scholarly journals Assessment of Current and Future Climate Change Impact on Soil Loss Rate of Agewmariam Watershed, Northern Ethiopia

2021 ◽  
Vol 14 ◽  
pp. 117862212199584
Author(s):  
Gebrehana Girmay ◽  
Awdenegest Moges ◽  
Alemayehu Muluneh
Keyword(s):  
Climate Change ◽  
Soil Erosion ◽  
Climate Change Impact ◽  
Soil Loss ◽  
Loss Rate ◽  
Future Climate Change ◽  
Northern Ethiopia ◽  
Rcp 8.5 ◽  
Change Impact ◽  
Soil Loss Rate

Soil erosion is 1 of the most important environmental problems that pose serious challenges to food security and the future development prospects of Ethiopia. Climate change influences soil erosion and is critical for the planning and management of soil and water resources. This study aimed to assess the current and future climate change impact on soil loss rate for the near future (2011-2040), middle future (2041-2070), and far future (2071-2100) periods relative to the reference period (1989-2018) in the Agewmariam watershed, Northern Ethiopia. The 20 models of Coupled Model Intercomparison Project phase 5 global climate models (GCMs) under Representative Concentration Pathway (RCP) 4.5 (intermediate scenario) and 8.5 (high emissions scenario) scenarios were used for climate projection. The statistical bias correction method was used to downscale GCMs. Universal Soil Loss Equation integrated with geographic information system was used to estimate soil loss. The results showed that the current average annual soil loss rate and the annual total soil loss on the study area were found to be 25 t ha−1 year−1 and 51 403.13 tons, respectively. The soil loss has increased by 3.0%, 4.7%, and 5.2% under RCP 4.5 scenarios and 6.0%, 9.52%, and 14.32% under RCP 8.5 scenarios in the 2020s, 2050s, and 2080s, respectively, from the current soil loss rate. Thus, the soil loss rate is expected to increase on all future periods (the 2020s, 2050s, and 2080s) under both scenarios (RCP 4.5 and RCP 8.5) due to the higher erosive power of the future intense rainfall. Thus, climate change will exacerbate the existing soil erosion problem and would need for vigorous new conservation policies and investments to mitigate the negative impacts of climate change on soil loss.

A process-based soil erosion model ensemble to reduce model uncertainty in climate change impact assessments

2021 ◽  
Author(s):  
Joris Eekhout ◽  
Agustín Millares-Valenzuela ◽  
Alberto Martínez-Salvador ◽  
Rafael García-Lorenzo ◽  
Pedro Pérez-Cutillas ◽  
...  
Keyword(s):  
Climate Change ◽  
Soil Erosion ◽  
Model Uncertainty ◽  
Extreme Precipitation ◽  
Climate Change Impact ◽  
Soil Loss ◽  
Model Ensemble ◽  
Erosion Model ◽  
Erosion Models ◽  
Change Impact

<p>The impact of climate change on future soil loss is commonly assessed with soil erosion models, which are potentially an important source of uncertainty. Here we propose a soil erosion model ensemble, with the aim to reduce the model uncertainty in climate change impact assessments. The model ensemble consisted of five continuous process-based soil erosion models that run at a daily time step, i.e. DHSVM, HSPF, INCA, MMF and SHETRAN. All models simulate detachment by raindrop impact (interrill erosion), detachment by runoff (rill erosion) and immediate deposition of sediment within the cell of its origin. The models were implemented in the SPHY hydrological model. The soil erosion model ensemble was applied in a semi-arid catchment in the southeast of Spain. We applied three future climate scenarios based on global mean temperature rise (+1.5, +2 and +3 ºC). Data from two contrasting regional climate models were used to assess how an increase and a decrease in extreme precipitation affect model uncertainty. Soil loss is projected to increase and decrease under climate change, mostly reflecting the change in extreme precipitation. Model uncertainty is found to increase with increasing slope, extreme precipitation and runoff, which reveals some inherent differences in model assumptions among the five models. Moreover, the model uncertainty increases in all climate change scenarios, independent on the projected change in annual precipitation and extreme precipitation. This supports the importance to consider model uncertainty through model ensembles of climate, hydrology, and soil erosion in climate change impact assessments.</p><p>This research was funded by ERDF/Spanish Ministry of Science, Innovation and Universities - State Research Agency (AEI) /Project CGL2017-84625-C2-1-R; State Program for Research, Development and Innovation Focused on the Challenges of Society.</p>

scholarly journals Estimating Landscape Vulnerability to Soil Erosion by RUSLE Model Using GIS and Remote Sensing: A Case of Zariema watershed, Northern Ethiopia

