Evaluation of the CREAMS model. II. Use of rainulator data to derive soil erodibility parameters and prediction of field soil losses using derived parameters

Soil Research ◽  
1989 ◽  
Vol 27 (3) ◽  
pp. 563 ◽  
Author(s):  
RJ Loch ◽  
DM Silburn ◽  
DM Freebairn
Keyword(s):  
Soil Loss ◽  
Confidence Regions ◽  
Soil Erodibility ◽  
Field Soil ◽  
Erosion Process ◽  
Erosion Model ◽  
Erosion Processes ◽  
Wide Range ◽  
Best Fit ◽  
Soil Losses

The first paper of this series identified several parameters to which predictions of the CREAMS erosion model were sensitive. Two of these, soil erodibility parameters nbov and K, cannot be measured directly. Therefore, this paper reports procedures for deriving nbov and K for the CREAMS erosion model from rainulator data. The procedures identify confidence regions for best fit combinations of nbov and K. Fairly specific values of nbov were obtained, but a wide range of K values provided similar near-optimal predictions. Optimum regions of nbov and K for plots where rilling was the dominant erosion process were significantly different to those for plots dominated by rain-flow erosion for two of the three soils studied. The parameters derived from rainulator data were used to predict soil losses for field catchments on two clay soils, for conditions where surface cover by stubble was 110%. Measured rainfall and runoff were used as inputs to the model. For an Irving clay site, the model gave excellent prediction of field soil losses. For a Moola clay site, the larger soil losses were considerably underpredicted, because resistance to rilling on the rainulator plots resulted in lower K values than required for erosion events where rilling is fully developed. The need for parameters to be derived from data reflecting the erosion processes of importance to field soil loss is illustrated. Nonetheless, this study shows that parameters for the CREAMS model can be obtained satisfactorily from rainulator data, provided that the erosion processes studied are relevant, and that there is sufficient replication within the rainulator studies.

Field rainfall simulator studies on two clay soils of the Darling Downs, Queensland. III. An evaluation of current methods for deriving soil erodbilities (K factors)

Soil Research ◽  
1984 ◽  
Vol 22 (4) ◽  
pp. 401 ◽  
Author(s):  
RJ Loch
Keyword(s):  
Soil Loss ◽  
Single Event ◽  
Erosion Process ◽  
Annual Average ◽  
Slope Length ◽  
Rainfall Simulator ◽  
Erosion Processes ◽  
Runoff Rate ◽  
Simulated Rain ◽  
Soil Losses

Simulated rain has been widely used to derive soil erodibility (K) values for the Universal Soil Loss Equation (USLE). Because of concern that recent work using smaller plots may not give realistic results, this paper considers the effects of plot length and erosion process on values of K derived from rainfall simulator studies. It also highlights problems in the calculation of K from rainfall simulator data, using the factors of the USLE. Rainulator data on slope length/erosion process interactions were used to calculate soil losses and K for plot lengths of 10.7 and 22.5 m tilled up and down the slope, on two soils, both on 4% slope. K showed up to threefold variation with changes in plot length, because different erosion processes contributed to soil loss. The results also showed major differences between single-event and annual average responses of erosion to slope length, leading to the conclusion that the annual average factors of the USLE cannot be used to analyse single-event rainfall simulator data. Instead, rainfall simulator data must be converted to average annual soil losses, which can then be validly analysed, using the factors of the USLE, to derive K. The procedures presently used to calculate annual average soil losses from rainfall simulator data do not take into account erosion process/runoff rate interactions, and are therefore unsatisfactory. Single-event soil loss models may provide a means for producing better estimates of annual average soil losses suitable for the derivation of K.

scholarly journals Soil Erosion Estimates in Arid Region: A Case Study of the Koutine Catchment, Southeastern Tunisia

