scholarly journals Multiseasonal probabilistic slope stability analysis of a large area of unsaturated pyroclastic soils

Landslides ◽  
2020 ◽  
Author(s):  
Sabatino Cuomo ◽  
Elena Benedetta Masi ◽  
Veronica Tofani ◽  
Mariagiovanna Moscariello ◽  
Guglielmo Rossi ◽  
...  
Keyword(s):  
Slope Stability ◽  
Failure Probability ◽  
Rainfall Data ◽  
Slope Instability ◽  
Time Range ◽  
Large Area ◽  
Seepage Analysis ◽  
Infinite Slope Stability Model ◽  
Hourly Rainfall

Abstract The analysis of slope stability over large areas is a demanding task for several reasons, such as the need for extensive datasets, the uncertainty of collected data, the difficulty of accounting for site-specific factors, and the considerable computation time required due to the size of investigated areas, which can pose major barriers, particularly in civil protection contexts where rapid analysis and forecasts are essential. However, as the identification of zones of higher failure probability is very useful for stakeholders and decision-makers, the scientific community has attempted to improve capabilities to provide physically based assessments. This study combined a transient seepage analysis of an unsaturated-saturated condition with an infinite slope stability model and probabilistic analysis through the use of a high-computing capacity parallelized platform. Both short- and long-term analyses were performed for a study area, and roles of evapotranspiration, vegetation interception, and the root increment of soil strength were considered. A model was first calibrated based on hourly rainfall data recorded over a 4-day event (December 14–17, 1999) causing destructive landslides to compare the results of model simulations to actual landslide events. Then, the calibrated model was applied for a long-term simulation where daily rainfall data recorded over a 4-year period (January 1, 2005–December 31, 2008) were considered to study the behavior of the area in response to a long period of rainfall. The calibration shows that the model can correctly identify higher failure probability within the time range of the observed landslides as well as the extents and locations of zones computed as the most prone ones. The long-term analysis allowed for the identification of a number of days (9) when the slope factor of safety was lower than 1.2 over a significant number of cells. In all of these cases, zones approaching slope instability were concentrated in specific sectors and catchments of the study area. In addition, some subbasins were found to be the most recurrently prone to possible slope instability. Interestingly, the application of the adopted methodology provided clear indications of both weekly and seasonal fluctuations of overall slope stability conditions. Limitations of the present study and future developments are finally discussed.

Short and long term probabilistic slope stability analyses of a large area of unsaturated pyroclastic soils

2021 ◽  
Author(s):  
Veronica Tofani ◽  
Sabatino Cuomo ◽  
Elena Benedetta Masi ◽  
Mariagiovanna Moscariello ◽  
Guglielmo Rossi ◽  
...  
Keyword(s):  
Slope Stability ◽  
Failure Probability ◽  
Rainfall Data ◽  
Slope Instability ◽  
Time Range ◽  
Large Area ◽  
Infinite Slope Stability Model ◽  
Hourly Rainfall ◽  
Short And Long Term

<p>The analysis of slope stability over large areas is a demanding task for several reasons, such as the need for extensive datasets, the uncertainty of collected data, the difficulty of accounting for site-specific factors, and the considerable computation time required due to the size of investigated areas, which can pose major barriers, particularly in civil protection contexts where rapid analysis and forecasts are essential. However, as the identification of zones of higher failure probability is very useful for stakeholders and decision-makers, the scientific community has attempted to improve capabilities to provide physically based assessments. This study combined a transient seepage analysis of an unsaturated-saturated condition with an infinite slope stability model and probabilistic analysis through the use of a high-computing capacity parallelized platform. Both short- and long-term analyses were performed for a study area, and roles of evapotranspiration, vegetation interception, and the root increment of soil strength were considered. A model was first calibrated based on hourly rainfall data recorded over a 4-day event (December 14–17, 1999) causing destructive landslides to compare the results of model simulations to actual landslide events. Then, the calibrated model was applied for a long-term simulation where daily rainfall data recorded over a 4-year period (January 1, 2005–December 31, 2008) were considered to study the behavior of the area in response to a long period of rainfall. The calibration shows that the model can correctly identify higher failure probability within the time range of the observed landslides as well as the extents and locations of zones computed as the most prone ones. The long-term analysis allowed for the identification of a number of days when the slope factor of safety was lower than 1.2 over a significant number of cells. In all of these cases, zones approaching slope instability were concentrated in specific sectors and catchments of the study area. In addition, some subbasins were found to be the most recurrently prone to possible slope instability. Interestingly, the application of the adopted methodology provided clear indications of both weekly and seasonal fluctuations of overall slope stability conditions.</p>

