The L-moment based regional approach to curve numbers for Slovak and Polish Carpathian catchments

Adamowski, K., 2000. Regional analysis of annual maximum and partial duration flood data by nonparametric and L-moment methods. J. Hydrol., 229, 219–231.10.1016/S0022-1694(00)00156-6Search in Google Scholar

Ajmal, M., Wassem, M., Ahn, J.-H., Kim, T.-W., 2015. Improved runoff estimation using event-based rainfall-runoff models. Water Resour. Manag., 29, 6, 1995–2010. http://dx.doi.org/10.1007/s11269-015-0924-z.10.1007/s11269-015-0924-zSearch in Google Scholar

Arnold, J.G., Williams, J.R., Srinivasan, R., King, K.W., 1995. SWAT: Soil Water Assessment Tool. Texas Agricultural Experiment Station: Blackland Research Center, Texas A&M University, Temple, TX, USA.Search in Google Scholar

Baltas, E.A., Dervos, N.A., Mimikou, M.A., 2007. Research on the initial abstraction – storage ratio and its effect on hydrograph simulation at a watershed in Greece. Hydrol. Earth Syst. Sci. Discuss., 4, 2169–2204. DOI: 10.5194/hessd-4-2169-2007.10.5194/hessd-4-2169-2007Search in Google Scholar

Banasik, K., Ignar, S., 1983. Estimation of effective rainfall using the SCS method on the base of measured rainfall and runoff. Rev. Geophys., XXVII (3–4), 401–408. (In Polish.)Search in Google Scholar

Banasik, K., Madeyski, M., Więzik, B., Woodward, D.E. 1997. Applicability of curve number technique for runoff estimation from small Carpathian catchments. In: Proceedings of the International Conference on Developments of Hydrology of Mountainous Areas. Slovak Committee of Hydrology, Stara Lesna, Sept. 14–16, 1994, pp. 240–242. IHP-Projects, H-5-5/H-5-6, Unesco, Paris. https://unesdoc.unesco.org/ark:/48223/pf0000109610.Search in Google Scholar

Banasik, K., Woodward, D., 2010. Empirical determination of runoff curve number for a small agricultural watershed in Poland. In: Proc. 2nd Joint Federal Interagency Conference, Las Vegas: NV, USA, June 27–July 1, 2010, pp. 1–11. http://acwi.gov/sos/pubs/2ndJFIC/Contents/10E_Banasik_28_02_10.Search in Google Scholar

Banasik, K., Woodward, D.E., Hawkins, R., 2014. Curve numbers for two agro-forested watersheds. In: Proceedings of the World Environmental and Water Resources Congress “Water Without Borders”, ASCE, Portland: Oregon, USA, June 1–5, 2014, pp. 2235–2246. Abstract available at: https://ascelibrary.org/doi/10.1061/9780784413548.223.10.1061/9780784413548.223Search in Google Scholar

Banasik, K., Rutkowska, A., Kohnová, S., 2014. Retention and curve number variability in a small agricultural catchment: the probabilistic approach. Water, 6, 5, 1118–1133.10.3390/w6051118Search in Google Scholar

Bartlett, M.S., Parolari, A.J., McDonnell, J.J., Porporato, A., 2016. Beyond the SCS-CN method: A theoretical framework for spatially lumped rainfall-runoff response. Water Resour. Res., 52, 4608–4627. DOI: 10.1002/2015WR018439.10.1002/2015WR018439Search in Google Scholar

Bartlett, M.S., Parolari, A.J., McDonnell, J.J., Porporato, A., 2017. Reply to comment by Fred L. Ogden et al. on “Beyond the SCS-CN method: A theoretical framework for spatially lumped rainfall-runoff response.” Water Resour. Res., 53, 6351–6354. DOI: 10.1002/2017WR020456.10.1002/2017WR020456Search in Google Scholar

Bingner, R.L., Theurer, F.D., 2005. AnnAGNPS Technical Processes: Documentation Version 3.2. USDA-ARS, National Sedimentation Laboratory, Oxford, Miss., USA.Search in Google Scholar

Bondelid, T., McCuen, R., Jackson, T., 1982. Sensitivity of SCS Models to curve number variation. J. Am. Water Resour. As., 18, 1, 111–116.10.1111/j.1752-1688.1982.tb04536.xSearch in Google Scholar

Burn, D.H., Goel, N.K., 2000. The formation of groups for regional flood frequency analysis. Hydrolog. Sci. J., 45, 97–112. DOI: 10.1080/02626660009492308.10.1080/02626660009492308Search in Google Scholar

Castellarin, A., Burn, D.H., Brath, A., 2001. Assessing the effectiveness of hydrological similarity measures for flood frequency analysis. J. Hydrol., 241, 270–285.10.1016/S0022-1694(00)00383-8Search in Google Scholar

Cazier, D.J., Hawkins, R.H., 1984. Regional application of the curve number method. In: Proceedings of Specialty Conference, Irrigation and Drainage Division, American Society of Civil Engineers, Flagstaff, AZ, abstract, p. 710.Search in Google Scholar

Dalrymple, T., 1960. Flood Frequency Analyses, Manual of Hydrology. Water Supply Paper 1543-A, U.S. Geological Survey, Reston, USA.Search in Google Scholar

Durán-Barroso, P., González, J., Valdés, J.B., 2017. Sources of uncertainty in the NRCS CN model: recognition and solutions. Hydrol. Process., 31, 22, 3898–3906. http://dx.doi.org/10.1002/hyp.1130510.1002/hyp.11305Search in Google Scholar

