Decision Support System for a Pilot Flash Flood Early Warning System in Central Chile
Flash Floods, together with landslides, are a common
natural threat for people living in mountainous regions and foothills.
One way to deal with this constant menace is the use of Early
Warning Systems, which have become a very important mitigation
strategy for natural disasters.
In this work we present our proposal for a pilot Flash Flood Early
Warning System for Santiago, Chile, the first stage of a more
ambitious project that in a future stage shall also include early
warning of landslides.
To give a context for our approach, we first analyze three existing
Flash Flood Early Warning Systems, focusing on their general
architectures. We then present our proposed system, with main focus
on the decision support system, a system that integrates empirical
models and fuzzy expert systems to achieve reliable risk estimations.
[1] B. Wisner, P. Blaikie, T. Cannon, and I. Davis, Risk: natural hazards,
people's vulnerability and disasters. London: Routledge, 2004.
[2] S.L. Cutter, and C. Emrich, “Are natural hazards and disaster losses in
the US increasing?,” Eos, Trans. American Geophysical Union, vol. 86,
no. 41, pp. 381-389, 2005.
[3] W. Hanka, J. Saul, B. Weber, J. Becker, and P. Harjadi, “Real-time
earthquake monitoring for tsunami warning in the Indian Ocean and
beyond,” Nat. Hazards Earth Syst. Sci., vol. 10, pp. 2611-2622, 2010.
[4] World Meteorological Organization, “Natural Hazard,” online article
http://www.wmo.int/pages/themes/hazards/index_en.html Accessed July
2014.
[5] C.D. Hill, F. Verjee, and C. Barrett, Flash Flood Early Warning System
Reference Guide. USA: University Corporation for Atmospheric
Research, 2010.
[6] World Meteorological Organization “Flash Flood Guidance System
(FFGS),” Paper for the CBS Management Group, World Meteorological
Organization, Commission for Basic Systems Management Group,
seventh session, Geneva, Switzerland, June 2007.
[7] E. Aristizábal, M.F. Gamboa, and F.J. Leoz, “Early Warning System for
rainfall-induced landslides in the Aburrá valley, Colombia,” Revista
EIA, no 13, pp. 155-169, July 2010.
[8] O. Krol, and T. Bernard “ELDEWAS - Online early warning system for
landslide detection by means of dynamic weather nowcasts and
knowledge based assessment,” in International Environmental
Modelling and Software Society (iEMSs) 2012 International Congress
on Environmental Modelling and Software Managing Resources of a
Limited Planet: Pathways and Visions under Uncertainty, Sixth Biennial
Meeting, Leipzig, Germany, pp. 212-219.
[9] D. Pinto, and A. Cipriano “Tsunami Early Warning System architecture
based on automation technologies,” in ICT-DM 2014: The First IEEE
International Conference on Information and Communication
Technologies for Disaster Management, Algiers, March 2014. To be
published.
[10] F.N. Correia, F.C. Rego, M.D.G. Saraiva, and I. Ramos, “Coupling GIS
with hydrologic and hydraulic flood modelling,” Water Resour.
Manage., vol. 12, no. 3, pp. 229-249, 1998.
[11] Y. Lian, I. Chan, J. Singh, M. Demissie, V. Knapp, and H. Xie,
“Coupling of hydrologic and hydraulic models for the Illinois River
Basin,” J. Hydrol., vol. 344, no. 3, pp. 210-222, 2007.
[12] M. Staudinger, “METEOALARM-EF, Final Report.” March, 2011.
Available at
http://ec.europa.eu/echo/civil_protection/civil/prote/pdfdocs/meteoalarm
_final_report_en.pdf
[13] J. Behrens, A. Androsov, A.Y. Babeyko, S. Harig, F. Klaschka, and L.
Mentrup “A new multi-sensor approach to simulation assisted tsunami
early warning,” Nat. Hazards Earth Syst. Sci. vol. 10, no. 6, pp. 1085-
1100, 2010.
[14] K.P. Georgakakos, “Analytical results for operational flash flood
guidance,” J. Hydrol., vol. 317, no. 1, pp. 81-103, 2006.
[15] T. Terano, K. Asai, M. Sugeno, and C. Aschmann, Applied fuzzy
systems. San Diego, CA: Academic Press Professional, Inc., 1994.
[16] S. Martinis, A. Twele, C. Strobl, J. Kersten, and E. Stein, “A Multi-
Scale Flood Monitoring System Based on Fully Automatic MODIS and
TerraSAR-X Processing Chains,” Remote Sens., vol. 5, no. 11, pp. 5598-
5619, 2013.
[17] H. Karl and A. Willig, Protocols and Architectures for Wireless Sensor
Networks. West Sussex: John Wiley & Sons, 2005.
[18] K. Sohraby, D. Minoli, and T. Znati, Wireless Sensor Networks:
Technology, Protocols, and Applications. New Jersey: Wiley-
Interscience, 2007.
