Search Results (49)

Irrigation scheduling plays a pivotal role in bridging water resource allocation and farmland production management. For decades, scheduling in irrigation districts has predominantly relied on operators’ experience and relatively rigid water delivery plans, making it difficult to simultaneously meet the demands for timely responsiveness and precise water allocation under the combined influence of meteorological variability, changing crop water requirements, and the dynamic adjustments of water conveyance and distribution systems. The advancement of digital technologies, such as the Internet of Things, machine learning, deep reinforcement learning, and digital twins, has opened new technical pathways for optimizing irrigation scheduling. Focusing on the development of smart irrigation and scheduling optimization in irrigation districts, this paper systematically reviews the relevant literature published from January 2000 to June 2026 and delineates its evolution into three stages. Early-stage research was grounded in physical models, empirical rules, and hydraulic simulations, establishing fundamental methods for evapotranspiration estimation, crop water requirement calculation, and canal water delivery simulation. The middle stage, marked by the introduction of the Internet of Things and machine learning, enabled real-time monitoring of hydrological conditions, soil moisture, and meteorological data and promoted a data-driven transformation of water demand forecasting methods. The recent stage is characterized by the integration of deep reinforcement learning, digital twins, and knowledge graphs, which extends irrigation district scheduling from isolated single-point optimization toward multi-agent coordination and closed-loop management. Existing evidence confirms that digital technologies have yielded water-saving and yield-increasing benefits at the field scale and improved water distribution efficiency in several demonstration irrigation districts; however, their wider deployment at the district scale still faces bottlenecks such as inadequate sensing of physical execution processes, underdeveloped multi-objective trade-off mechanisms, and limited model transferability and long-term operational sustainability. To address these challenges, this paper proposes future research directions oriented toward real-time perception of water delivery and distribution status, multi-objective robust optimization, explainable artificial intelligence, and human–machine collaborative decision-making, thereby providing a reference for the theoretical development, engineering deployment, and operational management of smart irrigation district scheduling systems. Full article

The Hajdúhát loess plateau in eastern Hungary has no perennial watercourse and overlies a drought-sensitive shallow aquifer, so irrigation supply security and allocation both constrain production. We coupled a dry-2018/wet-2020 MIKE Hydro River model of the East Main Canal (EMC) with a seventeen-year (2009–2025) MIKE SHE groundwater model, and a decision-support layer that couples conveyed-water allocation across sectors with a ranking of management responses. Calibration attains Moriasi Very Good bias-and-balance skill (mean |PBIAS| 1.59%/0.86%), with a head MAE of 1.431 m over 132 wells, and continuous validation reproduces measured discharge to within −7.7% bias over 2022–2025. Growing-season evapotranspiration (448 mm) exceeds precipitation (309 mm), leaving a 314 mm unsaturated-zone deficit; the dry-year canal terminus shows 34 of 92 no-flow days and a sustainability index of 0.09, against 0.34 when wet. A reconciled reach × sector balance and an isolating hydraulic test show the deficit is an allocation problem, not a conveyance limit. A Leopold/analytic-hierarchy-process ranking favors priority-ordered allocation over new capacity, and, in a two-objective time–quantity allocation, re-timing 8.57 × 10⁶ m³ of fish-pond filling into winter would remove the spring deficit without new infrastructure. Dry-year supply is thus a problem of allocation and timing as much as of capacity. Full article

Hydraulic structures disturb natural flow patterns, reducing water conveyance efficiency and increasing hydraulic energy losses, thereby affecting the sustainable management of water structures. Entrance-zone geometry, particularly upstream wing-wall configuration and canal inside slope, plays a critical role in controlling flow behavior, energy dissipation, upstream afflux, and hydraulic performance. However, the coupled effects of these geometric parameters have not been systematically investigated. Therefore, this study employed a validated HEC-RAS model to evaluate the combined influence of canal inside slope and upstream wing-wall configuration on the hydraulic performance of irrigation water structures and to support sustainable hydraulic design. Four wing-wall configurations (box, broken, curved, and splayed) and three canal inside slopes (1:1, 3:2, and 2:1) were analyzed under a fixed contraction ratio of 0.6 and upstream Froude numbers ranging from 0.12 to 0.18 under steady subcritical flow conditions. The model was validated against measurements from a 1:10 laboratory flume, demonstrating excellent agreement, with an average variation of 5.75% and coefficients of determination (R²) ranging from 0.97 to 0.99. Gradual entrance transitions significantly improved hydraulic performance by reducing flow disturbances and enhancing flow uniformity. For a canal inside slope of 1:1, the curved wing-wall configuration reduced relative heading-up and energy loss by 18.02% and 46.83%, respectively, whereas the splayed configuration achieved the best overall performance, with corresponding reductions of 27.63% and 73.11% compared with the conventional box configuration. Furthermore, dimensionless predictive equations were developed for the principal hydraulic performance indicators, achieving R² values of 0.96–0.99 and RMSE values of 0.001–0.01. The proposed framework improves water conveyance efficiency, minimizes hydraulic losses, and provides a validated, cost-effective numerical tool for evaluating alternative design scenarios, reducing reliance on extensive physical experimentation while supporting sustainable irrigation structures and long-term water resources management. Full article

