Resilient Water Research Articles

Empowering community participation for sustainable rural water supply: Navigating water scarcity in Karak district Pakistan

In the tapestry of life, water is the essential thread weaving through our existence. Imagine this thread not just as a simple element, but as the very pulse that sustains our communities. This study unravels the nuanced interplay between community engagement and sustainable water solutions in District Karak, shining a spotlight on a crucial but often overlooked aspect of rural water programs. Employing the theoretical framework of Social Capital Theory by Robert Putnam and Pierre Bourdieu, our research investigates the interconnected relationship between community participation and the long-term viability of water supply initiatives. Focusing randomly on three selected water supply schemes, we employed a sampling technique and collected data from 330 respondents through interviews. Community members, Community-Based Organizations (CBOs), and executing agencies were sampled to analyze the extent and impact of engagement across program phases. The findings underscore the pivotal role of participatory approaches facilitated by CBOs and executing agencies, revealing active community engagement as a linchpin for sustained water supply success. Results of the study reveal that the synergy of community satisfaction and engagement paves the way for a resilient water future, offering a blueprint for District Karak and similar regions to pursue a more secure water future and mitigate the adverse effects of water scarcity through the promotion of community participation.

Water and COVID-19 Pandemic: A Literature Review

This literature review analytically discovers how the complex dynamic between Water and the extraordinary challenges caused by the COVID-19 epidemic is associated the critical synthesis and Evaluation of the selected papers reveals a diverse set of techniques and results, contributing to the research knowledge of the complex interplay between the pandemic and water parameters. Ranging from different studies on the topic, the review comes up with a critical analysis of 15 water demand articles that deal in varied areas, covering water resilience in the United Kingdom and Ireland, water resource disruptions in India, and so on. What is more is that the analysis of varying results and methods leads to the highlight of common patterns and differences, which lays out the general direction of research on such a significant subject. By looking for common issues in different editions, the subject matter of the uncertainty involved becomes precise and complicated. The results highlight that the pandemic has affected multiple facets of Water globally. Each study offers a distinct perspective, from modeling in Saudi Arabia to researching water quality in Hawai'i during lockdowns. While "Water Sector Resilience in the United Kingdom and Ireland: The COVID-19 Challenge" focuses on adaptation strategies, "Changes in Water Use and wastewater generation influenced by the COVID-19 pandemic: A Case Study of China" looks at Regional Variations. The concluding section describes outcomes and suggestions for the broader perception of water associations with the pandemic.

Climate-resilient water resource management for Rohingya refugee camps in Bangladesh

The Rohingya refugee camps in Bangladesh face severe water resource challenges, exacerbated by the impacts of climate change. With a rapidly growing population, the demand for water in these camps has surged, leading to over-extraction of groundwater and deteriorating water quality. Seasonal variations, including monsoons and dry spells, further strain the limited water resources, creating periods of acute scarcity and contamination risks. Climate change intensifies these issues by altering precipitation patterns and increasing the frequency of extreme weather events, jeopardizing the sustainability of current water supply systems. This paper explores sustainable water resource planning strategies tailored to the unique context of the Rohingya camps, emphasizing climate resilience and community-based approaches. By integrating innovative technologies and policy interventions, the study aims to propose solutions that ensure long-term water security for the refugee population. Sustainable water resource planning is crucial for addressing the compounded challenges of water scarcity and quality in Rohingya refugee camps, particularly under the escalating pressures of climate change. As climate change alters precipitation patterns and increases the frequency of extreme weather events, the vulnerability of water systems in these densely populated settlements intensifies. Effective planning must integrate climate resilience, ensuring reliable access to safe water despite environmental uncertainties. This involves adopting adaptive management strategies, leveraging innovative technologies, and fostering community participation to enhance system robustness and flexibility. Sustainable planning not only addresses immediate water needs but also builds long-term resilience, reducing dependency on overstressed groundwater resources and mitigating the impacts of climate-induced disruptions. This paper underscores the importance of holistic and forward-thinking approaches in securing water resources for the Rohingya population in the face of a changing climate. The study identifies critical gaps in current water resource management practices within Rohingya refugee camps and emphasizes the necessity for sustainable planning amidst climate change impacts. Key findings reveal that over-reliance on groundwater, coupled with inadequate infrastructure and seasonal variability, significantly undermines water security. The research recommends the implementation of integrated water resource management (IWRM) strategies, incorporating both traditional and innovative solutions such as rainwater harvesting, solar-powered water purification, and community-led water conservation practices. Enhancing policy frameworks to support sustainable water management and fostering collaborations among stakeholders are also crucial. Furthermore, climate resilience measures, including infrastructure fortification against extreme weather events, are imperative for long-term sustainability. These recommendations aim to establish a resilient water supply system that can adapt to future climate conditions while ensuring equitable access to safe water for the Rohingya population.