2020 ◽  
Author(s):  
Yonas Hagos
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Loss Rate ◽  
Steep Slope ◽  
Annual Rainfall ◽  
Northern Ethiopia ◽  
Rusle Model ◽  
Watershed Area ◽  
Factor C ◽  
Soil Loss Rate

Abstract Background:Zariema watershed located in the Tekeze basin Northern highlands of Ethiopia has been a subject to serious problem of soil erosion. Soil degradation due to soil erosion is one of the key environmental and socioeconomic case which threats soil nutrient depletion and food security in northern Ethiopian highlands. This study was conducted to estimate the soil loss rate and identify hotspot areas using RUSLE model in the Zariema watershed, Tekeze basin, Ethiopia.Methods:The rainfall – runoff erosivity(R) factor was determined from mean annual rainfall, soil erodibility(K) factor from soil map, Topographic factor (Ls) were generated from DEM, Crop management factor (C) and Conservation support practice factor(P) obtained from land use/land cover map. Finally, the factors were integrated with Arc GIS 10.3 tools to estimate soil loss rates and landscape vulnerability to soil erosion of the study watershed. Results:Annual Soil losses rates were estimated to be between 0 ton ha-1 year-1 in plain areas and 989 ton ha-1 year-1 in steep slope areas of the study watershed. The total annual soil loss from the entire watershed area of 2239.33Sq. Km was about 3,603,895.23 tons. About 31.41% of the study areas were affected through the soil loss hazard which is above acceptable soil loss rate 11 ton ha-1 year-1. The spatial hazard classification rate was 68.59% of the watershed area categorized as slight (0 – 11 ton ha-1 year-1), 8.03% moderate (12 – 18 ton ha-1 year-1), 7.64% high (19 – 30 ton ha-1 year-1), 6.65% very high (31 – 50 ton ha-1 year-1) and 9.09% severe (>51 ton ha-1 year-1). Conclusion:As a result, In the cultivation land around steep slope the soil loss rate was in sever condition. To mitigate the severity of the soil erosion in the identified prone area which accounts for about 31.41% of the total watershed area immediate action of soil and water conservation required.

scholarly journals Climate change impact on soil erosion in the Mandakini River Basin, North India

2016 ◽  
Vol 7 (5) ◽  
pp. 2373-2383 ◽  
Author(s):  
Deepak Khare ◽  
Arun Mondal ◽  
Sananda Kundu ◽  
Prabhash Kumar Mishra
Keyword(s):  
Climate Change ◽  
Soil Erosion ◽  
River Basin ◽  
Climate Change Impact ◽  
North India ◽  
Change Impact

Application of Erosion 2D Model for Erosion Studies in Makurdi Metropolis of Benue State, Nigeria

2011 ◽  
Vol 367 ◽  
pp. 815-825 ◽  
Author(s):  
M.O. Isikwue ◽  
T.G. Amile
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Loss Rate ◽  
Physically Based Model ◽  
Cover Cropping ◽  
Physically Based ◽  
The City ◽  
Land Grading ◽  
2D Model ◽  
Soil Loss Rate

The equations of Erosion 2D Model (a physically based model) were transformed into a computer programme called EROSOFT and used to predict the rate of soil loss in Makurdi metropolis. The model has detachment, transport and deposition components. Four sites were chosen within the metropolis for this study. Soil samples were collected from the sites for laboratory analysis. Rainfall and runoff fluids were collected from the sites to determine their densities. Levelling instrument was used to detremine the channels slopes. The model predicted an average annual soil loss rate of 310kg m-2s-1 for the metropolis. The sensitivity analysis of the model indicates that straight slopes are more prone to soil erosion. The result of the model deviates slightly from established facts that, sandy soils are more erodible and hence prone to be easily detached. Nevertheless, the model shows that soil erosion is influenced by slope geometry and rainfall intensity. The study attributes the major causes of soil erosion in the city to urban runoff concentration and removal of vegetation, and therefore suggests the use of land grading, land forming and cover cropping as well as conservation structures like road side drains for the control of erosion in the metropolis.

