Natural Hazards and Earth System Science www.nat-hazards-earth-syst-sci.net 1561-8633 1684-9981 10 8 2010 10.5194/nhess-10-1679-2010 http://www.nat-hazards-earth-syst-sci.net/10/1679/2010/ http://www.nat-hazards-earth-syst-sci.net/10/1679/2010/nhess-10-1679-2010.html http://www.nat-hazards-earth-syst-sci.net/10/1679/2010/nhess-10-1679-2010.pdf 1679 1687 2010-08-03 Tsunami inundation modelling based on detailed roughness maps of densely populated areas G. Gayer gerhard.gayer@gkss.de S. Leschka I. Nöhren O. Larsen H. Günther GKSS Research Centre Geesthacht, 21502 Geesthacht, Germany DHI-WASY GmbH Syke, 28857 Syke, Germany DHI-NTU Research Centre & Education Hub, 200 Pandan Loop #08-03 Pantech 21, Singapore An important part within the German-Indonesian Tsunami Early Warning System (GITEWS) project was the detailed numerical investigation of the impact of tsunamis in densely populated coastal areas of Indonesia. This work, carried out by the German Research Centre Geesthacht (GKSS), in co-operation with DHI-WASY, also provides the basis for the preparation of high resolution hazard and risk maps by the German Aerospace Center (DLR). In this paper a method is described of how to prepare very detailed roughness maps for scenario computations performed with the MIKE 21 Flow Model FM in three highly resolved (~10 m) priority regions, namely Kuta (Bali), Padang (West-Sumatra), and Cilacap (southern coast of Java). Roughness values are assigned to 43 land use classes, e.g. different types of buildings, rural and urban sub-areas, by using equivalent coefficients found in literature or by performing numerical experiments. Comparisons of simulations using differentiated roughness maps with simulations using constant values (a widely used approach) are presented and it is demonstrated that roughness takes considerable influence on run-up and inundation. Out of all simulations, the results of the worst case scenarios for each of the three priority areas are discussed. Earthquakes with magnitudes of MW=8.5 or higher lead to considerable inundation in all study sites. A spatially distinguished consideration of roughness has been found to be necessary for detailed modelling onshore. Acrement, G. J., Schneider, J. R., and Schneider, V. R.: Guide for Selecting Manning's Roughness Coefficients for Natural Channels and Flood Plains, USGS Water-supply paper 2339, available at: http://www.fhwa.dot.gov/BRIDGE/wsp2339.pdf (last access: 10~October~2008), 1989. Babeyko, A. Y.: Process Simulator: An interactive modeling tool in support of TEWS – Personnel training and system verification, in: E-Proc. of the International Conference on Tsunami Warning, DSM17DE, Nusa Dua/Indonesia, 12–14 November, 2008). Babeyko, A. Y., Hoechner, A., and Sobolev, S. V.: Source modeling and inversion with near real-time GPS: a GITEWS perspective for Indonesia, Nat. Hazards Earth Syst. Sci., in press, 2010. Behrens, J., Androsov, A., Babeyko, A. Y., Harig, S., Klaschka, F., and Mentrup, L.: A new multi-sensor approach to simulation assisted tsunami early warning, Nat. Hazards Earth Syst. Sci., 10, 1085–1100, doi:10.5194/nhess-10-1085-2010, 2010. DHI Software: MIKE 21 FM Scientific Documentation, 2008a. DHI Software: MIKE 21 HD Scientific Documentation, 2008b. Fujii, Y. and Satake, K.: Source of the 2006 West Java tsunami estimated from tide gauge records, Geophys. Res. Let., 33, L24317, doi:10.1029/2006GL028049, 2006. Kongko, W., Leschka, S., Larsen, O., Gayer, G., Nöhren, I., and Günther, H.: A sensitivity test of tsunami modelling using various data: Case study in Cilacap Indonesia, in: E-Proc. of the International Conference on Tsunami Warning (ICTW), Nusa Dua/Indonesia, DMS07ID, 12–14 November 2008. Kouwen, N.: Modern approach to design grassed channels, J. Irrig. Drain. E.-ASCE, 118(5), 733–743, 1992. Latief, H. and Hadi, S.: The role of forest and trees in protecting coastal areas against tsunami, in: Proc. of the Workshop Coastal Protection in the Aftermath of the Indian Ocean Tsunami: What role for forests and trees?, Khao Lak 2007, United Nations Food and Agriculture organization, 2007. Leschka, S., Kongko, W., and Larsen, O.: On the influence of nearshore bathymetry data quality on tsunami runup modeling, part I: Bathymetry, in: Proc. of the 5th International Conference on Asian and Pacific Coasts (APAC2009), Singapore, edited by: Tan, S K. and Huang, Z., 1, 151–156, 13–18 October 2009a. Leschka, S., Kongko, W., and Larsen, O.: On the influence of nearshore bathymetry data quality on tsunami runup modeling, part II: Modeling, in: Proc. of the 5th International Conference on Asian and Pacific Coasts (APAC2009), Singapore, edited by: Tan, S K. and Huang, Z., 1, 157–163, 13–18 October 2009b Leschka, S., Pedersen, C., and Larsen, O.: On the requirements for data and methods in tsunami inundation modelling-Roughness map and uncertainties, in: Proc. of the South China Sea Tsunami Workshop, Penang, Malaysia, in review, 3–5 November 2009c. Leschka, S., Zosseder, K., Post, J., and Larsen, O.: On tsunami inundation modeling for hazard estimation at three coastal areas in Indonesia, European Geosciences Union, General Assembly, Session NH5.1, Vienna, Austria, 2–7 May 2010. Rudloff, A., Lauterjung, J., Münch, U., and Tinti, S.: Preface "The GITEWS Project (German-Indonesian Tsunami Early Warning System)", Nat. Hazards Earth Syst. Sci., 9, 1381–1382, doi:10.5194/nhess-9-1381-2009, 2009. Schneider, K.-J.: Bautabellen mit Berechnungshinweisen, Beispielen und europäischen Vorschriften, 10th edn., Werner Verlag, 1992 (in German). Weichel, T., Pappenberger, F., and Schulz, K.: Sensitivity and uncertainty in flood inundation modelling - concept of an analysis framework, Adv. Geosci., 11, 31–36, doi:10.5194/adgeo-11-31-2007, 2007.