Runooff ratio as a factor in the empirical modelling of soil erosion by individual rainstorms

Soil Research ◽  
1997 ◽  
Vol 35 (1) ◽  
pp. 1 ◽  
Author(s):  
P. I. A. Kinnell
Keyword(s):  
Soil Loss ◽  
Sediment Concentration ◽  
Rill Erosion ◽  
Local Conditions ◽  
Empirical Modelling ◽  
Control Practice ◽  
Number Of Factors ◽  
Erosion Models ◽  
Erosivity Index ◽  
Bare Fallow

A number of factors that influence erosion have separate and differing effects on flow discharge and sediment concentration, depending on local conditions. Empirical erosion models that do not have mechanisms to help account for these separate and differing effects often lack the capacity to predict event erosion adequately in many locations. In this paper, the product of the EI30 index, the erosivity index used in the Universal Soil Loss Equation (USLE) and the revised version (RUSLE), and the runoff ratio (QR) is discussed in relation to its capacity to act as an event erosivity index where sheet and rill erosion occur either separately or together in a rainstorm. An analysis of runoff and soil loss data shows the index to be superior to the EI30 index as an event erosivity index for storms on bare fallow plots at Holly Springs, Mississippi. The inclusion of runoff as an independent term in the USLE/RUSLE results in a need to determine new values for the soil erodibility factor, K. Existing USLE/RUSLE equations for determining L and S (topographic factors), C (a crop and crop management factor), and P (an erosion control practice factor) may be used as first approximations provided that the values of the new index are determined for the unit plot condition. Since many of the factors that determine L, S, C, and P influence runoff, new methods to determine these parameters need to be developed in the future if the new index is to be used most effectively.

Estimating rill erosion and sediment transport processes along a saturated purple soil slope

2021 ◽  
Author(s):  
Han Zhen ◽  
Xiaoyan Chen ◽  
Yanhai Li ◽  
Shiqi Chen ◽  
Xiaojie Gu ◽  
...  
Keyword(s):  
Sediment Transport ◽  
Sediment Concentration ◽  
Transport Processes ◽  
Purple Soil ◽  
Rill Erosion ◽  
Soil Slope ◽  
Sediment Transportation ◽  
Erosion Models ◽  
Increasing Trend ◽  
Soil Slopes

A plough pan with reduced permeability always accumulates infiltrated water along slopes then saturates the cultivated layer under continuous rain. Topsoil saturation is a frequent phenomenon and an important process of the special soil slopes. A methodology and device system was used in this study to keep cultivated purple soil saturated. Strands of scouring tests were developed to quantify the rill erosion and sediment transport processes along a saturated purple soil slope at four experiment slopes (5°, 10°, 15°, and 20°) and three flow discharges (2, 4 and 8 L min−1). The experimental results indicated that the sediment transport capacity on a saturated purple soil slope ranged from 0.03 to 1.56 kg s−1 m−1 with the increasing trend along the slope gradient and flow discharge, and the increasing trend could be well matched by a nonlinear multivariable equation. The sediment concentration of the saturated purple soil slope exponentially increased with rill length and decreased with the increment rate and the maximum sediment concentrations observed in this study in different hydraulic events ranged from 108.13 to 1174.20 kg m-3. Saturated and non-saturated purple soil slopes erode differently with the maximum sediment concentration of saturated purple soil slope recorded at approximately 1.42-2.10 times the values for non-saturated purple soil slope. The findings of this research help illustrate the sediment transportation and erosion behaviors of a saturated purple soil slope, and serve as the basis for determining the parameters in the erosion models of the purple soil slope.

Evaluation of WEPP for runoff and soil loss prediction at Gunnedah, NSW, Australia

Soil Research ◽  
2001 ◽  
Vol 39 (5) ◽  
pp. 1131 ◽  
Author(s):  
B. Yu ◽  
C. J. Rosewell
Keyword(s):  
Soil Loss ◽  
Prediction Models ◽  
Daily Rainfall ◽  
Sediment Concentration ◽  
Model Parameters ◽  
Slope Length ◽  
Erosion Prediction ◽  
Physically Based ◽  
Bare Fallow ◽  
Runoff And Soil Loss

It is important to use historical data to test physically based runoff and soil erosion prediction models as well as the method to estimate model parameters. WEPP (Water Erosion Prediction Project) was validated for bare fallow and annual wheat treatments at Gunnedah, New South Wales, Australia. Wheat stubble was either burned or mulched. Climate, soil, management, and runoff and soil loss data were collected for the period 1980–87 for 3 bare fallow plots, and 1950–74 for 10 annual wheat plots. Three slope lengths from 21 to 62 m were established for the treatment with stubble burned. Slope steepness varied from 8% to 9% at the site. Effective saturated hydraulic conductivity and soil erodibility parameters were estimated from measured soil properties. No further calibration of these parameters was attempted in order to assess the true potential of the model for runoff and soil loss predictions. WEPP worked well for the bare fallow plots with prediction efficiency of 0.97 for event runoff and soil losses. WEPP generally over-predicted the runoff, and consequently, the soil loss for annual wheat treatments for the site. WEPP was able to predict the effect of slope length on sediment concentration and soil loss for the site. CLIGEN, which provides the continuous climate input to WEPP, was found to produce adequately the mean daily rainfall, but produced higher than expected peak rainfall intensity, resulting in higher runoff and soil loss for all treatments.

