Abstract:
In Sub-Saharan Africa (SSA), about 95% of agriculture is mainly rain-fed, which means that the majority of the population depends on rain fed agriculture for their survival. In many countries of SSA growth of the agricultural sector has been reported to be low in the past decade, despite the fact that this sector is recognized as priority area in an effort to reduce poverty. This low growth is a result of poor farming practices as well as the effects of climate variability.Although the situation appears to be desperate, all is not lost as adoption of rain water harvesting (RWH) technologies might serve as a remedy, since they have shown promising potential for upgrading rain fed agriculture. However, most of the existing technologies in these areas have low performance rates, resulting in low adoption rates. It is against this background that this study was conducted with aim to the already existing knowledge base, which is paramount to formulating sustainable water and land resource management strategies for water scarce river basins in SSA. Enhancing water productivity may lead to improved food security and contribute to on-going global dialogue on water for food and environment with the aim of to meet the already stipulated Millennium Development Goals (MDGs).To achieve this goal, the study applied a rapid GIS based analytical tool to access suitability of various water system innovations (WSIs), such as rainwater harvesting technologies capable of improving agricultural productivity in these dry areas of SSA. Remote sensing technology was used to extract most of the data (from different remote multi-sensor missions) required for the various decision support tools (DSTs) applied during this study and this was complemented with the existing rich indigenous knowledge.In order to promote the uptake of these innovative water management technologies on larger scale, particularly amongst smallholder farmers, spatial multi criteria evaluation process (SMCE) was applied, a decision support tool to identify suitable areas for implementing appropriate RWH tools in the two basins: The Upper Ewaso Ng’iro North in Kenya and Pangani River Basin in Tanzania. A weighted linear combination procedure, which allowed for full tradeoffs amongst various factors influencing suitability for RWH was applied in the data rich Ewaso Ng’iro Basin. The results obtained were then transferred to a data scarce Makanya catchment located in the upstream of Pangani Basin in Tanzania. Suitability maps depicting suitable areas of RWH were produced, with attributes serving as indicators for targeted RWH interventions. The information generated can then be used to raise awareness and guide policy decisions on the contribution of RWH in meeting the MDGs.
