scholarly journals Integrating spatial and temporal probabilities for the annual landslide hazard maps in Shihmen watershed, Taiwan

2013 ◽  
Vol 1 (2) ◽  
pp. 471-508
Author(s):  
C. Y. Wu ◽  
S. C. Chen
Keyword(s):  
Landslide Hazard ◽  
Exceedance Probability ◽  
Cumulative Probability ◽  
Landslide Area ◽  
Related Factors ◽  
Screening Process ◽  
Spatial Probability ◽  
Annual Probability ◽  
Recurrence Intervals ◽  
Landslide Distribution

Abstract. Landslide spatial probability, temporal probability, and landslide size probability were employed to perform landslide hazard assessment in this study. Following a screening process, landslide susceptibility-related factors included eleven intrinsic geomorphological factors and two extrinsic rainfall factors, which were evaluated as effective factors because of the higher correlation with the landslide distribution. Landslide area analysis was first employed to establish the power law relationship between landslide area and noncumulative number, and a probability density function was then used to convert this relationship to cumulative probability of landslide area. The exceedance probability of rainfall with different recurrence intervals was used to determine the temporal probability of those events. Finally, the landslide spatial probability, landslide area probability, and exceedance probability were integrated to estimate the annual probability of each slope-unit with a landslide area exceeding a certain threshold in a watershed. The slope-units with high landslide probability were concentrated in Taigang River watershed, which should be the leading target of future management efforts.

scholarly journals Integrating spatial, temporal, and size probabilities for the annual landslide hazard maps in the Shihmen watershed, Taiwan

2013 ◽  
Vol 13 (9) ◽  
pp. 2353-2367 ◽  
Author(s):  
C. Y. Wu ◽  
S. C. Chen
Keyword(s):  
Probability Model ◽  
Landslide Hazard ◽  
Landslide Risk ◽  
Landslide Area ◽  
Related Factors ◽  
Frequency Distributions ◽  
Annual Probability ◽  
Pearson Type ◽  
Susceptibility Model ◽  
Recurrence Intervals

Abstract. Landslide spatial, temporal, and size probabilities were used to perform a landslide hazard assessment in this study. Eleven intrinsic geomorphological, and two extrinsic rainfall factors were evaluated as landslide susceptibility related factors as they related to the success rate curves, landslide ratio plots, frequency distributions of landslide and non-landslide groups, as well as probability–probability plots. Data on landslides caused by Typhoon Aere in the Shihmen watershed were selected to train the susceptibility model. The landslide area probability, based on the power law relationship between the landslide area and a noncumulative number, was analyzed using the Pearson type 5 probability density function. The exceedance probabilities of rainfall with various recurrence intervals, including 2, 5, 10, 20, 50, 100 and 200 yr, were used to determine the temporal probabilities of the events. The study was conducted in the Shihmen watershed, which has an area of 760 km2 and is one of the main water sources for northern Taiwan. The validation result of Typhoon Krosa demonstrated that this landslide hazard model could be used to predict the landslide probabilities. The results suggested that integration of spatial, area, and exceedance probabilities to estimate the annual probability of each slope unit is feasible. The advantage of this annual landslide probability model lies in its ability to estimate the annual landslide risk, instead of a scenario-based risk.

Public policy towards catastrophe

2008 ◽  
Author(s):  
Richard A. Posner
Keyword(s):  
Global Warming ◽  
New Orleans ◽  
Late Summer ◽  
Indian Ocean Tsunami ◽  
Cumulative Probability ◽  
Catastrophic Risk ◽  
Death Toll ◽  
Emotional Suffering ◽  
Unknown Probability ◽  
Annual Probability