This study assessed the current status of irrigation systems and water management practices in Rwanda’s irrigated agricultural zones, focusing on the Nasho Government-Funded Irrigation (GFI) scheme in Kirehe District and the Kagitumba Irrigation Scheme in Nyagatare District. A mixed descriptive approach was used, combining field observations with structured questionnaires administered via KoboToolbox to 224 respondents in Nasho and 188 in Kagitumba. Field observations were used to evaluate the physical condition and functionality of irrigation infrastructure, while questionnaires captured stakeholder perceptions, water management practices, institutional arrangements, and operational challenges. Results show that both irrigation schemes are operational but function below optimal efficiency due to multiple constraints. In Nasho, irrigation performance is primarily affected by sedimentation in canals and reservoirs, pump inefficiencies, and inadequate maintenance practices, resulting in unreliable water delivery. In Kagitumba, despite the use of modern center pivot systems, performance is constrained by pipeline corrosion, pressure losses, sediment-laden water, and uneven water distribution. Across both schemes, more than 80% of respondents reported frequent system failures, while over 95% indicated the absence of formal irrigation scheduling practices. Water management remains largely reactive, with limited preventive maintenance and weak technical capacity among users and institutions. The study concludes that improving irrigation efficiency in Rwanda requires integrated interventions that combine infrastructure rehabilitation, strengthened maintenance systems, improved water governance, and farmer capacity development to enhance sustainable water use and agricultural productivity. Full article

Irrigation water quality is a crucial factor for agricultural sustainability and food safety, particularly amid climate change, water scarcity, and inadequate rural infrastructure. This study identifies the behavioral and structural factors associated with the adoption of eight water contamination prevention practices among smallholder farmers in central Chile, including irrigation canal cleaning, use of water filters, rainwater collection systems, and irrigation methods that avoid contact between edible crop parts and water. Drawing on the Theory of Planned Behavior (TPB), behavioral constructs were integrated with structural features of production systems to capture both cognitive and contextual drivers of adoption. A survey of 101 farmers in the O’Higgins Region was conducted, and a binary logistic regression model was applied (n = 96; AUC = 0.821). Results indicate that adoption was significantly associated with favorable attitudes toward preventive practices (OR = 1.16; p = 0.014) and supportive subjective norms (OR = 1.21; p = 0.037), while perceived behavioral control showed no significant effect. Among structural factors, the use of modern irrigation technologies was the strongest predictor (OR = 16.55; p < 0.001), followed by diversified production systems (OR = 14.55; p = 0.003) and the cultivation of fruit trees or vines (OR = 9.00; p = 0.002). These findings indicate that attitudinal and normative factors are more consistently associated with adoption when supported by enabling infrastructure and production conditions. They underscore the need for integrated policy approaches that align motivational and material components to promote sustainable water management practices in resource-constrained agricultural contexts. Full article

Odontogenic cutaneous sinus tracts represent an uncommon clinical manifestation of chronic dental infection and are frequently misdiagnosed due to the absence of dental symptoms and their resemblance to dermatologic lesions. This case report describes the nonsurgical endodontic management of a cutaneous sinus tract of dental origin in a 13-year-old patient. The patient presented with a persistent extraoral lesion in the mandibular region, initially evaluated by non-dental specialists. Clinical and radiographic examination revealed a necrotic mandibular first molar associated with a periapical radiolucency and intraoral sinus tract. Nonsurgical root canal treatment was performed using chemomechanical debridement with sodium hypochlorite irrigation and calcium hydroxide as an intracanal medicament. Complete obturation was achieved following resolution of intracanal exudation. No surgical intervention of the cutaneous lesion was undertaken. Progressive healing of the periapical lesion and spontaneous resolution of the extraoral sinus tract were observed over a 6-month follow-up period. This case is noteworthy because it combines a prolonged diagnostic delay, an atypical extraoral manifestation in a child, and successful resolution by nonsurgical endodontic therapy alone without surgical excision of the cutaneous lesion. The 6-month follow-up confirms sustained clinical and radiographic healing, underscoring the importance of early recognition and conservative management in pediatric patients. Early identification and elimination of the dental source can prevent unnecessary surgical procedures and minimize the risk of permanent scarring. Full article

