Characterizing the Intensity and Dynamics of Land-Use Change in the Mara River Basin, East Africa

The objective of this study was to analyze patterns, dynamics and processes of land-use/cover changes in the transboundary Mara River Basin in East Africa. We specifically focused on deforestation and expansion of agriculture in the watershed. The intensity analysis approach was used to analyze data from satellite imagery-derived land-use/cover maps. Results indicate that swap change accounted for more than 50% of the overall change, which shows a very dynamic landscape transformation. Transition from closed forest to open forest was found to be a dominant landscape change, as opposed to a random change. Similarly, transition from open forest to small-scale agriculture was also found to be a dominant transition. This suggests a trend (pathway) of deforestation from closed forest to small-scale agriculture, with open forest as a transitional land cover. The observed deforestation may be attributed to continuous encroachment and a series of excisions of the forest reserve. Transition from rangeland to mechanized agriculture was found to be a dominant land-use change, which was attributed to change in land tenure. These findings are crucial for designing strategies and integrated watershed management policies to arrest further deforestation in the forest reserves as well as to sustainably control expansion of agriculture

Modelling crop production, river low flow, and sediment load trade-offs under agroforestry land-use scenarios in Nyangores catchment, Kenya

The largest impact of land-use change on catchment hydrology can be linked to deforestation. This change, driven by exponential population growth, intensified food and industrial production, has resulted in alterations in river flow regimes such as high peaks, reduced base flows, and silt deposition. To reverse this trend more extensive management practices are becoming increasingly important, but can also lead to severe losses in agricultural production. Land-use optimization tools can help catchment managers to explore numerous land-use configurations for the evaluation of trade-offs amongst various uses. In this study, the Soil and water assessment tool (SWAT) model was coupled with a genetic algorithm to identify land-use/management configurations with minimal trade-offs between environmental objectives (reduced sediment load, increased stream low flow) and the crop yields of maize and soybean in Nyangores catchment (Kenya). During the land-use optimization, areas under conventional agriculture could either remain as they are or change to agroforestry or conservation agriculture (CA), where the latter was represented by introducing contour farming and vegetative filter strips. From the sets of the resulting Pareto-optimal solutions we selected mid-range solutions, representing a fair compromise among all objectives, for further analysis. We found that a combined measure implementation strategy (agroforestry on certain sites and conservation agriculture on other sites within the catchment) proved to be superior over single measure implementation strategies. On the catchment scale, a 3.6% change to forests combined with a 35% change to CA resulted in highly reduced sediment loads (−78%), increased low flow (+14%) and only slightly decreased crop yields (<4%). There was a tendency of the genetic algorithm to implement more extensive management practices in the upper part of the catchment while leaving conventional agriculture in the lower part. Our study shows that a spatially targeted implementation strategy for different conservation management practices can remarkably improve environmental sustainability with only marginal trade-offs in crop production at the catchment-level. Incentive policies such as payments for ecosystem services (PES), considering upstream and downstream stakeholders, could offer a practical way to effect these changes

Impact of Land Use Change and Climate Variability on Watershed Hydrology in the Mara River Basin, East Africa

