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 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.

A process-based soil erosion model ensemble to reduce model uncertainty in climate change impact assessments

2021 ◽  
Author(s):  
Joris Eekhout ◽  
Agustín Millares-Valenzuela ◽  
Alberto Martínez-Salvador ◽  
Rafael García-Lorenzo ◽  
Pedro Pérez-Cutillas ◽  
...  
Keyword(s):  
Climate Change ◽  
Soil Erosion ◽  
Model Uncertainty ◽  
Extreme Precipitation ◽  
Climate Change Impact ◽  
Soil Loss ◽  
Model Ensemble ◽  
Erosion Model ◽  
Erosion Models ◽  
Change Impact

<p>The impact of climate change on future soil loss is commonly assessed with soil erosion models, which are potentially an important source of uncertainty. Here we propose a soil erosion model ensemble, with the aim to reduce the model uncertainty in climate change impact assessments. The model ensemble consisted of five continuous process-based soil erosion models that run at a daily time step, i.e. DHSVM, HSPF, INCA, MMF and SHETRAN. All models simulate detachment by raindrop impact (interrill erosion), detachment by runoff (rill erosion) and immediate deposition of sediment within the cell of its origin. The models were implemented in the SPHY hydrological model. The soil erosion model ensemble was applied in a semi-arid catchment in the southeast of Spain. We applied three future climate scenarios based on global mean temperature rise (+1.5, +2 and +3 ºC). Data from two contrasting regional climate models were used to assess how an increase and a decrease in extreme precipitation affect model uncertainty. Soil loss is projected to increase and decrease under climate change, mostly reflecting the change in extreme precipitation. Model uncertainty is found to increase with increasing slope, extreme precipitation and runoff, which reveals some inherent differences in model assumptions among the five models. Moreover, the model uncertainty increases in all climate change scenarios, independent on the projected change in annual precipitation and extreme precipitation. This supports the importance to consider model uncertainty through model ensembles of climate, hydrology, and soil erosion in climate change impact assessments.</p><p>This research was funded by ERDF/Spanish Ministry of Science, Innovation and Universities - State Research Agency (AEI) /Project CGL2017-84625-C2-1-R; State Program for Research, Development and Innovation Focused on the Challenges of Society.</p>

scholarly journals Storm-wise sediment yield prediction using hillslope erosion model in semi-arid abundant lands

2013 ◽  
Vol 8 (No. 1) ◽  
pp. 42-48 ◽  
Author(s):  
S. Fazli ◽  
H. Noor
Keyword(s):  
Soil Erosion ◽  
Sediment Yield ◽  
Land Surface ◽  
Soil Conservation ◽  
Soil Erodibility ◽  
Storm Events ◽  
Erosion Model ◽  
Sediment Yields ◽  
Slope Steepness ◽  
Erosion Models

Evaluation of soil erosion by existing models is needed as an important tool for managerial purposes in designation of proper water and soil conservation techniques. The present study aimed to assess the applicability of hillslope erosion model (HEM) as one of the newest erosion models for prediction of storm-wise sediment yield in Khosbijan rangeland with 20% slope steepness by using soil erosion standard plots. In order to run the model, runoff depth, land surface cover, soil texture, slope steepness and length were determined for 16 storm events. The results showed that the uncalibrated HEM did not simulate the observed sediment yields properly. Calibration of soil erodibility parameter and developing regression between observed and estimated data indicated that the model was capable of predicting sediment yield in plots by applying soil erodibility parameter of 0.15 with determination coefficient of 0.64 and estimate error of 40%. 

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.

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.

scholarly journals Estimation of soil loss using remote sensing and GIS-based universal soil loss equation in northern catchment of Lake Tana Sub-basin, Upper Blue Nile Basin, Northwest Ethiopia

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Veera Narayana Balabathina ◽  
R. P. Raju ◽  
Wuletaw Mulualem ◽  
Gedefaw Tadele
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Soil Erosion ◽  
Soil Loss ◽  
Erosion Rate ◽  
Soil Erodibility ◽  
Lake Tana ◽  
Erosion Rates ◽  
Soil Erosion Rate ◽  
Soil Loss Equation