Study on Slope Instability Disciplinarian on the Condition of Rainfall

2013 ◽  
Vol 353-356 ◽  
pp. 654-658
Author(s):  
Nan Tong Zhang ◽  
Xiao Chun Zhang ◽  
Hua Rong Wang ◽  
Chen Yan
Keyword(s):  
Slope Stability ◽  
Tensile Stress ◽  
Rainfall Intensity ◽  
Pore Water Pressure ◽  
Water Pressure ◽  
Road Construction ◽  
Slope Instability ◽  
Slope Surface ◽  
Large Area ◽  
Break Zone

Slope stability is one of the problems of road construction which should be faced with and solve. Rainfall can reduce the shear strength of slope soil and raise the underground water level which can lead to increase slope soil pore water pressure. The influence of rainfall infiltration on slop is mainly to change the slope seepage field, increase dynamic and hydrostatic water load on the slope soil and decrease of soil shear parameters. More abundant rainfall of typhoon area could make the road slope stability more fragile. Based on Matoushan Mountain along 104 state roads in Taizhou city, Zhejiang province, slope instability disciplinarian on the condition of rainfall is studied using the method of numerical simulation in this paper. As the results, when the rainfall intensity was 0.006 m/h and continuous rain was in 24 hours, the slope surface compressive stress tends to zero which began to appear tensile stress area on the condition of self-weight. And when the rainfall intensity was 0.01 m/h and continuous rain was in 24 hours, the large area of the slope surface was tensile stress area which means to appear break zone in slope surface and likely to landslide at the same time.

scholarly journals Cascade Rainfall Disaggregation Application in U.S. Central Plains

2017 ◽  
Vol 7 (4) ◽  
pp. 30 ◽  
Author(s):  
Jurgen D. Garbrecht ◽  
Rabi Gyawali ◽  
Robert W. Malone ◽  
John C. Zhang
Keyword(s):  
Time Series ◽  
Model Performance ◽  
Daily Rainfall ◽  
Rainfall Data ◽  
Rainfall Time Series ◽  
Random Component ◽  
Rainfall Characteristics ◽  
Hourly Rainfall ◽  
Replicated Observations

Long-term observations of daily rainfall are common and routinely available for a variety of hydrologic applications. In contrast, observations of 10 or more years of continuous hourly rainfall are rare. Yet, sub-daily rainfall data are required in rainfall-runoff models. Rainfall disaggregation can generate sub-daily time-series from available long term daily observations. Herein, the performance of Multiplicative Random Cascade (MRC) model at disaggregating daily-to-hourly rainfall was investigated. The MRC model was parameterized and validated with 15 years of continuous observed daily and hourly rainfall data at three weather stations in Oklahoma. Model performance, or degree to which the disaggregated rainfall time series replicated observations, was assessed using 46 variables of hourly rainfall characteristics, such as longest wet spell duration, average number of rainfall hours per year, and largest hourly rainfall. Findings include: a) average-type hourly rainfall characteristics were better replicated than single value characteristics such as longest, maximum, or peak hourly rainfall; b) the large number of sub-trace hourly rainfall values (<0.254 mm h-1) generated by the MRC model were not supported by observations; c) the random component of the MRC model led to a variation under 15% of the average value for most rainfall characteristics with the exceptions of the “longest wet spell duration” and “maximum hourly rainfall”; and d) the MRC model produced fewer persistent rainfall events compared to those in the observed rainfall record. The large number of generated trace rainfall values and difficulties to replicate reliably extreme rainfall characteristics, reduces the number of potential hydrologic applications that could take advantage of the MRC disaggregated hourly rainfall. Nevertheless, in most cases, the disaggregated rainfall generated by the MRC model replicated observed average-type rainfall characteristics well.

scholarly journals Can we get more out of rainfall thresholds? The temporal resolution tradeoff and the role of antecedent wetness and rainfall spatial variability

2020 ◽  
Author(s):  
Elena Leonarduzzi ◽  
Peter Molnar
Keyword(s):  
Temporal Resolution ◽  
Daily Rainfall ◽  
Rainfall Event ◽  
Rainfall Data ◽  
Antecedent Rainfall ◽  
Rainfall Thresholds ◽  
Total Rainfall ◽  
Hourly Rainfall ◽  
Landslide Triggering

