The Universal Soil Loss Equation is a powerful tool. It is in use by soil conservationists from last three decades for on-farm planning of soil conservation practices, inventorying and assessing the regional and national impacts of soil erosion and developing as well as implementing public policy related to soil conservation.
(c) Soil erodibility information is also expanded. (d) Slope-length factor that varies with the soil susceptibility to rill erosion, is accounted. (e) A linear slope steepness relationship that reduces the amount of computed soil loss for very steep slope is incorporated. (f) A sub factor method for computing the cover management factor is. .Note: The designer must use judgement to select the appropriate 'C' value within the range. Generally, larger areas with permeable soils, flat slopes and dense vegetation should have the lowest 'C' values. Smaller areas with dense soils, moderate to steep slopes, and sparse vegetation should assigned the highest 'C' values.
- These same principles apply in designating layers of organic soils. The prime symbol is used only to distinguish two or more horizons that have identical symbols. For example, Oi-C-O´i-C´ indicates a soil with two identical Oi and C layers and Oi-C-Oe-C´ indicates a soil with two identical C layers.
- Soil slope is particularly important in terms of its effect on erosion. Slope can be measured in. Percent (Rise/run).100,. The amount of surface residue required to reduce erosion increases with slope and as soil texture gets finer.
Over the last several years, a co-operative effort between scientists and users has also been made to update the USLE. The updated USLE is referred as Revised Universal Soil Loss Equation (RUSLE).
The various changes/modifications incorporated in the RUSLE are summarised as under:
1. Computerized algorithms to assist the calculations.
2. Introduction of new rainfall-runoff erosivity factor (R) based on more than 1200 gauging locations.
3. Some revisions and additions for high R-factor areas with flat slopes to adjust splash erosion, associated to the raindrops falling on ponded water.
4. Consideration of seasonally variable soil erodibility factor (K).
5. A new approach for calculating the cover-management factor (C) using sub-factors representing considerations of prior land use, crop canopy, surface cover and surface roughness.
6. Inclusion of new slope length and steepness factor (LS) algorithms, reflecting rill to inter-rill erosion ratio.
7. Introduction of new conservation practices factor (P) for rangelands, strip-crop rotations, contour and sub-surface drainage.
All these modifications are described as under:
The R-factor acts as input parameter in USLE that drives the sheet and rill erosion process. In assessing erosion the magnitude of R-factor and its seasonal distribution must be considered in relation to the cropping system, because the erosivity of rain is not distributed uniformly throughout the year, e.g. most of the erosive rains occur in the spring season, when row-cropped lands are found bare and ready for planting, as result the soil is more susceptible to get erosion by occurrence of erosive rains.
The computation of R is concerned, the following improvements have been incorporated in the method used under USLE:
i. One of major improvement in RUSLE is the revision of iso-erodent map with greater accuracy for the Western United States. About 1000 locations data have been counted for preparing new iso-erodent map. The previous map was prepared based on few point calculations considering two-year frequency and rainfall magnitude for six-hour duration. The new iso-erodent map is found to result about 7 times more value than the previous.
ii. Another modification in R-factor is to reduce its value, where slope is found to be flat in the regions of long and intense storms, as existing in the Southern United States.
The K-factor in USLE is the measure of inherent erodibility of a given soil under the standard condition of ‘unit plot’ (i.e. 22 m long with 9% slope) maintained in continuous fallow condition. Its value ranges from about 0.10 to 0.45 depending on the percentage sand, silt & clay contents in the soil. Soils having high sand and clay contents involve lower value of K, while a soil which is charged with high silt content includes higher K value. Since, the value of K has significant variation, therefore, its sensitivity to yield the soil erosion is given greater importance than the R-factor.
To select an appropriate value of K, is a difficult task for users. Although, the erodibility nomograph is most common tool for determining the K, but it is not fit for all the soils. In RUSLE, the K-factor is updated, using some guidelines to identify the soils.
