Alleviating some Environmental Impacts resulting from Artisanal and Small-scaleMining Sector: A Critical Review

This paper highlights the importance of transforming Artisanal and Small-scale Mining (ASM) sector into a more sustainable enterprise and shows  the reclamation of despoiled mined sites as an opportunity to return land to beneficial uses which do not compromise future development of the sites. It presents some of environmental impacts produced by ASM and the contribution of a geomorphological approach to alleviate them. The methodology consisted of the review supported by field survey in small-scale mining areas to summarize the most relevant scientific findings and the importance of stabilizing the land that will support sustainably reclamation structures. The impacts include haphazard excavations with no land reclamation plan, pits, trenches inadequately protected, siltation of open water bodies, soil and rock wastes, negative change of soil properties, and accelerated erosion of the mine sites. To transform the sector into a more responsible industry, ASM has to be placed within two integrated perspectives: (i) building the capacity of ASM sector, and (ii) promoting restoration approach by building a critical knowledge mass through collaboration of relevant stakeholders, with emphasis on multidisciplinary approach.The study opens a relevant new research field and emphasises on the collaboration of mining stakeholders including local communities to develop an integrated approach to address challenges that ASM industry is facing in developing countries. This review highlights the impacts of small-scale mining sector on land use potentials and it is essentialcontribution towards the sustainability of ASM industry and reclamation of despoiled mined lands. Key Words: small-scale mining sector, environmental impact, geomorphologic approach, sustainabilit

Integrating Remote Sensing and GIS to Model Forest Fire Rik in Virunga Massif, Central - Eastern Africa

This study aimed at developing a forest fire risk model using a combination of GIS and Remote sensing techniques, which helped to identify the level of forest fire vulnerability in Virunga Massif, located at the edge of central and eastern Africa. The Analytic Hierarchical Process (AHP) approach was employed to rank and weigh the key variables and combine them into different fire risk input factors which were later integrated into the main forest fire risk model. The main input datasets, which were linked with a potential source of a forest fire, include the land cover (specifically vegetation type data generated through the Landsat 8 image classification); topographic variables such as slope, elevation and aspect retrieved from the existing Digital Elevation Model (DEM) of Rwanda; the concentration of illegal activities and proximity to beehives sites; as well as visibility from the road and human settlements. Input factor maps were generated, assigned weights and combined in a GIS environment to produce a Virunga massif fire risk model map, which was validated using the existing burnt areas map, and ground truth points recorded using GPS. The study found that the ignition factors are the most forest fire triggering factors in Virunga massif, followed by topographic factors which play a major role in the fire spreading across the ecosystem. The high forest fire risk areas were found in steep slope location around the peaks of the volcanoes, whereas areas with the lowest risk of forest fire were found inside the forest at gentle slopes. The model was validated at 75% accuracy using ground truth data. The study proposes measure to halt the ignition factors through prevention of illegal activities in the Virunga massif for the successful prevention of the forest fire risk in the ecosystem, with much effort invested during the dry season, along with the relocation of beehives to a farther distance from the ecosystem’s edge. Keywords: Forest Fire Risk Modelling, Biodiversity, Illegal Activities, Ignition Factors, Topographic Factors, Analytic Hierarchy Proces

Spatial Modelling of Common Chimpanzees’ (Pan troglodytes schweinifurthii) Ecological Niche in the Western Part of Rwanda

