Water Usage Research Articles

Changes and driving factors of soil water in mixed-species plantations and different precipitation scenarios on the Loess Plateau of China

The implementation of the “Grain-for-Green” program in China led to the extensive introduction of artificial vegetation, thereby intensifying evapotranspiration and the overuse of water resources. Thus, selecting suitable ecological vegetation and planting patterns to save water is a major challenge in the region. Three typical plants were selected in the Loess Plateau of China. The plants had been growing for 13 years. The soil water dynamics were studied based on measurements and Hydrus-1D modeling simulations under different precipitation scenarios (wet, normal, and dry years) and planting patterns (Stipa monoculture (S), a mixture of Stipa and Medicago (SM), and a mixture of Stipa, Medicago, and Caragana (SMC)). The results indicated that the soil water contents with S and SM were 25 % and 8 % higher than the stable field water capacity (SFC), respectively, whereas the SMC was 33 % lower than the SFC in the 0–100 cm depth in relatively normal precipitation years. The evapotranspiration was lowest under S (296–524 mm), followed by SM (351–628 mm) and SMC (368–669 mm). The soil water storage were 19–91 % and 12–58 % higher under S and SM than SMC. The soil desiccation intensity was more severe under SMC (0.3–0.5) than SM (0.5–1.1) and S (0.6–1.4). The soil water storage increased significantly with the annual precipitation (P<0.05), and increased by 54–85 % in relatively abundant water scenarios compared with scarce water scenarios according to Hydrus-1D model simulations. Partial least squares path modeling demonstrated that the soil saturated hydraulic conductivity (path coefficient = 0.478) and soil porosity (–0.703) had significant effects on soil water storage (P<0.01). The results further suggested that using shallow-rooted grass as the dominant plant would reduce water usage in areas with water scarcity, and mixed-species plantations (i.e., a mixture of shallow-rooted and deep-rooted grass) could reduce the loss of sediment in regions.

Sustainable city tourism—A systematic analysis of Budapest and Mumbai

International Tourist arrivals, guest nights and their contribution to GDP are key indicators reflecting a country’s actual perception. A growing percentage of tourists prioritize environmental awareness across tourism products and services each year. Destinations aiming to meet the expectations of eco conscious travellers must center sustainability in their branding strategies. This approach aligns with UNWTO (World Tourism Organization of United Nations) Agenda 2030 of sustainable tourism development. This paper examines various dimensions of sustainability in tourism, focusing on Mumbai and Budapest. Using specific sustainability indicators, it employs sustainability city index to compare international tourism in these cities, which face distinct environmental and infrastructural challenges. By using specific sustainability indicators such as: (1) Carbon Emissions: Measurement of the total greenhouse gases produced by the city. (2) Proportion of Green Public Spaces: Evaluation of the percentage of urban areas dedicated to parks and natural spaces. (3) State of Infrastructure: Assessment of the quality and sustainability of urban infrastructure, including transportation systems. (4) Water Usage: Analysis of the amount of water consumed by the city and its conservation practices. (5) Waste Management: Review of the city’s effectiveness in managing and recycling waste. (6) Air Pollution: Monitoring of the levels of pollutants in the air to assess environmental health. This research provides a comprehensive view of how cities can attract environmentally conscious tourists. The findings offer guidance for policy makers and tourism professionals to align strategies with sustainable development goals. This detailed assessment highlights each city’s commitment to sustainability and delivers actionable insights for improving tourism strategies in accordance with global standards. While valuable for tourism professionals, it is important to note that this research covers only six SCI factors, with incomplete data for studied countries. The practical and social implications indicate areas needing improvement to enhance tourist appeal, beneficial for industry professionals and educational purposes. This comparative analysis aids in promoting sustainable tourism and can guide governments in achieving sustainability goals with raising awareness of environmental quality and conscious living.

Comparative Analysis of Machine Learning Techniques for Water Consumption Prediction: A Case Study from Kocaeli Province.

