2022 Early Hearing Detection & Intervention Virtual Conference

March 13 - 15, 2022

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5/23/2019 | 9:00 AM - 9:15 AM | INTEGRATING CITIZEN SCIENCE HYDROLOGIC OBSERVATIONS INTO A HYDROLOGIC MODEL FOR STREAMFLOW AND STREAM TEMPERATURE FORECASTING | 151 DEF

INTEGRATING CITIZEN SCIENCE HYDROLOGIC OBSERVATIONS INTO A HYDROLOGIC MODEL FOR STREAMFLOW AND STREAM TEMPERATURE FORECASTING

Small stream networks often lack traditional sources of observed hydrologic data (e.g., government monitored gauges). Crowd-sourced observations have the potential to bridge this data gap. This study explores the potential for real-time crowd-sourced data to improve complex computational hydrologic models. The Boyne River basin in northern Michigan was selected as a case study to demonstrate crowd-source data assimilation in a distributed hydrological model. We utilized CrowdHydrology, a citizen science hydrologic network, to obtain local stream stage and stream temperature measurements sent via text message by citizen scientists. Our approach retrieves CrowdHydrology observations and nearby weather data on a weekly basis, which are then integrated into a Soil and Water Assessment Tool (SWAT) hydrologic model of the Boyne River Watershed. Within this framework, the hydrologic model is re-calibrated on a bi-weekly schedule using the Ensemble Kalman Filter. Each new calibrated model provides a more accurate estimate of a 7-day forecast of streamflow and stream temperature throughout the river basin. This novel approach can potentially benefit small communities by providing information on local water resources derived from complex hydrological models.

Modeling
Watershed
Temperature

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Presenters/Authors

Darren Ficklin (), Indiana University, dficklin@indiana.edu;