Exploring the data needs and sources for severe weather impact forecasts and warnings : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Emergency Management at Massey University, Wellington, New Zealand

Figures 2.4 & 2.5 are re-used with permission.The journal articles in Appendices J, L & M are republished under respective Creative Commons licenses. Appendix K has been removed from the thesis until 1 July 2022 in accordance with the American Meteorological Society Copyright Policy, but is available open access at https://doi.org/10.1175/WCAS-D-21-0093.1Early warning systems offer an essential, timely, and cost-effective approach for mitigating the impacts of severe weather hazards. Yet, notable historic severe weather events have exposed major communication gaps between warning services and target audiences, resulting in widespread losses. The World Meteorological Organization (WMO) has proposed Impact Forecasts and Warnings (IFW) to address these communication gaps by bringing in knowledge of exposure, vulnerability, and impacts; thus, leading to warnings that may better align with the position, needs, and capabilities of target audiences. A gap was identified in the literature around implementing IFWs: that of accessing the required knowledge and data around impacts, vulnerability, and exposure. This research aims to address this gap by exploring the data needs of IFWs and identifying existing and potential data sources to support those needs. Using Grounded Theory (GT), 39 interviews were conducted with users and creators of hazard, impact, vulnerability, and exposure (HIVE) data within and outside of Aotearoa New Zealand. Additionally, three virtual workshops provided triangulation with practitioners. In total, 59 people participated in this research. Resulting qualitative data were analysed using GT coding techniques, memo-writing, and diagramming. Findings indicate a growing need for gathering and using impact, vulnerability, and exposure data for IFWs. New insight highlights a growing need to model and warn for social and health impacts. Findings further show that plenty of sources for HIVE data are collected for emergency response and other uses with relevant application to IFWs. Partnerships and collaboration lie at the heart of using HIVE data both for IFWs and for disaster risk reduction. This thesis contributes to the global understanding of how hydrometeorological and emergency management services can implement IFWs, by advancing the discussion around implementing IFWs as per the WMO’s guidelines, and around building up disaster risk data in accordance with the Sendai Framework Priorities. An important outcome of this research is the provision of a pathway for stakeholders to identify data sources and partnerships required for implementing a hydrometeorological IFW system

Risk assessment of groundwater contamination from hydraulic fracturing fluid spills in Pennsylvania

Thesis (S.M. in Technology and Policy)-- Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 109-115).Fast-paced growth in natural gas production in the Marcellus Shale has fueled intense debate over the risk of groundwater contamination from hydraulic fracturing and the shale gas extraction process at large. While several notable incidents of groundwater contamination near shale gas wells have been investigated, the exact causes are uncertain and widely disputed. One of the most frequently occurring and widely reported environmental incidents from shale gas development is that of surface spills. Several million gallons of fluid are managed on each well site; significant risk for spill exists at several stages in the extraction process. While surface spills have been primarily analyzed from the perspective of surface water contamination, spills also have the potential to infiltrate groundwater aquifers. This thesis develops a risk assessment framework to analyze the risk of groundwater resource contamination in Pennsylvania from surface spills of hydraulic fracturing fluid. It first identifies the major sources of spills and characterizes the expected frequency and volume distribution of spills from these sources using results from a preliminary expert elicitation. It then develops a stochastic groundwater contaminant transport model to analyze the worst-case potential for groundwater contamination in local water wells. Finally, it discusses the range of risk perception and incentives from a wide-ranging stakeholder base, including industry, communities, environmentalists, and government. This thesis concludes that while the vast majority of shale gas operations do not result in large spills, the worst-case potential for groundwater contamination is high enough to warrant further attention; it also recommends increased inclusion of community stakeholders in both industry and government risk management strategies.by Sarah Marie Fletcher.S.M.in Technology and Polic

Rethinking Environmentally Induced Displacement in the Global North (pubblicazione integrale della tesi di dottorato)

