scholarly journals Assessing the Effect of Landuse/Land Cover (1986-2020) on Soil Loss in Alluvium Geologic Formation Using Geospatial Technology in Southern Nigeria

2021 ◽  
pp. 1-11
Author(s):  
L. C. Orakwe ◽  
A. E. Ekpo ◽  
C. M. Abraham ◽  
N. Tom-Cyprian
Keyword(s):  
Land Cover ◽  
Soil Loss ◽  
Continuous Process ◽  
Image Data ◽  
Resource Planning ◽  
Thematic Mapper ◽  
Rainfall Erosivity ◽  
Land Use Land Cover ◽  
Slope Length ◽  
Rusle Model

The occurrence of soil loss is a continuous process and occurs spatially across the earth’s surface. The study of soil loss is a necessity for proper understanding of the processes and the rate of soil loss for conservational purpose. Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper Plus (ETM+)/Operational Land Imager (OLI) image data was acquired for 1986, 2003 and 2020 were used to derive the C factor of the RUSLE model while other factors of the model were kept fixed for the years considering their inability to change easily. The RUSLE model was used to determine the trend of the soil loss on the alluvium geologic formation considering their land use/land cover changes for 1986, 2003 and 2020. The rainfall erosivity of the study area had an average of 8201.45MJmmha-1h-1yr-1. The soil erodibility index of the soils obtained from Alluvium had an average of 0.150tons MJ-1 hmm-1. The slope length and steepness factor of the study area range from 0 to 2.574. the crop cover factor of for 1986 range from 0.52 to 0.87, 2003 range from 0.52 to 0.87 and 2020 range from 0.62 to 0.92. No active field conservation was found out within the study area as described by Wischmeier and Smith. The results obtained show that 1986, 2003 and 2020 had a soil loss of 1966.3, 2167.85 and 3361.14 tonha-1yr-1 respectively. The results show that the study area is experiencing an increased trend of soil loss. This result can serve as guide into understanding the past and current rate of soil loss for soil resource planning and management

scholarly journals EVALUATION OF THE IMPACTS OF LAND USE AND LAND COVER CHANGES USING EROSION ASSESSMENT MODEL AT TIKUR WUHA WATERSHED

2020 ◽  
Vol 8 (6) ◽  
Author(s):  
Tamirneh Kifle ◽  
Asnakew Deres ◽  
Assefa Birku ◽  
Tesfalem Aberham ◽  
Demke Mengist
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Soil Loss ◽  
Resource Planning ◽  
Assessment Model ◽  
Annual Rainfall ◽  
Land Cover Changes ◽  
Land Resource ◽  
Land Use Land Cover

Rapid increases in population, forest clearing   and   continuing search    for a farm   land   have induced pressure on natural resource.  In order to reverse such kind of problem assessing the level of problem and finding solution at watershed level is necessary. The studies of land use land cover changes and their effects on soil erosion and runoff patterns at the watershed level are essential in water resource planning and management. This study provides an approach to identify   the   effects   of   land   use land cover   changes   on runoff   and   sediment   in Tikur wuha watershed. The changes in land use land cover were associated with growing demand of wood for fire, charcoal, construction materials, household furniture, pulp and paper industries, and expansion of farming and grazing land. The study was conducted the impacts of land use land cover changes, to identify the main cause erosion, to assess soil loss rate in different slope classes, agricultural activities and its effect on land resource by using erosion assessment model. USLE is important to predict the annual soil loss by using different parameters. The necessary data were generated from mean annual rainfall, previous study of the area, erosivity factor, erodibilty factor, topographic factor (LS), the cropping management factor, erosion control factor, both primary and secondary data as well as key informants interview, field observation, by distribution of structural survey questionnaire and field measurement. The result of the analysis showed that the amount of soil loss at Tikur wuha watershed is about 5.58 ton/ ha/yr. The study finding suggest that understanding of some of the socio- economic, institutional and biophysical factors that determine land cover change of the area would contribute to advice appropriate strategies to achieve the desired change in SWC process and to alleviate damage land cover change in the study area. In selecting priority intervention areas in the rehabilitation of land use land cover, strategies should considered the socio-economic and specific land characteristics as well as farmers preference.  

