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Water supply and water scarcity.

1. Prolegomena

2. the main contribution of this special issue, 2.1. water management under water scarcity regimes, 2.2. rainwater harvesting (rwh), 2.3. quality of water resources, 2.4. climate change impacts on water resources, 3. challenges and opportunities for in improving water supply, 3.1. growing population and urbanization, 3.2. climate change (and/or variability), 3.3. improving water use efficiency, 3.4. alternative (non-conventional) water resources, 3.4.1. wastewater reuse, 3.4.2. rainwater harvesting, 3.4.3. desalination, 3.5. preserving water quality, 4. epilogue, author contributions, acknowledgments, conflicts of interest.

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Tzanakakis, V.A.; Paranychianakis, N.V.; Angelakis, A.N. Water Supply and Water Scarcity. Water 2020 , 12 , 2347. https://doi.org/10.3390/w12092347

Tzanakakis VA, Paranychianakis NV, Angelakis AN. Water Supply and Water Scarcity. Water . 2020; 12(9):2347. https://doi.org/10.3390/w12092347

Tzanakakis, Vasileios A., Nikolaos V. Paranychianakis, and Andreas N. Angelakis. 2020. "Water Supply and Water Scarcity" Water 12, no. 9: 2347. https://doi.org/10.3390/w12092347

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Inequalities in Water Insecurity in Kenya: A Multidimensional Approach

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• Open access
• Published: 24 September 2024

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• Cecilia Njoroge   ORCID: orcid.org/0000-0001-7707-8744 1 ,
• Anja Smith 1 &
• Marisa von Fintel 1  

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Water insecurity is a global concern likely to be compounded by increases in population and climate change. Existing water insecurity measurement methods capture multidimensional deprivation only at regional or sub-regional levels. Such estimates do not capture heterogeneous household experiences of water supply, proximity to water sources and affordability, which can vary substantially from regional averages. Accurate measurement requires a method that captures the incidence and intensity of a household’s simultaneous deprivation in dimensions of water accessibility, affordability, sufficiency and safety. We propose such a method and assess related inequalities using an approach analogous to the Alkire–Foster methodology for multidimensional poverty. Using household-level data from the Kenya Integrated Household Budget Survey 2015/16, we find that 63% of the Kenyan population experience multiple deprivation in water access. The dimensions of water affordability and sufficiency contribute most to multidimensional water insecurity, highlighting the need to ensure an adequate supply of affordable water. Disparities by household place of residence, dwelling type, and socio-economic status are evident. The estimates of multidimensional water insecurity are robust to different deprivation and poverty cutoffs. Our analysis is an invitation to rethink water insecurity metrics, allowing water deprivation to be measured more frequently and with greater precision to understand its impact clearly.

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1 Introduction

Access to clean and adequate water is a basic human right and fundamental for maintaining healthy lives. The United Nations ( 2015 ) Sustainable Development Goal (SDG) 6 commits to attaining universal access to clean, adequate and affordable water. Despite this, water insecurity, defined as the inability to access and benefit from adequate, safe and affordable water for a healthy life (Jepson et al., 2017 ), remains a global health and development concern. Globally, about 2.2 billion people lack access to safe water and estimates indicate that 3.3 billion people will face water scarcity by 2050 (United Nations, 2021 ; WHO/UNICEF, 2023 ). In Kenya, universal access to safe water has been a long-standing challenge. The Kenyan population without water supply points (23%) is the third highest in Sub-Saharan Africa (SSA), while approximately 40% lack access to safe water (UNICEF, 2017 ; WHO/UNICEF, 2019 , 2023 ).

Global concerns about water insecurity are primarily based on human health, though the consequences extend to food security, gender equality, quality of life and poverty (Bulled, 2017 ; Bisung and Elliott, 2018 ; Njoh et al., 2018 ; Nadeem et al., 2018 ; Adams et al., 2020 ; Miller et al., 2021 ). Population growth and economic development have increased water demand, and climate change affects water availability, making water insecurity increasingly difficult to address (Mulwa et al., 2021 ). An essential step towards addressing water insecurity is quantifying its extent at national or sub-national levels using metrics such as the Water Poverty Index (WPI) by Sullivan ( 2002 ). Though a step in the right direction towards understanding water insecurity, such geographic level estimates may obscure disparities in household water accessibility, supply and cost, which could exist even in regions identified as water (in)secure.

The measurement of household water insecurity is constrained by a lack of standardized tools allowing the incidence and intensity of simultaneous deprivations to be reflected in a single metric. This has led to household water insecurity being assessed mainly as one-dimensional, focusing separately on the dimensions of inadequate supply, affordability, physical inaccessibility and unsafe for consumption (Bisung and Elliott, 2018 ; Unfried et al., 2022 ; Badimo et al., 2021 ). Different thresholds have been suggested to assess each dimension. Such include a threshold of 1-km round trip or 30 min spent on water collection for water accessibility (Badimo et al., 2021 ), 20 or 50 l per capita per day for water sufficiency (Mutono et al., 2022 ; United Nations, 2014 ), and between 2.5 and 5% of household income for water affordability (Beard and Mitlin, 2021 ; Mitlin et al., 2019 ; WHO, 2017 ). While households could be deprived in more than one dimension, the scholarship on the water insecurity measurement largely fails to offer a way to explore these overlapping deprivations.

Establishing both the incidence and intensity of water insecurity at the individual or household level is essential to understanding whose water needs are unmet and the causes of unmet needs. The intensity of deprivation remains unexplored in the broader water access measurement literature. Not accounting for the depth of simultaneous deprivations experienced by households would mean that the severity of water insecurity is understated, and necessary resources will not be directed comprehensively towards addressing this challenge.

In this paper, we apply an approach similar to the Alkire–Foster methodology for poverty measurement to measure the level and intensity of multidimensional water insecurity at the household level. The Alkire and Foster ( 2011 ) methodology possesses some features that make it a high-resolution lens for assessing deprivation. First, it uses a dual cutoff approach in identifying deprivation in each dimension and the multidimensionally poor based on the composite index. Second, it has been shown to retain all the aximatic properties of conventional poverty measures, such as the focus axiom, which prioritizes the most vulnerable households. Lastly, estimates can be broken down by population sub-groups to reveal the most water-insecure households, and by dimensions to reveal the underlying composition of water insecurity.

We also assess inequalities in water insecurity by household place of residence, headship gender, dwelling type and socio-economic status through the decomposition property of the Alkire–Foster methodology. We use a nationally representative survey and consider dimensions of water accessibility, affordability, safety and sufficiency in measuring household water insecurity. The paper builds on the water access and measurement literature by providing evidence on multidimensional water insecurity in a more coherent framework. This is done in the Kenyan context. The applied method complements existing water insecurity measurement approaches and provides insights that could help in the development of a globally standardized water insecurity measurement metric.

The rest of the paper is organized as follows. The next Sect.  2 outlines the study setting. This is followed by a discussion of the data used and how this is combined in an approach analogous to the Alkire–Foster methodology to measure household water insecurity in Sect.  3 . Then, Sect.  4 presents and discusses the findings. The paper concludes in Sect.  5 .

2 Research Setting

Kenya is a low-middle income country in SSA, with a population of 48 million people who inhabit regions with varying socio-economic development levels and climatic conditions. Though the country has some of the largest water reservoirs in East Africa, it is estimated that 90% of the country is either arid or semi-arid (Davies and Gustafsson, 2015 ). Faced with water-related challenges of drought and reduced rainfall (Mulwa et al., 2021 ), population growth and economic development, Footnote 1 the country is likely to experience increased water insecurity. Davies and Gustafsson ( 2015 ) project that by 2030, the country will have a 31% gap between water demand and water supply.

According to the Kenya National Bureau of Statistics ( 2018 ), approximately 58% of households in Kenya have access to improved water sources based on the WHO/UNICEF Joint Monitoring Program (JMP) classification of water sources. Among households relying on improved water sources, 50% spend at least 30 min on water collection. Footnote 2 This is consistent with global figures of 260 million people who spend at least 30 min collecting water despite having access to safe water (WHO, 2017 ). The Kenya National Bureau of Statistics ( 2018 ) further indicates that 20% of households need to walk more than 1 km to fetch water.

The Kenya National Bureau of Statistics ( 2018 ) reports that only 21% of rural households have piped water, compared to 51% of urban households. In the absence of piped water or where piped water is intermittently supplied, households cope by purchasing water from private and informal vendors, and containers for storing water (Cook et al., 2016 ; Majuru et al., 2016 ; Beard and Mitlin, 2021 ; Joshi et al., 2023 ). Achore et al. ( 2020 ) argue that such expenditures affect water affordability. As Beard and Mitlin ( 2021 ) find, households purchasing water from private vendors pay 52 times as much as piped water utilities. This may explain the convergence of rural and urban households’ water expenditures reported in the Kenya National Bureau of Statistics ( 2018 ), as shown in Table 1 . Rural households, though with lower piped water access, also pay operational and maintenance fees for communal water points such as handpumps, which add to expenditures on water service providers.

In terms of daily per capita water consumption, the Kenya National Bureau of Statistics ( 2018 ) indicates that this is mostly at a basic level as households, on average, use approximately 20 l of water per capita per day. As displayed in Fig.  1 , a larger proportion of households use between 15 and 25 l per capita per day. This is less than the 50 l daily per capita volume of water recommended by the United Nations ( 2014 ) to lower health risks. Studies suggest that low water usage, especially in urban areas, is linked to the high cost of water, unequal distribution, water infrastructure degradation (Krueger et al., 2019 ) and governance (Miller et al., 2020 ). As climate change threatens water availability, concerns arise about whether households have sufficient amounts for drinking and domestic use without being pushed into poverty.

Source : Authors’ calibrations using KIHBS 2015/16

Distribution of quantity of water per individual per day by place of residence.

Jepson et al. ( 2017 ) argue that though uncertain how multidimensionality in household water insecurity can be integrated into one value, its consideration will give more meaningful information to untangle water insecurity causes and impacts. We aim to fill this gap by considering different aspects of water access (physical accessibility, affordability, sufficiency and safety) in a water-scarce and lower-middle-income setting to shed light on simultaneous deprivations that households could be experiencing.

3 Data and Methods

The study uses the Kenya Integrated Household Budget Survey (KIHBS) 2015/16, which is representative at national and county levels. The Kenya National Bureau of Statistics conducts the survey. The survey comprises 21,773 households drawn from a sample frame of 5360 clusters. The KIHBS is an extensive survey with information about household spending patterns and socio-economic indicators. The survey is designed to monitor poverty levels and progress in improving the population’s living standards. The Kenyan government is committed to eliminating poverty, as underscored by the social pillar of the Kenya Vision 2030, and this is given more stimulus by the SDGs which aim to eradicate poverty in all its forms.

The data were collected in the four quarters between September 2015 and August 2016 to capture seasonality. Despite the data being almost a decade old, the KIHBS 2015/16 is suitable for measuring household water insecurity and remains relevant in the present context in Kenya for various reasons. First, the survey contains the most recent data on fundamental dimensions such as water collection time, sources, expenditure and quantity. Data on these dimensions is often a challenge, leading to unimproved drinking water sources being a common proxy for water insecurity at the household level. Combining the data on dimensions of water accessibility, safety, sufficiency and affordability contained in the survey could provide a more precise understanding of household deprivations from a basic needs perspective.

Second, the proportion of the population without access to improved water sources in Kenya has remained relatively constant over the years. The proportion of the population without access to improved water sources is about 42% based on KIHBS 2015/16, 43% according to UNICEF ( 2017 ) and WHO/UNICEF ( 2019 ), and approximately 39% based on the Kenya Demographic Health Survey 2022. In terms of physical accessibility, the proportion of households who indicate spending at least 30 min on water collection is 24% based on the KIHBS 2015/16 and 24% based on the Kenya Demographic Health Survey 2022. These statistics highlight that water access patterns and challenges remain pertinent in present-day Kenya.

Third, the data collection exercise began in the same year that the United Nations ( 2015 ) adopted the Agenda 2030 development targets. One development goal is ensuring universal access to affordable, adequate and safe water. The KIHBS, therefore, provides baseline estimates of household water insecurity against which progress may be measured.

Last, the KIHBS is representative at the county level. In 2010, the Kenyan government adopted a devolved governance system with 47 counties, and the first term of devolution was between 2013 and 2017. The data allow an assessment of counties’ progress in attaining part of their constitutional mandate to enhance water access. In light of the aspects highlighted above, the estimates and policy recommendations derived from the KIHBS 2015/2016 analysis still offer valuable contributions to understanding and addressing water insecurity in Kenya.

3.2 Analytical Approach

Water insecurity at a large scale, such as regional and sub-regional levels, has been measured through the influential WPI by Sullivan ( 2002 ). The Sullivan ( 2002 ) WPI allows multiple dimensions of deprivation to be reflected in a single index, thereby enabling ranking of regions based on the severity of their deprivation. This, however, does not allow us to understand who and where water-insecure households are. While identifying the most water-deprived regions is key, there could be a mismatch between the levels of water insecurity experienced by a single household within a region and the region as a whole. For example, although a region might have the necessary water infrastructure to deliver water to the end user, certain households may not have actual access to safe water if the water source (hand pump or standpipe) closest to them is in disrepair. In addition, assessing water insecurity at a regional or sub-regional level does not capture heterogeneous household experiences of water supply, proximity to water sources and affordability, which can vary substantially from regional averages.

While correlated within geographical regions, water insecurity remains a problem primarily at the individual household level. However, water insecurity measurement is still a challenge at the household level, as few tools exist to quantify it. Some approaches have been developed to assess joint deprivation in household water insecurity, for example, by Jepson ( 2014 ) and Young et al. ( 2019 ). While yet to be validated and universalized for broad application, these approaches do not reflect the intensity of household joint deprivations.

