Taban Akışının Simbiyotik Arama Algoritması ile Tespit Edilmesi: Fırat Havzası Örneği
Year 2021,
Volume: 3 Issue: 2, 169 - 183, 31.12.2021
Kemal Saplıoğlu
,
Ramazan Acar
Abstract
Artan nüfus ve sanayileşme su kaynaklarının etkin bir biçimde kullanılmasını gerekli hale getirmektedir. Bu nedenle su kaynaklarını oluşturan parametrelerin doğru bir şekilde tespit edilerek projelendirilmesi önemlidir. Yüzeysel akışın yaklaşık %70’ini oluşturan taban akışı da bu parametrelerin başında gelmektedir. Literatürde taban akışının belirlenmesi ile ilgili pek çok çalışma mevcuttur. Bu çalışmada, literatürde mevcut Chapman yönteminin sabit katsayılı olması ile katsayının kalibre edilmesi arasındaki fark gösterilmiştir. Ayrıca Chapman formülünde yüzeysel akış ile taban akışının modeldeki etkisini belirleyen birbiri ile bağımlı katsayıların birbirinden bağımsız hale gelmesini sağlamak için bir yöntem önerilmiştir. Her iki model için de katsayıların kalibrasyonu için simbiyotik organizmalar arama algoritması (SOA) ile optimizasyonu gerçekleştirilmiştir. Elde edilen sonuçlara bakıldığında Chapman yöntemini baz alan çift parametreli ve SOA ile kalibre edilen metodun Chapman yöntemindeki hidrograftan uzaklaşma veya kurak dönemlerde yüzeysel akışla taban akışının birbirinden farklı olması problemini azalttığı gözlemlenmiştir. Model ile taban akışının hidrografı kesmemesi de sağlanmıştır.
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- Smakhtin, V. U. (2001). Low flow hydrology: a review. Journal of hydrology, 240(3-4), 147-186.
- Stewart, M. K. (2015). Promising new baseflow separation and recession analysis methods applied to streamflow at Glendhu Catchment, New Zealand. Hydrology and Earth System Sciences, 19(6), 2587-2603.
- Swed, F. S., & Eisenhart, C. (1943). Tables for testing randomness of grouping in a sequence of alternatives. The Annals of Mathematical Statistics, 14(1), 66-87.
- Tallaksen, L. M. (1995). A review of baseflow recession analysis. Journal of hydrology, 165(1-4), 349-370.
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Year 2021,
Volume: 3 Issue: 2, 169 - 183, 31.12.2021
Kemal Saplıoğlu
,
Ramazan Acar
References
- Arnold, J. G., Allen, P. M., Muttiah, R., & Bernhardt, G. (1995). Automated base flow separation and recession analysis techniques. Groundwater, 33(6), 1010-1018.
- Boughton, W. C. (1993). A hydrograph-based model for estimating the water yield of ungauged catchments. In Hydrology and Water Resources Symposium, Newcastle, IEAust, 1993.
- Brutsaert, W., & Nieber, J. L. (1977). Regionalized drought flow hydrographs from a mature glaciated plateau. Water Resources Research, 13(3), 637-643.
- Chapman, T. G. (1991). Comment on “Evaluation of automated techniques for base flow and recession analyses” by RJ Nathan and TA McMahon. Water Resources Research, 27(7), 1783-1784.
- Chapman, T. (1999). A comparison of algorithms for stream flow recession and baseflow separation. Hydrological Processes, 13(5), 701-714.
- Chapman, T. G., & Maxwell, I. A. (1996, May). Baseflow separation-comparison of numerical methods with tracer experiments. In NATIONAL CONFERENCE PUBLICATION-INSTITUTION OF ENGINEERS AUSTRALIA NCP (Vol. 2, pp. 539-546). Institution of Engineers, Australia.
- Cheng, M. Y., & Prayogo, D. (2014). Symbiotic organisms search: a new metaheuristic optimization algorithm. Computers & Structures, 139, 98-112.
- Collischonn, W., & Fan, F. M. (2013). Defining parameters for Eckhardt's digital baseflow filter. Hydrological Processes, 27(18), 2614-2622.
- Çelik, E. (2020). A powerful variant of symbiotic organisms search algorithm for global optimization. Engineering Applications of Artificial Intelligence, 87, 103294.
- Eckhardt, K. (2005). How to construct recursive digital filters for baseflow separation. Hydrological Processes: An International Journal, 19(2), 507-515.
- Eckhardt, K. (2008). A comparison of baseflow indices, which were calculated with seven different baseflow separation methods. Journal of Hydrology, 352(1-2), 168-173.
