IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v23y2009i5p899-929.html
   My bibliography  Save this article

Evaluation of the Adequacy of Statistical Distribution Functions for Deriving Unit Hydrograph

Author

Listed:
  • R. Rai
  • S. Sarkar
  • V. Singh

Abstract

The unit hydrograph (UH) is one of the commonly employed techniques for the determination of flood hydrographs. Since the UH satisfies all the properties of a probability distribution function (PDF), it seems logical that PDFs can be employed for deriving the UH. In practice, the gamma distribution function has been commonly employed to derive the UH. In this paper, Beta (Beta), Exponential (EXP), Gamma (GM), Normal, Lognormal (LN), Weibull (WB), Logistic (LG), Generalized logistic (GLG) and Pearson Type 3 (PT 3) distribution functions were employed for the derivation of UH. Parameters of these distribution functions were estimated using the real coded genetic algorithm optimization technique. These distributions were tested on the 13 watersheds of different characteristics and it was observed that except for the EXP distribution function, most other distribution functions produced UHs which were in satisfactory agreement with observed UHs. However, three-parameter distributions GLG, PT 3 and two parameter LG were not capable of reproducing UHs for large watersheds having drainage areas of 3,360 and 4,300 km 2 . For such large watersheds WB reproduced UHs satisfactorily. Combining the overall performance of the distributions over 13 watersheds, the order of ranking the suitability of distributions were as: GM > PT 3 > Beta ≥ GLG ≥ LN > WB. Copyright Springer Science+Business Media B.V. 2009

