Tag: environment

Integrating water quality and water quantity to diagnose the health of water metabolism systems in multi-core multi-level urban agglomerations

Author links open overlay panelYing Yang a1

, Jing Wen a1

, Meirong Su b

, Qionghong Chen cShow moreAdd to MendeleyShareCite

https://doi.org/10.1016/j.watres.2025.123899Get rights and content

Highlights

  • •The MRIO table was compiled for a multi-core multi-level urban agglomeration.
  • •A diagnostic framework was established by coupling ENA and MRIO approaches.
  • •Water quantity-water quality linkage was considered in the diagnostic framework.
  • •The IWMN was less vigorous and less organized than the QWMN.
  • •The IWMN tended slightly towards mutualism but had more negative collaborations.

Abstract

Urban agglomerations (UAs) are compelled to scrutinize the health of their water systems as the frequency of water crises increases. An urban water system’s health is closely related to metabolism processes. To date, water systems in multi-core multi-level UAs have not been analyzed using water quantity and water quality because of methodological constraints. To address this research gap, we developed an integrated water quality–water quantity model for diagnosing water metabolism systems that could process nested multi-region input-output (MRIO) tables. We coupled the MRIO tables and established two networks, an integrated water quantity–quality metabolism network (IWMN) and a water quantity metabolism network (QWMN). We tested the two networks with data from the Guangdong-Hong Kong-Macao UA and assessed four aspects of the networks’ health, namely vigor, organization, resilience, and collaboration, using ecological network analysis. We discovered that IWMN exhibited lower vigor (internal circulation 10.4 %) and organization dominated by dependency (total contribution intensity σ = -23) compared to the QWMN. Polity-driven disparities shaped the robustness distribution, while a mutualism tendency coexisted with a complex exploitation relationship (52.4 %), particularly in the core large-sized city of Hong Kong, where 58 new competitive pairs emerged. Thus, we recommend prioritizing Guangdong-Hong Kong-Macao trade optimization for high-water-content products to enhance system health.

Graphical abstract

Image, graphical abstract

Introduction

The surface water deficit experienced in 482 of the world’s largest cities is projected to reach 6.75 million tons by 2050 because of an imbalance between the water supply and the demand (Flörke et al., 2018). This trend has prompted growing interest in resource allocation and environmental protection within urban agglomerations (UAs). UAs are composed of multiple geographically adjacent cities with diverse sizes and characteristics (Fang et al., 2015). Diverse UAs with multi-core structures (classified by comprehensive urban engine functions) and multi-level systems (quantified by social indicators) face challenges due to high heterogeneity in population size and spatial resource allocation (Han et al., 2019; Chirigati, 2022; Zhao et al., 2021). Water quantity and water quality are important attributes of water resources. Changes in the water quantity caused by a lack of rainfall or heavy rainfall events affect the water quality by concentrating pollutants or diluting. Conversely, degraded water quality diminishes the availability of water resources (Li et al., 2023) and has direct effects on urban aquatic ecosystems (Liu and Yang, 2012). Therefore, to optimize water management in multi-core multi-level UAs, we need to know more about the combined effects of water quality and water quantity on the water resources.

When optimizing water management in urban areas, the water metabolism mechanism of the system should be analyzed, and key issues should be identified (Cao et al., 2021; He et al., 2020b; Liu et al., 2022). The concept of water metabolism originates from urban metabolism (Wolman, 1965), which describes water cycle processes (e.g., water input, output, and storage) driven by social activities in different cities (Wang and Chen, 2010). This concept can effectively identify hidden risks resulting from the allocation of social resources—such as population, industry and environment within UAs, thus challenging the traditional multilevel paradigm of urban water management. In assessing the health of water systems based on water metabolism mechanisms, processes analogous to those in natural ecosystems, such as vigor and collaboration (Y.J. Yang et al., 2020; Zhu et al., 2020), sustained and stable organization, and adaptability to external pressures (Yan et al., 2014), are employed. However, to date, most research has primarily focused on the efficiency of consumptive activities (Nishimura et al., 2021; Qi et al., 2021; Xu et al., 2020), while ignoring the underlying water metabolism processes.

Network methods are effective for characterizing critical resource metabolism processes (Liang et al., 2020). Ecological Network Analysis (ENA) (Hannon B, 1973) quantifies metabolic features via resource fluxes (Fath, 2004; Ulanowicz et al., 2009), offering insights into system health. For example, resource footprint circulation rates reflect node vigor; balanced control-dependency relationships enhance organizational capacity; maintaining metabolic orderliness optimizes resilience thresholds; and niche complementarity indices help analyze co-evolutionary collaboration. There is concern about the approaches used to quantitatively assess the resource flows within a network. A bottom-up approach uses industrial processes to track water flows (Vanham and Bidoglio, 2013), but a top-down approach quantitatively assesses the resource flows within a network (Feng et al., 2011). For example, input-output analysis (IOA), an accepted method for quantifying water flows in a water metabolism system, is preferred over bottom-up approaches because it can link industrial economic data to water consumption using input-output tables and produce a high-resolution view of the networked water flow transactions, helping us to address issues caused within UAs by economic trade, such as water-related resource flows, ecosystem services, and health status (Hubacek and Feng, 2016). However, our ability to carry out a comprehensive and accurate assessment of water system health within UAs is hampered by a lack of high-resolution MRIO data for multi-core multi-level UAs, which has resulted from the poor alignment of statistical standards used for trade data across cities of different levels.

To date, there is little clarity about how the combination of water quantity and water quality influences the health of water metabolism systems in UAs. Cao et al. (2021) were the first to evaluate the health of water networks using an assessment model that focused on water quantity, but excluded water quality. Adequate water quantity and sufficient water quality are essential for the sustainable use of urban water resources (Cai et al., 2023). A water footprint, which incorporates both water quantity and water quality, can be used to assess water flows (Hoekstra and Mekonnen, 2012). Various water footprints have been defined, and the blue water footprint (BWF) and grey water footprint (GWF) have been used to quantify both water quantity and water quality (Chapagain and Hoekstra, 2011; Yu et al., 2022). In previous studies, researchers have focused on either water quantity or water quality when assessing the intensity of resource transfers (Cai et al., 2023; Zhao et al., 2016) and the factors that influenced them (Cai and Guo, 2023; Guan et al., 2014). Some researchers have also simulated and evaluated the performance of metabolism systems using either water quantity or water quality as the independent metabolism medium (He et al., 2020b, 2020a; Liu et al., 2022). The conventional separation of water quantity and quality in current research paradigms makes it difficult to reveal the cascading effects of their synergistic interactions on multiscale metabolism systems, which may lead to ecological cognitive bias in system health assessments. As synergistic variables within regional metabolism system, the mechanisms underlying the interactions between water quantity and water quality remain underexplored. It is imperative to conceptualize water quantity and quality as an integrated metabolism medium and develop a corresponding theoretical framework to elucidate how their synergistic metabolic processes influence system health.

