Assessing spatial variation in water supply of a city using dasymetric mapping

Water scarcity affects more than 40% of people around the world, an alarming figure that is projected to escalate with increasing global temperatures as a consequence of climate change. By 2050, it is projected that at least one in four people will be affected by recurrent water shortages (Shiklomanov 1998). Studies suggest that as the effects of climate change worsen, it will impact a much larger population and water shortages will increase (Goklany 2005). The rapidly increasing population, the pollution of natural water resources, and climate change further aggravate the situation (World Bank 2018). Areas with high water stress would exhibit greater pressure on groundwater aquifers, which will be aggravated in the longer run (Nayyeri et al. 2021). The effect will be predominantly seen in urban areas where the concentration of population and water demand is much higher.

As urban areas continue to grow, the pressure on natural resources within the city and its periphery increases exponentially with time. Large cities require a huge amount of resources to sustain themselves and therefore expand beyond their physical and natural boundaries in the long run (Bahri 2012). Among all the resources that the city acquires, water as a resource is the most difficult to manage. Water, due to its inherent nature, is free-flowing and is not confined to any physical boundaries and cannot be stopped. Therefore, water management is a system that needs to be handled with coordination between various agencies and authorities. In urban areas, the management and distribution is governed by various factors and not only requires coordination within the city limits but also on its peripheral administrative entities through which it procures the resource.

In such a scenario, the scarcity of the water resource can be managed by making use of the available wastewater. While this is common knowledge and easier to understand, the implementation of the wastewater reuse system is difficult in Indian cities in the absence of data. This research tries to bridge the gap by identifying a framework through which the macro-scale variation of water consumption and wastewater generation can be identified by linking it to population and land use. This will help in providing better estimates for the local authorities to allocate and direct the resource towards its appropriate use.

Urbanization alters many natural processes in its immediate environment. Urbanization changes the physical and natural characteristics of the region, while also changing the uptake of resources and the disposal of waste. It modifies the physical environment by increasing impervious cover, reducing vegetation, and altering natural drainage patterns by increasing surface runoff (Leopold 1968; Eini et al. 2021). Compounded with an increasing concentration of people in a limited area; it puts pressure on the available resources, and over time, the city tends to look for supplies farther away indirectly putting a pressure on the surrounding peri-urban and rural environment.

The urban water system is a technocentric model, where there is an interrelationship between various subsystems such as engineering, management, governance, technology, and social behaviour (Everard 2020). Identification of a source, its management and distribution, and eventual disposal are required to be handled at various organizational levels. This requires coordination between physical and administrative boundaries while considering the hydrological entities. The movement of water through a regulated and designed pipeline system, its hierarchy and relationships are a primary characteristic of this urban water cycle. The major concern in this system though is that urban areas are inherently incapable of providing for their resources and therefore have to depend on surrounding rural areas for their demand. This leads to a mechanism that is not sustainable by itself and has a high dependency on neighbours. Therefore, in water studies, understanding the flow as well as the movement of the resource through temporal and spatial scales and its volume and quality is important (Oki & Kanae 2006). Whereas an efficient urban water management system improves the aquifer balance (Tork et al. 2021).

The current mechanism in urban water systems is a very linear and isolated model in which there is zero or no integration between water supply, wastewater, and stormwater. Most cities have engineering-based linear approaches in which wastewater and stormwater are considered separate entities and wastewater is quickly pumped out of cities into receiving waterways, leading to pollution of raw water resources. It is the need of the hour to consider wastewater as an integral part of the overall urban water cycle so as to identify its potential for alternate use.