This study presents a comparative analysis of various Machine Learning (ML) techniques for predicting water consumption using a comprehensive dataset from Kocaeli Province, Turkey. Accurate prediction of water consumption is crucial for effective water resource management and planning, especially considering the significant impact of the COVID-19 pandemic on water usage patterns. A total of four ML models, Artificial Neural Networks (ANN), Random Forest (RF), Support Vector Machines (SVM), and Gradient Boosting Machines (GBM), were evaluated. Additionally, optimization techniques such as Particle Swarm Optimization (PSO) and the Second-Order Optimization (SOO) Levenberg-Marquardt (LM) algorithm were employed to enhance the performance of the ML models. These models incorporate historical data from previous months to enhance model accuracy and generalizability, allowing for robust predictions that account for both short-term fluctuations and long-term trends. The performance of each model was assessed using cross-validation. The R2 and correlation values obtained in this study for the best-performing models are highlighted in the results section. For instance, the GBM model achieved an R2 value of 0.881, indicating a strong capability in capturing the underlying patterns in the data. This study is one of the first to conduct a comprehensive analysis of water consumption prediction using machine learning algorithms on a large-scale dataset of 5000 subscribers, including the unique conditions imposed by the COVID-19 pandemic. The results highlight the strengths and limitations of each technique, providing insights into their applicability for water consumption prediction. This study aims to enhance the understanding of ML applications in water management and offers practical recommendations for future research and implementation.

Ecological compensation mechanism controlled by both river ecological water demand and regional water rights

River ecological protection and rational utilization of water resources provide an important support for the sustainable development for human beings and nature. In view of the lack of ecological compensation research on river ecological water demand and socio-economic water demand, a mechanism and methodology for ecological compensation based on the synergistic control of river ecological water demand and river water rights allocation is proposed. The variable monthly flow method and the improved dynamic calculation method are applied to obtain the river basic and suitable ecological water demands as the river protection threshold. A two-layer decision model for water rights allocation is established, which realizes the cascading allocation of initial water rights from city to counties to sectors, and the socio-economic water usage threshold for each level is obtained based on the model. Developing compensation discrimination guidelines under the dual-threshold synergistic control and using the unilateral water resources value by sub-sector as the compensation standard, realize the quantification and sharing of compensation funds. The Nanyang section of the Bai River basin in China is used as an example. The ecological compensation value for wet year (2011), normal year (2012), and dry years (2014–2013) are 0, 15.09 × 108 and 12.04 × 108 (average value for dry years) RMB. The adoption of suitable ecological water demand thresholds in 2012 increases the ecological protection requirements thus leading to an internal compensation situation between Nanyang County and Xinye County. From 2014 to 2016, river runoff continued to be low, and excessive water intake from upstream lead to a chain of compensation situations in the midstream and downstream. It is essential to establish a basin and regionally nested ecological compensation mechanism. The research results are conducive to improving the eco-compensation theory and provide scientific references for water resources management and high-quality development in the basin.

Central Asian and Northern Cyprus Water Desalination Experience

Water supply in Famagusta, Northern Cyprus, presents a significant challenge, warranting detailed examination of the region&amp;apos;s water management practices. Drawing parallels with the desalination experiences in Central Asia and Northern Cyprus, this manuscript explores the intricate relationship between water infrastructure and the multifaceted challenges faced during young researchers experience exchange internship between Kazakhstan and Northern Cyprus. Through a comprehensive analysis of water desalination experiences and the evolution of water supply facilities in both regions, this study provides insights into effective water usage. Central Asia and Northern Cyprus share similar climate conditions and challenges in water management, thus serving as valuable case studies for understanding optimal water resource utilization. This paper emphasizes the significance of adopting a comprehensive approach to address the complexities of water supply. Current research underscores the importance of sustainable practices and innovative solutions in ensuring water security, particularly in the face of climate change. Sharing knowledge and experiences is crucial for addressing the challenges posed by climate change and ensuring the resilience of water management systems. Key terms such as water desalination, water management in Cyprus, and water issues in Central Asia are meticulously explored, offering valuable insights for policymakers, researchers, and practitioners in the field of water resource management.

