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Taşkın Pik Debisinin Belirlenmesinde WinTR-55 Hidrolojik Modelinin Kullanımı: Kırklareli Vize Deresi ve Samsun Minöz Deresi Havzaları Örneği

Yıl 2022, Cilt 8, Sayı 2, 305 - 316, 30.07.2022

Çayan ALKAN

https://doi.org/10.21324/dacd.1040189

Öz

İklim değişikliği, su kaynaklarını etkileyen başlıca parametredir. Bu parametre, kuraklık ve sel gibi ekstrem hidrolojik olayları şiddetlendirecektir. Tarımsal havzalarda muhtemel pik debilerin belirlenmesi, ürün kayıplarının önlenmesi açısından önemlidir. Tarımsal havzalara (hidrolojiye) uygun materyal ve yöntemin kullanıldığı, bu çalışmanın genel amacı; Windows Technical Release-55 (WinTR-55) modelinin tahmin gücünün başarısını belirlemektir. Bu çalışmada, Kırklareli Vize Deresi ve Samsun Minöz Deresi havzalarının verileri kullanılarak WinTR-55 modeliyle tahmin edilen pik debiler, gözlenen pik debilerle karşılaştırılmıştır. En başarılı tahmin; Vize Çayı havzasında %25 hata ile 100 yıllık tekerrür için, Minöz Çayı havzasında %2 hata ile 10 yıllık tekerrür için gerçekleşmiştir. Daha büyük pik debiler tahminlemeye eğilimli olan WinTR-55 yardımıyla, her bir tekerrür periyodunda gözlenen pik debilere kıyasla, daha büyük pik debiler tahmin edilmiştir. Böylece WinTR-55’in; Vize deresi ve Minöz deresi havzasında taşkın zararlarının önlenmesinde güvenle kullanılabileceği anlaşılmıştır. Sonuç olarak; Devlet Su İşleri (DSİ) gibi kamu kurumlarında hesaplanan pik debinin, WinTR-55 modeli yardımıyla yapılması önerilmektedir.