[19] G. Barrenetxea, F. Ingelrest, G. Schaefer, M. Vetterli, O. Couach, and
M. Parlange, “Sensorscope: Out- of-the-box environmental monitoring,”
in Information Processing in Sensor Networks, 2008. IPSN ’08.
International Conference on, St. Louis, MO, Apr. 2008, pp. 332–343.
[20] F. Ingelrest, G. Barrenetxea, G. Schaefer, M. Vetterli, O. Couach, and
M. Parlange, “Sensorscope: Application-specific sensor network for
environmental monitoring,” ACM Trans. Sen. Netw., vol. 6, no. 2, pp.
17:1–17:32, Mar. 2010.
[21] S. Simoni, S. Padoan, D. F. Nadeau, M. Diebold, A. Porporato, G.
Barrenetxea, F. Ingelrest, M. Vetterli, and M. B. Parlange, “Hydrologic
response of an alpine watershed: Application of a meteorological
wireless sensor network to understand streamflow generation,” Water
Resour. Res., vol. 47, no. 10, 2011.
[22] B. Kerkez, S. D. Glaser, R. C. Bales, and M. W. Meadows, “Design and
performance of a wireless sensor network for catchment-scale snow and
soil moisture measurements,” Water Resour. Res., vol. 48, no. 9, 2012.
[23] M. Berti, M.L.V. Martina, S. Franceschini, S. Pignone, A. Simoni, M.
Pizziolo, “Probabilistic rainfall thresholds for landslide occurrence using
a Bayesian approach,” J. Geophys. Res. Earth Surf. (2003–2012), vol.
117, no. F4, 2012.
[24] V. Montesarchio, E. Ridolfi, F. Russo, F. Napolitano,“Rainfall threshold
definition using an entropy decision approach and radar data,” Nat.
Hazards Earth Syst. Sci., vol. 11, no. 7, pp. 2061-2074, 2011.
[25] S.A. Sepúlveda, C. Padilla, “Rain-induced debris and mudflow
triggering factors assessment in the Santiago cordilleran foothills,
Central Chile,” Nat. Hazards, vol. 47, no. 2, pp. 201-215, 2008.
[1] B. Wisner, P. Blaikie, T. Cannon, and I. Davis, Risk: natural hazards,
people's vulnerability and disasters. London: Routledge, 2004.
[2] S.L. Cutter, and C. Emrich, “Are natural hazards and disaster losses in
the US increasing?,” Eos, Trans. American Geophysical Union, vol. 86,
no. 41, pp. 381-389, 2005.
[3] W. Hanka, J. Saul, B. Weber, J. Becker, and P. Harjadi, “Real-time
earthquake monitoring for tsunami warning in the Indian Ocean and
beyond,” Nat. Hazards Earth Syst. Sci., vol. 10, pp. 2611-2622, 2010.
[4] World Meteorological Organization, “Natural Hazard,” online article
http://www.wmo.int/pages/themes/hazards/index_en.html Accessed July
2014.
[5] C.D. Hill, F. Verjee, and C. Barrett, Flash Flood Early Warning System
Reference Guide. USA: University Corporation for Atmospheric
Research, 2010.
[6] World Meteorological Organization “Flash Flood Guidance System
(FFGS),” Paper for the CBS Management Group, World Meteorological
Organization, Commission for Basic Systems Management Group,
seventh session, Geneva, Switzerland, June 2007.
[7] E. Aristizábal, M.F. Gamboa, and F.J. Leoz, “Early Warning System for
rainfall-induced landslides in the Aburrá valley, Colombia,” Revista
EIA, no 13, pp. 155-169, July 2010.
[8] O. Krol, and T. Bernard “ELDEWAS - Online early warning system for
landslide detection by means of dynamic weather nowcasts and
knowledge based assessment,” in International Environmental
Modelling and Software Society (iEMSs) 2012 International Congress
on Environmental Modelling and Software Managing Resources of a
Limited Planet: Pathways and Visions under Uncertainty, Sixth Biennial
Meeting, Leipzig, Germany, pp. 212-219.
[9] D. Pinto, and A. Cipriano “Tsunami Early Warning System architecture
based on automation technologies,” in ICT-DM 2014: The First IEEE
International Conference on Information and Communication
Technologies for Disaster Management, Algiers, March 2014. To be
published.
[10] F.N. Correia, F.C. Rego, M.D.G. Saraiva, and I. Ramos, “Coupling GIS
with hydrologic and hydraulic flood modelling,” Water Resour.
Manage., vol. 12, no. 3, pp. 229-249, 1998.
[11] Y. Lian, I. Chan, J. Singh, M. Demissie, V. Knapp, and H. Xie,
“Coupling of hydrologic and hydraulic models for the Illinois River
Basin,” J. Hydrol., vol. 344, no. 3, pp. 210-222, 2007.
