Search Results (733)

Across human history, water has sustained communities while also shaping religious imagination as a symbol of life, danger, purification, and renewal. This review examines how water acquires religious meaning through symbolic associations, ritual uses, theological interpretations, sacred landscapes, and material water infrastructures across more than five millennia, drawing on examples from ancient civilizations, long-standing Asian traditions, Indigenous religions of the Americas and the Caribbean, and the three major Abrahamic religions. The study explores how rivers, springs, rain, floods, wells, sacred basins, and ritual waters have been understood as signs of creation, purification, fertility, healing, divine presence, destruction, and renewal, while also remaining part of everyday practices of settlement, agriculture, health, and communal life. The comparative analysis highlights recurring patterns and cultural differences. In some traditions, water appears as a primordial substance from which life emerges; in others, it functions as a medium of moral cleansing, ritual preparation, communal prayer, or sacred geography. The study argues that the religious meaning of water is best understood through the interaction of four closely related dimensions: symbolic interpretation, ritual practice, sacred or culturally charged landscapes, and material water infrastructures. By bringing these dimensions together, the article uses the concept of hydraulic heritage to connect religious water symbolism with sacred basins, wells, springs, hammams, monastic water systems, irrigation rituals, and other inherited water-related landscapes and practices. These connections offer a culturally grounded perspective for contemporary discussions on environmental ethics, water protection, and societies’ responsibility toward natural resources. Full article

In many orographically complex monsoon basins, rain gauge networks are sparse and lack the long-term continuous records required for reliable precipitation probability analysis. Traditional regional frequency analysis assumes spatially uniform precipitation across the analysis zone, which is inadequate for basins with steep rainfall gradients and strong seasonal variability. Gridded precipitation products (GPPs) provide spatially continuous, long-term records that enable grid-cell-level probability distribution fitting. However, GPPs may exhibit local biases and errors, and statistical evaluation against gauge observations is necessary before application. This study was conducted in the Phetchaburi–Prachuap Khiri Khan River Basin, western Thailand, a region with steep orographic and coastal rainfall gradients. Four GPPs, namely CHIRPS, CHELSA, WorldClim, and PERSIANN-CCS-CDR, were evaluated against gauge observations. The best-performing product, after monthly bias correction, was then used to generate spatially continuous monthly exceedance probability maps using grid-cell gamma distribution fitting. CHELSA showed the best overall performance across all evaluation metrics (correlation coefficient (r) = 0.908, percent bias (PBIAS) = 7.0%, root mean square error (RMSE) = 48.3 mm), passing the Kolmogorov–Smirnov (KS) goodness-of-fit test at all 96 station-months. CHIRPS and WorldClim showed satisfactory overall performance but exhibited localized biases in complex terrain, whereas PERSIANN-CCS-CDR substantially overestimated wet-season rainfall, limiting its suitability for this basin. Spatial precipitation patterns varied markedly between monsoon regimes, shifting from a dominant west-to-east orographic gradient during the southwest monsoon to a less differentiated advective pattern during the northeast monsoon. Furthermore, analysis at the 75% exceedance probability level showed that mean-based effective rainfall overestimated reliable water supply in high-variance months, leading to underestimation of supplemental irrigation demand. The generated maps provide spatially explicit dependable rainfall estimates across the basin, supporting probabilistic agricultural water management at multiple planning scales in orographically complex monsoon basins. Full article

