Part 2: Is data informing decisions in rural water security?

Helping CSOs use data well to diagnose water challenges in different geographies

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By Anjali Neelakantan

This is the second post of the Rural Water series that documents the journey of CSEI’s Food Futures Initiative so far. If you would like to collaborate with us, please reach out to the initiative lead, Anjali: anjali.neelakantan@atree.org.

Part 1: How do we make a dent in rural water security? discussed the problems in rural water security, especially focussing on the data use challenge.

Our interviews with 21 CSOs and 11 philanthropic organisations on implementation, evaluation and challenges of rural water security programmes, brought out one major insight. It was unclear how the data being collected was being used to inform their decisions.

Should water security plans focus on making more water available or using it efficiently?

To find out, we reached out to the CSOs for their water security plans. CSOs prepare water security plans as a part of a larger programme implementation. These plans typically have details on the water status of the programme region, mapping the water demand against water supply (water balance estimate) and using that to determine what interventions should be implemented.

We reviewed around 25 water security plans and made an interesting discovery.

Most of these programmes focus on supply-side interventions i.e., making more water available, even in areas where there is a water deficiency. In drier parts of India, most of the available water is already being used. We believe that water security plans should also focus on demand-side interventions i.e., making sure that available water is used efficiently and equitably. More of our insights are published in this research brief: Insights from the Review of Water Security Plans.

How are CSOs currently using data to estimate water security?

One of the main ways CSOs use data is to arrive at a water budget — an accounting tool used to estimate water availability and use. Often this is part of a donor or government mandate rather than a demand from the community.

The Atal Bhujal Yojana now requires gram panchayats to prepare water budgets as part of a rural water security planning process. The water budget accounts for all the surface and groundwater resources and identifies current and future needs. But coming up with these requires high technical expertise in every gram panchayat. As a result many of these water budgets are not being made scientifically. Here’s why we think digital tools could address this expertise bottleneck to some extent. Or watch this video to find out more:

Need for Digital Tools in Rural Water Security

To understand the on-ground challenges to creating water budgets, we decided to listen to CSOs. In July 2021, we invited 32 CSOs, donors and private sector enterprises creating or interested in creating water budgets to a Listening Circle on ‘Creating Data-Driven Water Budgets’.

Key takeaways from the Listening Circle

  1. Simplicity over precision: There is a need to look at different geographies and their water experiences and study how solutions can be replicated across regions. CSOs are not interested in complicated, high precision water budgeting tools. They need simple tools to estimate the water balance that local communities can use.
  2. Behaviour change: Even when we know that there is a water deficit it does not mean individual farmers will change their behaviour. There is a need to invest in research around understanding incentives for changing farmer behaviours around cropping choices and water usage.
  3. Implementing impact evaluation: Are interventions having the desired impact? CSOs raised doubts about even the efficacy of measures like switching to drip irrigation. There is a need to implement impact evaluation to understand if water interventions are achieving the desired impact.

Read more about our Listening Circle takeaways in this blogpost.

How do we help CSOs access and use the data more effectively to diagnose water challenges in different geographies?

We wanted to address the “expertise bottleneck” and the need for simple tools. As a first step, we set out to create a compendium of existing digital tools used in data collection, water budgeting and intervention planning. Alongside the review of water security plans, we also began developing a primer on water balance estimation in two mill watersheds in Handenahalli and Aralumallige, with the belief that these scoping exercises would help us clarify our approach and solutions.

Simultaneously, we worked on developing a tool (a QGIS plugin) to ease water security planning and water balance estimation. This tool allows users to view different map layers — administrative boundaries, land use/land cover, elevation, rainfall and soil related indicators — in one place. And also helps estimate the water balance for a village or watershed. Right now, we are piloting the tool with early users. Sign up here to be an early user.

We hope that as the tool develops, we will be able to pinpoint a location on the map of India and identify the water-related challenges of the district and provide specific solutions that will work in that district.

What impact could this work have?

The Food Futures Initiative at CSEI aims to transform data into usable knowledge in the form of tools, training materials and frameworks. By 2030, our goal is to help boost water security and restore degraded land to improve 150,000 livelihoods in 2000 villages.

To achieve that goal, we want to sharply define the problems in the water sector and understand what solutions work best. We will create digital tools to make data available and accessible. These tools will do away with the need for technical expertise in implementing organisations.

The impact we hope to create is two fold. As a result of our work, philanthropic organisations will be able to redirect investments and make data-driven decisions on which interventions to scale. CSOs will be able to design and implement their programmes better, creating better outcomes. We will move towards a circular approach where learnings from the past feed into future work.

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