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Establishing regional intensity-duration-frequency (IDF) relationships by using the L-moment approach and genetically based techniques for the Euphrates-Tigris basin

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Abstract

Regional intensity-duration-frequency (IDF) relationships for the Euphrates-Tigris basin were established using genetic programming (GP) and multi-gene genetic programming (MGGP). The regional homogeneity of the study area was provided with two sub-regions (SRI and SRII) using the L-moment method. Estimated intensity values for various recurrence periods from selected regional distributions, new IDF relationships were established through GP and MGGP approaches, and the successful results were compared with the results obtained from the distributions. In addition, the parameters of 11 empirical equations commonly used in the literature for rainfall intensities were determined according to particle swarm optimization (PSO), artificial bee colony (ABC), genetic algorithm (GA), and flow direction algorithm (FDA) optimization methods. The rainfall intensity results of both the new IDF equations established with GP and MGGP techniques and the highest-performing empirical equations showed that the closest findings to the data set from regional distributions were obtained with MGGP for SRI and GP for SRII.

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References

  • Adeloye AJ, Montaseri M (2002) Preliminary streamflow data analyses prior to water resources planning study. Hydrol Sci J 47:679–692. https://doi.org/10.1080/02626660209492973

    Article  Google Scholar 

  • Agbazo M, Koton’Gobi G, Kounouhewa B, Alamou E, Afouda A (2016) Estimation of IDF curves of extreme rainfall by simple scaling in Northern Oueme Valley, Benin Republic (West Africa). Earth Sci Res J 20:1–7. https://doi.org/10.15446/esrj.v20n1.49405

    Article  Google Scholar 

  • Akay B (2009) Performance analysis of artificial bee colony algorithm on numerical optimization problem. Ph.D. Thesis, Erciyes University, Graduate School of Natural and Applied Science

  • Akbaş Z (2015) Türkiye’nin Fırat ve Dicle sınıraşan sularından kaynaklanan güvenlik sorunu ve çatışma riski (Turkish). J Soc Sci Turkic World 72:93–116

    Google Scholar 

  • Altınbilek D (2004) Development and management of the Euprates-Tigris basin. Int J Water Resour Dev 20:15–33. https://doi.org/10.1080/07900620310001635584

    Article  Google Scholar 

  • Al-Wagdany AS (2020) Intensity-duration-frequency curve derivation from different rain gauge records. J King Saud Univ Sci 32:3421–3431. https://doi.org/10.1016/j.jksus.2020.09.028

    Article  Google Scholar 

  • Amjadi M (2015) Statistic and probabilistic variations and rainfall predictions of TRNC. Master Thesis, Eastern Mediterranean University, Gazimagusa North Cyprus

  • Anli AS (2009) Regıonal frequency analysis of rainfall data in Ankara Provınce vıa L-moment methods. Ph.D. Thesis, Ankara University, Graduate School of Natural and Applied Sciences

  • Asıkoglu ÖL, Benzeden E (2007) Stable frequency distribution models for the annual maximum rainfalls of standard durations. Sci Eng J Fırat Univ 19:543–551

    Google Scholar 

  • Basakın EE, Ekmekcioglu O, Ozger M, Citakoglu H (2021) Determination of intensity-duration-frequency relation by particle swarm optimization and genetic programming. In: II. International Applied Statistics Conference (UYIK-2021). Tokat, Turkey, pp 1–8

  • Belay GW, Azeze M, Melesse AM (2019) Reservoir operation analysis for Ribb reservoir in the Blue Nile basin (Chapter 16), 191–211. In: Melesse AM, Abtew W, Senay G (eds) Extreme hydrology and climate variability: monitoring, modelling, adaptation and mitigation

  • Bell FC (1969) Generalized rainfall-duration-frequency relationships. J Hydraul Div ASCE 95:311–327. https://doi.org/10.1061/JYCEAJ.0001942

    Article  Google Scholar 

  • Blackwell T, Kennedy J, Poli R (2007) Particle swarm optimization. Swarm Intell 1:33–57. https://doi.org/10.1007/s11721-007-0002-0

    Article  Google Scholar 

  • Bratton D, Kennedy J, (2007) Defining a standard for particle swarm optimization. IEEE Swarm Intelligence Symposium, Honolulu, HI, USA, pp 120–127. https://doi.org/10.1109/SIS.2007.368035