Background/Objectives: To compare the incidence of postoperative acute urinary retention (AUR) between traditional open laminectomy and percutaneous endoscopic lumbar surgery (PELS) using a large-scale real-world database, with specific stratification by urologic status, age, and sex. Methods: A retrospective, propensity score-matched analysis was conducted using the TriNetX Global Health Research Network (2015–2024). Adult patients undergoing PELS were compared to those undergoing open laminectomy. To rule out the confounding effect of routine intraoperative catheterization, the primary outcome was defined as de novo AUR occurring between 24 h and 3 months postoperatively. Subgroup analyses were performed for patients with benign prostatic hyperplasia (BPH), females, and age-stratified cohorts (<70 vs. ≥70 years). This study was approved by the Institutional Review Board (IRB/REC: CE25727C) and conducted under a waiver of informed consent. Results: In the matched cohorts of non-BPH males, females, and patients aged < 70 years, PELS was associated with a statistically significant reduction in AUR risk (Hazard Ratios: 0.445, 0.649, and 0.403, respectively) compared to open surgery. However, in males with BPH, the protective benefit of the endoscopic technique was attenuated and did not reach statistical significance (p = 0.0744), suggesting the study was underpowered for this subgroup or that baseline obstruction remains a dominant risk factor. Conclusions: Percutaneous endoscopic lumbar surgery was associated with a significantly lower risk of postoperative AUR compared to open laminectomy, particularly in patients without preexisting urologic obstruction. This benefit is likely attributable to minimized tissue trauma and the anti-inflammatory effects of continuous saline irrigation. However, in patients with BPH, baseline pathology outweighs surgical factors, necessitating medical prophylaxis regardless of the surgical approach. Full article

Salinity stress remains a major bottleneck for agriculture in arid regions. While Opuntia ficus-indica is known for its resilience, its young cladodes maintain a misleadingly healthy visual appearance and stable biomass even under heavy saline pressure, making traditional vegetation indices and standard statistics unreliable for early diagnosis. The objective of this study was to develop a non-destructive phenotyping framework for the early detection of latent salinity stress in young Opuntia cladodes. Controlled experiments were conducted using hyperspectral data cubes (400–1000 nm) acquired from plants exposed to six distinct salinity levels ranging from 2 to 21 dS m⁻¹. Our methodology integrates these high-dimensional spatial–spectral data with a tailor-made 3D Convolutional Neural Network (3D-CNN). Seven physiological vegetation indices—NDVI, PRI, WI, PSRI, MCARI, SIPI, and NDRE were extracted to track sub-clinical shifts and processed as a volumetric depth dimension within the network to preserve spatial–spectral integrity. The optimized 3D-CNN framework achieved a validation accuracy of 99.7% and a weighted F1-score of 99.1%, delivering 100% precision at critical stress thresholds (13 and 21 dS m⁻¹). Spatial confidence maps (Softmax > 0.95) further confirmed the high reliability of the diagnostic output. Requiring a training duration of approximately 8 s, this framework provides a robust basis for precision early-warning irrigation systems to sustain Opuntia cultivation in challenging environments. Full article

Accurate vineyard yield estimation is essential for harvest planning, resource allocation, and economic decision-making, particularly under conditions of high spatial variability. Traditional sampling-based methods are labor-intensive, destructive, and prone to error, especially in high-productivity free-canopy systems. This study developed and evaluated predictive models for commercial irrigated vineyards of Carménère and Chardonnay in Chile’s Maule Region across two growing seasons (2023–2025). Structural yield components, physiological measurements, and UAV-derived multispectral indices (NDVI, GNDVI, NDRE) were collected from georeferenced sampling grids. Modeling approaches included linear regression, stepwise selection, and machine learning algorithms (Random Forest, Multilayer Perceptron). Validation results showed that cluster number was the primary driver of yield variability, explaining up to 40% of variation. Incorporating physiological and spectral variables improved accuracy, with the best models (least squares and MLP) achieving R² values up to 0.66 and reducing errors to 12–15%. Spatial yield maps reproduced intra-vineyard variability patterns, demonstrating that integrating plant-level and canopy-level data substantially enhances yield prediction. These findings provide a robust framework for precision viticulture applications. Full article

