Investigation of innovative designs of high-velocity channels for damping kinetic energy of flows.

In our contemporary world, demanding sustainable resource management, the study focuses on innovative fast flow channel designs. It investigates their efficacy in reducing flow kinetic energy, aiming to optimize water and energy management and diminish flood risks. Employing diverse methodologies, it analyzes and develops these designs, proving their substantial impact on stream energy management. These innovations not only enhance energy efficiency but also mitigate risks associated with excess kinetic energy, promoting safer stream management. This research significantly contributes to fluid dynamics and engineering, deepening the understanding of kinetic energy control in flows and offering potential solutions for water supply, environmental sustainability, and infrastructure safety challenges.

Discharge coefficient of vertical sluice gates with broad crested weir under free-submerged orifice flows using best subset regression.

Accurate calculation of flow discharge for sluice gates is essential in irrigation, water supply, and structure safety. The measurement of discharge with the requirement of distinguishing flow regimes is not conducive to application. In this study, a novel approach that considers both free and submerged flow was proposed. The energy-momentum method was employed to derive the coefficient of discharge. Subsequently, the discharge coefficient was determined through the experiment which was performed on the physical model of a vertical sluice gate with a broad-crested weir. Feature engineering, incorporating dimensional analysis, feature construction, and correlation-based selection were performed. The best subset regression method was employed to develop regression equations of the discharge coefficient with the generated features. The derived formula was applied to compute the discharge coefficient in the vertical sluice gate and determine the flow discharge. The accuracy of adopted method was assessed by comparing it with recent studies on submerged flow, and the results demonstrate that the developed approach achieves a high level of accuracy in calculating flow discharge. The coefficient of determination for the calculated flow rate is 0.993, and the root mean square percentage error is 5.04%.

Assessing the quality of drinking water from selected water sources in Mbarara city, South-western Uganda.

This study assessed the physical, chemical, and microbiological quality with emphasis on risk score, source apportionment, geochemistry, feacal coliforms and water quality index of drinking water from selected water sources. A cross-sectional study was conducted in six villages in Mbarara city, south-western Uganda. Each selected source was inspected using a WHO-adopted sanitary inspection questionnaire. Each source's risk score was calculated. Thirty-seven samples were taken from one borehole, nine open dug wells, four rain harvest tanks, and twenty-three taps. The values for apparent color and phosphate were higher than the permissible level as set by the World Health Organization and Ugandan standards (US EAS 12). The isolated organisms were Klebsiella spp. (8.11%), Citrobacter divergens (62.16%), Citrobacter fluendii (2.7%), E. coli (35.14%), Enterobacter aerogenes (8.11%), Enterobacter agglomerus (5.4%), Proteus spp. (2.7%), Enterobacter cloacae (13.5%), and Proteus mirabilis (2.7%). Twelve water sources (32.4%) had water that was unfit for human consumption that was unfit for human consumption (Grade E), Five sources (13.5%) had water that had a very poor index (Grade D), nine (24.3%) had water of poor index (Grade C), eight (21.6%) had water of good water index (Grade B), and only three (8.1%) had water of excellent water quality index (Grade A). The piper trilinear revealed that the dominant water type of the area were Mgso4 and Caso4 type. Gibbs plot represents precipitation dominance. PCA for source apportionment showed that well, tap and borehole water account for the highest variations in the quality of drinking water. These results suggest that drinking water from sources in Mbarara city is not suitable for direct human consumption without treatment. We recommend necessary improvements in water treatment, distribution, and maintenance of all the available water sources in Mbarara City, South Western Uganda.

A "Prediction - Detection - Judgment" framework for sudden water contamination event detection with online monitoring.

The contamination detection technology helps in water quality management and protection in surface water. It is important to detect sudden contamination events timely from dynamic variations due to various interference factors in online water quality monitoring data. In this study, a framework named "Prediction - Detection - Judgment" is proposed with a method framework of "Time series increment - Hierarchical clustering - Bayes' theorem model". Time to detection is used as an evaluation index of contamination detection methods, along with the probability of detection and false alarm rate. The proposed method is tested with available public data and further applied in a monitoring site of a river. Results showed that the method could detect the contamination events with a 100% probability of detection, a 17% false alarm rate and a time to detection close to 4 monitoring intervals. The proposed index time to detection evaluates the timeliness of the method, and timely detection ensures that contamination events can be responded to and dealt with in time. The site application also demonstrates the feasibility and practicability of the framework proposed in this study and its potential for extensive implementation.

