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  • Animals
  • Electronic structure and strongly correlated systems
  • uncertainty
  • 2020-2022  (5)
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  • 1
    Publication Date: 2021-07-24
    Description: Hydrometeorological hazards caused losses of approximately 110 billion U.S. Dollars in 2016 worldwide. Current damage estimations do not consider the uncertainties in a comprehensive way, and they are not consistent between spatial scales. Aggregated land use data are used at larger spatial scales, although detailed exposure data at the object level, such as openstreetmap.org, is becoming increasingly available across the globe. We present a probabilistic approach for object-based damage estimation which represents uncertainties and is fully scalable in space. The approach is applied and validated to company damage from the flood of 2013 in Germany. Damage estimates are more accurate compared to damage models using land use data, and the estimation works reliably at all spatial scales. Therefore, it can as well be used for pre-event analysis and risk assessments. This method takes hydrometeorological damage estimation and risk assessments to the next level, making damage estimates and their uncertainties fully scalable in space, from object to country level, and enabling the exploitation of new exposure data.
    Keywords: 551.489 ; spatial scales ; risk assessment ; hydro-meteorological hazards ; object-based damage modeling ; uncertainty ; probabilistic approaches
    Language: English
    Type: article
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  • 2
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    University of Tasmania, School of Government
    In:  http://aquaticcommons.org/id/eprint/3328 | 424 | 2011-09-29 17:36:03 | 3328
    Publication Date: 2021-06-27
    Description: “Why does overfishing persist in the face of regulation?” The author argues that over fishing,a fundamental cause of the crisis facing our oceans, is the result of the failure of our fishing management agencies (ultimately our politicians and communities) to embrace a small suite of powerful tools (more correctly strategic approaches) which have been developed to account for uncertainty.Broad success in managing fisheries to achieve sustainability goals will only come if these tools are enthusiastically applied. This will not happen until organisational cultures within fishery management agencies undergo a major shift leading to an asset-based biodiversity conservation, rather than resource exploitation, to be placed at the centre of ocean governance.This thesis examines these issues in the context of case studies covering regional, national and provincial (State) fishery management agencies. With the exception of the case study of a regional fishery (the southern ocean krill fishery) all case studies are drawn from Australianexperiences. The central recommendation of the thesis is that fishery management agencies, worldwide, should be replaced by biodiversity asset management agencies.
    Description: PhD
    Keywords: Fisheries ; Australia ; ocean governance ; overfishing ; uncertainty ; precautionary principle ; precautionary approach ; ecosystem approach ; adaptive management ; krill ; orange roughy ; northern prawns ; western rock lobster ; abalone ; spearfishing
    Repository Name: AquaDocs
    Type: thesis
    Format: application/pdf
    Format: application/pdf
    Format: 440
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  • 3
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    Publication Date: 2021-07-21
    Description: The rapidly growing amount and diversity of data are confronting us more than ever with the need to make informed predictions under uncertainty. The adverse impacts of climate change and natural hazards also motivate our search for reliable predictions. The range of statistical techniques that geomorphologists use to tackle this challenge has been growing, but rarely involves Bayesian methods. Instead, many geomorphic models rely on estimated averages that largely miss out on the variability of form and process. Yet seemingly fixed estimates of channel heads, sediment rating curves or glacier equilibrium lines, for example, are all prone to uncertainties. Neighbouring scientific disciplines such as physics, hydrology or ecology have readily embraced Bayesian methods to fully capture and better explain such uncertainties, as the necessary computational tools have advanced greatly. The aim of this article is to introduce the Bayesian toolkit to scientists concerned with Earth surface processes and landforms, and to show how geomorphic models might benefit from probabilistic concepts. I briefly review the use of Bayesian reasoning in geomorphology, and outline the corresponding variants of regression and classification in several worked examples. © 2020 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd
    Keywords: 551.41 ; 550.285 ; Bayes' rule ; probability ; uncertainty ; prediction
    Language: English
    Type: article
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  • 4
    Publication Date: 2021-10-01
    Description: The distribution of German household environmental footprints (EnvFs) across income groups is analyzed by using EXIOBASE v3.6 and the consumer expenditure survey of 2013. Expenditure underreporting is corrected by using a novel method, where the expenditures are modeled as truncated normal distribution. The focus lies on carbon (CF) and material (MF) footprints, which for average German households are 9.1 ± 0.4 metric tons CO2e and 10.9 ± 0.6 metric tons material per capita. Although the lowest-income group has the lowest share of transportation in EnvFs, at 10.4% (CF) and 3.9% (MF), it has the highest share of electricity and utilities in EnvFs, at 39.4% (CF) and 16.7% (MF). In contrast, the highest-income group has the highest share of transportation in EnvFs, at 20.3% (CF) and 12.4% (MF). The highest-income group has a higher share of emissions produced overseas (38.6% vs. 34.3%) and imported resource use (69.9% vs. 66.4%) compared to the average households. When substituting 50% of imported goods with domestic ones in a counterfactual scenario, this group only decreases its CF by 2.8% and MF by 5.3%. Although incomes in Germany are distributed more equally (Gini index 0.28), the German household CF is distributed less equally (0.16). A uniform carbon tax across all sectors would be regressive (Suits index −0.13). Hence, a revenue recycling scheme is necessary to alleviate the burden on low-income households. The overall carbon intensity shows an inverted-U trend due to the increasing consumption of carbon-intensive heating for lower-income groups, indicating a possible rebound effect for these groups. This article met the requirements for a gold – gold JIE data openness badge described at http://jie.click/badges.
    Keywords: 363.7 ; carbon footprint ; carbon tax ; industrial ecology ; inequality ; input–output analysis (IOA) ; uncertainty
    Language: English
    Type: map
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  • 5
    Publication Date: 2020-11-12
    Description: Earthquake hypocentral location is perhaps the most classical problem in seismology, the solution of which is often affected by significant uncertainty. In monitoring the effects of underground anthropogenic activities, the earthquake hypocentral location, magnitude, and ground motions are important parameters for managing induced seismicity (as e.g., for operating traffic‐light systems). Such decisional systems define the operative reactions to be enacted once an earthquake, exceeding some magnitude or ground‐motion threshold, occurs within a monitoring volume defined in the neighborhood of a certain anthropogenic underground activity. In this case, a reliable evaluation of the hypocentral location, along with its uncertainty, becomes crucial for rational decision making. In this article, we analyze different sources of uncertainty that can be relevant for the determination of earthquake source locations, and introduce a logic‐tree‐based ensemble modeling approach for framing the problem in a decision‐making context. To demonstrate the performance of the proposed approach, we analyze uncertainties in the location of a seismic event that occurred on 22 July 2019 within the perimeter of the monitoring domain defined in the Val d’Agri oil field (southern Italy). We cast the result as a model ensemble that allows us to obtain samples from a parent distribution that better represents both aleatory and epistemic uncertainties of the earthquake location problem. We find that often‐neglected epistemic uncertainties (i.e., those that arise when considering alternative plausible modeling approaches or data) can be considerably larger and more representative of the state of knowledge about the source location, than the standard errors usually reported by the most common algorithms. Given the consequential repercussions of decision making under uncertainty, we stress that an objective evaluation of epistemic uncertainties associated with any parameter used to support decisional processes must be a priority for the scientific community.
    Description: Centro per il Monitoraggio delle attività di Sottosuolo (CMS).
    Description: Published
    Description: 2423–2440
    Description: 3SR TERREMOTI - Attività dei Centri
    Description: JCR Journal
    Keywords: Earthquake location ; uncertainty ; Traffic light systems ; Decision making ; 04.06. Seismology
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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