water quality problems essay

Water Inequality

Lack of safe drinking water and adequate sanitation effects countries around the globe.

Anthropology, Biology, Health, Conservation, Geography, Human Geography, Social Studies

Water Bucket Woman

A woman carries buckets full of water in a small village in northern India.

Photograph by Sean Gallagher

More than 70 percent of Earth’s surface is covered in water, yet lack of access to clean water is one of the most pressing challenges of our time. As of 2015, 29 percent of people globally suffer from lack of access to safely managed drinking water. More than double that number are at risk for water contamination from improper wastewater management. Poor water quality affects various aspects of society, from the spread of disease to crop growth to infant mortality. In some regions of the world, lack of sanitation infrastructure , water treatment facilities, or sanitary latrines lead to dire clean water crises. In several countries around the world, a major contributor to water contamination is open defecation—the practice of using fields, forests, lakes, rivers, or other natural, open areas to deposit feces. Almost one billion people worldwide still practice open defecation rather than using a toilet. It is particularly common in South Asian countries like India and Nepal, where it is practiced by about 32 percent of people in the region. A landlocked country in the Himalayas, Nepal has access to clean water from mountain rivers, but over 20 percent of the population lives below the poverty line. In a disturbing study, 75 percent of drinking water samples from schools in Nepal were contaminated with fecal bacteria. While open defecation is most common in rural communities, it still occurs in areas with sanitation access, indicating a need for awareness campaigns to teach the dangers of the practice. Moreover, pollution from open defecation is further complicated by contamination from natural disasters such as recurring floods. In sub-Saharan Africa, the proportion of the population practicing open defecation is slightly smaller—around 23 percent—but 40 percent of the population lacks safe drinking water. Moreover, the gender inequality in this region is more prominent than in South Asia. In sub-Saharan Africa, more than 25 percent of the population must walk 30 minutes or more to collect water, a burden that falls on women and girls the vast majority of the time. This trend of women tasked with the responsibility of water collection spans many developing nations and takes critical quality time away from income generation, child care, and household chores. Moreover, Africa has a high risk for desertification , which will reduce the availability of fresh water even further, and increase the threat of water inequality in the future. While South Asia and sub-Saharan Africa represent the largest percentage of people that lack access to safe drinking water, the water crisis is not limited to these areas, nor is it limited to developing countries. For example, the Arctic nations are deemed developed, but several suffer from water and sanitation challenges. Alaska in the United States, Russia, and Greenland all contain rural areas that lack safe in-house water and sanitation facilities. Some people living in these areas must not only carry their own water into their homes, they must also remove human waste themselves, collecting it and hauling it out of the home. The process is time consuming and risks contamination of household surfaces and drinking water. Furthermore, hauling water into homes is physically demanding, and storage capacity is limited, so households often function on inadequate water supplies. Several studies have connected these water-quality constraints with high disease rates in Arctic communities. Even in the United States and many nations in Europe, where advanced wastewater treatment facilities and expansive pipelines supply quality water to both cities and rural areas, poor system maintenance, infrastructure failures, and natural disasters reveal the very serious effects of poor water quality (even short-term) on developed nations. In a recent example, drinking water in Flint, Michigan, was inadequately treated beginning in 2014, and residents bathed in, cooked with, and drank water with toxic lead levels. Additionally, some communities in the contiguous United States chronically lack clean water and sanitation. According to the U.S. Environmental Protection Agency (EPA), in the Navajo Nation, the largest Native American reservation in the United States, almost 8,000 homes lack access to safe drinking water, and 7,500 have insufficient sewer facilities. Luckily, global organizations are committed to addressing the water-quality crisis. The 2030 Agenda for Sustainable Development from the United Nations tackles water inequality within one of its seventeen priority goals, to “ensure availability and sustainable management of water and sanitation for all.” This initiative is a continuation of the United Nations’ Millennium Development Goals from the 2000s, which also included goals to reduce the portion of the population that lacked access to infrastructure for quality water and sanitation. These goals have resulted in access to improved sources of drinking water for more than 90 percent of the world—and the 2030 Agenda seeks to continue to improve these numbers alongside greater strides in the area of sanitation. National Geographic Explorers are also committed to global water equality and are combatting these issues with diverse methods. Explorer Sasha Kramer is helping to implement sustainable sanitation practices in Haiti by recycling human waste into soil. Explorer Ashley Murray develops economically advantageous approaches to improving water quality in Ghana, exploring next-generation technologies and new business models to make waste management profitable. Explorer Alexandra Cousteau, granddaughter of the late and legendary Jacques Cousteau, uses storytelling and digital assets to educate people around the globe about the importance of water quality. Moreover, complementing these examples and the many other Explorer-driven efforts dedicated to improving water quality, Explorer Feliciano dos Santos uses music to educate remote villages in Mozambique about the importance of sanitation and hygiene.

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• Open access
• Published: 22 June 2021

The widespread and unjust drinking water and clean water crisis in the United States

• J. Tom Mueller   ORCID: orcid.org/0000-0001-6223-4505 1 &
• Stephen Gasteyer 2  

Nature Communications volume  12 , Article number:  3544 ( 2021 ) Cite this article

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• Water resources

An Addendum to this article was published on 13 June 2023

An Author Correction to this article was published on 13 June 2023

Many households in the United States face issues of incomplete plumbing and poor water quality. Prior scholarship on this issue has focused on one dimension of water hardship at a time, leaving the full picture incomplete. Here we begin to complete this picture by documenting incomplete plumbing and poor drinking water quality for the entire United States, as well as poor wastewater quality for the 39 states and territories where data is reliable. In doing so, we find evidence of a regionally-clustered, socially unequal household water crisis. Using data from the American Community Survey and the Environmental Protection Agency, we show there are 489,836 households lacking complete plumbing, 1,165 community water systems in Safe Drinking Water Act Serious Violation, and 9,457 Clean Water Act permittees in Significant Noncompliance. Further, elevated levels of water hardship are associated with rurality, poverty, indigeneity, education, and age—representing a nationwide environmental injustice.

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Introduction.

Both in and out of the country, most presume that residents of the United States live with close to universal access to potable water and sanitation. The United Nations Sustainable Development Goals Tracker, which tracks progress toward meeting Sustainable Development Goal Number 6—calling for universal access to potable water and sanitation for all by 2030—estimates that 99.2% of the US population has continuous access to potable water and 88.9% has access to sanitation 1 . By percentages and the lived experience of most Americans, this appears accurate. The American Community Survey shows that from 2014 to 2018 only an estimated 0.41% of occupied US households lacked access to complete plumbing—meaning access to hot and cold water, a sink with a faucet, and a bath or shower. Although this relative percentage may be low, this 0.41% corresponds to 489,836 households spread unevenly across the country, making the absolute number quite troubling. These numbers become even more dramatic when we broaden our scope to poor household water quality, where the estimates we provide in this paper show the issue affects a far greater share of the population (Table  1 ).

This study builds on a growing body of evidence showing access to plumbing, water quality, and basic sanitation are lacking for a disturbingly large number of US residents by providing a definitive picture of the ongoing household water crisis in the United States. Water and sanitation issues have been a growing concern in the United States, particularly among policy organizations, for the past 20 years 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 . For example, the now-dated Still Living without the Basics report used Census data from 2000 to show that more than 670,000 households (0.64% of households and 1.7 million people) lacked access to complete plumbing facilities 7 . Further, the Water Infrastructure Network published a report in 2004 citing a gap of $23 billion between available funding and needed water and sanitation infrastructure investments 6 . In line with this, the American Society of Civil Engineers has repeatedly given the United States a “D” grade for water infrastructure, and “D-” for wastewater infrastructure in their annual “Infrastructure Report Card” 11 . Although water hardship in the United States has experienced some academic attention, much of the work has become dated and has generally focused on a single dimension of the issue at a time—for example, recent scholarship has focused on exclusively incomplete plumbing 3 , 4 , 9 , water quality 5 , 10 , or on only urban parts of the country 2 . This has left our understanding of the scope of the issue incomplete. In this paper, we estimate and map the full scope of water hardship for the dimensions of incomplete plumbing and poor drinking water quality across the entire United States, while also estimating and mapping the scope of poor wastewater quality for the 39 states where EPA data is reliable, in order to complete this picture.

Prior work from academics and policy groups on dimensions of water hardship has found water access issues pattern along common social inequalities in the United States. The Natural Resources Defense Council released a report demonstrating the disproportionate impact on people of color posed by Safe Drinking Water and Clean Water Act regulatory burdens 12 , which built on similar peer reviewed findings 13 , 14 . Furthermore, both policy papers and peer reviewed studies have analyzed Census data to estimate the population lacking access to complete plumbing facilities and clean water 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 12 . The studies suggest low-income and non-White people—particularly indigenous populations who continue to face injustices related to legacies of settler colonialism 15 —are significantly more likely to have incomplete plumbing and unclean water 3 , 12 . Further, it appears incomplete plumbing may be a disproportionately rural issue, while poor water quality may be a disproportionately urban issue 5 , 9 . Direct comparisons, as we perform here, are needed to fully establish the variability of this inequality between dimensions of water hardship.

The prior scholarship on the inequitable distribution of plumbing and pollution speaks to the well-documented environmental injustices found throughout the United States. Environmental injustice, meaning the absence of “fair treatment and meaningful involvement of all people regardless of race, color, national origin, or income with respect to the development, implementation, and enforcement of environmental laws, regulations, and policies” (p. 558) 16 , has been documented in the United States along the social dimensions of income 17 , 18 , poverty 19 , race and ethnicity 20 , 21 , age 22 , education 22 , 23 , and rurality 22 , 24 , 25 . Based on the evidence of prior work on water hardship, it is clear household water access represents an ongoing environmental injustice in the United States 5 . However, the specific dimensions of this injustice, and how they vary between type of water hardship remain largely unknown. To address this gap, we estimate models of water injustice for the previously identified social dimensions at the county level for elevated levels of both incomplete plumbing and poor water quality.

Level of water hardship in the United States

Based upon the most recent available data reported by both the United States Census Bureau via the American Community Survey and the Environmental Protection Agency via Enforcement and Compliance History Online, we find that incomplete plumbing and poor water quality affects millions of Americans as of 2014–2018 and August 2020, respectively (Table  1 ) 26 , 27 . A total of 0.41% of households, or 489,836 households, lacked complete plumbing from 2014–2018 in the United States. Further, 509 counties, representing over 13 million Americans, have an elevated level of the issue where >1% of household do not have complete indoor plumbing (Table  2 ). Thus, even if individuals are not experiencing the issue themselves, they may live in a community where incomplete plumbing is a serious issue.

The portion of the population affected by poor water quality is much greater than that of incomplete plumbing. Poor water quality in our analysis is indicated in two ways, (1) Safe Drinking Water Act Serious Violators and (2) Clean Water Act Significant Noncompliance. For the first, community water systems are regulated under the Safe Drinking Water Act and are scored based on their violation and compliance history, those community water systems that are the most problematic are recorded as Serious Violators by the Environmental Protection Agency 27 . Second, any facility that discharges directly into waters in the United States is issued a Clean Water Act permit. Those which “hold a more severe level of environmental threat” are ruled as being in Significant Noncompliance 27 . Importantly, although data on Safe Drinking Water Act Serious Violators is available nationwide, the Clean Water Act data reported by the EPA is known to be inaccurate for 13 states. Thus, although we can draw national conclusions for incomplete plumbing and Safe Drinking Water Act violations, our understanding of Clean Water Act violations is limited to the 39 states and territories for which data are available and reliable.

Using these two measures of poor water quality, we find 2.44% of community water systems, a total of 1165, were Safe Drinking Water Act Serious Violators and 3.37% of Clean Water Act permittees in the 39 states and territories with accurate data (see Methods for more details), a total of 9457, were in Significant Noncompliance as of 18 August 2020. At the county level, this corresponds to an average of 2.86% of county community water systems being listed as Safe Drinking Water Act Significant Violators and an average of 6.23% of county Clean Water Act permittees being listed as Significant Noncompliers. Due to limitations in the data, we are unable to determine exactly how many individuals are linked to each problematic community water system or Clean Water Act permittee, however, we do find that over 81 million Americans live in counties where >1% of community water systems are listed as Significant Violators, and more than 153 million Americans in the 39 reliable states and territories live in counties where greater than one percent of Clean Water Act permittees are Significant Noncompliers. Thus, although the number of individuals impacted by these issues is certainly far smaller than these totals, a vast number of Americans live in communities where issues of water quality are elevated.

Due to our conservative approach of removing all states with Clean Water Act data issues, we test the sensitivity of our estimates by also calculating supplemental estimates of Clean Water Act Significant Noncompliance under two counterfactual scenarios. In the first, we include the data as-is from the EPA for all counties in the 50 states, DC, and Puerto Rico, and in the second, we duplicate the counties in the top and bottom 20% of Significant Noncompliance in states without data issues—with the rationale being that the 945 counties removed due to poor data represented roughly 40% of the total counties remaining when problems states were removed. Thus, this attempts to simulate total counts if those removed were balanced between very high and very low levels of noncompliance. Results using all EPA data increase national estimates of Significant Noncompliance (Tables 3 and 4 ), with the total percent of permittees in this status jumping from 3.37% to 6.01%. While the duplication test does raise our estimates, it is not nearly as dramatic, with the percent of permittees in Significant Noncompliance only rising to 3.87%. These results make sense given that the most common reason for data issues was an overreporting of noncompliance within states.

