From Impacts to Implementation: A Survey of Sand Dams in Sub-Saharan Africa

Jessica A Eisma, Purdue University

Abstract

International development projects are a massive business, with billions invested annually in the Global South. However, such projects have an unacceptably long record of high failure rates. The problem perpetuates, in part, due to the success factors by which international development projects are judged. Often, projects are assessed on the basis of donor-identified priorities that are not aligned with local impacts. One such international development project involves the construction of small-scale water harvesting structures known as sand dams. Non-governmental organizations (NGOs) continue to raise sufficient funds to build thousands of sand dams across sub-Saharan Africa, and yet 50% of sand dams are estimated to be non-functioning. Sand dams are small, reinforced concrete dams built across an impermeable streambed. Over time, sand settles behind the dam, creating an upstream sand reservoir that fills with rainwater and surface runoff. The sand helps filter the water, protects it from evapotranspiration, and can provide water to the local community for domestic and agricultural use during the dry season. Sand dams often fail due to poor construction, inadequate siting, and siltation. This dissertation explores methodologies for studying the regional and local impacts of sand dams and investigates the feasibility of developing model-based site selection guidelines for sand dams. Three objectives of this study are: (1) to develop a methodology to assess the ability of sand dams in improving the overall water availability in the region; (2) to examine claims made by non-scientific bodies about sand dam impacts by investigating how diverse sand dams influence macroinvertebrate habitat, vegetation, erosion, and local water availability; and (3) to create guidelines for siting new sand dams based on a fully integrated surface and groundwater flow model. For the first objective, two multiple regression models are developed to compare (1) water storage and (2) vegetation in an area with a high density of sand dams, termed the sand dam counties (SDC), to those in a control area. The models analyze remotely sensed datasets to assess whether evidence exists of significantly increased storage in the SDC relative to the control area. The results show that the remotely sensed water storage data is unable to consistently detect higher levels of water storage in the SDC. This is likely due to the low resolution of the dataset combined with the small magnitude of sand dams’ impact on regional water storage. The results of the vegetation model show that the sand dams have a consistent, positive impact on vegetation within the SDC relative to the control area. Because vegetation health and cover is often correlated with groundwater levels, these results likely indicate that the sand dams are also increasing local groundwater levels. Overall, this study shows that remotely sensed dataset can provide a useful basis to assess the impact of international development projects, particularly those that involve the natural environment. For the second objective, data relating to macroinvertebrates, vegetation, erosion, and water table elevations at three sand dams were collected and analyzed during a year-long field study in Tanzania.

Degree

Ph.D.

Advisors

Merwade, Purdue University.

Subject Area

Hydrologic sciences|Meteorology|Soil sciences|Sub Saharan Africa Studies|Water Resources Management

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