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.