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Journal articleWang S, Toumi R, 2022,
Author Correction: On the intensity decay of tropical cyclones before landfall.
, Sci Rep, Vol: 12 -
Journal articlePiggott M, 2022,
Multilevel multifidelity Monte Carlo methods for assessing coastal flood risk
, Natural Hazards and Earth System Sciences, Vol: 22, Pages: 2491-2515, ISSN: 1561-8633Abstract. When choosing an appropriate hydrodynamic model, there is always a compromise between accuracy and computational cost, with high fidelity models being more expensive than low fidelity ones. However, when assessing uncertainty, wecan use a multifidelity approach to take advantage of the accuracy of high fidelity models and the computational efficiencyof low fidelity models. Here, we apply the multilevel multifidelity Monte Carlo method (MLMF) to quantify uncertainty by computing statistical estimators of key output variables with respect to uncertain inputs, using the high fidelity hydrodynamicmodel XBeach and the lower fidelity coastal flooding model SFINCS. The multilevel aspect opens up the further advantageouspossibility of applying each of these models at multiple resolutions. This work represents the first application of MLMF in thecoastal zone and one of its first applications in any field. For both idealised and real-world test cases, MLMF can significantlyreduce computational cost for the same accuracy compared to both the standard Monte Carlo method and to a multilevel approach utilising only a single model (the multilevel Monte Carlo method). In particular, here we demonstrate using the case ofMyrtle Beach, USA, that this improvement in computational efficiency allows in-depth uncertainty analysis to be conducted inthe case of real-world coastal environments – a task that would previously have been practically unfeasible. Moreover, for thefirst time, we show how an inverse transform sampling technique can be used to accurately estimate the cumulative distributionfunction (CDF) of variables from the MLMF outputs. MLMF based estimates of the expectations and the CDFs of the variables of interest are of significant value to decision makers when assessing risk.
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Journal articleKreibich H, Van Loon AF, Schroeter K, et al., 2022,
The challenge of unprecedented floods and droughts in risk management
, Nature, Vol: 608, Pages: 80-+, ISSN: 0028-0836Risk management has reduced vulnerability to floods and droughts globally1,2, yet their impacts are still increasing3. An improved understanding of the causes of changing impacts is therefore needed, but has been hampered by a lack of empirical data4,5. On the basis of a global dataset of 45 pairs of events that occurred within the same area, we show that risk management generally reduces the impacts of floods and droughts but faces difficulties in reducing the impacts of unprecedented events of a magnitude not previously experienced. If the second event was much more hazardous than the first, its impact was almost always higher. This is because management was not designed to deal with such extreme events: for example, they exceeded the design levels of levees and reservoirs. In two success stories, the impact of the second, more hazardous, event was lower, as a result of improved risk management governance and high investment in integrated management. The observed difficulty of managing unprecedented events is alarming, given that more extreme hydrological events are projected owing to climate change3.
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Journal articleClare MCA, Leijnse TWB, McCall RT, et al., 2022,
Multilevel multifidelity Monte Carlo methods for assessing uncertainty in coastal flooding
, Natural Hazards and Earth System Sciences, Vol: 22, Pages: 2491-2515, ISSN: 1561-8633When choosing an appropriate hydrodynamic model, there is always a compromise between accuracy and computational cost, with high-fidelity models being more expensive than low-fidelity ones. However, when assessing uncertainty, we can use a multifidelity approach to take advantage of the accuracy of high-fidelity models and the computational efficiency of low-fidelity models. Here, we apply the multilevel multifidelity Monte Carlo method (MLMF) to quantify uncertainty by computing statistical estimators of key output variables with respect to uncertain input data, using the high-fidelity hydrodynamic model XBeach and the lower-fidelity coastal flooding model SFINCS (Super-Fast INundation of CoastS). The multilevel aspect opens up the further advantageous possibility of applying each of these models at multiple resolutions. This work represents the first application of MLMF in the coastal zone and one of its first applications in any field. For both idealised and real-world test cases, MLMF can significantly reduce computational cost for the same accuracy compared to both the standard Monte Carlo method and to a multilevel approach utilising only a single model (the multilevel Monte Carlo method). In particular, here we demonstrate using the case of Myrtle Beach, South Carolina, USA, that this improvement in computational efficiency allows for in-depth uncertainty analysis to be conducted in the case of real-world coastal environments – a task that would previously have been practically unfeasible. Moreover, for the first time, we show how an inverse transform sampling technique can be used to accurately estimate the cumulative distribution function (CDF) of variables from the MLMF outputs. MLMF-based estimates of the expectations and the CDFs of the variables of interest are of significant value to decision makers when assessing uncertainty in predictions.
