Search Results (336)

This study projects future Residential Water Use (RWU) under climate change scenarios using a Bayesian Neural Network (BNN) model that quantifies the relationship between observed temperatures and RWU. Eighteen Global Climate Models (GCMs) under the Shared Socioeconomic Pathway 5–8.5 (SSP5–8.5) scenario were used to assess the uncertainties across these models. The findings indicate that RWU in Republic of Korea (ROK) is closely linked to temperature changes, with significant increases projected in the distant future (F3), especially during summer. Under the SSP5–8.5 scenario, RWU is expected to increase by up to 10.3% by the late 21st century (2081–2100) compared to the historical baseline. The model achieved a root mean square error (RMSE) of 11,400 m³/month, demonstrating reliable predictive performance. Unlike conventional deep learning models, the BNN provides probabilistic forecasts with uncertainty bounds, enhancing its suitability for climate-sensitive resource planning. This study also projects inflows to the Paldang Dam, revealing an overall increase in future water availability. However, winter water security may decline due to decreased inflow and minimal changes in RWU. This study suggests enhancing summer precipitation storage while considering downstream flood risks. Demand management strategies are recommended for addressing future winter water security challenges. This research highlights the importance of projecting RWU under climate change scenarios and emphasizes the need for strategic water resource management in ROK. Full article

Rainfall–runoff processes and flood propagation were quantified to clarify floodwater dynamics in the upper Tenryu River basin. The basin is characterized by contrasting runoff behaviors between its left- and right-bank subbasins and large upstream river storage created by gorge topography. Radar rainfall and dam inflow data were analyzed to determine the runoff characteristics, on which the rainfall–runoff simulation was based. A higher storage capacity was observed in the left-bank subbasins, while an exceptionally large specific discharge was observed in one of the right-bank subbasins after several hours of intense rainfall. Based on these findings, the basin-scale storage was quantitatively evaluated. Water level peaks in the main channel appeared earlier at downstream locations, indicating that tributary inflows strongly affect the flood peak timing. A two-dimensional unsteady model successfully reproduced this behavior and captured the delay in the flood wave speed due to the complex morphology of the Tenryu River. The average α value, representing the ratio of flood wave speed to flow velocity, was 1.38 over the 70 km study reach. This analysis enabled quantification of river channel storage and clarified its relative relationship to basin storage, showing that river channel storage is approximately 12% of basin storage. Full article

Wetlands, as critical ecological systems, face increasing threats from anthropogenic pressures and climate change. This study investigates dynamic water allocation strategies for the restoration of Lake Marmara, a nationally important wetland within the Gediz River Basin of Türkiye, which has experienced complete desiccation in recent years. Within the scope of the PRIMA-funded “Mara-Mediterra” project, an integrated modeling approach was employed to evaluate multiple restoration scenarios using the WEAP (Water Evaluation and Planning) platform. Scenarios varied based on the initial storage capacity of Gördes Dam, irrigation demands, environmental flow priorities, and a potential water diversion investment from the Tabaklı reach. Results indicate that under current conditions, Lake Marmara’s ecological water needs can be sustained without the Tabaklı investment. However, under 2050 climate projections, scenarios lacking the Tabaklı investment or deprioritizing ecological needs consistently failed to meet the lake’s minimum water thresholds. Conversely, scenarios combining moderate dam storage levels, environmental prioritization, and Tabaklı inflow succeeded in restoring lake volumes by over 90%. These findings highlight the need for adaptive water planning that aligns with projected hydro-climatic shifts to ensure long-term wetland sustainability. Full article

Dam breaks can lead to important economic and human losses. Design floods, which are useful to assess possible dam breaks, are usually estimated through statistical analysis of rainfall and streamflow observed data. However, such available samples are commonly limited and, consequently, high uncertainties are associated with the design flood estimates. In addition, climate change is expected to increase the frequency and magnitude of extreme rainfall and flood events in the future. Therefore, a methodology based on a stochastic rainfall generator is proposed to assess hydrological dam safety by considering climate change. We selected the Eugui Dam on the Arga river in the north of Spain as a case study that has a spillway operated by gates with a maximum capacity of 270 m³/s. The stochastic rainfall generator STORAGE is used to simulate long time series of 15-min precipitation in both current and future climate conditions. Precipitation projections of 12 climate modeling chains, related to the usual three 30-year periods (2011–2024; 2041–2070 and 2071–2100) and two emission scenarios of AR5 (RCP 4.5 and 8.5), are used to consider climate change in the STORAGE model. The simulated precipitation time series are transformed into runoff time series by using the continuous COSMO4SUB hydrological model, supplying continuous 15-min runoff time series as output. Annual maximum flood hydrographs are selected and considered as inflows to the Eugui Reservoir. The Volume Evaluation Method is applied to simulate the operation of the Eugui Dam spillway gates, obtaining maximum water levels in the reservoir and outflow hydrographs. The results show that the peak outflows at the Eugui Dam will be lower in the future. Therefore, maximum reservoir water levels will not increase in the future. The methodology proposed could allow practitioners and dam managers to check the hydrological dam safety requirements, accounting for climate change. Full article