The diagnoses of water metabolism system health at the UA scale are constrained by a) a lack of MRIO tables, which hinders the accurate assessment of water flow within UAs with multi-core and multi-level cities, and b) a limited understanding of how the health of metabolism systems is influenced when water quantity and water quality are combined into a single metabolism medium. To address these issues, we proposed a method for compiling MRIO tables for multi-core multi-level UAs that resolved the methodological limitations associated with assessments of water flow. We created two networks based on MRIO and ENA, one that integrated water quantity and water quality and another for water quantity only, and assessed four attributes of the health of the two networks, namely vigor, organization, resilience, and collaboration. We then tested the method with data from the Guangdong-Hong Kong-Macao Greater Bay Area UA (GBA).

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https://www.sciencedirect.com/science/article/abs/pii/S0043135425008073?via%3Dihub

Influence of particulate matter air quality on water quality of atmospheric water harvesting

Author links open overlay panelMatthew Russell ab

, Alex Webster c

, Carl Abadam bd

, Katelin Fisher b

, Stephanie Campbell bd

, Carmen Atchley bd

, Kana Radius bd

, Paris Eisenman bd

, Ashley Apodaca-Sparks bd

, Astrid Gonzaga bd

, Rui Liu e

, Patrick Hudson f

, Anjali Mulchandani abdShow moreAdd to MendeleyShareCite

https://doi.org/10.1016/j.watres.2025.124213Get rights and content

Under a Creative Commons license

Open access

Abstract

Atmospheric water harvesting (AWH) is a decentralized water technology that dehumidifies air to provide water. When atmospheric water is condensed, other atmospheric particles and gases can enter the liquid water. For AWH to serve as drinking water, it is necessary to understand how these air constituents interact with water as it condenses and the resulting water quality. The objectives of this research were to determine: i) the variation of measured air and water quality contaminants at two sites, and ii) the extent of interaction between particulate matter concentration in the air and the water quality of atmospherically harvested water. This study performed AWH using compressor dehumidifiers at industrial and urban ambient air quality monitoring sites in Albuquerque, New Mexico, USA. Air contamination was greater at the industrial site compared to the urban site (range PM2.5 urban 1.3 – 33.4 μg/m3, industrial 1.8 – 127.5 μg/m3; range PM10 urban 3.7 – 99.2 μg/m3, industrial 4.4 – 1525 μg/m3). Water trace metals concentrations and turbidity were also greater at the industrial site. Aluminum concentrations ranged 22.9 – 600 μg/L (urban) and 22.1 – 1560 μg/L (industrial); Iron ranged 0.5 – 363 μg/L (urban), 3.4 – 828 μg/L (industrial); Manganese ranged 0.7 – 23.7 μg/L (urban), 1.3 – 69.2 μg/L (industrial); and turbidity ranged 0.3 – 28 NTU (urban), 0.5 – 52 NTU (industrial). Water quality exceeded U.S. EPA regulations for aluminum (39 % of samples at urban site, and 90 % of samples at industrial site > 200 µg/L) and turbidity (96 % at urban site, 100 % at industrial site > 0.3 NTU). A linear mixed-effects statistical model showed water quality was a function of air quality, but for only some parameters. At the industrial site, there was a strong positive relationship between PM2.5 and some metals (aluminum, calcium, iron [p<0.05]), and marginal significance with other metals (potassium, zinc [p<0.1]). At the urban site, there was only a strong positive relationship between PM2.5 and calcium. Large variations in PM concentrations and site differences in their characteristics could play an important role in how much of metals in the air enters atmospherically harvested water. Findings from this study can guide research on understanding if air quality can be used to predict AWH water quality, provide insight to further understand the mechanisms of interaction between gas-phase water and particles as they move from the air to condensed water, and drive treatment decisions to meet water quality goals.

Graphical abstract

Image, graphical abstract

Keywords

Dehumidification

Condensation

Aerosols

Water vapor

Pollutants

1. Introduction

Global warming and the increased variability and intensity of natural disasters (e.g., floods, droughts, wildfire) are a continuing concern to water supplies. Any of these natural disasters can impact municipal water supplies and limit access for weeks to months. The atmosphere is an alternative freshwater reservoir that contains 12,900 km3 of water (Shiklomanov, 1991), is universally accessible, and can serve as a water source when other supplies are inaccessible. Atmospheric water harvesting (AWH) can condense this available water vapor to provide access to water for communities in need during emergencies (Gayoso et al., 2024; Mulchandani and Westerhoff, 2020).

There are few studies on AWH water quality, and the relationship between air quality and water quality has only been minimally investigated for both condensation and sorption-based systems (Mulchandani et al., 2022; Zeng et al., 2024). These AWH water quality studies are often performed at a single site for around 12 months (Mulchandani et al. 2022), while few have studied AWH across multiple sites and months (Xia et al., 2015). These studies find turbidity, aluminum, iron, and manganese concentrations above United States Environmental Protection Agency (U.S. EPA) and World Health Organization (WHO) drinking water regulations in untreated AWH water, and aluminum and iron above regulatory values in treated AWH water (Zeng et al., 2024). As more studies are performed, it is apparent that there may be large variability in concentrations of metal and organic contaminants over space and time. The concentration of these contaminants may be impacted by variability in air quality, but this influence is not well studied. Xia et al. (2015) studied the relationship between particulate matter (PM) and ion contaminants in condensation-based atmospherically harvested water and found high concentrations of Cl–, SO42-, NH4+ and Ca2+ in industrial areas associated with soil dust and exhaust. This study was performed in a temperate climate (relative humidity ranged 60–80 %), and it is unknown whether these results are transferable or universal for all climate zones and pollution sources, specifically those experienced in more arid regions. For AWH to be considered a viable drinking water source in multiple regions, more data is needed to understand the extent and nature of air quality influence on AWH water quality. Spatial and temporal analysis across environments (e.g., arid with heavy agricultural and urban emissions sources, vs humid with heavy industrial emissions) is needed to determine the full range of potential water quality.

Air quality is influenced by natural and anthropogenic emissions of trace gases and aerosols as well as meteorological factors such as temperature, wind speed, and humidity. As such, air quality can vary across a geographic region and changes throughout the day (Hosein et al., 1977). The U.S. EPA classifies and measures outdoor air pollution by 6 criteria pollutants: ozone (O3), carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), lead (Pb) and particulate matter (PM) pollution (US EPA, 2015a). Of these pollutants, PM may be most likely to influence chemical makeup of AWH water quality due to the interaction between PM and gas phase water in the atmosphere.

Fig. S1 shows how PM and gas-phase water interact in the atmosphere. PM is formed through nucleation, accumulation and coarse modes. In nucleation mode, particles are freshly formed through combustion or atmospheric reactions from emissions sources such as traffic, industry and burning (EPA, 2023). These particles grow through coagulation with water vapor and other constituents to get to accumulation mode. As small particles stick together, the total particle number decreases, and the mass and surface area of each coagulated particle increase. Lastly, coarse mode generally consists of mechanically separated particles that may be resuspended from surfaces. PM is classified as fine (<2.5 m) and coarse (<10 m) and is often made up of clusters of different constituents depending on the emissions that influence the air quality (EPA, 2019). PM2.5 typically contains crustal material comprising of metal compounds (Al, Cu, Fe, K, Mn, etc.), soil, small liquids, elemental carbon, volatile organic compounds and various ions (SO42- and NO3–) (Chemical Elements, Minerals, Rocks, 2024; EPA, 2023; Hasheminassab et al., 2014). PM10 is typically produced by surface abrasion, sea spray, biological materials, and road, crop and livestock dust (EPA, 2023). Water vapor in the air continue to interact with particulates, which may partition with water vapor into condensed AWH waters. We theorize that when this water vapor condenses within an AWH system, particles of all sizes from various sources (e.g., traffic, industry and burning) containing constituents such as metals, carbon and gases will be collected in the harvested water and impact water quality.

