Comparative Discussion of Curve Number Methods in the Upper Aksu River Basin (Giresun, Türkiye)
Öz
Hydrological models are simplified tools designed to simulate the processes of the hydrological cycle. Beyond flood mapping and risk mitigation, they support evaluations of water availability, climate scenarios, environmental planning, and engineering applications. The demand for more accurate simulations has led researchers to develop increasingly refined modelling approaches. In this study, five Curve Number methods were compared in the steep, rugged upper basin of the Aksu River (Giresun, Turkey): the standard Curve Number method, three slope-adjusted methods, and one revised method. Modelling was conducted using CORINE 2012 land cover data, meteorological observations from the Kümbet Plateau and Yavuzkemal stations, and the national soil database. Given the distinct snow accumulation during cold periods and snowmelt during warm periods, analyses were separated by season to assess model performance under varying hydrometeorological conditions. Model outputs were validated using runoff data from the E22A061 stream gauge station, and performance was evaluated using Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE) metrics. Results indicate that all modified CN methods produced more accurate estimates than the standard method in both seasons. During the cold period, the slope-adjusted methods proposed by Sharpley & Williams and Ajmal et al. outperformed others due to the basin’s steep, rugged terrain. In contrast, delayed runoff induced by snowmelt significantly reduced the predictive accuracy of all methods during the warm period. The originality of this study lies in its evaluation of CN methods under snowmelt-driven delayed runoff and in steep, rugged topographic conditions. These findings highlight seasonal and rugged topographic effects in CN-based modelling. Furthermore, it contributes to a better understanding of the applicability of the CN method, which is an empirical model, in mountainous basins affected by snowfall.
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- Ahl, R. S., Woods, S. W., & Zuuring, H. R. (2008). Hydrologic Calibration and Validation of SWAT in a Snow‐Dominated Rocky Mountain Watershed, Montana, U.S.A. 1. JAWRA Journal of the American Water Resources Association, 44(6), 1411–1430. https://doi.org/10.1111/j.1752-1688.2008.00233.x
- Ajmal, M., Waseem, M., Ahn, J.-H., & Kim, T.-W. (2016). Runoff Estimation Using the NRCS Slope-Adjusted Curve Number in Mountainous Watersheds. Journal of Irrigation and Drainage Engineering, 142(4). https://doi.org/10.1061/(ASCE)IR.1943-4774.0000998
- Apaydın, A. (2021). 22 Ağustos 2020 Tarihli Taşkına Neden Olan Dereli Deresi (Giresun) Havza Analizleri, Taşkının Nedenleri ve Sonuçları. Karadeniz Fen Bilimleri Dergisi, 11(2), 392–425. https://doi.org/10.31466/kfbd.908878
- Ávila, L., Silveira, R., Campos, A., Rogiski, N., Gonçalves, J., Scortegagna, A., Freita, C., Aver, C., & Fan, F. (2022). Comparative Evaluation of Five Hydrological Models in a Large-Scale and Tropical River Basin. Water, 14(19), 3013. https://doi.org/10.3390/w14193013
- Bayrakdar, C., & Özdemir, Hasan. (2014). Kaçkar Dağı’nda bakı faktörünün glasiyal ve periglasiyal topografya gelişimi üzerindeki etkisi. Türk Coğrafya Dergisi, 0(54), 1–13. https://izlik.org/JA58LB98JG
- Chicco, D., Warrens, M. J., & Jurman, G. (2021). The coefficient of determination R-squared is more informative than SMAPE, MAE, MAPE, MSE and RMSE in regression analysis evaluation. PeerJ Computer Science, 7, e623. https://doi.org/10.7717/peerj-cs.623
- Choi, J., Engel, B. A., & Chung, H. W. (2002). Daily streamrunoff modelling and assessment based on the curve‐number technique. Hydrological Processes, 16(16), 3131–3150. https://doi.org/10.1002/hyp.1092
- CORINE Land Cover (CLC). (2012). https://land.copernicus.eu/en/products/corine-land-cover/clc-2012 Copernicus Land Monitoring Service.
- De Myttenaere, A., Golden, B., Le Grand, B., & Rossi, F. (2016). Mean Absolute Percentage Error for regression models. Neurocomputing, 192, 38–48. https://doi.org/10.1016/j.neucom.2015.12.114
- Deshmukh, D. S., Chaube, U. C., Ekube Hailu, A., Aberra Gudeta, D., & Tegene Kassa, M. (2013). Estimation and comparision of curve numbers based on dynamic land use land cover change, observed rainfall-runoff data and land slope. Journal of Hydrology, 492, 89–101. https://doi.org/10.1016/j.jhydrol.2013.04.001