Special Issue "Soil Conservation Service Curve Number (SCS-CN) Method Current Applications, Remaining Challenges, and Future Perspectives"

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydrology".

Deadline for manuscript submissions: closed (30 September 2020).

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Special Issue Editor

Dr. Konstantinos X. Soulis
E-Mail Website
Guest Editor
Department of Natural Resources Management and Agricultural Engineering, Agricultural University of Athens, Iera Odos 75, 11855, Athens, Greece.
Interests: hydrology; environmental hydrology; hydrological modeling; hydrometry; WRM; irrigation; irrigation water management; soil hydrology; geographical information systems (GIS)
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Special Issue Information

Dear Colleagues,

Predicting runoff in ungauged or poorly gauged watersheds is one of the key problems in applied hydrology. Thus, simple methods for runoff estimation are particularly important in hydrologic applications, such as flood design or water balance calculation models. Probably, the most well-documented and, at the same time, simple conceptual method for predicting runoff is the Soil Conservation Service curve number (SCS-CN) method. This method was originally developed by the U.S. Department of Agriculture, Soil Conservation Service to predict direct runoff volumes for given rainfall events and mainly for the evaluation of storm runoff in small agricultural watersheds. It was first published in 1956 in the National Engineering Handbook Section 4—Hydrology. Due to its simplicity and its extensive documentation, it soon became one of the most popular techniques among engineers and practitioners and is widely used in many hydrological applications. The main reasons are that it is a very simple but well-established method, it features easy to obtain and well-documented environmental inputs, and it accounts for many of the factors affecting runoff generation, incorporating them in a single CN parameter. The SCS-CN method has been adopted for various regions and for various land uses and climatic conditions. Furthermore, beyond its original scope for the evaluation of storm runoff, it has become an integral part of more complex, long-term watershed models. Nevertheless, the method is receiving ever-increasing attention in the hydrologic literature, with many contributions that enhance the current understanding and widen even further its range of applicability.

However, after many years of constant development and research, critical issues are still remaining, such as the following:

  • Improving the SCS-CN method runoff predictions and at the same time preserving its current level of simplicity;
  • Moving towards a unique generally accepted procedure for CN determination from rainfall runoff data and consideration of spatial variability in CN estimation;
  • Investigation of the gains and the implications of altered initial abstraction ratios;
  • Investigation of the scale dependency of CN values (Are CNs obtained at different scales (plot scale, catchment scale, etc.) compatible?);
  • Investigating the implications of using SCS-CN in continuous hydrological models. Implementation of various soil moisture accounting systems and CN;
  • Extending and adopting the existing CN documentation in a broader range of regions, land uses, and climatic conditions;
  • Utilizing novel modeling, geoinformation systems, and remote sensing techniques to improve the method’s performance and efficiency.

Accordingly, the aim of this Special Issue is to present the latest developments in SCS-CN methodology, including, but not limited to, novel applications, theoretical and conceptual studies broadening the current understanding, studies extending the method’s application in other geographical regions or other scientific fields, substantial evaluation studies, and ultimately key advancements towards addressing the remaining challenges.

Dr. Konstantinos Soulis
Guest Editor

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Keywords

  • Soil Conservation Service curve number (SCS-CN) method
  • Natural Resources Conservation Service curve number (NRCS-CN) method
  • Rainfall–runoff modeling
  • Hydrological modeling
  • Hydrological response
  • Direct runoff
  • CN determination.

Published Papers (9 papers)

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Editorial

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Editorial
Soil Conservation Service Curve Number (SCS-CN) Method: Current Applications, Remaining Challenges, and Future Perspectives
Water 2021, 13(2), 192; https://doi.org/10.3390/w13020192 - 14 Jan 2021
Cited by 1 | Viewed by 572
Abstract
Predicting runoff in ungauged or poorly gauged watersheds is one of the key problems in applied hydrology [...] Full article

