TY - THES A1 - Koç, Gamze T1 - A comprehensive analysis of severe flood events in Turkey T1 - Eine ausführliche Analyse schwerer Flutereignisse in der Türkei BT - event documentation, triggering mechanisms and impact modelling BT - Ereignisdokumentation, Auslösemechanismen und Auswirkungsmodellierung N2 - Over the past decades, natural hazards, many of which are aggravated by climate change and reveal an increasing trend in frequency and intensity, have caused significant human and economic losses and pose a considerable obstacle to sustainable development. Hence, dedicated action toward disaster risk reduction is needed to understand the underlying drivers and create efficient risk mitigation plans. Such action is requested by the Sendai Framework for Disaster Risk Reduction 2015-2030 (SFDRR), a global agreement launched in 2015 that establishes stating priorities for action, e.g. an improved understanding of disaster risk. Turkey is one of the SFDRR contracting countries and has been severely affected by many natural hazards, in particular earthquakes and floods. However, disproportionately little is known about flood hazards and risks in Turkey. Therefore, this thesis aims to carry out a comprehensive analysis of flood hazards for the first time in Turkey from triggering drivers to impacts. It is intended to contribute to a better understanding of flood risks, improvements of flood risk mitigation and the facilitated monitoring of progress and achievements while implementing the SFDRR. In order to investigate the occurrence and severity of flooding in comparison to other natural hazards in Turkey and provide an overview of the temporal and spatial distribution of flood losses, the Turkey Disaster Database (TABB) was examined for the years 1960-2014. The TABB database was reviewed through comparison with the Emergency Events Database (EM-DAT), the Dartmouth Flood Observatory database, the scientific literature and news archives. In addition, data on the most severe flood events between 1960 and 2014 were retrieved. These served as a basis for analyzing triggering mechanisms (i.e. atmospheric circulation and precipitation amounts) and aggravating pathways (i.e. topographic features, catchment size, land use types and soil properties). For this, a new approach was developed and the events were classified using hierarchical cluster analyses to identify the main influencing factor per event and provide additional information about the dominant flood pathways for severe floods. The main idea of the study was to start with the event impacts based on a bottom-up approach and identify the causes that created damaging events, instead of applying a model chain with long-term series as input and searching for potentially impacting events as model outcomes. However, within the frequency analysis of the flood-triggering circulation pattern types, it was discovered that events in terms of heavy precipitation were not included in the list of most severe floods, i.e. their impacts were not recorded in national and international loss databases but were mentioned in news archives and reported by the Turkish State Meteorological Service. This finding challenges bottom-up modelling approaches and underlines the urgent need for consistent event and loss documentation. Therefore, as a next step, the aim was to enhance the flood loss documentation by calibrating, validating and applying the United Nations Office for Disaster Risk Reduction (UNDRR) loss estimation method for the recent severe flood events (2015-2020). This provided, a consistent flood loss estimation model for Turkey, allowing governments to estimate losses as quickly as possible after events, e.g. to better coordinate financial aid. This thesis reveals that, after earthquakes, floods have the second most destructive effects in Turkey in terms of human and economic impacts, with over 800 fatalities and US$ 885.7 million in economic losses between 1960 and 2020, and that more attention should be paid on the national scale. The clustering results of the dominant flood-producing mechanisms (e.g. circulation pattern types, extreme rainfall, sudden snowmelt) present crucial information regarding