Sustainable millet-based ethanol production in India: a comprehensive analysis of water footprint and environmental impact

This research seeks to comprehensively assess the water footprint and environmental sustainability of millet-based ethanol production in India, responding to the growing interest in resilient and nutritious alternatives. Utilizing a life cycle assessment approach, the study will scrutinize water usage across the entire production process, from millet cultivation to ethanol extraction. The primary aim is to gain an in-depth understanding of water consumption at each stage, pinpointing areas for enhancement and efficiency. Rajasthan exhibited the highest total water footprint at 6596 m3/ton, primarily due to its substantial ETc value, while Andhra Pradesh showcased the lowest at 1906 m3/ton, owing to its high average yield. Haryana displayed significant water usage during crop production, with a water footprint of 5870 m3/ton, where WFgreen, WFblue, and WFgrey contributed 3730 m3/ton, 2010 m3/ton and 130 m3/ton respectively. Uttar Pradesh demonstrated a comparatively lower total water footprint of 2564 m3/ton. These findings are anticipated to offer valuable insights into the viability and sustainability of millet-derived ethanol as an eco-friendly biofuel option in India, guiding policymakers, researchers, and stakeholders in promoting its adoption and addressing environmental challenges linked with conventional fuel sources.

Integrated assessment of groundwater quality for sustainable irrigation in drought-prone central districts of Odisha, India

Crop productivity relies on the quantity and quality of irrigation water, with groundwater quality playing a major role. Exploitation of groundwater for irrigation is slowly increasing in central districts of Odisha. A study was carried out in these areas to assess the groundwater quality for irrigation for sustainable use of the groundwater resources. This was done by developing a Water Quality Index (WQI) for eight parameters. The groundwater quality was assessed using a framework that utilised the entropy weight approach and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). This framework was employed to determine the relative proximity of each solution to the ideal solution. The TOPSIS range is divided into three categories: low quality (less than 0.1), medium quality (0.1–0.5), and good quality (0.5–0.9). The low-quality category has a percentage of 6.45%, categorized as poor quality and unfit for drinking and irrigation uses; the medium-quality category has 52.07%, and the good quality category has 41.47% of the area falls under the very good category. These parameters are essential when considering water usage for agriculture, especially in regions where farmers use fertilizers and pesticides extensively to enhance crop production.

Estimating irrigation water use from remotely sensed evapotranspiration data: Accuracy and uncertainties at field, water right, and regional scales

Irrigated agriculture is the dominant user of water globally, but most water withdrawals are not monitored or reported. As a result, it is largely unknown when, where, and how much water is used for irrigation. Here, we evaluated the ability of remotely sensed evapotranspiration (ET) data, integrated with other datasets, to calculate irrigation water withdrawals and applications in an intensively irrigated portion of the United States. We compared irrigation calculations based on an ensemble of satellite-driven ET models from OpenET with reported groundwater withdrawals from hundreds of farmer irrigation application records and a statewide flowmeter database at three spatial scales (field, water right group, and management area). At the field scale, we found that ET-based calculations of irrigation agreed best with reported irrigation when the OpenET ensemble mean was aggregated to the growing season timescale (bias = 1.6–4.9 %, R2 = 0.53–0.74), and agreement between calculated and reported irrigation was better for multi-year averages than for individual years. At the water right group scale, linking pumping wells to specific irrigated fields was the primary source of uncertainty. At the management area scale, calculated irrigation exhibited similar temporal patterns as flowmeter data but tended to be positively biased with more interannual variability. Disagreement between calculated and reported irrigation was strongly correlated with annual precipitation, and calculated and reported irrigation agreed more closely after statistically adjusting for annual precipitation. The selection of an ET model was also an important consideration, as variability across ET models was larger than the potential impacts of conservation measures employed in the region. From these results, we suggest key practices for working with ET-based irrigation data that include accurately accounting for changes in soil moisture, deep percolation, and runoff; careful verification of irrigated area and well-field linkages; and conducting application-specific evaluations of uncertainty.