2021 ◽  
Vol 11 (15) ◽  
pp. 6763
Author(s):  
Mongi Ben Zaied ◽  
Seifeddine Jomaa ◽  
Mohamed Ouessar
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Scientific Evidence ◽  
Field Measurements ◽  
Spatiotemporal Variability ◽  
Soil Conditions ◽  
Storm Events ◽  
Erosion Processes ◽  
Study Results ◽  
Soil Losses

Soil erosion remains one of the principal environmental problems in arid regions. This study aims to assess and quantify the variability of soil erosion in the Koutine catchment using the RUSLE (Revised Universal Soil Loss Equation) model. The Koutine catchment is located in an arid area in southeastern Tunisia and is characterized by an annual mean precipitation of less than 200 mm. The model was used to examine the influence of topography, extreme rainstorm intensity and soil texture on soil loss. The data used for model validation were obtained from field measurements by monitoring deposited sediment in settlement basins of 25 cisterns (a traditional water harvesting and storage technique) over 4 years, from 2015 to 2018. Results showed that slope is the most controlling factor of soil loss. The average annual soil loss in monitoring sites varies between 0.01 and 12.5 t/ha/y. The storm events inducing the largest soil losses occurred in the upstream part of the Koutine catchment with a maximum value of 7.3 t/ha per event. Soil erosion is highly affected by initial and preceding soil conditions. The RUSLE model reasonably reproduced (R2 = 0.81) the spatiotemporal variability of measured soil losses in the study catchment during the observation period. This study revealed the importance of using the cisterns in the data-scarce dry areas as a substitute for the classic soil erosion monitoring fields. Besides, combining modeling of outputs and field measurements could improve our physical understanding of soil erosion processes and their controlling factors in an arid catchment. The study results are beneficial for decision-makers to evaluate the existing soil conservation and water management plans, which can be further adjusted using appropriate soil erosion mitigation options based on scientific evidence.

scholarly journals Identifying erosive periods by using RUSLE factors in mountain fields of the Central Spanish Pyrenees

2008 ◽  
Vol 12 (2) ◽  
pp. 523-535 ◽  
Author(s):  
M. López-Vicente ◽  
A. Navas ◽  
J. Machín
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Soil Loss ◽  
Rainfall Intensity ◽  
Soil Moisture Content ◽  
Rainfall Erosivity ◽  
Soil Erodibility ◽  
Maximum Rainfall ◽  
Freeze Thaw ◽  
Soil Losses

Abstract. The Mediterranean environment is characterized by strong temporal variations in rainfall volume and intensity, soil moisture and vegetation cover along the year. These factors play a key role on soil erosion. The aim of this work is to identify different erosive periods in function of the temporal changes in rainfall and runoff characteristics (erosivity, maximum intensity and number of erosive events), soil properties (soil erodibility in relation to freeze-thaw processes and soil moisture content) and current tillage practices in a set of agricultural fields in a mountainous area of the Central Pyrenees in NE Spain. To this purpose the rainfall and runoff erosivity (R), the soil erodibility (K) and the cover-management (C) factors of the empirical RUSLE soil loss model were used. The R, K and C factors were calculated at monthly scale. The first erosive period extends from July to October and presents the highest values of erosivity (87.8 MJ mm ha−1 h−1), maximum rainfall intensity (22.3 mm h−1) and monthly soil erosion (0.25 Mg ha−1 month−1) with the minimum values of duration of erosive storms, freeze-thaw cycles, soil moisture content and soil erodibility (0.007 Mg h MJ−1 mm−1). This period includes the harvesting and the plowing tillage practices. The second erosive period has a duration of two months, from May to June, and presents the lowest total and monthly soil losses (0.10 Mg ha−1 month−1) that correspond to the maximum protection of the soil by the crop-cover ($C$ factor = 0.05) due to the maximum stage of the growing season and intermediate values of rainfall and runoff erosivity, maximum rainfall intensity and soil erodibility. The third erosive period extends from November to April and has the minimum values of rainfall erosivity (17.5 MJ mm ha−1 h−1) and maximum rainfall intensity (6.0 mm h−1) with the highest number of freeze-thaw cycles, soil moisture content and soil erodibility (0.021 Mg h MJ−1 mm−1) that explain the high value of monthly soil loss (0.24 Mg ha−1 month−1). The interactions between the rainfall erosivity, soil erodibility, and cover-management factors explain the similar predicted soil losses for the first and the third erosive periods in spite of the strong temporal differences in the values of the three RUSLE factors. The estimated value of annual soil loss with the RUSLE model (3.34 Mg ha−1 yr−1) was lower than the measured value with 137Cs (5.38 Mg ha−1 yr−1) due to the low values of precipitation recorded during the studied period. To optimize agricultural practices and to promote sustainable strategies for the preservation of fragile Mediterranean agrosystems it is necessary to delay plowing till October, especially in dryland agriculture regions. Thus, the protective role of the crop residues will extend until September when the greatest rainfall occurs together with the highest runoff erosivity and 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.