The Indian Ocean tsunami of December 2004 focused attention on a type of disaster to which policymakers pay too little attention – a disaster that has a very low or unknown probability of occurring, but that if it does occur creates enormous losses. The flooding of New Orleans in the late summer of 2005 was a comparable event, although the probability of the event was known to be high; the Corps of Engineers estimated its annual probability as 0.33% (Schleifstein and McQuaid, 2002), which implies a cumulative probability of almost 10% over a thirty-year span. The particular significance of the New Orleans flood for catastrophic-risk analysis lies in showing that an event can inflict enormous loss even if the death toll is small – approximately 1/250 of the death toll from the tsunami. Great as that toll was, together with the physical and emotional suffering of survivors, and property damage, even greater losses could be inflicted by other disasters of low (but not negligible) or unknown probability. The asteroid that exploded above Siberia in 1908 with the force of a hydrogen bomb might have killed millions of people had it exploded above a major city. Yet that asteroid was only about 200 feet in diameter, and a much larger one (among the thousands of dangerously large asteroids in orbits that intersect the earth’s orbit) could strike the earth and cause the total extinction of the human race through a combination of shock waves, fire, tsunamis, and blockage of sunlight, wherever it struck. Another catastrophic risk is that of abrupt global warming, discussed later in this chapter. Oddly, with the exception of global warming (and hence the New Orleans flood, to which global warming may have contributed, along with manmade destruction of wetlands and barrier islands that formerly provided some protection for New Orleans against hurricane winds), none of the catastrophes mentioned above, including the tsunami, is generally considered an ‘environmental’ catastrophe. This is odd, since, for example, abrupt catastrophic global change would be a likely consequence of a major asteroid strike.

scholarly journals Statistical dynamics of regional populations and economies

2017 ◽  
Vol 28 (12) ◽  
pp. 1750150 ◽  
Author(s):  
Jie Huo ◽  
Xu-Ming Wang ◽  
Rui Hao ◽  
Peng Wang
Keyword(s):  
Power Law ◽  
Gaussian Distribution ◽  
Population Distribution ◽  
Hot Spot ◽  
Interdisciplinary Studies ◽  
Cumulative Probability ◽  
Generalized Langevin Equation ◽  
Surprising Result ◽  
Related Factors ◽  
Practical Result

Quantitative analysis of human behavior and social development is becoming a hot spot of some interdisciplinary studies. A statistical analysis on the population and GDP of 150 cities in China from 1990 to 2013 is conducted. The result indicates the cumulative probability distribution of the populations and that of the GDPs obeying the shifted power law, respectively. In order to understand these characteristics, a generalized Langevin equation describing variation of population is proposed, which is based on the correlations between population and GDP as well as the random fluctuations of the related factors. The equation is transformed into the Fokker–Plank equation to express the evolution of population distribution. The general solution demonstrates a transition of the distribution from the normal Gaussian distribution to a shifted power law, which suggests a critical point of time at which the transition takes place. The shifted power law distribution in the supercritical situation is qualitatively in accordance with the practical result. The distribution of the GDPs is derived from the well-known Cobb–Douglas production function. The result presents a change, in supercritical situation, from a shifted power law to the Gaussian distribution. This is a surprising result–the regional GDP distribution of our world will be the Gaussian distribution one day in the future. The discussions based on the changing trend of economic growth suggest it will be true. Therefore, these theoretical attempts may draw a historical picture of our society in the aspects of population and economy.

scholarly journals Prediction of the area affected by earthquake-induced landsliding based on seismological parameters

2017 ◽  
Vol 17 (7) ◽  
pp. 1159-1175 ◽  
Author(s):  
Odin Marc ◽  
Patrick Meunier ◽  
Niels Hovius
Keyword(s):  
Scaling Laws ◽  
Seismic Energy ◽  
Seismic Source ◽  
Distribution Area ◽  
Rupture Directivity ◽  
Source Depth ◽  
Landslide Area ◽  
Earthquake Parameters ◽  
Ground Shaking ◽  
Landslide Distribution