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Journal articleMorley JD, Myers RJ, Plancherel Y, et al., 2022,
A database for the stocks and flows of sand and gravel
, Resources, Vol: 11, Pages: 1-17, ISSN: 2079-9276Increasing demand for sand and gravel globally is leading to social, environmental, and political issues that are becoming more widely recognised. Lack of data and poor accessibility of the few available data contribute to exacerbating these issues and impair evidence-based management efforts. This paper presents a database to store stocks and flows data for sand and gravel from different sources. The classification system underlying within it builds on the Universal Materials Information System (UMIS) nomenclature, which is used to construct hierarchical order in the data and in the same manner as the Yale Stocks and Flow Database (YSTAFDB), a common data format. To illustrate how the database is built and used, a case study using UK data is presented. The UK is chosen owing to relatively better access to data compared to other locations. Quantitative analyses of the data show the supply chain of these materials to be currently stable for the UK as indigenous extraction contributes 95.6% to UK sand and gravel production, with imports accounting for the rest of the inputs, of which 50% is reliant on only one nation.
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Journal articleKaramanis R, Anastasiadis E, Stettler M, et al., 2022,
Vehicle Redistribution in Ride-Sourcing Markets Using Convex Minimum Cost Flows
, IEEE Transactions on Intelligent Transportation Systems, Vol: 23, Pages: 10287-10298, ISSN: 1524-9050Ride-sourcing platforms often face imbalances in the demand and supply of rides across areas in their operating road-networks. As such, dynamic pricing methods have been used to mediate these demand asymmetries through surge price multipliers, thus incentivising higher driver participation in the market. However, the anticipated commercialisation of autonomous vehicles could transform the current ride-sourcing platforms to fleet operators. The absence of human drivers fosters the need for empty vehicle management to address any vehicle supply deficiencies. Proactive redistribution using integer programming and demand predictive models have been proposed in research to address this problem. A shortcoming of existing models, however, is that they ignore the market structure and underlying customer choice behaviour. As such, current models do not capture the real value of redistribution. To resolve this, we formulate the vehicle redistribution problem as a non-linear minimum cost flow problem which accounts for the relationship of supply and demand of rides, by assuming a customer discrete choice model and a market structure. We demonstrate that this model can have a convex domain, and we introduce an edge splitting algorithm to solve a transformed convex minimum cost flow problem for vehicle redistribution. By testing our model using simulation, we show that our redistribution algorithm can decrease wait times by more than 50%, increase profit up to 10% with less than 20% increase in vehicle mileage. Our findings outline that the value of redistribution is contingent on localised market structure and customer behaviour.
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Journal articlePan W, Kramer SC, Piggott MD, et al., 2022,
Modeling landslide generated waves using the discontinuous finite element method
, International Journal for Numerical Methods in Fluids, Vol: 94, Pages: 1-33, ISSN: 0271-2091A new two-layer model for impulsive wave generation by deformable granular landslides is developed based upon a discontinuous Galerkin finite element discretization. Landslide motion is modeled using a depth-averaged formulation for a shallow subaerial debris flow, which considers the bed curvature represented by the local slope angle variable and accounts for inter-granular stresses using Coulomb friction. Wave generation and propagation are simulated with the three-dimensional non-hydrostatic coastal ocean model Thetis to accurately capture key features such as wave dispersion. Two different techniques are used in treating wetting and drying (WD) processes during the landslide displacement and wave generation, respectively. For the lower-layer landslide motion across the dry bed a classical thin-layer explicit WD method is implemented, while for the resulting free-surface waves interacted with the moving landslide an implicit WD scheme is utilized to naturally circumvent the artificial pressure gradient problem which may appear in the dynamic interaction between the landslide and water if using the thin-layer method. The two-layer model is validated using a suite of test cases, with the resulting good agreement demonstrating its capability in describing both the complex behaviors of granular landslides from initiation to deposition, and the consequent wave generation and propagation.