Reservoir operations play a pivotal role in shaping the flow regime of the Chao Phraya River Basin (CPRB), where two major reservoirs exert substantial hydrological influence. Despite ongoing efforts to manage water resources effectively, current operational strategies often lack the adaptability required to address the compounded uncertainties of climate change and increasing water demands. This research addresses this critical gap by developing an optimization model for reservoir operation that explicitly incorporates climate variability. An Adaptive Neuro-Fuzzy Inference System (ANFIS) was employed using four fundamental inputs: reservoir inflow, storage, rainfall, and water demands. Daily resolution data from 2000 to 2012 were used, with 2005–2012 selected for training due to the inclusion of multiple extreme hydrological events, including the 2011 flood, which enriched the model’s learning capability. The period 2000–2004 was reserved for testing to independently assess model generalizability. Eight types of membership functions (MFs) were tested to determine the most suitable configuration, with the trapezoidal MF selected for its favorable performance. The optimized models achieved Nash-Sutcliffe efficiency (NSE) values of 0.43 and 0.47, R² values of 0.59 and 0.50, and RMSE values of 77.64 and 89.32 for Bhumibol and Sirikit Dams, respectively. The model enables the evaluation of both dam operations and climate change impacts on downstream discharges. Key findings highlight the importance of adaptive reservoir management by identifying optimal water release timings and corresponding daily release-storage ratios. The proposed approach contributes a novel, data-driven framework that enhances decision-making for integrated water resources management under changing climatic conditions. Full article

Climate change and extreme events such as droughts, heavy rainfall and flooding can influence the water column stratification in reservoir dams, decrease storage capacity, increase sediment and pollutant loads and, as a result, affect water quality. The seasonal variation in the water column stratification of reservoirs is an important parameter for the study of dam life cycle as well as water management and use. In the present study a detailed bathymetric survey was carried out, and a digital elevation model (DEM) of the reservoir was constructed. Seasonal physicochemical monitoring data such as temperature, dissolved oxygen, pH and conductivity are presented. The seasonal thermal stratification was recorded, resulting in an isolated hypolimnion where anoxic layers formed below 17 m in summer and autumn. Manganese and iron concentrations exhibited values higher than 150 mg/L in the anoxic hypolimnion during summer and autumn, indicating solubilization from the sediment. The observed seasonal and depth-dependent variations in physicochemical parameters underline the reservoir’s susceptibility to eutrophication and metal mobilization, particularly during stratified periods. These findings are critical for designing management strategies to mitigate potential water quality issues. Full article

This article analyses the necessity of employing an interdisciplinary approach in the geotechnical practice of designing, constructing, and operating industrial hydraulic structures—tailings dams of processing plants. Tailings dam failures often lead to irreversible consequences for the ecological state of the environment. The interdisciplinary approach involves treating the foundation soils of structures and anthropogenic tailings deposits as a multicomponent system. In this system, soil acts as a medium hosting groundwater of varying compositions and contamination levels, containing biotic components and their metabolic products, including the gaseous phase. It has been demonstrated that the justified application of this approach increases the operational safety of existing structures and the long-term stability of starter and tailings dikes built on weak clay foundation soils. Particular emphasis is placed on the biotic component and the dual role of subsurface microorganisms. These bacteria negatively impact the strength and load-bearing capacity of water- and water–gas-saturated clay soils in the foundation of the structures under consideration. The diverse biocenosis in groundwater simultaneously facilitates self-purification from petroleum hydrocarbons to undetectable levels. This aspect holds fundamental importance, as groundwater discharges into river systems. Full article