Estimating storm erosion with a rainfall simulator

1997 ◽  
Vol 77 (4) ◽  
pp. 669-676 ◽  
Author(s):  
S. C. Nolan ◽  
L. J. P. van Vliet ◽  
T. W. Goddard ◽  
T. K. Flesch
Keyword(s):  
Soil Loss ◽  
Conventional Tillage ◽  
Reduced Tillage ◽  
Natural Soil ◽  
Rainfall Erosivity ◽  
Slope Length ◽  
Rainfall Simulator ◽  
Rainfall Events ◽  
Plot Size ◽  
Natural Rainfall

Interpreting soil loss from rainfall simulators is complicated by the uncertain relationship between simulated and natural rainstorms. Our objective was to develop and test a method for estimating soil loss from natural rainfall using a portable rainfall simulator (1 m2 plot size). Soil loss from 12 rainstorms was measured on 144-m2 plots with barley residue in conventional tillage (CT), reduced tillage (RT) and zero tillage (ZT) conditions. A corresponding "simulated" soil loss was calculated by matching the simulator erosivity to each storm's erosivity. High (140 mm h−1) and low (60 mm h−1) simulation intensities were examined. The best agreement between simulated and natural soil loss occurred using the low intensity, after making three adjustments. The first was to compensate for the 38% lower kinetic energy of the simulator compared with natural rain. The second was for the smaller slope length of the simulator plot. The third was to begin calculating simulator erosivity only after runoff began. After these adjustments, the simulated soil loss over all storms was 99% of the natural soil loss for CT, 112% for RT and 95% for ZT. Our results show that rainfall simulators can successfully estimate soil loss from natural rainfall events. Key words: Natural rainfall events, simulated rainfall, erosivity, tillage

scholarly journals Estimation of annual soil erosion dynamics (2005 - 2015) in Pakistan using Revised Universal Soil Loss Equation (RUSLE)

2021 ◽  
Author(s):  
Hammad Gilani ◽  
Adeel Ahmad ◽  
Isma Younes ◽  
Sawaid Abbas
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Management Practices ◽  
Climatic Factors ◽  
Universal Soil Loss Equation ◽  
Rainfall Erosivity ◽  
Slope Length ◽  
Conservation Practice ◽  
Administrative Units ◽  
Soil Loss Equation

Abrupt changes in climatic factors, exploitation of natural resources, and land degradation contribute to soil erosion. This study provides the first comprehensive analysis of annual soil erosion dynamics in Pakistan for 2005 and 2015 using publically available climatic, topographic, soil type, and land cover geospatial datasets at 1 km spatial resolution. A well-accepted and widely applied Revised Universal Soil Loss Equation (RUSLE) was implemented for the annual soil erosion estimations and mapping by incorporating six factors; rainfall erosivity (R), soil erodibility (K), slope-length (L), slope-steepness (S), cover management (C) and conservation practice (P). We used a cross tabular or change matrix method to assess the annual soil erosion (ton/ha/year) changes (2005-2015) in terms of areas and spatial distriburtions in four soil erosion classes; i.e. Low (<1), Medium (1–5], High (5-20], and Very high (>20). Major findings of this paper indicated that, at the national scale, an estimated annual soil erosion of 1.79 ± 11.52 ton/ha/year (mean ± standard deviation) was observed in 2005, which increased to 2.47 ±18.14 ton/ha/year in 2015. Among seven administrative units of Pakistan, in Azad Jammu & Kashmir, the average soil erosion doubled from 14.44 ± 35.70 ton/ha/year in 2005 to 28.03 ± 68.24 ton/ha/year in 2015. Spatially explicit and temporal annual analysis of soil erosion provided in this study is essential for various purposes, including the soil conservation and management practices, environmental impact assessment studies, among others.

scholarly journals RUSLE Model Based Annual Soil Loss Quantification for Soil Erosion Protection in Fincha Catchment, Abay River Basin, Ethiopia.

