| Peer-Reviewed

Using Monte Carlo Method for Predicting Rainfall -- Taking Xi'an Area, Shaanxi Province, China, as an Example

Received: 30 November 2015     Published: 1 December 2015
Views:       Downloads:
Abstract

Rainfall forecasting plays a vital role in the national economy, social development and human life. Based on Monte Carlo method, this paper uses P- III distribution function to fitting precipitation data in the past 63 years so as to forecast precipitation. Using this model to forecast the rainfall for the past ten years (2003 ~~2013) in Xi'an city, Shaanxi province, China, based on the past 63 years data. The predicted results indicate that the prediction has a high accuracy in normal rainfall year, but in extremely in dry condition and high rainfall year, the relative error is huge. So that,the method is more suitable for the prediction of rainfall in the flat water.

Published in Earth Sciences (Volume 4, Issue 5)
DOI 10.11648/j.earth.20150405.16
Page(s) 201-204
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2015. Published by Science Publishing Group

Keywords

Monte Carlo, P- III Distribution Curve, Precipitation Forecasting, Curve Fitting Method

References
[1] 朱聪.径流中长期预测模型研究[M].四川大学.2005.04。
[2] 冯文权.预测•头脑风暴法•特尔菲法[J].科学决策,1997(2):39-41。
[3] MunotA,A., Kumar, K.K.,.Long range prediction of Indian summer monsoon rainfall [J]. Journal of Earth System Science 1 I G(I), 2007: 73-79.
[4] Nayagam, L.R., Janardanan,R.,Mohan,H.S.R.. An empirical model for the seasonal prediction of southwest monsoon rainfall over Kerala, a meteorological subdivision of India[J]. International Journal of Climatology 28(6),2008: 823-831.
[5] Toth,E.,Brath,A.,Montanari,A.. Comparison of short-term rainfall prediction models for real-time flood forecasting[J]. Journal of Hydrology 2000. 239,132-147.
[6] 张德同,王学敏.径向基函数人工神经网络在白城市年降雨量预测中的应用[J].技术应用.2013,17-0122-01,118-122。
[7] 侯祥龙,阳辉.基于滑动无偏灰色马尔科夫模型的水库年降水量预测[J].水土保持通报.2014,34(3),181-184。
[8] 钱会,李培月,王涛.基于平均滑动—加权马尔科夫链的宁夏石嘴山市年降雨量预测[J].华北水利水电学院学报.2010,30(1),6-9。
[9] 采用遗传算法的小波神经网络在降雨量预测中的应用[J].河南工程学院学报(自然科学版).2015,27(1),53-57。
[10] Ganguly, A.R., Bras, R.L.. Distributed quantitative precipitation forecasting (DQPF) using information from radar and numerical weather prediction models [J]. Journal of Hydrometeorology. 2003. 1168-1180.
[11] 韦庆,卢文喜,田文君.运用蒙特卡罗方法预报年降雨量研究[J].干旱区资源与环境.2004,18(4),144-146。
[12] 杨金玲,吴亚楠,谢淼等.蒙特卡罗法在嫩江流域汛期降雨量预测中的应用[J].南水北调与水利科技.2011,9(3),28-32。
[13] 吴建华,李培月,钱会.西安市气象要素变化特征及可利用降雨量预测模型[J].南水北调与水利科技.2013,11(1),50-54。
[14] I.M. Sobol'. The distribution of points in a cube and the approximate evaluation of integrals. USSR Comp [J]. Math. and Math. Phys., 7: 86--112, 1967.
[15] H.Niederreiter. Point sets and sequences with small discrepancy [J]. Monatsh.Math.104: 273-337,1987.
[16] 陈志凯,暴雨及洪水频率计算方法的研究[R],北京:中国水利水电科学研究院水文研究所,1957。
[17] Water Resources Council, Hydrology committee, A uniform technique for determining flood flow frequencies, Bulletin 15, Washington, D.C., 1967.
Cite This Article
  • APA Style

    Wang Haike, Xu Panpan, Qian Hui. (2015). Using Monte Carlo Method for Predicting Rainfall -- Taking Xi'an Area, Shaanxi Province, China, as an Example. Earth Sciences, 4(5), 201-204. https://doi.org/10.11648/j.earth.20150405.16

    Copy | Download

    ACS Style

    Wang Haike; Xu Panpan; Qian Hui. Using Monte Carlo Method for Predicting Rainfall -- Taking Xi'an Area, Shaanxi Province, China, as an Example. Earth Sci. 2015, 4(5), 201-204. doi: 10.11648/j.earth.20150405.16

    Copy | Download

    AMA Style

    Wang Haike, Xu Panpan, Qian Hui. Using Monte Carlo Method for Predicting Rainfall -- Taking Xi'an Area, Shaanxi Province, China, as an Example. Earth Sci. 2015;4(5):201-204. doi: 10.11648/j.earth.20150405.16

    Copy | Download

  • @article{10.11648/j.earth.20150405.16,
      author = {Wang Haike and Xu Panpan and Qian Hui},
      title = {Using Monte Carlo Method for Predicting Rainfall -- Taking Xi'an Area, Shaanxi Province, China, as an Example},
      journal = {Earth Sciences},
      volume = {4},
      number = {5},
      pages = {201-204},
      doi = {10.11648/j.earth.20150405.16},
      url = {https://doi.org/10.11648/j.earth.20150405.16},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.earth.20150405.16},
      abstract = {Rainfall forecasting plays a vital role in the national economy, social development and human life. Based on Monte Carlo method, this paper uses P- III distribution function to fitting precipitation data in the past 63 years so as to forecast precipitation. Using this model to forecast the rainfall for the past ten years (2003 ~~2013) in Xi'an city, Shaanxi province, China, based on the past 63 years data. The predicted results indicate that the prediction has a high accuracy in normal rainfall year, but in extremely in dry condition and high rainfall year, the relative error is huge. So that,the method is more suitable for the prediction of rainfall in the flat water.},
     year = {2015}
    }
    

    Copy | Download

  • TY  - JOUR
    T1  - Using Monte Carlo Method for Predicting Rainfall -- Taking Xi'an Area, Shaanxi Province, China, as an Example
    AU  - Wang Haike
    AU  - Xu Panpan
    AU  - Qian Hui
    Y1  - 2015/12/01
    PY  - 2015
    N1  - https://doi.org/10.11648/j.earth.20150405.16
    DO  - 10.11648/j.earth.20150405.16
    T2  - Earth Sciences
    JF  - Earth Sciences
    JO  - Earth Sciences
    SP  - 201
    EP  - 204
    PB  - Science Publishing Group
    SN  - 2328-5982
    UR  - https://doi.org/10.11648/j.earth.20150405.16
    AB  - Rainfall forecasting plays a vital role in the national economy, social development and human life. Based on Monte Carlo method, this paper uses P- III distribution function to fitting precipitation data in the past 63 years so as to forecast precipitation. Using this model to forecast the rainfall for the past ten years (2003 ~~2013) in Xi'an city, Shaanxi province, China, based on the past 63 years data. The predicted results indicate that the prediction has a high accuracy in normal rainfall year, but in extremely in dry condition and high rainfall year, the relative error is huge. So that,the method is more suitable for the prediction of rainfall in the flat water.
    VL  - 4
    IS  - 5
    ER  - 

    Copy | Download

Author Information
  • College of Environmental Science and Engineering, Chang'an University, Xi'an, China

  • College of Environmental Science and Engineering, Chang'an University, Xi'an, China

  • College of Environmental Science and Engineering, Chang'an University, Xi'an, China

  • Sections