Data resolution effects onwater resource planning andmanagement : The Kisumu – Lake Victoria region study

Abstract: In the Kisumu District, Kenya, unreliable rainfall pattern has been identified as one of the main causes for poverty in rural areas. The negative effects of such unreliable patterns could be mitigated through improved water resource management and planning. However, estimates of current (and future) water availability will likely differ depending on whether managers draw upon data gathered at a local-scale or regional-scale. This is particularly important in developing regions where, due to lack of data availability, managers are often limited in their choice of data resolution. This study investigates the potential effect of spatial resolution of data on water management and planning by comparing hydro-climatic trends in local-scale data with trends in regional-scale data. The influence of adopting local-scale versus regional-scale data is further demonstrated by estimate the storage requirements of proposed irrigation ponds for farmers in the Orongo village of the Kisumu District located in Kenya, Africa. Results indicate a low correlation between local and regional hydro-climatic trends. Data spatial scale directly influences water resources management leading to a 300% difference in estimated storage requirement for the average farmer.