Search Results (405)

Despite its significant water-saving potential, the adoption of alternate wetting and drying (AWD) irrigation remains limited due to infrastructure constraints and intensive manual monitoring requirements. An automated precision irrigation system was developed and tested at the Bangladesh Rice Research Institute research farm in Gazipur, Bangladesh. The system combined ultrasonic water-level sensors, capacitive soil moisture sensors, an Arduino-based microcontroller, a GSM communication module, and solar-powered automatic control gates. Field performance was evaluated following a Randomized Complete Block Design (RCBD) under four irrigation treatments: IRRISAT, IRRI35, IRRI25, and continuous flooding (CF). The first three irrigation treatments were operated using scheduled daily decision windows, in which irrigation actions were automatically triggered based on predefined schedules and sensor threshold values. In IRRISAT, irrigation started when soil moisture dropped slightly below saturation and stopped at a ponding depth of 5 cm, while IRRI35 and IRRI25 were triggered at volumetric soil water contents of 35% and 25%, respectively, with the same upper cutoff of 5 cm ponding depth; CF served as the control. The IRRI35 treatment achieved a high grain yield (7.76 t ha⁻¹) while reducing water use by 28% and energy consumption by 37% compared to CF. Water use efficiency was considerably higher under IRRI35 (9.4 kg ha⁻¹ mm⁻¹) than under CF (6.7 kg ha⁻¹ mm⁻¹). The automated system proved to be reliable and precise in scheduled irrigation control, significantly reducing water use and labor requirements. The findings suggest that large-scale adoption of the system under real-world cultivation conditions could reduce irrigation energy needs and contribute to sustainable water governance in rice production. Full article

Climate change poses significant challenges to the operation and safety of dam and reservoir (D&R) systems, particularly in regions characterized by water scarcity and high climate variability. This study presents a structured methodology for climate risk assessment that integrates regional climate projections, system-specific thresholds, and a semi-quantitative risk matrix approach. A key innovation is the explicit linkage between climate indicators and system performance through physically based thresholds, combined with empirically derived exceedance probabilities from high-resolution climate projections. The methodology is applied to the Almopeos D&R system in northern Greece, using an ensemble of statistically downscaled CMIP6 simulations under two emission scenarios (SSP2-4.5 and SSP5-8.5) and two future periods (2041–2060 and 2081–2100). Three climate indicators are analyzed: TX35 (temperature extremes), CDD (consecutive dry days), and Rx1day (extreme precipitation). Results indicate that temperature increase is the dominant climate risk hazard, leading to increased irrigation demand and reduced system reliability, with risks classified as high to very high. Drought conditions represent a secondary but important risk, becoming critical during prolonged dry periods affecting reservoir storage, while extreme precipitation events exhibit low likelihood but potentially high consequences for dam safety. Adaptation measures are prioritized using a qualitative multi-criteria approach, highlighting the effectiveness of operational measures, while structural and monitoring interventions remain essential for ensuring system safety. The proposed methodology provides a transparent and transferable framework for climate-resilient planning of water infrastructure systems. Full article

This study comparatively assesses the Municipal Emission Reduction Plans (MERPs) of Spetses, Platanias, and Souli, examining their role as analytical and strategic tools for local climate planning, with particular emphasis on water-related infrastructure. A descriptive comparative analysis was conducted using secondary data extracted from officially approved MERPs, covering sectoral and total greenhouse gas emissions for 2019 and 2023, as well as reported mitigation actions and 2030 targets. The results reveal significant inter-municipal variations in emission patterns, driven by geomorphological characteristics, infrastructure configuration, and energy consumption, but also by governance structures and system boundaries. Water supply and irrigation systems are identified as highly energy-intensive sectors, particularly in municipalities with extensive, pumping-dependent networks. At the same time, the analysis shows that the inclusion or exclusion of outsourced services—such as water supply and wastewater management—substantially affects the representation of emissions and the prioritization of mitigation actions. The study concludes that MERPs can support climate planning at the municipal level, but their effectiveness is conditioned by data completeness, system boundaries, and governance models. These findings highlight the need to move beyond purely accounting-based approaches toward integrated planning frameworks that capture the full operational scope of municipal systems, enabling more accurate emission assessment and more effective, context-specific mitigation strategies within the water–energy–nexus. Full article

