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Meadows, Michael E. "Adjusting NRCS Curve Number for Rainfall Durations Less Than 24 Hours." Journal of South Carolina Water Resources, no. 3 (June 1, 2016): 43–47. http://dx.doi.org/10.34068/jscwr.03.05.
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The primary use of the Natural Resources Conservation Service (NRCS) curve number (CN) is to compute total storm runoff based on total rainfall. The method was originally created to determine the mean daily depth of runoff during flood producing events on small agricultural watersheds. CN values were determined using daily rainfall and runoff data. Practically, it did not rain for 24 hours during many, perhaps most, of the events, but since the data were recorded as daily rainfall, 24 hours became the implicit duration for values input to the curve number runoff model. NRCS references do not specifically state the CN applies only to the 24-hour storm. Even so, it may be inferred from what is published that the standard CN applies to the 24 hour duration storm. Many methods and computer models used for the analysis and design of stormwater management systems incorporate the NRCS CN method. Because some designs and performance evaluations are based on rainfalls with durations less than 24 hours, there is the need for a method to modify CN values for shorter duration events. It goes against basic hydrologic principles if the same CN is used for storms of all durations. Not yet formally published, the NRCS recently developed a procedure to modify CN values for rainfall durations less than 24 hours. With encouragement from the NRCS, introducing that method to the engineering community is the goal for this paper. The impact of adjusted CN values was demonstrated by calculations comparing runoff depths computed with standard and duration modified CN values for rainfalls of 1, 2, 3, 6, 12, and 24 hour duration. The standard CN significantly under-predicted runoff depths compared to the duration modified CN values. The differences increased with shorter duration storms. The impact of adjusted CN values also was demonstrated during a forensic assessment of the performance of a stormwater detention pond in a residential subdivision. The pond was designed compliant with regulations to limit the post-development peak discharge rate at or below the pre-development peak runoff rate for 2- and 10-year frequency 24-hour design storm events. Even though the pond design met regulatory standards for 24-hour design storms, downstream flooding and sediment problems frequently occurred during short duration events. As part of the forensic study, runoff hydrographs were simulated for pre-development, construction phase, and post-development land use conditions for rainfalls of 1, 2, 3, 6, 12, and 24 hour duration. The simulation results for post development conditions showed successful pond performance for the 24-hour rainfall. However, the peak outflow rates for storms with durations less than 24-hours were greater than the 24-hour pre-development peak runoff rate. The simulation results emphasize pond design calculations and decisions should include pond performance for events with duration less than 24 hours and should use duration modified CN values. It is recommended controlling regulations specify design events such as the 2- and 10-year 24-hour rainfalls, but include a mandatory check of other events, such as the 1, 2, 3, 6 and 12 hour events. Prudent and ethical practice suggests pond design be upgraded for the critical rainfall event.
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Ramadan, Anri Noor Annisa, Dicky Nurmayadi, Anwar Sadili, Rega Rizaldy Solihin, and Zefri Sumardi. "Pataruman Watershed Curve Number Determination Study Based on Indonesia Land Map Unit." MEDIA KOMUNIKASI TEKNIK SIPIL 26, no. 2 (2021): 258–66. http://dx.doi.org/10.14710/mkts.v26i2.26563.
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The rainfall-runoff model is commonly used in flood discharge computation. One of the most frequently employed methods to estimate the flood discharge in the ungauged basin is NRCS-CN. This study is aimed to determine the CN value with/without soil drainage capacity from the soil information in SPT Indonesia. The location used is Pataruman watershed by calibrating the simulation discharge results with the observed discharge. Soil conditions in the Pataruman watershed show that the soil texture has a fine texture (HSG D), a slightly fine texture (HSG C), and a slightly coarse texture (HSG A). The average composite CN in the Pataruman watershed without soil drainage capacity was 85.58 while soil drainage capacity was 81.01. The results of the analysis show that with/without taking into account the soil drainage capacity in the Pataruman watershed there is no significant difference in discharge with a relation coefficient of 0.734 (without soil drainage capacity) and 0.732 (with soil drainage capacity). CN calculations with/without soil drainage capacity are recommended for small watersheds.
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Tan, Wen Jia, Jen Feng Khor, Lloyd Ling та Yuk Feng Huang. "Misuse of Lambda (λ) in NRCS-CN Model". E3S Web of Conferences 65 (2018): 07006. http://dx.doi.org/10.1051/e3sconf/20186507006.
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Since 1954, the Soil Conservation Curve Number (SCS-CN) method is widely applied in hydrological field to predict the direct runoff resulting from event rainfall. Originally, the lambda value was fixed at 0.2. However, based on recent studies, the simplied SCS-CN method was unable to predict a consistent and accurate runoff amount. Most of the research studies in various countries claimed that lambda value was a variable and most likely should be less than 0.2. Most of the researchers applied either mean or median λ value directly without checking the statistics. Misuse of lambda value in SCS-CN model will lead to inconsistent runoff estimation. Moreover, although λ value can be determined, the equivalent CN0.2 cannot be found. Some of research studies or even Hydrology Textbook substitute Sλ directly into CN equation and lead to wrong CN calculation. In this study, the statistical significant λ value and regional specific S correlation are developed under the guide of non-parametric inferential statistics. by using bootstrapping, Bias corrected and accelerated (BCa) technique with 2000 samples.
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Młyński, Dariusz, and Andrzej Wałęga. "Identification of the Relationship between Rainfall and the CN Parameter in Western Carpathian Mountain Catchments in Poland." Sustainability 12, no. 22 (2020): 9317. http://dx.doi.org/10.3390/su12229317.
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The aim of this study was to identify the form of the dependence describing the relationship between rainfall (P) and the curve number (CN) parameter using the Natural Resources Conservation Service (NRCS-CN) method in the mountain catchments of the Western Carpathians. The study was carried out in 28 catchments areas in the Western Carpathians in the Upper Vistula Basin, Poland. The study was conducted in the following stages: determination of the volume of the direct runoff using the NRCS-CN method, determination of the P–CN relationship using asymptotic functions, kinetic equation and complementary error function; determination of the volume of the direct runoff from the catchment area, accounting for the correction of the decline; determination of the value of the efficiency coefficient of the analysed models. On the basis of the conducted study, a strong relationship was found between the direct runoff and the rainfall that caused it. The study showed that the empirical values of the CN parameter differed from the values determined on the basis of the volume of rainfall and runoff. The vast majority of study catchments were characterised by a standard P–CN relationship. The kinetic model was found to be the best model to describe the P–CN relationship. The asymptotic model showed the greatest stability for high rainfall episodes. It was shown that the application of the catchment slope correction improved the quality of the NRCS-CN model.
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Moon, Geon-Woo, Muhammad Ajmal, Jae-Hyun Ahn, and Tae-Woong Kim. "Investigating practical alternatives to the NRCS-CN method for direct runoff estimation using slope-adjusted curve numbers." KSCE Journal of Civil Engineering 20, no. 7 (2016): 3022–30. http://dx.doi.org/10.1007/s12205-016-0148-7.
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Walega, Andrzej, and Devendra M. Amatya. "Application of Modified SME-CN Method for Predicting Event Runoff and Peak Discharge from a Drained Forest Watershed on the North Carolina Atlantic Coastal Plain." Transactions of the ASABE 63, no. 2 (2020): 275–88. http://dx.doi.org/10.13031/trans.13838.