Khettara are traditional underground irrigation systems widely distributed in southern Morocco, many of which are currently abandoned. These semi-subterranean ecosystems may provide suitable microhabitats for phlebotomine sand flies, yet no entomological investigations have previously been conducted in the Khettara system of the Marrakech region. This study aimed to assess the abundance of sand fly and species composition within this unique environment and to evaluate its potential epidemiological significance. A total of 477 sand fly specimens (Diptera: Psychodidae) were collected and identified, representing six species; Phlebotomus (Phlebotomus) papatasi (28.72%) was the predominant species followed by Sergentomyia (Grassomyia) dreyfussi (23.06%), S. (Sergentomyia) fallax (18.87%), S. (S.) minuta (10.69%), P. (Larroussius) longicuspis (9.85%), and P. (Paraphlebotomus) sergenti (8.81%). Notably, S. (G.) dreyfussi was collected for the first time in the urban area of Marrakech. The findings demonstrate considerable sand fly diversity within the Khettara ecosystem compared to previously documented urban sand fly assemblages in Marrakech. Importantly, three of the six identified species are confirmed vectors of leishmaniasis in Morocco. These results suggest that the Khettara system may represent a potential refuge of some proven and potential vectors of leishmaniases in Morocco. Surveillance and integrated vector control strategies should therefore be considered in the Marrakech region, particularly in and around abandoned Khettara structures. Full article

Protected cultivation, as a core model of modern agriculture, holds a crucial strategic position in alleviating the shortage of arable land resources and increasing farmers’ income. However, due to the closed environment of protected cultivation, suitable temperature and humidity conditions for pathogen reproduction, serious continuous cropping obstacles, disease transmission easily caused by irrigation, and the lack of natural ultraviolet inhibition and crop rotation conditions, soil-borne pathogens accumulate year by year, resulting in early onset, rapid spread, and great difficulty in control. Traditional pesticide formulations often have limitations such as environmental hazards, low utilization rate, unstable active ingredients, excessive use, and short persistence in the control process. In recent years, pesticide slow-release carriers developed based on nanotechnology to regulate the slow-release behavior of pesticide active ingredients have shown great potential in improving pesticide efficacy and safety. This article reviews several commonly used materials for mineral carriers, metal oxide carriers, organic polymer carriers, and organic–inorganic hybrid carriers. With their high specific surface area, high drug loading rate, environmental friendliness, and stimulus-responsive properties, these materials can significantly improve the effective utilization rate of pesticides, extend the persistence period, and enhance targeting, thus providing strong technical support for solving the problem of soil-borne disease control in protected cultivation and promoting the green and sustainable development of protected cultivation. Full article

The article is devoted to developing methodological approaches to multi-criteria resource optimization of technological solutions in Nature Use Projects, considering the growing shortage of water and energy resources, climate change, and post-war transformation of Ukraine’s agricultural sector. The need to transition from traditional technical and economic optimization models to integrated assessment approaches, which consider ecological, resource, and economic aspects of the project implementation effectiveness, is substantiated. The methodological basis of the study is a combination of Multi-Criteria Decision-Making and the Water-Energy-Food Nexus concept, enabling the necessary adaptive management and formalizing the process of project decision-making under multifactor uncertainty. A set of indicators of resource-ecological and economic efficiency is proposed, including indicators of productivity, weather and climate risk, resource use, environmental reliability, investment attractiveness, etc. A key feature of this approach is the transformation of resource-ecological indicators into a value form, ensuring their integration with economic indicators within a single optimization model. Based on a machine experiment for the conditions of the Kherson region, an assessment of the effectiveness of various irrigation regimes, which differ from the project irrigation regime in terms of watering and irrigation norms, in terms of their level of provision with water and energy resources, was carried out. It was determined that, under the studied conditions, in dry years (p = 70%), the permissible deficit threshold is approximately 30%, achieving a compromise between economic efficiency and environmental acceptability. Adaptive management of irrigation regimes has been shown to reduce the resource intensity of production without a significant loss of productivity. This creates a basis for revising outdated design standards, which focused on 100% satisfaction of water needs, in favor of adaptive models that account for the real resource potential of the territory. This approach transforms irrigation from a resource-intensive industry into a tool for sustainable territorial development, where the priority is the efficiency of each cubic meter of water and kilowatt-hour of energy used, rather than gross collection. It has been proven that the implementation of resource optimization as a basic principle of natural resource project management contributes to increasing the efficiency of natural capital use, minimizing ecological risks, and ensuring the sustainable development of the agricultural sector. The obtained results can be used to substantiate engineering solutions in projects for the restoration and modernization of water management and land reclamation systems in Ukraine. Full article

