Design and Implementation of Regional LS Factor Computing Tool Based on GIS and Array Operation

2013 ◽  
Vol 394 ◽  
pp. 509-514
Author(s):  
Hong Ming Zhang ◽  
Qin Ke Yang ◽  
Shu Qin Li ◽  
Mei Li Wang ◽  
Ming Ying ◽  
...  
Keyword(s):  
Soil Loss ◽  
Large Scale ◽  
Universal Soil Loss Equation ◽  
Graphic User Interface ◽  
Slope Length ◽  
Long Time ◽  
Area Unit ◽  
User Friendly ◽  
Gis Software ◽  
Soil Loss Equation

For over 40 years, the universal soil loss equation (USLE) and its revised version the revised universal soil loss equation (RUSLE) have been used all over the world for soil mean annual loss per area unit. Because of the watershed erosion models are under developing, many researchers applied the USLE and RUSLE to estimate soil loss in watershed estimations. However, a major limitation is the difficulty in extracting the LS factor. The geographic information system-based (GIS-based) methods which have been developed for estimating the slope length for USLE and RUSLE model also have limitations. A series of ARC/INFO AML program was created that can calculate LS factor for the USLE, however the program need a very long time to run in wide-ranging areas. The flowpath and cumulative cell length-based method (FCL) overcomes this disadvantage but does not consider the following questions: (1) Some original AML program functions are not achieved, so results are different. (2) Using USLE to calculate LS factor that do not adapt to the erosion environment of China. (3) There isnt a friendly graphic user interface. The purpose of this research was to overcome these limitations and extend the FCL method through Integrating CSLE equation. We developed a LS calculation tool (LS-TOOL) in Microsofts .NET environment using C# with a user-friendly interface. Comparing the LS factor calculated with the FCL method and AML method, LS factor values generated by using LS-TOOL method delivers improved results. The LS-TOOL algorithm can automatically calculate slope length, slope steepness, L factor, S factor, and LS factors, providing the results as ASCII files which can be easily used in some GIS software. This study is an important step forward in conducting fast large-scale erosion evaluation.

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.

Digital mapping of RUSLE slope length and steepness factor across New South Wales, Australia

Soil Research ◽  
2015 ◽  
Vol 53 (2) ◽  
pp. 216 ◽  
Author(s):  
Xihua Yang
Keyword(s):  
Land Use Planning ◽  
Soil Loss ◽  
Overland Flow ◽  
New South ◽  
New South Wales ◽  
Slope Angle ◽  
Universal Soil Loss Equation ◽  
Slope Length ◽  
South Wales ◽  
Soil Loss Equation

The Universal Soil Loss Equation (USLE) and its main derivate, the Revised Universal Soil Loss Equation (RUSLE), are widely used in estimating hillslope erosion. The effects of topography on hillslope erosion are estimated through the product of slope length (L) and slope steepness (S) subfactors, or LS factor, which often contains the highest detail and plays the most influential role in RUSLE. However, current LS maps in New South Wales (NSW) are either incomplete (e.g. point-based) or too coarse (e.g. 250 m), limiting RUSLE-based applications. The aim of this study was to develop automated procedures in a geographic information system (GIS) to estimate and map the LS factor across NSW. The method was based on RUSLE specifications and it incorporated a variable cutoff slope angle, which improves the detection of the beginning and end of each slope length. An overland-flow length algorithm for L subfactor calculation was applied through iterative slope-length cumulation and maximum downhill slope angle. Automated GIS scripts have been developed for LS factor calculation so that the only required input data are digital elevation models (DEMs). Hydrologically corrected DEMs were used for LS factor calculation on a catchment basis, then merged to form a seamless LS-factor digital map for NSW with a spatial resolution ~30 m (or 1 s). The modelled LS values were compared with the reference LS values, and the coefficient of efficiency reached 0.97. The high-resolution digital LS map produced is now being used along with other RUSLE factors in hillslope erosion modelling and land-use planning at local and regional scales across NSW.

scholarly journals An improved method for calculating slope length (λ) and the LS parameters of the Revised Universal Soil Loss Equation for large watersheds