Abstract Background Soil erosion is one of the major environmental challenges and has a significant impact on potential land productivity and food security in many highland regions of Ethiopia. Quantifying and identifying the spatial patterns of soil erosion is important for management. The present study aims to estimate soil erosion by water in the Northern catchment of Lake Tana basin in the NW highlands of Ethiopia. The estimations are based on available data through the application of the Universal Soil Loss Equation integrated with Geographic Information System and remote sensing technologies. The study further explored the effects of land use and land cover, topography, soil erodibility, and drainage density on soil erosion rate in the catchment. Results The total estimated soil loss in the catchment was 1,705,370 tons per year and the mean erosion rate was 37.89 t ha−1 year−1, with a standard deviation of 59.2 t ha−1 year−1. The average annual soil erosion rare for the sub-catchments Derma, Megech, Gumara, Garno, and Gabi Kura were estimated at 46.8, 40.9, 30.9, 30.0, and 29.7 t ha−1 year−1, respectively. Based on estimated erosion rates in the catchment, the grid cells were divided into five different erosion severity classes: very low, low, moderate, high and extreme. The soil erosion severity map showed about 58.9% of the area was in very low erosion potential (0–1 t ha−1 year−1) that contributes only 1.1% of the total soil loss, while 12.4% of the areas (36,617 ha) were in high and extreme erosion potential with erosion rates of 10 t ha−1 year−1 or more that contributed about 82.1% of the total soil loss in the catchment which should be a high priority. Areas with high to extreme erosion severity classes were mostly found in Megech, Gumero and Garno sub-catchments. Results of Multiple linear regression analysis showed a relationship between soil erosion rate (A) and USLE factors that soil erosion rate was most sensitive to the topographic factor (LS) followed by the support practice (P), soil erodibility (K), crop management (C) and rainfall erosivity factor (R). Barenland showed the most severe erosion, followed by croplands and plantation forests in the catchment. Conclusions Use of the erosion severity classes coupled with various individual factors can help to understand the primary processes affecting erosion and spatial patterns in the catchment. This could be used for the site-specific implementation of effective soil conservation practices and land use plans targeted in erosion-prone locations to control soil erosion.

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

Application of Erosion 2D Model for Erosion Studies in Makurdi Metropolis of Benue State, Nigeria

2011 ◽  
Vol 367 ◽  
pp. 815-825 ◽  
Author(s):  
M.O. Isikwue ◽  
T.G. Amile
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Loss Rate ◽  
Physically Based Model ◽  
Cover Cropping ◽  
Physically Based ◽  
The City ◽  
Land Grading ◽  
2D Model ◽  
Soil Loss Rate

The equations of Erosion 2D Model (a physically based model) were transformed into a computer programme called EROSOFT and used to predict the rate of soil loss in Makurdi metropolis. The model has detachment, transport and deposition components. Four sites were chosen within the metropolis for this study. Soil samples were collected from the sites for laboratory analysis. Rainfall and runoff fluids were collected from the sites to determine their densities. Levelling instrument was used to detremine the channels slopes. The model predicted an average annual soil loss rate of 310kg m-2s-1 for the metropolis. The sensitivity analysis of the model indicates that straight slopes are more prone to soil erosion. The result of the model deviates slightly from established facts that, sandy soils are more erodible and hence prone to be easily detached. Nevertheless, the model shows that soil erosion is influenced by slope geometry and rainfall intensity. The study attributes the major causes of soil erosion in the city to urban runoff concentration and removal of vegetation, and therefore suggests the use of land grading, land forming and cover cropping as well as conservation structures like road side drains for the control of erosion in the metropolis.

Modelling of impacts of erosion processes on agricultural landscapes due to intensive rainfall events

2020 ◽  
Author(s):  
Silvia Kohnová ◽  
Zuzana Németová
Keyword(s):  
Soil Erosion ◽  
Soil Degradation ◽  
Agricultural Land ◽  
Assessment Methods ◽  
Rainfall Events ◽  
Degradation Processes ◽  
Erosion Processes ◽  
Erosion Models ◽  
Physically Based ◽  
Physically Based Models

<p>At present, the occurrence of extreme precipitation events is becoming more and more frequent and therefore it is important to quantify their impact on the landscape and soil degradation processes. Until now a wide range of soil erosion models have been developed and many significant studies performed to evaluate soil erosion processes at local and regional level, but there are still many modeling principles that suffer from a range of problems. The general problem in soil erosion modelling lies in the validation and verification of the methodologies used. The validation of erosion models is a very complicated and complex process due to lack of suitable sites, financial demands and due to the high temporal and spatial variability. The paper points to validate the physically and event-based Erosion-3D model predominantly developed to calculate the amounts of soil loss, surface runoff, and depositions resulting from natural and design rainfall events. In the study two different erosion assessment methods were chosen in order to compare diverse evaluation approaches. Both water erosion assessment methods used have certain advantages and disadvantages, but nowadays the use of physically-based models, which are a younger generation of models, are regarded to be a more innovative and effective technique for the evaluation of complex runoff-erosion processes, deposition and transport processes. The significant contribution of physically-based models is seen in their more precise representation of the erosion and deposition processes, a more proper calculation of the erosion, deposition and sediment yields and the application of more complicated characteristics, including fluctuating soil conditions and surface properties in comparison with empirical models. The validation of the models was performed based on the continuous rainfall events for the period selected (2015, 2016 and 2017). The extreme rainfall events occurring during the period were chosen and their serious impact on the agricultural land was modeled. The modelled sediment data were compared with the measured sediment deposition data obtained by a bathymetry survey of the Svacenicky Creek polder. The polder is situated in the middle of the Myjava hill lands in the western part of Slovakia and the bathymetry measurement were conducted using a hydrographical survey using the EcoMapper Autonomous Underwater Vehicle (AUV) device. The results of the study include a comparison between the modelled and measured data and an assessment of the impact of the intensive rainfall events on the investigated territory.</p><p>Key words: intensive rainfall events, agricultural land, soil degradation processes, hydrological extremes, physically-based model</p>

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