Currently, there is a knowledge gap regarding the relationship between PM concentrations and characteristics, and subsequent water quality of AWH, particularly as it varies by space and time to determine site specific impacts. These relationships may vary as a function of location, climate, and air quality. Closing this gap can provide key insight on the level and type of treatment required to make AWH a viable drinking water source. If there is a significant relationship between air quality measured as PM and water quality, air could be pre-filtered to remove PM before harvesting. Alternatively, post-harvesting water treatment may be applied to remove both particles and dissolved constituents.

The objectives of this research were to determine: i) the variation of measured air and water quality contaminants by site, and ii) the extent of interaction between particulate matter concentration in the air and the water quality of atmospherically harvested water. Condensation-based AWH devices were operated in a semi-arid high-desert metropolitan city. AWH devices were co-located with air quality monitoring instrumentation to directly compare air quality with AWH water quality. The air was not pre-filtered, and AWH water samples were not filtered or treated in order to gain a full understanding of the impact of PM on water quality. We hypothesized that air pollution and AWH water pollution would be greater at the industrial site compared to the urban site. Secondly, we hypothesized that there would be a positive linear relationship between both PM10 and PM2.5 and total organic carbon and metal concentrations, the nature of which may be specific to each site. Findings from this study can guide research on understanding if PM can be used to predict AWH water quality, provide insight to further understand the mechanisms of interaction between gas-phase water and particles as they move from the air to condensed water, and drive treatment decisions to meet water quality goals.

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https://www.sciencedirect.com/science/article/pii/S0043135425011200?via%3Dihub

Assessment of water quality and health hazards using water quality index and human health risk evaluation in district Talagang Pakistan

Scientific Reports volume 15, Article number: 5191 (2025) Cite this article

Abstract

This work was carried out for the determination of the water quality in the Talagang District of Pakistan, as water is essential for agriculture and drinking uses. This study aims to assess the water quality for irrigation, drinking, and health risks using the Water Quality Index (WQI) and Human Health Risk Assessment (HHRA) tools to identify regions with contaminated water, and to evaluate the associated risks. A total of 98 water samples were taken at various points from diverse sources such as hand pumps, streams, springs, dug wells, and tube wells for physio-chemical assessment. In the current study, the effectiveness of the irrigation water quality index (IWQI), human health risk assessment (HHRA), and water quality index (WQI) tools have been assessed. The characteristics of subterranean water are influenced by evaporation, ion exchange, rock-water interaction, and parent-rock weathering, as shown by the Piper and Gibbs diagram. According to the WQI results, the water quality is 20. 89% and 27.46% of the sample sites are moderate and poor, making them unfit for human intake. Based on HHRA, compared to adult males and females in the study area, children are deemed to be at a higher risk. A larger number of the sample localities are appropriate for irrigation purposes. The study assists in identifying contaminated regions and in monitoring newly implemented remediation actions to manage the source of contaminants in the study area.

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Evaluation of water quality index and geochemical characteristics of surfacewater from Tawang India

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Introduction

Surface and subterranean water are essential sources of drinking, farming, industrial, and domestic uses worldwide and also have a substantial effect on shaping the quality of lives and sustainability of societies1. Due to rapid growth and population increase, natural and human actions such as industry, urbanization, mining, and agriculture have resulted in water depletion and impairment issues2,3. Water quality degradation and depletion have emerged as significant global challenges, directly impacting public health, agriculture, and the environment4,5. The poor quality of water poses both direct and indirect health risks to the communities that rely on it, often leading to substantial public health issues and increased costs for water treatment and rehabilitation6. Direct health risks are associated with the consumption of contaminated water, such as heavy metal contamination, which can cause serious illnesses7,8. Indirect health risks occur when contaminated water is used for irrigation, affecting agricultural crops, horticulture, and aquaculture, leading to bioaccumulation of toxins in the food chain9.Heavy metals including Zn, Cu, and Mn are naturally occurring in water in trace amounts and are significantly essential for human metabolism and the growth of living things10. However, excessive amounts of these metals pose chronic and acute health issues. Other heavy metals including Pb, Cd, As, Cr, and Ni are severely toxic although in very low concentrations11. For example, the higher concentration of Pb is known to harm the development of the brain in children. Exposure to elevated concentrations of Cd causes chronic and acute diseases such as skeletal and kidney damage. The As causes many health problems in humans such as skin lesions, and cancer of the liver, brain, stomach, and kidney12,13. Higher intakes of Cr and Ni have been linked with liver, kidney, and heart problems14. The WQI is a handy means for evaluating the quality of water that is appropriate for residential practice. The weighted arithmetic and integrated WQI are extensively used in India for assessing surface and subterranean water because it yield results with greater accuracy1516. investigatedthe chemistry and quality index of groundwater in northwest China and noticed that 11.43% of sample locations had poor water quality, and 17.14% had very poor water quality. Similarly17, used weighted overlay analysis to assess groundwater quality for drinking and irrigation purposes in Bangladesh, revealing that 90% of water from deep wells and 57.6% from shallow wells were suitable for human consumption, according to the Drinking Water Quality Index (DWQI).

Several recent studies have employed various techniques to assess water quality, including the use of WQI, which integrates multiple physicochemical variables into a single dimensionless value representing overall water quality18,19,20,21,22. The WQI is an assessment model that can be used for integrating a variety of physicochemical variables into a dimensionless value that may depict the overall quality of the water18,20. n Pakistan, water quality contamination has been reported in several regions, affecting both surface and groundwater resources11. Given the importance of water for human health, agriculture, and overall well-being, it is crucial to evaluate the water quality in various regions. The primary objective of this study is to assess the surface and subsurface water quality for irrigation, drinking, and health risks in Talagang District, Pakistan, using the Water Quality Index (WQI) and Human Health Risk Assessment (HHRA) tools. This research aims to evaluate the hydro-chemical parameters of groundwater in the study area for both irrigation and drinking purposes, and to assess the associated health risks using the WQI and HHRA models. The findings will contribute to identifying areas where water quality poses health risks and help in formulating strategies for water management and remediation.

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https://www.nature.com/articles/s41598-025-89932-y?

