Modelling infiltration and geostatistical analysis of spatial variability of sorptivity and transmissivity in a flood spreading area

  • Fereshte Haghighi Fashi Faculty of Agricultural Engineering and Technology. University of Tehran. Tehran
  • Forood Sharifi Soil Conservation and Watershed Management Research Institute. Tehran
  • Koorosh Kamali Soil Conservation and Watershed Management Research Institute. Tehran
Keywords: Horton model, Kostiakov-Lewis model, kriging, Philip’s two-term model, SCS model, variogram


Knowledge of infiltration characteristics is useful in hydrological studies of agricultural soils. Soil hydraulic parameters such as steady infiltration rate, sorptivity, and transmissivity can exhibit appreciable spatial variability. The main objectives of this study were to examine several mathematical models of infiltration and to analyze the spatial variability of observed final infiltration rate, estimated sorptivity and estimated transmissivity in flood spreading and control areas in Ilam province, Iran. The suitability of geostatistics to describe such spatial variability was assessed using data from 30 infiltration measurements sampled along three lines. The Horton model provided the most accurate simulation of infiltration considering all measurements and the Philip’s two-term model provided less accurate simulation. A comparison of the measured values and the estimated final infiltration rates showed that the Kostiakov-Lewis, Kostiakov, and SCS models could not estimate the final infiltration rate as well as Horton model. Estimated sorptivity and transmissivity parameters of the Philip’s two-term model and final infiltration rate had spatial structure, and were considered to be structural variables over the transect pattern. The Gaussian model provided the best-fit theoretical variogram for these three parameters. Variogram values ranged from 99 and 88 m for sorptivity and final infiltration rate to 686 (spherical) and 384 m (Gaussian) for transmissivity. Sorptivity, transmissivity and final infiltration attributes showed a high degree of spatial dependence, being 0.99, 0.81 and 1, respectively. Results showed that kriging could be used to predict the studied parameters in the study area.


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How to Cite
Haghighi FashiF., SharifiF., & KamaliK. (2014). Modelling infiltration and geostatistical analysis of spatial variability of sorptivity and transmissivity in a flood spreading area. Spanish Journal of Agricultural Research, 12(1), 277-288.
Water management