When looking at the issue spatially, we can see that while water hardship affects all parts of the country to some degree, the issues are clustered in space (Figs.  1 – 3 ). Importantly, the clustering varies between each water issue. Incomplete plumbing is clustered in the Four Corners, Alaska, Puerto Rico, the borderlands of Texas, and parts of Appalachia (Fig.  1 ); Safe Drinking Water Act Serious Violators are clustered in Appalachia, New Mexico, Alaska, Puerto Rico, and the Northern Intermountain West (Fig.  2 ); and Clean Water Act Significant Noncompliance clearly follows state boundaries—likely speaking to variable monitoring by state. Although spatial representation is limited by the absence of 13 states with inaccurate EPA data, we can still see that Clean Water Act Significant Noncompliance is clustered in the Intermountain West, the Upper Midwest, Appalachia, and the lower Mississippi (Fig. 3 ). These regional clusters persist when we include the problem states, which is visible in the map included in the Supplemental Information (Supplementary Figure 1 ).

Households are determined to have incomplete plumbing if they do not have access to hot and cold water, a sink with a faucet, a bath or shower, and—up until 2016—a flush toilet.

Safe Drinking Water Act Serious Violators are those community water systems regarded by the Environmental Protection Agency as the most problematic due to violation and compliance history.

All facilities that discharge directly into water of the United States are issued a Clean Water Act permit, those who represent a more severe level of environmental threat due to violations and noncompliance are considered in Significant Noncompliance.

Water injustice modeling

Although we can easily see clustering by space in Figs.  1 through 3 , the maps do not tell us whether or not incomplete plumbing and poor water quality are also clustered by social dimensions, which would represent an environmental injustice. To assess this social clustering, we estimate linear probability models of elevated levels of incomplete plumbing and poor water quality with the previously identified environmental justice dimensions of age, income, poverty, race, ethnicity, education, and rurality as our independent variables. We include these independent variables due to their prevalence within prior work on environmental injustice in both rural and urban areas 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 . Further, although there is not a one-to-one overlap, these variables conceptually map onto the dimensions of the Center for Disease Control Social Vulnerability Index: Socioeconomic Status (i.e. income, poverty, education), Household Composition & Disability (i.e. age), Minority Status & Language (i.e. race and ethnicity), and Housing & Transportation (i.e. rurality) 28 .

For each outcome, we first estimate purely descriptive models with only one dimension of injustice included at a time, and then estimate a full model with all dimensions included. The outcomes are dichotomous measures of whether or not a county had >1% of households with incomplete plumbing, >1% of community water systems listed as Serious Violators, or >1% of Clean Water Act permittees in Significant Noncompliance. All descriptive statistics for the dichotomous outcomes are presented in Table 2 . Descriptive statistics for the continuous independent variables are presented in Supplementary Information (Supplementary Table  1 ). Here we present the outcomes of the purely descriptive models visually in Fig.  4 and discuss the full models in the narrative. Full regression results, including exact 95% confidence intervals and p -values, for all models are available in Supplementary Information (Supplementary Tables  2 , 3 and 4 ).

Different colors for plotted coefficients represent separate blocks of variables. Models are linear probability models with state fixed effects and cluster-robust standard errors at the state level. All tests two-tailed. Dots indicate point estimates and lines represent 95% confidence intervals. Models predicted elevated levels of each dimension of water hardship. For incomplete plumbing this is indicated by >1% of households in a county having incomplete plumbing ( N  = 3219). For Safe Drinking Water Act (SDWA) Serious Violation this is indicated by >1% of active community water systems being considered Serious Violators ( N  = 3143). For Clean Water Act (CWA) Significant Non-Compliance this is indicated by >1% of Clean Water Act permittees being considered in Significant Non-Compliance ( N  = 2261). Full model results, confidence intervals, and exact p -values available in SI.

We find elevated levels of incomplete plumbing at the county level were significantly ( p  < 0.05) associated with older populations, lower income, higher poverty, greater portions of indigenous people (American Indian, Alaska Natives, Native Hawaiian, and Other Pacific Islanders), lower levels of education, and more rural counties (Fig.  4 ). A great deal of these associations persisted in a full model with all dimensions of injustice (Supplementary Table  2 ). The only differences between the full model and the series of purely descriptive models were that income, percent with at least a bachelor’s degree, and non-metropolitan metropolitan adjacency were no longer significantly associated with elevated levels of incomplete plumbing. This indicates that the inequalities in plumbing access along the dimensions of age, poverty, indigeneity, low education, and extreme rurality persist at the county level, even when accounting for the other dimensions of environmental injustice.

The models for elevated levels of Safe Drinking Water Act Serious Violators indicated less social inequality than the models for incomplete plumbing. The purely descriptive models found elevated levels of Serious Violators were associated with higher income, higher poverty, and metropolitan counties (Fig.  4 ). The full model had minor variation, with median household income no longer being significant in the model (Supplementary Table  3 ). Thus, the full model shows that the association between elevated levels of Serious Violators and higher poverty and metropolitan status persists even when considering other social dimensions.

We see the fewest indicators of water injustice for elevated levels of Clean Water Act Significant Noncompliance—which only include counties within the 39 states and territories with accurate data. In the purely descriptive models, we find older populations, more Latino/a counties, less educated counties, and remote rural counties were significant less likely to have elevated levels of noncompliance (Fig. 4 ). In the full model, the association for education is no longer significant but age, Latino/a, and rurality remain (Supplementary Table 4 ). Similar to our national estimates, we also conducted model sensitivity tests using the same scenarios described above. As shown in Fig. 5 , neither scenario substantively changes our conclusions, with the only changes in significance being for percent Latino/a and percent without a high school diploma—both of which were only marginally significant in our primary models ( p  > 0.01).

Descriptive regression model results. Different colors for plotted coefficients represent separate blocks of variables. Models are linear probability models with state fixed effects and Huber/White/Sandwich cluster-robust standard errors at the state level. All tests are two-tailed. Dots indicate point estimates and lines represent 95% confidence intervals. Models predicted whether or not there were greater than 1% of Clean Water Act permittees being considered in Significant Noncompliance in the county. First model excludes counties in states with CWA data issues ( N  = 2261), second model includes all counties reported by the EPA ( N  = 3206), third model duplicates counties in the top and bottom 10% of CWA Significant Noncompliance within states without data issues ( N  = 3151). Full model results, confidence intervals, and exact p values available in SI.

Our findings demonstrate that the problem of water hardship in the United States is hidden, but not rare. Indeed, millions live in counties where more than 1 out of 100 occupied households lack complete plumbing. Millions more live in places with chronic Safe Drinking Water Act violations and Clean Water Act noncompliance. We present this paper to help sound the alarm of this significant household water crisis in the United States. Although the relative share of Americans experiencing this problem is low, the absolute number of people dealing with incomplete plumbing—a total of 489,836 households—and poor water quality—1165 community water systems nationwide and 9457 Clean Water Act permittees in the 39 accurate states and territories—remains quite high. Further, given the water infrastructure of the United States, consistently deemed as poor by experts 6 , 11 , if action is not taken the situation may only get worse.

These findings are even more concerning when considering that water hardship is spread unevenly across both space and society, reflecting the spatial patterning of social inequality due to settler colonialism, racism, and economic inequality in the United States. Figures  1 , 2 , and 3 document the clear regional clustering of these issues and our models of environmental injustice demonstrate the social inequalities found for this form of hardship. Particularly in the case of incomplete plumbing, we find significant environmental injustice at the county level along the social dimensions of age, income, poverty, indigeneity, education, and rurality. These associations certainly stem from multiple causal pathways—for example associations with indigeneity likely stem from legacies of injustice as well as ongoing policies placing limitations on land use and infrastructure development on American Indian reservations 15 . Remedying these injustices will require careful attention to the root causes of the problem. It is important to note that the signs of injustice for poor water quality were less clear than for incomplete plumbing, with far fewer significant associations. Further, the minimal support for injustice in the case of Clean Water Act Significant Noncompliance was evident in all three specifications of counties in our sensitivity tests. Suggesting that the removal of the states with data issues did little to impact coefficient estimates. These differences between dimensions of water hardship highlight the nuance between each of these specific forms of water hardship, and suggest a one-size-fits-all approach to remedying this crisis is unlikely to be effective. This need for place-based policy is made stark when we view the obvious state level differences in Clean Water Act Significant Noncompliance in Fig. 3 . A clear direction for future work is to investigate the cause of these notable state-level differences.

The household water access and quality crisis we have identified here is solvable. Policy is needed to specifically address these issues and bring this problem into the spotlight. However, as indicated by the persistently high levels of Safe Drinking Water Act Serious Violation and Clean Water Act Significant Noncompliance, any policy put in place must be enforceable and strong. As it currently stands, counties with elevated levels of incomplete plumbing and poor water quality in America—which are variously likely to be more indigenous, less educated, older, and poorer—are continuing to slip through the cracks.

Data sources

Data for this analysis were extracted from the American Community Survey (ACS) 5-year estimates for 2014–2018 via Integrated Public Use Microdata Series – National Historic Geographic information System (IPUMS-NHGIS) 26 , and from the Environmental Protection Agency’s (EPA) Enforcement and Compliance History Online (ECHO) Exporter 27 . Data were extracted at the county level for all 50 states, Washington DC, and Puerto Rico–the two non-state entities with available data. The ACS is an ongoing survey of the United States which documents a wide variety of social statistics ranging from simple population counts to housing characteristics. Due to the staggered sampling structure of the ACS, it takes 5 years for every county to be sampled. Because of this, researchers must use 5-year intervals to ensure complete data coverage. The data from these 5 years are projected into estimates for all counties in the United States for the 5-year period in question. As of this study, 2014–2018 was the most recently available data.

ECHO collates data from EPA-regulated facilities across the United States of America to report compliance, violation, and penalty information for all facilities for the most recent 5-year interval. ECHO data is updated weekly and the data for this paper was extracted on 18 August 2020. This means that the data in our analysis represents the status of each community water system or Clean Water Act permittee, as reported by the EPA, as of 18 August 2020. Only those community water systems or Clean Water Act permittees listed as Active by ECHO were included in this analysis. As ECHO data is at the level of the water system, permittee, or utility, we aggregated data up to the county level.

Safe Drinking Water Act data was geolocated using QGIS 3.10 based upon latitude and longitude. This was done because other geographic identifiers for the Safe Drinking Water Act data were often missing. In line with prior work 4 , 5 , 7 , 8 , and in order to facilitate a cleaner dataset, we only focus on those water systems labeled community water systems for our analysis. Community water systems were geolocated based upon the county in which their latitude and longitude were located, if a community water system had latitude and longitude over water, a nearest neighbor join was used. In total, 1334 out of 49,479 community water systems were dropped because of there being no reported latitude or longitude. Of these, a total of 4.0%, or 54 community waters systems, were reported as in serious violation. It should be noted that the EPA is aware of a small number of water systems in Washington for which ECHO data may be inaccurate. However, since this is a small number and it is not listed as a ‘Primary Data Alert,’ we retain all states in this portion of the analysis. Finally, the EPA is generally aware that there are “inaccuracies and underreporting of some data in this system,” which is listed as a Primary Data Alert 27 . However, due to the lack of specifics, we cannot exclude inaccurate cases. Thus, our analysis should be viewed as reflecting drinking water quality is as reported by the EPA in August of 2020, which may reflect some level of inaccuracy.

Active Clean Water Act permittees were first identified by listed county. This was done because 345,176 out of 350,476 permittees had a county reported. Those without a county reported were located using latitude and longitude in the same manner as community water systems. There were 10 permittees without latitude and longitude or county listed which were excluded from our analysis. Of these, seven were in significant noncompliance and three were not. Due to some Clean Water Act permittees having latitude and longitude placements far away from the United States, those over 100 km from their nearest county were excluded from analysis. Unfortunately, ECHO data for the Clean Water Act data during the study period is inaccurate for 13 states. Although the nature of the inaccuracy varies from state to state, these issues generally stem from difficulties in transferring state data into the federal system. Due to this, these states appear to have far more permittees in Significant Noncompliance than are actually in violation. To address this issue, we removed all counties within these states from our Clean Water Act analysis. The impacted states include Iowa, Kansas, Michigan, Missouri, Nebraska, North Carolina, Ohio, Pennsylvania, Vermont, Washington, West Virginia, Wisconsin, and Wyoming 29 . Finally, for community water systems and Clean Water Act permittees, some counties (76 for community water systems and 5 for Clean Water Act permittees) had no reported cases. Those counties were treated as zeroes for cartography and as missing for modeling purposes.

Similar to prior work in this area 4 , 5 , 8 , we restrict our analysis to the scale of the county for reasons related to data limitations and resulting conceptual validity. Although counties are arguably larger in geographic area than ideal for an environmental injustice analysis, if we were to use a smaller unit for which data is available such as the census tract, the conceptual validity of the analysis would be limited due to the apolitical nature of these units. As outlined above, ECHO data is messy and missing many geographic identifiers. What is provided is generally either the county or latitude and longitude. If only the county is provided, then we are constrained to using the county regardless of conceptual validity. However, even when latitude and longitude are provided—which is the case for many observations—the provided point location says nothing about which households the water system or permittee serves or impacts. Due to this, whatever geographic unit we use carries the assumption that those in the unit could be plausibly impacted by the water system or permittee. Given that counties are often responsible for both regulating drinking water, as well as maintaining and providing water infrastructure 30 , we were comfortable with this assumption between point location and presumed spatial impact when using the scale of the county. However, we believe this assumption would have been invalid and untestable for smaller apolitical units for which demographic data is available such as census tracts.