the source and pathway identification, which can be used as base information for hazard identification in the preliminary risk assessment process. The implementation of the UNDRR loss estimation model shows that the model with country-specific parameters, calibrated damage ratios and sufficient event documentation (i.e. physically damaged units) can be recommended in order to provide first estimates of the magnitude of direct economic losses, even shortly after events have occurred, since it performed well when estimates were compared to documented losses. The presented results can contribute to improving the national disaster loss database in Turkey and thus enable a better monitoring of the national progress and achievements with regard to the targets stated by the SFDRR. In addition, the outcomes can be used to better characterize and classify flood events. Information on the main underlying factors and aggravating flood pathways further supports the selection of suitable risk reduction policies. All input variables used in this thesis were obtained from publicly available data. The results are openly accessible and can be used for further research. As an overall conclusion, it can be stated that consistent loss data collection and better event documentation should gain more attention for a reliable monitoring of the implementation of the SFDRR. Better event documentation should be established according to a globally accepted standard for disaster classification and loss estimation in Turkey. Ultimately, this enables stakeholders to create better risk mitigation actions based on clear hazard definitions, flood event classification and consistent loss estimations. N2 - In den letzten Jahrzehnten verursachten Naturgefahren hohe humanitäre und wirtschaftliche Verluste, wobei viele dieser Ereignisse durch den Klimawandel verstärkt werden und einen zunehmenden Trend in Häufigkeit und Schwere aufweisen. Daher sind gezielte Verfahren zur Reduzierung von Katastrophenrisiken erforderlich, um zugrundeliegende Treiber zu verstehen und effektive Risikominderungspläne zu erstellen. Solche Verfahren werden durch das Sendai-Rahmenwerk für Katastrophenvorsorge 2015-2030 (SFDRR) eingefordert. Das SFDRR ist, ein internationales Rahmenwerk, das 2015 verabschiedet wurde und prioritäre Maßnahmen festlegt, z.B. eine Verbesserung der Wissensgrundlagen zum Katastrophenrisiko. Die Türkei ist eines der SFDRR-Vertragsländer und wurde in der Vergangenheit von vielen Naturgefahren, insbesondere Erdbeben und Überschwemmungen schwer getroffen. Über die Hochwassergefahren und -risiken in der Türkei ist jedoch vergleichsweise wenig bekannt. In dieser Arbeit wird daher zum ersten Mal eine umfassende Analyse der Hochwassergefahren in der Türkei durchgeführt, von den auslösenden Ursachen bis hin zu den Auswirkungen. Ziel ist es, das Verständnis über Hochwasserrisiken zu verbessern, Studien zur Minderung des Hochwasserrisikos anzuregen und das Monitoring der Fortschritte und Zielerreichung bei der Umsetzung des SFDRR zu erleichtern. Um das Auftreten und die Stärke von Überschwemmungen im Vergleich zu anderen Naturgefahren in der Türkei zu untersuchen und einen Überblick über die raumzeitliche Verteilung von Hochwasserschäden, wurde die Turkey Disaster Database (TABB) für den Zeitraum 1960 bis 2014 ausgewertet. Die TABB Datenbank wurde durch Vergleiche mit der Emergency Events Datenbank (EM-DAT), der Dartmouth Flood Observatory Datenbank, wissenschaftlicher Literatur und Nachrichtenarchive überprüft. Zudem wurden die stärksten Überschwemmungen zwischen 1960 und 2014 identifiziert. Diese bildeten die Basis für eine Analyse der Auslösemechanismen (bspw. atmosphärische Zirkulationsmuster und Niederschlagsmengen) und verstärkende Wirkungspfade (z.B. topographische Eigenschaften, Größe der Einzugsgebiete, Landnutzung und Bodeneigenschaften). Dafür wurde ein neues Verfahren entwickelt, und die Ereignisse wurden mithilfe von hierarchischen Clusteranalysen klassifiziert, um die Haupteinflussfaktoren pro Ereignis zu identifizieren und zusätzliche Informationen über die dominanten Wirkungspfade bei schweren Überschwemmungen bereitzustellen. Die grundlegende Idee dieser