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GÜNEY MARMARA HAVZASI’NDA SWAT+ MODELİ İLE HİDROLOJİK MODELLEME

Yıl 2024, Cilt: 12 Sayı: 3, 531 - 543, 26.09.2024
https://doi.org/10.21923/jesd.1473890

Öz

Bu çalışmada, SWAT+ hidrolojik modelinin ve SWAT+ Toolbox yazılımının Güney Marmara Havzası'ndaki performansı araştırılmaktadır. Hidrolojik modeller, hidrolojik döngüyü ve ilgili süreçleri analiz etmek için karmaşık havza yapılarını basitleştiren, su havzalarında etkili yönetim için kullanılan önemli araçlardır. Hidrolojik modeller, su yönetiminden hidrolojik araştırmalara kadar geniş bir uygulama alanına sahiptir. Hidrolojik modellerin özellikle son yıllarda kuraklık, taşkın, iklim değişikliği ve arazi kullanım değişikliği gibi nehir akımları ve diğer hidrolojik parametreler üzerindeki etkileşimini inceleyen çalışmalarda sıklıkla kullanıldığı görülmektedir. Bu çalışmada SWAT modelinin gelişmiş versiyonu olan SWAT+ ve SWAT+ Toolbox Türkiye özelinde uygulanmıştır; temel SWAT modeli Türkiye’de yaygın olarak kullanılsa da Swat+ modeli Türkiye'de henüz uygulanmamıştır. Bu araştırmanın temel amacı, SWAT+ ve SWAT+ Toolbox'ın Güney Marmara Havzası'ndaki performansını istatistiksel göstergeler kullanarak değerlendirmektir. Meteoroloji, toprak özellikleri, topoğrafya ve arazi kullanımı gibi havzadaki çeşitli faktörler hakkında ayrıntılı veri gerektiren SWAT+ hidrolojik modeli Güney Marmara havzasında başarıyla uygulanmıştır. SWAT+ modeli, SWAT modeline göre daha gelişmiş ve esnek olacak şekilde tasarlanmış olup, model dosyalarında herhangi bir ek değişiklik yapmadan kalibrasyon işleminin entegre bir şekilde yürütülmesine olanak sağlayan SWAT+ Toolbox'ın, model kurulumunda önemli avantajlar sağladığını görülmüştür. Araştırmada, modelin performansının hem kalibrasyon döneminde (NSE 0,596) hem de doğrulama döneminde (NSE 0,516) kabul edilebilir seviyenin üzerinde olduğunu, PBIAS değerlerine göre ise kalibrasyon döneminde modelin hafif yüksek tahmine (PBIAS %1,74) ve doğrulama döneminde düşük tahmine (PBIAS %-9,64) işaret ettiğini görülmektedir. Bu çalışma, Türkiye'de SWAT+ modelinin ve SWAT+ Toolbox'ın temel SWAT modeline benzer başarısını ortaya koyan ilk çalışmadır. SWAT+ modelinin sağladığı esneklik ve ek işlevler, Türkiye'deki hidrolojik modelleme çalışmalarına katkı sağlayacaktır. Bulgular, SWAT+ modelinin Türkiye'deki hidrolojik çalışmalarda başarıyla kullanılabileceğini göstermektedir.

