• The Journal of Engineering Geology
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• v.34 no.2
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• pp.173-191
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• 2024

Landslides pose significant threats to many countries globally, yet the development and implementation of effective landslide early warning systems (LEWS) remain challenging due to multifaceted complexities spanning scientific, technological, and political domains. Addressing these challenges demands a holistic approach. Technologically, integrating thresholds, such as rainfall thresholds, with real-time data within accessible, open-source software stands as a promising solution for LEWS. This article introduces LandScient_EWS, a PHP-based program tailored to address this need. The software facilitates the comparison of real-time measured data, such as rainfall, with predefined landslide thresholds, enabling precise calculations and graphical representation of real-time landslide advisory levels across diverse spatial scales, including regional, basin, and hillslope levels. To illustrate its efficacy, the program was applied to a case study in Medellin, Colombia, where a rainfall event on August 26, 2008, triggered a shallow landslide. Through pre-defined rainfall intensity and duration thresholds, the software simulated advisory levels during the recorded rainfall event, utilizing data from a rain gauge positioned within a small watershed and a single grid cell (representing a hillslope) within that watershed. By identifying critical conditions that may lead to landslides in real-time scenarios, LandScient_EWS offers a new paradigm for assessing and responding to landslide hazards, thereby improving the efficiency and effectiveness of LEWS. The findings underscore the software's potential to streamline the integration of rainfall thresholds into both existing and future landslide early warning systems.

• Journal of the Korean Society of Safety
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• v.37 no.6
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• pp.148-157
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• 2022

Every year, particularly during the monsoon rainy season, landslides at the Chuncheon province of South Korea cause tremendous damage to lives, properties, and infrastructures. More so, the high rainfall intensity and long rainfall days that occurred in 2020 have increased the water content in the soil, thereby increasing the chances of landslide occurrences. Besides this, the rainfall thresholds and characteristics responsible for the initiation of landslides in this region have not been properly identified. Therefore, this paper addresses the rainfall thresholds responsible for the initiation of landslides at Chuncheon from a regional perspective. Using data obtained from rainfall measurements taken from 2002 to 2011, we identify a threshold relationship between rainfall intensity and rainfall duration for the initiation of landslides. In addition, we identify the relationship between the rainfall intensity using a 3-day, 7-day, and 10-day antecedent rainfall observation. Specifically, we estimate the rainfall data at 8 sites where debris flow occurred in 2011 by kriging. Following this, the estimated data are used to construct the relationship between the intensity (I), duration (D), and frequency (F) of rainfall. The results of the intensity-duration-frequency (IDF) analysis show that landslides will occur under a rainfall frequency below a 2-year return period at two areas in Chuncheon. These results will be effectively used to design structures that can prevent the occurrence of landslides in the future.

• Atmosphere
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• v.27 no.2
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• pp.189-197
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• 2017

Progressing from weather forecasts and warnings to multi-hazard impact-based forecast and warning services represents a paradigm shift in service delivery. Urban flooding is a typical meteorological disaster. This study proposes support plan for urban flooding impact-based forecast by providing inundation risk matrix. To achieve this goal, we first configured storm sewer management model (SWMM) to analyze 1D pipe networks and then grid based inundation analysis model (GIAM) to analyze 2D inundation depth over the Gangnam drainage area with $7.4km^2$. The accuracy of the simulated inundation results for heavy rainfall in 2010 and 2011 are 0.61 and 0.57 in POD index, respectively. 20 inundation scenarios responding on rainfall scenarios with 10~200 mm interval are produced for 60 and 120 minutes of rainfall duration. When the inundation damage thresholds are defined as pre-occurrence stage, occurrence stage to $0.01km^2$, 0.01 to $0.1km^2$, and $0.1km^2$ or more in area with a depth of 0.5 m or more, rainfall thresholds responding on each inundation damage threshold results in: 0 to 20 mm, 20 to 50 mm, 50 to 80 mm, and 80 mm or more in the rainfall duration 60 minutes and 0 to 30 mm, 30 to 70 mm, 70 to 110 mm, and 110 mm or more in the rainfall duration 120 minutes. Rainfall thresholds as a trigger of urban inundation damage can be used to form an inundation risk matrix. It is expected to be used for urban flood impact forecasting.