In this paper, we aim to introduce an index that specifically captures the level of multidimensional water insecurity at the household level. To this purpose, we apply an approach parallel to the Alkire and Foster ( 2011 ) multidimensional poverty index, originally used to measure poverty. The method reflects simultaneous deprivation while showing the depth of deprivation. It also allows us to identify individual households deprived in a given region. In the subsequent sub-sections, we describe the Alkire–Foster methodology to shed more light on our analytical approach. We then discuss the parameters used to estimate household water insecurity.

3.2.1 The Alkire–Foster Methodology

In economic analysis of poverty and deprivation, the Alkire and Foster ( 2011 ) methodology of a multidimensional poverty index (MPI) offers a framework for measuring simultaneous deprivations in different dimensions. The method allows poverty to be measured at an aggregated level (regional or sub-regional), and the level of a household or an individual. While the framework originally aimed to measure poverty, Alkire et al. ( 2015a ) note that it is now being extended for broader application to focal areas such as governance, women empowerment and energy. This is made possible since the methodology offers flexibility in choosing dimensions, indicators and cutoffs.

The methodology uses a dual cutoff approach: the first cutoff identifies deprivation in each dimension, and the second one identifies the multidimensionally poor. This methodology consists of identification and aggregation methods.

The identification method first requires the definition of dimensions and their corresponding indicators (that is individual components within each indicator). Deprivation cutoffs ( \(z_{i}\) ) for each indicator are set to show the level of achievement a household needs to attain to be considered deprived or non-deprived in that dimension. The relative weights for each indicator are then selected in such a way that they sum up to one and are used to compute weighted deprivations to show the contribution of each dimension to the overall measure. The resultant value of weighted deprivations is the deprivation score ( \(c_{i}\) ), which reflects the breadth of each household’s deprivations across all dimensions. Lastly, a poverty cutoff ( k ) is defined to identify the proportion of weighted deprivations a household requires to experience to be considered multidimensionally poor.

The aggregation method involves computing the proportion of people identified as multidimensionally poor in the population, building on unidimensional axiomatic poverty measures. This is the headcount ratio (H) (also referred to as the raw/uncensored headcount ratio) of the multidimensionally poor. It also entails getting the average share of weighted indicators in which people are deprived to calculate the intensity of multidimensional poverty (A). The adjusted headcount ratio ( \(M_{0}\) ) can be obtained as a product of the headcount ratio and the intensity of deprivation. The equations in system 1 show how the headcount ratio (H), intensity (A) and adjusted headcount ratio ( \(M_{0}\) ) are computed.

In the equations in system 1 , q is the number of households that are multidimensionally water insecure, n is the total population, \(c_{i}\) is the deprivation score, and k is the poverty cutoff.

In the Alkire and Foster ( 2011 ) framework, dimensions, indicators, weights and cutoffs are left to the user’s choice. This flexibility allows us to apply an approach parallel to the Alkire and Foster ( 2011 ) methodology to quantify multidimensional household water insecurity. Because of the subjective choice of these parameters, robustness checks are carried out to assess the stability of estimates obtained and ascertain how meaningful the estimates are for policy implications.

Applying an approach analogous to the Alkire–Foster methodology to understand water insecurity is advantageous in several ways. First, it allows the identification of individual households that are water-insecure, even in communities that could be regarded as water-secure. Second, the approach goes beyond estimating the proportion of water-insecure households (incidence) to include the breadth of deprivation experienced by water-insecure households (intensity). Third, the decomposition feature of the Alkire–Foster methodology allows us to decompose the estimates by population sub-groups and indicators. Decomposing the estimates by population sub-groups reveals group-based inequalities, highlighting the marginalized. When estimates are broken by indicators, the approach shows the underlying structure of water insecurity.

3.2.2 Parameters for Identifying Water-Insecure Households

The literature on water insecurity links it to physical dimensions of accessibility, colour or taste (safety), sufficiency and availability, socio-economic dimension of affordability, and political dimensions of management and continuity in supply (Sullivan, 2002 ; Chenoweth, 2008 ; Jepson et al., 2017 ; Young et al., 2019 ). These dimensions have been assessed using different scales (Badimo et al., 2021 ; Bisung and Elliott, 2018 ; Beard and Mitlin, 2021 ; Mitlin et al., 2019 ; Young et al., 2019 ; Mack and Wrase, 2017 ).

The dimensions of water have also been recognized by development agencies such as the United Nations ( 2015 ) SDG 6 and the Human Right to Water framing by United Nations, OHCHR, UN-HABITAT and WHO ( 2010 ). The Human Right to Water entitles every individual to water that is sufficient, safe, acceptable, physically accessible and affordable for personal and domestic uses. We draw from this framing to argue that, at minimum, a household is water-insecure if water is unsafe, insufficient, physically inaccessible and unaffordable. This way, we consider dimensions of water accessibility, affordability, safety and sufficiency.

The next step is choosing the dimension-corresponding indicators and the deprivation cutoffs. In this paper, accessibility is captured by the time taken for water collection and distance to a water source, and a household is deprived if time spent on water collection exceeds 30 min or walks for more than 1 km to a water source. Water affordability is indicated by expenditures on water with a deprivation cutoff of 3% of household total expenditure. Footnote 3 The WHO/UNICEF JPM classification of improved and unimproved sources is used to proxy households’ water source safety. A threshold of 20 l per person per day is applied for water sufficiency. Footnote 4

The dimensional weights are also chosen by the user of the Alkire–Foster methodology. Alkire et al. ( 2015a ) argue that though different weights could be used for each indicator given that deprivations can have different degrees of relevance depending on the context, this kind of weighting creates challenges with the interpretation of the index. We therefore apply equal weights across the dimensions, similar to the Alkire and Foster ( 2011 ) and for simplicity. Equal weighting of the dimensions is also used on the basis that these dimensions are mostly inherently connected. For instance, if an individual walks long distances to collect water, water quantity and safety will be compromised. Footnote 5 Table 2 summarises the dimensions, indicators, deprivations and weights.

The determination of the multidimensionally water-insecure households depends on the poverty cutoff ( k ). The poverty cutoff is the most important component of the Alkire and Foster ( 2011 ) methodology as it determines the level of multidimensional poverty. The poverty cutoff remains an arbitrary value. The study defines the poverty cutoff as 0.33. By using this poverty cutoff, we suggest that a household is water-insecure if deprived in one-third (at least two) of the 5 weighted indicators. According to Alkire et al. ( 2015b ), while the poverty cutoff can be set at any level, a range of poverty cutoffs may identify the same households as poor. We vary the poverty cutoff later to assess the validity of our estimates.

The household data on dimensions and indicators of water insecurity, drawing from the Alkire and Foster ( 2011 ) methodology, is combined to assess how households could be simultaneously deprived in more than one dimension. This approach allows us to estimate both the incidence and intensity of multidimensional water insecurity. The multidimensionally water-insecure headcount ratio (H) is the incidence of water insecurity and gives the proportion of people who experience multiple deprivations. The intensity of water insecurity (A) shows the average proportion of deprivations experienced by poor people and indicates the breadth of deprivation.

The product of the incidence and intensity of water insecurity gives the adjusted headcount ratio ( \(M_{0}\) ). The \(M_{0}\) is the multidimensional water insecurity index and can be broken down into different population sub-groups to explore variation in multidimensional water insecurity. Specifically, the estimates are decomposed by households’ place of residence, headship gender, expenditure quintiles and type of dwelling. The decomposition results reveal the most water-insecure households, highlight the dimensions in which most of the deprivation is concentrated, and provide input regarding the extent of inequality across the population sub-groups.

4 Empirical Results

This section presents and discusses the estimates of household multidimensional water insecurity in Kenya. Results are presented by first considering the results from implementing the Alkire–Foster methodology to estimate multidimensional water insecurity along the dimensions of water accessibility, affordability, safety and sufficiency. Thereafter, we present the results from the decomposition of the index of multidimensional water insecurity by population sub-groups (place of residence, gender of household head, socio-economic status and dwelling type) to illustrate inequalities in water insecurity. Lastly, some robustness checks conducted to assess the validity of the estimates are presented.

4.1 Multidimensional Water Insecurity

The computation of the incidence (H) and intensity (A) of multidimensional water insecurity using an approach that is analogous to the Alkire and Foster ( 2011 ) methodology depends on two cutoffs: one indicates if a person is deprived or non-deprived in that dimension (giving the raw headcount ratio), while the other shows if a household is multidimensionally water insecure or not. Table 3 shows multidimensional water insecurity regarding the headcount ratios for each indicator and aggregate estimates.

The raw headcount ratios indicate the proportion of the population deprived in each dimension. The Kenyan population is mainly deprived in dimensions of water affordability and sufficiency while less deprived in water accessibility dimension. Our results indicate that about 62% of households spend more than 3% of their total expenditures on water and use less than 20 l of water for personal and domestic uses. This proportion is much higher than the about 20% of households who walk for more than 1 km (round trip) to fetch water. The deprivation estimates suggest that though households could be connected to water infrastructure such as piped water in their dwellings and yards, water could be inadequately supplied, unclean and costly.

The censored headcount ratios show the proportion that is both multidimensionally water-insecure and deprived in a specific dimension. The estimates show that about 51%, 51% and 33% of water-insecure households are deprived in dimensions of water affordability, sufficiency and safety, respectively.

The approach shows the incidence of multidimensional water insecurity, given the incidence of water insecurity (H). The incidence (H) shows the proportion of the population that is identified as multidimensionally water insecure. Our estimates indicate that approximately 63% of Kenyans are multidimensionally water insecure. The estimate of 63% multidimensionally water insecure households is higher than the 42% reported by WHO/UNICEF ( 2019 ) when the JMP categorization of improved or unimproved water sources is considered. There is a likelihood of underestimating the water-insecure population when one dimension is considered, underscoring the importance of multidimensionality in estimating water insecurity.

Moreover, our approach reveals the depth of deprivation (intensity of deprivation). The intensity of water insecurity (A) shows the average proportion of weighted deprivations a water-insecure household experiences. On average, the level of deprivation faced by water-insecure households is approximately 61%.

According to Alkire et al. ( 2021 ), the headcount ratio of water insecurity (H) can be multiplied by a country’s total population to determine the number of people who are multidimensionally water insecure. Taking the population of 2015, about 29.6 million Kenyans are multidimensionally water insecure. Footnote 6 In addition to this, the headcount ratio reports the incidence of multidimensional water insecurity transparently and intuitively (Alkire et al., 2015a ). This feature enables policymakers to understand and interpret the headcount ratio easily.

The usefulness of the headcount ratio in policymaking, however, is mainly undermined by its violation of the principle of dimensional monotonicity. This limitation led to the development of other improved measures of poverty and deprivation, such as by Foster et al. ( 2010 ). Dimensional monotonicity requires that if a poor household, who is not deprived in all dimensions, becomes deprived in an additional dimension, poverty should increase (Alkire et al., 2015a ). This principle ensures that the focus is not only on the incidence of water insecurity but also on the extent to which water-insecure households experience multiple deprivations. Another limitation of the headcount ratio is that it fails to provide essential information helpful in attaining the two vital goals of the SDGs: leaving no one behind and understanding how indicators are interlinked (Alkire et al., 2021 ). This way, the headcount ratio leaves out important information on how to reduce deprivation among the poorest population sub-groups. These limitations of the headcount ratio (H) are overcome by the adjusted headcount ratio ( \(M_{0}\) ), denoting the value addition of using \(M_{0}\) .

The adjusted headcount ratio is a product of the incidence and intensity of water insecurity and shows overlapping deprivations that the same household could be experiencing. Adjusting the headcount ratio with the intensity of water insecurity makes the obtained adjusted headcount ratio highly advantageous in two ways (Alkire et al., 2015a ). Firstly, \(M_{0}\) is sensitive to the number of deprivations the multidimensionally water-insecure households experience. This means that if a household experiences an additional deprivation, the intensity of water insecurity increases, thereby increasing \(M_{0}\) without changing the incidence of water insecurity. Because of this feature of \(M_{0}\) , the monotonicity property is satisfied. Secondly, \(M_{0}\) can be decomposed by various aspects of vulnerability allowing policy focus on the most affected population sub-groups. We show this decomposition of the adjusted headcount ratio in the subsequent sub-section. The adjusted headcount ratio indicates that 38% of the weighted deprivations are experienced out of the total potential deprivations the population could experience.

The measures of poverty and deprivation should also reveal the composition of poverty for policymakers to understand the contribution of each indicator. The adjusted headcount ratio can be broken down by indicators to indicate the underlying structure of water insecurity in Kenya. Information on the contribution of indicators to multidimensional water insecurity is helpful for resource allocation across sectors. Alkire et al. ( 2015a ) posit that when the contribution of each indicator exceeds its assigned weight, the implication is that there is a relatively high deprivation in this indicator. When the results are decomposed by indicators, distance to water source and time taken to collect water contribute 7% and 6% to overall water insecurity, respectively. This is less than the allocated weight of 12.5% (see Table 2 for assigned weights), indicating low deprivation when accessing water. The dimensions of safety and sufficiency each account for 33% of the overall water insecurity. Since the contribution of safety and sufficiency dimensions is higher than the weight assigned of 25% (see Table 2 for assigned weights), it indicates a high deprivation in these two dimensions. This points to the need to ensure that water supplied to households is clean and adequate to reduce household water insecurity.

The national estimates of multidimensional water insecurity appear to give a clear understanding of household water insecurity in Kenya and support monitoring the country’s progress at a global scale. Household water insecurity patterns are likely to vary spatially due to differences in climatic conditions across the country. To assess sub-national patterns of household water insecurity, the headcount ratio of multidimensional water insecurity is decomposed by the 47 counties in Kenya. We consider counties since this is the highest sub-national administrative level, and the counties are constitutionally mandated to deliver water services. Figure  2 shows household water insecurity patterns in Kenya at the county level.

Source : Authors’ calibrations based on headcount ratios

Incidence of water insecurity at the county level in Kenya. This figure shows the spatial distribution of the incidence of household water insecurity estimated using an approach similar to the Alkire–Foster methodology across Kenyan counties.