Beyond the issues presented by ECHO data, the county is also the appropriate scale of analysis for this study due to the estimate-based nature of the ACS. ACS estimates are based on a rolling 5-year sample structure and often have very large margins of error. At the census tract level, these standard errors can be massive, especially in rural areas 31 , 32 , 33 . Due to this variation, and the need to include all rural areas in this analysis, the county, where the margins of error are considerably smaller, is the appropriate unit for this study. All of this said, the county is, in fact, a larger unit than often desired or used in environmental justice studies. Studies focused on exclusively urban areas with clearer pathways of impact can and should use smaller units such as census tracts. It will be imperative for future scholarship focused on water hardship across the rural-urban continuum to gain access to reliable data on sub-county political units, as well as data linking water systems to users, to continue documenting and pushing for water justice.

Dependent variables

The dependent variables for this analysis were assessed in both a continuous and dichotomous format. For descriptive results and mapping, continuous measures were used. For models of water injustice, a dichotomous measure which classified counties as either having low levels of the specific water issue or elevated levels of the specific water issue, was used due to the low relative frequency of water access and quality issues relative to the whole United States population. For all three outcomes, we benchmark an elevated level of the issue as what would be viewed as an unacceptable level under United Nations Sustainable Development Goal 6.1, which states, “by 2030 achieve universal and equitable access to safe and affordable drinking water for all” 1 . As this goal focuses on ensuring all people have safe water, we deem a county as having an elevated level of the issue if >1% of households, community water systems, or permittees had incomplete plumbing, were in Significant Violation, or Significant Noncompliance, respectively. Although we could have used an even stricter threshold given the SDG’s emphasis on ensuring access for all people, we use 1% as our cut-off due to its nominal value and ease of interpretation.

For water access, the continuous measure was the percent of households in a county with incomplete household plumbing as reported by the ACS. The ACS currently asks respondents if they have access to hot and cold water, a sink with a faucet, and a bath or shower. Up until 2016, the question also included a flush toilet 34 . As we must use the most recent 2014–2018 5-year estimates to establish full coverage of all counties, this means that incomplete plumbing in this item may, or may not include a flush toilet depending on when the specific county was sampled. The dichotomous version of this variable benchmarked elevated levels of incomplete plumbing as whether or not 1% or more of households in a county had incomplete plumbing.

Water quality was assessed via both community water systems from the Safe Drinking Water Act, and from permit data via the Clean Water Act. For Safe Drinking Water Act data, the continuous measure was the percent of community water systems within a county classified as a Safe Drinking Water Act Serious Violator at time of data extraction. The EPA assigns point values of either 1, 5, or 10 based upon the severity of violations of the Safe Drinking Water Act. A Serious Violator is one who has “an aggregate score of at least eleven points as a result of some combination of: unresolved more serious violations (such as maximum contaminant level violations related to acute contaminants), multiple violations (health-based, monitoring and reporting, public notification and/or other violations), and/or continuing violations” 27 . The dichotomous measure benchmarked elevated rates of Safe Drinking Water Act Significant Violation as whether or not >1% of county community water systems were classified as Serious Violators.

For Clean Water Act permit data, the continuous measure was the percent of permit holders listed as in Significant Noncompliance at the time of data extraction. Significant Noncompliance in the Clean Water Act refers to those permit holders who may pose a “more severe level of environmental threat” and is based upon both pollution levels and reporting compliance 27 . The dichotomous measure again set the threshold for elevated levels of poor water quality at whether or not >1% of Clean Water Act permittees in a county were listed as in Significant Noncompliance at time of data extraction.

Independent variables

The independent variables we include in models of water injustice are those frequently shown to be related to environmental injustice in the United States. These include age, income, poverty, race, ethnicity, education, and rurality 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 . Age was included as median age. Income was included as median household income. Poverty was the poverty rate of the county as determined by the official poverty measure of the United States 35 . Race and ethnicity was included as percent non-Latino/a Black, percent non-Latino/a indigenous, and percent Latino/a. Because the focus was on indigeneity, percent American Indian or Alaska Native was collapsed with Native Hawaiian or Other Pacific Islander. We did not include percent non-Latino/a white due to issues of multicollinearity. Finally, rurality was included as a three-category county indicator of metropolitan, non-metropolitan metropolitan-adjacent, and non-metropolitan remote, as determined by the Office of Management and Budget in 2010 36 . The OMB determines a county is metropolitan if it has a core urban area of 50,000 or more people, or is connected to a core metropolitan county by a 25% or greater share of commuting 36 . A non-metropolitan county is simply any county not classified as metropolitan. Non-metropolitan metropolitan adjacent counties are those which immediately border a metropolitan county, and non-metropolitan remote counties are those that do not.

Water injustice modeling approach

Water injustice was assessed by estimating linear probability models for the three dichotomous outcome variables with state fixed effects to control for the visible state level heterogeneity and differences in policy, reporting, and enforcement (e.g. the clear state boundary effects in Fig.  3 ). We employ the conventional Huber/White/Sandwich cluster-robust standard errors at the state level—which account for heteroskedasticity while also producing a consistent standard error estimate in-light of the lack of independence found between counties in the same state. All modeling was performed in Stata 16.0 and mapping was performed in QGIS 3.10. We assessed all full models for multicollinearity via condition index and VIF values and the independent variables had an acceptable condition index of 5.48 for incomplete plumbing and Safe Drinking Water Act models and 5.63 for Clean Water Act models, well below the conservative cut-off of 15, as well as VIF values of <10. We initially included percent non-Latino/a white as an independent variable, but removed the item due to unacceptably high condition index levels (>20). All indications of statistical significance are at the p  < 0.05 level and 95% confidence intervals and exact p -values of all estimates are provided in Supplementary Information. Each dependent variable was analyzed through a series of six models. First, we estimated separate purely descriptive models, where the only independent variables included were those associated with that specific dimension and the state fixed effects, for all five dimensions of environmental injustice. After estimating these five models, we estimated a full model including all social dimensions at once.

The reason for this approach was to ensure that we provided a robust descriptive understanding of the on-the-ground social patterns of water hardship, in addition to a full model showing the strongest social correlates of this issue. For example, if when we only included income variables we found that incomplete plumbing is less likely in counties with higher median incomes, but this effect goes away when we include other social variables, this does not remove the fact that there is an unequal distribution of incomplete plumbing by income on-the-ground. All that it means is that this income effect does not persist over and above the other social dimensions of environmental injustice. It may be that once other dimensions such as structural racism, captured by race and ethnicity variables, are considered, income is no longer a significant predictor. However, at a pure associational level, incomplete plumbing would still be unequally distributed by income on-the-ground. In fact, this is exactly what we find for incomplete plumbing (Supplementary Table  2 ). Due to this, both the pure descriptive and full models are needed for full understanding. Complete tables of all results are presented in the Supplementary Information File (Supplementary Tables  1 through 4 ).

Sensitivity tests

Due to our conservative approach to remove all problem states from the Clean Water Act portion of our analysis, we conducted a series of sensitivity tests wherein we generated national estimates of Significant Noncompliance, as well as models of elevated Significant Noncompliance under two scenarios (Supplementary Tables 5 and 6 ). In the first scenario we include all data reported by the EPA, meaning that we use all data for the 50 states, DC, and Puerto Rico, regardless of any EPA data flags. In the second scenario, we replaced the data lost when dropping states by duplicating the counties in the top and bottom 20% of significant violations in the remaining counties. The top and bottom 20% was chosen because the 945 counties removed when the 13 states were dropped was roughly equal to 40% of the remaining 2262 counties. This counterfactual allows us to get closer to a plausible estimate of the absolute scope of CWA Significant Noncompliance by adopting a scenario where the counties dropped in problem states were either very high, or very low in terms of Significant Noncompliance. Functionally, duplicating the bottom 20% posed a challenge because the bottom 30% of counties had zero permittees in Significant Noncompliance. This zero-bias is one of the primary reasons why our outcome variable was dichotomized. To address this, we randomly selected two-thirds of these counties for duplication using a seeded pseudorandom number generator in Stata. Following duplication of cases, all estimates and models were generated in the same manner as the primary models of this study.

Reporting summary

Further information on research design is available in the  Nature Research Reporting Summary linked to this article.

Data availability

The raw and geolocated datasets are publicly available on the Open Science Framework project for this study at https://doi.org/10.17605/OSF.IO/ZPQR9 ( https://osf.io/zpqr9/ ).

Code availability

Analysis code is available on the Open Science Framework project for this study at https://doi.org/10.17605/OSF.IO/ZPQR9 ( https://osf.io/zpqr9/ ). As the raw data was not geolocated using a code-based operation, code for this portion of the analysis is not available. However, the raw data is posted, and should researchers wish they will be able to use our description provided here to replicate geolocation using the GIS software of their choice. All other elements of the analysis are easily replicated via our provided code. As the both the raw and geolocated datasets are provided, replication of our analysis should be straightforward.

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Acknowledgements

The authors would like to acknowledge Tom Dietz, Lauren Mullenbach, Matthew Brooks, and Jan Beecher for their feedback on this manuscript. They would also like to thank Colleen Keltz at the Washington State Department of Ecology for alerting us to the issues with Clean Water Act data for Washington and other states.

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Conceptualization: J.T.M. and S.G.; methodology: J.T.M.; formal analysis: J.T.M.; data curation: J.T.M.; writing- original draft preparation: J.T.M. and S.G.; writing – review and editing: J.T.M. and S.G.; visualization: J.T.M.

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Mueller, J.T., Gasteyer, S. The widespread and unjust drinking water and clean water crisis in the United States. Nat Commun 12 , 3544 (2021). https://doi.org/10.1038/s41467-021-23898-z

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Water Pollution: Everything You Need to Know

Our rivers, reservoirs, lakes, and seas are drowning in chemicals, waste, plastic, and other pollutants. Here’s why—and what you can do to help.

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What is water pollution?

What are the causes of water pollution, categories of water pollution, what are the effects of water pollution, what can you do to prevent water pollution.

Water pollution occurs when harmful substances—often chemicals or microorganisms—contaminate a stream, river, lake, ocean, aquifer, or other body of water, degrading water quality and rendering it toxic to humans or the environment.

This widespread problem of water pollution is jeopardizing our health. Unsafe water kills more people each year than war and all other forms of violence combined. Meanwhile, our drinkable water sources are finite: Less than 1 percent of the earth’s freshwater is actually accessible to us. Without action, the challenges will only increase by 2050, when global demand for freshwater is expected to be one-third greater than it is now.

Water is uniquely vulnerable to pollution. Known as a “universal solvent,” water is able to dissolve more substances than any other liquid on earth. It’s the reason we have Kool-Aid and brilliant blue waterfalls. It’s also why water is so easily polluted. Toxic substances from farms, towns, and factories readily dissolve into and mix with it, causing water pollution.

Here are some of the major sources of water pollution worldwide:

Agricultural

Toxic green algae in Copco Reservoir, northern California

Aurora Photos/Alamy

Not only is the agricultural sector the biggest consumer of global freshwater resources, with farming and livestock production using about 70 percent of the earth’s surface water supplies , but it’s also a serious water polluter. Around the world, agriculture is the leading cause of water degradation. In the United States, agricultural pollution is the top source of contamination in rivers and streams, the second-biggest source in wetlands, and the third main source in lakes. It’s also a major contributor of contamination to estuaries and groundwater. Every time it rains, fertilizers, pesticides, and animal waste from farms and livestock operations wash nutrients and pathogens—such bacteria and viruses—into our waterways. Nutrient pollution , caused by excess nitrogen and phosphorus in water or air, is the number-one threat to water quality worldwide and can cause algal blooms , a toxic soup of blue-green algae that can be harmful to people and wildlife.

Sewage and wastewater

Used water is wastewater. It comes from our sinks, showers, and toilets (think sewage) and from commercial, industrial, and agricultural activities (think metals, solvents, and toxic sludge). The term also includes stormwater runoff , which occurs when rainfall carries road salts, oil, grease, chemicals, and debris from impermeable surfaces into our waterways

More than 80 percent of the world’s wastewater flows back into the environment without being treated or reused, according to the United Nations; in some least-developed countries, the figure tops 95 percent. In the United States, wastewater treatment facilities process about 34 billion gallons of wastewater per day . These facilities reduce the amount of pollutants such as pathogens, phosphorus, and nitrogen in sewage, as well as heavy metals and toxic chemicals in industrial waste, before discharging the treated waters back into waterways. That’s when all goes well. But according to EPA estimates, our nation’s aging and easily overwhelmed sewage treatment systems also release more than 850 billion gallons of untreated wastewater each year.

Oil pollution

Big spills may dominate headlines, but consumers account for the vast majority of oil pollution in our seas, including oil and gasoline that drips from millions of cars and trucks every day. Moreover, nearly half of the estimated 1 million tons of oil that makes its way into marine environments each year comes not from tanker spills but from land-based sources such as factories, farms, and cities. At sea, tanker spills account for about 10 percent of the oil in waters around the world, while regular operations of the shipping industry—through both legal and illegal discharges—contribute about one-third. Oil is also naturally released from under the ocean floor through fractures known as seeps.

Radioactive substances

Radioactive waste is any pollution that emits radiation beyond what is naturally released by the environment. It’s generated by uranium mining, nuclear power plants, and the production and testing of military weapons, as well as by universities and hospitals that use radioactive materials for research and medicine. Radioactive waste can persist in the environment for thousands of years, making disposal a major challenge. Consider the decommissioned Hanford nuclear weapons production site in Washington, where the cleanup of 56 million gallons of radioactive waste is expected to cost more than $100 billion and last through 2060. Accidentally released or improperly disposed of contaminants threaten groundwater, surface water, and marine resources.

