IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i15p11568-d1203203.html
   My bibliography  Save this article

Enhancing Meteorological Drought Modeling Accuracy Using Hybrid Boost Regression Models: A Case Study from the Aegean Region, Türkiye

Author

Listed:
  • Enes Gul

    (Department of Civil Engineering, Inonu University, Malatya 44000, Türkiye)

  • Efthymia Staiou

    (Department of Industrial Engineering, Yasar University, Izmir 35100, Türkiye)

  • Mir Jafar Sadegh Safari

    (Department of Civil Engineering, Yasar University, Izmir 35100, Türkiye)

  • Babak Vaheddoost

    (Department of Civil Engineering, Bursa Technical University, Bursa 16310, Türkiye)

Abstract

The impact of climate change has led to significant changes in hydroclimatic patterns and continuous stress on water resources through frequent wet and dry spells. Hence, understanding and effectively addressing the escalating impact of climate change on hydroclimatic patterns, especially in the context of meteorological drought, necessitates precise modeling of these phenomena. This study focuses on assessing the accuracy of drought modeling using the well-established Standard Precipitation Index (SPI) in the Aegean region of Türkiye. The study utilizes monthly precipitation data from six stations in Cesme, Kusadasi, Manisa, Seferihisar, Selcuk and Izmir at Kucuk Menderes Basin covering the period from 1973 to 2020. The dataset is divided into three sets, training (60%), validation (20%), and testing (20%) sets. The study aims to determine the SPI-3, SPI-6 and SPI-12 using a multi-station prediction technique. Three boosting regression models (BRMs), namely Extreme Gradient Boosting (XgBoost), Adaptive Boosting (AdaBoost), and Gradient Boosting (GradBoost), were employed and optimized with the help of the Weighted Mean of Vectors (INFO) technique. Model performances were then evaluated with the Root Mean Square Error ( RMSE ), Mean Absolute Error ( MAE ), Mean Absolute Percentage Error ( MAPE ), Coefficient of Determination ( R 2 ) and the Willmott Index ( WI ). Results demonstrated a distinct superiority of the XgBoost model over AdaBoost and GradBoost in terms of accuracy. During the test phase, the XgBoost model achieved RMSEs of 0.496, 0.429 and 0.389 for SPI-3, SPI-6 and SPI-12, respectively. The WIs were 0.899, 0.901 and 0.825 for SPI-3, SPI-6 and SPI-12, respectively. These are considerably lower than the corresponding values obtained by the other models. Yet, the comparative statistical analysis further underscores the effectiveness of XgBoost in modeling extended periods of drought in the Aegean region of Türkiye.

