Preprints

Filtering by Subject: Applied Statistics

Challenges and Opportunities of Data Driven Advance Classification of Hard Rock TBMs

Georg H. Erharter, Paul Johannes Unterlaß, Nedim Radončić, et al.

Published: 2024-09-21
Subjects: Applied Statistics, Civil and Environmental Engineering, Civil Engineering, Earth Sciences, Geology, Geotechnical Engineering

Tunnel Boring Machines (TBMs) have revolutionized tunneling industry and are currently the dominant method of tunneling in all ground types including soil and rock. Traditional approaches to TBM advance classification, however, rely heavily on subjective assessments by onsite personnel, which are often hampered by limited access to the excavation face and discontinuous observation intervals. [...]

How much is enough? Uncertainty aware sample mass determination of coarse-grained soils for particle size analyses

Georg H. Erharter, Santiago Quinteros, Diana Cordeiro, et al.

Published: 2024-08-23
Subjects: Applied Statistics, Civil and Environmental Engineering, Civil Engineering, Earth Sciences, Engineering, Environmental Engineering, Environmental Monitoring, Geology, Geomorphology, Geotechnical Engineering, Hydraulic Engineering, Hydrology, Other Civil and Environmental Engineering, Other Earth Sciences, Probability, Sedimentology, Soil Science, Statistical Models, Statistics and Probability, Stratigraphy

Determining particle size distributions (PSD) of soils is a basic first step in many geotechnical analyses and guidance is given in different national standards. For ambiguous reasons, the recommended required minimum sample mass (m_min) for the PSD-analyses of soils with a main component of gravel or greater is always based on equations including the soil's maximum grain diameter (D_max). We [...]

Increasingly seasonal jet stream drives stormy episodes with joint wind-flood risk in Great Britain

John Hillier, Hannah Bloomfield, Colin Manning, et al.

Published: 2024-07-03
Subjects: Applied Statistics, Atmospheric Sciences, Climate, Hydrology, Multivariate Analysis

Ignoring a correlation between flooding and extreme winds underestimates risk to insurers or providers of critical infrastructure such as railways or electricity. We explore this potential underestimation for Northwest Europe, illustrated using Great Britain (GB), using an event-based analysis in regional 12 km UK Climate Projections (UKCP18, 1981-1999, 2061-2079 – RCP8.5). We derive a new [...]

A critical appraisal of water table depth estimation: Challenges and opportunities within machine learning

Joseph Janssen, Ardalan Tootchi, Ali A Ameli

Published: 2024-05-02
Subjects: Applied Statistics, Hydrology

Fine-resolution spatial patterns of water table depth (WTD) play a crucial role in shaping ecological resilience, hydrological connectivity, and anthropocentric objectives. Generally, a large-scale (e.g., continental or global) spatial map of static WTD can be simulated using either physically-based (PB) or machine learning-based (ML) models. We construct three fine-resolution (500 m) ML [...]

Estimating the mass eruption rate of volcanic eruptions from the plume height using Bayesian regression with historical data: the MERPH model

Mark James Woodhouse

Published: 2024-04-18
Subjects: Applied Statistics, Statistical Models, Statistics and Probability, Volcanology

The mass eruption rate (MER) of an explosive volcanic eruption is a commonly used quantifier of the magnitude of the eruption, and estimating it is importance in managing volcanic hazards. The physical connection between the MER and the rise height of the eruption column results in a scaling relationship between these quantities, allowing one to be inferred from the other. Eruption source [...]

Advancing forest aboveground biomass mapping by integrating GEDI with other Earth Observation data using a cloud computing platform: A case study of Alabama, United States

Janaki Sandamali, Lana Narine

Published: 2024-04-06
Subjects: Applied Statistics, Climate, Earth Sciences, Environmental Monitoring, Environmental Sciences, Forest Management, Other Forestry and Forest Sciences

Forest aboveground biomass (AGB) is a crucial indicator for monitoring carbon and requires accurate quantification. This study aimed to advance AGB estimation using open access Earth observation (EO) data and cloud computing, focusing on Alabama, USA. The specific objectives were to: (1) develop a workflow for creating a 30 m forest AGBD map with GEDI, using GEE, (2) evaluate and compare [...]

An updated landslide susceptibility model and a log-Gaussian Cox process extension for Scotland

Erin Kelly Bryce, Daniela Castro-Camilo, Claire Dashwood, et al.

Published: 2024-02-01
Subjects: Applied Statistics, Geomorphology

At the time of its development, GeoSure was created using expert knowledge based on a thorough understanding of the engineering geology of the rocks and soils of Great Britian. The ability to use a data-driven methodology to develop a national scale landslide susceptibility was not possible due to the relatively small size of the landslide inventory at the time. In the intervening 20 years the [...]