Hydrological and pedological effects of combining Italian alder and blackberries in an agroforestry windbreak system in South Africa

Abstract. The Western Cape in South Africa is a water-scarce region which will likely receive less rainfall and higher air temperatures under projected climate change scenarios. The integration of trees within agricultural systems provides an effective measure for improving water retention on agricultural land. Studying an established and irrigated agroforestry system (AFS) combining alder (Alnus cordata (Loisel.) Duby) as a linear windbreak with a blackberry (Rubus fructicosus L.) crop, we explore the water use dynamics of the intercrop as influenced by the windbreak element by combining methods from hydrology, soil science and forestry disciplines. Our objective is to explore whether the AFS positively impacts the water balance by combining measurement campaigns to characterise the spatial variability of various key system properties with continuous monitoring. The campaigns encompassed extensive soil sampling to determine soil characteristics (nutrient concentrations, hydraulic conductivity, texture, water retention) in the laboratory as well as terrestrial laser scans of the field site, especially of the windbreaks. The continuous measurements covered meteorological, soil water content and soil water potential observations over a 6-month period (in summer). These were applied to understand soil water dynamics during rainstorms and dry spells, including root water uptake as well as soil water storage. We recorded a total of 13 rainfall events delivering 2.5–117.6 mm of rainfall with maximum intensities of 4.1 to 82.6 mm h−1. Further analyses showed that infiltration is likely dominated by preferential flow, with root water uptake potentially occurring in two depth zones corresponding to different plant communities. While soil water content varied by depth and was influenced by physical and environmental factors, it was generally higher in the intercrop zone than within the windbreak-influenced zone. During dry spells, soil water content did not drop below the water content of the permanent wilting point (&lt;-1500 kPa). Values corresponding to soil water tensions above 1000 kPa were recorded on several occasions; these were mitigated by irrigation and, thus, did not result in water stress. Nutrient distribution and soil physical properties differed near the windbreak in comparison to the blackberry crop, and the carbon sequestration potential is great in comparison to monoculture farming. We could demonstrate positive effects of the windbreak on the water balance and dynamics in the blackberry field site, even though questions remain as to the extent of these benefits and how they compared to disadvantageous aspects brought about by the presence of the trees (e.g. increased water usage). Irrigation did, in fact, shift the AFS from a water-limited regime to an energy-limited one.

Genome editing for improvement of biotic and abiotic stress tolerance in cereals

Global agricultural production must quadruple by 2050 to fulfil the needs of a growing global population, but climate change exacerbates the difficulty. Cereals are a very important source of food for the world population. Improved cultivars are needed, with better resistance to abiotic stresses like drought, salt, and increasing temperatures, and resilience to biotic stressors like bacterial and fungal infections, and pest infestation. A popular, versatile, and helpful method for functional genomics and crop improvement is genome editing. Rapidly developing genome editing techniques including clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated protein (Cas) are very important. This review focuses on how CRISPR/Cas9 genome editing might enhance cereals’ agronomic qualities in the face of climate change, providing important insights for future applications. Genome editing efforts should focus on improving characteristics that confer tolerance to conditions exacerbated by climate change (e.g. drought, salt, rising temperatures). Improved water usage efficiency, salt tolerance, and heat stress resilience are all desirable characteristics. Cultivars that are more resilient to insect infestations and a wide range of biotic stressors, such as bacterial and fungal diseases, should be created. Genome editing can precisely target genes linked to disease resistance pathways to strengthen cereals’ natural defensive systems.

