Physical mechanics of aufeis growth

1981 ◽  
Vol 8 (2) ◽  
pp. 186-195 ◽  
Author(s):  
Douglas L. Kane
Keyword(s):  
Time Series ◽  
Pore Water ◽  
Pore Water Pressure ◽  
Water Pressure ◽  
Time Lag ◽  
Field Measurements ◽  
Warming Trend ◽  
Braided Rivers ◽  
Time Series Analyses ◽  
Made In

All arctic travelers have encountered streams and braided rivers swollen with ice during the winter months. Numerous field measurements were made in an attempt to develop an understanding of the mechanics of aufeis growth. Piezometers were installed at several sites in central Alaska to measure the pressure variations of the fluid in the porous streambank. Time series analyses were utilized for correlating the variations in the observed pore pressures with climatic variables. It was concluded from the piezometer measurements of pore water pressure that subpermafrost groundwater or groundwater from nonpermafrost regions was the source of water for these ice deposits. Water from the active layer did not contribute to these accumulations of ice. Time series analysis revealed that pore water pressures started to increase following warming trends. A time lag existed between the start of a warming trend and the corresponding changes in pore water pressure; this time lag increased as the thickness of ice increased.

Infiltration characteristics of two instrumented residual soil slopes

2003 ◽  
Vol 40 (5) ◽  
pp. 1012-1032 ◽  
Author(s):  
Illias Tsaparas ◽  
Harianto Rahardjo ◽  
David G Toll ◽  
Eng-Choon Leong
Keyword(s):  
Pore Water ◽  
Pore Water Pressure ◽  
Water Pressure ◽  
Field Measurements ◽  
Residual Soil ◽  
Rainfall Runoff ◽  
Rainfall Events ◽  
Pore Water Pressures ◽  
Soil Slopes ◽  
Pressure Changes

This paper presents the analysis of a 12 month long field study of the infiltration characteristics of two residual soil slopes in Singapore. The field measurements consist of rainfall data, runoff data of natural and simulated rainfall events, and pore-water pressure changes during infiltration at several depths and at several locations on the two slopes. The analysis of the field measurements identifies the total rainfall and the initial pore-water pressures within the two slopes as the controlling parameters for the changes in the pore-water pressures within the slopes during infiltration.Key words: infiltration, rainfall, runoff, pore-water pressure, field measurements.

Field measurement of anchor forces, ground temperatures, and pore-water pressures behind a retaining structure in northwestern Ontario

1992 ◽  
Vol 29 (1) ◽  
pp. 112-116
Author(s):  
K. D. Eigenbrod ◽  
J. P. Burak
Keyword(s):  
Pore Water ◽  
Pore Water Pressure ◽  
Water Pressure ◽  
Retaining Wall ◽  
Field Measurements ◽  
Strain Gauges ◽  
Ground Temperatures ◽  
Northwestern Ontario ◽  
Pore Water Pressures ◽  
Load Increase

Anchor forces, ground temperatures, and piezometric pressures were measured at a retaining wall in northwestern Ontario over a period of 2 years. The anchor forces were measured with strain gauges attached in pairs directly to the anchor rods. This method appeared practical in the field for time periods of less than 2 years as long as the strain gauges were carefully protected against moisture. The anchor forces increased from an average of 5 kN initially up to values of 50 kN during the winter periods and dropped during the summer periods back to the same values measured initially. The anchor forces were largely independent of pore-water pressure variations behind the wall. Rapid drawdown conditions, however, which were experienced during the second summer, were reflected in a load increase that was equivalent to the associated unloading effect in front of the wall. The pore-water pressures behind the wall were not noticeably affected by rapid drawdown, possibly due to the restraining effect of the anchors and the high rigidity of the low sheet pile wall. Ground temperatures at or below the groundwater table never dropped below 0 °C thus restricting the depth of frost penetration. Key words : anchor loads, freezing pressure, retaining walls, pore-water pressures, ground temperatures, field measurements.

When image correlation is needed: combining very dense radar-amplitude and optical times series for unravelling the complex dynamics of a not so slow slow-moving landslide in the tropics

2021 ◽  
Author(s):  
Antoine Dille ◽  
François Kervyn ◽  
Alexander Handwerger ◽  
Nicolas d’Oreye ◽  
Dominique Derauw ◽  
...  
Keyword(s):  
Time Series ◽  
Pore Water ◽  
Pore Water Pressure ◽  
Water Pressure ◽  
Image Correlation ◽  
Optical Data ◽  
Uniform Motion ◽  
Pixel Image ◽  
Slow Moving ◽  
Landslide Kinematics

