Moving towards a year-round picture of household rainwater harvesting by combining climate and household survey data

A modelling approach to estimate the seasonal household variation in harvested rainwater availability to gap-fill the data and knowledge for SDG monitoring, spatially targeted field surveys to assess harvesting systems, and demand for potential system upgrades.
Published in Sustainability
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During the survey campaign for a research project looking at the drinking-water contamination risks in rural western Kenya, we found rainwater harvesting systems widespread in all study villages. Many residents consider rainwater a gift from the God and thus the safest source of drinking-water. Most households harvest rainwater from roofs or directly using simple 20 litre jerrycans and/or pails, storing the excess for later use. Among the different types of rainwater harvesting and storage methods, what impressed us most was a ‘hybrid’ system that had intakes for both rainwater and piped water, so households could switch water sources in response dry spells or breakdowns in the piped system. The obvious value households placed on rainwater encouraged us to study it further.

Examples of rainwater harvesting systems in Siaya, Kenya

Poor rural households in countries facing severe water crisis such as Kenya often harvest rainwater (when available) in preference to other drinking-water sources because of its perceived quality, since it can be harvested free of charge, and does not have the same potential to cause community conflict as some other water sources. However, a big issue is its intermittent availability, which may force households to switch to other sources such as surface waters that are potentially less safe.

Water being available when needed is one of three key criteria identifying safely managed drinking water services, which form the indicator for Sustainable Development Goal (SDG) target 6.1 (universal and equitable access to safe, affordable drinking-water). Drinking-water availability can often be a broad topic, encompassing the quantity of water supplied alongside water supply continuity. Since many poor, rural populations depend on rainwater harvesting for drinking-water, we look specifically in this study at harvested rainwater reliability, meaning the proportion of days per year when water demand is fully met. At any one time, the national household surveys currently used for SDG monitoring provide a snapshot of rainwater use. For example, Malaria Indicator Survey fieldwork from November to December 2020 (1) showed 9.8 percent of rural Kenyan households used rainwater as their main drinking-water source at that time. However, there would be real benefits from moinge from this snapshot of rainwater harvesting at a single time-point to estimating rainwater reliability – how many days throughout the year that rainwater meets demand. this would not only enhance SDG monitoring, but could also help target follow-up fieldwork to assess harvesting systems and household demand for harvesting system upgrades.

In this context, our Kenyan case study estimates rainwater harvesting reliability by combining household survey and gridded precipitation data via a mixed effects modelling framework. Our OneHealthWater project team included members from the Kenya Medical Research Institute (KEMRI) who also led a Population-Based Animal Syndromic Surveillance (PBASS) project, which gave us the opportunity to draw on data through two local-scale household surveys. The household surveys used standard questions found in Demographic and Health Surveys (key to SDG6.1 monitoring), but supplemented these with two additional questions concerning the source of household stored drinking-water at the time of interview. Applying this approach to these data resources, we were able to estimate rainwater harvesting reliability with good predictive performance. This suggests that the addition of these two extended questions to Demographic and Health Surveys could facilitate rainwater reliability estimation at national level. In generating these estimates, we also found that harvested rainwater reliability varies markedly between households with and without alternative improved water sources to fall back on. This local-scale study thus demonstrates an alternative means of estimating rainwater harvesting system reliability for domestic use, which could also help in planning the seasonal timing of household survey implementation or interpreting past household survey findings in the light of likely seasonal household rainwater harvesting behaviours.

The OneHealthWater project team discuss a rainwater harvesting system

This research was a contribution to the OneHealthWater project, which received funding from the UK Medical Research Council/Department for International Development via a Global Challenges Research Fund foundation grant (Ref.: MR/P024920/1). The project team comprises two UK (University of Southampton and University of Brighton) and two Kenyan (VIRED International and KEMRI) research organisations with expertise in water resources, public health and geospatial data.

  1. Division of National Malaria Programme, Kenya National Bureau of Statistics, Icf. Kenya malaria indicator survey 2020. Nairobi, Kenya and Rockville, Maryland, USA: DNMP/ICF; 2021.

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