Land use change and climate variability are the main drivers of watershed hydrological processes. The main objective of this study was to assess the impact of land use change and climate variability on hydrology of the Mara River Basin in East Africa. Land use maps generated from satellite images were analyzed using the intensity analysis approach to determine the patterns, dynamics and intensity of land use change. Changes in measured streamflow caused separately by land use change and climate variability were separated using the catchment water-energy budget based approach of Budyko framework. The information on past impact of climate variability on streamflow was used to develop a runoff sensitivity equation which was then used to predict the future impact of climate change on streamflow. Finally, the impact of agroforestry on watershed water balance was predicted using SWAT (Soil and Water Assessment Tool) model. Deforestation and expansion of agriculture were found to be dominant and intensive land use changes in the watershed. The deforestation was attributed to illegal encroachment and excision of the forest reserve. The deforested land was mainly converted to small scale agriculture particularly in the headwaters of the watershed. There was intensive conversion of rangeland to largescale mechanized agriculture which accelerated with change of land tenure (privatization). The watershed has a very dynamic land use change as depicted by swap change (simultaneous equal loss and gains of a particular land use/cover) which accounted for more than half of the overall change. This implies that reporting only net change in land use (of MRB) underestimates the total land use change. The results show that streamflow of Nyangores River (a headwater tributary of the Mara River) significantly increased over the last 50 years. Land use change (particularly deforestation) contributed 97.5% of change in streamflow while the rest of the change (2.5%) was caused by climate variability. It was predicted that climate change would cause a moderate 15% increase in streamflow in the next 50 years. SWAT model simulations suggested that implementation of agroforestry in the watershed would reduce surface runoff, mainly due expected improvement of soil infiltration. Baseflow and total water yield would also decrease while evapotranspiration would increase. The changes in baseflow (reduction) and evapotranspiration (increase) were attributed to increased water extraction from the soil and groundwater by trees in agroforestry systems. The impact of agroforestry on water balance (surface runoff, baseflow, water yield and evapotranspiration) was proportional to increase in size of the watershed simulated with agroforestry. Modelling results also suggested that climate variability within the watershed has a profound effect on the change of water balance caused by implementation of agroforestry. It is recommended that authorities should pay more attention to land use change as the main driver of change in watershed hydrology of the basin. More effort should be focused on prevention of further deforestation and agroforestry may be considered as a practical management strategy to reverse/reduce degradation on the deforested parts of the watershed currently under intensive cultivation

Impact of Land Use Change and Climate Variability on Watershed Hydrology in the Mara River Basin, East Africa

Land use change and climate variability are the main drivers of watershed hydrological processes. The main objective of this study was to assess the impact of land use change and climate variability on hydrology of the Mara River Basin in East Africa. Land use maps generated from satellite images were analyzed using the intensity analysis approach to determine the patterns, dynamics and intensity of land use change. Changes in measured streamflow caused separately by land use change and climate variability were separated using the catchment water-energy budget based approach of Budyko framework. The information on past impact of climate variability on streamflow was used to develop a runoff sensitivity equation which was then used to predict the future impact of climate change on streamflow. Finally, the impact of agroforestry on watershed water balance was predicted using SWAT (Soil and Water Assessment Tool) model. Deforestation and expansion of agriculture were found to be dominant and intensive land use changes in the watershed. The deforestation was attributed to illegal encroachment and excision of the forest reserve. The deforested land was mainly converted to small scale agriculture particularly in the headwaters of the watershed. There was intensive conversion of rangeland to largescale mechanized agriculture which accelerated with change of land tenure (privatization). The watershed has a very dynamic land use change as depicted by swap change (simultaneous equal loss and gains of a particular land use/cover) which accounted for more than half of the overall change. This implies that reporting only net change in land use (of MRB) underestimates the total land use change. The results show that streamflow of Nyangores River (a headwater tributary of the Mara River) significantly increased over the last 50 years. Land use change (particularly deforestation) contributed 97.5% of change in streamflow while the rest of the change (2.5%) was caused by climate variability. It was predicted that climate change would cause a moderate 15% increase in streamflow in the next 50 years. SWAT model simulations suggested that implementation of agroforestry in the watershed would reduce surface runoff, mainly due expected improvement of soil infiltration. Baseflow and total water yield would also decrease while evapotranspiration would increase. The changes in baseflow (reduction) and evapotranspiration (increase) were attributed to increased water extraction from the soil and groundwater by trees in agroforestry systems. The impact of agroforestry on water balance (surface runoff, baseflow, water yield and evapotranspiration) was proportional to increase in size of the watershed simulated with agroforestry. Modelling results also suggested that climate variability within the watershed has a profound effect on the change of water balance caused by implementation of agroforestry. It is recommended that authorities should pay more attention to land use change as the main driver of change in watershed hydrology of the basin. More effort should be focused on prevention of further deforestation and agroforestry may be considered as a practical management strategy to reverse/reduce degradation on the deforested parts of the watershed currently under intensive cultivation

