Skip to main content
SpringerLink
Log in

Estimation and inter-comparison of infiltration models in the agricultural area of the Mitidja Plain, Algeria

  • Research Article
  • Published:
Journal of Arid Land Aims and scope Submit manuscript

Abstract

Infiltration is an important part of the hydrological cycle, and it is one of the main abstractions accounted for in the rainfall-runoff modeling. The main purpose of this study is to compare the infiltration models that were used to assess the infiltration rate of the Mitidja Plain in Algeria. Field infiltration tests were conducted at 40 different sites using a double ring infiltrometer. Five statistical comparison criteria including root mean squared error (RMSE), normalized root mean squared error (NRMSE), coefficient of correlation (CC), Nash-Sutcliffe efficiency (NSE), and Kling-Gupta efficiency (KGE) were used to determine the best performing infiltration model and to confirm anomalies between predicted and observed values. Then we evaluated performance of five models (i.e., the Philip model, Kostiakov model, Modified Kostiakov model, Novel model, and Horton model) in simulating the infiltration process based on the adjusted performance parameters cited above. Results indicated that the Novel model had the best simulated water infiltration process in the Mitidja Plain in Algeria. However, the Philip model was the weakest to simulate the infiltration process. The conclusion of this study can be useful for estimating infiltration rate at various sites using a Novel model when measured infiltration data are not available and are useful for planning and managing water resources in the study area.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Adeniji F A, Umara B G, Dibal J M, et al. 2013. Variation of infiltration rates with soil texture: A laboratory study. International Journal of Engineering and Innovative Technology, 3(2): 45 4–459.

    Google Scholar 

  • Angelaki A, Singh Nain S, Singh V, et al. 2021. Estimation of models for cumulative infiltration of soil using machine learning methods. ISH Journal of Hydraulic Engineering, 27(2): 162–169.

    Article  Google Scholar 

  • Bennett N G, Croke B F W, Guariso G et al. 2013. Characterising performance of environmental models. Environmental Modelling and Software, 40: 1–20.

    Article  Google Scholar 

  • Boufekane A, Meddi H, Meddi M. 2020. Delineation of groundwater recharge zones in the Mitidja Plain, North Algeria, using multi-criteria analysis. Journal of Hydroinformatics, 22(6): 1468–1484.

    Article  Google Scholar 

  • Boufekane A, Yahiaoui S, Meddi H, et al. 2021. Modified DRASTIC index model for groundwater vulnerability mapping using geostatistic methods and GIS in the Mitidja Plain Area (Algeria). Environmental Forensics, 23(5–6): 539–556.

    Google Scholar 

  • Bouziane O, Mohamed M, Juan Reca C. 2021. Characterization of the water holding capacity of the soils in the Mitidja Plain (Algeria) as a basis for the development of the irrigation water use. Journal of Taiwan Water Conservancy, 69(4): 27–39.

    Google Scholar 

  • Dahak A, Boutaghane H, Merabtene T. 2022. Parameter estimation and assessment of infiltration models for Madjez Ressoul Catchment, Algeria. Water, 14(8): 1185, doi: https://doi.org/10.3390/w14081185.

    Article  Google Scholar 

  • Duan R B, Clifford B F, John B. 2010. Field evaluation of infiltration models in lawn soils. Irrigation Science, 29(5): 379–389.

    Article  Google Scholar 

  • Esfandiari M, Maheshwari B L. 1997. Application of the optimization method for estimating infiltration characteristics in furrow irrigation and its comparison with other methods. Agricultural Water Management, 34(2): 169–185.

    Article  Google Scholar 

  • Farid H U, Mahmood-Khan Z, Ahmad I, et al. 2019. Estimation of infiltration models parameters and their comparison to simulate the onsite soil infiltration characteristics. International Journal of Agricultural and Biological Engineering, 12(3): 84–91.

    Article  Google Scholar 

  • Golmohammadi G, Prasher S O, Madani A, et al. 2014. Evaluating three hydrological distributed watershed models: MIKE-SHE, APEX, SWAT. Hydrology, 1(1): 20–39.

    Article  Google Scholar 

  • Haghighi F, Gorji M, Shorafa M, et al. 2010. Evaluation of some infiltration models and hydraulic parameters. Spanish Journal of Agricultural Research, 8(1): 210.

    Article  Google Scholar 

  • Iovino M, Angulo-Jaramillo R, Bagarello V, et al. 2017. Thematic issue on soil water infiltration. Journal of Hydrology and Hydromechanics, 65(3): 205–208.

    Article  Google Scholar 

  • Jain L, Chakma S. 2023. Effects of temperature and slope on the infiltration rate for a landfill surface. Current Science, 124(1): 94–101.

    Article  Google Scholar 

  • Knoben W J M, Freer J, Woods R. 2019. Technical note: Inherent benchmark or not? Comparing Nash-Sutcliffe and Kling-Gupta Efficiency Scores. Hydrology and Earth System Sciences, 23(10): 4323–4331.

    Article  Google Scholar 

  • Kumar M, Sihag P. 2019. Assessment of infiltration rate of soil using empirical and machine learning-based models. Irrigation and Drainage, 68(3): 588–601.

    Article  Google Scholar 

  • Lei G H, Fan G L, Zeng W J, et al. 2020. Estimating parameters for the Kostiakov-Lewis infiltration model from soil physical properties. Journal of Soils and Sediments, 20(1): 166–180.

    Article  Google Scholar 

  • Machiwal D, Jha M K, Mal B C. 2006. Modelling infiltration and quantifying spatial soil variability in a wasteland of Kharagpur, India. Biosystems Engineering, 95(4): 569–582.

