Using Meta-Heuristic Optimization Algorithms to Determine Baseflow and Comparing Their Temporal Performance

被引:0
作者
Ramazan Acar [1 ]
Kemal Sapliogu [2 ]
机构
[1] Munzur University,Department of Civil Engineering
[2] Süleyman Demirel University,Department of Civil Engineering
关键词
Baseflow; Genetic algorithm; Grey wolf optimizer; Optimization; Particle swarm optimization; Symbiotic organisms search algorithm;
D O I
10.1007/s40996-024-01558-8
中图分类号
学科分类号
摘要
Accurate and simple determination of baseflow is an extremely important issue. In this study, the baseflow levels of Göksu station number 1805 in the Seyhan basin were determined by calibrating the Lyne and Hollick, Chapman, Chapman and Maxwell methods available in the literature using meta-heuristic optimization methods. The meta-heuristic algorithms used for calibration in the study were run thirty times each. Thus the reliability, the reliability of the algorithms was tested with the standard deviations obtained. The study also measured the temporal performance of the algorithms. In addition, the baseflows of Göksu station were determined and their percentage rates were found separately according to all three methods and intuitive methods, and the results obtained were compared. By examining the results obtained in this section, the average baseflow rate of the basin was also determined. Furthermore, each phase of the study was repeated over a five-year period, with the objective of measuring its sustainability. Consequently, it has been demonstrated that the method can be employed over extended periods.
引用
收藏
页码:1851 / 1869
页数:18
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