scholarly journals Application of the KINEROS 2 Model to Natural Basin for Estimation of Erosion

2021 ◽  
Vol 11 (19) ◽  
pp. 9320
Author(s):  
Javier Fortuño Fortuño Ibáñez ◽  
Manuel Gómez Gómez Valentín ◽  
Dongwoo Jang
Keyword(s):  
Soil Loss ◽  
Solid Material ◽  
Empirical Models ◽  
Accurate Estimation ◽  
Protective Measures ◽  
Physically Based Model ◽  
Sewer Systems ◽  
Erosion Models ◽  
Physically Based ◽  
Basin Area

This study compares different methods to calculate erosion and sedimentation processes in the Aviar Basin, a natural peri-urban basin located in Comúd’Encamp (Andorra).The basin area is small, covering less than one square kilometer. Currently, increased densities of houses and buildings under natural basins can cause drainage problems. This is due to the heavy accumulation of eroded solid material in the sewer systems. Therefore, for a given basin condition, accurate estimation of erosion and sedimentation amounts is important. The development of erosion models aims to facilitate the estimation of eroded solid material and the design of possible protective measures to prevent soil losses. Both empirical and physically based erosion models were used to study the Aviar Basin for these purposes. Empirical models include USLE (Universal Soil Loss Equation), RUSLE (Revised USLE) and MUSLE (Modified USLE), while one physically based model, KINEROS 2, was used. The volumes of solid materials produced in the Aviar Basin during the year 2012 were determined using these four different erosion models and then compared between them. The results of this study show that the estimation of soil loss using KINEROS 2 is useful in practice because the results obtained are close to those obtained from the empirical 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.

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 Evaluation of Direct Horizontal Irradiance in China Using a Physically-Based Model and Machine Learning Methods

Energies ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 150 ◽  
Author(s):  
Feiyan Chen ◽  
Zhigao Zhou ◽  
Aiwen Lin ◽  
Jiqiang Niu ◽  
Wenmin Qin ◽  
...  
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
Spatiotemporal Variation ◽  
Multivariate Adaptive Regression Splines ◽  
Accurate Estimation ◽  
The Tibetan Plateau ◽  
Learning Methods ◽  
Physically Based Model ◽  
Machine Learning Methods ◽  
Physically Based

Accurate estimation of direct horizontal irradiance (DHI) is a prerequisite for the design and location of concentrated solar power thermal systems. Previous studies have shown that DHI observation stations are too sparsely distributed to meet requirements, as a result of the high construction and maintenance costs of observation platforms. Satellite retrieval and reanalysis have been widely used for estimating DHI, but their accuracy needs to be further improved. In addition, numerous modelling techniques have been used for this purpose worldwide. In this study, we apply five machine learning methods: back propagation neural networks (BP), general regression neural networks (GRNN), genetic algorithm (Genetic), M5 model tree (M5Tree), multivariate adaptive regression splines (MARS); and a physically based model, Yang’s hybrid model (YHM). Daily meteorological variables, including air temperature (T), relative humidity (RH), surface pressure (SP), and sunshine duration (SD) were obtained from 839 China Meteorological Administration (CMA) stations in different climatic zones across China and were used as data inputs for the six models. DHI observations at 16 CMA radiation stations were used to validate their accuracy. The results indicate that the capability of M5Tree was superior to BP, GRNN, Genetic, MARS and YHM, with the lowest values of daily root mean square (RMSE) of 1.989 MJ m−2day−1, and the highest correlation coefficient (R = 0.956), respectively. Then, monthly and annual mean DHI during 1960–2016 were calculated to reveal the spatiotemporal variation of DHI across China, using daily meteorological data based on the M5tree model. The results indicated a significantly decreasing trend with a rate of −0.019 MJ m−2during 1960–2016, and the monthly and annual DHI values of the Tibetan Plateau are the highest, while whereas the lowest values occur in the southeastern part of the Yunnan−Guizhou Plateau, the Sichuan Basin and most of the southern Yangtze River Basin. The possible causes for spatiotemporal variation of DHI across China were investigated by discussing cloud and aerosol loading.