Health risk assessment of groundwater use for drinking in West Nile Delta, Egypt

Scientific Reports volume 15, Article number: 7414 (2025) Cite this article

Abstract

Human health is at risk from drinking water contamination, which causes a number of health problems in many parts of the world. The geochemistry of groundwater, its quality, the origins of groundwater pollution, and the associated health risks have all been the subject of substantial research in recent decades. In this study, groundwater in the west Rosetta Nile branch of the Nile Delta Aquifer is examined for drinking potential. Numerous water quality indices were applied, such as water quality index (WQI), synthetic pollution index (SPI) models, and health risk assessment (HRA) method. The limits of the measured parameters are used to test its drinking validity on the basis of WHO recommendations. TDS in the southern regions is within the desirable to allowable limits with percent 25.3% and 29.33%, respectively. Nearly all the study area has desirable value for HCO3, Al and Ba. Ca and Mg have desirable values in the center and south portion of the investigated area, whereas in the north are unsuitable. Na, Cl and SO4 fall within the desired level in the regions of the south but become unsuitable towards the north. Mn and NO3 are inappropriate except in the northwestern part. Fe is within suitable range in the southwestern and northwestern regions. Pb, Zn, Cu, and Cd were undetected in the collected samples. Regarding to WQI the study area is classified into 4 classes good, poor, very poor and unfit for drinking water from south to north. According to SPI model, 20%, 18.7%, 18.7%, 8% and 34.6% of water samples are suitable, slightly, moderately, highly polluted and unfit, respectively from south to north. Based on HRA, Children are the most category endangered with percent 14.7% of the overall samples obtained, followed by females and males with percent 12% and 8%, respectively. This study offers insights into the conservation and management of coastal aquifers’ groundwater supplies. These findings have significant implications for developing strategies and executing preventative actions to reduce water resource vulnerability and related health hazards in West Nile Delta, Egypt.

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Introduction

In recent years, rapid urbanization and population growth, stress on natural resources, and global climate change have caused the demand for water to increase. Sustainable water resource management is becoming increasingly important to meet this demand. It is critical to manage water resources globally since groundwater is essential for meeting human needs and for sustaining life1,2,3,4. Furthermore, unregulated exploitation of groundwater resources has resulted in water shortages over recent decades, which has adversely affected groundwater quality and levels5,6,7,8,9,10. Salinization is a significant issue in many coastal regions globally, particularly in semi-arid and arid areas. It is seen as a crucial and visible issue that threatens future water resources and reduces water quality. Groundwater salinization is a key concern because it restricts water availability for both agricultural and urban needs, impacting the resilience and sustainability of coastal areas. An increase in total dissolved solids (TDS) or chloride (Cl) levels is a clear indicator of salinization11,12,13. The issue of water quality has garnered significant attention in coastal aquifers worldwide due to the aforementioned reasons for example, Thriassion Plain and Eleusis Gulf, Greece14, north Kuwait15, China15, Bangladesh16, Spain17, Mexico18, and others. As groundwater quality is equally important as its quantity, it is crucial to carefully assess it.

Heavy metals pose a toxic threat to human health and ecosystems when their concentrations surpass established limits as they can disrupt ecological systems, endanger human health, and worsen the quality of groundwater. Specific heavy metals, including copper (Cu), zinc (Zn), manganese (Mn), and chromium (Cr), are vital for metabolic processes in traces quantity, but become hazardous at high levels. In contrast, metals such as cadmium (Cd) are toxic even at minimal concentrations19,20. Tackling the presence of trace element-contaminated water resources is crucial for protecting both the ecosystem and human health21. Additionally, understanding the environmental behavior of these trace elements, including their transfer, fate, persistence, and the health risks they pose to consumers through the food chain, is vital. The health impacts of these elements are significantly influenced by factors such as their behavior, specific chemical composition, and binding state. Gaining insight into these factors is the key to assessing the potential risks of trace elements and devising effective strategies to minimize their harmful effects22,23. Controlling and mitigating these harmful effects can be achieved by monitoring heavy metal distribution, concentration, and health risks regularly.

Evaluating groundwater quality is a fundamental approach for ensuring the sustainable management of this essential resource. Various methodologies have been employed to assess groundwater quality, including stoichiometric, graphical, index-based, and inferential chemometric techniques, which are commonly used to analyze and monitor groundwater conditions and hydrogeochemical properties24,25,26. Additionally, advanced tools such as clustering, regression analysis, neural networks, and machine learning algorithms have been incorporated to observe and predict water quality trends effectively27,28,29. Given the variety of hydrochemical criteria, the water quality index (WQI) technique serves as an effective tool for evaluating groundwater quality. Due to its comprehensive calculation method, assessing groundwater quality through multiple hydrochemical parameters is considered a more reliable and robust approach. As a result, WQIs have been widely utilized in groundwater quality assessments. The most frequent techniques for assessing water quality are the WQI for drinking and synthetic pollution index (SPI). The Water Quality Index (WQI) for drinking water and the Synthetic Pollution Index (SPI) are effective tools for measuring and evaluating overall water quality, offering a more comprehensive approach than traditional techniques for evaluating the quality of water. Each of the two types of standard water quality index models (WQI and SPI) measure the cumulative impact of different physicochemical variables on groundwater quality based on weight and rate. Each physicochemical parameter is weighed according to its influence on drinking water quality30,31. Since many people rely on groundwater for drinking and other household purposes, high levels of nitrate in drinking water can result in serious health risks32,33,34. Therefore, health risk assessment (HRA) based on nitrate concentration was applied as drinking water quality criteria35,36,37. Combining water quality indices with GIS techniques provides the most effective method for detecting and visualizing changes in groundwater facies. Several studies have applied water quality indices (WQI and SPI) and HRA methods to evaluate groundwater quality for human use in various regions, and these techniques have proven successful. For instance, studies have been conducted on Makkah Al-Mukarramah Province (Saudi Arabia)38, coastal plain in Nigeria23, dumpsite in Awka (Nigeria)22, El Fayoum depression (Egypt)30, El Kharga Oasis (Egypt)39, and Central Nile Delta Region (Egypt)40.

The quaternary aquifer, coastal aquifer, is considered the main source of groundwater in the area west of Rosetta branch. Based on the previous studies, the groundwater within the study area exposed to several factors, which may lead to increase signs of groundwater quality deterioration. These factors are mainly attributed to anthropogenic activities and sea water intrusion12. Moreover, most previous studies conducted west of the Nile Delta have primarily focused on the morphological and geological features of the terrain41,42,43,44. Additionally, water sources have been examined in terms of their geochemical properties and suitability for irrigation purposes8,12,45,46. However, limited attention has been given to evaluating the quality of groundwater for drinking purposes within the study area. As a result, significant knowledge gaps remain regarding the suitability of groundwater for human consumption in this region.

Based on the aforementioned objectives, this study aimed to evaluate the quality of groundwater for drinking purposes in the region west of the Nile Delta’s Rosetta branch. This study was conducted to develop geospatial maps of physicochemical parameters in groundwater to determine the quality suitability of drinking water. Furthermore, in order to assess the water quality from the aspect of human health, two typical water quality index models are used, namely water quality index (WQI) and synthetic pollution index (SPI). In order to analyze the data concerning water quality, descriptive statistics and correlation matrices were applied. Eventually, human health risk (HRA) was assessed in the study region via contaminated water consumption by adults (males and females) and children. It is expected that this study will assist decision makers in identifying vulnerable zones and optimizing monitoring networks for groundwater quality.

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https://www.nature.com/articles/s41598-025-90477-3?