The North Eastern counties appear to be more water-insecure, and this can be attributed to the region being semi-arid, struck by droughts often and having few water reservoirs. Further analysis (by decomposing the estimates by indicators) highlights that the long distance to the water sources, unaffordable water and insufficient quantity of water are the key contributors to household water insecurity in these counties. Since these counties are semi-arid with little rainfall, exploiting the potential of groundwater resources in these areas can help meet households’ water needs.

There is a low concentration of water-insecure households in counties in the central and coastal regions. Counties in the central part of the country often receive high amounts of rainfall and have dams that help supply water to residents. The coastal area has major aquifers that enhance the provision of water to households through groundwater abstraction. These patterns suggest regional disparities in household water insecurity exist in Kenya.

Put differently, only one county (Baringo) has at most 25% multidimensionally water-insecure households, while 9 counties have between 25 and 50% multidimensionally water-insecure households. Most counties in the north-eastern and south-western regions have an incidence of water-insecure households above 75%. While the high incidence of water insecurity in these counties is a cause for concern, most are least populated due to adverse climatic conditions. Based on the Kenya National Bureau of Statistics ( 2019 ) Population and Housing Census report, approximately 33% of the Kenyan population resides in counties where at least 75% of the households are water-insecure.

The county governments in Kenya, which were assigned the responsibility of water service provision under the devolved system of governance, should target resources toward the rural and poor households within their jurisdiction for the country to make progress in attaining SDG 6. Our results highlight the need for all counties to provide affordable and safe water to households. This can be attained through tariff regulation or subsidizing commercial water service providers. Other policy options include investing in small-scale piped water systems and developing public water standpipes, which can be communally managed or through professionalized maintenance services contacted by the county governments.

4.2 Inequalities in Multidimensional Water Insecurity

Water insecurity is likely to vary across population groups by place of residence, gender, ethnicity, and socio-economic conditions. Such disparities hinder households from accessing clean and adequate water without being pushed into poverty. Disaggregating national estimates of water insecurity among key population sub-groups provides knowledge about marginalized households. This knowledge is key in (re)formulating policies targeting the provision of water supply systems and infrastructure to households who do not have physically accessible, adequate, safe and affordable water. Our analysis decomposes water insecurity estimates and then performs post-estimation tests using chi-square to assess if differences in H and \(M_{0}\) between population sub-groups are statistically significant (Pacifico and Poege 2017 ).

We start by disentangling rural–urban differences in water insecurity, and such differences are primarily reported in water access literature (Bain et al., 2014 ; Adams and Smiley, 2018 ; WHO/UNICEF, 2021 ). Consistent with most SSA countries, rural households in Kenya continue to lag in accessing safe water (WHO 2017 ).

Our estimates indicate that water insecurity incidence in rural areas is 69% compared to 54% in urban areas, as shown in Table 4 . The incidence of water insecurity between rural and urban areas is significantly different, as indicated by a significant chi-square statistic at a 1% significance level. The implication is that rural households in Kenya are more multidimensionally water insecure than urban households.

The raw headcount ratios in Table 4 show that 43% and 42% of rural households are deprived in dimensions of water safety and affordability, respectively. This may be explained by the high coping costs incurred by rural households in the absence of piped water systems (Cook et al., 2016 ). Provision of piped water is a challenge in rural areas due to households’ dispersed nature, and one way to increase access to safe water is through community-based water projects (Barde 2017 ). In urban areas, 57% and 55% of households are deprived in terms of the volume of water used and expenditure on water, respectively. Mutono et al. ( 2022 ) and Joshi et al. ( 2023 ) argue that insufficient water consumption arises from an intermittent water supply in urban areas such as Nairobi. Poor maintenance of water infrastructure and piped water outages may contribute to unreliable water supply, making households use less water. In response to intermittent water supply, households rely on water from vendors to meet their water needs, which, according to Mitlin et al. ( 2019 ) and Mutono et al. ( 2022 ), tends to be more expensive than piped water. The results indicate that in rural areas, policies should focus on providing affordable and safe water.

The JMP reports substantive differences in monitoring progress in water access between rural and urban areas based on the improved or unimproved water sources typology (WHO/UNICEF, 2019 , 2021 ). According to Queiroz et al. ( 2020 ), JMP fails to effectively incorporate inequalities into the indicators of quantity and affordability, representing a limitation in the institutionalization of commitment to attain universal access to safe, adequate and affordable water. The rural–urban inequalities found in this paper could thus give a more complete reflection of how other aspects of affordability, physical accessibility and sufficiency can compound differences in household water insecurity.

Disparities in water insecurity may also exist on a gender level. In feminist political ecology theory, Elmhirst ( 2011 ) argues that gender plays a crucial role in acquiring resources, and this can be extended to water access. Table 4 shows water insecurity estimates for female-headed households compared to male-headed ones. While the chi-square indicates a significant difference in the level of water insecurity between these two categories of households, there is little substantive difference (only 1% point) between the two types of households.

Other studies document gender differences in water access, where females have lower access to water compared to males (Bukachi et al., 2021 ; Nunbogu and Elliott, 2021 ; Winter et al., 2021 ). This may be explained by women having less control of economic and water resources and less involvement in water management. More consideration of women in water management and governance could help lower water insecurity among female-headed households.

The socio-economic status of households, such as the type of dwelling and wealth, may affect the possibility of having water infrastructure, such as piped water into the dwelling, and the ability to afford safe and adequate water. We find disparities in water insecurity by dwelling type summarized in Table 5 . For instance, the incidence of water insecurity among households whose dwellings are made of grass or mud is 70% relative to an incidence of 53% among households whose houses are made of cement or bricks. Our findings are similar to those documented in other developing countries such as South Africa (Oskam et al., 2021 ) and the developed world (Meehan et al., 2020 ). We further decompose the water insecurity estimates by households’ economic position as captured by expenditure quintiles since they reflect economic vulnerability better than income in household surveys (Ilinca et al., 2019 ; Beer et al., 2022 ). We find that households in the lowest quintile are more water-insecure with an incidence of 51% compared to 40% in the highest quintile, as shown in Table 5 . Such inequalities in water access put socio-economically disadvantaged households at a further disadvantage. Our results are consistent with evidence by Hernández-vasquéz et al. ( 2021 ) and Oskam et al. ( 2021 ).

The inequalities in water insecurity among different population sub-groups show that households’ experiences in water access differ along various dimensions. Reducing disparities in water insecurity among households is vital for universal access to water.

4.3 Robustness Analysis

In the Alkire and Foster ( 2011 ) methodology, decisions on key parameters such as dimensions and corresponding indicators, values of weights, deprivation and poverty cutoffs are left to the description of the user. The multidimensional deprivation or poverty estimates depend on these parameters (Alkire and Santos, 2014 ). As such, concerns have been raised on the sensitivity of results regarding who is poor or not to changes in these parameters (Thorbecke, 2011 ). Alkire and Santos ( 2014 ) propose varying these parameters to conduct robustness checks. Data constraints limit the number of robustness tests conducted in this paper, and the only parameters that varied are the poverty cutoff ( k ) and the dimensional thresholds.

4.3.1 Robustness by Varying the Poverty Cutoff

According to Alkire and Foster ( 2011 ), the poverty cutoff identifies who is poor, thereby defining the headcount ratio and effectively determining the poverty level. This makes the poverty cutoff the most fundamental parameter in the Alkire–Foster methodology. There are two ways to assess whether the estimates are robust when the poverty cutoff is varied according to Alkire and Santos ( 2014 ) and Alkire et al. ( 2015a ).

First, estimates are deemed robust if changes in water insecurity estimates at different poverty cutoffs do not alter water insecurity ordering (such as by population sub-groups). This can be assessed using headcount and adjusted headcount ratio curves (Alkire et al., 2015b ). We demonstrate how water insecurity estimates change at different values of the poverty cutoff (between 0.2 and 0.9). Figure  3 shows national, urban and rural water insecurity profiles at different values of k . All lines are downward sloping, implying that at higher poverty cutoffs, a lower proportion of households is identified as water-insecure. Footnote 7

Headcount and adjusted headcount ratios for water-insecure households for different poverty cutoffs, by household place of residence.

From Fig.  3 , headcount ratios of water-insecure households at the national level and rural–urban areas do not intersect at different values of k . The figure shows that rural households’ incidence and adjusted headcount ratios of water insecurity dominate that of urban areas and at the national level. In other words, rural households are more water-insecure compared to urban households, regardless of the change in the poverty cutoff.

Second, if the share of multidimensionally poor households is lower at higher poverty cutoffs, estimates are said to be robust. We assess this by including alternative poverty cutoffs of 0.2, 0.3, 0.4, and 0.5, based on the suggestion by Oxford Poverty and Human Development Initiative ( 2018 ). Using a value of \(k=0.2\) identifies households vulnerable to poverty, while a higher poverty cutoff of 0.5 identifies severely poor households. Table 6 summarizes the incidence (H) and adjusted headcount ratio ( \(M_{0}\) ) at various poverty cutoffs. The incidence and adjusted headcount ratio decline as k increases. At \(k=0.3\) , 63% of households are identified as water insecure, 63% at \(k=0.33\) and 60% at \(k=0.4\) .

The declining headcount ratios as k increases imply that households, on average, are deprived in more indicators. That is, an increase in deprivations experienced by households lowers the proportion of multidimensionally water-insecure households. Alkire et al. ( 2022 ) argue that changes in estimates arising from shifts in k have meaningful interpretation and may usefully point towards policy actions against joint deprivations.

4.3.2 Robustness by Varying the Deprivation Cutoffs

The next robustness test is carried out by varying the dimensional deprivation cutoffs. There are diverse viewpoints regarding thresholds that define water usage, affordability, accessibility and safety (Mutono et al., 2022 ; Mitlin et al., 2019 ; WHO, 2017 ; Beard and Mitlin, 2021 ; WHO/UNICEF, 2019 ; Badimo et al., 2021 ). We reclassify household water sources, rather than either improved or unimproved, into two JMP service ladders: basic and safely managed (which we call intermediate). The volume of water consumption is also varied to 50 l at the intermediate level while retaining a 20 l threshold for the basic level. Figure  4 illustrates the adjusted headcount ratio ( \(M_{0}\) ) when the dimension deprivation cutoffs are varied. For both basic and intermediate service levels, the values of \(M_{0}\) take a fairly homogeneous trend at different values of k .

Adjusted headcount ratio at various poverty cutoffs for basic and intermediate service ladders.

The robustness analysis evaluates the extent to which the initially obtained estimates of multidimensional water insecurity are stable and reliable when various parameters are changed. Varying the poverty and deprivation cutoffs confirms that the results are supported across a range of reasonable parameters. Other robustness checks proposed by Alkire and Santos ( 2014 ), such as using alternative indicators, are not conducted due to data limitations. The weighting structure for the dimensions has also not been varied. The robustness analysis conducted in this paper aims at assessing the stability of the H and \(M_{0}\) , and does not offer robustness checks in totality in the sense of recommendations by Alkire et al. ( 2022 ), Azpitarte et al. ( 2020 ) and Alkire et al. ( 2019 ). Despite this, the results obtained are robust and have meaningful policy implications.

5 Conclusion

Water insecurity is a challenge facing policymakers across the globe. This concern spans the dimensions of water quality, availability, quantity, affordability, infrastructure and accessibility. Water insecurity impacts key aspects of a household’s well-being ranging from health, nutrition, and food security to economic productivity. Water insecurity is currently measured in many ways, mostly in one-dimensional approaches with aggregated data at the national level. Such national estimates hinder awareness of household-level heterogeneity in water insecurity, while those based on a single dimension fail to show overlapping deprivations. To better assess household water insecurity, we measured household multidimensional water insecurity using an approach similar to the Alkire–Foster multidimensional poverty index methodology.

The results show that households in Kenya are mostly deprived in the dimensions of water sufficiency and affordability. The intermittent supply of water, which impacts water cost and adequacy, will likely increase as the population grows and as the water supply diminishes due to climate change. Households also bear the burden of time spent on water collection by travelling long distances or queuing for water. The results also indicate that households residing in informal houses, in rural areas and those who are economically disadvantaged are significantly water insecure. There are significantly 15% more water-insecure households in rural areas compared to urban areas, and 10% more water-insecure households in the lower expenditure quintile compared to those in the highest quintile. About 70% of households residing in mud or grass houses are water insecure compared to 53% of those in houses made of cement or bricks. This evidence points towards clear socio-economic and spatial inequalities in household water insecurity. Basic water needs are going unmet, particularly for poor and rural households.

We suggest enhancing constant water supply through infrastructural maintenance, expanding piped water supply networks, and formal housing to allow water plumbing. The devolved governance structure in Kenya, where county governments are tasked with the responsibility of water service delivery, allows better policy targeting and prioritization of water-insecure households, especially those that are economically disadvantaged and in the rural geographies in these counties. As county governments set their own budget, one way that could ensure a sustainable supply of water is by allocating part of their budgets for routine maintenance of the existing water infrastructure. In addition, regulating water tariffs and subsidizing private water providers could enhance water affordability. Physical accessibility of water can be enhanced if water sources are located close to the households’ dwellings and yards. This can be attained by increasing the number of water points shared at the community level and investing in small-scale piped water systems.

The deprivation levels found in this study provide baseline estimates of multidimensional water insecurity in Kenya. While the estimates obtained are sensitive to changes in the parameters chosen to measure multidimensional water insecurity, they are robust and support policies across a range of reasonable parameters.

The estimates of multidimensional water insecurity confirm criticisms of one-dimensional definitions of water insecurity, mostly of proximity and type of water source without considering if water is affordable and sufficiently supplied. Though SDG 6 offers a more comprehensive definition of water access, global monitoring by the WHO/UNICEF JMP with a target of having safely managed water presents a challenge in measuring progress in various aspects of this broad definition. We suggest having more appropriate and specific indicators for measuring water accessibility, affordability, safe and sufficiency to obtain a more accurate picture for monitoring progress in universal water access.

