EF30FORWARD:AN EFFICIENT INDICATION INSTRUMENT FORT HE ASSESSMENT OF RELIABIITY OF TORRENT CONTROL PROTECTION WORKS IN ALPINE WATERSHEDS – A WORKABLE CONCEPT IN THE FRAMEWORK OF INTEGRATED RISK MANAGEMENT.

(1)

– 88 – 1 – 8 –

EF30FORWARD:

AN EFFICIENT INDICATION INSTRUMENT FORT HE ASSESSMENT OF RELIABIITY OF TORRENT CONTROL PROTECTION WORKS IN ALPINE WATERSHEDS – A

WORKABLE CONCEPT IN THE FRAMEWORK OF INTEGRATED RISK MANAGEMENT.

Bruno Mazzorana¹ ABSTRACT

The Autonomous Province of Bolzano is an Alpine Province that, during the last century, invested a lot of resources in an active protection strategy against natural hazards constructing a huge number of torrent control protection measures, a basic condition for agricultural - rural and industrial development. The demand on a high protection level coupled with decreasing financial resources available for the construction of new protection structures implies that public offices devoted to the pri- marily to the construction of protection measures had and have to change their strategy empowering the maintenance sector; this again implies that there is an absolute need to know the location and condition of all protection measures constructed in the past, to have indications of possible natural hazard phenomena on the whole territory, to have clear prioritization criteria for implementing a successful and cost efficient maintenance strategy in the next decade. There is an absolute need to merge information about frequency and intensity of natural hazard phenomena, information about failure propensity of the protection works, information about the expected damage in the deposi- tional areas. Furthermore this information has to be easily obtained, should permit comparisons in time and space, should reveal univocally the weak points in the protection system and should be a useful information basis fort he decision making process on how to allocate the restricted budget available.

So the EF30foreward concept is based on available data sources or data that can be obtained in a rather short time and with sustainable efforts. The following key points are relevant: a) the availability of hazard indication maps; b) a procedure to assess both the structural and functional efficiency of the protection measures and the protection system as a whole; c) an indication on the damage potential. So three indicators have been developed:

• ERI: Indicator of external relevancy: Connects the relevancy of the objects that have to be saved or protected and the importance of the considered protection measure; it’s based on the hazard indication map and the map of potential damage categories;

• CFI: Indicator of condition and functionality: Explains the condition – failure predisposition – of the considered protection measure and its functional efficiency with respect to hazard reduction; it’s based on the survey forms for torrent control measure condition description EF30Full and E30Quick;

• LEI: Indicator of loading and effects: identifies particular loading configurations in certain torrent portions that could lead to selective failure processes of certain protection works. If this event takes place the near surroundings can be more easily endangered. It’s based on the outcomes of the compiled field survey forms and indications coming from post event docu- mentation.

These three indicators can be combined in order to obtain a measure of overall relevancy of the considered protection work. This indicator is named TPI: Indicator of priority in torrent control.

The next figure gives an overview on the workflow of the EF30foreward concept:

1 PHD – Student at Boku Vienna and Uni-Trento – is working at the Department of hydraulic engineering of the Auto- nomous Province of Bolzano e-mail: bruno.mazzorana@provincia.bz.it ; tel:0471414567 ; cell: 3477279927

2 Fig. 1: Workflow of the EF30foreward concept

The relative weights of the single indicators have to be assessed by means of an expert elicitation among both scientists and practitioners. The elicitation methodology refers to an adapted Delphi method used for similar purposed also in the field of dam safety. The inference module for the de- termination of the failure predisposition of a certain torrent control measure is based on neural network techniques. In principle a classification neural network has been adopted; it’s a feed forward ANN with a backward propagation learning algorithm. Further details will be exposed in the extended paper. The indicator TPI can be visualized as follows:

Fig. 2: the overall indicator TPI

The TPI Indicator shows effectively the overall condition of the protection system in Alpine watersheds. Each point repre- sents a certain protection measure and the distance from the origin of the coordinate system identifies the TPI Indicator. Also an efficient comparison between different protection systems (different point colors) can be performed. Furthermore it’s possible to monitor the evolution of the condition of the protection system in time (the points are moving in space) under the assumption of the availability the data of these two time periods.

In any case the goal is reduce as much as possible the distances of the points applying the maintenance strategy, which means that the sum of the different TPT indicator values has to be minimal.

An optimization of the allocation of resources should be possible. The modular architecture of EF30forward is adaptable to different levels of data availability. This could permit an extended application also in other Alpine Regions as well, contributing to the development of a common maintenance strategy in order to keep a high protection level.

Keywords: integrated risk management, Alpine watersheds 1

EF30FORWARD:

1

EF30FORWARD:

(2)

– 88 – – 8 – 2 Fig. 1: Workflow of the EF30foreward concept

The relative weights of the single indicators have to be assessed by means of an expert elicitation among both scientists and practitioners. The elicitation methodology refers to an adapted Delphi method used for similar purposed also in the field of dam safety. The inference module for the de- termination of the failure predisposition of a certain torrent control measure is based on neural network techniques. In principle a classification neural network has been adopted; it’s a feed forward ANN with a backward propagation learning algorithm. Further details will be exposed in the extended paper. The indicator TPI can be visualized as follows:

Fig. 2: the overall indicator TPI

The TPI Indicator shows effectively the overall condition of the protection system in Alpine watersheds. Each point repre- sents a certain protection measure and the distance from the origin of the coordinate system identifies the TPI Indicator. Also an efficient comparison between different protection systems (different point colors) can be performed. Furthermore it’s possible to monitor the evolution of the condition of the protection system in time (the points are moving in space) under the assumption of the availability the data of these two time periods.

In any case the goal is reduce as much as possible the distances of the points applying the maintenance strategy, which means that the sum of the different TPT indicator values has to be minimal.

An optimization of the allocation of resources should be possible. The modular architecture of EF30forward is adaptable to different levels of data availability. This could permit an extended application also in other Alpine Regions as well, contributing to the development of a common maintenance strategy in order to keep a high protection level.

Keywords: integrated risk management, Alpine watersheds 1

EF30FORWARD:

1