Kaynakça

  • Abbaspour, K. C., Yang, J., Maximov, I., Siber, R., Bogner, K., Mieleitner, J., ... & Srinivasan, R. (2007). Modelling hydrology and water quality in the pre-alpine/alpine Thur watershed using SWAT. Journal of hydrology, 333(2-4), 413-430.
  • Aksu, H., Korkmaz, M. S., (2019). Türkiye’de Hidrolojik Veri Yönetimi ve Üniversitelerin Katılımı ABD Örneği, Mühendislik Bilimler ve Tasarım Dergisi, 7(3), 699-704.
  • Armstrong, J. S., & Collopy, F. (1992). Error measures for generalizing about forecasting methods: Empirical comparisons. International journal of forecasting, 8(1), 69-80.
  • Arnold, J. G., & Allen, P. M. (1996). Estimating hydrologic budgets for three Illinois watersheds. Journal of hydrology, 176(1-4), 57-77.
  • Ateşoğlu, A. (2016). Havza çalışmalarında kullanılan CORINE 2006 arazi sınıflandırma verilerinin doğruluğunun araştırılması. Journal of the Faculty of Forestry Istanbul University, 66(1), 173-183.
  • Aune-Lundberg, L., & Strand, G. H. (2021). The content and accuracy of the CORINE Land Cover dataset for Norway. International Journal of Applied Earth Observation and Geoinformation, 96, 102266.
  • Bai, J., Shen, Z., & Yan, T. (2017). A comparison of single-and multi-site calibration and validation: a case study of SWAT in the Miyun Reservoir watershed, China. Frontiers of Earth Science, 11, 592-600.
  • Bieger, K., Arnold, J. G., Rathjens, H., White, M. J., Bosch, D. D., Allen, P. M., … Srinivasan, R. (2016). Introduction to SWAT+,, a completely restructured version of the soil and water assessment tool. JAWRA Journal of the American Water Resources Association, 53(1), 115–130. doi:10.1111/1752-1688.12482
  • Chawanda, C.J. (2021). SWAT+ Toolbox: User Manual; SWAT+, Soil & Water Assessment Tool. Available online: https://www.openwater.network/assets/downloads/SWATplusToolboxUserMannual.pdf.
  • Clark, M. P., Kavetski, D., & Fenicia, F. (2011). Pursuing the method of multiple working hypotheses for hydrological modeling. Water Resources Research, 47(9).
  • Crawford, N. H., & Linsley, R. K. (1966). Digital Simulation in Hydrology'Stanford Watershed Model 4.
  • Dile, Y., Srinivasan, R., & George, C. (2016). QGIS Interface for SWAT (QSWAT). Version, 1, 25.
  • Dracup, J. A., Lee, K. S., & Paulson Jr, E. G. (1980). On the definition of droughts. Water resources research, 16(2), 297-302.
  • Duygu, M. B. (2021). Opportunities and challenges in using soil moisture from cosmic ray neutron sensing for rainfall-runoff modelling.
  • FAO. (2022). Harmonized world soil database v1.2. FAO SOILS PORTAL. Available at: https://www.fao.org/soils-portal/data-hub/soil-maps-and-databases/harmonized-world-soil-database-v12/en/
  • Fıstıkoğlu, O. (1999) Hidrolojik Modeller. Türkiye İnşaat Mühendisliği 15. Teknik Kongre ve Sergisi Bildiriler Kitabı, 799-809, Ankara.
  • Fischer, G., Nachtergaele, F., Prieler, S., van Velthuizen, H. T., Verelst, L., & Wiberg, D. (2008). Global Agro-ecological Zones Assessment for Agriculture (GAEZ 2008). IIASA; FAO.
  • Hämäläinen, R. P. (2015). Behavioural issues in environmental modelling–The missing perspective. Environmental Modelling & Software, 73, 244-253.
  • Harifidy, R. Z., Hiroshi, I., Kazuyoshi, S., Jun, M., Harivelo, R. Z. M., & Fernández-Palomino, C. A. (2024). Multi-gauge calibration comparison for simulating streamflow across the Major River Basins in Madagascar: SWAT+ Toolbox, R-SWAT, and SWAT+ Editor Hard calibration. Hydrology Research, nh2024188.
  • Jouma, N., & Dadaser-Celik, F. (2021). Assessing hydrologic alterations due to reservoirs and intensified irrigation in a semi-arid agricultural river basin using SWAT. Irrigation and Drainage, 71(2), 452–471.