This research investigates how the environmentally induced displacement phenomenon is perceived in the Global North on the basis of the evidence gathered in in two Italian catatsrophes. An analysis on the environmental resources management and the vulnerability in Italy has been associated with a study over media coverage, political discourses and personal experiences about environmentally induced displacements following the two landslides in Sarno (1998) and Cerzeto (2005), highlighting the limits of the use of this concept. Moreover, this research illustrated how, contrarily to the current debate, the phenomenon is likely to occur both in the Global North and Global South contexts. The theoretical, political and media discourses and representations seem to be, in fact, mostly focused on specific geographical areas of the Global South. The motivations behind these different descriptions and narratives on the same concept are investigated, through geographical and political science tools. The findings of this research reveal a political agenda exploiting the debate to reinforce the power unbalance within the Global North and between the Global North and the Global South

Monitoring radionuclides in beach discharges: a new perspective on coastal groundwater risk near a UK nuclear site

Observations of radioactivity from beach springs over a period of four decades provides insights into field scale characteristics of a migrating tritium groundwater plume from the oldest UK nuclear site at Sellafield, in Cumbria. The utility of high resolution spatial and decades long temporal tritium coastal discharge data is demonstrated as an indicator tracer of groundwater flows and radionuclide fate to coastal environmental receptors. Data mined from as far back as 1975 is presented to be of historical significance as one of the earliest unpublished radionuclide contaminant plume investigations in the coastal environment. New field data is presented for tritium activity in beach springs and delineates a distinct asymmetric groundwater plume discharge footprint stretching 2600 metres northwards of the site along the foreshore. The spatial distribution of the tritium is further to the north-west than predicted by the Sellafield Ltd conceptual model and extends beyond the perimeter of the current site groundwater monitoring well network. The spatial footprint was further confirmed by additional sample analysis for technetium-99 with similar contributing source areas. The results of the project suggest that the groundwater flow regime to the north-west of the nuclear site is highly complex and narrow plume contaminant contributions are from more than one source, merging and surfacing in low flow beach springs in the intertidal zone. It is recommended that nuclear sites located near the coast should adopt this simple and inexpensive beach spring monitoring practice as a useful spatial and temporal diagnostic tool at the field scale. This method is complimentary to traditional groundwater monitoring wells and has improved far-field conceptualisation of contaminant sources and resultant pathways to the beach springs and concluded low risk levels to the coastal region (as of 2018)

Investigating groundwater governance arrangements for unconventional gas exploration and production in main Karoo Basin, South Africa

Magister Scientiae - MSc (Environ & Water Science)South Africa relies on coal and imported crude oil for most of its energy. The possible production of shale gas in the main Karoo Basin of South Africa provides a potential opportunity to diversify the primary energy mix. However, shale gas exploration and production is associated with environmental impacts that include potential groundwater contamination. Protecting groundwater resources involves an effective governance regime in place to regulate such risks on groundwater resources. This study made use of a qualitative approach to investigate groundwater governance arrangements in relation to the proposed shale gas development. Further, the study developed and used an analytical framework to assess groundwater governance provisions and capacity at local level for shale gas development

A Deep Learning approach for monitoring severe rainfall in urban catchments using consumer cameras. Models development and deployment on a case study in Matera (Italy) Un approccio basato sul Deep Learning per monitorare le piogge intense nei bacini urbani utilizzando fotocamere generiche. Sviluppo e implementazione di modelli su un caso di studio a Matera (Italia)