There is no doubt that additive manufacturing (AM) with mortars presents an opportunity within the framework of a circular economy that should not be overlooked. The concepts of reduce, reuse, and recycle are fully aligned with this technology. One of the less explored possibilities is the utilisation of mining tailings as aggregates in printing mortars. This idea not only incorporates the concept of recycling but also contributes to a reduction in the production of potentially hazardous waste that would otherwise require storage in dams, thereby decreasing long-term environmental risks and improving the management of mineral resources. We employed a mortar composed of 12.5% material derived from mining tailings to highlight aspects of AM that are typically not subject to analysis, such as the necessity of considering contact interfaces between layers in structural design, the stackability of layers during the construction process, and the behaviour under fire and seismic events, which must be taken into account during the operational phase. Without aiming for exhaustiveness, we conducted a series of tests and computational modelling to show the significance of these factors, with the intention of drawing the attention of different stakeholders—including construction companies, regulatory authorities, standardisation agencies, insurers, and end-users. Full article

Plasticized polyvinyl chloride (PVC-P) geomembranes (GMBs) are applied as anti-seepage materials in membrane-faced rockfill dams and pumped storage power stations. Assessing their lifetime to ensure durability during operation is crucial. This study conducted accelerated aging tests on three PVC-P GMBs immersed in water, along with axial tensile tests to investigate the degradation of mechanical properties. The degradation model was constructed using the Arrhenius equation, and the time to nominal failure (TNF) was predicted based on this model and failure criterion. The prediction model’s accuracy was verified using test data collected over 180 days at 20 °C. The results demonstrate that the TNF of PVC-P GMBs is influenced by water temperature, plasticizer content, and thickness of GMBs. Elevated temperatures accelerate the loss rate of plasticizers. Specifically, at 20 °C in a water environment, the estimated TNFs of Materials A and B with identical thicknesses were 49.05 and 153.76 years, respectively. This suggests that increasing the initial plasticizer content and enhancing its structural stability can significantly extend the TNF. Furthermore, Material C, which has a composition similar to Material B but with increased thickness, exhibited a predicted TNF of 181.30 years, indicating that greater thickness can effectively reduce the migration rate of plasticizers. The findings provide a theoretical basis for evaluating the TNF of PVC-P GMBs in reservoir bottom and below dead water level applications during operation. Full article

Continuous monitoring is key to the safety of such critical infrastructure as Tailings storage facilities. Due to the high risk of liquification of the dams, it is crucial to move the water as far as possible from the dam crest. In order to control the distance from the water to the dam, regular manual inspections need to be carried out. In this article, we propose a method for automatic detection of the water-beach line based on photographs from an unmanned aerial vehicle (UAV). An algorithm based on MobileNet v2 convolutional neural network architecture was developed for the classification of images collected by the UAV. Based on the results of this classification, the border between the water and the beach is defined. Several approaches to the model training were tested. Accuracy for the validation set reaches up to 97% for particular image fragments. Full article

This paper investigated sectoral water use and trends in the Mzimvubu to Tsitsikamma Water Management Area 7 (WMA7). The investigation considered the Water Authorisation and Registration Management System (WARMS) database and field surveys as a source of water use information. The study was able to successfully make use of time series statistical analysis to show water use trends for identified priority sectors over a 5-year period by sourcing historical water use data of the study area. Further, the groundwater stress index and streamflow impact were applied to assess water use impacts on the surface and groundwater. The WARMS database and field survey results identified major sectoral water users such as agriculture (irrigation), municipal water services, dam storage, afforestation, power generation, recreation, mining, and industries. Study findings revealed that the agricultural sector is a major water user, with an estimated 60% of the total water requirement over a 5-year period (2018 to 2022). The application of the groundwater stress index revealed that the majority of the Quaternary catchments have surplus groundwater available. The application of streamflow impact revealed that the majority of catchments have low flow or no flow. The rise of water use clearly indicates a lack of water use compliance and enforcement. An increase in total water use could put water resources under stress, including an impact on the aquatic ecosystem, reduced water quality, and economic and social consequences. Therefore, the study recommends that a follow-up on compliance of surface water and groundwater use licenses be regularly conducted. Full article