Punjab, Pakistan, is experiencing severe groundwater depletion due to excessive and unplanned extraction, declining surface water availability, rapid population growth, and increasing climate variability. Groundwater has become the primary source of irrigation and drinking water across the province, contributing about 50%, 90% and 95% of the requirements of agricultural, domestic, and industrial water demands. Natural recharge rates have been reduced due to construction, pavements, and the lining of irrigation channels. This study presents the first pilot-scale Managed Aquifer Recharge (MAR) initiative implemented by the Irrigation Research Institute (IRI) of the Punjab Irrigation department. Floodwater has been diverted into the bed of the abandoned Old Mailsi Canal (OMC), which off-takes from Islam Headworks. About 144 recharge wells have been constructed in the bed of the OMC. During the 2025 flood season, approximately 12,000 acre-feet of floodwater was diverted and stored through engineered ponding, canal-bed rehabilitation, and recharge wells. A comprehensive monitoring program was established, including piezometers, automated data loggers, groundwater quality sampling, pumping tests, geophysical surveys, and sediment analyses. The results indicate a maximum groundwater level rise of up to 11 ft., with average increases ranging from 2.6 to 5.2 ft across the recharge ponds. Groundwater quality also showed an improvement following MAR implementation; electrical conductivity decreased from 900 to 650 μS/cm in Pond-I and from 850 to 750 μS/cm in Pond-III. These findings demonstrate that repurposing abandoned canal infrastructure for floodwater-based MAR provides a technically feasible, environmentally sustainable, and climate-resilient strategy for enhancing groundwater availability for sustainable management in Punjab and other water-stressed regions. Full article

Irrigation water use efficiency (IWUE) is a core indicator for assessing agricultural water use efficiency. However, existing studies predominantly focus on linear relationships between IWUE and individual correlates, with insufficient attention to the nonlinear interactions among multiple factors and the staged pathways of IWUE improvement. Taking 153 large- and medium-sized irrigation districts in Anhui Province as a case study, this research identifies seven key influencing factors—including canal lining rate (CLR), proportion of water-saving irrigation area (WSIR), and water price (WP)—and employs a random forest model coupled with SHAP (SHapley Additive exPlanations) interpretability analysis to uncover the driving mechanisms and enhancement pathways of IWUE. The results reveal that CLR, WSIR, and WP are the top three correlates, collectively contributing 67.80% to IWUE variation, with CLR being the most influential (28.75%). Their effects exhibit strong nonlinearity and threshold behavior: the marginal benefit of CLR diminishes significantly beyond approximately 75%; the optimal incentive range for WP lies between 0.09 and 0.14 CNY/m³; and precipitation exerts a persistent negative constraint. Moreover, IWUE improvement follows a sequential hierarchy: CLR serves as the foundational prerequisite; once CLR reaches a certain threshold, advancing WSIR becomes essential; and further gains require synergistic interaction between WSIR and WP after both attain sufficient levels. This study elucidates the nonlinear response mechanisms and stage-dependent driving patterns of IWUE, offering scientific insights and quantitative support for targeted, precision-oriented upgrades of irrigation infrastructure in Anhui Province and analogous humid/semi-humid regions, thereby contributing to sustainable agricultural water management. Full article

