Demonstrating the value of community-based ('citizen science') observations for catchment modelling and characterisation

JOURNAL OF HYDROLOGY

卷:548

Article

Starkey, Eleanor¹  Parkin, Geoff¹  Birkinshaw, Stephen¹  Large, Andy²  Quinn, Paul¹  Gibson, Ceri^3,4 

[1] Newcastle Univ, Sch Civil Engn & Geosci, Newcastle Upon Tyne NE1 7RU, Tyne & Wear, England

[2] Newcastle Univ, Sch Geog Polit & Sociol, Newcastle Upon Tyne NE1 7RU, Tyne & Wear, England

[3] Shawwell Business Ctr, Tyne Rivers Trust, Unit 8, Corbridge NE45 5PE, Northd, England

[4] Freshwater Biol Assoc, Ambleside LA22 0LP, Cumbria, England

关键词: Community-based;    Citizen science;    Monitoring;    Flash flood;    Hydrological modelling;    SHETRAN;   

DOI  :  10.1016/j.jhydrol.2017.03.019

来源: Elsevier

【 摘 要 】

Despite there being well-established meteorological and hydrometric monitoring networks in the UK, many smaller catchments remain ungauged. This leaves a challenge for characterisation, modelling, forecasting and management activities. Here we demonstrate the value of community-based ('citizen science') observations for modelling and understanding catchment response as a contribution to catchment science. The scheme implemented within the 42 km(2) Haltwhistle Burn catchment, a tributary of the River Tyne in northeast England, has harvested and used quantitative and qualitative observations from the public in a novel way to effectively capture spatial and temporal river response. Community-based rainfall, river level and flood observations have been successfully collected and quality-checked, and used to build and run a physically-based, spatially-distributed catchment model, SHETRAN. Model performance using different combinations of observations is tested against traditionally-derived hydro graphs. Our results show how the local network of community-based observations alongside traditional sources of hydro-information supports characterisation of catchment response more accurately than using traditional observations alone over both spatial and temporal scales. We demonstrate that these community-derived datasets are most valuable during local flash flood events, particularly towards peak discharge. This information is often missed or poorly represented by ground-based gauges, or significantly underestimated by rainfall radar, as this study clearly demonstrates. While community-based observations are less valuable during prolonged and widespread floods, or over longer hydrological periods of interest, they can still ground-truth existing traditional sources of catchment data to increase confidence during characterisation and management activities. Involvement of the public in data collection activities also encourages wider community engagement, and provides important information for catchment management. (C) 2017 The Authors. Published by Elsevier B.V.

【 授权许可】

Free