2021 ◽  
Author(s):  
Habtamu Tamiru ◽  
Meseret Wagari
Keyword(s):  
Soil Erosion ◽  
River Basin ◽  
Soil Loss ◽  
Annual Rainfall ◽  
Rainfall Erosivity ◽  
Landsat 8 ◽  
Land Resources ◽  
Rusle Model ◽  
Factor C ◽  
Significant Factors

Abstract Background: The quantity of soil loss as a result of soil erosion is dramatically increasing in catchment where land resources management is very weak. The annual dramatic increment of the depletion of very important soil nutrients exposes the residents of this catchment to high expenses of money to use artificial fertilizers to increase the yield. This paper was conducted in Fincha Catchment where the soil is highly vulnerable to erosion, however, where such studies are not undertaken. This study uses Fincha catchment in Abay river basin as the study area to quantify the annual soil loss, where such studies are not undertaken, by implementing Revised Universal Soil Loss Equation (RUSLE) model developed in ArcGIS version 10.4. Results: Digital Elevation Model (12.5 x 12.5), LANDSAT 8 of Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS), Annual Rainfall of 10 stations (2010-2019) and soil maps of the catchment were used as input parameters to generate the significant factors. Rainfall erosivity factor (R), soil erodibility factor (K), cover and management factor (C), slope length and steepness factor (LS) and support practice factor (P) were used as soil loss quantification significant factors. It was found that the quantified average annual soil loss ranges from 0.0 to 76.5 t ha-1 yr-1 was obtained in the catchment. The area coverage of soil erosion severity with 55%, 35% and 10% as low to moderate, high and very high respectively were identified. Conclusion: Finally, it was concluded that having information about the spatial variability of soil loss severity map generated in the RUSLE model has a paramount role to alert land resources managers and all stakeholders in controlling the effects via the implementation of both structural and non-structural mitigations. The results of the RUSLE model can also be further considered along with the catchment for practical soil loss quantification that can help for protection practices.

scholarly journals Effect of Land Use Land Cover and Climate Change on River Flow and Soil Loss in Didessa River Basin, South West Blue Nile, Ethiopia

Hydrology ◽  
2018 ◽  
Vol 6 (1) ◽  
pp. 2 ◽  
Author(s):  
Kinati Chimdessa ◽  
Shoeb Quraishi ◽  
Asfaw Kebede ◽  
Tena Alamirew
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Land Cover ◽  
River Basin ◽  
Sediment Yield ◽  
Soil Loss ◽  
River Flow ◽  
Land Use Land Cover ◽  
The Impact ◽  
Soil Losses

In the Didessa river basin, which is found in Ethiopia, the human population number is increasing at an alarming rate. The conversion of forests, shrub and grasslands into cropland has increased in parallel with the population increase. The land use/land cover change (LULCC) that has been undertaken in the river basin combined with climate change may have affected the Didessa river flow and soil loss. Therefore, this study was designed to assess the impact of LULCC on the Didessa river flow and soil loss under historical and future climates. Land use/land cover (LULC) of the years 1986, 2001 and 2015 were independently combined with the historical climate to assess their individual impacts on river flow and soil loss. Further, the impact of future climates under Representative Concentration Pathways (RCP2.6, RCP4.5 and RCP8.5) scenarios on river flow and soil loss was assessed by combining the pathways with the 2015 LULC. A physically based Soil and Water Assessment Tool (SWAT2012) model in the ArcGIS 10.4.1 interface was used to realize the purpose. Results of the study revealed that LULCC that occurred between 1986 and 2015 resulted in increased average sediment yield by 20.9 t ha−1 yr−1. Climate change under RCP2.6, RCP4.5 and RCP8.5 combined with 2015 LULC increased annual average soil losses by 31.3, 50.9 and 83.5 t ha−1 yr−1 compared with the 2015 LULC under historical climate data. It was also found that 13.4%, 47.1% and 87.0% of the total area may experience high soil loss under RCP2.6, RCP4.5 and RCP8.5, respectively. Annual soil losses of five top-priority sub catchments range from 62.8 to 57.7 per hectare. Nash Stuncliffe Simulation efficiency (NSE) and R2 values during model calibration and validation indicated good agreement between observed and simulated values both for flow and sediment yield.

