IMPACT OF LULC ON SOIL EROSION RATES USING RUSLE MODEL AND GIS TECHNIQUES – A STUDY OF NAGAVALI RIVER BASIN

Abstract. Large uncertainties exist in estimated rates and the extent of soil erosion by surface runoff on a global scale. This limits our understanding of the global impact that soil erosion might have on agriculture and climate. The Revised Universal Soil Loss Equation (RUSLE) model is, due to its simple structure and empirical basis, a frequently used tool in estimating average annual soil erosion rates at regional to global scales. However, large spatial-scale applications often rely on coarse data input, which is not compatible with the local scale on which the model is parameterized. Our study aims at providing the first steps in improving the global applicability of the RUSLE model in order to derive more accurate global soil erosion rates. We adjusted the topographical and rainfall erosivity factors of the RUSLE model and compared the resulting erosion rates to extensive empirical databases from the USA and Europe. By scaling the slope according to the fractal method to adjust the topographical factor, we managed to improve the topographical detail in a coarse resolution global digital elevation model. Applying the linear multiple regression method to adjust rainfall erosivity for various climate zones resulted in values that compared well to high resolution erosivity data for different regions. However, this method needs to be extended to tropical climates, for which erosivity is biased due to the lack of high resolution erosivity data. After applying the adjusted and the unadjusted versions of the RUSLE model on a global scale we find that the adjusted version shows a global higher mean erosion rate and more variability in the erosion rates. Comparison to empirical data sets of the USA and Europe shows that the adjusted RUSLE model is able to decrease the very high erosion rates in hilly regions that are observed in the unadjusted RUSLE model results. Although there are still some regional differences with the empirical databases, the results indicate that the methods used here seem to be a promising tool in improving the applicability of the RUSLE model at coarse resolution on a global scale.

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Soil erosion rates in two karst peak-cluster depression basins of northwest Guangxi, China: Comparison of the RUSLE model with 137Cs measurements

Geomorphology ◽

10.1016/j.geomorph.2015.10.013 ◽

2016 ◽

Vol 253 ◽

pp. 217-224 ◽

Cited By ~ 40

Author(s):

Teng Feng ◽

Hongsong Chen ◽

Viktor O. Polyakov ◽

Kelin Wang ◽

Xinbao Zhang ◽

...

Keyword(s):

Soil Erosion ◽

Peak Cluster ◽

Rusle Model ◽

Erosion Rates ◽

Soil Erosion Rates

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Improving the global applicability of the RUSLE model – adjustment of the topographical and rainfall erosivity factors

Geoscientific Model Development Discussions ◽

10.5194/gmdd-8-2991-2015 ◽

2015 ◽

Vol 8 (3) ◽

pp. 2991-3035 ◽

Cited By ~ 6

Author(s):

V. Naipal ◽

C. Reick ◽

J. Pongratz ◽

K. Van Oost

Keyword(s):

High Resolution ◽

Soil Erosion ◽

Global Scale ◽

Rainfall Erosivity ◽

Large Spatial Scale ◽

Rusle Model ◽

Erosion Rates ◽

Coarse Resolution ◽

Soil Erosion Rates ◽

The Usa

Abstract. Large uncertainties exist in estimated rates and the extent of soil erosion by surface runoff on a global scale, and this limits our understanding of the global impact that soil erosion might have on agriculture and climate. The Revised Universal Soil Loss Equation (RUSLE) model is due to its simple structure and empirical basis a frequently used tool in estimating average annual soil erosion rates at regional to global scales. However, large spatial scale applications often rely on coarse data input, which is not compatible with the local scale at which the model is parameterized. This study aimed at providing the first steps in improving the global applicability of the RUSLE model in order to derive more accurate global soil erosion rates. We adjusted the topographical and rainfall erosivity factors of the RUSLE model and compared the resulting soil erosion rates to extensive empirical databases on soil erosion from the USA and Europe. Adjusting the topographical factor required scaling of slope according to the fractal method, which resulted in improved topographical detail in a coarse resolution global digital elevation model. Applying the linear multiple regression method to adjust rainfall erosivity for various climate zones resulted in values that are in good comparison with high resolution erosivity data for different regions. However, this method needs to be extended to tropical climates, for which erosivity is biased due to the lack of high resolution erosivity data. After applying the adjusted and the unadjusted versions of the RUSLE model on a global scale we find that the adjusted RUSLE model not only shows a global higher mean soil erosion rate but also more variability in the soil erosion rates. Comparison to empirical datasets of the USA and Europe shows that the adjusted RUSLE model is able to decrease the very high erosion rates in hilly regions that are observed in the unadjusted RUSLE model results. Although there are still some regional differences with the empirical databases, the results indicate that the methods used here seem to be a promising tool in improving the applicability of the RUSLE model on a coarse resolution on global scale.

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The application of137Cs and210Pbexmethods in soil erosion research of Titel loess plateau, Vojvodina, Northern Serbia

Open Geosciences ◽

10.1515/geo-2020-0002 ◽

2020 ◽

Vol 12 (1) ◽

pp. 11-24

Author(s):

Kristina S. Kalkan ◽

Sofija Forkapić ◽

Slobodan B. Marković ◽

Kristina Bikit ◽

Milivoj B. Gavrilov ◽

...

