Water Management System Research Articles

Significance of Having Integrated Water Resource Plan in a Complex Watershed System for Better Water Management during Covid Pandemic: The Case of Mahaweli River Basin

Significance of Having Integrated Water Resource Plan in a Complex Watershed System for Better Water Management during Covid Pandemic: The Case of Mahaweli River Basin

The Effect of Irrigation on the Vineyard Canopy and Individual Leaf Morphology Evaluated with Proximal Sensing, Colorimetry, and Traditional Morphometry

The high number of grapevine (Vitis vinifera L.) cultivars grown world-wide are described and identified according to detailed morphological and morphometric descriptor lists. The grapevine leaf is of utmost importance in characterization, despite its traits being very sensitive to environmental factors. In this study, the effect of irrigation/drought stress on the individual leaf morphology and morphometry of the ‘Hárslevelű’ grapevine (Vitis vinifera L.) cultivar was examined. To verify the effect of the applied irrigation methods (drip and subsoil irrigation) on the plant’s water status, water potential measurements were carried out during the 2022 season. The effect of the applied treatments on the vegetative growth was evaluated according to point quadrat and a multichannel LiDAR analysis in order to describe the width of the canopy area, row volume, and area coverage index. The individual leaf morphology was assessed via traditional morphometry and colorimetry. Our results showed that rainfed plants had a significantly lower stem ψ compared to the drip- and subsoil-irrigated plants at all examined dates. The point quadrat results indicate that the leaf layer number was significantly (p < 0.05) influenced by the position, while the treatment showed no effect on the leaf layer number. The leaf colorimetry showed a difference among the samples, as significant alterations were found in 28 out of the 32 examined color properties. Within the traditional morphometric analysis, 54 traits were evaluated, and 14 of the traits were significantly altered due to the different water management systems.

Too much ado about data: continuous remote monitoring of water temperatures, circulation and throughput can assist in the reduction of hospital-associated waterborne infections

National and international guidance provides advice on maintenance and management of water systems in healthcare buildings; however, healthcare-associated waterborne infections (HAWIs) are increasing. To identify parameters critical to water quality in healthcare buildings and to assess whether remote sensor monitoring can deliver safe water systems, thus reducing HAWIs. A narrative review was performed using the following search terms: (1) consistent water temperature AND waterborne pathogen control OR nosocomial infection; (2) water throughput AND waterborne pathogen control OR nosocomial infection; (3) remote monitoring of in-premises water systems AND continuous surveillance for temperature OR throughput OR flow OR use. Databases employed were PubMed, CDSR (Clinical Study Data Request) and DARE (Database of Abstracts of Reviews of Effects) from January 2013 to March 2024. Single ensuite-patient rooms, expansion of handwash basins, widespread glove use, alcohol gel and wipes have increased water system stagnancy resulting in amplification of waterborne pathogens and transmission risk of legionella, pseudomonas, and non-tuberculous mycobacteria. Manual monitoring does not represent temperatures across large complex water systems. This review deems that multiple-point continuous remote sensor monitoring is effective at identifying redundant and low use outlets, hydraulic imbalance and inconsistent temperature delivery across in-premises water systems. As remote monitoring becomes more common there will be greater recognition of failures in temperature control, hydraulics, and balancing in water systems, and there remains much to learn as we adopt this developing technology within our hospitals.

Optimizing water and nitrogen management for saline wasteland improvement: A case study on Suaeda salsa

Cultivating Suaeda salsa (S. salsa) is a promising strategy for the improvement and development of saline wastelands. However, the absence of a scientifically reasonable water and fertilizer management system has long hindered the large-scale improvement and utilization of saline wastelands. Therefore, we performed field experiments for two consecutive years to investigate the effects of water-nitrogen coupling on biomass, forage quality, salt absorption capacity, soil improvement effect, and economic benefits of S. salsa. The optimal water and nitrogen dosages for multi-objective optimization were determined using multiple regression and spatial analysis methods. Three irrigation levels were established for the experiment based on 0.35 (W1), 0.50 (W2), and 0.65 (W3) of the local ETo (Where ETo denotes the reference evapotranspiration calculated based on the FAO-56 recommended by the Food and Agriculture Organization). The three nitrogen application levels were 150 (F1), 250 (F2), and 350 (F3) kg ha−1 in the complete combination design. At the same nitrogen application level, the biomass and economic benefits of the W3 irrigation level were the highest. However, the forage quality, salt absorption capacity, salt reduction, and water productivity at the W3 irrigation level were lower than those at the W2 irrigation level, and the water productivity at the W1 irrigation level was the highest. At the same irrigation level, when the nitrogen application level was F2, the biomass, forage quality, salt absorption, salt reduction, and net profit, all reached their maximum values, and water productivity was the highest at the F3 level. The optimal amount of water and nitrogen applied for each parameter was different, so it was impossible to obtain the highest biomass, forage quality, salt absorption, salt reduction, water productivity, and net profit at the same time. Therefore, multi-objective optimization was needed, the optimal irrigation volume range was 3350.11–3485.97 m3 ha−1, and the nitrogen application rate range was 273.49–326.66 kg ha−1. These findings provide a scientific basis for the large-scale cultivation of S. salsa in extreme arid region, which is helpful for the improvement and utilization of saline-alkali land.

