Skip to main content
SpringerLink
Log in

Using the Particle Swarm Optimization (PSO) Algorithm for Baseflow Separation and Determining the Trends for the Yesilirmak River (North Turkey)

  • Published:
Russian Meteorology and Hydrology Aims and scope Submit manuscript

Abstract

Estimation of baseflow is a complex hydrographic task. Baseflow techniques and coefficients vary from basin to basin, stream to stream, and year to year. In this study, meta-heuristic optimization is used to automatically identify baseflow. The Particle Swarm Optimization (PSO), a meta-heuristic optimization approach, is chosen. The constraint and cost functions were determined using the PSO algorithm, Lyne and Hollick techniques, and a computer application. Over the period 1980–2015, the data were collected at the Kale station in the Yesilirmak River basin to validate the study model. The results show that the hydrographs and baseflow dividing line were separated effectively. It has also been revealed that the PSO has a high speed as well as a high level of precision. In the research, in addition to the baseflow separation, the hydrograph, baseflow, and ratio of the baseflow to the streamflow at the station No. 1402 were assessed using the Mann–Kendall test and Innovative Trend Test (ITA), and as a result, their trends have been found. By the use of both of these methods, it has been shown that all parameters have an unfavorable trend. In addition, the research came to some other significant conclusions, such as the fact that the baseflow declines in tandem with the flow values and that the baseflow rates are low in years with high peak values of the hydrograph.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

REFERENCES

  1. E. Agbo, C. Ekpo, and C. Edet, "Analysis of the Effects of Meteorological Parameters on Radio Refractivity, Equivalent Potential Temperature and Field Strength via Mann–Kendall Test," Theor. and Appl. Climatol., No. 3, 143 (2021).

    Article  Google Scholar 

  2. M. Alam, M. Islam, Z. Muyen, M. Mamun, and S. Islam, "Water Quality Parameters along Rivers," Int. J. Environ. Sci. and Technol., No. 1, 4 (2007).

    Article  CAS  Google Scholar 

  3. E. Albek and S. Goncu, "Investigation of Changes in Suspended Solids in Turkish Rivers over the Years," Anadolu University Journal of Science and Technology: A-Applied Sciences and Engineering, No. 2, 6 (2005) [in Turkish].

  4. J. Arnold and P. Allen, "Automated Methods for Estimating Baseflow and Ground Water Recharge from Streamflow Records 1," J. Amer. Water Resour. Association, No. 2, 35 (1999).

    Article  Google Scholar 

  5. M. S. Arumugam, "New and Improved Versions of Genetic and PSO Algorithms for a Class of Hybrid Systems and Steel Annealing Process," Doctoral Dissertation (Multimedia University, 2008).

  6. R. Bakis and S. Goncu, "Completion of Missing Data in Rivers Flow Measurement: Case Study of Zab River Basin," Anadolu University Journal of Science and Technology: A-Applied Sciences and Engineering, No. 1, 16 (2015).

    Google Scholar 

  7. S. Bastola, Y. Seong, D. Lee, I. Youn, S. Oh, Y. Jung, and D. Jang, "Contribution of Baseflow to River Streamflow: Study on Nepal’s Bagmati and Koshi Basins," KSCE J. Civil Eng., No. 11, 22 (2018).

    Article  Google Scholar 

  8. M. Birsan, L. Zaharia, V. Chendes, and E. Branescu, "Seasonal Trends in Romanian Streamflow," Hydrol. Processes, No. 15, 28 (2014).

    Article  Google Scholar 

  9. D. Burn and N. Hesch, "Trends in Evaporation for the Canadian Prairies," J. Hydrol., No. 1–2, 336 (2007).

    Article  Google Scholar 

  10. T. Chapman, "Comment on "Evaluation of Automated Techniques for Base Flow and Recession Analyses by R. J. Nathan and T. A. McMahon," Water Resour. Res., No. 7, 27 (1991).

    Article  Google Scholar 

  11. H. Chen and R. Teegavarapu, "Comparative Analysis of Four Baseflow Separation Methods in the South Atlantic-Gulf Region of the US," Water, No. 1, 12 (2020).