Abstract. We present an analytical, seismologically consistent expression for the surface area of the region within which most landslides triggered by an earthquake are located (landslide distribution area). This expression is based on scaling laws relating seismic moment, source depth, and focal mechanism with ground shaking and fault rupture length and assumes a globally constant threshold of acceleration for onset of systematic mass wasting. The seismological assumptions are identical to those recently used to propose a seismologically consistent expression for the total volume and area of landslides triggered by an earthquake. To test the accuracy of the model we gathered geophysical information and estimates of the landslide distribution area for 83 earthquakes. To reduce uncertainties and inconsistencies in the estimation of the landslide distribution area, we propose an objective definition based on the shortest distance from the seismic wave emission line containing 95 % of the total landslide area. Without any empirical calibration the model explains 56 % of the variance in our dataset, and predicts 35 to 49 out of 83 cases within a factor of 2, depending on how we account for uncertainties on the seismic source depth. For most cases with comprehensive landslide inventories we show that our prediction compares well with the smallest region around the fault containing 95 % of the total landslide area. Aspects ignored by the model that could explain the residuals include local variations of the threshold of acceleration and processes modulating the surface ground shaking, such as the distribution of seismic energy release on the fault plane, the dynamic stress drop, and rupture directivity. Nevertheless, its simplicity and first-order accuracy suggest that the model can yield plausible and useful estimates of the landslide distribution area in near-real time, with earthquake parameters issued by standard detection routines.

scholarly journals Prediction of the area affected by earthquake-induced landsliding based on seismological parameters

2017 ◽  
Author(s):  
Odin Marc ◽  
Patrick Meunier ◽  
Niels Hovius
Keyword(s):  
Scaling Laws ◽  
Distribution Area ◽  
Rupture Directivity ◽  
Source Depth ◽  
Landslide Area ◽  
Earthquake Parameters ◽  
Critical Acceleration ◽  
Ground Shaking ◽  
Landslide Volume ◽  
Landslide Distribution

Abstract. We present an analytical, seismologically consistent expression for the surface area of the region within which landslides induced by a given earthquake are distributed. The expression is based on scaling laws relating seismic moment, source depth and focal mechanism with ground shaking and fault rupture length and assumes a globally constant critical acceleration for onset of systematic mass wasting. The seismological assumptions are identical to those recently used to propose a seismologically consistent expression for total landslide volume and area. To test the accuracy of the model we gathered geophysical information and estimates of the landslide distribution area for 83 earthquakes. To reduce uncertainties and inconsistencies in the estimation of the landslide distribution area, we propose an objective definition based on the shortest distance from the seimsic wave emission line containing 95 % of the total landslide area. Without any empirical calibration the model explains 56 % of the variance in our dataset, and predicts 35 to 49 out of 83 cases within a factor two, depending on how we account for uncertainties on the seismic source depth. For most cases with comprehensive landslide inventories we show that our prediction compares well with the smallest region around the fault containing 95 % of the total landslide area. Aspects ignored by the model that could explain the residuals include, local variations of the critical acceleration and processes modulating the surface ground shaking, such as the distribution of seismic energy release on the fault plane, the dynamic stress drop or the rupture directivity. Nevertheless, its simplicity and first order accuracy suggest that the model can yield plausible and useful estimates of the landslide distribution area in near-real time, with earthquake parameters issued by standard detection routines.

scholarly journals Preliminary Forecasting of Rainfall-Induced Shallow Landslides in the Wildfire Burned Areas of Western Greece

Land ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 877
Author(s):  
Spyridon Lainas ◽  
Nikolaos Depountis ◽  
Nikolaos Sabatakakis
Keyword(s):  
Daily Rainfall ◽  
Rainfall Threshold ◽  
Shallow Landslide ◽  
Exceedance Probability ◽  
Landscape Characteristics ◽  
Burned Areas ◽  
Annual Probability ◽  
Geological Conditions ◽  
Landslide Forecasting ◽  
Western Greece