Machine Learning Predicts Highest-Risk Groundwater Sites to Improve Water Quality Monitoring

 Matt Shipman  

illustration shows a digital screen displaying data related to groundwater quality

For Immediate Release

Yaroslava Yinglingyara_yingling@ncsu.edu

Paul Westerhoffp.westerhoff@asu.edu

Matt Shipmanmatt_shipman@ncsu.edu

An interdisciplinary team of researchers has developed a machine learning framework that uses limited water quality samples to predict which inorganic pollutants are likely to be present in a groundwater supply. The new tool allows regulators and public health authorities to prioritize specific aquifers for water quality testing.

This proof-of-concept work focused on Arizona and North Carolina but could be applied to fill critical gaps in groundwater quality in any region.

Groundwater is a source of drinking water for millions and often contains pollutants that pose health risks. However, many regions lack complete groundwater quality datasets.

“Monitoring water quality is time-consuming and expensive, and the more pollutants you test for, the more time-consuming and expensive it is,” says Yaroslava Yingling, co-corresponding author of a paper describing the work and Kobe Steel Distinguished Professor of Materials Science and Engineering at North Carolina State University.

“As a result, there is interest in identifying which groundwater supplies should be prioritized for testing, maximizing limited monitoring resources,” Yingling says. “We know that naturally occurring pollutants, such as arsenic or lead, tend to occur in conjunction with other specific elements due to geological and environmental factors. This posed an important data question: with limited water quality data for a groundwater supply, could we predict the presence and concentrations of other pollutants?”

“Along with identifying elements that pose a risk to human health, we also wanted to see if we could predict the presence of other elements – such as phosphorus – which can be beneficial in agricultural contexts but may pose environmental risks in other settings,” says Alexey Gulyuk, a co-first author of the paper and a teaching professor of materials science and engineering at NC State.

To address this challenge, the researchers drew on a huge data set, encompassing more than 140 years of water quality monitoring data for groundwater in the states of North Carolina and Arizona. Altogether, the data set included more than 20 million data points, covering more than 50 water quality parameters.

“We used this data set to ‘train’ a machine learning model to predict which elements would be present based on the available water quality data,” says Akhlak Ul Mahmood, co-first author of this work and a former Ph.D. student at NC State. “In other words, if we only have data on a handful of parameters, the program could still predict which inorganic pollutants were likely to be in the water, as well as how abundant those pollutants are likely to be.”

One key finding of the study is that the model suggests pollutants are exceeding drinking water standards in more groundwater sources than previously documented. While actual data from the field indicated that 75-80% of sampled locations were within safe limits, the machine learning framework predicts that only 15% to 55% of the sites may truly be risk-free.

“As a result, we’ve identified quite a few groundwater sites that should be prioritized for additional testing,” says Minhazul Islam, co-first author of the paper and a Ph.D. student at Arizona State University. “By identifying potential ‘hot spots,’ state agencies and municipalities can strategically allocate resources to high-risk areas, ensuring more targeted sampling and effective water treatment solutions”

“It’s extremely promising and we think it works well,” Gulyuk says. “However, the real test will be when we begin using the model in the real world and seeing if the prediction accuracy holds up.”

Moving forward, researchers plan to enhance the model by expanding its training data across diverse U.S. regions; integrating new data sources, such as environmental data layers, to address emerging contaminants; and conducting real-world testing to ensure robust, targeted groundwater safety measures worldwide.

“We see tremendous potential in this approach,” says Paul Westerhoff, co-corresponding author and Regents’ Professor in the School of Sustainable Engineering and the Built Environment at ASU. “By continuously improving its accuracy and expanding its reach, we’re laying the groundwork for proactive water safety measures across the globe.”

“This model also offers a promising tool for tracking phosphorus levels in groundwater, helping us identify and address potential contamination risks more efficiently,” says Jacob Jones, director of the National Science Foundation-funded Science and Technologies for Phosphorus Sustainability (STEPS) Center at NC State, which helped fund this work. “Looking ahead, extending this model to support broader phosphorus sustainability could have a significant impact, enabling us to manage this critical nutrient across various ecosystems and agricultural systems, ultimately fostering more sustainable practices.”

The paper, “Multiple Data Imputation Methods Advance Risk Analysis and Treatability of Co-occurring Inorganic Chemicals in Groundwater,” is published open access in the journal Environmental Science & Technology. The paper was co-authored by Emily Briese and Mohit Malu, both Ph.D. students at Arizona State; Carmen Velasco, a former postdoctoral researcher at Arizona State; Naushita Sharma, a postdoctoral researcher at Oak Ridge National Laboratory; and Andreas Spanias, a professor of digital signal processing at Arizona State.

This work was supported by the NSF STEPS Center; and by the Metals and Metal Mixtures: Cognitive Aging, Remediation and Exposure Sources (MEMCARE) Superfund Research Center based at Harvard University, which is supported by the National Institute of Environmental Health Science under grant P42ES030990.

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Note to Editors: The study abstract follows.

“Multiple Data Imputation Methods Advance Risk Analysis and Treatability of Co-occurring Inorganic Chemicals in Groundwater”

Authors: Akhlak U. Mahmood, Alexey V. Gulyuk and Yaroslava G. Yingling, North Carolina State University; Minhazul Islam, Emily Briese, Carmen A. Velasco, Mohit Malu, Naushita Sharma, Andreas Spanias and Paul Westerhoff, Arizona State University

Published: Nov. 7, Environmental Science & Technology

DOI: 10.1021/acs.est.4c05203

Abstract: Accurately assessing and managing risks associated with inorganic pollutants in groundwater is imperative. Historic water quality databases are often sparse due to rationale or financial budgets for sample collection and analysis, posing challenges in evaluating exposure or water treatment effectiveness. We utilized and compared two advanced multiple data imputation techniques, AMELIA and MICE algorithms, to fill gaps in sparse groundwater quality data sets. AMELIA outperformed MICE in handling missing values, as MICE tended to overestimate certain values, resulting in more outliers. Field data sets revealed that 75% to 80% of samples exhibited no co-occurring regulated pollutants surpassing MCL values, whereas imputed values showed only 15% to 55% of the samples posed no health risks. Imputed data unveiled a significant increase, ranging from 2 to 5 times, in the number of sampling locations predicted to potentially exceed health-based limits and identified samples where 2 to 6 co-occurring chemicals may occur and surpass health-based levels. Linking imputed data to sampling locations can pinpoint potential hotspots of elevated chemical levels and guide optimal resource allocation for additional field sampling and chemical analysis. With this approach, further analysis of complete data sets allows state agencies authorized to conduct groundwater monitoring, often with limited financial resources, to prioritize sampling locations and chemicals to be tested. Given existing data and time constraints, it is crucial to identify the most strategic use of the available resources to address data gaps effectively. This work establishes a framework to enhance the beneficial impact of funding groundwater data collection by reducing uncertainty in prioritizing future sampling locations and chemical analyses.

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https://news.ncsu.edu/2024/11/predicting-risk-in-groundwater-supplies/?

Development, agriculture present risks for drinking water quality

Date:May 6, 2025

Source:North Carolina State University

Summary:Converting forest land to urban development or agricultural use can present risks to water quality when done near streams or river sources. This study examined data from 15 water treatment plants in the Middle Chattahoochee watershed to model the impacts of four potential land use scenarios several decades into the future.Share:

    

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A new study from North Carolina State University researchers finds that conversion of forests to urban development or agriculture near streams can have harmful effects on water quality downstream, presenting both health concerns and raising the cost of water treatment.