Model Ensemble with Dropout for Uncertainty Estimation in Binary Sea Ice or Water Segmentation using Sentinel-1 SAR

Rafael Pires de Lima, Morteza Karimzadeh

Published: 2024-01-20
Subjects: Applied Statistics, Environmental Monitoring, Signal Processing

Despite the growing use of deep learning in sea ice mapping with SAR imagery, the study of model uncertainty and segmentation results remains limited. Deep learning models often produce overconfident predictions, a concern in sea ice mapping where misclassification can impact marine navigation safety. We incorporate and compare dropout and model ensemble within a convolutional neural network [...]

Demystifying the Dynamics of Global and Regional Sea Level Trends from 1993 to 2021

Ashraf Rateb, Bridget R. Scanlon

Published: 2023-07-07
Subjects: Applied Statistics, Earth Sciences, Physical Sciences and Mathematics, Statistical Models

As global sea levels rise, questions persist about the robustness of trends and their dynamics. Here, we offer a fresh perspective by examining the dynamics of global and regional mean sea-level trends using a probabilistic framework applied to the altimetric record. We show that the global mean sea-level (GMSL) rise accelerated from 2.5 mm/yr (1993-2000) to 4.2 mm/yr (2014-2021) with an average [...]

Assessing vertical accuracy and spatial coverage of ICESat-2 and GEDI spaceborne lidar for creating global terrain models

Maarten Pronk, Marieke Eleveld, Hugo Ledoux

Published: 2023-07-06
Subjects: Applied Statistics, Geomorphology, Remote Sensing

Digital elevation models (DEMs) are a necessity for modelling many large-scale environmental processes. In this study, we investigate the potential of data from two spaceborne lidar altimetry missions, ICESat-2 and GEDI—with respect to their vertical accuracies and planimetric data collection patterns—as sources for rasterisation towards global DEMs. We validate the terrain [...]

Carbon Utilization and Storage through Rehabilitation of Groundwater Wells

Vivek Vidyadhar Patil, Gabriella Basso, Steven Catania, et al.

Published: 2023-05-21
Subjects: Applied Statistics, Civil and Environmental Engineering, Climate, Earth Sciences, Environmental Sciences, Geochemistry, Hydrology, Longitudinal Data Analysis and Time Series, Oil, Gas, and Energy, Statistical Methodology, Statistical Models, Statistics and Probability

According to the Intergovernmental Panel on Climate Change (IPCC) of the United Nations (UN), rise in atmospheric concentration of carbon dioxide (CO2) due to anthropogenic factors is considered as the primary driver for global climate change. With almost every major corporation around the world working towards their “net-zero goals”, it is becoming increasingly important to have more [...]

Assessing multi-hazard susceptibility to cryospheric hazards: lesson learnt from an Alaskan example

Letizia Elia, Silvia Castellaro, Ashok Dahal, et al.

Published: 2023-04-28
Subjects: Applied Statistics, Geomorphology, Glaciology, Statistical Models

Classifying a given landscape on the basis of its susceptibility to surface processes is a standard procedure in low to mid-latitudes. Conversely, these procedures have hardly been explored in periglacial regions, primarily because of the limited presence of human settlements and, therefore, the little need for risk assessment. However, global warming is radically changing this situation and [...]

Global multi-hazard risk assessment in a changing climate

Zélie Stalhandske, Carmen B. Steinmann, Simona Meiler, et al.

Published: 2023-04-20
Subjects: Applied Statistics, Climate, Numerical Analysis and Scientific Computing, Risk Analysis

Natural hazards pose significant risks to people and assets in many regions of the world. Quantifying associated risks is crucial for many applications such as adaptation option appraisal and insurance pricing. However, traditional risk assessment approaches have focused on the impacts of single hazards, ignoring the effects of multi-hazard risks and potentially leading to underestimations or [...]

Dynamic rainfall thresholds for landslide early warning in Progo Catchment, Java, Indonesia

Ratna Satyaningsih, Victor Jetten, Janneke Ettema, et al.

Published: 2023-01-20
Subjects: Applied Statistics, Earth Sciences, Geomorphology, Hydrology, Meteorology

This study aims to derive and evaluate new empirical rainfall thresholds as the basis for landslide early warning in Progo Catchment, Indonesia, using high-resolution rainfall datasets. Although attempts have been made to determine such thresholds for regions in Indonesia, they used coarse-resolution data and fixed rainfall duration that might not reflect the characteristics of rainfall events [...]

From ground motion simulations to landslide occurrence prediction

Ashok Dahal, David Alejandro Casto Cruz, Hakan Tanyas, et al.

Published: 2023-01-17
Subjects: Applied Statistics, Earth Sciences, Geomorphology, Geophysics and Seismology, Physical Sciences and Mathematics, Soil Science, Statistical Models, Statistics and Probability

Ground motion simulations solve wave equations in space and time, thus producing detailed estimates of the shaking time series. This is essentially uncharted territory for geomorphologists, for we have yet to understand which ground motion (synthetic or not) parameter, or combination of parameters, is more suitable to explain the coseismic landslide distribution. To address this gap, we developed [...]

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