and plastic film mulching (ODRP); and organic fertilizer with deep tillage, furrow-ridging, and biodegradable film mulching (ODRB). Compared to conventional farmer practice (FP), the optimized rainfall management (ODRP) implemented in early summer fallow increased winter wheat grain yield by an average of 26.3 %, with spike number identified as the primary yield determinant. Between 2022 and 2024, the average efficiency of summer fallow rainfall storage under the OF, OD, ODRP, and ODRB treatments exceeded that of the FP treatment by 4.5 %, 36.3 %, 48.1 %, and 27.0 %, respectively. Notably, the ODR treatment reduced rainfall storage efficiency by 25.1 % relative to OD. The application of organic fertilizer during early summer fallow enhanced soil organic carbon content in the 0–40 cm soil profile by 8.8–24.8 % in the 0–20 cm layer and by 17.8–46.7 % in the 20–40 cm layer. Improved water and nutrient availability during the summer fallow period led to a decrease in the relative abundance of oligotrophic bacteria (Acidobacteria) and an increase in copiotrophic bacteria (Firmicutes). Correlation analyses demonstrated significant positive associations among soil moisture, Firmicutes abundance, and winter wheat yield. Partial least squares path modelling, coupled with Monte Carlo uncertainty analysis, identified soil moisture as the principal factor influencing yield formation via its effect on spike number, accounting for 63 % of the yield variability. Additionally, soil moisture and microbial metabolic activity contributed to organic carbon sequestration. In summary, maximizing rainfall-harvesting efficiency during the summer fallow period in conjunction with organic fertilizer application, constitutes a crucial strategy for promoting sustainable and high-quality agricultural development in the dryland wheat systems of the Loess Plateau.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"324 ","pages":"Article 110099"},"PeriodicalIF":6.5,"publicationDate":"2026-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145941026","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 user-friendly decision support tool for irrigation scheduling in smallholder olive orchards","authors":"L. Bonet ,&nbsp;F. Thomas ,&nbsp;M.A. Martínez-Gimeno ,&nbsp;M. Tasa ,&nbsp;E. Badal ,&nbsp;J.G. Pérez-Pérez ,&nbsp;U. Werban","doi":"10.1016/j.agwat.2026.110131","DOIUrl":"10.1016/j.agwat.2026.110131","url":null,"abstract":"<div><div>Water scarcity and climate variability threaten Mediterranean agriculture, particularly for smallholder growers who often lack the knowledge to use advanced irrigation technologies. This study presents the development and validation of a user-friendly decision support tool (DST) designed to optimise irrigation scheduling through a simplified, sensor-based balance model, the Soil-Atmosphere Adjusted Model (SAAM). The tool delivers weekly irrigation recommendations via a mobile application. The SAAM algorithm adjusts irrigation volumes based on weekly variations in reference evapotranspiration (ET₀) and relative soil water status (RWS) from capacitive soil moisture sensors. Field trials were conducted during 2022 and 2023 in a commercial olive orchard in eastern Spain with a dual objective: (<em>i</em>) to empirically define crop-specific physiological thresholds for RWS, and (<em>ii</em>) to validate the performance of the DST under real farming conditions. The drought cycles implemented enabled the identification of optimal RWS boundaries (RWS_LL = 0.63, RWS_UL = 0.73) based on stem water potential (Ψ_stem) and stomatal conductance (<em>g</em>_<em>s</em>) responses. In parallel, the SAAM demonstrated its capacity to reduce irrigation volumes by 11 % (11.9 mm) compared to a conventional technician-guided strategy (99.4 mm and 111.3 mm, respectively), while maintaining Ψ_stem and <em>g</em>_<em>s</em> within non-limiting physiological ranges. No significant differences were observed in olive or oil yields between treatments, resulting in improved irrigation water productivity under the DST approach. The modular DST architecture ensured robust, automated data acquisition, quality control, and real-time output via a user-friendly interface. These findings highlight the DST framework as a solution to promote smart irrigation and water use efficiency.