Using a model called the Soil and Water Assessment Tool, researchers mapped out the current and projected future effects of four land-use scenarios at 15 water intake locations across the Middle Chattahoochee watershed in Georgia and Alabama. By combining a series of potential socioeconomic outcomes and climate change models reaching out to 2070, researchers examined several potential land use change scenarios to predict their effects on water quality.

Katherine Martin, associate professor in the NC State University College of Natural Resources and co-author of a paper on the study, said that in models where forest cover was converted to other land uses, water quality suffered.

“In terms of aspects of water quality that we have long term data on, two of the biggest are nitrogen levels and the amount of sediment in the water. Looking at those two, in places where we’re losing forest cover, we see both of those increasing,” she said. “Those are both detrimental to the quality of drinking water, and they require more filtration.”

Part of the issue, Martin said, is the relatively high level of fertilizer used in large-scale agriculture. Urban development results in large areas of impermeable surfaces, where rainwater cannot soak into the ground and instead runs off into rivers and streams. This causes the water to carry more sediment into those waterways than it would if it had been absorbed into the ground.

Increased filtration has several knock-on effects, Martin said. Not only is it potentially harmful for aquatic life, but it also increases the cost of managing water treatment plants. For facilities that do not serve large populations, this can lead to large per-capita price increases that end up being passed on to residents. These areas are also more likely to see increased development, due to their abundance of open land. The study suggests that more attention should be paid to where development might have serious effects on water quality for people living nearby, Martin said.

“Agriculture and urban development are beneficial, and this study does not say otherwise,” she said. “What we are seeing is that there are tradeoffs when we lose forest cover, and we need to open up the conversation about those.”

This work was supported by the U.S. Department of Agriculture Forest Service Southern Research Station agreement number 20-CS-11330180-053.

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https://www.sciencedaily.com/releases/2025/05/250506131518.htm?

Harmful microplastics infiltrating drinking water

Wastewater treatment plants are still not effectively removing dangerous microplastics

Date:April 21, 2025

Source:University of Texas at Arlington

Summary:Despite advances in wastewater treatment, tiny plastic particles called microplastics are still slipping through, posing potential health and environmental hazards, according to new research.Share:

    

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Despite advances in wastewater treatment, tiny plastic particles called microplastics are still slipping through, posing potential health and environmental hazards, according to new research from The University of Texas at Arlington.

Because plastic is inexpensive to produce yet lightweight and sturdy, manufacturers have found it ideal for use in nearly every consumer good, from food and beverage packaging to clothing and beauty products. The downside is that when a plastic item reaches the end of its useful life, it never truly disappears. Instead, it breaks down into smaller and smaller pieces called microplastics — particles five millimeters or less, about the width of a pencil eraser — that end up in our soil and water.

“What our systematic literature review found is that while most wastewater treatment facilities significantly reduce microplastics loads, complete removal remains unattainable with current technologies,” said Un-Jung Kim, assistant professor of earth and environmental sciences at UT Arlington and senior author of the study published in Science of the Total Environment.

“As a result, many microplastics are being reintroduced into the environment, likely transporting other residual harmful pollutants in wastewater, such the chemicals Bisphenols, PFAS and antibiotics,” Dr. Kim added. “These microplastics and organic pollutants would exist in trace level, but we can get exposure through simple actions like drinking water, doing laundry or watering plants, leading to potential long-term serious human health impacts such as cardiovascular disease and cancer.”

According to the study, one of the main challenges in detecting and mitigating microplastics is the lack of standardized testing methods. The researchers also call for a unified approach to define what size particle qualifies as a microplastic.

“We found that the effectiveness of treatments varies depending on the technology communities use and how microplastics are measured to calculate the removal rates,” said the study’s lead author, Jenny Kim Nguyen. “One way to better address the growing microplastics issue is to develop standardized testing methods that provide a clearer understanding of the issue.”

Nguyen began this research as an undergraduate student in Kim’s Environmental Chemistry Lab. She is now pursuing a master’s degree in earth and environmental sciences at UTA, where she is working to develop standardized experimental protocols for studying microplastics in air and water.

“This work helps us understand the current microplastics problem, so we can address its long-term health impacts and establish better mitigation efforts,” said Karthikraj Rajendiran, a co-author of the study and assistant professor of research from UTA’s Bone Muscle Research Center within the College of Nursing and Health Innovations.

The team also emphasizes the need for greater public awareness of microplastics to help consumers make more eco-friendly choices.

“While communities must take steps to improve microplastic detection and screening at the wastewater and water quality monitoring, consumers can already make a difference by choosing to buy clothing and textiles with less plastics whenever feasible, knowing that microfibers are the most common microplastic continually released through wastewater,” Kim added.

Funding for the project was provided by UTA’s Research Enhancement Program, which supports multidisciplinary researchers in launching new projects.

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https://www.sciencedaily.com/releases/2025/04/250421162936.htm?

Twenty-year study shows cleaner water slashes cancer and heart disease deaths

Date:November 27, 2025

Source:Columbia University’s Mailman School of Public Health

Summary:A 20-year project in Bangladesh reveals that lowering arsenic levels in drinking water can slash death rates from major chronic diseases. Participants who switched to safer wells had the same risk levels as people who were never heavily exposed. The researchers tracked individual water exposure with detailed urine testing. Their results show how quickly health improves once contaminated water is replaced.Share:

    

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Safer Wells Save Lives in Bangladesh
Cleaner water dramatically reduces chronic disease deaths, even for those exposed to arsenic for years. Credit: Shutterstock

A large 20-year investigation following nearly 11,000 adults in Bangladesh found that reducing arsenic in drinking water was tied to as much as a 50 percent drop in deaths from heart disease, cancer and several other chronic illnesses. The research offers the strongest long-term evidence so far that lowering arsenic exposure can reduce mortality, even for people who lived with contaminated water for many years. These results appear in JAMA.

Scientists from Columbia University, the Columbia Mailman School of Public Health and New York University led the analysis, which addresses a widespread health concern. Naturally occurring arsenic in groundwater remains a significant challenge across the world. In the United States, more than 100 million people depend on groundwater that can contain arsenic, particularly those using private wells. Arsenic continues to be one of the most common chemical contaminants in drinking water.

“We show what happens when people who are chronically exposed to arsenic are no longer exposed,” said co-lead author Lex van Geen of the Lamont-Doherty Earth Observatory, part of the Columbia Climate School. “You’re not just preventing deaths from future exposure, but also from past exposure.”

Two Decades of Data Strengthen the Evidence

Co-lead author Fen Wu of NYU Grossman School of Medicine said the findings offer the clearest proof yet of the connection between lowering arsenic exposure and reduced mortality risk. Over the course of two decades, the researchers closely tracked participants’ health and repeatedly measured arsenic through urine samples, which strengthened the precision of their analysis.

“Seeing that our work helped sharply reduce deaths from cancer and heart disease, I realized the impact reaches far beyond our study to millions in Bangladesh and beyond now drinking water low in arsenic,” said Joseph Graziano, Professor Emeritus at Columbia Mailman School of Public Health and principal investigator of the NIH-funded program. “A 1998 New York Times story first brought us to Bangladesh. More than two decades later, this finding is deeply rewarding. Public health is often the ultimate delayed gratification.”