Desalination and transboundary water governance in conflict settings.

Desalination can reduce both water scarcity and variability in supplies, two factors identified as drivers of transboundary water conflict. As such, some have predicted that increasing development of desalination capacity may reduce conflict over shared waters. Others have claimed that desalination may become a source of new conflicts. Additionally, desalination may open up new avenues for cooperation, but also may allow for unilateral action by parties, thereby decreasing cooperation. This study looks at the impact of the introduction of desalination on hydro-political relations in two protracted conflict settings: the island of Cyprus and the Arab-Israeli conflict. Using both quantitative and qualitative assessments, we find that desalination has fundamentally altered hydro-political relations, but find no consistent trends in terms of levels of conflict and cooperation. These findings suggest that the influence of desalination on hydro-political relations is likely to be a function of, rather than a transformer of, the larger geopolitical context.

Risk assessment of inter-basin water transfer plans through integration of Fault Tree Analysis and Bayesian Network modelling approaches.

Inter-basin water transfer projects are a common method used to balance water resources and meet regional demand, particularly in the drinking water supply sector. The potential failure risk associated with inter-basin water transfer projects was examined using Fault Tree Analysis (FTA) and Fuzzy Fault Tree Analysis (FFTA) methodologies in this study. Additionally, the conversion of Fault Tree models into Bayesian Network (BN) and Fuzzy Bayesian Network (FBN) models was explored. Ten basic events were identified as factors that could affect the success of inter-basin water transfer plans, including socio-political, environmental, water resource, economic, and technical criteria. Fault Tree and Fuzzy Fault Tree models were utilized to conduct a risk analysis, which was then converted into crisp and fuzzy FTA-BN through an integrated approach. This approach was applied to evaluate inter-basin water transfer scenarios from the Great Karun basin to the Central Iran Plateau. The superior scenario among eight water transfer scenarios was found to be water transfer from the Behesht-Abad Basin to Isfahan province and from the Khersan Basin to Kerman and Yazd provinces, with a failure risk of 0.649 and 0.601 respectively, based on the crisp and fuzzy integrated models. Basic events were ranked based on their contribution to the occurrence of the top event using two FIM and BI indices in the Fault Tree model and two indices of MI and SI in the Bayesian Network. Furthermore, after considering the correlation between basic events and risk factors, the risk obtained by crisp and fuzzy integrated models was found to increase to 0.811 and 0.789 respectively. The results of this study demonstrate that an integrated approach can assist decision-makers and stakeholders in evaluating inter-basin water transfer projects.

Deep reinforcement learning challenges and opportunities for urban water systems.

The efficient and sustainable supply and transport of water is a key component to any functioning civilisation making the role of urban water systems (UWS) inherently crucial to the wellbeing of its customers. However, managing water is not a simple task. Whether it is ageing infrastructure, transient flows, air cavities or low pressures; water can be lost as a result of many issues that face UWSs. The complexity of those networks grows with the high urbanisation trends and climate change making water companies and regulatory bodies in need of new solutions. So, it comes as no surprise that many researchers are invested in innovating within the water industry to ensure that the future of our water is safe. Deep reinforcement learning (DRL) has the potential to tackle complexities that used to be very challenging as it relies on deep neural networks for function approximation and representation. This technology has conquered many fields due to its impressive results and can effectively revolutionise UWS. In this article, we explain the background of DRL and the milestones of this field using a novel taxonomy of the DRL algorithms. This will be followed by with a novel review of DRL applications in the UWS which focus on water distribution networks and stormwater systems. The review will be concluded with critical insights on how DRL can benefit different aspects of urban water systems.

A system dynamics simulation-based strategic analysis of integrated water resources utilization and management in Shenzhen city.