Backwater effects of the Feilaixia Reservoir caused frequent inundations in the reservoir tail and complicated flood regulations in the North River basin. Currently, how backwater effects impact wedge storages and flood stages in the Feilaixia Reservoir remains unknown. This study established the 1D HEC-RAS model to simulate the water level profile and dynamic storage capacity in the Feilaixia Reservoir during two flood events and in 25 regulation scenarios. The results show that the simulated water levels aligned well with the measured data during the flood events in June 2022 and April 2024. The impact of backwater effects on flood stages, i.e., the water level difference between reservoir regulation and natural river, gradually diminished from the dam to the reservoir tail. The larger flood flow and higher water levels in front of the dam triggered greater wedge storages and higher flood stages and inundation risks in the reservoir. The narrow Mangzaixia Gorge produced a secondary backwater effect in the reservoir tail, resulting in distinct water level profile patterns above the Lianjiangkou confluence in the main stream and in the Lian River tributary. The backwater effects on wedge storage and flood stages were exceptionally large, and the ratios of wedge storages to static water storages in the Feilaixia Reservoir were 125% and 147% during both flood events, and even up to 199% as inflow reaches 20,000 m³/s, which should be carefully considered in operational flood regulation and levee height design in the reservoir. Full article

For a country to be able to sustain a policy of increasing the use of renewable energy sources to supply electricity, it must be able to continue to provide a reliable electricity supply service to its customers. Typically, electricity reliability is maintained by thermal electricity generation. To substitute solar PV for thermal electricity generation to a significant degree, it is imperative to determine the least-cost complementary technologies that will provide system reliability. In many parts of Africa and Asia, potential sites for seasonal storage dams are available or have been built. In the case studied here, maintaining service reliability by expanding the capacity of the generation plant of a seasonal storage dam in all scenarios is less costly than providing service reliability by a thermal alternative. However, maintaining service reliability while expanding generation by solar PV is in all cases costly. The levelized financial cost of the incremental energy supplied when a reliable service is maintained is between 30% and 89% greater than the levelized cost of a standalone solar PV plant. For the same set of scenarios, the range of the economic levelized cost is 28% to 85% greater with reliability than the standalone solar PV field without reliability. Given the circumstances of the electricity market, the least-cost technology to maintain a reliable service may be specific to the market. The analysis also shows that when the economic opportunity cost of funds increases from 2% to 11.5%, the levelized cost of renewable electricity generation systems doubles. Hence, if the developed countries of the world want low-income countries to maintain policies to reduce the use of fossil fuels to generate electricity, capital subsidies to low-income countries that are facing high economic opportunity costs of funds are likely to be necessary. Full article

Water allocation under uncertainty remains a critical challenge in water-scarce regions. This study presents an integrated water allocation model that explicitly incorporates uncertainty through stochastic streamflow simulations and addresses multiple objectives—efficiency, equity, and sustainability—within a unified framework. The model uses historical inflow data, future demand projections, and a multi-objective optimization approach based on the NSGA-II to generate trade-off solutions. To support decision-making, TOPSIS is applied to identify the most balanced allocation strategies from the Pareto-optimal sets. The model is applied to the Namhan River Basin in South Korea, with two key applications: (1) developing adaptive water allocation strategies under dry, normal, and wet hydrological conditions, and (2) proposing targeted infrastructure enhancements—including new dams, transmission lines, and intake points—to address vulnerabilities in dry years. The results demonstrate that the proposed model improves supply reliability, economic efficiency, equity across regions, and sustainability through river maintenance and reservoir storage compliance. This study provides a generalizable and practical decision-support tool for long-term water planning under climate and demand uncertainties, offering actionable insights for water-deficient basins. Full article

Desertification affects over 90% of Moroccan territory, leading to soil degradation that reduces agricultural productivity, diminishes biodiversity, and alters environmental functions. This study estimates the total economic cost of desertification in Morocco using a zonal approach based on regional sensitivity. The methodology includes two stages: quantifying productivity losses from water and wind erosion, salinization, overgrazing, silting of dams, carbon storage loss, and land-use changes; and monetizing impacts using methods such as productivity change, replacement cost, and the social cost of carbon. The total cost is estimated at USD 2.1 billion per year, with 78.02% from agricultural and grazing land productivity losses, 2.95% from dam silting, 18.47% from carbon storage loss, and 0.56% from land-use changes. These findings underscore the urgency of public policies, including land use planning, sustainable agriculture, irrigation modernization, and community engagement. Drawing on successful initiatives in the MENA region and globally, Morocco can mitigate desertification’s impacts and foster sustainable development. Full article