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Developing an agricultural flood loss estimation function (case study: rice)

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  • Zahra Ganji
  • Alireza Shokoohi
  • Jamal Samani

Abstract

In recent years, flood control has been replaced by flood management concept in terms of living with flood, making benefit of it, and minimizing its losses. Succeeding in flood management in any region depends on the evaluation of different types of flood losses. Because of providing water resources and suitable arable lands, especially in arid and semiarid countries, floodplains are very important for agricultural activities. These lands are naturally vulnerable to flood; henceforth, determining the degree of protection and acceptable risk in flood damage-reduction projects without agricultural flood loss evaluation could be unrealistic. In this research, effective hydraulic parameters for flood loss estimation were determined and a set of laboratory tests were performed to evaluate the loss of rice, as the main crop in the study region, under different hydraulic conditions. In this regard, flow parameters like depth, velocity, multiplication of depth and velocity, shear stress, the Froude number, and the Reynolds number were employed for different rice growth stages including after transplanting, shooting, clustering, and harvesting. Analyzing the results showed that the Reynolds number, as a dimensionless parameter, is the best one for simulation of flood physical factor-loss function. Statistical analysis revealed that the logarithmic function is the best regression equation fitted to the Reynolds number-loss function. The amount of loss depends on growth stage; therefore, the time of flood occurrence is of vital importance for agricultural loss estimation. In this research, it was realized that the amount of loss is increased in the following order: after transplanting, shooting, harvesting, and clustering. Copyright Springer Science+Business Media B.V. 2012

Suggested Citation

  • Zahra Ganji & Alireza Shokoohi & Jamal Samani, 2012. "Developing an agricultural flood loss estimation function (case study: rice)," 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. 64(1), pages 405-419, October.
  • Handle: RePEc:spr:nathaz:v:64:y:2012:i:1:p:405-419
    DOI: 10.1007/s11069-012-0250-1
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    References listed on IDEAS

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    1. Xin Huang & Hongzhuan Tan & Jia Zhou & Tubao Yang & Abuaku Benjamin & Shi Wen & Shuoqi Li & Aizhong Liu & Xinhua Li & Shuidong Fen & Xinli Li, 2008. "Flood hazard in Hunan province of China: an economic loss analysis," 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. 47(1), pages 65-73, October.
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    Cited by:

    1. Beatrice Monteleone & Iolanda Borzí & Brunella Bonaccorso & Mario Martina, 2023. "Quantifying crop vulnerability to weather-related extreme events and climate change through vulnerability curves," 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. 116(3), pages 2761-2796, April.
    2. Vahid Mojtahed & Carlo Giupponi & Claudio Biscaro & Animesh K. Gain & Stefano Balbi, 2013. "Integrated Assessment of Natural Hazards and Climate-Change Adaptation: II. The SERRA Methodology," Working Papers 2013:07, Department of Economics, University of Venice "Ca' Foscari".

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