An equation that gives useful estimate of K, is developed from erodibility data collected from all around the world. This equation estimates the K as the function of average diameter of soil particles. However, use of this relationship is recommended for the regions where nomograph or other procedure does not apply.
The RUSLE also indicates that there is variation in K-factor from season to season, because of the fact that it does not remain same throughout the year, but varies, e.g. it is being highest in spring season with soft feathering soil due to freeze-thaw actions, and lowest in mid-fall and winter following rainfall compaction or a frozen soil.
The effect of seasonal variation on K is incorporated by weighting the instantaneous estimate of K in proportion to the EI for 15-day intervals. The instantaneous K are estimated from the equations relating the K to the frost-free period and the annual R-factor.
The RUSLE also incorporates the effect of rock fragments lying on the ground surface and in the soil, on K-value. Its effect is evaluated by treating the rock fragments as mulch which develops an effect on soil permeability and runoff.
3. L and S Factor:
About these two factors, there are several questions and concerns are expressed than any of the other factors of USLE. This is mainly due to consideration of different slope lengths for similar conditions by the concerns. In order to make uniformity in the selection of slope-length, the RUSLE contains some improved guidelines, which are as follows – The L factor is not always warranted, because soil loss is found less sensitive to the slope-length than do any other factors of USLE. It has been reported that, for the typical slope conditions a 10% error in the slope length factor results up to 5% error in the computed soil loss. The RUSLE incorporates to use three separate relationships for slope-length factor.
They are outlined as under:
(a) A function for slope steepness as in USLE.
(b) A function relating the susceptibility of soil to rill erosion relative to inter-rill erosion.
(c) A slope-length relationship specifically for the Pacific-North West region. (Palouse region).
Regarding importance of slope-steepness factor on estimate of soil loss, it has been reported that the soil loss is much sensitive to change in slope-steepness than do slope-length. Field experiment reveals that, in USLE a 10% error in the slope-steepness results about 20% error in the computed soil loss.
Looking this in view, it is essential to provide more attention to obtain a better estimate of slope-steepness factor than the factor-L. For the slope less than 20%, the soil loss computed by use of USLE and RUSLE is the same, but for the slope greater than 20%, the computed soil loss by RUSLE is reduced by half amount than do USLE.
The experimental data and field observation of range land do not support the quadratic relationship for steep-slope condition of USLE, while RUSLE which involves the slope-steepness relationship for shorter slope, supports very well to grassland. The another remarkable point is that, the slope segment considered by USLE is as a single plane uniform slope, represents poor topography, while in RUSLE the complex slopes can be considered readily to incorporate a better topographic effect on soil loss estimation.
This is an important factor of USLE, because it accounts the conditions that can be easily managed on the soil to reduce the erosion. The values of C-factor can vary from about zero for a very well protected (covered) soil to 1.5 for a finely tilled and ridged surface that play causative factor to generate ample runoff, and also leave the soil highly susceptible for rill erosion.
The values of C are determined as a weighted average soil loss ratios (SLRs), defined as the ratio of soil loss for a given condition of vegetative cover at a specific time to that of the unit plot soil loss. As per this definition, the SLRs vary within the year duration, because soil cover conditions are likely to change appreciably. To obtain C value the SLRs are weighted according to the erosivity distribution during the entire year.
In RUSLE to compute SLRs a sub-factor method is introduced, which is the function of four sub-factors, namely:
(i) Prior land use sub-factor (PLU)
(ii) Crop canopy sub-factor (CC)
(iii) Surface cover sub-factor (SC); and
(iv) Surface roughness sub-factor (SR).
The sub-factor relationship is given as under –
C = PLU.CC.SC.SR … (21.45)
The values of sub-factors PLU and SR for soil-effect are determined with the help of existing amount of bio-mass in the soil that has been accumulated from the crop’s root and incorporation of crop residues. The residue decomposition in the soil is determined by using the residue decomposition model described by Gregory et. al. (1985).