The water supply in Indian cities is limited in its coverage. Only about 68% of households in seven major Indian cities had exclusive access to water supply within premises in the year 2005 (Shaban & Sharma 2007). Over the years, various programmes and policies have focused on providing adequate water to all residents. However, there has been little progress to achieve this. One of the reasons is that the water supply systems in India have old infrastructure and are built around earlier requirements. The added pressure of high-rise residential units or the increase in density in older areas leads to the breakdown of the existing system and water shortages. Households that have installed booster pumps to store water in household-level water tanks create reduced pressure on the water line for other users (McKenzie & Ray 2009). The High-Powered Expert Committee (HPEC) (Ahluwalia & Shrivastava 2011) created to evaluate Urban Infrastructure and Services has stated that, in India as of 2011, only 64% of the urban population is covered by individual pipes and stand posts, compared to 91% in China, 86% in South Africa, and 88% in Brazil (Ahluwalia et al. 2014).

Another major issue plaguing Indian cities is the inequality in water supply. The frequency and quantity of water supplied vary throughout the city. Poorer neighbourhoods often get a smaller share of the supply at odd hours, while economically higher neighbourhoods have better supply (Kumar & Saleth 2018). In times of crisis, poorer neighbourhoods bear the greatest brunt. For example, the poorer neighbourhoods of Madurai and Chennai suffered the worst during the 2013 and 2019 water crises (Ramesh 2021). Several Indian cities are under water stress and have water shortages and reduced supply times, especially during dry seasons (Chakraborti et al. 2019). Unaccounted for water (UFW), lack of metered connections, non-availability of water supply within premises, and excessive dependence on groundwater especially during summer months are some of the other problems plaguing Indian cities (Bajpai & Bhandari 2001; Janakarajan et al. 2006; McKenzie & Ray 2009; Chakraborti et al. 2019).

In such a scenario and with the threat of low availability of resources as per all known predictions, there has to be an alternate resource to satisfy some non-potable water needs of the population. As freshwater shortages are expected to increase in the future, the need of the hour is to identify alternative means of resources to ensure a better allocation of the raw resource. Wastewater is a well-known alternative that has multiple uses and can be explored as a resource. Countries such as Israel, which are already water scarce, use treated wastewater as a resource (Liao et al. 2021). Singapore is another such country that is developing strategies for wastewater use and has developed a 100% wastewater treatment rate (Liao et al. 2021).

Most urban areas generate a large amount of wastewater as a by-product. All the needs of the city do not require a potable quality of water. Non-potable uses such as watering parks and lawns, urban irrigation, augmentation of surface, and groundwater sources are few uses which can be accommodated through the reuse of treated wastewater. For such uses, wastewater that is treated to appropriate limits, so that it does not cause any harm to users, can be an alternative resource (Bauer & Wagner 2022). The specific intended use of the treated wastewater will determine the treatment required, quality of the water, quantity of water required, and the seasonal variation if any (Palacios et al. 2017).

In the Indian scenario, most urban centres do not have sufficient coverage of the sewer network. Most of the generated sewage is collected in septic tanks and then disposed of in treatment facilities. Smaller towns may have areas where wastewater is discharged directly into streams and water channels. Current reports show that wastewater generated from cities and towns in India is not fully treated, with only 11,787 million litres per day (MLD) receiving treatment from 38,255 MLD (Visanji et al. 2020). Municipalities work with the assumption that 70–80% of the water supplied is discharged as wastewater (Never & Stepping 2018).

One of the important factors affecting wastewater reuse is the scepticism about the health effects of the use of treated wastewater among the general public. Public opposition to wastewater reuse schemes results from attitudes, prejudiced beliefs, lack of knowledge, and fear and distrust, which are often not unjustified judging by the failures of wastewater treatment plants worldwide (Friedler & Lahav 2006; Smith et al. 2018). Therefore, the solution lies in developing treatment facilities that can stand up to scrutiny over a period of time. Small-scale solutions, such as reuse on a neighbourhood scale, can improve the applicability and acceptability of the approach. Some of the popular non-potable uses are gardening and landscaping, agriculture, coolant water in industries, toilet flushing and groundwater recharge, etc. (Kumar & Goyal 2020; Bauer & Wagner 2022). There needs to be a large-scale application of wastewater reuse and stressing the difference it would cause to the ecosystem in the long run is important to generate acceptance towards wastewater reuse.