WATER RESILIENCE UNDER CLIMATE CHANGE IN AZERBAIJAN

Water resilience under climate change in Azerbaijan is increasingly vital as rising temperatures and erratic precipitation patterns strain water resources. Addressing these challenges requires a comprehensive strategy that integrates adaptive water management practices and stakeholder collaboration to ensure sustainable water access and mitigate the impacts of climate variability. The aim of this article is to analyze the challenges posed by climate change on water resources in Azerbaijan and propose strategies to enhance water resilience. The paper discusses how effective are existing water conservation policy in Azerbaijan, are and what effective solutions can be proposed to enhance water resilience in the face of scarcity under climate change. The research employs both quantitative and qualitative methodologies to comprehensively address various dimensions of water scarcity. Quantitative methods, including hydrological modelling and statistical assessments, enable an exploration of the tangible aspects of water availability and distribution, aiding in our understanding of the physical dynamics involved. In terms of ensuring water resilience in Azerbaijan during the analysis of changes in the volume of water taken from natural water sources was observed a decrease in the volume of water taken from surface water sources, an increase in the volume of water taken from groundwater sources. If the amount of extracting from water sources continues at the current rate, it is projected to reach 13.8 km3 in 2030, 14.8 km3 in 2040, and 15.8 km3 in 2050 in Azerbaijan.

CaRDS - the statewide California Residential water Demand and Supply open dataset

As water scarcity becomes the new norm in the Western United States, states such as California have increased their efforts to improve water resilience. Achieving water security under climate change, population growth, and urbanization requires an integrated multi-sectoral approach, where adaptation strategies combine supply and demand management interventions. Yet, most studies consider supply-side and demand-side management strategies separately. Water conservation efforts are mainly driven by policy requirements and publicly available data to assess the effectiveness of demand- and supply-side management policies is often hard to find and unstructured. Here we present CaRDS - the statewide California Residential water Demand and Supply open dataset. CaRDS encompasses nine years (2013-2021) of monthly water supply and demand time series for 404 water suppliers in California, USA, compiled from different open-access data sources. Access to detailed temporal and spatial water supply operations and demands at the state-level can be useful to researchers and practitioners to realize applications such as evaluating the effectiveness of water conservation policies and discovering regional differences in water resilience measures.

A validation workflow for treatment wetland performance data

ABSTRACT Treatment wetlands (TWs) effectively remove target pollutants and enhance urban water circularity and resilience. They constitute a prominent solution for urban wastewater treatment, thanks to their adaptability across various types of wastewater, scales and climatic conditions. However, the disparity in TW designs and the focus on a restricted set of variables applicable to research studies impede any comprehensive evaluation and comparison of TW performance. Our study introduces a methodology for data validation, in concurrently establishing a workflow specific to TW. This approach is aimed at defining the scope and relationships within the data, implementing checks and concatenating them into a quality flag, as an initial step towards building reliable statistical models. We underscore the importance of both mobilising comprehensive knowledge and identifying customary, yet implicit, choices intertwined in data processing. As for the application workflow, we collected and analysed data sourced from peer-reviewed papers on horizontal and vertical flow TW. Deficiencies were noted in key data elements like dimensions, concentrations and operational conditions. For the data analysis, relationships are highlighted between variables introduced for modelling purposes. These methodologies and workflows assess the quality of the data, in paving the way towards more dependable statistical models for TW design and implementation.

Conservation tillage: a way to improve yield and soil properties and decrease global warming potential in spring wheat agroecosystems.

