The backbone of the Amsterdam Ordnance Datum (NAP) is a network of about 400 primary subsurface markers. Relative movements between the primary subsurface markers are measured with spirit levelling once in 10-20 years. However, little is known about absolute vertical movements of the primary network. This information is indispensable for the interpretation of water level measurements at the tide gauges along the Dutch coast. It may be provided by gravity measurements. Here we present a time-series analysis of more than twenty years of gravity measurements at the stations Westerbork, Epen, Zundert, and Radio Kootwijk. It reveals that only station Epen shows a statistically significant movement of -0:252±0:066 μGal yr-1, which corresponds to an uplift of 1:3±0:5mmyr-1. For the other stations, the trends are statistically not different from zero at a significance level of 0.05. Corrections for water table variations are found to be indispensable; peak-to-peak amplitudes range from 4 μGal (Westerbork) to 28 μGal (Radio Kootwijk). Depsite some fundamental objections, corrections for instrumental offsets reduce the data scatter. First experiments with 7 years of soil moisture data acquired at station Radio Kootwijk reveal that the gravity signal of soil moisture variations has a standard deviation of 2:2 μGal, which is comparable to the noise standard deviation of measured gravity.

We present a local quasi-geoid (QG) model which combines a satellite-only global gravity model with local data sets using weighted least squares. The QG is computed for an area comprising the Netherlands, Belgium, and the southern North Sea. It uses a two-scale spherical radial basis function model complemented by bias parameters to account for systematic errors in the local gravity data sets. Variance factors are estimated for the noise covariance matrices of all involved data sets using variance component estimation. The standard deviation (SD) of the differences between the computed QG and GPS/leveling data is 0.95 and 1.52 cm for the Netherlands and Belgium, respectively. The fact that the SD of the control data is about 0.60 and 1.20 cm for the Netherlands and Belgium, respectively, points to a lower mean SD of the computed QG model of about 0.7 cm for the Netherlands and 1.0 cm for Belgium. The differences to a QG model computed with the remove-compute-restore technique range from −5.2 to 2.6 cm over the whole model domain and from −1.5 to 1.5 cm over the Netherlands and Belgium. A variogram analysis of the differences with respect to GPS/leveling data reveals a better performance of the computed QG model compared to a remove-compute-restore-based QG model for wavelengths >100 km for Belgium but not for the Netherlands. The latter is due to the fact that at the spatial scales resolved by the global gravity model, variance component estimation assigns significantly lower weights to the local data set in favor of the global gravity model.