For computation of sub-factor for SLRs the characteristics of tillage operation play an important role. The value of SLRs for conservation tillage in RUSLE is less than the USLE, because RUSLE computes the SLRs for greater effective ground cover.
The surface roughness sub-factor (SC) is determined based on the surface ground cover. The research studies revealed that at 50% ground cover the soil loss is reduced by about 65%; even in some cases it also goes up to 95%. The following formula can be used to compute the value of sub-factor SC –
SC = exp (– b M) … (21.46)
b = coefficient, taken as 0.035. Its value increases when tendency of rill erosion is dominating to inter-rill erosion
M = percentage ground cover.
It is observed that among all the USLE factors the values of factor P are least accurate. The P-factor accounts the effect of surface conditions on flow paths and flow hydraulics, and ultimately on the soil loss. For example, the contouring or tillage marks on soil surface make the direct paths for runoff yield. A little change in runoff yield can cause significant change in the runoff-erosivity.
Summary of RUSLE:
In brief, the various improvements made in USLE to result as RUSLE, are given as under:
(a) A greatly expanded iso-erodent map for the Western United States is prepared.
(b) Minor changes in factor-R for Eastern United States is incorporated.
(c) Soil erodibility information is also expanded.
(d) Slope-length factor that varies with the soil susceptibility to rill erosion, is accounted.
(e) A linear slope steepness relationship that reduces the amount of computed soil loss for very steep slope is incorporated.
(f) A sub factor method for computing the cover management factor is introduced.
(g) An improved value of factor P for the effect of contouring, terracing, strip cropping and management practices for rangeland, is developed.
It is developed by the USDA-Agricultural Research Service, and was released in the year 1993. This is the RUSLE model to predict longtime average annual soil loss caused raindrop splash and runoff from specific field slopes for specified cropping and management systems; and from the rangeland.
It is the replacement of the Universal Soil Loss Equation (USLE), includes the six factors. These factors are the rainfall and runoff factor (R), soil erodibility factor (K), slope length and steepness factors (LS), cover and management factor (C), and the support practices factor (P). This model can be used for prediction of rill and, inter-rill erosion on cropland, rangeland and other land uses.
2. RUSLE 1.06:
This is the upgraded version of the RUSLE, used for predicting the longtime average annual soil loss resulting from raindrop splash and runoff from specific field slopes in specified cropping and management systems and from rangeland. This version of RUSLE can also be suitably used for predicting soil loss from mined lands, construction sites and reclaimed lands. New features of this version are the computation of sediment depositions on concave slopes, in terrace channels, and in sediment basins; and improved computation of the effectiveness of ground cover on steep slopes.
The RUSLE-2 is a new model for predicting soil loss. It has quite different features and capabilities as compared to the RUSLE. It is well suitable to estimate the soil loss, sediment yield etc. from rill and inter-rill erosions clue to rainfall and overland flow.
The RUSLE-2 includes the factors associated to the climate (erosivity, precipitation and temperature), soil erodibility, topography, cover-management, and soil conservation support practices.
This model predicts the long-term average-annual soil erosion by water for a broad range of farming systems, conservation and mining, construction, and forestry uses. It has objective-oriented and Windows interface, allows scientific and graphical advances. It is derived from the previous DOS RUSLE software based on the widely used Revised Universal Soil Loss Equation (RUSLE); and can reuse much of the extensive data available for that model.
The other features are outlined as under:
i. It is a mathematical model to calculate the soil erosion rate.
ii. Its major component is the database with extensive values describing site-specific conditions.
iii. The RUSLE-2 can be used for computing the soil loss of cropland, rangeland, disturbed forestland, construction sites, reclaimed mined land, landfills, military training sites, and all those areas where mineral soil is exposed to the direct rainfall and overland flow.
iv. RUSLE-2 is used to evaluate potential erosion rates at specific sites.
v. It can be used as a guide for soil conservation and erosion control planning, and for preparation of inventory of erosion rates over large geographic areas.
vi. It can be used for estimating the sediment yield on upland areas in the watersheds.
vii. It uses a modem and powerful graphical user interface instead of the text-based interface.
viii. It can be used in the US customary units and SI units, both.
ix. It can manipulate the attributes of variables, such as graphing, changing units and setting various digits.
