Loss data collection at the local level Experience from Germany Heidi Kreibich 1 & Annegret H. Thieken 2 1 German Research Centre for Geosciences – GFZ 2 University of Potsdam

 Objective:  Risk modelling (development of loss models, model testing and validation)  Forensic disaster analyses (understand damaging processes, quantify loss reduction via private precaution, learn from past events) Flood loss data collection – development of a procedure

 Development of guidelines for a good practice of flood loss data collection:  Comparison of different data collection methods  Suggestions for a minimal items set in different economic sectors  Suggestions for data collection, processing, management and documentation  Development of a flood loss database for Germany (HOWAS 21):  Collection of available data on flood losses  Community based use concept  Quality control of the data  Loss data collection after flood events in Germany:  Method: computer aided telephone interviews with flood affected private households and companies  Surveys undertaken after the floods in 2002, 2005/2006, 2010/2011, 2013 Flood loss data collection – development of a procedure

 Development of guidelines for a good practice of flood loss data collection:  Comparison of different data collection methods  Suggestions for a minimal items set in different economic sectors  Suggestions for data collection, processing, management and documentation  Development of a flood loss database for Germany (HOWAS 21):  Collection of available data on flood losses  Community based use concept  Quality control of the data  Loss data collection after flood events in Germany:  Method: computer aided telephone interviews with flood affected private households and companies  Surveys undertaken after the floods in 2002, 2005/2006, 2010/2011, 2013 Flood loss data collection – development of a procedure But: guidelines are “only” a scientific suggestion, not legally binding, no official recommendation But: no funding available for the database But: funding needs to be acquired on an ad hoc basis via third party research projects, i.e. no guarantee for regular loss data collection

Process to derive guidelines and min. standard Workshop with representatives from public administration, insurance industry and academia in 2005 Expert survey (online, Delphi method with three rounds) to derive a catalogue of relevant items in 2006 and 2007 (Elmer, Kreibich, Seifert, Thieken (2010). Risk Analysis 30(1): ) Compilation of the guidelines and the data base (HOWAS 21) in 2007 and 2008 Review and revision of guidelines and data base in 2008 and 2009 (Chapter 4 in Thieken, Seifert, Merz, 2010 Hochwasserschäden)

Building Surveyors: Polls: - high level of standardisation- answers dependent on respondent - consistent data quality- unknown data quality - limited set of parameters- representativeness via sampling - expensive method (100 € per case)- lower costs (25-40€ per case) Loss data collection methods

Building Surveyors: Polls: - high level of standardisation- answers dependent on respondent - consistent data quality- unknown data quality - limited set of parameters- representativeness via sampling - expensive method (100 € per case)- lower costs (25-40€ per case) Loss data collection methods CommitmentAmount of questions Return rateCosts On site interviews Telephone interviews Written-postal survey Web-based survey Characteristics of different polls

Development of minimum standards for loss data collection Workshop (15 experts) and Delphi expert survey (55 experts) Mean perception of importance for risk analyses of different loss categories in 6 sectors (1 = highly important; 6 = not important at all)

Catalogue of items that meet minimum requirements Thieken et al. (2009) HYWa 53(3)

Guidelines for flood loss data collection Contents 1.Introduction and definitions for flood loss data collection 2.Overview of loss data collection methods 3.Minimum Standards and suggestions for further information to be collected for various sectors 4.Suggestions for data collection organisation, data processing, quality control and storage a.Documentation and quality control b.Event and hazard description c.Private households / residential properties d.Companies and municipal infrastructure e.Agriculture and forestry f.Traffic and transport g.Water courses and flood defences Review by 25 external experts

Guidelines for flood loss data collection

Bavaria Saxony Saxony-Anhalt Flood events / / Private households Companies Questions about: characteristics of the flood, characteristics of the building, the household or company, the inventory, machinery and equipment damaged items, monetary losses warning and emergency measures precautionary measures previously experienced floods Loss data collection via computer aided telephone interviews Number of Interviews per campaign Max. amount of possible interviews

Standardised questionnaires for private households: 180 questions, interview duration ca. 30 min; companies: 90 questions, interview duration ca. 15 min. The software guides through the questionnaire, next question appears only if an answer to the previous one is keyed in. If one answer makes some following questions inapplicable, these are automatically not stated. To avoid errors, only meaningful answers are accepted by the system. Wherever possible, answers were cross checked, e.g., if the given outside storage area is larger than the given area of the premises, the interviewer was informed about this contradiction and prompted to clarify the situation. Always more questions to the same topic, e.g. detailed questions addressing not only total damage but also the area affected per story, the damage ratio, the type and amount of the most expensive item damaged, and the type and costs of all building repairs and all expensive domestic appliances affected. Damage estimates confirmed to be rel. reliable by a comparison of the damage data collected with official damage data (Thieken et al., 2005). Questionnaires: Loss data collection via computer aided telephone interviews

Flood damage database for Germany: HOWAS21