Перспективы развития водного хозяйства Ростовской области в системе отношений «вода – энергия – продовольствие»

In modern socio-economic and environmental challenges, the sustainable development of regional water management systems must be carried out within the framework of a circular paradigm. However, not all circular approaches are sustainable. Therefore, implementing circular business models should be carried out on the principles of industrial symbiosis. The possibilities of achieving the synergistic effects of the circular economy increase significantly by implementing the water-energy-food relationship. The article substantiates the possibilities and prospects for the development of water management in the Rostov region based on intersectoral interactions between the water, energy, and food sectors of the economy. The prerequisites for the implementation of industrial symbiosis relations in the Rostov region were identified. Possible options for implementing industrial symbiosis relations, which showed good results, are proposed. The characteristics of the main processes implemented by the hydraulic system of the region to achieve sustainable development goals are given. The conclusions about the need for state institutional and infrastructural support for the development of the circular economy are drawn. The novelty of the results is that they go beyond the framework of the circular economy and represent a more holistic vision of the prospects for the development of regional water management. The conclusions can be used in regional management when adopting and developing a strategy for the development of regional water management.

Impact of Ancient Water Management Systems on Agricultural Productivity and Sustainability

Ancient water management practices had a significant influence on agricultural sustainability and productivity, which this article delves into. Mesopotamian, Egyptian, and Indus Valley civilisations, among others, had highly developed systems for managing and distributing water, which greatly improved their agricultural productivity and sustainability in the long run. This study reveals the technical advancements, engineering methods, and ecological tactics that helped these old practices succeed by analysing a variety of systems, from terraced fields and canals to qanats. The study also delves into the monetary and societal effects, showing how efficient water management paved the way for industrial farming and city expansion. By contrasting these ancient systems with modern approaches, the study highlights their continued relevance and offers insights into how they can influence current agriculture and water management tactics. In order to tackle present and future sustainability issues, the study concludes that it is valuable to preserve and learn from old water management systems.

“Design and analysis of bamboo fiber-based anchor spray irrigation system for sustainable water management in agriculture”

“Design and analysis of bamboo fiber-based anchor spray irrigation system for sustainable water management in agriculture”

Monitoring and management of green information in water ecological environment based on sensors and big data

With the continuous development of industrial production, the pollution of water resources is becoming more and more serious, and the damage to aquatic organisms is also increasing. Therefore, strengthening water environment monitoring has become a key measure to prevent and solve this problem. Aiming at the limitation of traditional water environment monitoring methods, a water ecological environment monitoring scheme is proposed. This study uses advanced sensor technology, including water quality sensor, water level sensor, weather sensor, etc., to monitor the indicators of water in real time. Through data acquisition and storage technology, the data obtained by the sensor is integrated and analyzed. At the same time, big data analysis method is used to predict and simulate the change trend of water ecological environment. This scheme designs and develops a sensor network monitoring system, which can collect water temperature data in real time at the monitoring point, transmit the sampled information to the aggregation node through the sensor network, and finally transmit to the information intelligent monitoring equipment through GPRS, so as to realize timely display and early warning. At the same time, combined with the water quality monitoring instrument, it can realize the remote query and processing of monitoring data. The experimental results show that the water ecological environment monitoring and management system based on sensor and big data technology can efficiently and accurately monitor the indicators of water. Through the comprehensive monitoring of the water ecological environment, abnormal situations can be found in time, and corresponding measures can be taken to protect and repair. The results of big data analysis provided by the system can provide scientific basis and guidance for decision makers.

