Gördes Havzası Akışlarının Modellenmesinde Era5-Land Verilerinin Performans Değerlendirmesi

İklim değişikliğinin akarsu akımları üzerindeki etkilerinin hidrolojik modeller yardımıyla belirlenmesinde küresel atmosferik veri setlerinden sıklıkla faydalanılmaktadır. Sunulan çalışmada, Ege bölgesinde yer alan Gördes Havzası akımlarının hem küresel veri setleri hem de lokal istasyon verileri ile akışlarının modellenmesi ve bu model sonuçları dikkate alınarak performansın değerlendirmesi amaçlanmıştır. Küresel veri seti olarak ECMWF (European Centre for Medium-Range Weather Forecasts) tarafından sunulan 1959-2022 yılları arasında veri sağlayan ERA5 Land veri seti ve hidrolojik model olarak da abcd aylık yağış akış modeli kullanılmıştır. Model performansını değerlendirmek için Nash-Shutcliffe performans fonksiyonu seçilmiş olup optimum model parametrelerin tahmini için Parçacık Sürü Optimizasyonu Algoritması (PSO) kullanılmıştır. Çalışmada elde edilen bulgular ERA5 Land veri setinin Gördes Havzası’nın aylık akımlarının modellenmesinde havzanın hidrolojik özelliklerini başarılı bir şekilde yansıttığı ve bu veri setini kullanmanın modelleme çalışmalarında kolaylaştırıcı olacağı gösterilmiştir.

Anahtar Kelimeler:

