‘Water poverty’ is a hidden crisis in selected Palika's of Nepal, arising from factors such as population growth, climate change, land use alterations, and erratic infrastructure development, significantly impacting water resource quantity and quality. Addressing this requires location-specific indicators like the Water Poverty Index (WPI) for effective water resource planning. This study investigates water poverty causes in the area, analyzing five WPI components: Access, Resource, Usage, Capacity, and Environment. Introducing 10 WPI indicators and 13 context-specific variables tailored to Nepal, the research assesses water poverty across different spatial scales (metropolitan, sub-metropolitan, municipality, and rural municipality). The results show WPI scores ranging from 62.96 to 72.77, highlighting the need for targeted policy interventions. While no clear trend emerges across scales, higher resource and access scores prevail in all areas, with use, environment, and capacity scores higher in metropolitan and sub-metropolitan regions. These disparities underscore the need for tailored policies and management plans across scales to improve water poverty in the studied regions.

  • This is a comparative study of different geographical locations.

  • This study was performed at different Palikas of the country.

  • The current scenario is to analyze the impact in the study area.

  • More effective policies and interventions to address water-related challenges in the local units of the study area are needed.

Water is undeniably a fundamental resource for humanity, playing an irreplaceable role in our well-being and development throughout history (Sullivan et al. 2003). It has been a driving force behind the rise of civilizations, the growth of economies, and the improvement of living standards (Miller 1999). Yet, in recent years, we have faced unprecedented challenges related to water scarcity, driven by a confluence of factors that demand our immediate attention (Lee et al. 2020). Safe potable water, efficient sanitation, and optimal hygiene practices as both intrinsic objectives and driving forces of development exert a direct influence on various other Sustainable Development Goals (SDGs) (Breuer et al. 2019). The management of water resources is becoming challenging due to the declining trends in water availability and rising demand (Baral et al. 2023). This scenario is due to environmental changes, population growth, straining existing resources and infrastructure, and socioeconomic development, leading to higher scarcity worldwide (Riswan et al. 2019). The combined impacts of climate change and swift urban transformations are poised to worsen the issue of water scarcity on a global, regional, national, and local level (Merz & Blöschl 2003). It is projected that nearly 6 billion people will face a deficit of access to clean water in 2050, and its availabilities are becoming dwindled especially in developing countries (Lacombe et al. 2019). The water resources in Nepal are under significant pressure due to a mix of factors such as fast-paced population increase, unplanned urban development, evolving lifestyles, and a heavy reliance on agriculture for livelihoods (Yadav 2023). Developing innovative management strategies that blend traditional practices with scientific research is crucial to meet water needs and protect water quality in Nepal's rural watersheds (Pandey 2021). Nepal benefits from a plethora of rivers and streams originating from the Northern Himalayas, establishing it as one of the world's most water-abundant nations. However, the challenge of guaranteeing urban water security, encompassing essential needs like drinking water, irrigation, and industrial purposes, has become an increasingly pressing concern. This issue extends beyond Nepal and impacts various South Asian countries (Lacombe et al. 2019). Challenges related to water frequently exhibit location-specific characteristics, being shaped by human actions and their intricate interactions with various elements, including environmental, social, technological, and so on (Akhtar et al. 2021). ‘Dealing with the multifaceted aspects of water-related challenges is a daunting yet essential task, and indices encompassing social, environmental, economic, and managerial factors prove to be the most suitable means for assessing water poverty’ (Molle & Mollinga 2003). These indices offer a structured framework for addressing water-related challenges across various levels of governance, spanning from municipal to federal scales (ADPC 2021). Falkenmark index (Ruess 2015), Water Resource Vulnerability Index (Kanakoudis et al. 2016), and Water Availability Index (Xu & Wu 2017) are tools that are currently being employed to evaluate water stress by utilizing one-dimensional indicators. Likewise, the Water Poverty Index (WPI) is a holistic method designed to evaluate water scarcity, mainly at the community level and on a site-specific basis, considering various dimensions by Sullivan (2001).