Comparative analysis of machine learning methods for prediction of chlorophyll-a in a river with different hydrology characteristics: A case study in Fuchun River, China

Eutrophication is a serious threat to water quality and human health, and chlorophyll-a (Chla) is a key indicator to represent eutrophication in rivers or lakes. Understanding the spatial-temporal distribution of Chla and its accurate prediction are significant for water system management. In this study, spatial-temporal analysis and correlation analysis were applied to reveal Chla concentration pattern in the Fuchun River, China. Then four exogenous variables (wind speed, water temperature, dissolved oxygen and turbidity) were used for predicting Chla concentrations by six models (3 traditional machine learning models and 3 deep learning models) and compare the performance in a river with different hydrology characteristics. Statistical analysis shown that the Chla concentration in the reservoir river segment was higher than in the natural river segment during August and September, while the dominant algae gradually changed from Cyanophyta to Cryptophyta. Moreover, air temperature, water temperature and dissolved oxygen had high correlations with Chla concentrations among environment factors. The results of the prediction models demonstrate that extreme gradient boosting (XGBoost) and long short-term memory neural network (LSTM) were the best performance model in the reservoir river segment (NSE = 0.93; RMSE = 4.67) and natural river segment (NSE = 0.94; RMSE = 1.84), respectively. This study provides a reference for further understanding eutrophication and early warning of algal blooms in different type of rivers.

Tailored approaches of data collection for improved water system management in resource constrained contexts: lessons from Ethiopia

ABSTRACT Access to water has improved globally; however, nearly 800 million people continue to lack access, particularly in resource constrained contexts. Current efforts are not on track to meet the Sustainable Development Goals aim of safe and affordable drinking water for all. Innovative and contextualized solutions are required. This article describes a university–government collaboration in Ethiopia that addressed key data limitations, without which equity-based decision-making was not possible. These efficient and cost-effective ways for obtaining and managing data support improved decision-making, and also identified avenues for improving water system governance through policy shifts and citizen participation.

From test case to trusted tool: Lithuania’s evolving SWAT system for water and agricultural management

Lithuania’s development of the river modelling system (RMS) exemplifies an institutional development and application of integrated modelling for water and agricultural management. What started as a test case, continued to develop focusing on environmental compliance with the EU regulations. Currently, the RMS is a part of decision-making. By incorporating the soil and water assessment tool (SWAT) model and comprehensive data sources, the system facilitates in-depth analysis and policy formulation. Applications in water management plans, pollution assessments, and climate change studies demonstrate the reliability of RMS. Despite data quality and skill retention challenges, institutional commitment and collaboration ensure the RMS’s persistence. This experience emphasizes the value of sustained investment in integrated modelling systems for achieving sustainable environmental governance and signifies Lithuania’s shift towards data driven green transition practices.

Integrated urban land cover analysis using deep learning and post‐classification correction

AbstractThe quantification of urban impervious area has important implications for the design and management of urban water and environmental infrastructure systems. This study proposes a deep learning model to classify 15‐cm aerial imagery of urban landscapes, coupled with a vector‐oriented post‐classification processing algorithm for automatically retrieving canopy‐covered impervious surfaces. In a case study in Corpus Christi, TX, deep learning classification covered an area of approximately 312 km2 (or 14.86 billion 0.15‐m pixels), and the post‐classification effort led to the retrieval of over 4 km2 (or 0.18 billion pixels) of additional impervious area. The results also suggest the underestimation of urban impervious area by existing methods that cannot consider the canopy‐covered impervious surfaces. By improving the identification and quantification of various impervious surfaces at the city scale, this study could directly benefit a variety of environmental and infrastructure management practices and enhance the reliability and accuracy of processed‐based models for urban hydrology and water infrastructure.

Water park of the future: Monarch butterfly slide with eco-friendly design and smart water management

In this study, an innovative water park concept slide that aims to keep water consumption low was designed and produced. Traditional water parks are out of use at a rate of approximately 65% because they are inefficient in water and energy consumption. This work will be a pioneering step in the sector with the combination of environmentally friendly design, smart water management systems, and sustainable technologies. Users entering the 43% inclined butterfly body will reach a speed of 16 m/sec while performing the vertical swing movement and will move with an acceleration of 0.5m/sec2 on the horizontal axis. Since the high-pressure water coming from the nozzles on the slide will be used only when there is movement, approximately 70% water and 50% energy savings will be achieved and sliding safety will also be increased. The proposed saving system will be produced using the inverter, integrated circuit, smart card, and software developed to be added to the pump and will be adapted to all slides. The fact that this study is a first in the sector will inspire other water parks and lead to the development of projects that consider sustainability and savings issues.