  • Chang KB, Lai SH, Faridah O (2013) RainIDF: automated derivation of rainfall intensity–duration–frequency relationship from annual maxima and partial duration series. J Hydroinformatics 15:1224–1233. https://doi.org/10.2166/hydro.2013.192

    Article  Google Scholar 

  • Chen CL (1983) Rainfall intensity-duration-frequency formulas. ASCE J Hydraulic Eng 109:1603–1621. https://doi.org/10.1061/(ASCE)0733-9429(1983)109:12(1603)

    Article  Google Scholar 

  • Citakoglu H, Demir V (2023) Developing numerical equality to regional intensity–duration–frequency curves using evolutionary algorithms and multi-gene genetic programming. Acta Geophys 71:469–488. https://doi.org/10.1007/s11600-022-00883-8

    Article  Google Scholar 

  • Coles S (2001) An introduction to statistical modeling of extreme values. Springer Series in Statistics. London, Springer-Verlag, p 208. https://doi.org/10.1007/978-1-4471-3675-0

    Book  Google Scholar 

  • Cunnane C (1989) Statistical distributions for flood frequency analysis. WMO Report No. 718. World Meteorological Organization, Geneva

    Google Scholar 

  • Dalrymple T (1960) Flood frequency methods. U. S. Geological Survey. Water Supply Paper 1543A:11–51

    Google Scholar 

  • Degirmenci S (2007) Turkey’s transboundary waters and water problem in Middle East within the context of Firat, Dicle, Asi Rivers. M.Sc. Thesis, Pamukkale University Graduate School of Social Sciences

  • Demir AF, Pamukçu ÖK (1996) Fırat Dicle Havzasında Türkiye’nin Su Politikas. Değişen Dünya ve Türkiye Der. Faruk Sönmezoğlu. Bağlam Yayınları, İstanbul, pp 267–286

    Google Scholar 

  • Dupont BS, Allen DL (2000) Revision of the rainfall intensity duration curves for the commonwealth of Kentucky. Kentucky Transportation Center, College of Engineering, University of Kentucky, Research Report: KTC-00–18

  • Elsebaie IH (2012) Developing rainfall intensity–duration–frequency relationship for two regions in Saudi Arabia. J King Saud Univ Eng Sci 24:131–140. https://doi.org/10.1016/j.jksues.2011.06.001

    Article  Google Scholar 

  • Fadhel S, Rico-Ramirez MA, Han D (2017) Uncertainty of intensity–duration–frequency (IDF) curves due to varied climate baseline periods. J Hydrol 547:600–612. https://doi.org/10.1016/j.jhydrol.2017.02.013

    Article  Google Scholar 

  • Farzin S, Anaraki MV (2021) Modeling and predicting suspended sediment load under climate change conditions: a new hybridization strategy. J Water Clim Chang 12:2422–2443. https://doi.org/10.2166/wcc.2021.317

    Article  Google Scholar 

  • Farzin S, Anaraki MV, Naeimi M, Zandifar S (2022) Prediction of groundwater table and drought analysis; a new hybridization strategy based on bi-directional long short-term model and the Harris hawk optimization algorithm. J Water Clim Chang 13:2233–2254. https://doi.org/10.2166/wcc.2022.066

    Article  Google Scholar 

  • Fernando DAK, Jayawardena AW (1994) Generation and forecasting of monsoon rainfall data. 20th WEDC Conference on Affordable Water Supply and Sanitation, Colombo, pp. 310–313

  • Gado TA, Salama AM, Zeidan BA (2021) Selection of the best probability models for daily annual maximum rainfalls in Egypt. Theoret Appl Climatol. https://doi.org/10.1007/s00704-021-03594-0

    Article  Google Scholar 

  • Gandomi AH, Alavi AH (2012) A new multi-gene genetic programming approach to nonlinear system modeling—part I:materials and structural engineering problems. Neural Comput Appl 21:171–187

    Article  Google Scholar 

  • Gebru TA (2020) Rainfall intensity-duration-frequency relations under changing climate for selected stations in the Tigray region Ethiopia. J Hydrol Eng 25:05020041. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001999

    Article  Google Scholar 

  • Gocic M, Velimirovic L, Stankovic M, Trajkovic S (2021) Regional precipitation-frequency analysis in Serbia based on methods of L-moment. Pure Appl Geophys. https://doi.org/10.1007/s00024-021-02688-0