This research intends to provide an insight into how the WPI can be utilized to evaluate the condition of the water crisis at the subnational level, with a specific emphasis on the four Palikas in eastern Nepal. We employ the WPI to examine and graphically depict the situation of water supply in eastern Nepal. This research incorporates five elements: water Resource (R), Use (U), Access (A), Capacity (C), and Environmental quality (E) as defined by the WPI (Koirala et al. 2020). Indicators for each component were selected based on relevance to the local context, data availability, and review of relevant literature. Our study provides essential background information for future scientific research, allowing for temporal comparisons. It is also a valuable resource for policymakers, investors, development workers, and donors, helping them understand regional water poverty in selected Palikas. This information can guide policies to promote sustainable livelihoods through enhanced adaptation and water management practices. In addition, the study's findings will assist development planners in identifying significant constraints affecting livelihoods at a spatial scale.

Water poverty assessment in Nepal

In extensive research carried out by Lawrence & Meigh (2003), Nepal is identified as a country undergoing moderate water stress, as demonstrated by a WPI score of 54.4. There has been a scarce quantitative evaluation of water poverty at the subnational level in Nepal, with only a handful of researchers utilizing the WPI as an instrument for assessing water poverty. These studies have consistently shown an increase in the WPI, attributed to elements like inadequate water supply, escalating agricultural and domestic needs, and declining water quality (Panthi et al. 2019); sluggish economic growth and rising population (Dahal et al. 2016); and limited human and institutional capacity to efficiently and effectively manage available water resources (Panthi et al. 2015). Similarly, some large watersheds have also been studied: the Indrawati Basin (WWF Nepal 2012), the Upper Bagmati River Basin (Thakur et al. 2017), and the Gandaki River Basin (Pandey et al. 2012). Still, there have been only a limited number of studies conducted at the local level. Accordingly, there is a substantial demand for small-scale, watershed-specific research, especially in the eastern region of Nepal. This research work is focused on the computation of the WPI within specific Palikas located in eastern Nepal. Its main objective is to conduct a thorough analysis of water conditions and evaluate the presence of WPI in Birgunj Metropolitan (Parsa District), Manara Siswa Municipality (Mahottari District), Budhiganga Rural Municipality (Morang District), and Dharan Sub-metropolitan (Sunsari District).

Study area

The selected Palikas are situated in the eastern region of Nepal, with Kathmandu as a reference point. These Palikas are located in the Inner Terai region of Nepal, each within a distinct basin and district. For instance, Birgunj Metropolitan is in Parsa District within the Narayani River Basin, Manra Siswa Municipality is in Mahottari District within the Kamala River Basin, Budhiganga Rural Municipality is in Morang District, and Dharan Sub-metropolitan is in Sunsari District, both within the Koshi Basin. Birgunj Metropolitan is the headquarters of the Parsa District and is situated in the southern part of Nepal, near the India–Nepal border (Parsa National Park and its Buffer Zone, Management Plan, online). This metropolitan area holds substantial economic and strategic significance, primarily serving as a pivotal trade and transit point connecting Nepal and India. Birgunj Metropolitan spans a geographical range between approximately 27°02′30″ to 27°06′30″N latitude and 84°37′48″ to 84°51′32″E longitude. There are 32 wards to cover an area of 132.07 km2, with elevations ranging from 80 to 100 m above sea level (m.a.s.l.). Manara Siswa Municipality lies 12 km southwest of the headquarters, Jaleshwor, of the Mahottari district (Jha & Jha 2019). This municipality was established through the unification of seven Village Development Committees named Siswa Kataiya, Bathnaha, Sadha, Sarpallo, Manara, Itaharwa Katti, and Sunail. The municipality's geographical extent is from 26°57′13″ to 27°03′23″N latitude and 85°48′8″ to 86°00′32″E longitude. It is divided into 10 wards to cover an area of 49.78 km2, with an elevation range of 70–100 m.a.s.l. Similarly, Budhiganga Rural Municipality is located in Morang District in Koshi Pradesh with the geographical extent of from 26°51′13″ to 26°57′24″N latitude and 85°54′08″ to 86°03′12″E longitude. This Palika was formed by merging the former Village Development Committees of Tankisinuwari, Hathimudha, Sisabanibadahara, and Dangraha. Budhiganga Rural Municipality is located in the northern part of Morang District, sharing borders with Jhapa District to the north, Sunsari District to the east, and Biratnagar Metropolitan City to the south and west (Poudyal 2019).