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"324 ","pages":"Article 110131"},"PeriodicalIF":6.5,"publicationDate":"2026-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145941097","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":"Solar irrigation for adapting to climate change in cocoa farming: A choice experiment approach identifying Ghanaian farmers’ preferences","authors":"Kekeli Kofi Gbodji ,&nbsp;William Quarmine ,&nbsp;Marie-Charlotte Buisson ,&nbsp;Archisman Mitra ,&nbsp;Petra Schmitter","doi":"10.1016/j.agwat.2025.110118","DOIUrl":"10.1016/j.agwat.2025.110118","url":null,"abstract":"<div><div>Future climate conditions will be characterized by substantial uncertainty in weather patterns. For cocoa production, adapting to climate change will require securing water application and soil moisture by investing in irrigation infrastructure. In Ghana, government and private sector organizations have introduced solar-powered groundwater irrigation solutions to address the challenges. However, high upfront costs, limited access to institutional finance, and hydro-geological uncertainties constrain demand. We employed a discrete choice experiment approach to examine cocoa farmers’ willingness to adopt solar-based irrigation, surveying 550 farmers across seven regions depending on type of ownership, incentivized loans, and cutbacks on drilling uncertainties. The study revealed that cocoa irrigation investment decision depends primarily on access to longer-term loans, followed by cost reduction through group ownership, with the last factor being the reduction of uncertainties associated with borehole drilling. However, there are differences in farmers’ stated preferences based on wealth resources, gender, farm access, cocoa farm size, and household size. These findings suggest that policymakers should prioritize initiatives that alleviate financial constraints through longer-term loans to promote climate-resilient and sustainable agriculture. In addition, it indicates that a one-size-fits-all approach to promoting solar irrigation investment is unlikely to be effective, due to substantial heterogeneity in preferences amongst farmers. Instead, targeted policies are needed to increase solar pump adoption among marginalized groups like women and resource-poor farmers.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"324 ","pages":"Article 110118"},"PeriodicalIF":6.5,"publicationDate":"2026-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145941098","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":"Rainwater harvesting potential zone identification using GIS –Machine learning approach and comparison of their performance","authors":"Tade Mule Asrade ,&nbsp;Sintayehu Adefires Abebe ,&nbsp;Kassahun Birhanu Tadesse","doi":"10.1016/j.agwat.2026.110134","DOIUrl":"10.1016/j.agwat.2026.110134","url":null,"abstract":"<div><div>Rainwater harvesting (RWH) systems play a vital role in sustainable water management, yet their adoption is often constrained by the difficulty of accurately assessing site suitability and economic feasibility. This study aims to develop a machine learning (ML)–based geospatial framework to map RWH suitability in the Choke Watershed, Ethiopia, using twelve biophysical and hydrological conditioning factors. All spatial datasets were standardized and processed at a 30-m resolution, and the final suitability maps were generated at the same spatial scale to ensure consistent spatial comparability. Three ML algorithms—Random Forest (RF), Gradient Boosting (GB), and Extreme Gradient Boosting (XGBoost)—were trained and validated using 175 suitable and 75 non-suitable inventory points, with a 70/30 training–testing split. Prior to model development, continuous predictors were normalized using min–max scaling, and all datasets were checked for missing values; incomplete DEM-derived pixels were corrected using bilinear interpolation, and unresolved records in thematic layers were removed to avoid bias during training. Model performance was evaluated using confusion-matrix metrics and the area under the receiver operating characteristic curve (AUC-ROC). The GB and XGBoost models showed the highest predictive accuracy (AUC = 0.97), followed by RF (AUC = 0.96). Spatial analysis revealed that highly suitable RWH zones are concentrated in flat terrain with loam and clay-loam soils and higher rainfall availability. This study represents the first application of GB and XGBoost models for RWH suitability mapping in the Choke Watershed and demonstrates the effectiveness of ML-driven geospatial modeling for identifying optimal RWH locations. The findings provide a valuable decision-support tool for planners and policymakers seeking to improve water resource management and climate-resilient agricultural development in the region.