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Fuzzy Logic for Rainfall-Runoff Modelling Considering Soil Moisture

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  • Gokmen Tayfur
  • Luca Brocca

Abstract

This study developed Mamdani-type fuzzy logic model to simulate daily discharge as a function of soil moisture measured at three different depths (10, 20 and 40 cm) and rainfall. The model was applied to 13 km 2 size Colorso Basin in central Italy for a period from October 2002 to April 2004. For each variable of soil moisture, rainfall, and discharge, 9 fuzzy subsets were employed while 30 fuzzy rules, relating the input variables (soil moisture and rainfall) to the output variable (discharge), were optimized. The model employed the min inferencing, max composition, and the centroid method. The model application results revealed that Mamdani-type fuzzy logic model can be employed to incorporate soil moisture along with rainfall to simulate discharge. Using soil moisture measured at 40 cm soil depth along with rainfall produced better simulation of discharge with NS = 0.68 and R = 0.82. The performance of the model was also tested against a conceptual rainfall-runoff model of MISDc (Modello Idrologico Semi-Distribuito in continuo). MISDc couples an event-specific component with a module for continuous time soil water balance for taking into account the variable antecedent wetness conditions. The MISDc model requires estimation of seven parameters and the measurements of the hydrometeorological variables such as rainfall and air temperature. The comparative study revealed that fuzzy model performs better in capturing runoff peak rates and overall trend of high and small flooding events. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • Gokmen Tayfur & Luca Brocca, 2015. "Fuzzy Logic for Rainfall-Runoff Modelling Considering Soil Moisture," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(10), pages 3519-3533, August.
    • Handle: RePEc:spr:waterr:v:29:y:2015:i:10:p:3519-3533
    DOI: 10.1007/s11269-015-1012-0
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    References listed on IDEAS

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    1. Renato Morbidelli & Corrado Corradini & Carla Saltalippi & Luca Brocca, 2012. "Initial Soil Water Content as Input to Field-Scale Infiltration and Surface Runoff Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(7), pages 1793-1807, May.
    2. X. Wang & R. Zhao & Y. Hao, 2011. "Flood Control Operations Based on the Theory of Variable Fuzzy Sets," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(3), pages 777-792, February.
    3. Gokmen Tayfur & Vijay Singh, 2011. "Predicting Mean and Bankfull Discharge from Channel Cross-Sectional Area by Expert and Regression Methods," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(5), pages 1253-1267, March.
    4. A. kumar & Manish Goyal & C. Ojha & R. Singh & P. Swamee & R. Nema, 2013. "Application of ANN, Fuzzy Logic and Decision Tree Algorithms for the Development of Reservoir Operating Rules," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(3), pages 911-925, February.
    5. Gokmen Tayfur & Ata Nadiri & Asghar Moghaddam, 2014. "Supervised Intelligent Committee Machine Method for Hydraulic Conductivity Estimation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(4), pages 1173-1184, March.
    6. D. Panigrahi & P. Mujumdar, 2000. "Reservoir Operation Modelling with Fuzzy Logic," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 14(2), pages 89-109, April.
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    Cited by:

    1. Riya Dutta & Rajib Maity & Parul Patel, 2022. "Short and Medium Range Forecast of Soil Moisture for the Different Climatic Regions of India Using Temporal Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(1), pages 235-251, January.
    2. Jinjin Gu & Mo Li & Ping Guo & Guohe Huang, 2016. "Risk Assessment for Ecological Planning of Arid Inland River Basins Under Hydrological and Management Uncertainties," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(4), pages 1415-1431, March.
    3. Jinjin Gu & Mo Li & Ping Guo & Guohe Huang, 2016. "Risk Assessment for Ecological Planning of Arid Inland River Basins Under Hydrological and Management Uncertainties," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(4), pages 1415-1431, March.
    4. Ahmet Emre Tekeli & Hesham Fouli, 2017. "Reducing False Flood Warnings of TRMM Rain Rates Thresholds over Riyadh City, Saudi Arabia by Utilizing AMSR-E Soil Moisture Information," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(4), pages 1243-1256, March.

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