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Using Meteorological Data to Adjust Water-Pricing of Urban Resident Households

Received: 20 January 2019     Published: 28 April 2019
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Abstract

In this paper, a dynamic method is presented for setting the price of urban residential water. Using a model called Seasonal Water Pricing (SWP); urban residential water pricing was set by taking into account the fact that some of the characteristics of temperature and precipitation may also influence residential water supply levels. In this work, an SWP model was adopted and used to estimate correction coefficients for urban residential water prices. The adjusted cost of water was < 3% of the disposable per capita income of customers. Thus, this work offers a basis for reforming water resource pricing in China.

Published in Journal of Energy and Natural Resources (Volume 8, Issue 1)
DOI 10.11648/j.jenr.20190801.15
Page(s) 30-36
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), 2019. Published by Science Publishing Group

Keywords

Water Prices, SWP Model, Temperature, Precipitation, Adjusted Water Pricing, Xi’an

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  • APA Style

    Juan Zhao, Xingmin Mu, Wenbing Shi, Mei Ou. (2019). Using Meteorological Data to Adjust Water-Pricing of Urban Resident Households. Journal of Energy and Natural Resources, 8(1), 30-36. https://doi.org/10.11648/j.jenr.20190801.15

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    ACS Style

    Juan Zhao; Xingmin Mu; Wenbing Shi; Mei Ou. Using Meteorological Data to Adjust Water-Pricing of Urban Resident Households. J. Energy Nat. Resour. 2019, 8(1), 30-36. doi: 10.11648/j.jenr.20190801.15

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    AMA Style

    Juan Zhao, Xingmin Mu, Wenbing Shi, Mei Ou. Using Meteorological Data to Adjust Water-Pricing of Urban Resident Households. J Energy Nat Resour. 2019;8(1):30-36. doi: 10.11648/j.jenr.20190801.15

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  • @article{10.11648/j.jenr.20190801.15,
      author = {Juan Zhao and Xingmin Mu and Wenbing Shi and Mei Ou},
      title = {Using Meteorological Data to Adjust Water-Pricing of Urban Resident Households},
      journal = {Journal of Energy and Natural Resources},
      volume = {8},
      number = {1},
      pages = {30-36},
      doi = {10.11648/j.jenr.20190801.15},
      url = {https://doi.org/10.11648/j.jenr.20190801.15},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jenr.20190801.15},
      abstract = {In this paper, a dynamic method is presented for setting the price of urban residential water. Using a model called Seasonal Water Pricing (SWP); urban residential water pricing was set by taking into account the fact that some of the characteristics of temperature and precipitation may also influence residential water supply levels. In this work, an SWP model was adopted and used to estimate correction coefficients for urban residential water prices. The adjusted cost of water was < 3% of the disposable per capita income of customers. Thus, this work offers a basis for reforming water resource pricing in China.},
     year = {2019}
    }
    

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  • TY  - JOUR
    T1  - Using Meteorological Data to Adjust Water-Pricing of Urban Resident Households
    AU  - Juan Zhao
    AU  - Xingmin Mu
    AU  - Wenbing Shi
    AU  - Mei Ou
    Y1  - 2019/04/28
    PY  - 2019
    N1  - https://doi.org/10.11648/j.jenr.20190801.15
    DO  - 10.11648/j.jenr.20190801.15
    T2  - Journal of Energy and Natural Resources
    JF  - Journal of Energy and Natural Resources
    JO  - Journal of Energy and Natural Resources
    SP  - 30
    EP  - 36
    PB  - Science Publishing Group
    SN  - 2330-7404
    UR  - https://doi.org/10.11648/j.jenr.20190801.15
    AB  - In this paper, a dynamic method is presented for setting the price of urban residential water. Using a model called Seasonal Water Pricing (SWP); urban residential water pricing was set by taking into account the fact that some of the characteristics of temperature and precipitation may also influence residential water supply levels. In this work, an SWP model was adopted and used to estimate correction coefficients for urban residential water prices. The adjusted cost of water was < 3% of the disposable per capita income of customers. Thus, this work offers a basis for reforming water resource pricing in China.
    VL  - 8
    IS  - 1
    ER  - 

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Author Information
  • Institute of Soil and Water Conservation, Northwest A & F University, Yangling, China

  • Institute of Soil and Water Conservation, Northwest A & F University, Yangling, China

  • College of Resource and Environmental Engineering, Guizhou University, Guiyang, China

  • Mingde College, Guizhou University, Guiyang, China

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