scholarly journals Experimental validation of some basic assumptions used in physically based soil erosion models

2011 ◽  
Vol 8 (1) ◽  
pp. 1247-1286 ◽  
Author(s):  
S. Wirtz ◽  
M. Seeger ◽  
J.-F. Wagner ◽  
J. B. Ries
Keyword(s):  
Soil Erosion ◽  
Experimental Validation ◽  
Sediment Concentration ◽  
External Factors ◽  
Fallow Land ◽  
Rill Erosion ◽  
Basic Assumptions ◽  
Erosion Models ◽  
Physically Based ◽  
Process Based Models

Abstract. In spring 2009, four rill experiments were accomplished on a fallow land. Most external factors as well as discharge quantity (9 L min-1) were held constant or at least in the same range. Following most process based soil erosion models, detachment or runoff values should therefore be similar, but the experimental results show clear differences in sediment concentration, runoff and other measured and calculated values. This fact underlines the problems of process based models: concerning rill erosion, different processes take part and the process described by the models is only responsible for a part of the eroded material.

scholarly journals Soil Erosion Susceptibility Prediction in Railway Corridors Using RUSLE, Soil Degradation Index and the New Normalized Difference Railway Erosivity Index (NDReLI)

2022 ◽  
Vol 14 (2) ◽  
pp. 348
Author(s):  
Yashon O. Ouma ◽  
Lone Lottering ◽  
Ryutaro Tateishi
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Soil Degradation ◽  
Bare Soil ◽  
Landsat 8 ◽  
Arid Environments ◽  
Degradation Index ◽  
Erosivity Index ◽  
Loss Index ◽  
Very High

This study presents a remote sensing-based index for the prediction of soil erosion susceptibility within railway corridors. The empirically derived index, Normalized Difference Railway Erosivity Index (NDReLI), is based on the Landsat-8 SWIR spectral reflectances and takes into account the bare soil and vegetation reflectances especially in semi-arid environments. For the case study of the Botswana Railway Corridor (BRC), the NDReLI results are compared with the RUSLE and the Soil Degradation Index (SDI). The RUSLE model showed that within the BRC, the mean annual soil loss index was at 0.139 ton ha−1 year−1, and only about 1% of the corridor area is susceptible to high (1.423–3.053 ton ha−1 year−1) and very high (3.053–5.854 ton ha−1 year−1) soil loss, while SDI estimated 19.4% of the railway corridor as vulnerable to soil degradation. NDReLI results based on SWIR1 (1.57–1.65 μm) predicted the most vulnerable areas, with a very high erosivity index (0.36–0.95), while SWIR2 (2.11–2.29 μm) predicted the same regions at a high erosivity index (0.13–0.36). From empirical validation using previous soil erosion events within the BRC, the proposed NDReLI performed better that the RUSLE and SDI models in the prediction of the spatial locations and extents of susceptibility to soil erosion within the BRC.

scholarly journals Effect of natural rainfall on the migration characteristics of runoff and sediment on purple soil sloping cropland during different planting stages

2021 ◽  
Author(s):  
Yi Wang ◽  
Jiupai Ni ◽  
Chengsheng Ni ◽  
Sheng Wang ◽  
Deti Xie
Keyword(s):  
Sediment Yield ◽  
Soil Loss ◽  
Heavy Rain ◽  
Sediment Concentration ◽  
Purple Soil ◽  
Torrential Rain ◽  
Sediment Yields ◽  
Natural Rainfall ◽  
Sediment Loss ◽  
Rain Events

Abstract Due to the difficulty in monitoring subsurface runoff and sediment migration, their loss loads are still not clear and need further study. This study monitored water and soil loss occurring within experimental field plots for two calendar years under natural rainfall events. The sediment loss load was quantified by considering the corresponding water flow flux and its sediment concentration. The results showed that 60.04% of the runoff and 2.83% of the sediment were lost underground. The annual underground sediment loss reached up to 54.6 kg*ha−1*yr−1. A total of 69.68% of the runoff yield and 67.25% of the sediment yield were produced during the corn planting stage (CPS: March–July). Heavy rain and torrential rain events produced 94.45%, 65.46% of the annual runoff and 94.45%, 76.21% of the sediment yields during the corn-planting stage and summer fallow period (SFP: August–September). The rain frequency, rainfall, and rainfall duration of each planting stage significantly affected the resulting runoff and sediment yield. Measures aimed at the prevention and control of water-soil loss from purple soil sloping land should heavily focus on torrential rain and heavy rain events during the CPS and SFP. This paper aims to provide a practical reference for quantifying the water and soil loss from purple soil sloping cropland.

