94 citations as recorded by crossref.

1. Estimation of Initial Abstraction for Hydrological Modeling Based on Global Land Data Assimilation System–Simulated Datasets Y. Zheng et al. 10.1175/JHM-D-19-0202.1
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3. Variability of the asymptotic curve number in mountainous undeveloped arid basins based on historical data: Case study in Saudi Arabia M. Farran & A. Elfeki 10.1016/j.jafrearsci.2019.103697
4. Improving Initial Abstraction Method of NRCS-CN for Estimating Effective Rainfall D. Park et al. 10.3741/JKWRA.2015.48.6.491
5. Effects of initial abstraction ratios in SCS-CN method on runoff prediction of green roofs in a semi-arid region W. Liu et al. 10.1016/j.ufug.2021.127331
6. The analysis of urban flood risk propagation based on the modified susceptible infected recovered model P. Wang et al. 10.1016/j.jhydrol.2021.127121
7. Spatial mapping and testing the applicability of the curve number method for ungauged catchments in Northern Ethiopia D. Gebresellassie Zelelew 10.1016/j.iswcr.2017.06.003
8. Statistical analysis of NRCS curve number (NRCS-CN) in arid basins based on historical data M. Farran & A. Elfeki 10.1007/s12517-019-4993-9
9. The LTER-Greece Environmental Observatory Network: Design and Initial Achievements N. Skoulikidis et al. 10.3390/w13212971
10. GIS and remote sensing techniques for the assessment of the impact of land use change on runoff Ü. Köylü & A. Geymen 10.1007/s12517-016-2514-7
11. Ancient runoff agriculture at Early Bronze Age Jawa (Jordan): Water availability, efficiency and food supply capacity J. Meister et al. 10.1016/j.jasrep.2016.06.033
12. Excess Stormwater Quantification in Ungauged Watersheds Using an Event-Based Modified NRCS Model M. Ajmal et al. 10.1007/s11269-016-1231-z
13. Empirical Investigation of Curve Number Method Parameters in the Mediterranean Area F. D’Asaro & G. Grillone 10.1061/(ASCE)HE.1943-5584.0000570
14. Particulate nutrient loss from drylands to grasslands/forestlands in a large-scale highly erodible watershed L. Wu et al. 10.1016/j.ecolind.2019.105673
15. Evaluating Pre- and Post-Fire Peak Discharge Predictions across Western U.S. Watersheds A. Kinoshita et al. 10.1111/jawr.12226
16. Curve Numbers Seasonal Variation in Mid-Mediterranean Area F. D’Asaro et al. 10.1061/(ASCE)IR.1943-4774.0001334
17. On relationship between curve numbers and phi indices D. Chin 10.1016/j.wse.2018.09.006
18. Land Use Effect on the CN Model Parameters in a Tropical Dry Environment E. Andrade et al. 10.1007/s11269-017-1732-4
19. SCS Curve Number and Green-Ampt Infiltration Models G. Baiamonte 10.1061/(ASCE)HE.1943-5584.0001838
20. Influence of hydrological runoff and catchment characteristics on accumulation floatable litter load in gross pollutant trap (GPT) N. Malik et al. 10.1007/s10163-021-01205-8
21. Accounting for Spatiotemporal Variations of Curve Number Using Variable Initial Abstraction and Antecedent Moisture V. Santikari & L. Murdoch 10.1007/s11269-018-2124-0
22. Sensitivity and fuzzy uncertainty analyses in the determination of SCS-CN parameters from rainfall–runoff data S. Hosseini & N. Mahjouri 10.1080/02626667.2018.1437272
23. Effects of Spatial Distribution of Prairie Vegetation in an Agricultural Landscape on Curve Number Values D. Dziubanski et al. 10.1111/1752-1688.12510
24. Assessment of Soil and Water Conservation Practices in the Loess Hilly Region Using a Coupled Rainfall-Runoff-Erosion Model M. Cai et al. 10.3390/su12030934
