Effects of Initial Abstraction Ratio in SCS-CN Method on Modeling the Impacts of Urbanization on Peak Flows

Abstract. Predicting event runoff and soil loss under different land covers is essential to quantitatively evaluate the hydrological responses of vegetation restoration in the Loess Plateau of China. The Soil Conservation Service Curve Number (SCS-CN) and Revised Universal Soil Loss Equation (RUSLE) models are widely used in this region to this end. This study incorporated antecedent moisture condition (AMC) in runoff production and initial abstraction of the SCS-CN model, and considered the direct effect of runoff on event soil loss by adopting a rainfall-runoff erosivity factor in the RUSLE model. The modified SCS-CN and RUSLE models were coupled to link rainfall-runoff-erosion modeling. The effects of AMC, slope gradient and initial abstraction ratio on curve number of SCS-CN, as well as those of vegetation cover on cover-management factor of RUSLE were also considered. Three runoff plot groups covered by sparse young trees, native shrubs and dense tussock, respectively, were established in the Yangjuangou catchment of Loess Plateau. Rainfall, runoff and soil loss were monitored during the rainy season in 2008–2011 to test the applicability of the proposed approach. The original SCS-CN model significantly underestimated the event runoff, especially for the rainfall events that have large 5-day antecedent precipitation, whereas the modified SCS-CN model could predict event runoff well with Nash-Sutcliffe model efficiency (EF) over 0.85. The original RUSLE model overestimated low values of measured soil loss and under-predicted the high values with EF only about 0.30. In contrast to it, the prediction accuracy of the modified RUSLE model improved satisfactorily with EF over 0.70. Our results indicated that the AMC should be explicitly incorporated in runoff production, and direct consideration of runoff should be included in predicting event soil loss. Coupling the modified SCS-CN and RUSLE models appeared to be appropriate for runoff and soil loss simulation at plot scale in the Loess Plateau. The limitations and future study scopes of the proposed models were also indicated.

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Application of the SCS–CN Method to the Hancheon Basin on the Volcanic Jeju Island, Korea

Water ◽

10.3390/w12123350 ◽

2020 ◽

Vol 12 (12) ◽

pp. 3350

Author(s):

Minseok Kang ◽

Chulsang Yoo

Keyword(s):

Negative Correlation ◽

The Other ◽

Jeju Island ◽

Antecedent Soil Moisture ◽

Moisture Condition ◽

Soil Moisture Condition ◽

Rainfall Events ◽

Initial Abstraction ◽

Other Hand ◽

Scs Cn

This study investigates three issues regarding the application of the SCS–CN (Soil Conservation Service–Curve Number) method to a basin on the volcanic Jeju Island, Korea. The first issue is the possible relation between the initial abstraction and the maximum potential retention. The second is the determination of the maximum potential retention, which is also closely related to the estimation of CN. The third issue is the effect of the antecedent soil moisture condition (AMC) on the initial abstraction, maximum potential retention and CN. All of these issues are dealt with based on the analysis of several rainfall events observed in the Hancheon basin, a typical basin on Jeju Island. In summary, the results are that, firstly, estimates of initial abstraction, ratio λ, maximum potential retention, and CN were all found to be consistent with the SCS–CN model structure. That is, CN and the maximum potential retention showed a strong negative correlation, and the ratio λ and the maximum potential retention also showed a rather weak negative correlation. On the other hand, a significant positive correlation was found between CN and the ratio λ. Second, in the case where the accumulated number of days is four or five, the effect of antecedent precipitation amount is clear. The antecedent five-day rainfall amount for the AMC-III condition is higher than 400 mm, compared to the AMC-I condition of less than 100 mm. Third, an inverse proportional relationship is found between the AMC and the maximum potential retention. On the other hand, a clear linear proportional relation is found between the AMC and CN. Finally, the maximum potential retention for the Hancheon basin is around 200 mm, with the corresponding CN being around 65. The ratio between the initial abstraction and the maximum potential retention is around 0.3. Even though these results are derived by analyzing a limited number of rainfall events, they are believed to properly consider the soil characteristics of Jeju Island.