Research

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Article
Application of the SCS–CN Method to the Hancheon Basin on the Volcanic Jeju Island, Korea
Water 2020, 12(12), 3350; https://doi.org/10.3390/w12123350 - 29 Nov 2020
Cited by 1 | Viewed by 570
Abstract
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 [...] Read more.
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. Full article
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Article
Improvement of SCS-CN Initial Abstraction Coefficient in the Czech Republic: A Study of Five Catchments
Water 2020, 12(7), 1964; https://doi.org/10.3390/w12071964 - 10 Jul 2020
Cited by 6 | Viewed by 894
Abstract
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 [...] Read more.
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. Full article
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Article
A Pragmatic Slope-Adjusted Curve Number Model to Reduce Uncertainty in Predicting Flood Runoff from Steep Watersheds
Water 2020, 12(5), 1469; https://doi.org/10.3390/w12051469 - 21 May 2020
Cited by 7 | Viewed by 951
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 (λ = 0.2), and because choosing the most suitable watershed CN values is still [...] Read more.
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 (λ = 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 λ and watershed slope factor effect in estimating runoff. Our proposed slope-adjusted CN (CNIIα) 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 λ = 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. Full article
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Article
Possibility of Using Selected Rainfall-Runoff Models for Determining the Design Hydrograph in Mountainous Catchments: A Case Study in Poland
Water 2020, 12(5), 1450; https://doi.org/10.3390/w12051450 - 20 May 2020
Cited by 6 | Viewed by 907
Abstract
The aim of the study was to analyze the possibility of using selected rainfall-runoff models to determine the design hydrograph and the related peak flow in a mountainous catchment. The basis for the study was the observed series of hydrometeorological data for the [...] Read more.
The aim of the study was to analyze the possibility of using selected rainfall-runoff models to determine the design hydrograph and the related peak flow in a mountainous catchment. The basis for the study was the observed series of hydrometeorological data for the Grajcarek catchment area (Poland) for the years 1981–2014. The analysis was carried out in the following stages: verification of hydrometeorological data; determination of the design rainfall; and determination of runoff hydrographs with the following rainfall-runoff models: Snyder, NRCS-UH, and EBA4SUB. The conducted research allowed the conclusion that the EBA4SUB model may be an alternative to other models in determining the design hydrograph in ungauged mountainous catchments. This is evidenced by the lower values of relative errors in the estimation of peak flows with an assumed frequency for the EBA4SUB model, as compared to Snyder and NRCS-UH. Full article
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Article
Using SCS-CN and Earth Observation for the Comparative Assessment of the Hydrological Effect of Gradual and Abrupt Spatiotemporal Land Cover Changes
Water 2020, 12(5), 1386; https://doi.org/10.3390/w12051386 - 13 May 2020
Cited by 12 | Viewed by 1813
Abstract
In this study a comparative assessment of the impacts of urbanization and of forest fires as well as their combined effect on runoff response is investigated using earth observation and the Soil Conservation Service Curve Number (SCS-CN) direct runoff estimation method in a [...] Read more.
In this study a comparative assessment of the impacts of urbanization and of forest fires as well as their combined effect on runoff response is investigated using earth observation and the Soil Conservation Service Curve Number (SCS-CN) direct runoff estimation method in a Mediterranean peri-urban watershed in Attica, Greece. The study area underwent a significant population increase and a rapid increase of urban land uses, especially from the 1980s to the early 2000s. The urbanization process in the studied watershed caused a considerable increase of direct runoff response. A key observation of this study is that the impact of forest fires is much more prominent in rural watersheds than in urbanized watersheds. However, the increments of runoff response are important during the postfire conditions in all cases. Generally, runoff increments due to urbanization seem to be higher than runoff increments due to forest fires affecting the associated hydrological risks. It should also be considered that the effect of urbanization is lasting, and therefore, the possibility of an intense storm to take place is higher than in the case of forest fires that have an abrupt but temporal impact on runoff response. It should be noted though that the combined effect of urbanization and forest fires results in even higher runoff responses. The SCS-CN method, proved to be a valuable tool in this study, allowing the determination of the direct runoff response for each soil, land cover and land management complex in a simple but efficient way. The analysis of the evolution of the urbanization process and the runoff response in the studied watershed may provide a better insight for the design and implementation of flood risk management plans. Full article
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Article
An Improved SCS-CN Method Incorporating Slope, Soil Moisture, and Storm Duration Factors for Runoff Prediction
Water 2020, 12(5), 1335; https://doi.org/10.3390/w12051335 - 08 May 2020