  12. H. Chen and R. Teegavarapu, "Spatial and Temporal Variabilities in Baseflow Characteristics across the Continental USA," Theor. and Appl. Climatol., No. 3, 143 (2021).

    Article  Google Scholar 

  13. M. Dorigo, V. Maniezzo, and A. Colorni, Positive Feedback as a Search Strategy (1991).

  14. K. Eckhardt, "A Comparison of Baseflow Indices, Which Were Calculated with Seven Different Baseflow Separation Methods," J. Hydrol., No. 1–2, 352 (2008).

    Article  Google Scholar 

  15. M. Ellis, B. Westfall, and M. Ellis, Determination of Water Quality, Vol. 9 (US Government Printing Office, 1946).

    Google Scholar 

  16. E. Seris, "Sparation of Base Flow in Karst Region Streams," Geol. Eng. J., No. 1, 41 (2017) [in Turkish].

  17. S. Ghoshal, "Optimizations of PID Gains by Particle Swarm Optimizations in Fuzzy Based Automatic Generation Control," Electric Power Systems Res., No. 3, 72 (2004).

    Article  Google Scholar 

  18. M. Gocic and S. Trajkovic, "Analysis of Changes in Meteorological Variables Using Mann–Kendall and Sen’s Slope Estimator Statistical Tests in Serbia," Global and Planetary Change, 100 (2013).

    Article  Google Scholar 

  19. Y. Guclu, "Improved Visualization for Trend Analysis by Comparing with Classical Mann–Kendall Test and ITA," J. Hydrol., 124674, 584 (2020).

    Article  Google Scholar 

  20. Y. Guclu, "Multiple Sen-innovative Trend Analyses and Partial Mann–Kendall Test," J. Hydrol., 566 (2018).

    Article  Google Scholar 

  21. A. Gustard, A. Bullock, and J. Dixon, Low Flow Estimation in the United Kingdom (Institute of Hydrology, 1992).

    Google Scholar 

  22. A. Gustard, S. Curry, D. Marshall, A. Sekulin, C. Webb, H. Dracos, and S. Higgs, Low Flow Studies (Institute of Hydrology, Wallingford, 1980).

    Google Scholar 

  23. B. Hagedorn and C. Meadows, "Trend Analyses of Baseflow and BFI for Undisturbed Watersheds in Michigan—Constraints from Multi-Objective Optimization," Water, No. 4, 13 (2021).

    Article  CAS  Google Scholar 

  24. R. Hirsch, J. Slack, and R. Smith, "Techniques of Trend Analysis for Monthly Water Quality Data," Water Resour. Res., No. 1, 18 (1982).

    Article  Google Scholar 

  25. D. A. Hirst and R. ob Morris, "Water Quality of Scottish Rivers: Spatial and Temporal Trends," Sci. Total Environ., No. 1–3, 265 (2001).

    Article  Google Scholar 

  26. C. Hu, D. Zhao, and S. Jian, "Baseflow Estimation in Typical Catchments in the Yellow River Basin, China," Water Supply, No. 2, 21 (2021).

    Article  Google Scholar 

  27. N. Jahedi and M. Ghorbani, "Trend Analysis of Precipitation and River Flow in the Qara-Su River Basin," Geography and Planning, No. 52, 19 (2015).

    Google Scholar 

  28. S. Jain and V. Kumar, "Trend Analysis of Rainfall and Temperature Data for India," Current Science (2012).

  29. C. Juang and C. Lu, "Load-frequency Control by Hybrid Evolutionary Fuzzy PI Controller," IEE Proceedings-generation, Transmission and Distribution, No. 2, 153 (2006).

    Article  Google Scholar 

  30. E. Kahya and S. Kalayci, "Trend Analysis of Streamflow in Turkey," J. Hydrol., No. 1–4, 289 (2004).

    Article  Google Scholar 

  31. J. Kampata, B. Parida, and D. Moalafhi, "Trend Analysis of Rainfall in the Headstreams of the Zambezi River Basin in Zambia," Physics and Chemistry of the Earth, Parts A/B/C, No. 8–13, 33 (2008).

