Open Geosci. 2016; 8:711–727 Research Article Open Access Giorgos Kochilakis, Dimitris Poursanidis*, Nektarios Chrysoulakis, Vassiliki Varella, Vassiliki Kotroni, Giorgos Eftychidis, Kostas Lagouvardos, Chrysoula Papathanasiou, George Karavokyros, Maria Aivazoglou, Christos Makropoulos, and Maria Mimikou FLIRE DSS: A web tool for the management of floods and wildfires in urban and periurban areas DOI 10.1515/geo-2016-0068 are likely to flood and thus save human lives. Real-time Received Sep 25, 2015; accepted May 17, 2016 weather data from ground stations provide the necessary inputs for the calculation of the fire model in real-time, Abstract: A web-based Decision Support System, named and a high resolution weather forecast grid supports flood FLIRE DSS, for combined forest fire control and planning modeling as well as the development of “what-if” scenar- as well as flood risk management, has been developed and ios for the fire modeling. All these can be accessed byvar- is presented in this paper. State of the art tools and models ious computer sources including PC, laptop, Smartphone have been used in order to enable Civil Protection agencies and tablet either by normal network connection or by us- and local stakeholders to take advantage of the web based ing 3G and 4G cellular network. The latter is important for DSS without the need of local installation of complex soft- the accessibility of the FLIRE DSS during firefighting or res- ware and their maintenance. Civil protection agencies can cue operations during flood events. All these methods and predict the behavior of a fire event using real time data tools provide the end users with the necessary information and in such a way plan its efficient elimination. Also, dur- to design an operational plan for the elimination of the fire ing dry periods, agencies can implement “what-if” scenar- events and the efficient management of the flood events in ios for areas that are prone to fire and thus have available almost real time. Concluding, the FLIRE DSS can be easily plans for forest fire management in case such scenarios oc- transferred to other areas with similar characteristics due cur. Flood services include flood maps and flood-related to its robust architecture and its flexibility. warnings and become available to relevant authorities for visualization and further analysis on a daily basis. When Keywords: DSS System; on-line simulation; fire; flood; nat- flood warnings are issued, relevant authorities may pro- ural disaster ceed to efficient evacuation planning for the areas that 1 Introduction *Corresponding Author: Dimitris Poursanidis: Foundation for Research and Technology, Hellas, Institute of Applied and Computa- A Decision Support System is a computer-based informa- tional Mathematics, www.rslab.gr, Nikolaou Plastira 100, Vassilika Vouton, P.O. Box 1385, GR71110, Heraklion, Crete, Greece; Email: tion system which has the efficiency to support business [email protected] or organizational decision-making activities. In this envi- Giorgos Kochilakis, Nektarios Chrysoulakis: Foundation for ronment, the computer is the “silent partner” as the key Research and Technology, Hellas, Institute of Applied and Computa- factor, responsible for engagement of the computers in tional Mathematics, www.rslab.gr, Nikolaou Plastira 100, Vassilika the decision-making process. Through the computers, the Vouton, P.O. Box 1385, GR71110, Heraklion, Crete, Greece Vassiliki Varella, Giorgos Eftychidis: Algosystems S.A., Syggrou information is treated as the sixth resource besides the Avenue 206, Athens, Greece, P.O. 17672 machines, the money, the people, the materials and the Vassiliki Kotroni, Kostas Lagouvardos: Institute for Environmen- management [1]. Such systems can provide services for tal Research and Sustainable Development, National Observatory of the planning, operation and management of an organi- Athens, Athens, Greece zation in order to aid decision making. Thus, DSS intro- Chrysoula Papathanasiou, George Karavokyros, Christos duces multiple interdisciplinary aspects into the planning Makropoulos, Maria Mimikou: Department of Water Resources and Environmental Engineering, School of Civil Engineering, Na- process in complex decision environments by adding the tional Technical Univ. of Athens, 5, Iroon Politechniou St., Zografou, geospatial domain [2]. The basis of such systems is the Athens 15780, Greece Geographic Information System (GIS) that includes data Maria Aivazoglou: Department of Civil and Environmental Engi- management, graphic display, spatial modeling and spa- neering, Imperial College London, London, United Kingdom © 2016 G. Kochilakis et al., published by De Gruyter Open. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License. 