The prediction of the erosion of mudflats is hampered by inaccurate estimates of the erodibility distribution of the sediment bed. To investigate how erodibility varies in space and what the vertical distribution over the sediment depth is, comprehensive observations of the sediment properties, hydrodynamics and bed-level changes were conducted on an intertidal flat in the Western Scheldt Estuary, the Netherlands. The erosion potential on a mudflat is determined by the critical shear stress for erosion (τ_e), erosion rate coefficient (M) and local hydrodynamic conditions. A clear difference in hydrodynamic forcing was observed, leading to significant bed level variations at the low water line, where erosion often occurs during very shallow water condition, and a nearly constant bed level at the upper part. The erosion parameters τ_e and M could be determined over a sediment bed of 12 cm at the low water line. The erosion coefficient M can be considered constant with depth, although there is a large spreading. A clear vertical variation of τ_e was found: τ_e increased significantly downward from 0.10 Pa at the sediment surface to 1.13 Pa at 12 cm below the surface. Additionally, there was a strong indication that the presence of diatoms enhanced τ_e in the upper 2 mm of sediment by five times of the abiotic τ_e (from 0.09 Pa to 0.46 Pa). These findings lead to the following improvement for predicting morphological changes of tidal mudflats: (1) very shallow conditions should be better simulated, (2) the vertical distribution of τ_e should be considered. Otherwise, erosion rates can be overestimated, especially during extreme events, because exposure of the deeper well-consolidated layer likely occurs; and (3) an appropriate description of the effect of diatoms should be considered as part of the bottom boundary condition.

This paper introduces and compares two types of GML-based data standards for indoor location-based services, i.e., iIndoorGML and iIndoorLocationGML. By elaborating the advantages of the both standards and their data models, we conclude that the two data standards are complementary to each other. A jointed data model is presented to show the integration of the two standards. iIndoorGML can supply subdivision of building for data of iIndoorLocationGML, and the semantics of locations defined in iIndoorLocationGML can be added to iIndoorGML. By proposing two use cases, we take the initiative in attempting to combine the use of the two standards. The first case is to collect details from files of the two standards for an indoor path; the second one is to generate verbal directions for indoor guidance from files of the two standards. Some future work is given for further development, such as automatic integration of separate data from both standards.