  • Keleş Özgenç, E. (2024). Evaluation using the SWAT model of the effects of land use land cover changes on hydrological processes in the Gala Lake Basin, Turkey. Environmental Quality Management, 00, 1–15.
  • Marhaento, H., Booij, M. J., Rientjes, T. H. M., & Hoekstra, A. Y. (2017). Attribution of changes in the water balance of a tropical catchment to land use change using the SWAT model. Hydrological Processes, 31(11), 2029–2040. doi:10.1002/hyp.11167
  • McMillan, H. K., Westerberg, I. K., & Krueger, T. (2018). Hydrological data uncertainty and its implications. Wiley Interdisciplinary Reviews: Water, 5(6), e1319.
  • Mekonnen, D. F., Duan, Z., Rientjes, T., & Disse, M. (2018). Analysis of combined and isolated effects of land-use and land-cover changes and climate change on the upper Blue Nile River basin's streamflow. Hydrology and Earth System Sciences, 22(12), 6187-6207.
  • Moriasi, D. N., Arnold, J. G., Van Liew, M. W., Bingner, R. L., Harmel, R. D., & Veith, T. L. (2007). Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of the ASABE, 50(3), 885-900.
  • Mulvaney, T.J. (1850) On the use of self-registering rain and flood gauges. Transactions of the Institution of Civil Engineers of Ireland, 4(2), 1-8.
  • Nash, J. E., & Sutcliffe, J. V. (1970). River flow forecasting through conceptual models part I—A discussion of principles. Journal of hydrology, 10(3), 282-290.
  • Neitsch, S. L., Arnold, J. G., Kiniry, J. R., & Williams, J. R. (2011). Soil and water assessment tool theoretical documentation version 2009. Texas Water Resources Institute.
  • Nguyen, T. V., Dietrich, J., Dang, T. D., Tran, D. A., Van Doan, B., Sarrazin, F. J., ... & Srinivasan, R. (2022). An interactive graphical interface tool for parameter calibration, sensitivity analysis, uncertainty analysis, and visualization for the Soil and Water Assessment Tool. Environmental Modelling & Software, 156, 105497.
  • Oruç, H. N., Çelen, M., Gülgen, F., Öncel, M. S., Vural, S., & Kılıç, B. (2022). Assessing hydrologic alterations due to reservoirs and intensified irrigation in a semi-arid agricultural river basin using SWAT. Urban Water Journal, 20(10), 1592–1607.
  • Peker, İ. B., & Cuceloglu, G. (2022). SWAT (Soil and Water Assessment Tool) Modeline Genel Bir Bakış ve Modelin Türkiye’deki Uygulamaları. Çevre İklim ve Sürdürülebilirlik, 23(1), 9-26.
  • Probst, E., & Mauser, W. (2022). Evaluation of ERA5 and WFDE5 forcing data for hydrological modelling and the impact of bias correction with regional climatologies: A case study in the Danube River Basin. Journal of Hydrology: Regional Studies, 40, 101023.
  • Pulighe, G., Lupia, F., Chen, H., & Yin, H. (2021). Modeling climate change impacts on water balance of a Mediterranean watershed using SWAT+. Hydrology, 8(4), 157. https://doi.org/10.3390/hydrology8040157
  • Singh, L., & Saravanan, S. (2020). Simulation of monthly streamflow using the SWAT model of the Ib River watershed, India. HydroResearch, 3, 95-105.
  • Singh, V. P., & Woolhiser, D. A. (2002). Mathematical modeling of watershed hydrology. Journal of hydrologic engineering, 7(4), 270-292.
  • Swalih, S. A., & Kahya, E. (2021). Hydrological model optimization using multi-gauge calibration (MGC) in a mountainous region. Journal of Hydroinformatics, 23(2), 340-351.
  • Tolson, B. A., & Shoemaker, C. A. (2007). Dynamically dimensioned search algorithm for computationally efficient watershed model calibration. Water Resources Research, 43(1).
  • Turkes, M. (2012). Türkiye’de gözlenen ve öngörülen iklim değişikliği, kuraklık ve çölleşme. Ankara Üniversitesi Çevrebilimleri Dergisi, 4(2), 1-32.
  • Van Loon, A. F. (2015). Hydrological drought explained. Wiley Interdisciplinary Reviews: Water, 2(4), 359-392.

