H110
Uncertainty and Error in Hydrological Citizen Science Observations
Uncertainty and Error in Hydrological Citizen Science Observations
Session ID#: 156874
Session Description:
The engagement of non-scientists in data collection and analysis has greatly enriched many areas of hydrologic research. However, owing to the non-professional nature and variable skills of citizen scientists, this approach typically entails significant biases and uncertainty. The low-quality, qualitative, and fragmentary nature of many of these hydrologic datasets engenders a lack of trust – for academic and industrial workers, and policymakers – that may reduce their uptake and preclude future operationalisation of proof-of-concept studies. A generalised lack of formal data validation also raises questions about their utility. It is therefore critical to bracket uncertainty and properly characterise error in such citizen-collected hydrologic datasets.
We welcome submissions across all hydrologic data collection activities including those related to natural hazards. This session aims to showcase analytical and numerical techniques to quantify and tackle uncertainty and error in such datasets, as well as proof-of-concept and field-based examples of data collection activities.
Index Terms:
1848 Monitoring networks [HYDROLOGY]
1873 Uncertainty assessment [HYDROLOGY]
1880 Water management [HYDROLOGY]
9810 New fields (not classifiable under other headings) [GENERAL OR MISCELLANEOUS]
Primary Convener: Jonathan D. Paul, Royal Holloway University of London, Department of Earth Sciences, Egham, United Kingdom
Conveners: Jessica Abbie Eisma, University of Texas at Arlington, Civil Engineering, Arlington, TX, United States and Jeffrey C. Davids, California State University Chico, Chico, CA, United States
Student/Early Career Convener: Rajaram Prajapati, Smartphones For Water Nepal, Lalitpur, Nepal
See more of: Hydrology