Cited by 4 | Viewed by 1259
Abstract
Soil Conservation Service Curve Number (SCS-CN) is a popular surface runoff prediction method because it is simple in principle, convenient in application, and easy to accept. However, the method still has several limitations, such as lack of a land slope factor, discounting the [...] Read more.
Soil Conservation Service Curve Number (SCS-CN) is a popular surface runoff prediction method because it is simple in principle, convenient in application, and easy to accept. However, the method still has several limitations, such as lack of a land slope factor, discounting the storm duration, and the absence of guidance on antecedent moisture conditions. In this study, an equation was developed to improve the SCS-CN method by combining the CN value with the tabulated CN2 value and three introduced factors (slope gradient, soil moisture, and storm duration). The proposed method was tested for calibration and validation with a dataset from three runoff plots in a watershed of the Loess Plateau. The results showed the model efficiencies of the proposed method were improved to 80.58% and 80.44% during the calibration and validation period, respectively, which was better than the standard SCS-CN and the other two modified SCS-CN methods where only a single factor of soil moisture or slope gradient was considered, respectively. Using the parameters calibrated and validated by dataset of the initial three runoff plots, the proposed method was then applied to runoff estimation of the remaining three runoff plots in another watershed. The proposed method reduced the root-mean-square error between the observed and estimated runoff values from 5.53 to 2.01 mm. Furthermore, the parameters of soil moisture (b1 and b2) is the most sensitive, followed by parameters in storm duration (c) and slope equations (a1 and a2), and the least sensitive parameter is the initial abstraction ratio λ on the basis of the proposed method sensitivity analysis. Conclusions can be drawn from the above results that the proposed method incorporating the three factors in the SCS method may estimate runoff more accurately in the Loess Plateau of China. Full article
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Article
Variability of the Initial Abstraction Ratio in an Urban and an Agroforested Catchment
Water 2020, 12(2), 415; https://doi.org/10.3390/w12020415 - 04 Feb 2020
Cited by 7 | Viewed by 967
Abstract
The Curve Number method is one of the most commonly applied methods to describe the relationship between the direct runoff and storm rainfall depth. Due to its popularity and simplicity, it has been studied extensively. Less attention has been given to the dimensionless [...] Read more.
The Curve Number method is one of the most commonly applied methods to describe the relationship between the direct runoff and storm rainfall depth. Due to its popularity and simplicity, it has been studied extensively. Less attention has been given to the dimensionless initial abstraction ratio, which is crucial for an accurate direct runoff estimation with the Curve Number. This ratio is most often assumed to be equal to 0.20, which was originally proposed by the method’s developers. In this work, storm events recorded in the years 2009–2017 in two small Polish catchments of different land use types (urban and agroforested) were analyzed for variability in the initial abstraction ratio across events, seasons, and land use type. Our results showed that: (i) estimated initial abstraction ratios varied between storm events and seasons, and were most often lower than the original value of 0.20; (ii) for large events, the initial abstraction ratio in the catchment approaches a constant value after the rainfall depth exceeds a certain threshold value. Thus, when using the Soil Conservation Service-Curve Number (SCS-CN) method, the initial abstraction ratio should be locally verified, and the conditions for the application of the suggested value of 0.20 should be established. Full article
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Article
A Calibrated, Watershed-Specific SCS-CN Method: Application to Wangjiaqiao Watershed in the Three Gorges Area, China
Water 2020, 12(1), 60; https://doi.org/10.3390/w12010060 - 22 Dec 2019
Cited by 8 | Viewed by 1270
Abstract
The Soil Conservation Service curve number ( S C S-C N) method is one of the most popular methods used to compute runoff amount due to its few input parameters. However, recent studies challenged the inconsistent runoff results obtained by the method which set the initial abstraction ratio λ as 0.20. This paper developed a watershed-specific S C S-C N calibration method using non-parametric inferential statistics with rainfall–runoff data pairs. The proposed method first analyzed the data and generated confidence intervals to determine the optimum values for S C S- C N model calibration. Subsequently, the runoff depth and curve number were calculated. The proposed method outperformed the runoff prediction accuracy of the asymptotic curve number fitting method, linear regression model and the conventional S C S-C N model with the highest Nash–Sutcliffe index value of 0.825, the lowest residual sum of squares value of 133.04 and the lowest prediction error. It reduced the residual sum of squares by 66% and the model prediction errors by 96% when compared to the conventional S C S-C N model. The estimated curve number was 72.28, with the confidence interval ranging from 62.06 to 78.00 at a 0.01 confidence interval level for the Wangjiaqiao watershed in China. Full article
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