To address pollution and protect water we need to understand where the pollution is coming from (point source or nonpoint source) and the type of water body its impacting (groundwater, surface water, or ocean water).

Where is the pollution coming from?

Point source pollution.

When contamination originates from a single source, it’s called point source pollution. Examples include wastewater (also called effluent) discharged legally or illegally by a manufacturer, oil refinery, or wastewater treatment facility, as well as contamination from leaking septic systems, chemical and oil spills, and illegal dumping. The EPA regulates point source pollution by establishing limits on what can be discharged by a facility directly into a body of water. While point source pollution originates from a specific place, it can affect miles of waterways and ocean.

Nonpoint source

Nonpoint source pollution is contamination derived from diffuse sources. These may include agricultural or stormwater runoff or debris blown into waterways from land. Nonpoint source pollution is the leading cause of water pollution in U.S. waters, but it’s difficult to regulate, since there’s no single, identifiable culprit.

Transboundary

It goes without saying that water pollution can’t be contained by a line on a map. Transboundary pollution is the result of contaminated water from one country spilling into the waters of another. Contamination can result from a disaster—like an oil spill—or the slow, downriver creep of industrial, agricultural, or municipal discharge.

What type of water is being impacted?

Groundwater pollution.

When rain falls and seeps deep into the earth, filling the cracks, crevices, and porous spaces of an aquifer (basically an underground storehouse of water), it becomes groundwater—one of our least visible but most important natural resources. Nearly 40 percent of Americans rely on groundwater, pumped to the earth’s surface, for drinking water. For some folks in rural areas, it’s their only freshwater source. Groundwater gets polluted when contaminants—from pesticides and fertilizers to waste leached from landfills and septic systems—make their way into an aquifer, rendering it unsafe for human use. Ridding groundwater of contaminants can be difficult to impossible, as well as costly. Once polluted, an aquifer may be unusable for decades, or even thousands of years. Groundwater can also spread contamination far from the original polluting source as it seeps into streams, lakes, and oceans.

Surface water pollution

Covering about 70 percent of the earth, surface water is what fills our oceans, lakes, rivers, and all those other blue bits on the world map. Surface water from freshwater sources (that is, from sources other than the ocean) accounts for more than 60 percent of the water delivered to American homes. But a significant pool of that water is in peril. According to the most recent surveys on national water quality from the U.S. Environmental Protection Agency, nearly half of our rivers and streams and more than one-third of our lakes are polluted and unfit for swimming, fishing, and drinking. Nutrient pollution, which includes nitrates and phosphates, is the leading type of contamination in these freshwater sources. While plants and animals need these nutrients to grow, they have become a major pollutant due to farm waste and fertilizer runoff. Municipal and industrial waste discharges contribute their fair share of toxins as well. There’s also all the random junk that industry and individuals dump directly into waterways.

Ocean water pollution

Eighty percent of ocean pollution (also called marine pollution) originates on land—whether along the coast or far inland. Contaminants such as chemicals, nutrients, and heavy metals are carried from farms, factories, and cities by streams and rivers into our bays and estuaries; from there they travel out to sea. Meanwhile, marine debris— particularly plastic —is blown in by the wind or washed in via storm drains and sewers. Our seas are also sometimes spoiled by oil spills and leaks—big and small—and are consistently soaking up carbon pollution from the air. The ocean absorbs as much as a quarter of man-made carbon emissions .

On human health

To put it bluntly: Water pollution kills. In fact, it caused 1.8 million deaths in 2015, according to a study published in The Lancet . Contaminated water can also make you ill. Every year, unsafe water sickens about 1 billion people. And low-income communities are disproportionately at risk because their homes are often closest to the most polluting industries.

Waterborne pathogens, in the form of disease-causing bacteria and viruses from human and animal waste, are a major cause of illness from contaminated drinking water . Diseases spread by unsafe water include cholera, giardia, and typhoid. Even in wealthy nations, accidental or illegal releases from sewage treatment facilities, as well as runoff from farms and urban areas, contribute harmful pathogens to waterways. Thousands of people across the United States are sickened every year by Legionnaires’ disease (a severe form of pneumonia contracted from water sources like cooling towers and piped water), with cases cropping up from California’s Disneyland to Manhattan’s Upper East Side.

A woman using bottled water to wash her three-week-old son at their home in Flint, Michigan

Todd McInturf/The Detroit News/AP

Meanwhile, the plight of residents in Flint, Michigan —where cost-cutting measures and aging water infrastructure created a lead contamination crisis—offers a stark look at how dangerous chemical and other industrial pollutants in our water can be. The problem goes far beyond Flint and involves much more than lead, as a wide range of chemical pollutants—from heavy metals such as arsenic and mercury to pesticides and nitrate fertilizers —are getting into our water supplies. Once they’re ingested, these toxins can cause a host of health issues, from cancer to hormone disruption to altered brain function. Children and pregnant women are particularly at risk.

Even swimming can pose a risk. Every year, 3.5 million Americans contract health issues such as skin rashes, pinkeye, respiratory infections, and hepatitis from sewage-laden coastal waters, according to EPA estimates.

On the environment

In order to thrive, healthy ecosystems rely on a complex web of animals, plants, bacteria, and fungi—all of which interact, directly or indirectly, with each other. Harm to any of these organisms can create a chain effect, imperiling entire aquatic environments.

When water pollution causes an algal bloom in a lake or marine environment, the proliferation of newly introduced nutrients stimulates plant and algae growth, which in turn reduces oxygen levels in the water. This dearth of oxygen, known as eutrophication , suffocates plants and animals and can create “dead zones,” where waters are essentially devoid of life. In certain cases, these harmful algal blooms can also produce neurotoxins that affect wildlife, from whales to sea turtles.

Chemicals and heavy metals from industrial and municipal wastewater contaminate waterways as well. These contaminants are toxic to aquatic life—most often reducing an organism’s life span and ability to reproduce—and make their way up the food chain as predator eats prey. That’s how tuna and other big fish accumulate high quantities of toxins, such as mercury.

Marine ecosystems are also threatened by marine debris , which can strangle, suffocate, and starve animals. Much of this solid debris, such as plastic bags and soda cans, gets swept into sewers and storm drains and eventually out to sea, turning our oceans into trash soup and sometimes consolidating to form floating garbage patches. Discarded fishing gear and other types of debris are responsible for harming more than 200 different species of marine life.

Meanwhile, ocean acidification is making it tougher for shellfish and coral to survive. Though they absorb about a quarter of the carbon pollution created each year by burning fossil fuels, oceans are becoming more acidic. This process makes it harder for shellfish and other species to build shells and may impact the nervous systems of sharks, clownfish, and other marine life.

With your actions

We’re all accountable to some degree for today’s water pollution problem. Fortunately, there are some simple ways you can prevent water contamination or at least limit your contribution to it:

• Learn about the unique qualities of water where you live . Where does your water come from? Is the wastewater from your home treated? Where does stormwater flow to? Is your area in a drought? Start building a picture of the situation so you can discover where your actions will have the most impact—and see if your neighbors would be interested in joining in!
• Reduce your plastic consumption and reuse or recycle plastic when you can.
• Properly dispose of chemical cleaners, oils, and nonbiodegradable items to keep them from going down the drain.
• Maintain your car so it doesn’t leak oil, antifreeze, or coolant.
• If you have a yard, consider landscaping that reduces runoff and avoid applying pesticides and herbicides .
• Don’t flush your old medications! Dispose of them in the trash to prevent them from entering local waterways.
• Be mindful of anything you pour into storm sewers, since that waste often won’t be treated before being released into local waterways. If you notice a storm sewer blocked by litter, clean it up to keep that trash out of the water. (You’ll also help prevent troublesome street floods in a heavy storm.)
• If you have a pup, be sure to pick up its poop .

With your voice

One of the most effective ways to stand up for our waters is to speak out in support of the Clean Water Act, which has helped hold polluters accountable for five decades—despite attempts by destructive industries to gut its authority. But we also need regulations that keep pace with modern-day challenges, including microplastics, PFAS , pharmaceuticals, and other contaminants our wastewater treatment plants weren’t built to handle, not to mention polluted water that’s dumped untreated.

Tell the federal government, the U.S. Army Corps of Engineers, and your local elected officials that you support water protections and investments in infrastructure, like wastewater treatment, lead-pipe removal programs, and stormwater-abating green infrastructure. Also, learn how you and those around you can get involved in the policymaking process . Our public waterways serve every one of us. We should all have a say in how they’re protected.

This story was originally published on May 14, 2018, and has been updated with new information and links.

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Essay on Water Quality

Students are often asked to write an essay on Water Quality in their schools and colleges. And if you’re also looking for the same, we have created 100-word, 250-word, and 500-word essays on the topic.

Let’s take a look…

100 Words Essay on Water Quality

What is water quality.

Water quality tells us how clean or dirty water is. It is important because it affects the health of people, animals, and plants. Clean water is safe to drink and supports life.

Why Water Quality Matters

Good water quality is crucial for our health. Drinking dirty water can make us very sick. It also matters for fish and other water animals to live.

Things That Pollute Water

Many things can make water dirty. Chemicals from factories, waste from homes, and oil spills are big problems. These pollutants harm water quality.

Keeping Water Clean

To keep water clean, we should not throw trash or chemicals into water. Everyone can help by being careful about what goes down the drain.

250 Words Essay on Water Quality

Water quality: the foundation of life, water is the elixir of life, sustaining all living organisms on our planet. its quality directly impacts our health and well-being. good water quality ensures clean drinking water, healthy ecosystems, and thriving communities., sources of water pollution, numerous factors contribute to water pollution. industrial waste, agricultural runoff, sewage discharge, and littering are major culprits. these pollutants contaminate water sources, making them unsafe for consumption and damaging aquatic life., consequences of poor water quality, poor water quality leads to a range of health issues, including waterborne diseases like cholera, typhoid, and dysentery. contaminated water also affects aquatic ecosystems, leading to biodiversity loss and disrupting the food chain. additionally, it hinders economic activities like fishing and tourism, which rely on clean water., water treatment and conservation, to ensure access to clean water, water treatment facilities employ various methods like filtration, disinfection, and reverse osmosis. these processes remove impurities and harmful substances, making water safe for consumption. water conservation practices such as rainwater harvesting, leak detection, and efficient irrigation techniques help reduce demand and preserve water resources., individual and collective action, improving water quality requires collective efforts. as individuals, we can reduce our water footprint by taking shorter showers, fixing leaky faucets, and using water-saving appliances. additionally, supporting policies that promote water conservation, pollution control, and sustainable development is crucial. in conclusion, water quality is paramount to life on earth. by understanding the sources of pollution, its consequences, and the importance of water treatment and conservation, we can work together to protect this vital resource and ensure a healthy future for generations to come., 500 words essay on water quality.

Water is the elixir of life, an indispensable resource that sustains all living organisms on Earth. Its quality directly impacts our health, environment, and overall well-being. Understanding water quality and taking steps to preserve it are crucial for ensuring a healthy and sustainable future.

Various human activities contribute to water pollution, contaminating our precious water sources. Industrial waste, agricultural runoff, sewage discharge, and littering are major culprits. These pollutants, when released into water bodies, can cause severe damage to aquatic ecosystems and pose health risks to humans.

Effects of Water Pollution

Polluted water has numerous detrimental effects. It can cause a range of waterborne diseases, such as diarrhea, typhoid, and cholera, when consumed. Additionally, it harms aquatic life, leading to a decline in biodiversity and disruption of the food chain. Water pollution also affects the aesthetics of water bodies, making them unpleasant for recreational activities like swimming and fishing.

Importance of Water Quality

Maintaining good water quality is essential for several reasons. It ensures safe drinking water, preventing waterborne diseases and promoting public health. Healthy water bodies support thriving aquatic ecosystems, providing habitat for diverse plants and animals. Clean water is also vital for various economic activities, including agriculture, fishing, and tourism, contributing to sustainable livelihoods.

Water Quality Monitoring

Monitoring water quality is crucial for assessing its health and taking appropriate action to protect it. Regular testing for various parameters, such as pH, dissolved oxygen, and the presence of pollutants, helps identify potential problems and track water quality trends over time. This information is essential for developing effective water management and pollution control strategies.

Water Conservation and Preservation

Conserving water and preventing pollution are critical steps in maintaining water quality. Reducing water consumption, using water-efficient appliances, and fixing leaky faucets can help conserve precious water resources. Additionally, implementing pollution control measures, such as wastewater treatment plants and proper waste disposal systems, helps minimize the discharge of pollutants into water bodies.

Water quality is a fundamental aspect of our planet’s health and well-being. With increasing human activities, protecting our water resources from pollution is more crucial than ever. By understanding the sources and effects of water pollution, and implementing effective water quality monitoring and conservation measures, we can ensure a sustainable future where clean water is accessible to all.

That’s it! I hope the essay helped you.

If you’re looking for more, here are essays on other interesting topics:

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• Essay on Water Is Essential For Life
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Discharge from a Chinese fertilizer factory winds its way toward the Yellow River. Like many of the world's rivers, pollution remains an ongoing problem.

Water pollution is a rising global crisis. Here’s what you need to know.

The world's freshwater sources receive contaminants from a wide range of sectors, threatening human and wildlife health.

