Preprints

Filtering by Subject: Applied Statistics

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

Morteza Karimzadeh, Rafael Pires de Lima

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 two spaceborne lidar altimetry instruments, 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 measurements of both missions [...]

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 [...]

Estimation and Uncertainty Quantification of Magma Interaction Times using Statistical Emulation

Luca Insolia, Stéphane Guerrier, Chiara Paola Montagna, et al.

Published: 2022-12-02
Subjects: Applied Statistics, Earth Sciences, Physical Sciences and Mathematics, Volcanology

Evolution of volcanic plumbing systems towards eruptions of different styles and sizes largely depends on processes at crustal depths that are outside our observational capabilities. These processes can be modeled and the outputs of the simulations can be compared with the chemistry of the erupted products, geophysical and geodetic data to retrieve information on the architecture of the plumbing [...]

Standardised indices to monitor energy droughts

Sam Allen, Noelia Otero

Published: 2022-12-01
Subjects: Applied Statistics, Environmental Sciences, Physical Sciences and Mathematics, Sustainability

To mitigate the effects of climate change, energy systems are becoming increasingly reliant on renewable energy sources. Since these energy sources are typically dependent on the prevailing weather, renewable energy systems are susceptible to shortages during certain weather conditions. As renewable sources become larger contributors to the energy mix, the risks associated with these shortages, [...]

Fisher Discriminant Analysis for Extracting Interpretable Phenological Information from Multivariate Time Series Data

Conor Doherty, Meagan S Mauter

Published: 2022-10-24
Subjects: Applied Statistics, Environmental Engineering, Environmental Monitoring, Environmental Sciences, Remote Sensing

For many applications in environmental remote sensing, the interpretation of a given measurement depends strongly on what time of year the measurement was taken. This is particularly the case for phenology studies concerned with identifying when plant developmental transitions occur, but it is also true for a wide range of applications including vegetation species classification, crop yield [...]

A data-driven framework for landslide size space-time modelling

Zhice Fang, Yi Wang, Cees J. van Westen, et al.

Published: 2022-10-10
Subjects: Applied Statistics, Geomorphology, Multivariate Analysis, Statistical Models

Landslide susceptibility assessment using data-driven models has predominantly focused on predicting where landslides may occur and not on how large they might be. The spatio-temporal evaluation of landslide susceptibility has only recently been addressed, as a basis for predicting where and when landslides might occur. The present study combines these new developments by proposing a data-driven [...]

Machine learning for understanding inland water quantity, quality, and ecology

Alison Paige Appling, Samantha Kay Oliver, Jordan S. Read, et al.

Published: 2022-09-03
Subjects: Applied Statistics, Fresh Water Studies, Hydrology

This chapter provides an overview of machine learning models and their applications to the science of inland waters. Such models serve a wide range of purposes for science and management: predicting water quality, quantity, or ecological dynamics across space, time, or hypothetical scenarios; vetting and distilling raw data for further modeling or analysis; generating and exploring hypotheses; [...]

Space-time landslide susceptibility modelling in Taiwan

Zhice Fang, Yi Wang, Cees J. van Westen, et al.

Published: 2022-07-27
Subjects: Applied Statistics, Geomorphology, Multivariate Analysis, Statistical Models

Portraying spatiotemporal variations in landslide susceptibility patterns is crucial for landslide prevention and management. In this study, we implement a space-time modeling approach to predict the landslide susceptibility on a yearly basis across the main island of Taiwan, from 2004 to 2018. We use a Bayesian version of a binomial generalized additive model, which assumes that landslide [...]

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