| 06 May 2026
Network-Based Subbasin-Scale Mapping of Streamflow Alteration in Ontario, Canada
Abstract. Dams, reservoirs, and waterpower facilities are central to regional water management, but they can induce streamflow alterations that propagate downstream through connected river networks and complicate hydrologic modeling and aquatic ecosystem assessment. Existing streamflow indicators often quantify alteration only at discrete locations (e.g., hydrometric gauges), thus limiting spatially continuous, subbasin-scale mapping of where upstream infrastructure may influence downstream flows. We propose the Streamflow Alteration Index (SAI), a network-based screening metric that propagates point-based alteration signal sources downstream through a routing network to map potential alteration influence. The framework includes paired indices: SAI_I (0–100 %) and SAI_II (0–100 %), representing two levels of influence derived from confirmed (Level I) and potential (Level II) alteration signal sources. We implemented SAI to develop the SAI v1.0 database for Ontario, Canada, using the Ontario Lake and River Routing Product Version 2 (OLRRP v2) network and an inventory of 643 alteration signal sources compiled from provincial datasets. The resulting product provides seamless, high-resolution, network-based, subbasin-scale mapping of streamflow alteration across Ontario and enables SAI estimates at both gauged and ungauged nodes within the routing network. We validated SAI by classifying subbasins containing hydrometric gauges as natural, conditional, or altered and compared these classes against two independent references: Reference Hydrometric Basin Network (RHBN) gauges (with minimal human impact) and Water Survey of Canada (WSC) gauge “Natural” and “Regulated” labels. SAI shows strong agreement for gauges labelled natural: 86 % of RHBN natural gauges and 86 % of WSC-natural gauges are classified as natural by SAI. For WSC-regulated gauges, SAI classifies 74 % as conditional or natural. Overall, SAI v1.0 provides a practical, objective screening product for large-domain hydrologic and aquatic applications without requiring detailed dam operating information, and it offers a scalable pathway toward national- to global-scale, network-based screening products for streamflow alteration.
Review of ESSD-2026-286 “Network-Based Subbasin-Scale Mapping of Streamflow Alteration in Ontario, Canada” by Shen et al.
This is a timely database that provides quantification of the local and downstream influence of reservoirs on streamflow proxy across Ontario, Canada. A Streamflow Alteration Index (SAI) is presented, but not as a hydrologic metric, as a simpler areal metric. The value of a simple metric is a spatially complete picture of reservoir influence throughout a river network. This reviewer appreciates the presentation using two types to express some uncertainty. The reviewer also agrees with the routing approach using hydrologic sequencing and nodes. Well done. This reviewer has very little feedback regarding how to improve the presentation. Below are a few specific comments to consider for perhaps some improved clarity or suggestions for next steps.
32: What is the precision of Lehner 2024? Are these waterbodies 0.1 square km or above. Most ponds by number are smaller than that (e.g., https://doi.org/10.1029/2019GL083937). A reader may benefit from some size classification.
33: It would be more useful to express as volume (% of total water volume) and area (% of drainage area) if possible for better context.
36: other good citations regarding network fragmentation: https://doi.org/10.5194/hess-13-2413-2009 and https://doi.org/10.1126/science.1107887.
128: this reviewer agrees that a simple streamflow alteration metric is needed and useful.
171: How comprehensive are these datasets? Meaning, are there other waterbodies perhaps missed? A reader would benefit from knowledge of completeness.
527: spatially complete.
533: A spatial/static picture is valuable. How would one update the SAI for dynamic representation? A reader may benefit from a statement that with a SAI, a next step could be dynamic optimization to adjust the SAI as needed.
540: good point. Also consider some discussion around the idea that not all waterbodies are created equal, and their geometries may be another factor to consider in the SAI (https://doi.org/10.1038/s41467-018-05156-x). Also, while this approach assumes drainage area scales with streamflow, how could this SAI metric be used as a water-quality influence indicator?