Water balance calculations at the watershed scale are fundamental to water resource planning and the sustainable management of limited water supplies. These calculations rely on stream and canal gaging networks operated by local, state and federal entities, whose availability has varied over time due to cost, staffing constraints, and limitations on suitable gaging locations. The Green River Basin (GRB) above Fontenelle Dam in Wyoming illustrates this trend, where the number of operational stream gaging sites has varied over time and the majority of locations have less than 15 years of streamflow records. Recent advancements in the ability to perform streamflow reconstruction and estimate agricultural water use offer a new avenue for estimating the water balance for watersheds with discontinuous gage observations. But the use of these datasets and approaches has not been tested. Therefore, this paper proposes and tests a novel framework that combines discontinuous streamflow observations with new datasets (OpenET, ET-Demands, and GEOGLOWS) to calculate monthly water balances in the GRB from water year 1991 to 2023. Focusing on two main test basins, the Green River and the New Fork River, the integration of modern datasets enables the successful calculation of the water balance in the GRB with good agreement with downstream gaging records, achieving a Nash–Sutcliffe efficiency (NSE) of 0.88 for the New Fork River and 0.80 for the Green River. By improving the ability to quantify water balance components in data-limited basins, this framework supports more transparent water accounting and informed decision-making for sustainable water management, including irrigation planning, drought response, and long-term resource allocation in semi-arid river systems. Full article

Water structures play a vital role in regulating irrigation water within open-channel networks by controlling discharge, water levels, flow direction, and velocity. Despite their importance, these structures act as hydraulic obstructions that induce flow disturbances, which may reduce hydraulic efficiency and threaten structural integrity. One of the most critical consequences is localized erosion downstream, posing serious risks to structural safety and long-term performance. From a sustainability perspective, maintaining structural stability and hydraulic efficiency is essential to ensure reliable water delivery, minimize maintenance costs, and extend the service life of irrigation structures. Therefore, mitigating such adverse hydraulic effects is a key component of sustainable water resources management. This study aims to investigate the mechanisms responsible for this phenomenon and propose engineering solutions to reduce its impacts. The geometry of upstream wing walls significantly influences flow behavior both through and downstream of the structure. Additionally, irrigation canals are constructed with varying side slopes depending on soil conditions, which further affect flow characteristics. However, the combined effect of different upstream wing wall configurations and canal inside slopes has not been sufficiently addressed. Accordingly, this research evaluates their integrated impact to support the development of more efficient, resilient, and sustainable irrigation structures. A total of 435 laboratory experiments were conducted using a physical model under varying discharge conditions. Common canal inside slopes were tested with four widely used wing wall types. Scour hole geometry, including depth, length, and shape, was measured and analyzed. Results indicate that the splayed wing wall configuration outperforms the box type, reducing maximum scour depth and length by approximately 22.74% and 23.61%, respectively, when combined with a 1:1 canal inside slope. Additionally, new dimensionless empirical equations were developed to predict downstream scour behavior, providing practical tools for selecting optimal wing wall configurations under different canal conditions. 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

Rational allocation and coordinated operation of water resources in arid inland river basins are crucial for sustaining irrigated agriculture, maintaining ecological baseflow and ensuring reservoir safety. To address this need, this study develops and evaluates joint-operation schemes for the Jingou River-Hongshan Reservoir irrigation system in Xinjiang, northwestern China, to improve coordination among irrigation water supply, ecological baseflow maintenance and reservoir safety. A monthly reservoir-canal-irrigation operation model is formulated with irrigation demands, ecological flow constraints and key engineering limits. Using this model, operating schemes are generated to explore trade-offs among three objectives: shortages, reliability and non-beneficial reservoir releases. The non-dominated schemes obtained from multi-objective optimization are then ranked using an entropy-weighted TOPSIS framework, from which representative solutions are selected for further interpretation. The results indicate that the top-ranked schemes deliver comparable and relatively well-balanced performance across the objectives. Under the preferred compromise scheme, annual irrigation shortages amount to about 39% of total demand, the mean satisfaction level of irrigation and ecological requirements reaches roughly 57%, and the combined index of spill losses and end-of-year storage deviation remains low. Schemes that push shortage reduction or reliability enhancement to extremes tend to increase spill losses, compromise storage security or both, thereby degrading overall performance. The proposed optimization-ranking framework offers a transparent basis for identifying robust operating strategies that reflect local management priorities and is transferable to other reservoir-supported irrigation systems in arid regions. Full article

