Kim et al. (2026) Comparative Simulation of Hillslope Runoff Using Two Infiltration Equations

Identification

• Journal: Water Resources Management
• Year: 2026
• Date: 2026-02-19
• Authors: Hwansuk Kim, Kristine Joy B. Mallari, Anya Catherine C. Arguelles, Yonca Çavuş, M. Levent Kavvas, Hafzullah Aksoy, Jaeyoung Yoon
• DOI: 10.1007/s11269-026-04511-8

Research Groups

• Program in Environmental Technology and Policy, Korea University, Sejong, South Korea
• Department of Environmental Engineering, Korea University, Sejong, South Korea
• Department of Civil Engineering, Istanbul Beykent University, Istanbul, Turkey
• Department of Civil and Environmental Engineering, University of California, Davis, CA, USA
• Department of Civil Engineering, Istanbul Technical University, Istanbul, Turkey

Short Summary

This study compared the performance of Horton and Green-Ampt infiltration equations, coupled with a physically-based overland flow model explicitly accounting for rill-interrill microtopography, in simulating hillslope runoff against field data. It found the Green-Ampt equation superior in validation due to its consideration of antecedent soil moisture, and highlighted that runoff is more sensitive to infiltration parameters than to surface friction.

Objective

• To compare the performance of the Horton and Green-Ampt infiltration equations, when coupled with a physically-based overland flow model that explicitly accounts for rill-interrill microtopography, in simulating hillslope runoff using field experimental data.
• To perform a sensitivity analysis of the model parameters to understand their influence on runoff generation.

Study Configuration

• Spatial Scale: A 24.4-meter long and 9.14-meter wide hillslope section with a 2:3 slope, featuring rill-interrill microtopography, located near Buckhorn Summit, Northern California, USA.
• Temporal Scale: Two rainfall events in July (16 minutes) and September (11 minutes) of 1990, with a constant rainfall intensity of 152 mm/h. Model calibration and validation used a time interval of 0.25 hours.

Methodology and Data

• Models used:
  • Physically-based overland flow model (Yoon and Kavvas, 2000; Arguelles et al., 2013) incorporating interrill and rill flow equations with Chezy roughness coefficients.
  • Horton infiltration equation (empirical).
  • Green-Ampt infiltration equation (physically-based, modified by Mein and Larson, 1973).
  • Ponding time calculations for both infiltration equations.
  • Model evaluation using Nash-Sutcliffe Efficiency (NSE) and determination coefficient (R^2).
  • Local sensitivity analysis using the parameter perturbation technique and condition numbers.
• Data sources:
  • Field experimental data from a hillslope near Buckhorn Summit, Northern California, USA (Govindaraju and Kavvas, 1992).
  • Constant rainfall intensity of 152 mm/h.
  • Hillslope discharge measured at the downstream end using an H flume.
  • Detailed microtopographic features of the hillslope.

Main Results

• Calibration Performance: Both Horton and Green-Ampt coupled overland flow models showed "very good" performance during calibration (NSE > 0.80, R^2 > 0.85), with the Horton model being slightly better.
• Validation Performance: The Green-Ampt-coupled model maintained "good" performance during validation (NSE > 0.7, R^2 > 0.75), while the Horton-coupled model "overpredicted the amount of runoff by about 60%" and was classified as "unsatisfactory" (NSE < 0.5, R^2 < 0.6).
• Reason for Green-Ampt's Superiority: The Green-Ampt equation's ability to explicitly account for antecedent soil moisture conditions was identified as the key factor for its improved robustness and predictive performance during validation.
• Runoff Sensitivity (Horton): Runoff was most sensitive to the final infiltration rate (fc), followed by the decay constant (k), and least sensitive to the initial infiltration rate (f0). The roughness coefficient had minimal effect.
• Runoff Sensitivity (Green-Ampt): Runoff was most sensitive to the saturated hydraulic conductivity (K_s), followed by the soil suction head (ψ), and then the effective porosity (Δθ). The roughness coefficient also had minimal effect.
• Overall Sensitivity: Runoff generation was found to be significantly more sensitive to infiltration parameters than to the hillslope surface friction factor (Chezy roughness coefficient).
• Infiltration Sensitivity: Infiltration itself showed similar sensitivity patterns to its respective parameters as runoff, but in an inverse relationship (e.g., increased infiltration leads to decreased runoff).

Contributions

• This study provides the first integrated and consistent evaluation of widely used infiltration equations (Horton and Green-Ampt) within an overland flow framework that explicitly represents microtopographic effects through rill–interrill interactions at the hillslope scale using field data.
• It offers practical guidance for infiltration model selection in hillslope overland flow modeling, emphasizing the critical role of antecedent soil moisture conditions for robust predictions beyond calibration.
• The research demonstrates that runoff generation is predominantly controlled by infiltration processes rather than surface friction characteristics, highlighting the crucial importance of accurate calibration of infiltration-related parameters.
• It contributes to the limited body of work on runoff prediction by overland flow models calibrated and validated under actual field conditions.

Funding

• National Research Foundation of Korea grant (NRF-2020R1I1A3064269)
• Korea University grant (K1607741)
• National Research Foundation of Korea grant (NRF-2013R1A1A4A01007676)
• Open access funding provided by the Scientific and Technological Research Council of Türkiye (TÜBİTAK)

Citation

@article{Kim2026Comparative,
  author = {Kim, Hwansuk and Mallari, Kristine Joy B. and Arguelles, Anya Catherine C. and Çavuş, Yonca and Kavvas, M. Levent and Aksoy, Hafzullah and Yoon, Jaeyoung},
  title = {Comparative Simulation of Hillslope Runoff Using Two Infiltration Equations},
  journal = {Water Resources Management},
  year = {2026},
  doi = {10.1007/s11269-026-04511-8},
  url = {https://doi.org/10.1007/s11269-026-04511-8}
}