Soil Erosion: Application of 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&#160;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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Evaluation of Soil Erosion and Its Prediction Protocols around the Hilly Areas of Mubi Region, Northeast Nigeria

10.5772/intechopen.100477 ◽

2021 ◽

Author(s):

Ijasini John Tekwa ◽

Abubakar Musa Kundiri

Keyword(s):

Soil Erosion ◽

Soil Nutrient ◽

Surface Erosion ◽

Mountain Ranges ◽

Concentrated Flow ◽

Erosion Processes ◽

Physically Based ◽

Physically Based Models ◽

Peasant Farmers ◽

Northeast Nigeria

Soil erosion is a severe degradation phenomena that has since received huge attention among earth scientists in the developed worlds, and same efforts are now extending to Africa and other parts of underdeveloped worlds. This chapter focuses on collation, analyzing and appraising of soil ero¬sion studies around Mubi region, Northeast Nigeria, where the Mandara mountain ranges is notably responsible for spurring soil erosion. This chapter reviewed reports on the: (a) Mubi regional soil properties, erosion processes and principles of their occurrence, (b) soil erosion predictions using empirical and physically-based models by researchers, and, (c) economicimplications and managements of soil erosion in the region. This chapter reveals that classical and rill/ephemeral gully (EG) erosion features received more research attention than surface erosion such as splash and sheet. No information was reported on effects of landslides/slumping noticeable along rivers/stream banks around the region. The few economic analysis reported for soil nutrient and sediments entrained by concentrated flow channels were very high and intolerable to the predominantly peasant farmers in the region. It is hoped that the considerable volumes of erosion researches and recommendations assembled in this chapter shall be carefully implemented by prospective farmers, organizations, and residents in the Mubi region.

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Sediment Yield Prediction in Tanzania:Case study of Dodoma District Catchments

Tanzania Journal of Engineering and Technology ◽

10.52339/tjet.v31i1.417 ◽

2008 ◽

Vol 31 (1) ◽

pp. 63-71

Author(s):

Mathew K. Mulemgera

Keyword(s):

Water Resources ◽

Soil Erosion ◽

Sediment Yield ◽

Development Projects ◽

Yield Prediction ◽

Erosion Prediction ◽

Yield Modeling ◽

Physically Based ◽

Physically Based Models ◽

Rating Curves

Soil erosion and sedimentation is serious and is resulting in rapid sedimentation of streams and reservoirs in Tanzania. This makes sediment yield modeling important before undertaking water resources development projects, although it has so far not been done in the country. At present sediment yield prediction can be done using physically based models,empirical soil erosion and sediment yield models, and sediment rating curves. The physically based models contain numerous parameters that are difficult to measure or estimate, making them inappropriate in developing countries like Tanzania. The rating curves give rough estimates while the empirical sediment yield models need runoff data that is notavailable in Tanzania. The revised USLE parametric (empirical) model that had been tested and found to be suitable for soil erosion prediction was selected for sediment yield prediction study reported in this paper. The testing of the model has shown to give acceptable results. For sediment measurements ranging from about 7 t/ha.year to 11 t/ha.year, the model predicted sediments yields ranging from about 6 t/ha.year to 12 t/ha.year, withcoefficent of determination (R 2 ) equal to about 0.53. Since soil erosion and sedimentation of water resources are serious problems in Tanzania, sediment yield modeling using the RUSLE can be a very useful tool in the country when used.

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

Water ◽

10.3390/w13243517 ◽

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.

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On the residual strength of aging cast iron trunk mains: Physically-based models for asset failure

Materials Science and Engineering A ◽

10.1016/j.msea.2016.03.029 ◽

2016 ◽

Vol 663 ◽

pp. 204-212 ◽

Cited By ~ 8

Author(s):

Azadeh Fahimi ◽

Timothy S. Evans ◽

Jeff Farrow ◽

David A. Jesson ◽

Mike J. Mulheron ◽

...

Keyword(s):

Cast Iron ◽

Residual Strength ◽

Physically Based ◽

Physically Based Models

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Performance of the dynamically dimensioned search algorithm: influence of parameter initialization strategy when calibrating a physically based hydrological model

Hydrology Research ◽

10.2166/nh.2017.139 ◽

2017 ◽

Vol 49 (4) ◽

pp. 971-988 ◽

Cited By ~ 5

Author(s):

Franck Lespinas ◽

Ashu Dastoor ◽

Vincent Fortin

Keyword(s):

Search Algorithm ◽

Low Cost ◽

Initial Parameter ◽

Cost Strategy ◽

Physically Based ◽

Physically Based Models ◽

Calibration Solution ◽

Low Cost Strategy ◽

Parameter Values ◽

Initialization Strategy

Abstract This study presents an evaluation of the performance of the dynamically dimensioned search (DDS) algorithm when calibrating the hydrological component of the Visualizing Ecosystems for Land Management Assessments (VELMA) ecohydrological model. Two calibration strategies were tested for the initial parameter values: (1) a ‘high-cost strategy’, where 100 sets of initial parameter values were randomly chosen within the overall parameter space, and (2) a ‘low-cost strategy’, where a unique set of initial parameter values was derived from the available field data. Both strategies were tested for six different values of the maximum number of model evaluations ranging between 100 and 10,000. Results revealed that DDS is able to converge rapidly to a good parameter calibration solution of the VELMA hydrological component regardless of the parameter initialization strategy used. The accuracy and convergence efficiency of the DDS algorithm were, however, slightly better for the low-cost strategy. This study suggests that initializing the parameter values of complex physically based models using information on the watershed characteristics can increase the efficiency of the automatic calibration procedures.

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Evaluating performances of simplified physically based models for landslide susceptibility

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-12-13217-2015 ◽

2015 ◽

Vol 12 (12) ◽

pp. 13217-13256 ◽

Cited By ~ 5

Author(s):

G. Formetta ◽

G. Capparelli ◽

P. Versace

Keyword(s):

Landslide Susceptibility ◽

Goodness Of Fit ◽

Shallow Landslides ◽

Model Parameters ◽

Test Case ◽

Susceptibility Analysis ◽

Physically Based ◽

Private And Public ◽

Physically Based Models

Abstract. Rainfall induced shallow landslides cause loss of life and significant damages involving private and public properties, transportation system, etc. Prediction of shallow landslides susceptible locations is a complex task that involves many disciplines: hydrology, geotechnical science, geomorphology, and statistics. Usually to accomplish this task two main approaches are used: statistical or physically based model. Reliable models' applications involve: automatic parameters calibration, objective quantification of the quality of susceptibility maps, model sensitivity analysis. This paper presents a methodology to systemically and objectively calibrate, verify and compare different models and different models performances indicators in order to individuate and eventually select the models whose behaviors are more reliable for a certain case study. The procedure was implemented in package of models for landslide susceptibility analysis and integrated in the NewAge-JGrass hydrological model. The package includes three simplified physically based models for landslides susceptibility analysis (M1, M2, and M3) and a component for models verifications. It computes eight goodness of fit indices by comparing pixel-by-pixel model results and measurements data. Moreover, the package integration in NewAge-JGrass allows the use of other components such as geographic information system tools to manage inputs-output processes, and automatic calibration algorithms to estimate model parameters. The system was applied for a case study in Calabria (Italy) along the Salerno-Reggio Calabria highway, between Cosenza and Altilia municipality. The analysis provided that among all the optimized indices and all the three models, the optimization of the index distance to perfect classification in the receiver operating characteristic plane (D2PC) coupled with model M3 is the best modeling solution for our test case.

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