The effects of conceptual land cover change scenarios on the generation of storm runoffs were evaluated in the Nyando Basin. The spatial scenarios represented alternatives that vary between full deforestation and reforestation. Synthetic storm events of depths 40, 60 and 80 mm were formulated according to the rainfall patterns and assumed to have durations corresponding to the runoff times of concentration. The Natural Resource Conservation Service–Curve Number model was used to generate runoff volumes within the sub‐catchments, which were subsequently routed downstream to obtain effects in the whole basin. The simulated land cover change impacts were evaluated relative to values obtained from the actual land cover state of the basin in the year 2000. From the results, an agricultural land cover scenario constituting of about 86 per cent of agriculture indicated increased runoff volumes in the entire basin by about 12 per cent. An agricultural‐forested land cover scenario with 40 and 51 per cent of forest and agriculture respectively revealed reduced runoff volumes by about 12 per cent. Alternatively, a scenario depicting a largely forested land cover state with about 78 per cent of forests reduced the runoff volumes by about 25 per cent according to the model estimates. Runoff volumes in the basin were also likely to reduce by about 15 per cent if the appropriate land cover scenario for the respective sub‐catchments were to be assumed for runoff management purposes. Considering the prevalent data uncertainty, the study effectively highlights the potential hydrological vulnerability of the basin. The results obtained can form a basis for appropriate catchment management of the area. Copyright © 2012 John Wiley & Sons, Ltd.

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.

Physiographic and topographic changes in Luvuvhu River Catchment are negatively impacting on the catchment hydrology of the area. A study was carried out to extract and analyze the morphologic and hydrologic properties using GIS techniques. Digital Elevation Modeling hydro-processing procedures were used within an ArcGIS environment where Arc hydro tools were used to extract and show the spatial distribution of the properties. A hydrologically correct Digital Elevation Modeling (DEM) was generated and used to obtain primary and derived terrain elements. The results showed the automated delineation of sub-catchments and the spatial distribution of morphometric and hydrologic properties. The analysis showed how the physiographic changes were impacting on the river regimes and water resources.

The effects of land use changes on the characteristics of floods in the Nyando River basin were investigated. Historical changes in the state of land cover were derived by processing multi-temporal Landsat images. The detected changes, together with other spatial datasets were subsequently used to estimate the physically based catchment and hydrologic model parameters for runoff generation and transformation, and for channel flow routing. The results obtained indicated that the basin experienced significant increases in peak discharge values, especially in the upstream areas where higher rates of deforestation were detected. Over the study period, the peak discharges increased by 16% in all of the 14 sub-catchments in the basin. Simulated flood volumes in the basin also increased by 10% over the same period. Based on the results obtained, the study outlined the consequences of land use change for flood events in the basin.

Luvuvhu River Catchment experiences floods resulting from heavy rainfall intensities exceeding 15 mm per hour. The generation of runoff is triggered by the rainfall intensity and soil moisture status. In this study, remote sensing and GIS techniques were used to analyse the hydrologic response to land cover changes. Runoff was calculated as a product of the net precipitation and a curve number coefficient. It was then routed using the Muskingum-Cunge method using a diffusive wave transfer model that enabled the calculation of response functions between start and end point. Flood frequency was determined using theoretical probability distributions. Spatial data on land cover was obtained from multi-temporal Landsat images while data on rainfall, soil type, runoff and stream discharges were obtained by direct measurements in the field, Department of Water Affairs and from the South African Weather Services. The results showed that land cover changes had impacted negatively on the hydrology of the catchment. Peak discharges in the catchment were noted to have increased by 17% over the study period while flood volumes were noted to have increased by 11% over the same period. The synergism between remotely sensed digital data and GIS for land surface analysis and modelling was realised, and it was therefore concluded that hydrologic modelling has potential for determining the influence of changes in land cover on the hydrologic response of the catchment.