From big pieces of garbage to invisible chemicals, a wide range of pollutants ends up in our planet's lakes, rivers, streams, groundwater, and eventually the oceans. Water pollution—along with drought, inefficiency, and an exploding population—has contributed to a freshwater crisis , threatening the sources we rely on for drinking water and other critical needs.

Research has revealed that one pollutant in particular is more common in our tap water than anyone had previously thought: PFAS, short for poly and perfluoroalkyl substances. PFAS is used to make everyday items resistant to moisture, heat, and stains; some of these chemicals have such long half-lives that they are known as "the forever chemical."

Safeguarding water supplies is important because even though nearly 70 percent of the world is covered by water, only 2.5 percent of it is fresh. And just one percent of freshwater is easily accessible, with much of it trapped in remote glaciers and snowfields.

Water pollution causes

Water pollution can come from a variety of sources. Pollution can enter water directly, through both legal and illegal discharges from factories, for example, or imperfect water treatment plants. Spills and leaks from oil pipelines or hydraulic fracturing (fracking) operations can degrade water supplies. Wind, storms, and littering—especially of plastic waste —can also send debris into waterways.

Thanks largely to decades of regulation and legal action against big polluters, the main cause of U.S. water quality problems is now " nonpoint source pollution ," when pollutants are carried across or through the ground by rain or melted snow. Such runoff can contain fertilizers, pesticides, and herbicides from farms and homes; oil and toxic chemicals from roads and industry; sediment; bacteria from livestock; pet waste; and other pollutants .

Finally, drinking water pollution can happen via the pipes themselves if the water is not properly treated, as happened in the case of lead contamination in Flint, Michigan , and other towns. Another drinking water contaminant, arsenic , can come from naturally occurring deposits but also from industrial waste.

Freshwater pollution effects

Water pollution can result in human health problems, poisoned wildlife, and long-term ecosystem damage. When agricultural and industrial runoff floods waterways with excess nutrients such as nitrogen and phosphorus, these nutrients often fuel algae blooms that then create dead zones , or low-oxygen areas where fish and other aquatic life can no longer thrive.

Algae blooms can create health and economic effects for humans, causing rashes and other ailments, while eroding tourism revenue for popular lake destinations thanks to their unpleasant looks and odors. High levels of nitrates in water from nutrient pollution can also be particularly harmful to infants , interfering with their ability to deliver oxygen to tissues and potentially causing " blue baby syndrome ." The United Nations Food and Agriculture Organization estimates that 38 percent of the European Union's water bodies are under pressure from agricultural pollution.

Globally, unsanitary water supplies also exact a health toll in the form of disease. At least 2 billion people drink water from sources contaminated by feces, according to the World Health Organization , and that water may transmit dangerous diseases such as cholera and typhoid.

Freshwater pollution solutions

In many countries, regulations have restricted industry and agricultural operations from pouring pollutants into lakes, streams, and rivers, while treatment plants make our drinking water safe to consume. Researchers are working on a variety of other ways to prevent and clean up pollution. National Geographic grantee Africa Flores , for example, has created an artificial intelligence algorithm to better predict when algae blooms will happen. A number of scientists are looking at ways to reduce and cleanup plastic pollution .

There have been setbacks, however. Regulation of pollutants is subject to changing political winds, as has been the case in the United States with the loosening of environmental protections that prevented landowners from polluting the country’s waterways.

Anyone can help protect watersheds by disposing of motor oil, paints, and other toxic products properly , keeping them off pavement and out of the drain. Be careful about what you flush or pour down the sink, as it may find its way into the water. The U.S. Environmental Protection Agency recommends using phosphate-free detergents and washing your car at a commercial car wash, which is required to properly dispose of wastewater. Green roofs and rain gardens can be another way for people in built environments to help restore some of the natural filtering that forests and plants usually provide.

For Hungry Minds

Related topics.

• WATER POLLUTION
• ENVIRONMENT AND CONSERVATION
• FRESH WATER
• GROUNDWATER
• WATER QUALITY
• WATER RESOURCES

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A comprehensive review of water quality indices (WQIs): history, models, attempts and perspectives

• Review paper
• Published: 11 March 2023
• Volume 22 , pages 349–395, ( 2023 )

Cite this article

• Sandra Chidiac   ORCID: orcid.org/0000-0002-1822-119X 1 ,
• Paula El Najjar 1 , 2 ,
• Naim Ouaini 1 ,
• Youssef El Rayess 1 &
• Desiree El Azzi 1 , 3  

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Water quality index (WQI) is one of the most used tools to describe water quality. It is based on physical, chemical, and biological factors that are combined into a single value that ranges from 0 to 100 and involves 4 processes: (1) parameter selection, (2) transformation of the raw data into common scale, (3) providing weights and (4) aggregation of sub-index values. The background of WQI is presented in this review study. the stages of development, the progression of the field of study, the various WQIs, the benefits and drawbacks of each approach, and the most recent attempts at WQI studies. In order to grow and elaborate the index in several ways, WQIs should be linked to scientific breakthroughs (example: ecologically). Consequently, a sophisticated WQI that takes into account statistical methods, interactions between parameters, and scientific and technological improvement should be created in order to be used in future investigations.

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1 Introduction

Water is the vital natural resource with social and economic values for human beings (Kumar 2018 ). Without water, existence of man would be threatened (Zhang 2017 ). The most important drinking sources in the world are surface water and groundwater (Paun et al. 2016 ).

Currently, more than 1.1 billion people do not have access to clean drinking water and it is estimated that nearly two-thirds of all nations will experience water stress by the year 2025 (Kumar 2018 ).

With the extensive social and economic growth, such as human factors, climate and hydrology may lead to accumulation of pollutants in the surface water that may result in gradual change of the water source quality (Shan 2011 ).

The optimal quantity and acceptable quality of water is one of the essential needs to survive as mentioned earlier, but the maintenance of an acceptable quality of water is a challenge in the sector of water resources management (Mukate et al. 2019 ). Accordingly, the water quality of water bodies can be tested through changes in physical, chemical and biological characteristics related to anthropogenic or natural phenomena (Britto et al. 2018 ).

Therefore, water quality of any specific water body can be tested using physical, chemical and biological parameters also called variables, by collecting samples and obtaining data at specific locations (Britto et al. 2018 ; Tyagi et al. 2013 ).

To that end, the suitability of water sources for human consumption has been described in terms of Water Quality Index (WQI), which is one of the most effective ways to describe the quality of water, by reducing the bulk of information into a single value ranging between 0 and 100 (Tyagi et al. 2013 ).

Hence, the objective of the study is to review the WQI concept by listing some of the important water quality indices used worldwide for water quality assessment, listing the advantages and disadvantages of the selected indices and finally reviewing some water quality studies worldwide.

2 Water quality index

2.1 history of water quality concept.

In the last decade of the twentieth century, many organizations involved in water control, used the water quality indices for water quality assessment (Paun et al. 2016 ). In the 1960’s, the water quality indices was introduced to assess the water quality in rivers (Hamlat et al. 2017 ).

Horton ( 1965 ), initially developed a system for rating water quality through index numbers, offering a tool for water pollution abatement, since the terms “water quality” and “pollution” are related. The first step to develop an index is to select a list of 10 variables for the index’s construction, which are: sewage treatment, dissolved oxygen (DO), pH, coliforms, electroconductivity (EC), carbon chloroform extract (CCE), alkalinity, chloride, temperature and obvious pollution. The next step is to assign a scale value between zero and 100 for each variable depending on the quality or concentration. The last step, is to designate to each variable is a relative weighting factor to show their importance and influence on the quality index (the higher the assigned weight, the more impact it has on the water quality index, consequently it is more important) (Horton 1965 ).

Later on, Brown et al. ( 1970 ) established a new water quality index (WQI) with nine variables: DO, coliforms, pH, temperature, biochemical oxygen demand (BOD), total phosphate, nitrate concentrations, turbidity and solid content based on a basic arithmetic weighting using arithmetic mean to calculate the rating of each variable. These rates are then converted not temporary weights. Finally, each temporary weight is divided by the sum of all the temporary weights in order to get the final weight of each variable (Kachroud et al. 2019a ; Shah and Joshi 2017 ). In 1973, Brown et al., considered that a geometric aggregation (a way to aggregate variables, and being more sensitive when a variable exceeds the norm) is better than an arithmetic one. The National Sanitation Foundation (NSF) supported this effort (Kachroud et al. 2019a ; Shah and Joshi 2017 ).

Steinhart et al. ( 1982 ) developed a novel environmental quality index (EQI) for the Great Lakes ecosystem in North America. Nine variables were selected for this index: biological, physical, chemical and toxic. These variables were: specific conductance or electroconductivity, chloride, total phosphorus, fecal Coliforms, chlorophyll a , suspended solids, obvious pollution (aesthetic state), toxic inorganic contaminants, and toxic organic contaminants. Raw data were converted to subindex and each subindex was multiplied by a weighting factor (a value of 0.1 for chemical, physical and biological factors but 0.15 for toxic substances). The final score ranged between 0 (poor quality) and 100 (best quality) (Lumb et al. 2011a ; Tirkey et al. 2015 ).

Dinius ( 1987 ), developed a WQI based on multiplicative aggregation having a scale expressed with values as percentage, where 100% expressed a perfect water quality (Shah and Joshi 2017 ).

In the mid 90’s, a new WQI was introduced to Canada by the province of British Columbia, and used as an increasing index to evaluate water quality (Lumb et al. 2011b ; Shah and Joshi 2017 ). A while after, the Water Quality Guidelines Task Group of the Canadian Council of Ministers of the Environment (CCME) modified the original British Columbia Water Quality Index (BCWQI) and endorsed it as the CCME WQI in 2001(Bharti and Katyal 2011 ; Lumb et al. 2011b ).

In 1996, the Watershed Enhancement Program (WEPWQI) was established in Dayton Ohio, including water quality variables, flow measurements and water clarity or turbidity. Taking into consideration pesticide and Polycyclic Aromatic Hydrocarbon (PAH) contamination, is what distinguished this index from the NSFWQI (Kachroud et al. 2019a , b ).

Liou et al. (2003) established a WQI in Taiwan on the Keya River. The index employed thirteen variables: Fecal coliforms, DO, ammonia nitrogen, BOD, suspended solids, turbidity, temperature, pH, toxicity, cadmium (Cd), lead (Pb), copper (Cu) and zinc (Zn). These variables were downsized to nine based on environmental and health significance: Fecal coliforms, DO, ammonia nitrogen, BOD, suspended solids, turbidity, temperature, pH and toxicity. Each variable was converted into an actual value ranging on a scale from 0 to 100 (worst to highest). This index is based on the geometric means (an aggregation function that could eliminate the ambiguous caused from smaller weightings) of the standardized values (Akhtar et al. 2021 ; Liou et al. 2004 ; Uddin et al. 2021 ).

Said et al. ( 2004 ) implemented a new WQI using the logarithmic aggregation applied in streams waterbodies in Florida (USA), based on only 5 variables: DO, total phosphate, turbidity, fecal coliforms and specific conductance. The main idea was to decrease the number of variables and change the aggregation method using the logarithmic aggregation (this function does not require any sub-indices and any standardization of the variables). This index ranged from 0 to 3, the latter being the ideal value (Akhtar et al. 2021 ; Kachroud et al. 2019a , b ; Said et al. 2004 ; Uddin et al. 2021 ).

The Malaysian WQI (MWQI) was carried out in 2007, including six variables: DO, BOD, Chemical Oxygen Demand (COD), Ammonia Nitrogen, suspended solids and pH. For each variable, a curve was established to transform the actual value of the variable into a non-dimensional sub-index value.

The next step is to determine the weighting of the variables by considering the experts panel opinions. The final score is determined using the additive aggregation formula (where sub-indices values and their weightings are summed), extending from 0 (polluted) to 100 (clean) (Uddin et al. 2021 ).

The Hanh and Almeida indices were established respectively in 2010 on surface water in Vietnam and 2012 on the Potrero de los Funes in Argentina, based on 8 (color, suspended solids, DO, BOD, COD, chloride, total coliforms and orthophosphate) and 10 (color, pH, COD, fecal coliforms, total coliforms, total phosphate, nitrates, detergent, enterococci and Escherichia coli .) water quality variables. Both indices were based on rating curve- based sum-indexing system (Uddin et al. 2021 ).

The most recent developed WQI model in the literature was carried out in 2017. This index tried to reduce uncertainty present in other water quality indices. The West Java Water Quality Index (WJWQI) applied in the Java Sea in Indonesia was based on thirteen crucial water quality variables: temperature, suspended solids, COD, DO, nitrite, total phosphate, detergent, phenol, chloride, Zn, Pb, mercury (Hg) and fecal coliforms. Using two screening steps (based on statistical assessment), parameter (variable) redundancy was determined to only 9: temperature, suspended solids, COD, DO, nitrite, total phosphate, detergent, phenol and chloride. Sub-indices were obtained for those nine variables and weights were allocated based on expert opinions, using the same multiplicative aggregation as the NSFWQI. The WJWQI suggested 5 quality classes ranging from poor (5–25) to excellent (90–100) (Uddin et al. 2021 ).

2.2 Phases of WQI development

Mainly, WQI concept is based on many factors as displayed in Fig.  1 and described in the following steps:

Phases of WQI development

Parameter selection for measurement of water quality (Shah and Joshi 2017 ):

The selection is carried out based on the management objectives and the environmental characteristics of the research area (Yan et al. 2015 ). Many variables are recommended, since they have a considerable impact on water quality and derive from 5 classes namely, oxygen level, eutrophication, health aspects, physical characteristics and dissolved substances (Tyagi et al. 2013 ).

