HEIMDALL: a technological solution for floods and multi-hazard management support

The Horizon 2020-funded project HEIMDALL (Multi-Hazard Cooperative Management Tool for Data Exchange, Response Planning and Scenario Building) aims to improve immediate and long-term collaborative strategic planning on a regional, national and international scale among affected disaster risk management and response stakeholders. Today, the collective interoperability is not sufficiently achieved during disaster events, which reduces the ability to effectively undertake planning and response actions that require collaborative working among all the stakeholders involved. To address this shortcoming, the project develops a platform that offers a wide range of tools, products and services to support decision-making processes, and in particular different activities in the response planning process for complex multi-hazard crisis situations. The platform is designed in a modular approach, using various data sources as inputs and proposing a set of services that assist command and control centres, first responders and local populations in taking risk-informed decisions during the preparedness and response phases of disaster management. Some of the core functionalities are built around the ability to integrate space-based, ground-based and aerial-based data in order to forecast and monitor floods and other disaster events, and to feed the system with operational and external data sources to provide major inputs to emergency coordination. 1 Context of the HEIMDALL Solution Managing floods and other natural and man-made disasters usually involves multiple emergency management organisations, multiple jurisdictions and even multiple countries in case of cross-border events. Following the initial disaster event, cascading effects can further amplify the degree and complexity of disaster situations. This imposes a high need and degree of crossorganisational communication and cooperation, not only during response but also in the preparedness phase, between all stakeholders (civil protection, medical services, police and fire fighting units) working at command and control centres or on the field. However, relevant studies have revealed that collective interoperability is not sufficiently achieved, which reduces the ability to perform collaborative activities, including decision making and action implementation (House et al., 2014). Moreover, information overload and uncertainty in a crisis situation hinder situation awareness and decision-making capabilities. Managing disasters begins before the disaster happens by being ready and aware of hazards, considering risks, possibilities and preventive measures, building scenarios and training. There is clearly a need to ensure efficient societal preparedness, to improve incident and emergency situation response mechanisms in order to minimise the impact on people, property, the environment, and the society as a whole. An element of this improvement should be the provision of a flexible platform for multihazard emergency planning and management to disaster risk management first responders. Such a platform makes use of innovative technologies for the definition of realistic multi-disciplinary scenarios and response plans. Developing such a tool is the ambition of the European Union’s Horizon 2020 project HEIMDALL (HEIMDALL, 2017). Budapest University of Technology and Economics (BME) In the following sections the concept of the HEIMDALL project is outlined and demonstrated within the context of flood management. 2 A Multi-Hazard Cooperative Management Platform HEIMDALL, standing for Multi-Hazard Cooperative Management Tool for Data Exchange, Response Planning and Scenario Building, aims to improve immediate and long-term collaborative strategic planning on a regional, national and international scale among the many affected disaster risk management and response stakeholders. The objective is to design and provide decision makers and other stakeholders a platform offering a wide range of tools which facilitate emergency management. In particular, HEIMDALL aims to support technically different typical response planning activities involving complex multi-hazard scenarios (Friedemann et al., 2018). The main solutions that have been designed and implemented include the: (a) support in the creation, analysis and exchange of realistic multi-disciplinary disaster scenarios, (b) provision of more, better, clearer and validated data, (c) recording of conditions, actual events and actions as the situation evolves, (d) analysis of possible futures of a situation and potential consequences to assess the effectiveness of potential working strategies and identify options and contingencies, (e) evaluation and revision of response plans based on lessons learnt from disasters, (f) interand cross-organizational communication and sharing of existing knowledge, situational information, disaster scenarios, strategies and response plans including communication to the public. Domain standards are respected where applicable. HEIMDALL results are the fruit of a wide variety of technological specialists and potential end-users collaborating. End-users from medical emergency services, police, firefighting units, civil protection, command and control centres from different organisations and countries are participating in the project. This enables the platform to address as best as possible the requirements of the different actors involved in disaster risk management. The project addresses some of the main disaster types regularly affecting European countries – floods, forest fires and landslides – including scenarios of cross-border incidents, multi-disciplinary events, interorganisational cooperation and population awareness.

