IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v29y2015i3p901-912.html
   My bibliography  Save this article

Classification-Based Spatiotemporal Variations of Pan Evaporation Across the Guangdong Province, South China

Author

Listed:
  • Yanhu He
  • Kairong Lin
  • Xiaohong Chen
  • Changqing Ye
  • Lei Cheng

Abstract

Change in pan evaporation (E pan ) has evoked general scientific interest because it involves both climatic and hydrological effects. The enhanced greenhouse effect may be the casual factor, although the mechanism still needs to be further confirmed. Based on meteorological data (Pan evaporation, rainfall, air temperature, sunshine duration, relative humidity, wind speed, cloud cover, and water vapor pressure) of 85 sites from 1957 to 2006, classification-based spatiotemporal variations of pan evaporation and possible causes were studied in the Guangdong province, South China (with a coastline of 8,500 km), which is one of China’s most prosperous provinces with the largest population. The Guangdong province was spatially divided into 4 parts, i.e., Southwest part, East part, Central part, and Northwest part, according to E pan and seven other climatic factors based on cluster analysis. Results showed that pan evaporation in this study area declined −3.35 mm year −1 on average in time, and mainly decreased from the seashore area to the inland area in space. Results also showed that all the climatic factors can contribute to change in E pan , but their contributions were different over the space. Sunshine duration (SD) and wind speed (WS) had a positive correlation with E pan , while rainfall (R) and air temperature (T a ) were negatively correlated to E pan . Among all the 7 climatic factors, SD was identified as the dominant driving force of E pan change in the Guangdong province. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • Yanhu He & Kairong Lin & Xiaohong Chen & Changqing Ye & Lei Cheng, 2015. "Classification-Based Spatiotemporal Variations of Pan Evaporation Across the Guangdong Province, South China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(3), pages 901-912, February.
  • Handle: RePEc:spr:waterr:v:29:y:2015:i:3:p:901-912
    DOI: 10.1007/s11269-014-0850-5
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11269-014-0850-5
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11269-014-0850-5?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ashoke Basistha & D. Arya & N. Goel, 2008. "Spatial Distribution of Rainfall in Indian Himalayas – A Case Study of Uttarakhand Region," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 22(10), pages 1325-1346, October.
    2. Sungwon Kim & Jalal Shiri & Ozgur Kisi & Vijay Singh, 2013. "Estimating Daily Pan Evaporation Using Different Data-Driven Methods and Lag-Time Patterns," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(7), pages 2267-2286, May.
    3. Sungwon Kim & Jalal Shiri & Ozgur Kisi, 2012. "Pan Evaporation Modeling Using Neural Computing Approach for Different Climatic Zones," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(11), pages 3231-3249, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yanhu He & Jie Yang & Xiaohong Chen & Kairong Lin & Yanhui Zheng & Zhaoli Wang, 2018. "A Two-stage Approach to Basin-scale Water Demand Prediction," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(2), pages 401-416, January.
    2. Kairong Lin & Youqin Lin & Pan Liu & Yanhu He & Xinjun Tu, 2016. "Considering the Order and Symmetry to Improve the Traditional RVA for Evaluation of Hydrologic Alteration of River Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(14), pages 5501-5516, November.
    3. Jie Zhao & Zongxue Xu & Vijay P. Singh & Depeng Zuo & Mo Li, 2016. "Sensitivity of Potential Evapotranspiration to Climate and Vegetation in a Water-Limited Basin at the Northern Edge of Tibetan Plateau," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(13), pages 4667-4680, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ozgur Kisi & Levent Latifoğlu & Fatma Latifoğlu, 2014. "Investigation of Empirical Mode Decomposition in Forecasting of Hydrological Time Series," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(12), pages 4045-4057, September.
    2. Youngmin Seo & Sungwon Kim & Vijay Singh, 2015. "Estimating Spatial Precipitation Using Regression Kriging and Artificial Neural Network Residual Kriging (RKNNRK) Hybrid Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(7), pages 2189-2204, May.
    3. Ozgur Kisi & Taner Cengiz, 2013. "Fuzzy Genetic Approach for Estimating Reference Evapotranspiration of Turkey: Mediterranean Region," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(10), pages 3541-3553, August.
