DAĞLIK BİR HAVZADA UYDU VERİSİ DESTEKLİ HİDROLOJİK MODELLEME

Yıl 2020, Cilt: 25 Sayı: 2, 813 - 830, 31.08.2020

Emin Taş , Arda Şorman

https://doi.org/10.17482/uumfd.726255

Öz

Su kaynakları planlama ve yönetimi çalışmalarının birçoğunda yağış-akış simülasyonunu gerçekleştirmek için hidrolojik modelleme yapılması büyük önem arz etmektedir. Bu bağlamda, kar
erimesinin etkili olduğu dağlık bir havza olan Afyonkarahisar Çay Deresi havzasında, yağışlı-yağışsız dönemi birlikte değerlendiren kavramsal, yarı-dağılımlı ve uydu verisi destekli bir modelleme çalışması uygulanmıştır. 2011-2013 su yılları arasında günlük akımların simülasyonu HEC-HMS modeli kullanılarak elde edilmiştir. Modelleme süreci; hazırlık aşamaları, parametre seçimi, kalibrasyon (2011-2012 yılları) ve validasyon (2013 yılı) aşamalarından oluşmaktadır. Model akım performansı NSE (Nash-Sutcliffe Efficiency), RMSE (Root Mean Square Error) ve MAE (Mean Absolute Error) değerlendirme ölçütleri ile test edilmiş olup, kalibrasyon periyodu için değerleri sırasıyla 0,89; 0,3 m3/s ve 0,2 m3/s  iken; validasyon periyodu için 0,78; 0,4 m3/s ve 0,2 m3/s bulunmuştur. Akım sonuçlarının yanında IMS (Interactive Multisensor Snow and Ice Mapping System) kar kaplı alan ürünleriyle de modelin doğruluğu desteklenmiştir. Çalışma havzasında başarılı sonuçların elde edildiği HEC-HMS hidrolojik modelinin kullanıma hazır olması; Çay Deresi mansap kısmında yer alan Çay ilçe yerleşiminin taşkın tehlikesi, sulama-içme suyu amaçlı Çay Barajının hazne işletimi ve Çay Deresinin döküldüğü Eber Gölünün ekolojik analizi çalışmaları açısından faydalı olabilir. 

Anahtar Kelimeler

Hidrolojik modelleme, HEC-HMS, Yağış-akış, Uydu verisi, Afyonkarahisar Çay deresi

Satellite-supported Hydrological Modeling in a Mountainous Basin

Öz

In many of the water resource planning and management studies, hydrological modeling is essential to perform precipitation-runoff simulations. In this context, a conceptual, semi-distributed and satellite-supported modeling study considering both wet and dry periods is applied to the Afyonkarahisar Çay watershed, which is a snow-dominated mountainous basin. The simulation of daily streamflow between 2011-2013 water years is implemented using HEC-HMS model. The modeling process consists of data preparation, parameter selection, calibration (2011-2012 years) and validation (2013 year) steps. The model streamflow performance is tested with NSE (Nash-Sutcliffe Efficiency), RMSE (Root Mean Square Error) and MAE (Mean Absolute Error) evaluation criteria, and the values are 0,89; 0,3 m3/s, 0,2 m3/s for the calibration period and 0,78; 0,4 m3/s, 0,2 m3/s for the validation period, respectively. Besides of the streamflow results, model accuracy is also supported with IMS (Interactive Multisensor Snow and Ice Mapping System) snow covered area products. The ready-to-use HEC-HMS hydrological model where successful results are obtained in the study basin can be useful for flood hazard mapping of Çay district settlement in the downstream of Çay stream; reservoir operation of Çay dam for irrigation-potable water purposes; and ecological analysis of the Eber Lake where the Çay stream flows into. 

Anahtar Kelimeler

Hydrological modeling, HEC-HMS, Precipitation-runoff, Satellite data, Afyonkarahisar Çay stream

