scholarly journals Control and Prevent Land Subsidence Caused by Foundation Pit Dewatering in a Coastal Lowland Mega City: Indicator Definition, Numerical Simulation and Regression Analysis

2022 ◽  
Author(s):  
Jianxiu Wang ◽  
Tianliang Yang ◽  
Guotao Wang ◽  
Xiaotian Liu ◽  
Na Xu ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Numerical Simulations ◽  
Sea Level ◽  
Land Subsidence ◽  
Regression Models ◽  
Numerical Models ◽  
Global Climate ◽  
Foundation Pit ◽  
Groundwater Exploitation ◽  
Coastal Lowland

Abstract Coastal mega cities are often commercial centers because of convenient traffic. Safe elevation above sea level is vital for their sustainable development. Global climate change and sea level rising increase flood risk especially in the lowland subsidence area. Shanghai of China was selected as research background. Although groundwater exploitation had been strictly restrained to control land subsidence and reserve safe elevation, lowering groundwater level during underground excavation cannot be avoided. Foundation pit dewatering (FPD) was intensively performed in underground exploitation during urbanization and city renewal. The FPD settlement accelerated land subsidence. Controlling FPD subsidence was urgent. Normally, the maximum horizontal influence radius of foundation pit excavation was less than three times excavation depth (H), and the 3H settlement was only caused by the FPD. The 3H maximum settlement was defined as the evaluating indicator of FPD land subsidence, and the corresponding 3H drawdown was defined as the control indicator of land subsidence. The FPD conceptual models were established on the basis of estimation and investigation of foundation pit information, including pit area, pit shape, pit depth, and curtain depth. Numerical models were established and a total of 5650 FPD numerical simulations were performed to investigate the land subsidence and FPD drawdown. Multi-factor regression analysis was conducted to obtain relations between land subsidence and FPD drawdown. Regression models were established between the 3H drawdown and the shape, area, depth, and curtain depth of foundation pit on the basis of the numerical simulations. A typical example introduced to verify the regression models. The regression models were used to manage the FPD land subsidence by controlling the 3H FPD drawdown. The results can provide reference for the land subsidence control in a coastal lowland city.

scholarly journals Compound Hydrometeorological Extremes: Drivers, Mechanisms and Methods

2021 ◽  
Vol 9 ◽  
Author(s):  
Wei Zhang ◽  
Ming Luo ◽  
Si Gao ◽  
Weilin Chen ◽  
Vittal Hari ◽  
...  
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Statistical Modeling ◽  
Storm Surge ◽  
Climate Models ◽  
Heat Waves ◽  
Numerical Models ◽  
Global Climate ◽  
The State ◽  
Global Climate Models

Compound extremes pose immense challenges and hazards to communities, and this is particularly true for compound hydrometeorological extremes associated with deadly floods, surges, droughts, and heat waves. To mitigate and better adapt to compound hydrometeorological extremes, we need to better understand the state of knowledge of such extremes. Here we review the current advances in understanding compound hydrometeorological extremes: compound heat wave and drought (hot-dry), compound heat stress and extreme precipitation (hot-wet), cold-wet, cold-dry and compound flooding. We focus on the drivers of these extremes and methods used to investigate and quantify their associated risk. Overall, hot-dry compound extremes are tied to subtropical highs, blocking highs, atmospheric stagnation events, and planetary wave patterns, which are modulated by atmosphere-land feedbacks. Compared with hot-dry compound extremes, hot-wet events are less examined in the literature with most works focusing on case studies. The cold-wet compound events are commonly associated with snowfall and cold frontal systems. Although cold-dry events have been found to decrease, their underlying mechanisms require further investigation. Compound flooding encompasses storm surge and high rainfall, storm surge and sea level rise, storm surge and riverine flooding, and coastal and riverine flooding. Overall, there is a growing risk of compound flooding in the future due to changes in sea level rise, storm intensity, storm precipitation, and land-use-land-cover change. To understand processes and interactions underlying compound extremes, numerical models have been used to complement statistical modeling of the dependence between the components of compound extremes. While global climate models can simulate certain types of compound extremes, high-resolution regional models coupled with land and hydrological models are required to simulate the variability of compound extremes and to project changes in the risk of such extremes. In terms of statistical modeling of compound extremes, previous studies have used empirical approach, event coincidence analysis, multivariate distribution, the indicator approach, quantile regression and the Markov Chain method to understand the dependence, greatly advancing the state of science of compound extremes. Overall, the selection of methods depends on the type of compound extremes of interests and relevant variables.