South African irrigation schemes face critical challenges of water scarcity, infrastructure deterioration, and limited monitoring capacity, threatening agricultural productivity and food security. This scoping review systematically analyses 59 peer-reviewed publications (2000–2025) on sensor-based and acoustic irrigation monitoring technologies in South Africa, using transformer-based natural language processing (Sentence-BERT embeddings), unsupervised Machine Learning (UMAP dimensionality reduction, HDBSCAN clustering), and geospatial mapping applied to literature retrieved from Web of Science and Scopus. Results show that water quality monitoring (42.4% of studies) and remote sensing (25.4%) dominate the national research landscape, while soil moisture sensing and modelling remain comparatively limited. Notably, no peer-reviewed studies applying acoustic monitoring technologies to irrigation were identified, representing a critical gap despite proven international applications for leak detection (95–98% accuracy), widespread infrastructure aging (over 50% of schemes exceeding 30 years), and reported water losses of 30–60% in poorly managed systems. Reported experimental water savings range from 15% to 30%, yet applications remain largely confined to pilot-scale implementations concentrated within a limited number of Water Management Areas. Persistent adoption barriers include infrastructure unreliability, financial inaccessibility, limited digital literacy, and weak institutional coordination. The review recommends: (i) expanding research coverage across underrepresented regions and Water Management Areas; (ii) strengthening extension support and technical training to enable broader adoption; and (iii) integrating low-cost sensor networks with predictive, data-driven irrigation advisory systems. These priorities aim to support scalable, context-sensitive irrigation modernisation under increasing water scarcity pressures. Full article

As just transition debates extend into agricultural land use, this study examines landscape transition in Huwei Township, Taiwan, through a procedural justice lens. To address severe land subsidence, the state has promoted a shift from paddy rice cultivation to dryland farming, but the transition remains politically contested. Based on a systematic review of 55 empirical studies (2020–2026) and 12 semi-structured interviews, the study identifies a key mismatch in problem attribution: official accounts emphasize irrigation, whereas farmers point to urban development pressures and infrastructure burdens. The findings also show that cultivation-decoupled subsidies enable landowners to capture compensation while shifting operational risks onto tenant farmers and other vulnerable groups. The study argues that a socially sustainable transition depends on incorporating local knowledge and redesigning subsidy eligibility and risk-sharing rules to strengthen procedural justice, representativeness, and accountability. Full article

The geological environment of southeastern Tibet is characterized by complex tectonics and high climatic sensitivity, and giant accumulation landslides pose significant threats to infrastructure and human safety. This study investigates the Pangcun giant accumulation landslide using SBAS-InSAR (2017–2024), UAV photogrammetry, field investigations, and wavelet coherence analysis to examine its deformation and driving mechanisms. The landslide exhibits continuous, slow deformation with clear spatial heterogeneity, divided into two zones, with the largest displacement occurring in the middle of Zone B. Field evidence is consistent with the InSAR results. Wavelet coherence analysis reveals a lagged response of displacement to precipitation at a timescale of about three months. The landslide’s evolution is controlled by unfavorable topography and fragmented materials, with precipitation as the primary trigger. Human activities (agricultural irrigation and slope-toe road excavation) and seismic disturbances also contribute to its progressive development. Full article

Waterlogging and secondary salinization are major drivers of land degradation in irrigated dryland regions, undermining soil productivity and long-term sustainability. Pakistan’s Indus Basin Irrigation System (IBIS), one of the world’s largest irrigation networks, supports national food security over approximately 16.7 million hectares (Mha). However, large-scale canal irrigation, combined with flat topography, monsoonal recharge, and inefficient water management, has disrupted groundwater balance, leading to persistent shallow water tables and widespread land degradation. Currently, nearly one-third of the irrigated area is affected by groundwater depths of less than 3 m. This review synthesizes six decades of waterlogging development and management in the IBIS, analyzing the evolution of drainage infrastructure, salinity control strategies, groundwater exploitation, and institutional reforms within a land sustainability perspective. Although large-scale interventions—including 61 Salinity Control and Reclamation Projects (SCARPs) and major outfall systems—initially reclaimed substantial areas, long-term performance has been constrained by governance fragmentation, inadequate operation and maintenance, and environmentally problematic effluent disposal. The Indus Basin experience underscores the need to move beyond infrastructure-centered solutions towards more integrated land–water governance and adaptive management to enhance land system resilience in irrigated regions facing growing climatic and resource pressures. Full article

Background: Global water scarcity, intensified by climate change, demands optimization of irrigation systems consuming 70% of freshwater resources. Despite significant investments in modernizing irrigation infrastructure from open channels to pressurized networks, performance often falls below expectations. Objective: This study develops an integrated diagnostic and simulation framework for evaluating and improving large-scale pressurized irrigation systems by adapting the Mapping System and Services for Pressurized Irrigation (MASSPRES) methodology. Methods: The framework integrates three components: (1) demand flow dynamics determination using stochastic modelling; (2) hydraulic performance simulation incorporating multiple flow regimes; and (3) performance analysis using relative pressure deficit and reliability indicators. The methodology combines deterministic soil water balance calculations with stochastic farmer behaviour modelling. Results: Application to the Sinistra Ofanto irrigation scheme revealed localized pressure deficits during peak demand periods. The rehabilitation strategy restored full hydraulic feasibility of the network, increasing the proportion of hydraulically satisfied operating configurations from 62% to 100% under peak demand conditions and ensuring adequate pressure at all 317 hydrants across the system. Conclusions: The methodology provides robust decision support for cost-effective rehabilitation, ensuring reliable water delivery while promoting water-energy efficiency. Full article