In the last 50 years, flooding has figured as the most frequent and widespread natural disaster globally. Extreme precipitation events stemming from climate change could alter the hydro-geological regime resulting in increased flood risk. Near real-time precipitation monitoring at local scale is essential for flood risk mitigation in urban and suburban areas, due to their high vulnerability. Presently, most of the rainfall data is obtained from ground‐based measurements or remote sensing that provide limited information in terms of temporal or spatial resolution. Other problems may be due to the high costs. Furthermore, rain gauges are unevenly spread and usually placed away from urban centers. In this context, a big potential is represented by the use of innovative techniques to develop low-cost monitoring systems. Despite the diversity of purposes, methods and epistemological fields, the literature on the visual effects of the rain supports the idea of camera-based rain sensors but tends to be device-specific. The present thesis aims to investigate the use of easily available photographing devices as rain detectors-gauges to develop a dense network of low-cost rainfall sensors to support the traditional methods with an expeditious solution embeddable into smart devices. As opposed to existing works, the study focuses on maximizing the number of image sources (like smartphones, general-purpose surveillance cameras, dashboard cameras, webcams, digital cameras, etc.). This encompasses cases where it is not possible to adjust the camera parameters or obtain shots in timelines or videos. Using a Deep Learning approach, the rainfall characterization can be achieved through the analysis of the perceptual aspects that determine whether and how a photograph represents a rainy condition. The first scenario of interest for the supervised learning was a binary classification; the binary output (presence or absence of rain) allows the detection of the presence of precipitation: the cameras act as rain detectors. Similarly, the second scenario of interest was a multi-class classification; the multi-class output described a range of quasi-instantaneous rainfall intensity: the cameras act as rain estimators. Using Transfer Learning with Convolutional Neural Networks, the developed models were compiled, trained, validated, and tested. The preparation of the classifiers included the preparation of a suitable dataset encompassing unconstrained verisimilar settings: open data, several data owned by National Research Institute for Earth Science and Disaster Prevention - NIED (dashboard cameras in Japan coupled with high precision multi-parameter radar data), and experimental activities conducted in the NIED Large Scale Rainfall Simulator. The outcomes were applied to a real-world scenario, with the experimentation through a pre-existent surveillance camera using 5G connectivity provided by Telecom Italia S.p.A. in the city of Matera (Italy). Analysis unfolded on several levels providing an overview of generic issues relating to the urban flood risk paradigm and specific territorial questions inherent with the case study. These include the context aspects, the important role of rainfall from driving the millennial urban evolution to determining present criticality, and components of a Web prototype for flood risk communication at local scale. The results and the model deployment raise the possibility that low‐cost technologies and local capacities can help to retrieve rainfall information for flood early warning systems based on the identification of a significant meteorological state. The binary model reached accuracy and F1 score values of 85.28% and 0.86 for the test, and 83.35% and 0.82 for the deployment. The multi-class model reached test average accuracy and macro-averaged F1 score values of 77.71% and 0.73 for the 6-way classifier, and 78.05% and 0.81 for the 5-class. The best performances were obtained in heavy rainfall and no-rain conditions, whereas the mispredictions are related to less severe precipitation. The proposed method has limited operational requirements, can be easily and quickly implemented in real use cases, exploiting pre-existent devices with a parsimonious use of economic and computational resources. The classification can be performed on single photographs taken in disparate conditions by commonly used acquisition devices, i.e. by static or moving cameras without adjusted parameters. This approach is especially useful in urban areas where measurement methods such as rain gauges encounter installation difficulties or operational limitations or in contexts where there is no availability of remote sensing data. The system does not suit scenes that are also misleading for human visual perception. The approximations inherent in the output are acknowledged. Additional data may be gathered to address gaps that are apparent and improve the accuracy of the precipitation intensity prediction. Future research might explore the integration with further experiments and crowdsourced data, to promote communication, participation, and dialogue among stakeholders and to increase public awareness, emergency response, and civic engagement through the smart community idea.Negli ultimi 50 anni, le alluvioni si sono confermate come il disastro naturale più frequente e diffuso a livello globale. Tra gli impatti degli eventi meteorologici estremi, conseguenti ai cambiamenti climatici, rientrano le alterazioni del regime idrogeologico con conseguente incremento del rischio alluvionale. Il monitoraggio delle precipitazioni in tempo quasi reale su scala locale è essenziale per la mitigazione del rischio di