IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v36y2022i2d10.1007_s11269-021-03042-8.html
   My bibliography  Save this article

European Multi Model Ensemble (EMME): A New Approach for Monthly Forecast of Precipitation

Author

Listed:
  • Morteza Pakdaman

    (Climatological Research Institute (CRI))

  • Iman Babaeian

    (Climatological Research Institute (CRI))

  • Zohreh Javanshiri

    (Climatological Research Institute (CRI))

  • Yashar Falamarzi

    (Climatological Research Institute (CRI))

Abstract

Regarding the ability of data mining algorithms for post-processing the output of climate models, and on the other hand, the successful application of multi-model ensemble approaches in climate forecasts, in this paper, some important data mining algorithms are evaluated for the monthly forecast of precipitation over Iran. For this purpose, four European climate models, from DWD, ECMWF, CMCC and Meteo-France, with six lead times, are used to be post-processed by applying four different algorithms including artificial neural networks, support vector regression, decision tree and random forests. Based on the proposed approach, 72 different models are provided for 12 months, each month with six lead times. The approach is applied for the monthly forecast of precipitation over Iran. According to the results, the neural network and random forest methods performed better than the decision tree and the support vector machine. This advantage preserved for all months of the year. Also, the proposed multi-model approach outperformed any of the individual European models.

Suggested Citation

  • Morteza Pakdaman & Iman Babaeian & Zohreh Javanshiri & Yashar Falamarzi, 2022. "European Multi Model Ensemble (EMME): A New Approach for Monthly Forecast of Precipitation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(2), pages 611-623, January.
    • Handle: RePEc:spr:waterr:v:36:y:2022:i:2:d:10.1007_s11269-021-03042-8
    DOI: 10.1007/s11269-021-03042-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11269-021-03042-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11269-021-03042-8?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. Saeed Azimi & Mehdi Azhdary Moghaddam, 2020. "Modeling Short Term Rainfall Forecast Using Neural Networks, and Gaussian Process Classification Based on the SPI Drought Index," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(4), pages 1369-1405, March.
    2. Kostas Moustris & Ioanna Larissi & Panagiotis Nastos & Athanasios Paliatsos, 2011. "Precipitation Forecast Using Artificial Neural Networks in Specific Regions of Greece," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(8), pages 1979-1993, June.
    3. Chih-Chiang Wei, 2020. "Real-time Extreme Rainfall Evaluation System for the Construction Industry Using Deep Convolutional Neural Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(9), pages 2787-2805, July.
    4. Getachew Tegegne & Assefa M. Melesse, 2020. "Multimodel Ensemble Projection of Hydro-climatic Extremes for Climate Change Impact Assessment on Water Resources," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(9), pages 3019-3035, July.
    5. Wen-chuan Wang & Yu-jin Du & Kwok-wing Chau & Dong-mei Xu & Chang-jun Liu & Qiang Ma, 2021. "An Ensemble Hybrid Forecasting Model for Annual Runoff Based on Sample Entropy, Secondary Decomposition, and Long Short-Term Memory Neural Network," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(14), pages 4695-4726, November.
    6. Samireh Saymohammadi & Kiumars Zarafshani & Mohsen Tavakoli & Hossien Mahdizadeh & Farzad Amiri, 2017. "Prediction of Climate Change Induced Temperature & Precipitation: The Case of Iran," Sustainability, MDPI, vol. 9(1), pages 1-13, January.
    7. 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.
    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. Aikaterini Lyra & Athanasios Loukas, 2023. "Simulation and Evaluation of Water Resources Management Scenarios Under Climate Change for Adaptive Management of Coastal Agricultural Watersheds," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(6), pages 2625-2642, May.
    2. Fuping Liu & Ying Liu & Chen Yang & Ruixun Lai, 2022. "A New Precipitation Prediction Method Based on CEEMDAN-IWOA-BP Coupling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(12), pages 4785-4797, September.