[12] M. Staudinger, “METEOALARM-EF, Final Report.” March, 2011.
Available at
http://ec.europa.eu/echo/civil_protection/civil/prote/pdfdocs/meteoalarm
_final_report_en.pdf
[13] J. Behrens, A. Androsov, A.Y. Babeyko, S. Harig, F. Klaschka, and L.
Mentrup “A new multi-sensor approach to simulation assisted tsunami
early warning,” Nat. Hazards Earth Syst. Sci. vol. 10, no. 6, pp. 1085-
1100, 2010.
[14] K.P. Georgakakos, “Analytical results for operational flash flood
guidance,” J. Hydrol., vol. 317, no. 1, pp. 81-103, 2006.
[15] T. Terano, K. Asai, M. Sugeno, and C. Aschmann, Applied fuzzy
systems. San Diego, CA: Academic Press Professional, Inc., 1994.
[16] S. Martinis, A. Twele, C. Strobl, J. Kersten, and E. Stein, “A Multi-
Scale Flood Monitoring System Based on Fully Automatic MODIS and
TerraSAR-X Processing Chains,” Remote Sens., vol. 5, no. 11, pp. 5598-
5619, 2013.
[17] H. Karl and A. Willig, Protocols and Architectures for Wireless Sensor
Networks. West Sussex: John Wiley & Sons, 2005.
[18] K. Sohraby, D. Minoli, and T. Znati, Wireless Sensor Networks:
Technology, Protocols, and Applications. New Jersey: Wiley-
Interscience, 2007.
[19] G. Barrenetxea, F. Ingelrest, G. Schaefer, M. Vetterli, O. Couach, and
M. Parlange, “Sensorscope: Out- of-the-box environmental monitoring,”
in Information Processing in Sensor Networks, 2008. IPSN ’08.
International Conference on, St. Louis, MO, Apr. 2008, pp. 332–343.
[20] F. Ingelrest, G. Barrenetxea, G. Schaefer, M. Vetterli, O. Couach, and
M. Parlange, “Sensorscope: Application-specific sensor network for
environmental monitoring,” ACM Trans. Sen. Netw., vol. 6, no. 2, pp.
17:1–17:32, Mar. 2010.
[21] S. Simoni, S. Padoan, D. F. Nadeau, M. Diebold, A. Porporato, G.
Barrenetxea, F. Ingelrest, M. Vetterli, and M. B. Parlange, “Hydrologic
response of an alpine watershed: Application of a meteorological
wireless sensor network to understand streamflow generation,” Water
Resour. Res., vol. 47, no. 10, 2011.
[22] B. Kerkez, S. D. Glaser, R. C. Bales, and M. W. Meadows, “Design and
performance of a wireless sensor network for catchment-scale snow and
soil moisture measurements,” Water Resour. Res., vol. 48, no. 9, 2012.
[23] M. Berti, M.L.V. Martina, S. Franceschini, S. Pignone, A. Simoni, M.
Pizziolo, “Probabilistic rainfall thresholds for landslide occurrence using
a Bayesian approach,” J. Geophys. Res. Earth Surf. (2003–2012), vol.
117, no. F4, 2012.
[24] V. Montesarchio, E. Ridolfi, F. Russo, F. Napolitano,“Rainfall threshold
definition using an entropy decision approach and radar data,” Nat.
Hazards Earth Syst. Sci., vol. 11, no. 7, pp. 2061-2074, 2011.
[25] S.A. Sepúlveda, C. Padilla, “Rain-induced debris and mudflow
triggering factors assessment in the Santiago cordilleran foothills,
Central Chile,” Nat. Hazards, vol. 47, no. 2, pp. 201-215, 2008.
@article{"International Journal of Business, Human and Social Sciences:69640", author = "D. Pinto and L. Castro and M.L. Cruzat and S. Barros and J. Gironás and C. Oberli and M. Torres and C. Escauriaza and A. Cipriano", title = "Decision Support System for a Pilot Flash Flood Early Warning System in Central Chile", abstract = "Flash Floods, together with landslides, are a common
natural threat for people living in mountainous regions and foothills.
One way to deal with this constant menace is the use of Early
Warning Systems, which have become a very important mitigation
strategy for natural disasters.
In this work we present our proposal for a pilot Flash Flood Early
Warning System for Santiago, Chile, the first stage of a more
ambitious project that in a future stage shall also include early
warning of landslides.
To give a context for our approach, we first analyze three existing
Flash Flood Early Warning Systems, focusing on their general
architectures. We then present our proposed system, with main focus
on the decision support system, a system that integrates empirical
models and fuzzy expert systems to achieve reliable risk estimations.
", keywords = "Decision Support System, Early Warning Systems,
Flash Flood, Natural Hazard.", volume = "9", number = "3", pages = "990-8", }