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HighlightsProposed new method to assess subsurface and surface runoff from drained forested watershed.Factor Fp in the graphical peak discharge method is less in forested wetland watershed than recommended by USDA.Modified graphical peak discharge method correctly approximated observed peak discharges.Abstract. The NRCS curve number (CN) method is a widely used event-based model for estimating runoff using readily available watershed parameters and rainfall data from upland agricultural catchments. However, there is limited literature on application of the CN method in drained forest systems. This study proposes an application of the modified Sahu-Mishra-Eldho (SME) CN method developed and tested in earlier studies. In this study, the SME method was further modified by redefining the maximum potential retention to assess subsurface drainage and surface runoff, which are parts of total outflow, separately for a pine forest watershed with a high water table soil drained by ditches spaced 100 m apart in coastal North Carolina. Assuming that the measured outflow from the drained watershed was dominated by subsurface drainage, computed event outflow using the modified SME-CN (MSME-CN) model showed good agreement with the observed outflow data (without extreme rainfall events) for the study watershed, yielding a Nash-Sutcliffe coefficient of 0.97, R2 = 0.97, and RMSE = 3.46 mm. Linking the direct runoff from the MSME model into the SCS graphical peak discharge method (GPDM) also improved event peak flow estimates compared to those from the GPDM using SCS-CN based outflow, with calculated RMSE of 11.93 and 31.35 L s-1 and modeling efficiency (EF) of 0.79 and -0.45, respectively. In addition, based on analysis, the wetland factor (Fp) of 0.72 recommended in the GPDM was found to be very large and unsuitable for the study watershed with its high retention capacity. The authors suggest multi-site-year validation of the MSME-CN model, which is sensitive to input parameters such as PET5, P, CN, and a, to gain more confidence in it and the associated GPDM. Keywords: Peak discharge, Pine forest, Poorly drained soil, Potential retention, Subsurface runoff, Surface runoff.
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Moniruzzaman, Md, Praveen K. Thakur, Pramod Kumar, et al. "Decadal Urban Land Use/Land Cover Changes and Its Impact on Surface Runoff Potential for the Dhaka City and Surroundings Using Remote Sensing." Remote Sensing 13, no. 1 (2020): 83. http://dx.doi.org/10.3390/rs13010083.
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Rapid urban growth processes give rise to impervious surfaces and are regarded as the primary cause of urban flooding or waterlogging in urban areas. The high rate of urbanization has caused waterlogging and urban flooding in many parts of Dhaka city. Therefore, the study is undertaken to quantify the changes in land use/land cover (LULC) and urban runoff extent based on the Natural Resources Conservation Service (NRCS) Curve Number (CN) during 1978–2018. The five-decadal LULC has been analyzed using three-generation Landsat time-series data considering six different classes, namely agriculture, built-up, wetland, open land, green spaces, and water bodies for the years 1978, 1988, 1998, 2007, and 2018. Significant changes in LULC for the study area from 1978–2018 are observed as 13.1%, 4.8%, and 7.8% reduction in agricultural land, green spaces, and water bodies, respectively, and a 22.1% increase in the built-up area is estimated. Within Dhaka city, 14.6%, 16.0%, and 12.3% reduction in agricultural land, green spaces, and water bodies, respectively, and a radical increase of 41.9% in built-up area are reckoned. The decadal runoff assessment has been carried out using the NRCS-CN method, considering an extreme rainfall event of 341 mm/day (13 September 2004). The catchment area under very high runoff category is observed as 159.5 km2 (1978) and 318.3 km2 (2018), whereas, for Dhaka city, the setting is dynamic as the area under the very high runoff category has increased from 74.24 km2 (24.44%) to 174.23 km2 (57.36%) in years 1978 and 2018, respectively, and, mostly, the very high runoff potential areas correspond to the dense built-up surfaces.
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Afkril, Baina, M. Pramono Hadi, and Slamet Suprayogi. "A New Algorithm For The Grid Cell-Based Runoff Routing Model Based on Travel Time Concept." Geosfera Indonesia 5, no. 2 (2020): 160. http://dx.doi.org/10.19184/geosi.v5i2.17351.
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The grid cell-based routing model has recently been used to simulate direct runoff hydrographs at catchment scales. This study develops a flexible event-based runoff routing algorithm to simulate a direct runoff hydrograph (DRH). The experiment was based on the spatiotemporal inputs of a hydrological data set. The flexibility is based on the time step and grid cell size applied in the original STORE-DHM. Rainfall distribution was obtained using radar data adjusted by the measured point ground, while the runoff yield was determined using the NRCS-CN method. The parameter distribution was captured in the GIS environment as raster data formats. Furthermore, it was converted into ASCII data formats for scripting the routing algorithm using Matlab programming codes. The model algorithm was tested for storm events within two small study river systems in Yogyakarta, Indonesia. One event in each catchment was selected and calibrated to the observed hydrograph, treating the Curve Number (CN) and Manning coefficient (n) values as parameter calibrations. In the end, two events were selected for validation. The proposed routing model algorithm simulates DRHs of all selected events in the study areas with excellent performance. The Nash-Sutcliffe coefficient was greater than 0.75 for all DRH during validation, and the volume bias and peak discharge error were less than 25%.
 Keywords: Algorithm; Cell-based runoff routing; Travel time; GIS; Direct runoff hydrograph.
 
 Copyright (c) 2020 Geosfera Indonesia Journal and Department of Geography Education, University of Jember
 This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License
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Mohamed, E. S., M. A. Abdellatif, Sameh Kotb Abd-Elmabod, and M. M. N. Khalil. "Estimation of surface runoff using NRCS curve number in some areas in northwest coast, Egypt." E3S Web of Conferences 167 (2020): 02002. http://dx.doi.org/10.1051/e3sconf/202016702002.
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The sustainable agricultural development in the northwest coast of Egypt suffers constantly from the effects of surface runoff. Moreover, there is an urgent need by decision makers to know the effects of runoff. So the aim of this work is to integrate remote sensing and field data and the natural resource conservation service curve number model (NRCS-CN).using geographic information systems (GIS) for spatial evaluation of surface runoff .CN approach to assessment the effect of patio-temporal variations of different soil types as well as potential climate change impact on surface runoff. DEM was used to describe the effects of slope variables on water retention and surface runoff volumes. In addition the results reflects that the magnitude of surface runoff is associated with CN values using NRCS-CN model . The average of water retention ranging between 2.5 to 3.9m the results illustrated that the highest value of runoff is distinguished around the urban area and its surrounding where it ranged between 138 - 199 mm. The results show an increase in the amount of surface runoff to 199 mm when rainfall increases 200 mm / year. The north of the area may be exposed to erosion hazards more than the south and a change in the soil quality may occur in addition to the environmental imbalance in the region.
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Gonzalez, Alvaro, Marouane Temimi, and Reza Khanbilvardi. "Adjustment to the curve number (NRCS-CN) to account for the vegetation effect on hydrological processes." Hydrological Sciences Journal 60, no. 4 (2015): 591–605. http://dx.doi.org/10.1080/02626667.2014.898119.
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Chandel, Sumita, and M. S. Hadda. "Quantification of surface runoff in Patiala-Ki-Rao watersheds using modified NRCS model: a case study." Journal of Applied and Natural Science 9, no. 3 (2017): 1573–81. http://dx.doi.org/10.31018/jans.v9i3.1403.
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Quantification of the surface runoff in a watershed is of vital importance for solution of many water resource problems. It can be quantified by employing large number of estimation approaches. Of these, SCS-CN approach is quite simple effective and requires less number of parameters. Thus, the objective of the study was to employ soil conservation service-curve number (SCS-CN) approach and their modifications to estimate surface runoff for Patiala-Ki-Rao watershed, district SAS, Nagar, Punjab and to choose the best model of the 8-different employed models. Soil moisture retention parameter was characterised and optimised by using the descriptive statistics and later used in the models. The mean and median valueof soil moisture retention parameter was 47.2 mm and 35.9 mm for June to September months and 35.4 to 30.8 mm for October to March months. The models were evaluated on the basis of Root Mean Square Error (RMSE), Nash- Scutcliffe Efficiency (NSE), Coefficient of Determination (R2) and Per cent Bias (PB). Of the evaluated and tested models, NRCS model (M5) performed best with the highest score of 32 and 31 by employing mean andmedian values of soil moisture retention parameter in Patiala-Ki-Rao watersheds over the other models. Further, the results of the study suggested in evaluating the performance of NRCS model (M5) in other treated micro-watersheds at Patiala-Ki-Rao, Punjab, over the control.