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"324 ","pages":"Article 110134"},"PeriodicalIF":6.5,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145941099","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":"Subsoiling with straw return optimizes the maize root system and water productivity","authors":"Fengbin Li ,&nbsp;Tianping Gao ,&nbsp;Ying Shen ,&nbsp;Qian Yang ,&nbsp;Hongxiang Zhao ,&nbsp;Geng Li ,&nbsp;Zhen Liu ,&nbsp;Yakov Kuzyakov ,&nbsp;Tangyuan Ning","doi":"10.1016/j.agwat.2026.110127","DOIUrl":"10.1016/j.agwat.2026.110127","url":null,"abstract":"<div><div>Long-term conventional tillage exacerbates subsoil compaction, restricting root penetration and water and nutrient uptake. Although subsoiling is known to mitigate plough pan formation, the interactive effects of tillage and straw return on root system architecture (RSA) and water productivity (WP) in maize remain poorly understood. Based on a long-term field experiment, this study evaluated three tillage methods (plough tillage, PT; subsoiling tillage, ST; and rotary tillage, RT) and two straw management practices (no return and all straw return). We investigated effects of tillage and straw management on soil hydro-physical properties, maize RSA, and their consequent impacts on grain yield and WP. ST significantly reduced soil bulk density by 5.4 % and increased porosity by 6.4 % in the 0–40 cm soil compared to PT. The integration of subsoiling with straw return (STA) was particularly effective, enhancing subsoil fertility and promoting a deeper, coarser root system. STA increased root length density by 33 %, root weight density by 28 %, and root diameter by 41 % in the subsoil (40–60 cm soil). This optimized RSA improved access to deep soil water and nutrients, resulting in a 4.7 % increase in grain yield and a 3.8 % increase in WP compared to plough tillage with straw return. Subsoiling tillage-straw synergy reshapes RSA by alleviating mechanical impedance and enhancing subsoil fertility, offering a scalable strategy to improve crop resilience and resource efficiency.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"324 ","pages":"Article 110127"},"PeriodicalIF":6.5,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145941096","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":"Study on dynamic change characteristics of shallow groundwater in arid and semi-arid areas: A case study in the Minqin Oasis, China","authors":"Zhao Lu ,&nbsp;Daqing Wang ,&nbsp;Jie Zhu ,&nbsp;Hongfei Zhao ,&nbsp;Yue Shi ,&nbsp;Haoli Xu ,&nbsp;Yong Huang ,&nbsp;Jiazheng Zhao","doi":"10.1016/j.agwat.2025.110119","DOIUrl":"10.1016/j.agwat.2025.110119","url":null,"abstract":"<div><div>Groundwater serves as a critical water resource in arid and semi-arid regions. Analyzing long-term dynamic characteristics of groundwater provides valuable insights for guiding rational development, utilization, and ecological restoration with greater precision. In this study, we focused on Minqin Oasis, a representative arid and semi-arid region in China. Utilizing groundwater depth data collected from 4065 civilian wells during winter and summer of 2019, we simulated groundwater levels using the ordinary kriging interpolation method to delineate spatial distribution patterns. Based on continuous groundwater monitoring data from 12 observation wells spanning 2004–2019, this study analyzed long-term trends in groundwater level variations. Nine indicators related to discharge and recharge processes were selected and examined using principal component analysis to identify key factors influencing groundwater dynamics. The results reveal significant seasonal fluctuations in groundwater levels during 2019, with notably higher variations in winter and summer. Agricultural water use was found to exert a substantial impact on groundwater levels in the study area. Although the declining trend observed since 2004 has been gradually mitigated, and most monitoring sites have exhibited varying degrees of recovery since 2013—with a maximum rise rate of 0.397 m/year—groundwater levels at approximately three-quarters of the observation wells remained below those recorded in 2004 as of 2019. Furthermore, a continued declining trend persists at a few individual sites. These findings underscore the need for enhanced measures to protect and restore groundwater levels in the region.