    Article  Google Scholar 

  • Goldberg DE (1989) Genetic algorithms in search, optimization and machine learning, 1st edn. Addison-Wesley Longman Publishing Co., Inc, USA

    Google Scholar 

  • Gorkemli B, Citakoglu H, Haktanir T, Karaboga D (2022) A new method based on artificial bee colony programming for the regional standardized intensity–duration-frequency relationship. Arab J Geosci. https://doi.org/10.1007/s12517-021-09377-1

    Article  Google Scholar 

  • Gubareva TS, Gartsman BI (2010) Estimating distribution parameters of extreme hydrometeorological characteristics by L-moment method. Water Resour 37:437–445. https://doi.org/10.1134/S0097807810040020

    Article  Google Scholar 

  • Haddad K (2021) Selection of the best fit probability distributions for temperature data and the use of L-moment ratio diagram method: a case study for NSW in Australia. Theoret Appl Climatol 143:1261–1284. https://doi.org/10.1007/s00704-020-03455-2

    Article  Google Scholar 

  • Hassan MU, Noreen Z, Ahmed R (2021) Regional frequency analysis of annual daily rainfall maxima in Skåne, Sweden. Int J Climatol 41:4307–4320. https://doi.org/10.1002/joc.7074

    Article  Google Scholar 

  • Hinchliffe MP, Willis MJ, Hiden H, Tham MT, McKay B, Barton GW (1996) Modelling chemical process systems using a multi-gene genetic programming algorithm. In Genetic Programming: Proceedings of the First Annual Conference, pp 56–65

  • Hosking JRM (1990) L-moments: analyzing and estimation of distributions using linear combinations of order statistics. J R Stat Soc B 52:105–124. https://doi.org/10.1111/j.2517-6161.1990.tb01775.x

    Article  Google Scholar 

  • Hosking JRM, Wallis JR (1993) Some statistics useful in regional frequency analysis. Water Resour Res 29:271–281. https://doi.org/10.1029/92WR01980

    Article  Google Scholar 

  • Hosking JRM, Wallis JR (1997) Regional frequency analysis: an approach based on L-moments. Cambridge University Press, Cambridge

    Book  Google Scholar 

  • IPCC (2012) Managing the risks of extreme events and disasters to advance climate change adaptation. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change. Cambridge and New York: Cambridge University Press p 582 

  • IPCC (2007) IPCC Climate Change 2007: The Physical Science Basis (eds Solomon, S. et al.) Cambridge Univ. Press

  • Jain NK, Nangia U, Jain J (2018) A review of particle swarm optimization. J Instit Eng (India) Ser B 99:407–411

    Article  Google Scholar 

  • Karaboga D, Gorkemli B, Ozturk C, Karaboga N (2014) A comprehensive survey: artificial bee colony (ABC) algorithm and applications. Artif Intel Rev 42:21–57. https://doi.org/10.1007/s10462-012-9328-0

    Article  Google Scholar 

  • Karaboga D (2005) An idea based on honey bee swarm for numerical optimizasyon technical report-TR06, Erciyes Üniversitey, Engineering Faculty, Computer Engineering Department

  • Karahan H (2012) Determining rainfall-intensity-duration-frequency relationship using particle swarm optimization. KSCE J Civ Eng 16:667–675. https://doi.org/10.1007/s12205-012-1076-9

    Article  Google Scholar 

  • Karahan H, Ozkan E (2012) Best fitting distributions for the standard duration annual maximum precipitations in the Aegean Region. Pamukkale Univ J Eng Sci 19:152–157. https://doi.org/10.5505/pajes.2013.29392

    Article  Google Scholar 

  • Karahan H, Ceylan H, Tamer Ayvaz M (2007) Predicting rainfall intensity using a genetic algorithm approach. Hydrol Process 21:470–475. https://doi.org/10.1002/hyp.6245

    Article  Google Scholar 

  • Karahan H, Ayvaz MT, Gürarslan G (2008) Determination of intensity-duration-frequency relationship by genetic algorithm: case study of GAP. Techn J 19:4393–4407 (In Turkish)

    Google Scholar 

  • Karami H, Anaraki MV, Farzin S, Mirjalili S (2021) Flow direction algorithm (FDA): a novel optimization approach for solving optimization problems. Comput Ind Eng 156:107224. https://doi.org/10.1016/j.cie.2021.107224

    Article  Google Scholar 

  • Kaygusuz K (1999) Energy and water potential of the southeastern Anatolia project (GAP). Energy Sources 21:913–922. https://doi.org/10.1080/00908319950014281

