This research addresses the issue of rising soil temperatures, driven by climate change. As the Drinking Water Distribution System (DWDS) is located in the sub-surface, the drinking water temperature in the distribution mains attains this rising soil temperature. Because the temperature of drinking water is an important determinant of water quality, Dutch law mandates that drinking water temperature may not exceed 25 °C. This study assesses several measures, including their quantitative impact on soil temperature reduction, and consequently on drinking water temperature reduction. These measures center on modifying the ground coverage, as this measure can be implemented without excavation and disrupting existing infrastructure in the sub-surface. This includes different types of ground coverage (e.g. changing concrete tiles, which are the existing top layer type, to vegetation), and creating temporary shade or applying white paint to the existing coverage type. The effect of (re)locating pipes to a deeper level or in the shade are also considered. The effect at the depth of a distribution main is analysed, which is shallow (0.7 m) in Rotterdam, and 1 m depth in general in the Netherlands.
Measurements confirm the significant influence of the ground coverage, mainly impacting the soil temperature in vertical (in-depth) direction. A detailed analysis reveals the quantitative effectiveness of the considered measures, indicating substantial cooling potential by modifying the ground coverage. Replacing concrete tiles with vegetation (in sandy soil) results in the most cooling effect of all analysed measures. White paint on concrete tiles emerges as particularly effective in reducing the soil temperature at the current depth in Rotterdam (0.7 m), and is considered an easily executable measure to prevent exceedances of the 25 °C threshold, mainly in case of urgency. In general, modifying the top layer as measure is considered feasible. This is because it avoids the need for excavation, in contrast to the alternative measures of relocation to a deeper level or in the shade. Additionally, the study quantifies soil temperature through simulations. A comparative analysis between simulations conducted by the soil temperature model and measurements facilitates an examination of the anticipated progression and the predicted effect of measures by the model, allowing for the formulation of recommendations to enhance the model.
As the results indicate that modifications to the ground coverage can significantly contribute to cooling the soil, this can mitigate potential threats to drinking water quality. The study advocates an integrated approach to decision-making, which includes collaboration between municipalities, drinking water companies, and research institutes. This cooperative effort is essential for identifying and implementing the most suitable and effective measures to safeguard high-quality drinking water, both now and in the future.

Personal weather station (PWS) networks have the potential to supply precipitation data at high spatial and temporal resolution for urban hydrological modeling. Past research has shown promising results on the quality of PWS data, for example from Netatmo gauges, but studies on other PWS brands are limited. This thesis assesses the quality of precipitation measurements from the Alecto WS-5500 personal weather station. During a controlled experimental setup in an urban environment, the Alecto was found to overestimate rainfall due to incomplete emptying of the tipping bucket. Correcting this mechanical error by a 10 percent reduction factor lowered the relative bias to 0.00 or 0.06, when comparing the station to official KNMI gauge or KNMI gauge-adjusted radar, respectively. Correlations were high between stations with non-faulty setups, but at the 5 minute resolution, correlations were substantially lowered by sampling errors caused during the data transfer to PWS data platforms. A quality control method from de Vos et al. (2019) was adapted and applied to data from a citizen science project in Delft, the Netherlands, which had a 12-month period of measurements for 20 stations, and a 3-month period of measurements from 40 stations. The filtering of faulty zero measurements was improved by applying the filter on hourly accumulations, and the bias correction was stabilized. The variation over individual PWSs, however, remained high due to setup differences. The complex installation process for citizens and issues with software and data accessibility are limiting factors and warrant further research to improve the usability of PWS data for urban hydrological applications.