HYDROLOGICAL MODELLING IN THE SOUTHERN MARMARA BASIN USING SWAT+

Yıl 2024, Cilt: 12 Sayı: 3, 531 - 543, 26.09.2024
https://doi.org/10.21923/jesd.1473890

Öz

This study investigates the performance of the SWAT+ hydrological model and the SWAT+ Toolbox in the South Marmara Basin. Hydrological models are crucial tools for effective management in water basins, simplifying complex basin structures to analyze the hydrological cycle and related processes. Hydrological models have application range from water resource planning to hydrological research. Especially in recent years hydrological models are frequently used in studies examining the interaction of drought, flood, and climate change and land use change on flow rates and other hydrological parameters. This research investigates the application of the advanced version of the SWAT model, SWAT+, and the SWAT+ Toolbox in Türkiye, despite the widespread use of the basic SWAT model, Swat+ model has not been utilized in Türkiye. The primary aim of this research is to evaluate the performance of SWAT+ and SWAT+ Toolbox in the South Marmara Basin using performance indicators. SWAT+ hydrological model successfully implemented in the South Marmara basin, which requires detailed data on various factors in the basin such as meteorology, soil properties, topography, and land use. SWAT+ model is designed to be more advanced and flexible than the SWAT model, and we found that SWAT+ Toolbox, which allows the calibration process to be run in an integrated manner without making any additional changes in the model files, provide significant advantages in model setup and operation. Our findings indicate that the performance of the model is above the acceptable level in both the calibration period (NSE 0.596) and the validation period (NSE 0.516), with PBIAS values indicating slight overestimation (PBIAS 1.74%) during calibration and underestimation (PBIAS -9.64%) during validation. This study is the first to demonstrate the similar success of the SWAT+ model and the SWAT+ Toolbox to the basic SWAT model in Türkiye. The flexibility and additional functions provided by the SWAT+ model will contribute to hydrological modeling studies in Türkiye finding indicates that the SWAT+ model can be successfully used in hydrological studies in Türkiye.