Clear Drop in Risk When Arsenic Exposure Falls

People whose urinary arsenic levels fell from high to low had mortality rates that matched those who had consistently low exposure for the entire study. The size of the drop in arsenic was closely tied to how much mortality risk declined. Those who continued drinking high-arsenic water did not show any reduction in chronic disease deaths.

Arsenic naturally accumulates in groundwater and has no taste or smell, meaning people can drink contaminated water for years without knowing it. In Bangladesh, an estimated 50 million people have consumed water exceeding the World Health Organization’s guideline of 10 micrograms per liter. The WHO has described this as the largest mass poisoning in history.

From 2000 to 2022, the Health Effects of Arsenic Longitudinal Study (HEALS) monitored thousands of adults in Araihazar, Bangladesh. The project tested more than 10,000 wells in a region where many families rely on shallow tube wells with arsenic levels ranging from extremely low to dangerously high.

Researchers periodically measured arsenic in participants’ urine, a direct marker of internal exposure, and recorded causes of death. These detailed data allowed the team to compare long-term health outcomes for people who reduced their exposure with those who remained highly exposed.

Community Efforts Created a Natural Comparison Group

Throughout the study period, national and local programs labeled wells as safe or unsafe based on arsenic levels. Many households switched to safer wells or installed new ones, while others continued using contaminated water. This created a natural contrast that helped researchers understand the effects of reducing exposure.

Arsenic exposure decreased substantially in Araihazar during the study. The concentration in commonly used wells fell by about 70 percent as many families sought cleaner water sources. Urine tests confirmed a corresponding decline in internal exposure, averaging a 50 percent reduction that persisted through 2022.

Reduced Exposure Brings Lasting Health Benefits

These trends held true even after researchers accounted for differences in age, smoking and socioeconomic factors. Participants who remained highly exposed, or whose exposure rose over time, continued to face significantly higher risks of death from chronic diseases.

The researchers compared the health benefits of lowering arsenic to quitting smoking. The risks do not disappear immediately but drop gradually as exposure decreases.

In Bangladesh, well testing, labeling unsafe sources, drilling private wells and installing deeper government wells have already improved water safety for many communities.

“Our findings can now help persuade policymakers in Bangladesh and other countries to take emergency action in arsenic ‘hot spots’,” said co-author Kazi Matin Ahmed of the University of Dhaka.

To reach more households, the research team is collaborating with the Bangladeshi government to make well data easier to access. They are piloting NOLKUP (“tubewell” in Bangla), a free mobile app created from more than six million well tests. Users can look up individual wells, review arsenic levels and depths, and locate nearby safer options. The tool also helps officials identify communities that need new or deeper wells.

Clean Water Investments Can Save Lives

The study shows that health risks can fall even for people who were exposed to arsenic for years. This highlights an important opportunity: investing in clean water solutions can save lives within a single generation.

“Sustainable funding to support the collection, storage and maintenance of precious samples and data over more than 20 years have made this critically important work possible,” said Ana Navas-Acien, MD, PhD, Professor and Chair of Environmental Health Sciences at Columbia Mailman School of Public Health. “Science is difficult and there were challenges and setbacks along the way, but we were able to maintain the integrity of the samples and the data even when funding was interrupted, which has allowed us to reveal that preventing arsenic exposure can prevent disease.”

The study team included researchers from Columbia University’s Mailman School of Public Health, the New York University Grossman School of Medicine, Lamont-Doherty Earth Observatory, Boston University School of Public Health, the Department of Geology at the University of Dhaka and the Institute for Population and Precision Health at the University of Chicago.

The HEALS project was launched by Columbia University through the National Institute of Environmental Health Sciences’ Superfund Research Program, with most U.S. collaborators based at Columbia when the study began.

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https://www.sciencedaily.com/releases/2025/11/251127010327.htm?

ASM and AGU Offer Critical Strategies to Protect Public Health and Safe Drinking Water Amid Climate Change

June 9, 2025

Washington, D.C.—The American Academy of Microbiology, the honorific leadership group and think tank within the American Society for Microbiology (ASM), and the American Geophysical Union (AGU) have released a new report, Water, Waterborne Pathogens and Public Health: Environmental Drivers. Developed by leading scientists and informed by expert deliberations from a December 2024 colloquium organized by ASM and AGU, with support from the Association for the Sciences of Limnology and Oceanography (ASLO), the report presents a holistic strategy to reduce waterborne infections and safeguard public health as climate change increasingly disrupts water systems worldwide. 

“Water is a critical determinant of both ecosystem integrity and human health, yet it is increasingly compromised by anthropogenic pressures and broader environmental change,” said Dr. Rita Colwell, Co-Chair of the Colloquium Steering Committee, former ASM President and past Chair of the Academy. “Addressing this public health risk requires coordinated, cross-disciplinary strategies for effective microbial and environmental surveillance, early-warning systems and support for resilient water infrastructure that can withstand intensifying climate stressors.” 

Each year, more than 3.5 million people die from waterborne illnesses, with the heaviest burden falling on low- and middle-income countries, where over 4 billion people rely on water sources that are often unmonitored and unsafe. While many microbes that exist in water are harmless, some can cause serious disease when humans drink or interact with contaminated water. Environmental changes through more frequent and intense floods, hurricanes and heatwaves, coupled with aging infrastructure, are increasing human exposure to waterborne pathogens and threatening access to safe drinking water. 

The report is part of the Academy’s Climate Change & Microbes Scientific Portfolio, a 5-year initiative to advance microbial science to inform climate policy, foster innovation and support development of microbial technologies that can be applied globally. Supported by a grant from the Burroughs Wellcome Fund (BWF), the report shares expert-driven insights and highlights key strategies to strengthen prevention and response to waterborne disease outbreaks, including:   

  • Enhance surveillance and monitoring: Implement robust systems to track water quality and pathogen presence. 
  • Modernize water infrastructure: Invest in advanced water treatment and distribution systems to ensure safe drinking water. 
  • Promote interdisciplinary research: Initiate collaboration across microbial sciences, hydrology and climate science to address health relevant challenges. 
  • Improve public awareness and engagement: Raise awareness of the importance of safe water and sanitation and engage local communities to develop collaborative solutions. 

“Microbial datasets and environmental monitoring are foundational to explaining the dynamic interdependencies between ecological processes and human health outcomes,” said Antarpreet Jutla, Ph.D., Co-Chair of the Colloquium Steering Committee, AGU member and recipient of AGU’s 2023 Charles S. Falkenberg Award. “Integrating these data streams within interdisciplinary, systems-based frameworks facilitates the design of adaptive infrastructure and predictive modeling platforms, ultimately strengthening public health resilience and promoting socio-economic stability in the context of accelerating environmental change.” 

While a wealth of environmental and weather data, public health information and waterborne pathogen monitoring exists, resources for this information are often siloed. The report emphasizes integrating data systems with technologies like artificial intelligence and machine learning to develop predictive models for communities that allow proactive warning of waterborne disease outbreaks. 

Investment in water infrastructure that addresses region-specific geographical and environmental conditions and meets the needs of local communities is critical. The report highlights the promise of microbes as a nature-based solution that improves water treatment, prevents infrastructure degradation and provides new ways to build systems that hold up against changing weather parameters. 

