Optimizing river flow rate predictions: integrating cognitive approaches and meteorological insights

Veysi Kartal (), Erkan Karakoyun (), Muhammed Ernur Akiner (), Okan Mert Katipoğlu () and Alban Kuriqi ()
Additional contact information
Veysi Kartal: Siirt University
Erkan Karakoyun: Mus Aplarslan University
Muhammed Ernur Akiner: Akdeniz University
Okan Mert Katipoğlu: Erzincan Binali Yıldırım University
Alban Kuriqi: Universidade de Lisboa

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2025, vol. 121, issue 5, No 24, 5729-5756

Abstract: Abstract The models used in this study make it possible to make more accurate predictions about river discharge. These results can influence flood protection strategies, water resource management, and hydropower generation. Due to their ability to capture the underlying temporal relationships in the data, time series forecasts have become increasingly popular in recent years. This study examines the critical processes in river forecasting for the Kizilirmak River basin. We begin with a look at data collection and preparation, followed by an overview of time series forecasting models. Finally, we look at the process of model testing and selection. Seven techniques were used to predict streamflow from meteorological data: Artificial Neural Network (ANN), Firefly-based ANN (FFA-ANN), Random Forest (RF), K-Nearest Neighbors (KNN), Generalized Linear Regression (GLR), Support Vector Machines (SVM), Least Squares Boosted Trees (LSBT). The performance of the models was evaluated using the statistical indicators. The LSBT, RF, and ANN models provided the best results for Kayseri, Kırşehir, and Gemerek stations, respectively. The RF, ANN and GLR models provided second best results for these stations, respectively.

Keywords: Intelligent algorithms; Meteorological data; River flow rate; Time series forecasting (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11069-024-07043-9 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:nathaz:v:121:y:2025:i:5:d:10.1007_s11069-024-07043-9

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11069

DOI: 10.1007/s11069-024-07043-9

Access Statistics for this article

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards is currently edited by Thomas Glade, Tad S. Murty and Vladimír Schenk

More articles in Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards from Springer, International Society for the Prevention and Mitigation of Natural Hazards
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().