- Ezugwu, A. E. S., & Adewumi, A. O. (2017). Discrete symbiotic organisms search algorithm for travelling salesman problem. Expert Systems with Applications, 87, 70-78.
- Ezugwu, A. E. S., Adewumi, A. O., & Frîncu, M. E. (2017). Simulated annealing based symbiotic organisms search optimization algorithm for traveling salesman problem. Expert Systems with Applications, 77, 189-210.
- Freeze, R. A. (1972). Role of subsurface flow in generating surface runoff: 1. Base flow contributions to channel flow. Water Resources Research, 8(3), 609-623.
- Güçlü, Y. S. (2020). Improved visualization for trend analysis by comparing with classical Mann-Kendall test and ITA. Journal of Hydrology, 584, 124674.
- Hall, F. R. (1968). Base‐flow recessions—A review. Water resources research, 4(5), 973-983.
- Hu, C., Zhao, D., & Jian, S. (2021). Baseflow estimation in typical catchments in the Yellow River Basin, China. Water Supply, 21(2), 648-667.
- Kissel, M., & Schmalz, B. (2020). Comparison of baseflow separation methods in the german low mountain range. Water, 12(6), 1740.
- Ladson, A. R., Brown, R., Neal, B., & Nathan, R. (2013). A standard approach to baseflow separation using the Lyne and Hollick filter. Australasian Journal of Water Resources, 17(1), 25-34.
- Li, L., Maier, H. R., Lambert, M. F., Simmons, C. T., & Partington, D. (2013). Framework for assessing and improving the performance of recursive digital filters for baseflow estimation with application to the Lyne and Hollick filter. Environmental modelling & software, 41, 163-175.
- Li, L., Maier, H. R., Partington, D., Lambert, M. F., & Simmons, C. T. (2014). Performance assessment and improvement of recursive digital baseflow filters for catchments with different physical characteristics and hydrological inputs. Environmental Modelling & Software, 54, 39-52.
- Linsley Jr, R. K., Kohler, M. A., & Paulhus, J. L. (1975). Hydrology for engineers.
- Lyne, V., & Hollick, M. (1979, September). Stochastic time-variable rainfall-runoff modelling. In Institute of Engineers Australia National Conference (Vol. 79, No. 10, pp. 89-93). Barton, Australia: Institute of Engineers Australia.
- Meshgi, A., Schmitter, P., Babovic, V., & Chui, T. F. M. (2014). Predicting Baseflow Using Genetic Programing.
- Murphy, R., Graszkiewicz, Z., Hill, P., Neal, B., Nathan, R. J., & Ladson, T. (2009). Project 7: Baseflow for catchment simulation (Phase 1-Selection of baseflow separation approach). Australian Rainfall and Runoff Technical Committee: Australia.
- Nathan, R. J., & McMahon, T. A. (1990). Evaluation of automated techniques for base flow and recession analyses. Water resources research, 26(7), 1465-1473.
- Novita, E., & Wahyuningsih, S. (2016). Preliminary study on baseflow separation at watersheds in East Java regions. Agriculture and Agricultural Science Procedia, 9, 538-550.
- Price, K. (2011). Effects of watershed topography, soils, land use, and climate on baseflow hydrology in humid regions: A review. Progress in physical geography, 35(4), 465-492.
- SAPLIOĞLU, K., ÇOBAN, E., ŞENEL, F. A., & UZUNDURUKAN, S. Beton Ağırlıklı Barajların Simbiyotik Arama Algoritması ile Optimizasyonu. Bitlis Eren Üniversitesi Fen Bilimleri Dergisi, 9(4), 1734-1744.
- Smakhtin, V. U. (2001). Low flow hydrology: a review. Journal of hydrology, 240(3-4), 147-186.
- Stewart, M. K. (2015). Promising new baseflow separation and recession analysis methods applied to streamflow at Glendhu Catchment, New Zealand. Hydrology and Earth System Sciences, 19(6), 2587-2603.
- Swed, F. S., & Eisenhart, C. (1943). Tables for testing randomness of grouping in a sequence of alternatives. The Annals of Mathematical Statistics, 14(1), 66-87.
- Tallaksen, L. M. (1995). A review of baseflow recession analysis. Journal of hydrology, 165(1-4), 349-370.
Xie, J., Liu, X., Wang, K., Yang, T., Liang, K., & Liu, C. (2020). Evaluation of typical methods for baseflow separation in the contiguous United States. Journal of Hydrology, 583, 124628.
- Yıldırım, A. (2006). Karakaya Barajı ve Doğal Çevre Etkileri. Dicle Üniversitesi Ziya Gökalp Eğitim Fakültesi Dergisi, (6), 32-39.