Preprints
Filtering by Subject: Statistical Models
A new OSL dose model to account for post-depositional mixing of sediments
Published: 2023-06-07
Subjects: Earth Sciences, Statistical Models, Statistics and Probability
In applications of optically stimulated luminescence (OSL) dating to unconsolidated sediments, the burial age of a sample of grains is estimated using statistical models of the distribution of the experimentally determined equivalent doses of the grains, together with estimates of the environmental dose rate. For grains that have been vertically mixed after deposition (e.g., due to bioturbation), [...]
Carbon Utilization and Storage through Rehabilitation of Groundwater Wells
Published: 2023-05-20
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
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 [...]
From ground motion simulations to landslide occurrence prediction
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 [...]
Improving Shoreline Forecasting Models with Multi-Objective Genetic Programming
Published: 2023-01-10
Subjects: Artificial Intelligence and Robotics, Climate, Environmental Engineering, Environmental Monitoring, Geomorphology, Hydrology, Numerical Analysis and Scientific Computing, Oceanography, Sedimentology, Statistical Models
Given the current context of climate change and increasing population densities at coastal zones, there is an increasing need to be able to predict the development of our coasts. Recent advances in artificial intelligence allow for automatic analysis of observational data. This work makes use of Symbolic Regression, a type of Machine Learning algorithm, to evolve interpretable shoreline [...]
Efficient Estimation of Climate State and Its Uncertainty Using Kalman Filtering with Application to Policy Thresholds and Volcanism
Published: 2022-10-18
Subjects: Longitudinal Data Analysis and Time Series, Non-linear Dynamics, Planetary Sciences, Statistical Models
We present the Energy Balance Model – Kalman Filter (EBM-KF), a hybrid model projecting and assimilating the global mean surface temperature (GMST) and ocean heat content anomaly (OHCA). It combines an annual energy balance model (difference equations) with 17 parameters drawn from the literature and a statistical Extended Kalman Filter assimilating GMST and OHCA, either observed timeseries or [...]
A data-driven framework for landslide size space-time modelling
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 [...]
Space-time landslide susceptibility modelling in Taiwan
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 [...]
Hybrid Machine Learning for Integrating Pedological Knowledge into Digital Soil Mapping to Advance Next-Generation Earth System Models
Published: 2022-07-22
Subjects: Environmental Monitoring, Soil Science, Statistical Models
Land surface and Earth System models require reliable soil maps to represent the influence of spatial variability of soil properties on ecosystem fluxes and storages. However, mapping soils using conventional in situ survey protocols is time-consuming and costly. We addressed the outdated spatial information on soil physico-chemical properties for a tropical region with a ~700-km longitudinal [...]
The Lock-Down Effects of COVID-19 on the Air Pollution Indices in Iran and Its Neighbors
Published: 2022-07-02
Subjects: Applied Statistics, Environmental Public Health, Environmental Sciences, Environmental Studies, Near and Middle Eastern Studies, Other Statistics and Probability, Statistical Methodology, Statistical Models
Introduction The Covid-19 restrictions have a lot of various peripheral negative and positive effects like economic shocks and decreasing air pollution, respectively. Many studies showed NO2 reduction in most parts of the world. Method Iran and its land and maritime neighbors have about 7.4% of the world population and 6.3% and 5.8% of World COVID-19 cases and deaths, respectively. The air [...]
Towards Robust River Plastic Detection: Combining Lab and Field-based Hyperspectral Imagery
Published: 2022-06-29
Subjects: Earth Sciences, Environmental Monitoring, Environmental Sciences, Hydrology, Statistical Models
Plastic pollution in aquatic ecosystems has increased dramatically in the last five decades, with strong impacts on human and aquatic life. Recent studies endorse the need for innovative approaches to monitor the presence, abundance, and types of plastic in these ecosystems. One approach gaining rapid traction is the use of multi- and hyperspectral cameras. However, most experiments using this [...]
Robust Probabilities of Detection and Quantification Uncertainty for Aerial Methane Detection: Examples for Three Airborne Technologies
Published: 2022-06-17
Subjects: Atmospheric Sciences, Climate, Environmental Monitoring, Mechanical Engineering, Oil, Gas, and Energy, Statistical Methodology, Statistical Models
Thorough characterization of probabilities of detection (POD) and quantification uncertainties is fundamentally important to understand the place of aerial measurement technologies in alternative means of emission limitation (AMEL) or alternate fugitive emissions management programs (Alt-FEMP); monitoring, reporting, and verification (MRV) efforts; and surveys designed to support [...]
Reducing the Uncertainty of Multi-Well Petrophysical Interpretation from Well Logs via Machine-Learning and Statistical Models
Published: 2022-03-22
Subjects: Analysis, Earth Sciences, Engineering, Geophysics and Seismology, Mining Engineering, Multivariate Analysis, Statistical Methodology, Statistical Models
Well-log interpretation provides in situ estimates of formation properties such as porosity, hydrocarbon pore volume, and permeability. Reservoir models based on well-log-derived formation properties deliver reserve-volume estimates, production forecasts, and help with decision making in reservoir development. However, due to measurement errors, variability of well logs due to multiple [...]
Wildfire Smoke Exposure Worsens Learning Outcomes
Published: 2021-12-08
Subjects: Environmental Public Health, Environmental Sciences, Environmental Studies, Statistical Models
Wildfires have increased in frequency and severity over the past two decades, threatening to undo substantial air quality improvements. We investigate the effect of wildfire smoke exposure on learning outcomes across the US using standardized test scores from 2009-2016 for nearly 11,700 school districts and satellite-derived estimates of daily smoke exposure. Relative to a school year with no [...]
Estuarine-deltaic controls on coastal carbon burial in the western Ganges-Brahmaputra delta over the last 5,000 years
Published: 2021-11-26
Subjects: Applied Statistics, Biogeochemistry, Earth Sciences, Environmental Sciences, Geochemistry, Geology, Geomorphology, Other Earth Sciences, Other Environmental Sciences, Other Statistics and Probability, Physical Sciences and Mathematics, Sedimentology, Statistical Methodology, Statistical Models, Statistics and Probability, Water Resource Management
The Ganges–Brahmaputra fluvial system drains the Himalayas and is one of the largest sources of terrestrial biosphere carbon to the ocean. It represents a major continental reservoir of CO2 associated with c. 1–2 billion tons of sediment transported each year. Shallow coastal environments receive substantial inputs of terrestrial carbon (900 Tg C yr−1), with allochthonous carbon capture on [...]