IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i2p1109-d1027754.html
   My bibliography  Save this article

Prediction of Streamflow Drought Index for Short-Term Hydrological Drought in the Semi-Arid Yesilirmak Basin Using Wavelet Transform and Artificial Intelligence Techniques

Author

Listed:
  • Okan Mert Katipoğlu

    (Department of Civil Engineering, Erzincan Binali Yıldırım University, Erzincan 24002, Turkey)

Abstract

The prediction of hydrological droughts is vital for surface and ground waters, reservoir levels, hydroelectric power generation, agricultural production, forest fires, climate change, and the survival of living things. This study aimed to forecast 1-month lead-time hydrological droughts in the Yesilirmak basin. For this purpose, support vector regression, Gaussian process regression, regression tree, and ensemble tree models were used alone and in combination with a discrete wavelet transform. Streamflow drought index values were used to determine hydrological droughts. The data were divided into 70% training (1969–1998) and 30% (1999–2011) testing. The performance of the models was evaluated according to various statistical criteria such as mean square error, root means square error, mean absolute error, and determination coefficient. As a result, it was determined that the prediction performance of the models obtained by decomposing into subcomponents with the discrete wavelet transform was optimal. In addition, the most effective drought-predicting model was obtained using the db10 wavelet and MGPR algorithm with mean squared error 0.007, root mean squared error 0.08, mean absolute error 0.04, and coefficient of determination (R 2 ) 0.99 at station 1413. The weakest model was the stand-alone FGSV (RMSE 0.88, RMSE 0.94, MAE 0.76, R 2 0.14). Moreover, it was revealed that the db10 main wavelet was more accurate in predicting short-term drought than other wavelets. These results provide essential information to decision-makers and planners to manage hydrological droughts in the Yesilirmak basin.

Suggested Citation

  • Okan Mert Katipoğlu, 2023. "Prediction of Streamflow Drought Index for Short-Term Hydrological Drought in the Semi-Arid Yesilirmak Basin Using Wavelet Transform and Artificial Intelligence Techniques," Sustainability, MDPI, vol. 15(2), pages 1-24, January.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:2:p:1109-:d:1027754
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/2/1109/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/2/1109/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Salim Djerbouai & Doudja Souag-Gamane, 2016. "Drought Forecasting Using Neural Networks, Wavelet Neural Networks, and Stochastic Models: Case of the Algerois Basin in North Algeria," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(7), pages 2445-2464, May.
    2. Abhinav Kumar Singh & Pankaj Kumar & Rawshan Ali & Nadhir Al-Ansari & Dinesh Kumar Vishwakarma & Kuldeep Singh Kushwaha & Kanhu Charan Panda & Atish Sagar & Ehsan Mirzania & Ahmed Elbeltagi & Alban Ku, 2022. "An Integrated Statistical-Machine Learning Approach for Runoff Prediction," Sustainability, MDPI, vol. 14(13), pages 1-30, July.
    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. Anurag Malik & Anil Kumar & Rajesh P. Singh, 2019. "Application of Heuristic Approaches for Prediction of Hydrological Drought Using Multi-scalar Streamflow Drought Index," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(11), pages 3985-4006, September.
    5. Sedigheh Mohamadi & Saad Sh. Sammen & Fatemeh Panahi & Mohammad Ehteram & Ozgur Kisi & Amir Mosavi & Ali Najah Ahmed & Ahmed El-Shafie & Nadhir Al-Ansari, 2020. "Zoning map for drought prediction using integrated machine learning models with a nomadic people optimization algorithm," 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. 104(1), pages 537-579, October.
    6. Junfei Chen & Ming Li & Weiguang Wang, 2012. "Statistical Uncertainty Estimation Using Random Forests and Its Application to Drought Forecast," Mathematical Problems in Engineering, Hindawi, vol. 2012, pages 1-12, September.
    7. Hossein Tabari & Jaefar Nikbakht & P. Hosseinzadeh Talaee, 2013. "Hydrological Drought Assessment in Northwestern Iran Based on Streamflow Drought Index (SDI)," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(1), pages 137-151, January.
    8. Farshad Ahmadi & Saeid Mehdizadeh & Babak Mohammadi, 2021. "Development of Bio-Inspired- and Wavelet-Based Hybrid Models for Reconnaissance Drought Index Modeling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(12), pages 4127-4147, September.
    9. 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)

