scholarly journals Initial abstraction ratio and Curve Number estimation using rainfall and runoff data from a tropical watershed

RBRH ◽  
2019 ◽  
Vol 24 ◽  
Author(s):  
Luiz Claudio Galvão do Valle Junior ◽  
Dulce Buchala Bicca Rodrigues ◽  
Paulo Tarso Sanches de Oliveira
Keyword(s):  
Conversion Factor ◽  
Poor Performance ◽  
Curve Number ◽  
Storm Events ◽  
Rainfall Runoff ◽  
Initial Abstraction ◽  
Rainfall Depth ◽  
Standard Value ◽  
Tropical Watershed ◽  
Runoff Events

ABSTRACT The Curve Number (CN) method is extensively used for predict surface runoff from storm events. However, remain some uncertainties in the method, such as in the use of an initial abstraction (λ) standard value of 0.2 and on the choice of the most suitable CN values. Here, we compute λ and CN values using rainfall and runoff data to a rural basin located in Midwestern Brazil. We used 30 observed rainfall-runoff events with rainfall depth greater than 25 mm to derive associated CN values using five statistical methods. We noted λ values ranging from 0.005 to 0.455, with a median of 0.045, suggesting the use of λ = 0.05 instead of 0.2. We found a S0.2 to S0.05 conversion factor of 2.865. We also found negative values of Nash-Sutcliffe Efficiency (to the estimated and observed runoff). Therefore, our findings indicated that the CN method was not suitable to estimate runoff in the studied basin. This poor performance suggests that the runoff mechanisms in the studied area are dominated by subsurface stormflow.

scholarly journals Variability of the Initial Abstraction Ratio in an Urban and an Agroforested Catchment

Water ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 415 ◽  
Author(s):  
Adam Krajewski ◽  
Anna E. Sikorska-Senoner ◽  
Agnieszka Hejduk ◽  
Leszek Hejduk
Keyword(s):  
Land Use ◽  
Curve Number ◽  
Threshold Value ◽  
Storm Events ◽  
Direct Runoff ◽  
Initial Abstraction ◽  
Land Use Types ◽  
Rainfall Depth ◽  
Storm Rainfall ◽  
Service Curve

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.

scholarly journals Determination of Curve Number for snowmelt-runoff floods in a small catchment

2015 ◽  
Vol 370 ◽  
pp. 167-170 ◽  
Author(s):  
L. Hejduk ◽  
A. Hejduk ◽  
K. Banasik
Keyword(s):  
Soil Conservation ◽  
Curve Number ◽  
Rainfall Runoff ◽  
Snowmelt Runoff ◽  
Ungauged Catchments ◽  
Department Of Agriculture ◽  
Small Catchment ◽  
Rainfall Depth ◽  
Runoff Events

Abstract. One of the widely used methods for predicting flood runoff depth from ungauged catchments is the curve number (CN) method, developed by Soil Conservation Service (SCS) of US Department of Agriculture. The CN parameter can be computed directly from recorded rainfall depths and direct runoff volumes in case of existing data. In presented investigations, the CN parameter has been computed for snowmelt-runoff events based on snowmelt and rainfall measurements. All required data has been gathered for a small agricultural catchment (A = 23.4 km2) of Zagożdżonka river, located in Central Poland. The CN number received from 28 snowmelt-runoff events has been compared with CN computed from rainfall-runoff events for the same catchment. The CN parameter, estimated empirically varies from 64.0 to 94.8. The relation between CN and snowmelt depth was investigated in a similar procedure to relation between CN and rainfall depth.

scholarly journals Statistical and Type II Error Assessment of a Runoff Predictive Model in Peninsula Malaysia

Mathematics ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 812
Author(s):  
Lloyd Ling ◽  
Zulkifli Yusop ◽  
Joan Lucille Ling
Keyword(s):  
Curve Number ◽  
Technological Advancement ◽  
Type Ii ◽  
Error Assessment ◽  
Type Ii Error ◽  
Storm Events ◽  
Rainfall Runoff ◽  
Scs Model ◽  
Rainfall Depth ◽  
Runoff Model

