Uncertainty quantification of coal seam gas production prediction using Polynomial Chaos

A surrogate model approximates a computationally expensive solver. Polynomial Chaos is a method to construct surrogate models by summing combinations of carefully chosen polynomials. The polynomials are chosen to respect the probability distributions of the uncertain input variables (parameters); this allows for both uncertainty quantification and global sensitivity analysis. In this paper we apply these techniques to a commercial solver for the estimation of peak gas rate and cumulative gas extraction from a coal seam gas well. The polynomial expansion is shown to honour the underlying geophysics with low error when compared to a much more complex and computationally slower commercial solver. We make use of advanced numerical integration techniques to achieve this accuracy using relatively small amounts of training data

The agricultural impact of the 2015–2016 floods in Ireland as mapped through Sentinel 1 satellite imagery

peer-reviewedIrish Journal of Agricultural and Food Research | Volume 58: Issue 1 The agricultural impact of the 2015–2016 floods in Ireland as mapped through Sentinel 1 satellite imagery R. O’Haraemail , S. Green and T. McCarthy DOI: https://doi.org/10.2478/ijafr-2019-0006 | Published online: 11 Oct 2019 PDF Abstract Article PDF References Recommendations Abstract The capability of Sentinel 1 C-band (5 cm wavelength) synthetic aperture radio detection and ranging (RADAR) (abbreviated as SAR) for flood mapping is demonstrated, and this approach is used to map the extent of the extensive floods that occurred throughout the Republic of Ireland in the winter of 2015–2016. Thirty-three Sentinel 1 images were used to map the area and duration of floods over a 6-mo period from November 2015 to April 2016. Flood maps for 11 separate dates charted the development and persistence of floods nationally. The maximum flood extent during this period was estimated to be ~24,356 ha. The depth of rainfall influenced the magnitude of flood in the preceding 5 d and over more extended periods to a lesser degree. Reduced photosynthetic activity on farms affected by flooding was observed in Landsat 8 vegetation index difference images compared to the previous spring. The accuracy of the flood map was assessed against reports of flooding from affected farms, as well as other satellite-derived maps from Copernicus Emergency Management Service and Sentinel 2. Monte Carlo simulated elevation data (20 m resolution, 2.5 m root mean square error [RMSE]) were used to estimate the flood’s depth and volume. Although the modelled flood height showed a strong correlation with the measured river heights, differences of several metres were observed. Future mapping strategies are discussed, which include high–temporal-resolution soil moisture data, as part of an integrated multisensor approach to flood response over a range of spatial scales

Dynamique des inondations dans le continuum rivière-estuaire-océan littoral du delta du Bengale : synergie de la modélisation hydrodynamique et de la télédétection spatiale

Le delta du Bengale est le plus vaste au monde. Il est formé par la confluence des trois rivières transfrontalières que sont le Gange, le Brahmapoutre et la Meghna. Des inondations massives frappent régulièrement cette région côtière très densément peuplée, située à seulement quelques mètres au-dessus du niveau moyen de la mer. Elles résultent du puissant cycle saisonnier des débits fluviaux, de la marée océanique très ample, et des cyclones tropicaux fréquents. Au cours des cinquante dernières années, les inondations de la partie littorale du delta ont fait plus de 500'000 victimes. La montée du niveau moyen de la mer ne va faire qu'aggraver la vulnérabilité de cette région où le taux de pauvreté est très élevé. Le long du littoral, les estrans sont les zones alternativement inondées à marée haute et découvertes à marée basse. Leur topographie joue un rôle important dans l'hydrodynamique littorale et dans les submersions qui surviennent lors des évènements extrêmes. En mettant en œuvre une synergie entre l'imagerie par télédétection spatiale de la constellation Sentinel-2 et la modélisation numérique de la marée, nous avons cartographié la topographie de l'estran du delta du Bengale sur une superficie de 1134 km2, avec une résolution de 10 m. Les marées, qui sont le facteur dominant de la variabilité du niveau de la mer côtier, sont apparues comme sensibles à la montée du niveau de la mer. Dans une hiérarchie de scénarios de montée du niveau de la mer représentatifs de l'évolution attendue au 21ème siècle, nous avons conclu que l'amplitude de marée devrait augmenter significativement avec la montée du niveau de la mer, à la fois dans le Sud-Ouest et dans le Sud-Est du delta. Au contraire, l'extension graduelle et massive de la superficie des estrans dans la partie centrale du delta devrait induire une nette atténuation de la marée, dans ces scénarios futurs. La marée joue par ailleurs un rôle central dans l'évolution des surcotes cyloniques. Un exercice de prévision du dernier super-cyclone ayant frappé le delta du Bengale avec notre plate-forme de modélisation hydrodynamique couplée marée-surcote-vagues a révélé la nécessité du couplage dynamique entre ces trois composantes de la submersion, et nous avons pu confirmer le rôle-clé de la topographie côtière dans le succès des prévisions numériques. Grâce à une approche ensembliste basée sur la simulation numérique hydrodynamique de plusieurs milliers de cyclones synthétiques, cohérents tant du point de vue de la physique que de la statistique, nous avons pu conclure qu'il y a à l'heure actuelle de l'ordre de 10% de la population côtière du delta, soit trois millions de personnes, résidant dans la zone exposée à la submersion cinquentennale. La compréhension et la quantification des mécanismes de l'inondation exposés dans cette thèse constituent une information pertinente pour contribuer à l'ingénierie des infrastructures côtières, à la gestion du risque, ainsi qu'à l'élaboration de l'agenda de la recherche en hydrodynamique côtière sur le delta du Bengale.The Bengal delta is the largest in the world. It is formed by the confluence of three transboundary rivers - Ganges, Brahmaputra, and Meghna. Flooding induced by large seasonal continental discharge, strong tide, and frequent deadly storm surges, regularly strikes this densely populated (density > 1000 person/km2), low-lying coastal region (<5 m above mean sea level). In the last five decades, coastal flooding took more than half a million lives. Ongoing global sea level rise (SLR) will only further aggravate the vulnerability of this impoverished region. Along the shoreline, intertidal zones are the first landmass that gets flooded, periodically between each high- and low-tide. Their topography plays an important role in the coastal hydrodynamics and associated flooding during extremes. A synergy between remote sensing from Sentinel-2 constellation and tidal numerical modelling allowed us to map an intertidal area of 1134 km2 and its topography at 10 m resolution. Tides, that prominently drive the variability of coastal sea level, are shown to be sensitive to SLR. In future SLR scenarios in line with the 21st century forecasts, we found that the tidal amplitude will significantly increase with SLR over both the south-western and south-eastern parts of the delta. In contrast, the central part of the delta will potentially experience massive free-flooding of river banks, hereby inducing a decay of the tidal amplitude. Tide plays a vital role in the evolution of storm surges also. Hindcast simulation of a recent super cyclone with our coupled tide-surge-wave model reveals the necessity of the coupling between tide, surge and wave modelling, and confirmed the crucial role played by the coastal topography for effective inundation modelling and forecast. With an ensemble forecast of thousands of physically and statistically consistent synthetic cyclones, we could conclude that about 10% of the coastal population of the Bengal delta, amounting to 3 million people, currently lives exposed to the 50-year return period flooding. The understanding and quantification of the inundation mechanisms extended in this study is expected to help with coastal infrastructure engineering, risk zoning, resource allocation and future adaptation to coastal flood across the Bengal delta

