WebGIS as boundary tools between scientific geoinformation and disaster risk reduction action in volcanic areas

As the amount of spatial data is growing, there is increased interest in developing tools to explore, visualize and interpret them, with the final aim of informing decision making efficiently. Within the European MIAVITA project, we examined this issue in the case of volcanic areas, where existing geospatial databases are particularly complex due to the number of threats to be considered, including volcanic (e.g. lava flows, ash fall) and non-volcanic hazards, such as landslides or tsunamis. We involved a group of hazard and risk analysts and managers, civil security officers, GIS analysts and system developers to design a Web-based geographical information system (WebGIS). We tested the system at the Mount Cameroon volcano, taking advantage of a complex hazard and risk geographical database. This study enabled identifying key requirements for such tools in volcanic areas, such as the need to manage user privileges differently according to their profile and the status of the volcano. This work also highlights that, in addition to the development of large geoinformation clearinghouses, there is a need for site-specific information systems focused on working procedures of users, in order to fill the last gap between data producers and users

A method for multi-hazard mapping in poorly known volcanic areas: an example from Kanlaon (Philippines)

Hazard mapping in poorly known volcanic areas is complex since much evidence of volcanic and non-volcanic hazards is often hidden by vegetation and alteration. In this paper, we propose a semi-quantitative method based on hazard event tree and multi-hazard map constructions developed in the frame of the FP7 MIAVITA project. We applied this method to the Kanlaon volcano (Philippines), which is characterized by poor geologic and historical records. We combine updated geological (long-term) and historical (short-term) data, building an event tree for the main types of hazardous events at Kanlaon and their potential frequencies. We then propose an updated multi-hazard map for Kanlaon, which may serve as a working base map in the case of future unrest. The obtained results extend the information already contained in previous volcanic hazard maps of Kanlaon, highlighting (i) an extensive, potentially active ~5 km long summit area striking north–south, (ii) new morphological features on the eastern flank of the volcano, prone to receiving volcanic products expanding from the summit, and (iii) important riverbeds that may potentially accumulate devastating mudflows. This preliminary study constitutes a basis that may help local civil defence authorities in making more informed land use planning decisions and in anticipating future risk/hazards at Kanlaon. This multi-hazard mapping method may also be applied to other poorly known active volcanoes

Preface: Approaches and methods to improve risk management in volcanic areas

Active volcanoes can generate multiple types of geological hazards. Besides syneruptive threats (e.g., lava, pyroclastic flows or ash fall), other adverse events such as landslides or lahars can occur at any time. To manage these threats efficiently, three key objectives must be jointly addressed: (1) improving prevention tools, through the collection and acquisition of data on hazards and risks, and its dissemination as maps and scenarios; (2) improving crisis management capabilities, based on monitoring and early warning systems, but also reliable communications systems; and (3) reducing people’s vulnerability and developing recovery and resilience capabilities after an event has occurred. The special issue “Approaches and methods to improve risk management in volcanic areas” presents research results focusing on these three objectives. It demonstrates the utility of addressing them jointly, and particularly examines the case of volcanoes where little knowledge is available. These results were presented at the conference Integrated Approaches for Volcanic Risk Management (Hohenheim University, Stuttgart, 11/12 September 2012) of the European MIAVITA (MItigate and Assess risk from Volcanic Impact on Terrain and human Activities) project

A method to characterize the different extreme waves for islands exposed to various wave regimes: a case study devoted to Reunion Island

This paper outlines a new approach devoted to the analysis of extreme waves in presence of several wave regimes. It entails discriminating the different wave regimes from offshore wave data using classification algorithms, before conducting the extreme wave analysis for each regime separately. The concept is applied to the pilot site of Reunion Island which is affected by three main wave regimes: southern waves, trade-wind waves and cyclonic waves. Several extreme wave scenarios are determined for each regime, based on real historical cases (for cyclonic waves) and extreme value analysis (for non-cyclonic waves). For each scenario, the nearshore wave characteristics are modelled all around Reunion Island and the linear theory equations are used to back calculate the equivalent deep-water wave characteristics for each portion of the coast. The relative exposure of the coastline to the extreme waves of each regime is determined by comparing the equivalent deep-water wave characteristics. <br><br> This method provides a practical framework to perform an analysis of extremes within a complex environment presenting several sources of extreme waves. First, at a particular coastal location, it allows for inter-comparison between various kinds of extreme waves that are generated by different processes and that may occur at different periods of the year. Then, it enables us to analyse the alongshore variability in wave exposition, which is a good indicator of potential runup extreme values. For the case of Reunion Island, cyclonic waves are dominant offshore around the island, with equivalent deep-water wave heights up to 18 m for the northern part. Nevertheless, due to nearshore wave refraction, southern waves may become as energetic as cyclonic waves on the western part of the island and induce similar impacts in terms of runup and submersion. This method can be easily transposed to other case studies and can be adapted, depending on the data availability

Uncertainties in shoreline projections to 2100 at Truc Vert Beach (France): Role of sea‐level rise and equilibrium model assumptions