    Article  Google Scholar 

  • Kennedy J, Eberhart RC (1995) Particle swarm optimization. Proc IEEE Int Conf Neural Netw 4:1942–1948. https://doi.org/10.1109/ICNN.1995.488968

    Article  Google Scholar 

  • Khan MSR, Hussain Z, Ahmad I (2020) Regıonal flood frequency analysis, using L-moments, artificial neural networks and Ols regression, of various sites of Khyber-Pakhtunkhwa, Pakıstan. Appl Ecol Envıron Res 19:471–489. https://doi.org/10.15666/aeer/1901_471489

    Article  Google Scholar 

  • Koutsoyiannis D, Kozonis D, Manetas A (1998) A mathematical framework for studying rainfall intensity-duration-frequency relationships. J Hydrol 206:118–135. https://doi.org/10.1016/S0022-1694(98)00097-3

    Article  Google Scholar 

  • Koza JR (1992) Genetic programming: on the programming of computers by means of natural selection. MIT Press, Cambridge

    Google Scholar 

  • Labat D, Godderis Y, Probst JL, Guyot JL (2004) Evidence for global runoff increase related to climate warming. Adv Water Resour 27(631):642. https://doi.org/10.1016/j.advwatres.2004.02.020

    Article  Google Scholar 

  • Lestari S, King A, Vincent C (2019) Seasonal dependence of rainfall extremes in and around Jakarta. Indones Weather Clim Extrem 24:100202. https://doi.org/10.1016/j.wace.2019.100202

    Article  Google Scholar 

  • Modarres R, Sarhadi A (2010) Statistically-based regionalization of rainfall climates of Iran. Global Planet Change. https://doi.org/10.1016/j.gloplacha.2010.10.009

    Article  Google Scholar 

  • Müftüoğlu F (1997) Ortadoğu Su Meseleleri ve Türkiye. Marifet Yayınları, İstanbul (In Turkish)

    Google Scholar 

  • Nachar N (2008) The Mann Whitney U: a test for assessing whether two independent samples come from the same distribution. Quant Meth Psych 4:13–20

    Google Scholar 

  • Nain M, Hooda BK (2021) Regional frequency analysis of maximum monthly rainfall in Haryana State of India using L-moments. J Reliab Stat Stud 14:33–56. https://doi.org/10.13052/jrss0974-8024.1413

    Article  Google Scholar 

  • Nhat L, Tachikawa J, Takara K (2006) Establishment of intensity-duration-frequency curves for precipitation in the monsoon area of Vietnam. Annuals of Disas Prev Res Inst, Kyoto Univ., No. 49 B

  • Okonkwo GI, Mbajiorgu CC (2010) Rainfall intensity-duration-frequency analyses for South Eastern Nigeria. Agric Eng Int CIGR Ej. Manuscript 1304. Vol. XII

  • Ouali D, Cannon AJ (2018) Estimation of rainfall intensity–duration–frequency curves at ungauged locations using quantile regression methods. Stoch Environ Res Risk Assess 32:2821–2836. https://doi.org/10.1007/s00477-018-1564-7

    Article  Google Scholar 

  • Ozis U, Ozdemir Y (2008) Euphrates-Tigris rivers basin and Turkey. (In Turkish) TMMOB 2. Water Policy Congress, IMO Congress and Cultures Center, Ankara, Turkey, pp 443–445

  • Paola FD, Giugni M, Topa ME, Bucchignani E (2014) Intensity-duration-frequency (IDF) rainfall curves, for data series and climate projection in African cities. Springerplus 3:1–18. https://doi.org/10.1186/2193-1801-3-133

    Article  Google Scholar 

  • Park JS, Jung HS, Kim RS, Oh JH (2001) Modelling summer extreme rainfall over the Korean Peninsula using wakeby distribution. Int J Climatol 21:1371–1384. https://doi.org/10.1002/joc.701

    Article  Google Scholar 

  • Raiford JP, Aziz NM, Khan AA, Powell DN (2007) Rainfall depth-duration-frequency relationships for South Carolina, North Carolina, and Georgia. Am J Environ Sci 3:78–84

    Article  Google Scholar 

  • Rao AR, Hamed KH (2000) Flood frequency analysis. CRC Press, Boca Raton

    Google Scholar 

  • Rasel M, Islam M (2015) Generation of rainfall intensity-duration frequency relationship for north-western region in Bangladesh. J Environ Sci, Toxicol Food Technol (IOSR-JESTFT) 9:41–47