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Tan, Wen Jia, Jen Feng Khor, Lloyd Ling, and Yuk Feng Huang. "Exploratory Research of New Curve Number System." E3S Web of Conferences 65 (2018): 07005. http://dx.doi.org/10.1051/e3sconf/20186507005.
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In the past, the CN was determined through SCS handbook. In order to determine runoff prediction using SCS-CN model, selection of CN is important. However, the conventional CN methodology with inappropriate CN selection often produces inconsistent runoff estimation. Thus, the new direct curve number derivation technique based on rainfall-runoff datasets with supervised numerical optimization technique under the guide of inferential statistics was developed to improve the accuracy of surface runoff prediction. Furthermore, the two decimal point CN system was proposed in this study. The optimum CN of Melana site is 90.45 at alpha 0.01 with BCa 99 % confidence interval range from 90.45 to 95.12. The regional specific calibrated SCS-CN model with two decimal point CN derivation technique is out-performed the runoff prediction of conventional SCS-CN model and the asymptotic curve number fitting method.
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Soomro, Abdul Ghani, Muhammad Munir Babar, Anila Hameem Memon, Arjumand Zehra Zaidi, Arshad Ashraf, and Jewell Lund. "Sensitivity of Direct Runoff to Curve Number Using the SCS-CN Method." Civil Engineering Journal 5, no. 12 (2019): 2738–46. http://dx.doi.org/10.28991/cej-2019-03091445.
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This study explores the impact of runoff curve number (CN) on the hydrological model outputs for the Morai watershed, Sindh-Pakistan, using the Soil Conservation Service Curve Number (SCS-CN) method. The SCS-CN method is an empirical technique used to estimate rainfall-runoff volume from precipitation in small watersheds, and CN is an empirically derived parameter used to calculate direct runoff from a rainfall event. CN depends on soil type, its condition, and the land use and land cover (LULC) of an area. Precise knowledge of these factors was not available for the study area, and therefore, a range of values was selected to analyze the sensitivity of the model to the changing CN values. Sensitivity analysis involves a methodological manipulation of model parameters to understand their impacts on model outputs. A range of CN values from 40-90 was selected to determine their effects on model results at the sub-catchment level during the historic flood year of 2010. The model simulated 362 cumecs of peak discharge for CN=90; however, for CN=40, the discharge reduced substantially to 78 cumecs (a 78.46% reduction). Event-based comparison of water volumes for different groups of CN values—90-75, 80-75, 75-70, and 90-40 —showed reductions in water availability of 8.88%, 3.39%, 3.82%, and 41.81%, respectively. Although it is known that the higher the CN, the greater the discharge from direct runoff and the less initial losses, the sensitivity analysis quantifies that impact and determines the amount of associated discharges with changing CN values. The results of the case study suggest that CN is one of the most influential parameters in the simulation of direct runoff. Knowledge of accurate runoff is important in both wet (flood management) and dry periods (water availability). A wide range in the resulting water discharges highlights the importance of precise CN selection. Sensitivity analysis is an essential facet of establishing hydrological models in limited data watersheds. The range of CNs demonstrates an enormous quantitative consequence on direct runoff, the exactness of which is necessary for effective water resource planning and management. The method itself is not novel, but the way it is proposed here can justify investments in determining the accurate CN before initiating mega projects involving rainfall-runoff simulations. Even a small error in CN value may lead to serious consequences. In the current study, the sensitivity analysis challenges the strength of the results of a model in the presence of ambiguity regarding CN value.
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Kim, Sangdan, and Suhee Han. "Urban Stormwater Capture Curve Using Three-Parameter Mixed Exponential Probability Density Function and NRCS Runoff Curve Number Method." Water Environment Research 82, no. 1 (2010): 43–50. http://dx.doi.org/10.1002/j.1554-7531.2010.tb00255.x.
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Cayson, F. C., C. L. Patiño, and M. J. L. Flores. "RUNOFF ESTIMATION USING SCS RUNOFF CURVE NUMBER METHOD IN CEBU ISLAND." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W19 (December 23, 2019): 109–15. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w19-109-2019.
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Abstract. Cebu, with its growing development and increasing demand for water, needs tools and inputs to efficiently understand and manage its water resources. Rainfall runoff models were developed to model surface runoff which may be used to assess water availability. Soil Conservation System (SCS) Runoff Curve Number (CN) method predicts runoff based on an empirical curve number for ungauged watersheds. This study aims to estimate the amount of runoff for the catchments of Cebu Island using the SCS-CN Runoff technique. The data needed for the application of the method in this study were rainfall distribution data, land use/land cover and soil texture for curve number assignment, LiDAR DEM for the delineation of the catchments, and supporting runoff measurements from a different runoff estimation model for assessment of the results. The collected data were prepared by assigning the mean statistics of the rainfall distribution and the composite curve number for each catchment using Geographic Information System (GIS). The calculation of the runoff was also done using the same framework. Maps representing Cebu Island’s catchments’ runoff estimates were produced. Since observed runoff data were unavailable, the results were verified by comparing the SCS-CN estimated runoff to the results of a physically-based distributed hydrologic and hydraulics modelling software, FLO-2D. The SCS-CN estimations were found to coincide with the FLO-2D runoff estimates based on various statistical assessments. Although the results may have higher uncertainties due to the unavailability of observed runoff data, the SCS-CN Runoff method provided relevant results to that of a complex simulation model. Thus, the method may be applied to estimate runoff of ungauged catchments of Cebu Island, the results of which could provide relevant information for water resource management.
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Nachabe, Mahmood H. "EQUIVALENCE BETWEEN TOPMODEL AND THE NRCS CURVE NUMBER METHOD IN PREDICTING VARIABLE RUNOFF SOURCE AREAS." Journal of the American Water Resources Association 42, no. 1 (2006): 225–35. http://dx.doi.org/10.1111/j.1752-1688.2006.tb03836.x.
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Santikari, Vijay P., and Lawrence C. Murdoch. "Including effects of watershed heterogeneity in the curve number method using variable initial abstraction." Hydrology and Earth System Sciences 22, no. 9 (2018): 4725–43. http://dx.doi.org/10.5194/hess-22-4725-2018.
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Abstract. The curve number (CN) method was developed more than half a century ago and is still used in many watershed and water-quality models to estimate direct runoff from a rainfall event. Despite its popularity, the method is plagued by a conceptual problem where CN is assumed to be constant for a given set of watershed conditions, but many field observations show that CN decreases with event rainfall (P). Recent studies indicate that heterogeneity within the watershed is the cause of this behavior, but the governing mechanism remains poorly understood. This study shows that heterogeneity in initial abstraction, Ia, can be used to explain how CN varies with P. By conventional definition, Ia is equal to the cumulative rainfall before the onset of runoff and is assumed to be constant for a given set of watershed conditions. Our analysis shows that the total storage in Ia (IaT) is constant, but the effective Ia varies with P, and is equal to the filled portion ofIaT, which we call IaF. CN calculated using IaF varies with P similar to published field observations. This motivated modifications to the CN method, called variable Ia models (VIMs), which replace Ia with IaF. VIMs were evaluated against conventional models CM0.2 (λ = 0.2) and CMλ (calibrated λ) in their ability to predict runoff data generated using a distributed parameter CN model. The performance of CM0.2 was the poorest, whereas those of the VIMs were the best in predicting overall runoff and watershed heterogeneity. VIMs also predicted the runoff from smaller events better than the CMs and eliminated the false prediction of zero-runoffs, which is a common shortcoming of the CMs. We conclude that including variable Ia accounts for heterogeneity and improves the performance of the CN method while retaining its simplicity.