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 Effects of Climate and Land-Cover Changes on Soil Erosion in Brazilian Pantanal

2019 ◽  
Vol 11 (24) ◽  
pp. 7053 ◽  
Author(s):  
Carina Colman ◽  
Paulo Oliveira ◽  
André Almagro ◽  
Britaldo Soares-Filho ◽  
Dulce Rodrigues
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Soil Erosion ◽  
Land Cover ◽  
Ecosystem Service ◽  
Soil Loss ◽  
Land Cover Changes ◽  
Rainfall Erosivity ◽  
Comprehensive Planning ◽  
Brazilian Pantanal

The Pantanal biome integrates the lowlands of the Upper Paraguay Basin (UPB), which is hydrologically connected to the biomes of the Cerrado and Amazon (the highlands of the UPB). The effects of recent land-cover and land-use (LCLU) changes in the highlands, combined with climate change, are still poorly understood in this region. Here, we investigate the effects of soil erosion in the Brazilian Pantanal under climate and LCLU changes by combining different scenarios of projected rainfall erosivity and land-cover management. We compute the average annual soil erosion for the baseline (2012) and projected scenarios for 2020, 2035, and 2050. For the worst scenario, we noted an increase in soil loss of up to 100% from 2012 to 2050, associated with cropland expansion in some parts of the highlands. Furthermore, for the same period, our results indicated an increase of 20 to 40% in soil loss in parts of the Pantanal biome, which was associated with farmland increase (mainly for livestock) in the lowlands. Therefore, to ensure water, food, energy, and ecosystem service security over the next decades in the whole UPB, robust and comprehensive planning measures need to be developed, especially for the most impacted areas found in our study.

scholarly journals Land use/land cover change effect on Soil erosion and Sediment Delivery on Winike Watershed, Omo Gibe Basin, Ethiopia

2019 ◽  
Author(s):  
Abreham Berta Aneseyee
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Land Cover ◽  
Land Cover Change ◽  
Soil Loss ◽  
Management Practices ◽  
Delivery Ratio ◽  
Land Use Land Cover ◽  
Sediment Delivery ◽  
Sediment Export

Abstract Background: Information on soil loss and sediment export is essential to identify hotspots of soil erosion for conservation interventions in a given watershed. This study aims at investigating the dynamic of soil loss and sediment export associated with land use/land cover change and identifies soil loss hotspot areas in Winike watershed of Omo-gibe basin of Ethiopia. Spatial data collected from satellite images, topographic maps, meteorological and soil data were analyzed. Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) of sediment delivery ratio (SDR) model was used based on analysis of land use/land cover maps and RUSLE factors. Result: The results showed that total soil loss increased from 774.86 thousand tons in 1988 to 951.21 thousand tons in 2018 while the corresponding sediment export increased by 3.85 thousand tons in the same period. These were subsequently investigated in each land-use type. Cultivated fields generated the highest soil erosion rate, which increased by 10.02 t/ha/year in 1988 to 43.48 t/ha/year in 2018. This corresponds with the expansion of the cultivated area that increased from 44.95 thousand ha in 1988 to 59.79 thousand ha in 2018. This is logical as the correlation between soil loss and sediment delivery and expansion of cultivated area is highly significant (p<0.01). Sub-watershed six (SW-6) generated the highest soil loss (62.77 t/ha/year) and sediment export 16.69 t/ha/year, followed by Sub-watershed ten (SW-10) that are situated in the upland plateau. Conversely, the lower reaches of the watershed are under dense vegetation cover and experiencing less erosion. Conclusion: Overall, the changes in land use/land cover affect significantly the soil erosion and sediment export dynamism. This research is used to identify an area to prioritize the watershed for immediate management practices. Thus, land use policy measures need to be enforced to protect the hydropower generation dams at downstream and the ecosystem at the watershed.

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