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  • 1
    Publication Date: 2022-06-16
    Description: Abstract
    Description: As the negative impacts of hydrological extremes increase in large parts of the world, a better understanding of the drivers of change in risk and impacts is essential for effective flood and drought risk management and climate adaptation. However, there is a lack of comprehensive, empirical data about the processes, interactions and feedbacks in complex human-water systems leading to flood and drought impacts. To fill this gap, we present an IAHS Panta Rhei benchmark dataset containing socio-hydrological data of paired events, i.e. two floods or two droughts that occurred in the same area (Kreibich et al. 2017, 2019). The contained 45 paired events occurred in 42 different study areas (in three study areas we have data on two paired events), which cover different socioeconomic and hydroclimatic contexts across all continents. The dataset is unique in covering floods and droughts, in the number of cases assessed and in the amount of qualitative and quantitative socio-hydrological data contained. References to the data sources are provided in 2022-002_Kreibich-et-al_Key_data_table.xlsx where possible. Based on templates, we collected detailed, review-style reports describing the event characteristics and processes in the case study areas, as well as various semi-quantitative data, categorised into management, hazard, exposure, vulnerability and impacts. Sources of the data were classified as follows: scientific study (peer-reviewed paper and PhD thesis), report (by governments, administrations, NGOs, research organisations, projects), own analysis by authors, based on a database (e.g. official statistics, monitoring data such as weather, discharge data, etc.), newspaper article, and expert judgement. The campaign to collect the information and data on paired events started at the EGU General Assembly in April 2019 in Vienna and was continued with talks promoting the paired event data collection at various conferences. Communication with the Panta Rhei community and other flood and drought experts identified through snowballing techniques was important. Thus, data on paired events were provided by professionals with excellent local knowledge of the events and risk management practices.
    Keywords: hydrological extremes ; risk dynamics ; human-flood system ; human-drought system ; socio-hydrology ; risk management ; flood ; drought ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 ENVIRONMENTAL GOVERNANCE/MANAGEMENT 〉 WATER MANAGEMENT ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 NATURAL HAZARDS 〉 DROUGHTS ; EARTH SCIENCE 〉 HUMAN DIMENSIONS 〉 NATURAL HAZARDS 〉 FLOODS ; EARTH SCIENCE SERVICES 〉 DATA ANALYSIS AND VISUALIZATION ; environmental assessment 〉 environmental risk assessment
    Type: Dataset , Dataset
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  • 2
    Publication Date: 2022-09-02
    Description: Risk management has reduced vulnerability to floods and droughts globally, yet their impacts are still increasing. An improved understanding of the causes of changing impacts is therefore needed, but has been hampered by a lack of empirical data. 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 change.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , NonPeerReviewed
    Format: application/pdf
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  • 3
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    John Wiley & Sons, Inc. | Hoboken, USA
    Publication Date: 2022-08-05
    Description: In‐depth understanding of the potential implications of climate change is required to guide decision‐ and policy‐makers when developing adaptation strategies and designing infrastructure suitable for future conditions. Impact models that translate potential future climate conditions into variables of interest are needed to create the causal connection between a changing climate and its impact for different sectors. Recent surveys suggest that the primary strategy for validating such models (and hence for justifying their use) heavily relies on assessing the accuracy of model simulations by comparing them against historical observations. We argue that such a comparison is necessary and valuable, but not sufficient to achieve a comprehensive evaluation of climate change impact models. We believe that a complementary, largely observation‐independent, step of model evaluation is needed to ensure more transparency of model behavior and greater robustness of scenario‐based analyses. This step should address the following four questions: (1) Do modeled dominant process controls match our system perception? (2) Is my model's sensitivity to changing forcing as expected? (3) Do modeled decision levers show adequate influence? (4) Can we attribute uncertainty sources throughout the projection horizon? We believe that global sensitivity analysis, with its ability to investigate a model's response to joint variations of multiple inputs in a structured way, offers a coherent approach to address all four questions comprehensively. Such additional model evaluation would strengthen stakeholder confidence in model projections and, therefore, into the adaptation strategies derived with the help of impact models.
    Description: A comprehensive evaluation of climate change impact models combining both observation‐based and response‐based strategies.
    Description: This article is categorized under: Climate Models and Modeling 〉 Knowledge Generation with Models Assessing Impacts of Climate Change 〉 Evaluating Future Impacts of Climate Change
    Description: Alexander von Humboldt‐Stiftung http://dx.doi.org/10.13039/100005156
    Description: Engineering and Physical Sciences Research Council http://dx.doi.org/10.13039/501100000266
    Keywords: ddc:551.6
    Language: English
    Type: doc-type:article
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