Kaynakça

  • Abbaspour, K. C., Yang, J., Maximov, I., Siber, R., Bogner, K., Mieleitner, J., ... & Srinivasan, R. (2007). Modelling hydrology and water quality in the pre-alpine/alpine Thur watershed using SWAT. Journal of hydrology, 333(2-4), 413-430.
  • Aksu, H., Korkmaz, M. S., (2019). Türkiye’de Hidrolojik Veri Yönetimi ve Üniversitelerin Katılımı ABD Örneği, Mühendislik Bilimler ve Tasarım Dergisi, 7(3), 699-704.
  • Armstrong, J. S., & Collopy, F. (1992). Error measures for generalizing about forecasting methods: Empirical comparisons. International journal of forecasting, 8(1), 69-80.
  • Arnold, J. G., & Allen, P. M. (1996). Estimating hydrologic budgets for three Illinois watersheds. Journal of hydrology, 176(1-4), 57-77.
  • Ateşoğlu, A. (2016). Havza çalışmalarında kullanılan CORINE 2006 arazi sınıflandırma verilerinin doğruluğunun araştırılması. Journal of the Faculty of Forestry Istanbul University, 66(1), 173-183.
  • Aune-Lundberg, L., & Strand, G. H. (2021). The content and accuracy of the CORINE Land Cover dataset for Norway. International Journal of Applied Earth Observation and Geoinformation, 96, 102266.
  • Bai, J., Shen, Z., & Yan, T. (2017). A comparison of single-and multi-site calibration and validation: a case study of SWAT in the Miyun Reservoir watershed, China. Frontiers of Earth Science, 11, 592-600.
  • Bieger, K., Arnold, J. G., Rathjens, H., White, M. J., Bosch, D. D., Allen, P. M., … Srinivasan, R. (2016). Introduction to SWAT+,, a completely restructured version of the soil and water assessment tool. JAWRA Journal of the American Water Resources Association, 53(1), 115–130. doi:10.1111/1752-1688.12482
  • Chawanda, C.J. (2021). SWAT+ Toolbox: User Manual; SWAT+, Soil & Water Assessment Tool. Available online: https://www.openwater.network/assets/downloads/SWATplusToolboxUserMannual.pdf.
  • Clark, M. P., Kavetski, D., & Fenicia, F. (2011). Pursuing the method of multiple working hypotheses for hydrological modeling. Water Resources Research, 47(9).
  • Crawford, N. H., & Linsley, R. K. (1966). Digital Simulation in Hydrology'Stanford Watershed Model 4.
  • Dile, Y., Srinivasan, R., & George, C. (2016). QGIS Interface for SWAT (QSWAT). Version, 1, 25.
  • Dracup, J. A., Lee, K. S., & Paulson Jr, E. G. (1980). On the definition of droughts. Water resources research, 16(2), 297-302.
  • Duygu, M. B. (2021). Opportunities and challenges in using soil moisture from cosmic ray neutron sensing for rainfall-runoff modelling.
  • FAO. (2022). Harmonized world soil database v1.2. FAO SOILS PORTAL. Available at: https://www.fao.org/soils-portal/data-hub/soil-maps-and-databases/harmonized-world-soil-database-v12/en/
  • Fıstıkoğlu, O. (1999) Hidrolojik Modeller. Türkiye İnşaat Mühendisliği 15. Teknik Kongre ve Sergisi Bildiriler Kitabı, 799-809, Ankara.
  • Fischer, G., Nachtergaele, F., Prieler, S., van Velthuizen, H. T., Verelst, L., & Wiberg, D. (2008). Global Agro-ecological Zones Assessment for Agriculture (GAEZ 2008). IIASA; FAO.
  • Hämäläinen, R. P. (2015). Behavioural issues in environmental modelling–The missing perspective. Environmental Modelling & Software, 73, 244-253.
  • Harifidy, R. Z., Hiroshi, I., Kazuyoshi, S., Jun, M., Harivelo, R. Z. M., & Fernández-Palomino, C. A. (2024). Multi-gauge calibration comparison for simulating streamflow across the Major River Basins in Madagascar: SWAT+ Toolbox, R-SWAT, and SWAT+ Editor Hard calibration. Hydrology Research, nh2024188.
  • Jouma, N., & Dadaser-Celik, F. (2021). Assessing hydrologic alterations due to reservoirs and intensified irrigation in a semi-arid agricultural river basin using SWAT. Irrigation and Drainage, 71(2), 452–471.
  • Keleş Özgenç, E. (2024). Evaluation using the SWAT model of the effects of land use land cover changes on hydrological processes in the Gala Lake Basin, Turkey. Environmental Quality Management, 00, 1–15.
  • Marhaento, H., Booij, M. J., Rientjes, T. H. M., & Hoekstra, A. Y. (2017). Attribution of changes in the water balance of a tropical catchment to land use change using the SWAT model. Hydrological Processes, 31(11), 2029–2040. doi:10.1002/hyp.11167