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Hejduk, L., A. Hejduk, and K. Banasik. "Determination of Curve Number for snowmelt-runoff floods in a small catchment." Proceedings of the International Association of Hydrological Sciences 370 (June 11, 2015): 167–70. http://dx.doi.org/10.5194/piahs-370-167-2015.
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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.
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R, Selvakumar, Nasir N, and Suribabu C R. "Determination of Watershed Characteristics and Curve Number (CN) for Ponnaniyaru Dam Catchment Area." International Journal of Engineering & Technology 7, no. 3.12 (2018): 558. http://dx.doi.org/10.14419/ijet.v7i3.12.16179.
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In SCS-CN method, curve number is significant parameter in estimating runoff from the catchment of the reservoir or inflow to the reservoir. As this curve number is function of several parameters like hydrological soil group, LULC, land treatment, hydrologic conditions and AMC, the selection of CN for prediction of inflow to the lake or reservoir is considered as a crucial in the hydrological studies. LULC, micro-watershed, drainage density, and catchment slope are obtained using spatial analysis and also SCS Curve Number value for Ponnaniyaru dam catchment area is derived from the LULC data. Further, CN value is evaluated from actual rainfall data and runoff volume collected at the reservoir. The study reveals the significant variation of CN value among each event. The present case study highlights the sensitiveness of CN value in the computation of runoff from the watershed. Keywords: Curve number, LULC, AMC, drainage density.
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Mware, Mugo, Benjamin Mwasi, Francis Mburu, Peter Sirma, and Eric Koech. "Adaptation of the Natural Resources Conservation Service (NRCS) curve number (CN) model in estimating direct run-off from humid tropical forest catchments." Water and Environment Journal 27, no. 4 (2012): 474–83. http://dx.doi.org/10.1111/j.1747-6593.2012.00346.x.
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Carvalho, Fábio, Jefferson Gomes Confessor, and Sílvio Carlos Rodrigues. "Utilização de simulador de chuvas para determinação do valor CN e abstração inicial na cultura do café em ambiente de cerrado brasileiro." Physis Terrae - Revista Ibero-Afro-Americana de Geografia Física e Ambiente 2, no. 2 (2021): 101–26. http://dx.doi.org/10.21814/physisterrae.3083.
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O conhecimento do funcionamento hidrológico de uma bacia hidrográfica permite adotar medidas de planejamento ambiental de forma a garantir a perenidade dos recursos naturais ali inseridos. A adoção de modelos que visam expor as dinâmicas de funcionamento de fluxos de bacias se mostram de grande interesse, como o Método SCS-CN desenvolvido pelo NRCS (Natural Research Conservation Service – USDA – Departamento de Agricultura dos EUA). Entretanto, esse modelo foi elaborado sob condições edafoclimáticas distintas do território brasileiro, carecendo a calibração dos índices sob as condições ambientais específicas de cada local. O objetivo deste trabalho consiste em apresentar uma metodologia para determinar os parâmetros do Método SCS-CN, abstração inicial, escoamento superficial e os respectivos valores CN (valores Curve Number) para a cultura de café Arábica, inserida em ambiente de cerrado, por meio do uso de um simulador de chuvas em dois períodos pré-definidos (primavera-verão e outono-inverno). Os índices de abstração inicial do simulador de chuva (λsi) foram menores do que λ=0,2 e variaram entre as simulações de 0,03 a 0,14 observando a interferência do volume de precipitação no índice de abstração inicial. O escoamento superficial esteve entre 0,18 mm a 6,26 mm, apresentando variações no volume de escoamento entre as calhas. Em síntese, observa-se um aumento do volume de escoamento superficial da primeira simulação em relação à segunda simulação, não alterando significativamente os valores CNsi.
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Pathak, Shray, Chandra Shekhar Prasad Ojha, Rahul Dev Garg, Min Liu, Daniel Jato-Espino, and Rajendra Prasad Singh. "Spatiotemporal Analysis of Water Resources in the Haridwar Region of Uttarakhand, India." Sustainability 12, no. 20 (2020): 8449. http://dx.doi.org/10.3390/su12208449.
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Watershed management plays a dynamic role in water resource engineering. Estimating surface runoff is an essential process of hydrology, since understanding the fundamental relationship between rainfall and runoff is useful for sustainable water resource management. To facilitate the assessment of this process, the Natural Resource Conservation Service-Curve Number (NRCS-CN) and Geographic Information Systems (GIS) were integrated. Furthermore, land use and soil maps were incorporated to estimate the temporal variability in surface runoff potential. The present study was performed on the Haridwar city, Uttarakhand, India for the years 1995, 2010 and 2018. In a context of climate change, the spatiotemporal analysis of hydro meteorological parameters is essential for estimating water availability. The study suggested that runoff increased approximately 48% from 1995 to 2010 and decreased nearly 71% from 2010 to 2018. In turn, the weighted curve number was found to be 69.24, 70.96 and 71.24 for 1995, 2010 and 2018, respectively. Additionally, a validation process with an annual water yield model was carried out to understand spatiotemporal variations and similarities. The study recommends adopting water harvesting techniques and strategies to fulfill regional water demands, since effective and sustainable approaches like these may assist in the simultaneous mitigation of disasters such as floods and droughts.
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Ibrahim, Sayran A., and Zahraa M. Klari. "Application of SCS-Curve Number Method to estimate Runoff using GIS for Gali-Bandawa Watershed." Academic Journal of Nawroz University 10, no. 1 (2021): 318. http://dx.doi.org/10.25007/ajnu.v10n1a1108.
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In any hydrologic study, the most important parameter is the runoff which is necessary for designing any hydraulic structure, and for determining the risk of flood. As there is a scare in the availability of runoff data in many sites, hydrologists have developed indirect methods to determine the runoff to accelerate the program of watershed management for conserving and developing water resources management. Many methods are used to estimate the runoff; Soil conservation curve number (SCS-CN) method is widely used and gives a reliable result compared with other methods. The present study aims to calculate the surface runoff depth depending on the SCS-CN method using a Geographic information system (GIS). For this Gali-Bandawa watershed in Duhok, north of Iraq has been selected, the geographical area of this watershed is about 92Km2 and the average annual rainfall is around 620mm, the weighted CN is 76. The results show that the depth of annual average runoff for the Gali-Bandawa watershed is 70mm, and the average volume of runoff from the same watershed is 6470360 m3. The amount of runoff represents 11.4% of the total annual rainfall. This approach could be applied in other Iraqi's watersheds for the planning of various conservation measures.
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Chavda, Dipesh, Jaydip Makwana, Hitesh Parmar, Arvind Kunapara, and Girish Prajapati. "Estimation of Runoff for Ozat Catchment using RS and GIS Based SCS-CN Method." Current World Environment 11, no. 1 (2016): 212–17. http://dx.doi.org/10.12944/cwe.11.1.26.
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Estimation of runoff in a watershed is a prerequisite for design of hydraulic structures, reservoir operation and for soil erosion control measures. Water resource planning and management is important and critical issue in arid and semi-arid regions. Runoff from a watershed affected by several geo-morphological parameters and for a particular watershed land use change can affect the runoff volume and runoff rate significantly. Several methods are investigated to estimate the surface runoff from a catchment but the Curve Number method is mostly used. Present study was undertaken to estimate surface runoff and water availability for two sites (Ozat-2 and Zanzesri) in the Ozat catchment situated in Junagadh, Gujarat, India using RS and GIS based curve number method. The Weight curve number for the ozat catchment is 73.00. The correlation coefficient between calculated and observed runoff was good for both catchments. In this study found that SCS-curve number method along with RS and GIS can be used successfully in semi-arid region to simulate rainfall runoff and to estimate total surface water.