Era5-Land, Abcd Modeli, Parçacık Sürü Optimizasyonu, Gördes Havzası

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[1] Uchenna, U. P., Lancia, M., Viaroli, S., Ugbaja, A. N., Galluzzi, M., & Zheng, C. “Groundwater sustainability in African Metropolises: Case study from Calabar, Nigeria”, Journal of Hydrology: Regional Studies, 45, 101314, 2023.
[2] Anteneh, Y., Alamirew, T., Zeleke, G., & Kassawmar, T. “Modeling runoff-sediment influx responses to alternative BMP interventions in the Gojeb watershed, Ethiopia, using the SWAT hydrological model” Environmental Science and Pollution Research, 30(9), 22816-22834, 2023
[3] Singh, V. P., & Frevert, D. K. “ Watershed modeling” In World water & environmental resources congress 2003 (pp. 1-37), 2003.
[4] Fıstıkoğlu, O., “Hidrolojik modeller” Türkiye İnşaat Mühendisliği 15. Teknik Kongre ve Sergisi Bildiriler Kitabı içinde (799-809). Ankara, 1999.
[5] Fistikoglu, O., & Okkan, U. “Statistical downscaling of monthly precipitation using NCEP/NCAR reanalysis data for Tahtali River Basin in Turkey” Journal of Hydrologic Engineering, 16(2), 157-164, 2011.
[6] Girgin, G., & Şen, Ö. L. “GRIDDED PRECIPITATION DATASETS: HOW CONSISTENT ARE THEY FOR TURKEY, A COUNTRY WITH COMPLEX TOPOGRAPHY?” In This 8th Atmospheric Sciences Symposium; ATMOS2017 built upon the series that began at Istanbul Technical University, Department of Meteorological Engineering in 1981. Subsequent meetings have been held in 1991; 2003; 2008; 2011; 2013 and 2015 in Istanbul, Turkey. And it is not just enough to produce scientific data for people but it is also necessary to process the data and share the results of those data as a source for students and a starting point for all., November 2017.
[7] Yang, Y., Li, Q., Song, Z., Sun, W., & Dong, W. “A comparison of global surface temperature variability, extremes and warming trend using reanalysis datasets and CMST‐Interim”, International Journal of Climatology, 42(11), 5609-5628, 2022.
[8] Nacar, S., Kankal, M., & Okkan, U. “Evaluation of the suitability of NCEP/NCAR, ERA-Interim and, ERA5 reanalysis data sets for statistical downscaling in the Eastern Black Sea Basin, Turkey” Meteorology and Atmospheric Physics, 134(2), 39, 2022.
[9] Essou, G. R., Sabarly, F., Lucas-Picher, P., Brissette, F., & Poulin, A. (2016). Can precipitation and temperature from meteorological reanalyses be used for hydrological modeling?. Journal of Hydrometeorology, 17(7), 1929-1950
[10] Tarek, M., Brissette, F. P., & Arsenault, R. (2020). Evaluation of the ERA5 reanalysis as a potential reference dataset for hydrological modelling over North America. Hydrology and Earth System Sciences, 24(5), 2527-2544.
[11] Gomis-Cebolla, J., Rattayova, V., Salazar-Galán, S., & Francés, F. (2023). Evaluation of ERA5 and ERA5-Land reanalysis precipitation datasets over Spain (1951–2020). Atmospheric Research, 284, 106606
[12] Muñoz-Sabater, J., Dutra, E., Agustí-Panareda, A., Albergel, C., Arduini, G., Balsamo, G., ... & Thépaut, J. N. “ERA5-Land: A state-of-the-art global reanalysis dataset for land applications” Earth System Science Data, 13(9), 4349-4383, 2021
[13] Okkan, U., Fistikoglu, O., Ersoy, Z. B., & Noori, A. T. “Investigating adaptive hedging policies for reservoir operation under climate change impacts” Journal of Hydrology, 619, 129286, 2023.
[14] Okkan, U., & Kiymaz, H. (2020). Questioning of empirically derived and locally calibrated potential evapotranspiration equations for a lumped water balance model. Water Supply, 20(3), 1141-1156.
[15] Talebmorad, H., Ahmadnejad, A., Eslamian, S., Ostad-Ali-Askari, K., & Singh, V. P. “Evaluation of uncertainty in evapotranspiration values by FAO56-Penman-Monteith and Hargreaves-Samani methods” International Journal of Hydrology Science and Technology, 10(2), 135-147, 2020.
[16] Çaktu, Y. “Identifying impacts of climate change on water resources using CMIP6 simulations Havran basin case” Master's thesis, Middle East Technical University, 2022.
[17] Sabater, J. M. “ERA5-Land monthly averaged data from 1981 to present” Copernicus Climate Change Service (C3S) Climate Data Store (CDS), 10, 2019.
[18] Thomas, H.A., “Improved methods for national water assessment: Final report” U.S. Geol. Surv. Water Resour. Contract WR15249270, 44.PP, 1981.
[19] Wang, D., & Tang, Y. “A one‐parameter Budyko model for water balance captures emergent behavior in Darwinian hydrologic models”, Geophysical Research Letters, 41(13), 4569-4577, 2014.
[20] OKKAN, U., & KIRDEMİR, U. “BAYES MODEL ORTALAMASI YÖNTEMİYLE KAVRAMSAL YAĞIŞ-AKIŞ MODELİ ÇIKTILARININ DEĞERLENDİRİLMESİ” DSI Technical Bulletin/DSI Teknik Bülteni, (121), 2016.
[21] Bai, P., Liu, X., & Liu, C. “ Improving hydrological simulations by incorporating GRACE data for model calibration” Journal of Hydrology, 557, 291-304, 2018.
[22] Alley, W. M. “Water balance models in one‐month‐ahead streamflow forecasting” Water Resources Research, 21(4), 597-606., 1985.
[23] Al-Lafta, H. S., Al-Tawash, B. S., & Al-Baldawi, B. A. (2013). Applying the “abcd” monthly water balance model for some regions in the United States. Advances in Physics Theories and Applications, 25(1), 36-47
[24] Bai, Q. “Analysis of particle swarm optimization algorithm” Computer and information science, 3(1), 180, 2010.
[25] Eberhart, R., & Kennedy, J. “A new optimizer using particle swarm theory” In MHS'95. Proceedings of the sixth international symposium on micro machine and human science (pp. 39-43). Ieee, October 1995.
[26] Okkan, U., & Kırdemir, U. “Budyko yaklaşımına dayanan bir su bütçesi modeli ve parçacık sürü optimizasyonu algoritması ile kalibrasyonu” Doğal Afetler ve Çevre Dergisi, 2(1), 1-10, 2016.
[27] Tayfur, G. “Modern optimization methods in water resources planning, engineering and management” Water Resources Management, 31, 3205-3233, 2017.
[28] Afshar, A., Shojaei, N., & Sagharjooghifarahani, M. “Multiobjective calibration of reservoir water quality modeling using multiobjective particle swarm optimization (MOPSO)”. Water resources management, 27, 1931-1947, 2013.
[29] Yates, D., & Strzepek, K. M. (1994). Potential evapotranspiration methods and their impact on the assessment of river basin runoff under climate change.
[30] Suryaningtyas, L. S., Ery, S., & Rispiningtati, R. “Hydrological analysis of TRMM (Tropical rainfall measuring mission) data in lesti sub watershed”, Civil and Environmental Science Journal Vol. III, No. 01, pp. 018-030, 2020
[31] Moriasi, D. N., Arnold, J. G., Van Liew, M. W., Bingner, R. L., Harmel, R. D., & Veith, T. L. “Model evaluation guidelines for systematic quantification of accuracy in watershed simulations” Transactions of the ASABE, 50(3), 885-900, 2007.