Anahtar Kelimeler

Taşkın Pik Debisi, Vize ve Minöz Dereleri Havzası, Wintr-55, Hidrolojik Model

Kaynakça

  • Abdi D.A., Ayenew T., (2021), Evaluation of the WEAP model in simulating subbasin hydrology in the Central Rift Valley basin, Ethiopia, Ecological Processes, 10, 41, doi: 10.1186/s13717-021-00305-5.
  • Alkan C., (2016), A Researh on Applicability of Small Watershed Hydrologic Model WinTR-55 to the Basin of Some Small Earth Dams Aimed at Irrigation in Bursa, MSc Thesis, Graduate of school of natural and applied sciences of Uludağ University, Department of Biosystem Engineering, Bursa, Turkey.
  • Bakanogullari F., Gunay S., (2010), Rainfall and Discharge Characteristics of Kirklareli – Vize Stream Watershed, Ataturk Directorate of Soil and Water Resources Research Institute, Kirklareli, 97ss.
  • Bauer R. D., (2005), Optimization of detention ponds for urbanizing watersheds, MSc thesis, Department of Civil and Environmental Engineering in the Graduate School, Southern Illinois University, USA.
  • Citakoglu H., Demir V., Haktanir T., (2017), Regional frequency analysis of annual flood peaks of natural streams discharging to the Black sea by the L-moments method, Omer Halisdemir University Journal of Engineering Sciences, 6(2), 571-580.
  • Daniel E. B., Camp J. V., LeBoeuf E. J., Penrod J. R., Dobbins J. P., Abkowitz M. D., (2011), Watershed Modeling and its Applications: A State-of-the-Art Review, The Open Hydrology Journal, 5, 26-50.
  • Demir V., Keskin A. U., (2019), Determination of Manning roughness coefficient by Cowan method and Remote Sensing, Gazi journal of engineering sciences, 5(2), 167-177.
  • Demir V., Keskin A. U., (2020), Obtaining the Manning roughness with terrestrial-remote sensing technique and flood modeling using FLO-2D: A case study Samsun from Turkey, Geofizika, 37 (2), 131–156.
  • Demir V., Keskin A. U., (2022), Flood flow calculation and flood modeling in rivers that do not have enough flow measurement (Samsun, Mert River sample), Journal of Geomatics, 7(2), 149-162.
  • Demir V., Kisi O., (2016), Flood hazard mapping by using Geographic Information System and Hydraulic Model: Mert River, Samsun, Turkey, Advances in Meteorology, 2016, 4891015, doi: 10.1155/2016/4891015.
  • Erel A., (2010), Rainfall and Discharge Characteristics of Samsun-Minoz Stream Watershed (Report 1994-2008), T.R. ministry of agriculture and rural affairs general directorate of agricultural research, Topraksu-2010/99, Samsun.
  • Fidal J., Kjeldsen T. R., (2020), Accounting for soil moisture in rainfall-runoff modeling of urban areas, Journal of Hydrology, 589, doi: 10.1016/j.jhydrol.2020.125122.
  • Gholami V., Khaleghi M. R., (2021), A simulation of the rainfall-runoff process using artificial neural network and HEC-HMS model in forest lands, Journal of Forest Science, 67(4), 165–174.
  • Gulbahar N., (2016), A comparison study of some flood estimation methods in terms of design of water structures, International journal of engineering Technologies, 2(1), 8-13.
  • Gulbaz S., (2019), Developing Flood Extent Map by using Numerical Models and Determination of Areas under Flood Risk: Türkköse Stream Case, Journal of Natural Hazards and Environment, 5(2), 335-349.
  • Henning J. L., (2009), Stormwater and flooding on the UNR campus: A current and future modeling assessment, MSc Thesis, Graduate of University of Nevada, Department of Environmental Science and Health, Nevada, USA.
  • Huffman R. L., Fangmeier D. D., Elliot W. J., Workman S. R., (2013), Soil and water conservation engineering, American society of agricultural and biological engineers (ASABE), Michigan, 515ss.
  • Krishna Rao D. V. S., Premalatha M., Naveen C., (2018), Analysis of different combinations of meteorological parameters in predicting the horizontal global solar radiation with ANN approach: A case study, Renewable and Sustainable Energy Reviews, 91, 248–258.
  • Lane R. A., Coxon G., Freer J. E., Wagener T., Johnes P. J., Bloomfield J. P., Greene S., Macleod C. J. A., Reaney S. M., (2019), Benchmarking the predictive capability of hydrological models for river flow and flood peak predictions across over 1000 catchments in Great Britain, Hydrol. Earth Syst. Sci., 23, 4011–4032.
  • Lee S. B., Yoon C. G., Jung K. W., Hwang H. S., (2010), Comparative evaluation of runoff and water quality using HSPF and SWMM, Water Science and Technology, 62, 6, doi: 10.2166/wst.2010.302.
  • Mesta B., Kargi P. G., Tezyapar I., Ayvaz M. T., Goktas R. K., Kentel E., Tezel U., (2019), Determination of rainfall-runoff relationship in Yenicegoruce Basin with HEC-HMS hydrologic model, Pamukkale University Journal of Engineering Sciences 25(8), 949-955.
  • Ozturk M., Kaya N., Aşkan A. H., (2003), Evaluation of the flood calculation methods used in the design of the culverts, Sakarya University Journal of Science, 7 (2), 167-171.
  • Poovakka A.K., Eldho T.I., (2019), A comparative study of conceptual rainfall-runoff models GR4J, AWBM and Sacramento at catchments in the upper Godavari river basin, India, J. Earth Syst. Sci., 128, 33, doi: 10.1007/s12040-018-1055-8.
  • Roberts R., Lea J., Foreman L., Moody H. F., Quan Q. D., Merkel W., Visser K., Hoeft C., McNeill A., McClung J., Funderburk T., Werner J., Cronshey R., Woodward D., (2009), Small Watershed Hydrology Win Tr 55 User Guide, United States Department of Agriculture Natural Resources Conservation Service Conservation Engineering Division, USA.
  • Sutjiningsih D., Soeryantono H., Anggraheni E., (2015), Estimation of sediment yield in a small urban ungauged watershed based on the Schaffernak approach at Sugutamu watershed, ciliwung, west java, International Journal of Technology, 5, 809-818.
  • Swathi V., Raju K. S., Varma M. R. R., (2020), Addition of overland runoff and flow routing methods to SWMM—model application to Hyderabad, India, Environmental Monitoring and Assessment, 192, 643, doi: 10.1007/s10661-020-08490-0.
  • Sonmez O., Ozturk M., Dogan E., (2012), Estimation of flood discharge in Istanbul rivers, Sakarya University Journal of Science, 16(2), 130-135.
  • Sorman A. A., Tas E., Dogan Y. O., (2020), Comparison of hydrological models in upper Aras Basin, Pamukkale University Journal of Engineering Sciences, 26(6), 1015-1022, doi:10.5505/pajes.2019.98852.
  • Ulke A., Beden N., Demir V., Menek N., (2017), Numerical modeling of Samsun Mert River floods, European Water, 57, 27-34.
  • Yaghoubi B., Hosseini S. A., Nazif S., (2019), Monthly prediction of streamflow using data-driven models, J. Earth Syst. Sci., 128, 141, doi: 10.1007/s12040-019-1170-1.

