Citation:

Gudino-Elizondo, N., T. Biggs, R. Bingner, Y. Yuan, E. Langendoen, K. Taniguchi, T. Kretzschmar, E. Taguas, AND D. Liden. Modelling Ephemeral Gully Erosion from Unpaved Urban Roads: Equifinality and Implications for Scenario Analysis. Geosciences. MDPI, Basel, Switzerland, 8(4):137, (2018). https://doi.org/10.3390/geosciences8040137

Impact/Purpose:

Excessive flooding and sedimentation threaten both ecosystems and human populations. In the Tijuana-San Diego region, the Tijuana Estuary in the United States suffers from “excessive sedimentation”, gully erosion has been identified as one of the major sediment sources. However, mapping and modeling gully erosion in urban areas is challenging due to microtopographic complexity that alters water flow paths, and difficulties in parameter identification. In this study, we calibrated a model (AnnAGNPS) of an ephemeral gully network that formed following a storm event in a rapidly urbanizing watershed (0.2 km2) in Tijuana, Mexico, using unmanned aerial vehicles (UAVs) and Structure-from-Motion (SfM) to generate a high-resolution Digital Elevation Model (DEM) for flow routing and to measure gully erosion. Latin hypercube sampling was performed to create different parameter ensembles to assess model equifinality and to constrain parameter values. Gullies were formed almost exclusively on unpaved roads characterized by erodible soils and concentrated flow. Simulated results using the AnnAGNPS model were close to observed gully erosion rates (RMSE=2.1mm, 64%). The SCS curve number, operation tillage depth (Td) and critical shear stress (τc) were the most sensitive parameters in gully erosion modeling. Changes in parameters involved in runoff generation (SCS curve number, Manning’s n) were compensated by changes in parameters describing soil properties (Td, τc), resulting in uncertainty in the final parameter values. Four combinations of the model parameters to provide suitable results (behavioral models) were identified and used to evaluate the impact of paving the roads. The τc in the behavioral models was smaller than the τc measured using a jet-test, suggesting that areas of very low τc, that were not sampled by the jet test, are contributing to gully formation. Modelling exercises showed that the impact of paving the roads were (+400 to +1200%) on total runoff, (+600 to +2100%) peak discharge, and (-73 to -85%) sediment load reduction among the four behavioral models. The methodology described in this paper can be used in other watersheds to simulate runoff and gully erosion, and to quantify the uncertainty of model-estimated impacts of management activities on runoff and erosion in topographically complex urban environments.

Description:

Modelling gully erosion in urban areas is challenging due to difficulties with equifinality and parameter identification, which complicates quantification 0of management impacts on runoff and sediment production. We calibrated a model (AnnAGNPS) of an ephemeral gully network that formed on unpaved roads following a storm event in an urban watershed (0.2 km2) in Tijuana, Mexico. Latin hypercube sampling was used to create 500 parameter ensembles. Modelled sediment load was most sensitive to the Soil Conservation Service (SCS) curve number, tillage depth (TD), and critical shear stress (τc). Twenty-one parameter ensembles gave acceptable error (behavioural models), though changes in parameters governing runoff generation (SCS curve number, Manning’s n) were compensated by changes in parameters describing soil properties (TD, τc), resulting in uncertainty in the optimal parameter values. The most suitable parameter combinations or “behavioural models” were used to evaluate uncertainty under management scenarios. Paving the roads increased runoff by 146–227%, increased peak discharge by 178–575%, and decreased sediment load by 90–94% depending on the ensemble. The method can be used in other watersheds to simulate runoff and gully erosion, to quantify the uncertainty of model-estimated impacts of management activities on runoff and erosion, and to suggest critical field measurements to reduce uncertainties in complex urban environments.

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