Urban water issues impacting sustainable development can be analyzed, modeled, and mapped through cutting-edge geospatial technologies; however, the water sector in developing countries suffers various spatial data-related problems such as limited coverage, unreliable data, limited coordination, and sharing. Available spatial data are limited to the aggregate level (i.e., national, state, and district levels) and lack details to make informed policy decisions and allocations. Despite significant advancements in geospatial technologies, their application and integration at the policy and decision-making level are rare. The current research provides a broad GIS-centric framework for actionable science, which focuses on real context and facilitates geospatial maps and theoretical and practical knowledge to address various water issues. The study demonstrates the application of the proposed Geospatial Framework from technical and institutional perspectives in water-stressed zones in Pune city, showing where and how to solve problems and where proposed actions can most impact creating a sustainable water-secured future. The framework makes it possible for everyone to explore datasets that can provide a baseline for research, and analysis, contribute to the process, propose, and act on solutions, and take the benefits of the outcomes and policy recommendations.

  • A Geospatial Framework is developed to measure and monitor water security through geospatial technologies.

  • The study demonstrates the application of the proposed Geospatial Framework from technical and institutional perspectives in water-stressed zones in Pune city.

  • The study can collaborate with Municipal Corporation mutually beneficial and work toward open-linked geospatial data for water security.

Water insecurity remains one of the most pressing resilience challenges worldwide (Cook & Bakker 2012; Rockefeller Foundation 2015), making indispensable the need for conservation and collaboration between cities, partners, and stakeholders to find an innovative and actionable solution (Rockefeller Foundation 2015). The concept of ‘water security’ emerged in the 1990s (Cook & Bakker 2012) generally measured in terms of access to safe water at any level from the household to the global, while ensuring that the natural environment is protected and improved.

In recent years, the development community has come to realize the need for geospatial technologies for water security. Greg & Abbas (2017) provided significant insights into integrating geospatial technologies to solve various sustainable development challenges. The availability of comprehensive and highly accurate geospatial data advances innovation and intensely enhances the preparedness for water resilience (Goodchild 2007). It is necessary to have real-time spatial data on sustainable development measures (Dangermond 2020). Complete datasets increase efficiency in local planning, allow users to take the data offline, analyze the geographical context, model, and map to achieve the Sustainable Development Goals (SDGs) (Guan et al. 2012; Greg & Abbas 2017; United Nations 2019; Dangermond 2020). Guan et al. (2012) explained how a geographic interface helps visualize and analyze spatial data from global to local scales. Recently, the Ministry of Science and Technology, Govt. of India, encouraged leveraging modern geospatial technologies, which would help improve the planning and management of resources and better serve the specific needs of citizens (DST 2021).

The biggest challenge is a lack of digital geographic data. Developing countries often lack digital geospatial information precludes some countries from using available technical capabilities (Mennecke & West 2001). Furthermore, outdated maps or the absence of a national mapping effort add to these nations' challenges. What is needed to answer basic questions related to water security challenges that are influenced by location information? And how can geospatial information support national priorities and circumstances while securing a safe and beneficial data ecosystem for citizens? To map all this, decision-makers need accurate and up-to-date data so they can plan and take necessary actions. Much of the data are currently not available at the appropriate geographic level to make the best decisions. The need for this type of geospatial and statistical data will only continue to grow in the future which will likely challenge our communities (UN GGIM 2020). The study recommends creating a rich framework of water data content and making geospatial data available that are supporting policymaking and scientific research.

The water supply system in the city of Pune is affected due to the fast and chaotic development in and around the city. Rockefeller Foundation has selected Pune city, which is facing the problem of water insecurity as part of its 100 resilient cities (100 RC) initiative to build resilient cities across the world. Pune Municipal Corporation (PMC) merged 11 fringe villages in 2017 and recently 23 more villages within its limit in 2021, however, unable to supply water to many of these peripheral villages. Furthermore, the quantity of per capita water supply and hours of supply per day varies substantially across the city. Some central parts of the city are benefited from a large availability of water as compared to peripheral areas. According to previous research and assessments, urban water services are below the stipulated standards in terms of accessibility, water quality, intermittent water supplies, non-revenue water (NRW) due to leakages, unauthorized connections, billing, and collection inefficiencies. Keeping these challenges in mind, the study prioritized improvements in urban water service delivery and ensures the availability of a basic level of safe water services to all. Understanding water supply services with a geospatial approach is a clear research need.