Uncertainties of creek evolution in coastal wetlands facing sea-level rise

2020 ◽  
Author(s):  
Xiaorong Li ◽  
Nicoletta Leonardi ◽  
Andy Plater
Keyword(s):  
Climate Change ◽  
Sea Level Rise ◽  
Sea Level ◽  
Coastal Wetlands ◽  
Numerical Models ◽  
Global Climate ◽  
Environmental Stressors ◽  
Loss Of Life ◽  
Global Challenge

<p>Adaptation of coastal areas facing climate change is a global challenge. Some of these low‐lying regions are commonly managed and engineered to reduce damage, loss of life, and environmental degradation caused by natural hazards originating from the sea. However, sea-level rise and changes in storm regimes are putting unprecedented pressure on these managed systems, forcing the adoption of “no active intervention” or “managed realignment” strategies in areas where “hold the line” options cannot be justified due to financial constraints. The aim of this research is to explore how disintegration of sea defences would affect creek topology under present day and future sea level rise scenarios, using the Hesketh marsh as a case study.  A reduced complexity numerical model is applied to produce ensemble predictions for analysis. Without the presence of vegetation, results suggest that creek geometry efficiency and density of tidal creeks are insensitive to sea level rise.</p><p>The model assumes the erodibility of the wetland is homogeneous and constant which leaves room for improvement because coastal environment is subject to changes as a result of global climate change and human activities. Changes in environmental stressors, such as sea level rise, elevated CO<sub>2</sub> concentration, changing storm patterns, etc. could adjust the resistance of the wetland to erosion in either way. Hence, the adequacy of current parameterizations of soil erodibility in numerical models requires further investigation.</p>

scholarly journals Prevention partition for land subsidence induced by engineering dewatering in Shanghai

2015 ◽  
Vol 372 ◽  
pp. 207-210
Author(s):  
J. X. Wang ◽  
X. T. Liu ◽  
T. L. Yang
Keyword(s):  
Land Subsidence ◽  
Early Years ◽  
Confined Aquifer ◽  
Foundation Pit ◽  
Rapid Urbanization ◽  
Groundwater Exploitation

Abstract. Land subsidence in shanghai has been found for more than 70 years. In the early years, it was mainly caused by groundwater exploitation. In recent years, engineering dewatering in shallow ground (within 90 m) has become a major source for land subsidence in the rapid urbanization course. A management partition of land subsidence induced by foundation pit dewatering for the first confined aquifer was suggested.

Antarctic Climate History and Global Climate Changes

2017 ◽  
Author(s):  
Pontus Lurcock ◽  
Fabio Florindo
Keyword(s):  
Ocean Circulation ◽  
Climate Changes ◽  
Numerical Models ◽  
Global Climate ◽  
Sediment Cores ◽  
Ice Sheets ◽  
Global Ocean ◽  
Climate History ◽  
Global Climate Changes ◽  
Planetary Albedo

Antarctic climate changes have been reconstructed from ice and sediment cores and numerical models (which also predict future changes). Major ice sheets first appeared 34 million years ago (Ma) and fluctuated throughout the Oligocene, with an overall cooling trend. Ice volume more than doubled at the Oligocene-Miocene boundary. Fluctuating Miocene temperatures peaked at 17–14 Ma, followed by dramatic cooling. Cooling continued through the Pliocene and Pleistocene, with another major glacial expansion at 3–2 Ma. Several interacting drivers control Antarctic climate. On timescales of 10,000–100,000 years, insolation varies with orbital cycles, causing periodic climate variations. Opening of Southern Ocean gateways produced a circumpolar current that thermally isolated Antarctica. Declining atmospheric CO2 triggered Cenozoic glaciation. Antarctic glaciations affect global climate by lowering sea level, intensifying atmospheric circulation, and increasing planetary albedo. Ice sheets interact with ocean water, forming water masses that play a key role in global ocean circulation.

scholarly journals On the geophysical processes impacting palaeo-sea-level observations

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Yusuke Yokoyama ◽  
Anthony Purcell
Keyword(s):  
Sea Level ◽  
Large Scale ◽  
Global Climate ◽  
Sea Level Change ◽  
Sea Level Changes ◽  
Factors Affecting ◽  
Ice Volume ◽  
Level Change ◽  
Recent Developments ◽  
Geophysical Processes