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Shi, Wenhai, and Ni Wang. "Improved SMA-based SCS-CN method incorporating storm duration for runoff prediction on the Loess Plateau, China." Hydrology Research 51, no. 3 (2020): 443–55. http://dx.doi.org/10.2166/nh.2020.140.
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Abstract In the Soil Conservation Service Curve Number (SCS-CN) method for estimating runoff, three antecedent moisture condition (AMC) levels produce a discrete relation between the curve number (CN) and soil water content, which results in corresponding sudden jumps in estimated runoff. An improved soil moisture accounting (SMA)-based SCS-CN method that incorporates a continuous function for the AMC was developed to obviate sudden jumps in estimated runoff. However, this method ignores the effect of storm duration on surface runoff, yet this is an important component of rainfall-runoff processes. In this study, the SMA-based method for runoff estimation was modified by incorporating storm duration and a revised SMA procedure. Then, the performance of the proposed method was compared to both the original SCS-CN and SMA-based methods by applying them in three experimental watersheds located on the Loess Plateau, China. The results indicate that the SCS-CN method underestimates large runoff events and overestimates small runoff events, yielding an efficiency of 0.626 in calibration and 0.051 in validation; the SMA-based method has improved runoff estimation in both calibration (efficiency = 0.702) and validation (efficiency = 0.481). However, the proposed method performed significantly better than both, yielding model efficiencies of 0.810 and 0.779 in calibration and validation, respectively.
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Malekani, L., S. Khaleghi, and M. Mahmoodi. "APPLICATION OF GIS IN MODELING ZILBERCHAI BASIN RUNOFF." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-2/W3 (October 22, 2014): 181–86. http://dx.doi.org/10.5194/isprsarchives-xl-2-w3-181-2014.
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Runoff is one of most important hydrological variables that are used in many civil works, planning for optimal use of reservoirs, organizing rivers and warning flood. The runoff curve number (CN) is a key factor in determining runoff in the SCS (Soil Conservation Service) based hydrologic modeling method. The traditional SCS-CN method for calculating the composite curve number consumes a major portion of the hydrologic modeling time. Therefore, geographic information systems (GIS) are now being used in combination with the SCS-CN method. This work uses a methodology of determining surface runoff by Geographic Information System model and applying SCS-CN method that needs the necessary parameters such as land use map, hydrologic soil groups, rainfall data, DEM, physiographic characteristic of the basin. The model is built by implementing some well known hydrologic methods in GIS like as ArcHydro, ArcCN-Runoff for modeling of Zilberchai basin runoff. The results show that the high average weighted of curve number indicate that permeability of the basin is low and therefore likelihood of flooding is high. So the fundamental works is essential in order to increase water infiltration in Zilberchai basin and to avoid wasting surface water resources. Also comparing the results of the computed and observed runoff value show that use of GIS tools in addition to accelerate the calculation of the runoff also increase the accuracy of the results. This paper clearly demonstrates that the integration of GIS with the SCS-CN method provides a powerful tool for estimating runoff volumes in large basins.
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Krisnayanti, Denik Sri, Wilhelmus Bunganaen, John H. Frans, Yustinus A. Seran, and Djoko Legono. "Curve Number Estimation for Ungauged Watershed in Semi-Arid Region." Civil Engineering Journal 7, no. 6 (2021): 1070–83. http://dx.doi.org/10.28991/cej-2021-03091711.
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The Benanain Watershed is located in East Nusa Tenggara with an area of 3,181 km2 and is divided into 29 sub-watersheds. The East Nusa Tenggara itself is an eastern region of Indonesia with a unique climate condition called semi-arid. The high rainfall intensity occurring in short duration results in large surface runoff and erosion. Floods and erosion in semi-arid areas due to sensitive soils to drought and heavy rainfall extremely. This paper presents the application of the Soil Conservation Services-Curve Number (SCS-CN) real-flood flows through a digital map of soil type, land use, topography, and the heterogeneity of physical condition, especially for ungauged watersheds. The method used is an approach empirical to estimate runoff from the relationship between rainfall, land use, and soil hydrology groups. This watershed has a large area that must analyze every sub-watershed. The land-use of the Benanain watershed is secondary dryland forest by 44.26% and the hydrological soil group on the B group classification with medium to high absorption potential by 46.502% from the total area. The curve number value of the Benanain Watershed ranges from 56.54 to 73.90, where the mean CN value of 65.32. The rainfall (mm) for the 29 sub-watersheds in the Benanain Watershed has decreased by about 74.65% when being surface runoff or only 25.35% of water becomes surface runoff. The relationship between rainfall depth and CN is classified as standard response and trend line (flat slope) equilibrium occurs when rainfall depth value of 56.71 mm and CN is close to 66.30. The high variability of intense rainfall between the rainy season and the dry season had a significant influence on the curve number value in a large watershed area. Further analysis will be more accurate if it is supported by long rainfall data and observation runoff data as a control. Doi: 10.28991/cej-2021-03091711 Full Text: PDF
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Wang, Dingbao. "A new probability density function for spatial distribution of soil water storage capacity leads to the SCS curve number method." Hydrology and Earth System Sciences 22, no. 12 (2018): 6567–78. http://dx.doi.org/10.5194/hess-22-6567-2018.
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Abstract. Following the Budyko framework, the soil wetting ratio (the ratio between soil wetting and precipitation) as a function of the soil storage index (the ratio between soil wetting capacity and precipitation) is derived from the Soil Conservation Service Curve Number (SCS-CN) method and the variable infiltration capacity (VIC) type of model. For the SCS-CN method, the soil wetting ratio approaches 1 when the soil storage index approaches ∞, due to the limitation of the SCS-CN method in which the initial soil moisture condition is not explicitly represented. However, for the VIC type of model, the soil wetting ratio equals the soil storage index when the soil storage index is lower than a certain value, due to the finite upper bound of the generalized Pareto distribution function of storage capacity. In this paper, a new distribution function, supported on a semi-infinite interval x∈[0,∞), is proposed for describing the spatial distribution of storage capacity. From this new distribution function, an equation is derived for the relationship between the soil wetting ratio and the storage index. In the derived equation, the soil wetting ratio approaches 0 as the storage index approaches 0; when the storage index tends to infinity, the soil wetting ratio approaches a certain value (≤1) depending on the initial storage. Moreover, the derived equation leads to the exact SCS-CN method when initial water storage is 0. Therefore, the new distribution function for soil water storage capacity explains the SCS-CN method as a saturation excess runoff model and unifies the surface runoff modeling of the SCS-CN method and the VIC type of model.
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Jani, Janmaizatulriah, Wardah Tahir, and Marfiah Ab. Wahid. "Analysis on the Effect of Land Use Changes on Flooding Using SCS Method and GIS." Scientific Research Journal 4, no. 2 (2007): 27. http://dx.doi.org/10.24191/srj.v4i2.5657.
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The research investigated the effect of land use changes on flood estimation by focusing on a widely used method developed by the US Soil Conservation Services, namely SCS Curve Number method. This method was developed to estimate the peak flow and flood hydrograph based on several parameters, one of it is known as the Curve Number (CN). The CN which can be measured effectively using GIS is an indirect measure of soil potential storage and is dependent on the land use. The research explored the feasibility of the method to Malaysian catchments by firstly, analysed the CN in a small urban catchment of UiTM campus at Shah Alam and secondly compared the hydrograph calculated by the method with the observed ones. The results indicated a close proximity of the CN values obtained from the observed rainfall runoff and the values published by the US SCS (around 8 % difference). In addition, comparison between observed unit hydrographs and SCS unit hydrographs for the same rainfall duration indicated that the estimated values of peak discharge from the synthetic method were not very far from the observed values. Finally, it was shown that changes in land use especially during urbanization process would increase the peak flow, hence increase the possibility of flooding.