&lt;p&gt;Rainfall event properties like maximum intensity, total rainfall depth, or their representation in the form of intensity-duration (ID) or total rainfall-duration (ED) curves, are commonly used to determine the triggering rainfall (event) conditions required for landslide initiation. This rainfall data-driven prediction of landsliding can be extended by the inclusion of antecedent wetness conditions. Although useful for first order assessment of landslide triggering conditions in warning systems, this approach relies heavily on data quality and temporal resolution, which may affect the overall predictive model performance as well as its reliability.&lt;/p&gt;&lt;p&gt;In this work, we address three key aspects of rainfall thresholds when applied at large spatial scales: (a) the tradeoffs between higher and lower temporal resolution (hourly or daily) (b) the spatial variability associated with long term rainfall, and (c) the added value of antecedent rainfall as predictor. We explore all of these by utilizing a long-term landslide inventory, containing more than 2500 records in Switzerland and 3 gridded rainfall records: a long daily rainfall dataset and two derived hourly products, disaggregated using stations or radar hourly measurements.&lt;/p&gt;&lt;p&gt;We observe that while predictive performances improve slightly when utilizing high quality hourly record (using radar information), the length of the record decreases, as well as the number of landslides in the inventory, which affects the reliability of the thresholds. A tradeoff has to be found between using long records of less accurate daily rainfall data and landslide timing, and shorter records with highly accurate hourly rainfall data and landslide timing. Even daily rainfall data may give reasonable predictive performance if thresholds are estimated with a long landslide inventory. Good quality hourly rainfall data significantly improve performance, but historical records tend to be shorter or less accurate (e.g. fewer stations available) and landslides with known timing are fewer. Considering antecedent rainfall, we observe that it is generally higher prior to landslide-triggering events and this can partially explain the false alarms and misses of an intensity-duration threshold. Nevertheless, in our study antecedent rainfall shows less predictive power by itself than the rainfall event characteristics. Finally, we show that we can improve the performances of the rainfall thresholds by accounting for local climatology in which we define new thresholds by normalizing the event characteristics with a chosen quantile of the local rainfall distribution or using the mean annual precipitation.&lt;/p&gt;

Movement of Large Convective Rainstorms in Relation to Winds Aloft

1958 ◽  
Vol 39 (3) ◽  
pp. 129-136 ◽  
Author(s):  
C. W. Newton ◽  
Sey Katz
Keyword(s):  
Wind Speed ◽  
Wind Direction ◽  
Rainfall Data ◽  
Squall Lines ◽  
Hourly Rainfall ◽  
The Difference ◽  
Strong Winds

By means of hourly rainfall data from the Hydroclimatic Network, the motions of large rainstorms, of the kind associated with squall lines, are examined in relation to the winds aloft. Very little correlation is found between the speed of movement of the rainstorms and the wind speed at any level, although the fastest moving storms were associated with strong winds aloft. Significant correlation is found between direction of motion of rainstorms, and wind direction at 700 mb or higher levels. On the average, the rainstorms move with an appreciable component toward right of the wind direction. The difference between these results, and those from other studies based on small precipitation areas, is ascribed to propagation. The mechanism involved is discussed briefly.

Surface Cleaning Challenges for Organic Light Emitting Diodes

2021 ◽  
Vol 314 ◽  
pp. 3-8
Author(s):  
Noel Giebink
Keyword(s):  
Light Emitting Diodes ◽  
Surface Cleaning ◽  
Organic Light Emitting Diodes ◽  
Large Area ◽  
Light Emitting ◽  
Organic Light ◽  
Organic Optoelectronic Devices ◽  
Soft Thin Film ◽  
Organic Optoelectronic

Organic optoelectronic devices such as light-emitting diodes and solar cells present unique challenges for surface cleaning and preparation because of their large area and the ‘soft’, thin film nature of the materials involved. This paper gives an introduction to this class of semiconductor devices and covers a recent example of how surface cleaning impacts the long-term reliability of organic light-emitting diodes being commercialized for solid-state lighting.

scholarly journals Snow Avalanches and Acoustic Emissions

1983 ◽  
Vol 4 ◽  
pp. 271-276 ◽  
Author(s):  
R. A. Sommerfeld ◽  
H. Gubler
Keyword(s):  
Acoustic Emissions ◽  
Limited Range ◽  
Slope Instability ◽  
Type I ◽  
Type Ii ◽  
Noise Levels ◽  
Active Layers ◽  
Differential Movement ◽  
Emission Activity