Geoderma ◽  
2017 ◽  
Vol 308 ◽  
pp. 36-45 ◽  
Author(s):  
Hongming Zhang ◽  
Jicheng Wei ◽  
Qinke Yang ◽  
Jantiene E.M. Baartman ◽  
Lingtong Gai ◽  
...  
Keyword(s):  
Soil Loss ◽  
Universal Soil Loss Equation ◽  
Improved Method ◽  
Slope Length ◽  
Soil Loss Equation

scholarly journals Remote Sensing Analysis In RUSLE Erosion Estimation

2018 ◽  
Author(s):  
Ketut Wikantika
Keyword(s):  
Remote Sensing ◽  
Vegetation Cover ◽  
Soil Loss ◽  
Spatial Information ◽  
Universal Soil Loss Equation ◽  
Large Area ◽  
Coverage Area ◽  
Erosion Processes ◽  
Long Time ◽  
Soil Loss Equation

Soil erosion is a major issue in various hemispheres. It is because erosion affects the survival of ecosystem. Diverse human actions, e.g., bushes burning and illegal logging, play a role in accelerating erosion. Climate factor such as rain intensity has also an influence in the release of soil particles. Therefore, a regular identification of those factors that affect erosion processes is highly needed in order to keep an environmental sustainable. Different areas in Indonesia have different erosion variable characteristics. One of the characteristics is indicated by the varieties ofvegetation cover, where a loose vegetation cover causes soil surfaces open for a long time period. Till now, researches dealing with the modeling of erosions with wide area coverage are few, since erosion observations have always been conducted by direct observations in the field, hence time consuming. Therefore, an erosion mapping model that is applied in a wide coverage area and the up to date of data is needed. Spatially, erosions can be depicted in a form of spatial information system model describing their potential class levels. There are several erosion models that can be used to find out the erosion occurring on a land, among others Universal Soil Loss Equation (USLE) model or its modification Revised Universal Soil Loss Equation (RUSLE). RUSLE erosion model consists of rainfall, soil erodibility, vegetation cover, slope gradient and length, and support practice factors. Recent technology in remote sensing allowed vegetation cover to beanalysed from satellite imagery, make the possibility of erosion analysis in large area in shorter time.

Assessment of Soil Loss using Revised Universal Soil Loss Equation (RUSLE): A Remote Sensing and GIS Approach

2018 ◽  
Vol 2 (1) ◽  
pp. 65-75 ◽  
Author(s):  
Ajaykumar Kadam ◽  
B. N. Umrikar ◽  
R. N. Sankhua
Keyword(s):  
Remote Sensing ◽  
Soil Loss ◽  
Remote Sensing Data ◽  
Tropical Rainfall Measuring Mission ◽  
Remote Sensing And Gis ◽  
Universal Soil Loss Equation ◽  
Rainfall Erosivity ◽  
Slope Length ◽  
Gis Environment ◽  
Soil Loss Equation

A comprehensive methodology that combines Revised Universal Soil Loss Equation (RUSLE), Remote Sensing data and Geographic Information System (GIS) techniques was used to determine the soil loss vulnerability of an agriculture mountainous watershed in Maharashtra, India. The spatial variation in rate of annual soil loss was obtained by integrating raster derived parameter in GIS environment. The thematic layers such as TRMM [Tropical Rainfall Measuring Mission] derived rainfall erosivity (R), soil erodibility (K), GDEM based slope length and steepness (LS), land cover management (C) and factors of conservation practices (P) were calculated to identify their effects on average annual soil loss. The highest potential of estimated soil loss was 688.397 t/ha/yr. The mean annual soil loss is 1.26 t/ha/yr and highest soil loss occurs on the main watercourse, since high slope length and steepness. The spatial soil loss maps prepared with RUSLE method using remote sensing and GIS can be helpful as a lead idea in arising plans for land use development and administration in the ecologically sensitive hilly areas.

Identifying Potential Erosion-Prone Areas in the Indian Himalayan Region Using the Revised Universal Soil Loss Equation (RUSLE)

2021 ◽  
Vol 18 (1) ◽  
pp. 15-23
Author(s):  
Dorje Dawa ◽  
Vairaj Arjune
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Large Scale ◽  
Equation Model ◽  
Universal Soil Loss Equation ◽  
Himalayan Region ◽  
Remotely Sensed Data ◽  
Study Region ◽  
Indian Himalayan Region ◽  
Soil Loss Equation