Climate change is one of the main challenges, and it poses a tough challenge to the agriculture industry globally. Additionally, greenhouse gas (GHG) emissions are the main contributor to climate change; however, croplands are a prominent source of GHG emissions. Yet this complex challenge can be mitigated through climate-smart agricultural practices. Conservation tillage is commonly known to preserve soil and mitigate environmental change by reducing GHG emissions. Nonetheless, there is still a paucity of information on the influences of conservation tillage on wheat yield, soil properties, and GHG flux, particularly in the semi-arid Dingxi belt. Hence, in order to fill this gap, different tillage systems, namely conventional tillage (CT) control, straw incorporation with conventional tillage (CTS), no-tillage (NT), and stubble return with no-tillage (NTS), were laid at Dingxi, Gansu province of China, under a randomized complete block design with three replications to examine their impacts on yield, soil properties, and GHG fluxes. Results depicted that different conservative tillage systems (CTS, NTS, and NT) significantly (p < 0.05) increased the plant height, number of spikes per plant, seed number per meter square, root yield, aboveground biomass yield, thousand-grain weight, grain yield, and dry matter yield compared with CT. Moreover, these conservation tillage systems notably improved the soil properties (soil gravimetric water content, water-filled pore space, water storage, porosity, aggregates, saturated hydraulic conductivity, organic carbon, light fraction organic carbon, carbon storage, microbial biomass carbon, total nitrogen, available nitrogen storage, microbial biomass nitrogen, total phosphorous, available phosphorous, total potassium, available potassium, microbial counts, urease, alkaline phosphatase, invertase, cellulase, and catalase) while decreasing the soil temperature and bulk density over CT. However, CTS, NTS, and NT had non-significant effects on ECe, pH, and stoichiometric properties (C:N ratio, C:P ratio, and N:P ratio). Additionally, conservation-based tillage regimes NTS, NT, and CTS significantly (p < 0.05) reduced the emission and net global warming potential of greenhouse gases (carbon dioxide, methane, and nitrous oxide) by 23.44, 19.57, and 16.54%, respectively, and decreased the greenhouse gas intensity by 23.20, 29.96, and 18.72%, respectively, over CT. We conclude that NTS is the best approach to increasing yield, soil and water conservation, resilience, and mitigation of agroecosystem capacity.

Forest Treatment Effects on Watershed Responses Under Warming

AbstractThe effects of forest treatments on watershed hydrology have often been studied in isolation from climate change. Consequently, under a warming climate, it is unclear how forest thinning will impact snowpacks, evapotranspiration, and streamflow availability. In this study, we used a distributed hydrologic model to provide insight into the effects of warming and forest treatment on the hydrologic response of the Beaver Creek watershed (∼1,100 km2) of central Arizona. Prior to the numerical experiments, confidence in the hydrologic model performance was established by comparisons to long‐term observations (2003–2018) of snow water equivalent and streamflow using station observations and through spatially distributed estimates. Results indicated that warming during the 21st century could increase mean annual streamflow by 1.5% for warming levels up to +1°C, followed by a −29% decrease for continued warming up to +6°C, due to the varying effects of warming on snow sublimation, soil evaporation, and plant transpiration. On average, forest thinning increased streamflow by +12% (or 7 mm/yr) through lower plant transpiration by −19% (or −18 mm/yr), while also increasing the change in soil water storage by +42% (or 11 mm/yr). Forest thinning delayed the detrimental effects of warming on streamflow until +4°C, as compared to +2°C without forest treatment. Furthermore, model results suggested that forest cover reductions laterally displace water availability and evapotranspiration to downstream sites. These model‐derived mechanisms provide insights on the potential for water resilience toward warming effects afforded through treatment projects in southwestern US ponderosa pine forests.

Burnhope Reservoir: improving drawdown capabilities and water network resilience

A statutory inspection of Burnhope Reservoir completed under Section 10(3) of the Reservoirs Act 1975 noted that the 30 inch washout valve at the outlet tunnel portal had not been tested for some time. A measure in the interests of safety was to simply open and close the 30 inch washout valve over its full range to prove its operability. However, the washout valve is located on the outlet of the 40 inch supply main, which provides both a raw water supply to the water treatment works (WTW) and can also be used for emergency drawdown. Should the washout valve fail, the consequence would be a loss of pressure to the WTW, which would shut down. To maintain deployable output throughout the testing of the washout, its subsequent replacement and installation of a new free discharge control valve, a new 600 mm cross-connection pipeline was installed between the independent 40 inch supply/emergency drawdown main and 30 inch scour main. This cross-connection pipeline then removed the risk of interrupting the water supply and permitted the washout to be tested and subsequently replaced while also providing a resilient water network and much improved control of the 40 inch supply main drawdown asset.

