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

Wang Haike; Xu Panpan; Qian Hui

doi:doi:10.11648/j.earth.20150405.16

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

Wang Haike, Xu Panpan, Qian Hui

Published in Earth Sciences (Volume 4, Issue 5)

Received: 30 November 2015 Published: 1 December 2015

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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

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[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。
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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

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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

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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

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@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}
}

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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  -

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Author Information

Wang Haike

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

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

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

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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

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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

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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}
}

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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  -

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