Hwang et al. analysed the risk and vulnerability of a regional water supply system in Tucson, Arizona, and found that decentralized wastewater system effectively served as a backup potable water supply during the failure of a centralized water supply system and recharge wells (Hwang et al. 2015). Batool and Shahzad proposed a decentralized wastewater treatment system that has the possibility of upgrading as the area develops and the population expands (Batool & Shahzad 2021). Urban areas with heterogeneous users and uses have a greater potential to use and reuse treated wastewater. The quantum of water that moves through the system also makes it economically viable to develop such a system. To promote decentralized wastewater reuse, it should be included in government policies, and promotional schemes such as incentives and tax benefits should be given. This will encourage local communities to adopt these practices (dos Santos Amorim et al. 2020).

Vij et al. identified that low treatment capacity, inadequate sewerage network, and lack of financial and policy inclusions are a deterrent to reuse of wastewater in India (Vij et al. 2021). The change in mindset is now visible in India; with increasing awareness among the population, many localities in Mumbai have started wastewater recycling on a project basis (Matto et al. 2014). Bangalore, India has explored the possibilities of using treated wastewater for non-potable use (Evans et al. 2015). However, in the absence of a city-wide sewer network, it would be practical to create or identify pockets suitable for decentralized wastewater treatment and reuse. Decentralized wastewater treatment plants are in that sense a suitable solution to work in a local neighbourhood based on social acceptability (Akpan et al. 2020).

The absence of suitable methods for estimating and assessing distributed wastewater across the city is another issue faced by the decision-makers. There are other theoretical methods such as those proposed by Tsoukalas et al. (2017) to identify and assess the quantum of sewage generated and how it can be used. Ghafoori et al. used the clustering analysis method to identify priority areas for wastewater reuse (Ghafoori et al. 2021). Refsgaard used the multi-criteria analysis method to evaluate and identify appropriate alternatives to wastewater handling (Refsgaard 2006), whereas Sotelo et al. used the structured systems analysis and design method to assess techniques that can improve wastewater management and to identify communities that can benefit from wastewater reuse (Sotelo et al. 2021). However, all these methods need detailed data on sewage network topology, land use, type of users, etc., rendering these methods unsuitable for the Indian situation.

As mentioned in the previous section, wastewater can be an attractive alternative resource to avoid water scarcity. However, to do that, detailed information is required about where wastewater is generated, its quantity and quality, and the needs of the intended users. For an effective analysis, a combination of spatial data about the locations of users and type of land use; and non-spatial data on consumption and temporal variations of the water use are required. Since the information on wastewater in most Indian cities is very limited, evaluating and analysing the water supplied and its use can provide an idea of the generated wastewater. Planning for an effective wastewater reuse system is inefficient due to the insufficiency of such detailed data on wastewater generation and its intended consumption.

In order to decide on the allocation of the treated wastewater, local authorities require detailed information about the various functional uses of water, its distribution in the urban area and the variation in demand by the intended users. Most Indian cities, however, lack this kind of micro-level mapping of water needs, details about consumption, expenditure pattern, and population growth (Bajpai & Bhandari 2001). Also, water distribution systems (WDSs) are typically designed using a uniform demand pattern, while there may be notable differences between region-specific demand patterns (Diao et al. 2019). Mapping the consumption pattern and profile of users and land uses could therefore be useful in managing the resource in the densely populated core areas of the city and could be helpful in planning new areas. Water supply authorities could play a significant role in the planning and development of cities by extending their concern for provision of reticulated water and sewerage services to include consideration of the form of development and its impact on water consumption (Bowonder & Chettri 1984; Troy & Holloway 2004).