Arbeit bestand darin, bei den Ereignisauswirkungen als Bottom-up-Ansatz zu beginnen und die Ursachen für Schadensereignisse zu identifizieren, anstatt eine Modellkette mit Langzeitreihen als Eingabe anzuwenden und darin nach potenziellen Schadensereignissen zu suchen. Bei der Häufigkeitsanalyse von hochwasserauslösenden Zirkulationsmustern wurde jedoch festgestellt, dass einige schwer Niederschlagsereignisse nicht in der Liste der schwersten Hochwasserereignisse waren, d.h., ihre Auswirkungen waren nicht in nationalen und internationalen Schadensdatenbanken dokumentiert, wurden jedoch in Nachrichtenarchiven erwähnt und vom türkischen staatlichen Wetterdienst gemeldet. Dieses Erkenntnis stellt den Bottom-up-Modelansatz in Frage und unterstreicht die Dringlichkeit einer konsistenten Ereignis- und Schadensdokumentation. Daher wurde im nächsten Schritt gezielt das Schadenmodell der Vereinten Nationen für Katastrophenvorsorge (UNDRR) für kürzlich aufgetretene starke Flutereignisse (2015-2020) angepasst, validiert und angewendet. Damit wurde ein konsistentes Hochwasserschadenmodell für die Türkei bereitgestellt, das es den Behörden ermöglicht, Verluste so schnell wie möglich nach Ereignissen abzuschätzen, zum Beispiel um eine bessere Koordination von finanziellen Hilfen zu gewährleisten. Diese Arbeit zeigt, dass Überschwemmungen mit mehr als 800 Todesfällen und 885,7 Millionen US Dollar wirtschaftlichen Schaden zwischen 1960 und 2020 nach Erdbeben den zweit höchsten zerstörerischen Effekt in der Türkei in Bezug auf humanitäre und wirtschaftliche Auswirkungen haben. Daher sollte dieses Thema mehr Aufmerksamkeit auf nationaler Ebene erhalten. Die Cluster-Ergebnisse der dominanten hochwasser-auslösenden Mechanismen (z.B. Zirkulationsmuster, Starkniederschlag, plötzliche Schneeschmelze) erhalten wichtige Informationen zur Quell- und Pfad-Identifikation, welche als Basisinformation für Gefahren-identifikation in der vorläufigen Risikoeinschätzung dienen kann. Die Implementierung des UNDRR-Schadenmodells zeigt, dass das Modell mit länderspezifischen Parametern, kalibrierten Schadensgraden und ausreichender Ereignisdokumentation (d.h. physischer geschädigte Einheiten) empfohlen werden kann, um erste Schätzungen zur Höhe der direkten wirtschaftlichen Schäden bereitzustellen -- auch unmittelbar nach Eintreten von Ereignissen, da die Modellschätzungen im Vergleich mit dokumentierten Verlusten gut übereinstimmten. Die präsentierten Ergebnisse können dazu beitragen, die nationale Schadensdatenbank der Türkei zu verbessern, und somit ein besseres Monitoring der nationalen Fortschritte und Erfolge im Hinblick auf die Ziele des SFDRR ermöglichen. Zusätzlich können die Ergebnisse für eine bessere Charakterisierung und Klassifizierung von Hochwasserereignissen verwendet werden. Informationen zu den zugrundeliegenden Einflussfaktoren und verstärkenden Wirkungspfaden unterstützen die Auswahl geeigneter Risikomanagementstrategien. Alle Eingabevariablen dieser Arbeit wurden aus öffentlich verfügbaren Daten bezogen. Die Ergebnisse sind zugänglich und können für die weitere Forschung verwendet werden. Insgesamt konnte festgestellt werden, dass die konsistente Erfassung von Schadensdaten und eine bessere Ereignisdokumentation mehr Beachtung finden muss, um die Implementierung des SFDRR verlässlich zu überwachen. Bessere Ereignisdokumentationen sollten nach einem weltweit anerkannten Standard für Gefahrenklassifizierung und Schadensabschätzung in der Türkei etabliert werden. Letztendlich ermöglicht dies den Verantwortlichen auf Basis von eindeutigen Gefahrendefinitionen, Hochwasser-Ereignisklassifizierungen und konsistenten Schadenschätzungen bessere Maßnahmen zur Risikominderung zu erarbeiten. KW - Flood hazards KW - Turkey KW - Triggering mechanisms KW - Cluster analysis KW - Hochwassergefahren KW - Türkei KW - Auslösemechanismen KW - Clusteranalyse KW - Impact modelling KW - Schadenmodell Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-517853 ER - TY - JOUR A1 - Koç, Gamze A1 - Petrow, Theresia A1 - Thieken, Annegret T1 - Analysis of the Most Severe Flood Events in Turkey (1960–2014) BT - Which Triggering Mechanisms and Aggravating Pathways Can be Identified? JF - Water N2 - The most severe flood events in Turkey were determined for the period 1960–2014 by considering the number of fatalities, the number of affected people, and the total economic losses as indicators. The potential triggering mechanisms (i.e., atmospheric circulations and precipitation amounts) and aggravating pathways (i.e., topographic features, catchment size, land use types, and soil properties) of these 25 events were analyzed. On this basis, a new approach was developed to identify the main influencing factor per event and to provide additional information for determining the dominant flood occurrence pathways for severe floods. The events were then classified through hierarchical cluster analysis. As a result, six different clusters were found and characterized. Cluster 1 comprised flood events that were mainly influenced by drainage characteristics (e.g., catchment size and shape); Cluster 2 comprised events aggravated predominantly by urbanization; steep topography was identified to be the dominant factor for Cluster 3; extreme rainfall was determined as the main triggering factor for Cluster 4; saturated soil conditions were found to be the dominant factor for Cluster 5; and orographic effects of mountain ranges characterized Cluster 6. This study determined pathway patterns of the severe floods in Turkey with regard to their main causal or aggravating mechanisms. Accordingly, geomorphological properties are of major importance in large catchments in eastern and northeastern Anatolia. In addition, in small catchments, the share of urbanized area seems to be an important factor for the extent of flood impacts. This paper presents an outcome that could be used for future urban planning and flood risk prevention studies to understand the flood mechanisms in different regions of Turkey. KW - hierarchical clustering KW - Hess-Brezowsky Großwetterlagen classification KW - ERA5 KW - flood hazards KW - pathway KW - Turkey Y1 - 2020 U6 - https://doi.org/10.3390/w12061562 SN - 2073-4441 VL - 12 IS - 6 PB - MDPI CY - Basel ER - TY - GEN A1 - Koç, Gamze A1 - Petrow, Theresia A1 - Thieken, Annegret T1 - Analysis of the Most Severe Flood Events in Turkey (1960–2014) BT - Which Triggering Mechanisms and Aggravating Pathways Can be Identified? T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - The most severe flood events in Turkey were determined for the period 1960–2014 by considering the number of fatalities, the number of affected people, and the total economic losses as indicators. The potential triggering mechanisms (i.e., atmospheric circulations and precipitation amounts) and aggravating pathways (i.e., topographic features, catchment size, land use types, and soil properties) of these 25 events were analyzed. On this basis, a new approach was developed to identify the main influencing factor per event and to provide additional information for determining the dominant flood occurrence pathways for severe floods. The events were then classified through hierarchical cluster analysis. As a result, six different clusters were found and characterized. Cluster 1 comprised flood events that were mainly influenced by drainage characteristics (e.g., catchment size and shape); Cluster 2 comprised events aggravated predominantly by urbanization; steep topography was identified to be the dominant factor for Cluster 3; extreme rainfall was determined as the main triggering factor for Cluster 4; saturated soil conditions were found to be the dominant factor for Cluster 5; and orographic effects of mountain ranges characterized Cluster 6. This study determined pathway patterns of the severe floods in Turkey with regard to their main causal or aggravating mechanisms. Accordingly, geomorphological properties are of major importance in large catchments in eastern and northeastern Anatolia. In addition, in small catchments, the share of urbanized area seems to be an important factor for the extent of flood impacts. This paper presents an outcome that could be used for future urban planning and flood risk prevention studies to understand the flood mechanisms in different regions of Turkey. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 1003 KW - hierarchical clustering KW - Hess-Brezowsky Großwetterlagen classification KW - ERA5 KW - flood hazards KW - pathway KW - Turkey Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-477331 IS - 1003 ER - TY - JOUR A1 - Koç, Gamze A1 - Natho, Stephanie A1 - Thieken, Annegret T1 - Estimating direct economic impacts of severe flood events in Turkey (2015-2020) JF - International journal of disaster risk reduction : IJDRR N2 - Over the past decades, floods have caused significant financial losses in Turkey, amounting to US$ 800 million between 1960 and 2014. With the Sendai Framework for Disaster Risk Reduction 2015-2030 (SFDRR), it is aimed to reduce the direct economic loss from disasters in relation to the global gross domestic product (GDP) by 2030. Accordingly, a methodology based on experiences from developing countries was proposed by the United Nations Office for Disaster Risk Reduction (UNDRR) to estimate direct economic losses on the macro-scale. Since Turkey also signed the SFDRR, we aimed to adapt, validate and apply the loss estimation model proposed by the UNDRR in Turkey for the first time. To do so, the well-documented flood event in Mersin of 2016 was used to calibrate the damage ratios for the agricultural, commercial and residential sectors, as well as educational facilities. Case studies between 2015 and 2020 with documented losses were further used to validate the model. Finally, model applications provided initial loss estimates for floods occurred recently in Turkey. Despite the limited event documentation for each sector, the calibrated model yielded good results when compared to documented losses. Thus, by implementing the UNDRR method, this study provides an approach to estimate the direct economic losses in Turkey on the macro-scale, which can be used to fill gaps in event databases, support the coordination of financial aid after flood events and facilitate monitoring of the progress toward and achievement of Global Target C of the Sendai Framework for Disaster Risk Reduction 2015-2030. KW - Direct economic loss KW - Flood KW - Turkey KW - Event documentation KW - UNISDR KW - Loss KW - modelling Y1 - 2021 U6 - https://doi.org/10.1016/j.ijdrr.2021.102222 SN - 2212-4209 VL - 58 PB - Elsevier CY - Amsterdam ER - TY - GEN A1 - Koç, Gamze A1 - Thieken, Annegret T1 - Societal and economic impacts of flood hazards in Turkey BT - an overview T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - Turkey has been severely affected by many natural hazards, in particular earthquakes and floods. Although there is a large body of literature on earthquake hazards and risks in Turkey, comparatively little is known about flood hazards and risks. Therefore, with this study it is aimed to investigate flood patterns, societal and economic impacts of flood hazards in Turkey, as well as providing a comparative overview of the temporal and spatial distribution of flood losses by analysing EM-DAT (Emergency Events Database) and TABB (Turkey Disaster Data Base) databases on disaster losses throughout Turkey for the years 1960-2014. The comparison of these two databases reveals big mismatches of the flood data, e.g. the reported number of events, number of affected people and economic loss, differ dramatically. With this paper, it has been explored reasons for mismatches. Biases and fallacies for loss data in the two databases has been discussed as well. Since loss data collection is gaining more and more attention, e.g. in the Sendai Framework for Disaster Risk Reduction 2015-2030 (SFDRR), the study could offer a base-work for developing guidelines and procedures on how to standardize loss databases and implement across the other hazard events, as well as substantial insights for flood risk mitigation and adaptation studies in Turkey and will offer valuable insights for other (European) countries. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 903 KW - Engineering , Environmental KW - Engineering, Civil KW - Environmental Sciences KW - Geosciences, Multidisciplinary KW - Regional & Urban Planning KW - Water Resources Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-438779 SN - 1866-8372 IS - 903 ER -