Probabilistic Impact Assessment of Domestic Rainwater Harvesting in Urban Slums: West Africa Case Study
Abstract
Urban populations now exceed rural populations worldwide, creating unique challenges in providing basic services, especially in developing countries where informal or illegal settlements grow in peri-urban areas. West Africa is an acute example of the problems created by rapid urban growth, with high levels of urban poverty and low water and sanitation access rates. Although considerable effort has been made in providing improved water access and urban services to slum communities, research indicates that clean water access rates are not keeping up with urbanization rates in several areas of the world and that rapidly growing slum communities are beginning to overwhelm many prior water improvements projects. In the face of these challenges, domestic rainwater harvesting is proposed as a technologically appropriate and economically viable option for enhancing water supplies to urban slum households. However, assessing the reliability, potential health impacts, and overall cost-effectiveness of these systems on a regional level is difficult for several reasons. First, long daily rainfall records are not readily available in much of the developing world, including many regions of sub-Saharan Africa. Second, significant uncertainties exist in the relevant cost, water use, and health data. Third, to estimate the potential future impacts at the regional scale, various global change scenarios should be investigated. Finally, in addition to these technical challenges, there is also a need to develop relatively simple and transparent assessment methods for informing policy makers. A procedure is presented for assessment of domestic rainwater harvesting systems using a combination of scenario, sensitivity, and trade-off analyses. Using data from West Africa, simple stochastic weather models are developed to generate rainfall sequences for the region, which are then used to estimate the reliability of providing a range of per capita water supplies. Next, a procedure is proposed for quantifying the health impacts of improved water supplies, and sensitivity analysis of cost and health data provides an indication of cost- effectiveness. Climate change impacts are assessed via weather model parameter adjustment according to statistical downscaling of general circulation model output. Future work involving the interpolation of model parameters to ungaged sites, incorporation of additional global change scenarios (e.g., population, emissions), and extension of the procedure to a full Monte Carlo analysis will be discussed as time allows.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2007
- Bibcode:
- 2007AGUFM.H21G0822C
- Keywords:
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- 1635 Oceans (1616;
- 3305;
- 4215;
- 4513);
- 1807 Climate impacts;
- 1854 Precipitation (3354);
- 1869 Stochastic hydrology;
- 1884 Water supply