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Journal articleKarmpadakis I, Swan C, Christou M, 2022,
A new wave height distribution for intermediate and shallow water depths
, Coastal Engineering, Vol: 175, Pages: 1-15, ISSN: 0378-3839The present paper addresses the short-term distribution of zero-crossing wave heights in intermediate and shallow water depths. New physical insights are provided regarding the effects of nonlinearity, directionality, reduced effective water depth and finite spectral bandwidth. These are demonstrated through the analysis of a large database of experimental simulations of short-crested sea-states on flat bed bathymetries. A new wave height model is proposed building upon these physical insights and is calibrated using the experimental data. Independent comparisons between field measurements and the proposed model indicate that it is appropriate to a wide range of incident wave conditions and that it provides considerable improvement over existing models.
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Journal articleVeness WA, Butler AP, Ochoa-Tocachi BF, et al., 2022,
Localizing hydrological drought early warning using in situ groundwater sensors
, Water Resources Research, Vol: 58, Pages: 1-12, ISSN: 0043-1397Drought early warning systems (DEWSs) aim to spatially monitor and forecast risk of water shortage to inform early, risk-mitigating interventions. However, due to the scarcity of in situ monitoring in groundwater-dependent arid zones, spatial drought exposure is inferred using maps of satellite-based indicators such as rainfall anomalies, soil moisture, and vegetation indices. On the local scale, these coarse-resolution proxy indicators provide a poor inference of groundwater availability. The improving affordability and technical capability of modern sensors significantly increases the feasibility of taking direct groundwater level measurements in data-scarce, arid regions on a larger scale. Here, we assess the potential of in situ monitoring to provide a localized index of hydrological drought in Somaliland. We find that calibrating a lumped groundwater model with a short time series of groundwater level observations substantially improves the quantification of local water availability when compared to satellite-based indices. By varying the calibration length, we find that a 5-week period capturing both wet and dry season conditions provides most of the calibration capacity. This suggests that short monitoring campaigns are suitable for improving estimations of local water availabilities during drought. Short calibration periods have practical advantages, as the relocation of sensors enables rapid characterization of a large number of wells. These well simulations can supplement continuous in situ monitoring of strategic point sources to setup large-scale monitoring systems with contextualized and localized information on water availability. This information can be used as early warning evidence for the financing and targeting of early actions to mitigate impacts of hydrological drought.
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Journal articleAllen RW, Collier JS, Henstock TJ, 2022,
The role of crustal accretion variations in determining slab hydration at an Atlantic subduction zone
, Journal of Geophysical Research. Solid Earth, Vol: 127, ISSN: 2169-9356We present a 2D P-wave velocity model from the outer rise region of the Lesser Antilles island arc, the first wide-angle seismic study of outer rise processes at an Atlantic subduction zone. The survey consists of 46 OBS receivers over a 174 km profile with velocities resolved to 15 km below top basement. The final velocity model, produced through tomographic inversion, shows a clear decrease in the velocity of the lower crust and upper mantle of the incoming plate as it approaches the trench. We attribute this drop to outer rise bend-related hydration, similar to Pacific cases, but superimposed on spatial variations in hydration generated at the slow-spreading ridge axis. In thin, tectonically controlled crust formed under magma-poor spreading conditions the superposition of these sources of hydration results in compressional velocities as low as 6.5 km s−1 beneath the PmP reflector. In contrast, segments of crust interpreted as having formed under magma-rich conditions show velocity reductions and inferred hydrous alteration more like that observed in the Pacific. Hence, variations in the style of crustal accretion, which is observed on 50–100 km length scales both along and across isochrons, is a primary control over the distribution of water within the slab at Atlantic subduction systems. This heterogeneous pattern of water storage within the slab is likely further complicated by along strike variations in outer rise bending, subducting fracture zones and deformation at segment ends and may have important implications for our understanding of long-term patterns of hazard at Atlantic subduction systems.
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