AI-ready hydraulic risk prioritization of deteriorated Andean concrete channels
Journal
Frontiers in Built Environment
ISSN
22973362
Date Issued
2026-09-01
Author(s)
Núñez, Mayra Alejandra
Núñez, Samanda Monserrath
Guevara, Arlette Dayana
Type
Article
Abstract
Introduction
Open concrete channels in Andean watersheds convey irrigation water and urban stormwater, and their deterioration raises Manning’s roughness coefficient (n), alters specific energy (E) and consumes freeboard. Managers know that a channel is degraded but lack a reproducible procedure for turning that observation into a defensible intervention priority.
Methods
We characterise ten consecutive reaches (219 m) of a rectangular cyclopean-concrete channel in Ambato, Ecuador (b = 0.645 m; Q = 0.21 m
3
/s; s
0
≈ 0.03). Each reach was scored on a 1–5 Structural Damage Index and mapped to a Manning coefficient through an additive decomposition reported reach by reach. The coefficients were propagated through the Manning–Strickler equation, solved simultaneously with continuity, to obtain normal depth, velocity, Froude number, specific energy and freeboard. Because these quantities are deterministic functions of the assigned n, they are reported as transfer curves rather than as statistical relationships; analysis is confined to the observations themselves and to the propagation of observer uncertainty.
Results
Assigned coefficients ranged from 0.016 to 0.034, that is 23%–162% above the design value of 0.013. Departure of specific energy from the design condition ranged from 14.5% to 30.9%, and freeboard fell from 0.277 m to 0.160 m in the most degraded reach, a loss of 42% of the original margin. The transfer curve is not monotonic: the departure peaks near n ≈ 0.030 and declines beyond it, because specific energy passes through its minimum at the critical regime, reached here at n ≈ 0.0304. A one-class error in visual scoring displaces the departure by 8.6 percentage points on average and would change the intervention tier of six of the ten reaches; the two requiring immediate intervention are not among them.
Conclusion
Structured visual assessment combined with transparent hydraulic propagation yields a traceable intervention hierarchy reproducible with a camera, a total station and an open-source solver. The hydraulic values are model-derived estimates conditional on the assigned coefficients, not measurements; calibration against
in situ
measurement remains necessary and generalisation beyond this channel is not demonstrated. The protocol, imagery and scripts are released as an openly licensed dataset intended as ground truth for future classifiers.
Open concrete channels in Andean watersheds convey irrigation water and urban stormwater, and their deterioration raises Manning’s roughness coefficient (n), alters specific energy (E) and consumes freeboard. Managers know that a channel is degraded but lack a reproducible procedure for turning that observation into a defensible intervention priority.
Methods
We characterise ten consecutive reaches (219 m) of a rectangular cyclopean-concrete channel in Ambato, Ecuador (b = 0.645 m; Q = 0.21 m
3
/s; s
0
≈ 0.03). Each reach was scored on a 1–5 Structural Damage Index and mapped to a Manning coefficient through an additive decomposition reported reach by reach. The coefficients were propagated through the Manning–Strickler equation, solved simultaneously with continuity, to obtain normal depth, velocity, Froude number, specific energy and freeboard. Because these quantities are deterministic functions of the assigned n, they are reported as transfer curves rather than as statistical relationships; analysis is confined to the observations themselves and to the propagation of observer uncertainty.
Results
Assigned coefficients ranged from 0.016 to 0.034, that is 23%–162% above the design value of 0.013. Departure of specific energy from the design condition ranged from 14.5% to 30.9%, and freeboard fell from 0.277 m to 0.160 m in the most degraded reach, a loss of 42% of the original margin. The transfer curve is not monotonic: the departure peaks near n ≈ 0.030 and declines beyond it, because specific energy passes through its minimum at the critical regime, reached here at n ≈ 0.0304. A one-class error in visual scoring displaces the departure by 8.6 percentage points on average and would change the intervention tier of six of the ten reaches; the two requiring immediate intervention are not among them.
Conclusion
Structured visual assessment combined with transparent hydraulic propagation yields a traceable intervention hierarchy reproducible with a camera, a total station and an open-source solver. The hydraulic values are model-derived estimates conditional on the assigned coefficients, not measurements; calibration against
in situ
measurement remains necessary and generalisation beyond this channel is not demonstrated. The protocol, imagery and scripts are released as an openly licensed dataset intended as ground truth for future classifiers.