Satellite-observed greening in arid regions is often interpreted as ecological restoration success, yet this assessment may conflate natural recovery with agricultural expansion. We developed an Arid Remote Sensing Ecological Index (ARSEI) incorporating a Comprehensive Salinity Index (CSI) to address systematic biases in the traditional RSEI when applied to irrigated drylands. ARSEI scores were validated against MODIS Net Primary Production (NPP) ($R^2>0.75$ at the regional scale), confirming its reliability in capturing ecosystem productivity, while CSI effectively maps the upper-bound of surface salinization potential dictated by intrinsic soil properties. Applied to China’s Mu Us Sandy Land (2000–2024), the ARSEI reveals that 2327 km² of sandy land—54% of current cropland—was converted to agriculture, creating “assessment-induced false greening” signals. While the traditional RSEI increased monotonically (+135%), the ARSEI shows a nuanced pattern with plateau (2010–2015) and decline (2015–2020) phases, reflecting salinization risks masked by high crop NDVI. Optimal Parameters-Based Geographical Detector analysis demonstrates that Land Cover × Precipitation interactions (q = 0.28) drive spatial heterogeneity through irrigation-mediated water redistribution. The ARSEI provides a dialectical evaluation framework: acknowledging agricultural greening’s economic benefits while monitoring subsurface degradation risks. This study offers a critical methodological advance for sustainable land assessment in global drylands undergoing agricultural intensification. Full article

With increasing water scarcity and growing food demand, enhancing agricultural productivity has become a pressing necessity, aligning with the Sustainable Development Goals (SDGs). Maize is a strategic crop, yet under surface irrigation, modern technologies are required to optimize irrigation efficiency and reduce water losses. Two field trials were conducted during the summer seasons of 2024 and 2025 on a private farm in Banha, Qalyubia Governorate, Egypt, using a three-replication split-block design. This study evaluated three land slopes (0, 0.05, and 0.15%) and two furrow lengths (50 and 75 m) under furrow irrigation in clay loam soil, using the maize hybrid “Single Cross 2036.” The results demonstrated that both furrow length and land slope significantly affected all measured parameters. Shorter furrows (50 m) consistently outperformed longer ones (75 m), achieving better growth parameters, higher grain yield, improved harvest index, and enhanced irrigation water productivity. Regarding land slope, the 0.15% slope produced the best results, although it was not significantly different from the 0.05% slope in most cases. The interaction between furrow length and land slope was significant; the combination of 50 m furrows with 0.15% slope produced the highest values across all parameters. For longer furrows (75 m), the gentler 0.05% slope was more effective than the steeper 0.15% slope. Notably, 50 m furrows, even with 0% slope, performed better than 75 m furrows with the optimal 0.05% slope, indicating that furrow length is more critical than slope for maximizing maize productivity in clay loam soils. Economic analysis confirmed these findings, with the combination of 50 m furrows and 0.15% slope achieving the highest net return (29,565 EGP ha⁻¹) and revenue-to-cost ratio (1.38), representing a substantial increase in net profit compared to traditional practices. Therefore, a 0.15% slope is recommended for shorter furrows (50 m), while a gentler 0.05% slope is more suitable for longer furrows (75 m). These findings provide a practical pathway for policymakers and farmers to enhance resource efficiency and contribute to SDG 2 (Zero Hunger) and SDG 6 (Clean Water and Sanitation). Full article