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Jani, Janmaizatulriah, Wardah Tahir, and Marfiah Abd. Wahid. "Analysis on the Effect of Land Use Changes on Flooding Using SCS Method and GIS." Scientific Research Journal 4, no. 2 (2007): 27. http://dx.doi.org/10.24191/srj.v4i2.9342.
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The research investigated the effect of land use changes on flood estimation by focusing on a widely used method developed by the US Soil Conservation Services, namely SCS Curve Number method. This method was developed to estimate the peak flow and flood hydrograph based on several parameters, one of it is known as the Curve Number (CN). The CN which can be measured effectively using GIS is an indirect measure of soil potential storage and is dependent on the land use. The research explored the feasibility of the method to Malaysian catchments by firstly, analysed the CN in a small urban catchment of UiTM campus at Shah Alam and secondly compared the hydrograph calculated by the method with the observed ones. The results indicated a close proximity of the CN values obtained from the observed rainfall runoff and the values published by the US SCS (around 8 % difference). In addition, comparison between observed unit hydrographs and SCS unit hydrographs for the same rainfall duration indicated that the estimated values of peak discharge from the synthetic method were not very far from the observed values. Finally, it was shown that changes in land use especially during urbanization process would increase the peak flow, hence increase the possibility of flooding.
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Matomela, Nametso, Li Tianxin, Lehlohonolo Morahanye, Obadia Kyetuza Bishoge, and Harrison Odion Ikhumhen. "Rainfall-runoff estimation of Bojiang lake watershed using SCS-CN model coupled with GIS for watershed management." Journal of Applied and Advanced Research 4, no. 1 (2019): 16. http://dx.doi.org/10.21839/jaar.2019.v4i1.263.
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A proper understanding of watershed spatio-temporal hydrological characteristics is critical to the management of a watershed and its natural resources such as water and vegetation. Rainfall runoff estimation plays an important role as an integral part of watershed management. Runoff volume and distribution data provides valuable information for water management strategies such as selection of artificial water abstraction sites, water storage facilities, and soil erosion control strategies. In the present study Bojiang lake watershed was used to indicate the application of Soil Conservation Service Curve Number method (SCS-CN) coupled with Geographic Information System (GIS) and Remote Sensing (RS) techniques. The watershed falls within Erdos Larus Relictus National Nature Reserve (ELRNNR) which was listed under the wetlands of international importance in 2002. Rainfall runoff is influenced by a variety of factors within a watershed such as soil and land use/cover types, soil moisture content, rainfall, drainage density, and shape and size of the watershed. The SCS Curve number is the most popular and widely applied method for runoff estimation. GIS and Remote Sensing play an important role in estimating surface runoff by SCS-CN method. ArcGIS 10.2 software was used to overlay different thematic layers and develop an attribute table and calculate a weighted curve number. The weighted curve number was applied to the SCS-CN equations to estimate daily, monthly, and yearly runoff. Correlation coefficient (r) was used to test for the relationship between rainfall and runoff, and verify the computation of the method. The results show an average runoff of 17.78 mm which is about 7.18% of the annual average rainfall for the years 2001-2016. The derived output maps can assist in identifying suitable areas for water recharge/abstraction. The study demonstrates that SCS-CN in conjunction with GIS and RS can be used to calculate runoff for ungagged watersheds and assist in watershed management strategies.
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Sishah, Shimelis. "Rainfall runoff estimation using GIS and SCS-CN method for awash river basin, Ethiopia." International Journal of Hydrology 5, no. 1 (2021): 33–37. http://dx.doi.org/10.15406/ijh.2021.05.00263.
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Understanding hydrological behavior is an important part of effective watershed management and planning. Runoff resulted from rainfall is a component of hydrological behavior that is needed for efficient water resource planning. In this paper, GIS based SCS-CN runoff simulation model was applied to estimate rainfall runoff in Awash river basin. Global Curve Number (GCN250), Maximum Soil Water Retention (S) and Rainfall was used as an input for SCS-CN runoff simulation model. The final surface runoff values for the Awash river basin were generated on the basis of total annual rainfall and maximum soil water retention potential (S) of the year 2020. Accordingly, a runoff variation that range from 83.95 mm/year to a maximum of 1,416.75 mm/year were observed in the study region. Conversely, recently developed Global Curve Number (GCN250) data was tested with Pearson correlation coefficient to be used as an input for SCS-CN runoff simulation model. In doing so, predicted runoff generated in SCS-CN using GCN250 as a model input was validated with observed runoff obtained from station gauges in the study region. The results of validation show that, predicted runoff was well correlated with observed runoff with correlation coefficient of 0.9253. From this stand point, it is observed that the new GCN250 data can be used as an input for SCS-CN model to estimate rainfall runoff at basin level. Furthermore, correlation analysis was performed to explain the relationship between mean annual rainfall and surface runoff. The relationship between these two variables indicates a strong linear relationship with correlation coefficient of 0.9873.
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Soulis, Konstantinos X. "Soil Conservation Service Curve Number (SCS-CN) Method: Current Applications, Remaining Challenges, and Future Perspectives." Water 13, no. 2 (2021): 192. http://dx.doi.org/10.3390/w13020192.
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Raja, Viji. "Gis Based SCS - CN Method For Estimating Runoff In Kundahpalam Watershed, Nilgries District, Tamilnadu." Earth Sciences Research Journal 19, no. 1 (2015): 59–64. http://dx.doi.org/10.15446/esrj.v19n1.44714.
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<p>Divination and determination of catchment surface runoff are the most important contestable process of hydrology. Soil Conservation Service - Curve Number (SCS – CN) method is employed to estimate the runoff. It is one of the physical based and spatially distributed hydrological models. In this model, the curve number is a primary factor used for runoff calculation. The selection of curve number is based on the land use pattern and HSG (Hydrological Soil Group) present in the study area. Since the spatial distribution of CN estimation by the conventional way is very difficult and time consuming, the GIS (Geographic Information System) based CN method is generated for Kundapallam watershed. With the combination of land use and HSG the estimated composite CN for AMC (Antecedent Moisture Condition) I, AMC II and AMC III for the entire watershed was about 48, 68 and 83 respectively. The average annual runoff depth estimated by SCS-CN method for the average annual rainfall of 173.5 mm was found to be 72.5 mm. The obtained results were comparable to measured runoff in the watershed.</p><p> </p><p><strong>Resumen</strong></p>La predicción y la determinación del caudal de escorrentía de una cuenca son procesos de amplio debate en la hidrología. El método coeficiente de escurrimiento, del Servicio de Conservación de Suelos (SCS-CN, inglés) fue utilizado en este trabajo para estimar la escorrentía. Este es uno de los modelos hidrológicos basados en conceptos físicos y distribución espacial. En este modelo el coeficiente de escurrimiento es un factor de relevancia para el cálculo de la escorrentía. La selección del coeficiente de escurrimiento está basada en los patrones del uso de la tierra y del Grupo de Suelos Hidrológicos (HSG, inglés) relativos a esta área de estudio. Debido a que la estimación del coeficiente de escurrimiento en la distribución espacial es compleja, para la cuenca Kundapallam se implementó un método a partir de un Sistema de Información Geográfica (GIS, inglés), y basado en el coeficiente de escurrimiento. Con la combinación del uso de suelos y el HSG, la estimación compuesta del coeficiente de escurrimiento para el Antecedente de Condición de Humedad AMCI, AMCII y AMCIII para toda la cuenca fue de 48, 68 y 83. El promedio anual de escorrentía profunda estimada por el método SCS-CN con una media anual de lluvia de 173,5 mm fue de 72,5 mm. Los resultados fueron comparados con la escorrentía medida en la cuenca.
