ELDEWAS - Online early warning system for landslide detection by means of dynamic weather nowcasts and knowledge based assessment

Transcription

1 Fraunhofer IOSB ELDEWAS - Online early warning system for landslide detection by means of dynamic weather nowcasts and knowledge based assessment Oliver Krol & Thomas Bernard iemss Conference, 1 st 5 th July 2012 Leipzig

2 Outline Introduction Characterization of Landslides Disposition Variable Disposition Activating Events Concept of ELDEWAS Landslide Assessment by Fuzzy Logic Example Current state and future work Summary

3 Introduction INCA-CE EU Interreg IV Project 16 Partners from Central Europe, Lead: ZAMG INCA Integrated Nowcast through Comprehensive Analysis Application of nowcast in three domains: Hydrology, Road Safety and Civil Protection IOSB: Development of Landslide warning system Support from Wildbach- und Lawinenverbauung Niederösterreich (WLV) BUWELA-Project Landslides Increasing frequency due to climate change in alpine areas Material damage, Human injury Different types of landslides Different mechanisms but similar causes

4 Characterization of Landslide Events Disposition Long-term constant factors ( decades, centuries) Magnitude Variable Disposition Temporal variable Middle-term and short-term events monthly, daily events seasonal, cyclic Magnitude and Frequency Activating Event Temporal variable Short-term events Weeks, days, hours, minutes Magnitude and Frequency Actual current disposition Landslide process

5 Characterization of Landslide Events Activating Events Load variable Disposition Current Disposition Disposition Time

6 Disposition Slope exposition Soil structure Land cover Land use

7 Variable Disposition Variable in Time and Space Metrology Precipitation Temperature Wind Velocity Variable in Space Geology Sand, Clay, Gravel, Pebble, Rock Weathering Bed Load Potential Disposition Hydrology Soil Moisture Groundwater Level

8 Activating events Thunder storms Several days lasting precipitations Snow melts Sudden outbreaks of lakes in mountainous regions

9 Concept of ELDEWAS Identification of regions with high disposition Slope Exposition Geotechnical structure Land Cover/Land Use Monitoring and forecast of dynamic variables Precipitation Temperature Hydrological variables Fusion of geo-related data online Estimation of susceptability Identification of hazard zones Alarming

10 Why Fuzzy Logic? Fuzzy Logic is feasible if data are hard to measure data are imprecise/ incomplete complex nonlinear processes incomplete experts knowledge should be incorporated the evaluation should be human like (by rules in linguistic terms)

11 Preconditions and Requirements Preconditions and Requirements in Landslide modeling Spatially and temporally distributed problem No comprehensive exact measurements possible Incomplete data base Different resolutions Exact relations inducing landslide are not known Incomplete knowledge Nonlinearities Fuzzy Methods are appropriate

12 Definition of Input Variables Angle of internal friction Characterization of substrate type Five linguistic variables Very small (vs), small (s), middle (m), high (h), very high (vh) Slope exposition Eight linguistic variables Very small (vs), small (s), small to middle (stm), middle (m), middle to high (mth) high (h), very high (vh), very very high (vvh)

13 Definition of Output Variable & Rule Base Disposition/Susceptability 4 linguistic variables: very small (vs), small (s), middle (m), high (h)

14 Angle of internal friction Definition of Rules Table IF-THEN-Rules: IF slope is very high AND internal friction is small THEN Disposition is high IF slope is small Rule Table: AND internal friction is small THEN Disposition is very small slope vs s stm m mth h vh vvh vs vs s m m h h h h s vs vs s m m h h h m vs vs vs s m m h h h vs vs vs vs s m m h vh vs vs vs vs vs s m h

15 Disposition Characteristic Diagram of Susceptability

16 Disposition online Implementation of ELDEWAS INCA-Data Slope Geol. Structure Land use/cover offline ELDEWAS *) online Warning etc. * ) ELDEWAS = Early Landslide Detection and Warning System

17 Current State of ELDEWAS Reading and Displaying of grids Offline Mode: Loading of historical Data for a specific time period Load and Save of projects Basic Evaluation Functions Definition of single and multiple thresholds Graphical representation of detected locations