    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. Mohamed Shenify & Amir Danesh & Milan Gocić & Ros Taher & Ainuddin Abdul Wahab & Abdullah Gani & Shahaboddin Shamshirband & Dalibor Petković, 2016. "Precipitation Estimation Using Support Vector Machine with Discrete Wavelet Transform," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(2), pages 641-652, January.
    2. Seyedeh Hadis Moghadam & Parisa-Sadat Ashofteh & Hugo A. Loáiciga, 2022. "Optimal Water Allocation of Surface and Ground Water Resources Under Climate Change with WEAP and IWOA Modeling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(9), pages 3181-3205, July.
    3. Saeid Mehdizadeh & Javad Behmanesh & Keivan Khalili, 2018. "New Approaches for Estimation of Monthly Rainfall Based on GEP-ARCH and ANN-ARCH Hybrid Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(2), pages 527-545, January.
    4. R Maheswaran & Rakesh Khosa, 2014. "A Wavelet-Based Second Order Nonlinear Model for Forecasting Monthly Rainfall," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(15), pages 5411-5431, December.
    5. Peyman Abbaszadeh, 2016. "Improving Hydrological Process Modeling Using Optimized Threshold-Based Wavelet De-Noising Technique," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(5), pages 1701-1721, March.
    6. Clara Estrela-Segrelles & Gabriel Gómez-Martínez & Miguel Ángel Pérez-Martín, 2023. "Climate Change Risks on Mediterranean River Ecosystems and Adaptation Measures (Spain)," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(6), pages 2757-2770, May.
    7. Icen Yoosefdoost & Abbas Khashei-Siuki & Hossein Tabari & Omolbani Mohammadrezapour, 2022. "Runoff Simulation Under Future Climate Change Conditions: Performance Comparison of Data-Mining Algorithms and Conceptual Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(4), pages 1191-1215, March.
    8. Xi Yang & Zhihe Chen & Min Qin, 2024. "Monthly Runoff Prediction Via Mode Decomposition-Recombination Technique," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 38(1), pages 269-286, January.
    9. Lamine Diop & Saeed Samadianfard & Ansoumana Bodian & Zaher Mundher Yaseen & Mohammad Ali Ghorbani & Hana Salimi, 2020. "Annual Rainfall Forecasting Using Hybrid Artificial Intelligence Model: Integration of Multilayer Perceptron with Whale Optimization Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(2), pages 733-746, January.
    10. Georgia Papacharalampous & Hristos Tyralis & Demetris Koutsoyiannis, 2018. "Univariate Time Series Forecasting of Temperature and Precipitation with a Focus on Machine Learning Algorithms: a Multiple-Case Study from Greece," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(15), pages 5207-5239, December.
    11. Fuping Liu & Ying Liu & Chen Yang & Ruixun Lai, 2022. "A New Precipitation Prediction Method Based on CEEMDAN-IWOA-BP Coupling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(12), pages 4785-4797, September.
    12. Yaning Qiao & Eshan Dave & Tony Parry & Omar Valle & Lingyun Mi & Guodong Ni & Zhenmin Yuan & Yuefeng Zhu, 2019. "Life Cycle Costs Analysis of Reclaimed Asphalt Pavement (RAP) Under Future Climate," Sustainability, MDPI, vol. 11(19), pages 1-16, September.
    13. Marijana Hadzima-Nyarko & Anamarija Rabi & Marija Šperac, 2014. "Implementation of Artificial Neural Networks in Modeling the Water-Air Temperature Relationship of the River Drava," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(5), pages 1379-1394, March.
    14. Conor Murphy & Anthony Kettle & Hadush Meresa & Saeed Golian & Michael Bruen & Fiachra O’Loughlin & Per-Erik Mellander, 2023. "Climate Change Impacts on Irish River Flows: High Resolution Scenarios and Comparison with CORDEX and CMIP6 Ensembles," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(5), pages 1841-1858, March.
    15. Kyriakos Skarlatos & Eleni S. Bekri & Dimitrios Georgakellos & Polychronis Economou & Sotirios Bersimis, 2023. "Projecting Annual Rainfall Timeseries Using Machine Learning Techniques," Energies, MDPI, vol. 16(3), pages 1-20, February.
    16. D. Parker & S. Priest, 2012. "The Fallibility of Flood Warning Chains: Can Europe’s Flood Warnings Be Effective?," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(10), pages 2927-2950, August.
    17. Shuai Liu & Hui Qin & Guanjun Liu & Yang Xu & Xin Zhu & Xinliang Qi, 2023. "Runoff Forecasting of Machine Learning Model Based on Selective Ensemble," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(11), pages 4459-4473, September.
    18. 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.
    19. Peyman Abbaszadeh, 2016. "Improving Hydrological Process Modeling Using Optimized Threshold-Based Wavelet De-Noising Technique," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(5), pages 1701-1721, March.
    20. Ekaterini Hadjisolomou & Konstantinos Stefanidis & George Papatheodorou & Evanthia Papastergiadou, 2018. "Assessment of the Eutrophication-Related Environmental Parameters in Two Mediterranean Lakes by Integrating Statistical Techniques and Self-Organizing Maps," IJERPH, MDPI, vol. 15(3), pages 1-16, March.

    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:36:y:2022:i:2:d:10.1007_s11269-021-03042-8. 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.