Performance Evaluation of Connectivity and Capacity of Dynamic Spectrum Access Networks

Recent measurements on radio spectrum usage have revealed the abundance of under- utilized bands of spectrum that belong to licensed users. This necessitated the paradigm shift from static to dynamic spectrum access (DSA) where secondary networks utilize unused spectrum holes in the licensed bands without causing interference to the licensed user. However, wide scale deployment of these networks have been hindered due to lack of knowledge of expected performance in realistic environments and lack of cost-effective solutions for implementing spectrum database systems. In this dissertation, we address some of the fundamental challenges on how to improve the performance of DSA networks in terms of connectivity and capacity. Apart from showing performance gains via simulation experiments, we designed, implemented, and deployed testbeds that achieve economics of scale. We start by introducing network connectivity models and show that the well-established disk model does not hold true for interference-limited networks. Thus, we characterize connectivity based on signal to interference and noise ratio (SINR) and show that not all the deployed secondary nodes necessarily contribute towards the network\u27s connectivity. We identify such nodes and show that even-though a node might be communication-visible it can still be connectivity-invisible. The invisibility of such nodes is modeled using the concept of Poisson thinning. The connectivity-visible nodes are combined with the coverage shrinkage to develop the concept of effective density which is used to characterize the con- nectivity. Further, we propose three techniques for connectivity maximization. We also show how traditional flooding techniques are not applicable under the SINR model and analyze the underlying causes for that. Moreover, we propose a modified version of probabilistic flooding that uses lower message overhead while accounting for the node outreach and in- terference. Next, we analyze the connectivity of multi-channel distributed networks and show how the invisibility that arises among the secondary nodes results in thinning which we characterize as channel abundance. We also capture the thinning that occurs due to the nodes\u27 interference. We study the effects of interference and channel abundance using Poisson thinning on the formation of a communication link between two nodes and also on the overall connectivity of the secondary network. As for the capacity, we derive the bounds on the maximum achievable capacity of a randomly deployed secondary network with finite number of nodes in the presence of primary users since finding the exact capacity involves solving an optimization problem that shows in-scalability both in time and search space dimensionality. We speed up the optimization by reducing the optimizer\u27s search space. Next, we characterize the QoS that secondary users can expect. We do so by using vector quantization to partition the QoS space into finite number of regions each of which is represented by one QoS index. We argue that any operating condition of the system can be mapped to one of the pre-computed QoS indices using a simple look-up in Olog (N) time thus avoiding any cumbersome computation for QoS evaluation. We implement the QoS space on an 8-bit microcontroller and show how the mathematically intensive operations can be computed in a shorter time. To demonstrate that there could be low cost solutions that scale, we present and implement an architecture that enables dynamic spectrum access for any type of network ranging from IoT to cellular. The three main components of this architecture are the RSSI sensing network, the DSA server, and the service engine. We use the concept of modular design in these components which allows transparency between them, scalability, and ease of maintenance and upgrade in a plug-n-play manner, without requiring any changes to the other components. Moreover, we provide a blueprint on how to use off-the-shelf commercially available software configurable RF chips to build low cost spectrum sensors. Using testbed experiments, we demonstrate the efficiency of the proposed architecture by comparing its performance to that of a legacy system. We show the benefits in terms of resilience to jamming, channel relinquishment on primary arrival, and best channel determination and allocation. We also show the performance gains in terms of frame error rater and spectral efficiency

