Debi Prasanna Kanungo

Approaches for comparative evaluation of raster GIS-based landslide susceptibility zonation maps

Abstract Evaluation of maps generated from different conceptual models or data processing approaches at spatial level has importance in many geoenvironmental applications. This paper addresses the spatial comparison of different landslide susceptibility zonation (LSZ) raster maps of the same area derived from various procedures. In hilly regions such as the Himalayas, occurrence of landslides is frequent, which necessitates the study of landslides in the region for future developmental planning. A critical aspect in landslide studies is the procedure for assignment of weights to various causative factors affecting the occurrence of landslides. A detailed study on conventional, artificial neural network (ANN) black box, fuzzy set based and combined neural and fuzzy weighting procedures for LSZ mapping in the Himalayas has recently been published by the authors in [Kanungo, D.P., Arora, M.K., Sarkar, S., Gupta, R.P., 2006. A comparative study of conventional, ANN black box, fuzzy and combined neural and fuzzy weighting procedures for landslide susceptibility zonation in Darjeeling Himalayas. Engineering Geology 85, 347–366]. The evaluation of various maps in that study was however based only on comparison of areal extents of various landslide susceptibility zones. In this paper, we present a spatial level comparative evaluation of those maps to get a detailed insight into the performance of each of the weighting procedures for landslide susceptibility zonation. The evaluation has been done through three approaches, viz., landslide density analysis, error matrix analysis and difference image analysis. Based on the landslide density values, it is inferred that the combined neural and fuzzy procedure for LSZ mapping appears to be significantly better than other procedures. The error matrix analysis highlights the significant difference between the conventional subjective weight assignment procedure and the objective combined neural and fuzzy procedure. Finally, the significant influence of a causative factor has been revealed by difference image analysis. The use of these spatial evaluation approaches in tandem may be highly beneficial to quantitatively assess the landslide susceptibility zonation or any other such maps.

A fuzzy set based approach for integration of thematic maps for landslide susceptibility zonation

Spatial prediction of landslides is termed landslide susceptibility zonation (LSZ). In this study, an objective weighting approach based on fuzzy concepts is used for LSZ in a part of the Darjeeling Himalayas. Relevant thematic layers pertaining to landslide causative factors have been generated using remote sensing and geographic information system (GIS) techniques. The membership values for each category of thematic layers have been determined using the cosine amplitude fuzzy similarity method and are used as ratings. The integration of these ratings led to the generation of LSZ map. The integration of different ratings to generate an LSZ map has been performed using a fuzzy gamma operator apart from the arithmetic overlay approach. The process is based on determination of combined rating known as the landslide susceptibility index (LSI) for all the pixels using the fuzzy gamma operator and classification using the success rate curve method to prepare the LSZ map. The results indicate that as the gamma value increases, the accuracy of the LSZ map also increases. It is observed that the LSZ map produced by the fuzzy algebraic sum has reflected a more real situation in terms of landslides in the study area.

Strength parameter identification and application of soil-rock mixture for steep-walled talus slopes in southwestern China

Soil–rock mixture (SRM) is a heterogeneous geomaterial which is widely used in geotechnical engineering projects. As a special engineering geological body, SRM is composed of many complex components and is a heterogeneous multiphase material with various structural characters, and, thus, exhibits complex mechanical characteristics. The mechanical and physical properties of SRM are major factors which lead to different developmental patterns and deformation characteristics for talus slides. The formation mechanism and mechanical parameters of SRM also play important roles in research regarding slope stability. Taking the Mahe talus slide of the Lenggu hydropower station located on the Yalong River in southwestern China as a study example, many methods, such as the analogy method used in engineering, as well as laboratory model tests, large in situ shear tests, the back analysis method and numerical experiments, are applied in the comprehensive analysis of SRM from a macroscopic–microscopic perspective. The SRM samples collected from the Mahe talus slide consist of various soil and rock contents. The parameters gained from the frontal methods are applied in the stability of the Mahe talus slide. The main contents of the study are as follows: (1) according to the special structure of SRM, ten groups of SRM samples collected from different slide parts are used to perform particle size analysis experiments. The grading combination of the ten groups of samples is analyzed and the gradation curves are obtained from laboratory tests; (2) based on the intensive considerations of different particle compositions, the ten SRM group samples collected from the talus slide are used to perform direct shear tests; (3) due to the fact that the samples containing large-sized particles cannot be simulated by means of indoor direct shear tests, large in situ SRM shear tests are performed in the field; (4) SRM containing large-size particles is used to carry out numerical experiments using the similarity ratio, which is determined by contrasting the results of the laboratory tests and numerical experiments for the same size samples containing the same particle combinations. The numerical experiments are then adopted to obtain the shear strength parameters of different large size samples containing different particle combinations from the perspectives of rock content, particle size, and particle graduation; (5) according to the terrain, geomorphology and stability of the talus slide, the shear strength parameters in the case of natural conditions and magnitude 6 earthquakes on the Richter Scale are obtained using the back analysis method from the perspective of the limit equilibrium of the talus slide; and (6) the shear strength parameters of the various methods listed above are contrast-analyzed. The general shear strength parameters of the SRM are attained properly by using the weighted superposition of the safety coefficients from the different calculation methods. The general strength parameters are used to calculate the stability factor of the Mahe talus slide.