It encompasses a total area of 56.41 km2, divided into seven wards. Dharan Sub-metropolitan is widely recognized for its captivating allure in the eastern region of Nepal within the academic community. This sub-metropolitan city sprawls across a vast expanse of 192.32 km2 and is geographically situated between approximately 26°42′41″ to 26°52′42″N latitude and 87°12′04″ to 87°21′23″E longitude (Yadav 2023). This municipality has 20 wards as shown in Figure 1. Three of these regions, located in Inner Terai, rely on hand pumps for most of their water demand (groundwater), while the Dharan Sub-municipality depends entirely on surface water sourced from the Dharan Water Supply Management Board and various other Water User Associations. However, these selected Palikas are grappling with an escalating array of water-related challenges arising from climatic fluctuations, population growth, and agricultural demands. These factors are likely to exacerbate stress on existing water resources, as well as impact the environment and society. Consequently, there is a pressing need to assess the water resources situation comprehensively, serving as the foundation for crafting effective policy interventions in the region within an academic context.
Figure 1

The study area (selected Palikas of eastern Nepal).

Figure 1

The study area (selected Palikas of eastern Nepal).

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This study's methodology is based on a WPI framework developed by Sullivan and others in 2002, 2003, and 2006 (Garriga & Foguet 2010). It incorporates five key components that link physical water availability with socioeconomic and environmental factors: Resource (R), Access (A), Use (U), Capacity (C), and Environment (E) as shown in Figure 2. As shown in Figure 2, we have identified 13 subcomponents, considering factors such as data availability and expert insights. Considering the disparities in water poverty concerns and indicators across various regions, it is crucial to conduct a thorough examination and careful selection of each indicator during the computation of the WPI. The WPI amalgamates data pertaining to physical, social, economic, and environmental factors associated with water scarcity, water accessibility, and the ability to use water beneficially. The relationship between the subcomponents and the overall WPI can display either a direct or an inverse proportionality.
Figure 2

The framework developed by Sullivan.

Figure 2

The framework developed by Sullivan.

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Data collection

Four Palikas are selected for this study from four different districts as depicted in Figure 1. The selection of Palikas was based on a multi-criteria approach, including factors such as elevation, river network, temperature, precipitation, socio-ethnic settlement, and accessibility. The specific Palika within the sub-watershed were selected through stakeholder consultation and the current scenario. Primary data collection is done via key informant questionnaire surveys, including district water supply and sewerage officers, disaster management coordination committee members, and irrigation officers, and focus group discussion (FGD). Secondary data were gathered from various sources, including government records, UN official reports, and gray literature. This study incorporated the climate component into the environmental component of the existing WPI indicators since climatic indicators are part of the broader environmental context. Temperature and rainfall data were collected from weather stations near each district but within the vicinity of the case study watershed. These data were obtained from the Department of Hydrology and Meteorology (DHM) covering the period from 1998 to 2022 for each respective station. The WPI components, subcomponents, and their associations are detailed in Table 1, along with their respective data sources in Table 2.

Table 1

Major components, subcomponents, and sources, and their relationship with WPI

Major componentsSubcomponentsSourceRelationship with WPI
Resource (R) Runoff potential DHM Inverse 
Rain potential 
Rainfall variability Data analysis Direct 
Access (A) Time to reach the water source Survey Direct 
Irrigation sufficiency Inverse 
Percentage coverage of pipe water supply DWSS Inverse 
Capacity (C) Economically active population CBS Inverse 
Literacy rate 
Use (U) Percentage HH owning only agricultural land 
Water consumption (per person per day) Survey Direct 
Percentage HH with agricultural land and livestock 
Environment (E) Area with natural vegetation ICIMOD Inverse 
Quality index of water sources Data analysis 
Major componentsSubcomponentsSourceRelationship with WPI
Resource (R) Runoff potential DHM Inverse 
Rain potential 
Rainfall variability Data analysis Direct 
Access (A) Time to reach the water source Survey Direct 
Irrigation sufficiency Inverse 
Percentage coverage of pipe water supply DWSS Inverse 
Capacity (C) Economically active population CBS Inverse 
Literacy rate 
Use (U) Percentage HH owning only agricultural land 
Water consumption (per person per day) Survey Direct 
Percentage HH with agricultural land and livestock 
Environment (E) Area with natural vegetation ICIMOD Inverse 
Quality index of water sources Data analysis 

Note: DHM, Department of Hydrology and Meteorology; HH, Households; DWSS, Department of Water Supply and Sewerage; CBS, Central Bureau of Statistics; ICIMOD, International Centre for Integrated Mountain Development.

