This PhD project aims to examine the potential of “crowdsourcing”, meaning observations of voluntary participants. As the name suggests, the project looks at the potential of crowdsourcing in the field of hydrology. We will collect water level, streamflow and soil moisture data, as well as data about the dynamics of temporary streams, plastic pollution and general stream type data. The project does not only look at the possibilities of collecting data but also at the value of this data for hydrological forecasts. The long-term aim of the project is to collect a large amount of data and to improve the forecast of hydrological events, such as droughts or floods.
There are two basic parts of the CrowdWater project. On one hand, we will assess public involvement in hydrological observations. For this we use a “geocaching” type approach with the help of smartphones. By using an app users can install a virtual measuring station, called spot. Anyone can add their observations to this station and all observations will be collected and published anonymously in the data overview. Another goal of the CrowdWater project is to analyse the potential of using the collected data for hydrological models. This question will be addressed by using hydrological computer models to predict streamflow. These models will assess the benefit of the crowd-sourced data.