The study complements the existing measures of water security and demonstrates how different dimensions can be combined to estimate multidimensional water insecurity. Because our understanding of water insecurity is limited when one dimension is considered, measuring multidimensional water insecurity will not only provide more precise estimates, but also be of value for different stakeholders in the health, education, gender equality and agriculture sectors. Water insecurity needs to be measured more frequently and precisely because water is critical in the attainment of other development goals. Therefore, there is a need for more approaches to measuring water insecurity to be developed, albeit from different perspectives.

Kenya Vision 2030 aims to transform the country into an industrialized middle-income country and includes development targets such as having 1.2 million ha of irrigation, which will increase water demand.

WHO/UNICEF JPM classifies water sources as improved if they potentially deliver safe water. These include piped water access, public water kiosks, protected wells and springs, boreholes and tubewells, rainwater and packaged water in bottles and sachets. Unimproved water sources include unprotected wells and springs, surface water and water sold in buckets and jerricans.

The deprivation cutoff of affordability is based on households’ total expenditures rather than income because income is often misreported in national household surveys (Beer et al., 2022 ).

The dimensions considered are outlined as critical aspects of the Human Right to Water. The corresponding indicators and thresholds are derived from recommendations by WHO ( 2003 ), United Nations, OHCHR, UN-HABITAT and WHO ( 2010 ), JMP classification in WHO/UNICEF ( 2019 , 2021 ) reports and Howard et al. ( 2020 ). While there is no clear consensus on what it means for water to be affordable, accessible, safe and sufficient, the paper uses the basic thresholds of the diverse policy frameworks. This is because the research setting is a low-income country where 69% of the population lives in rural areas with low use of flush toilets. The country is classified as a water-scare country, and it is estimated that 90% of the country is semi-arid (Davies and Gustafsson, 2015 ).

In future analyses, we aim to explore the application of the Analytic Hierarchy Process by Saaty ( 1980 ) and Saaty and Vargas ( 1987 ), a tool used in calculating weights and priorities in multi-criteria decision analysis.

This estimate is based on the population in 2015 since 51% of the interviews were conducted in 2015. However, it should be noted that if the estimate was based on the 2016 population, about 31 million Kenyans would be considered multidimensionally water insecure.

According to Alkire et al. ( 2022 ) both the headcount and adjusted headcount ratios are declining monotonic functions of k .

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Njoroge, C., Smith, A. & von Fintel, M. Inequalities in Water Insecurity in Kenya: A Multidimensional Approach. Soc Indic Res (2024). https://doi.org/10.1007/s11205-024-03435-3

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The world’s road to water scarcity: shortage and stress in the 20th century and pathways towards sustainability

1 Water & Development Research Group (WDRG), Aalto University, Espoo, Finlan, d

J. H. A. Guillaume

2 National Centre for Groundwater Research and Training & Integrated Catchment Assessment and Management Centre, The Fenner School of Environment and Society, The Australian National University, Australia

3 Institute for Environmental Studies (IVM), Vrije Universiteit Amsterdam, Amsterdam, Netherlands

4 Center for Environmental Systems Research (CESR), University of Kassel, Germany

M. Flörke

5 Institute of Crop Science and Resource Conservation (INRES), University of Bonn, Germany

T. I. E. Veldkamp

Associated data.

Water scarcity is a rapidly growing concern around the globe, but little is known about how it has developed over time. This study provides a first assessment of continuous sub-national trajectories of blue water consumption, renewable freshwater availability, and water scarcity for the entire 20 th century. Water scarcity is analysed using the fundamental concepts of shortage (impacts due to low availability per capita) and stress (impacts due to high consumption relative to availability) which indicate difficulties in satisfying the needs of a population and overuse of resources respectively. While water consumption increased fourfold within the study period, the population under water scarcity increased from 0.24 billion (14% of global population) in the 1900s to 3.8 billion (58%) in the 2000s. Nearly all sub-national trajectories show an increasing trend in water scarcity. The concept of scarcity trajectory archetypes and shapes is introduced to characterize the historical development of water scarcity and suggest measures for alleviating water scarcity and increasing sustainability. Linking the scarcity trajectories to other datasets may help further deepen understanding of how trajectories relate to historical and future drivers, and hence help tackle these evolving challenges.

The overexploitation of freshwater resources threatens food security and the overall wellbeing of humankind in many parts of the world 1 . The maximum global potential for consumptive freshwater use (i.e. freshwater planetary boundary) 2 , 3 is approaching rapidly 4 , regardless of the estimate used. Due to increasing population pressure, changing water consumption behaviour, and climate change, the challenge of keeping water consumption at sustainable levels is projected to become even more difficult in the near future 5 , 6 .

Although many studies have increased the understanding of current blue water scarcity 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , and how this may increase in the future 5 , 6 , 15 , the historical development of water scarcity is less well understood 10 . Trajectories of these past changes at the global scale could be used to identify patterns of change, to provide a basis for addressing future challenges, and to highlight the similarities and differences in water scarcity problems that humanity shares around the world. This requires crossing scales, performing analyses globally, but at a sub-national resolution. Identifying recurring patterns of change can further provide evidence of key drivers of scarcity and thus help to recognise types of problems and solutions. Understanding what has occurred previously can thus help us to avoid repeating mistakes and to build on past successes.

Like other forms of scarcity, physical blue water scarcity can be fundamentally divided into two aspects: shortage and stress. Water shortage refers to the impact of low water availability per person. In “crowded” conditions, when a large population has to depend on limited resources, the capacity of the resource might become insufficient to satisfy otherwise small marginal demands, such as dilution of pollutants in a water body, and competition may result in disputes 16 . Given a resource and per capita requirements, water shortage can therefore be seen as population-driven scarcity. Water stress refers to the impact of high water use (either withdrawals or consumption) relative to water availability. Use of a large portion of a resource 1 , 13 might lead to difficulties in accessing the resource, including side effects 16 , e.g. social and environmental impacts. Stress can be seen as demand-driven scarcity, potentially occurring even if the population is not large enough to cause shortage.

These two aspects have commonly been assessed in isolation from each other 7 , 10 , despite being combined in the seminal work on water scarcity by Falkenmark 1 , 16 , 17 , as well as some later works 15 , 18 . Indeed, the indicators of water shortage and stress are fundamentally related through per capita water use, and therefore provide a more complete picture when used together:

There are, however, multiple ways each of the terms can be defined, yielding different families of indicators for shortage and stress. For example, use can refer to consumption or withdrawals. Availability might refer to water from different sources, of different quality, or at decadal, annual or seasonal time scales. The population in question might be that which is dependent on a resource, which is physically located within a region, or only that which has access to the resource.

Given the complexity of the impacts, these are clearly crude indicators of actual impacts involved in stress and shortage. There is substantial uncertainty in determining at what value of the stress and shortage indicators, stress and shortage impacts actually occur. Even when justified thresholds are selected, the value of the indicator is typically also reported, so that the reader can form their own opinion of whether stress and shortage have really occurred.

Despite their high level of abstraction, and the multiple ways in which they can be used, the concepts of shortage and stress and their defining indicators are central to understanding the development of scarcity over time. Therefore, they provide an obvious first step in analysing trajectories of past changes.

This paper first explores how water consumption has evolved globally over the entire 20 th century. The analysis uses recently released spatially explicit data for the entire past century on socio-economic development 19 and irrigation 20 , which allow us to assess past water consumption trends in greater detail, using the WaterGAP2 hydrological and water use models 19 , 21 (see Methods). This evolution is put into context by assessment of water scarcity based on the concepts of shortage, stress and per-capita consumption, structured graphically using a Falkenmark matrix 1 , 16 , 17 . Archetypes and shapes of the trajectories are introduced as new concepts to characterize the historical development of water scarcity in regions, and hence to assess the effectiveness of potential alleviation strategies and define pathways towards sustainability.

The version of the shortage and stress indicators we use consider decadal scale water availability and consumption at sub-national scales. They therefore capture the effect of long term sub-national water scarcity, but not the seasonal variation in demand and supply, inter-annual variability or sub-regional variation. We focus on physical blue water scarcity, meaning that issues of access are omitted, and emphasis is on water in lakes, rivers and renewable groundwater rather than “green” water, soil water from precipitation directly used by plants, or non-renewable fossil groundwater. Moderate (high) shortage is deemed to occur when total water availability drops below a requirement of 1700 m 3 cap −1 yr −1 , (1000 m 3 cap −1 yr −1 ) 1 , 7 . Moderate (high) stress is deemed to occur when more than 20% (40%) of available water is consumed 1 . The stress threshold was originally applied to water withdrawals but is used here for water consumption to account for substantial return flows that are still available for downstream users 22 , 23 . The focus on consumption also means that water degradation caused by return flows is not considered as part of stress, though it is still (indirectly) captured through population-driven pollutant load as part of shortage.

This study’s findings show a nearly 16-time increase in population under water scarcity since the 1900s although total population increased only 4-fold over the same time period. Per capita water consumption only shows a slight and irregular increase over the past century, while the expansion of water scarcity is predominantly explained by the effects of spatial distribution of population growth relative to water resources.

Water consumption

The global population has almost quadrupled over the past hundred years, and it reached 6.5 billion in the last time step of the study period, i.e. the 2000s (given decadal results are averages over specified decades, in this case 2001–2010) 24 . Over the same period, annual consumptive blue water use per capita (see Methods for details) increased only from 209 m 3 cap −1 yr −1 in the 1900s (i.e., 1901–1910) to 230 m 3 cap −1 yr −1 in the 2000s, with some variation between decades and a maximum of 256 m 3 cap −1 yr −1 in the 1960s ( Fig. 1B ). The increases in population and per capita water consumption resulted in a total water consumption increase from 358 km 3 yr −1 in the 1900s to 1500 km 3 yr −1 in the 2000s ( Fig. 1B ).

Regional ( A ) and global ( B ) consumptive water use trends over the 20 th century. The filled area represents per capita water consumption trends while the dashed line represents the total water consumption trends. The per capita consumption is divided into different water use sectors. The trend in per capita consumption at the FPU scale is shown as a background. [Adobe Illustrator CS5, ArcGIS 9.2 and Matlab 2015b softwares were used to create the figure; http://www.adobe.com/products/illustrator.html , http://www.esri.com , and http://www.mathworks.com ].

The trends of water consumption over the 20 th century were not, however, similar across the globe ( Fig. 1A ). The consumption per capita seems to have remained rather stable in many regions, such as Southern Africa and South America, but declined in the Middle East (since the 1950s), Northern Africa and South Asia. However, per capita consumption increased rapidly in Australia-Pacific, being over 6-fold greater in the 2000s compared to the 1900s. Increases were also found in Eastern Europe & Central Asia (until the 1990s) and Western Europe, although less rapid.

At the FPU (i.e., food production unit; see Methods) scale, this dataset shows that trends in per capita water consumption also varied significantly within the regions ( Fig. 1A ). A good example is North America, where the west coast experienced a decreasing trend while on the east coast, water consumption per capita increased. Of the world population, 46%, 25% and 29% live in FPUs where per capita consumption respectively increased, decreased, or showed no statistically significant trend over time (two-sided p -value > 0.05 with the Mann-Kendall test).

Although the trend in per capita water consumption varied between regions, total water consumption increased in all regions due to increased population except in Eastern Europe and Central Asia, where the total consumption decreased slightly (~7%) since the collapse of the Soviet Union in 1990 ( Fig. 1A ). Growth was greatest in Australia-Pacific (30-fold increase) followed by Central America, Southern Africa, and Southeast Asia (approximately eight-fold). In a number of regions, consumption increased 3–4 fold, with the lowest increase in Northern Africa with about a three-fold increase.

Globally, irrigation was by far the largest water consumer over the entire study period, with a share ranging over time between 90–94% of global water consumption ( Supplementary Fig. 1B ). It had the largest share in South Asia (96–98%) due to extensive rice cultivation, and in the Middle East (97–99%) due to arid conditions 20 . In Western Europe, the irrigation share of total water consumption was lowest (62–74%), as it includes areas where irrigation is not extensively practiced for food production. Moreover, the economy is more industrialised than, for example, in Asia. Globally, the second largest sector until the 1990s was domestic water consumption. However, this was surpassed by industrial water consumption in the final time step (2000s; domestic 3.7%, industrial 4.3%). A second notable global trend is the emergence of water consumption due to thermal electricity production (~1% share). Regionally, results show larger changes in the shares of different sectors, though the real-world significance of the changes is difficult to judge. In some areas (e.g. Western Europe, Australia/Pacific), the proportion of water consumption used for irrigation has increased and the proportion for domestic consumption has decreased. The opposite has occurred in other areas (e.g. North America, Supplementary Fig. 1A ).

Global and regional water scarcity

Despite only small variations in per capita water consumption over time ( Fig. 1A ), rapidly expanding local populations and increases in total water consumption resulted in a nearly 16-fold overall increase in the population under water scarcity within the 20 th century ( Figs 2 and ​ and 3). 3 ). Whilst in the 1900s just over 200 million people (14% of global population) lived in areas under some degree of water scarcity, this number increased to over two billion by the 1980s (42%), and reached 3.8 billion people (58%) by the 2000s ( Table 1 ; Fig. 2B ).

Regional ( A ) and global ( B ) water scarcity trajectories. Filled graphs represent the absolute population under water scarcity (in billions) while dashed lines represent the population relative to total regional population. M WStr refers to moderate water stress, H WStr to high water stress, M WSh to moderate water shortage, and H WSh to high water shortage. See definitions of these different water scarcity dimensions, and their combinations, in Table 1 and Fig. 4A . [Adobe Illustrator CS5, ArcGIS 9.2 and Matlab 2015b softwares were used to create the figure; http://www.adobe.com/products/illustrator.html , http://www.esri.com , and http://www.mathworks.com ].

Mapped water scarcity categories for years 1905 ( A ), 1935 ( B ), 1965 ( C ), 1985 ( D ), and 2005 ( E ). The definition for each scarcity category is given in Table 1 and Fig. 4A . [Adobe Illustrator CS5 and ArcGIS 9.2 softwares were used to create the figure; http://www.adobe.com/products/illustrator.html , http://www.esri.com ].

