A Pragmatic Slope-Adjusted Curve Number Model to Reduce Uncertainty in Predicting Flood Runoff from Steep Watersheds
- Authors
- Ajmal, Muhammad; Waseem, Muhammad; Kim, Dongwook; Kim, Tae-Woong
- Issue Date
- May-2020
- Publisher
- MDPI
- Keywords
- initial abstraction coefficient; slope-adjusted curve number; rainfall; precise runoff; model accuracy
- Citation
- WATER, v.12, no.5
- Indexed
- SCIE
SCOPUS
- Journal Title
- WATER
- Volume
- 12
- Number
- 5
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/1139
- DOI
- 10.3390/w12051469
- ISSN
- 2073-4441
2073-4441
- Abstract
- The applicability of the curve number (CN) model to estimate runoff has been a conundrum for years, among other reasons, because it presumes an uncertain fixed initial abstraction coefficient (lambda = 0.2), and because choosing the most suitable watershed CN values is still debated across the globe. Furthermore, the model is widely applied beyond its originally intended purpose. Accordingly, there is a need for more case-specific adjustments of the CN values, especially in steep-slope watersheds with diverse natural environments. This study scrutinized the lambda and watershed slope factor effect in estimating runoff. Our proposed slope-adjusted CN (CNII alpha) model used data from 1779 rainstorm-runoff events from 39 watersheds on the Korean Peninsula (1402 for calibration and 377 for validation), with an average slope varying between 7.50% and 53.53%. To capture the agreement between the observed and estimated runoff, the original CN model and its seven variants were evaluated using the root mean square error (RMSE), Nash-Sutcliffe efficiency (NSE), percent bias (PB), and 1:1 plot. The overall lower RMSE, higher NSE, better PB values, and encouraging 1:1 plot demonstrated good agreement between the observed and estimated runoff by one of the proposed variants of the CN model. This plausible goodness-of-fit was possibly due to setting lambda = 0.01 instead of 0.2 or 0.05 and practically sound slope-adjusted CN values to our proposed modifications. For more realistic results, the effects of rainfall and other runoff-producing factors must be incorporated in CN value estimation to accurately reflect the watershed conditions.
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