Hyunuk An

Quantitative assessment of disaster resilience: An empirical study on the importance of post-disaster recovery costs

Recovery costs are as important as losses for decision-making in disaster mitigation given that recovery costs reflect the restorative capacity of affected regions. Hence, this study analyses recovery costs. Results show that the total post-disaster recovery costs in Korea are on average one and a half times the actual losses, mainly because of the private sector. This ratio depends on the hazard type. In Korea, the highest ratio (almost four) arises after heavy rains because of the weak restorative capacity of river systems to heavy rains. The study introduces the community resilience cost index (CRCI), obtained by adding recovery costs and losses and dividing the resultant sum by the magnitude of exposure levels to quantify national and regional resilience. Results show that the recovery cost is an essential component for assessing resilience. In particular, the high ratio of recovery costs to losses owing to heavy rains changes the priorities determined by losses only. The key contribution of this work is that the ratios between losses and recovery costs can estimate the recovery costs based on losses given the high correlation. The study ascertains the most vulnerable system and explains why this is so through analyzing the recovery costs. The importance of recovery costs in quantitative resilience assessments is exemplified. Last, the CRCI is transferrable to other countries to assess their resilience and to establish their priorities and vulnerabilities.

A Comparative Analysis on Slope Stability Using Specific Catchment Area Calculation

There has been an increase for the landslide areas and restoration expenses due, in large part, to the increased locally heavy rains caused by recent climate change as well as the reckless development. This study carried out a slope stability analysis by the application of distributed wetness index, using the GIS-based infinite slope stability model, which took the root cohesion effect into consideration, for part of Mt. Umyeon in Seoul, where landslide occurred in July 2011, in order to compensate the defects of existing analysis method, and subsequently compared its result with the case on the exploitation of lumped wetness index. In addition, this study estimated the distributed wetness index by methodology, applying three methods of specific catchment area calculation: single flow direction (SFD), multiple flow direction (MFD), and infinity flow direction (IFD), for catchment area, one of the variables of distributed wetness indices, and finally implemented a series of comparative analysis for slope stability by methodology. The simulation results showed that most unstable areas within the study site were dominantly located in cutting-area surroundings along with the residential area and the mountaintop and unstable areas of IFD and lumped wetness index method were similar while SFD and MFD provided smaller unstable areas than the two former methods.

Comparing the performance of TRIGRS and TiVaSS in spatial and temporal prediction of rainfall-induced shallow landslides

Abstract This study compares the performance of transient rainfall infiltration and grid-based regional slope stability (TRIGRS) model and time-variant slope stability (TiVaSS) model in the prediction of rainfall-induced shallow landslides. TRIGRS employs one-dimensional (1-D) subsurface flow to simulate the infiltration rate, whereas a three-dimensional (3-D) model is utilized in TiVaSS. The former has been widely used in landslide modeling, while the latter was developed only recently. Both programs are used for the spatiotemporal prediction of shallow landslides caused by rainfall. This study uses the July 2011 landslide event that occurred in Mt. Umyeon, Seoul, Korea, for validation. The performance of the two programs is evaluated by comparison with data of the actual landslides in both location and timing by using a landslide ratio for each factor of safety class (

Creating an advanced backpropagation neural network toolbox within GIS software

{\text{LR}}_{\text{class}}

Numerical Simulation of Urban Flash Flood Experiments Using Adaptive Mesh Refinement and Cut Cell Method

LRclass index), which was developed for addressing point-like landslide locations. Moreover, the influence of surface flow on landslide initiation is assessed. The results show that the shallow landslides predicted by the two models are highly consistent with those of the observed sliding sites, although the performance of TiVaSS is slightly better. Overland flow affects the buildup of the pressure head and reduces the slope stability, although this influence was not significant in this case. A slight increase in the predicted unstable area from 19.30 to 19.93% was recorded when the overland flow was considered. It is concluded that both models are suitable for application in the study area. However, although it is a well-established model requiring less input data and shorter run times, TRIGRS produces less accurate results.