Use of the WinTR-55 Hydrologic Model on Determination of Flood Peak Discharge: The Case of Kirklareli Vize Stream and Samsun Minoz Stream Watersheds

Yıl 2022, Cilt 8, Sayı 2, 305 - 316, 30.07.2022

Çayan ALKAN

https://doi.org/10.21324/dacd.1040189

Öz

Climate change is the main parameter affecting water resources. This parameter will exacerbate hydrologic extreme events like drought and flood. Determination of possible peak flow in the agricultural watershed is important in terms of preventing crop losses. The materials and the methods suitable for agricultural watersheds (hydrology) were used in this study. The general aim of this study is to determine the success of estimation power of the Windows Technical Release-55 (WinTR-55) Model. In this study, the peak flows estimated by the WinTR-55 model using the data of the Kirklareli Vize and Samsun Minoz Stream watersheds were compared with the observed peak flows. The most successful estimation was for the 100-year return period with error 25% in the Vize stream watershed and was for the 10-year return period with error 2% in the Minoz Stream watershed. With the aid of the WinTR-55, which tends to predict larger peak flow rates, greater peak flow rates were estimated compared with observed peak flow for each return period. So, it was understood that WinTR-55 can be used for the prevention of flood damage in the Vize and Minoz Stream watersheds confidently. As a result, it is recommended that calculated peak flow in public institutions such as State Hydraulics Works (SHW) should made with the help of the WinTR-55 model.

Anahtar Kelimeler

Flood Peak Discharge, Vize and Minoz Stream Watersheds, Wintr-55, Hydrologic Model

