The downstream ecological effects of large impoundments have previously been reviewed; however, little is known about the downstream ecological effects of small man-made impoundments. In this review, we examine 94 papers focusing on the effects of small impoundments on stream habitat conditions and macroinvertebrates. Most studies (89.3%) address the effects of small impoundments on physical and chemical habitat conditions, while fewer studies (48.9%) address the effects on macroinvertebrates. In general, most studies report no significant downstream effects of small impoundments on physico-chemical variables, whereas macroinvertebrates richness and abundance increased or decreased. Mean effect sizes (as Cohen’s d) for physico-chemical variables range from −0.82 to 0.68 (small weir: −0.21 to 0.35; run-of-river dam: −0.82 to 0.64; low head dam: −0.49 to 0.68), and from −0.03 to 0.63 for macroinvertebrates abundance and richness. Our assessment of the published literature demonstrates the advantage of combining qualitative and quantitative analyses, and that, while small impoundments may have minimal significant effects on most physico-chemical variables, macroinvertebrates’ richness and density may be affected. This review is relevant for management and scientific communities to identify potential alterations of stream habitats and biota by small impoundments.
Landsat series multispectral remote sensing imagery has gained increasing attention in providing solutions to environmental problems such as land degradation which exacerbate soil erosion and landslide disasters in the case of rainfall events. Multispectral data has facilitated the mapping of soils, land-cover and structural geology, all of which are factors affecting landslide occurrence. The main aim of this research was to develop a methodology to visualize and map past landslides as well as identify land degradation effects through soil erosion and land-use using remote sensing techniques in the central region of Kenya. The study area has rugged terrain and rainfall has been the main source of landslide trigger. The methodology comprised visualizing landslide scars using a False Colour Composite (FCC) and mapping soil erodibility using FCC components applying expert based classification. The components of the FCC were: the first independent component (IC1), Principal Component (PC) with most geological information, and a Normalised Difference Index (NDI) involving Landsat TM/ETM+ band 7 and 3. The FCC components formed the inputs for knowledge-based classification with the following 13 classes: runoff, extreme erosions, other erosions, landslide areas, highly erodible, stable, exposed volcanic rocks, agriculture, green forest, new forest regrowth areas, clear, turbid and salty water. Validation of the mapped landslide areas with field GPS locations of landslide affected areas showed that 66% of the points coincided well with landslide areas mapped in the year 2000. The classification maps showed landslide areas on the steep ridge faces, other erosions in agricultural areas, highly erodible zones being already
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