In this paper, we developed a holistic, digital Geographic Information System (GIS)-centric framework for water security, including a vast array of spatial maps, wide-ranging spatial thematic layers, methods for analysis, and various useful strategies and policies for water security. Furthermore, the paper shows the applications of the Geospatial Framework exploring the potential areas of water supply within the context of the peripheral villages in Pune city. The Geospatial Framework aims to provide a common platform for geospatially enabled administrative and other water-related thematic data from across a range of sources that can be integrated based on location and ensure that these data can be integrated with other geospatial information. The framework can be used by diverse stakeholders who are concerned about water security. The current research can collaborate with PMC in a mutually beneficial manner and work toward open-linked geospatial data for water security and environmentally sensible urban water management. The Framework is designed considering the need of citizens to have a system of online geospatial data and engage them with communities, promote transparency, and collaborate across departments. Maps give insight into spatial interconnection, spatial interdependence, and context for decision-making.

The water sector in India suffers several data-related problems such as limited coverage, limited coordination, and sharing (NITI Aayog 2019). The Ministry of Jal Shakti, Govt. of India launched a web-based centralized platform of geospatial data called India-WRIS in 2009, which was further revised in 2016 to fulfill water security (India-WRIS 2009). Indian Space Research Organization (ISRO, Bhuvan 2015) also provides geospatial data, including several thematic maps related to disasters, agriculture, water resources, and land. However, the data on these platforms are available at an aggregate level (i.e., national-, state-, district-, block-level, and hydrological levels such as basin and sub-basins) and lack the details required to run any sort of analysis to make informed policy decisions. Furthermore, PMC (2020) GIS portal provides access to geospatial data, which is limited to visualization purposes and does not allow the user to download the data for any further spatial analysis.

Any research efforts need complete datasets with adequate metadata to facilitate their use. Due to the unavailability of comprehensive spatial data, it is difficult to assess the impact of different factors on water resilience, thereby reducing efficiencies in policy formulation, infrastructure maintenance, research, and innovation (NITI Aayog 2019). Goodchild (2007) encouraged creating valuable spatial data, which provides access to not only those who are doing serious geospatial investigations, including GIS professionals, academic scholars, and small GIS organizations but also to the general public who are not GIS professionals. The available spatial data can be used to compose dynamic maps online or offline that can help achieve SDG #6. Furthermore, decision-makers, planners, and policymakers need to marry scientists and technology to solve real-world issues. Cities need a cross-cutting framework that integrates and aligns a wide range of central and state-level policies for water security. The study recommends creating a rich framework of water data content and making geospatial data available that are supporting policymaking and scientific research.

The piped water supply is the most reliable drinking water supply system. However, Houngbo (2018) argues that reservoirs and water treatment plants (WTPs) are not the only water management solutions. With the growing urban population, it is essential to look at alternative water supply systems instead of relying on centralized infrastructure approaches, i.e., piped water, limiting the option of more environmentally sensitive, flexible, and resilient approaches (Brown et al. 2011; Megdal & Forrest 2015; Civitelli & Gruère 2017; Houngbo 2018). The additional water supply must be arranged from local and sustainable sources located outside the boundaries of the cities (Lundqvist et al. 2003; Megdal & Forrest 2015; Civitelli & Gruère 2017) like Delhi, India, where only 57% of the population has access to the piped water supply. However, 34% of the population obtains water from non-piped sources, such as traditional underground water tanks. Rural communities can use treated wastewater for irrigation purposes instead of groundwater (Civitelli & Gruère 2017).

Several recent studies have investigated incorporating green spaces into development to maintain higher levels of evapotranspiration and minimize the impacts of urban development (Walsh et al. 2016; Wright et al. 2021). Wright et al. (2021) assessed the effectiveness of different policies related to protecting riparian zone, preserving forest areas, hills, hilltops, and promoting denser development and green neighborhood for water balance to reduce the impacts of urbanization. Wetlands also act as natural barriers that soak up and capture rainwater, restrict soil erosion and prevent the impacts of floods. Few studies have explored the combined effect of the specific sets of location-specific policies on watershed management regional stakeholders (Walsh et al. 2016; Kumar & Paramanik 2020; Wright et al. 2021). Megdal & Forrest (2015) also encouraged sustainable water management approaches instead of building a new water distribution infrastructure for addressing long-term water scarcity problems.

Groundwater resources are the lifeline of India's water supply in both the rural-agrarian situations and in the growing urban-industrial context (Kale et al. 2022). In the mountainous regions livelihood of the people are mainly dependent on the springs for drinking water (Kumar & Sen 2020). About 50% of urban water supplies are groundwater-based. It is recommended to employ sustainable approaches such as traditional and indigenous knowledge like nature-based solution (NBS) and green infrastructure (Houngbo 2018; Kumar & Sen 2020; Niasse & Varis 2020). Traditional urban planning always integrated nature in India, which has shown great potential to improve the management of water resources in urban areas (Chandran et al. 2021; Zhixin et al. 2023). Green solutions such as preserving the functions of ecosystems, planting trees, restoring wetlands, recycling, and harvesting water, recharging groundwater, and protecting watersheds have shown great potential to improve the management of water resources in urban areas (Srinivasan et al. 2013; Walsh et al. 2016; Mathur 2017; Houngbo 2018; Niasse & Varis 2020; Wright et al. 2021).