Transformation of the raw data parameter into a common scale (Paun et al. 2016 ):

Different statistical approach can be used for transformation, all parameters are transformed from raw data that have different dimensions and units (ppm, saturation, percentage etc.) into a common scale, a non-dimensional scale and sub-indices are generated (Poonam et al. 2013 ; Tirkey et al. 2015 ).

Providing weights to the parameters (Tripathi and Singal 2019 ):

Weights are assigned to each parameter according to their importance and their impact on water quality, expert opinion is needed to assign weights (Tirkey et al. 2015 ). Weightage depends on the permissible limits assigned by International and National agencies in water drinking (Shah and Joshi 2017 ).

Aggregation of sub-index values to obtain the final WQI:

WQI is the sum of rating and weightage of all the parameters (Tripathi and Singal 2019 ).

It is important to note that in some indices, statistical approaches are commonly used such as factor analysis (FA), principal component analysis (PCA), discriminant analysis (DA) and cluster analysis (CA). Using these statistical approaches improves accuracy of the index and reduce subjective assumptions (Tirkey et al. 2015 ).

2.3 Evolution of WQI research

2.3.1 per year.

According to Scopus ( 2022 ), the yearly evolution of WQI's research is illustrated in Fig.  2 (from 1978 till 2022).

Evolution of WQI research per year (Scopus 2022 )

Overall, it is clear that the number of research has grown over time, especially in the most recent years. The number of studies remained shy between 1975 and 1988 (ranging from 1 to 13 research). In 1998, the number improved to 46 studies and increased gradually to 466 publications in 2011.The WQI's studies have grown significantly over the past decade, demonstrating that the WQI has become a significant research topic with the goal of reaching its maximum in 2022 (1316 studies) (Scopus, 2022 ).

2.3.2 Per country

In Fig.  3 , the development of WQI research is depicted visually per country from 1975 to 2022.

Evolution of WQI research per country (Scopus 2022 )

According to Scopus ( 2022 ), the top three countries were China, India and the United States, with 2356, 1678 and 1241 studies, respectively. Iran, Brazil, and Italy occupy the fourth, fifth, and sixth spots, respectively (409, 375 and 336 study). Malaysia and Spain have approximately the same number of studies, respectively 321 and 320 study. The studies in the remaining countries decrease gradually from 303 document in Spain to 210 documents in Turkey. This demonstrates that developing nations, like India, place a high value on the development of water quality protection even though they lack strong economic power, cutting-edge technology, and a top-notch scientific research team. This is because water quality is crucial to the long-term social and economic development of those nations (Zhang 2019 ).

2.4 Different methods for WQI determination

Water quality indices are tools to determine water quality. Those indices demand basic concepts and knowledge about water issues (Singh et al. 2013 ). There are many water quality indices such as the: National Sanitation Foundation Water Quality Index (NSFWQI), Canadian Council of Ministers of Environment Water Quality Index (CCMEWQI), Oregon Water Quality Index (OWQI), and Weight Arithmetic Water Quality Index (WAWQI) (Paun et al. 2016 ).

These water quality indices are applied in particular areas, based on many parameters compared to specific regional standards. Moreover, they are used to illustrate annual cycles, spatio-temporal variations and trends in water quality (Paun et al. 2016 ). That is to say that, these indices reflect the rank of water quality in lakes, streams, rivers, and reservoirs (Kizar 2018 ).

Accordingly, in this section a general review of available worldwide used indices is presented.

2.4.1 National sanitation foundation (NSFWQI)

The NSFWQI was developed in 1970 by the National Sanitation Foundation (NSF) of the United States (Hamlat et al. 2017 ; Samadi et al. 2015 ). This WQI has been widely field tested and is used to calculate and evaluate the WQI of many water bodies (Hamlat et al. 2017 ). However, this index belongs to the public indices group. It represents a general water quality and does not take into account the water’s use capacities, furthermore, it ignores all types of water consumption in the evaluation process (Bharti and Katyal 2011 ; Ewaid 2017 ).

The NSFWQI has been widely applied and accepted in Asian, African and European countries (Singh et al. 2013 ), and is based on the analysis of nine variables or parameters, such as, BOD, DO, Nitrate (NO 3 ), Total Phosphate (PO 4 ), Temperature, Turbidity, Total Solids(TS), pH, and Fecal Coliforms (FC).

Some of the index parameters have different importance, therefore, a weighted mean for each parameter is assigned, based on expert opinion which have grounded their opinions on the environmental significance, the recommended principles and uses of water body and the sum of these weights is equal to 1 (Table 1 ) (Ewaid 2017 ; Uddin et al. 2021 ).

Due to environmental issues, the NSFWQI has changed overtime. The TS parameter was substituted by the Total Dissolved Solids (TDS) or Total Suspended Solids (TSS), the Total Phosphate by orthophosphate, and the FC by E. coli (Oliveira et al. 2019 ).

The mathematical expression of the NSFWQI is given by the following Eq. ( 1 ) (Tyagi et al. 2013 ):

where, Qi is the sub-index for ith water quality parameter. Wi is the weight associated with ith water quality parameter. n is the number of water quality parameters.

This method ranges from 0 to 100, where 100 represents perfect water quality conditions, while zero indicates water that is not suitable for the use and needs further treatment (Samadi et al. 2015 ).

The ratings are defined in the following Table 2 .

In 1972, the Dinius index (DWQI) happened to be the second modified version of the NSF (USA). Expended in 1987 using the Delphi method, the DWQI included twelve parameters (with their assigned weights): Temperature (0.077), color (0.063), pH (0.077), DO (0.109), BOD (0.097), EC (0.079), alkalinity (0.063), chloride (0.074), coliform count (0.090), E. coli (0.116). total hardness (0.065) and nitrate (0.090). Without any conversion process, the DWQI used the measured variable concentrations directly as the sub-index values (Kachroud et al. 2019b ; Uddin et al. 2021 ).

Sukmawati and Rusni assessed in 2018 the water quality in Beratan lake (Bali), choosing five representative stations for water sampling representing each side of the lake, using the NSFWQI. NSFWQI’s nine parameters mentioned above were measured in each station. The findings indicated that the NSFWQI for the Beratan lake was seventy-eight suggesting a good water quality. Despite this, both pH and FC were below the required score (Sukmawati and Rusni 2019 ).

The NSFWQI indicated a good water quality while having an inadequate value for fecal coliforms and pH. For that reason, WQIs must be adapted and developed so that any minor change in the value of any parameter affects the total value of the water quality index.

A study conducted by Zhan et al. ( 2021 ) , concerning the monitoring of water quality and examining WQI trends of raw water in Macao (China) was established from 2002 to 2019 adopting the NSFWQI. NSFWQI's initial model included nine parameters (DO, FC, pH, BOD, temperature, total phosphates, and nitrates), each parameter was given a weight and the parameters used had a significant impact on the WQI calculation outcomes. Two sets of possible parameters were investigated in this study in order to determine the impact of various parameters. The first option was to keep the original 9-parameter model, however, in the second scenario, up to twenty-one parameters were chosen, selected by Principal Component Analysis (PCA).

The latter statistical method was used to learn more about the primary elements that contributed to water quality variations, and to calculate the impact of each attribute on the quality of raw water. Based on the PCA results, the 21-parameter model was chosen. The results showed that the quality of raw water in Macao has been relatively stable in the period of interest and appeared an upward trend overall. Furthermore, the outcome of environmental elements, such as natural events, the region's hydrology and meteorology, can have a significant impact on water quality. On the other hand, Macao's raw water quality met China's Class III water quality requirements and the raw water pollution was relatively low. Consequently, human activities didn’t have a significant impact on water quality due to effective treatment and protection measures (Zhan et al. 2021 ).

Tampo et al. ( 2022 ) undertook a recent study in Adjougba (Togo), in the valley of Zio River. Water samples were collected from the surface water (SW), ground water (GW) and treated wastewater (TWW), intending to compare the water quality of these resources for irrigation and domestic use.

Hence, WQIs, water suitability indicators for irrigation purposes (WSI-IPs) and raw water quality parameters were compared using statistical analysis (factor analysis and Spearman’s correlation).

Moreover, the results proposed that he water resources are suitable for irrigation and domestic use: TWW suitable for irrigation use, GW suitable for domestic use and SW suitable for irrigation use.

The NSFWQI and overall index of pollution (OPI) parameters were tested, and the results demonstrated that the sodium absorption ratio, EC, residual sodium carbonate, Chloride and FC are the most effective parameters for determining if water is suitable for irrigation.

On the other hand, EC, DO, pH, turbidity, COD, hardness, FC, nitrates, national sanitation foundation's water quality index (NSFWQI), and overall index of pollution (OPI) are the most reliable in the detection of water suitability for domestic use (Tampo et al. 2022 ).

Following these studies, it is worth examining the NSFWQI. This index can be used with other WQI models in studies on rivers, lakes etc., since one index can show different results than another index, in view of the fact that some indices might be affected by other variations such as seasonal variation.

Additionally, the NSFWQI should be developed and adapted to each river, so that any change in any value will affect the entire water quality. It is unhelpful to have a good water quality yet a low score of a parameter that can affect human health (case of FC).

2.4.2 Canadian council of ministers of the environment water quality index (CCMEWQI)

The Canadian Water Quality Index adopted the conceptual model of the British Colombia Water Quality Index (BCWQI), based on relative sub-indices (Kizar 2018 ).

The CCMEWQI provides a water quality assessment for the suitability of water bodies, to support aquatic life in specific monitoring sites in Canada (Paun et al. 2016 ). In addition, this index gives information about the water quality for both management and the public. It can furthermore be applied in many water agencies in various countries with slight modification (Tyagi et al. 2013 ).

The CCMEWQI method simplifies the complex and technical data. It tests the multi-variable water quality data and compares the data to benchmarks determined by the user (Tirkey et al. 2015 ). The sampling protocol requires at least four parameters sampled at least four times but does not indicate which ones should be used; the user must decide ( Uddin et al. 2021 ). Yet, the parameters may vary from one station to another (Tyagi et al. 2013 ).

After the water body, the objective and the period of time have been defined the three factors of the CWQI are calculated (Baghapour et al. 2013 ; Canadian Council of Ministers of the Environment 1999 ):

The scope (F1) represents the percentage of variables that failed to meet the objective (above or below the acceptable range of the selected parameter) at least once (failed variables), relative to the total number of variables.

The frequency (F2) represents the percentage of tests which do not meet the objectives (above or below the acceptable range of the selected parameter) (failed tests).

The amplitude represents the amount by which failed tests values did not meet their objectives (above or below the acceptable range of the selected parameter). It is calculated in three steps.

The excursion is termed each time the number of an individual parameter is further than (when the objective is a minimum, less than) the objective and is calculated by two Eqs. ( 4 , 5 ) referring to two cases. In case the test value must not exceed the objective:

For the cases in which the test value must not fall below the objective:

The normalized sum of excursions, or nse , is calculated by summing the excursions of individual tests from their objectives and diving by the total number of tests (both meetings and not meeting their objectives):

F3 is then calculated an asymptotic function that scales the normalized sum of the excursions from objectives (nse) to yield a range between 0 and 100:

Finally, the CMEWQI can be obtained from the following equation, where the index changes in direct proportion to changes in all three factors.

where 1.732 is a scaling factor and normalizes the resultant values to a range between 0 and 100, where 0 refers to the worst quality and one hundred represents the best water quality.

Once the CCME WQI value has been determined, water quality in ranked as shown in Table 3

Ramírez-Morales et al. ( 2021 ) investigated in their study the measuring of pesticides and water quality indices in three agriculturally impacted micro catchments in Costa Rica between 2012 and 2014. Surface water and sediment samples were obtained during the monitoring experiment.

The specifications of the water included: Pesticides, temperature, DO, oxygen saturation, BOD, TP, NO3, sulfate, ammonium, COD, conductivity, pH and TSS.

Sediment parameters included forty-two pesticides with different families including carbamate, triazine, organophosphate, phthalimide, pyrethroid, uracil, benzimidazole, substituted urea, organochlorine, imidazole, oxadiazole, diphenyl ether and bridged diphenyl.

WQIs are effective tools since they combine information from several variables into a broad picture of the water body's state. Two WQIs were calculated using the physicochemical parameters: The Canadian Council of Ministers of the Environment (CCME) WQI and the National Sanitation Foundation (NSF) WQI.

These were chosen since they are both extensively used and use different criteria to determine water quality: The NSF WQI has fixed parameters, weights, and threshold values, whereas the CCME has parameters and threshold values that are customizable.

The assessment of water quality using physico-chemical characteristics and the WQI revealed that the CCME WQI and the NSF WQI have distinct criteria. CCME WQI categorized sampling point as marginal/bad quality, while most sampling locations were categorized as good quality in the NSF WQI. Seemingly, the water quality classifications appeared to be affected by seasonal variations: during the wet season, the majority of the CCME WQI values deteriorated, implying that precipitation and runoff introduced debris into the riverbed. Thus, it’s crucial to compare WQIs because they use various factors, criteria, and threshold values, which might lead to different outcomes (Ramírez-Morales et al. 2021 ).

Yotova et al. ( 2021 ) directed an analysis on the Mesta River located between Greece and Bulgaria. The Bulgarian section of the Mesta River basin, which is under the supervision of the West-Aegean Region Basin Directorate, was being researched. The goal was to evaluate the surface water quality of ten points of the river using a novel approach that combines composite WQI developed by the CCME and Self organizing map (SOM) on the required monitoring data that include: DO, pH, EC, ammonium, nitrite, nitrate, total phosphate, BOD and TSS.

