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Belay Simane   Dr.  University Educator/Researcher 
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Belay Simane published an article in March 2019.
Top co-authors See all
Martha C. Anderson

220 shared publications

U.S. Department of AgricultureAgricultural Research Service, Hydrology and Remote Sensing Lab Beltsville MD USA

Benjamin F. Zaitchik

50 shared publications

Department of Earth and Planetary Sciences, Johns Hopkins University, Baltimore, MD 21218, USA

Mutlu Özdoğan

42 shared publications

Department of Forest and Wildlife Ecology, University of Wisconsin, 1630 Linden Drive, Madison, WI 53726, USA

Jeremy D. Foltz

23 shared publications

University of Wisconsin-Madison

Shimelis Setegn

18 shared publications

Environmental and Occupational Health, Florida International University, 11200 S.W. 8th St., Miami, FL 33199, USA

Publication Record
Distribution of Articles published per year 
(1970 - 2019)
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Article 0 Reads 0 Citations Land Use Evaluation over the Jema Watershed, in the Upper Blue Nile River Basin, Northwestern Highlands of Ethiopia Mintesinot Taye, Belay Simane, Benjamin F. Zaitchik, Yihenew... Published: 19 March 2019
Land, doi: 10.3390/land8030050
DOI See at publisher website ABS Show/hide abstract
Generating land capability class guidelines at a watershed scale has become a priority in sustainable agricultural land use. This study analyzed the area of cultivated land use situated on the non-arable land-capability class in the Jema watershed in the Upper Blue Nile River Basin. Soil surveys, meteorological ground observations, a digital elevation model (DEM) at 30 m, Meteosat at 10 km × 10 km and Landsat at 30 m were used to generate the sample soil texture class, average annual total rainfall (ATRF in mm), terrain, slope (%), elevation (m a.s.l) and land-use land cover (%). The land capability class was analyzed by considering raster layers of terrain, the average ATRF and soil texture. Geo-statistics was employed to fit a surface of soil texture and average ATRF estimates. An overlay technique was used to compute the proportion of cultivated land placed on non-arable land. As per the results of the terrain analysis, the elevation (m a.s.l) of the watershed is in the range of 1895 to 3518 m. The slope was found to be in the range of 0 to 45%. The amount of estimated rainfall ranged from 1640 to 131 mm with value declined from the lower to the higher elevation. Clay loam, clay and heavy clay were found to be the major soil texture classes. Four land capability classes, i.e., II, III, IV (arable) and V (non-arable), were identified with proportions of 28.56%, 45.74%, 22.16% and 3.54%, respectively. Seven land-use land covers were identified, i.e., annual crop land, grazing land, bush land, bare land, settlement land, forestland and water bodies, with proportions of 42.1, 35.9, 8.90, 8.3, 2.6, 2.1, and 0.2, respectively. Around 1707.7 ha of land in the watershed is categorized under non-arable land that cannot be used for annual crop cultivation at any level of intensity. Around 437 ha (3.5%) of land was cultivated on non-arable land. To conclude, the observed unsustainable crop land use could maximize soil loss in upstream regions and siltation and flooding downstream. The annual crop land use that was observed on non-arable land needs to be replaced with perennial crops, pasture and/or forest land uses.
Article 0 Reads 0 Citations Analysis of the Spatial Patterns of Rainfall across the Agro-Climatic Zones of Jema Watershed in the Northwestern Highla... Mintesinot Taye, Belay Simane, Benjamin F. Zaitchik, Shimeli... Published: 30 December 2018
Geosciences, doi: 10.3390/geosciences9010022
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The association between elevation (agro-climatic zones, ACZs) and the mean annual total rainfall (MATRF) is not straightforward in different parts of the world. This study sought to estimate the amount of MATRF across four elevation zones of Jema watershed, which is situated in the northwestern highlands of Ethiopia, by employing an appropriate interpolation method. The elevation of the watershed ranges from 1895 to 3518 m a.s.l. For the sake of this study, 34 sample MATRF data were extracted from satellite and nearby gauge stations that were recorded from 1983 to 2010. These data sources were reconstructed by International Research Institute for Climate and Society at Columbia University, USA, at a scale of 10 km by 10 km. An elevation data set generated from a digital elevation model with 30-m resolution (DEM 30 m) was considered as a covariable to estimate the MATRF. To identify the optimal interpolation model, mean errors were computed using cross-validation statistics. The root-mean-square error (RMSE) analysis showed that ordinary cokriging (OCK) was the most accurate model with a predictive power of 87.3%. The root-mean-square standardized (RMSSE) analysis showed that the best precision value (0.72) occurred in OCK. Stable and Gaussian trend lines together with local polynomial types of trend removal, and an elliptical neighborhood search function could perform best to maximize the accuracy and the precision of estimating MATRF. Elevation, as a covariable, enhanced the degree of accuracy and precision of estimation. The value of the trend line function (least square) between the MATRF and elevation was very weak (R2 = 0.07), whereas the value of trend line function (least square) between the MATRF and the longitude coordinates (east–west direction) was medium (R2 = 0.34). The estimated MATRF for the entire watershed under study ranged from 1228 to 1640 mm. To conclude, elevation could contribute to the estimation of the MATRF. The value of the MATRF showed a declining pattern from the lower to higher elevation areas of the watershed.
