Water Resources Management

, Volume 27, Issue 13, pp 4579–4590

Evaluating Infiltration Mechanisms Using Breakthrough Curve and Mean Residence Time


DOI: 10.1007/s11269-013-0427-8

Cite this article as:
Simin, Q., Tao, W., Weimin, B. et al. Water Resour Manage (2013) 27: 4579. doi:10.1007/s11269-013-0427-8


Determination of infiltration mechanism is crucial for the calculation of infiltration flux in the soil which would influence the water balance computation. Two infiltration experiments with different isotopic compositions of rainfall were conducted to analyze the infiltration type by measuring isotopic concentrations (deuterium and oxygen 18) of collected outflow water samples. Models with three transfer functions were used to simulate the isotopic variation of outflows in a soil column. The model performance was evaluated with the comparison of computed and observed isotopic values of outflow. Breakthrough curve based on the isotopic composition of rainfall, initial soil water and outflow, and mean residence time estimated on the best fitting transfer function model were applied to identify the infiltration type in the soil. The results show that infiltration type determination using the comparison between estimated and observed mean residence time and breakthrough curve are similar. Furthermore, we found that soil structure and isotope measurement error affected the determination of mean residence time. Results from this study may provide a framework for describing the infiltration processes in the soil column.


Transfer function model Mean residence time Infiltration type Breakthrough curve 

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.State Key Laboratory of Hydrology-Water Resources and Hydraulic EngineeringHohai UniversityNanjingChina
  2. 2.College of Water Resources and HydrologyHohai UniversityNanjingChina
  3. 3.HydroChina Chengdu Engineering CorporationChengduChina
  4. 4.Department of GeoscienceUniversity of Nevada Las VegasLas VegasUSA

Personalised recommendations