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An earth observation- and integrated assessment (EOIA) approach to the governance of the Lake Naivasha basin, Kenya

Project duration: 2010 - 2014

Universities

Egerton University
University of Nairobi
University of Twente


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The horticultural industry around Naivasha in Kenya is seen as an example of a successful economic growth path to be copied by other African countries. Export of flowers sustains an economy that previously suffered from low employment and low income. However, the environmental price of fast economic growth is hefty: the rapidly growing population, large water abstractions for irrigation, changing land use, and inflow from agrochemicals, put the ecosystem under pressure.

We focus on how Earth Observation (EO) and derivative geo-information may help to overcome societal clashes in a collaborative stakeholder setting within Kenyan society. The innovation we apply is to couple EO via Integrated Assessment. EO provides such detailed data that, in connection with standard secondary data, we are able to perform the physical and social analyses necessary to allow stakeholders to deliberate about their common future. For urban areas socio-economic information estimation now covers population estimation, employment estimation, and GDP estimation. The consequent social analyses now deal with migration patterns, land use and land cover change, and the establishment of quality-of-life indicators (Wu 2007). The benefit for developing countries is a cost-effective way of data collection and processing, because in comparison with census data, EO data are available on an almost daily basis. The scientific tool we apply is a system description based on an Integrated Assessment (IA). IA aims to integrate knowledge over a range of relevant disciplines, and to provide new information how complex real-world systems might behave, thus enabling decision-making. Cross-sectoral implications that might be missed in more traditional assessments can be explicitly explored in ways that are meaningful to stakeholders. Key decision variables as output of this system analysis are livelihood and employment as description of efficiency and equity characteristics of the socio-economic structure upstream and downstream; a differentiation is made in order to reckon with gender. Secondly, water quality and water quantity are assessed as a characterisation of Lake Naivasha. Finally, habitat and minimum viable population are determined as portrayal of the ecosystem. These final decision variables feed into a stakeholder process as has been already in the pre-proposal phase.



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Contact

Prof. dr. A. (Anne) van der Veen
project leader Netherlands
Email: veen@itc.nl
Phone: +31 (0)53 487 44 84