GIS estimation of annual average soil loss rate from Hangar River watershed using RUSLE

2019 ◽  
Vol 11 (2) ◽  
pp. 529-539 ◽  
Author(s):  
Mahmud Mustefa ◽  
Fekadu Fufa ◽  
Wakjira Takala
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Loss Rate ◽  
Study Finding ◽  
Mitigation Measures ◽  
Rainfall Erosivity ◽  
Vegetative Cover ◽  
Annual Average ◽  
Slope Length ◽  
Soil Loss Rate

Abstract Currently, soil erosion is the major environmental problem in the Blue Nile, Hangar watershed in particular. This study aimed to estimate the spatially distributed mean annual soil erosion and map the most vulnerable areas in Hangar watershed using the revised universal soil loss equation. In this model, rainfall erosivity (R-factor), soil erodibility (K-factor), slope steepness and slope length (LS-factor), vegetative cover (C-factor), and conservation practice (P-factor) were considered as the influencing factors. Maps of these factors were generated and integrated in ArcGIS and then the annual average soil erosion rate was determined. The result of the analysis showed that the amount of soil loss from the study area ranges from 1 to 500 tha−1 yr−1 with an average annual soil loss rate of 32 tha−1 yr−1. Considering contour ploughing with terracing as a fully developed watershed management, the resulting soil loss rate was reduced from 32 to 19.2 tha−1 yr−1. Hence, applying contour ploughing with terracing effectively reduces the vulnerability of the watershed by 40%. Based on the spatial vulnerability of the watershed, most critical soil erosion areas were situated in the steepest part of the watershed. The result of the study finding is helpful for stakeholders to take appropriate mitigation measures.

scholarly journals Assessment of Future Climate Change Impact on Groundwater recharge, Baseflow and Sediment in Steep Sloping Watershed

2014 ◽  
Vol 16 (2) ◽  
pp. 173-185 ◽  
Author(s):  
Ji Min Lee ◽  
Younghun Jung ◽  
Younshik Park ◽  
Hyunwoo Kang ◽  
Kyoung Jae Lim ◽  
...  
Keyword(s):  
Climate Change ◽  
Groundwater Recharge ◽  
Climate Change Impact ◽  
Future Climate ◽  
Future Climate Change ◽  
Change Impact

scholarly journals Assessing climate change impact on the hydropower potential of the Bamboi catchment (Black Volta, West Africa)

2021 ◽  
Vol 384 ◽  
pp. 349-354
Author(s):  
Yacouba Yira ◽  
Tariro Cynthia Mutsindikwa ◽  
Aymar Yaovi Bossa ◽  
Jean Hounkpè ◽  
Seyni Salack
Keyword(s):  
Climate Change ◽  
West Africa ◽  
Climate Change Impact ◽  
Climate Models ◽  
Future Climate Change ◽  
Mean Annual Precipitation ◽  
Hydropower Generation ◽  
Hydropower Potential ◽  
Change Impact ◽  
The Impact

Abstract. This study evaluates the impact of future climate change (CC) on the hydropower generation potential of the Bamboi catchment (Black Volta) in West Africa using a conceptual rainfall-runoff model (HBV light) and regional climate models (RCMs)–global climate models (GCMs). Two climate simulation datasets MPI-ESM-REMO (CORDEX) and GFDL-ESM2M-WRF (WASCAL) under RCP4.5 were applied to the validated hydrological model to simulate the catchment runoff. Based on reference and future simulated discharges, a theoretical 1.3 MW run of river hydro power plant was designed to evaluate the hydropower generation. Hydrological and hydropower generation changes were expressed as the relative difference between two future periods (2020–2049 and 2070–2099) and a reference period (1983–2005). The climate models' ensemble projected a mean annual precipitation increase by 8.8 % and 7.3 % and discharge increase by 11.4 % and 9.735 % for the 2020–2049 and 2070–2099 periods respectively (for bias corrected data). On the contrary an overall decrease of hydropower generation by −9.1 % and −8.4% for the 2020–2049 and 2070–2099 periods was projected respectively. The results indicate that projected increases in discharge should not solely be considered as leading to an increase in hydropower potential when prospecting climate change impact on hydropower.

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