Abiotic stresses caused by climate change pose a significant challenge to global food security, making it necessary to develop stress-resistant crops. Foxtail millet (Setaria italica (L.) P. Beauv.) is a drought-tolerant C₄ cereal and serves as a model crop for elucidating stress adaptation mechanisms and promoting climate-resilient agricultural solutions. This paper reviews the tolerance mechanisms of foxtail millet to abiotic stresses. Physiologically, the species exhibits excellent water-use efficiency, requiring 75% less irrigation than traditional cereals, achieved through enhanced osmotic adjustment via soluble substance accumulation and the maintenance of ion homeostasis. Morphological adaptations include reduced leaf area, adjusted stomatal density, well-developed root systems, and specialized anatomical features that optimize water conservation. At the molecular level, stress tolerance involves complex transcriptional networks mediated by multiple transcription factor family members, including those (NF-Y, DREB, NAC, WRKY, MYB) that coordinate stress-responsive gene expression, antioxidant defense systems, and osmotic adjustment pathways. Furthermore, this review summarizes multi-omics characteristics, including genomics (such as QTL mapping and GWAS), proteomics, transcriptomics, metabolomics, and regulatory networks, for foxtail millet under abiotic stress tolerance. Additionally, reproductive resilience is maintained through efficient mobilization of stem reserves to panicles, phenological plasticity in flowering timing, and preserved gametic viability under thermal stress. Combining advanced molecular breeding with the inherent tolerance of foxtail millet positions this crop as both a solution to climate change and a genetic resource for enhancing the stress resistance of other cereals. These findings establish foxtail millet as a valuable model for developing sustainable agricultural technologies essential for food security under projected climate scenarios. Full article

Under the background of global change, the threshold for the propagation of meteorological drought to hydrological drought is crucial for drought early warning and water resource management. However, traditional threshold studies often adopt subjective and fixed conditional probabilities and lack the revelation of the driving mechanisms under macroscopic natural geographical differentiation. This study integrates terrestrial water storage anomaly (TWSA) data derived from the Gravity Recovery and Climate Experiment (GRACE) and its Follow-On (GRACE-FO) mission, the standardized precipitation evapotranspiration index (SPEI), and multi-source environmental data to construct an objective threshold identification method based on Copula joint distribution and “system resilience loss”, and combines explainable machine learning to systematically explore the critical threshold for meteorological drought, triggering a TWSA deficit and its driving mechanisms from the perspectives of three major natural regions, the Eastern Monsoon Region (EMR), the Northwestern Arid Region (NAR), and the Tibetan Plateau Region (TPR). The results show that: (1) from 2005 to 2024, the TWSA significantly decreased in nearly half of China’s regions, with significant regional differentiation; (2) the response of the TWSA to meteorological drought has a significant lag (an average of 9–12 months), and shows a spatial pattern of slower in the east and faster in the northwest; (3) the probability of a TWSA deficit and the triggering threshold both have obvious grade dependence and spatial heterogeneity, with the lowest threshold in the northwest arid region, which is the most sensitive; (4) the threshold is driven by the synergy of multiple factors, with “water dominance and energy modulation”, and the dominant factors show regional differentiation; and (5) irrigation agriculture significantly reduces the drought triggering threshold and exacerbates system vulnerability. This study provides a scientific basis for understanding the geographical differentiation laws of drought propagation and regional early warning management. Full article

