Reconstructing Flow Dynamics of Temporary Streams Using Citizen Science Data and a Hierarchical Network Structure

Abstract. Temporary (i.e., non-perennial) streams form a large fraction of the global stream network and are important habitats. However, they are generally excluded from official monitoring networks. Visual observations by citizen scientists provide a valuable opportunity to collect temporary stream data, but these observations are irregular in space and time. We used observations by citizen scientists to derive the hierarchical structure (i.e., fixed order) of stream wetting and drying for a forested hill in Zurich, Switzerland. The dataset consists of 2 to 235 (median: 64) observations for 55 sites, and at least one observation for 402 days over the three-year period. In addition, an expert determined the stream state for 59 sites on 24 days during a six-month period. The hierarchical structure was more uncertain for the citizen science dataset than for the expert data, likely due to the irregularity of the observations. However, the hierarchical structures were comparable when considering only the 26 overlapping sites for the overlapping observation period. The hierarchical structure could be used to predict the stream state based on observations for other sites, allowing us to fill in data gaps. The correlation between the percentage of sites with flowing water and cumulative net precipitation, furthermore, allowed us to extend the prediction of stream states to days for which there were no observations. This study highlights the usefulness of citizen science-based observations of intermittent streams for understanding stream network dynamics. Information on the accuracy of the hierarchy can be used to determine which sites are particularly useful to observe for gap filling and thus to give feedback to citizen scientists.