The spatial arrangement of activities and users in urban areas is also one of the factors that determine the availability of municipal services and infrastructure. As new areas fall under the purview of the municipal system, the associated infrastructure must catch up. For urban peripheries, challenges are directly related to their highly heterogeneous mosaic of physical environments (with different densities and land uses), their fast-changing social and cultural structures, and diverse forms of governance that encompass several institutional regimes at different administrative levels (Geneletti et al. 2017). On the contrary, in the central areas of the city, it is assumed that the densities remain the same for a longer period of time. The provision of services in these highly dense areas of the city can substantially reduce investment cost, allowing funds to be used more appropriately for the peripheral areas. Another important aspect to consider is the physiography and natural drainage of the city. Segregated pockets based on the topography of the city can be a deterrent to developing a well-functioning water supply distribution network (Bhat 2014). Therefore, it is necessary to identify and plan systems with spatial, social, political, and ecological boundaries to understand behaviour and interaction within and between local, federal, private, and public organizations (Goharian & Burian 2018).

Sanchez et al. have used landscape metrics to assess this relationship and have found results that indicate that incorporating spatial configuration into both non-spatial and spatial modelling techniques better explains the sensitivity of water uses to development patterns (Sanchez et al. 2018). Small-scale models are laborious to analyse data and do not necessarily reflect the movement of water across larger spatial scales. Bouziotas et al. have created a cellular automata model to explain the relationship between urban growth and water management and have concluded that understanding this relationship helps in long-term scenario planning for more sustainable water infrastructure (Bouziotas et al. 2015). A suitable measurement scale used in this spatial analysis is a neighbourhood scale with the resolution of 100 m × 100 m, which is relevant for evaluation on a finer scale (Bouziotas et al. 2015). Jarvis has used the same scale along with the Voronoi diagrams and Monte Carlo sampling to produce an ordered ranking of areas with different water needs (Jarvis et al. 2021). Identifying indicators and applying them on a suitable scale with appropriate resolution to assess trends and determining threshold values in spatial and temporal analysis can help administrators evaluate the impact of land use practices and the impact of the development pattern on water use (Sanchez et al. 2018; Rogers et al. 2020).

In the foreseeable future, unless pertinent action is taken, the problem of water scarcity is estimated to aggravate. Therefore, the need of the hour is to manage the available resources appropriately and efficiently. An in-depth understanding of the needs of users and the variations in demand due to economic, climatic, and social factors is needed. To obtain reliable results regarding water consumption variability, multiyear observations with spatial information are needed that can assess local risks and potential threats to the water system and help identify faster interventions (Pronk et al. 2021; Wawrzosek et al. 2021).

In most Indian cities, wastewater is collected centrally and treated according to the required disposal standards according to the technology available at the treatment facility. The water is then disposed of in nearby streams. There are only a few cases where this treated wastewater is sent back to the system or used in a set-up outside the system. These are usually where decentralized treatment facilities are available. Large-scale city-wide use of treated wastewater is not in practice in India. A key issue in the implementation of such a city-wide programme is the lack of data on the exact locations where water is supplied, where it is consumed and the type of wastewater generated. To estimate the wastewater generated, identifying the locations of water consumption across the city is required.

The study, therefore, proposes a technique to estimate and map the spatial variation of water consumption throughout the city and calculate wastewater using standard norms of wastewater generation. The highest accuracy of the analysis can be achieved if a refined dataset on water consumption, land use/land cover (LULC), and population is available. Water meter data at each individual household can be used to estimate water supplied and wastewater generation information with high accuracy at various spatial and temporal scales (Lund et al. 2021). However, most Indian cities do not have such data. Therefore, the study has created an approach to estimate water consumption using dasymetric analysis and collating it with water supply data.