scholarly journals Modeling of water erosion by the erosion potential method in a pilot subbasin in southern Minas Gerais

2019 ◽  
Vol 40 (2) ◽  
pp. 555 ◽  
Author(s):  
André Silva Tavares ◽  
Velibor Spalevic ◽  
Junior Cesar Avanzi ◽  
Denismar Alves Nogueira ◽  
Marx Leandro Naves Silva ◽  
...  
Keyword(s):  
Soil Loss ◽  
Water Erosion ◽  
Minas Gerais ◽  
Universal Soil Loss Equation ◽  
Southeastern Brazil ◽  
Erosion Processes ◽  
Total Soil ◽  
The Mean ◽  
Soil Losses ◽  
Soil Loss Equation

Soil losses due to water erosion threaten the sustainability of agriculture and the food security of current and future generations. This study estimated potential soil losses and sediment production under different types of land uses in a subbasin in the Municipality of Alfenas, southern Minas Gerais, southeastern Brazil. The objective of this research was to evaluate the application of the Potential Erosion Method by the Intensity of Erosion and Drainage program and correlate the findings with the results obtained by the Revised Universal Soil Loss Equation as well as geoprocessing techniques and statistical analyses. In the Potential Erosion Method, the coefficient indicating the mean erosion intensity was 0.37, which corresponded to erosion category IV and indicated weak laminar erosion processes, and the total soil loss was 649.31 Mg year-1 and the mean was 1.46 Mg ha-1 year-1. These results were consistent in magnitude with those obtained in the Revised Universal Soil Loss Equation, which estimated a mean soil loss of 1.52 Mg ha-1 year-1 and a total soil loss of 668.26 Mg year-1. The Potential Erosion Method suggests that 1.5% of the area presents potential soil losses above the soil loss tolerance limit, which ranged from 5.19 to 5.90 Mg ha-1 year-1, while the Revised Universal Soil Loss Equation indicated that 7.3% of the area has potential soil losses above the limit. The maximum sediment discharge was 60 Mg year-1, meaning that 9.3% of the total soil loss reached the depositional areas of the river plains or watercourses. The Potential Erosion Method was efficient in the evaluation of water erosion in tropical soils, and the results were consistent with models widely employed in the estimation of soil losses. Thus, the model can support the evaluation of soil losses in Brazil and is a robust tool for evaluating the sustainability of agricultural activities.

scholarly journals Determination of wind erosion intensity on heavy clay soils

2010 ◽  
Vol 58 (2) ◽  
pp. 155-160
Author(s):  
Jana Kozlovsky Dufková ◽  
Vladan Jareš ◽  
Petr Húsek
Keyword(s):  
Soil Loss ◽  
Wind Erosion ◽  
Clay Soils ◽  
Soil Erodibility ◽  
Clay Particles ◽  
Heavy Clay ◽  
Deep Soils ◽  
Soil Losses ◽  
Erosion Intensity