China’s farmland titling program aims to strengthen tenure security and promote agricultural productivity. This study examines whether land titling affects grain production capacity at the prefecture level using panel data from 30 cities over 2011–2021. We employ a staggered Difference-in-Differences (DID) design that exploits variation in the timing of titling milestones across cities. The results show no statistically significant average treatment effect on grain output, grain yield, or per capita grain production. However, the effect on grain yield exhibits substantial conditional heterogeneity: titling reduces yield in cities with weak agricultural infrastructure but increases yield in cities with high irrigation and mechanization intensity. Mechanism analysis indicates that land transfer intensity, irrigation, and mechanization correlate positively with grain yield, consistent with the hypothesis that titling requires complementary infrastructure to translate into productivity gains. These findings suggest that land tenure reforms alone do not guarantee food security improvements; coordinated investments in agricultural infrastructure remain essential. Full article

(1) Background: Robotics and advanced control architectures are increasingly central to the development of precision agriculture (PA), supporting automated, efficient, and data-driven farm management. This review offers a comprehensive analysis of scientific literature on robotic control systems applied to PA, focusing on technological progress, methodological approaches, and emerging research trends. (2) Methods: A systematic review was conducted according to PRISMA guidelines, combined with a bibliometric analysis using VOSviewer to examine term co-occurrences, thematic clusters, and topic evolution over time. Publications indexed in Scopus between 1976 and 2025 were analyzed. (3) Results: Results reveal a sharp growth in publications after 2010, with a strong acceleration from 2015 onward, reflecting advances in autonomous systems and the integration of artificial intelligence, sensor technologies, and distributed software frameworks. Three principal clusters emerged: algorithmic and control methods (e.g., neural networks, path tracking, simulation); sensing and infrastructure technologies (e.g., LiDAR, SLAM, IMU, ROS, deep learning-based perception); and agronomic applications, including crop monitoring, irrigation, yield estimation, and farm management. Citation trends indicate a shift from foundational control theory to AI-driven solutions. (4) Conclusions: Overall, control architectures are evolving toward modular, scalable, and interoperable systems enabling autonomous decision-making in complex agricultural environments. Full article

Urban green infrastructure plays a crucial role in enhancing environmental resilience in cities, particularly in arid regions characterized by water scarcity, soil salinity, and high climatic stress. However, arid coastal cities remain insufficiently studied with regard to spatially explicit assessments of the structure and dynamics of green infrastructure. This study evaluates the state and spatial organization of urban green infrastructure in Aktau, Kazakhstan, over the period 2015–2025, with the most recent satellite observations obtained in June 2025. Sentinel-2 satellite imagery was used to calculate seasonal Normalized Difference Vegetation Index (NDVI) and Soil-Adjusted Vegetation Index (SAVI) values, and zonal statistics were applied to assess intra-urban differentiation across functional zones. In addition, inventory-based indicators—Green Planting Density (GPD), Structural Composition of Greenery (SCG), and Protective Green Infrastructure (PGI)—were integrated to complement the remote sensing analysis. The results indicate a moderate overall increase in mean NDVI values (from 0.21 to 0.28), with the most significant growth observed in central and coastal areas (ΔNDVI = +0.12; ΔSAVI = +0.21), while industrial and newly developed zones exhibit only limited changes. Despite these localized improvements, the spatial configuration of green infrastructure remains fragmented, reflecting a persistent center–periphery asymmetry in urban greening. These results underline the importance of irrigation practices and spatially targeted greening strategies for improving vegetation conditions in arid urban environments. The proposed integrated approach combining satellite-derived vegetation indices and inventory-based indicators can serve as a useful tool for monitoring urban green infrastructure and supporting evidence-based planning in arid coastal cities. Full article