A new methodology for shallow landslide forecasting in wildfire burned areas is proposed by estimating the annual probability of rainfall threshold exceedance. For this purpose, extensive geological fieldwork was carried out in 122 landslides, which have been periodically activated in Western Greece, after the devastating wildfires that occurred in August 2007 and burned large areas in several parts of Western Greece. In addition, daily rainfall data covering more than 40 years has been collected and statistically processed to estimate the exceedance probability of the rainfall threshold above which these landslides are activated. The objectives of this study are to quantify the magnitude and duration of rainfall above which landslides in burned areas are activated, as well as to introduce a novel methodology on rainfall-induced landslide forecasting. It has been concluded that rainfall-induced landslide annual exceedance probability in the burned areas is higher when cumulative rainfall duration ranges from 6 to 9 days with local differences due to the prevailing geological conditions and landscape characteristics. The proposed methodology can be used as a basis for landslide forecasting in wildfire-affected areas, especially when triggered by rainfall, and can be further developed as a tool for preliminary landslide hazard assessment.

scholarly journals Applying logistic regression method to determine combinatorial optimization of landslide-related factors and construct landslide hazard map in Khanh Vinh district, Khanh Hoa Province

2017 ◽  
Vol 20 (K4) ◽  
pp. 76-83
Author(s):  
Danh Thanh Nguyen ◽  
Ngo Van Dau ◽  
Dung Quoc Ta
Keyword(s):  
Logistic Regression ◽  
Combinatorial Optimization ◽  
Regression Method ◽  
Landslide Hazard ◽  
Optimization Models ◽  
Hazard Map ◽  
Related Factors ◽  
Maximum Precipitation ◽  
Logistic Regression Method ◽  
Landslide Hazard Map

The purpose of this study is to produce landslide hazard map in Khanh Vinh district, Khanh Hoa province using logistic regression method integrated with GIS analytical tools. The spatial relationship between landslide-related factors such as topography; lithology; vegetation; maximum precipitation in year; distance from roads; distance from drainages; distance from faults and the distribution of landslides were used in the landslide hazard analyses. Using success rate and prediction rate curve assess the fit and accuracy of logistic regression method. The results show that this method have the goodness of fit and the high accuracy (Areas Under Curves - AUC = 0.8 ~ 0.9). Bayesian Model Average (BMA) of the R statistical software was applied to identify the most influential factors and the combinatorial optimization models of landslide-related factors. There are four the most important landslide-related factors and five combinatorial optimization models of landslide-related factors. Model 3 (slope angle, slope aspect, altitude, distance from roads and maximum precipitation in year) is the best optimization.

Pick up pattern from logic fuzzy in mathematics for zonation of ‎landslide hazard

2017 ◽  
Vol 7 (1) ◽  
pp. 5-8
Author(s):  
Rahman Sharifi
Keyword(s):  
Fuzzy Logic ◽  
Watershed Management ◽  
High Sensitivity ◽  
Landslide Hazard ◽  
Class Numbers ◽  
Hazard Zonation ◽  
Landslide Hazard Zonation ◽  
Landslide Area ◽  
Average Sensitivity ◽  
Low Sensitivity

First landslide hazard zonation provided based on Fuzzy logic by landslide area laid on the Slope map, ‎Geology( lithology) map, Aspect map. Then, these maps classes of priority and coming next determine based ‎on existing landslides area in the geology, slope, and aspect of maps. In the geology map of tuff, shale, and ‎conglomerate rocks, about with hectare 1440.43(about percent 23.94 ) and shelly limestone ‎‎ about with hectare ‎‎0.88 (about percent 0.01 ) and in the slope map, X>45 classes about with hectare 2794 ( about percent 46.44 ) ‎and 15-25 classes about with hectare 737 ( about percent 12.25) and in the aspect map, East classes with about ‎hectare 1882 ( about percent 31.28 ) and west classes with hectare 579 ( about percent 9.62 ) sequential have ‎most and least landslide area. Then, in the final drawer to dimension centimeters 2 in region watershed ‎management of map and we counted from 0 until 863 based on geology, slope and aspect that exist the only unit ‎‎624 counted from 0 until 623. Then (y) units settled sequential, numbers 0 to 105 in very low sensitivity class ‎‎(one class), numbers 106 to 207 in low sensitivity class (two class), numbers 208 to 345 in average sensitivity ‎class (three class), numbers 346 to 498 in high sensitivity class (four class) and numbers 499 to 623. then ‎landslide hazard zonation provided a base on Fuzzy logic.‎

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