Landslide susceptibility mapping by using fuzzy logic: a case study of Cham-gardalan catchment,Ilam, Iran

Landslides are introduced as regional movements, which influence different engineering structures such as roads, railways, and dams and cause the person’s death. Identification of landslide zones may decrease the financial losses and human injuries or deaths. This study tries to achieve a landslide susceptibility mapping in Cham-gardalan catchment by weighting the main criteria and the membership functions of fuzzy logic. For this, we applied the best relationship function between the presence and absence of landslides as well as a collection of the elements. At first, the landslide points were identified by the means of some components those of satellite images, topographical (1:50,000) and geographical (1:100,000) maps, field visits, and Google Earth software followed by the preparation of landslide distribution maps. Then, all effective landslide factors such as percentage of slope, slope aspect, height, geology, land uses, distance from roads, distance from drainages, distance from breakage, and precipitation map have been utilized in order to conduct the fuzzy analyses. Landslide susceptibility map was performed by fuzzy operators (Gamma, Product, Sum, Or, And) in the study area. After fuzzificating and weighting, the effective criteria of landslides were determined through fuzzy Gamma operators with the landaus of 0.2, 0.5, 0.8, and 0.9 and by comparing final maps for making an appropriate model of landslide susceptibility mapping. The regional susceptibility map represents the landslide-prone areas in five categories those of very low, low, moderate, high, and very high. Our results indicated that among the applied operators, Gamma with landau of 0.9 can be used as an appropriate method for mapping the landslide susceptibility due to the suitable fuzzification of given criteria based on landslide distribution maps. In addition, the elements of road, percentage of slope, distance from drainage, and geology were recognized as the most important factors for occurring the landslides.     

Utilization of Silica Fume to Maximize the Filler and Pozzolanic Effects of Stabilized Soil with Cement

Silica fume is identified as a pozzolan and supplementary cementitious material that can utilize to improve the mechanical properties of stabilized soil with cement. Silica fume wherein mixes with cemented soil in a proper dosage, it is susceptible to induce pozzolanic effect in cemented soil due to its fineness and high content of SiO₂ and Al₂O₃. The pozzolanic effect is vital to ensure ongoing strength of stabilized soil with cement. Up to now, stabilization of clay with cement and silica fume is not completely explored. This paper investigates: (i) the capability of utilizing the silica fume as a supplementary material for cement to maximize the filler and pozzolanic effects of compacted and stabilized soil (ii) the mechanical properties of compacted and stabilized clay with various proportions of cement and silica fume. For this purpose, a total of 120 untreated and stabilized soil admixtures were prepared by replacing ordinary Portland cement with silica fume. The influence of partial replacement of cement with silica fume on the bearing capacity, shear and compressive strength of compacted and stabilized soil was investigated. To achieve such aims, the stabilized soil specimens were examined in laboratory under direct shear, unconfined compression and California bearing ratio tests. Based on the findings of this paper the 28-day UCS of the stabilized soil with 2% partial substitution of cement with silica fume is almost 3.5-fold greater than that of the untreated. It was found that the optimum mix design for the stabilized soil is 6% cement and 2% silica fume. In conclusion, a notable discovery is that the partial substitution of cement with 2% silica fume in the optimum mix design significantly refined the pore spaces as a result of pozzolanic activity and filler effect of silica fume.     

Evaluation of ANFIS and LR models for seismic rockfalls’ susceptibility mapping: a case study of Firooz Abad-Kojour,Iran, Earthquake (2004)

Seismic rockfall is one of the prevalent geohazards that cause huge losses in the earthquake-stricken areas. In the present research, a model is developed to map susceptibility (occurrence probability) of seismic rockfalls in a regional scale using Logistic Regression (LR) and Adaptive Neuro-Fuzzy Inference System (ANFIS) techniques. In this research, Firooz Abad-Kojour earthquake of 2004 was introduced as the benchmark and the model base. The susceptible zones predicted by LR and ANFIS methods were compared with the database (distribution map) of seismic rockfalls, by which the results revealed a good overlapping between the susceptible zones predicted by the ANFIS and the field observation of rockfalls triggered by this earthquake. Besides, for the statistical evaluation of results obtained by LR and ANFIS models, the verification parameters with high accuracy such as density ratio (Dr), quality sum (Qs), and receiver-operating characteristic curve (ROC) were used. By analyzing the susceptibility maps and considering the Qs index obtained by LR (21.04184) and ANFIS (26.75592), it could be found that the Qs of ANFIS is higher than that of LR. Moreover, based on the obtained value of the area under the curve (AUC) from LR (0.972) and ANFIS (0.984) methods, ANFIS provided a higher accuracy in zonation and susceptibility mapping of rockfalls triggered by Firooz Abad-Kojour earthquake of 2004 compared to the LR method.     