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

&lt;p&gt;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.&lt;/p&gt;

Climate resilience of small-town water utilities in Eastern Ethiopia

Climate change threatens the safety of water supplies globally, but small water supplies in rapidly growing and urbanizing towns in low- and middle-income countries are especially at risk. Despite the efforts of the Government of Ethiopia, research shows that that small-town water utilities in Ethiopia are poorly equipped to prioritize developing and maintaining climate-resilient water services. We applied the How tough is WASH framework for climate resilient water supplies to ten town water utilities in Eastern Ethiopia to identify their strengths and weaknesses in preparing for climate change. We found reports of weak institutional support from service authorities and exclusion of climate risk management from trainings, which cascades down to service providers in the form of lack of emergency response, inadequate staffing and financial mismanagement. This is consistent with previous studies on sustainability of town water utilities, and highlights the applicability of this tool into existing monitoring frameworks that have been proposed for town water utilities in Ethiopia. We also modified the How tough is WASH framework to capture these findings and better reflect the complexity of a utility-managed piped water supply.

The New Dutch Water Defense Line (Nieuwe Waterlinie): Preserving Historical Qualities in a Context of Very High Spatial Pressure

The New Dutch Water Defense Line (Nieuwe Waterlinie): Preserving Historical Qualities in a Context of Very High Spatial Pressure

Marine Renewable-Driven Green Hydrogen Production toward a Sustainable Solution and a Low-Carbon Future in Morocco

Oceanic energy sources, notably offshore wind and wave power, present a significant opportunity to generate green hydrogen through water electrolysis. This approach allows for offshore hydrogen production, which can be efficiently transported through existing pipelines and stored in various forms, offering a versatile solution to tackle the intermittency of renewable energy sources and potentially revolutionize the entire electrical grid infrastructure. This research focusses on assessing the technical and economic feasibility of this method in six strategic coastal regions in Morocco: Laayoune, Agadir, Essaouira, Eljadida, Casablanca and Larache. Our proposed system integrates offshore wind turbines, oscillating water column wave energy converters, and PEM electrolyzers, to meet energy demands while aligning with global sustainability objectives. Significant electricity production estimates are observed across these regions, ranging from 14 MW to 20 MW. Additionally, encouraging annual estimates of hydrogen production, varying between 20 and 40 tonnes for specific locations, showcase the potential of this approach. The system’s performance demonstrates promising efficiency rates, ranging from 13% to 18%, while maintaining competitive production costs. These findings underscore the ability of oceanic energy-driven green hydrogen to diversify Morocco’s energy portfolio, bolster water resilience, and foster sustainable development. Ultimately, this research lays the groundwork for comprehensive energy policies and substantial infrastructure investments, positioning Morocco on a trajectory towards a decarbonized future powered by innovative and clean technologies.

Regionalization of GRACE data in shorelines by ensemble of artificial intelligence methods

Groundwater (GW) plays a crucial role in coastal aquifers and arid regions, serving as a lifeline for communities by providing a reliable and resilient water source, making its monitoring essential for sustainable water management. This study aimed at modeling GW via regionalization of the Gravity Recovery and Climate Experiment (GRACE) data based on two methods. The first method directly regionalized the GRACE data for modeling GW via in situ measurements, including the lake level, precipitation, temperature, observed GW and Penman-Monteith-Leuning (PML) evapotranspiration data. The second method included two stages, in the first stage, the GRACE data were downscaled via the Famine Early Warning Systems Network Land Data Assimilation System (FLDAS) data which contains satellite based precipitation, temperature, soil moisture, and snow water equivalent data. In the second stage, the downscaled GRACE was bias corrected to provide regionalized data. Artificial intelligence models consist of shallow networks (Feed Forward Neural Network (FFNN), Adaptive neuro fuzzy (ANFIS), Support Vector Machine (SVR)), the ensemble of shallow networks and Long-Short Term Memory (LSTM) deep learning method were employed in the modeling process and the observed GW level data were targeted for the regionalization. The Link CluE clustering ensemble method was implemented to cluster the piezometers of the aquifer to separate different GW patterns in the area. The proposed methodology was examined over the Miandoab plain, one of the sub-basins of the Lake Urmia, located in Northwest Iran. The modeling results demonstrated that the first method could exhibit superior performance with the Nash-Sutcliffe Efficiency (NSE) of up to 17% higher than the second method. Thus, using in situ observed data for downscaling proved to be more accurate than relying on the data based on the satellite imagery. The results indicated that the ensemble of shallow networks could lead to more precise results than using the deep and shallow learning models, individually, where the NSE for the ensemble of shallow networks was up to 50% higher compared to the LSTM model.