M WStr refers to moderate water stress, H WStr to high water stress, M WSh to moderate water shortage and H WSh to high water shortage. See matrix of the scarcity classes in Fig. 4A .

In the 2000s, roughly half of the people under water scarcity suffered either moderate water shortage or moderate water stress ( Table 1 ), while the other half lived in areas facing both water stress and water shortage. Of these, 1.1 billion people (17% of global population) lived in areas facing both high water shortage and high water stress ( Table 1 ; Fig. 2B ). Most of these people lived in South and East Asia, North Africa and Middle East ( Fig. 2A ), with 61–89% of the population under water scarcity. The regions with the lowest proportion of population under water scarcity were Australia-Pacific, South America, North America, and Southeast Asia (7–29%, Fig. 2A ). Around a half of the population under water scarcity in the 2000s suffered water shortage alone, without water stress ( Table 1 ; Fig. 2B ). These areas are located in Sub-Saharan Africa, Central America, Europe, and South and East Asia ( Figs 2A and ​ and3E). 3E ). A small part of the population (2%) suffered water stress alone ( Table 1 ), occurring mostly in North America, Middle East, and Australia ( Fig. 3E ).

A global water scarcity trend-plot ( Fig. 2B ) reveals that the population under water shortage, or a combination of high water stress and water shortage, has increased rapidly since the 1960s, while water stress alone has remained rather low over the entire study period. There are, however, differences in regional trajectories ( Fig. 2A ), indicating that, for example, in the Middle East, Northern Africa and North America, scarcity has developed gradually over the whole study period while in many other regions (e.g. Central America, Southern Africa, South Asia, Southeast Asia, and East Asia) there has been a steep increase in scarcity trend since the 1960s.

Different FPUs show distinct population dynamics, climate patterns, and developments of water consumption per capita. An FPU’s long-term water scarcity trajectory over time is visualised using the Falkenmark matrix 16 ( Fig. 4 ) that distinguishes between population-driven water shortage and demand-driven water stress, and highlights the relationship with per capita consumption using superimposed diagonal lines. Drivers and adaptation strategies are strongly dependent on the level and type of water scarcity an FPU is experiencing ( Fig. 4B ). As defined in Table 2 and discussed below, the notions of archetypes and shapes help to make sense of these trajectories. The archetype refers to the positioning within the Falkenmark matrix ( Fig. 5 ), whilst shape ( Fig. 6 ) refers to the direction of change over time.

( A ) the water scarcity categories; and ( B ) Drivers and alleviation measures. The diagonal lines in tile B refer to per capita consumption isolines. [Adobe Illustrator CS5 –software was used to create the figure; http://www.adobe.com/products/illustrator.html ].

FPU water scarcity trajectories by scarcity archetypes in a map ( A ) and within the Falkenmark matrix ( B–G ). Archetypes categorise FPUs according to their water scarcity status (corresponding to position on the plot) and where both shortage and stress occur, according to which occurs first (which is related to the level of per capita consumption). The trajectories are grouped based on irrigation zone 20 they are located in. See Table 2A for definitions and Supplementary Table 2 for percentage of population in each archetype – irrigation zone combination. Note: only FPUs with more than one million people are included. [Adobe Illustrator CS5 and R studio softwares were used to create the figure; http://www.adobe.com/products/illustrator.html , https://www.rstudio.com ].

( A and B ) FPU shapes shown as map, separated according to whether scarcity has been experienced ( B ) or not ( A ). ( C ) Examples of shapes of FPU water scarcity trajectories. The diagonal lines refer to per capita consumption isolines and numbers to FPUs (location indicated in tile B ). See Table 2B for definition of each shape category and Supplementary Fig. 2 for each FPU trajectory categorised by their shape. [Adobe Illustrator CS5 and R studio softwares were used to create the figure; http://www.adobe.com/products/illustrator.html , https://www.rstudio.com ].

* Trajectories are characterised in two different ways.

+ Trajectories are assigned to the first applicable category.

FPU water scarcity trajectories: archetypes

The concept of water scarcity trajectory archetypes captures issues related to water scarcity status and per capita consumption. Trajectory archetypes are thus also useful to identify possible adaptation measures in an FPU. Their definitions are summarised in Table 2A while Fig. 5 maps the regions belonging to each archetype, and displays their trajectories. Each archetype is discussed further below.

The archetypes stress alone or stress first (before shortage) are experienced if per capita consumption is high ( Fig. 5F,G ), such that scarcity is demand-driven. FPUs in this category would thus benefit most from demand-side oriented adaptation strategies. The archetypes shortage alone or shortage first ( Fig. 5C,D ) are experienced if per capita consumption is low, such that scarcity is population-driven. This calls for supply-side adaptation strategies in particular. This division of adaptation strategies also corresponds to a distinction between ‘soft’ behaviour-change and ‘hard’ infrastructure-based solutions, respectively 1 , 17 , 25 , 26 ( Supplementary Table 1 ).

Specifically, using a threshold of stress of 20% and a per capita water availability (shortage) threshold of 1700 m 3 cap −1 yr −1 , the switch-over point between stress first and shortage first occurs at a per capita consumption of 340 m 3 cap −1 yr −1 ( Fig. 5A–F ; Methods). The stress and shortage at same time archetype is a borderline case, in which per capita consumption varies near that switch-over point. For that archetype, both adaptation strategies may be relevant. When an FPU is of a no scarcity archetype, no direct adaptation measures are necessary. However, as population grows, the per capita consumption of an FPU sets it on a trajectory towards either stress first or shortage first, and so the above introduced guidelines may apply.

For stress first and stress alone archetypes, the need for demand management rather than supply side measures 1 is motivated by the common ideological point of view that high per capita water consumption should be reduced. In practice, however, there seems to be a tendency to meet demand first, for example in the case of trajectories with a constant per capita demand shape (see Fig. 6C ). This might be explained in terms of the “hydraulic mission” 27 , common around the world in the 20 th century, which aims to dominate nature in order to increase food production and provide water and food security. This has to some extent been curbed by increased emphasis on social and environmental impact assessment 27 , 28 . Ideally, adaptation strategies should focus first on increasing water productivity (domestic, agricultural, and industrial) or on shifting to lower water footprint goods and services. The latter might include reducing virtual water exports 29 and/or increasing virtual water imports 30 . Several of these actions would not be captured by the data and analysis applied, and may have already occurred, as suggested by recent studies 29 , 31 , 32 , 33 , 34 .

For cases where shortage occurs before stress, supply-side options are in principle preferred because lower per capita water consumption provides less potential for demand-side intervention than when stress occurs first. There are, however, two main ways to handle water shortage: (i) increasing available water, or (ii) limiting population. Available water can be increased by using desalination (in coastal areas) 35 , introducing physical water transfers 36 , 37 and/or reducing non-productive evaporation 38 . Increased storage capacity is likely to play a smaller role at decadal scale, but is a common strategy to increase seasonal or inter-annual water availability. Emigration and lowered birth rates may limit population, but are perhaps better treated as side-effects of other developments rather than explicit water scarcity strategies. Moreover, an area can adapt to water shortage by using the strategies to reduce per capita water consumption. Possibilities for reducing water requirements include more efficient irrigation 39 , reduction of food losses 40 , reduction of water-intensive goods 41 , 42 , and reduction of leakages in public supply systems 43 .

The potential for reducing blue water consumption notably depends on green water availability (soil water from precipitation), especially in the case of agriculture 13 , but also, for example, on urban parks and golf courses. Areas with reliable green water resources tend to have lower blue water consumption, and hence less stress. While this study does not quantify green water availability, it does show that different archetypes occur depending on the reason for irrigation consumption (which is the largest water-consumption sector in most areas). As discussed in Siebert et al . 20 , irrigation is notably driven by: (i) the desire to make agriculture possible in arid areas; (ii) the desire to increase productivity in semi-arid and temperate areas; or (iii) weed-suppression by controlling the water level when growing rice. The results by irrigation zones 20 (see Fig. 5 for trajectories by irrigation zones, and tabulated results for population in Supplementary Table 2 ) indicate, for example, that most of the high per capita consumption stress first (90% of FPUs within those archetypes) or stress alone (82% of FPUs) trajectories occur in arid regions, consistent with higher crop water requirements due to irrigation. Shortage alone in turn occurs commonly in wet areas (50% of FPUs), consistent with low water requirements and high population pressure.

In practice, it appears that shortage is not directly tackled until stress occurs. Moderate shortage is tolerated, perhaps buffered by low consumption and other water sources, such as virtual water imports, green water and fossil groundwater. This avoids tackling the underlying issue of population growth, and stress is reached some time later. For example, in North-eastern Mainland China, some FPUs have experienced shortage since before 1905, and others more recently since 1925 and 1975 ( Supplementary Fig. 3 ). Stress followed years or decades later, as population grew. Groundwater and a number of inter-basin transfers are already in use, and additional south-north transfers are in development 44 , 45 . These FPUs are good examples where per capita blue water consumption is low enough that shortage occurred first. There is, however, significant potential for further reductions due to large virtual water exports, which could avoid the need for inter-basin transfers 45 .

FPU water scarcity trajectories: shapes

When FPU trajectories are distinguished by their shape , it is possible to understand the dynamics of consumption over time, and how that has impacted on the scarcity type (shapes are summarised in Table 2B ; example trajectories for each shape are shown in Fig. 6C and all trajectories in Supplementary Fig. 2 ). Further, shapes can be used to assess what needs to be done for an FPU to be put on a sustainable pathway, avoiding both water stress and water shortage in the long term. The majority of FPUs show significant temporal variation in per capita water consumption, stress, and shortage, consistent with the expected tension between population growth, water supply and demand management. In general, achieving sustainable water consumption on a decadal scale requires a combination of stabilising population, enforcing limits of sustainable supply, mitigating impacts of water stress and/or reducing water requirements.

All these strategies are likely to be required to deal with FPUs in the shape categories increasing scarcity and other . The former face both incessant population growth and intensification of water consumption, which currently leads to strictly increasing stress and shortage (6.6% of global population in 2000s, Fig. 6 ), for example in parts of the Balkans (FPU 169, Fig. 6 ). The other shape category (32.2% of the population) shows complex trajectories for which specific recommendations cannot be made without other economic or demographic data.

In FPUs where the trajectory shape is determined by constant per capita demand (29% of population), changes in scarcity are predominantly determined by population growth. Constant per capita demand is visible as a (relatively) straight diagonal trajectory in the Falkenmark matrix ( Figs 4B and 6C ). As long as per capita consumption is kept in check, stabilising population is an effective strategy for FPUs with any trajectory shape as it avoids increases in shortage and total consumption, and hence stress.

In FPUs with strictly increasing stress but varying shortage (4.9% of population), consistent intensification of water consumption is the key concern, for example in northern France (FPU 121, Fig. 6 ). Recognising the socio-economic importance of exploitation of the local water resource and potential difficulty in curbing water consumption, achieving sustainability may involve mitigation measures to allow greater water consumption than would otherwise be possible. Examples include improving water allocation and other governance mechanisms, providing storage and channelling engineering works, optimising environmental flows, and benefit-sharing to compensate other impacted users. This corresponds to the idea of ‘decoupling’ growth from impacts 46 .

In FPUs with strictly increasing shortage but varying stress (15% of population), the key concern is strong population growth, as in northern India (FPU 494, Fig. 6 ). Recognising that addressing the drivers of population growth may take time, achieving sustainability may involve reducing local water requirements, so that consumption does not grow in parallel with population. This corresponds to decoupling growth from resource use and may be achieved by improved water productivity or decreasing water-dependent production 40 , 41 . Decoupling from resource use already appears to be occurring in many areas, as shown by decreasing trends for per capita consumption ( Fig. 1 ). In FPUs where irrigation is important, per capita consumption is particularly influenced by area equipped for irrigation and a combination of irrigation efficiency and climate effects. However, the most prominent examples of decoupling from local resource use are FPUs dominated by cities, taking as an example FPU 307 in western Africa (32 million people in 2000s), which includes the megacity of Lagos in Nigeria. While some food and other water-dependent products are produced in the hinterland, they can also be imported from elsewhere (along with virtual water) 47 . Such areas can therefore have relatively low local blue water requirements, mainly for domestic and industrial water supply (83% of total water consumption at FPU 307). The sustainability of such FPUs depends largely on their interactions with regional and global water resources.

In addition to cases where trends suggest that decoupling is occurring, the analysis identifies some cases with a stress decrease -shape (10% of population), or where stress stabilised ( stress ceiling -shape, 2% of population). In most cases, this occurs as a result of decreases in consumption, but appears to be driven often by socio-economic factors rather than limited water availability. Results show that FPUs that have reached a stress ceiling are mostly those with high per capita consumption that suffer water stress alone ( cf. Figs 3 and ​ and6B) 6B ) in North America, Central Asia, or Africa. However, stress ceilings occur even with a stress level of 10% (e.g. in Northern Africa), and decreases in stress in FPUs that are not water scarce in large parts of the former Soviet Union ( Fig. 6A ), following the dissolution of the Soviet Union. This may thus be related to the region’s political and economic changes. Consistent with the idea of a “hydraulic mission” 27 , 28 , dams and canals increased supply to allow irrigation demand to expand. Reductions in consumption then occurred not just due to improvements in irrigation efficiency but also due to a shift from exported cotton (and virtual water 29 ) to food self-sufficiency in the newly independent nation states 48 , 49 . Water scarcity trajectories and their sustainability are closely tied with other socio-economic and political issues.

This study highlights key issues in understanding global historical water scarcity and pathways for future adaptation. Considering both forms of water scarcity, this analysis provides an improved understanding of blue water consumption and trajectories of past water scarcity development globally at sub-national level for the entire 20 th century. The results show that more people are under water scarcity than previously estimated ( Supplementary Table 4 ).

