Spatio-temporal modeling of lake’s ecosystem and dynamism in response to changing environment. A case study of L. Olbolossat in Kenya

Abstract

Abstract Lakes’ ecosystems are vulnerable to environmental dynamisms prompted by natural processes and anthropogenic activities happening in catchment areas. The present study aimed at modeling the response of Lake Olbolossat ecosystem in Kenya to changing environment between 1992 to 2022, and its future scenario in 2030. The study used temperature, stream power index, rainfall, land use land cover, normalized difference vegetation index, slope and topographic wetness index as datasets. A GIS-ensemble modeling approach coupling the analytical hierarchical process and principal component analysis was used to simulate the lake’s extents between 1992–2022. Cellular Automata-Markov chain analysis was used to predict the lake extent in 2030. The results revealed that between 1992–2002, the lake extent shrunk by about 18%; between 2002–2012, the lake extent increased by about 13.58%; and between 2012–2022, the lake expanded by about 26%. The spatial temporal changes exhibited that the lake has been changing haphazardly depending on prevailing climatic conditions and anthropogenic activities. The comparison between the simulated and predicted lake extents in 2022 produced Kno, Klocation, KlocationStrata, Kstandard, and average index values of 0.80, 0.81, 1.0, 0.74, and 0.84, respectively, which ascertained good performance of generated prediction probability matrices. The predicted results exhibited there would be an increase in lake extent by about 13% by the year 2030. The research findings provide baseline information which would assist in protecting and conserving the lake Olbolossat ecosystem which is very crucial in promoting tourism activities and provision of water for domestic and commercial use in the region.