Comparative analysis of two infiltration models for application in a physically based overland flow model

Kristine Joy B. Mallari, Anya Catherine C. Arguelles, Hwansuk Kim, Hafzullah Aksoy, M. Levent Kavvas, Jaeyoung Yoon*

*Bu çalışma için yazışmadan sorumlu yazar

Araştırma sonucu: Dergiye katkıMakalebilirkişi

12 Atıf (Scopus)

Özet

In the prediction of overland flow, infiltration is an essential component, which should be modeled accurately to achieve optimum runoff rates. Many mathematical models that simulate the details of runoff and erosion process in hillslopes, where the rill-interrill configuration significantly affects overland flow, employ Horton’s model for infiltration due to its simplicity. However, Horton’s model does not handle adequately antecedent moisture condition (AMC) of soil. In this study, the Green-Ampt infiltration model is incorporated into a physically based overland flow model, which was originally coupled with Horton’s equation in an effort to improve the overland flow model’s prediction ability. In so doing, the model used the Horton and Green-Ampt model as an infiltration component separately and simulated flow to directly compare which infiltration equation performs better with the overland flow model. Calibration using laboratory data produced good results for both Horton with NSE = 0.88 and r2 = 0.92 and Green-Ampt with NSE = 0.90 and r2 = 0.95 while in validation, the Horton-coupled model produced lower NSE = 0.64 and r2 = 0.84 than the Green-Ampt which produced NSE = 0.85 and r2 = 0.85. The results suggest that the Green-Ampt equation can improve the performance of the overland flow model with its ability to account more accurately the AMC and flow processes in the soil.

Orijinal dilİngilizce
Sayfa (başlangıç-bitiş)1579-1587
Sayfa sayısı9
DergiEnvironmental Earth Sciences
Hacim74
Basın numarası2
DOI'lar
Yayın durumuYayınlandı - 26 Tem 2015

Bibliyografik not

Publisher Copyright:
© 2015, Springer-Verlag Berlin Heidelberg.

Finansman

This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2013R1A1A4A01007676) and a research grant from Korea University.

FinansörlerFinansör numarası
Korea University
Ministry of EducationNRF-2013R1A1A4A01007676
National Research Foundation of Korea

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