Drought intensification in Brazilian catchments: implications for water and land management

Droughts exert widespread impacts on both natural and social systems, and there is accumulating evidence that this situation may worsen in the context of global warming. Despite the importance of assessing changes in droughts to understand their potential future impacts on society, studies are unevenly distributed worldwide. In this study, utilizing bias-corrected CMIP6 simulations and a standard precipitation-evaporation index based approach, we quantified expected changes in future drought properties across 735 Brazilian catchments under SSP2-4.5 and SSP5-8.5 scenarios. Beyond evaluating the statistical properties of future droughts, we assessed their occurrence under both land use and water demand perspectives and propose a new framework to better understand their link with changes in long- and short-term conditions of precipitation ( P ) and potential evapotranspiration ( PET ). Our results indicate that drought events are projected to become more frequent and severe in the future, with high CMIP6 model agreement. According to the SSP5-8.5 scenario, at least half of Brazilian cropland and pasture areas will experience an increase of over 30% in drought properties by the end of the century. Furthermore, among the 85% of catchments expected to experience more severe droughts, nearly 90% are also projected to exhibit increased water demand, which will likely exacerbate future water scarcity. The investigation of the relationship between droughts changes and climate variables suggests that catchments with augmented droughts in the future will likely exhibit increased long-term average PET and P -variability, but not necessarily long-term average P . For instance, over 50% of evaluated Brazilian catchments are expected to experience an intensification of drought properties even with increases in Pmean . We believe this study may contribute (a) to improve Brazilian water resiliency by helping achieve the objectives of the National Water Security Plan and (b) to deepen our understanding of droughts in an uncertain future.

Assessment of Agricultural Drought Using the Normalized Difference Drought Index (NDDI) to Prediction Drought at Corong River Basin

As a complex and widespread natural phenomenon, drought poses a significant threat to the agricultural sector, especially in developing countries, resulting in significant economic losses. Its close relationship with water resilience and crop production necessitates sophisticated monitoring approaches for agricultural drought. Leveraging satellite remote sensing technology and various data types such as multispectral, thermal infrared, and microwave, can monitors drought on a large scale. This technology provides a comprehensive perspective for timely and spatial data collection, facilitating monitoring vegetation in vast agricultural areas. The study focuses on developing an agricultural drought model from 2017 to 2021, using Landsat 8 imagery. The model integrates the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI), resulting in the establishment of the Normalized Difference Drought Index (NDDI) method. To predict agricultural drought in the Corong River Basin, the study employs the Seasonal Autoregressive Integrated Moving Average (SARIMA) model. Findings reveal varying degrees of dryness in the Corong River Basin, with 77% categorized as Strong dry conditions, 1% as Dry, 0.3% as Moderate wetness, and 21.6% as wetness. Drought predominantly occurs between July and October, impacting approximately 78% of the total dry area and extending across almost the entire region. The SARIMA (0,0,1)(3,0,0)12 model, with a MAPE value of 0.2399, emerges as the most effective for predicting agricultural drought. These forecasted results provide critical insights into the level of agricultural drought in the Corong River Basin and valuable information for drought mitigation strategies, especially in regulating the distribution of irrigation water.