Assessment of soil erosion models for predicting soil loss in cracked vegetated compacted surface layer

2021 ◽  
Author(s):  
Manash Jyoti Bora ◽  
Sanandam Bordoloi ◽  
Sreeja Pekkat ◽  
Ankit Garg ◽  
Sreedeep Sekharan ◽  
...  
Keyword(s):  
Surface Layer ◽  
Soil Erosion ◽  
Soil Loss ◽  
Erosion Models

COMPARISON OF PREDICTED AND MEASURED SHEET AND RILL EROSION LOSSES IN SOUTHERN ONTARIO

1979 ◽  
Vol 59 (2) ◽  
pp. 211-213 ◽  
Author(s):  
L. J. P. VAN VLIET ◽  
G. J. WALL
Keyword(s):  
Soil Loss ◽  
Universal Soil Loss Equation ◽  
Rill Erosion ◽  
Southern Ontario ◽  
Loss Data ◽  
Soil Losses ◽  
Runoff Plots ◽  
Soil Loss Equation

Sheet and rill erosion losses evaluated by the universal soil loss equation were compared with 4–6 yr of measured soil loss data from runoff-plots at two locations in southern Ontario. Results indicated no significant differences (P = 0.10) between predicted and measured soil losses.

Application of a physically based soil erosion model, GUEST, in the absence of data on runoff rates I. Theory and methodology

Soil Research ◽  
1999 ◽  
Vol 37 (1) ◽  
pp. 1 ◽  
Author(s):  
B. Yu ◽  
C. W. Rose
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Soil Erodibility ◽  
Erosion Model ◽  
Erosion Models ◽  
Loss Data ◽  
Physically Based ◽  
Set Up ◽  
Data Requirements

When physically based erosion models such as GUEST are used to determine soil erodibility parameters or to predict the rate of soil loss, data on runoff rates, as distinct from event runoff amount, are often needed. Data on runoff rates, however, are not widely available. This paper describes methods that can be used to overcome this lack of data on runoff rates. These methods require only rainfall rates and runoff amounts, which are usually available for sites set up primarily to test and validate the USLE technology. In addition, the paper summarises the data requirements for the erosion model GUEST and application procedures. In the accompanying paper, these methods are applied to 4 experimental sites in the ASIALAND Network.

Measuring Soil Loss and Subsequent Nutrient and Organic Matter Loss on Farmland

2017 ◽  
Author(s):  
Vito Ferro ◽  
Vincenzo Bagarello
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Soil Loss ◽  
Soil Structure ◽  
Overland Flow ◽  
Organic Matter Content ◽  
Matter Content ◽  
Water Infiltration ◽  
Surface Erosion ◽  
Rill Erosion

Field plots are often used to obtain experimental data (soil loss values corresponding to different climate, soil, topographic, crop, and management conditions) for predicting and evaluating soil erosion and sediment yield. Plots are used to study physical phenomena affecting soil detachment and transport, and their sizes are determined according to the experimental objectives and the type of data to be obtained. Studies on interrill erosion due to rainfall impact and overland flow need small plot width (2–3 m) and length (< 10 m), while studies on rill erosion require plot lengths greater than 6–13 m. Sites must be selected to represent the range of uniform slopes prevailing in the farming area under consideration. Plots equipped to study interrill and rill erosion, like those used for developing the Universal Soil Loss Equation (USLE), measure erosion from the top of a slope where runoff begins; they must be wide enough to minimize the edge or border effects and long enough to develop downslope rills. Experimental stations generally include bounded runoff plots of known rea, slope steepness, slope length, and soil type, from which both runoff and soil loss can be monitored. Once the boundaries defining the plot area are fixed, a collecting equipment must be used to catch the plot runoff. A conveyance system (H-flume or pipe) carries total runoff to a unit sampling the sediment and a storage system, such as a sequence of tanks, in which sediments are accumulated. Simple methods have been developed for estimating the mean sediment concentration of all runoff stored in a tank by using the vertical concentration profile measured on a side of the tank. When a large number of plots are equipped, the sampling of suspension and consequent oven-drying in the laboratory are highly time-consuming. For this purpose, a sampler that can extract a column of suspension, extending from the free surface to the bottom of the tank, can be used. For large plots, or where runoff volumes are high, a divisor that splits the flow into equal parts and passes one part in a storage tank as a sample can be used. Examples of these devices include the Geib multislot divisor and the Coshocton wheel. Specific equipment and procedures must be employed to detect the soil removed by rill and gully erosion. Because most of the soil organic matter is found close to the soil surface, erosion significantly decreases soil organic matter content. Several studies have demonstrated that the soil removed by erosion is 1.3–5 times richer in organic matter than the remaining soil. Soil organic matter facilitates the formation of soil aggregates, increases soil porosity, and improves soil structure, facilitating water infiltration. The removal of organic matter content can influence soil infiltration, soil structure, and soil erodibility.

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