Soil erosion is a serious and continuous environmental problem in Ethiopia. Lack of land use planning, environmental protection, over-cultivation, and overgrazing are prominent causes of erosion and sedimentation. This study is conducted in Anjeb watershed located in the Upper Blue Nile Basin, Ethiopia. In this study, the quantity and distribution of soil erosion, sediment delivery ratio (SDR), and sediment yield of the watershed were assessed by employing remote sensing, geographic information system (GIS), and revised universal soil loss equation analysis capabilities. Important data sets of topography, soil, conservations practices, cover management, and rainfall factors were processed and superimposed in GIS analysis, and soil loss rate, SDR, and sediment yield of the watershed were derived. Based on the result found, the watershed was categorized into six classes of erosion: slight (0–5), moderate (5–10), high (10–15), very high (15–30), severe (30–50), and very severe (> 50) t ha−1 yr−1. The estimated average annual soil loss was 17.3 t ha−1 yr−1. The soil loss rate is higher in the steeper and topographically dissected part of the watershed. The average sediment delivery capacity was about 0.122. The result showed that the average sediment yield in the watershed was grouped into classes of low (< 2.5), moderate (2.5–7.5), high (7.5–12.5), very high (12.5–22.5), severe (22.5–40), and very severe (> 40) t ha−1 yr−1. It is found that from a total of 20,125.5 t yr−1 eroded soil over the whole watershed 2254.5 t yr−1 of sediment has been brought and deposited to the channels. Sediment accumulation from the watershed threatens the storage capacity and life span of Anjeb reservoir which is the source of irrigation water downstream. The study provides an insight to planners and resource managers to design and implement practices of watershed management to reduce erosion and enhance land productivity and to minimize the reservoir sediment accumulation.

This work illustrates the efficiency of field spectroscopy for rapid identification of minerals in ore body, alteration zone and host rocks. The adopted procedure involves collection of field spectra, their processing for noise, spectral matching and spectral un-mixing with selected library end-members. Average weighted spectral similarity and effective peak matching techniques were used to draw end-members from library. Constrained linear mixture modelling technique was used to convolve end-member spectra. Linear mixture model was optimized based on root mean square error between field-and modelled-spectra. Estimated minerals and their abundances were subsequently compared with conventional procedures such as petrography, X-ray diffraction and X-ray fluorescence for accuracy assessment. The mineralized zone is found to contain azurite, galena, chalcopyrite, bornite, molybdenite, marcacite, gahnite, hematite, goethite, anglesite and malachite. The alteration zone contains chlorite, kaolinite, actinolite and mica. These mineral assemblages correlate well with the petrographic measurements (R 2 = 0.89). Subsequently, the bulk chemistry of field samples was compared with spectroscopically derived cumulative weighted mineral chemistry and found to correlate well (R 2 = 0.91-0.98) at excellent statistical significance levels (90-99%). From this study, it is evident that field spectroscopy can be effectively used for rapid mineral identification and abundance estimation.

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