Community-led Initiatives for Water Resource Management in Sumenep Regency, Indonesia

Water scarcity is a global issue affecting human health, well-being, and the environment. Community participation is vital to managing water resources, particularly in addressing water scarcity. In Indonesia, East Java is one of the provinces that frequently experiences water shortages. This research explores how local communities manage water resources and utilize local knowledge to address the vulnerability to clean water crises in Desa Parsanga, Sumenep, and East Java. This study employed a qualitative approach using interviews, observations, and document analysis as data collection methods. The research findings revealed that the local community's initiative is demonstrated through their participation in the construction of drilled wells. This participation is facilitated through an organization formed by the local community in Desa Parsanga called the Association of Drinking Water Users (HIPPAM). HIPPAM constructed five drilled wells that supply clean water to approximately 500 households. This initiative demonstrates that the local communityplays a strategic role in water resource management and can promote sustainable practices. This research provides insights into the potential of communities and local knowledge in addressing global water issues.

Carbon dioxide emission equivalent calculation and inter-sectoral transfer pattern of different water use terminals in China

In the context of global climate change, all industries have put forward the requirements for carbon emission reduction. The effective use of water resources is the key to achieving carbon emission reduction, so it is particularly important to review the carbon dioxide emission equivalents of water resource utilization behaviors (CEE-WRUBs) of water users. However, existing research on CEE-WRUBs across various water sectors remains inadequate. Therefore, this study integrates the enhanced CEEA method, LMDI decomposition model, and IOA method to analyze CEE-WRUBs across diverse water use terminals. Then seeks their main driving factors and their transfer pattern among different industries, which are crucial to the realization of the global carbon neutrality objective. The results showed that: (1) China's CEE-WRUBs show a significant downward trend. Industrial water use emerges as the primary source of CEE, but the CEE-WRUBs of most industrial water terminals show a fluctuating downward trend. Grains' water use behavior (WRUBs) absorbed the largest CEE, reaching 14,698 Mt in 2020. (2) the water efficiency effect emerges as the predominant driver behind the increase in CEE-WRUBs most of the time, and holding a prominent position. The carbon emission intensity effect primarily steers the reduction of CEE-WRUBs. (3) the largest net outflow sector of WRUBs embodied carbon in 2007–2020 was transformed from basic material heavy industry (−153.54 Mt in 2007) to agriculture (−128.26 Mt in 2020). Most of the WRUBs embodied carbon of agriculture flows into light industry, while most of the WRUBs embodied carbon of basic material heavy industry flows into finishing heavy industry and construction. The methods and results of this study provide a potential reference for investigating the regional water-carbon relationship and advancing the global carbon neutrality objective.

IoT-based smart irrigation management system to enhance agricultural water security using embedded systems, telemetry data, and cloud computing

Agriculture, the key sector for food production, faces challenges exacerbated by the growing global demand for food and the scarcity of water resources. Traditional irrigation methods often lead to inefficient use of water, resulting in wastage. Moreover, unpredictable weather conditions and the need to adopt sustainable farming practices are driving us to develop advanced irrigation systems. This paper proposed a smart irrigation management system using new technology like 1) embedded systems, 2) Internet of Things (IoT), 3) telemetry data, 4) cloud computing, communication protocol, and 5) sensors to collect and process real-time data of the smart agriculture. This new technology and intelligent algorithm are used in this paper to improve agricultural practices. The architecture of the proposed scheme comprises three layers: 1) IoT devices, 2) ThingsBoard cloud, and 3) the dashboard, each playing a pivotal role in ensuring seamless data flow, secure communication, and enhanced user interaction. The algorithm orchestrates system operations, incorporating sensor data reading, JavaScript Object Syntax (JSON) payload creation, and secure telemetry data transmission via Hypertext Transfer Protocol (HTTP) protocol to the ThingsBoard cloud. Pump activation decisions are governed by predefined thresholds, preventing an over-irrigation system. The evaluation of system performance involves deploying temperature, humidity, moisture, and water level sensors in a testing field. Further, before data is sent to the cloud, sensor values are calibrated using a functional map. Tests carried out with temperature, humidity, and water level sensors demonstrate the system's dynamic efficiency. By visualizing and analyzing environmental information via ThingsBoard, the results provide real-time data on environmental parameters of the system proposed, improving the efficiency of water use and the sustainability of farming practices. In addition, the system features e-mail notifications for alerts. The integration of e-mail notifications reinforces monitoring and management practices by alerting farm owners and users. This study showcases the efficacy of the proposed paper in enhancing sustainability, water usage, and supporting smart agriculture practices. Further, this paper integrates embedded systems, IoT, cloud computing, and advanced algorithms to optimize and enhance crop productivity and contribute to global food and water security.