Theory and Assumptions:
The RUSLE-2 considers basic processes of water erosion, i.e. detachment, transportation and deposition of soil particles along overland flow path. In erosion process, firstly the soil particle gets detach from the soil mass, and then transported by the runoff. The deposition takes place, when land slope gets flatten or flow is obstructed by the support practices or other causes. The amount of runoff likely to be generated from the rainfall is estimated by using CN method. The processes of soil detachment, transportation and deposition are described as under:
The RUSLE-2 assumes that the particles detachment is due to impacting forces of raindrop and overland flow. The overland flow gets generate only when rainfall intensity exceeds the infiltration rate. It involves similar formula as the USLE for computing the average annual soil loss (detachment) for each day of the year, given as under –
ai = ri ki li Sci pi
ai = average annual soil loss for ith day of the year
ri = rainfall erosivity factor for ith day of the year
kj = soil credibility factor for ith day of the year
li = slope length factor for ith day of the year
S = slope steepness factor
ci = cover-management factor for the ith day of the year
pi = support practices factor for ith day of the year
In above equation the slope steepness factor (S) is being same for every day of the year. The values of all the factors are in terms of average annual for a particular day of the year; but not the average value for the year. The RUSLE-2 also assumes that the net detachment caused by a single storm is directly proportional to the product of storm energy (KE) and its maximum 30-minute intensity (I30).
There is linear relationship between soil detachment and storm erosivity (El). The individual storm’s Els are added together to determine the monthly or annual El values. This equation also reveals that the average annual erosion is computed for each day of the year, although erosion does not actually takes place on every day of the year.
Type C Soil Slope Ratio
Runoff Transport and Deposition:
The version 2 of RUSLE assumes that the transportation and deposition of detached soil particles is carried out by the runoff. The runoff can be computed by using the CN method based on the storm event of 24-h duration and 10-years recurrence interval. The deposition of transported soil particles takes place, when sediment load exceeds the transport capacity of overland flow in a particular segment of path.
The purpose of considering the storm event of 10-years frequency and 24-hour duration is for computing the storm erosivity and runoff to determine the factor values for contouring, critical slope length of contouring, sediment transport capacity and the effect of ponding on reducing erosivity. The sediment transport capacity is required for determining the deposition by runoff, when it enters the slope segments of concave shape, dense vegetation and high ground cover.
The computational unit of RUSLE-2 is the single overland flow path along the hill slope. The overland flow path refers to the path that overland flow follows, which is extended from the origin of overland flow to the point where it enters a major flow concentration. The locations of major flow concentration on the landscape may be the place where sides of hill slope intersect and create space for collecting the overland flow. The ephemeral channels and gullies are mainly these points.
These channels are quite different than the rills in respect of following points:
i. Rills are approximately in parallel sequence.
ii. Depth is sufficiently shallow which can be removed by the tillage or grading operations.
In RUSLE-2 the consideration of climate is in respect of computation of storm erosivity (EI) and thereby the erosivity density. The erosivity density is defined as the ratio of monthly erosivity to the monthly rainfall. The requirement of erosivity density is to determine the erosivity values to maximize the number of precipitation data to provide a consistent set of erosivity values for conservation and erosion control planning.
2021 slots for kindle. In RUSLE-2 three types of erosivity inputs are used; they are:
i. Erosivity density
Class C Soil Slope Minimum
ii. Monthly erosivity values; and
iii. Average annual erosivity value along with erosivity distribution curve for the EI zone of the site where RUSLE-2 is being applied.
The monthly erosivity can be computed by multiplying the monthly erosivity density and monthly precipitation. And annual erosivity is computed as the sum of monthly erosivity values.