25. Hydrological Response of Natural Mediterranean Watersheds to Forest Fires K. Soulis et al. 10.3390/hydrology8010015
26. Development of a Model to Identify the Flow at any Location of an Ungauged Stream for Selection of Sites for Small Hydel in the Kalimpong Subdivision of West Bengal P. Paul & S. Das 10.1007/s12594-018-0833-x
27. Distributed rainfall-runoff modelling for flood frequency estimation and flood forecasting L. Brocca et al. 10.1002/hyp.8042
28. SCS-CN parameter determination using rainfall-runoff data in heterogeneous watersheds – the two-CN system approach K. Soulis & J. Valiantzas 10.5194/hess-16-1001-2012
29. Impact of Monthly Curve Number on Daily Runoff Estimation for Ozat Catchment in India M. Gundalia & M. Dholakia 10.4236/ojmh.2014.44014
30. A Pragmatic Slope-Adjusted Curve Number Model to Reduce Uncertainty in Predicting Flood Runoff from Steep Watersheds M. Ajmal et al. 10.3390/w12051469
31. Sources of uncertainty in the NRCS CN model: Recognition and solutions P. Durán-Barroso et al. 10.1002/hyp.11305
32. Hydrological modelling for flood forecasting: Calibrating the post-fire initial conditions C. Papathanasiou et al. 10.1016/j.jhydrol.2015.07.038
33. A CN-Based Ensembled Hydrological Model for Enhanced Watershed Runoff Prediction M. Ajmal et al. 10.3390/w8010020
34. Green-Ampt Curve-Number mixed procedure as an empirical tool for rainfall-runoff modelling in small and ungauged basins S. Grimaldi et al. 10.1002/hyp.9303
35. A GIS-Based Approach for the Sustainable Management of Livestock Effluents on Alpine Meadows F. Gubert et al. 10.3389/fsufs.2018.00055
36. Application of the SCS–CN Method to the Hancheon Basin on the Volcanic Jeju Island, Korea M. Kang & C. Yoo 10.3390/w12123350
37. The Role of the Spatial Distribution of Radar Rainfall on Hydrological Modeling for an Urbanized River Basin in Japan S. P. C. et al. 10.3390/w11081703
38. Estimation of Peak Discharges under Different Rainfall Depth–Duration–Frequency Formulations A. Gioia et al. 10.3390/hydrology8040150
39. Evaluation of the Soil Conservation Service curve number methodology using data from agricultural plots M. Lal et al. 10.1007/s10040-016-1460-5
40. Adjustment to the curve number (NRCS-CN) to account for the vegetation effect on hydrological processes A. Gonzalez et al. 10.1080/02626667.2014.898119
41. Relationship between Curve Number and ϕ-Index N. Karpathy & D. Chin 10.1061/(ASCE)IR.1943-4774.0001426
42. Drying Urban lakes: A consequence of climate change, urbanization or other anthropogenic causes? An insight from northern India D. Singh & N. Singh 10.1111/lre.12262
43. Runoff Curve Numbers for Peat-Dominated Watersheds M. Menberu et al. 10.1061/(ASCE)HE.1943-5584.0001038
44. Improved Algorithm of SCS-CN Model Parameters in Typical Inland River Basin in Central Asia J. Wang et al. 10.1088/1755-1315/57/1/012051
45. Effect of the North Atlantic Oscillation on winter daily rainfall and runoff in the Abruzzo region (Central Italy) L. Vergni et al. 10.1007/s00477-015-1194-2
46. Comparison of conceptual rainfall–runoff models in semi‐arid watersheds of eastern Algeria I. Abdi & M. Meddi 10.1111/jfr3.12672
47. An Improved SCS-CN Method Incorporating Slope, Soil Moisture, and Storm Duration Factors for Runoff Prediction W. Shi & N. Wang 10.3390/w12051335
48. Comparison of SCS-CN determination methodologies in a heterogeneous catchment A. Walega et al. 10.1007/s11629-015-3592-9