Only a few previous studies assessed historical water scarcity using multiple water use sectors 10 , 19 , 50 , and even then only for the past 50 years. This study’s results compare well with previous trends and estimates of water consumption since 1960, the starting period of existing assessments 10 , 50 ( Supplementary Table 3 ). The largest improvement in this study, in terms of water consumption trends, is the use of historical spatially explicit irrigation maps 20 rather than national values. This results in large differences in the location and extent of irrigation areas, particularly in large countries, such as the USA 20 .

Findings for population under stress and shortage separately also show good agreement with existing studies of historical water scarcity ( Supplementary Table 4 ). The existing studies focus on water stress alone 10 or water shortage alone 7 , or assess both forms of scarcity at only one or two time steps 16 or scenarios 29 , with the exception of one study 18 that assesses the interannual variability of blue water scarcity. Assessing both shortage and stress over several decades provides additional insights on the development of water scarcity. The FPU-level trajectories show signs not just of differences in resource endowments and local history, but also similarities due to shared problems and diffusion of solutions, suggestive of a global shared destiny for which collaboration is essential. Classifying sub-national water scarcity trajectories in terms of archetypes ( Fig. 5 ) helps to highlight possible adaptation actions to cope with shortage and/or stress, depending on the level of water consumption in per capita terms. Classifying trajectories in terms of their shape ( Fig. 6 ) helps to highlight different approaches to put FPUs on a sustainable pathway. Nearly all FPUs show an increase in scarcity over time as population increases ( Fig. 6 ; Supplementary Fig. 2 ), indicating that understanding of scarcity adaptation actions and pathways to sustainability will only become more important in the future. These historical trajectories provide a common foundation from which further work can dig deeper to identify mistakes to avoid repeating, and past successes worth replicating, in order to better tackle future challenges of water scarcity.

As noted in Introduction, results presented correspond to a well-defined scope focussed on scarcity associated with a long-term view of consumptive blue water use. The selected indicators are widely adopted and can be linked to previous studies 8 , 9 , 10 , 14 , 18 . Additional information sources that would allow more sophisticated water scarcity analysis are not available for the entire study period. These include water quality, technological and social access to water and trade of virtual water. Future studies could include these aspects.

Furthermore, the analysis is commensurate with the significant uncertainty involved in the datasets and models used to cover the globe for the past 110 years 51 , 52 . In this study, two important datasets are combined: water availability and water use, both provided by the WaterGAP2 model. In order to reduce uncertainty in water availability estimates, the model has been calibrated in a basin-specific manner against mean annual river discharge using 1319 gauging stations 53 . Previous studies have reported that the model performs well in relation to other global hydrological models when compared to observations 51 , giving confidence in our water availability estimates. Water use data, on the other hand, is viewed as particularly uncertain 54 . For example, in a multi-model comparison, Wada et al . 55 show that modelled irrigation demand compares reasonably well to country-scale reported values (deviations in the range of +/− 15% in most cases) and conclude that most models are capable of simulating regional variability in irrigation water demand across the globe. Since irrigation constitutes the largest share to global total water consumption and is the dominant water-consuming sector in many parts of the world, it is very likely to also dominate the uncertainty in estimated total water consumption.

We compared the water consumption data of this study to two previous studies assessing the past water consumption 10 , 50 ( Supplementary Table 3 ), and found that the consumption estimates vary on the order of 35%, this study being the most conservative one. When our water scarcity results were compared to existing studies 10 , 18 ( Supplementary Table S4 ), we found that estimates of global population under shortage, and population under stress vary on the order of 15% and 30% respectively.

Besides these two key input data products, various assumptions have been made in the analysis itself. A notable assumption relates to the thresholds used to differentiate different states of water stress and shortage. Whilst these assumed thresholds directly affect the amount of population living under water scarcity, they do not affect the trajectory lines in the Falkenmark matrix themselves. Correspondingly, the shapes of the trajectories are not affected by these thresholds. However, trajectory archetypes would somewhat be impacted, as changing these thresholds would mean a specific FPU reaches a certain level of scarcity a decade earlier or later.

As a result, our emphasis is on drawing coherent insights rather than providing precise estimates. In this context, specific numbers represent one possible realisation in the context of significant uncertainty. This is important when comparing our results for a specific year with other studies. The key conclusions of this study are, however, robust, namely the interpretation of sub-national shortage and stress trajectories and the importance of population growth and per capita water consumption in determining local development of scarcity. They are consistent with existing understanding, and strongly influenced by patterns in input data (e.g. population growth and expansion of irrigation area) that are independent of other assumptions made in the analyses.

The analytical approach used and the initial insights it provides could also be used as a foundation for further research. Additional information about uncertainty could be obtained by systematically repeating the analysis with other models and forcing datasets, as has been done in comparable contexts 5 . This would, however, require a carefully chosen, meaningful set of scenarios. A range of different assumptions can be used regarding scarcity thresholds and indicators, focussing on different issues delimiting different perspectives on safe and just operating spaces for socio-ecological systems 3 , 56 . Calculating indicators at seasonal 11 , 57 or annual scale 18 , 58 would allow investigation of how shortage and stress occur at shorter time scales, more closely related to every-day operations rather than long-term planning. Ideally, availability would be tied to access, which would help alleviate problems related to selection of spatial scale 59 . Focussing on water quality 60 , 61 , unsustainable water sources 62 , and on spatially explicit environmental flow requirements 4 , 63 (the thresholds used for water stress assume global environmental flow requirements of 30% 17 ) would explicitly identify the portion of available water that should not be used to avoid stress according to different criteria. Similarly, focussing on self-sufficiency of water and food 12 , 58 , 64 would identify specific water requirements for shortage, though it would also require greater consideration of both blue and green water 13 .

Whether self-sufficiency is required is particularly relevant in the context of trade 65 and virtual water transfers 31 , which are not captured in this study. From an economics perspective, scarcity is not intrinsically problematic, but rather raises questions of optimal allocation of the scarce resources, trade to make use of comparative advantages, and the inclusion of externalities. Prominent issues include the role of water quality and safety 66 , and accessibility and equity determined by social, economic and political circumstances 25 , 67 , 68 , 69 , 70 , 71 . Linking the trajectories to other datasets may help deepen understanding, expanding and better explaining the shapes introduced here ( Table 2B ), and how they relate to historical and future drivers as well as limits to adaptation.

Analysis unit: Food production units

This study used food production units (FPUs), a combination of river basin and administrative boundaries 7 , 72 , 73 , as an analysis unit. These are reported to be suitable for water scarcity studies 7 , 58 . For this project, a set of FPUs were developed that are consistent with the basin delineation of the WaterGAP2 hydrological and water use models, resulting in 548 FPUs. It is important to use the same delineation for FPUs as watersheds of the WaterGAP2 model, as the way water availability is dealt with (see Fig. 7 ) requires that FPUs do not cross the borders of large river basins. Results are also aggregated from the FPU scale to regional ( n  = 12) scale. The regions are based on UN macro regions aggregating the countries to larger units 74 with the difference that some of the largest regions were divided into smaller regions by Kummu et al . 7 to be more suitable for (historical) water analyses.

Water availability calculations in a large basin with several FPUs, i.e. each FPU is a sub-basin for the large basin. A: schematic illustration of a basin with four FPUs; B: Runoff of each grid cell in km 3 yr −1 ; and C: discharge of each grid cell in km 3 yr −1 . The share of available water resources is calculated as the sum of discharges of each grid cell within an SBA divided by the sum of discharges of all grid cells within a basin. The available water resources are then calculated by multiplying that share with the total available runoff of the whole basin. [Adobe Illustrator CS5 –software was used to create the figure; http://www.adobe.com/products/illustrator.html ]

Water availability

This analysis used the global hydrological model WaterGAP2 53 to derive gridded estimates for runoff and river discharge at 30 arc-min spatial resolution for the study period of 1901–2010. Based on daily meteorological forcing fields and spatially distributed physiographic information (e.g. soil, land cover), the model simulates the terrestrial water cycle by a sequence of storage equations for the storage compartments canopy, snowpack, soil, renewable groundwater, and surface water bodies. For this study, simulations were driven by WATCH Forcing Data (WFD) which is available for the period 1901–2001 75 . Since it is not recommended to combine WFD with other similar data-sets 53 , 76 in order to derive full coverage over the study period 1901–2010, simulations for the period beyond the year 2001 were based on 1990s climate forcing.

Since this analysis focuses on long-term trends in water scarcity, the 10-yr annual average over each decade was calculated for both discharge and runoff to compensate for inter-annual variability. These data were then used to assess the water availability in each FPU. The calculation of water availability can be divided into two cases:

• In cases when an FPU consisted of one basin or several small basins, water availability was simply the sum of annual runoff generated within the area of a specific FPU.
• In cases of large river basins that were divided into several FPUs, a simple ‘water sharing rule’ was used to assign the available freshwater resources within each FPU 5 , 12 . This was developed in a way that it would be usable for both water shortage and water stress calculations, i.e. the sum of water availability of the FPUs within the basin cannot exceed the annual runoff of the basin. The water sharing rule was based on a discharge proportion of FPUs within a basin multiplied with the annual runoff, as illustrated in Fig. 7 .

The water use model of WaterGAP2 simulates water withdrawals and consumption of the following sectors: i) irrigation, ii) livestock farming, iii) thermal electricity production, iv) manufacturing industries, and v) households and small businesses (domestic).

To indicate the area equipped for irrigation (AEI), the analysis used the HID product by Siebert et al . 20 , which gives spatially explicit AEI for the entire 20 th century. The proportion of irrigated harvested rice area was based on the MIRCA-2000 dataset 77 . The proportions were kept at year 2000 level throughout the study period due to lack of historical data. As in the case of the water availability simulations (see above), to simulate the irrigation water consumption beyond 2001, climate forcing data from the 1990s were used. The estimate of consumption for the 2000s should therefore not be included when assessing trend in per capita consumption. Irrigation water consumption is the amount of water that must be applied to the crops by irrigation in order to achieve optimal crop growth. Monthly consumptive irrigation requirements are therefore based on climate, the spatial extent of AEI and crop type (rice and non-rice). Return flows, i.e. water withdrawal minus water consumption, which account for water that infiltrates and returns to the water cycle, are not quantified in this study.

Livestock water consumption was calculated on the basis of gridded information on the number of livestock units and water consumption per head and year, taking into account 10 livestock types 21 . Due to limited data prior to the year 1960, livestock water consumption for the period of 1900–1960 was kept at the level of 1960. Overall, this may lead to an underestimation or overestimation in livestock water consumption depending on the FPU 78 , which is expected to be minor as the amount of livestock water consumption is small compared to the other sectors. Water consumption estimates for electricity, manufacturing, and domestic sectors were based on the methodologies described in Flörke et al . 19 . In brief, domestic water consumption is estimated from population and domestic water use intensity, taking into account structural and technological changes. Country-scale water consumption in the manufacturing sector is calculated from manufacturing structural water use intensity, gross value added, and consumption coefficients; again taking into account technological change. The amount of water withdrawn and consumed for cooling purposes in thermoelectric power production is determined from the annual thermal electricity production and the water use intensity of each power station, distinguishing three cooling system types (once-through, pond, and tower cooling systems) and several fuel types (fossil/biomass/waste-fuelled, nuclear, natural gas/oil combined, coal/petroleum residuum-fuelled). Based on this information, the model approach distinguishes 14 combinations of plant type (PT) and cooling system (CS). In 2010, about 2.8% of cooling water abstractions evaporated, i.e. most of the water withdrawn was discharged back into rivers (Flörke et al . 19 ).

To get the total water consumption, all the water use sectors are summed together. Trends in per capita consumption (see background in Fig. 1A ) were determined with the Mann-Kendall test, calculating the Kendall correlation of demand with time. A p -value of 0.05 was used as part of a two-sided test of whether the correlation was statistically significantly different from zero.

Water stress calculations

The indicator of blue water stress is the water use to availability ratio. We use consumption rather than withdrawals, such that water ‘use’ means that water is no longer available for other users. The indicator was calculated for each decade and for each FPU. The water stress thresholds used are, however, those for the withdrawal-based water stress index (WSI) developed by Falkenmark 16 , and used by a number of other studies 8 , 10 , 57 , 78 :

• WSI <0.2: no water stress
• WSI = 0.2–0.4: moderate water stress
• WSI >0.4: high water stress

Using withdrawals risks over-estimating the actual stress as a substantial part of the withdrawals are available for downstream users as return flows 22 , 23 . On the other hand, using water consumption, as in this study, might underestimate the water stress. Recent work by Munia et al . 79 uses consumption and withdrawals as minimum and maximum levels of scarcity, respectively. They show that the difference between these two estimates results in an 18 percent point difference in the amount of population under water stress. Similar uncertainties in the absolute amount of people under water scarcity should be considered for the numbers quoted in this study. This may also be worthwhile approach for future work. Finally, it should be stressed that the thresholds used assume a global environmental flow requirements of 30% 17 .

Water shortage calculations

For water shortage calculations the analysis is based the water crowding index (WCI) developed by Falkenmark 17 , 80 . WCI is calculated by dividing the water availability by total population of an FPU. Here, historical, spatially explicit, population data is from HYDE 3.1 81 . The water shortage thresholds are as follows:

• WCI >1700 m 3 cap −1 yr −1 : no water shortage
• WCI = 1000–1700 m 3 cap −1 yr −1 : moderate water shortage
• WCI <1000 m 3 cap −1 yr −1 : high water shortage

Water scarcity matrix and related calculations

To illustrate the combination of water stress and water shortage, the analysis used the Falkenmark water scarcity matrix ( Fig. 4 ). By plotting water stress against shortage over time, water scarcity trajectories were derived for each FPU. These trajectories in turn were categorised for archetypes and shapes ( Table 2 , and see below).

The formulas used for the indicators mean that for any combination of stress and shortage, per capita consumption can also be calculated (see diagonal lines in Fig. 4B ). For example, consider the point where an FPU is classified as under both water stress and water shortage:

The corresponding per capita consumption can be calculated for those values of stress and shortage (see also Fig. 4B ):

For a given per capita consumption, this formula can be rearranged to identify whether an FPU would already be stressed when the shortage threshold is reached (shortage = 1700 m 3 cap −1 yr −1 ).