Wind erosion, common problem of light-textured soils, was determined on heavy clay soils in the foothills of Bílé Karpaty Mountains, Czech Republic. Soil erodibility by wind was determined from the Map of potential erodibility of soil by wind and from the calculation of potential and real soil loss by wind. All the determinations show underestimation of soil erodibility by wind on heavy clay soils, because methods that are used for this are based above all on the assessment of clay particles content and the presumption the more clay particles soil contains, the less vulnerable to wind erosion is. The potential erodibility of soil by wind is 0,09 t . ha−1 per year. The determined value does not exceed the tolerable soil loss limit 10 t . ha−1 per year for deep soils. The real average erodibility of soil by wind has the highest value 1,47 g . m−2 on November 30th, 2008. Other soil losses that do not exceed the tolerable soil loss limit 1,4 g . m−2, were determined on March 18th and 28th, 2008. Big difficulties come with the assessment of the erodibility of heavy clay soils in the areas, where soil erosion ve­ri­fia­bly exists, but it is not assessable by objective calculating methods. Evident necessity of new know­ledge concerning the determination of wind erosion intensity follows from the results.

scholarly journals Comparing watershed soil erosion of Taiwan and Thailand

2018 ◽  
Vol 192 ◽  
pp. 02041
Author(s):  
Yi-Hsin Liu ◽  
Kieu Anh Nguyen ◽  
Walter Chen ◽  
Jatuwat Wattanasetpong ◽  
Uma Seeboonruang
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Soil Erodibility ◽  
Erosion Model ◽  
Shihmen Reservoir ◽  
Soil Erodibility Factor ◽  
Tropical Watersheds ◽  
Reservoir Watershed ◽  
Soil Loss Equation ◽  
Steepness Factor

Tropical watersheds in Taiwan and Thailand face the same severe soil erosion problem that is increasing at an alarming rate. In order to evaluate the severity of soil erosion, we quantitatively investigate the issue using a common soil erosion model (Universal Soil Loss Equation, USLE) on the Shihmen reservoir watershed of Taiwan and the Lam Phra Ploeng basin of Thailand, and compare their respective erosion factors. The results show an interesting contrast between the two watersheds. Some of the factors (rainfall factor, slope-steepness factor) are higher in the Shihmen reservoir watershed, while others (soil erodibility factor, cover and management factor) are higher in the Lam Phra Ploeng basin. The net result is that these factors cancel each other out, and the amount of soil erosion of the two watersheds are very similar at 68.03 t/ha/yr and 67.57 t/ha/yr, respectively.

scholarly journals Soil losses in the State of Rondônia, Brazil

2021 ◽  
Vol 51 (5) ◽  
Author(s):  
Guilherme Henrique Expedito Lense ◽  
Taya Cristo Parreiras ◽  
Velibor Spalevic ◽  
Junior Cesar Avanzi ◽  
Ronaldo Luiz Mincato
Keyword(s):  
Water Conservation ◽  
Soil Loss ◽  
Agricultural Land ◽  
Water Discharge ◽  
Water Erosion ◽  
The State ◽  
Erosion Process ◽  
Management Scenarios ◽  
Model Soil ◽  
Soil Losses

ABSTRACT: In the state of Rondônia, deforestation, and inadequate soil use and management have intensified the water erosion process, causing degradation of agricultural land. Modeling is a tool that can assist in the adoption of targeted and effective measures for soil and water conservation in the region. In this context, the objective of the research was to model soil losses due to water erosion in the state of Rondônia using the Revised Universal Soil Loss Equation (RUSLE). The parameters related to rain erosivity, relief, erodibility, and soil cover, as well as the conservation practices of the state of Rondônia, were considered. The modeling steps were performed with the aid of the Geographic Information System. Results were validated with data of total sediments transported with water discharge. The estimated total soil loss was about 605 million tons per year, corresponding to an average loss of 22.50 Mg ha-1 year-1. In 19% of the state, the erosion rate was higher than the soil loss tolerance(T), and these areas should be prioritized for adopting measures to mitigate the erosion process. The RUSLE underestimated the generation of sediments at 0.56 Mg ha-1 year-1, which corresponds to an error of 18.60%. Results obtained can assist in the development of different soil use and management scenarios and provide options for policymakers to encourage soil conservation in the state of Rondônia.