  • McMillan, H. K., Westerberg, I. K., & Krueger, T. (2018). Hydrological data uncertainty and its implications. Wiley Interdisciplinary Reviews: Water, 5(6), e1319.
  • Mekonnen, D. F., Duan, Z., Rientjes, T., & Disse, M. (2018). Analysis of combined and isolated effects of land-use and land-cover changes and climate change on the upper Blue Nile River basin's streamflow. Hydrology and Earth System Sciences, 22(12), 6187-6207.
  • Moriasi, D. N., Arnold, J. G., Van Liew, M. W., Bingner, R. L., Harmel, R. D., & Veith, T. L. (2007). Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of the ASABE, 50(3), 885-900.
  • Mulvaney, T.J. (1850) On the use of self-registering rain and flood gauges. Transactions of the Institution of Civil Engineers of Ireland, 4(2), 1-8.
  • Nash, J. E., & Sutcliffe, J. V. (1970). River flow forecasting through conceptual models part I—A discussion of principles. Journal of hydrology, 10(3), 282-290.
  • Neitsch, S. L., Arnold, J. G., Kiniry, J. R., & Williams, J. R. (2011). Soil and water assessment tool theoretical documentation version 2009. Texas Water Resources Institute.
  • Nguyen, T. V., Dietrich, J., Dang, T. D., Tran, D. A., Van Doan, B., Sarrazin, F. J., ... & Srinivasan, R. (2022). An interactive graphical interface tool for parameter calibration, sensitivity analysis, uncertainty analysis, and visualization for the Soil and Water Assessment Tool. Environmental Modelling & Software, 156, 105497.
  • Oruç, H. N., Çelen, M., Gülgen, F., Öncel, M. S., Vural, S., & Kılıç, B. (2022). Assessing hydrologic alterations due to reservoirs and intensified irrigation in a semi-arid agricultural river basin using SWAT. Urban Water Journal, 20(10), 1592–1607.
  • Peker, İ. B., & Cuceloglu, G. (2022). SWAT (Soil and Water Assessment Tool) Modeline Genel Bir Bakış ve Modelin Türkiye’deki Uygulamaları. Çevre İklim ve Sürdürülebilirlik, 23(1), 9-26.
  • Probst, E., & Mauser, W. (2022). Evaluation of ERA5 and WFDE5 forcing data for hydrological modelling and the impact of bias correction with regional climatologies: A case study in the Danube River Basin. Journal of Hydrology: Regional Studies, 40, 101023.
  • Pulighe, G., Lupia, F., Chen, H., & Yin, H. (2021). Modeling climate change impacts on water balance of a Mediterranean watershed using SWAT+. Hydrology, 8(4), 157. https://doi.org/10.3390/hydrology8040157
  • Singh, L., & Saravanan, S. (2020). Simulation of monthly streamflow using the SWAT model of the Ib River watershed, India. HydroResearch, 3, 95-105.
  • Singh, V. P., & Woolhiser, D. A. (2002). Mathematical modeling of watershed hydrology. Journal of hydrologic engineering, 7(4), 270-292.
  • Swalih, S. A., & Kahya, E. (2021). Hydrological model optimization using multi-gauge calibration (MGC) in a mountainous region. Journal of Hydroinformatics, 23(2), 340-351.
  • Tolson, B. A., & Shoemaker, C. A. (2007). Dynamically dimensioned search algorithm for computationally efficient watershed model calibration. Water Resources Research, 43(1).
  • Turkes, M. (2012). Türkiye’de gözlenen ve öngörülen iklim değişikliği, kuraklık ve çölleşme. Ankara Üniversitesi Çevrebilimleri Dergisi, 4(2), 1-32.
  • Van Loon, A. F. (2015). Hydrological drought explained. Wiley Interdisciplinary Reviews: Water, 2(4), 359-392.
Toplam 39 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Su Kaynakları Mühendisliği
Bölüm Araştırma Makaleleri \ Research Articles
Yazarlar

Halil Emre Kışlıoğlu 0000-0002-1852-6970

Şehnaz Şule Bekaroğlu 0000-0003-0917-7219

Filiz Dadaser-celik 0000-0003-3623-7723

Yayımlanma Tarihi 26 Eylül 2024
Gönderilme Tarihi 26 Nisan 2024
Kabul Tarihi 10 Ağustos 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 12 Sayı: 3

Kaynak Göster

APA Kışlıoğlu, H. E., Bekaroğlu, Ş. Ş., & Dadaser-celik, F. (2024). GÜNEY MARMARA HAVZASI’NDA SWAT+ MODELİ İLE HİDROLOJİK MODELLEME. Mühendislik Bilimleri Ve Tasarım Dergisi, 12(3), 531-543. https://doi.org/10.21923/jesd.1473890