Table 2

Water poverty intensity scale (WWF Nepal 2012)

WPI scaleWater poverty intensity
75–85 Very low 
65–75 Low 
55–65 Medium-low 
45–55 Medium 
35–45 Medium-high 
25–35 High 
15–25 Very high 
WPI scaleWater poverty intensity
75–85 Very low 
65–75 Low 
55–65 Medium-low 
45–55 Medium 
35–45 Medium-high 
25–35 High 
15–25 Very high 

WPI structure and its components calculation

The WPI was calculated at the Palika level by considering the values of five components, as determined by the following equation:
formula
(1)
where R refers to Resource, A refers to Access, U refers to Use, C refers to Capacity, E refers to Environment, and Wi denote the weight assigned to each of the five components. These components are standardized to yield a WPI value between 0 and 100, where 100 signifies the best situation and 0 is the worst. The water poverty intensity scale tool is utilized to gauge the severity of water poverty within a specific region. Its purpose is to measure the degree to which water-related challenges impact the local population. This scale is commonly employed to determine the requisite level of intervention or policy measures necessary to effectively alleviate water poverty. The water poverty intensity scale is shown in Table 2.

WPI components

This section will provide a detailed explanation of the methodology used to compute the values of individual components, establish benchmark levels for each component, and determine the final score for the WPI. The selection of indicators and benchmark levels is based on the data available within the study area. The procedure involves calculating sub-indices, which are then used in the final WPI calculation using Equation (1). The weights in the equation can be estimated based on the local conditions prevailing in the chosen Palikas as in Table 3.

Table 3

How the five components are calculated (Tiwari et al. 2023)

ComponentMain formulaSupportive formulaeConditionDescriptions
Resources (R)    Ir: Rain index 
P: Precipitation 
  P1: Precipitation percent lower than the amount of water the crop needs in a year 
  R1: Runoff index 
 Q: Runoff 
B: Perennial river benefit factor 
  B = 1, all settlements benefits 
Access (A)   Id: Water carrying time index 
Ii: Irrigation Access Index 
T: Time to collect water (min) 
Tmax: Maximum time to carry water (min) 
 At VDC scale ω1: Number of households reliant on distant water supply 
ω2: Number of households reliant on piped water 
Id1Id for distant water supply 
Id2Id for piped water 
 Ti: Total area accessible to irrigation (km2
Ta: Cultivable land (km2
Capacity (C)   Ic: Education capacity index 
Iic: Income capacity index 
L: Literacy rate (%) 
 Te: Households involved in economic activity 
Th: All households 
Use (U)   S: Total water demand (lpcd) 
Smin: Minimum water requirement (lpcd) 
Sr: Optimum water requirement (lpcd) 
Tw: Total water demand (L/day) 
Tw: Total population 
Environment (E)   Iw calculated using Table 4  Iw: WQI 
Iv: Vegetation coverage index 
V: Vegetative cover area (km2
A: Total area (km2
ComponentMain formulaSupportive formulaeConditionDescriptions
Resources (R)    Ir: Rain index 
P: Precipitation 
  P1: Precipitation percent lower than the amount of water the crop needs in a year 
  R1: Runoff index 
 Q: Runoff 
B: Perennial river benefit factor 
  B = 1, all settlements benefits 
Access (A)   Id: Water carrying time index 
Ii: Irrigation Access Index 
T: Time to collect water (min) 
Tmax: Maximum time to carry water (min) 
 At VDC scale ω1: Number of households reliant on distant water supply 
ω2: Number of households reliant on piped water 
Id1Id for distant water supply 
Id2Id for piped water 
 Ti: Total area accessible to irrigation (km2
Ta: Cultivable land (km2
Capacity (C)   Ic: Education capacity index 
Iic: Income capacity index 
L: Literacy rate (%) 
 Te: Households involved in economic activity 
Th: All households 
Use (U)   S: Total water demand (lpcd) 
Smin: Minimum water requirement (lpcd) 
Sr: Optimum water requirement (lpcd) 
Tw: Total water demand (L/day) 
Tw: Total population 
Environment (E)   Iw calculated using Table 4  Iw: WQI 
Iv: Vegetation coverage index 
V: Vegetative cover area (km2
A: Total area (km2

Abbreviations: lpcd, liter per capita day; VDC, Village Development Committee.

