Modelling Ephemeral Gully Erosion from Unpaved Urban Roads: Equifinality and Implications for Scenario Analysis

Abstract

Modelling gully erosion in urban areas is challenging due to difficulties with equifinality and parameter identification, which complicates quantification of 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.

Modelling Runoff and Sediment Loads in a Developing Coastal Watershed of the US-Mexico Border

“…The critical shear stress ( τ c ) and soil erodibility in the non-cobbly sandy conglomerate (Lf) were taken from Gudino-Elizondo et al [14], who used a mini-jet erosion test device following the methodology described by Hanson [36]. Values of τ c for conglomerate soil were initially taken from USGS [37] and were modified during calibration.…”

“…The soils map was used to link the required physical variables from the SSURGO database to the model such as soil texture and erodibility, bulk density, and saturated conductivity. Tillage depth is the depth to an impervious soil layer, which limits the potential depth of gullies, and was determined as the depth of the gullies observed in the field [14]. The main equations solved within AnnAGNPS to estimate soil erosion are listed in Table 1.…”

“…Hillslope erosion and sediment production can be simulated using numerical models that consider the relationship between terrain attributes and climate regimes [11,12]. These models vary in structure, assumptions, and data requirements [13,14]. Erosion modeling is often used to simulate various erosional processes, such as sheet, rill, gully, and channel erosion, to develop sediment budgets and to assess the effect of Best Management Practices (BMPs) on total sediment reduction.…”

“…The AnnAGNPS model has been tested in small Mediterranean watersheds (< 1.3 km 2 ) [14,23,30]. Licciardello et al [30] evaluated AnnAGNPS in a steep catchment under pasture in Eastern Italy.…”

“…Taguas et al [23] evaluated the effect of different management activities on total sediment reduction in an agricultural environment in Spain, where ephemeral gullies are a significant contributor to the total sediment production. Gudino-Elizondo et al [14] reported good performance of AnnAGNPS in simulating ephemeral gullies at the neighborhood scale in an urban watershed. However, AnnAGNPS has not been tested to model hillslope erosion rates in an urbanizing catchment under different soil types and land uses.…”