18 Graphical User Interface ELDEWAS

19 Future Work Scientific Work Testing of Fuzzy Logic by historical case studies Technical Development Real Online Link to weather Service GUI for Fuzzy-Logic-based Evaluation Reporting Help-Function

20 Summary Description of Landslide Events Concept of ELDEWAS Landslide Assessment by Fuzzy Logic Example Current state and future work Thank you for your attention

21 Literature Collison, A., S.Wade, J. Griffiths, and M. Dehn. Modelling the impact of predicted climate change on landslide frequency and magnitude in se england. Engineering Geology, 55: , Gamma, P. dfwalk -Ein Murgang-Simulationsprogramm zur Gefahrenzonierung. PhDthesis, Philosophisch-naturwissenschaftliche Fakultät, Universität Bern, Hamberger, M. Rutschungserkennung mit Klassifikationssystemen. PhD thesis, Naturwissenschaftliche Fakultät, Friedrich-Alexander Universitäat Erlangen-Nürnberg, Huggel, C., J. Clague, and O. Korup. Is climate change responsble for changing landslide activity in high mountains? Earth Surface Processes and Landforms, 37:77 91, INCA-CE. Integrated Nowcasting through comprehensive Analysis in Central Europe. Technical report, InterReg IV Central Europe, Jang, J. R. Fuzzy logic toolbox. Design, 1997(6):557 8, Kienholz, H. Gefahrenkarten: Massgebliche Parameter und Kriterien zur Festlegung der Intensitätsstufen. In Tagungspublikation Internationales Symposium INTERPRAEVENT Garmisch-Partenkirchen, volume 3, pages , Liener, S., M. Liniger, B. Krummenacher, and H. Kienholz. Abgrenzung rutschgefährdeter Gebiete - Entwicklung eines Dispositionsmodells. In Tagungspublikation Internationales Symposium INTERPRAEVENT Garmisch-Partenkirchen, volume 3, pages , Madson, F. Tonmineralische Grundlagen der Scherfestigkeit tonhaltiger Lockergesteine. In Oddsson, B., editor, Instabile Hänge und andere risikorelevante Instabilitäten. Birkhäuser Verlag Basel Boston Berlin, Malet, J.-P., Y. Durand, A. Rematre, O. Maquaire, P. Etchevers, G. Guyomarch, M. Déqué, and L. van Beek. Assessing the influence of climate change on the activity of landslides in the ubaye valley. In McInnes, R., editor, Proceedings of the International Conference on Landslides and Climate Change - Challenges and Solutions, pages pp Taylor & Francis, London, Oddsson, B., editor. Instabile Hänge und andere risikorelevante Instabilitäten. Birkhäuser Verlag Basel Boston Berlin, Schindler, C. Einführung in die Grundtypen von Instabilitäten. Instabile Hänge und andere risikorelevante Instabilitäten. Birkhäuser Verlag Basel Boston Berlin, 1996 Takagi, T. and M. Sugeno. Fuzzy identification of systems and its application to modeling and control. IEEE Transactions on Systems, Man and Cybernetics, 15, Tilch, N., S. Melzner, C. Janda, and A. Kociu. Teil 3: GIS-basierte Raumgliederungs- und Regionalisierungsverfahren zur Erstellung von Substrat- Konzeptkarten und Prozessgrunddispositionskarten. Technical report, Geologische Bundesanstalt Wien, Mai Tobler, D., B. Technical report, InterReg IIIb Alpine Space Program, 2006.rummenacher, and W. Rohr. GIS-basierte Modellierung von Rutschungen und Hangmuren; Teilprojekt Graub unden des Interreg IIIb Projektes CatchRisk.

22 Evaluation of Landslide Susceptability Static Parameter Maps (e.g. slope, lithology, land use, land cover etc.) Dynamic Data (precipitation, temperature, wind velocity, etc.) Evaluation by Fuzzy Logic Warning module

23 Disposition Natural Cover Bed Load Potential Soil Structure Slope