Measuring sheet erosion using synthetic color‐contrast aggregates

The bulk of eroded soils measured at the outlets of plots, slopes and watersheds are suspended sediments, splash‐induced sheet erosion. It is depending on rainfall intensity and antecedent soil moisture contents and contributes to a significant proportion of soil loss that usually is ignored in soil erosion and sediment studies. A digital image processing method for tracing and measuring non‐suspended soil particles detached/transported by splash/runoff was therefore used in the present study. Accordingly, fine mineral pumice grains aggregated with white cement and coloured with yellow pigment powder, with the same size, shape and specific gravity as those of natural soil aggregates, called synthetic color‐contrast aggregates, were used as tracers for detecting soil particle movement. Subsequently, the amount of non‐suspended soil particles detached and moved downward the slope was inferred with the help of digital image processing techniques using MATLAB R2010B software (Mathworks, Natick, Massachusetts, USA). The present study was conducted under laboratory conditions with four simulated rainfall intensities between 30–90 mm h^‐1, five antecedent soil moisture contents between 12–44 % v v^‐1 and a slope of 30%, using sandy loam soils taken from a summer rangeland in the Alborz Mountains, Northern Iran. A range of total transported soil between 90.34 and 1360.93 g m^‐2 and net splash erosion between 36.82 and 295.78 g m^‐2were observed. The results also showed the sediment redeposition ratio ranging from 87.27% [sediment delivery ratio (SDR) = 12.73%] to 96.39% (SDR = 3.61%) in various antecedent soil moisture contents of rainfall intensity of 30 mm h^‐1 and from 80.55% (SDR = 19.45%) to 89.42% (SDR = 10.58%) in rainfall intensity of 90 mm h^‐1. Copyright © 2013 John Wiley & Sons, Ltd.     

Hydrochemical Characteristics and Sodification of Groundwater in the Shirin Sou, Hamedan, Western Iran

Salinity and sodicity of groundwater are the principal water quality concerns in irrigated areas of arid and semi-arid regions. The hydrochemical characteristics and sodicity of groundwater in the Shirin Sou area, western Iran were investigated in this study by chemical analyses of groundwater samples from 49 wells. Chemical analysis of the groundwater showed that the mean concentration of the cations was in the order: Na⁺ > Ca²⁺ > Mg²⁺ > K⁺, while that for anions was SO₃ ²⁻ > Cl⁻ > HCO₃ ⁻ > NO₃ ⁻. The most prevalent water type is Na–SO₄ followed by water types Na–Cl and Ca–SO₄. The chemical evolution of groundwater is primarily controlled by water–rock interactions: mainly weathering of aluminosilicates, dissolution of sulfate minerals, and cation exchange reactions. Sulfate dissolution and pyrite weathering may both contribute to the SO₄ ²⁻ load of the groundwater. High Na⁺ concentrations in groundwater participate in ion-exchange processes, resulting in the displacement of base cations into solution and raised concentrations in groundwater. The principal component analysis (PCA) performed on groundwater identified three principal components controlling variability of groundwater chemistry. Electrical conductivity, Ca²⁺, Mg²⁺, Na⁺, SO₄ ²⁻, and Cl⁻ content were associated in the same component (PC1) (salinity), most likely linked to anthropogenic activities.     

Numerical Modelling Investigation of Wave Interaction on Composite Berm Breakwater

China Ocean Engineering - The breakwaters have experienced many changes during their construction history. These changes have been considered to improve their performance, depending on their...     

Time-domain two-dimensional site response analysis of non-homogeneous topographic structures by a hybrid BE/FE method

In this paper, an advanced formulation of the time-domain, two-dimensional hybrid finite element–boundary element method (FEM/BEM) is presented, and applied to carry out site response analysis of homogeneous and non-homogeneous topographic structures subjected to incident in-plane motions. Seismic responses of half-plane, horizontally layered site, alluvial valley and ridge sections subjected to incident P and SV waves are analyzed in order to demonstrate the applicability and efficiency of the presented method. The numerical results show that hybrid BE/FE methods require smaller time steps than those needed by BEM schemes. They also show that in case of surface irregularities with height to half-width ratio of up to one, the topography effect could be noticeable, if incident waves have wavelengths of less than approximately eight times the width.     

Application of newly developed ensemble machine learning models for daily suspended sediment load prediction and related uncertainty analysis

ABSTRACT

Ensemble machine learning models have been widely used in hydro-systems modeling as robust prediction tools that combine multiple decision trees. In this study, three newly developed ensemble machine learning models, namely gradient boost regression (GBR), AdaBoost regression (ABR) and random forest regression (RFR) are proposed for prediction of suspended sediment load (SSL), and their prediction performance and related uncertainty are assessed. The SSL of the Mississippi River, which is one of the major world rivers and is significantly affected by sedimentation, is predicted based on daily values of river discharge (Q) and suspended sediment concentration (SSC). Based on performance metrics and visualization, the RFR model shows a slight lead in prediction performance. The uncertainty analysis also indicates that the input variable combination has more impact on the obtained predictions than the model structure selection.