The use of WQI factors in SOM calculations allows for the identification of specific WQI profiles for various object groups and identifying groupings of river basin which have similar sampling conditions. The use of both could reveal and estimate the origin and magnitude of anthropogenic pressure. In addition, it might be determined that untreated residential wastewaters are to blame for deviations from high quality requirements in the Mesta River catchment.

Interestingly, this study reveals that WQI appear more accurate and specific when combined with a statistical test such as the SOM (Yotova et al. 2021 ).

2.4.3 Oregon water quality index (OWQI)

The Oregon Water Quality Index is a single number that creates a score to evaluate the water quality of Oregon’s stream and apply this method in other geographical region (Hamlat et al. 2017 ; Singh et al. 2013 ). The OWQI was widely accepted and applied in Oregon (USA) and Idaho (USA) (Sutadian et al. 2016 ).

Additionally, the OWQI is a variant of the NSFWQI, and is used to assess water quality for swimming and fishing, it is also used to manage major streams (Lumb et al. 2011b ). Since the introduction of the OWQI in 1970, the science of water quality has improved noticeably, and since 1978, index developers have benefited from increasing understanding of stream functionality (Bharti and Katyal 2011 ). The Oregon index belongs to the specific consumption indices group. It is a water classification based on the kind of consumption and application such as drinking, industrial, etc. (Shah and Joshi 2017 ).

The original OWQI dropped off in 1983, due to excessive resources required for calculating and reporting results. However, improvement in software and computer hardware availability, in addition to the desire for an accessible water quality information, renewed interest in the index (Cude 2001 ).

Simplicity, availability of required quality parameters, and the determination of sub-indexes by curve or analytical relations are some advantages of this approach (Darvishi et al. 2016a ). The process combines eight variables including temperature, dissolved oxygen (percent saturation and concentration), biochemical oxygen demand (BOD), pH, total solids, ammonia and nitrate nitrogen, total phosphorous and bacteria (Brown 2019 ). Equal weight parameters were used for this index and has the same effect on the final factor (Darvishi et al. 2016a ; Sutadian et al. 2016 ).

The Oregon index is calculated by the following Eq.  9 (Darvishi et al. 2016a ):

where,n is the number of parameters (n = 8) SI i is the value of parameter i.

Furthermore, the OWQI scores range from 10 for the worse case to 100 as the ideal water quality illustrated in the following Table 4 (Brown 2019 ).

Kareem et al. ( 2021 ) using three water quality indices, attempted to analyze the Euphrates River (Iraq) water quality for irrigation purposes in three different stations: WAWQI, CCMEWQI AND OWQI.

For fifteen parameters, the annual average value was calculated, which included: pH, BOD, Turbidity, orthophosphate, Total Hardness, Sulphate, Nitrate, Alkalinity, Potassium Sodium, Magnesium, Chloride, DO, Calcium and TDS.

The OWQI showed that the river is “very poor”, and since the sub-index of the OWQI does not rely on standard-parameter compliance, there are no differences between the two inclusion and exclusion scenarios, which is not the case in both WAWQI and CCMEWQI (Kareem et al. 2021 ).

Similarly, the OWQI showed a very bad quality category, and it is unfit for human consumption, compared to the NSFWQI and Wilcox indices who both showed a better quality of water in Darvishi et al., study conducted on the Talar River (Iran) (Darvishi et al. 2016b ).

2.4.4 Weighted arithmetic water quality index (WAWQI)

The weighted arithmetic index is used to calculate the treated water quality index, in other terms, this method classifies the water quality according to the degree of purity by using the most commonly measured water quality variables (Kizar 2018 ; Paun et al. 2016 ).This procedure has been widely used by scientists (Singh et al. 2013 ).

Three steps are essential in order to calculate the WAWQI:

Further quality rating or sub-index was calculated using the following equation (Jena et al. 2013 ):

Qn is the quality rating for the nth water quality parameter.

Vn is the observed value of the nth parameter at a given sampling station.

Vo is the ideal value of the nth parameter in a pure water.

Sn is the standard permissible value of the nth parameter.

The quality rating or sub index corresponding to nth parameter is a number reflecting the relative value of this parameter in polluted water with respect to its permissible standard value (Yogendra & Puttaiah 2008 ).

The unit weight was calculated by a value inversely proportional to the recommended standard values (Sn) of the corresponding parameters (Jena et al. 2013 ):

Wn is the unit weight for the nth parameter.

K is the constant of proportionality.

Sn is the standard value of the nth parameter.

The overall WQI is the aggregation of the quality rating (Qn) and the unit weight (Wn) linearly (Jena et al. 2013 ):

After calculating the WQI, the measurement scale classifies the water quality from “unsuitable water” to “excellent water quality” as given in the following Table 5 .

Sarwar et al. ( 2020 ) carried out a study in Chaugachcha and Manirampur Upazila of Jashore District (Bangladesh). The goal of this study was to determine the quality of groundwater and its appropriateness for drinking, using the WAWQI including nine parameters: turbidity, EC, pH, TDS, nitrate, ammonium, sodium, potassium and iron. Many samplings point was taken from Chaugachcha and Manirampur, and WQI differences were indicated (ranging from very poor to excellent). These variations in WQI were very certainly attributable to variances in geographical location. Another possibility could be variations in the parent materials from which the soil was created, which should be confirmed using experimental data. It is worth mentioning that every selected parameter was taken into consideration during calculation. Similarly, the water quality differed in Manirampur due to the elements contained in the water samples that had a big impact on the water quality (Sarwar et al. 2020 ).

In 2021, García-Ávila et al. undertook a comparative study between the CCMEWQI and WAWQI for the purpose of determining the water quality in the city of Azogues (Ecuador). Twelve parameters were analyzed: pH, turbidity, color, total dissolved solids, electrical conductivity, total hardness, alkalinity, nitrates, phosphates, sulfates, chlorides and residual chlorine over 6 months. The average WAWQI value was calculated suggesting that 16.67% of the distribution system was of 'excellent' quality and 83.33% was of 'good' quality, while the CCMEWQI indicated that 100% of the system was of ‘excellent’ quality.

This difference designated that the parameters having a low maximum allowable concentration have an impact on WAWQI and that WAWQI is a valuable tool to determine the quality of drinking water and have a better understanding of it (García-Ávila et al. 2022a , b ).

2.4.5 Additional water quality indices

The earliest WQI was based on a mathematical function that sums up all sub-indices, as detailed in the 2.1. History of water quality concept section (Aljanabi et al. 2021 ). The Dinius index (1972), the OWQI (1980), and the West Java index (2017) were later modified from the Horton index, which served as a paradigm for later WQI development (Banda and Kumarasamy 2020 ).

Based on eleven physical, chemical, organic, and microbiological factors, the Scottish Research Development Department (SRDDWQI) created in 1976 was based on the NSFWQI and Delphi methods used in Iran, Romania, and Portugal. Modified into the Bascaron index (1979) in Spain, which was based on 26 parameters that were unevenly weighted with a subjective representation that allowed an overestimation of the contamination level. The House index (1989) in the UK valued the parameters directly as sub-indices. The altered version was adopted as Croatia's Dalmatian index in 1999.

The Ross WQI (1977) was created in the USA using only 4 parameters and did not develop into any further indices.

In 1982, the Dalmatian and House WQI were used to create the Environmental Quality Index, which is detailed in Sect.  2.1 . This index continues to be difficult to understand and less powerful than other indices (Lumb et al. 2011a ; Uddin et al. 2021 ).

The Smith index (1990), is based on 7 factors and the Delphi technique in New Zealand, attempts to eliminate eclipsing difficulties and does not apply any weighting, raising concerns about the index's accuracy (Aljanabi et al. 2021 ; Banda and Kumarasamy 2020 ; Uddin et al. 2021 ).

The Dojildo index (1994) was based on 26 flexible, unweighted parameters and does not represent the water's total quality.

With the absence of essential parameters, the eclipse problem is a type of fixed-parameter selection. The Liou index (2004) was established in Taiwan to evaluate the Keya River based on 6 water characteristics that were immediately used into sub-index values. Additionally, because of the aggregation function, uncertainty is unrelated to the lowest sub-index ranking (Banda and Kumarasamy 2020 ; Uddin et al. 2021 ).

Said index (2004) assessed water quality using only 4 parameters, which is thought to be a deficient number for accuracy and a comprehensive picture of the water quality. Furthermore, a fixed parameter system prevents the addition of any new parameters.

Later, the Hanh index (2010), which used hybrid aggregation methods and gave an ambiguous final result, was developed from the Said index.

In addition to eliminating hazardous and biological indicators, the Malaysia River WQI (MRWQI developed in the 2.1 section) (2007) was an unfair and closed system that was relied on an expert's judgment, which is seen as being subjective and may produce ambiguous findings (Banda and Kumarasamy 2020 ; Uddin et al. 2021 ).

Table illustrated the main data of the studies published during 2020–2022 on water quality assessments and their major findings:

2.5 Advantages and disadvantages of the selected water quality indices

A comparison of the selected indices is done by listing the advantages and disadvantages of every index listed in the Table 7 below.

2.6 New attempts of WQI studies

Many studies were conducted to test the water quality of rivers, dams, groundwater, etc. using multiple water quality indices throughout the years. Various studies have been portrayed here in.

Massoud ( 2012 ) observed during a 5-year monitoring period, in order to classify the spatial and temporal variability and classify the water quality along a recreational section of the Damour river using a weighted WQI from nine physicochemical parameters measured during dry season. The WWQI scale ranged between “very bad” if the WQI falls in the range 0–25, to “excellent” if it falls in the range 91–100. The results revealed that the water quality of the Damour river if generally affected by the activities taking place along the watershed. The best quality was found in the upper sites and the worst at the estuary, due to recreational activities. If the Damour river is to be utilized it will require treatment prior any utilization (Massoud 2012 ).

Rubio-Arias et al. ( 2012 ) conducted a study in the Luis L. Leon dam located in Mexico. Monthly samples were collected at 10 random points of the dam at different depths, a total of 220 samples were collected and analyzed. Eleven parameters were considered for the WQI calculation, and WQI was calculated using the Weighted WQI equation and could be classified according to the following ranges: < 2.3 poor; from 2.3 to 2.8 good; and > 2.8 excellent. Rubio-Arias et al., remarked that the water could be categorized as good during the entire year. Nonetheless, some water points could be classified as poor due to some anthropogenic activities such as intensive farming, agricultural practices, dynamic urban growth, etc. This study confirms that water quality declined after the rainy season (Rubio-Arias et al. 2012 ).

In the same way, Haydar et al. ( 2014 ) evaluated the physical, chemical and microbiological characteristics of water in the upper and lower Litani basin, as well as in the lake of Qaraaoun. The samples were collected during the seasons of 2011–2012 from the determined sites and analyzed by PCA and the statistical computations of the physico-chemical parameters to extract correlation between variables. Thus, the statistical computations of the physico-chemical parameters showed a correlation between some parameters such as TDS, EC, Ammonium, Nitrate, Potassium and Phosphate. Different seasons revealed the presence of either mineral or anthropogenic or both sources of pollution caused by human interference from municipal wastewater and agricultural purposes discharged into the river. In addition, temporal effects were associated with seasonal variations of river flow, which caused the dilution if pollutants and, hence, variations in water quality (Haydar et al. 2014 ).

Another study conducted by Chaurasia et al., ( 2018 ), proposed a groundwater quality assessment in India using the WAWQI. Twenty-two parameters were taken into consideration for this assessment, however, only eight important parameters were chosen to calculate the WQI. The rating of water quality shows that the ground water in 20% of the study area is not suitable for drinking purpose and pollution load is comparatively high during rainy and summer seasons. Additionally, the study suggests that priority should be given to water quality monitoring and its management to protect the groundwater resource from contamination as well as provide technology to make the groundwater fit for domestic and drinking (Chaurasia et al. 2018 ).

Daou et al. ( 2018 ) evaluated the water quality of four major Lebanese rivers located in the four corners of Lebanon: Damour, Ibrahim, Kadisha and Orontes during the four seasons of the year 2010–2011. The assessment was done through the monitoring of a wide range of physical, chemical and microbiological parameters, these parameters were screened using PCA. PCA was able to discriminate each of the four rivers according to a different trophic state. The Ibrahim River polluted by mineral discharge from marble industries in its surroundings, as well as anthropogenic pollutants, and the Kadisha river polluted by anthropogenic wastes seemed to have the worst water quality. This large-scale evaluation of these four Lebanese rivers can serve as a water mass reference model (Daou et al. 2018 ).

Moreover, some studies compared many WQI methods. Kizar ( 2018 ), carried out a study on Shatt Al-Kufa in Iraq, nine locations and twelve parameters were selected. The water quality was calculated using two methods, the WAWQI and CWQI. The results revealed the same ranking of the river for both methods, in both methods the index decreased in winter and improved in other seasons (Kizar 2018 ).