alluvione in ambito urbano e periurbano, aree connotate da un'elevata vulnerabilità. Attualmente, la maggior parte dei dati sulle precipitazioni è ottenuta da misurazioni a terra o telerilevamento che forniscono informazioni limitate in termini di risoluzione temporale o spaziale. Ulteriori problemi possono derivare dagli elevati costi. Inoltre i pluviometri sono distribuiti in modo non uniforme e spesso posizionati piuttosto lontano dai centri urbani, comportando criticità e discontinuità nel monitoraggio. In questo contesto, un grande potenziale è rappresentato dall'utilizzo di tecniche innovative per sviluppare sistemi inediti di monitoraggio a basso costo. Nonostante la diversità di scopi, metodi e campi epistemologici, la letteratura sugli effetti visivi della pioggia supporta l'idea di sensori di pioggia basati su telecamera, ma tende ad essere specifica per dispositivo scelto. La presente tesi punta a indagare l'uso di dispositivi fotografici facilmente reperibili come rilevatori-misuratori di pioggia, per sviluppare una fitta rete di sensori a basso costo a supporto dei metodi tradizionali con una soluzione rapida incorporabile in dispositivi intelligenti. A differenza dei lavori esistenti, lo studio si concentra sulla massimizzazione del numero di fonti di immagini (smartphone, telecamere di sorveglianza generiche, telecamere da cruscotto, webcam, telecamere digitali, ecc.). Ciò comprende casi in cui non sia possibile regolare i parametri fotografici o ottenere scatti in timeline o video. Utilizzando un approccio di Deep Learning, la caratterizzazione delle precipitazioni può essere ottenuta attraverso l'analisi degli aspetti percettivi che determinano se e come una fotografia rappresenti una condizione di pioggia. Il primo scenario di interesse per l'apprendimento supervisionato è una classificazione binaria; l'output binario (presenza o assenza di pioggia) consente la rilevazione della presenza di precipitazione: gli apparecchi fotografici fungono da rivelatori di pioggia. Analogamente, il secondo scenario di interesse è una classificazione multi-classe; l'output multi-classe descrive un intervallo di intensità delle precipitazioni quasi istantanee: le fotocamere fungono da misuratori di pioggia. Utilizzando tecniche di Transfer Learning con reti neurali convoluzionali, i modelli sviluppati sono stati compilati, addestrati, convalidati e testati. La preparazione dei classificatori ha incluso la preparazione di un set di dati adeguato con impostazioni verosimili e non vincolate: dati aperti, diversi dati di proprietà del National Research Institute for Earth Science and Disaster Prevention - NIED (telecamere dashboard in Giappone accoppiate con dati radar multiparametrici ad alta precisione) e attività sperimentali condotte nel simulatore di pioggia su larga scala del NIED. I risultati sono stati applicati a uno scenario reale, con la sperimentazione attraverso una telecamera di sorveglianza preesistente che utilizza la connettività 5G fornita da Telecom Italia S.p.A. nella città di Matera (Italia). L'analisi si è svolta su più livelli, fornendo una panoramica sulle questioni relative al paradigma del rischio di alluvione in ambito urbano e questioni territoriali specifiche inerenti al caso di studio. Queste ultime includono diversi aspetti del contesto, l'importante ruolo delle piogge dal guidare l'evoluzione millenaria della morfologia urbana alla determinazione delle criticità attuali, oltre ad alcune componenti di un prototipo Web per la comunicazione del rischio alluvionale su scala locale. I risultati ottenuti e l'implementazione del modello corroborano la possibilità che le tecnologie a basso costo e le capacità locali possano aiutare a caratterizzare la forzante pluviometrica a supporto dei sistemi di allerta precoce basati sull'identificazione di uno stato meteorologico significativo. Il modello binario ha raggiunto un'accuratezza e un F1-score di 85,28% e 0,86 per il set di test e di 83,35% e 0,82 per l'implementazione nel caso di studio. Il modello multi-classe ha raggiunto un'accuratezza media e F1-score medio (macro-average) di 77,71% e 0,73 per il classificatore a 6 vie e 78,05% e 0,81 per quello a 5 classi. Le prestazioni migliori sono state ottenute nelle classi relative a forti precipitazioni e assenza di pioggia, mentre le previsioni errate sono legate a precipitazioni meno estreme. Il metodo proposto richiede requisiti operativi limitati, può essere implementato facilmente e rapidamente in casi d'uso reali, sfruttando dispositivi preesistenti con un uso parsimonioso di risorse economiche e computazionali. La classificazione può essere eseguita su singole fotografie scattate in condizioni disparate da dispositivi di acquisizione di uso comune, ovvero da telecamere statiche o in movimento senza regolazione dei parametri. Questo approccio potrebbe essere particolarmente utile nelle aree urbane in cui i metodi di misurazione come i pluviometri incontrano difficoltà di installazione o limitazioni operative o in contesti in cui non sono disponibili dati di telerilevamento o radar. Il sistema non si adatta a scene che sono fuorvianti anche per la percezione visiva umana. I limiti attuali risiedono nelle approssimazioni intrinseche negli output. Per colmare le lacune evidenti e migliorare l'accuratezza della previsione dell'intensità di precipitazione, sarebbe possibile un'ulteriore raccolta di dati. Sviluppi futuri potrebbero riguardare l'integrazione con ulteriori esperimenti in campo e dati da crowdsourcing, per promuovere comunicazione, partecipazione e dialogo aumentando la resilienza attraverso consapevolezza pubblica e impegno civico in una concezione di comunità smart