Water, water, everywhere and not a drop to drink: Responding to water disruptions in two coastal healthcare facilities

Having a consistent and readily available clean water supply is essential, not only for convenience but also to safeguard public health. While disruptions to the supply of clean water can impact communities of all kinds, some infrastructures and healthcare facilities are more vulnerable than others, such as those located in remote areas or within First Nations communities. This paper presents a case study of water disruption events within Sechelt and the First Nations community of Bella Bella, describing also the associated response efforts and lessons learned. Both events shared similar response activities, requiring the curtailing of normal water usage, the establishment of emergency operations centres, the sourcing of resources via supply chain or transportation partners, implementation of infection prevention and public health considerations, and collaboration with internal and external agencies. The learnings highlight a need for greater focus on building resiliency within healthcare facilities, especially those that serve remote or First Nations communities. The study also presents recommendations for water disruption response planning at the site and community level, and the establishment of non-centralised backup water systems.

An Estimation of Water Deficits considering the Hwanggang Dams on the Imjin River, North Korea

Water resources are essential for sustaining economic activities; therefore, water conflicts between nations and regions are common. The Imjin and Bukhan rivers, which are shared by South and North Korea, have been the sources of several disputes related to water usage and management between both nations. This study is intended to investigate such water deficits and provide elementary data for future responses by quantifying the water deficit in the Imjin River according to current water usage criteria. The researchers collected records on river water usage and flow rates in the Imjin River Basin from 2001 to 2023 and estimated the river maintenance flow. They analyzed eight runoff stations to assess the river maintenance flow and hydrological phenomena to determine the presence of a water deficit. Through a comparative analysis of the flow rates of the Imjin and Hantan rivers, using 2008 as the reference year, they determined the cause of the water deficit to be a North Korean dam. At the ten-year return-period drought, the total water deficit in the Imjin River Basin amounted to 114.5 million cubic meters, with 92.8% of the deficit occurring in the middle reaches of the Imjin River and the remaining 7.2% in the Hantan River.

Diagnostic screening of private well water using gas chromatography with high resolution mass spectrometry to support well water management

In the US, private well users are responsible for their own water quality testing, but local health officials are often uncertain what tests to recommend, particularly for regulated organic chemical contaminants. This study evaluated the utility of suspect and non-target screening (NTS) high resolution mass spectrometry (HRMS) as a tool to identify a wide range of organic chemicals of emerging concern in private well water and to inform well water management decisions. Qualitative NTS, which detects chemicals without providing concentrations, was used to analyze 25 private well water samples from Wake County, North Carolina. Using the NIST 20 mass spectral database (M1), NTS tentatively identified 106 unique organic chemicals across the 25 samples and an average of 11 organic chemicals per sample. At least one USEPA ToxCast chemical was identified in each private well water sample. Private well water users were interviewed prior to and after their sample's NTS results were reported back; four county groundwater managers were interviewed after aggregated results for all 25 water samples were reported back. All but one well user participant chose to participate in the reporting-back post-interview. The 24 private well users found NTS results useful and valued the contextualization of their results using NTS results for other well users and a local municipal water sample. Most private well users (67%) were surprised by their well water results, especially regarding the number of tentatively identified organic chemicals detected. All the groundwater managers believed the NTS results were useful and could help improve their testing recommendations to private well users. Even with qualitative limitations, NTS results can be an effective and valuable tool to inform the public and governance stakeholders in decisions around groundwater quality management.