scholarly journals Comparison of the Applicability of Different Soil Erosion Models to Predict Soil Erodibility Factor and Event Soil Losses on Loess Slopes in Hungary

Water ◽  
2021 ◽  
Vol 13 (24) ◽  
pp. 3517
Author(s):  
Boglárka Keller ◽  
Csaba Centeri ◽  
Judit Alexandra Szabó ◽  
Zoltán Szalai ◽  
Gergely Jakab
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Coefficient Of Determination ◽  
Soil Erodibility ◽  
The European Union ◽  
Extreme Precipitation Events ◽  
Erosion Models ◽  
Physically Based ◽  
Physically Based Models ◽  
Soil Losses

Climate change induces more extreme precipitation events, which increase the amount of soil loss. There are continuous requests from the decision-makers in the European Union to provide data on soil loss; the question is, which ones should we use? The paper presents the results of USLE (Universal Soil Loss Equation), RUSLE (Revised USLE), USLE-M (USLE-Modified) and EPIC (Erosion-Productivity Impact Calculator) modelling, based on rainfall simulations performed in the Koppány Valley, Hungary. Soil losses were measured during low-, moderate- and high-intensity rainfalls on cultivated soils formed on loess. The soil erodibility values were calculated by the equations of the applied soil erosion models and ranged from 0.0028 to 0.0087 t ha h ha−1 MJ−1 mm−1 for the USLE-related models. EPIC produced larger values. The coefficient of determination resulted in an acceptable correlation between the measured and calculated values only in the case of USLE-M. Based on other statistical indicators (e.g., NSEI, RMSE, PBIAS and relative error), RUSLE, USLE and USLE-M resulted in the best performance. Overall, regardless of being non-physically based models, USLE-type models seem to produce accurate soil erodibility values, thus modelling outputs.

Application of a physically based soil erosion model, GUEST, in the absence of data on runoff rates II.

Soil Research ◽  
1999 ◽  
Vol 37 (1) ◽  
pp. 13 ◽  
Author(s):  
B. Yu ◽  
C. W. Rose ◽  
A. Sajjapongse ◽  
D. Yin ◽  
Z. Eusof ◽  
...  
Keyword(s):  
Soil Loss ◽  
Storm Event ◽  
Soil Erodibility ◽  
Storm Events ◽  
Erosion Model ◽  
Physically Based ◽  
Runoff Rate ◽  
Model Efficiency ◽  
Coarse To Fine ◽  
Event Basis

Runoff rates were estimated from rainfall rates and runoff amounts for 4 experimental sites in China, Malaysia, and Thailand before a physically based erosion model GUEST was used to determine the soil erodibility parameter and evaluate the potential to use the erosion model to predict the amount of soil loss on an event basis. We also examined 3 different ways of determining the soil erodibility parameter for the same storm event using: (i) hydrographs estimated from rainfall intensities and runoff amounts; (ii) an effective runoff rate calculated from the hydrograph; (iii) an estimate of the effective runoff rate based on a scaling technique involving the peak rainfall intensity and the gross runoff coefficient. All 3 methods can produce consistent soil erodibility parameters for a given runoff event. The calculated soil erodibility for individual storm events for all sites shows considerable temporal variation and for most sites a decreasing trend over time, as observed elsewhere in the same region. Among the 4 soils examined, the average soil erodibility tends to decrease as the ratio of coarse to fine materials decreases. When the erosion model GUEST is used to predict event soil loss using estimated soil erodibility parameters, an average model efficiency of 0·68 is achieved for the sites tested.

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