Traditional irrigation management for tomatoes in solar greenhouses relies heavily on empirical manual experience and single soil moisture indicators, often leading to irrigation scheduling that lacks crop-specific physiological evidence and results in suboptimal water-use efficiency. To address these challenges, this study developed an intelligent, plant-centric irrigation decision-making framework for greenhouse tomatoes in the arid region of Xinjiang. Central to this framework is the precise identification of irrigation timing—the most critical first step and a fundamental prerequisite for achieving true on-demand irrigation. By monitoring the high-frequency dynamics of stem diameter (SD) and integrating soil moisture data, the physiological responsiveness of tomatoes to water stress was systematically analyzed. A hybrid predictive model, STL-LSTM, was constructed by coupling Seasonal-Trend decomposition using Loess (STL) with Long Short-Term Memory (LSTM) networks to forecast 24-h SD trends. Furthermore, an innovative dual-threshold irrigation mechanism was established, utilizing a physiological trigger (Maximum Daily Shrinkage, MDS > 70 μm) and a soil moisture constraint (Volumetric Water Content, VWC ≤ 17%). Results demonstrated that tomato SD exhibited distinct diurnal rhythms, with MDS and Daily Increment (DI) identified as highly sensitive indicators of plant water status. The proposed STL-LSTM model achieved superior predictive performance during the peak fruiting stage, with a coefficient of determination (R²) of 0.9184, representing an improvement of 14.8% and 27.56% over standalone LSTM and ARIMA models, respectively. The validation of the dual-threshold mechanism confirms its ability to balance real-time crop water demand with conservation requirements, effectively mitigating the risks of premature or delayed irrigation inherent in traditional methods. This research provides scientific rationale and technical support for the transition of greenhouse agriculture in arid regions towards precision irrigation and optimised water resource management. Full article

Viticulture is highly vulnerable to weather variability and climate change. Growers increasingly face risks associated with extreme weather events, water scarcity, and emerging pests and diseases. To address these challenges, this study presents the development and implementation of the first operational digital decision support platform (DSP) tailored to Montenegrin vineyards within the MONTEVITIS project. The platform integrates IoT sensor data, national meteorological records and high-resolution global climate datasets to provide real-time monitoring and climate projections for vineyard management. The system was piloted in four vineyards representing diverse microclimatic and soil conditions of Montenegro. Key functionalities include phenology, irrigation and disease alerts supported by a user-friendly dashboard, map-based visualisation tools and data export functions. The pilot deployment demonstrated that combining heterogeneous data streams increases the reliability of outputs and enables timely, site-specific recommendations. Challenges identified during implementation include connectivity limitations, gaps in data and variable levels of digital expertise among growers; however, lessons learned point to the importance of continuous stakeholder engagement and institutional support for sustained use. The MONTEVITIS experience demonstrates how digital agriculture tools can bridge tradition and innovation in viticulture. By fostering collaboration between growers, researchers and policy makers, the platform enables adaptive strategies for climate resilience and sustainable vineyard management. Although the platform has been successfully deployed and tested under pilot conditions, a comprehensive long-term validation of its performance and impact on vineyard decision-making remains part of ongoing future work. Full article

On the North China Plain, the winter wheat season is poorly synchronized with precipitation, making the traditional winter wheat–summer maize system heavily dependent on supplemental irrigation and associated carbon inputs. Based on a split-plot field experiment in Shenzhou, Hebei, from October 2022 to October 2025, this study evaluated the trade-off between annual system yield and area-scaled carbon emission among six cropping systems under conventional irrigation (CK) and rainfed management (R). The winter wheat–summer maize system (WM) maintained the highest grain-oriented annual system yield (22.91 t ha⁻¹ yr⁻¹ under CK), but it also showed the highest area-scaled carbon emission (11.97 t CO₂-eq ha⁻¹ yr⁻¹). The winter wheat–summer maize–spring maize system (WMM) reduced area-scaled carbon cost relative to WM (8.97 vs. 11.97 t CO₂-eq ha⁻¹ yr⁻¹ under CK), whereas its product-scaled carbon footprint remained comparable to or slightly higher than that of WM. Under a unified dry-matter basis, the double silage-maize system (FM) showed the lowest dry-matter-scaled carbon footprint (CF_DM; 193.85 and 175.71 kg CO₂-eq t DM⁻¹ under CK and R, respectively). Soil respiration in 2025 varied mainly with observation date and cropping-system configuration, and soil organic carbon (SOC) stock at the 2025 harvest differed among cropping systems, water-management regimes, and soil depths. Overall, WM remained the highest-yielding option under a grain-supply objective, whereas FM, the ryegrass–early-summer maize system (RM), and the forage winter wheat–early-summer maize system (FWM) were relatively more suitable under multifunctional biomass-supply and low-carbon-transition objectives. Full article