Conjunctive management of groundwater and surface water resources using a hybrid simulation–optimization method

ABSTRACT This study aimed to determine the optimal conjunctive utilization of groundwater and surface water resources in the Halil River basin, one of the most significant study regions in Kerman Province (Iran). Multi-verse optimizer (MVO) and the ANFIS (adaptive neuro-fuzzy inference systems) simulation model, known as the MVO–ANFIS simulation–optimization model, were used for this purpose. Moreover, the optimal exploitation policy for the studied basin was presented. The ANFIS model yielded a coefficient of determination greater than 0.99 in Baft, Rabor, and Jiroft. This model had a high capability to simulate groundwater levels in these three regions. Therefore, the ANFIS model was adopted as the simulation model to predict the aquifer water table in these regions. Regarding the conjunctive utilization of groundwater and surface water resources, the exploitation policy resulting from the MVO–ANFIS simulation–optimization model had a desirable performance by supplying 91.70, 87.75, and 97.58% of the total demands of Baft, Rabor, and Jiroft, respectively. Moreover, results of water system performance indicators, including reliability (82.96, 72.65, 95.07), resiliency (70, 53.47, 80), vulnerability (29.54, 25.64, 17.02), and sustainability (74.24%, 66.10%, 85.78%) in the mentioned regions, respectively, showed the appropriate performance of the proposed model for the simulation–optimization problem.

Water resiliency score – Is relying on freshwater to generate electricity a good idea?

One commonly-used argument against fluctuating renewables is their unpredictability. In contrast, thermal power generation and hydropower are regularly presented as reliable and dispatchable. However, droughts and floods can render useless the share of the power generation infrastructure that directly depends on freshwater. In this work, the global power sector is analysed from an energy-water nexus perspective to evaluate its reliability in case of severe water scarcity on a per-power plant basis, proposing a new method for combining it with water stress scores. At a country level, known individual thermal and hydropower plants are paired with regional water stress projections from 2020 to 2030 and their water source as a bottom-up approach to account for the capacities at risk and identify the points where water dependence could render a power system unreliable. The results show that, globally, about 65 % of generating capacities are directly freshwater-dependent. Moreover, the share of capacities placed in the low-resiliency group increases from 9 % of the total installed in 2020 to over 24 % in 2030 in all scenarios. The findings could help guide the development of the global power sector towards a less water-dependent system and accelerate the deployment of low water-demand power generation technologies.

Visualising the Complexity of Drought: A Network Analysis Based on the Water Resilience Assessment Framework and the Actor-Relational Approach

This paper discusses the increasing severity of droughts due to climate change. It emphasises the complexity of defining drought and the diverse perspectives among stakeholders. Lots of stakeholders with unclear responsibilities are involved, which can lead to uncertainty and indecisiveness in addressing the issue. To tackle this, the present paper proposes a methodology to dissect drought systems and reveal the intricate relationships between their components. This approach combines a comprehensive definition of drought with the “Water Resilience Assessment Framework” and an “Actor-Relational Approach”, visualised through network analysis. The methodology was applied to a case study situated in the Leie Basin of Flanders, Belgium. By employing this strategy, policymakers and mediators can gain a deeper understanding of drought, identify its root causes, and prioritise necessary changes for more effective drought and water management.

Innovative Machine Learning Applications in Non-Revenue Water Management: Challenges and Future Solution

The escalating global concerns surrounding Non-Revenue Water (NRW) necessitate a paradigm shift in water management strategies, and innovative machine learning (ML) applications emerge as a transformative solution. This paper investigates the intersection of ML and NRW management, recognizing the pressing need to curb water losses due to leaks, theft, and inaccuracies. As water utilities grapple with the economic and environmental repercussions of NRW, this paper explores the potential of ML algorithms, such as predictive analytics to revolutionize traditional approaches. The discussion encompasses the intricate landscape of challenges, including data quality issues, model interpretability, and the inherent complexity of implementation. Recognizing the multidisciplinary nature of these challenges, the journal emphasizes the collaborative efforts required to harmonize technological innovation with practical implementation. As the world confronts the imperative to optimize water resources, this paper posits that innovative ML applications present a pivotal opportunity to not only enhance the accuracy and efficiency of NRW management but also to foster a more sustainable and resilient water infrastructure. Through a comprehensive grasp of challenges and a proactive pursuit of remedies, stakeholders can establish sustainable, resilient, and equitable water management systems. This paper acts as a valuable reference, providing a detailed discussion encompassing Europe, China, Japan, South Korea, and specific states within Malaysia, with a specific focus on non-revenue water (NRW) systems.