• Journal of the Korean Geotechnical Society
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• v.30 no.12
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• pp.5-14
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• 2014

Most of slope failures have taken place between June and September in Korea, which cause a considerable damage to society. Rainfall intensity and duration are very significant triggering factors for landslide. In this paper, landslide-triggering rainfall threshold consisting of rainfall intensity-duration (I-D) was proposed. For this study, total 255 landslides were collected in landslide inventory during 1999 to 2012 from NDMI (National Disaster Management Institute), various reports, newspapers and field survey. And most of the required rainfall data were collected from KMA (Korea Meteorological Administration). The collected landslides were classified into three categories: debris flow, shallow landslide and unconfirmed. A rainfall threshold was proposed based on landslide type using statistical method such as quantile-regression method. Its validation was carried out based on 2013 landslide database. The proposed rainfall threshold was also compared with previous rainfall thresholds. The proposed landslide-triggering rainfall thresholds could be used in landslide early warning system in Korea.

• Journal of the Korea Society of Computer and Information
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• v.29 no.9
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• pp.125-136
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• 2024

This study presents an automated Python algorithm for analyzing rainfall characteristics to establish critical rainfall thresholds as part of a landslide early warning system. Rainfall data were sourced from the Korea Meteorological Administration's Automatic Weather System (AWS) and the Korea Forest Service's Automatic Mountain Observation System (AMOS), while landslide data from 2020 to 2023 were gathered via the Life Safety Map. The algorithm involves three main steps: 1) processing rainfall data to correct inconsistencies and fill data gaps, 2) identifying the nearest observation station to each landslide location, and 3) conducting statistical analysis of rainfall characteristics. The analysis utilized power law and nonlinear regression, yielding an average R² of 0.45 for the relationships between rainfall intensity-duration, effective rainfall-duration, antecedent rainfall-duration, and maximum hourly rainfall-duration. The critical thresholds identified were 0.9-1.4 mm/hr for rainfall intensity, 68.5-132.5 mm for effective rainfall, 81.6-151.1 mm for antecedent rainfall, and 17.5-26.5 mm for maximum hourly rainfall. Validation using AUC-ROC analysis showed a low AUC value of 0.5, highlighting the limitations of using rainfall data alone to predict landslides. Additionally, the algorithm's speed performance evaluation revealed a total processing time of 30 minutes, further emphasizing the limitations of relying solely on rainfall data for disaster prediction. However, to mitigate loss of life and property damage due to disasters, it is crucial to establish criteria using quantitative and easily interpretable methods. Thus, the algorithm developed in this study is expected to contribute to reducing damage by providing a quantitative evaluation of critical rainfall thresholds that trigger landslides.

• Journal of The Korean Society of Agricultural Engineers
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• v.56 no.4
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• pp.53-58
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• 2014

The objective of this study is to suggest rainfall threshold for landslide forecasting and warning. For this study, we chose the research area where landslide have occurred. And we performed infiltration-stability analysis with rainfall intensity-duration. As the results of this study, slope stability variation chart with rainfall intensity-duration are established. This kind of chart is believed to be able to be used for forecasting and warning the landslide caused by rainfall.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.5
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• pp.791-803
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• 2016

Recently, frequency of extreme rainfall events in South Korea has been substantially increased due to the enhanced climate variability. Korea is prone to flooding due to being surrounded by mountains, along with high rainfall intensity during a short period. In the past three decades, an increase in the frequency of heavy rainfall events has been observed due to enhanced climate variability and climate change. This study aimed to analyze extreme rainfalls informed by their frequency of occurrences using a long-term rainfall data. In this respect, we developed a Poisson-Generalized Pareto Distribution (Poisson-GPD) based rainfall frequency method which allows us to simultaneously explore changes in the amount and exceedance probability of the extreme rainfall events defined by different thresholds. Additionally, this study utilized a Bayesian approach to better estimate both parameters and their uncertainties. We also investigated the synoptic patterns associated with the extreme events considered in this study. The results showed that the Poisson-GPD based design rainfalls were rather larger than those of based on the Gumbel distribution. It seems that the Poisson-GPD model offers a more reasonable explanation in the context of flood safety issue, by explicitly considering the changes in the frequency. Also, this study confirmed that low and high pressure system in the East China Sea and the central North Pacific, respectively, plays crucial roles in the development of the extreme rainfall in South Korea.