The study proposes a two-step methodology where the first step is to create an urban built form ancillary layer and to use population census data at the municipal ward level (‘Ward’ is the smallest municipal unit in an urban local body that has an elected representative), disaggregate the population on a finer scale based on the urban built form using dasymetric mapping tool, and then the second step is to collate the information with the locations and supply areas of municipal water tanks to estimate water supplied and wastewater generated. If the information pertaining to the capacity of the water tank, its supply frequency, and its source is also available, then it provides a more refined dataset that captures the actual variation in the water supply throughout the city. It is generally assumed that the per capita water supplied across the city is uniform; however, analysis such as this actually reveals the variation based on location, availability of resources, and physical infrastructure. The list of data and information required to complete the analysis as suggested in this research is given in Table 1.

Type 2 is compact mid-rise development, type 3 is compact low-rise, type 6 is open low-rise, type 7 is lightweight low-rise, type 9 is sparsely built, type 10 is industrial development, type 11 is dense trees, type 14 is bush/scrubland, and type 16 is soil/sand/agriculture, while type 17 is water.

The dasymetric map created for Bhopal city provided a spatial representation of the population distribution in the city as per population in 2019. As anticipated, the core areas of the city show a higher population density compared to the peripheral areas. The highest population was observed at 1020 persons/sq. km. Scattered population density is seen in few particular wards on the peripheries, whereas the higher density is predominantly seen towards the South and North of Bhopal. The dasymetric map was then used to identify population pockets with similar urban form characteristics based on density.

In the next stage, information related to the water tanks, overhead tanks (OHTs)/elevated service reservoirs (ESRs), was collected from the Bhopal Municipal Corporation. Bhopal procures its water from four different resources, with two: Kolar Dam and Narmada River, lying in a different district and river basin, respectively. While the peripheral areas of the city depend on groundwater and other sources such as water tanker supply, for the purpose of this study, only the municipal water supply network is considered.

In summary, as an essential data, the urban built form map was created using LCZ classification. The census information collected from the local municipal body was used to create a dasymetric population map as shown in Figure 6. The location of water tanks was plotted and analysed for frequency and source of water using the data procured from the local municipal body. Since the exact localities to which the tank supplies water is not available, the Voronoi diagrams was used to identify the variation per capita in the city, as shown in Figure 7.

As expected, most of the city has a limited water supply of 100 MLD per person. Only a few localities have a higher than usual supply. It is also noteworthy that, depending on the source, the frequency of water supplied varies throughout the city. Bhopal has water supply from four different sources. Although the traditional source is Upper Lake, it is now insufficient to meet the needs of the population and, therefore, water is supplied on alternate days. The other three sources, Kolar Dam, Kerwa Dam, and Narmada River are used on a daily basis.

On intersecting the Voronoi polygons with ward boundaries, it is found that six wards out of the 85 wards in the city, all of which are the most densely populated and are in the core area of the city, generate wastewater more than 50 litres/sq. m. Seven wards generate less than 1 litre/sq. m, out of which four are on the periphery of the city, whereas the other three are well within the city but have large empty pockets of vacant land. This analysis demonstrates that wastewater generation is a reflective of all factors combined, namely population, land use, and urban built form.

Bhopal city has 13 active STPs located across the city. However, all of them treat wastewater to primary or secondary level treatment and discharge it to the nearest natural drain. None of the STPs currently distribute treated wastewater for reuse although it can be used for municipal non-potable uses effectively. Due to its geography, the city of Bhopal has the potential to decentralize the city into spatial pockets and identify new treatment plants (if unavailable) or focus on existing STPs to distribute treated wastewater for alternative uses. Collecting this information on a periodic basis would enable the local municipal body to make informed decisions in future about this resource.

The framework can work at multiple assessment levels. On a broader city-wide scale, the population distribution is derived from the LCZ mapping, as mentioned above. Even with severe data limitation, when information is available only about average per capita water supply to residents across the city, a spatial variation map can be generated that identifies the amount of water consumed on a particular city grid corresponding to its population density. Grids with similar urban forms can be collated to calculate the water consumed in that particular spatial pocket. Wastewater generated in each of these pockets can then be identified based on standard values. However, due to data limitation, variation can only be accounted for by population distribution. Variation due to differential supply in the wards cannot be identified at this assessment level.