As one of the most rapidly developing cities in China, Shenzhen grapples with an increasing challenge in managing water resources due to escalating conflicts with its soaring water demand. This study established a system dynamics (SD) model based on a causal loop diagram to explore the intricate interconnections within the urban water resources system. Through simulating water supply and demand in Shenzhen from 2021 to 2035, the model identified key sensitive factors and examined various utilization scenarios for multiple water resources. Results indicated that water scarcity posed a significant obstacle to Shenzhen's development. To tackle this challenge, several effective measures should be implemented, including enhancing water conservation capabilities, developing seawater resources, promoting water reuse, optimizing the economic structure, and managing population growth. Prioritizing water conservation efforts and maximizing the utilization of seawater resources were regarded as the most impactful strategies in alleviating the water crisis. Furthermore, the relationship between water conservation capabilities and seawater utilization scale was analyzed using the SD model, contributing to the development of a comprehensive water resources management strategy. The findings from this study would provide insights into robust methods for allocating water resources, thereby enhancing sustainable water management strategies applicable to regions facing similar challenges.

Private groundwater contamination and risk management: A comparative scoping review of similarities, drivers and challenges across two socio-economically developed regions.

Consolidation of multi-domain risk management research is essential for strategies facilitating the concerted government (educational) and population-level (behavioural) actions required to reduce microbial private groundwater contamination. However, few studies to date have synthesised this literature or sought to ascertain the causal generality and extent of supply contamination and preventive responses. In light of the Republic of Ireland (ROI) and Ontario's high reliance and research focus on private wells and consequent utility for empirical comparison, a scoping review of pertinent literature (1990-2022) from both regions was undertaken. The SPICE (Setting, Perspective, Intervention, Comparison, Evaluation) method was employed to inform literature searches, with Scopus and Web of Science selected as primary databases for article identification. The review identified 65 relevant articles (Ontario = 34, ROI = 31), with those investigating well user actions (n = 22) and groundwater quality (n = 28) the most frequent. A markedly higher pooled proportion of private supplies in the ROI exhibited microbial contamination (38.3 % vs. 4.1 %), despite interregional similarities in contamination drivers (e.g., weather, physical supply characteristics). While Ontarian well users demonstrated higher rates of historical (≥ 1) and annual well testing (90.6 % vs. 71.1 %; 39.1 % vs. 8.6 %) and higher rates of historical well treatment (42.3 % vs. 24.3 %), interregional levels of general supply knowledge were analogous (70.7 % vs. 71.0 %). Financial cost, organoleptic properties and residence on property during supply construction emerged as predictors of cognition and behaviour in both regions. Review findings suggest broad interregional similarities in drivers of supply contamination and individual-level risk mitigation, indicating that divergence in contamination rates may be attributable to policy discrepancies - particularly well testing incentivisation. The paucity of identified intervention-oriented studies further highlights the importance of renewed research and policy agendas for improved, targeted well user outreach and incentivised, convenience-based services promoting routine supply maintenance.

Does interstate trade of agricultural products in the U.S. alleviate land and water stress?

Interregional free-trade of agricultural products is expected to transfer embodied (virtual) water from more to less water-productive regions. However, irrigation in semi-arid to arid regions may significantly push up agricultural productivity but cause local water scarcity. This may result in a puzzle: inter-regional trade may save overall water consumption but lead to more severe local water scarcity. An analogous puzzle may exist for farmland, for instance, trade may save farmland but not address farmland scarcity. To test the existence of these two important puzzles, we applied environmentally extended multi-regional input-output models to obtain the inter-regional virtual agricultural water and land transfer across 48 states of the conterminous U.S. and estimated their agricultural land and water footprints in 2017. Such a detailed analysis showed that while the land-abundant Midwestern states exported a sizable amount of virtual farmland to other densely populated areas and foreign nations, the water-stressed Western U.S. and Southwestern U.S. states, like California, Arizona, and New Mexico, exported considerable amounts of water-intensive crops such as fruits, vegetables and tree nuts to the Eastern U.S. and overseas, thus worsen the local water scarcity of those water scarce states. Our analysis highlights a critical dilemma inherent in an economic productivity-focused incentive regime: It frequently leads to increased withdrawal of scarce water. Therefore, resource scarcity rents need to be reflected in inter-regional trade with the support of local environmental policies.

Adaptive reservoir operation considering water quantity and quality objectives: Application of parallel cellular automata and sub-seasonal streamflow forecasts.