Rock slope stability assessment using finite element based modelling – examples from the Indian Himalayas

Numerical modelling of rock slides is a versatile approach to understand the failure mechanism and the dynamics of rock slopes. Finite element slope stability analysis of three rock slopes in Garhwal Himalaya, India has been carried out using a two dimensional plane strain approach. Two different modelling techniques have been attempted for this study. Firstly, the slope is represented as a continuum in which the effect of discontinuities is considered by reducing the properties and strength of intact rock to those of rock mass. The equivalent Mohr-Coulomb shear strength parameters of generalised Hoek-Brown (GHB) criterion and modified Mohr-Coulomb (MMC) criterion has been used for this continuum approach. Secondly, a combined continuum-interface numerical method has been attempted in which the discontinuities are represented as interface elements in between the rock walls. Two different joint shear strength models such as Barton-Bandis and Patton’s model are used for the interface elements. Shear strength reduction (SSR) analysis has been carried out using a finite element formulation provided in the PHASE2. For blocky or very blocky rock mass structure combined continuum-interface model is found to be the most suitable one, as this model is capable of simulating the actual field scenario.

Effect of the combination characteristics of rock structural plane on the stability of a rock-mass slope

The structural planes play an important role in rock mass slope stability. In this paper, a series of triaxial tests on the rock mass samples with different dip angles, plane numbers and plane spacing of structural surfaces were carried out to study the effect of the combination characteristics of the rock structural plane on rock mass mechanic parameters. Based on the test results and the combination characteristics of the field structural plane, the rock mechanics parameters for the spillway lock chamber slope of the Liyuan hydroelectric station were forecast. The stability of the slope was rationally evaluated based on the forecasted rock mass mechanical parameters. Finally, the safety factor was obtained based on the shear strength reduction method.

Landslide hazard assessment in the upper Alaknanda valley of Indian Himalayas

Landslides are one of the major natural disasters that are frequently occurring in the Indian Himalayas causing considerable loss of lives and property every year. A proper landslide hazard assessment is imperative to minimize such losses. In the upper reaches of Alaknanda valley of Garhwal Himalaya, there are several landslide potential zones along the Pipalkoti–Badrinath National Highway (NH-58). In the present study, landslide hazard assessment has been carried out in the above said area by delineating a few landslide potential zones. An attempt has been made to define landslide intensity to assess the degree of hazard in these potential zones of landslide. A landslide intensity scale was defined for this part of Garhwal Himalaya. So far the criterion for landslide intensity has not been defined in the Indian context. The approach used can be used in other potential landslide areas of the Himalayas.

Artificial Neural Network (ANN) and Regression Tree (CART) applications for the indirect estimation of unsaturated soil shear strength parameters

The shear strength parameters of soil (cohesion and angle of internal friction) are quite essential in solving many civil engineering problems. In order to determine these parameters, laboratory tests are used. The main objective of this work is to evaluate the potential of Artificial Neural Network (ANN) and Regression Tree (CART) techniques for the indirect estimation of these parameters. Four different models, considering different combinations of 6 inputs, such as gravel %, sand %, silt %, clay %, dry density, and plasticity index, were investigated to evaluate the degree of their effects on the prediction of shear parameters. A performance evaluation was carried out using Correlation Coefficient and Root Mean Squared Error measures. It was observed that for the prediction of friction angle, the performance of both the techniques is about the same. However, for the prediction of cohesion, the ANN technique performs better than the CART technique. It was further observed that the model considering all of the 6 input soil parameters is the most appropriate model for the prediction of shear parameters. Also, connection weight and bias analyses of the best neural network (i.e., 6/2/2) were attempted using Connection Weight, Garson, and proposed Weight-bias approaches to characterize the influence of input variables on shear strength parameters. It was observed that the Connection Weight Approach provides the best overall methodology for accurately quantifying variable importance, and should be favored over the other approaches examined in this study.

