Optimizing Rural Drinking Water Supply Infrastructure to Account for Spatial Variations in Groundwater Quality and Household Welfare in Coastal Bangladesh

Abstract

The 2030 Agenda for Sustainable Development, as articulated in Target 6.1, aims to achieve universal and equitable access to safe and affordable drinking water, using the proportion of population using safely managed drinking water services as the associated indicator (UN, 2015). Despite the progress in increasing "access" to technologically improved sources as part of the Millennium Development Goals (MDG), as of 2017, over 2 billion people lack safely managed drinking water and 785 million do not even have "basic" services (WHO/UNICEF, 2019). Progress to improve water security is most challenging in contexts where financial and institutional resources are limited and where water resources are threatened by chronic (e.g., groundwater contamination) and acute (e.g., floods and cyclones) threats. Bangladesh typifies these chronic and idiosyncratic water security risks, particularly in the coastal region, where around 20 million people live precarious lives with uncertain futures (M. A. Hoque et al., 2016;Shammi et al., 2017).The financial resources that are available for investment of water supplies are inevitably scarce, so governments and development organizations face difficult prioritization problems. Should they adopt a utilitarian approach to maximize for the greater good for the greatest number of people or a Rawlsian social justice approach which prioritizes the "most in need" (Sen, 1974)? The question is complicated by the interaction between public works to provide water supplies and private actors who are willing and able to pay to satisfy their own water needs. In this case, actions by the state may actually crowd out private investments. These competing policy choices are not irreconcilable but present a sequencing and prioritization problem compounded by identification and measurement issues. Without information on the welfare or infrastructure distribution, information asymmetries can lead to perverse outcomes in the spatial distribution of infrastructure, as has been documented in arsenic affected areas in Bangladesh (van Geen et al., 2016). New

A Review and Analysis of Water Research, Development, and Management in Bangladesh

“…As per this study, the development of a community-based model is needed to solve drinking water problems, which should incorporate all levels of governments, non-government organizations (NGOs), and community people. Roman et al [20] investigated investment scenarios to provide safe drinking water in coastal areas of Bangladesh, which have been badly affected by a high level of salinity. They compared several options, including deep tube wells, desalination plants, and piped systems, and the results of this study can inform investment in the water supply in the coastal region of Bangladesh.…”

Socio-spatial and seasonal dynamics of small, private water service providers in Khulna district, Bangladesh

“…Grey and Sadoff (2007) argue that 'difficult hydrologies', caused by the unavailability or contamination of water resources, require higher infrastructure investments to transport or treat water, which in turn entails strong institutions for cost recovery and service reliability. Public investments, seeking to achieve 'greatest good for the greater number', are channelled towards areas with lower environmental risks, often leaving behind those in 'greater need' (Roman et al, 2021). This unmet need, coupled with negligible regulatory barriers, creates a fertile ground for private WSPs to flourish.…”

Piped water revenue and investment strategies in rural Africa

“…Decision frameworks can support planners as they optimise water infrastructure investments for future social and environmental conditions (Murgatroyd andHall 2021, Roman et al 2021) but require a robust empirical basis to minimise uncertainty. Existing evidence of financial performance in the water supply sector is biased to urban piped systems (Andres et al 2019) with one example of rural cost recovery across multiple countries (McNicholl et al 2019).…”