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Hydrological Models

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Climate Change in Sustainable Water Resources Management

Part of the book series: Springer Water ((SPWA))

Abstract

Hydrological modelling can be characterized as the process of abstracting real hydrological features through small-scale physical models, mathematical analogs, or computer simulations (Chen et al. 2021). Hydrologic models can be separated into several classes according to model structures and spatial processes. In this chapter, after a discussion about the history of these models, a concise glance at the impacts of clime change is examined. Finally, in the last part, the structure of some recognized hydrological models is explained.

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Notes

  1. 1.

    Artificial Neural Networks.

  2. 2.

    Fuzzy Logic.

  3. 3.

    Genetic Programming.

  4. 4.

    Wavelet Models.

  5. 5.

    Complex surface.

  6. 6.

    Boundary conditions.

  7. 7.

    Stochastic Model.

  8. 8.

    Deterministic Model.

  9. 9.

    United States Department of Agriculture.

  10. 10.

    Topography based Hydrological Model (Beven and Kirkby 1979; Beven et al. 1984) Source code for TOPMODEL written in R can be found at: https://idea.isnew.info/r.topmodel.html.

  11. 11.

    Hydrologiska Byråns Vattenbalansavdelning (Bergström 1992) http://www.geo.uzh.ch/en/units/h2k/Services/HBVModel.html.

  12. 12.

    National Weather Service River Forecast System (Burnash et al. 1973) http://www.nws.noaa.gov/iao/iao_hydroSoftDoc.php.

  13. 13.

    Visualizing Ecosystem Land Management Assessments (Abdelnour et al. 2011; McKane et al. 2014) https://www.epa.gov/water-research/visualizing-ecosystem-land-management-assessments-velma-model-20.

  14. 14.

    Variable Infiltration Capacity Model (Liang et al. 1994) http://www.hydro.washington.edu/Lettenmaier/Models/VIC/indexold.shtml.

  15. 15.

    MIKE System Hydrologique European (Abbott et al. 1986) https://www.mikepoweredbydhi.com/products/mike-she.

  16. 16.

    Penn State Integrated Hydrologic Modeling System (Qu et al. 2004) http://www.pihm.psu.edu/.

  17. 17.

    Kinematic Runoff and Erosion Model (Woolhiser et al. 1990) http://www.tucson.ars.ag.gov/kineros/.

  18. 18.

    Penn State Integrated Hydrologic Modeling.

  19. 19.

    Thiessen Polygon Method.

  20. 20.

    North American Land Data Assimilation System.

  21. 21.

    Computational Intelligence.

  22. 22.

    Data Driven Modelling.

  23. 23.

    Data Mining.

  24. 24.

    Knowledge Discovery in Databases.

  25. 25.

    Intelligent Data Analysis.

  26. 26.

    Soft Computing.

  27. 27.

    Neural Networks.

  28. 28.

    Fuzzy Logic.

  29. 29.

    Pattern Recognition.

  30. 30.

    Evolutionary Computation.

  31. 31.

    Bayesian Reasoning.

  32. 32.

    Fuzzy Rule-Based Systems.

  33. 33.

    Statistical Method.

  34. 34.

    Nonlinear Partial Differential Equations.

  35. 35.

    Partial Differential Equations.

  36. 36.

    Modified Global Soil Loss Equation.

  37. 37.

    Digital terrain analysis.

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Authors and Affiliations

  1. Department of Sciences and Water Engineering, Faculty of Agriculture, University of Birjand, Birjand, Iran

    Icen Yoosefdoost

  2. Department of Irrigation and Reclamation Engineering, Faculty of Agricultural Engineering and Technology, College of Agriculture and Natural Resources, University of Tehran, Karaj, Tehran, Iran

    Omid Bozorg-Haddad

  3. Department of Biological and Agricultural Engineering, Zachry Department of Civil and Environmental Engineering, Texas A&M University, College Station, Texas, 77843-2117, USA

    Vijay P. Singh

  4. Civil and Hydraulic Engineering, Hong Kong Polytechnic University, Hung Hom, Hong Kong

    Kwok Wing Chau

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  1. Icen Yoosefdoost
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  2. Omid Bozorg-Haddad
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  3. Vijay P. Singh
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  4. Kwok Wing Chau
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Correspondence to Omid Bozorg-Haddad .

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  1. Irrigation and Reclamation Engineering, University of Tehran, Karaj, Iran

    Omid Bozorg-Haddad

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Yoosefdoost, I., Bozorg-Haddad, O., Singh, V.P., Chau, K.W. (2022). Hydrological Models. In: Bozorg-Haddad, O. (eds) Climate Change in Sustainable Water Resources Management. Springer Water. Springer, Singapore. https://doi.org/10.1007/978-981-19-1898-8_8

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