On a comparatively finer scale, when location, quantity, and frequency of the water supply information is available at the ward level, a city-wide analysis using the same framework provides more detailed results on the population and water supply in each of the wards and accounting for the variation in the supply, if any. At the ward-wise data availability, the population distribution is derived according to LCZ mapping. In the next stage, the locations of all OHTs and ESRs and their service area are identified (if available). In case the service area is difficult to identify, we use the Thiessen polygon or Voronoi meshing approach to identify the coverage of the water supply network. An assumption in doing this is that all areas lying within two separate supply points are included under municipal water supply, whether through piped systems or standpipes in the absence of individual connections. The superimposed map can then be used to recalculate the variation corresponding to the urban built form and the variation in per capita supply and subsequently the wastewater generated.

The most accurate results for wastewater generation can be obtained if metered water supply data is available at each individual household level that details the water consumed throughout the day. However, as discussed before, this information is not available for Indian cities. Thus, the strong point of the proposed framework is that it overcomes this serious data limitation.

The study presents a framework to estimate water consumed and wastewater generated at a finer scale than the usual gross average of water supplied and wastewater generated. It does not aim to provide accurate results, rather the main purpose of the study is to spatially identify the variation and assess the potential of reuse of wastewater within the city based on different users, their activities, and land use classes in absence of detailed data. However, a limitation of this study is that the results obtained for Bhopal city could not be verified on ground due to non-availability of relevant dataset to cross check the results.

The study has successfully demonstrated the proposed framework by applying it to the case study city Bhopal and produced useful information about distributed wastewater generation across the city. The study identifies that although it is assumed that all residents of the city have an equitable supply, the detailed analysis reveals a variation based on the source, frequency, and quantity of water supplied. Although it can be assumed that a particular urban form is suggestive of a particular economic class, the variation of supply in different wards of the same urban form presents a difference due to the spatial location of that form within the city and the availability of OHTs and ESRs in the vicinity. Higher-income localities and surrounding areas are far better in terms of availability, whereas old city cores are poorer due to higher population and densely packed neighbourhoods and there is jostling for the same resource. The density of the locality and the proximity to the water tank are also another factor that alters the water supplied in that locality. The amount of wastewater generated also depends on the type of users and land use apart from the quantity of water supplied.

The study thus concludes that to better allocate the resource for future needs, spatial mapping and understanding the variation of the availability of the resource are needed. The mapping reveals the discrepancies and inequity in the distribution of the resource and also helps identify the future potential for the city's development. The appropriate use of available resources is the need of the hour and, therefore, identifying the various uses, users, and future growth of the city's needs can help decision-makers plan and allocate resources progressively. Furthermore, by using this methodology, the local municipal body can identify the type and quantity of wastewater generated throughout the city, and relating it to existing land use can help identify potential users of this treated wastewater.

Wastewater reuse is an alternative that requires exploration and widespread application. To identify probable uses and users, this technique will help determine the type, quality, and quantity of treated wastewater suitable for reuse. Identifying the potential uses can help decision-makers direct and manage the resource to an appropriate user and better allocate the raw water resource to potable needs. The study is useful in formulating a technique that links form-based urban development with population density to the actual condition of the water supplied. In the absence of detailed information on the wastewater generated, its quantity and quality, and any temporal and spatial variations, if any, this technique helps fill that gap. When the data and information are available at micro-level, the authorities can identify, delegate, and fulfil the needs of the population effectively. There should also be continuous updating of this data set on temporal and spatial scales so that the most recent and accurate information is available to the local municipal body. Regular analysis of this information on a temporal scale of every few years correlated with spatial growth will enable them to refine the distribution of the resource. Changes in development and consumption patterns can then be included in the analysis to improve allocation with changing perceptions and social dynamics. Over time, re-evaluating the existing condition with updated information will improve decision-making.

Data cannot be made publicly available; readers should contact the corresponding author for details.

The authors declare there is no conflict.