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"324 ","pages":"Article 110119"},"PeriodicalIF":6.5,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145941094","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":"Management of critical source areas (CSAs) in pasture grazed by deer to reduce contaminant losses to water","authors":"Richard W. Muirhead ,&nbsp;Peter Green","doi":"10.1016/j.agwat.2025.110106","DOIUrl":"10.1016/j.agwat.2025.110106","url":null,"abstract":"<div><div>Agriculture is important for producing food but can have environmental impacts on water quality. There is a need to develop mitigation strategies for pastoral farming systems to find a better balance between food production and environmental footprint. This study used a paired catchment experimental design to test the effectiveness of three mitigation strategies targeting the critical source areas (CSAs) that were ephemeral streams in deer grazed pastures. The runoff from four small catchments on the same hill slope (2.2–3.6 ha) was monitored for 2 years, under typical farm management. The mitigation options of: full fencing, partial fencing and temporary fencing was then applied to the CSA areas in three of the catchments. The fourth catchment was left unchanged as a control to account for different weather conditions in the pre- and post-treatment phases. Post-treatment monitoring was conducted for a further 2 years. The effectiveness of the mitigation options was calculated for both reducing contaminant concentrations (nitrogen, phosphorus, sediment and <em>E. coli</em>) under low-flow conditions and contaminant loads during storm events. The effectiveness of the three mitigation options for reducing low-flow concentrations ranged from not effective for filterable reactive phosphorus (FRP), total phosphorus (TP), and total suspended solids (TSS) to 83 % effective for reducing <em>E. coli</em>. The effectiveness of the three mitigation options for reducing storm-flow event loads ranged from not effective for FRP to 93 % effective for reducing <em>E. coli</em>. The CSA managements all mitigate multiple contaminants and hence will have multiple water quality benefits downstream.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"324 ","pages":"Article 110106"},"PeriodicalIF":6.5,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145941095","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":"Coupled model for optimizing the water distribution and gate control of the canal system in an irrigation district","authors":"Yu Fan ,&nbsp;Ke Zhou ,&nbsp;Zhanyi Gao ,&nbsp;Mingming Yang ,&nbsp;Xinrong Zheng ,&nbsp;Xufeng Zhang","doi":"10.1016/j.agwat.2025.110117","DOIUrl":"10.1016/j.agwat.2025.110117","url":null,"abstract":"<div><div>Irrigation district canal systems deliver water to fields timely and adequately via check gates, with gate operation timings critical for service quality and operational efficiency. This study develops a coupled optimization model integrating a Linear-Quadratic Regulator (LQR) for precise canal water level control and a rotational irrigation grouping model to reduce energy consumption and equipment wear from frequent gate adjustments. The model was validated on a main canal section of a large-scale irrigation district in China, which was divided into three canal pools by four check gates. Three typical scheduling modes were implemented, namely top-down distribution, bottom-up distribution, and flexible distribution. Compared with the traditional Proportional-Integral (PI) control algorithm, the proposed method can significantly reduce both canal water level deviations and gate adjustment frequency. Taking Pool 2 as an example, the deviation reduction rate reaches 68 %-71 % during its key operational stages. Among the three scheduling modes, the flexible distribution mode achieves the shortest total operation duration of 244.85 h—compared with 259.8 h for the top-down distribution mode and 285.36 h for the bottom-up distribution mode—while simultaneously ensuring a higher water demand satisfaction rate. However, it may cause management inconvenience when canals with a long distance between upstream and downstream are grouped into the same rotation irrigation group. In contrast, the other two are easier to management but involve more frequent adjustments. This coupled model provides a novel technical approach for irrigation district water distribution and gate control, with important theoretical and practical value for improving water resource utilization efficiency and service quality.