Resources

Water scarcity and water reliability are crucial considerations in evaluating resource availability, as exemplified by the equation stated in Table 3 (WWF Nepal 2012). The rain and runoff indices are utilized as indicators to assess water availability and scarcity in the study area. In cases of excessive rainfall, a rating of 1 is assigned. Conversely, in instances of rainfall insufficiency, a rain sub-index is calculated. The adjusted rainfall factor takes into account variations in climatic conditions. The runoff index measures the current runoff in relation to the required levels, with a maximum threshold of 1. A surface water rating of 1 indicates a sufficient water supply. Settlements located near rivers that are fed by melting snow benefit from a ‘perennial river benefit factor’ (B). The corrected runoff index is determined by multiplying the perennial runoff index by B.

Access

Access to water resources is a fundamental aspect evaluated by the WPI. This assessment encompasses both the quantity and quality of water available in a specific geographical region. Several factors are taken into consideration, including the proximity to water sources, the reliability of water supply, and the affordability of water services (Sullivan et al. 2003). In this study, water availability is evaluated using the household water carrying time index and the irrigation access index. The water carrying time index calculates the time needed for water collection and storage, with adjustments made according to an inverse scoring method outlined in Table 3. Any negative values are set to zero. Field research shows that carrying water takes up to 480 min, while households with direct pipe supply have zero carrying time. The irrigation access index is the ratio of total area with access to irrigation facility to total arable land.

Capacity

‘Capacity’ refers to the ability of the study area to effectively manage and utilize water resources. This encompasses infrastructure, governance, technical expertise, and financial resources, all of which are vital for supporting water projects and facilitating efficient water management. Evaluating capacity involves using the education capacity index and the income capacity index (Koirala et al. 2020). The education capacity index is determined based on the literacy rate. Similarly, the income capacity of households engaged in economic activities within the study area is defined as activities that result in indirect financial gain, such as running businesses, working for wages, receiving remittances, serving in government positions, and more.

Use

The term ‘Use’ is used in this study to refer to the distribution of water for domestic purposes. This includes an assortment of everyday activities. The equation provided in Table 3 can be used to calculate the amount of water required per person per day within a household. To determine the total water demand per capita for ‘Use’, the relationship between total water demand per day and the total population, as stated in Table 3, is utilized. The minimum domestic water demand is set at 1 L per capita per day (WHO & UNICEF 2000), while the maximum water demand is set at 100 L per capita per day (Howard et al. 2003).

Environment

The environmental factor evaluates the benefits and services of aquatic habitats and their environmental integrity. The weight of the environmental components is determined using the relationship between the water quality index (WQI) and natural vegetation coverage index, as shown in Table 3. The National Sanitation Foundation (NSF) established the procedures for calculating the WQI in 1970 (Brown et al. 1970). According to the NSF, a linear weighted sum of the sub-indices was used to determine the WQI, as illustrated in Table 4. Similarly, the vegetation index is determined by considering the relationship between the total area and the area covered in vegetation, as mentioned in Table 3.

Table 4

Significance weights for the WQI calculation (Tiwari et al. 2023)

ParametersUnitImportance weight (Wi)
Dissolve oxygen (DO) % saturation 0.17 
Fecal coliforms (FC) Count in 100 mL 0.15 
pH no unit 0.12 
Biochemical oxygen demand (BOD5mg/L 0.1 
Nitrate (NO3mg/L 0.1 
Phosphate (PO4mg/L 0.1 
Temperature variation °C 0.1 
Turbidity NTU 0.08 
Total dissolved solids (TDS) mg/L 0.08 
ParametersUnitImportance weight (Wi)
Dissolve oxygen (DO) % saturation 0.17 
Fecal coliforms (FC) Count in 100 mL 0.15 
pH no unit 0.12 
Biochemical oxygen demand (BOD5mg/L 0.1 
Nitrate (NO3mg/L 0.1 
Phosphate (PO4mg/L 0.1 
Temperature variation °C 0.1 
Turbidity NTU 0.08 
Total dissolved solids (TDS) mg/L 0.08 