    Article  Google Scholar 

  32. D. Karaboga, "An Idea Based on Honey Bee Swarm for Numerical Optimization," Technical report-tr06, Erciyes University, Engineering Faculty, Computer Engineering Department, 200 (2005) [in Turkish].

  33. M. Kendall, Appendix: Mann–Kendall Trend Tests (1975).

  34. J. Kennedy and R. Eberhart, "Particle Swarm Optimization," in Proceedings of ICNN’95-International Conference on Neural Networks, Vol. 4 (1995).

  35. K. Kille, "Das Verfahren MoMNQ, ein Beitrag zur Berechnung der Mittleren langjahrigen Grundwasserneubildung mit Hilfe der Monatlichen Niedrigwasserabflüsse," Zeitschrift der Deutschen Geologischen Gesellschaft (1970).

  36. M. Kissel and B. Schmalz, "Comparison of Baseflow Separation Methods in the German Low Mountain Range," Water, No. 6, 12 (2020).

    Article  Google Scholar 

  37. A. Ladson, R. Brown, B. Neal, and R. Nathan, "A Standard Approach to Baseflow Separation Using the Lyne and Hollick Filter," Austral. J. Water Resour., No. 1, 17 (2013).

    Article  Google Scholar 

  38. D. Lee, J. Lee, J. Kim, K. Lim, B. Engel, J. Yang, and Y. Jung, "Effects of Slope Magnitude and Length on SWAT Baseflow Estimation," J. Irrigation and Drainage Eng., No. 1, 145 (2019).

    Article  Google Scholar 

  39. K. Lim, B. Engel, Z. Tang, J. Choi, K. Kim, S. Muthukrishnan, and D. Tripathy, "Automated Web GIS Based Hydrograph Analysis Tool, WHAT 1," J. Amer. Water. Resour Association, No. 6, 41 (2005).

    Article  Google Scholar 

  40. H. Lins and J. Slack, "Streamflow Trends in the United States," Geophys. Res. Lett., No. 2, 26 (1999).

    Article  Google Scholar 

  41. V. Lyne and M. Hollick, "Stochastic Time-variable Rainfall-runoff Modelling," in Institute of Engineers Australia National Conference (1979).

  42. J. Mallick, S. Talukdar, M. Alsubih, R. Salam, M. Ahmed, N. Kahla, and M. Shamimuzzaman, "Analysing the Trend of Rainfall in Asir Region of Saudi Arabia Using the Family of Mann–Kendall Tests, Innovative Trend Analysis, and Detrended Fluctuation Analysis," Theor. and Appl. Climatol., No. 1, 143 (2021).

    Article  Google Scholar 

  43. H. Mann, "Nonparametric Tests against Trend," Econometrica: J. Econometric Soc. (1945).

  44. A. McLeod, K. Hipel, and B. Bodo, "Trend Analysis Methodology for Water Quality Time Series," Environmetrics, No. 2, 2 (1991).

    Article  Google Scholar 

  45. S. Meshram, E. Kahya, C. Meshram, M. Ghorbani, B. Ambade, and R. Mirabbasi, "Long-term Temperature Trend Analysis Associated with Agriculture Crops," Theor. and Appl. Climatol., No. 3, 140 (2020).

    Article  Google Scholar 

  46. S. Meyer, "Analysis of Base Flow Trends in Urban Streams, Northeastern Illinois, USA," Hydrogeo J., No. 5–6, 13 (2005).

    Article  Google Scholar 

  47. A. Mondal, S. Kundu, and A. Mukhopadhyay, "Rainfall Trend Analysis by Mann–Kendall Test: A Case Study of North-eastern Part of Cuttack District, Orissa," Int. J. Geol., Earth and Environ. Sci., No. 1, 2 (2012).

    Google Scholar 

  48. K. Murat, "Determination of the Variation of Spatial Precipitation Distribution in Yesilirmak Basin by Deterministic and Stochastic Methods," Geosciences, No. 3, 39 (2018) [in Turkish].

  49. V. Nourani, A. Mehr, and N. Azad, "Trend Analysis of Hydroclimatological Variables in Urmia Lake Basin Using Hybrid Wavelet Mann–Kendall and Sen Tests," Environ. Earth Sci., No. 5, 77 (2018).