This paper presents a new framework for the adaptive reservoir operation considering water quantity and quality objectives. In this framework, using the European Centre for Medium-Range Weather Forecasts (ECMWF) database, the monthly precipitation forecasts, with up to 6-month lead time, are downscaled and bias corrected. The rainfall forecasts are used as inputs to a rainfall-runoff simulation model to predict sub-seasonal inflows to reservoir. The water storage at the end of a short-term planning horizon (e.g. 6 months) is obtained from some probabilistic optimal reservoir storage volume curves, which are developed using a long-term reservoir operation optimization model. The adaptive optimization model is linked with the CE-QUAL-W2 water quality simulation model to assess the quality of outflow from each gate as well as the in-reservoir water quality. At the first of each month, the inflow forecasts for the coming months are updated and operating policies for each gate are revised. To tackle the computational burden of the adaptive simulation-optimization model, it is run using Parallel Cellular Automata with Local Search (PCA-LS) optimization algorithm. To evaluate the applicability and efficiency of the framework, it is applied to the Karkheh dam, which is the largest reservoir in Iran. By comparing the run times of the PCA-LS and the Non-dominated Sorting Genetic Algorithms II (NSGA-II), it is shown that the computational time of PCA-LS is 95 % less than NSGA-II. According to the results, the difference between the objective function of the proposed adaptive optimization model and a perfect model, which uses the observed inflow data, is only 1.68 %. It shows the appropriate accuracy of the adaptive model and justifies using the proposed framework for the adaptive operation of reservoirs considering water quantity and quality objectives.

Does the South-to-North Water Diversion Project promote the growth of enterprises above designated size in the water-receiving areas?-Evidence from 31 provincial-level administrative regions in China.

The South-to-North Water Diversion Project (SNWDP) is believed to drive the next phase of sustainable productivity growth, meeting growing water demand, so as to address increasing environmental sustainability challenges. The Middle Route of SNWDP is regarded as an extremely large long-distance inter-basin water diversion project, which has benefited Henan, Hebei, Tianjin and Beijing since 2014 with great sustainable changes to the cities, groundwater, ecological environment, industrial structure and social development of the beneficiary areas. Taking the number of industrial enterprises above designated size (IEDS) in the water-receiving areas as the research object, this paper takes the year of policy implementation 2014 as the basic time point, evaluating the change of the number of IEDS in the beneficiary areas of the Middle Route of SNWDP through difference-in-difference model. The results show that: (1) The Middle Route of SNWDP promotes the additional growth of the number of IEDS in the beneficiary areas. (2) When the Middle Route of SNWDP promotes the growth of the number of IEDS in beneficiary areas, there is no regional difference for regions with different development levels. (3) The reasons why the Middle Route of SNWDP contributes to the additional growth of the number of IEDS are composed of promoting mixed ownership reform of enterprises in beneficiary areas, increasing water supply and increasing population. However, the Middle Route of SNWDP has not had a significant impact on the traditional total factor productivity or the components of production factors, technology and capital. From the final outcome, the South-to-North Water Diversion Project has played a facilitating role in the sustainable development of large-scale enterprises in the water-receiving areas.

Effect of flow fluctuation on water pollution in drinking water distribution systems.

The detachment of biofilm caused by changes in hydraulic conditions is an essential reason for the pollution of water in the drinking water distribution system (DWDS). In this research, the effect of flow fluctuation on bulk water quality was studied. The turbidity, iron concentration, manganese concentration, the total number of bacteria, biodegradable dissolved organic carbon (BDOC), bacterial community structure, and pathogenic genes in bacteria of bulk water were analyzed. The results indicate that the detachment of biofilm caused by fluctuant flow and reverse flow (especially instant reverse flow) can lead to the pollution of water. Throughout the entire experimental period, the turbidity under fluctuant flow velocity is 4.92%∼49.44% higher than that under other flow velocities. BDOC concentration is 5.68%∼53.99% higher than that under low and high flow velocities. The flow fluctuation increases bacterial regrowth potential (BRP) and reduces the biological stability of the bulk water. Low flow velocity is more conducive to the expression of pathogenic functional genes. In the short term, the water quality under low flow velocity is the best. Nevertheless, in a long-term operation (about seven days later), the water quality under high flow velocity is better than that under other flow velocities. This research brings new knowledge about the fluctuant hydraulic conditions on the bulk water quality within the DWDS and provides data support for stable drinking water distribution.

Suboptimal Bacteriological Quality of Household Water in Municipal Ibadan, Nigeria.