Siltation in irrigation canals adversely affects overflow capacity and accessibility, making its identification crucial for dredging, prevention, and maintenance, among other purposes. In this study, the siltation risks of Golmud irrigation canals were assessed from three perspectives: hydrodynamic impact, anthropogenic impact, and greening impact. The assessment factors included sediment deposition risk, bed erosion risk, proximity to public administration and services, proximity to residential areas, proximity to commercial services, and proximity to green spaces. The entropy weight method and TOPSIS method were employed to calculate the comprehensive siltation risk level, with model validation confirming a high overall accuracy of 94%. The results showed that among the six factors, proximity to public administration and services had the greatest influence on siltation, with a weight of 0.29. Additionally, the most vulnerable siltation locations were primarily in the city center, reflecting the susceptibility of urban areas to anthropogenic activities. This study develops a rapid and objective risk-scanning tool that couples hydrodynamics with land-use factors, providing a standardized technical pathway for the checking of large-scale urban infrastructure. Full article

Climate change is increasingly affecting groundwater resources in the Carpathian Basin, while rising temperatures are likely to increase irrigation demand and pressure on aquifers. We assessed climate- and pumping-driven impacts on the Nyírség recharge–discharge system (north-eastern Hungary) by combining shallow groundwater monitoring (1970–2022) with hydroclimate indicators from CHIRPS precipitation and ERA5-Land air temperature and snow depth (1981–2024). Using these datasets, we developed and calibrated a MODFLOW groundwater-flow model for representative wet (2010) and dry (2022) conditions, incorporating permitted abstraction and scenario-based estimates of unregistered pumping. We then ran scenario simulations to evaluate mid-century (2050) conditions and managed aquifer recharge (MAR) options. Precipitation exhibits strong interannual variability, but the region shows marked warming and a pronounced decline in snow storage, implying reduced cold-season buffering and higher evaporative demand. Simulations reproduce the observed post-2010 decline in shallow groundwater, with the largest decreases in higher-elevation recharge areas, whereas increased pumping mainly intensifies localized drawdown near major well fields. Scenario results indicate that climate-driven reductions in recharge dominate basin-scale declines by 2050, while MAR provides primarily local benefits; direct subsurface injection performs best among the tested options. These findings support practical groundwater management by prioritizing measurable and enforceable abstraction (including unregistered withdrawals), demand-side irrigation efficiency and adaptive caps in recharge areas, and targeted subsurface MAR where source water and infrastructure are available. Full article

Collective action serves as a critical mechanism for addressing deficiencies in small-scale irrigation infrastructure and fostering a virtuous cycle of their operation and maintenance. Village leaders, as central figures in organizing and mobilizing farmers toward collective action, play a pivotal role in shaping participatory irrigation management (PIM) outcomes through their public leadership. Drawing on micro-survey data from 723 farm households across Ningxia, Shanxi, and Shandong provinces in China’s Yellow River basin, this study employed a multi-group structural equation model (SEM) to analyze the impact of public leadership on collective action in PIM. The findings indicate that: (1) public leadership is directly associated with collective action, with a direct effect of 0.530; (2) public leadership indirectly enhances collective action through mediating variables—cadre–mass relationship, institutional trust, and grassroots democracy—with an indirect effect of 0.045; and (3) the personal characteristics of village leaders moderate the influence of public leadership on collective action. Specifically, public leadership exerts a strong effect when leaders belong to the village elite, possess a least a high school education, or are not members of the village’s major clan. These insights suggest that policymakers should explicitly consider public leadership in fostering collective action within the PIM framework. Full article

Modern agriculture has to alleviate extremes in water demand and/or water waste. In this regard, this work showcases how soil moisture instruments can be combined with low-end microcontrollers, energy-efficient communication protocols, single-board computers, flow and pressure sensors, and purpose-built actuators to form a synergistic platform able to generate and study realistic irrigation scenarios. These scenarios, potentially emulating anomalies such as clogged emitters or pipe leaks with a satisfactory time granularity of a few minutes, provide valuable data that pave the way for the creation of intelligent models intercepting water misuse events and/or irrigation failures. The proposed system utilizes widely available, well-documented, low-cost components to form a functioning whole which is optimized for outdoor, low-power, low-maintenance and long-term operation and is accessible remotely via typical end-user devices. Two drip irrigation points were set up, each having a TEROS 12 and a TEROS 10 instrument placed at different depths, while a prototype water flow/pressure control and report system was developed. All modules sent data in real time, via LoRa, to a central node implemented using a Raspberry Pi for further processing and to make them widely available via common network infrastructures, also provisioning for remote scenario invocation. The system does not claim to achieve specific irrigation water savings, but it contributes to maintaining/increasing the benefits of modern irrigation practices (such as drip irrigation). This goal is served by emulating a wide variety of irrigation events and by gathering and studying the corresponding data. These multimodal data are collected at a frequency of a few minutes, reflecting key irrigation-specific parameters with an accuracy better than or equal to 3%. The exact steps for specific hardware and software component interoperation are clearly explained, allowing other teams of researchers and/or university educators worldwide to be inspired and benefit from platform replication. Full article