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Predicting site-specific storm wave run-up
Storm wave run-up causes beach erosion, wave overtop**, and street flooding. Extreme runup estimates may be improved, relative to predictions from...
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On the Construction of Uncertain Time Series Surrogates Using Polynomial Chaos and Gaussian Processes
The analysis of time series is a fundamental task in many flow simulations such as oceanic and atmospheric flows. A major challenge is the design of...
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A Review of Surrogate Models and Their Ensembles to Develop Saltwater Intrusion Management Strategies in Coastal Aquifers
The complex physical processes in a typical coastal aquifer system with transient inputs to numerical simulation models (NSM) result in substantial...
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Evaluation and projections of the East Asian summer monsoon in a perturbed parameter ensemble
The East Asian summer monsoon (EASM) is a dominant driver of East Asian climate, with variations in its strength potentially impacting the...
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Assessing the quality of state-of-the-art regional climate information: the case of the UK Climate Projections 2018
In this paper, we assess the quality of state-of-the-art regional climate information intended to support climate adaptation decision-making. We use...
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Multi-level emulation of complex climate model responses to boundary forcing data
Climate model components involve both high-dimensional input and output fields. It is desirable to efficiently generate spatio-temporal outputs of...
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Probabilistic assessment of the impact of coal seam gas development on groundwater: Surat Basin, Australia
Modelling cumulative impacts of basin-scale coal seam gas (CSG) extraction is challenging due to the long time frames and spatial extent over which...
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A polynomial chaos framework for probabilistic predictions of storm surge events
We present a polynomial chaos-based framework to quantify the uncertainties in predicting hurricane-induced storm surges. Perturbation strategies are...
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Finding plausible and diverse variants of a climate model. Part 1: establishing the relationship between errors at weather and climate time scales
The main aim of this two-part study is to use a perturbed parameter ensemble (PPE) to select plausible and diverse variants of a relatively expensive...
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Surrogate-based Bayesian comparison of computationally expensive models: application to microbially induced calcite precipitation
Geochemical processes in subsurface reservoirs affected by microbial activity change the material properties of porous media. This is a complex...
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The influence of climate model uncertainty on fluvial flood hazard estimation
Floods are the most common and widely distributed natural hazard, threatening life and property worldwide. Governments worldwide are facing...
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Introduction to “Twenty Five Years of Modern Tsunami Science Following the 1992 Nicaragua and Flores Island Tsunamis, Volume I”
Twenty-two papers on tsunamis are included in the Pure and Applied Geophysics topical issue “Twenty five years of modern tsunami science following...
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Reconstruction of a flash flood event using a 2D hydrodynamic model under spatial and temporal variability of storm
In this paper, the catastrophic flash flood event which occurred in the western part of Attica (Greece) in November 2017 is reconstructed. The flood...
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Development of Mobile Application to Assess and Enhance Earthquake Preparedness Level of Individuals and Community in India
Earthquake is one of the natural hazards that affected the mankind the most with large scale destruction and loss of lives. According to IS...
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Learning Strategies and Population Dynamics During the Pleistocene Colonization of North America
Being able to identify individual populations has long been of interest in archaeology, but within the last several decades it has become a specific...
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A learning-from-data approach with soft clustering and path relinking to the history-matching problem
History matching is an important reservoir engineering process whereby the values of uncertain attributes of a reservoir model are changed to find...
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A Surrogate Modelling Approach Based on Nonlinear Dimension Reduction for Uncertainty Quantification in Groundwater Flow Models
In this paper, we develop a surrogate modelling approach for capturing the output field (e.g. the pressure head) from groundwater flow models...
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Probabilistic Sea Level Projections at the Coast by 2100
As sea level is rising along many low-lying and densely populated coastal areas, affected communities are investing resources to assess and manage...
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Gaussian Process Emulators for Computer Experiments with Inequality Constraints
Physical phenomena are observed in many fields (science and engineering) and are often studied by time-consuming computer codes. These codes are...
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Deep global model reduction learning in porous media flow simulation
In this paper, we combine deep learning concepts and some proper orthogonal decomposition (POD) model reduction methods for predicting flow in...