Intensive urbanisation enhances warming of cities’ ambient and subsoil environment. The local drinking water distribution system (DWDS) is likewise affected. Hotspots of anthropogenic heating were perceived to influence drinking water temperature and pose a threat for microbial drinking water quality. Information on temporal and spatial relation between drinking water temperature and microbial indicating parameters was however scarce. This is especially the case for a full scale unchlorinated DWDS in a metropolitan area. Therefore, this research aimed to explore the spatial and temporal relation between drinking water temperature and microbial indicating parameters Aeromonas and Heterotrophic Plate count (HPC). 11 Years of sample data from the DWDS in the metropole of Amsterdam was explored, with the objective to possibly draw conclusions beyond this DWDS. This DWDS consists of two interconnected subsystems. Each subsystem is fed by its own treatment facility. Areas with repetitive exceedance of threshold temperature (14 oC) for accelerating Aeromonas growth, were not inextricably tied to repetitive exceedance of the Aeromonas standard for safe drinking water. Areas with repetitive exceedance of the Aeromonas standard were often linked to prolonged residence time. For regions on the outskirt of observed DWDS it was suggested that the influence of residence time was more important than the absolute water temperature to explain Aeromonas concentrations.

Long-term sea level change and its spatial and temporal variability measured with tide gauge stations along the Dutch coast have been studied. This study investigates how time series length and modeling choices influence the adoption of a quadratic over a linear sea level model. We apply linear and quadratic models to corrected tide gauges, for differing model start years. Longer models show more consistent results between stations, with less inter-station variability and smaller uncertainties. This improvement of consistency diminishes when using time series longer than 40 years. We find indications of a break-point in trends in the period 1978-1998. Quadratic models result in minor but relevant acceleration for longer time series, but do not perform sufficiently for time series shorter than 20 years. Comparing model quality between linear and quadratic models generally indicate better performance of quadratic models, but results are not conclusive to justify model adoption. A station mean is less conclusive for quadratic models than for linear models and sensitive to choice of stations and model length. Keywords: mean sea level variability, sea level change, sea level acceleration, tide gauge records, Dutch coast