  • Riccardo P, William BL, Nicholas FM, Koza JR (2008) A field guide to genetic programming, Lulu Enterprises. UK Ltd. Reprint edition. http://www.gp-field-guide.org.uk

  • Rougé C, Ge Y, Cai X (2013) Detecting gradual and abrupt changes in hydrological records. Adv Water Resour 53:33–44. https://doi.org/10.1016/j.advwatres.2012.09.008

    Article  Google Scholar 

  • Searson DP, Leahy DE, Willis MJ (2010) GPTIPS: an open source genetic programming toolbox for multigene symbolic regression. In: Proceedings of the International MultiConference of Engineers and Computer Scientists (IMECS ’10), March 17-19, Hong Kong, pp 77–80

  • Šimková T (2017) Homogeneity testing for spatially correlated data in multivariate regional frequency analysis. Water Resour Res 53:7012–7028. https://doi.org/10.1002/2016WR020295

    Article  Google Scholar 

  • Yuksek O, Anılan T, Saka F, Örgün E (2022) Rainfall intensity-duration-frequency analysis in Turkey, with the emphasis of Eastern Black Sea basin. Techn J 33:12087–12103. https://doi.org/10.18400/tekderg.727085

    Article  Google Scholar 

  • Yurekli K (2015) Impact of climate variability on precipitation in the upper Euphrates-Tigris rivers basin of Southeast Turkey. Atmos Res 154:25–38. https://doi.org/10.1016/j.atmosres.2014.11.002

    Article  Google Scholar 

  • Yurekli K (2022) Identification of possible risks to hydrological design under non-stationary climate conditions. Nat Hazards. https://doi.org/10.1007/s11069-022-05686-0

    Article  Google Scholar 

  • Yurekli K, Modarres R, Ozturk F (2009) Regional daily maximum rainfall estimation for CekerekWatershed by L-moments. Meteorol Appl 16:435–444. https://doi.org/10.1002/met.139

    Article  Google Scholar 

  • Yurekli K, Erdogan M, Ismail AH, Shareef MA (2021) Hydrochemical characteristics of surface water and its suitability for drinking and irrigation: a case study of the Euphrates river basin, Turkey. Sustain Water Resour Manag 7:1–11. https://doi.org/10.1007/s40899-021-00507-x

    Article  Google Scholar 

  • Zakwan M (2016) Application of optimization technique to estimate IDF parameters. Water Energy Int 59:69–71

    Google Scholar 

  • Zeder J, FisCher EM (2020) Observed extreme precipitation trends and scaling in Central Europe. Weather Clim Extrem 29:100266. https://doi.org/10.1016/j.wace.2020.100266

    Article  Google Scholar 

  • Zhang Q, Xu C, Tao H, Tao J, Chen YD (2009) Climate changes and their impacts on water resources in the arid regions: a case study of the Tarim River basin, China. Stoch Environ Res Risk Assess 24:349–358. https://doi.org/10.1007/s00477-009-0324-0

    Article  Google Scholar 

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Acknowledgements

The authors thank the General Directorate of Meteorology for helping to provide the data used in this study.

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Authors and Affiliations

  1. Department of Civil Engineering, Aksaray University, Aksaray, 68100, Turkey

    Mehmet Ali Hinis

  2. Department of Biosystem Engineering, Gaziosmanpasa University, Tokat, Turkey

    Kadri Yurekli & Muberra Erdogan

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  1. Mehmet Ali Hinis
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Contributions

All authors contributed to the study’s conception and design. Data collection and data curation were performed by Kadri Yurekli. The methodology was performed by Mehmet Ali Hinis, Kadri Yurekli, and Muberra Erdogan. The investigation and writing – review and editing were performed by Mehmet Ali Hinis and Kadri Yurekli. Supervision was performed by Mehmet Ali Hinis and Kadri Yurekli. Analysis was performed by Mehmet Ali Hinis and Muberra Erdogan. All authors have read and agreed to the final version of the manuscript.

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Hinis, M.A., Yurekli, K. & Erdogan, M. Establishing regional intensity-duration-frequency (IDF) relationships by using the L-moment approach and genetically based techniques for the Euphrates-Tigris basin. Theor Appl Climatol 155, 1363–1380 (2024). https://doi.org/10.1007/s00704-023-04695-8

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