Linking Scientific Research to Development Agenda: The Case of a Hydrometeorological Project in the Notwane Catchment, Botswana

Linking Scientific Research to Development Agenda: The Case of a Hydrometeorological Project in the Notwane Catchment, Botswana

P. K. Kenabatho (University of Botswana, Botswana), B. P. Parida (University of Botswana, Botswana), B. Matlhodi (University of Botswana, Botswana) and D.B. Moalafhi (University of Botswana, Botswana)
Copyright: © 2018 |Pages: 18
DOI: 10.4018/978-1-5225-3440-2.ch023
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In recent years, the scientific community has been urged to undertake research that can immediately have impact on development issues, including national policies, strategies, and people's livelihoods, among others. While this is a fair call from decision makers, it should also be realized that science by nature is about innovation, discovery and knowledge generation. In this context, there is need for a balance between long term scientific investigations and short term scientific applications. With regard to the former, researchers spend years investigating (or need data of sufficient record length) to provide sound and reliable solutions to a problem at hand while in the latter, it is possible to reach a solution with few selected analyses. In all cases, it is advisable that researchers, where possible should link their studies to topical development issues in their case studies. In this paper, we use a hydrometeorological project in the Notwane catchment, Botswana, to show the importance of linking research to development agenda for mutual benefit of researchers and policy makers. The results indicate that some key development issues are being addressed by the Project and the scope exists to improve the impact of the project.
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The Project

The project was set up to address some of the major challenges in semi-arid areas, being (i) high spatial and temporal variability of rainfall and hydrological processes, (ii) the inherent non-linearity of response between rainfall and runoff, and (iii) lack of instrumentation of good spatial coverage to capture this high spatial variability (Pilgrim et al, 1988, Wheater et al, 2008). Through these, there arises uncertainty when spatial rainfall estimates are made from limited observations particularly when they are to be used in rainfall-runoff modeling at catchment scales (Mcintyre and Al-Qurashi, 2009). This particular problem is well documented for catchments within southern Africa (Parida et al, 2006, Hughes et al., 2010), and in the catchment under study (Parida et al., 2006).

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