Sandy shorelines morphodynamics responds to a myriad of processes interacting at different spatial and temporal scales, making shoreline predictions challenging. Shoreline modeling inherits uncertainties from the primary driver boundary conditions (e.g., sea-level rise and wave forcing) as well as uncertainties related to model assumptions and/or misspecifications of the physics. This study presents an analysis of the uncertainties associated with future shoreline evolution at the cross-shore transport dominated sandy beach of Truc Vert (France) over the 21st century. We explicitly resolve wave-driven shoreline change using two different equilibrium modeling approaches to provide new insight into the contributions of sea-level rise, and free model parameters uncertainties on future shoreline change in the frame of climate change. Based on a Global Sensitivity Analysis, shoreline response during the first half of the century is found to be mainly sensitive to the equilibrium model parameters, with the influence of sea-level rise emerging in the second half of the century (∼2050 or later), under several simulated scenarios. The results reveal that the seasonal and interannual variability of the predicted shoreline position is sensitive to the choice of the wave-driven equilibrium-based model. Finally, we discuss the importance of the chronology of wave events in future shoreline change, calling for more continuous wave projection time series to further address uncertainties in future wave conditions. Our contribution demonstrates that unmitigated climate change can result in shoreline retreat of several tens of meters by 2100, even for sectors that have been stable or slightly accreting over the last century

Climate change-driven coastal erosion modelling in temperate sandy beaches: Methods and uncertainty treatment

Developing future projections of shoreline change requires a good understanding of the driving coastal processes. These processes result primarily from the combination of mean sea level, waves, storm surges and tides, which are affected by global and regional climate change, and whose uncertainty increases with time. This paper reviews the current state of the art of methods used to model climate change-induced coastal erosion focusing on how climate change-related drivers and the associated uncertainty are considered. We identify research gaps, describe and analyse the key components of a comprehensive framework to derive future estimates of shoreline change and make suggestions for good practice. Within the scope of the review, we find that although significant progress has been made over the last decade, most of the studies limit uncertainty sampling to considering ranges of variation of forcing variables and ensembles of emissions scenarios, and applications with high level of probabilistic development remain few. Further research is necessary to fully (a) incorporate projected time series of coastal drivers into the erosion models, including bias correction; (b) sufficiently sample the uncertainty associated with each step of the top-down approach, including the consideration of different emission scenarios, inter- and intra-model variability, and multiple runs of erosion models or model ensembles; and (c) reduce uncertainty in shoreline change estimates by developing better datasets and model parameterisations, and progressing in detection and attribution

Probabilistic sea level projections at the coast by 2100

As sea level is rising along many low-lying and densely populated coastal areas, affected communities are investing resources to assess and manage future socio-economic and ecological risks created by current and future sea level rise. Despite significant progress in the scientific understanding of the physical mechanisms contributing to sea level change, projections beyond 2050 remain highly uncertain. Here, we present recent developments in the probabilistic projections of coastal mean sea level rise by 2100, which provides a summary assessment of the relevant uncertainties. Probabilistic projections can be used directly in some of the decision frameworks adopted by coastal engineers for infrastructure design and land use planning. However, relying on a single probability distribution or a set of distributions based upon a common set of assumptions can understate true uncertainty and potentially misinform users. Here, we put the probabilistic projections published over the last 5 years into context

Beliefs on the local effects of climate change: causal attribution of flooding and shoreline retreat

Adaptation to climate change is a process that should engage different participants, including not only researchers and technicians but also other stakeholders and local individuals, and, therefore, it is important to understand their beliefs on the local effects of climate change. Recent studies illustrate a linear relation between coastal distance and scepticism, which is lower in coastal zones than in inland. A possible explanation is that people living inland do not experience (or do not perceive) particular natural hazards as being caused by climate change, or attribute the natural hazards to other causes, apart from climate change. This might influence the relative importance of dealing with direct anthropogenic effects and planning adaptation to climate change. Therefore, the goal of this work was to explore this effect by comparing beliefs on the local effects of climate change in Aveiro region (Portugal), specifically in Baixo Vouga Lagunar (BVL, located in the inner side of Ria de Aveiro Coastal Lagoon, 10 km distance from the coast) with the nearby coastal zone between Esmoriz and Vagueira settlements. Stakeholders were interviewed and local individuals were surveyed in order to explore causal attributions towards relevant local environmental problems and compare with data available from the coastal zone. Natural hazards concerned flooding in BVL and shoreline retreat in the coastal zone. Results suggest that in BVL both stakeholders and local residents did not attribute local natural hazards mostly to climate change. However, in the coastal zone, local natural hazards were indeed mostly attributed to climate change. This attribution to climate change was further correlated to a higher risk perception of natural hazards in the coastal zone but not in BVL. Thereby, it is important to consider distance from the shoreline in order to promote local processes of adaptation to climate change.info:eu-repo/semantics/publishedVersio

Uncertainty and Bias in Global to Regional Scale Assessments of Current and Future Coastal Flood Risk

This study provides a literature-based comparative assessment of uncertainties and biases in global to world-regional scale assessments of current and future coastal flood risks, considering mean and extreme sea-level hazards, the propagation of these into the floodplain, people and coastal assets exposed, and their vulnerability. Globally, by far the largest bias is introduced by not considering human adaptation, which can lead to an overestimation of coastal flood risk in 2100 by up to factor 1300. But even when considering adaptation, uncertainties in how coastal societies will adapt to sea-level rise dominate with a factor of up to 27 all other uncertainties. Other large uncertainties that have been quantified globally are associated with socio-economic development (factors 2.3–5.8), digital elevation data (factors 1.2–3.8), ice sheet models (factor 1.6–3.8) and greenhouse gas emissions (factors 1.6–2.1). Local uncertainties that stand out but have not been quantified globally, relate to depth-damage functions, defense failure mechanisms, surge and wave heights in areas affected by tropical cyclones (in particular for large return periods), as well as nearshore interactions between mean sea-levels, storm surges, tides and waves. Advancing the state-of-the-art requires analyzing and reporting more comprehensively on underlying uncertainties, including those in data, methods and adaptation scenarios. Epistemic uncertainties in digital elevation, coastal protection levels and depth-damage functions would be best reduced through open community-based efforts, in which many scholars work together in collecting and validating these data