Therefore, the following interpretation can be made when assuming shortage of 1700 m 3 cap −1 yr −1 :

If per capita consumption = 340 m 3 cap −1 yr −1 → stress = 0.2 (stress and shortage same time)

If per capita consumption >340 m 3 cap −1 yr −1 → stress >0.2 (stress occurs first)

If per capita consumption <340 m 3 cap −1 yr −1 → stress <0.2 (shortage occurred first)

Scarcity archetypes

The scarcity archetypes define the water scarcity status and level of per capita consumption (see Table 2A ). Scarcity categorisation for archetypes is based on the lowest stress (20%) and shortage thresholds (1700 m 3 cap −1 yr −1 ). ‘No scarcity yet’ are FPUs that have never reached the lowest threshold of water stress (20%) or shortage (1700 m 3 cap −1 yr −1 ). For ‘Shortage alone’, water availability has passed the threshold of 1700 m 3 cap −1 yr −1 , but stress has remained below the threshold of 20%. ‘Stress alone’ occurs where stress exceeds 20% but water availability (i.e. shortage) has never dropped below 1700 m 3 cap −1 yr −1 . ‘Stress first’, ‘Shortage first’ and ‘Stress and shortage at same time’ occur when the trajectory has exceeded both the stress and shortage thresholds, sub-categorised according to which type of strategy is reached first.

Scarcity shapes

The scarcity shapes, in turn, divide the trajectories into categories based on their shape when plotted in the Falkenmark matrix. Specific rules for each shape were developed as outlined in Table 2B .

Additional Information

How to cite this article : Kummu, M. et al . The world’s road to water scarcity: shortage and stress in the 20th century and pathways towards sustainability. Sci. Rep. 6 , 38495; doi: 10.1038/srep38495 (2016).

Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Material

Acknowledgments.

Study was funded by Academy of Finland project SCART (grant no. 267463), Emil Aaltonen foundation (‘eat-less-water’ project), Academy of Finland funded SRC project ‘Winland’, and Maa- ja vesitekniikan tuki ry . Additionally, P.J. Ward received funding from the Netherlands Organisation for Scientific Research (NWO) in the form of a VENI grant (grant no. 863-11-011) and T.I.E. Veldkamp from EU 7th Framework Programme through the projects ENHANCE (grant agreement no. 308438) and EartH2Observe (grant agreement no. 603608). Authors are grateful to Suvi Sojamo and Olli Varis for their comments and support.

Author Contributions M.K., J.H.A.G., H.d.M., S.E., S.S. and P.J.W. designed this study in consultation with M.F. and T.I.E.V. The modelling was conducted by S.E. and M.F. supported by M.K., J.H.A.G., H.d.M. and M.P. Analyses were conducted by H.d.M., J.H.A.G. and M.K. in consultation with S.E., S.S. and P.J.W. Statistical analyses for trajectory classification were conducted by J.H.A.G. M.K., J.H.A.G., S.E. and T.I.E.V. wrote the article, with contributions from all co-authors.

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• Published: 31 July 2019

Reassessing the projections of the World Water Development Report

• Alberto Boretti   ORCID: orcid.org/0000-0002-3374-0238 1 , 2 &
• Lorenzo Rosa   ORCID: orcid.org/0000-0002-9210-5680 3 , 4  

npj Clean Water volume  2 , Article number:  15 ( 2019 ) Cite this article

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The 2018 edition of the United Nations World Water Development Report stated that nearly 6 billion peoples will suffer from clean water scarcity by 2050. This is the result of increasing demand for water, reduction of water resources, and increasing pollution of water, driven by dramatic population and economic growth. It is suggested that this number may be an underestimation, and scarcity of clean water by 2050 may be worse as the effects of the three drivers of water scarcity, as well as of unequal growth, accessibility and needs, are underrated. While the report promotes the spontaneous adoption of nature-based-solutions within an unconstrained population and economic expansion, there is an urgent need to regulate demography and economy, while enforcing clear rules to limit pollution, preserve aquifers and save water, equally applying everywhere. The aim of this paper is to highlight the inter-linkage in between population and economic growth and water demand, resources and pollution, that ultimately drive water scarcity, and the relevance of these aspects in local, rather than global, perspective, with a view to stimulating debate.

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Introduction.

The 2018 edition of the United Nations (UN) World Water Development Report (WWDR) 1 has provided an update on the present trends of clean water availability and future expectations. Water security, the capacity of a population to safeguard sustainable access to adequate quantities of water of acceptable quality, is already at risk for many, and the situation will become worse in the next few decades. 2 Clean water scarcity is a major issue in today’s’ world of 7.7 billion people. The strain on the water system will grow by 2050 when the world population will reach between 9.4 and 10.2 billion, a 22 to 34% increase. The strain will be aggravated by unequal population growth in different areas unrelated to local resources. Most of this population growth is expected in developing countries, first in Africa, and then in Asia, where scarcity of clean water is already a major issue.

At present, slightly less than one half of the global population, 3.6 billion people or 47%, live in areas that suffer water scarcity at least 1 month each year. 1 According to, 3 the number is even larger, 4.0 billion people, or 52% of the global population. By 2050, more than half of the global population (57%) will live in areas that suffer water scarcity at least one month each year. 1 This estimate by 1 may be an underestimation. The water demand, water resources, and water quality forecast by 1 depends on many geopolitical factors that are difficult to predict. The decline of water resources and water quality only partially discussed in, 1 may be much harder to control.

The WWDR 1 focuses on the application of nature-based-solutions (NBS), measures inspired by nature such as the adoption of dry toilets, which will have a negligible effect on the huge problem. More concrete regulatory measures are needed to tackle the clean water crisis, directly acting on water use and conservation. There are major obstacles to providing adequate water planning. First is the refusal to admit that unbounded growth is unsustainable. 4 Overpopulation arguments are portrayed as “anti-poor”, “anti-developing country” and “anti-human”. 4 Population size as a fundamental driver of scarcity is dubbed as a “faulty notion”. 5 This denial is partly responsible for lack of good water planning, supported by overconfidence in NBS. The key points of the WWDR 1 are summarized and discussed in the following sections.

Water demand by 2050

Increasing water demand follows population growth, economic development and changing consumption patterns. 1 Global water demand has increased by 600% over the past 100 years. 5 This corresponds to an annual increment rate of 1.8%. According to, 6 the present annual growth rate is less, only 1%, but this figure may be optimistic. Global water demand will grow significantly over the next two decades in all the three components, industry, domestic and agriculture. 1 Industrial and domestic demand will grow faster than agricultural demand but demand for agriculture will remain the largest. 1 The growth in non-agricultural demand will exceed the growth in agricultural demand. 7

Global water demand for all uses, presently about 4,600 km 3 per year, will increase by 20% to 30% by 2050, up to 5,500 to 6,000 km 3 per year. 2 Global water demand for agriculture will increase by 60% by 2025. 8 By 2050 the global population will increase to between 9.4 to 10.2 billion people, an increment of 22% to 32%. 1 Most of the population growth will occur in Africa, +1.3 billion, or +108% of the present value, and Asia, +0.75 billion, or +18% of the present value. 9 Two-thirds of the world population will live in cities. 1 These estimates of future population and water demand are the best we have, though it is realized such forecasts are difficult. 5

Globally, water use for agriculture presently accounts for 70% of the total. Most are used for irrigation. Global estimates and projections are uncertain. 1 The food demand by 2050 will increase by 60%, 1 and this increment will require more arable land and intensification of production. This will translate into increased use of water. 10 Global use of water for industry presently accounts for 20% of the total. Energy production accounts for 75% of the industry total and manufacturing the remaining 25%. 11 Water demand for the industry by 2050 will increase everywhere around the world, with the possible exceptions of North America and Western Europe. 5 Water demand for the industry will increase by 800% in Africa, where present industry use is negligible. Water demand for the industry will increase by 250% in Asia. Global water demand for manufacturing will increase by 400%.

Global water use for energy will increase 20% over the period 2010–2035, 5 and by 2050 will increase by 85%. 12 Domestic global water use currently accounts for 10% of the total. Domestic water demand is expected to increase significantly over the period 2010–2050 in all the world regions except for Western Europe. The greatest increment, 300%, will occur in Africa and Asia. The increase will be 200% in Central and South America. 5 This growth is attributed to the increase in water supply services to urban settlements. 5

Clearly, the demand for water by 2050 will increase dramatically, but unequally, across all the continents. Quantitative estimates are difficult to provide with accuracy. The estimates of the WWDR 1 are not expected to be very accurate, and likely optimistic.

Water resources by 2050

Water demand cannot exceed water availability. While water demand is increasing, water availability is shrinking, because of shrinking resources and, as discussed in the next paragraph, pollution. The available surface water resources are forecast to remain about constant at continental level, 5 although quality will deteriorate, and spatial and temporal distribution will change. More likely, aquifers will shrink, and salt intrusion in coastal areas will be very dramatic. In contrast, the growth of population, gross domestic product (GDP), and water demand will increase globally and unequally. 5 Changes will be much more pronounced at the sub-regional level than at the country level, and the global average. 5

Many countries are already experiencing water scarcity conditions. 13 Many more countries will face a reduced availability of surface water resources by 2050. 13 In the early to mid-2010s, 1.9 billion people, or 27% of the global population, lived in potential severely water-scarce areas. 1 In 2050, this number will increase 42 to 95%, or 2.7 to 3.2 billion peoples. 1 If monthly, rather than annual, variability is considered, 3.6 billion people worldwide, slightly less than 50% of the global population, presently live in potential water-scarce areas at least 1 month per year. This number will increase from 33 to 58% to 4.8 to 5.7 billion by 2050. 13 About 73% of the people affected by water scarcity presently live in Asia. 1

In the 2010s, groundwater use globally amounted to 800 km 3 per year. 5 India, the United States, China, Iran, and Pakistan accounted for 67% of the global extractions. 5 Water withdrawals for irrigation are the primary driver of groundwater depletion worldwide. The increment of groundwater extractions by 2050 will be 1,100 km 3 per year, or 39%. 5 Improving the efficiency of irrigation water use may lead to an overall intensification of water depletion at the basin level. 14 At about 4,600 km 3 per year, current global withdrawals are already near maximum sustainable levels. 15

More than 30% of the world largest groundwater systems are now in distress. 16 The largest groundwater basins are being rapidly depleted. In many places, there is no accurate knowledge about how much water remains in these basins 17 and. 18 People are consuming groundwater quickly without knowing when it will run out, 17 and. 18 According to, 19 the world’s supply of fresh water may be much more limited than what is thought because unlimited groundwater was assumed. Challenges more severe than global are expected at regional and local scales. 16

Coastal zones have special problems. They are more densely populated than the hinterland, and they exhibit higher population growth rates and urbanization. Water withdrawal is already causing significant land subsidence, that combined to thermo-steric sea level rise, translate in relative sea level rise in coastal areas and salinization of aquifers, 20 , 21 , 22 , 23 Water withdrawal-induced subsidence is reported in many coastal areas of the world, from North America, 24 , 25 , 26 to East Asia, 27 , 28 , 29 , 30 , 31 Population growth rates and urbanization in coastal areas are expected to further increase in the future, 32 , 33 Thermo-steric and land subsidence driven relative sea level rise will also reduce arable lands along the coast and within estuaries, 29 , 30 and reshape coastal regions. Especially coastal regions, which are home to a large and growing share of the global population, are undergoing an environmental decline 33 impacting water availability. The neglected dramatic changes of coastal areas, due to relative sea level rise by land subsidence and thermo-steric effects, that directly and indirectly affect water availability, are missing points in the WWDR. 1

Coral islands are a special case, however affecting a small share of the global population, as they depend on a lens of groundwater for their water supply. Overuse of water causes shrinkage of the groundwater lens, which eventually leads to saltwater intrusion. Increasing population also leads to more contamination of the groundwater, so many islands are suffering a reduction in water resources as well as increasing pollution.

Apart from the discovery of new aquifers, desalination is the most effective measure to increase water resources. However, it is expensive, and it requires significant energy inputs. Currently, about 1% of the world’s population living in coastal areas is dependent on desalination. The progress of desalination to 2050 is hard to predict, depending on economic and energetic energy issues.

The simple message is that water resources will decrease dramatically by 2050. Likely, the estimates of the WWDR 1 are not very accurate, and probably optimistic.

Water quality by 2050

The problem of water pollution is a weak part of the WWDR. 1 Pollution is becoming worse, especially in the last few decades, but seems to be inadequately reported. Pollution of water is correlated with population density and economic growth. 34 At present 12% of the world population drinks water from unimproved and unsafe sources. 34 More than 30% of the world population, or 2.4 billion people, lives without any form of sanitation. 34 Lack of sanitation contributes to water pollution. 90% of sewage in developing countries is discharged into the water untreated. 35 Every year 730 million tons of sewage and other effluents are discharged into the water. 36 Industry discharges 300 to 400 megatons of waste into the water every year.