Kaynakça

• 1. Azmat, M., Qamar, M. U., Ahmed, S., Hussain, E., Umair, M. (2017) Application of HEC-HMS for the event and continuous simulation in high-altitude scarcely-gauged catchment under changing climate, European Water, 57, 77-84.
• 2. Bora, E., Onuşluel Gül, G. (2019) Modeling of floods in Güvenç basin, Ankara using HEC-HMS, Turkish Journal of Water Science and Management, 3(1), 44-47. doi:10.31807/tjwsm.429776
• 3. Chang, C. (2009). Application of SCS CN method in HEC-HMS in Shihmen watershed simulation of rainfall-runoff hydrologic model, MSc Thesis, Florida State University, USA.
• 4. Chu, X., Steinman, A. (2009) Event and continuous hydrologic modeling with HEC-HMS, J. of Irrigation and Drainage Engineering, 135(1), 119-124. doi:10.1061/(ASCE)0733-9437(2009)135:1(119)
• 5. Copernicus Land Monitoring Service, CORINE Land Cover 2012, https://land.copernicus.eu/pan-european/corine-land-cover/clc-2012, Erişim Tarihi: 09.05.2020.
• 6. Dingman, S. L. (2002) Physical Hydrology, Waveland Press, Inc., USA.
• 7. DSİ, Su Veri Tabanı Rasatlar Bilgi Bankası, http://svtbilgi.dsi.gov.tr/Bilgi.aspx?istasyon=D11A021%20%C3%87AY%20%C3%87AY%20D, Erişim Tarihi: 22.04.2020.
• 8. FAO (Food and Agriculture Organization), (1977) Guidelines for Predicting Crop Water Requirements, FAO lrrigation and Drainage. Paper, 24, Rome, Italy.
• 9. Fleming, M., Neary, V. (2004) Continuous hydrologic modeling study with the Hydrologic Modeling System, J. of Hydrologic Engineering, 9(3), 175-183. doi:10.1061/(ASCE)1084-0699(2004)9:3(175)
• 10. Geetha, K., Mishra, S. K., Eldho, T. I., Rastogi, A. K., Pandey, R. P. (2007) Modifications to SCS-CN method for long-term hydrologic simulation, J. of Irrigation and Drainage Engineering, 133(5), 475-486. doi:10.1061/(ASCE)0733-9437(2007)133:5(475)
• 11. Geetha, K., Mishra, S. K., Eldho, T. I., Rastogi, A. K., Pandey, R. P. (2008) SCS-CN-based continuous simulation model for hydrologic forecasting, Water Resources Management, 22, 165-190. doi:10.1007/s11269-006-9149-5
• 12. Grimaldi, S., Petroselli, A., Serinaldi, F. (2012) A continuous simulation model for design-hydrograph estimation in small and ungauged watersheds, Hydrological Sciences Journal, 57(6), 1035-1051. doi:10.1080/02626667.2012.702214
• 13. Gülbaz, S. (2019) Sayısal modeller ile taşkın yayılım haritasının oluşturulması ve risk altında olan alanların belirlenmesi: Türkköse deresi örneği, Doğal Afetler ve Çevre Dergisi, 5(2), 335-349. doi:10.21324/dacd.491529
• 14. Gyawali, R., Watkins, D. W. (2013) Continuous hydrologic modeling of snow-affected watersheds in the Great Lakes basin using HEC-HMS, J. of Hydrologic Engineering, 18(1), 29-39. doi:10.1061/(ASCE)HE.1943-5584.0000591
• 15. Hengl, T., Mendes de Jesus, J., Heuvelink, G. B. M., Ruiperez Gonzalez, M., Kilibarda, M., Blagotić, A., et al. (2017) SoilGrids250m: Global gridded soil information based on machine learning, PLoS ONE, 12(2), 1-40. doi:10.1371/journal.pone.0169748
• 16. Hjelmfelt, A. T. (1982) Closure to empirical investigation of the curve number technique, J. of the Hydraulics Division American Society of Civil Engineers, 108(4), 614-616.
• 17. IWMI, Küresel İklim Modeli, http://wcatlas.iwmi.org/Default.asp, Erişim Tarihi: 22.04.2020.
• 18. Kirpich, Z. P. (1940) Time of concentration in small agricultural watersheds, Civil Engineering, 10(6), 362-368.
• 19. Meselhe, E. A., Habib, E. H., Oche, O. C., Gautam, S. (2009) Sensitivity of conceptual and physically based hydrologic models to temporal and spatial rainfall sampling, J. of Hydrologic Engineering, 14(7), 711-720. doi:10.1061/(ASCE)1084-0699(2009)14:7(711)
• 20. 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, American Society of Agricultural and Biological Engineers, 50(3), 885-900. doi:10.13031/2013.23153
