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 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 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.

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 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.

scholarly journals Application of a continuous Rainfall-Runoff model to the basin of Kosynthos river using the hydrological software HEC-HMS

2014 ◽  
Vol 16 (1) ◽  
pp. 188-203 ◽  
Keyword(s):  
Soil Conservation ◽  
Curve Number ◽  
Hydrologic Model ◽  
Army Corps ◽  
Soil Conservation Service ◽  
Rainfall Runoff ◽  
Runoff Hydrograph ◽  
Rainfall Runoff Model ◽  
Runoff Model ◽  
Continuous Rainfall

<div> <h1 style="text-align: justify;"><span style="font-size:11px;"><span style="font-family:arial,helvetica,sans-serif;">In this paper, the application of a continuous rainfall-runoff model to the basin of Kosynthos River (district of Xanthi, Thrace, northeastern Greece), as well as the comparison of the computational runoff results with field discharge measurements are presented. The rainfall losses are estimated by the widely known Soil Conservation Service-Curve Number model, while the transformation of rainfall excess into direct runoff hydrograph is made by using the dimensionless unit hydrograph of Soil Conservation Service. The baseflow is computed by applying an exponential recession model. The routing of the total runoff hydrograph from the outlet of a sub-basin to the outlet of the whole basin is achieved by the Muskingum-Cunge model. The application of this complex hydrologic model was elaborated with the HEC-HMS 3.5 Hydrologic Modeling System of the U.S. Army Corps of Engineers. The results of the comparison between computed and measured discharge values are very satisfactory.</span></span></h1> </div> <p>&nbsp;</p>

scholarly journals SCS-CN parameter determination using rainfall-runoff data in heterogeneous watersheds – the two-CN system approach

2012 ◽  
Vol 16 (3) ◽  
pp. 1001-1015 ◽  
Author(s):  
K. X. Soulis ◽  
J. D. Valiantzas
Keyword(s):  
Land Cover ◽  
Spatial Variability ◽  
System Approach ◽  
Parameter Determination ◽  
Rainfall Runoff ◽  
Simple Method ◽  
Rainfall Depth ◽  
Natural Watersheds ◽  
Scs Cn

Abstract. The Soil Conservation Service Curve Number (SCS-CN) approach is widely used as a simple method for predicting direct runoff volume for a given rainfall event. The CN parameter values corresponding to various soil, land cover, and land management conditions can be selected from tables, but it is preferable to estimate the CN value from measured rainfall-runoff data if available. However, previous researchers indicated that the CN values calculated from measured rainfall-runoff data vary systematically with the rainfall depth. Hence, they suggested the determination of a single asymptotic CN value observed for very high rainfall depths to characterize the watersheds' runoff response. In this paper, the hypothesis that the observed correlation between the calculated CN value and the rainfall depth in a watershed reflects the effect of soils and land cover spatial variability on its hydrologic response is being tested. Based on this hypothesis, the simplified concept of a two-CN heterogeneous system is introduced to model the observed CN-rainfall variation by reducing the CN spatial variability into two classes. The behaviour of the CN-rainfall function produced by the simplified two-CN system is approached theoretically, it is analysed systematically, and it is found to be similar to the variation observed in natural watersheds. Synthetic data tests, natural watersheds examples, and detailed study of two natural experimental watersheds with known spatial heterogeneity characteristics were used to evaluate the method. The results indicate that the determination of CN values from rainfall runoff data using the proposed two-CN system approach provides reasonable accuracy and it over performs the previous methods based on the determination of a single asymptotic CN value. Although the suggested method increases the number of unknown parameters to three (instead of one), a clear physical reasoning for them is presented.

scholarly journals A Test of Snowmelt-Runoff Model for a Major River Basin in Western Himalayas

1989 ◽  
Vol 20 (3) ◽  
pp. 167-178 ◽  
Author(s):  
B. Dey ◽  
V. K. Sharma ◽  
A. Rango
Keyword(s):  
River Basin ◽  
Lapse Rate ◽  
Western Himalayas ◽  
Rainfall Runoff ◽  
Snowmelt Runoff ◽  
Major River ◽  
Updating Procedure ◽  
Runoff Model ◽  
Kabul River

In the Snowmelt-Runoff Model (SRM), the estimate of discharge volume is based on temperature condition in the form of degree days which are used to melt the snowpack in the area of the basin covered by snow as observed from satellites. Precipitation input is used to add any rainfall runoff to the snowmelt component. When SRM was applied to the large, international Kabul River basin, initial simulations were much above the observed stream flow values. Close inspection revealed several problems in the application of SRM to the Kabul Basin that were easily corrected. Foremost among the corrections were determination of an appropriate lapse rate, substitution of a more representative mean elevation for extrapolation of temperature data, and use of an automatic streamflow updating procedure. These improvements led to a simulation for 1976 that was comparable to other simulations on large, inaccessible basins. As SRM is applied to more basins similar to the Kabul River, the determination of suitable parameters for new basin will be enhanced. Additional improvements in simulations would result from installation of climate stations at the mean elevation of basins and work to assure delivery of timely and reliable satellite snow cover data.

scholarly journals CN Modeling for Predicting Discharge in Lesti Sub-watershed

2019 ◽  
Vol 8 (12) ◽  
pp. 4890-4896
Keyword(s):  
United States ◽  
Land Use ◽  
Curve Number ◽  
The United States ◽  
United States Department ◽  
Department Of Agriculture ◽  
Mathematical Formula ◽  
States Department ◽  
Soil Group ◽  
Rainfall Depth

This research intends to accurately mapping the Curve Number (CN) that is as the function of cover type, land use treatment, hydrology condition, and hydrologic soil group in the Lesti sub-watershed,. The methodology consists of to build the suitable CN modeling for predicting discharge in the Lesti sub-watershed and then to evaluate the result accurately. The value of CN is obtained from the mathematical formula with the input is rainfall depth and discharge. The result of CN modeling for the Lesti sub-watershed is accurate enough as is made by the United States Department of Agriculture (USDA) in USA. In addition, the CN mapping can be directly used by the engineers of the manager and designer on the water resources structures in Lesti sub-watershed

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.

Sign in / Sign up

Export Citation Format

Share Document