49. Development of a robust runoff-prediction model by fusing the Rational Equation and a modified SCS-CN method X. Wang et al. 10.1080/02626667.2012.701305
50. Identifying areas sensitive to land use/land cover change for downstream flooding in a coastal Alabama watershed N. Noori et al. 10.1007/s10113-016-0931-5
51. A revisit of NRCS-CN inspired models coupled with RS and GIS for runoff estimation S. Verma et al. 10.1080/02626667.2017.1334166
52. Physical verification of the effect of land features and antecedent moisture on runoff curve number M. Lal et al. 10.1016/j.catena.2015.06.001
53. Curve Numbers for Olive Orchard Catchments: Case Study in Southern Spain E. Taguas et al. 10.1061/(ASCE)IR.1943-4774.0000892
54. Uncertainty Estimation of HEC-HMS Flood Simulation Model using Markov Chain Monte Carlo Algorithm م. نورعلی et al. 10.29252/jwmr.8.15.235
55. Stability assessment of the curve number methodology used to estimate excess rainfall in forest-dominated watersheds M. Ajmal et al. 10.1007/s12517-016-2421-y
56. Investigation of the direct runoff generation mechanism for the analysis of the SCS-CN method applicability to a partial area experimental watershed K. Soulis et al. 10.5194/hess-13-605-2009
57. Effect of formal and informal likelihood functions on uncertainty assessment in a single event rainfall-runoff model M. Nourali et al. 10.1016/j.jhydrol.2016.06.022
58. Reconstructing the Tropical Storm Ketsana flood event in Marikina River, Philippines C. Abon et al. 10.5194/hess-15-1283-2011
59. Derivation of Soil Moisture Recovery Relation Using Soil Conservation Service (SCS) Curve Number Method J. Kim et al. 10.3390/w10070833
60. Damage assessment of infrastructure based on urban flood inundation simulation Z. Yifan et al. 10.1051/e3sconf/202019405056
61. A review of the current state of process-based and data-driven modelling: guidelines for Lake Erie managers and watershed modellers A. Neumann et al. 10.1139/er-2020-0070
62. A Web-Based Model to Estimate the Impact of Best Management Practices Y. Park et al. 10.3390/w6030455
63. Runoff Estimation Using the NRCS Slope-Adjusted Curve Number in Mountainous Watersheds M. Ajmal et al. 10.1061/(ASCE)IR.1943-4774.0000998
64. Evaluation and validity of the antecedent moisture condition (AMC) of Natural Resources Conservation Service-Curve Number (NRCS-CN) procedure in undeveloped arid basins M. Farran & A. Elfeki 10.1007/s12517-020-5242-y
65. Urban Flood Depth Estimate With a New Calibrated Curve Number Runoff Prediction Model L. Ling et al. 10.1109/ACCESS.2020.2964898
66. Improvement of SCS-CN Initial Abstraction Coefficient in the Czech Republic: A Study of Five Catchments M. Caletka et al. 10.3390/w12071964
67. Development of a fully-distributed daily hydrologic feedback model addressing vegetation, land cover, and soil water dynamics (VELAS) C. Park et al. 10.1016/j.jhydrol.2013.04.027
68. Quantifying Excess Stormwater Using SCS-CN–Based Rainfall Runoff Models and Different Curve Number Determination Methods M. Ajmal & T. Kim 10.1061/(ASCE)IR.1943-4774.0000805
69. Curve Number: Empirical Evaluation and Comparison with Curve Number Handbook Tables in Sicily F. D’Asaro et al. 10.1061/(ASCE)HE.1943-5584.0000997
70. Anomalous Behavior of the Curve-Number Infiltration Model D. Chin 10.1061/(ASCE)IR.1943-4774.0001381
71. Research on the SCS-CN initial abstraction ratio using rainfall-runoff event analysis in the Three Gorges Area, China Z. Shi et al. 10.1016/j.catena.2008.11.006