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.

scholarly journals A new approach to mapping landslide hazards: a probabilistic integration of empirical and physically based models in the North Cascades of Washington, USA

2019 ◽  
Vol 19 (11) ◽  
pp. 2477-2495
Author(s):  
Ronda Strauch ◽  
Erkan Istanbulluoglu ◽  
Jon Riedel
Keyword(s):  
Statistical Approach ◽  
Joint Probability ◽  
North Cascades ◽  
Physically Based Model ◽  
New Approach ◽  
The North ◽  
Debris Avalanches ◽  
Landslide Hazards ◽  
Infinite Slope Stability Model ◽  
Physically Based

Abstract. We developed a new approach for mapping landslide hazards by combining probabilities of landslide impacts derived from a data-driven statistical approach and a physically based model of shallow landsliding. Our statistical approach integrates the influence of seven site attributes (SAs) on observed landslides using a frequency ratio (FR) method. Influential attributes and resulting susceptibility maps depend on the observations of landslides considered: all types of landslides, debris avalanches only, or source areas of debris avalanches. These observational datasets reflect the detection of different landslide processes or components, which relate to different landslide-inducing factors. For each landslide dataset, a stability index (SI) is calculated as a multiplicative result of the frequency ratios for all attributes and is mapped across our study domain in the North Cascades National Park Complex (NOCA), Washington, USA. A continuous function is developed to relate local SI values to landslide probability based on a ratio of landslide and non-landslide grid cells. The empirical model probability derived from the debris avalanche source area dataset is combined probabilistically with a previously developed physically based probabilistic model. A two-dimensional binning method employs empirical and physically based probabilities as indices and calculates a joint probability of landsliding at the intersections of probability bins. A ratio of the joint probability and the physically based model bin probability is used as a weight to adjust the original physically based probability at each grid cell given empirical evidence. The resulting integrated probability of landslide initiation hazard includes mechanisms not captured by the infinite-slope stability model alone. Improvements in distinguishing potentially unstable areas with the proposed integrated model are statistically quantified. We provide multiple landslide hazard maps that land managers can use for planning and decision-making, as well as for educating the public about hazards from landslides in this remote high-relief terrain.

New physically based model for thermal induced initial stress in 3D for silicon germanium films after deposition

2014 ◽  
Vol 33 (6) ◽  
pp. 2121-2138 ◽  
Author(s):  
Abderrazzak El Boukili
Keyword(s):  
Thermal Expansion ◽  
Initial Stress ◽  
Silicon Germanium ◽  
Rate Of Change ◽  
Thermal Mismatch ◽  
Electronic Band ◽  
Physically Based Model ◽  
Content Type ◽  
Physically Based ◽  
Pmos Transistor

Purpose – The purpose of this paper is to provide a new three dimension physically based model to calculate the initial stress in silicon germanium (SiGe) film due to thermal mismatch after deposition. We should note that there are many other sources of initial stress in SiGe films or in the substrate. Here, the author is focussing only on how to model the initial stress arising from thermal mismatch in SiGe film. The author uses this initial stress to calculate numerically the resulting extrinsic stress distribution in a nanoscale PMOS transistor. This extrinsic stress is used by industrials and manufacturers as Intel or IBM to boost the performances of the nanoscale PMOS and NMOS transistors. It is now admitted that compressive stress enhances the mobility of holes and tensile stress enhances the mobility of electrons in the channel. Design/methodology/approach – During thermal processing, thin film materials like polysilicon, silicon nitride, silicon dioxide, or SiGe expand or contract at different rates compared to the silicon substrate according to their thermal expansion coefficients. The author defines the thermal expansion coefficient as the rate of change of strain with respect to temperature. Findings – Several numerical experiments have been used for different temperatures ranging from 30 to 1,000°C. These experiments did show that the temperature affects strongly the extrinsic stress in the channel of a 45 nm PMOS transistor. On the other hand, the author has compared the extrinsic stress due to lattice mismatch with the extrinsic stress due to thermal mismatch. The author found that these two types of stress have the same order (see the numerical results on Figures 4 and 12). And, these are great findings for semiconductor industry. Practical implications – Front-end process induced extrinsic stress is used by manufacturers of nanoscale transistors as the new scaling vector for the 90 nm node technology and below. The extrinsic stress has the advantage of improving the performances of PMOSFETs and NMOSFETs transistors by enhancing mobility. This mobility enhancement fundamentally results from alteration of electronic band structure of silicon due to extrinsic stress. Then, the results are of great importance to manufacturers and industrials. The evidence is that these results show that the extrinsic stress in the channel depends also on the thermal mismatch between materials and not only on the material mismatch. Originality/value – The model the author is proposing to calculate the initial stress due to thermal mismatch is novel and original. The author validated the values of the initial stress with those obtained by experiments in Al-Bayati et al. (2005). Using the uniaxial stress generation technique of Intel (see Figure 2). Al-Bayati et al. (2005) found experimentally that for 17 percent germanium concentration, a compressive initial stress of 1.4 GPa is generated inside the SiGe layer.

A physically based model to simulate maxillo-facial surgery from 3D CT images

1999 ◽  
Vol 15 (2) ◽  
pp. 217-221 ◽  
Author(s):  
Alessandro Sarti ◽  
Roberto Gori ◽  
Claudio Lamberti
Keyword(s):  
Ct Images ◽  
3D Ct ◽  
Physically Based Model ◽  
Facial Surgery ◽  
Physically Based
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