Network-based subbasin-scale mapping of streamflow alteration in Ontario, Canada
- 1Department of Civil and Environmental Engineering, University of Waterloo, Ontario, Canada
- 2Environmental and Life Sciences Graduate Program, Trent University, Ontario, Canada
- 3Aquatic Research and Monitoring Section, Ministry of Natural Resources, Trent University, Ontario, Canada
Abstract
Dams, reservoirs, waterpower facilities, and other water-control structures can modify streamflow and propagate their influence downstream through connected river networks, complicating hydrologic modelling and aquatic ecosystem assessment. Large-domain assessments often rely on binary agency classifications at hydrometric gauges (e.g., “natural” and “regulated”) or on storage- and discharge-based metrics that are difficult to apply consistently where operational data are incomplete. We introduce the Streamflow Alteration Index (SAI), a parsimonious, network-based screening metric that estimates the percentage of upstream drainage area whose routed flow passes through mapped alteration signal sources. Under a first-order drainage-area scaling approximation, SAI provides a proxy for the fraction of streamflow potentially exposed to upstream alteration sources, rather than a measure of the exact magnitude of hydrologic alteration. The framework comprises two paired indices, SAI_I (0 %–100 %) and SAI_II (0 %–100 %), independently representing confirmed Level I and potential Level II sources; values are propagated downstream by drainage-area-weighted mixing and reset at new sources of the same level. We compiled 2528 infrastructure records, of which 2476 were retained after geospatial alignment and screening. Following source classification and consolidation of multiple records within the same subbasin, 643 unique subbasins were identified as Level I and/or Level II alteration signal locations. The resulting SAI v1.0 database provides province-wide subbasin and river-reach layers for screening potential instream alteration at gauged and ungauged locations. We evaluated SAI-derived natural, conditional, and altered classes against 148 Reference Hydrometric Basin Network (RHBN) gauges, 125 additional Water Survey of Canada (WSC) gauges labelled natural, and 215 WSC-regulated gauges. SAI classified 86 % of both natural reference groups as natural, with no RHBN gauge classified as altered. Among WSC-regulated gauges, 26 % were classified as altered, 40 % as conditional, and 34 % as natural, highlighting differences between binary agency labels and the SAI screening framework and identifying sites requiring follow-up assessment. SAI v1.0 therefore provides a practical, transparent, and reproducible screening baseline for large-domain hydrologic and ecological applications without requiring detailed operating rules and offers a scalable framework for broader network-based assessments of potential streamflow alteration. The SAI v1.0 dataset is available from Zenodo (Shen et al., 2026; https://doi.org/10.5281/zenodo.19547932).
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BibTeX
@article{shen2026networkbased,
title = {{Network-based subbasin-scale mapping of streamflow alteration in Ontario, Canada}},
author = {H. Shen and B. A. Tolson and J. R. Craig and R. A. Metcalfe and R. A. Metcalfe and J. Romero-Cuellar and J. J. Luce},
journal = {Earth System Science Data},
year = {2026},
month = nov,
doi = {10.5194/essd-18-7915-2026},
url = {https://doi.org/10.5194/essd-18-7915-2026},
note = {CC BY},
}
RIS
TY - JOUR
TI - Network-based subbasin-scale mapping of streamflow alteration in Ontario, Canada
AU - H. Shen
AU - B. A. Tolson
AU - J. R. Craig
AU - R. A. Metcalfe
AU - R. A. Metcalfe
AU - J. Romero-Cuellar
AU - J. J. Luce
PY - 2026
DA - 2026/11/02
JO - Earth System Science Data
DO - 10.5194/essd-18-7915-2026
UR - https://doi.org/10.5194/essd-18-7915-2026
AB - Dams, reservoirs, waterpower facilities, and other water-control structures can modify streamflow and propagate their influence downstream through connected river networks, complicating hydrologic modelling and aquatic ecosystem assessment. Large-domain assessments often rely on binary agency classifications at hydrometric gauges (e.g., “natural” and “regulated”) or on storage- and discharge-based metrics that are difficult to apply consistently where operational data are incomplete. We introduce the Streamflow Alteration Index (SAI), a parsimonious, network-based screening metric that estimates the percentage of upstream drainage area whose routed flow passes through mapped alteration signal sources. Under a first-order drainage-area scaling approximation, SAI provides a proxy for the fraction of streamflow potentially exposed to upstream alteration sources, rather than a measure of the exact magnitude of hydrologic alteration. The framework comprises two paired indices, SAI_I (0 %–100 %) and SAI_II (0 %–100 %), independently representing confirmed Level I and potential Level II sources; values are propagated downstream by drainage-area-weighted mixing and reset at new sources of the same level. We compiled 2528 infrastructure records, of which 2476 were retained after geospatial alignment and screening. Following source classification and consolidation of multiple records within the same subbasin, 643 unique subbasins were identified as Level I and/or Level II alteration signal locations. The resulting SAI v1.0 database provides province-wide subbasin and river-reach layers for screening potential instream alteration at gauged and ungauged locations. We evaluated SAI-derived natural, conditional, and altered classes against 148 Reference Hydrometric Basin Network (RHBN) gauges, 125 additional Water Survey of Canada (WSC) gauges labelled natural, and 215 WSC-regulated gauges. SAI classified 86 % of both natural reference groups as natural, with no RHBN gauge classified as altered. Among WSC-regulated gauges, 26 % were classified as altered, 40 % as conditional, and 34 % as natural, highlighting differences between binary agency labels and the SAI screening framework and identifying sites requiring follow-up assessment. SAI v1.0 therefore provides a practical, transparent, and reproducible screening baseline for large-domain hydrologic and ecological applications without requiring detailed operating rules and offers a scalable framework for broader network-based assessments of potential streamflow alteration. The SAI v1.0 dataset is available from Zenodo (Shen et al., 2026; https://doi.org/10.5281/zenodo.19547932).
SN - 1866-3508
SN - 1866-3516
ER -