Flood related disasters continue to threaten mankind despite preventative efforts in technological advancement. Since 1954, the Soil Conservation Services (SCS) Curve Number (CN0.2) rainfall-runoff model has been widely used but reportedly produced inconsistent results in field studies worldwide. As such, this article presents methodology to reassess the validity of the model and perform model calibration with inferential statistics. A closed form equation was solved to narrow previous research gap with a derived 3D runoff difference model for type II error assessment. Under this study, the SCS runoff model is statistically insignificant (alpha = 0.01) without calibration. Curve Number CN0.2 = 72.58 for Peninsula Malaysia with a 99% confidence interval range of 67 to 76. Within these CN0.2 areas, SCS model underpredicts runoff amounts when the rainfall depth of a storm is < 70 mm. Its overprediction tendency worsens in cases involving larger storm events. For areas of 1 km2, it underpredicted runoff amount the most (2.4 million liters) at CN0.2 = 67 and the rainfall depth of 55 mm while it nearly overpredicted runoff amount by 25 million liters when the storm depth reached 430 mm in Peninsula Malaysia. The SCS model must be validated with rainfall-runoff datasets prior to its adoption for runoff prediction in any part of the world. SCS practitioners are encouraged to adopt the general formulae from this article to derive assessment models and equations for their studies.

scholarly journals Research on the initial abstraction – storage ratio and its effect on hydrograph simulation at a watershed in Greece

2007 ◽  
Vol 4 (4) ◽  
pp. 2169-2204 ◽  
Author(s):  
E. A. Baltas ◽  
N. A. Dervos ◽  
M. A. Mimikou
Keyword(s):  
Empirical Equation ◽  
Storm Events ◽  
Rainfall Runoff ◽  
Unit Hydrograph ◽  
Time To Peak ◽  
Initial Abstraction ◽  
Time Period ◽  
The Difference ◽  
Runoff Events

Abstract. The present research was conducted at an experimental watershed in the prefecture of Attica, Greece, using the selected observed rainfall-runoff events from a four-year time period. The objectives of this study were two: The first was the determination of the initial abstraction Ia – watershed storage S ratio. The average ratio (Ia/S) 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 at the extent of the watershed. The second objective of the study was to examine the effect of the SCS empirical equation on hydrograph simulation. This was investigated through the comparison between the observed and two different simulated hydrographs at each one out of eighteen selected storm events. The simulated hydrographs were calculated by applying on the watershed's unit hydrograph two time distributions of excess rainfall that derived from the SCS method using two different approaches. In the first approach, the initial abstraction was determined from the observed rainfall-runoff data, while in the second, it was calculated using the SCS empirical equation. It was found that the SCS empirical equation estimates greater amount of initial abstraction and leads to the delayed start of the excess rainfall and the simulated runoff. This resulted in the overestimation of the peak flow rate and the time to peak at the majority of the storm events.

scholarly journals Coupling the modified SCS-CN and RUSLE models to simulate hydrological effects of restoring vegetation in the Loess Plateau of China

2012 ◽  
Vol 9 (3) ◽  
pp. 4193-4233 ◽  
Author(s):  
G. Y. Gao ◽  
B. J. Fu ◽  
Y. H. Lü ◽  
Y. Liu ◽  
S. Wang ◽  
...  
Keyword(s):  
Loess Plateau ◽  
Soil Loss ◽  
Curve Number ◽  
Rainfall Runoff ◽  
The Loess Plateau ◽  
Rusle Model ◽  
Initial Abstraction ◽  
Runoff And Soil Loss ◽  
Scs Cn ◽  
Runoff Production

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.

HYDROLOGICAL MODELLING OF UNGAUGED ARID VOLCANIC ENVIRONMENTS AT UPPER BATHAN CATCHMENT, MADINAH, SAUDI ARABIA

2016 ◽  
Vol 78 (9-4) ◽  
Author(s):  
Fahad Alahmadi ◽  
Norhan Abd Rahman ◽  
Zulkifli Yusop
Keyword(s):  
Saudi Arabia ◽  
Land Cover ◽  
Soil Conservation ◽  
Daily Rainfall ◽  
Curve Number ◽  
Hydrological Modelling ◽  
Time Interval ◽  
Storm Events ◽  
Ungauged Catchments ◽  
Rainfall Depth

Hydrological modelling of ungauged catchments is still a challenging task especially in arid regions with a unique land cover features such as highly fracture volcanic basalt rocks. In this study, upper Bathan catchment (103 km2) in Madinah, western of Saudi Arabia is selected. The aim of this paper is to simulate the hydrological responses of volcanic catchment to daily design storm events. The weighted areal average of two daily design rainfall depth scenarios are computed, which are 50 years and 100 years return period and correspondent predicted rainfall are 80.6 mm and 94.1 mm, respectively. SCS Type II temporal synthetic distribution of daily rainfall is selected to disaggregate the daily rainfall into smaller time interval. Excess rainfall is computed using Soil Conservation Services Curve Number (SCS-CN) method based on Land Cover and Land Use (LCLU) and hydrological soil groups (HSG) maps, while direct runoff hydrograph is developed using Soil Conservation Services dimensionless unit hydrograph (SCS-UH) method using lag time equation. HEC-HMS software is used, and it showed that the runoff volumes of the two rainfall scenarios are 50% and 54% of the total rainfall depth, and the peak discharges are 123 m3/sec and 158 m3/sec. This study provided an indication of the hydrograph characteristics of basaltic catchments and the result of this paper can be used for further flood studies in arid ungauged volcanic catchments.  