Drinking water supply should not be limited to centralized solutions; instead, decentralized, community-based approaches should be promoted (Anthony 2007; Srinivasan et al. 2013; Civitelli & Gruère 2017). However, there have been very few decentralized approaches such as community-controlled systems in urban areas in India (Anthony 2007). There is a need for new forms of urban governance and planning institutions capable of managing both centralized actions by utilities and decentralized actions by millions of households (Srinivasan et al. 2013; Megdal & Forrest 2015; Civitelli & Gruère 2017) to reduce vulnerability to water shortages.

Local governments are responsible for water supply services in cities. Private sector participation (PSP) in water delivery is still rare in India. The National Water Policy of the Government of India (2012) encouraged PSP in water resources. Mathur (2017) encouraged public-private partnerships for municipal water supply in developing countries with a case example of water service delivery improvement in Karnataka. The significant benefits of the private sector include financial sustainability, technical expertise, and operational and management efficiencies (Guardiola et al. 2010; World Bank 2014; Vedachalam et al. 2016; Mathur 2017). However, some authors argued in their research that privatization could be problematic in lower-income economies and claimed that government-owned utilities are better than private utilities (Crook 2003; Kirkpatrick et al. 2006).

Study area

Pune city is located at the confluence of two major rivers, the Mula and Mutha. The study area covers the current boundaries of the PMC. Pune city has expanded from 7.74 km2 to a massive 516.18 km2 over the past 70 years. The first expansion was to include 18 villages in 1958, followed by the merging of 23 villages out of the proposed 38 villages in 1997. The Maharashtra State government proposed a merger of 34 villages in 2014, out of which PMC merged 11 villages with a population of 2.39 lakh and an area of 80.7 km2 in the city's periphery in 2017. After merging the remaining 23 villages recently on June 30, 2021, PMC now has a total of 516.18 km2 of land area within its boundary (Figure 1). Pune has officially become the city with the largest geographical area in Maharashtra.
Figure 1

Study area: PMC limit.

Figure 1

Study area: PMC limit.

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Pune city is unique in terms of historical and environmental aspects. As a result, the city has tremendous growth potential, which has been witnessed in phenomenal growth over the past 60 years. As more and more people move to urban areas, cities typically expand their geographic boundaries to accommodate migrated inhabitants. Over the years, the growth of the city has been on a ring and radial pattern, with a reliance on road-based transport.

Pune has a semi-arid hot climate (Köppen-Geiger classification: BSh) bordering tropical wet and dry (Aw). Pune experiences three seasons: Summer, Monsoon, and winter. Typical summer months are from March to June, with maximum temperatures sometimes reaching 42 °C (108 °F). The city receives an annual rainfall of 722 mm (28.43 in.) between June and October, and July is the wettest month of the year. Winter traditionally begins in November; the daytime temperature hovers around 26 °C (79 °F) while the night temperature is below 9 °C (48 °F) for most of December and January, often dropping to 5–6 °C (41–43 °F).

PMC supplies water to Pune city from four storage reservoirs namely, Panshet, Varasgaon, Temghar, and Khadakwasla, which belong to the Irrigation Department of the Government of Maharashtra (PMC 2014). The total storage capacity of these reservoirs is 29.12 thousand million cubic feet (TMC) or 824,573.57 Million liters (ML), including Panshet (10.64 TMC or 301,286.50 ML), Varasgaon (12.81 TMC or 362,733.08 ML), Temghar (3.71 TMC or 105,053.84 ML), and Khadakwasla (1.96 TMC or 55,500.14 ML). The Katraj and Pashan lakes are not directly used for water supply by the PMC but play an important role in recharging groundwater which is used by thousands of city dwellers. PMC buys water from the Irrigation Department, then treats it and supplies it to citizens of Pune city.

The PMC presently provides a pipe water supply of about 1,250 million liters per day (MLD) covering almost the entire Pune city, including Cantonment areas, Defense establishments, and a few rural fringe areas. Water is supplied to different parts of the city through a network of WTPs, pump stations, service reservoirs, and pipelines. Currently, the city has nine WTPs with a combined capacity of 1,289 MLD. Water from these WTPs is pumped to existing service reservoirs (currently 58 in number). Water is supplied to different parts of the city through a network of pumping stations and pipelines.

Water is the most basic requirement for human existence. Managing such a resource is more complicated in urban areas where supplies and infrastructure must meet the needs of a heterogeneous burgeoning population. As the population grows, the percentage of people in urban areas is also growing. Table 1 indicates the gap between water supply and demand after 2030. Long-term water demand is tied to supply limitations.