Article 0 Reads 1 Citation Analysis of the Spatial Variability of Soil Texture in a Tropical Highland: The Case of the Jema Watershed, Northwestern... Mintesinot Taye, Belay Simane, Yihenew G. Selsssie, Benjamin... Published: 01 September 2018
International Journal of Environmental Research and Public Health, doi: 10.3390/ijerph15091903
DOI See at publisher website PubMed View at PubMed ABS Show/hide abstract
This study sought to analyze the degree of spatial association of soil texture with agro-climatic zones and slope classes on the farmlands of the Jema watershed, in the Northwestern Highlands of Ethiopia. The agro-climatic zones (elevation zones) determine the micro-climate and biota of the study area. Thirty six soil composite samples for texture (the proportion of clay, silt and sand) analysis from four agro-climatic (elevation) zones and seven slope classes were collected. One-Way-ANOVA was employed to compute the mean variability of texture among the identified terrain classes, and linear regression was used to analyze the degree of association between texture and the terrain attributes. The measured values of sand, silt and clay in the watershed ranged from 11.4 to 43.4, 6.0 to 34.8, and 21.8 to 77.8, respectively. The One-Way-ANOVA indicated a significant (p < 0.05) soil texture variation in both slope and agro-climatic zone classes. Heavy clay, clay and clay loam were identified as the major texture classes in the lower, middle and upper parts of the watershed, respectively. The regression analysis showed that texture was more influenced by the difference in the elevation values than in slope values in the watershed. The standardized beta coefficients of slope and elevation for clay particles were 0.499 and 0.767, respectively. For sand, the regression coefficients for slope and agro-climatic zone were 0.485 and 0.812, respectively. This implies that an interactive effect of micro-climate and biota governed by elevation influenced the spatial distribution of soil texture more than slope.
Article 0 Reads 0 Citations Determinants in the adoption of climate change adaptation strategies: evidence from rainfed-dependent smallholder farmer... Amogne Asfaw, Belay Simane, Amare Bantider, Ali Hassen Published: 05 April 2018
Environment, Development and Sustainability, doi: 10.1007/s10668-018-0150-y
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Article 22 Reads 10 Citations Variability and time series trend analysis of rainfall and temperature in northcentral Ethiopia: A case study in Woleka ... Amogne Asfaw, Belay Simane, Ali Hassen, Amare Bantider Published: 01 March 2018
Weather and Climate Extremes, doi: 10.1016/j.wace.2017.12.002
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Examining the spatiotemporal dynamics of meteorological variables in the context of changing climate, particularly in countries where rainfed agriculture is predominant, is vital to assess climate-induced changes and suggest feasible adaptation strategies. To that end, trend analysis has been employed to inspect the change of rainfall and temperature in northcentral Ethiopia using gridded monthly precipitation data obtained from Global Precipitation and Climate Centre (GPCC V7) and temperature data from Climate Research Unit (CRU TS 3.23) with 0.5° by 0.5° resolution from 1901 to 2014. Data have been analyzed using coefficient of variation, anomaly index, precipitation concentration index and Palmer drought severity index. Furthermore, Mann-Kendall test was used to detect the time series trend. The result revealed intra- and inter-annual variability of rainfall while Palmer drought severity index value proved the increasing trend of the number of drought years. Annual, belg and kiremt rainfall have decreased with a rate of 15.03, 1.93 and 13.12 mm per decade respectively. The declining trend for annual and kiremt rainfall was found to be statistically significant while that of belg was not significant. The rate of change of temperature was found to be 0.046, 0.067 and 0.026 °C per decade for mean, minimum and maximum respectively. The Mann-Kendall trend analysis test result revealed increasing trend for mean and minimum average temperatures through time significantly while the trend for maximum temperature exhibited a non-significant increasing trend. We recommend strategies designed in the agricultural sector have to take the declining and erratic nature of rainfall and increasing trend of temperature into consideration.
BOOK-CHAPTER 3 Reads 0 Citations Fostering the Use of Rainwater for Off-Season Small-Scale Irrigation in Arid and Semi-arid Areas of Ethiopia Belay Simane, Taffa Tulu, Amare Lantideru, Desalegn Dawit Published: 30 December 2017
Rainwater-Smart Agriculture in Arid and Semi-Arid Areas, doi: 10.1007/978-3-319-66239-8_8
DOI See at publisher website