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Determination of SCS-CN initial abstraction ratio in a catchment prone to flash floods

Pollack Periodica ◽

10.1556/606.2020.15.1.11 ◽

2020 ◽

Vol 15 (1) ◽

pp. 112-123 ◽

Cited By ~ 1

Author(s):

Martin Caletka ◽

Monika Šulc Michalková

Keyword(s):

Surface Runoff ◽

Soil Conservation ◽

Curve Number ◽

Flash Floods ◽

Soil Conservation Service ◽

Initial Abstraction ◽

Service Curve ◽

Scs Cn ◽

Proper Setting

Abstract The soil conservation service - curve number method is a globally used approach to simulations of surface runoff for its simplicity and applicability. Nevertheless, relevant simulations require proper setting of the model's components. This work focuses on optimization of initial abstraction ratio λ in the Husí potok sub-catchments in Czech Republic. Due to favorable morphology, the watershed is prone to flash floods and accurate modeling of surface runoff is of high interest. The analysis was conducted using pairs of discharge and rainfall measurements. The results outline that the traditional value λ= 0.2 is too high in this watershed and should be reduced.

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Improvement of SCS-CN Initial Abstraction Coefficient in the Czech Republic: A Study of Five Catchments

Water ◽

10.3390/w12071964 ◽

2020 ◽

Vol 12 (7) ◽

pp. 1964 ◽

Cited By ~ 2

Author(s):

Martin Caletka ◽

Monika Šulc Michalková ◽

Petr Karásek ◽

Petr Fučík

Keyword(s):

Czech Republic ◽

Model Fitting ◽

Principal Component ◽

Event Analysis ◽

Rainfall Runoff ◽

The Czech Republic ◽

Direct Runoff ◽

Initial Abstraction ◽

Universal Applicability ◽

Scs Cn

The SCS-CN method is a globally known procedure used primarily for direct-runoff estimates. It also is integrated in many modelling applications. However, the method was developed in specific geographical conditions, often making its universal applicability problematic. This study aims to determine appropriate values of initial abstraction coefficients λ and curve numbers (CNs), based on measured data in five experimental catchments in the Czech Republic, well representing the physiographic conditions in Central Europe, to improve direct-runoff estimates. Captured rainfall-runoff events were split into calibration and validation datasets. The calibration dataset was analysed by applying three approaches: (1) Modifying λ, both discrete and interpolated, using the tabulated CN values; (2) event analysis based on accumulated rainfall depth at the moment runoff starts to form; and (3) model fitting, an iterative procedure, to search for a pair of λ, S (CN, respectively). To assess individual rainfall characteristics’ possible influence, a principal component analysis and cluster analysis were conducted. The results indicate that the CN method in its traditional arrangement is not very applicable in the five experimental catchments and demands corresponding modifications to determine λ and CN (or S, respectively). Both λ and CN should be viewed as flexible, catchment-dependent (regional) parameters, rather than fixed values. The acquired findings show the need for a systematic yet site-specific revision of the traditional CN method, which may help to improve the accuracy of CN-based rainfall-runoff modelling.

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Variation of runoff source areas under different soil wetness conditions in a semi-arid mountain region, Iran

Water SA ◽

10.4314/wsa.v44i2.14 ◽

2018 ◽

Vol 44 (2 April) ◽

Cited By ~ 2

Author(s):

Hassan Rezaei-Sadr ◽

Golfam Sharifi

Keyword(s):

Mountain Region ◽

Soil Conditions ◽

Original Form ◽

Catchment Management ◽

Soil Water Retention ◽

Study Region ◽

Source Areas ◽

Initial Abstraction ◽

Soil Wetness ◽

Scs Cn

Runoff source areas can serve as focus areas for water quality monitoring and catchment management. In this study, a conceptual form of the Soil Conservation Service Curve Number method (SCS-CN) is used to define variable-source runoff areas in a meso-scale catchment in the Zagros mountain region, southwest of Iran. The analysis indicates that for the average and dry antecedent soil wetness (the dominant soil moisture conditions), the original SCS-CN criterion that assumes the initial abstraction of rainfall to be equal to 20% of the maximum potential soil water retention fails to predict runoff source areas correctly, suggesting the ineffectiveness of the original form of the method for the study region. However, the determination of the initial abstraction based on hydrograph-hyetograph matching technique provides reasonable results, outperforms the original form of the SCS-CN based method and, more importantly, highlights the significance of having localized rainfall and runoff data. Under wet soil conditions, both techniques provide similar results; the robustness of the SCS-CN based method is thus supported only for wet soil conditions.