The Western Part of Rwanda is a mountainous region that hosts two important forest parks namely the Nyungwe National Park (NNP) and Gishwati-Mukura National Park (GMNP). The two parks which are located in the Albertine Rift region are known for their high endemism and harbour several endangered plant and animal species, including particularly the Common Chimpanzees (Pan troglodytes schweinifurthii). However, these forests are facing threats including mainly habitat loss, aggravated by climate change both of which are continuously having direct and indirect effects to the Chimpanzees. While conservation of chimpanzees appears critical, there is a need to deeply understand the dynamics of their habitat. This study aimed at modelling the ecological niche of common chimpanzee by integrating species distribution data and environmental layers. Species location data collected in both NNP and GMNP were integrated with environmental variables (temperature, precipitation, altitude, and land cover) through Maximum Entropy (MaxEnt), and Generic Algorithm for Rule-based Prediction (GARP) Models. The results of both models showed that chimpanzees prefer the Southern and the Northern parts of the study area (0.5 < p < 0.87), which is characterised by high altitude, low temperature, and intensive rainfall. It was also noted that MaxEnt predictions were more accurate compared to the GARP’s. MaxEnt predictions showed that 35% (2058.61 ha) of the Western Province are suitable for chimpanzees, while GARP predicted that only 24% (1411.62 ha) are suitable. Furthermore, the study found that the high precipitation, annual and maximum precipitations, and food availability are the most determinants of chimpanzees' habitat. The land use in the Western Province has made the central part less suitable to chimpanzees and therefore, this study recommends that special efforts for the conservation of Common chimpanzees in Rwanda should be concentrated in the Southern Part (around NNP) Nyungwe National Park (main forest and Cyamudongo fragment) and the northern Part (around GMNP) Keywords: Spatial Modelling, Common Chimpanzee, Ecological Niche, Nyungwe National Park, Gishwati-Mukura National Park, Rwanda

Estimation of Soil Erosion Using RUSLE Model and GIS: The Case of Satinskyi Catchment, Western Rwanda

The problem of soil erosion in Rwanda has been highlighted in previous studies. They have shown that half of the country’s farmland suffers moderate to severe erosion, with the highest soil loss rates found in the steeper and highly rainy northern and western highlands of the country. The purpose of this study was to estimate soil loss in Satinskyi, one of the catchments located in Ngororero District of Western Rwanda. This has been achieved using the Revised Universal Soil Loss Equation (RUSLE) model, which has been implemented in a Geographic Information Systems (GIS) environment. The methods consisted of preparing a set of input factor layers including Slope Length and Steepness (LS) factor, Rainfall Erosivity (R) factor, Soil Erodibility (K) factor, Support Practice (P) factor, and Land Surface Cover Management Factor (C) factor, for the model. The input factors have been integrated for soil loss estimates computation using RUSLE model, and this has enabled to quantitatively assess variations in the mean of the total estimated soil loss per annum in relation to topography and land-use patterns of the studied catchment. The findings showed that the average soil loss in Satinskyi catchment is estimated at 38.4 t/ha/year. It was however found that about 91% of the study area consists of areas with slope angle exceeding 15°, a situation which exposes the land to severe soil loss rates ranging between 31 t/ha/year and 41 t/ha/year. Apart from the steep slope, changes in land use also contribute to high rates of soil loss in the catchment. Keywords: Soil Erosion Estimation, GIS, RUSLE, Satinskyi Catchment, Rwand

Spatio-temporal Analysis of Urban Growth and Its Effects on Wetlands in Rwanda: The Case of Rwampara Wetland in the City of Kigali

This study aimed at analyzing the spatio-temporal patterns of urban growth and its effects on Rwampara wetland, located in the City of Kigali,  Rwanda. First, the study was based on the application of remote sensing technology, where 4 Landsat images (1987, 1999, 2009 & 2018) were  classified using maximum likelihood classification algorithm. This helped in analyzing the Land Use and Land Cover (LULC) trends in the study area. Secondly, it used the existing LULC data for the years 1990, 2000, 2010 and 2018 in order to investigate the overall changes in LULC in Kigali City. Finally, semi-structured interviews were used to collect data from local people and decision-makers about their past and future management strategies of Rwampara wetland. In this regard, 30 local communities (mainly natives from the study area), 15 local government authorities at sector and district levels as well as 4 senior government authorities in the central administration were interviewed. The findings revealed that over the past 4 decades, urban growth in Kigali City has rapidly increased at the expense of resource degradation in Rwampara wetland. Specifically, there has been an increase of about 77% of the built-up area over the last 31 years (1987-2018) which has led to the decrease of the wetland surface area from 24 ha in 1987 to only 7.7 ha in 2018. The results also revealed that demographic factors (i.e. a high population growth rate and high population  densities) were mainly responsible for urban growth and degradation of wetland resources in the area under investigation. Keywords: urban growth, wetland, wetland resources, wetland degradation, wetland managemen

Spatio-temporal Analysis of Urban Growth and Its Effects on Wetlands in Rwanda: The Case of Rwampara Wetland in the City of Kigali

