Analysis of spatio-temporal land cover changes for hydrological impact assessment within the Nyando River Basin of Kenya

Abstract

The spatio-temporal changes in the land cover states of the Nyando Basin were investigated for auxiliary hydrological impact assessment. The predominant land cover types whose conversions could influence the hydrological response of the region were selected. Six Landsat images for 1973, 1986, and 2000 were processed to discern the changes based on a methodology that employs a hybrid of supervised and unsupervised classification schemes. The accuracy of the classifications were assessed using reference datasets processed in a GIS with the help of ground-based information obtained through participatory mapping techniques. To assess the possible hydrological effect of the detected changes during storm events, a physically based lumped approach for infiltration loss estimation was employed within five selected sub-basins. The results obtained indicated that forests in the basin declined by 20% while agricultural fields expanded by 16% during the entire period of study. Apparent from the land cover conversion matrices was that the majority of the forest decline was a consequence of agricultural expansion. The model results revealed decreased infiltration amounts by between 6% and 15%. The headwater regions with the vast deforestation were noted to be more vulnerable to the land cover change effects. Despite the haphazard land use patterns and uncertainties related to poor data quality for environmental monitoring and assessment, the study exposed the vast degradation and hence the need for sustainable land use planning for enhanced catchment management purposes.

Impacts of Land Cover Change Scenarios on Storm Runoff Generation: A Basis for Management of the Nyando Basin, Kenya

“…A widespread problem identified in the region was the vast land cover degradation within the riparian upstream catchments important in the sustainability of the existing water resources. The Nyando River Basin (NRB) with its headwaters in the endangered Mau Forest Complex (MFC) region in particular was seen to epitomize the degradation because of its physical susceptibility, coupled with the existence of poor land and water management strategies (Krhoda, ; Olang et al ., ). Previous studies of the NRB involving change detection from time‐series Landsat satellite images have revealed varying proportions of spatio‐temporal changes.…”

“…The lower parts of the basin, however, exhibited subtle land cover fluctuations that varied between agriculture and grasslands on seasonal basis. From the land cover conversion patterns, it is concluded the basin was more likely to be converted into an agricultural area in the near future if the land cover change trends continued unabated (Rambaldi et al ., ; Olang et al ., ). Further research studies using hydrological models have also revealed the changing response of the Nyando basin, particularly during storm events of the long rainy season (LRS) (Opere and Okello, ; Olang and Fürst, ).…”

Land Use Change Impact on Flooding Areas: The Case Study of Cervaro Basin (Italy)

“…Land cover features are part of the ecosystem equilibrium, and any environmental changes that affect them is worth studying [1]-particularly due to the increasing expansion of urban areas which causes permeable land reduction and increased flooding [2,3]. It is widely accepted that the magnitude and frequency of floods is currently increasing [4].…”

Rating curve uncertainty and change detection in discharge time series: case study with 44‐year historic data from the Nyangores River, Kenya

“…Two headwater tributaries of the Mara, the Nyangores and Amala Rivers, descend from the Mau escarpment, one of Kenya's five so‐called water towers. The Mau Forest, which crowns the escarpment, has been subject to an alarming rate of deforestation in recent years (Baldyga et al ., ) that appears to have affected the hydrology of a number of basins (Krhoda ; Raini, ; Olang et al ., ), including possibly the Mara. Historic hydrometeorological conditions in the Nyangores and Amala basins have been studied (Melesse et al ., ), but without consideration of temporal change and variability.…”