Study on the Permeability Characteristics of Polyurethane Soil Stabilizer Reinforced Sand

A polymer material of polyurethane soil stabilizer (PSS) is used to reinforce the sand. To understand the permeability characteristics of PSS reinforced sand, a series of reinforcement layer form test, single-hole permeability test, and porous permeability test of sand reinforced with PSS have been performed. Reinforcement mechanism is discussed with scanning electron microscope images. The results indicated that the permeability resistance of sand reinforced with polyurethane soil stabilizer is improved through the formation of reinforcement layer on the sand surface. The thickness and complete degree of the reinforcement layer increase with the increasing of curing time and PSS concentration. The water flow rate decreases with the increasing of curing time or PSS concentration. The permeability coefficient decreases with the increasing of curing time and PSS concentration and increases with the increasing of depth in specimen. PSS fills up the voids of sand and adsorbs on the surface of sand particle to reduce or block the flowing channels of water to improve the permeability resistance of sand. The results can be applied as the reference for chemical reinforcement sandy soil engineering, especially for surface protection of embankment, slope, and landfill.

A Comparison of ANFIS and ANN for the Prediction of Peak Ground Acceleration in Indian Himalayan Region

Peak ground acceleration (PGA) plays an important role in assessing effects of earthquakes on the built environment, persons, and the natural environment. It is a basic parameter of seismic wave motion based on which earthquake resistant building design and construction are made. The level of damage is, among other factors, directly proportional to the severity of the ground acceleration, and it is important information for disaster-risk prevention and mitigation programs. In this study, a hybrid intelligent system called ANFIS (the adaptive neuro fuzzy inference system) is proposed for predicting Peak Ground Acceleration (PGA). Artificial neural network and Fuzzy logic provide attractive ways to capture nonlinearities present in a complex system. Neuro-Fuzzy modelling, which is a newly emerging versatile area, is a judicious integration of merits of above mentioned two approaches. In ANFIS, both the learning capabilities of a neural network and reasoning capabilities of fuzzy logic are combined in order to give enhanced prediction capabilities, as compared to using a single methodology alone. The input variables in the developed ANFIS model are the earthquake magnitude, epi-central distance, focal depth, and site conditions, and the output is the PGA values. Results of ANFIS model are compared with earlier results based on artificial neural network (ANN) model. It has been observed that ANN model performs better for PGA prediction in comparison to ANFIS model.

Experimental Study on Unconfined Compressive Strength of Organic Polymer Reinforced Sand

The natural sand is loose in structure with a small cohesive force. Organic polymer can be used to reinforce this sand. To assess the effectiveness of organic polymer as soil stabilizer (PSS), a series of unconfined compressive strength tests have been performed on reinforced sand. The focus of this study was to determine a curing method and a mix design to stabilize sand. The curing time, PSS concentration, and sand density were considered as variables in this study. The reinforcement mechanism was analyzed with images of scanning electron microscope (SEM). The results indicated that the strength of stabilized sand increased with the increase in the curing time, concentration, and sand density. The strength plateaus are at about curing time of 48 h. The UCS of samples with density of 1.4 g/cm3 at 10%, 20%, 30%, 40%, and 50% PSS concentration are 62.34 kPa, 120.83 kPa, 169.22 kPa, 201.94 kPa, and 245.28 kPa, respectively. The UCS of samples with PSS concentration of 30% at 1.4 g/cm3, 1.5 g/cm3, and 1.6 g/cm3 density are 169.22 kPa, 238.6 kPa 5, and 281.69 kPa, respectively. The chemical reaction between PSS and sand particle is at its microlevel, which improves the sand strength by bonding its particles together and filling the pore spaces. In comparison with the traditional reinforcement methods, PSS has the advantages of time saving, lower cost, and better environment protection. The research results can be useful for practical engineering applications, especially for reinforcement of foundation, embankment, and landfill.