期刊
HYDROLOGICAL SCIENCES JOURNAL
卷 65, 期 5, 页码 823-841出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/02626667.2019.1578966
关键词
citizen science; crowdsourcing; stream level; stream level class; streamflow; accuracy; CrowdWater
资金
- Swiss National Science Foundation [Schweizerischer Nationalfonds zur Forderung der Wissenschaftlichen Forschung] [163008]
Streamflow data are important for river management and the calibration of hydrological models. However, such data are only available for gauged catchments. Citizen science offers an alternative data source, and can be used to estimate streamflow at ungauged sites. We evaluated the accuracy of crowdsourced streamflow estimates for 10 streams in Switzerland by asking citizens to estimate streamflow either directly, or based on the estimated width, depth and velocity of the stream. Additionally, we asked them to estimate the stream level class by comparing the current stream level with a picture that included a virtual staff gauge. To compare the different estimates, the stream level class estimates were converted into streamflow. The results indicate that stream level classes were estimated more accurately than streamflow, and more accurately represented high and low flow conditions. Based on this result, we suggest that citizen science projects focus on stream level class estimates instead of streamflow estimates.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据