Cost-Benefit Analysis of Minor Irrigation Tank Rehabilitation Using Run-Off and Storage Capacity: A Case Study from Ambuliyar Sub-Basin, Tamil Nadu, India

This research examines the significance of restoring efficient water management systems in India’s semiarid environment, with special emphasis on the role of traditional irrigation structures, such as tanks, in collecting and storing limited water resources. Assessing the benefits of any restoration program, especially when socioeconomic and environmental benefits are involved, is challenging. In the context of tank rehabilitation, a cost-benefit analysis will be conducted regarding economic and ecological returns in the post-desiltation phase. Since the restoration process requires a significant investment, assessing the project’s viability during the planning stage is better. The present study proposes a novel method to indirectly analyse the cost-benefit of the tank restoration process by correlating run-off and storage capacity of tanks before the planning phase. The Ambuliyar sub-basin, which covers an area of 930 square kilometres in Tamil Nadu, India, comprising 181 tanks (water bodies) of varying sizes and shapes, was taken for this study. This study employed the Soil Conservation Service Curve Number (SCS-CN) method, incorporating factors such as soil type, land cover, land use practices, and advanced remote sensing and Geographic Information System (GIS) tools to simulate surface run-off. Run-off volume and tank capacity were compared for all seasons at the micro-watershed level. The results demonstrated that the run-off volume in each micro-watershed significantly exceeded the tank capacity across all seasons. Even during the summer, the run-off volumes in the micro-watershed were considerably higher than the tank capacity. The findings suggest tank restoration can effectively store run-off and significantly fulfil agricultural and other essential needs throughout the year, thereby improving the local rural economy. This study also highlights the need for periodic maintenance and rehabilitation of these tank systems to retain their functionality.

Climate‐driven runoff variability in semi‐mountainous reservoirs of the Vietnamese Mekong Delta: Insights for sustainable water management

AbstractThe Mekong Delta, South East Asia's ‘rice bowl’, sustains more than 18 million people through its agricultural output. This yield is secured by efficient water management systems but is susceptible to climatic changes. As Vietnam's policies aim to optimize the delta's semi‐mountainous regions reliant on rain‐fed agriculture, this study investigates drought risks and climate change impacts on runoff in the O Ta Soc and O Tuk Sa reservoirs, An Giang Province, Vietnam. Using simulation models, we determined runoff volumes for specific rainfall return periods and climate scenarios for the 2030s and 2050s. Using the storm water management model (SWMM), we simulated the reservoir water balance considering rainfall, evaporation and infiltration. Our findings suggest potentially increased runoff and reservoir storage due to intensified monsoons and reduced off‐season rainfall. The 4.77 km2 drainage of the O Ta Soc reservoir could benefit from this, while the 2.55 km2 drainage of the O Tuk Sa watershed may require alternative water‐sourcing strategies. This research offers insights for drought predictions, flood management and water strategies in An Giang. To refine these predictions, future research should consider upcoming rainfall patterns.

A comprehensive analytical and computational assessment of soil water characteristics curves in Atlantic Canada: Application of a novel SelectKbestbased GEP model

For sustainable agriculture, irrigation is one of the most important management practices in a semi-arid climate. Determining the site-specific soil type-based irrigation water requirements requires the development of a soil water characteristics curve (SWCC). This study focuses on exploring the suitability of analytical SWCC models based on the observed data of SWCC developed using the pressure membrane apparatus. A novel SelectKbest gene expression programming (GEP) model is used to create the generalized machine learning SWCC model for Atlantic Canadian soils. The composite soil samples with representative soil textures of loamy sand, loam, and sandy loam are collected from the selected locations in Prince Edward Island and New Brunswick provinces of Canada. The suitability of models at three regions shows that at all sites, including PEI-1 (loam soil) 1, PEI-2 (loamy sand), and NB-3 (sandy loam) if SWCC data has four measured suction potential levels, then McBee & Bomb and Tani exponential models may be selected. Van Genuchten, double exponential, Ruso, Kosuki, and Gardner's four parameters models should be a good choice for five-section potential. Similarly, for six measured suction potential values, the Fredlund & Xing, Omuto, and Van Genuchten models having parameters should be selected for determining the optimum soil hydraulic parameters. The HydroMe program with Brooks and Corey, four, and five parameters Van Genuchten models performed well. The HydroMe program is calibrated and validated with standard RETC for selected regions of Atlantic Canada, which suggests that the HydroMe program is flexible in developing efficient agricultural water management algorithms. Various performance metrics like R2 and RMSE are employed to assess the robustness of the model. A generalized SWCC model (R2=0.976 and RMSE=0.04) is developed using a novel SelectKbest-based GEP modeling approach for Atlantic Canadian soils. These novel approaches can significantly improve site-specific agricultural water management and decision support systems.

