This study discusses the application of a multiple logistic regression analysis in Khao Chai Son and Mueang Phatthalung districts (Phatthalung Province in southern Thailand), which were the two worst flooded districts in the 2011 inundation. The aim is to test an easy, rapid, and cost-effective method to asses flood susceptibility in a data-poor country. Climatic, topographic, and geological data have been overlaid with those of the flood events occurred in the study area from 2007 to 2011. Results showed a positive spatial correlation between the northeast monsoon precipitation and flooding. Moreover, using the rainfall projection of the U.S. National Center for Atmospheric Research the proposed model forecasts a sharp increase of flood susceptibility in the study area by the year 2050. Given the versatility of such model, local governments could easily use it to define the areas in their territories most exposed to flood hazard and timely implement risk reduction policies and practices.
A rapid method for flood susceptibility mapping in two districts of Phatthalung Province (Thailand): present and projected conditions for 2050 / Marconi, Michele; Gatto, Beatrice; Magni, Michele; Marincioni, Fausto. - In: NATURAL HAZARDS. - ISSN 0921-030X. - STAMPA. - 81:1(2016), pp. 329-346. [10.1007/s11069-015-2082-2]
A rapid method for flood susceptibility mapping in two districts of Phatthalung Province (Thailand): present and projected conditions for 2050
MARINCIONI, Fausto
Writing – Review & Editing
2016-01-01
Abstract
This study discusses the application of a multiple logistic regression analysis in Khao Chai Son and Mueang Phatthalung districts (Phatthalung Province in southern Thailand), which were the two worst flooded districts in the 2011 inundation. The aim is to test an easy, rapid, and cost-effective method to asses flood susceptibility in a data-poor country. Climatic, topographic, and geological data have been overlaid with those of the flood events occurred in the study area from 2007 to 2011. Results showed a positive spatial correlation between the northeast monsoon precipitation and flooding. Moreover, using the rainfall projection of the U.S. National Center for Atmospheric Research the proposed model forecasts a sharp increase of flood susceptibility in the study area by the year 2050. Given the versatility of such model, local governments could easily use it to define the areas in their territories most exposed to flood hazard and timely implement risk reduction policies and practices.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.