Soil erosion is one of the most critical environmental issues with severe consequences. Hence, it continues to be a significant limitation in the progress of many developing countries. Prediction and assessment of soil loss are, therefore, of utmost importance for soil fertility conservation, land and water management. Recent technological advances have provided useful models through which remotely-sensed data for a large scale area can be analysed and interpreted. The present study adopts a physiographically, biologically and climatically unique model for the assessment of soil erosion in the Indian Himalayan Region. The Revised Universal Soil Loss Equation model was applied in conjunction with Geographic Information System to estimate the average annual rate of soil erosion at both state and district levels in India. The model was deployed using coarse resolution datasets to identify specific areas vulnerable to soil erosion. In determining the spatial distribution of average annual soil erosion within the study region, all cell-based parameters of the model were multiplied in the specified 500 m × 500 m spatial resolution. The spatial pattern of annual soil erosion indicates that maximum soil loss occurs in northern and eastern states whereas low rates of erosion is observed in the eastern-most part of the study area.

scholarly journals Assessment of Soil Erosion Hazard in Prambanan District Using RUSLE (Revised Universal Soil Loss Equation)

2021 ◽  
Vol 884 (1) ◽  
pp. 012010
Author(s):  
S. A Mulya ◽  
N. Khotimah
Keyword(s):  
Soil Loss ◽  
Hazard Index ◽  
Universal Soil Loss Equation ◽  
Annual Rainfall ◽  
Rainfall Erosivity ◽  
Slope Length ◽  
Erosion Hazard ◽  
Erosion Processes ◽  
Factor C ◽  
Soil Loss Equation

Abstract Prambanan District which located in Daerah Istimewa Yogyakarta Province has the potential for land degradation due to erosion processes. With the characteristics of annual rainfall more than 2000 mm / year, topography with a slope of more than 20% in upland areas, as well as the conversion of upland to dryland agriculture are factors that can trigger the erosion process more quickly. If the rate of erosion speed exceeds the ability of the soil to regenerate the soil body, its productivity will be disrupted and accelerate the formation of critical soil. Therefore, it is necessary to know the estimated rate of erosion, tolerable distribution of erosion, and the potential danger of erosion that occurs. The purpose of this study was to (1) predict the rate of erosion, (2) calculate the permissible erosion value, (3) identify the rate & index of erosion hazard. Data were collected using field surveys and soil sampling using stratified random sampling techniques with land units as the unit of analysis. The value of erosion was predicted using the Revised Universal Soil Loss Equation (RUSLE) method. The RUSLE method is described by the following equation, A=R*K*L*S*C*P, where; A as estimated averages annual loss of soil, R is the rainfall erosivity factor, K is the soil erodibility factor, LS is the slope length factor, C is the cover management factor, & P is the conservation practice factor. The results showed that the erosion value ranged from 0.39 - 268.55 tons/ha/year. Permissible erosion ranges from 8.4 – 15 tons/ha/year for Latosol and 27.4 ton/ha/year for Regosol. The Rate of Erosion Hazard is dominated by moderate erosion, covering an area of 1330.7 ha or 31.8% of the total area. The Erosion Hazard Index is dominated by the low class (<1.0) which is covered over 2703.1 ha or 64.61% of the total area.

EFFECTS OF POTATO CROPPING PRACTICES ON WATER RUNOFF AND SOIL EROSION

1990 ◽  
Vol 70 (2) ◽  
pp. 137-148 ◽  
Author(s):  
T. L. CHOW ◽  
H. CORMIER ◽  
J. L. DAIGLE ◽  
I. GHANEM
Keyword(s):  
Soil Loss ◽  
Universal Soil Loss Equation ◽  
Water Runoff ◽  
Slope Length ◽  
Cropping Practices ◽  
Erosion Index ◽  
Factor C ◽  
Runoff And Soil Loss ◽  
Soil Loss Equation ◽  
Rainfall Erosion

Using runoff-erosion plots (10 m wide × 30 m long), the effects of cropping practices on surface runoff and soil loss were examined on a Hommesville gravelly loam soil to evaluate the applicability of the Universal Soil Loss Equation in New Brunswick. The amount of water runoff and soil loss from continuous fallow, up-and-down slope planting of potatoes (Solanum tuberosum), and clover (Trifolium pratense) on 8 and 11% slopes were measured from 1983 to 1985. In addition, runoff and soil loss from contour planting of potatoes were measured on the 11% slope. Slope planting of potatoes resulted in higher runoff and soil loss than on fallow plots. There was considerable reduction in runoff and soil loss when potatoes were planted along the contour. Runoff and soil loss under clover were negligible. Rainfall erosion index (R) and slope length and steepness (LS) correlated well with the measured soil losses. However, both the measured soil credibility factor (K) and the cover and management factor (C) deviated markedly from the current values used for conservation planning. Key words: Universal Soil Loss Equation, rainfall erosion index, topographic factor, soil erodibility factor, cover and management factor, support practice factor

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