712 Ë G. Kochilakis et al. tial analysis functions. Across these common GIS decision impacts, including loss of human lives, health and qual- utilities, special features may also be included like model ity of life degradation, loss of private and public property optimization as well as statistical and spatial interaction and destruction of economic activities. At the European functions [3]. The fundamental components of a DSS are level, flood events are the most frequently reported nat- the database or the database management system (DBMS), ural disasters, affecting 25% more people than any other the model (the decision context and user criteria) or the type of natural disaster [12] while Price et al. [13, 14] recog- model based management system (MBMS) and the user in- nised that flash floods are among the costliest natural haz- terface, which is usually a standalone software on a per- ards around the globe and used lightning data to better sonal computer (PC) or nowadays, a web - based Graph- understand and predict flash floods in the Mediterranean. ical User Interface (GUI) which is accessible via any web Papagiannaki et al. [15] presented a database which in- browser from any platform [4]. The revolution in communi- cludes the weather events that have high-impact in Greece cation networks (3G, 4G cellular networks) and digital me- during 2001-2011. They found out that almost the half of dia (smartphones, tablets) has changed the original con- the weather events were the flash floods. These constitute cept of modules implemented within Commercial-Off-The- the most frequent type of the examined phenomena dur- Shelf (COTS) software or closed software which includes ing this decade. From 51 prefectures of Greece, Attica was all the components of a system. Yet the elements of a sys- among the more often influenced areas, mostly from flash tem can be distributed in components in different geo- floods. Regarding the seasonality of flash floods, autumn graphic remote locations and by implementing this archi- in Greece is actually the season with the higher frequency tecture, the use of iconic structures is apparent. This al- of rainfall and the highest accumulated rainfall, particu- lows the use of models and information from their original larly in the mainland [16–19]. As well, economic damages storage devices (hardware), reducing expenses for data resulting from wildfires (i.e., the reduced ability of a burnt capture and analysis, integration and management. Web- forest to offer recreation opportunities) are also signifi- based DSS systems remain less common, especially in the cant, especially in Mediterranean regions, where their fre- field of natural disaster management, while the World quency is considerably high. This ecological degradation Wide Web technologies can provide integrated platforms becomes even more severe in the case of combined action, for the design, development, implementation and deploy- i.e. a flood event becomes more probable and more catas- ment of such Decision Support Systems. Current systems trophic when occurring in a formerly forested area that provide the end users with a broad range of capabilities has been devastated by wildfire. The occurrence and the and decision tasks, including information gathering and extent of both natural disasters strongly depend not only analysis, model building, sensitivity analysis, collabora- on the existing weather conditions in an area, but also on tion, decision implementation, spatial analysis and spa- human intervention, which is particularly pronounced in tial visualization [5]. Also, by using the web-based ap- peri-urban areas and can magnify the environmental im- proach, DSS systems become more flexible as all the com- pact. Typically, these phenomena have been investigated ponents of the system are located on the web, distributed separately, with different systems collecting information in different locations, while the calculations for the out- and modeling the resulting risk. This approach overlooks puts and the results of the models are running “on the two significant facts: fly”. Therefore, the models have been designed with opti- • The field data required in both cases are essentially mizations in order to provide real time information. Thus, the same, and hence a “collect once – use for many the information provided to the person responsible for the purposes” paradigm can be adopted resulting in in- confrontation of natural disasters will be available in a creased accuracy and economies and, manner of real-time response. DSS are popular in several • The phenomena are tightly interrelated, with forest fields like water resources management [6], renewable re- fires exacerbating the risk of flooding and preceding