Sensitivity analysis

The WPI serves as a holistic metric encompassing numerous dimensions pertaining to water resources, including their availability, accessibility, governance, and ecological considerations (Zare-Bidaki et al. 2023). This index is pivotal in assessing the multifaceted nature of water-related challenges and formulating effective strategies to address them. To delve into this complex landscape, researchers have employed advanced statistical techniques such as principal component analysis (PCA) and geographically weighted PCA (GWPCA). PCA enables the extraction of underlying patterns from a set of correlated variables by transforming them into a smaller set of uncorrelated variables known as principal components. GWPCA extends this approach by considering spatial variations in data, making it especially relevant for analyzing local nuances in water poverty dynamics. In this study, PCA was initially employed to generate diverse weighting schemes, providing insights into the relative importance of different factors contributing to water poverty (Ghimire & Johnston 2017). By employing mean-variance scaled PCA, researchers were able to identify key drivers of water poverty while considering both the mean and variance of the data distribution, thus enhancing the robustness of the analysis. Furthermore, the application of GWPCA became imperative when local distinctions played a significant role in shaping water poverty conditions. By incorporating geographical weighting into the analysis, GWPCA accounted for spatial heterogeneity, enabling a more nuanced understanding of water poverty at the local level.

Results

The WPI has been computed for selected Palikas originating from diverse districts and is found to be better than the national level (WPI = 54.4) given by Lawrence & Meigh (2003). These selected Palikas comprise one metropolitan, one sub-metropolitan, another municipality, and a fourth rural municipality. The results of the WPI values of those Palikas are graphically represented in Figures 35. Conspicuously, the WPI calculations assigned equal weights to each of its components, as there was no compelling rationale to assign preferential weight to any one component over the others. The examination of data from meteorological stations reveals that the average rainfall index values are 0.68, 0.71, 0.71, and 0.77 for Birgunj Metropolitan, Dharan Sub-metropolitan, Manara Siswa Municipality, and Budhiganga Rural Municipality, respectively. Concurrently, the runoff index is noted to be 0.24, 0.23, 0.27, and 0.26, respectively. Similarly, the ward profiles of the chosen Palikas offer a glimpse into the literacy rates, expressed in percentages, which are 76.04, 87.42, 58.85, and 75.93 for Birgunj Metropolitan, Dharan Sub-metropolitan, Manara Municipality, and Budhiganga Rural Municipality, respectively. Further analysis to extract the components of the water index determined that the resource component ranges from 12 to 18 with an average of 15 for Birgunj metropolitan, 10–16 with an average of 13 for Dharan Sub-metropolitan, 13–16 with an average of 15 for Manara Siswa Municipality, and 15–17 with an average of 16 for Budhiganga Rural Municipality. In the same vein, the average Access component is found to be 17, 10, 16, and 16 for the corresponding Palikas, respectively. The analysis also revealed that the average value of the Capacity component is 9, 14, 10, and 13; the Use component is 11, 16, 14, and 16; and the Environment component is 15, 10, 14, and 12 for Birgunj Metropolitan, Dharan Sub-metropolitan, Manara Siswa Municipality, and Budhiganga rural municipality, respectively. The WPI components of Birgunj metropolitan are found in the order Access > resources > Environment > Capacity > Use and WPI is found to be medium-low to very low. The WPI of Dharan Sub-metropolitan is found to be medium-low to low, and its components are in the order of Use > Capacity > Resources > Environment > Access. Similarly, the WPI of Manara Siswa municipality is found to be medium-low to low and its components are in the order of Access > Resources > Environments > Use > Capacity, and the WPI of Budhiganga rural municipality is found to be low to very low and its components are in the order of Use > Resources > Access > Capacity > Environments. Table 5 shows that Dharan Sub-metropolitan has a medium-low WPI with a score of 62.96, and the other three selected Palikas have a low WPI with scores of 66.75 (Birgunj Metropolitan), 68.33 (Manara Siswa Municipality), and 72.77 (Budhiganga Rural Municipality). This study indicates that the Inner Tarai area has a medium-low poverty index while the bottom of the hill has a low poverty index (Figure 6).
Table 5

Calculated values of WPI and its spatial components

PalikasResources (R)Access (A)Capacity (C)Use (U)Environment (E)WPI
Birgunj Metropolitan 14.90 17.04 8.86 11.32 14.63 66.75 
Dharan Sub-metropolitan 12.85 9.59 13.62 16.54 10.36 62.96 
Manara Siswa Municipality 14.81 16.08 9.62 13.69 14.13 68.33 
Budhiganga Rural Municipality 16.21 15.78 12.91 16.28 11.59 72.77 
PalikasResources (R)Access (A)Capacity (C)Use (U)Environment (E)WPI
Birgunj Metropolitan 14.90 17.04 8.86 11.32 14.63 66.75 
Dharan Sub-metropolitan 12.85 9.59 13.62 16.54 10.36 62.96 
Manara Siswa Municipality 14.81 16.08 9.62 13.69 14.13 68.33 
Budhiganga Rural Municipality 16.21 15.78 12.91 16.28 11.59 72.77 
Figure 3