The Maharashtra River Basin's Flood-Drought-Water Scarcity Nexus

<p>India's droughts and floods, which have affected 8 million hectares yearly since the 1950s, make future adaptation and mitigation plans necessary, as well as an awareness of potential changes. In order to address the growing issues of flood and drought events in urban settings, the study emphasizes the importance of comprehensive water management strategies that ensure both routine water needs and severe event readiness. This study article recommends including drought and flood considerations in building codes and urban planning regulations to boost urban water resilience. The paper provides workable solutions for developing water-sensitive urban design, rainwater collecting, greywater reuse programs, and decentralized water management systems through a collection of case studies and strategy models. It also emphasizes the importance of teaching the population about the dangers of droughts and floods, water conservation methods, and emergency response procedures. The recommendations place a lot of emphasis on the need for a variety of policies that encourage cooperation between stakeholders, including local and state governments, business owners, community leaders, and experts. The policy recommendations include requests for green infrastructure, building standards for flood-resistant homes, water conservation requirements, and climate-responsive legislation, among other subjects. By encouraging sustainable water use behaviors, these concepts aim to increase urban resilience and make cities better prepared to mitigate the consequences of drought and flooding. These recommendations can aid local and state governments in creating a culture of preparedness for catastrophes, protecting communities, and fostering urban water resilience. This case study looks at the intricate relationships between a specific Maharashtrian river's floods, droughts, and water scarcity.</p>

Bangladesh towards green growth: a review of environmental sustainability indicators

Pursuing green growth is crucial for Bangladesh to transition from an unsustainable economic trajectory to a more sustainable and inclusive one. Bangladesh is picked for this study because of impending and severe economic and environmental threats. This study intends to review the present scenario of various environmental sustainability-related indicators in Bangladesh, focusing on renewable energy consumption, freshwater resources, water productivity, CO2 emissions, energy intensity, air pollution, and natural resource rents. The World Bank database has been utilized to obtain secondary time series data of Bangladesh spanning from 2000 to 2020. As a descriptive study, cross-sectional and observational research methods as well as descriptive statistics and figures are used to elucidate the secondary data. Data demonstrate that Bangladesh now generates 41.16% of its energy from renewables, despite considerable variability. Regardless of the variation in freshwater availability, averaging at 708.19 cubic meters per capita, efficient water productivity remains consistent, indicating a robust water management system. The country demonstrates a relatively low carbon footprint, emitting 0.35 metric tons of CO2 per capita, alongside varying energy intensity levels, highlighting the need for enhanced efficiency measures. While pervasive PM2.5 air pollution poses a significant health risk, Bangladesh's reliance on natural resource rents underscores the importance of sustainable resource management practices for long-term economic stability. The observations of this study might assist in the formulation of policies of water management systems, air pollution control initiatives, and conservation of ecology to promote Bangladesh's long-term sustainability objectives and formulate policies.

From advanced hydraulic modelling to performance indicator for the efficiency of investments in leakage management of pressurized water systems

IntroductionThe digital transition is meant as the review of processes using digital technologies and strategies to increase efficiency based on a simpler collection of representative data. The process of interest here is the leakage management in systems distributing water. ObjectiveTo develop a novel key performance indicator (KPI) for leakage management considering the needs of ongoing digital transition in the water sector, which is opening a new era in the management of drinking water infrastructures. MethodologyThe novel KPI, named Asset Management Support Indicator, is developed starting from advanced hydraulic modelling and the physical laws governing leakage outflows, in order to be physically based and rational for increasing the efficiency of leakage management activities using representative process data. ResultsThe Asset Management Support Indicator supports effective leakage management strategies by driving towards efficiency, as discussed and demonstrated using several real case studies. ConclusionThe novel indicator is consistent with the digital transition perspective and current need of increasing the efficiency of water utilities, and it is also suitable to be adopted by water authorities to benchmark their performances, because it overcomes the weaknesses of traditional KPIs.

Image-based security techniques for water critical infrastructure surveillance

Security-related image analysis of critical infrastructures involves using advanced technologies to analyze visual data to identify potential threats, vulnerabilities, or abnormal activities. This type of analysis can be crucial for safeguarding critical infrastructure such as water management systems, power plants, transportation systems, communication networks, and more. In this paper, we propose two-factor-based authentication and pose-based monitoring tasks for water critical infrastructures. In the first phase, we detect and recognize the faces of authorized persons and check their liveness for anti-spoofing by eye-clicking checking and multimodal ensemble methods. In the second phase, we create our dataset, WCI-Pose, and we use four pose-based approaches – OpenPose, AlphaPose, Kapao, and YOLOv8 – for human action recognition. Experimental results show that OpenPose algorithm provides more favorable results compared to the other algorithms with an accuracy of 92.4%. SVM with multimodal data has the best performance score with an accuracy of 92% for face anti-spoofing.