Kaynakça

  • Abdi D.A., Ayenew T., (2021), Evaluation of the WEAP model in simulating subbasin hydrology in the Central Rift Valley basin, Ethiopia, Ecological Processes, 10, 41, doi: 10.1186/s13717-021-00305-5.
  • Alkan C., (2016), A Researh on Applicability of Small Watershed Hydrologic Model WinTR-55 to the Basin of Some Small Earth Dams Aimed at Irrigation in Bursa, MSc Thesis, Graduate of school of natural and applied sciences of Uludağ University, Department of Biosystem Engineering, Bursa, Turkey.
  • Bakanogullari F., Gunay S., (2010), Rainfall and Discharge Characteristics of Kirklareli – Vize Stream Watershed, Ataturk Directorate of Soil and Water Resources Research Institute, Kirklareli, 97ss.
  • Bauer R. D., (2005), Optimization of detention ponds for urbanizing watersheds, MSc thesis, Department of Civil and Environmental Engineering in the Graduate School, Southern Illinois University, USA.
  • Citakoglu H., Demir V., Haktanir T., (2017), Regional frequency analysis of annual flood peaks of natural streams discharging to the Black sea by the L-moments method, Omer Halisdemir University Journal of Engineering Sciences, 6(2), 571-580.
  • Daniel E. B., Camp J. V., LeBoeuf E. J., Penrod J. R., Dobbins J. P., Abkowitz M. D., (2011), Watershed Modeling and its Applications: A State-of-the-Art Review, The Open Hydrology Journal, 5, 26-50.
  • Demir V., Keskin A. U., (2019), Determination of Manning roughness coefficient by Cowan method and Remote Sensing, Gazi journal of engineering sciences, 5(2), 167-177.
  • Demir V., Keskin A. U., (2020), Obtaining the Manning roughness with terrestrial-remote sensing technique and flood modeling using FLO-2D: A case study Samsun from Turkey, Geofizika, 37 (2), 131–156.
  • Demir V., Keskin A. U., (2022), Flood flow calculation and flood modeling in rivers that do not have enough flow measurement (Samsun, Mert River sample), Journal of Geomatics, 7(2), 149-162.
  • Demir V., Kisi O., (2016), Flood hazard mapping by using Geographic Information System and Hydraulic Model: Mert River, Samsun, Turkey, Advances in Meteorology, 2016, 4891015, doi: 10.1155/2016/4891015.
  • Erel A., (2010), Rainfall and Discharge Characteristics of Samsun-Minoz Stream Watershed (Report 1994-2008), T.R. ministry of agriculture and rural affairs general directorate of agricultural research, Topraksu-2010/99, Samsun.
  • Fidal J., Kjeldsen T. R., (2020), Accounting for soil moisture in rainfall-runoff modeling of urban areas, Journal of Hydrology, 589, doi: 10.1016/j.jhydrol.2020.125122.
  • Gholami V., Khaleghi M. R., (2021), A simulation of the rainfall-runoff process using artificial neural network and HEC-HMS model in forest lands, Journal of Forest Science, 67(4), 165–174.
  • Gulbahar N., (2016), A comparison study of some flood estimation methods in terms of design of water structures, International journal of engineering Technologies, 2(1), 8-13.
  • Gulbaz S., (2019), Developing Flood Extent Map by using Numerical Models and Determination of Areas under Flood Risk: Türkköse Stream Case, Journal of Natural Hazards and Environment, 5(2), 335-349.
  • Henning J. L., (2009), Stormwater and flooding on the UNR campus: A current and future modeling assessment, MSc Thesis, Graduate of University of Nevada, Department of Environmental Science and Health, Nevada, USA.
  • Huffman R. L., Fangmeier D. D., Elliot W. J., Workman S. R., (2013), Soil and water conservation engineering, American society of agricultural and biological engineers (ASABE), Michigan, 515ss.
  • Krishna Rao D. V. S., Premalatha M., Naveen C., (2018), Analysis of different combinations of meteorological parameters in predicting the horizontal global solar radiation with ANN approach: A case study, Renewable and Sustainable Energy Reviews, 91, 248–258.
  • Lane R. A., Coxon G., Freer J. E., Wagener T., Johnes P. J., Bloomfield J. P., Greene S., Macleod C. J. A., Reaney S. M., (2019), Benchmarking the predictive capability of hydrological models for river flow and flood peak predictions across over 1000 catchments in Great Britain, Hydrol. Earth Syst. Sci., 23, 4011–4032.
  • Lee S. B., Yoon C. G., Jung K. W., Hwang H. S., (2010), Comparative evaluation of runoff and water quality using HSPF and SWMM, Water Science and Technology, 62, 6, doi: 10.2166/wst.2010.302.
  • Mesta B., Kargi P. G., Tezyapar I., Ayvaz M. T., Goktas R. K., Kentel E., Tezel U., (2019), Determination of rainfall-runoff relationship in Yenicegoruce Basin with HEC-HMS hydrologic model, Pamukkale University Journal of Engineering Sciences 25(8), 949-955.
  • Ozturk M., Kaya N., Aşkan A. H., (2003), Evaluation of the flood calculation methods used in the design of the culverts, Sakarya University Journal of Science, 7 (2), 167-171.
  • Poovakka A.K., Eldho T.I., (2019), A comparative study of conceptual rainfall-runoff models GR4J, AWBM and Sacramento at catchments in the upper Godavari river basin, India, J. Earth Syst. Sci., 128, 33, doi: 10.1007/s12040-018-1055-8.
  • Roberts R., Lea J., Foreman L., Moody H. F., Quan Q. D., Merkel W., Visser K., Hoeft C., McNeill A., McClung J., Funderburk T., Werner J., Cronshey R., Woodward D., (2009), Small Watershed Hydrology Win Tr 55 User Guide, United States Department of Agriculture Natural Resources Conservation Service Conservation Engineering Division, USA.
  • Sutjiningsih D., Soeryantono H., Anggraheni E., (2015), Estimation of sediment yield in a small urban ungauged watershed based on the Schaffernak approach at Sugutamu watershed, ciliwung, west java, International Journal of Technology, 5, 809-818.
  • Swathi V., Raju K. S., Varma M. R. R., (2020), Addition of overland runoff and flow routing methods to SWMM—model application to Hyderabad, India, Environmental Monitoring and Assessment, 192, 643, doi: 10.1007/s10661-020-08490-0.
  • Sonmez O., Ozturk M., Dogan E., (2012), Estimation of flood discharge in Istanbul rivers, Sakarya University Journal of Science, 16(2), 130-135.
  • Sorman A. A., Tas E., Dogan Y. O., (2020), Comparison of hydrological models in upper Aras Basin, Pamukkale University Journal of Engineering Sciences, 26(6), 1015-1022, doi:10.5505/pajes.2019.98852.
  • Ulke A., Beden N., Demir V., Menek N., (2017), Numerical modeling of Samsun Mert River floods, European Water, 57, 27-34.
  • Yaghoubi B., Hosseini S. A., Nazif S., (2019), Monthly prediction of streamflow using data-driven models, J. Earth Syst. Sci., 128, 141, doi: 10.1007/s12040-019-1170-1.