Analyses of several years of data show that acoustic emission activity is greater from unstable snowpacks than from stable snowpacks. Two types of signals have been identified: type I spikes and type II long-term elevation of the noise level. It is thought that the type I signals originate from macroscopic cracks. The type II signals may originate from differential movement on shearing surfaces, but this is less certain. Increased noise levels of both types correlate well with slope instability, when the slope stability is known. In some climates the limited range of signal detection might be a significant problem. A foam-mounted geophone set into the snow near active layers appears to be the best sensor available at present.

scholarly journals The contribution of chestnut coppice forests on slope stability in abandoned territory: a case study

2013 ◽  
Vol 44 (2s) ◽  
Author(s):  
Chiara Bassanelli ◽  
Gian Battista Bischetti ◽  
Enrico Antonio Chiaradia ◽  
Lorenzo Rossi ◽  
Chiara Vergani
Keyword(s):  
Slope Stability ◽  
Root Diameter ◽  
Slope Instability ◽  
Economic Changes ◽  
Sweet Chestnut ◽  
Forestry Practices ◽  
Short Rotation ◽  
Root Cohesion ◽  
Chestnut Coppice ◽  
High Level

Sweet chestnut has been for many centuries fundamental for the Italian mountainous economies, where this kind of forest was traditionally managed in short rotation to rapidly produce wood biomass. Due to the social and economic changes, which made such management scheme unprofitable especially on the steep and remote slopes, such practice has been mainly abandoned and most of chestnut forests became over-aged and very dense, causing an increase of localized slope instability. In this work the effect of over-aged chestnut coppice forests on shallow landslides was analysed by evaluating and comparing mechanical contribution to soil shear strength provided by root systems in differently managed chestnut stands. The study area is located in Valcuvia (Lombardy Prealps) where three different stands, one managed and the others abandoned (over 40 year aged), established on cohesionless slopes (quaternary moraine deposits) were chosen having care to select homogeneous conditions in terms of substrate, aspect and elevation. As slope steepness strongly affects forestry practices and steeper stands are more frequently abandoned, the considered stands have different terrain inclination, 30-35° in abandoned stands and 13° in the managed one. Slope stability of the three sites was evaluated by applying the infinite slope approach accounting for additional root cohesion and tree surcharge. Additional root cohesion was estimated through the Fiber Boundle Model approach by collecting roots in the field and measuring their resistance in laboratory, and by measuring root diameter and density distribution with depth by the wall technique method. The results, as expected, showed that over-aging does not affect root mechanical properties, whereas it significantly affects root distribution within the soil. In terms of slope stability, when steepness exceeds 35°, instability phenomena can be triggered by high level of soil saturation in the case of over-aged forests, whereas for less extreme cases chestnut forests, although over-aged, are able and fundamental to guarantee safe conditions.

scholarly journals Hydrological model calibration for derived flood frequency analysis using stochastic rainfall and probability distributions of peak flows

2014 ◽  
Vol 18 (1) ◽  
pp. 353-365 ◽  
Author(s):  
U. Haberlandt ◽  
I. Radtke
Keyword(s):  
Time Series ◽  
Frequency Analysis ◽  
Model Calibration ◽  
Hydrological Model ◽  
Probability Distributions ◽  
Flood Frequency ◽  
Rainfall Data ◽  
Flood Frequency Analysis ◽  
Peak Flows ◽  
Hourly Rainfall

Abstract. Derived flood frequency analysis allows the estimation of design floods with hydrological modeling for poorly observed basins considering change and taking into account flood protection measures. There are several possible choices regarding precipitation input, discharge output and consequently the calibration of the model. The objective of this study is to compare different calibration strategies for a hydrological model considering various types of rainfall input and runoff output data sets and to propose the most suitable approach. Event based and continuous, observed hourly rainfall data as well as disaggregated daily rainfall and stochastically generated hourly rainfall data are used as input for the model. As output, short hourly and longer daily continuous flow time series as well as probability distributions of annual maximum peak flow series are employed. The performance of the strategies is evaluated using the obtained different model parameter sets for continuous simulation of discharge in an independent validation period and by comparing the model derived flood frequency distributions with the observed one. The investigations are carried out for three mesoscale catchments in northern Germany with the hydrological model HEC-HMS (Hydrologic Engineering Center's Hydrologic Modeling System). The results show that (I) the same type of precipitation input data should be used for calibration and application of the hydrological model, (II) a model calibrated using a small sample of extreme values works quite well for the simulation of continuous time series with moderate length but not vice versa, and (III) the best performance with small uncertainty is obtained when stochastic precipitation data and the observed probability distribution of peak flows are used for model calibration. This outcome suggests to calibrate a hydrological model directly on probability distributions of observed peak flows using stochastic rainfall as input if its purpose is the application for derived flood frequency analysis.

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