ATTN HPCN-TTN
[DEUTSCHE Projektbeschreibung]

The FLOAT Project


Saving freight costs by predicting Danube water levels

The problem

Inland shipping companies do not fully load their barges in order to increase their chances of navigating all sections of the waterway they are travelling without delay. If water levels drop below expectations and barges waste time waiting to pass a shallow stretch of river or must lighten their load via additional transshipment, transport costs are increased. It is only from April to July that ship operators may not expect problems with the water levels at the critical sections of the waterway. The critical sections in Austria are: Wachau and Wien-Bratislava.

Donau - critical sections of the waterway
Danube Map courtesy of ÖIR

This has a strong negative impact on the competitiveness of inland shipping. On one of the rivers most prone to this kind of problem - the Danube. However this mode of transport is an important alternative to land freighting, especially - in view of the growth in trade with Central and Eastern European Countries.

The idea

Given access to sufficiently accurate prediction of water levels on the Danube, in particular on critical sections of this waterway, carriers could adjust schedules and levels of cargo to the given water situation. This would reduce or eliminate waiting times, thus improving reliability of delivery, and raise the average load transported, lowering the freight costs. This applies to many European waterways and their users, but is of extreme relevance for Danube navigation.

The project

The project goals:

Project Partners

The goal of this project was to determine whether there is a need for HPCN techniques in order to create a water level prediction model which could be used to determine water levels at critical sections of a route one day in advance.

ÖIR selected some hydrological data from 1991-1994 and forwarded these to EVIS:

EVIS, a machine learning software product based on applying genetic algorithms to symbolic computation, was selected as the basis for the model generation.

Water level prediction model:
Based on the above mentioned hydrological and meteorological data the software provided by EVIS was trained to evolve a water level prediction model for one day in advance, using the data from 1991-1993.

How the EVIS Software works:

Why HPCN is used:

Results

To evaluate the quality of the prediction model, the results have been compared with the observed water level data of the next day for a one year period (4th year). The mean absolute deviation was 8,6 cm between the predicted and the actual water level.

The accuracy for the test prediction based on the training data set previously mentioned, was very promising for the 1 day prognosis. Although only a very small amount of input data was used for the prediction we obtained a very accurate prognosis: 85% of all predicted water levels for one year deviated no more than +/- 15 cm from the actual value.

Since the most important information for shipping companies is the prediction of low water levels we concentrated on the prediction of those data. Based on the small input data set first attempts were made to extend the prediction model to 7 days.

It is possible to parallelize the EVIS Software. Doubling the amount of computing resources can nearly halve the execution time. In order to calculate a water level prediction up to 14 days in advance - as demanded from the shipping companies with EVIS, the amount of data as well as the demand of computational power will raise. By using of HPCN an accurate prediction of water levels within reasonable time can be achieved.

FLOAT was integrated into activities carried out by the ÖIR as partner in EUDET, funded by the EC/DGVII under the IVth Framework Programme.

Please find further information at:
http://www.evis.co.at
http://www.impetus.gr/eudet.htm

Radio sound file (MS wave format), Copyright by ORF 1998