A Comprehensive IoT edge based smart irrigation system for tomato cultivation

Agriculture industry is the primary engine for a country's economic development. Growing crops using minimum irrigation water is a major challenge for farmers. In conventional farming, crops may be affected by various diseases due to inadequate irrigation scheduling. Recent proposals have suggested using Edge-IoT, AI, and distributed computing to accelerate the inference procedure utilized in smart irrigation applications. The use of resource-constrained edge servers and edge devices used to deliver smart agriculture applications can cause latency-sensitive workloads to interfere with one another. To address this issue, we design a long-range (LoRa) edge IoT computing-based sustainable and customized smart irrigation framework to capture the real-time data of tomato plants. This helps in automatic underground drip irrigation scheduling. This also predicts total water demand and usage, and measure plant growth status. The edge-IoT cloud data transmission control and optimization has been enforced using Smart irrigation data optimization and robust transmission (SIDORT) Message Queuing Telemetry Transport (MQTT) system. We develop a hybrid algorithm named Linked least traversal (LLT) for machine-to-machine communication (M2M). Also, a Reinforcement learning (RL) based Optimal Soil Wetness Closeness Policy (OSWCP) for irrigation scheduling has been proposed. The performance of the proposed smart irrigation models has been validated through extensive experiments using real-time data in which OSWCP performance has been measured at a 97.88 % accuracy rate. Additionally, a comparison of our proposed architecture has been accomplished by resolving the existing smart irrigation system challenges.

Analysis of Heavy Metals in Water and Wastewater

The primary focus of the study is to assess the presence and concentration of heavy metals in the water and evaluate its suitability for drinking purposes. Given that a significant portion of the local population depends on groundwater for their daily needs, the study is critical in understanding the potential health risks associated with consuming contaminated water. The study begins with a comprehensive survey to gauge the extent of water usage among the local population and their perceptions of water quality. Results from the survey reveal that nearly half of the households in the region are not connected to a formal drinking water network, relying instead on wells and springs. While the majority of respondents perceive the water quality as good, the analytical findings suggest otherwise. Groundwater samples were collected from twelve wells and three springs across the region. These samples were subjected to rigorous analysis using inductively coupled plasma-atomic emission spectrometry (ICP-AES) to detect the concentration of various heavy metals, including aluminum, silver, iron, cadmium, arsenic, chromium, cobalt, zinc, lead, and copper. The results indicate that many of these metals are present in concentrations that exceed the World Health Organization's recommended limits for safe drinking water. Iron, in particular, was found at high levels in all sampled locations, raising significant concerns. The study also employs the Heavy Metal Pollution Index (HPI) to provide a more comprehensive assessment of water quality. The HPI values calculated for the sampled water sources reveal that a majority of the wells and all of the springs have levels of heavy metal contamination that render the water non-potable. This finding is particularly alarming given the region's dependence on water, especially during periods of drought when alternative water sources are scarce.

Water usage in cooling systems for electricity production: an event study of retrofitted coal-fired power plants in the United States

Water usage in cooling systems for electricity production: an event study of retrofitted coal-fired power plants in the United States

Revealing Conditions of Detailed Water Usage, Daily Life Water Quality, and Awareness Related to Waste Water at Urban Kampung in Indonesia

This research aimed to investigate the actual water use of residents and the quality of well water used daily at the urban kampung located in Bandung, Indonesia. The status of wastewater treatment and residents' awareness of the water environment were also investigated in the target area. The methodology used included a survey of residents, water quality testing, and an assessment of wastewater practices. The results showed that approximately one-half of the respondents used water from the water utility, with the other half using well water as their main domestic water source. Identifying water sources by end-use revealed that residents mainly used bottled water for drinking and cooking. Since Escherichia coli was detected in many wells, it is not recommended that residents drink well water without disinfection. In addition, most of the wastewater in the area was discharged into a nearby river without treatment.