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik, Yerbilimleri, Ortak Disiplinler
Yayınlanma Tarihi Temmuz 2022
Bölüm Araştırma Makalesi
Yazarlar

Çayan ALKAN> (Sorumlu Yazar)
BILECIK SEYH EDEBALI UNIVERSITY
0000-0002-4574-448X
Türkiye

Yayımlanma Tarihi 30 Temmuz 2022
Yayınlandığı Sayı Yıl 2022, Cilt 8, Sayı 2

Kaynak Göster

Bibtex @araştırma makalesi { dacd1040189, journal = {Doğal Afetler ve Çevre Dergisi}, eissn = {2528-9640}, address = {}, publisher = {Artvin Çoruh Üniversitesi}, year = {2022}, volume = {8}, number = {2}, pages = {305 - 316}, doi = {10.21324/dacd.1040189}, title = {Use of the WinTR-55 Hydrologic Model on Determination of Flood Peak Discharge: The Case of Kirklareli Vize Stream and Samsun Minoz Stream Watersheds}, key = {cite}, author = {Alkan, Çayan} }
APA Alkan, Ç. (2022). Use of the WinTR-55 Hydrologic Model on Determination of Flood Peak Discharge: The Case of Kirklareli Vize Stream and Samsun Minoz Stream Watersheds . Doğal Afetler ve Çevre Dergisi , 8 (2) , 305-316 . DOI: 10.21324/dacd.1040189
MLA Alkan, Ç. "Use of the WinTR-55 Hydrologic Model on Determination of Flood Peak Discharge: The Case of Kirklareli Vize Stream and Samsun Minoz Stream Watersheds" . Doğal Afetler ve Çevre Dergisi 8 (2022 ): 305-316 <http://dacd.artvin.edu.tr/tr/pub/issue/71418/1040189>
Chicago Alkan, Ç. "Use of the WinTR-55 Hydrologic Model on Determination of Flood Peak Discharge: The Case of Kirklareli Vize Stream and Samsun Minoz Stream Watersheds". Doğal Afetler ve Çevre Dergisi 8 (2022 ): 305-316
RIS TY - JOUR T1 - Use of the WinTR-55 Hydrologic Model on Determination of Flood Peak Discharge: The Case of Kirklareli Vize Stream and Samsun Minoz Stream Watersheds AU - Çayan Alkan Y1 - 2022 PY - 2022 N1 - doi: 10.21324/dacd.1040189 DO - 10.21324/dacd.1040189 T2 - Doğal Afetler ve Çevre Dergisi JF - Journal JO - JOR SP - 305 EP - 316 VL - 8 IS - 2 SN - -2528-9640 M3 - doi: 10.21324/dacd.1040189 UR - https://doi.org/10.21324/dacd.1040189 Y2 - 2022 ER -
EndNote %0 Doğal Afetler ve Çevre Dergisi Use of the WinTR-55 Hydrologic Model on Determination of Flood Peak Discharge: The Case of Kirklareli Vize Stream and Samsun Minoz Stream Watersheds %A Çayan Alkan %T Use of the WinTR-55 Hydrologic Model on Determination of Flood Peak Discharge: The Case of Kirklareli Vize Stream and Samsun Minoz Stream Watersheds %D 2022 %J Doğal Afetler ve Çevre Dergisi %P -2528-9640 %V 8 %N 2 %R doi: 10.21324/dacd.1040189 %U 10.21324/dacd.1040189
ISNAD Alkan, Çayan . "Use of the WinTR-55 Hydrologic Model on Determination of Flood Peak Discharge: The Case of Kirklareli Vize Stream and Samsun Minoz Stream Watersheds". Doğal Afetler ve Çevre Dergisi 8 / 2 (Temmuz 2022): 305-316 . https://doi.org/10.21324/dacd.1040189
AMA Alkan Ç. Use of the WinTR-55 Hydrologic Model on Determination of Flood Peak Discharge: The Case of Kirklareli Vize Stream and Samsun Minoz Stream Watersheds. Doğ Afet Çev Derg. 2022; 8(2): 305-316.
Vancouver Alkan Ç. Use of the WinTR-55 Hydrologic Model on Determination of Flood Peak Discharge: The Case of Kirklareli Vize Stream and Samsun Minoz Stream Watersheds. Doğal Afetler ve Çevre Dergisi. 2022; 8(2): 305-316.
IEEE Ç. Alkan , "Use of the WinTR-55 Hydrologic Model on Determination of Flood Peak Discharge: The Case of Kirklareli Vize Stream and Samsun Minoz Stream Watersheds", Doğal Afetler ve Çevre Dergisi, c. 8, sayı. 2, ss. 305-316, Tem. 2022, doi:10.21324/dacd.1040189
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