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"324 ","pages":"Article 110117"},"PeriodicalIF":6.5,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145897890","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":"Modelling perennial saffron growth and yield under different irrigation water salinities, irrigation water levels and planting methods","authors":"Maryam Dastranj ,&nbsp;Ali Reza Sepaskhah","doi":"10.1016/j.agwat.2025.110097","DOIUrl":"10.1016/j.agwat.2025.110097","url":null,"abstract":"<div><div>Decision-making on efficient field management for crop production requires modeling crop growth and yield, especially in relation to varying climate issues. In this regard, the SYEM model was developed and modified for saffron. The data used in this research were obtained from Dastranj and Sepaskhah (2019). In the current study, the ability of the modified SYEM model to simulate soil water and salt transport, saffron growth and its yield components under different irrigation water salinities [0.45 (well water, S₁), 1.0 (S₂), 2.0 (S₃), 3.0 (S₄) dS m⁻¹], irrigation water levels [100 % (I₁). 75 % (I₂) and 50 % (I₃) of saffron water requirement (W<em>R</em>)] and planting methods [basin (P₁) and in-furrow (P₂) planting] was investigated. According to the NRMSE and d indices, the modified SYEM model simulated ET, E, and T with good accuracy (NRMSE ranging from 10 % to 20 %). Also, the values of NRMSE and d (index of agreement) for predicting dry matter, saffron yield, and corm yield varied between 10 % and 20 % and 0.85 and 0.95, which indicated a good ability of the model in simulating these parameters in both calibration and validation steps. The model's ability to simulate LAI during the growing season was good in the calibration step; however, it was fairly acceptable in the validation step. Also, the model was not able to predict the day on which the maximum LAI occurred. Soil water salinity and soil water content were also simulated by modified SYEM with an acceptable accuracy (NRMSE from 20 % to 30 %) in both calibration and validation steps. The model overestimated the soil water salinity, especially in the in-furrow planting. Finally, it is concluded that the modified SYEM model is a simple and user-friendly tool for predicting saffron yield, thereby facilitating better field management.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"323 ","pages":"Article 110097"},"PeriodicalIF":6.5,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145938693","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":"Atmospheric dryness and flash drought severity drive the shifts of different flash drought types into agricultural droughts","authors":"Chen Hu ,&nbsp;Dunxian She ,&nbsp;Liping Zhang ,&nbsp;Gangsheng Wang ,&nbsp;Zhaoxia Jing ,&nbsp;Si Hong ,&nbsp;Jun Xia","doi":"10.1016/j.agwat.2025.110109","DOIUrl":"10.1016/j.agwat.2025.110109","url":null,"abstract":"<div><div>Flash droughts, characterized by their rapid onset and intensification, can evolve into long-term agricultural droughts, thereby amplifying adverse impacts on water resources, agriculture, and ecosystems. However, the propagation from short-term flash droughts to long-term agricultural droughts remains limited understood, particularly across different flash drought types. Here we developed an integrated framework that combined convergent cross mapping (CCM), the random forest model, and the copula-based Bayesian approach to investigate the propagation pathways and underlying mechanisms. We applied this framework to analyze the propagation of meteorological, soil, and evaporative flash droughts into agricultural droughts in the Middle and Lower Reaches of the Yangtze River Basin (MLRYRB) from 2000 to 2022. Our results revealed strong causal relationships between flash droughts and agricultural droughts, with an average propagation time of 36.8–48.8 days. Meteorological flash droughts showed the shortest propagation time, while evaporative flash droughts exhibited the longest. Soil flash droughts demonstrated the highest propagation frequency, rate, and sensitivity to agricultural droughts, while evaporative flash droughts showed the lowest translation rates to agricultural droughts. We further found that flash drought severity strongly influenced the propagation of all flash drought types, particularly soil flash droughts, with a threshold value of 11.2 ± 2.3. Additionally, precipitation and vapor pressure deficit (VPD) emerged as the most critical factor for meteorological and evaporative flash drought propagation, with threshold values of 14.3 ± 7.6 mm and 7.8 ± 2.3 hPa, respectively. These findings can advance our understanding of flash drought dynamics and mechanisms, offering important insights for effective drought mitigation.</div></div>","PeriodicalId":7634,"journal":{"name":"Agricultural Water Management","volume":"323 ","pages":"Article 110109"},"PeriodicalIF":6.5,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145938575","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}