Abstract
The aims of this paper are to (I) clarify some issues related to the popular rainfall–runoff SCS-CN (Soil Conservation Service Curve Number) methodology and (II) propose enhanced SCS-CN inspired models for simulation of long-duration (viz., bimonthly, monthly, seasonally, and annually) rainfall-generated runoff and compares its performance with the existing SCS-CN models and Mishra and Singh 1999 model. Issues of SCS-CN are: (a) both C (runoff coefficient) and CN (curve number) with P (rainfall) in contrast to that exhibited by field data, (b) F (infiltration) with Q (direct runoff), (c) Ia (initial abstraction) with S (potential maximum retention), and (d) CN that is also taken as an index of runoff potential. The performance of the proposed SCS-CN inspired models (M3-M8), the existing SCS-CN models (M1 and M2), Mishra and Singh 1999 model (M9), and a special case of M9 that hypothesizes that initial abstraction coefficient (λ) = 0 (M10) are tested using rainfall–runoff data of four different agro-climatic river basins in Ethiopia. The performance of the models is evaluated using three statistical criteria involving NSE, RSR, and PBIAS. The resulting high NSE values and lowest RSR and PBIAS for the proposed models reveal that proposed models performed better to different (majority) duration datasets than the existing models. Similarly, the proposed models, when employed to the observed datasets of different timescales, performed satisfactorily in both calibration and validation for all watersheds, underlining the efficacy of the proposed models in field applications.
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Data availability
Data used during the study are available from the corresponding author by request and with permission of the National Meteorological Agency of Ethiopia and the Ministry of Water, Irrigation and Electricity of Ethiopia.
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The authors express their thanks to the National Meteorological Agency of Ethiopia (NMAoE) and the Ministry of Water, Irrigation and Electricity of Ethiopia (MoWIE) for providing the climate and hydrological data respectively.
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Communicated by Dr. Michael Nones (CO-EDITOR-IN-CHIEF).
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Aragaw, H.M., Mishra, S.K. Clarification of issues and long-duration hydrologic simulation SCS-CN-based proxy modelling. Acta Geophys. 70, 729–756 (2022). https://doi.org/10.1007/s11600-022-00730-w
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DOI: https://doi.org/10.1007/s11600-022-00730-w