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Muzik, I., and S. J. Pomeroy. "A geographic information system for prediction of design flood hydrographs." Canadian Journal of Civil Engineering 17, no. 6 (1990): 965–73. http://dx.doi.org/10.1139/l90-108.
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A geographic information system (GIS) supporting a flood hydrograph prediction software package is described. The hydrograph prediction method is based on the convolution of excess rainfall with a synthetic unit hydrograph, derived by the Soil Conservation Service runoff curve number and a regional dimensionless unit hydrograph method, respectively. The GIS uses a raster method to store the following data: land use and land cover, soil type, rainfall intensity–frequency–duration statistics, runoff curve numbers (CN), regional dimensionless unit hydrograph, and regional lag-time relationship. The GIS has also the capability of computing a number of watershed and hydrologic parameters required for predictions, such as a watershed average rainfall and CN value, area, centroid, stream length, etc. Most of the data for such computations are input from a digitizer. Substantial time and cost savings are possible once the data base has been created. Application of the system is illustrated by an example of predicting flood frequency curves for selected watersheds in Alberta's Rocky Mountain foothills. Key words: geographic information system, flood hydrograph, curve number, hydrologic simulation, flood frequency.
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Banasik, Kazimierz, Adam Krajewski, Anna Sikorska, and Leszek Hejduk. "Curve Number Estimation for a Small Urban Catchment from Recorded Rainfall-Runoff Events." Archives of Environmental Protection 40, no. 3 (2014): 75–86. http://dx.doi.org/10.2478/aep-2014-0032.
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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.
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Ling, Lloyd, Zulkifli Yusop, Wun-She Yap, Wei Lun Tan, Ming Fai Chow, and Joan Lucille Ling. "A Calibrated, Watershed-Specific SCS-CN Method: Application to Wangjiaqiao Watershed in the Three Gorges Area, China." Water 12, no. 1 (2019): 60. http://dx.doi.org/10.3390/w12010060.
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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.
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Kovář, P., D. Fedorova, and H. Bačinová. "Implementation of the curve number method and the KINFIL model in the Smeda Catchment to mitigate overland flow with the use of terraces." Soil and Water Research 13, No. 2 (2018): 98–107. http://dx.doi.org/10.17221/163/2017-swr.
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The Smeda catchment, where the Smeda Brook drains an area of about 26 km<sup>2</sup>, is located in northern Bohemia in the Jizerské hory Mts. This experimental mountain catchment with the Bily Potok downstream gauge profile was selected as a model area for simulating extreme rainfall-runoff processes, using the KINFIL model supplemented by the Curve Number (CN) method. The combination of methods applied here consists of two parts. The first part is an application of the CN theory, where CN is correlated with hydraulic conductivity K<sub>s</sub> of the soil types, and also with storage suction factor S<sub>f</sub> at field capacity FC: CN = f(K<sub>s</sub>, S<sub>f</sub>). The second part of the combined KINFIL/CN method, represented by the KINFIL model, is based on the kinematic wave method which, in combination with infiltration, mitigates the overland flow. This simulation was chosen as an alternative to an enormous amount of field measurements. The combination used here was shown to provide a successful method. However, practical application would require at least four sub-catchments, so that more terraces can be placed. The provision of effective measures will require more investment than is currently envisaged.
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Tikno, Sunu, Teguh Hariyanto, Nadjadji Anwar, Asep Karsidi, and Edvin Aldrian. "APLIKASI METODE CURVE NUMBER UNTUK MEMPRESENTASIKAN HUBUNGAN CURAH HUJAN DAN ALIRAN PERMUKAAN DI DAS CILIWUNG HULU – JAWA BARAT." Jurnal Teknologi Lingkungan 13, no. 1 (2016): 25. http://dx.doi.org/10.29122/jtl.v13i1.1402.
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Aliran permukaan/limpasan (run off) merupakan salah satu variabel hidrologi yang sangat penting di dalam menunjang kegiatan pengembangan sumber daya air. Metode prediksi yang handal untuk menghitung jumlah dan laju limpasan yang berasal dari permukaan tanah dan bergerak menuju sungai di suatu DAS yang tidak dilengkapi alat ukur (ungaged watershed) adalah suatu pekerjaan yang sangat sulit dan memerlukanwaktu yang banyak. Penelitian ini dilakukan di DAS Ciliwung Hulu, yang merupakan daerah penting dalam kotribusi banjir di Jakarta. Untuk mengetahaui run off yang terjadi, digunakan data curah hujan dan debit Tahun 2007-2009. Sebagai model, untuk mengetahui run off menggunakan peta penggunaan lahan, peta jenis tanah, dan topografi. Peta-peta tersebut diolah dengan menggunakan Arcview, sehingga didapatkannilai CN. Berdasarkan analisis perhitungan, besarnya debit mendekati 50% dari tebal hujan. Kondisi ini mengindikasikan bahwa kondisi DAS Ciliwung Hulu sudah tidak mampu lagi menyerap curah hujan dengan baik. Korelasi antara hasil prediksi run off model yang menggunakan CN dengan perhitungan run off observasi cukup baik. Hal ini menunjukkan bahwa metode Curve Number cukup dapat mepresentaskan hubungancurah hujan dengan aliran permukaan (run off). kata kunci : Run off observasi, run off model, curve number AbstractRun off (surface flow) is one of the most important hydrological variable in supporting the activities of water resources development. A reliable prediction method to calculate the amount and rate of runoff from the land surface caused by the rain that falls in a watershed that is not equipped with measuring devices (un gauge watershed) is a verydifficult job and requires a lot of time. The research was conducted in the watershed Ciliwung Hulu, which is an important area in relation to the incidence of flooding in Jakarta. Curve Number (CN) method can be used to predict the amount of runoff from a watershed. This model required input of rainfall; land cover maps; soil type maps,and topography. The maps are processed using Arc View software, so we get the value of CN. In this study, we used of rainfall and discharge data 2007-2009. Based on the analysis of calculation, known that amount of surface flow approaching 50% of rainfall depth. This condition indicates that the Ciliwung Hulu watershed conditions were not ableand proper to absorb of rainfall. The correlation between the results of run-off prediction models using CN with run-off observation was quite good. This indicated that the Curve Number method could be able to represent the relationship of rainfall with surface flow (run off) and also to predict runoff key words: Run off observation, run-off model, curve number
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hoseinzadeh, mohammad mahdi, and sepide imeni. "Estimating Height runoff by using curve number method and Arc- CN Runoff tool in Afjeh Catchment." Journal of Spatial Analysis Environmental Hazarts 5, no. 2 (2018): 91–106. http://dx.doi.org/10.29252/jsaeh.5.2.91.
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Munna, Gulam Md, Md Jahir Bin Alam, Md Misbah Uddin, Nabila Islam, Afrida Ahmed Orthee, and Khairul Hasan. "Runoff prediction of Surma basin by curve number (CN) method using ARC-GIS and HEC-RAS." Environmental and Sustainability Indicators 11 (September 2021): 100129. http://dx.doi.org/10.1016/j.indic.2021.100129.
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Kohnová, Silvia, Agnieszka Rutkowska, Kazimierz Banasik, and Kamila Hlavčová. "The L-moment based regional approach to curve numbers for Slovak and Polish Carpathian catchments." Journal of Hydrology and Hydromechanics 68, no. 2 (2020): 170–79. http://dx.doi.org/10.2478/johh-2020-0004.