    4. Xianming Dou & Yongguo Yang & Jinhui Luo, 2018. "Estimating Forest Carbon Fluxes Using Machine Learning Techniques Based on Eddy Covariance Measurements," Sustainability, MDPI, vol. 10(1), pages 1-26, January.
    5. Jet-chau Wen & Yen-jen Lee & Shin-jen Cheng & Ju-huang Lee, 2014. "Changes of rural to urban areas in hydrograph characteristics on watershed divisions," 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. 74(2), pages 887-909, November.
    6. Zhang, Lei & Traore, Seydou & Cui, Yuanlai & Luo, Yufeng & Zhu, Ge & Liu, Bo & Fipps, Guy & Karthikeyan, R. & Singh, Vijay, 2019. "Assessment of spatiotemporal variability of reference evapotranspiration and controlling climate factors over decades in China using geospatial techniques," Agricultural Water Management, Elsevier, vol. 213(C), pages 499-511.
    7. Youngmin Seo & Sungwon Kim & Ozgur Kisi & Vijay P. Singh & Kamban Parasuraman, 2016. "River Stage Forecasting Using Wavelet Packet Decomposition and Machine Learning Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(11), pages 4011-4035, September.
    8. H. Assaf & M. Saadeh, 2009. "Geostatistical Assessment of Groundwater Nitrate Contamination with Reflection on DRASTIC Vulnerability Assessment: The Case of the Upper Litani Basin, Lebanon," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(4), pages 775-796, March.
    9. Alina Barbulescu, 2016. "A New Method for Estimation the Regional Precipitation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(1), pages 33-42, January.
    10. Sungwon Kim & Jalal Shiri & Ozgur Kisi & Vijay Singh, 2013. "Estimating Daily Pan Evaporation Using Different Data-Driven Methods and Lag-Time Patterns," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(7), pages 2267-2286, May.
    11. Zhenfang He & Yaonan Zhang & Qingchun Guo & Xueru Zhao, 2014. "Comparative Study of Artificial Neural Networks and Wavelet Artificial Neural Networks for Groundwater Depth Data Forecasting with Various Curve Fractal Dimensions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(15), pages 5297-5317, December.
    12. Pravat Jena & Sarita Azad, 2022. "Identification of wet-prone regions over Northwest Himalaya using high-resolution satellite seasonal estimates," 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. 112(2), pages 1727-1748, June.
    13. Sungwon Kim & Vijay Singh & Youngmin Seo & Hung Kim, 2014. "Modeling Nonlinear Monthly Evapotranspiration Using Soft Computing and Data Reconstruction Techniques," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(1), pages 185-206, January.
    14. Nazzareno Diodato & Gianni Tartari & Gianni Bellocchi, 2010. "Geospatial Rainfall Modelling at Eastern Nepalese Highland from Ground Environmental Data," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(11), pages 2703-2720, September.
    15. Alina Barbulescu, 2016. "A New Method for Estimation the Regional Precipitation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(1), pages 33-42, January.
    16. Jian Tang & Xin-An Yin & Pan Yang & ZhiFeng Yang, 2014. "Assessment of Contributions of Climatic Variation and Human Activities to Streamflow Changes in the Lancang River, China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(10), pages 2953-2966, August.
    17. Miao Zhang & Bo Su & Majid Nazeer & Muhammad Bilal & Pengcheng Qi & Ge Han, 2020. "Climatic Characteristics and Modeling Evaluation of Pan Evapotranspiration over Henan Province, China," Land, MDPI, vol. 9(7), pages 1-14, July.
    18. Watinee Thavorntam & Netnapid Tantemsapya & Leisa Armstrong, 2015. "A combination of meteorological and satellite-based drought indices in a better drought assessment and forecasting in Northeast Thailand," 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. 77(3), pages 1453-1474, July.
    19. M. Samanta & P. Punetha & S. Sarkar & A. Dwivedi & M. Sharma, 2019. "Slope stability assessment and design of remedial measures for Tungnath Temple at Uttarakhand, India: a case study," 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. 96(1), pages 225-246, March.
    20. Rajesh Kumar & Shaktiman Singh & Ramesh Kumar & Atar Singh & Anshuman Bhardwaj & Lydia Sam & Surjeet Singh Randhawa & Akhilesh Gupta, 2016. "Development of a Glacio-hydrological Model for Discharge and Mass Balance Reconstruction," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(10), pages 3475-3492, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:waterr:v:29:y:2015:i:3:p:901-912. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.