Over the past two decades, climate change and climatic variability have received significant attention from the scientific community. The present study investigates the impact of future climate change on irrigation water requirements in the coastal districts of Odisha, Eastern India, specifically within the Phulnakhara distributary’s command area of the main Puri canal system. Field investigations were conducted during the kharif and rabi seasons of 2019–2020 and 2020–2021. The study offers a new perspective involving a future climate data-driven model with water requirements of RCP 4.5 for this canal command area, and after integrating this with the optimal cropping area, the optimal future irrigation water needs for the kharif and rabi seasons were determined. The study focused on assessing future irrigation water demands under changing climatic conditions, with an emphasis on the conjunctive use of surface and groundwater resources. Projections indicate that peak irrigation demand will occur in the kharif season of 2042–2043 and the rabi season of 2044–2045. Furthermore, a significant decline in groundwater levels is anticipated, ranging from 1.23 to 1.42 m below ground level (BGL) during the kharif season and from 1.46 to 1.64 m BGL during the rabi season, over the next 30 years (2021–2022 to 2050–2051). The most pronounced groundwater table decline is projected for the years 2042–2043 (kharif) and 2044–2045 (rabi), highlighting the need for sustainable water resource management strategies in the region. Based on this study, integrating the optimal crop area with future irrigation water needs will result in groundwater table fluctuations under the permissible limit. Full article

Groundwater is essential for irrigated agriculture, yet its use remains unsustainable in many regions worldwide. In countries like Pakistan, the situation is particularly pressing. The irrigated agriculture of Pakistan heavily relies on groundwater resources owing to limited canal-water availability. The groundwater quality in the region ranges from good to poor, with the lower-quality water adversely affecting soil structure and plant health, leading to reduced agricultural productivity. The delineation of quality zones with respect to irrigation parameters is thus crucial for optimizing its sustainable use and management. Therefore, this research study was carried out in the Lower Chenab Canal (LCC) irrigation system to assess the spatial distribution of groundwater quality. The geostatistical analysis was conducted using Gamma Design Software (GS+) and the Kriging interpolation method was applied within a Geographic Information System (GIS) framework to generate groundwater-quality maps. Semivariogram models were evaluated for major irrigation parameters such as electrical conductivity (EC), residual sodium carbonate (RSC), and sodium adsorption ratio (SAR) to identify the best fit for various Ordinary Kriging models. The spherical semivariogram model was the best fit for EC, while the exponential model best suited SAR and RSC. Overlay analysis was performed to produce combined water-quality maps. During the pre-monsoon season, 17.83% of the LCC area demonstrated good irrigation quality, while 42.84% showed marginal quality, and 39.33% was deemed unsuitable for irrigation. In the post-monsoon season, 17.30% of the area had good irrigation quality, 44.53% exhibited marginal quality, and 38.17% was unsuitable for irrigation. The study revealed that Electrical Conductivity (EC) was the primary factor affecting water quality, contributing to 71% of marginal and unsuitable conditions. In comparison, the Sodium Adsorption Ratio (SAR) accounted for 38% and Residual Sodium Carbonate (RSC) contributed 45%. Therefore, it is recommended that groundwater in unsuitable zones be subjected to artificial recharge methods and salt-tolerated crops to enhance its suitability for agricultural applications. Full article

Sediment accumulation in irrigation channels poses a significant challenge to water resource management, impacting hydraulic efficiency and agricultural sustainability. This study introduces an innovative multidisciplinary framework that integrates advanced image analysis (FIJI/ImageJ 1.54p), statistical validation (RStudio), and vector field modeling with a novel Sinusoidal Morphodynamic Bedload Transport Equation (SMBTE) to predict sediment deposition patterns with high precision. Conducted along the Malacatos River in La Tebaida Linear Park, Loja, Ecuador, the research captured a natural sediment transport event under controlled flow conditions, transitioning from pressurized pipe flow to free-surface flow. Observed sediment deposition reduced the hydraulic cross-section by approximately 5 cm, notably altering flow dynamics and water distribution. The final SMBTE model (Model 8) demonstrated exceptional predictive accuracy, achieving RMSE: 0.0108, R²: 0.8689, NSE: 0.8689, MAE: 0.0093, and a correlation coefficient exceeding 0.93. Complementary analyses, including heatmaps, histograms, and vector fields, revealed spatial heterogeneity, local gradients, and oscillatory trends in sediment distribution. These tools identified high-concentration sediment zones and quantified variability, providing actionable insights for optimizing canal design, maintenance schedules, and sediment control strategies. By leveraging open-source software and real-world validation, this methodology offers a scalable, replicable framework applicable to diverse water conveyance systems. The study advances understanding of sediment dynamics under subcritical (Fr ≈ 0.07) and turbulent flow conditions (Re ≈ 41,000), contributing to improved irrigation efficiency, system resilience, and sustainable water management. This research establishes a robust foundation for future advancements in sediment transport modeling and hydrological engineering, addressing critical challenges in agricultural water systems. Full article