Global water: issues and insights

This book brings together some of the world’s leading water researchers with an especially written collection of chapters on: water economics; transboundary water; water and development; water and energy; and water concepts. Introduction Freshwater governance holds a prominent position in the global policy agenda. Burgeoning water demand due to population growth and rising incomes is combining with supply-side pressures, such as environmental pollution and climate change, to create acute conditions of global water scarcity. This is a major concern because water is a primary input for agriculture, manufacturing, environmental health, human health, energy production and just about every economic sector and ecosystem. In addition to its importance, the management of freshwater resources is a complex, multidisciplinary topic. Encompassing a range of fields in the physical and social sciences, the task of sustainably meeting human and environmental water needs requires a depth and breadth of understanding unparalleled by most other policy problems. Our objective in this volume is to provide knowledge and insights into major issues and concepts related to freshwater governance. The book is divided into five themed parts: Economics, Transboundary governance, Development, Energy and Water Concepts. A part addresses each theme and opens with an introduction that provides an overview of key topics. For example, the introduction to the economics section presents two main foci: measuring the value of water and managing trade-offs between different water uses. The thematic case studies discuss issues such as water pricing in Organisation for Economic Co-operation and Development (OECD) countries, finance of water supply and irrigation infrastructure and improving agricultural production with enhanced water management. The aim of the volume is to accessibly communicate academic research from the many fields of freshwater governance. Too often, academic research is paywalled and/or written in a style that caters to colleagues in the same field, rather than a broader audience from other disciplines, the policy-making community and the general public. This open-access book presents the research of a range of global experts on freshwater governance in brief, insightful chapters that do not presume a high level of pre-existing knowledge of their respective subjects. This format is intended to present knowledge on the key problems of and solutions to global freshwater challenges. The final part presents research from several United Nations Educational, Social, and Cultural Organisation (UNESCO) supported water research Chairs and Centres. Support and coordination of the insititutions highlighted in this part of the book is provided by UNESCO. One water research Chair is The Australian National University – UNESCO Chair in Water Economics and Transboundary Governance, which was established in April 2010 and works with partners in southern Africa, UNESCO, the Global Water Partnership and other organisations to: (1) increase the skills, capacity, networks and potential of leaders and prospective water managers and policy-makers; (2) sustain and strengthen institutional capacity (especially in southern Africa) by providing a platform for collaboration and institutional development; and, (3) develop innovative research, tools, case-studies, and insights on water economics, water governance and equity. Established by the ANU–UNESCO Chair, the Global Water Forum (GWF) seeks to disseminate knowledge regarding freshwater governance and build the capacity of students, policy-makers and the general public to respond to local and global water issues. The GWF publishes accessible, subscription-free articles highlighing the latest research and practice concerning freshwater governance. A broad range of water-related topics are discussed in a non-technical manner, including water security, development, agriculture, energy and environment. In addition to publishing articles, reports and books, the GWF is engaged in a range of activities, such as the annual Emerging Scholars Award and hosting a portal to educational resources on freshwater. We hope that you enjoy reading this book and, more importantly, gain an improved understanding of the complex freshwater-governance challenges facing us all on a global scale and at a local level