Land Suitability Analysis for Pineapple Cultivation in Kiambu County, Kenya

Driven by dwindling incomes from coffee and tea and the need to diversify their sources of income, farmers in Kiambu County are increasingly shifting to pineapple cultivation in areas formerly dominated by coffee and tea cultivation. However, not all areas in the County are suitable for pineapple production due to spatial variability of factors affecting growth (climate, soils, topography). There is therefore a need to identify and delineate suitable areas for growing pineapples in the County.  Land suitability assessment for pineapple production in Kiambu County was carried out by a combination of GIS and the Analytical Hierarchical Process (AHP) model. Using GIS, thematic maps of all factors affecting pineapple growth (soil, climate and topography) were developed showing their spatial variability within the county. The maps (of factors affecting growth) were assessed against the published optimum parameter value ranges for pineapple cultivation. AHP was used to assign ratings/weights (of importance) of the thematic layers in regard to pineapple production. The land suitability map was developed from a weighted overlay of the thematic layers in ArcGIS. The map was categorized into four classes based on pineapple cultivation's suitability; highly suitable, moderately suitable, marginally suitable, and not suitable. From the results, 38% of the (Kiambu) County is highly suitable for pineapple cultivation while 5% is not suitable. The rest of the County is moderately suitable (41%) and marginally suitable (16%). We recommend the use of these findings by agricultural extension officers for the planning and guiding farmers on where to invest in pineapple productio

Assessing the impact of a multimetric calibration procedure on modelling performance in a headwater catchment in Mau Forest, Kenya

Study region: Nyangores catchment, Mara catchment, Kenya. Study focus: Hydrologic models are widely used tools in watershed management to assist in decision making by representing catchment functions under alternative scenarios. This study focused on the evaluation of the 5 segment Flow Duration Curve based calibration procedure (5FDC) for the period 1975–1978 using the Soil Water Assessment Tool (SWAT). The Normal Calibration Procedure (NCP) based on the hydrograph was compared to the 5FDC. Two separate ensembles each containing 10 Pareto calibration runs were obtained individually from each method and evaluated based on their goodness-of-fit. A final Combined Procedure (CP), which was an intersection of 5FDC and NCP was executed. With this supplementary analysis, the parameter distribution and water component balance were analyzed and compared. New hydrological insights for the region: The comparison of 5FDC and NCP shows that the 5FDC provides a better representation of the low and mid-level section of the flow duration curve as compared to the NCP, which greatly overestimates these flows. This method also closely matches the observed runoff ratios. This indicates that the 5FDC calibration may be well suited for water resource applications focused on low flows. The CP combines the advantages of both procedures by improving parameter identifiability, leading to better representation of high and low flows. Keywords: 5 segmented Flow Duration Curve (5FDC), Normal Calibration Procedure(NCP), Parameter identifiability, Pareto set, Pareto analysis, Water balance, Multimetric calibration, Latin hypercube sampling, Performance metrics, Uncertainty, Prediction, Hydrologic model, Simulation, Equifinality, Base flows, Variability, Optimum, Stepwise intersection, Ensemble, Water partitionin

Relative contribution of land use change and climate variability on discharge of upper Mara River, Kenya