scholarly journals Curve Number Estimation for a Small Urban Catchment from Recorded Rainfall-Runoff Events

2014 ◽  
Vol 40 (3) ◽  
pp. 75-86 ◽  
Author(s):  
Kazimierz Banasik ◽  
Adam Krajewski ◽  
Anna Sikorska ◽  
Leszek Hejduk
Keyword(s):  
Urban Areas ◽  
Land Use Changes ◽  
Low Impact Development ◽  
Curve Number ◽  
Rainfall Runoff ◽  
Ungauged Catchments ◽  
Department Of Agriculture ◽  
Urban Catchment ◽  
Urban Catchments ◽  
Runoff Events

Abstract Runoff estimation is a key component in various hydrological considerations. Estimation of storm runoff is especially important for the effective design of hydraulic and road structures, for the flood flow management, as well as for the analysis of land use changes, i.e. urbanization or low impact development of urban areas. The curve number (CN) method, developed by Soil Conservation Service (SCS) of the U.S. Department of Agriculture for predicting the flood runoff depth from ungauged catchments, has been in continuous use for ca. 60 years. This method has not been extensively tested in Poland, especially in small urban catchments, because of lack of data. In this study, 39 rainfall-runoff events, collected during four years (2009–2012) in a small (A=28.7 km2), urban catchment of Służew Creek in southwest part of Warsaw were used, with the aim of determining the CNs and to check its applicability to ungauged urban areas. The parameters CN, estimated empirically, vary from 65.1 to 95.0, decreasing with rainfall size and, when sorted rainfall and runoff separately, reaching the value from 67 to 74 for large rainfall events.

scholarly journals Adequacy of methodologies for determining SCS / CN in a watershed with characteristics of the Pampa biome

2021 ◽  
Vol 16 (4) ◽  
pp. 1
Author(s):  
Zandra Almeida da Cunha ◽  
Samuel Beskow ◽  
Maíra Martim de Moura ◽  
Tamara Leitzke Caldeira Beskow ◽  
Carlos Rogério de Mello
Keyword(s):  
Curve Number ◽  
Rainfall Runoff ◽  
Antecedent Moisture ◽  
Pampa Biome ◽  
Definition Of ◽  
Service Curve ◽  
The Impact ◽  
Runoff Events

The Soil Conservation Service Curve Number Model is a conceptual model intended for estimating effective rainfall (ER). This model is grounded in a parameter – referred to as Curve Number (CN), which is determined from information on the characteristics of the watershed. The Standard Method (M1) for determining the CN is based on soil and land-use tables; however, some authors have proposed alternative methodologies for defining the CN value from monitored rainfall-runoff events, such as those described by Hawkins (1993) (M2), Soulis and Valiantzas (2012) (M3), and Soulis and Valiantzas (2013) (M4). The objective of this study was to evaluate the impact of using these methods for determination of the CN parameter on the estimation of ER, taking as reference forty rainfall-runoff events monitored between 2015 and 2018 in the Cadeia River Watershed, which has characteristics of the Pampa biome. The different methods assessed for definition of the CN parameter resulted in contrasting performances with respect to the estimation of ER for CRW, as the following findings: i) M1 gave ER values with little reliability, mainly due to the classification of antecedent moisture content classes; ii) M3 provided the best results in determining ER, followed by M2; and iii) the ER values estimated according to M4 differed from those observed, mainly for events with lower rainfall depths.

CN-China: Revised runoff curve number by using rainfall-runoff events data in China

2020 ◽  
Vol 177 ◽  
pp. 115767 ◽  
Author(s):  
Huishu Lian ◽  
Haw Yen ◽  
Jr-Chuan Huang ◽  
Qingyu Feng ◽  
Lihuan Qin ◽  
...  
Keyword(s):  
Curve Number ◽  
Rainfall Runoff ◽  
Runoff Curve Number ◽  
Events Data ◽  
Runoff Events
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