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Improved SCS-CN Model Incorporating Storm Duration and Rainfall-based Initial Abstraction for Runoff Estimation

10.20944/preprints202104.0352.v1 ◽

2021 ◽

Author(s):

Ravindra Kumar Verma ◽

Sangeeta Verma ◽

Nand Kishor Sharma ◽

Surendra Kumar Mishra ◽

Ashish Pandey

Keyword(s):

Root Mean Square Error ◽

Mean Square Error ◽

Root Mean Square ◽

Surface Runoff ◽

Mean Square ◽

Rainfall Events ◽

Initial Abstraction ◽

Statistical Measures ◽

Storm Duration ◽

Scs Cn

The need of incorporating storm intensity or duration in Soil Conservation Service Curve Number (SCS-CN) methodology for improved direct surface runoff estimation for a watershed has been highlighted by many engineers and hydrologists since long and despite this fact, it is still poorly explored. Therefore, this study aims to present storm duration-based improved SCS-CN models for estimating more accurate direct surface runoff from rainfall events. The accuracy and consistency of improved models are tested on a large rainfall-runoff dataset (18,660 rainfall events) derived from 39 watersheds in the USDA-ARS. Furthermore, the quantitative model’s performance is also evaluated employing six widely accepted statistical measures viz. root mean square error (RMSE), mean absolute error (MAE), normalized root mean square error (NRMSE), Nash-Sutcliffe efficiency (NSE), percent bias (PBIAS), observations standard deviation ratio (RSR), and several grading criteria. These models are compared with the original SCS-CN model (M1) and its simple form (M2) with traditionally fixed initial abstraction ratio (λ) as 0.2. The resulting lowest values of RMSE, NRMSE, MAE, NSE, PBIAS and highest values of RSR and ranking grading system (RGS) for the proposed models (M3-M5) reveal that their performance is better than M1 and M2 models. The proposed M5 model incorporating both storm duration and varying initial abstraction (Ia) as a certain percentage of rainfall, performed the best followed by M3 incorporating only storm duration. According to RGS, M5 also ranked first with the highest marks (195) followed by M3 (140). Due to high accuracy in predicted runoff, M5 can be recommended for both small and large watersheds as it overcomes the following issues: fixed λ (=0.2), assumption of constant rainfall intensity (time-independent), fixation of Ia at 2% of rainfall and applicability to only small watersheds, restricting the application of original SCS-CN and its modified versions.

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Technical Note: Determination of the SCS initial abstraction ratio in an experimental watershed in Greece

Hydrology and Earth System Sciences ◽

10.5194/hess-11-1825-2007 ◽

2007 ◽

Vol 11 (6) ◽

pp. 1825-1829 ◽

Cited By ~ 86

Author(s):

E. A. Baltas ◽

N. A. Dervos ◽

M. A. Mimikou

Keyword(s):

Spatial Distribution ◽

Technical Note ◽

Rainfall Runoff ◽

Average Ratio ◽

Initial Abstraction ◽

The Difference ◽

Geological Formations ◽

Scs Cn ◽

Runoff Events

Abstract. The present study was conducted in an experimental watershed in Attica, Greece, using observed rainfall/runoff events. The objective of the study was the determination of the initial abstraction ratio of the watershed. The average ratio (Ia/S) of the entire watershed was equal to 0.014. The corresponding ratio at a subwatershed was 0.037. The difference was attributed to the different spatial distribution of landuses and geological formations at the extent of the watershed. Both of the determined ratios are close to the ratio value of 0.05 that has been suggested from many studies for the improvement of the SCS-CN method.

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