Irrigation Science

, Volume 24, Issue 1, pp 25–35

Infiltration parameters from surface irrigation advance and run-off data

Original Paper


A computer model was developed to employ runoff data in the calculation of the infiltration parameters of the modified Kostiakov equation. The model (IPARM) uses a simple volume balance approach to estimate the parameters from commonly collected field data. Several data sets have been used to verify the procedure. Infiltration parameters were calculated using both advance and runoff data combined and advance data alone. Simulations of each example using SIRMOD were compared to the measured data to identify the possible benefits of the procedure. The inclusion of runoff did not compromise the ability to reproduce the advance curve however the simulations are more capable of reproducing the measured runoff rates and volumes and therefore offer better estimations of the total volume applied to the soil (in one case a reduction in error of the total infiltration from 22% to 1%). This procedure will be of most benefit where the infiltration parameters are expected to represent soil hydraulic characteristics for times greater than the completion of the advance phase. Further analysis has shown that the infiltration parameters are more sensitive to runoff than the advance highlighting the requirement for accurate field measurement and a weighting factor between the advance and runoff errors.


  1. Dalton P, Raine SR, Broadfoot K (2001) Best management practices for maximising whole farm irrigation efficiency in the Australian cotton Industry. Final report to the Cotton Research and Development Corporation. National Centre for Engineering in Agriculture Report. 179707/2, USQ, ToowoombaGoogle Scholar
  2. Elliott RL, Walker WR (1982) Field evaulation of furrow infiltration and advance functions. Trans ASAE 25(2):396–400Google Scholar
  3. Elliott RL, Walker WR, Skogerboe GV (1983) Infiltration parameters from furrow irrigation advance data. Trans ASAE 26(6):1726–1731Google Scholar
  4. McClymont DJ, Smith RJ (1996) Infiltration parameters from optimization on furrow irrigation advance data. Irrigation Sci 17(1):15–22CrossRefGoogle Scholar
  5. Renault D, Wallender WW (1996) Initial-inflow-variation impacts on furrow irrigation evaluation. J Irrigation Drainage Eng 122(1):7–14CrossRefGoogle Scholar
  6. Renault D, Wallender WW (1997) Surface storage in furrow irrigation evaluation. J Irrigation Drainage Eng 123(6):415–422CrossRefGoogle Scholar
  7. Scaloppi EJ, Merkley GP, Willardson LS (1995) Intake parameters from advance and wetting phases of surface irrigation. J Irrigation Drainage Eng 121(1):57–70CrossRefGoogle Scholar
  8. Walker WR (1999) SIRMOD II surface irrigation design, evaluation and simulation software–User’s guide and technical documentation, Utah State University, Logan, UtahGoogle Scholar
  9. Walker WR (2005) Multi-level calibration of furrow infiltration and roughness. J Irrigation Drainage Eng 131(2):129–135CrossRefGoogle Scholar
  10. Walker WR, Skogerboe GV (1987) Surface irrigation : theory and practice. Prentice-Hall, Englewood CliffsGoogle Scholar

Copyright information

© Springer-Verlag 2005

Authors and Affiliations

  1. 1.National Centre for Engineering in Agriculture and Cooperative Research Centre for Irrigation FuturesUniversity of Southern QueenslandToowoombaAustralia

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