Non-point source pollution from agriculture and urban areas and industry point source pollution contribute to the pollutant load. More than 30% of the global biodiversity has been lost because of the degradation of fresh-water ecosystems due to the pollution of water resources and aquatic ecosystems. 37 Wastewater recycling in agriculture, that is important for livelihoods also brings serious health risks. 1 Over the last 3 decades, water pollution has worsened, affecting almost every river in Africa, Asia and Latin America. 38

Water pollution will intensify over the next few decades 39 and become a serious threat to sustainable development. 39 At present 80% of industrial and municipal wastewaters are released untreated. 40 Effluents from wastewater are projected to increase because of rapid urbanization and the high cost of wastewater treatment. 41 Nutrient loading is the most dangerous water quality threat, often associated with pathogen loading. 38 Agriculture is the predominant source of nitrogen and a significant source of phosphorus. 38 Current levels of nitrogen and phosphorus pollution from agriculture may already exceed the globally sustainable limits. 42 Global fertilizer use is projected to increase from around 90 million tons in 2000 43 to more than 150 million tons by 2050. 44 Intensified biofuel production will lead to high nitrogen fertilizer consumption. 43 Nitrogen and phosphorus effluents by 2050 will increase by 180 % and 150 % respectively. 45 Other chemicals also impact on water quality. Global chemicals used for agriculture currently amount to 2 million tons per year, with herbicides 47.5%, insecticides 29.5%, fungicides 17.5% and other chemicals 5.5%. 46

The list of contaminants of concern is increasing, 47 as a novel or varied contaminants are used, often suddenly detected at concentrations much higher than expected. 47 Novel contaminants include pharmaceuticals, hormones, industrial chemicals, personal care products, flame retardants, detergents, perfluorinated compounds, caffeine, fragrances, cyanotoxins, nanomaterials and cleaning agents. 47 Exposure to pollutants will increase dramatically in low-income and lower-middle income countries. 38 Pollution will be driven by higher population and economic growth in these countries, 38 and the lack of wastewater treatment. 40 Pollution will be particularly strong in Africa. 38

In brief, the demand for water will increase by 2050 but the availability of water will be reduced. Water resources will reduce. Pollution will further reduce the amount of clean fresh water. This aspect is marginally factored in the WWDR. 1

Other ecological changes by 2050

Changes in the ecosystems will be affected by changes in the water demand and availability and vice versa. Conservation or restoration of the ecosystems will impact on water availability for human consumption, both resources, and quality. 1 About 30% of the global land area is forested, and 65% of this area is already in a degraded state. 48 Grasslands and areas with trees, but dominated by grass, presently exceed the area of forests. Large areas of forests and wetlands have been converted into grasslands, for livestock grazing or production of crops. Wetlands only cover 2.6% of the land but play a significant role in hydrology. 49

The loss of natural wetland area has been 87% since 1700. The rate of wetland loss has been 370% faster during the 20 th and early 21st centuries. 49 Since 1900 there has been a loss of 64% to 71% of wetlands. 49 Losses have been larger, and are now faster, for inland, rather than coastal, wetlands. 49 The rate of loss is presently highest in Asia. The effects of sea level rise are underrated in. 49

Soils are also changing. Most of the world’s soils are in only fair, poor or very poor condition, 50 and the situation is expected to worsen in the future. 50 The major global issues are soil erosion, loss of soil organic carbon and nutrient imbalance. Presently, soil erosion from croplands carries away 25 to 40 billion tons of soil every year. Crop yields and soil’s ability to regulate water, carbon, and nutrients are reduced. 23 to 42 million tons of nitrogen and 15 to 26 million tons of phosphorus are presently transported off the land. Soil erosion and nutrient run-off have negative effects on water quality. 50 Sodicity and salinity of the soils are global issues in both irrigated and non-irrigated areas. Sodicity and salinity take out 0.3 to 1.5 million ha of farmland each year. 50 The production potential is also reduced by 20 to 46 million ha. 50

Ecosystems, biodiversity, and soil degradation are expected to continue to 2050, at an ever-faster rate. This will have an impact on the availability and quality of water, which is only partially considered in the WWDR. 1

The data presented in, 1 provide an optimistic, but still dramatic, estimation of water scarcity by 2050. Their gentle, nature-based-solutions (NBS) are quite inadequate to tackle this serious problem. Limitation of population and economic growth cannot be enforced easily. Ad hoc responses seem to be necessary but hard to be implemented.

Figure 1 presents in (a) the global water withdrawal, the GPD pro-capita and the world population since the year 1900, and in (b) the population of the world and of selected countries of Asia and Africa since the year 1950. The figure also presents in (c) the graphical concept of water scarcity, resulting from a more than linear growing demand, and a similarly more than linear reducing availability of clean water. It is intuitive that growing demand and shrinking availability will ultimately cross each other, locally earlier than globally.

a Water withdrawal, GDP pro-capita, and world population. The water withdrawal data to 2014 is from. 71 The GPD pro-capita data to 2016 is from. 73 The population data to 2018 is from. 72 b The population of the world and selected countries of Asia and Africa. The data to 2018 is from ref. 72 The values for 2050 are obtained by linear extrapolations from recent years. c Graphical concept of water scarcity, resulting from a more than linear growing demand and a similarly more than a linear reduction of clean water availability

Demand for water, same of food or energy, increases with the growth of population and gross domestic product (GDP) pro-capita. 51 In addition to the growth of population, also the generation of wealth worldwide translates in increased consumption, resulting in increased water demand. The expected changes in wealth are coupled to alterations in the consumption patterns, including changes to diet. As agriculture worldwide accounts for up to 70% of the total consumption of water, 52 , 53 , 54 , 55 with much higher levels in arid and semi-arid regions, food and water demands are on a collision path. One example of conflicting demands for water, food, and energy, within a context of regional population and economic growth, is the Mekong Delta. The morphology of the Mekong Delta as we know today developed in between 5.5 and 3.5 ka (thousand years before present). The relatively stable configuration experienced during the last 3.5 ka has been dramatically undermined during the last few decades. The delta itself may completely disappear in less than one century.

The increased demand for food, water, and energy of a growing population and a growing economy has translated in the extraction of larger quantities of groundwater in the delta, the construction of hydroelectric dams along the course of the river, the diverted water flow for increased upstream water uses, and the riverbed mining for sand. The reduced flow of water and sediments to the delta, 56 , 57 , 58 , 59 , 60 coupled to the subsidence from excessive groundwater withdrawal and soil compaction, 58 , 61 , 62 , 63 , 64 , 65 and the thermo-steric sea level rise, 66 , 68 , 74 have translated in the sinking and shrinking of the delta. In the short term, this has translated in salinization of coastal aquifers, depletion of aquifers, and arsenic pollution of deep groundwater, additional to salinization of soil, flooding, destruction of rice harvesting and depletion of wild fish stocks, impacting on water and food availability, 67 , 68 In the longer term, the delta itself may completely disappear as the result of not sustainable growth. 69 , 70

As previously mentioned, apart from the discovery of new aquifers, increased use of desalination and water purification may lessen the reduction of available water. However, desalination needs significant economic and energetic energy input, difficult to predict. The water withdrawal data is obtained from. 71 The population data is obtained from. 72 The GPD pro-capita data is obtained from. 73 The values by 2050 are obtained by linear extrapolations. The global water withdrawal is correlated to the world population, but it has been growing faster than the world population. The GPD pro-capita has been growing even faster than the world population. While we do not have any reliable data on water quality and resources vs. time, over the same time window, we expect that the water quality and resources have also been deteriorating more than proportionally to the economic and population growth.

Use of fertilizers has grown even faster than the global water withdrawal. 74 Production and consumption of nitrogen, phosphate and potash fertilizers since 1961 has similar growing patterns. 75 Global pesticide production is also growing continuously. 76 The key driver for pollution is the growth of the population and the economy. 41 The groundwater basins are being quickly exhausted by excessive withdrawals. Additionally, because of the relative sea level rise, thermo-steric and groundwater withdrawal generated subsidence, aquifers in coastal lands and estuaries are being rapidly compromised, while fertile lands are turned unproductive, 29 , 30 Similarly, to water demand, also water resources and water quality are thus linked to economic and demographic growths. Opposite to the population and GDP data, the data of fresh water usage, fresh-water resources, and pollution of fresh water, are more difficult to be sorted out with the accuracy needed, making every forecast to 2050 problematic.

Regarding the economy, it must be added that the IMF’s Global Debt Database 77 indicates that the debt has reached globally in 2017 an all-time high of $184 trillion, or 225% of the GDP. The world’s debt now exceeds $86,000 per capita, which is more than 250% of the average income per capita. The most indebted economies in the world are the richer ones, with the United States, China, and Japan accounting for more than half of the global debt, and the poorer countries on their way to becoming indebted.

The three key aspects of water scarcity, water demand, water resources, water pollution, are strongly related to population growth and economic growth. They are strongly interconnected, and dramatically variable in space and time, with local conditions that will be much worse than the global conditions. Many countries are experiencing population growth largely exceeding the already alarming global average. Linear extrapolations to 2050 are in some cases in excess, and in some cases in defect, of the values forecast in, 72 demonstrating complex dynamics. For example, the population forecast to 2050 for Uganda is 105,698,201, or +2,110% vs. the values of 1950. The linear extrapolation to 2050 is 89,313,923, or +1,783% vs. the values of 1950. Opposite, the population forecast to 2050 for the world is, optimistically, 9,771,822,753, or +385% vs. the values of 1950. The linear extrapolation to 2050 is 10,274,650,493, or +405% vs. the values of 1950. Global growths of 385 to 405% over 100 years are everything but sustainable. Even less sustainable are local growths that at the country level are exceeding 2,000% over 100 years. It is impossible to provide clean fresh water to support such growth rates.

As clean water demand is increasing, and clean water availability is reducing, with local situations much worse than global, clean water demand will eventually exceed the availability of clean water at some local levels much earlier than at the global level. These break-points may occur earlier than 2050 in many areas of the world. Considering when a vital resource is in short supply, people will fight for it, provision of water to 2050 will be very likely played against a social background of competition and probably conflict if nothing will be done to prevent a water crisis.

Conclusions

The paper has discussed the correlation between the exponential growth in global population and GDP and water scarcity, that is the result of the competing water demand, water resources, and water pollution. Population and economic growth to 2050 will be very likely strong, and unequal across the globe, with the largest growth rates expected in third world countries. Water demand to 2050 will grow even more than the population and the economy, same of the reduction of water quality and resources. Local patterns will be more critical than global patterns, making the problem more difficult to be solved.

Water is ultimately a finite resource and the marginal solutions for water scarcity currently being proposed in the United Nations (UN) World Water Development Report (WWDR) will prove hopelessly inadequate by 2050 in the absence of any serious effort to tackle these underlying truths. Improvements in the science and technology of water treatment, water management and clean water supply, and in the awareness of water conservation and savings, while developing nature-based-solutions (NBS), may certainly alleviate future clean water scarcity. However, a better policy is much more urgent than scientific, technological and philosophical advances, as this will not be enough. There is a clear regulatory promulgation and enforcement issue especially in the developing countries that needs to be addressed the sooner the better. We need the political will to enforce global regulations, especially where economies and population are building up, as unregulated development is not sustainable anymore.

There is no specific remedial measure to propose, if not to support more sustainable population and economic growths, with local rather than global focus, keeping in mind that growth cannot be infinite in a finite world. As the Economist Kenneth Boulding declared to the United States Congress 78 “Anyone who believes exponential growth can go on forever in a finite world is either a madman or an economist”. However, as noted in, 79 the pursuit of economic growth has been the prevalent policy goal across the world for the past 70 years. The aim of this paper is simply to highlight the connection between population and economic growth and water demand, resources and pollution, that ultimately drive water scarcity, and the relevance of these aspects in local, more than global perspective, to stimulate an urgent and comprehensive debate.

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Acknowledgements

We thank Cliff Ollier and Pamela Matlack-Klein for the comments and suggestions provided.

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Alberto Boretti

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Lorenzo Rosa

Swinburne University of Technology, Centre for Microphotonics, Hawthorn, VIC, Australia

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Boretti, A., Rosa, L. Reassessing the projections of the World Water Development Report. npj Clean Water 2 , 15 (2019). https://doi.org/10.1038/s41545-019-0039-9

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Smart Water Metering: lessons learned to help us tackle water scarcity

5 min read 24 September 2024 By Will Lewis, Expert in Smart Water Metering, and Jo Waterhouse, Expert in Water

Without action we will be short of 5,000 million litres of water per day in England and Wales by 2050 , around 25% of current levels of supply . Data from Smart Water Meters is critical to help ing tackle this, for example enabling the identification of leaks and losses at a property or help ing cons u m ers and prosumers to understand how to save water ( and reduce bills ) .

But this means installing meters at the majority of homes and businesses in the country and then using the data effectively to engage customers – the scale and complexity of this challenge requires a more joined-up approach and level of collaboration than we have today.  

This is the conclusion of a Baringa report, commissioned by Ofwat, and published today.  

"We are grateful that Ofwat commissioned Baringa to undertake this important research on Smart Water Metering. Smart has a key role in helping tackle the looming water scarcity challenge in England and Wales. We hope the study enables the UK Water Sector to make informed choices on the strategic direction of Smart Water Metering."

Will Lewis, Expert in Smart Water Metering, Baringa

Summary findings

Baringa found that Smart Water Metering requires:  

• A greater level of central coordination and governance.  
• A set of common standards and metrics that help drive the target outcomes.  
• Collective investment in marketing, data sharing and solutions to common challenges.  
• A review of barriers to progress such as policy, funding or supply chain constraints.  

In addition, there are strategic and operational points for individual water companies to consider that will help them set up and deliver their programmes successfully, such as:  

• Innovative commercial models that focus on getting reliable, timely, accurate data.  
• Aligned incentives to ensure technology, comms and install providers work together.  
• Deployment capabilities that are continuously improved to reduce install failure rates.  
• New capabilities and operating models that harness the power of smart data to drive benefits.  

This study aims to be a foundational resource for the UK Water Sector, on which it can make informed choices on the strategic direction and operational roll out of Smart Water Metering.  

About the research 

Baringa’s Water and Smart Metering subject matter experts, undertook proprietary research and analysis including in-depth interviews with more than 70 stakeholders from 50 organisations and a review of more than 40 published studies and white papers. 

It lays out a set of findings and recommendations for governing bodies and the wider industry to consider in delivering Smart Water Metering, which is critical for us to tackle a looming water scarcity challenge.  

View the full report here

"It is Ofwat’s ambition to prioritise water efficiency on par with energy efficiency and other sustainability challenges, promote its efficient use, gather greater understanding, and remove barriers to help water companies deliver on their responsibilities"

Learning from experience: What the roll out of smart metering in energy can teach us about smart metering in water

Our Experts

Expert in Smart Water Metering

Jo Waterhouse

Expert in water

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