18 Jul 2023
 | 18 Jul 2023

Leveraging gauge networks and strategic discharge measurements to aid development of continuous streamflow records

Michael J. Vlah, Matthew R. V. Ross, Spencer Rhea, and Emily S. Bernhardt

Abstract. Streamflow, or discharge, is an essential measure in the study of rivers and streams. However, quantifying continuous discharge can be difficult, especially for nascent monitoring efforts, due to the challenges of establishing gauging locations, sensor protocols, and installations. Here, we investigate the potential for both simple and complex models to accurately estimate continuous discharge (at least daily estimates), using only discrete manual measurements of streamflow. We were inspired to do this work because some continuous discharge series generated by the National Ecological Observatory Network (NEON) during its pre- and early-operational phases (2015–present) are marked by anomalous data due to sensor drift, gauge movement, and incomplete rating curves. Using field-measured discharge as truth, we reconstructed continuous discharge for all 27 NEON stream gauges over this period via linear regression on nearby donor gauges and/or prediction from neural networks trained on a large corpus of established gauge data. Top reconstructions achieved median efficiencies of 0.83 (Nash-Sutcliffe, or NSE) and 0.81 (Kling-Gupta, or KGE) across all sites, and improved KGE at 11 sites versus published data. Estimates from this analysis inform ~199 site-months of missing data in the official record, and can be used jointly with NEON data to enhance the descriptive and predictive value of NEON’s stream data products. We provide 5-minute composite discharge series for each site that combine the best estimates across modeling approaches and NEON’s published data.

Michael J. Vlah et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-1178', Roy Sando, 16 Aug 2023
  • RC2: 'Comment on egusphere-2023-1178', Anonymous Referee #2, 26 Aug 2023
  • CC1: 'Comment on egusphere-2023-1178', Nick Harrison, 30 Aug 2023

Michael J. Vlah et al.

Data sets

Composite discharge series for all NEON river/stream sites, plus figures and all input/output data associated with Vlah, Ross, Rhea, Bernhardt. 2023. "Virtual gauges: the surprising potential to reconstruct continuous streamflow from strategic measurements" Michael J. Vlah, Matthew R. V. Ross, Spencer Rhea, Emily S. Bernhardt

Model code and software

vlahm/neon_q_sim: Preprint phase Michael J. Vlah

Michael J. Vlah et al.


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Short summary
Virtual stream gauging enables continuous streamflow estimation where a gauge might be difficult or impractical to install. We reconstructed flow at 27 gauges of the National Ecological Observatory Network (NEON), informing ~199 site-months of missing data in the official record, and improving upon official estimates at 11 sites. This study shows that machine learning, but also routine regression methods, can be used to supplement existing gauge networks and reduce monitoring costs.