Abstract:
For the sustainable governance of river basins a wide range of variables from natural and human subsystems may need to be studied as the effectiveness of governance can be judged from a wide range of perspectives. Governance of natural resources is affected by processes that are taking place across various scales and by interventions from multiple levels of organization. Especially when there is competition over scarce resources among stakeholders and interests there is a need for Integrated Assessment (IA). An IA may result in indicators for sustainable governance through the integration over scientific disciplines in ways and at temporal and spatial scales meaningful to stakeholders. This implies that knowledge from different scientific disciplines, focusing on different subsystems, should be used for incorporating interdependencies that are of critical importance for overall system dynamics. The design of appropriate model structures (e.g. extent, resolution) depends on the spatial and temporal resolutions of the available data, levels at which process interactions take place and the desired level of output presentation for stakeholders. The quality of an Integrated Assessment approach relies on extensive datasets. In this regard, this study explores the added value of using detailed spatial information derived from Earth Observation (EO) time-series. As an example the Lake Naivasha basin (Kenya) is studied. In this study knowledge gaps are identified and discussed. The scientific disciplines covered in this study are hydrology, limnology, ecology, socioeconomics and governance. Finally a framework for IA is assembled around a proposed set of sustainability indicators for the Lake Naivasha basin.