Study region Nyangores River watershed, headwater catchment of Mara River basin in Kenya. Study focus Climate variability and human activities are the main drivers of change of watershed hydrology. The contribution of climate variability and land use change to change in streamflow of Nyangores River, was investigated. Mann Kendall and sequential Mann Kendall tests were used to investigate the presence and breakpoint of a trend in discharge data (1965–2007) respectively. The Budyko framework was used to separate the respective contribution of drivers to change in discharge. Future response of the watershed to climate change was predicted using the runoff sensitivity equation developed. New hydrological insights for the region There was a significant increasing trend in the discharge with a breakpoint in 1977. Land use change was found to be the main driver of change in discharge accounting for 97.5% of the change. Climate variability only caused a net increase of the remaining 2.5% of the change; which was caused by counter impacts on discharge of increase in rainfall (increased discharge by 24%) and increase in potential evapotranspiration (decreased discharge by 21.5%). Climate change was predicted to cause a moderate 16% and 15% increase in streamflow in the next 20 and 50 years respectively. Change in discharge was specifically attributed to deforestation at the headwaters of the watershed

Using soil erosion as an indicator for integrated water resources management: a case study of Ruiru drinking water reservoir, Kenya

Functions and services provided by soils play an important role for numerous sustainable development goals involving mainly food supply and environmental health. In many regions of the Earth, water erosion is a major threat to soil functions and is mostly related to land-use change or poor agricultural management. Selecting proper soil management practices requires site-specific indicators such as water erosion, which follow a spatio-temporal variation. The aim of this study was to develop monthly soil erosion risk maps for the data-scarce catchment of Ruiru drinking water reservoir located in Kenya. Therefore, the Revised Universal Soil Loss Equation complemented with the cubist–kriging interpolation method was applied. The erodibility map created with digital soil mapping methods (R2 = 0.63) revealed that 46% of the soils in the catchment have medium to high erodibility. The monthly erosion rates showed two distinct potential peaks of soil loss over the course of the year, which are consistent with the bimodal rainy season experienced in central Kenya. A higher soil loss of 2.24 t/ha was estimated for long rains (March–May) as compared to 1.68 t/ha for short rains (October–December). Bare land and cropland are the major contributors to soil loss. Furthermore, spatial maps reveal that areas around the indigenous forest on the western and southern parts of the catchment have the highest erosion risk. These detected erosion risks give the potential to develop efficient and timely soil management strategies, thus allowing continued multi-functional use of land within the soil–food–water nexus

Image_1_Modelling crop production, river low flow, and sediment load trade-offs under agroforestry land-use scenarios in Nyangores catchment, Kenya.jpg

The largest impact of land-use change on catchment hydrology can be linked to deforestation. This change, driven by exponential population growth, intensified food and industrial production, has resulted in alterations in river flow regimes such as high peaks, reduced base flows, and silt deposition. To reverse this trend more extensive management practices are becoming increasingly important, but can also lead to severe losses in agricultural production. Land-use optimization tools can help catchment managers to explore numerous land-use configurations for the evaluation of trade-offs amongst various uses. In this study, the Soil and water assessment tool (SWAT) model was coupled with a genetic algorithm to identify land-use/management configurations with minimal trade-offs between environmental objectives (reduced sediment load, increased stream low flow) and the crop yields of maize and soybean in Nyangores catchment (Kenya). During the land-use optimization, areas under conventional agriculture could either remain as they are or change to agroforestry or conservation agriculture (CA), where the latter was represented by introducing contour farming and vegetative filter strips. From the sets of the resulting Pareto-optimal solutions we selected mid-range solutions, representing a fair compromise among all objectives, for further analysis. We found that a combined measure implementation strategy (agroforestry on certain sites and conservation agriculture on other sites within the catchment) proved to be superior over single measure implementation strategies. On the catchment scale, a 3.6% change to forests combined with a 35% change to CA resulted in highly reduced sediment loads (−78%), increased low flow (+14%) and only slightly decreased crop yields (<4%). There was a tendency of the genetic algorithm to implement more extensive management practices in the upper part of the catchment while leaving conventional agriculture in the lower part. Our study shows that a spatially targeted implementation strategy for different conservation management practices can remarkably improve environmental sustainability with only marginal trade-offs in crop production at the catchment-level. Incentive policies such as payments for ecosystem services (PES), considering upstream and downstream stakeholders, could offer a practical way to effect these changes.</p