Table 1

Summary of water supply and demand

Sr. No.Water supply zonesWater supply in MLD
Water demand in MLD
2032204720322047
Parvati 212.46 280.36 456.25 390.73 
Pune Cantonment 260.2 357.47 70.8 357.47 
Vadgaon 277.45 356.71 277.45 356.71 
Warge 428.49 461.96 428.49 461.96 
Holkar 31.19 33.01 31.19 33.01 
Bhama-Askhed 214.68 306.56 214.68 306.54 
 Total 1424.47 1796.07 1478.86 1906.42 
Sr. No.Water supply zonesWater supply in MLD
Water demand in MLD
2032204720322047
Parvati 212.46 280.36 456.25 390.73 
Pune Cantonment 260.2 357.47 70.8 357.47 
Vadgaon 277.45 356.71 277.45 356.71 
Warge 428.49 461.96 428.49 461.96 
Holkar 31.19 33.01 31.19 33.01 
Bhama-Askhed 214.68 306.56 214.68 306.54 
 Total 1424.47 1796.07 1478.86 1906.42 

Source:PMC (2014).

The PMC proposed new sources of water including a supply of 200 MLD from Bhama-Askhed and 22 MLD from Chikhali in 2032 (285 MLD in 2047) for increasing further the water supply for Pune to satisfy the demand in the period 2032–2047. Among other possibilities that are presently being investigated is that there is an increase in withdrawal from the Bhama-Askhed Dam up to 285 MLD. The additional supply of 85 MLD (increased up to 285 MLD) is considered from Bhama-Askhed, and the remaining supply is from the Khadakwasla system.

Proposed Geospatial Framework

The Framework is intended to support policymakers, both at the city and regional level, as well as inform the public and community stakeholders of what is underway in this urgent mobilization to combat water insecurity. The proposed water security Geospatial Framework is rich in geographic content and designed with the aim of being publicly accessible using any of the web browsers. The user may select several thematic layers, overlay, analyze spatial patterns and relationships between data sets, and download the data for offline spatial analysis. The framework supports various data formats (i.e., shapefiles, GeoTIFF images, KML, and coverage) and projections. The framework is not static; it can be expanded with more map layers, tools and techniques, new policies, and guidelines. The framework has three major components of water security including (1) geospatial data; (2) tools, techniques, and methods to analyze geospatial data; and (3) water resource planning and schemes.

The data can be added and a web map can be prepared in ArcGIS Online, which is a cloud-based GIS and facilitates collaboration and access to GIS resources. Furthermore, the framework can be used to build a water security web app. The workflow includes: (i) publishing data and map layers to ArcGIS Online as services; (ii) creating and configuring a web map; (iii) using a template to share a web map as a web app; and (iv) match the level of sharing to users' needs.

Geospatial data and maps

The proposed Geospatial Framework includes a package of thematic layers (Table 2) and geospatial maps (Table 3). All the elements of the water cycle, i.e., evapotranspiration, condensation, precipitation, infiltration, surface runoff, river, lakes, soil moisture, and groundwater are interdependent (NWP 2012). Through its multi-dimensional listing, we have tried to cover the entire trajectory from the environmental source of water supply to distribution in the proposed Geospatial Framework. It provides access to reliable geospatial data that helps promote public safety and inform government decisions concerning water security. It is an effort in geospatial data building involving numerous partners, local, state, and central government agencies; the private sector; and academia. The framework facilitates creating and analyzing geospatial data within a city to reduce different organizations' duplicative efforts. Thematic layers can be made up of either features or imagery. Possible interactions include viewing attribution information, editing features, and performing analysis.

Table 2

Geospatial Framework: package of thematic layers related to water resilience

 
 
Table 3

Geospatial Framework: geospatial maps related to water resilience

 
 

Tools, techniques, and methods to analyze GeoDataial data

The framework is simple and can be used by people even without a GIS background. The framework aims to allow the user to visualize, download, upload spatial data, prepare maps, investigate, share, and communicate and significantly enhance the ability of non-GIS academics and researchers to conduct their research.

The framework focused on automating the mapping process so maps could be produced and printed. The framework provides various tools and techniques to answer critical questions. Most often, maps are used as tools to visualize current situations and project future impacts. The various tools include selection, find, identify, buffer, clip, intersect, union, merge and dissolve.

Standard GIS analysis tools include proximity, interpolation, map overlay, and connectivity measurement.

The Framework includes various tools to measure, visualize and map the performance indicators of water supply services including (i) coverage of water supply connections; (ii) per capita supply of water; (iii) the extent of metering of water connections; (iv) the extent of NRW; (v) continuity of water supply; (vi) quality of water supplied; (vii) efficiency in the redressal of customer complaints; (viii) cost recovery in water supply services, and (ix) efficiency in the collection of water supply-related charges.