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AbstractThe main objective of the paper was to propose and evaluate the performance of a regional approach to estimate CN values and to test the impact of different initial abstraction ratios. The curve number (CN) was analyzed for five Slovak and five Polish catchments situated in the Carpathian Mountains. The L-moment based method of Hosking and Wallis and the ANOVA test were combined to delineate the area in two homogenous regions of catchments with similar CN values. The optimization condition enabled the choice of the initial abstraction ratio, which provided the smallest discrepancy between the tabulated and estimated CNs and the antecedent runoff conditions. The homogeneity in the CN within the regions of four Slovak and four Polish catchments was revealed. Finally, the regional CN was proposed to be at the 50% quantile of the regional theoretical distribution function estimated from all the CNs in the region.The approach is applied in a group of Slovak and Polish catchments with physiographic conditions representative for the Carpathian region. The main benefit of introducing a common regional CN is the opportunity to apply this procedure in catchments of similar soil-physiographic characteristics and to verify the existing tabulated CN. The paper could give rise to an alternative way of estimating the CN values in forested catchments and catchments with a lack of data or without observations.
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Song, Chul Min. "Hydrological Image Building Using Curve Number and Prediction and Evaluation of Runoff through Convolution Neural Network." Water 12, no. 8 (2020): 2292. http://dx.doi.org/10.3390/w12082292.
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This study developed a runoff model using a convolution neural network (CNN), which had previously only been used for classification problems, to get away from artificial neural networks (ANNs) that have been extensively used for the development of runoff models, and to secure diversity and demonstrate the suitability of the model. For this model’s input data, photographs typically used in the CNN model could not be used; due to the nature of the study, hydrological images reflecting effects such as watershed conditions and rainfall were required, which posed further difficulties. To address this, the method of a generating hydrological image using the curve number (CN) published by the Soil Conservation Service (SCS) was suggested in this study, and the hydrological images using CN were found to be sufficient as input data for the CNN model. Furthermore, this study was able to present a new application for the CN, which had been used only for estimating runoff. The model was trained and generalized stably overall, and R2, which indicates the relationship between the actual and predicted values, was relatively high at 0.82. The Pearson correlation coefficient, Nash–Sutcliffe efficiency (NSE), and root mean square error (RMSE), were 0.87, 0.60, and 16.20 m3/s, respectively, demonstrating a good overall model prediction performance.
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Kang, Minseok, and Chulsang Yoo. "Application of the SCS–CN Method to the Hancheon Basin on the Volcanic Jeju Island, Korea." Water 12, no. 12 (2020): 3350. http://dx.doi.org/10.3390/w12123350.
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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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Soulis, K. X., and J. D. Valiantzas. "SCS-CN parameter determination using rainfall-runoff data in heterogeneous watersheds. The two-CN system approach." Hydrology and Earth System Sciences Discussions 8, no. 5 (2011): 8963–9004. http://dx.doi.org/10.5194/hessd-8-8963-2011.
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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 values can be estimated by being selected from tables. However, it is more accurate to estimate the CN value from measured rainfall-runoff data (assumed available) in a watershed. Previous researchers indicated that the CN values calculated from measured rainfall-runoff data vary systematically with the rainfall depth. 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 novel hypothesis that the observed correlation between the calculated CN value and the rainfall depth in a watershed reflects the effect of the inevitable presence of soil-cover complex spatial variability along watersheds 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 behavior of the CN-rainfall function produced by the proposed two-CN system concept is approached theoretically, it is analyzed 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 original method 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.
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Jain, M. K., S. K. Mishra, P. Suresh Babu, and K. Venugopal. "On the Ia–S relation of the SCS-CN method." Hydrology Research 37, no. 3 (2006): 261–75. http://dx.doi.org/10.2166/nh.2006.011.
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The initial abstraction (Ia) versus maximum potential retention (S) relation in the Soil Conservation Service Curve Number (SCS-CN) methodology was revisited, and a new non-linear relation incorporating storm rainfall (P) and S was proposed and tested on a large set of storm rainfall-runoff events derived from the water database of United States Department of Agriculture-Agriculture Research Service (USDA-ARS). Employing root mean square error (RMSE), the performance of both the existing and proposed models was evaluated using the complete database, and for model calibration and validation, data were split into two groups: based on ordered rainfall (P-based) and runoff (Q-based). A specific formulation of the proposed model Ia=λS(P/(P+S))α with λ=0.3 and α=1.5 was found to generally perform better than the existing Ia=0.2S, and therefore was recommended for field applications. When evaluated using the observed Ia data, the proposed version performed significantly better than the existing one.
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Malamassam, Miranda R., and Sandra E. Pakasi. "ANALISIS PERUBAHAN BILANGAN KURVA ALIRAN PERMUKAAN PADA BEBERAPA SKENARIO PEMANFAATAN LAHAN DI SUB DAS LATOMA, DAS KONAWEHA, SULAWESI TENGGARA." PERENNIAL 3, no. 1 (2007): 19. http://dx.doi.org/10.24259/perennial.v3i1.166.
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Sub watershed of Latoma has to be considered as an area of the important regions in South East Sulawesi, because it takes a great responsibility as a water supplier in Konaweha watershed. Konaweha watershed is a source of irrigation and domestic water for Kolaka Regency, Konawe Regency, South Konawe Regency and Kendari Municipality which has been recently in a critical condition. For this reason, it should be well managed. This study was implemented with the aim of establishing model of land use in Latoma sub watershed that can preserve the land and water resources. The method employs a system analysis with simulation technique by using the Run-off Curve Number (CN) model based on Geographical Information Systems (GIS). The result of the research revealed that the run-off curve number is 70,34. It showed that maximum potential water retention or infiltration rate is 107,10 mm. Restructuring of land use pattern should be done to improve the condition of the area to achieve a sustainability objectives. Keywords : Watershed, land use, run-off curve number (CN), GIS
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Panjabi, Kishore, Ramesh Rudra, Pradeep Goel, Syed Ahmed, and Bahram Gharabaghi. "A Modified Distributed CN-VSA Method for Mapping of the Seasonally Variable Source Areas." Water 13, no. 9 (2021): 1270. http://dx.doi.org/10.3390/w13091270.
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Many watershed models employ the Soil Conservation Service Curve Number (SCS-CN) approach for runoff simulation based on soil and land use information. These models implicitly assume that runoff is generated by the Hortonian process and; therefore, cannot correctly account for the effects of topography, variable source area (VSA) and/or soil moisture distribution in a watershed. This paper presents a new distributed CN-VSA method that is based on the SCS-CN approach to estimate runoff amount and uses the topographic wetness index (TWI) to distribute the runoff-generating areas within the watershed spatially. The size of the saturated-watershed areas and their spatial locations are simulated by assuming an average annual value of potential maximum retention. However, the literature indicates significant seasonal variation in potential maximum retention which can considerably effect water balance and amount of nonpoint source pollution. This paper focuses on developing a modified distributed CN-VSA method that accounts for the seasonal changes in the potential maximum retention. The results indicate that the modified distributed CN-VSA approach is better than distributed CN-VSA to simulate runoff amount and spatial distribution of runoff-generating areas. Overall, the study results are significant for improved understanding of hydrological response of watershed where seasonal factors describe the potential maximum retention, and, thus, saturation excess runoff generation in the watershed.
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Fan, Fenglei, Yingbin Deng, Xuefei Hu, and Qihao Weng. "Estimating Composite Curve Number Using an Improved SCS-CN Method with Remotely Sensed Variables in Guangzhou, China." Remote Sensing 5, no. 3 (2013): 1425–38. http://dx.doi.org/10.3390/rs5031425.
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Verma, S., P. K. Singh, S. K. Mishra, V. P. Singh, Vishal Singh, and A. Singh. "Activation soil moisture accounting (ASMA) for runoff estimation using soil conservation service curve number (SCS-CN) method." Journal of Hydrology 589 (October 2020): 125114. http://dx.doi.org/10.1016/j.jhydrol.2020.125114.
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