Suggested Citation

  • Enes Gul & Efthymia Staiou & Mir Jafar Sadegh Safari & Babak Vaheddoost, 2023. "Enhancing Meteorological Drought Modeling Accuracy Using Hybrid Boost Regression Models: A Case Study from the Aegean Region, Türkiye," Sustainability, MDPI, vol. 15(15), pages 1-17, July.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:15:p:11568-:d:1203203
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/15/11568/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/15/11568/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Luca Di Persio & Nicola Fraccarolo, 2023. "Energy Consumption Forecasts by Gradient Boosting Regression Trees," Mathematics, MDPI, vol. 11(5), pages 1-17, February.
    2. G. Tsakiris & D. Pangalou & H. Vangelis, 2007. "Regional Drought Assessment Based on the Reconnaissance Drought Index (RDI)," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(5), pages 821-833, May.
    3. Ali Danandeh Mehr & Rifat Tur & Mohammed Mustafa Alee & Enes Gul & Vahid Nourani & Shahrokh Shoaei & Babak Mohammadi, 2023. "Optimizing Extreme Learning Machine for Drought Forecasting: Water Cycle vs. Bacterial Foraging," Sustainability, MDPI, vol. 15(5), pages 1-17, February.
    4. Manish Pandey & Masoud Karbasi & Mehdi Jamei & Anurag Malik & Jaan H. Pu, 2023. "A Comprehensive Experimental and Computational Investigation on Estimation of Scour Depth at Bridge Abutment: Emerging Ensemble Intelligent Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(9), pages 3745-3767, July.
    5. Carmona, Pedro & Climent, Francisco & Momparler, Alexandre, 2019. "Predicting failure in the U.S. banking sector: An extreme gradient boosting approach," International Review of Economics & Finance, Elsevier, vol. 61(C), pages 304-323.
    6. I. Nalbantis & G. Tsakiris, 2009. "Assessment of Hydrological Drought Revisited," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(5), pages 881-897, March.
    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. Ioannis M. Kourtis & Harris Vangelis & Dimitris Tigkas & Anna Mamara & Ioannis Nalbantis & George Tsakiris & Vassilios A. Tsihrintzis, 2023. "Drought Assessment in Greece Using SPI and ERA5 Climate Reanalysis Data," Sustainability, MDPI, vol. 15(22), pages 1-19, November.
    2. Murat Can, 2024. "Invasive-Weed-Optimization-Based Extreme Learning Machine for Prediction of Lake Water Level Using Major Atmospheric–Oceanic Climate Scenarios," Sustainability, MDPI, vol. 16(17), pages 1-13, 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. Lampros Vasiliades & Athanasios Loukas & Nikos Liberis, 2011. "A Water Balance Derived Drought Index for Pinios River Basin, Greece," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(4), pages 1087-1101, March.
    2. Youxin Wang & Tao Peng & Qingxia Lin & Vijay P. Singh & Xiaohua Dong & Chen Chen & Ji Liu & Wenjuan Chang & Gaoxu Wang, 2022. "A New Non-stationary Hydrological Drought Index Encompassing Climate Indices and Modified Reservoir Index as Covariates," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(7), pages 2433-2454, May.
    3. Dimitrios Myronidis & Konstantinos Ioannou & Dimitrios Fotakis & Gerald Dörflinger, 2018. "Streamflow and Hydrological Drought Trend Analysis and Forecasting in Cyprus," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(5), pages 1759-1776, March.
    4. Jagadish Padhiary & Kanhu Charan Patra & Sonam Sandeep Dash, 2022. "A Novel Approach to Identify the Characteristics of Drought under Future Climate Change Scenario," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(13), pages 5163-5189, October.
    5. Peng Qi & Y. Jun Xu & Guodong Wang, 2020. "Quantifying the Individual Contributions of Climate Change, Dam Construction, and Land Use/Land Cover Change to Hydrological Drought in a Marshy River," Sustainability, MDPI, vol. 12(9), pages 1-16, May.
    6. Nadjib Haied & Atif Foufou & Samira Khadri & Adel Boussaid & Mohamed Azlaoui & Nabil Bougherira, 2023. "Spatial and Temporal Assessment of Drought Hazard, Vulnerability and Risk in Three Different Climatic Zones in Algeria Using Two Commonly Used Meteorological Indices," Sustainability, MDPI, vol. 15(10), pages 1-25, May.
    7. Jianzhu Li & Shuhan Zhou & Rong Hu, 2016. "Hydrological Drought Class Transition Using SPI and SRI Time Series by Loglinear Regression," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(2), pages 669-684, January.
    8. Dilayda Soylu Pekpostalci & Rifat Tur & Ali Danandeh Mehr & Mohammad Amin Vazifekhah Ghaffari & Dominika Dąbrowska & Vahid Nourani, 2023. "Drought Monitoring and Forecasting across Turkey: A Contemporary Review," Sustainability, MDPI, vol. 15(7), pages 1-23, March.
    9. Mohsin Butt & Ahmad Waqas & Rashed Mahmood, 2010. "The Combined Effect of Vegetation and Soil Erosion in the Water Resource Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(13), pages 3701-3714, October.
    10. Rajendra Pandey & Ashish Pandey & Ravi Galkate & Hi-Ryong Byun & Bimal Mal, 2010. "Integrating Hydro-Meteorological and Physiographic Factors for Assessment of Vulnerability to Drought," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(15), pages 4199-4217, December.
    11. Ionuţ Minea & Marina Iosub & Daniel Boicu, 2022. "Multi-scale approach for different type of drought in temperate climatic conditions," 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. 110(2), pages 1153-1177, January.
    12. Alireza Shokoohi & Reza Morovati, 2015. "Basinwide Comparison of RDI and SPI Within an IWRM Framework," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(6), pages 2011-2026, April.
    13. Ali Tabrizi & Davar Khalili & Ali Kamgar-Haghighi & Shahrokh Zand-Parsa, 2010. "Utilization of Time-Based Meteorological Droughts to Investigate Occurrence of Streamflow Droughts," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(15), pages 4287-4306, December.
    14. U. Surendran & B. Anagha & P. Raja & V. Kumar & K. Rajan & M. Jayakumar, 2019. "Analysis of Drought from Humid, Semi-Arid and Arid Regions of India Using DrinC Model with Different Drought Indices," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(4), pages 1521-1540, March.
    15. Dimitrios Myronidis & Dimitrios Stathis & Konstantinos Ioannou & Dimitrios Fotakis, 2012. "An Integration of Statistics Temporal Methods to Track the Effect of Drought in a Shallow Mediterranean Lake," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(15), pages 4587-4605, December.
    16. Panagiotis Angelidis & Fotios Maris & Nikos Kotsovinos & Vlassios Hrissanthou, 2012. "Computation of Drought Index SPI with Alternative Distribution Functions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(9), pages 2453-2473, July.
    17. Jae Ryu & Mohammad Sohrabi & Anil Acharya, 2014. "Toward Mapping Gridded Drought Indices to Evaluate Local Drought in a Rapidly Changing Global Environment," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(11), pages 3859-3869, September.
    18. Iraj Emadodin & Daniel Ernesto Flores Corral & Thorsten Reinsch & Christof Kluß & Friedhelm Taube, 2021. "Climate Change Effects on Temperate Grassland and Its Implication for Forage Production: A Case Study from Northern Germany," Agriculture, MDPI, vol. 11(3), pages 1-17, March.
    19. Jianzhu Li & Shuhan Zhou & Rong Hu, 2016. "Hydrological Drought Class Transition Using SPI and SRI Time Series by Loglinear Regression," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(2), pages 669-684, January.
    20. G. Tsakiris & I. Nalbantis & H. Vangelis & B. Verbeiren & M. Huysmans & B. Tychon & I. Jacquemin & F. Canters & S. Vanderhaegen & G. Engelen & L. Poelmans & P. Becker & O. Batelaan, 2013. "A System-based Paradigm of Drought Analysis for Operational Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(15), pages 5281-5297, December.

    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:gam:jsusta:v:15:y:2023:i:15:p:11568-:d:1203203. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.