The proposed Framework also provides tools to predict water supply and a common understanding of the available water supply in new areas. It can also be used to identify where action and investment to build water resilience will be most effective, or where deeper analysis or understanding is required.

Water resource planning and schemes

The current research offers a comprehensive geospatial approach that can be used in policy formulation over different spatial extents within the cities and exploring the combined effect of the specific sets of policies to achieve sustainable development. A major component focuses on taking the standard analyses, assessments, and interventions. The proposed Geospatial Framework includes a comprehensive resilience strategy that can be applied to solving the challenge of water in Pune city. The framework aims for conforming to future improvement and long-term water sustainability.

A well-maintained Geospatial Framework of water security provides the foundation for resilient future development. It is very important to reach out to the common people to help them ensure universal access to water. The proposed framework is dedicated to raising the level of spatial data literacy used in water policy. We use GIS to analyze water supply distribution data and maps to show stakeholders the patterns and possible outcomes, and then engage the larger community in the implementation and outcomes. The Framework provides a full set of guidance and resources to help citizens. The Framework makes it possible for everyone to explore datasets that can provide a baseline for research, and analysis, contribute to the process, propose and act on solutions, and enjoy the benefits of the outcomes and policy recommendations.

According to previous research and assessments, urban water services are below the stipulated standards in terms of accessibility, water quality, intermittent water supplies, NRW due to leakages, unauthorized connections, billing, and collection inefficiencies. Keeping these challenges in mind, the study prioritizes improvements in urban water service delivery and ensures the availability of a basic level of safe water services to all, identifies areas of improvement, and learns where to allocate resources. Predict water supply and a common understanding of the available water supply in new areas. It can also be used to identify where action and investment to build water resilience will be most effective, or where deeper analysis or understanding is required. If urban water services are below the stipulated standards in terms of accessibility, drinking water supply should not be limited to centralized solutions, i.e., piped water instead, it is essential to look at alternative water supply systems. The additional water supply must be arranged from sources located outside the boundaries of the cities

Following are the guidelines to prepare a priority map for water security:

  • 1.

    The scheme can be implemented based on the evaluation of water supply services' performance in a city by calculating performance indicators and the water index. Standardized service level indicators and benchmarks released by MoUD (2008, 2018a, 2018b) can be used.

  • 2.

    The results of each performance indicator and water index can be visualized through geospatial maps. The geospatial maps provide greater efficiencies in problem-solving, identify areas of improvement and learn where to allocate resources.

  • 3.

    Predict water supply and a common understanding of the available water supply in new areas. Tholiya et al. (2022) demonstrated the statistical significance of spatial effects of three variables viz., slope, distance from service reservoirs, and the number of supply hours behind the inequitable distribution of water supply. The determinants can be used in predicting water supply. It can also be used to identify where action and investment to build water resilience will be most effective, or where deeper analysis or understanding is required.

  • 4.

    If urban water services are below the stipulated standards in terms of accessibility, water quality, intermittent water supplies, NRW due to leakages, unauthorized connections, billing, and collection inefficiencies, prioritize improvements in urban water service delivery and ensure the availability of a basic level of safe water services to all, understand water supply services in local contexts with a geospatial approach.

  • 5.

    Drinking water supply should not be limited to centralized solutions, i.e., piped water instead, it is essential to look at alternative water supply systems. The additional water supply must be arranged from sources located outside the boundaries of the cities.

  • 6.

    Measure and monitor water security through geospatial technologies.

The proposed framework is designed to help stakeholders to learn about the water sources that are local and sustainable for instance the presence of traditional wells, spring water, green spaces, water bodies, watershed boundaries, wetlands, and groundwater recharge zones. Ensure optimum utilization of surface and groundwater available.

The result section showcases the application of the Geospatial Framework, its functionality as well as capability through some case examples including the assessment of water supply services in Pune city, identifying the determinants of geographical inequalities in domestic water supply, and evaluation of dynamic groundwater resources scenario around Pune city.

Case 1 – geospatial assessment for water supply services in Pune city

Tholiya & Chaudhary (2022) evaluated water supply services' performance through geospatial techniques in 141 water supply zones in Pune city. The study used standardized service level indicators and benchmarks released by the Ministry of Urban Development (MoUD 2008, 2018a, 2018b), Government of India. The indicators include (i) coverage of water supply connections; (ii) per capita supply of water; (iii) the extent of metering of water connections; (iv) the extent of NRW; (v) continuity of water supply; (vi) quality of water supplied; (vii) efficiency in the redressal of customer complaints; (viii) cost recovery in water supply services, and (ix) efficiency in the collection of water supply-related charges. The performance indicators and water indexes for each water supply zone were computed, analyzed, and visualized in GIS (Figure 2). These indicators were computed in ArcGIS Desktop 10.5 using consumer survey data, which were acquired from the Water Supply Department at PMC and local officials' interviews. Five out of nine indicators viz. coverage, per capita water supply, metering connections, continuity, and quality were computed, mapped spatially, and visualized at the water supply zone level (total 141), and the remaining four indicators viz. NRW, efficiency in the redressal of customer complaints, cost recovery in water supply services, and efficiency in collecting water supply-related charges were measured at the city level because of the unavailability of detailed data at the water supply zone level. Tholiya & Chaudhary (2022), explained methods to calculate the water indexes, the indicator's value, the rationale for selecting the indicator, the unit of measurement, and the service level benchmark for each indicator.
Figure 2

Water index: water supply zone-level performance on the water supply service.

