This paper is mainly focused on identifying the socio economic and institutional factors infl uencing agroforestry adoption in Southern Province. Field survey was conducted during July to September, 2019 using structured questionnaire. This study was carried out in four districts in southern province of Rwanda. The number of respondents involved in the study was 650 farmers. A descriptive survey design was used in this study. For the selection of the sample, the study adopted a stratifi ed random sampling technique and simple random technique. Binary logit regression model has been used to determine the factors affecting farmers adopting agroforestry. Finally, Binary regression analysis showed no signifi cant association between the adoption of agroforestry practices and respondent's age, gender, marital status, farming experience or income range of the respondents. On the other hand, there is a positive signifi cant association between the adoption of agroforestry practices and household size is 0.00 p-value as well as the farm size of the respondents. It is expected that farmers with larger household size are more likely to adopt agroforestry practices than farmers with smaller household size and also shows that most of the farmers who were more likely to adopt agroforestry had a bigger land acreage for planting more trees.

Freshwater availability in sufficient quantity and quality is necessary for both people and nature. Environmental flow data is useful in the management and allocation of water resources. This study aimed at quantifying stream flows and their trends in the Malewa Basin rivers in central rift valley, Kenya. Daily stream flow data in four gauges (2GB01, 2GB05, 2GB0708 and 2GC04) were subjected to exploratory data analysis, fixed interval method of baseflow separation and Mann Kendall trend test. The results shows that on average, the Malewa river at Gauge 2GB01 discharge (excluding abstractions) about 191.2 million cubic metres of water annually, equivalent to a discharge of 6.06 m 3 /s. While discharges had not experienced a step change, huge annual fluctuations were noted suggesting periodicity with changes in climatic conditions. No trend was noted in annual stream data for the four gauges assessed. However, extreme low and high flows, median flows and baseflows for daily data showed either positive or negative trends. The baseflow index for daily flows showed trends: 2GB01 (Z = 4.519), 2GB05 (Z = -6.861), 2GB0708 (Z = -16.326) and 2GC04 (Z = 5.593). The findings suggest that Malewa rivers are likely experiencing effects of extreme climatic conditions and land cover changes. Land cover degradation seems to create conditions of increased flow, although the intensity varies from sub-catchment to another. The data also seems to suggest that stream discharge is much dependent on baseflows. There is need to regulate water use, improve soil cover and manage or adapt to the adverse effects of climate change.

This study employed the Water Evaluation and Planning model to evaluate selected policy-based water development and management options on water resources of the upper Mara Basin of Kenya. The major water resources of the region were identified and quantified to establish the current demand versus supply status. Data on domestic water consumption, agricultural demand and industrial consumption were collected through a rigorous fieldwork campaign and used to define the current state of water use and demand. The water resource model was calibrated and validated against observed discharges and subsequently used to simulate the selected policy-based options. Results indicate that an increase between 49% and 180%, depending on the assumed scenario, in annual water demand is expected by the year 2030. As a conclusion, the simulations demonstrate that there is both the need and significant potential to reduce the demand by implementing water conservation measures. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Impact of development and management options on water resources of the upper Mara River Basin of Kenya P. Omonge et al.

Detection of land cover change helps in the understanding of how humans modify the natural environment. Modification is attributed to both restoration and degradation processes. Such information guides decisions on mitigating landscape degradation and advancing restoration. This study sets to determine land cover changes from 1973 to 2013 in the Malewa River Basin (1,760 km 2) in central rift valley, Kenya. Satellite imageries from Landsat (Landsat Multispectral Scanner, 1973; Landsat TM (Thematic Mapper), 1986; ETM+ (Enhanced Thematic Mapper Plus), 2000; and SPOT, 2013) were analyzed using various imaging techniques available in ArcGIS 10.1 and ERDAS Imagine software. The results showed a cumulative growth of 25,617.0 ha (28.8%) in area under cropland, an increase of 4,310.1 ha (11.3%) in forestland and 688.0 ha (490.7%) of wetland. There was a net decrease of 28,953.8 ha (72.2%) in the area under shrubland and 1,747.4 ha (19.2%) under grassland. The findings suggest that increased demand for arable land is mainly driven by food and income needs of the human population. This exerted enormous pressure particularly on shrublands and grassland. Increased forest cover suggests an improvement in forest restoration efforts during the last ten years. There is need to manage expansion into new arable areas by improving land productivity and tackling the drivers of land cover change.

Purpose: Groundwater recharge is an important process for sustainable groundwater development and its quantification is a prerequisite for efficient management of groundwater resources. The purpose of this study was to evaluate the scale and spatial-temporal variation of groundwater recharge from precipitation in the semi-arid Stony Athi sub-catchment. Methodology: A descriptive case study approach was used for the evaluation. WetSpass-M, a GIS physically based, spatially distributed watershed model was applied. The model integrates biophysical and climatic characteristics of a watershed to simulate the long term mean groundwater recharge. Grid maps of the sub-catchment characteristics were prepared from primary and secondary data using ArcMap. The model was applied for four periods, namely, 1984, 1995, 2005 and 2017. Besides the average groundwater recharge, other outputs of the model include surface run-off and actual evapotranspiration. The study was carried out between January and December 2018. Findings: Land cover in the Stony Athi sub-catchment is comprised of built-up area, agricultural land, grassland, shrub-land, mixed forest and bare land. Topography ranges from 1493 m to 2,082 m above sea level with a slope of between 0% and 30%. Soil types include sandy loam, loam, sandy clay loam, sandy loam and clay. The mean annual precipitation is about 634 mm while the potential evapotranspiration is about 1,490 mm. Annual temperature averages 19.0°C with a mean maximum of 25°C and a mean minimum of 12.7°C. The results of the simulation indicated that the long-term temporal and spatial average annual rainfall of 634 mm is distributed as 88 mm (14%) recharge, 77 mm (12%) surface runoff while 475 mm (75%) is lost through evapotranspiration.   Unique contribution to theory, practice and policy: This study demonstrate the importance of physically-based spatially-distributed hydrological models in estimating the water balance. The study provides a theoretical basis for scientific, rational resource allocation and utilization as well as creating awareness of the need to enhance groundwater governance. Results from this study can be used as an input for building an integrated groundwater modelling and for evaluation of potential sites for managed artificial recharge through harvesting runoff to improve groundwater storage.