How Do Extreme Climate Events Impact WASH system?

REPORT

Assessing Risks to India’s Drinking Water, Sanitation, and Hygiene Systems from Extreme Climate Events

20 December, 2024 | Sustainable Water

Ekansha Khanduja, Aditya Vikram Jain, Tanuj Goswami, Soorya K K, Upasana Negi, Yashita Singhi, Kushal Pratap Mall, Koushiki Banerjee, Mainak Chatterjee, and Nitin Bassi

Suggested citation: UNICEF and CEEW. 2024. Assessing Risks to India's Drinking Water, Sanitation, and Hygiene Systems from Extreme Climate Events. New Delhi, India: Council on Energy, Environment and Water (CEEW), India.

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Overview

This study, in collaboration with the United Nations Children’s Fund (UNICEF), develops and computes a district-level risk index for India's drinking water, sanitation, and hygiene (WASH) services. It is conducted from an interdisciplinary lens and focuses on risk to the WASH systems in households, educational, and healthcare facilities.

It first shortlists frameworks for conducting a systematic review of the literature; reviews grey and non-grey literature to identify indicators for climate risk assessment of the WASH services in India; shortlist and assign weightage to 50+ indicators using inputs from stakeholders convening following the two steps Delphi approach; and computes the risk index to WASH services for each district of the country using the methodology presented in the Fifth Assessment Report (AR5) framework of the Intergovernmental Panel on Climate Change (IPCC).

Key highlights

About 60 per cent of the districts in the country have very low to moderate risk to their WASH services. The remaining 40 per cent lie in the high or very category of risk. Such districts are spread in nine states of India, including Uttar Pradesh, Tamil Nadu, Bihar, Telangana, Gujarat, Maharashtra, Punjab, Rajasthan, and parts of Karnataka.
Hazards are high to very high in the districts spread across Gujarat, Maharashtra, Uttar Pradesh, Bihar, Odisha, Tamil Nadu, Karnataka, and Rajasthan; exposure in districts of Gujarat, Telangana, Punjab, Uttar Pradesh, Tamil Nadu, and Rajasthan; and vulnerability in districts from Uttar Pradesh, Bihar, Tamil Nadu, Telangana, Madhya Pradesh, Assam, Karnataka, and Maharashtra.
The climate-proofing of the WASH sector can reduce the risk posed by hydromet extremes and aid the attainment of seven sustainable development goals (SDGs) and 10 targets under them.
To build climate resilience of WASH services, state governments need to mainstream granular-level interdisciplinary risk assessments, at least at the district level, by undertaking such exercises regularly, targeting interventions, and making finances available for those in the high to very high-risk category. Assessment and systematically building capacities of government institutions to enable these is crucial.
For more efficient and comprehensive computation of risk to WASH services, there is a need to strengthen the datasets and their monitoring of indicators required for risk assessment; and to set up open-access and interactive dashboards that provide a one-stop solution for information on such assessments.

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Ekansha Khanduja

Programme Associate

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"Building climate resilience of the WASH sector is of utmost importance - WASH services are essential for economic growth, and for human survival and dignity. Climate risk assessments that capture WASH and associated elements at a granular scale can help to formulate more effective and targeted hyperlocal strategies that can ensure the continued and adequate provisioning of WASH services at all times, including during and post disasters.”

Executive summary

Climate change induced extreme events like floods, cyclones, droughts, etc. has been affecting India making it one of the most at risk nations globally (Eckstein, Künzel, and Schäfer 2021). For example, between 2000 and 2019, India experienced an average of 17 flood events per year, making it the second most flood-affected country in the world (CRED and UNDRR 2020). Also, in 2021, about 83 per cent of its population was exposed to droughts (UNCCD 2021). More than 80 per cent of India’s population lives in districts highly vulnerable to extreme hydro-meteorological disasters (Mohanty and Wadhawan 2021). The increasing frequency and intensity of such extreme events is leading to infrastructural and service-delivery failures, especially in the drinking water, sanitation, and hygiene (WASH) sector. Inadequate delivery of WASH services, whether in terms of quantity, quality, or frequency and time of availability, has far-reaching consequences for socio-economic inequities, and this can be directly corroborated through impacts on public health. Estimates by the World Health Organization (WHO) and the Institute of Health Metrics and Evaluation (IHME) for 2016 and 2019 attribute 1.6 million and 1.9 million deaths, respectively, worldwide to unsafe WASH practices (Wolf et al. 2023). Another estimate from 2019 on the burden of diseases attributable to unsafe WASH practices shows that for the year 2019, 69 per cent of diarrhoeal diseases, 14 per cent of acute respiratory infections, 10 per cent of undernutrition-related diseases, and 100 per cent of the burden of soil-transmitted helminthiasis could have been avoided with safe WASH practices (Wolf et al. 2023).

The burden of (climate change–exacerbated) WASH-attributable diseases is borne disproportionately by women, children, elderly people, and impoverished people (WHO 2023b; WaterAid 2017). In 2023, it was estimated that about 1.8 billion people did not have drinking water on their premises, and in two out of three households, women were primarily responsible for water collection (UNICEF and WHO 2023). Improving access to WASH in households, healthcare facilities (HCFs), and educational facilities has been linked to better income, gender equity, lower maternal mortality, and lower child mortality (Richardson et al. 2024; UN Water n.d.; WaterAid 2017).