Decision Making of Environmental Engineers on Project Selection

Some environmental engineers do not understand how to perceive profitable opportunities in redeveloping the large number of contaminated brownfield sites in New Jersey. The purpose of this qualitative exploratory case study was to find effective decision-making strategies that help environmental engineers acquire profitable environmental redevelopment projects. The target population consisted of 4 environmental engineers in an environmental organization in Camden County, New Jersey who possessed proven decision-making strategies that helped them acquire profitable environmental redevelopment projects in the past 5 years. The conceptual framework for this study was the multiple criteria decision method (MCDM). Semistructured interviews were conducted with the engineers, and company documents were additional sources of data gathered. Triangulation and member checking were used to ensure the trustworthiness of interpretations. Five themes emerged from the analyses relating to strategies for an MCDM assessment in project management, a go/no-go assessment in project selections, education and training, ethics as an organizational value, and project management. These findings may lead to social change in Camden County, New Jersey community organizations, such as schools, daycare centers, and local businesses, which may benefit from the knowledge and safety recommendations of remediation decision making. Furthermore, these findings may provide opportunities for environment organizations to teach and train stakeholders on environmental processes while providing profitable opportunities to shareholders through sustainable practices

STUK’s statement and safety assessment on the construction of the Olkiluoto encapsulation plant and disposal facility for spent nuclear fuel

Summary Posiva submitted the construction licence application for the encapsulation plant and the disposal facility in Olkiluoto to the Ministry of Employment and the Economy (MEE) in December 2012. The MEE requested from Radiation and Nuclear Safety Authority (STUK) a statement required by the Nuclear Energy Act section 23 and a safety assessment report required by the Nuclear Energy Decree section 36 in February 2013. This publication presents STUK’s statement, safety assessment report and the statement from the nuclear safety advisory board as required by the Nuclear Energy Decree section 37. The statement was submitted to the MEE in February 2015. STUK’s safety assessment report and statement are based on the review of construction licence technical documentation and on the inspection programme carried out during the review. Based on the review STUK accepted Posiva’s preliminary safety analysis report, post closure safety case, probabilistic risk assessment of the design stage, proposal for a classification document, description of quality management during the construction of the nuclear facility, preliminary plans for the arrangements for security and emergencies, a plan for arranging the safeguards control that is necessary to prevent the proliferation of nuclear weapons, and the applicant’s arrangements for the implementation of regulatory oversight by STUK. The inspection programme focused on Posiva’s safety culture, organization, management system, resources, competence and procedures. Inspections in accordance with the programme were extended also to Posiva’s suppliers. In STUK’s safety assessment report and statement STUK concludes that, based on Posiva’s construction licence application documentation, the encapsulation plant and the disposal facility for spent nuclear fuel proposed by Posiva can be constructed to be safe. Radiation doses for workers and local residents arising from the operation of the encapsulation plant and the disposal facility will be below the limits given in legislation with high probability. After the closure of the disposal facility radiation exposure for local residents and other biosphere will fall below the regulatory limits with high probability. As part of the radiation and nuclear safety review STUK assessed that Posiva’s organization, management system, resources, arrangements for security, emergency preparedness and safeguards are at a sufficient level, so that the project can be carried out safely.1. paino