• Journal of the Korean GEO-environmental Society
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• v.17 no.12
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• pp.5-16
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• 2016

This study aims to assess the influence of rainfall patterns on shallow landslides initiation. Doing so, five typical rainfall patterns with the same cumulative amount and intensity components comprising Advanced (A1 and A2), Centralized (C), and Delayed (D1 and D2) were designed based on a historical rainstorm event in Jinbu. Mt area. Those patterns were incorporated as the hydrological conditions into the Transient Rainfall Infiltration and Grid-based Regional Slope-stability Model (TRIGRS) to assess their influences on groundwater pressure and changes in the stability of the slope. The results revealed that not only the cumulative rainfall thresholds necessary to initiate landslides, but also the rate at which the factor of safety decreases and the time required to reach the critical state, are governed by rainfall patterns. The sooner the peak rainfall intensity, the smaller the cumulative rainfall threshold, and the shorter the time until landslide occurrence. Left-skewed patterns were found to have a greater effect on landslide initiation. Specifically, among five rainfalls, pattern (A1) produced the most critical state. The severity of response was followed by patterns A2, C, D1, and D2. Our conclusion is that rainfall patterns have a significant effect on the cumulative rainfall threshold, the build-up of groundwater pressure, and the occurrence of shallow landslides.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.202-202
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• 2016

Despite the potentially major influence of rainstorm patterns on the prediction of shallow landslides, this relationship has not yet received significant attention. In this study, five typical temporal rainstorm patterns with the same cumulative amount and intensity components comprising Advanced (A1 and A2), Centralized (C), and Delayed (D1 and D2) were designed based on a historical rainstorm event occurred in 2006 in Mt. Jinbu area. The patterns were incorporated as the hydrological conditions into the Transient Rainfall Infiltration and Grid-based Regional Slope-stability Model (TRIGRS), in order to assess their influences on pore pressure variation and changes in the stability of the covering soil layer in the study area. The results revealed that not only the cumulative rainfall thresholds necessary to initiate landslides, but also the rate at which the factor of safety (FS) decreases and the time required to reach the critical state, are governed by rainstorm pattern. The sooner the peak rainfall intensity occurs, the smaller the cumulative rainfall threshold, and the shorter the time until landslide occurrence. Left-skewed rainfall patterns were found to have a greater effect on landslide initiation. More specifically, among the five different patterns, the Advanced storm pattern (A1) produced the most critical state, as it resulted in the highest pore pressure across the entire area for the shortest duration; the severity of response was then followed by patterns A2, C, D1, and D2. Thus, it can be concluded that rainfall patterns have a significant effect on the cumulative rainfall threshold, the build-up of pore pressure, and the occurrence of shallow landslides, both in space and time.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.1
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• pp.117-133
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• 2014

In this study, we analysed impacts of the recent increasing trend of exceedance rainfall thresholds for separation of data set and different research periods using Quantile Regression (QR) approach. And also we performed significant test for time series data using linear regression, Mann-Kendall test and Sen test over the Korean major 8-city. Spring and summer precipitation was tend to significant increase, fall and winter precipitation was tend to decrease, and heavy rainy days in last 30 years have increased from 3.1 to 15 percent average. In addition, according to the annual ranking of rainfall occurs Top $10^{th}$ percentile of precipitation for 3IQR (inter quartile range) of the increasing trend, most of the precipitation at the point of increasing trend was confirmed. Quantile 90% percentile of the average rainfall 43.5mm, the increasing trend 0.1412mm/yr, Quantile 99% percentile of the average rainfall 68.0mm, the increasing trend in the 0.1314mm/yr were analyzed. The results can be used to analyze the recent increasing trend for the annual maximum value series information and the threshold extreme hydrologic information. And also can be used as a basis data for hydraulic structures design on reflect recent changes in climate characteristics.