WPI and its components for Birgunj Metropolitan

Figure 3

WPI and its components for Birgunj Metropolitan

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Figure 4

WPI and its components for Dharan Sub-metropolitan

Figure 4

WPI and its components for Dharan Sub-metropolitan

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Figure 5

WPI and its components for Manara Municipality

Figure 5

WPI and its components for Manara Municipality

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Figure 6

WPI and its components for Budhiganga Rural Municipality

Figure 6

WPI and its components for Budhiganga Rural Municipality

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Variation of the water poverty at different spatial scales in selected Palikas

The scores for the Resource component are lower in Dharan Sub-metropolitan (12.85), moderate in Birgunj Metropolitan (14.81), and Manara Siswa Municipality, compared to Budhiganga Rural Municipality (16.21). This variation can be linked to limited water availability and significant variability in rainfall in the area. Access to water resources (A) is more satisfactory in Birgunj Sub-metropolitan (17.04), Manara Siswa Municipality (16.08), and Budhiganga Rural Municipality (15.78). However, it needs improvement in Dharan Sub-metropolitan (9.59) to reach the desired levels. The Capacity (C) of individuals to manage water and related issues effectively varies, with Dharan Sub-metropolitan scoring the highest at 13.62, followed by Budhiganga Rural Municipality at 12.91. However, Birgunj Metropolitan and Manara Siswa Municipality has lower scores, with 8.86 and 9.62, respectively. Notably, Dharan Sub-metropolitan and Budhiganga Rural Municipality have a larger economically active population and more nonagricultural job opportunities than the other Palikas. This has led to increased income levels and better access to water resources and technologies, ultimately assisting in managing water-related challenges. The water use ranges from 16.54 in Dharan Sub-metropolitan, 16.28 in Budhiganga Rural Municipality, 13.69 in Manara Siswa Municipality, and 11.32 in Birgunj Metropolitan. This indicates high domestic water use in Dharan municipality and high use in Budhiganga rural municipality for both domestic and agricultural purposes. In contrast, there is poor domestic and agricultural water use in Birgunj Sub-metropolitan and Manara Siswa Municipality. This suggests that management strategies need to be developed in a comprehensive manner, considering the limited availability and variability of water resources to optimize the use of available water in the selected Palikas. The Environmental component (E) performs better in metropolitan and sub-metropolitan areas compared to municipalities and rural municipalities. However, a detailed analysis of its indicators reveals inadequate vegetation coverage in metropolitan and sub-metropolitan areas compared to municipalities and rural municipalities. In general, the WPI in the Inner Terai Palikas is better than that in hilly areas within the selected Palikas. However, there is potential for improvement across all five components, and further development would be beneficial at various spatial scales. The implementation of policies and planning specific to the scale and particular issues can play a crucial role in improving the water poverty situation across the basin (Figure 7).
Figure 7

The WPI component values at selected Palikas.

Figure 7

The WPI component values at selected Palikas.

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Correlation analysis among WPI components

Birgunj Metropolitan
Manra Siswa Municipality
Budhiganga Rural Municipality
Dharan Sub-Metropolitan
ComponentsRACUERACUERACUERACUE
1.0     1.0     1.0     1.0     
0.8 1.0    0.7 1.0    −0.2 1.0    0.5 1.0    
−0.3 −0.8 1.0   −0.2 −0.3 1.0   −0.1 −0.3 1.0   −0.4 −0.1 1.0   
−0.2 −0.7 1.0 1.0  0.0 0.1 0.8 1.0  0.2 0.1 0.7 1.0  0.2 0.0 0.3 1.0  
0.4 0.8 −1.0 −0.9 1.0 −0.7 −0.4 0.01 −0.2 1.0 0.2 0.4 0.2 0.1 1.0 0.3 0.1 −0.3 −0.1 1.0 
Birgunj Metropolitan
Manra Siswa Municipality
Budhiganga Rural Municipality
Dharan Sub-Metropolitan
ComponentsRACUERACUERACUERACUE
1.0     1.0     1.0     1.0     
0.8 1.0    0.7 1.0    −0.2 1.0    0.5 1.0    
−0.3 −0.8 1.0   −0.2 −0.3 1.0   −0.1 −0.3 1.0   −0.4 −0.1 1.0   
−0.2 −0.7 1.0 1.0  0.0 0.1 0.8 1.0  0.2 0.1 0.7 1.0  0.2 0.0 0.3 1.0  
0.4 0.8 −1.0 −0.9 1.0 −0.7 −0.4 0.01 −0.2 1.0 0.2 0.4 0.2 0.1 1.0 0.3 0.1 −0.3 −0.1 1.0 

(R- Resources, A-Access, C- Capacity, U- Use and E- Environment).