    Article  Google Scholar 

  50. K. Parsopoulos and M. Vrahatis, "Particle Swarm Optimization and Intelligence," Advances and Applications (2010).

  51. T. Partal and E. Kahya, "Trend Analysis in Turkish Precipitation Data," Hydrol. Processes: An Int. J., No. 9, 20 (2006).

    Article  Google Scholar 

  52. W. Pettyjohn and R. Henning, Reliminary Estimate of Regional Effective Ground-water Recharge Rates in Ohio (Ohio State University, Water Resources Center, 1979).

    Google Scholar 

  53. A. Piggott, S. Moin, and C. Southam, "A Revised Approach to the UKIH Method for the Calculation of Baseflow," Hydrol. Sci. J., No. 5, 50 (2005).

  54. D. A. Post and A. J. Jakeman, "Relationships between Catchment Attributes and Hydrological Response Characteristics in Small Australian Mountain Ash Catchments," Hydrol. Processes, No. 6, 10 (1996).

    Article  Google Scholar 

  55. A. Ratnawera, S. K. Halgamuge, and H. C. Watson, "Self-Organizing Hierarchical Particle Swarm Optimizer with Time-varying Acceleration Coefficients," IEEE Transactions on Evolutionary Computation, No. 3, 8 (2004).

    Article  Google Scholar 

  56. W. Reeves, "Particle Systems—a Technique for Modeling a Class of Fuzzy Objects," ACM Transactions on Graphics (TOG), No. 2, 2 (1983).

  57. C. Reynolds, "Flocks, Herds and Schools: A Distributed Behavioral Model," in Proceedings of the 14th Annual Conference on Computer Graphics and Interactive Techniques (1987).

  58. A. Rutledge, Computer Programs for Describing the Recession of Ground-water Discharge and for Estimating Mean Ground-water Recharge and Discharge from Streamflow Records: Update, No. 98 (US Department of the Interior, US Geological Survey, 1998).

  59. K. Saplioglu, "A New Methodology for Trend Analysis: A Case Study in Burdur and Isparta, Turkey," Fresenius Environ. Bull., 24 (2015).

    CAS  Google Scholar 

  60. K. Saplioglu and M. Cimen, "A New Method for Base Flow Separation," Eng. Sci., No. 4, 5 (2010) [in Turkish].

  61. K. Saplioglu and Y. Guclu, "Combination of Wilcoxon Test and Scatter Diagram for Trend Analysis of Hydrological Data," J. Hydrol., 612 (2022).

    Article  Google Scholar 

  62. K. Saplioglu, M. Kilit, and B. Yavuz, "Trend Analysis of Streams in the Western Mediterranean Basin of Turkey," Fresenius Environ. Bull., No. 1, 23 (2014).

    CAS  Google Scholar 

  63. K. Saplioglu, T. Ozturk, and R. Acar, "Optimization of Open Channels Using Particle Swarm Optimization Algorithm," J. Intelligent and Fuzzy Systems (2020).

    Article  Google Scholar 

  64. S. Sawaske and D. Freyberg, "An Analysis of Trends in Baseflow Recession and Low-flows in Rain-dominated Coastal Streams of the Pacific Coast," J. Hydrol., 519 (2014).

    Article  Google Scholar 

  65. Z. Sen, "Innovative Trend Analysis Methodology," J. Hydrol. Eng., No. 9, 17 (2012).

    Article  Google Scholar 

  66. Z. Sen, "Trend Identification Simulation and Application," J. Hydrol. Eng., No. 3, 19 (2014).

    Article  Google Scholar 

  67. S. Senocak and S. Tasci, "Determination of Coruh Basin Baseflow by British Institute of Hydrology Rounded Minimums Method," Erzincan University Institute of Science and Technology J., No. 1, 13 (2020) [in Turkish].

  68. A. Serrano, V. Mateos, and J. Garcia, "Trend Analysis of Monthly Precipitation over the Iberian Peninsula for the Period 1921–1995," Physics and Chemistry of the Earth, Part B: Hydrology, Oceans and Atmosphere, No. 1–2, 24 (1999).