Figure 2

Water index: water supply zone-level performance on the water supply service.

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The standardized service level indicators for water supply services including access to sufficient drinking water, adequate quantity to sustain, and quality have always played a fundamental and critical role in human life and societies. Therefore, all parameters are essential and carry equal weightage. Weight assignment of the indicators is based on the Composite Water Management Index (CWMI) established by NITI Aayog (2019) in association with the Ministry of Jal Shakti and Ministry of Rural Development for monitoring the performance of water supply services in various states in the country.

Tholiya & Chaudhary (2022) found that 50% of the city's total water supply zones are high-performing, 26% medium-performing, and 24% low-performing zones for their water supply services. The study provides greater efficiencies in problem-solving, identifies areas of improvement, and enables decision-makers to allocate resources to achieve equitable water supply services to their citizens.

Case 2 – determinants of geographical inequalities in domestic water supply

Tholiya et al. (2022) employed Ordinary Least Squares (OLS) Regression, Geographically Weighted Regression (GWR), and the new version of GWR termed Multi-scale Geographically Weighted Regression (MGWR) models to better understand the factors behind observed spatial patterns of water supply distribution and to predict water supply in newly merged and proposed villages in the Pune city's periphery (Tholiya et al. 2022). Results showed the statistical significance of slope; distance from service reservoirs; and water supply hour. MGWR and GWR models improved our results (adjusted R2: 0.916 and 0.710, respectively) significantly over those of the OLS model (adjusted R2: 0.252) and proved how local conditions influence variables. The maps of GWR display how a particular variable is highly important in some areas but less important in other parts of the city.

Tholiya et al. (2022) validated the model based on locations at which parameters were estimated were the locations at which the observations in the dataset had been collected. This allowed predictions for the dependent variable, i.e., water supply (lpcd) and residuals to be computed for determining the goodness of fit of the model. The models were validated and various statistics were calculated as diagnostics that indicate whether the model and its associated parameter values were reasonable. GWR predicted the spatial distribution of water supply ranging from 16.13 to 251.78 lpcd in the newly merged peripheral villages (Figure 3). The GWR model resulted in the spatial distribution of local R2 values, a y-intercept, regression coefficients for slope percent, distance from service reservoirs, and water supply hours for newly merged peripheral villages in Pune city. These parameters (y-intercept and regression coefficients) varied considerably ranging from a negative value to a positive value, representing spatial heterogeneity.
Figure 3

Predicted water supply (lpcd) in the newly merged village in Pune City.

Figure 3

Predicted water supply (lpcd) in the newly merged village in Pune City.

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The results can help decision-makers to make appropriate decisions for future planning to achieve Sustainable Development Goal number 6 (SDG #6), which focuses on achieving universal and equitable access to safe and affordable drinking water for all.

Case 3 – dynamic groundwater resources scenario around Pune city

The study evaluated the groundwater-level time series for the period 2011–2021 for analyzing the trends and variability of groundwater around Pune city. Results revealed that in the pre-monsoon season (Figure 4), a decline in groundwater levels was observed in 61% of 18 monitoring wells on the southern and south-eastern sides, in comparison to rises of 39% of the analyzed wells on the northern and north-western sides; the overall rate of decline was 0.46 m per year. In the post-monsoon season (Figure 5), however, the groundwater level declined by 66% of the analyzed wells on the northern and north-western sides, groundwater level increased in 28% of the wells in the southern and south-eastern sides, and 6% showed no change; the overall declining rate of 0.43 m per year. The rise and decline in water level are primarily in the 0–5 m range. The decline of water level is quite prominent in the village Wagholi, Koregaon Mul, and Moshi, with a decline of more than 4.8 m of water level. Spatial patterns of declining and rising trends indicate a generally coherent occurrence, i.e., occur in clusters. Although groundwater-level fluctuation is more of a location-specific response to recharge and discharge at the initial stage, the persistent tendency progressively spreads to the whole system as aquifers are hydraulically connected and the trends are interdependent.
Figure 4

Pre-monsoon water level fluctuation.

Figure 4

Pre-monsoon water level fluctuation.