This study aimed at analyzing the spatio-temporal patterns of urban growth and its effects on Rwampara wetland, located in the City of Kigali, Rwanda. First, the study was based on the application of remote sensing technology, where 4 Landsat images (1987, 1999, 2009 & 2018) were classified using maximum likelihood classification algorithm. This helped in analyzing the Land Use and Land Cover (LULC) trends in the study area. Secondly, it used the existing LULC data for the years 1990, 2000, 2010 and 2018 in order to investigate the overall changes in LULC in Kigali City. Finally, semi-structured interviews were used to collect data from local people and decision-makers about their past and future management strategies of Rwampara wetland. In this regard, 30 local communities (mainly natives from the study area), 15 local government authorities at sector and district levels as well as 4 senior government authorities in the central administration were interviewed. The findings revealed that over the past 4 decades, urban growth in Kigali City has rapidly increased at the expense of resource degradation in Rwampara wetland. Specifically, there has been an increase of about 77% of the built-up area over the last 31 years (1987-2018) which has led to the decrease of the wetland surface area from 24 ha in 1987 to only 7.7 ha in 2018. The results also revealed that demographic factors (i.e. a high population growth rate and high population densities) were mainly responsible for urban growth and degradation of wetland resources in the area under investigation

THE USE OF GIS TECHNOLOGIES IN ANALYZING CHALLENGES AND OPPORTUNITIES FOR THE MANAGEMENT OF URBAN GREEN SPACES IN KIGALI CITY, RWANDA

This study was assessing the challenges and opportunities for managing Green Spaces (GS) of the Urban Part of Kigali City (UPKC). To find out the GS classes and their threats, the land use classes were identified using GIS technologies. Its output was completed by the field visit, questionnaire survey, informal interviews and desk review of the existing environmental and biodiversity policies and laws. The land use assessment has shown that the built up areas is the most predominant and occupies 74.3%, while the green spaces occupy only 25.3% of the total areas of Urban Part of Kigali City (UPKC). Among the GS classes identified in UPKC, wetlands occupy about 62.6% of the total area of the GS, forests 25%, gardens that are combination of the road side trees, the roundabouts, and playgrounds occupy 12.4% of the total area of GS while the seasonal and perennial crops areas are not significant in the city. In addition, results have shown that GS play different roles in the city among others, the beautification of the city, the air purification and refreshment, waste water treatment, heat reduction, mind refreshment; act as habitat, food and corridors for a good number of animal, etc. Even though there is no specific law or policy to the urban GS management and protection, the Government of Rwanda (GoR) has put in place a good number of opportunities that take them into consideration. Those include, (1) the governmental policies such as Environmental Policy, Biodiversity Policy, and Forest Policy; (2) the laws such as Organic Environmental Law and, (3) the plans such the master plans for the three districts that make Kigali City. Despite these opportunities, the management of GS in Kigali City is still facing some challenges that the Kigali City authorities are still trying to address. Those include the lack of policies on GS management, low level of awareness on GS management among local people, and the demographic pressure particularly caused by the rural migration that has led to inappropriate human settlement in some areas of the city, wastes management and pollution

Assessment of Grain Legumes Adaptation to Climate Change in Bugesera District, Rwanda

The aim of this study was to assess the adaptability to climate change of selected grain legumes (including beans, peas and soybeans) in Bugesera district in Rwanda. Climate change was analysed by considering significant changes in mean, minimum and maximum temperature and the mean annual rainfall from 1970 until 2014, the year during which data for this study were collected. The sampling strategy followed a cluster area sampling and random sampling approach, which led to the sample size of 99 households surveyed using a structured questionnaire. MAKESENS model and Analysis of Variances (ANOVA) were applied to analyze climate data and information from the household survey. This study revealed significant increase of mean temperature (0.39oC and 0.46oC per decade for rainy seasons A and B respectively) and irregularity of rainfalls during both rainy seasons. The Diurnal Temperature Range (DTR) has been decreasing considerably, impacting the crops development traits such as internode length. The farmers’ responses indicated low adaptation capacity to the climate change, leading to a high sensitivity of the grain legumes. For an improved mitigation of climate change impacts, the following strategies were proposed: land consolidation and creation of grain legumes farmers’ cooperatives, improved economic capacity of the farmers, use of climate-resilient selected seeds, creation of the off-farm activities, improved climate information reliability and dissemination