• 21. Nash, J. E., Sutcliffe, J. V. (1970) River flow forecasting through conceptual models. Part I-A Discussion of principles, J. of Hydrology, 10(3), 282-290. doi:10.1016/0022-1694(70)90255-6
• 22. National Ice Center, (2008). Updated Daily. IMS Daily Northern Hemisphere Snow and Ice Analysis at 1 km, 4 km, and 24 km Resolutions, Boulder, Colorado, USA. NSIDC: National Snow and Ice Data Center. doi:10.7265/N52R3PMC.
• 23. NOAA NESDIS (National Oceanic and Atmospheric Administration National Environmental Satellite, Data and Information Service), (2019). Interactive Multisensor Snow and Ice Mapping System Version 3 (IMS V3) Algorithm Theoretical Basis Document Draft Version 2.5, Center for Satellite Applications and Research (STAR), Maryland, USA.
• 24. Quader, A., Guo, Y. (2009) Relative importance of hydrological and sediment-transport characteristics affecting effective discharge of small urban streams in southern Ontario, J. of Hydrologic Engineering, 14(7), 698-710. doi:10.1061/(ASCE)HE.1943-5584.0000042
• 25. Rathod, P., Borse, K., Manekar, V. L. (2015) Simulation of rainfall-runoff process using HEC-HMS (case study: Tapi river, India), 20th International Conference on Hydraulics, Water Resources and River Engineering, Roorkee, India, 17-19 December.
• 26. Razmkhah, H. (2016) Comparing performance of different loss methods in rainfall runoff modeling, Water Resources, 43(1), 207-224. doi:10.1134/S0097807816120058
• 27. Sardoii, E. R., Rostami, N., Sigaroudi, S. K., Taheri, S. (2012) Calibration of loss estimation methods in HEC-HMS for simulation of surface runoff (case study: Amirkabir dam watershed, Iran), Advances in Environmental Biology, 6(1), 343-348.
• 28. Sensoy, A., Uysal, G., Sorman, A. A. (2018) Developing a decision support framework for real time flood management using integrated models, J. of Flood Risk Management, 11(2), 866-883. doi:10.1111/jfr3.12280
• 29. SoilGrids, Global Gridded Soil Information, soilgrids.org, Erişim Tarihi: 22.04.2020.
• 30. Sorman, A. A., Tas, E., Dogan, Y. O. (2020) Comparison of hydrological models in upper Aras basin, Pamukkale University Journal of Engineering Sciences, Kabul Tarihi: 18.12.2019. doi:10.5505/pajes.2019.98852 (basım aşamasında)
• 31. Šraj, M., Dirnbek, L., Brilly, M. (2010) The influence of effective rainfall on modeled runoff hydrograph, J. of Hydrology and Hydromechanics, 58(1), 3-14. doi:10.2478/v10098-010-0001-5
• 32. SRTM, Digital Elevation Database, http://srtm.csi.cgiar.org/srtmdata, Erişim Tarihi: 22.04.2020.
• 33. Tassew, B. G., Belete, M. A., Miegel, K. (2019) Application of HEC-HMS model for flow simulation in the Lake Tana basin: The case of Gilgel Abay catchment, upper Blue Nile basin, Ethiopia, Hydrology, 6(21), 1-17. doi:10.3390/hydrology6010021
• 34. USACE (US Army Corps of Engineers), (2000). Hydrologic Modeling System HEC-HMS Technical Reference Manual, Hydrologic Engineering Center, Davis, USA.
• 35. USDA (US Department of Agriculture), (1951). Soil Survey Manual, Soil Conservation Service, Washington, USA.
• 36. USDA (US Department of Agriculture), (1972). National Engineering Handbook, Soil Conservation Service, Washington, USA.
• 37. USDA (US Department of Agriculture), (1986). Urban Hydrology for Small Watersheds, Natural Resources Conservation Service Technical Release 55, Washington, USA.
• 38. Yavuz, O., Uysal, G., Sensoy, A., Sorman, A. A., Akgun, T., Gezgin, T. (2012) Using HEC-HMS as a decision support system to minimize the downstream flooding risk in Yuvacık dam basin, Conference on Water Observation and Information Systems (BALWOIS), Ohrid, Macedonia, 28 May-2 June.
• 39. Yilmaz, A. G., Imteaz, M. A., Ogwuda, O. (2012) Accuracy of HEC-HMS and LBRM models in simulating snow runoffs in upper Euphrates basin, J. of Hydrologic Engineering, 17(2), 342-347. doi:10.1061/(ASCE)HE.1943-5584.0000442