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Figure 5

Post-monsoon water level fluctuation.

Figure 5

Post-monsoon water level fluctuation.

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We further calculated the Groundwater Drought Index (GWDI), which is useful for assessing groundwater availability for drinking water supply purposes. The groundwater records for May and October month were used for 10 years for the computation of the mean value. The computation procedure for GWDI is as in Equation (1).
(1)
where GWDIij = Groundwater Drought Index for ith month and jth year. In this study, it is computed for the month of May and October for the year 2021; MGWDi = Mean depth to groundwater table below the surface (in meter). In this study, the mean depth to groundwater has been computed for the period of 10 years 2011–2021. GWDij = Depth to groundwater table in ith month and jth year (in meter). In this study, it is computed for the month of May and Oct for the year 2021. GWDi max = Maximum depth to groundwater table in ith month in available data set for n number of years (in meter). In this study n = 10 years; i = 1,2,3,4,……,12; j = 1, 2,3,……, n; n = total numbers of years for which monthly groundwater records are used.

The classification of GWDI is based on the standard classification (Table 4) provided by the Department of Agriculture and Farmers Welfare, Ministry of Agriculture and Farmers Welfare, Government of India, New Delhi (2016). Results reveal that in both Pre-monsoon and Post-monsoon seasons, 83% of monitoring wells have GWDI above −0.15, which is classified as normal, and 17% of monitoring wells have GWDI between −0.16 and −0.30, classified as mild.

Table 4

GWDI classification

Groundwater Drought Index (GWDI)Groundwater deficit class
>− 0.15 Normal 
−0.16 to −0.30 Mild 
−0.31 to −0.45 Moderate 
−0.46 to −0.60 Severe 
<− 0.60 Extreme 
Groundwater Drought Index (GWDI)Groundwater deficit class
>− 0.15 Normal 
−0.16 to −0.30 Mild 
−0.31 to −0.45 Moderate 
−0.46 to −0.60 Severe 
<− 0.60 Extreme 

Source: Ministry of Agriculture and Farmers Welfare, Government of India, New Delhi (2016).

Results reveal that groundwater resources around Pune city are in the safe zone, with normal GWDI. The area around Pune city shows a long-term water level having shallow water levels (<10.0 mbgl) in pre-monsoon is a favorable location for groundwater development. Therefore, future development of groundwater resources should be taken up with proper care and planning coupled with groundwater augmentation efforts to have longer sustainability. It is recommended that incorporating green spaces into development to maintain higher levels of evapotranspiration and minimize the impacts of urban development and protect riparian zone, preserve forest areas, hills, hilltops, and promote denser development and green neighborhood for water balance to reduce the impacts of urbanization.

The current research provides a broad GIS-centric framework for actionable science, which focuses on real context and facilitates geospatial maps and theoretical and practical knowledge to address various water issues such as water scarcity, water supply distribution, water quality management, and groundwater management (Guan et al. 2012; Greg & Abbas 2017; United Nations 2019; Dangermond 2020). The current research demonstrates the application of the proposed Geospatial Framework in the assessment of water supply services in Pune city (Tholiya & Chaudhary 2022), identifying the determinants of geographical inequalities in domestic water supply (Tholiya et al. 2022), and evaluating dynamic groundwater resources scenarios around Pune city.

In case 1, the study demonstrates the evaluation of water supply services' performance through geospatial techniques in 141 water supply zones in Pune city. The study measures the physical dimension of water security at the intracity level, i.e., the water supply zone level using a set of standard performance parameters that are commonly understood and used by all stakeholders across the country. A uniform set of indicators enables meaningful comparisons with other cities and performance improvement planning and policy implementations. The results represent a broad range of heterogeneity in terms of performance related to water supply services in the entire city. The geospatial maps point out where action and investment to build resilience will be most effective. The results of this geospatial assessment of water supply services can be used and integrated by urban local bodies (ULBs) in their decisions related to policy, resource allocations, and regulatory considerations for water security.

The study illustrates the spatial extent to which a specific policy can be formulated and applied over different spatial extents within the cities to mitigate the issue of water supply. The city- or state-level analysis explored the combined effect and offered a single policy at the city or state level, however, the current study encourages integrating geospatial information at a policy level considering spatial effects of neighboring water supply zones to contribute more holistically to measuring and monitoring the targets and indicators of the SDGs at a technical level. We recognize the importance of geospatial information for sustainable development policymaking as geospatial maps display that a particular policy could be highly important in some areas but less important in other parts of the city. Location-specific data on urban water supply services combined with spatially specific policies can provide the information needed to analyze for local action and catalyze innovation at the micro level, which can be scaled up and replicated to achieve SDG 6, which is about achieving universal and equitable access to safe and affordable water for all.