Positive correlation between Access indicates that the study area has abundant water resources with better access to water sources, while a positive correlation between Resources and Environment implies improved water access leads to healthier ecosystems. Negative correlation between Capacity and Use highlights challenges in effective water management, while the negative correlation between Resources and Use suggests areas with limited capacity struggle to utilize water efficiently. Capacity-building through education and infrastructure is crucial for sustainable water management and economic benefits.

Discussion

The outcomes of the WPI are vital for the planning, management, and research of water resources. They assist in prioritizing needed enhancements in a region's water conditions, thereby averting planning mishaps and wasteful investments. Evaluating water poverty at a higher level in the Inner Terai Palikas (Birgunj Metropolitan, Manara Siswa Municipality, and Budhiganga Rural Municipality) might mask the water poverty at a lower level in Dharan Sub-metropolitan located at the foothill. Therefore, a thorough assessment of water poverty across different spatial scales is essential for effective management strategies. In practice, the WPI value can direct the prioritization and selection of study areas, such as administrative units or watersheds, when decisions need to be made. For instance, in this study, the four study Palikas could be ranked in descending order of priority, like Budhiganga Rural Municipality, Manara Municipality, Birgunj Metropolitan, and Dharan Sub-metropolitan. Component values aid in identifying the focus areas within the selected or prioritized study area, while indicator values highlight specific sub-areas for attention and progress tracking. It is important to note that some factors influencing water poverty are beyond direct control, such as resource availability and variability. Others are linked to development policies, like water supply and sanitation, and some are connected to the sociodemographic and economic status of the area. Enhancing the water poverty situation might be relatively easier when focusing on factors susceptible to development policies, which can be influenced by policy interventions. However, addressing sociodemographic and economic challenges may require long-term policies and programs.

This research presents a set of water poverty indicators designed specifically for Nepal, taking into account the unique local issues and constraints in data. The WPI offers a comprehensive approach to measure water poverty, utilizing 10 indicators and 12 variables to streamline the understanding of water poverty conditions. The research assesses water poverty in various Palikas of eastern Nepal, exploring the differences in water poverty at multiple levels such as metropolitan, sub-metropolitan, municipal, and rural areas. The findings suggest that the water poverty conditions in these Palikas are comparatively better than the national average, with the main problems being inefficient water usage and environmental degradation. This points to the necessity for better water management practices over concerns of water scarcity. Consequently, policy efforts should focus on reinforcing water management techniques to make the most of the existing water resources. The WPI analysis within the Palikas indicates disparities, with scores ranging from 72.77 in Budhiganga Rural Municipality to 62.96 in Dharan Sub-metropolitan. A closer look at the WPI components within the districts shows variances in aspects such as water resource availability, accessibility, environmental quality, and capacity, identifying areas in need of enhancement across the Palikas. The WPI suggests a sequence for addressing water poverty, prioritizing Budhiganga Rural Municipality, followed by Manara Siswa Municipality, Birgunj Metropolitan, and Dharan Sub-metropolitan. The WPI comparison across three different spatial dimensions does not reveal a consistent pattern, with marginally higher scores in the Inner Terai regions like Birgunj Metropolitan (66.75) and Manara Siswa Municipality (72.77) as opposed to the lower hill areas like Dharan Sub-metropolitan (62.96). In general, a detailed review of the WPI components shows better scores in Resource and Access in all the Palikas, while the metropolitan and sub-metropolitan areas score higher in Usage, Environmental, and Capacity aspects. The research emphasizes the importance of tailored policy measures and management strategies to improve the overall water poverty conditions in the targeted area.

We would like to express our sincere gratitude to the DHM, Nepal, for providing the climate and hydrological data, and the people of the selected Palikas for participating in our survey.

All relevant data are available from an online repository or repositories. https://drive.google.com/drive/folders/1l5-vWHETHe01PGQdFEzAgaH21waN4QTG?usp=drive_link

The authors declare there is no conflict.

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