The attainment of sustainable development goals (SDGs) 6.1 (safe and affordable drinking water for all), 6.2 (adequate and equitable sanitation and hygiene for all), 1.4 (aspects of no poverty), 3.3 and 3.9 (aspects of good health and well-being), 4.a (aspects of quality education), 5 (gender equality and empowerment of women and girls), 11.b and 11.5 (aspects of sustainable cities and communities, including disaster resilience), and 13.1 (aspects of climate action), is contingent on climate proofing of the WASH sector to ensure universal access to adequate WASH services. Estimates show that annualised net benefits worth USD 168 billion can be reaped from 2021 to 2040 by achieving universal access to safely managed water, basic hygiene, and safely managed sanitation (WaterAid 2021).

It is thus imperative for policymakers to prioritise the integration of climate adaptation strategies into WASH planning to safeguard the well-being of India’s most vulnerable populations and to ensure functionality of WASH services during and after hydrometeorological disasters. This will prevent declines in the gains achieved under the Swachh Bharat Mission (SBM) and Jal Jeevan Mission (JJM), India’s two major flagships schemes under WASH. For India, an investment of USD 1 towards adaptation could reduce the annualised average loss from extreme events, slow-onset hazards, and biological hazards by USD 5.5 (UNESCAP 2022). This necessitates identifying underlying risk concerns on a granular level through extensive risk assessments across sectors. This study is an effort in the same direction.

Objectives of risk assessment of the WASH sector in India

The purpose of this study is to develop a comprehensive climate risk assessment framework specifically tailored to the WASH sector in India. By taking into account the effects of acute and chronic climate events at the district level, the framework provides a granular understanding of how the WASH sector is impacted in different regions by climate-related risks. The study thus has the following objectives:

Identification and finalisation of the list of indicators for climate extremes–induced WASH risk in India, with a focus on children, women, and vulnerable groups.
Computation of the district-level climate extremes–induced WASH risk index.
Identification of risk hotspots and the factors driving the same.

Methodology for the development, computation, and representation of the risk index

The definition of risk used in this study is from the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5), whereby risk is defined as a product of hazard, exposure, and vulnerability (adaptive capacity and sensitivity) (Pachauri and Meyer 2014). The methodology consisted broadly of five steps, starting from conducting a systematic literature review (SLR) of 97 studies from the grey and non-grey literature to plotting the GISbased maps, as seen in Figure ES1.

The method used for the SLR was the larger ‘PSAlSAR’ framework, under which the research protocol was defined using the ‘PICOST’ framework (Figure ES1) and reporting of results was done using the ‘PRISMA’ format. The search phrases used in the SLR were such that there was a special focus on women, children, low-income groups, and caste, to align with the aims of the current study.

This helped with identification of the long list of indicators (428 in total), which were further shortlisted to 53 indicators after applying the inclusion and exclusion criteria. Of these 53 indicators, 19 focus on children, women, scheduled castes (SCs), scheduled tribes (STs), people with disabilities, rural agricultural landless households, and distressed migration (refer to indicator numbers 17, 18, 19, 20, 23, 25, 26, 27, 30, 31, 32, 33, 35, 37, 39, 40, 42, 43, and 44 in Table 4). Figure ES2 presents a synthesised version of findings from the various stages using the PRISMA format.

The shortlisted indicators were ranked using the Delphi method in online and offline mode on a scale of relevance ranging from 0 to 4, whereby 0 corresponds to not relevant, 1 to less relevant, 2 to moderately relevant, 3 to highly relevant, and 4 to very highly relevant. Finally, 53 indicators were selected, some of which were added during the Delphi process by the stakeholders. The ranks were utilised for assigning weights to the indicators. Thus, the risk index was computed and GIS maps were prepared for hazard, exposure, and vulnerability sub-indices and the overall risk index to WASH from climate extremes was determined.

Figure ES1 Research methodology used in this study

Figure ES2 PRISMA chart on reporting of SLR steps

Key findings

Figure ES3 shows the climate extremes risk map for the Indian WASH sector. More than 40 per cent of districts in India are either at very high or high risk. Furthermore, it can be seen in Figure ES3 that pockets of very high risk to WASH services are seen in nine states: Uttar Pradesh, Tamil Nadu, Bihar, Telangana, Gujarat, Maharashtra, Punjab, Rajasthan, and parts of Karnataka. The districts in the high-risk category are dispersed among seven states, including Uttar Pradesh, Bihar, Madhya Pradesh, Tamil Nadu, Maharashtra, Telangana, and Gujarat. The insights gained from studying the sub-components used in calculating the risk are as follows:

Hazards: About 40 per cent of districts in the country fall under the very high and high category of hazards. Districts in Gujarat, Maharashtra, Uttar Pradesh, Bihar, Odisha, Tamil Nadu, Karnataka, and Rajasthan fall under the very high category of hazards. Many districts in Uttar Pradesh, Tamil Nadu, Rajasthan, Bihar, and Madhya Pradesh fall under the high category. All the indicators are equally important and pose similar risks to WASH services. The names of the top 5 districts of these states in very high and high hazard category is listed in table ES1 below.
Exposure: More than 40 per cent of districts in the country fall under very high and high categories of exposure. Pockets of very high exposure are seen in Gujarat, Telangana, Punjab, Uttar Pradesh, Tamil Nadu, and Rajasthan. Some districts in Uttar Pradesh, Madhya Pradesh, Tamil Nadu, and Maharashtra fall under the high-exposure category. The top five indicators identified for exposure are water resource availability per capita in the district, the average percentage of storm water drainage to total area of the district, the percentage of forest cover to total area in the district, and the percentage of rural population to the total district population in 2022, as well as the percentage of rural water supply schemes which are less than or equal to five years of age, at the district level. The names of the top 5 districts of these states in very high and high exposure category is listed in table ES1 below.

Figure ES3 Risk map for the WASH sector at the district scale for India

Vulnerability: More than 41 per cent of districts, including those in Uttar Pradesh, Bihar, Tamil Nadu, Telangana, Madhya Pradesh, Assam, Karnataka, and Maharashtra show very high to high levels of vulnerability. In this study, the top five indicators of both sensitivity and adaptive capacity were identified. The top five drivers identified for sensitivity are as follows: altitude (elevation) of the district; percentage of all rural drinking water schemes relying only on surface water in the district; percentage of all rural drinking water schemes relying only on groundwater in the district; percentage of the total SC and ST households in the district with access to at least basic hygiene facilities; and percentage of the total SC and ST households in the district with access to at least basic sanitation facilities.

For adaptive capacity, the top five indicators are the number of functional government health facilities in the district per 1,000 population; the density of automatic weather stations (AWSs) and automatic rain gauge (ARG) stations in the district, per square kilometre; the percentage of rural schools and aanganwadis with availability of drinking water through tap connection, at the district level; the annual average budget expenditure by the government on WASH in rural areas per district per household for the years 2020–23; and the percentage of the total wards/urban local bodies declared as ODF++, in the district. The names of the top 5 districts of these states in very high and high vulnerability category is listed in table ES1 below.

Table ES1: The names of the states and top 5 districts under them (in bracket) lying in very high and high categories of risk, hazard, exposure, and vulnerability

Recommendations

The findings can inform the development of hyperlocal strategies that can minimise impacts and avert or reduce loss and damage to WASH systems and services during disasters. We make the following recommendations to ensure the same:

Set up data dashboards to facilitate proper use of risk assessments: Open-access and interactive dashboards that provide a one-stop solution for information on such assessments can help in designing more efficient and comprehensive risk-informed interventions to make WASH climate resilient. These dashboards can be set up as a joint effort between the Ministry of Jal Shakti (MoJS) and the National Disaster Management Authority (NDMA) at the national level, showing an aggregate of state level similar assessments. At the state level, such dashboards can be hosted by the water supply or public health and engineering department (PHED), with relevant editing rights to all the departments from whom input for such risk assessments is sought.
Strengthen existing datasets to enable such assessments: The datasets that can enable a more nuanced and efficient risk assessment of the sector need to be harmonised and should focus on aspects that are necessary for the holistic assessment of any indicator. Furthermore, since aspects of WASH are linked to the right to life as mandated in the Constitution of India, all datasets should be freely available in the public domain at an adequate scale.
Mainstream granular-level, interdisciplinary assessments for climate extremes– induced risks in the WASH sector: There is a need for the government to encourage risk assessments of the WASH sector to climate extremes at the sub-national (district and block) level and through an interdisciplinary lens. This is necessary because different aspects of WASH are governed by different ministries and departments (for instance, women and child development, rural development, panchayati raj, water supply and sanitation, groundwater), and the variation in the natural factors that influence WASH can only be captured at finer spatial levels. Therefore, the government should use comprehensive risk analysis frameworks that can capture these interdisciplinary nuances, such as those deployed in this study
Assess and build capacities of the government institutions to enable such assessments: There is a need to assess and systematically build the capacities of government institutions to make such risk-informed assessments. These would include capacities related to data management, monitoring and impact evaluation of existing WASH systems and services, innovative and participatory planning and implementation of new WASH systems, collaboration and coordination for operation and maintenance of WASH services, and other related technical aspects such as climate science and risk, and disaster management (Abraham et al. 2024). The participatory planning process should be guided by principles of inclusivity, such that the needs of women, children, and other vulnerable or under-represented groups are realised and incorporated.
Risk assessment–based prioritisation and financing of WASH schemes: In order to climate proof the WASH sector in the country, it is crucial to formulate budgets and allocate resources based on the identification of climate change hotspots. Identifying specific vulnerabilities and adaptation capacity gaps at the district or local level can inform priority setting for judicious allocation of financial resources. Such assessments at the state level should be a joint effort between the water supply department/public health and engineering department (PHED) and the state disaster management authority (SDMA), with the former leading it. Other state departments should be consulted for inputs at various stages of the assessment.