Skylab/EREP application to ecological, geological, and oceanographic investigations of Delaware Bay

The author has identified the following significant results. Skylab/EREP S190A and S190B film products were optically enhanced and visually interpreted to extract data suitable for mapping coastal land use; inventorying wetlands vegetation; monitoring tidal conditions; observing suspended sediment patterns; charting surface currents; locating coastal fronts and water mass boundaries; monitoring industrial and municipal waste dumps in the ocean; and determining the size and flow direction of river, bay, and man-made discharge plumes. Film products were visually analyzed to identify and map ten land use and vegetation categories at a scale of 1:125,000. Thematic maps were compared with CARETS land use maps, resulting in classification accuracies of 50 to 98%. Digital tapes from S192 were used to prepare thematic land use maps. The resolutions of the S190A, S190B, and S192 systems were 20-40m, 10-20m, and 70-100m, respectively

Scoring, selecting, and developing physical impact models for multi-hazard risk assessment

This study focuses on scoring, selecting, and developing physical fragility (i.e., the probability of reaching or exceeding a certain DS given a specific hazard intensity) and/or vulnerability (i.e., the probability of impact given a specific hazard intensity) models for assets, with particular emphasis on buildings. Given a set of multiple relevant hazards for a selected case-study region, the proposed procedure involves 1) mapping the relevant asset classes (i.e., construction types for a given occupancy) in the region to a set of existing candidate fragility, vulnerability and/or damage-to-impact models, also accounting for specific modelling requirements (e.g., time dependency due to ageing/deterioration of buildings, multi-hazard interactions); 2) scoring the candidate models according to relevant criteria to select the most suitable ones for a given application; or 3) using state-of-the-art numerical or empirical methods to develop fragility/vulnerability models not already available. The approach is demonstrated for the buildings of the virtual urban testbed “Tomorrowville”, considering earthquakes, floods, and debris flows as case-study hazards

Modelling Coastal Vulnerability: An integrated approach to coastal management using Earth Observation techniques in Belize

This thesis presents an adapted method to derive coastal vulnerability through the application of Earth Observation (EO) data in the quantification of forcing variables. A modelled assessment for vulnerability has been produced using the Coastal Vulnerability Index (CVI) approach developed by Gornitz (1991) and enhanced using Machine learning (ML) clustering. ML has been employed to divide the coastline based on the geotechnical conditions observed to establish relative vulnerability. This has been demonstrated to alleviate bias and enhanced the scalability of the approach – especially in areas with poor data coverage – a known hinderance to the CVI approach (Koroglu et al., 2019).Belize provides a demonstrator for this novel methodology due to limited existing data coverage and the recent removal of the Mesoamerican Reef from the International Union for Conservation of Nature (IUCN) List of World Heritage In Danger. A strong characterization of the coastal zone and associated pressures is paramount to support effective management and enhance resilience to ensure this status is retained.Areas of consistent vulnerability have been identified using the KMeans classifier; predominantly Caye Caulker and San Pedro. The ability to automatically scale to conditions in Belize has demonstrated disparities to vulnerability along the coastline and has provided more realistic estimates than the traditional CVI groups. Resulting vulnerability assessments have indicated that 19% of the coastline at the highest risk with a seaward distribution to high risk observed. Using data derived using Sentinel-2, this study has also increased the accuracy of existing habitat maps and enhanced survey coverage of uncharted areas.Results from this investigation have been situated within the ability to enhance community resilience through supporting regional policies. Further research should be completed to test the robust nature of this model through an application in regions with different geographic conditions and with higher resolution input datasets

Skylab/EREP application to ecological, geological, and oceanographic investigations of Delaware Bay

Skylab/EREP S190A and S190B film products were optically enhanced and visually interpreted to extract data suitable for; (1) mapping coastal land use; (2) inventorying wetlands vegetation; (3) monitoring tidal conditions; (4) observing suspended sediment patterns; (5) charting surface currents; (6) locating coastal fronts and water mass boundaries; (7) monitoring industrial and municipal waste dumps in the ocean; (8) determining the size and flow direction of river, bay and man-made discharge plumes; and (9) observing ship traffic. Film products were visually analyzed to identify and map ten land-use and vegetation categories at a scale of 1:125,000. Digital tapes from the multispectral scanner were used to prepare thematic maps of land use. Classification accuracies obtained by comparison of derived thematic maps of land-use with USGS-CARETS land-use maps in southern Delaware ranged from 44 percent to 100 percent