[1]  Charles F. F. Karney Algorithms for geodesics , 2011, Journal of Geodesy.

[2]  Louis Anthony (Tony) Cox,et al.  Some Limitations of Qualitative Risk Rating Systems , 2005, Risk analysis : an official publication of the Society for Risk Analysis.

[3]  Roberto Rudari,et al.  EO data for rapid risk analysis with the RASOR platform , 2015, 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).

[4]  Laurence Alison,et al.  A systematic review of the potential hurdles of interoperability to the emergency services in major incidents: recommendations for solutions and alternatives , 2013, Cognition, Technology & Work.

[5]  Stefan Dech,et al.  Tsunami early warning and decision support , 2010 .

[6]  Wayne Goodridge,et al.  Sensitivity Analysis Using Simple Additive Weighting Method , 2016 .

[7]  A. Parodi,et al.  Severe hydrometeorological events in Liguria region: calibration and validation of a meteorological indices‐based forecasting operational tool , 2017 .

[8]  Fabio Castelli,et al.  Quantification of flood risk mitigation benefits: A building-scale damage assessment through the RASOR platform. , 2018, Journal of environmental management.

[9]  Margreth Keiler,et al.  Challenges of analyzing multi-hazard risk: a review , 2012, Natural Hazards.

[10]  Darren Lumbroso,et al.  FIM FRAME: a method for assessing and improving emergency plans for floods , 2012 .

[11]  F. Silvestro,et al.  Quantitative Flood Forecasting on Small- and Medium-Sized Basins: A Probabilistic Approach for Operational Purposes , 2011 .

[12]  A. Mahmood,et al.  The International Charter ‘Space and Major Disasters’ , 2015 .

[13]  Jörn Behrens,et al.  A new multi-sensor approach to simulation assisted tsunami early warning , 2010 .

[14]  Petra Perner,et al.  Data Mining - Concepts and Techniques , 2002, Künstliche Intell..

[15]  Giorgio Boni,et al.  A hydrometeorological approach for probabilistic flood forecast , 2005 .

[16]  F. Silvestro,et al.  What if the 25 October 2011 event that struck Cinque Terre (Liguria)had happened in Genoa, Italy? Flooding scenarios, hazard mapping anddamage estimation , 2016 .

[17]  Valerie J. Davidson,et al.  Fuzzy risk assessment tool for microbial hazards in food systems , 2006, Fuzzy Sets Syst..

[18]  G. Roth,et al.  Applicability of a forecasting chain in a different morphological environment in Italy , 2005 .

[19]  Simon Plank,et al.  The Use of Sentinel-1 Time-Series Data to Improve Flood Monitoring in Arid Areas , 2018, Remote. Sens..

[20]  H. Marks,et al.  Qualitative and quantitative risk assessment , 1999 .

[21]  Mariele Evers,et al.  Multi-criteria decision-making for flood risk management: a survey of the current state of the art , 2016 .

[22]  Daniel J. Power,et al.  Understanding Data-Driven Decision Support Systems , 2008, Inf. Syst. Manag..

[23]  Franco Siccardi,et al.  Dealing with uncertainty: an analysis of the severe weather events over Italy in 2006 , 2009 .

[24]  V. Ducrocq,et al.  Hydrometeorological multi-model ensemble simulations of the 4 November 2011 flash flood event in Genoa, Italy, in the framework of the DRIHM Project , 2014 .

[25]  Bruno Merz,et al.  Review article "Assessment of economic flood damage" , 2010 .

[26]  R. C. Honey,et al.  An Investigation of Operational Decision Making in Situ , 2015, Hum. Factors.

[27]  Sandro Martinis,et al.  A fully automated TerraSAR-X based flood service , 2015 .

[28]  I. Kelman,et al.  An overview of flood actions on buildings , 2004 .

[29]  Robert G. Bell,et al.  Quantitative multi-risk analysis for natural hazards: a framework for multi-risk modelling , 2011 .

[30]  Simon Plank,et al.  Sentinel-1-based flood mapping: a fully automated processing chain , 2016 .