This study's empirical focus was water-scarce urban areas of developing countries. The study provides value for researchers across the world by giving them a window into the water supply situation in developing countries and possible solutions that can be employed. Similar models based on intracity water supply performance could be helpful in assessing the physical dimension of water security in similar settings.

In case 2, the study has demonstrated statistically significant spatial effects of three variables viz., slope, distance from service reservoirs, and the number of supply hours in predicting water supply in new areas. The policies involving these three variables for achieving equitable access to the water supply would be different in different areas of the city depending upon the relationships whether strong or weak between the dependent variable and each explanatory variable which change geographically. The results in the model can help policymakers and water managers devise regulations specific to an area where water supply is less or there is no supply. In such areas, water conservation or other remediation strategies can be taken into consideration. Results can benefit decision-makers to evaluate how well-existing service reservoirs are currently located concerning water supply and demand. The decision-makers can identify suitable new sites for service reservoirs based on the coefficients associated with distance from service reservoirs in a particular area.

The current research can be used to facilitate a common understanding of the available water supply among diverse stakeholders. It can also be used to identify where action and investment to build water resilience will be most effective, or where deeper analysis or understanding is required. The determinants to predict the domestic water supply identified in this research can be deployed in other metro cities for achieving desired universal and equitable access to safe and affordable water for all. These findings can contribute to municipal corporations and other public and private organizations that need to manage water resources and provide services to people living in rapidly growing cities.

In case 3, the study demonstrates analyzing the trends and variability of groundwater around Pune city. Results revealed that groundwater resources around Pune city are in the safe zone, however, citizens of Pune are worried about the water supply after merging the remaining 23 villages in June 2021 as PMC is already under stress and unable to provide basic facilities to already merged 11 villages in 2017. The merger will help the government to create a land bank. however, there should be a regional plan to preserve green spaces, protect riparian zone, preserve forest areas, hills, and hilltops, and promote denser development and green neighborhood for water balance to reduce the impacts of urbanization in the fringe villages (Megdal & Forrest 2015; Walsh et al. 2016; Houngbo 2018; Wright et al. 2021). PMC should implement a decentralization model as suggested in Geospatial Framework for water supply (Greg & Abbas 2017).

ACWADAM (2019) estimated about 20% of Pune's water needs are met by groundwater as thousands of housing societies have borewells. It is recommended to adopt a comprehensive area-based approach and NBSs (Lundqvist et al. 2003; Brown et al. 2011; Megdal & Forrest 2015; Civitelli & Gruère 2017; Houngbo 2018). The traditional stepwells need to be protected and revived. The PMC has already taken up its Handewadi project to revive a water percolation pond in southeast Pune, which encourages a large public initiative on sustainable water management. Furthermore, the concretization of streams and nullahs should be stopped, which causes floods and reduce groundwater recharge (Houngbo 2018).

The current research provides a broad GIS-centric framework for actionable science, which facilitates geospatial maps, thematic layers, and theoretical and practical knowledge to address various water issues such as water supply distribution, groundwater management, flood management, water quality management, etc. Seeing the holistic view of water availability through a geographic interface provides great insight into the entire region and maintains details of each water zones individually.

The proposed Framework is an engagement platform that rallies communities around issues and initiatives. The Framework can be used to facilitate a common understanding of resilience among diverse stakeholders. It can also be used to identify where there are critical gaps, where action and investment to build resilience will be most effective, or where deeper analysis or understanding is required. The final layer will be the variables and metrics that result in the City Resilience Index. The Framework will enable cities to carry out an objective assessment of their resilience and measure progress against an initial baseline.

We conclude that the proposed Geospatial Framework is a valuable, user-friendly, and self-assessment tool that will enable cities to carry out an objective assessment of their resilience and measure progress against an initial baseline. The current research provides a water-resilient Geospatial Framework to implement global SDG #6 at the local level, which is about achieving universal and equitable access to safe and affordable water for all. The Geospatial Framework enables users, including city officials, urban planners, researchers, residents, and consultants, to access and engage with geospatial data, obtain GIS training and resources, and learn how to use the data effectively to drive action on SDG #6. The Framework can be used for better decision-making and policy intervention and to prepare improvement plans at the city level. This is the future of water security, everyone needs to be geospatially conscious, and GIS people must bring SDGs into practice. The initial setup for the Geospatial Framework has been proposed, which can be expanded with new functionality. We can integrate any layer created by any other geospatial group for water security. PMC can integrate this Geospatial Framework into its existing GIS portal and adopt the environmentally sensitive approach of condensing development and protecting natural areas, riparian areas, open space, and watersheds in peripheral villages in their planning and zoning. If established and implemented, it will be a demonstration of good practice that can be taken up at the national level.

The data used during the study were provided by the Water Supply Department at Pune Municipal Corporation (PMC). Data can be available with the permission of PMC.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.

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