    Article  Google Scholar 

  69. V. Smakhtin, "Low Flow Hydrology: A Review," J. Hydrol., No. 3–4, 240 (2001).

    Article  Google Scholar 

  70. J. Stafford, G. Wendler, and J. Curtis, "Temperature and Precipitation of Alaska: 50 Year Trend Analysis," Theor. and Appl. Climatol., No. 1, 67 (2000).

    Article  Google Scholar 

  71. F. S. Swed and C. Eisenhart, "Tables for Testing Randomness of Grouping in a Sequence of Alternatives," Ann. Math. Stat., No. 1, 14 (1943).

    Article  Google Scholar 

  72. H. Tabari and S. Marofi, "Changes of Pan Evaporation in the West of Iran," Water Resour. Manag., No. 1, 25 (2011).

    Article  Google Scholar 

  73. S. Uzundurukan and K. Saplioglu, "Investigation of Height-cost Relationship in Cantilever Retaining Walls with Particle Swarm Algorithm," Duzce University J. Science and Technol., No. 4, 8 (2020) [in Turkish].

  74. K. Wahl and T. Wahl, "Determining the Flow of Comal Springs at New Braunfels, Texas," Proceedings of Texas Water, No. 6, 95 (1995).

    Google Scholar 

  75. W. Wang, P. Van Gelder, and J. Vrijiling, "Trend and Stationarity Analysis for Streamflow Processes of Rivers in Western Europe in the 20th Century," in IWA International Conference on Water Economics, Statistics, and Finance, Rethymno, Greece (2005).

  76. R. Woods, J. Hendrikx, R. Henderson, and A. Tait, "Estimating Mean Flow of New Zealand Rivers," J. Hydrol. (New Zealand), No. 2, 45 (2006).

    Google Scholar 

  77. J. Xie, X. Liu, K. Wang, T. Yang, K. Liang, and C. Liu, "Evaluation of Typical Methods for Baseflow Separation in the Contiguous United States," J. Hydrol., 583 (2020).

    Article  Google Scholar 

  78. Y. Yu, S. Zou, and D. Whittemore, "Non-parametric Trend Analysis of Water Quality Data of Rivers in Kansas," J. Hydrol., No. 1, 150 (1993).

    Article  CAS  Google Scholar 

  79. I. Yuksel and A. Ceribasi, Estimation of Solid Flow Carried by the Sakarya River with Trend Analysis Method (1996) [in Turkish].

  80. J. R. Zhang, J. Zhang, T. M. Lok, and M. R. Lyu, "A Hybrid Particle Swarm Optimization–Back-propagation Algorithm for Feedforward Neural Network Training," Appl. Mathematics and Computation, 185 (2007).

    Article  Google Scholar 

  81. J. Zhang, Y. Zhang, J. Song, and L. Cheng, "Evaluating Relative Merits of Four Baseflow Separation Methods in Eastern Australia," J. Hydrol., 549 (2017).

    Article  Google Scholar 

  82. F. Zhao, Z. Ren, D. Yu, and Y. Yang, "Application of an Improved Particle Swarm Optimization Algorithm for Neural Network Training," in Proceedings of the IEEE International Conference on Neural Networks and Brain, Vol. 3 (Beijing, China, 2005).

Download references

Author information

Authors and Affiliations

  1. Department of Civil Engineering, Munzur University, Tunceli, Turkey

    R. Acar

  2. Department of Civil Engineering, Suleyman Demirel University, Isparta, Turkey

    K. Saplioglu

Authors
  1. R. Acar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. K. Saplioglu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to R. Acar.

Additional information

Translated from Meteorologiya i Gidrologiya, 2024, No. 1, pp. 58-71. https://doi.org/10.52002/0130-2906-2024-1-58-71.

Publisher’s Note. Allerton Press remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Acar, R., Saplioglu, K. Using the Particle Swarm Optimization (PSO) Algorithm for Baseflow Separation and Determining the Trends for the Yesilirmak River (North Turkey). Russ. Meteorol. Hydrol. 49, 40–51 (2024). https://doi.org/10.3103/S1068373924010060

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.3103/S1068373924010060

Keywords

Search

Navigation