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Sciences in Cold and Arid Regions ›› 2018, Vol. 10 ›› Issue (1): 55-68.doi: 10.3724/SP.J.1226.2018.00055

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Comparative study of probable maximum precipitation and isohyetal maps for mountainous regions, Pakistan

Muhammad Waseem Boota1,2, Ghulam Nabi2, Tanveer Abbas2, HuiJun Jin3, Ayesha Yousaf4, Muhammad Azeem Boota5   

  1. 1. Department of Technology (Civil), The University of Lahore, Lahore 54500, Pakistan;
    2. Centre of Excellence in Water Resources Engineering, University of Engineering and Technology Lahore, Lahore 54890, Pakistan;
    3. State Key Laboratory of Frozen Soils Engineering, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, Gansu 730000, China;
    4. Department of Mechanical Engineering, University of Engineering & Technology Lahore, Lahore 54890, Pakistan;
    5. Department of Agricultural Engineering, The University of Agriculture Faisalabad, Faisalabad 38040, Pakistan
  • Received:2017-06-06 Online:2018-02-01 Published:2018-11-23
  • Contact: Muhammad Waseem Boota, engr.waseemboota@gmail.com E-mail:engr.waseemboota@gmail.com
  • Supported by:
    This research work was part of Msc thesis and supported by Centre of Excellence in Water Resources Engineering, University of Engineering and Technology Lahore. We also express special appreciation to Pakistan Meteorological Department (PMD) for providing climatic data to conduct this research.

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Abstract: Probable maximum precipitation (PMP) is widely used by hydrologists for appraisal of probable maximum flood (PMF) used for soil and water conservation structures, and design of dam spillways. A number of methods such as empirical, statistical and dynamic are used to estimate PMP, the most favored being statistical and hydro-meteorological. In this paper, PMP estimation in mountainous regions of Pakistan is studied using statistical as well as physically based hydro-meteorological approaches. Daily precipitation, dew point, wind speed and temperature data is processed to estimate PMP for a one-day duration. Maximum precipitation for different return periods is estimated by using statistical approaches such as Gumble and Log-Pearson type-III (LP-III) distribution. Goodness of fit (GOF) test, chi-square test, correlation coefficient and coefficient of determination were applied to Gumble and LP-III distributions. Results reveal that among statistical approaches, Gumble distribution performed the best result compared to LP-III distribution. Isohyetal maps of the study area at different return periods are produced by using the GIS tool, and PMP in mountainous regions varies from 150 to 320 mm at an average value of 230.83 mm. The ratio of PMP for one-day duration to highest observed rainfall (HOR) varied from 1.08 to 1.29 with an average value of 1.18. An appropriate frequency factor (Km) is very important which is a function of mean for observed precipitation and PMP for 1-day duration, and Km values varies from 2.54 to 4.68. The coefficient of variability (Cv) varies from minimum value of 28% to maximum value of 43.35%. It was concluded that the statistical approach gives higher results compared to moisture maximization (MM) approach. In the hydro-meteorological approach, moisture maximization (MM) and wind moisture maximization (WMM) techniques were applied and it was concluded that wind moisture maximization approach gives higher results of PMP as compared to moisture maximization approach as well as for Hershfield technique. Therefore, it is suggested that MM approach is the most favored in the study area for PMP estimation, which leads to acceptable results, compared to WMM and statistical approaches.

Key words: PMP, Hershfield method, Gumble and LP-III method, Hydro-meteorological approaches, Goodness of fit (GOF) tests

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