Access to potable water is difficult for many African residents. This study evaluated the bacteriological quality of household water collected in the dry and wet seasons across five municipal local government areas (LGAs) in Ibadan, a large city in southwest Nigeria. A total of 447 water samples (dry season, n = 250; wet season, n = 197) were aseptically collected from a random sample of mapped households within Ibadan's five municipal LGAs. The pH values and total aerobic and coliform bacterial counts were measured, and samples were screened for Escherichia coli, Salmonella, Shigella, and Yersinia by standard phenotypic techniques and multiplex polymerase chain reaction. The most common source of water was well (53.2%), followed by borehole (34%). None of the households used municipal tap water. Cumulatively, aerobic (P = 0.0002) and coliform (P = 0.0001) counts as well as pH values (P = 0.0002) changed significantly between seasons, with increasing and decreasing counts depending on the LGA. Nonpotable water samples were found to be very common during the dry (86.8%) and wet (74.1%) seasons. Escherichia coli spp., as indicators of recent fecal contamination, were isolated from 115 (25.7%) of the household water sources. Thirty three Salmonella, four enteroaggregative E. coli, and four enterotoxigenic E. coli isolates but no Shigella or Yersinia isolates were identified. This study revealed the absence of treated tap water and the poor quality of alternative sources with detectable pathogens in municipal Ibadan. Addressing the city-wide lack of access to potable water is an essential priority for preventing a high prevalence of feco-orally transmitted infections.

Trihalomethane prediction model for water supply system based on machine learning and Log-linear regression.

Laboratory determination of trihalomethanes (THMs) is a very time-consuming task. Therefore, establishing a THMs model using easily obtainable water quality parameters would be very helpful. This study explored the modeling methods of the random forest regression (RFR) model, support vector regression (SVR) model, and Log-linear regression model to predict the concentration of total-trihalomethanes (T-THMs), bromodichloromethane (BDCM), and dibromochloromethane (DBCM), using nine water quality parameters as input variables. The models were developed and tested using a dataset of 175 samples collected from a water treatment plant. The results showed that the RFR model, with the optimal parameter combination, outperformed the Log-linear regression model in predicting the concentration of T-THMs (N25 = 82-88%, rp = 0.70-0.80), while the SVR model performed slightly better than the RFR model in predicting the concentration of BDCM (N25 = 85-98%, rp = 0.70-0.97). The RFR model exhibited superior performance compared to the other two models in predicting the concentration of T-THMs and DBCM. The study concludes that the RFR model is superior overall to the SVR model and Log-linear regression models and could be used to monitor THMs concentration in water supply systems.

Physical and virtual water transfers in China and their implication for water planetary boundary.

China is an extremely water-scarce country with an uneven distribution of regional water resources. We define two absolute sustainability indicators, using the multi-regional input‒output (MRIO) model to outline the contribution of China's physical and virtual water transfers in mitigating the problem of regional water boundary-exceeding. Although the overall use of freshwater resources is within the safe operation space, 55% of province's water resource development transgresses the local water planetary boundary. Physical and virtual water transfers effectively mitigate the stress of water supply to the water planetary boundary in China's water-scarce regions. Among them, the role of virtual water transfers occupies the main part. The cost of using physical water in water-receiving regions and the situation of virtual water flowing from water-scarce regions to developed water-rich regions cannot be ignored, and a small number of provinces are responsible for most of the virtual water net imports and exports. The obtained results are helpful for the redistribution of water planetary boundary transgressing responsibilities among provinces and the formulation of absolute sustainable water resources management policies.

Climate-related risk assessment in water safety plans: the case study of Acque Bresciane (Italy).

Acque Bresciane is a public company that manages the integrated water cycle for more than 580,000 inhabitants in the Province of Brescia, in the north of Italy, providing drinking water, waste water treatment, and sewer systems. Drinking water systems are supplied with different types of groundwater, springs, and surface water sources (from lakes and rivers) whose availability and quality can be affected by climate change events. A multidisciplinary team, in collaboration with the University of Milano Bicocca, developed a specific Water Safety Plan (WSP) risk matrix focusing on the evaluation of climate-related hazardous events and calculation of their likelihood of occurrence, also using thematic maps. Moreover, to reduce the residual risks, in the risk matrix, possible control measures are suggested, such as the activation of an emergency plan, the use of other water sources, storage tanks, and interconnection with other water distribution networks. This work shows a simple and effective tool that can be applied by drinking water utilities to evaluate climate-related catchment risks, using a WSP risk matrix, thematic maps, and possible control measures to reduce risks in terms of water quality and availability and to respond with resilience to changes.