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Accurate water levels using PREMO

M. Schroevers, A.C. Bijlsma, M. Verlaan, L.L. Dorst

The Hydrographic Service of the Royal Netherlands Navy publishes navigation charts for the Dutch sector of the North Sea. A major source of error in the charted depths based on echo soundings is the so-called “tidal reduction” of the measurements. Tidal reduction is the correction for the local water level, depending on tides and meteorological conditions, relative to a specified reference surface. At sea the vertical position, and thereby the reduction, cannot be determined sufficiently accurate from satellite positioning (GPS). Therefore, the water levels in the survey areas are obtained from “bottom tide gauges” or by spatial interpolation between fixed tidal stations. The availability of hydrodynamic models predicting the daily movement of the North Sea sparked the redesign of the reduction tool PREMO (PREdiction Module) The new version uses data-assimilated model predictions of water levels, astronomical tides and surges stored in the databases of Rijkswaterstaat. PREMO enables the hydrographic vessels of the Navy and Rijkswaterstaat to retrieve the water level along their route using an internet connection to access the databases. The main advantage of the model-based approach is that with every model update the user benefits directly from increased accuracy. By 2013, the inclusion of a new hydrodynamic model will make the PREMO results more accurate than the interpolation methods and reduce the need for bottom tide gauges. Increased accuracy will allow hydrographic measurements to be spaced further apart saving time and money while still meeting the accuracy requirements.
Nowadays water movement data in general is continuously available over large areas, but these are buried in databases. The techniques used in PREMO can make this information available for a large group of users for whom vertical positioning, wave predictions or current are important, for example for offshore and shipping activities. This approach can help to optimize cost and reduce risks.