Uncertainty assessment of soil erosion model using particle filtering

최근 지구온난화 및 기후변화에 의한 재난이 빈발하고 있어 미국이나 네덜란드 같은 제방 선진국에서는 특수한 경우 적게는 500년, 크게는 10,000년 빈도의 홍수위까지도 고려하는 극단적인 수준의 제방설계기준을 적용하고 있다. 우리나라도 지난 몇 년간 국가하천을 중심으로 대하천 정비사업이 추진되었다. 주로 하천준설과 제방증축 및 신축 등으로 진행된 사업에 의해 하천환경이 광범위하게 변화되었으나 제방의 안전과 관련된 하천환경 변화에 대응하는 구체적인 대응방안을 제시하지는 못하고 있는 실정이다. 따라서 본 연구에서는 제방침투감지시스템 Testbed가 구축되어 있는 낙동강 회천의 율지제를 대상으로 제방 안전성을 평가하였다. 평가방법은 간극수압 계측자료를 이용하여 2차원 지하수 침투모형인 SEEP/W를 이용하여 제방의 파이핑 현상을 분석하였으며, 제방의 형상과 홍수파형에 따른 침투현상을 모의하여 제방안정성을 평가하였다. 【Because of the rapid rising of water related disasters due to the global warming, the extreme design criteria of levee construction for severe flood has been applied in several developed countries such as USA and Netheland. In Korea, the national river restoration projects were carried out on 4 major rivers in recent several years. The projects consisted of riverbed dredge and levee reinforcement, and new construction have caused wide change of river environment. However, concrete countermeasures for levee safety and river management have not been suggested until now. Therefore, this study assesses the levee safety of Yulji levee located in Hoechon, Nakdong Basin, where the Levee Seepage Monitoring System installed. The stability of levee is assessed based on the simulation performed by SEEP/W(2D unsaturated seepage model) and the simulated results are compared with the observed data. The effects of the flood wave and levee shape on the levee safety are investigated through several simulations.】

Levee Stability Assessment depending on Level of Inland and Riverside land in Flow State

An artificial neural network (ANN) toolbox is created within GIS software for spatial interpolation, which will help GIS users to train and test ANNs, perform spatial analysis, and display results as a single process. The performance is compared to that of the open source Fast Artificial Neural Network library and conventional interpolation methods by creating digital elevation models (DEMs) given that nearly exact solutions exist. Simulation results show that the advanced backpropagations such as iRprop speed up the learning, while they can get stuck in a local minimum depending on initial weight sets. Besides, the division of input–output examples into training and test data affects the accuracy, particularly when the distribution of the examples is skewed and peaked, and the number of data is small. ANNs, however, show the similar performance to inversed distance weighted or kriging and outperform polynomial interpolations as a global interpolation method in high-dimensional data. In addition, the neural network residual kriging (NNRK) model, which combines the ANN toolbox and kriging within GIS software, is performed. The NNRK outperforms conventional methods and well captures global trends and local variations. A key outcome of this work is that the ANN toolbox created within the de facto standard GIS software is applicable to various spatial analysis including hazard risk assessment over a large area, in particular when there are multiple potential causes, the relationship between risk factors and hazard events is not clear, and the number of available data is small given its performance for DEM generation.

Improvement of the Method using the Coefficient of Variation for Automatic Multi-segmentation Method of a Rating Curve

ABSTRACT In hydraulic research, numerical modelling of complex flows is essential for managing water risks. High-resolution finite volume schemes have become popular for shallow water flow modelling due to their mass and momentum balance characteristics and their ability to capture shocks. These methods use slope limiters to suppress numerical oscillations near discontinuities. However, one-dimensional limiters do not assure numerical accuracy in multidimensional applications, occasionally leading to excessive or insufficient numerical dissipation. For this reason, a multidimensional limiting process (MLP) was developed for oscillation control in multidimensional compressible flows. In this paper, we implement MLP on adaptive quadtree grids for shallow water flow simulations and compare MLP performance with simulations using conventional limiters. Four simulation cases show that MLP outperforms conventional limiters, and yield more accurate and stable solutions on adaptive quadtree grids. The capability of MLP for oscillation control is more noticeable on quadtree than on uniform grids.