    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. V. K. Prajapati & M. Khanna & M. Singh & R. Kaur & R. N. Sahoo & D. K. Singh, 2021. "Evaluation of time scale of meteorological, hydrological and agricultural drought indices," 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. 109(1), pages 89-109, October.
    2. Anurag Malik & Anil Kumar & Rajesh P. Singh, 2019. "Application of Heuristic Approaches for Prediction of Hydrological Drought Using Multi-scalar Streamflow Drought Index," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(11), pages 3985-4006, September.
    3. Neeta Nandgude & T. P. Singh & Sachin Nandgude & Mukesh Tiwari, 2023. "Drought Prediction: A Comprehensive Review of Different Drought Prediction Models and Adopted Technologies," Sustainability, MDPI, vol. 15(15), pages 1-19, July.
    4. Elnaz Ghabelnezam & Raoof Mostafazadeh & Zeinab Hazbavi & Guangwei Huang, 2023. "Hydrological Drought Severity in Different Return Periods in Rivers of Ardabil Province, Iran," Sustainability, MDPI, vol. 15(3), pages 1-16, January.
    5. Hossein Tabari & Reza Zamani & Hossein Rahmati & Patrick Willems, 2015. "Markov Chains of Different Orders for Streamflow Drought Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(9), pages 3441-3457, July.
    6. Beshavard, Mahdi & Adib, Arash & Ashrafi, Seyed Mohammad & Kisi, Ozgur, 2022. "Establishing effective warning storage to derive optimal reservoir operation policy based on the drought condition," Agricultural Water Management, Elsevier, vol. 274(C).
    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. Mahdi Soleimani Motlagh & Hoda Ghasemieh & Ali Talebi & Khodayar Abdollahi, 2017. "Identification and Analysis of Drought Propagation of Groundwater During Past and Future Periods," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(1), pages 109-125, January.
    9. 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.
    10. T. Thomas & R. K. Jaiswal & Ravi Galkate & P. C. Nayak & N. C. Ghosh, 2016. "Drought indicators-based integrated assessment of drought vulnerability: a case study of Bundelkhand droughts in central India," 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. 81(3), pages 1627-1652, April.
    11. Hasrul Hazman Hasan & Siti Fatin Mohd Razali & Nur Shazwani Muhammad & Asmadi Ahmad, 2022. "Modified Hydrological Drought Risk Assessment Based on Spatial and Temporal Approaches," Sustainability, MDPI, vol. 14(10), pages 1-28, May.
    12. Seyed Mohammad Ehsan Azimi & Seyed Javad Sadatinejad & Arash Malekian & Mohammad Hossein Jahangir, 2023. "Application of artificial intelligence hybrid models for meteorological drought prediction," 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. 116(2), pages 2565-2589, March.
    13. Chen-Feng Yeh & Jinge Wang & Hsin-Fu Yeh & Cheng-Haw Lee, 2015. "SDI and Markov Chains for Regional Drought Characteristics," Sustainability, MDPI, vol. 7(8), pages 1-20, August.
    14. 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.
    15. Furat A. M. Al-Faraj & Dimitris Tigkas, 2016. "Impacts of Multi-year Droughts and Upstream Human-Induced Activities on the Development of a Semi-arid Transboundary Basin," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(14), pages 5131-5143, November.
    16. Farhang Rahmani & Mohammad Hadi Fattahi, 2021. "A multifractal cross-correlation investigation into sensitivity and dependence of meteorological and hydrological droughts on precipitation and temperature," 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. 109(3), pages 2197-2219, December.
    17. 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.
    18. Pragya Pradhan & Trang Thi Huyen Pham & Sangam Shrestha & Ho Huu Loc & Edward Park, 2022. "Projecting the impact of human activities and climate change on water resources in the transboundary Sre Pok River Basin," Climatic Change, Springer, vol. 172(3), pages 1-23, June.
    19. Reza Zamani & Hossein Tabari & Patrick Willems, 2015. "Extreme streamflow drought in the Karkheh river basin (Iran): probabilistic and regional analyses," 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. 76(1), pages 327-346, March.
    20. Anas Mahmood Al-Juboori, 2023. "Prediction of Hydrological Drought in Semi-arid Regions Using a Novel Hybrid Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(9), pages 3657-3669, July.

    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:2:p:1109-:d:1027754. 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.