Assessing the correlation between interannual climate Variability and land cover change, and flow regime of sub-catchments, and their impact on communities of the Mara river basin, Kenya
MNGUBE, FREDRICK MHINA
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Climate variability and Land Cover Changes (LC) have negative consequences on watershed management. Whereas, the role of climate variability on land cover changes and stream flow regimes have affected people’s livelohoods and caused resources use conflicts in the Mara river basin, little is known of their impact at the sub-catchment level where majority of communities live, hence the need to fill this gap. The main objective of this study was to determine correlation between inter-annual climate variability, land cover changes and flow regimes and socioeconomic status of communities of the Mara River Sub-catchments, Kenya. The specific objectives were to; determine the correlation between rainfall and temperature variability and LC in Amala, Nyangores, Talek and Sand river sub-catchments of the Mara River tributaries, Kenya; evaluate the effects of land cover changes on stream flow of Amala and Nyangores tributaries of the Mara River, Kenya; forecast future changes in LC for the Amala, Nyangores, Talek and Sand River sub-catchments of the Mara River, Kenya; assess the effects of land cover changes on the socio-economic status on the communities of Amala, Nyangores, Talek and Sand River subcatchments of the Mara River, Kenya. Empirical and cross-sctional designs were used. Rainfall and temperature, Landsat images for LC and the Normalized Difference Vegetation Index (NDVI) and soil data were obtained from websites. The socio-economic data and focused Group Discussion (FGD) were collected using questionnaire from sample size of 422 adults derived from target population of 1,000,000. Mann-Kendall test was used to establish trends in climate, coefficient of determination used to measure the correlation between climate variables, LC changes and stream flows. Markov Chain model used to forecast future LC. A generalized linear model was used to correlate drivers of LC and stream flows. Results indicated that LC classes correlated with temperature and rainfall in different ranges (r = 0.23 to 0.99). Temperature showed strong correlation with built-up areas (r = 0.99), and weaker with grasslands (R2 = 0.23). Rainfall showed positive correlation with bare land (R2 = 0.98) and weaker with grasslands (R2 = 0.02). Annual flow ranged between R2 = 0.07 to 0.99). The strongest correlation was observed in built up areas (R2 = 0.99) and the weakest in grassland land (R2 = 0.07). Change detection matrix showed significant but varying degrees changes by 2027. Majority of the household (89.7%) reported having noticed changes in LC in the past 30 years, unpredictable rainy pattern and increase in temperature were the main drivers of LC and stream flows. FGD participants observed irregular rainfall patterns and increase in temperature, and were supportive of environmental protective measures to reverse negative land cover changes. There was a correlation between temperature and rainfall and land cover change. LC dynamics affected mean annual water flows in Nyangores and Amala. The simulated results indicated there were high water flows in built areas and lowest in grasslands. Future LC projection showed significant increase in grassland and reduced cropland. Types of trees planted, irregular rain pattern and increased temperature were the the drivers of LC change. The study recommends adaptation to temperature and rainfall variability; a multidisciplinary approach towards the hydrologic processes that maintain ecological health and communities’ livelihood; suitable land use practices to improve future land cover; and an integrated plan to address the drivers of LC changes.