Probabilistic landslide susceptibility mapping in the Lai Chau province of Vietnam: focus on the relationship between tectonic fractures and landslides

This study evaluates the susceptibility of landslides in the Lai Chau province of Vietnam using Geographic Information System (GIS) and remote sensing data to focus on the relationship between tectonic fractures and landslides. Landslide locations were identified from aerial photographs and field surveys. Topographic, geological data and satellite images were collected, processed, and constructed into a spatial database using GIS data and image-processing techniques. A scheme of the tectonic fracturing of crust in the Lai Chau region was established. Lai Chau was identified as a region with many crustal fractures, where the grade of tectonic fracture is closely related to landslide occurrence. The influencing factors of landslide occurrence were: distance from a tectonic fracture, slope, aspect, curvature, soil, and vegetative land cover. Landslide prone areas were analyzed and mapped using the landslide occurrence factors employing the probability–frequency ratio model. The results of the analysis were verified using landslide location data and showed 83.47% prediction accuracy. That emphasized a strong relationship between the susceptibility map and the existing landslide location data. The results of this study can form a basis stable development and land use planning for the region.     

Fracture mechanics analysis of multiple cracks in anisotropic media

This paper presents a single‐domain boundary element method (BEM) for linear elastic fracture mechanics analysis in the two‐dimensional anisotropic material. In this formulation, the displacement integral equation is collocated on the un‐cracked boundary only, and the traction integral equation is collocated on one side of the crack surface only. A special crack‐tip element was introduced to capture exactly the crack‐tip behavior. A computer program with the FORTRAN language has been developed to effectively calculate the stress intensity factors of an anisotropic material. This BEM program has been verified having a good accuracy with the previous researches. Furthermore, by analyzing the different anisotropic degree cracks in a finite plate, we found that the stress intensity factors of crack tips had apparent influence by the geometry forms of cracks and media with different anisotropic degrees. Copyright © 2010 John Wiley & Sons, Ltd.     

A multiphase approach for evaluating the horizontal and rocking impedances of pile group foundations

This paper advocates the use of a multiphase model, already developed for static or quasi‐static geotechnical engineering problems, for simulating the behaviour of piled raft foundations subject to horizontal as well as rocking dynamic solicitations. It is shown that such a model, implemented in a FEM code, yields appropriate predictions for the foundation impedance characteristics, provided that shear and bending effects in the piles are taken into account, thus corroborating the findings of the asymptotic homogenization theory. Besides, it is notably pointed out that such a multiphase‐based computational tool makes it possible to assess the dynamic behaviour of pile groups in a much quicker way than when using direct numerical simulations, which may face oversized problems when large pile groups are concerned. Copyright © 2016 John Wiley & Sons, Ltd.     

The data‐driven approach as an operational real‐time flood forecasting model

Accurate water level forecasts are essential for flood warning. This study adopts a data‐driven approach based on the adaptive network–based fuzzy inference system (ANFIS) to forecast the daily water levels of the Lower Mekong River at Pakse, Lao People's Democratic Republic. ANFIS is a hybrid system combining fuzzy inference system and artificial neural networks. Five ANFIS models were developed to provide water level forecasts from 1 to 5 days ahead, respectively. The results show that although ANFIS forecasts of water levels up to three lead days satisfied the benchmark, four‐ and five‐lead‐day forecasts were only slightly better in performance compared with the currently adopted operational model. This limitation is imposed by the auto‐ and cross‐correlations of the water level time series. Output updating procedures based on the autoregressive (AR) and recursive AR (RAR) models were used to enhance ANFIS model outputs. The RAR model performed better than the AR model. In addition, a partial recursive procedure that reduced the number of recursive steps when applying the AR or the RAR model for multi‐step‐ahead error prediction was superior to the fully recursive procedure. The RAR‐based partial recursive updating procedure significantly improved three‐, four‐ and five‐lead‐day forecasts. Our study further shows that for long lead times, ANFIS model errors are dominated by lag time errors. Although the ANFIS model with the RAR‐based partial recursive updating procedure provided the best results, this method was able to reduce the lag time errors significantly for the falling limbs only. Improvements for the rising limbs were modest. Copyright © 2011 John Wiley & Sons, Ltd.