Ultimately, addressing these challenges will require cross-disciplinary collaboration. The report calls for active engagement with local communities, especially those most affected by water insecurity, to co-develop effective and long-lasting solutions.  

“Safeguarding global health demands an integrated perspective and coordinated action,” said Jay Lennon, Ph.D., Chair of the Academy Climate Change Task Force. “Around the globe, scientists, public health advocates, policymakers, local leaders and philanthropists must work hand in hand to build a future where every person has access to safe and reliable water.” 

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The American Society for Microbiology is one of the largest professional societies dedicated to the life sciences and is composed of over 32,000 scientists and health practitioners. ASM’s mission is to promote and advance the microbial sciences. 
 
ASM advances the microbial sciences through conferences, publications, certifications, educational opportunities and advocacy efforts. It enhances laboratory capacity around the globe through training and resources. It provides a network for scientists in academia, industry and clinical settings. Additionally, ASM promotes a deeper understanding of the microbial sciences to all audiences. 

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The American Geophysical Union is an international association of more than 60,000 advocates and experts in Earth and space science. Fundamental to our mission since our founding in 1919 is to live our values, which we do through our net zero energy building in Washington, D.C., and by making scientific discoveries and research accessible and engaging to all to help protect society and prepare global citizens for the challenges and opportunities ahead.

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The Association for the Sciences of Limnology and Oceanography (ASLO) is an international aquatic science society that was founded in 1948. For more than 70 years, it has been the leading professional organization for researchers and educators in the field of aquatic science. The purpose of ASLO is to foster a diverse, international scientific community that creates, integrates and communicates knowledge across the full spectrum of aquatic sciences, advances public awareness and education about aquatic resources and research and promotes scientific stewardship of aquatic resources for the public interest. Its products and activities are directed toward these ends. With 3,000 members in more than 70 countries worldwide, the society has earned an outstanding reputation and is best known for its journals and interdisciplinary meetings. For more information about ASLO, please visit our website. 

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https://asm.org/press-releases/2025/june/asm-and-agu-offer-critical-strategies-to-protect-p?

Scientists discover what’s linking floods and droughts across the planet

Date:January 13, 2026

Source:University of Texas at Austin

Summary:Scientists tracking Earth’s water from space discovered that El Niño and La Niña are synchronizing floods and droughts across continents. When these climate cycles intensify, far-apart regions can become unusually wet or dangerously dry at the same time. The study also found a global shift about a decade ago, with dry extremes becoming more common than wet ones. Together, the results show that water crises are part of a global pattern, not isolated events.Share:

    

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Earth’s Water Extremes Are Suddenly Linked
Across the globe, floods and droughts aren’t striking at random — they’re moving to a shared rhythm driven by El Niño and La Niña. Credit: Shutterstock

Droughts and floods can disrupt daily life, damage ecosystems, and strain local and global economies. Scientists at The University of Texas at Austin set out to better understand these water extremes by studying how they develop and spread across the planet. Their work points to a powerful climate force that links distant regions in surprising ways.

A new study published in AGU Advances shows that during the past 20 years, ENSO, a recurring climate pattern in the equatorial Pacific Ocean that includes El Niño and La Niña, has played the leading role in driving extreme changes in total water storage worldwide. The researchers also found that ENSO tends to line up these extremes so that different continents experience unusually wet or dry conditions at the same time.

Why Synchronized Extremes Matter

According to study co-author Bridget Scanlon, a research professor at the Bureau of Economic Geology at the UT Jackson School of Geosciences, understanding these global patterns has real-world consequences.

“Looking at the global scale, we can identify what areas are simultaneously wet or simultaneously dry,” Scanlon said. “And that of course affects water availability, food production, food trade — all of these global things.”

When multiple regions face water shortages or excesses at once, the impacts can ripple through agriculture, trade, and humanitarian planning.

Measuring All the Water on Earth

Total water storage is a key climate indicator because it accounts for all forms of water in a region. This includes rivers and lakes, snow and ice, moisture in the soil, and groundwater below the surface. By focusing on this full picture, researchers can better understand how water moves and changes over time.

The study is one of the first to examine total water storage extremes alongside ENSO (The El Niño-Southern Oscillation) on a global scale. This approach made it possible to see how extreme wet and dry conditions are connected across large distances, said lead author Ashraf Rateb, a research assistant professor at the bureau.

“Most studies count extreme events or measure how severe they are, but by definition extremes are rare. That gives you very few data points to study changes over time,” Rateb said. “Instead, we examined how extremes are spatially connected, which provides much more information about the patterns driving droughts and floods globally.”

Satellites Reveal Hidden Water Changes

To estimate total water storage, the scientists relied on gravity measurements from NASA’s GRACE and GRACE Follow-On (GRACE-FO) satellites. These data allow researchers to detect changes in water mass over areas about 300 to 400 kilometers wide, roughly the size of Indiana.

The team classified wet extremes as water storage levels above the 90th percentile for a given region. Dry extremes were defined as levels below the 10th percentile.

Their analysis showed that unusual ENSO activity can push widely separated parts of the world into extreme conditions at the same time. In some regions, El Niño is linked to dry extremes, while in others the same dry conditions are associated with La Niña. Wet extremes tend to follow the opposite pattern.

Real-World Examples Across Continents

The researchers pointed to several striking cases. During the mid-2000s, El Niño coincided with severe dryness in South Africa. Another El Niño event was linked to drought in the Amazon during 2015-2016. By contrast, La Niña in 2010-2011 brought exceptionally wet conditions to Australia, southeast Brazil, and South Africa.

Beyond individual events, the study also identified a broader shift in global water behavior around 2011-2012. Before 2011, unusually wet conditions were more common worldwide. After 2012, dry extremes began to dominate. The researchers attribute this change to a long-lasting climate pattern in the Pacific Ocean that influences how ENSO affects global water.

Filling the Gaps in Satellite Records

Because GRACE and GRACE-FO data are not continuous, including an 11-month gap between missions in 2017-2018, the team used probabilistic models based on spatial patterns to reconstruct missing periods of total water storage extremes.

Although the satellite record covers only 22 years (2002-2024), it still reveals how closely climate and water systems are linked across the Earth, said JT Reager, deputy project scientist for the GRACE-FO mission at NASA’s Jet Propulsion Laboratory and JPL Discipline Program manager for the Water and Energy Cycle.

“They’re really capturing the rhythm of these big climate cycles like El Niño and La Niña and how they affect floods and droughts, which are something we all experience,” said Reager, who was not involved in the study. “It’s not just the Pacific Ocean out there doing its own thing. Everything that happens out there seems to end up affecting us all here on land.”

Preparing for Extremes, Not Just Shortages

Scanlon said the findings underscore the need to rethink how society talks about water challenges. Instead of focusing only on scarcity, she said, it is critical to plan for swings between too much and too little water.

“Oftentimes we hear the mantra that we’re running out of water, but really it’s managing extremes,” Scanlon said. “And that’s quite a different message.”

The research was funded by the UT Jackson School of Geosciences.

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https://www.sciencedaily.com/releases/2026/01/260112214304.htm?