On the other hand, Zotou et al. ( 2018 ), undertook a research on the Polyphytos Reservoir in Greece, taking into consideration thirteen water parameters and applying 5 WQIs: Prati’s Index of Pollution (developed in 1971, based on thirteen parameter and mathematical functions to convert the pollution concentration into new units. The results of PI classified water quality into medium classes (Gupta and Gupta 2021 ). Bhargava’s WQI (established in 1983, the BWQI categorize the parameters according to their type: bacterial indicators, heavy metals and toxins, physical parameters and organic and inorganic substances. The BWQI tends to classify the water quality into higher quality classes, which is the case in the mentioned study (Gupta and Gupta 2021 ). Oregon WQI, Dinius second index, Weighted Arithmetic WQI, in addition to the NSF and CCMEWQI. The results showed that Bhargava and NSF indices tend to classify the reservoir into superior quality classes, Prati’s and Dinius indices fall mainly into the middle classes of the quality ranking, while CCME and Oregon could be considered as “stricter” since they give results which range steadily between the lower quality classes (Zotou et al. 2018 ).

In their study, Ugochukwu et al. ( 2019 ) investigated the effects of acid mine drainage, waste discharge into the Ekulu River in Nigeria and other anthropogenic activities on the water quality of the river. The study was performed between two seasons, the rainy and dry season. Samples were collected in both seasons, furthermore, the physic-chemistry parameters and the heavy metals were analyzed. WQI procedure was estimated by assigning weights and relative weights to the parameters, ranking from “excellent water” (< 50) to “unsuitable for drinking” (> 300). The results showed the presence of heavy metals such as lead and cadmium deriving from acid mine drainage. In addition, the water quality index for all the locations in both seasons showed that the water ranked from “very poor” to “unsuitable for drinking”, therefore the water should be treated before any consumption, and that enough information to guide new implementations for river protection and public health was provided (Ugochukwu et al. 2019 ).

The latest study in Lebanon related to WQI was carried out by El Najjar et al. ( 2019 ), the purpose of the study was to evaluate the water quality of the Ibrahim River, one of the main Lebanese rivers. The samples were collected during fifteen months, and a total of twenty-eight physico-chemical and microbiological parameters were tested. The parameters were reduced to nine using the Principal Component Analysis (PCA) and Pearson Correlation. The Ibrahim WQI (IWQI) was finally calculated using these nine parameters and ranged between 0 and 25 referring to a “very bad” water quality, and between 91 and 100 referring to an “excellent” water quality. The IWQI showed a seasonal variation, with a medium quality during low -water periods and a good one during high-water periods (El Najjar et al. 2019 ).

3 Conclusion

WQI is a simple tool that gives a single value to water quality taking into consideration a specific number of physical, chemical, and biological parameters also called variables in order to represent water quality in an easy and understandable way. Water quality indices are used to assess water quality of different water bodies, and different sources. Each index is used according to the purpose of the assessment. The study reviewed the most important indices used in water quality, their mathematical forms and composition along with their advantages and disadvantages. These indices utilize parameters and are carried out by experts and government agencies globally. Nevertheless, there is no index so far that can be universally applied by water agencies, users and administrators from different countries, despite the efforts of researchers around the world (Paun et al. 2016 ). The study also reviewed some attempts on different water bodies utilizing different water quality indices, and the main studies performed in Lebanon on Lebanese rivers in order to determine the quality of the rivers (Table 6 ).

As mentioned in the article (Table 7 ); WQIs may undergo some limitations. Some indices could be biased, others are not specific, and they may not get affected by the value of an important parameter. Therefore, there is no interaction between the parameters.

Moreover, many studies exhibited a combination between WQIs and statistical techniques and analysis (such as the PCA, Pearson’s correlation etc.). with a view to obtain the relation between the parameters and which parameter might affect the water quality.

In other research, authors compared many WQIs to check the difference of water quality according to each index. Each index can provide different values depending on the sensitivity of the parameter. For that reason, WQIs should be connected to scientific advancements to develop and elaborate the index in many ways (example: ecologically). Therefore, an advanced WQI should be developed including first statistical techniques, such as Pearson correlation and multivariate statistical approach mainly Principal Component Analysis (PCA) and Cluster Analysis (CA), in order to determine secondly the interactions and correlations between the parameters such as TDS and EC, TDS and total alkalinity, total alkalinity and chloride, temperature and bacteriological parameters, consequently, a single parameter could be selected as representative of others. Finally, scientific and technological advancement for future studies such as GIS techniques, fuzzy logic technology to assess and enhance the water quality indices and cellphone-based sensors for water quality monitoring should be used.

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Chidiac, S., El Najjar, P., Ouaini, N. et al. A comprehensive review of water quality indices (WQIs): history, models, attempts and perspectives. Rev Environ Sci Biotechnol 22 , 349–395 (2023). https://doi.org/10.1007/s11157-023-09650-7

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U.S. Plan to Protect Oceans Has a Problem, Some Say: Too Much Fishing

An effort to protect 30 percent of land and waters would count some commercial fishing zones as conserved areas.

By Catrin Einhorn

New details of the Biden administration’s signature conservation effort, made public this month amid a burst of other environmental announcements, have alarmed some scientists who study marine protected areas because the plan would count certain commercial fishing zones as conserved.

The decision could have ripple effects around the world as nations work toward fulfilling a broader global commitment to safeguard 30 percent of the entire planet’s land, inland waters and seas. That effort has been hailed as historic, but the critical question of what, exactly, counts as conserved is still being decided.

This early answer from the Biden administration is worrying, researchers say, because high-impact commercial fishing is incompatible with the goals of the efforts.

“Saying that these areas that are touted to be for biodiversity conservation should also do double duty for fishing as well, especially highly impactful gears that are for large-scale commercial take, there’s just a cognitive dissonance there,” said Kirsten Grorud-Colvert, a marine biologist at Oregon State University who led a group of scientists that in 2021 published a guide for evaluating marine protected areas .

The debate is unfolding amid a global biodiversity crisis that is speeding extinctions and eroding ecosystems, according to a landmark intergovernmental assessment . As the natural world degrades, its ability to give humans essentials like food and clean water also diminishes. The primary driver of biodiversity declines in the ocean, the assessment found, is overfishing. Climate change is an additional and ever-worsening threat.

Fish are an important source of nutrition for billions of people around the world. Research shows that effectively conserving key areas is an key tool to keep stocks healthy while also protecting other ocean life.

Nations are watching to see how the United States enacts its protections.

The American approach is specific because the broader plan falls under the United Nations biodiversity treaty, which the United States has never ratified. The effort in the United States is happening under a 2021 executive order by President Biden.

Still, the United States, a powerful donor country, exerts considerable influence on the sidelines of the U.N. talks. Both the American and international efforts are known as 30x30.

On April 19, federal officials launched a new website updating the public on their 30x30 efforts. They did not indicate how much land was currently conserved (beyond approximately 13 percent of permanently protected federal lands), stating that they needed to better understand what was happening at the state, tribal and private levels. But they announced a number for the ocean: about a third of U.S. marine areas are currently conserved, the website said.

The problem, according to scientists, is how the Biden administration arrived at that figure.

Everyone seems to agree that the highly protected areas classified as marine national monuments should count as conserved, and they did: four in the Pacific around Hawaii, Guam and American Samoa that were set up and expanded between 2006 and 2016; and one in the Atlantic southeast of Cape Cod, designated in 2016. A vast area of the Arctic where commercial fishing is banned was also included, with wide agreement.

But other places on the list should not be counted unless protections there are tightened, said Lance Morgan, a marine biologist and president of the Marine Conservation Institute, a nonprofit group that maintains a global map of the ocean’s protected areas.

For example, 15 National Marine Sanctuaries are included. While these areas typically restrict activities like oil and gas drilling, they do not require reduced quotas of commercial fishing. High-impact fishing techniques like bottom trawling, which damages seafloor habitat and captures vast amounts of fish, are prohibited in certain sanctuaries but permitted in others.

Also included on the list are “deep sea coral protection areas” that ban seafloor fishing like bottom trawling, but not some other commercial fishing methods.

“Much more effort should be focused on improving the National Marine Sanctuary program and ensuring that new areas being created provide conservation benefits and ban commercial fishing methods like bottom trawling and long-lining,” Dr. Morgan said.

Senior officials with the Biden administration emphasized that ocean work under 30x30 was far from over. Very little of the conserved marine area is near the continental United States, for example, and one of the administration’s priorities is adding places there to make the effort more geographically representative.

But they defended the decision to include areas that allow commercial fishing. Despite the high-impact gear, national marine sanctuaries have long been considered protected areas by the United Nations, they pointed out. More generally, they said, the administration weighed various approaches to defining what it would count.

For example, while an atlas of marine protected areas maintained by Dr. Morgan’s group considers 25 percent of American waters to be conserved, the U.S. Fishery Management Councils puts that number at more than 72 percent . Administration officials said their number reflected important conservation work by a variety of agencies and stakeholders.

“We do have very highly regulated fisheries in the U.S.,” said Matt Lee-Ashley, the chief of staff at the White House Council on Environmental Quality, which is helping to coordinate the 30x30 effort. “And so, our domestic definition of conservation may be a little bit different, and other countries’ definitions may be a little bit different.”

Even though the United States has not ratified the biodiversity treaty, it will still submit a conservation total to be counted toward the global 30x30 commitment. Officials said they were still weighing which areas to submit.

In a statement, representatives of the Fishery Management Councils praised the inclusion of commercial fishing areas, noting that they are managed under “very stringent sustainability and conservation standards.”

But sustainably managed commercial fishing is what should be happening in the rest of the ocean, said Enric Sala, a marine biologist who studies and advocates for marine protected areas. Allowing commercial fishing in places conserved under 30x30, he said, is “padding the numbers.”

“People are looking up to the U.S.,” Dr. Sala, who is originally from Spain, said. “That sends a really bad signal.”

Catrin Einhorn covers biodiversity, climate and the environment for The Times. More about Catrin Einhorn

Water Quality Importance Essay

Quality of water and public health, water quality and quantity concerns in the us, works cited.

Having accessibility to high-quality water is essential for the survival of humans. We all use water, not only for drinking but for other purposes such as cleaning, cooking, bathing, and so forth. We are constantly in contact with water, hence one must ensure that the water does not contain substances harmful to one’s health.

The human body is 70% water. Water in other words is an essential component of all processes that take place within our system. Therefore, a component that is so significant must be safe, such that it does not harm one’s health.

However, this is not the case. In a lot of areas, the water available to the public is contaminated; that is it has substances that can be of great harm to public health. Health risks due to the quality of water may include Water-contact diseases, Water Borne diseases, Vector-Borne diseases, and Poisoning. (water quality and health)

Dirty water when accumulates in an area, is the start of numerous harmful diseases. This is usually what happens in slums, and the reason behind the death of many innocent people.

For instance, due to the immense increase in industrialization, most of the waste products are dumped into the seas and oceans for their convenience. This waste contains heavy metals, which can be fatal for the human body. If they make their way into the public drinking or cooking water supply, our health is immediately at great risk. Metals such as mercury and lead can destroy one’s immune system, making one vulnerable to any diseases. Metals such as arsenic and cadmium can cause human poisoning. Not only this, if these metals are dumped into the sea, and go into the bodies of the fish we eat, we too will be indirect victims of the harmful effects. Already the quantity of water available in the world is decreasing as it is, polluting it just leaves us with no options. (water quality information).

Water-Borne diseases can be fatal for human health. If our drinking water or say the water we normally go swim in, is contaminated with pathogenic organisms, we can acquire certain diseases which may include: diarrhea, malaria, polio, dengue, typhoid, and many others. These can destroy human lives, and examples can be seen in areas with low water maintenance. (Water Borne Diseases).

Water quality concerns can be found all over the world. In some areas, they are on a larger scale as compared to others. In the United States, let us look at a report from 2002. In that year 695, 540 miles of rivers and streams, or 19% of the nation’s approximately 3.7 million stream miles were assessed for their quality by the state. It was identified that 45% of it was contaminated, that is not suitable for its appropriate use, 55% was suitable for usage and 5% was heavily contaminated. In 2000 99% of all fish advisories were affected by toxic substances such as mercury lead and so on. Now, whoever had those fish had been at risk, hence, stating that there are quality concerns in the US. (water quality report 2002) (water quality facts)

As far as water quantity is concerned, the United States never really faced such a serious problem. However, more recently, with the increase in industrialization and urbanization, water shortage problems in certain areas have been identified. The state has established rights given to each area regarding their quantity limits; which is a good thing. (Water Quantity and policy)

If one compares these concerns with the developing countries, one will find stark differences. Since these countries have an increasing population, their resources are limited. Not only do they have a shortage of quality water, but even the contaminated water for cleaning and reuse is scarcely available. This is mainly because of industrialization and the race to develop their industries to fit into the world market. Then again there are natural causes such and drought which unfortunately strike some areas more than others.

Findings. Web.

Water Borne Diseases . Web.

Water quality and health. Web.

Water quality facts. Web.

Water quality information. Web.

Water quality report 2002. Web.

Water Quantity and policy. Web.

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Florida Health Department issues water quality advisory for two Fort Walton Beach parks

FORT WALTON BEACH — The Florida Department of Health in Okaloosa County has issued two water quality health advisories at two parks within the Fort Walton Beach city limits.

According to a news release, tests were conducted on April 29 at Liza Jackson Park and Garniers Beach Park. The water quality at both locations did not meet the recreational standards for Enterococcus bacteria set by FDOH.

DOH-Okaloosa officials advise the public against any water-related activities at both locations due to "an increased risk of illness in swimmers." The water quality test, done during a regular water quality test, showed that the level of bacteria exceeded state guidelines.

DOH-Okaloosa officials say the advisory will be in effect until bacteria levels are below the accepted health level.

For more information, visit HealthyOkaloosa.com or call 850-833-9247.