72. New Paradigm for Sizing Riparian Buffers to Reduce Risks of Polluted Storm Water: Practical Synthesis M. Walter et al. 10.1061/(ASCE)0733-9437(2009)135:2(200)
73. Initial abstraction and curve numbers for semiarid watersheds in Southeastern Arizona Y. Yuan et al. 10.1002/hyp.9592
74. Investigation of SCS-CN and its inspired modified models for runoff estimation in South Korean watersheds M. Ajmal et al. 10.1016/j.jher.2014.11.003
75. Evaluation of urban growth effects on surface runoff using SCS-CN method and Green-Ampt infiltration model C. Suribabu & J. Bhaskar 10.1007/s12145-014-0193-z
76. Sediment Reallocations due to Erosive Rainfall Events in the Three Gorges Reservoir Area, Central China F. Stumpf et al. 10.1002/ldr.2503
77. Climate change, water supply and environmental problems of headwaters: The paradigmatic case of the Tiber, Savio and Marecchia rivers (Central Italy) L. Di Matteo et al. 10.1016/j.scitotenv.2017.04.153
78. Estimation of SCS Curve Number variation following forest fires K. Soulis 10.1080/02626667.2018.1501482
79. SCS-CN-Based Improved Models for Direct Surface Runoff Estimation from Large Rainfall Events R. Verma et al. 10.1007/s11269-021-02831-5
80. Improving Curve Number Based Storm Runoff Estimates Using Soil Moisture Proxies H. Beck et al. 10.1109/JSTARS.2009.2031227
81. Deficiencies in the Curve Number Method D. Chin 10.1061/(ASCE)IR.1943-4774.0001552
82. The Use of Asymptotic Functions for Determining Empirical Values of CN Parameter in Selected Catchments of Variable Land Cover A. Wałęga et al. 10.1515/sgem-2017-0041
83. Coupling the modified SCS-CN and RUSLE models to simulate hydrological effects of restoring vegetation in the Loess Plateau of China G. Gao et al. 10.5194/hess-16-2347-2012
84. A micro focus with macro impact: Exploration of initial abstraction coefficient ratio (λ) in Soil Conservation Curve Number (CN) methodology L. Ling & Z. Yusop 10.1088/1755-1315/18/1/012121
85. Comparison of design peak flow estimation methods for ungauged basins in Iran A. Petroselli et al. 10.1080/02626667.2019.1686506
86. Étude de l'impact de l'extension et de la densification du tissu urbain sur les coefficients de ruissellement dans le bassin versant des oueds El-Ghrich et El-Greb (Tunis) par l'application de la méthode SCS aux évènement N. Fehri & Y. Zahar 10.4000/physio-geo.4769
87. Feasible Ranges of Runoff Curve Numbers for Korean Watersheds Based on the Interior Point Optimization Algorithm J. Lee et al. 10.1007/s12205-019-0901-9
88. A Calibrated, Watershed-Specific SCS-CN Method: Application to Wangjiaqiao Watershed in the Three Gorges Area, China L. Ling et al. 10.3390/w12010060
89. Including effects of watershed heterogeneity in the curve number method using variable initial abstraction V. Santikari & L. Murdoch 10.5194/hess-22-4725-2018
90. On the possibilities of watershed parameterization for extreme flow estimation in ungauged basins S. Kohnová et al. 10.5194/piahs-370-171-2015
91. The L-moment based regional approach to curve numbers for Slovak and Polish Carpathian catchments S. Kohnová et al. 10.2478/johh-2020-0004
92. Probabilistic properties of a curve number: A case study for small Polish and Slovak Carpathian Basins A. Rutkowska et al. 10.1007/s11629-014-3123-0
93. Sensitivity and fuzzy uncertainty analyses in the determination of SCS-CN parameters from rainfall–runoff data S. Hosseini & N. Mahjouri 10.1080/02626667.2018.1437272
94. The LTER-Greece Environmental Observatory Network: Design and Initial Achievements N. Skoulikidis et al. 10.3390/w13212971