<p>Slow-moving landslides exhibit persistent but non-uniform motion at low rates which makes them exceptional natural laboratories to study the mechanisms that control the dynamics of unstable hillslopes. Here we leverage 4.5+ years of satellite-based radar and optical remote sensing data to quantify the kinematics of a slow-moving landslide in the tropical rural environment of the Kivu Rift, with unprecedented high spatial and temporal resolution. We measure landslide motion using sub-pixel image correlation methods and invert these data into dense time series that capture weekly to multi-year changes in landslide kinematics. We cross-validate and compare our satellite-based results with very-high-resolution Unoccupied Aircraft System topographic datasets, and explore how rainfall, simulated pore-water pressure, and nearby earthquakes control the overall landslide behaviour. The landslide exhibited seasonal and multi-year velocity variations that varied across the landslide kinematic units. While rainfall-induced changes in pore-water pressure exerts a primary control on the landslide motion, these alone cannot explain the observed variability in landslide behaviour. We suggest instead that the observed landslide kinematics result from internal landslide dynamics, such as extension, compression, material redistribution, and interactions within and between kinematic units. Our study provides, a rare, detailed overview of the deformation pattern of a landslide located in a tropical environment. In addition, our work highlights the viability of sub-pixel image correlation with long time series of radar-amplitude satellite data to quantify surface deformation in tropical environments where optical data is limited by persistent cloud cover and emphasize the importance of exploiting synergies between multiple types of data to capture the complex kinematic pattern of landslides.</p>

scholarly journals Artificial Neural Network Modeling for Spatial and Temporal Variations of Pore-Water Pressure Responses to Rainfall

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
M. R. Mustafa ◽  
R. B. Rezaur ◽  
H. Rahardjo ◽  
M. H. Isa ◽  
A. Arif
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Pore Water ◽  
Pore Water Pressure ◽  
Water Pressure ◽  
Temporal Variations ◽  
Spatial And Temporal Variations ◽  
Ann Model ◽  
Soil Pore Water ◽  
Pore Water Pressures

Knowledge of spatial and temporal variations of soil pore-water pressure in a slope is vital in hydrogeological and hillslope related processes (i.e., slope failure, slope stability analysis, etc.). Measurements of soil pore-water pressure data are challenging, expensive, time consuming, and difficult task. This paper evaluates the applicability of artificial neural network (ANN) technique for modeling soil pore-water pressure variations at multiple soil depths from the knowledge of rainfall patterns. A multilayer perceptron neural network model was constructed using Levenberg-Marquardt training algorithm for prediction of soil pore-water pressure variations. Time series records of rainfall and pore-water pressures at soil depth of 0.5 m were used to develop the ANN model. To investigate applicability of the model for prediction of spatial and temporal variations of pore-water pressure, the model was tested for the time series data of pore-water pressure at multiple soil depths (i.e., 0.5 m, 1.1 m, 1.7 m, 2.3 m, and 2.9 m). The performance of the ANN model was evaluated by root mean square error, mean absolute error, coefficient of correlation, and coefficient of efficiency. The results revealed that the ANN performed satisfactorily implying that the model can be used to examine the spatial and temporal behavior of time series of pore-water pressures with respect to multiple soil depths from knowledge of rainfall patterns and pore-water pressure with some antecedent conditions.

scholarly journals Reduction of Groundwater Buoyancy on the Basement in Weak-Permeable/Impervious Foundations

2019 ◽  
Vol 2019 ◽  
pp. 1-11
Author(s):  
Jikai Zhou ◽  
Chenghuan Lin ◽  
Chen Chen ◽  
Xiyao Zhao
Keyword(s):  
Pore Water ◽  
Groundwater Level ◽  
Pore Water Pressure ◽  
Water Pressure ◽  
Field Measurements ◽  
Laboratory Model ◽  
Test Results ◽  
Underground Structures ◽  
Significant Difference ◽  
Reduction Coefficient

At present, groundwater buoyancy is directly calculated by Archimedes’ principle for the antifloating design of underground structures. However, this method may not be applicable to weak-permeable/impervious soils, e.g., clayey foundations, because there is a significant difference between the groundwater buoyancy obtained from field measurements and that calculated by Archimedes’ principle. In order to determine whether the method of calculating groundwater buoyancy in weak-permeable/impervious soil layers by Archimedes’ principle is reasonable, this paper investigated the groundwater buoyancy on the basement in such foundations through laboratory model tests. The following factors that may influence the magnitude of groundwater buoyancy were investigated: change of groundwater level, duration of pore water pressure, and buried depth of the basement. In this study, model test results show that the groundwater buoyancy obtained from measurements is evidently lower than that calculated by Archimedes’ principle. Reduction extent can be expressed by a “reduction coefficient,” which can be calculated by a fitting formula. Moreover, experimental groundwater buoyancy increases with the increase in the groundwater level, and it almost does not change with the growth of duration of pore water pressure. Reduction coefficient ranges between 0.25 and 0.52 depending on different buried depths of the basement. In general, experimental groundwater buoyancy decreases with the increase in the buried depth of the basement.

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