Suggested Citation

  • R. Rai & S. Sarkar & V. Singh, 2009. "Evaluation of the Adequacy of Statistical Distribution Functions for Deriving Unit Hydrograph," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(5), pages 899-929, March.
  • Handle: RePEc:spr:waterr:v:23:y:2009:i:5:p:899-929
    DOI: 10.1007/s11269-008-9306-0
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11269-008-9306-0
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11269-008-9306-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. R. Rai & M. Jain & S. Mishra & C. Ojha & V. Singh, 2007. "Another Look at Z-transform Technique for Deriving Unit Impulse Response Function," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(11), pages 1829-1848, November.
    2. Dooge, James C. I., 1973. "Linear Theory of Hydrologic Systems," Technical Bulletins 160041, United States Department of Agriculture, Economic Research Service.
    3. Kuo, Sheng-Feng & Merkley, Gary P. & Liu, Chen-Wuing, 2000. "Decision support for irrigation project planning using a genetic algorithm," Agricultural Water Management, Elsevier, vol. 45(3), pages 243-266, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Khodayar Abdollahi & Pablo Guzmán & Marijke Huysmans & Okke Batelaan, 2016. "Rainfall-runoff modelling using a spatially distributed electrical circuit analogue," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 82(2), pages 1279-1300, June.
    2. Ahmet Ozan Celik & Volkan Kiricci & Canberk Insel, 2017. "Reassessment of the flood damage at a river diversion hydropower plant site: lessons learned from a case study," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 86(2), pages 833-847, March.
    3. R. Rai & S. Sarkar & Alka Upadhyay & V. Singh, 2010. "Efficacy of Nakagami-m Distribution Function for Deriving Unit Hydrograph," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(3), pages 563-575, February.
    4. Osman Mohammadpour & Yousef Hassanzadeh & Ahmad Khodadadi & Bahram Saghafian, 2014. "Selecting the Best Flood Flow Frequency Model Using Multi-Criteria Group Decision-Making," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(12), pages 3957-3974, September.
    5. Yousef Hassanzadeh & Amin Abdi & Siamak Talatahari & Vijay Singh, 2011. "Meta-Heuristic Algorithms for Hydrologic Frequency Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(7), pages 1855-1879, May.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. R. Rai & S. Sarkar & Alka Upadhyay & V. Singh, 2010. "Efficacy of Nakagami-m Distribution Function for Deriving Unit Hydrograph," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(3), pages 563-575, February.
    2. Bonfante, A. & Monaco, E. & Manna, P. & De Mascellis, R. & Basile, A. & Buonanno, M. & Cantilena, G. & Esposito, A. & Tedeschi, A. & De Michele, C. & Belfiore, O. & Catapano, I. & Ludeno, G. & Salinas, 2019. "LCIS DSS—An irrigation supporting system for water use efficiency improvement in precision agriculture: A maize case study," Agricultural Systems, Elsevier, vol. 176(C).
    3. Jia Liu & Jianhua Wang & Shibing Pan & Kewang Tang & Chuanzhe Li & Dawei Han, 2015. "A real-time flood forecasting system with dual updating of the NWP rainfall and the river flow," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 77(2), pages 1161-1182, June.
    4. Rui M. S. Pereira & Sofia Lopes & Amélia Caldeira & Victor Fonte, 2018. "Optimized Planning of Different Crops in a Field Using Optimal Control in Portugal," Sustainability, MDPI, vol. 10(12), pages 1-16, December.
    5. C. Sivapragasam & G. Vasudevan & P. Vincent, 2007. "Effect of inflow forecast accuracy and operating time horizon in optimizing irrigation releases," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(6), pages 933-945, June.
    6. Parolo, Gilberto & Ferrarini, Alessandro & Rossi, Graziano, 2009. "Optimization of tourism impacts within protected areas by means of genetic algorithms," Ecological Modelling, Elsevier, vol. 220(8), pages 1138-1147.
    7. Ojeda-Bustamante, Waldo & Gonzalez-Camacho, Juan Manuel & Sifuentes-Ibarra, Ernesto & Isidro, Esteban & Rendon-Pimentel, Luis, 2007. "Using spatial information systems to improve water management in Mexico," Agricultural Water Management, Elsevier, vol. 89(1-2), pages 81-88, April.
    8. Jiang, Yao & Xu, Xu & Huang, Quanzhong & Huo, Zailin & Huang, Guanhua, 2016. "Optimizing regional irrigation water use by integrating a two-level optimization model and an agro-hydrological model," Agricultural Water Management, Elsevier, vol. 178(C), pages 76-88.
    9. Hassan-Esfahani, Leila & Torres-Rua, Alfonso & McKee, Mac, 2015. "Assessment of optimal irrigation water allocation for pressurized irrigation system using water balance approach, learning machines, and remotely sensed data," Agricultural Water Management, Elsevier, vol. 153(C), pages 42-50.
    10. Avinash Agarwal & R. Singh, 2004. "Runoff Modelling Through Back Propagation Artificial Neural Network With Variable Rainfall-Runoff Data," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 18(3), pages 285-300, June.
    11. Hamideh Noory & Mona Deyhool & Farhad Mirzaei, 2019. "A Simulation-Optimization Model for Conjunctive Use of Canal and Pond in Irrigating Paddy Fields," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(3), pages 1053-1068, February.
    12. S. Dutta & B.C. Sahoo & Rajashree Mishra & S. Acharya, 2016. "Fuzzy Stochastic Genetic Algorithm for Obtaining Optimum Crops Pattern and Water Balance in a Farm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(12), pages 4097-4123, September.
    13. Dariane, A.B. & Ghasemi, M. & Karami, F. & Azaranfar, A. & Hatami, S., 2021. "Crop pattern optimization in a multi-reservoir system by combining many-objective and social choice methods," Agricultural Water Management, Elsevier, vol. 257(C).
    14. A. Vasan & Komaragiri Raju, 2007. "Application of Differential Evolution for Irrigation Planning: An Indian Case Study," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(8), pages 1393-1407, August.
    15. Mateos, Luciano & Lopez-Cortijo, Ignacio & Sagardoy, Juan A., 2002. "SIMIS: the FAO decision support system for irrigation scheme management," Agricultural Water Management, Elsevier, vol. 56(3), pages 193-206, August.
    16. Shanshan Guo & Fan Zhang & Chenglong Zhang & Chunjiang An & Sufen Wang & Ping Guo, 2018. "A Multi-Objective Hierarchical Model for Irrigation Scheduling in the Complex Canal System," Sustainability, MDPI, vol. 11(1), pages 1-15, December.
    17. K. Srinivasa Raju & D. Nagesh Kumar, 2004. "Irrigation Planning using Genetic Algorithms," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 18(2), pages 163-176, April.
    18. Zaw Latt, 2015. "Application of Feedforward Artificial Neural Network in Muskingum Flood Routing: a Black-Box Forecasting Approach for a Natural River System," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(14), pages 4995-5014, November.
    19. A. Garudkar & A. Rastogi & T. Eldho & S. Gorantiwar, 2011. "Optimal Reservoir Release Policy Considering Heterogeneity of Command Area by Elitist Genetic Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(14), pages 3863-3881, November.
    20. A. Sohail & K. Watanabe & S. Takeuchi, 2008. "Runoff Analysis for a Small Watershed of Tono Area Japan by Back Propagation Artificial Neural Network with Seasonal Data," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 22(1), pages 1-22, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:waterr:v:23:y:2009:i:5:p:899-929. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.