The consideration of soil is for soil erodibility factor-K, which is the measure of potential susceptibility of soil to get erode due to external forces. In USLE the evaluation of factor K is through unit plot studies.
C Slope Soil Definition
The dimension of unit plot is 22.1 m as length and 9% slope, in continuous fallow, tilled up and down hill periodically to control the weeds and break the crusts formed on the soil surface. This procedure determines the empirical K value, i.e. site/soil specific where the effect of cover-management on soil erodibility is not there.
The factor K indicates the combine effect of soil susceptibility to detachment and transportability of eroded soil mass or sediment, and the amount and rate of runoff yield per unit rainfall erosivity under unit plot conditions. In RUSLE-2 the soil erodibility factor is defined by the erosivity EI30. In this case, the erodibility factor is not directly related to the specific erosion process; and not to the soil property such as texture.
In RUSLE-2 the K values are considered to get vary during the year, i.e. the value may be high in the early spring and immediately following thawing and other periods, especially when soil is in wet condition. On the other hand, the values may be low in the late summer when soil moisture and runoff is very less, might be due to greater evaporation loss from the soil because of high atmospheric temperatures.
In RUSLE-2, the effect of slope length is considered to be as the function of rill erosion relative to inter-rill erosion. In which inter-rill erosion is assumed to be due to raindrop impact, and independent of location along the overland flow path.
C Slope Soil Types
The variables that affect the inter-rill erosion are also assumed to be constant along the overland flow path. The rill erosion is caused by surface runoff, which gets change linearly along the overland flow path because of runoff accumulation. The slope length exponent m is given by the following expression –
In which, β is the ratio of rill to inter-rill erosion, reflects the relative contribution of rill and inter-rill erosions. Its value varies between 0 and 1. The value of m approaching zero indicates the dominancy of inter-rill erosion, which is normally when slope is flatter; and m near to 1 indicates the dominancy of rill erosion, which is basically when soil is bare and slope is steep.
The slope length effect varies daily because of change in cover-management conditions. In USLE the slope length factor is independent of other factors, except slope steepness. The slope steepness factor (S) is also the function of soil and cover-management, similar to the slope length; however, it is not so easy to incorporate these effects into RUSLE-2.
In RUSLE-2 the cover-management factor (ci) is land use independent. It uses sub-factors affecting the rill and inter-rill erosions. These sub-factors are the canopy, ground cover, soil roughness, ridge height, soil biomass and soil consolidation. The value of each sub-factor is evaluated separately for each day; and multiplying them together to get the daily value of factor ci. The cover-management variables also affect the topographic and support practices factor of RUSLE-2.
Overall, the topographic, cover-management and support practices factors are importantly required to get verified to have the complete effect of land use and management on erosion estimates by RUSLE-2. The canopy refers to the lying of live and dead vegetative cover over the soil surface. These covers intercept the falling raindrops during rainfall. In case of canopy effect on soil erosion, the degree of cover and effective fall height are the two main parameters.
As for as ground cover is concerned, the materials in contact with the soil surface, which slow down the overland flow and intercept the raindrops and water drops falling from the canopy are mainly taken into consideration. The ground cover includes all the materials, which touch the soil surface, are considered to be very effective regarding erosion control. These covers reduce the erosion by protecting the soil surface from direct raindrop impact; which in turn to reduce the inter-rill erosion.
Also, the slow-down of surface runoff due to ground cover, results into reduction of detachment and transport capacity of surface runoff. This effect also causes reduction in rill erosion. Experimentally, it has been found that if ground cover is less than about 15%, and cover pieces are long and oriented across the slope, then there is reduction in soil loss due to deposition of eroded soil mass between the spaces of cover pieces.
C Soil Slope
These effects in combine form reduce the rill erosion. In RUSLE-2 the variations in effect of cover on soil erosion is considered at daily basis, in the terms of ratio of rill to inter-rill erosion. By application of this equation the average annual soil loss can be computed for any region; but before using it, its validity should be verified.
C Slope Soil