Keyword(s):

Soil Erosion ◽

Loess Plateau ◽

Alternative Methods ◽

Delivery Ratio ◽

Undisturbed Soil ◽

Migration Model ◽

Erosion Rates ◽

Soil Erosion Rates ◽

Profile Distribution ◽

And Migration

AbstractSoil erosion is one of the largest global problems of environmental protection and sustainable development, causing serious land degradation and environmental deterioration. The need for fast and accurate soil rate assessment of erosion and deposition favors the application of alternative methods based on the radionuclide measurement technique contrary to long-term conventional methods. In this paper, we used gamma spectrometry measurements of 137Cs and unsupported 210Pbex in order to quantify the erosion on the Titel Loess Plateau near the Tisa (Tisza) River in the Vojvodina province of Serbia. Along the slope of the study area and in the immediate vicinity eight representative soil depth profiles were taken and the radioactivity content in 1 cm thick soil layers was analyzed. Soil erosion rates were estimated according to the profile distribution model and the diffusion and migration model for undisturbed soil. The net soil erosion rates, estimated by 137Cs method range from −2.3 t ha−1 yr−1 to −2.7 t ha−1 yr−1, related to the used conversion model which is comparable to published results of similar studies of soil erosion in the region. Vertical distribution of natural radionuclides in soil profiles was also discussed and compared with the profile distribution of unsupported 210Pbex measurements. The use of diffusion and migration model to convert the results of 210Pbex activities to soil redistribution rates indicates a slightly higher net erosion of −3.7 t ha−1 yr−1 with 98% of the sediment delivery ratio.

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Assessing Changes in Soil Erosion Rates: A Markov Chain Analysis

Journal of Agricultural and Applied Economics ◽

10.1017/s1074070800008877 ◽

1999 ◽

Vol 31 (3) ◽

pp. 611-622 ◽

Cited By ~ 3

Author(s):

Rhonda Skaggs ◽

Soumen Ghosh

Keyword(s):

Markov Chain ◽

Soil Erosion ◽

Great Plains ◽

Markov Chain Analysis ◽

Conservation Policies ◽

Erosion Rates ◽

National Resources Inventory ◽

Long Run ◽

Chain Analysis ◽

Soil Erosion Rates

AbstractMarkov chain analysis (one-step and long-run) is applied to the National Resources Inventory (NRI) database to evaluate changes in wind-based soil erosion rates over time. The research compares changes in soil erosion rates between NRI sample sites with and without applied conservation practices for a random sample of Great Plains counties. No significant differences between sites are found for half of the counties evaluated. The effectiveness and efficiency of conservation policies are thus questioned in light of these research results.

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Dynamics of soil erosion rates and controlling factors in the Northern Ethiopian Highlands – towards a sediment budget

Earth Surface Processes and Landforms ◽

10.1002/esp.1569 ◽

2008 ◽

Vol 33 (5) ◽

pp. 695-711 ◽

Cited By ~ 80

Author(s):

Jan Nyssen ◽

Jean Poesen ◽

Jan Moeyersons ◽

Mitiku Haile ◽

Jozef Deckers

Keyword(s):

Soil Erosion ◽

Sediment Budget ◽

Controlling Factors ◽

Ethiopian Highlands ◽

Erosion Rates ◽

Soil Erosion Rates

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Plastic Covered Cropping Systems: Runoff Patterns and Soil Erosion Rates

10.13031/2013.39254 ◽

2011 ◽

Author(s):

Sebastian Arnhold ◽

Christopher L Shope ◽

Bernd Huwe

Keyword(s):

Soil Erosion ◽

Cropping Systems ◽

Erosion Rates ◽

Soil Erosion Rates

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

10.21203/rs.3.rs-250848/v1 ◽

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.

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Do suspended sediment and bedload move progressively from the summit to the sea along Magela Creek, northern Australia?

Proceedings of the International Association of Hydrological Sciences ◽

10.5194/piahs-367-283-2015 ◽

2015 ◽

Vol 367 ◽

pp. 283-290

Author(s):

W. D. Erskine ◽

M. J. Saynor ◽

K. Turner ◽

T. Whiteside ◽

J. Boyden ◽

...

Keyword(s):

Soil Erosion ◽

Suspended Sediment ◽

Waste Rock ◽

Uranium Mine ◽

Northern Australia ◽

Sediment Yields ◽

Flood Plains ◽

Erosion Rates ◽

Base Level ◽

Soil Erosion Rates

Abstract. Soil erosion rates on plots of waste rock at Ranger uranium mine and basin sediment yields have been measured for over 30 years in Magela Creek in northern Australia. Soil erosion rates on chlorite schist waste rock are higher than for mica schist and weathering is also much faster. Sediment yields are low but are further reduced by sediment trapping effects of flood plains, floodouts, billabongs and extensive wetlands. Suspended sediment yields exceed bedload yields in this deeply weathered, tropical landscape, but the amount of sand transported greatly exceeds that of silt and clay. Nevertheless, sand is totally stored above the topographic base level. Longitudinal continuity of sediment transport is not maintained. As a result, suspended sediment and bedload do not move progressively from the summit to the sea along Magela Creek and lower Magela Creek wetlands trap about 90.5% of the total sediment load input.

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