A. Carrara (CNR-CSITE, Bologna, Italy)

M. Cardinali, F. Guzzetti and P. Reichenbach (CNR-IRPI, Perugia, Italy)

 

In the recent years, the diffusion of new technologies has led among institutions and individuals to a great expectation on their potential in coping with natural disasters. Today industrialised societies are increasingly less eager to invest a great deal of money to reduce natural risks by means of structural measures; hence, the new issue consists in the development of warning systems which should minimise the loss of lives without large, long-term investments. Several popular misconceptions were then borne and spread out. A computer-generated map is considered more accurate and credible than the same map but hand-drafted. Likewise, a landslide hazard map which was obtained through GIS operations, is often assumed to be more objective and unbiased than a comparable hand-made product attained with the same input data and founded on the same conceptual model. A great expectation is currently placed on the exploitation of satellite imagery and ground wicrowave systems for timely forecasting extreme rainfall events. The reality seems to be somewhat less than those optimistic hopes. Investigators are increasingly investing in tuning up hazard models founded upon existing, ill-reliable data than attempting to initiate long-term, academically ill-rewarded, projects for the acquisition of new basic information on the causal factors of catastrophic events. Governmental institutions are frequently involved in risk reduction projects whose design and implementation appear guided more from political issues than technical ones. There is a general unwise tendency to search for data which can be collected at low cost than to attempt to capture those which are most physically related to the causes of catastrophes. If the economic, political and cultural causes of this unhealthy state cannot be removed, the International Decade for Natural Disaster Reduction will likely end without significant advancements in the prediction and control of natural disasters.