AbstractPast sea-level change represents the large-scale state of global climate, reflecting the waxing and waning of global ice sheets and the corresponding effect on ocean volume. Recent developments in sampling and analytical methods enable us to more precisely reconstruct past sea-level changes using geological indicators dated by radiometric methods. However, ice-volume changes alone cannot wholly account for these observations of local, relative sea-level change because of various geophysical factors including glacio-hydro-isostatic adjustments (GIA). The mechanisms behind GIA cannot be ignored when reconstructing global ice volume, yet they remain poorly understood within the general sea-level community. In this paper, various geophysical factors affecting sea-level observations are discussed and the details and impacts of these processes on estimates of past ice volumes are introduced.

Effects of groundwater exploitation and recharge on land subsidence and infrastructure settlement patterns in Shanghai

2021 ◽  
pp. 105995
Author(s):  
Ming-Guang Li ◽  
Jin-Jian Chen ◽  
Ye-Shuang Xu ◽  
Da-Gui Tong ◽  
Wei-Wei Cao ◽  
...  
Keyword(s):  
Land Subsidence ◽  
Settlement Patterns ◽  
Groundwater Exploitation

scholarly journals Regression Models in Complex Survey Sampling for Sensitive Quantitative Variables

Mathematics ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 609
Author(s):  
María del Mar Rueda ◽  
Beatriz Cobo ◽  
Antonio Arcos
Keyword(s):  
Regression Analysis ◽  
Regression Models ◽  
Regression Coefficients ◽  
Randomized Response ◽  
Statistical Tool ◽  
Complex Survey ◽  
Complex Sample ◽  
Qualitative Variables ◽  
World Survey ◽  
Sensitive Variable

Randomized response (RR) techniques are widely used in research involving sensitive variables, such as drugs, violence or crime, especially when a population mean or prevalence must be estimated. However, they are not generally applied to examine relationships between a sensitive variable and other characteristics. This type of technique was initially applied to qualitative variables, and studies later showed that a logistic regression may be performed with RR data. Since many of the variables considered in this context are quantitative, RR techniques were extended to these cases to estimate the values required. Regression analysis is a valuable statistical tool for exploring relationships among variables and for establishing associations between responses and covariates. In this article, we propose a design-based regression analysis for complex sample designs based on the unified RR approach. We present estimators of the regression coefficients, study their theoretical properties and consider different ways to estimate their variance. The properties of these estimation techniques were simulated using various quantitative randomized models. The method proposed was also used to analyse the findings from a real-world survey.

scholarly journals Estimation of Outdoor PM2.5 Infiltration into Multifamily Homes Depending on Building Characteristics Using Regression Models

2021 ◽  
Vol 13 (10) ◽  
pp. 5708
Author(s):  
Bo-Ram Park ◽  
Ye-Seul Eom ◽  
Dong-Hee Choi ◽  
Dong-Hwa Kang
Keyword(s):  
Regression Analysis ◽  
Correlation Analysis ◽  
Field Test ◽  
Outer Surface ◽  
Regression Models ◽  
Field Tests ◽  
Test Results ◽  
Correlation And Regression Analysis ◽  
Building Characteristics ◽  
Pm2.5 Concentration

The purpose of this study was to evaluate outdoor PM2.5 infiltration into multifamily homes according to the building characteristics using regression models. Field test results from 23 multifamily homes were analyzed to investigate the infiltration factor and building characteristics including floor area, volume, outer surface area, building age, and airtightness. Correlation and regression analysis were then conducted to identify the building factor that is most strongly associated with the infiltration of outdoor PM2.5. The field tests revealed that the average PM2.5 infiltration factor was 0.71 (±0.19). The correlation analysis of the building characteristics and PM2.5 infiltration factor revealed that building airtightness metrics (ACH50, ELA/FA, and NL) had a statistically significant (p < 0.05) positive correlation (r = 0.70, 0.69, and 0.68, respectively) with the infiltration factor. Following the correlation analysis, a regression model for predicting PM2.5 infiltration based on the ACH50 airtightness index was proposed. The study confirmed that the outdoor-origin PM2.5 concentration in highly leaky units could be up to 1.59 times higher than that in airtight units.

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