    Article  Google Scholar 

  • Meddi M, Eslamian S. 2021. Uncertainties in rainfall and water resources in Maghreb countries under climate change. In: Leal Filho W, Oguge N, Ayal D, et al. Handbook of Climate Change Adaptation. Cham: Springer, 1967–2003.

    Chapter  Google Scholar 

  • Mishra S K, Tyagi J V, Singh V P. 2003. Comparison of infiltration models. Hydrological Processes, 17(13): 2629–2652.

    Article  Google Scholar 

  • Ogbe V B, Jayeoba J O, Ode S O. 2011. Comparison of four soil infiltration models on a sandy soil in Lafia, southern guinea savanna zone of Nigeria. Production agricultural and Technology, 7: 116–126.

    Google Scholar 

  • Oku E, Aiyelari A. 2011. Predictability of Philip and Kostiakov infiltration models under inceptisols in the humid forest zone, Nigeria. Kasetsart Journal-Natural Science, 45(4): 604–611.

    Google Scholar 

  • Parhi P K, Mishra S, Singh R. 2007. A modification to Kostiakov and Modified Kostiakov infiltration models. Water Resources Management, 21(11): 1973–1989.

    Article  Google Scholar 

  • Philip J R, De Vries D A. 1957. Moisture movement in porous materials under temperature gradients. Transactions, American Geophysical Union, 38(2): 222–232.

    Article  Google Scholar 

  • Rasool T, Dar A, Wani M A. 2021. Comparative evaluation of infiltration models under different land covers. Water Resources, 48(4): 624–634.

    Article  CAS  Google Scholar 

  • Richards L A. 1931. Capillary conduction of liquids through porous mediums. Physics, 1(5): 318–333.

    Article  Google Scholar 

  • Schumann A H. 1998. Infiltration: Introduction. In: Herschy R W, Fairbridge R W. Hydrology and Lakes. Encyclopedia of Earth Science. Dordrecht: Springer, 418.

    Google Scholar 

  • Sihag P, Tiwari N K, Ranjan S. 2017. Estimation and inter-comparison of infiltration models. Water Science, 31(1): 34–43.

    Article  Google Scholar 

  • Singh B, Sihag P, Singh K P. 2018. Comparison of infiltration models in NIT Kurukshetra campus. Applied Water Science, 8(2): 54.

    Article  CAS  Google Scholar 

  • Soil Science Equipment Double Ring Infiltrometer Surface Measure. 2020. SDE Council. [2022-10-22]. https://environnement.sdec-france.com/double-ring-infiltrometer-for-soil-science.html.

  • Tadj M, Benmouiza K, Cheknane A, et al. 2014. Improving the performance of PV systems by faults detection using GISTEL approach. Energy Conversion and Management, 80: 298–304.

    Article  Google Scholar 

  • Thomas A D, Ofosu A E, Amuzu E, et al. 2020. Comparison and estimation of four infiltration models. Open Journal of Soil Science, 10(2): 45–57.

    Article  Google Scholar 

  • Vand A S, Sihag P, Singh B, et al. 2018. Comparative evaluation of infiltration models. KSCE Journal of Civil Engineering, 22(10): 4173–4184.

    Article  Google Scholar 

  • Wang T T, Stewart C E, Ma J B, et al. 2017. Applicability of five models to simulate water infiltration into soil with added biochar. Journal of Arid Land, 9(5): 701–711.

    Article  Google Scholar 

  • Zakwan M, Muzzammil M, Alam J. 2016. Application of spreadsheet to estimate infiltration parameters. Perspectives in Science, 8: 702–704.

    Article  Google Scholar 

  • Zeybek M. 2018. Nash-Sutcliffe efficiency approach for quality improvement. Journal of Applied Mathematics and Computation, 2(11): 496–503.

    Article  Google Scholar 

Download references

Acknowledgements

This study was conducted by the Water and Environment Engineering Laboratory (GEE) of the Higher National School of Hydraulics (ENSH), and this study is carried out within the framework of the SWATCH project (Prima project) funded by the DGRSDT, Algeria.

Author information

Authors and Affiliations

  1. Higher National School of Hydraulics of Blida, Blida, 09000, Algeria

    Amina Mazighi, Hind Meddi, Mohamed Meddi & Ishak Abdi

  2. Department of Civil Engineering and Hydraulics, University of Jijel, Jijel, 18000, Algeria

    Ishak Abdi

  3. Department of Civil and Environmental Engineering, Polytechnic University of Milan, Milan, 20133, Italy

    Giovanni Ravazzani & Mouna Feki

Authors
  1. Amina Mazighi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hind Meddi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mohamed Meddi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ishak Abdi
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Giovanni Ravazzani
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Mouna Feki
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conceptualization: Amina MAZIGHI, Mohamed MEDDI; Methodology: Amina MAZIGHI, Mohamed MEDDI, Giovanni RAVAZZANI, Mouna FEKI; Formal analysis: Amina MAZIGHI, Mohamed MEDDI, Ishak ABDI; Writing - original draft preparation: Amina MAZIGHI, Mohamed MEDDI, Hind MEDDI; Writing - review and editing: Amina MAZIGHI, Hind MEDDI; Funding acquisition: Mohamed MEDDI, Hind MEDDI; Resources: Amina MAZIGHI, Mohamed MEDDI, Giovanni RAVAZZANI, Mouna FEKI, Ishak ABDI, Hind MEDDI; Supervision: Mohamed MEDDI, Hind MEDDI.

Corresponding author

Correspondence to Mohamed Meddi.

Ethics declarations

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mazighi, A., Meddi, H., Meddi, M. et al. Estimation and inter-comparison of infiltration models in the agricultural area of the Mitidja Plain, Algeria. J. Arid Land 15, 1474–1489 (2023). https://doi.org/10.1007/s40333-023-0037-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40333-023-0037-0

Keywords

Search

Navigation