Elhakeem, M., Papanicolaou, A.N., 2009. Estimation of the runoff curve number via direct rainfall simulator measurements in the state of Iowa, USA. Water Resour. Manag., 23, 12, 2455–2473. http://dx.doi.org/10.1007/s11269-008-9390-1.10.1007/s11269-008-9390-1Search in Google Scholar

Gaál, L., Kohnová, S., Szolgay, J., 2013. Regional flood frequency analysis in Slovakia: Which pooling approach suits better? In: Klijn, Schweckendiek (Eds): Comprehensive Flood Risk Management: Research for policy and practice. pp. 27–30.10.1201/b13715-7Search in Google Scholar

Gaswirth, J.L., Gel, Y.R., Miao, W., 2009. The impact of Levene’s test of equality of variances on statistical theory and practice. Stat. Sci., 24, 3, 343–360. DOI: 10.1214/09-STS301.10.1214/09-STS301Search in Google Scholar

Geetha, K., Mishra, S., Eldho, T., Rastogi, A., Pandey, R., 2007. Modifications to SCS-CN method for long-term hydrologic simulation. J. Irrig. Drain. Eng., 133, 5, 475–486.10.1061/(ASCE)0733-9437(2007)133:5(475)Search in Google Scholar

Hawkins, R., 1973. Improved prediction of storm runoff in mountain watersheds. J. Irrig. Drain. Div., 99, 4, 519–523.10.1061/JRCEA4.0000957Search in Google Scholar

Hawkins, R., 1979. Runoff Curve Numbers from Partial Area Watersheds. J. Irrig. Drain. Div., 105, 4, 375–389.10.1061/JRCEA4.0001275Search in Google Scholar

Hawkins, R., 1993. Asymptotic determination of curve numbers from data. J. Irrig. Drain. Div., 119, 334–345.10.1061/(ASCE)0733-9437(1993)119:2(334)Search in Google Scholar

Hawkins, R.H., Khojeini, A.V., 2000. Initial abstraction and loss in the curve number method. Proc. of Arizona Hydrological Society, Tucson, Arizona.Search in Google Scholar

Hawkins, R.H., Hjelmfelt, Jr. A.T., Zevenbergen, A.W., 1985. Runoff probability, storm depth, and Curve Numbers. J. Irrig. Drain. Div., 111, 4, 330–340.10.1061/(ASCE)0733-9437(1985)111:4(330)Search in Google Scholar

Hawkins, R.H., Ward, T.J., Woodward, D.E., van Mullem, J.A. (Eds.), 2009. Curve Number Hydrology: State of the Practice. American Society of Civil Engineers, Reston, VA, USA.10.1061/9780784410042Search in Google Scholar

Hitchcock, D.R., Jayakaran, A.D., Loflin, D.R., Williams, T.M., Amatya, D.M., 2013. Curve number derivation for watersheds draining two headwater streams in Lower Coastal Plain of South Carolina, USA. J. Am. Water. Resor. As., 49, 1284–1295.10.1111/jawr.12084Search in Google Scholar

Hjelmfelt, A., 1991. Investigation of curve number procedure. J. Hydraul. Eng., 117, 6, 725–737.10.1061/(ASCE)0733-9429(1991)117:6(725)Search in Google Scholar

Hjelmfelt Jr., A.T., Kramer, L.A., Burwell, R.E., 1983. Curve numbers as random variables. In: Proceedings of the Specialty Conference on Advances in Irrigation and Drainage: Surviving External Pressures. Jackson, Wy, USA, pp. 365–370.Search in Google Scholar

Hosking, J.R.M., Wallis, J.R., 1990. L-moments: analysis and estimation of distributions using linear combinations of order statistics. J. R. Stat. Soc. B., 52, 1, 105–124.10.1111/j.2517-6161.1990.tb01775.xSearch in Google Scholar

Hosking, J.R.M., Wallis, J.R., 1997. Regional Frequency Analysis. An Approach Based on L-Moments. Cambridge University Press, Cambridge, UK, 244 p.10.1017/CBO9780511529443Search in Google Scholar

Hosking, J.R.M., 2019. Regional frequency analysis using Lmoments. R package, version 3.2. URL: https://cran.rproject.org/web/packages/lmomRFA/lmomRFA.pdfSearch in Google Scholar

Jiang, R., 2001. Investigation of runoff curve number initial abstraction ratio. MS thesis. Watershed Management, University of Arizona, Tucson, AZ, 120 p.Search in Google Scholar

Jeon, J.-H., Lim, K. J., Engel, B.A., 2014. Regional calibration of CSC-CN L-THIA model: application for ungauged basins. Water, 6, 1339–1359. DOI: 10.3390/w6051339.10.3390/w6051339Search in Google Scholar

Karabová, B., Marková, R., 2013. Testing of regionalization of SCS-CN parameters in the Upper Hron River region, Slovakia. Adolf Patera Seminar 2013, Prague, Czech Republic.Search in Google Scholar

Kochanek, K., Strupczewski, W.G., Bogdanowicz, E., 2012. On seasonal approach to flood frequency modelling. Part II: flood frequency analysis of Polish rivers. Hydrol. Process., 26, 71–73. DOI: 10.1002/hyp.8178.10.1002/hyp.8178Search in Google Scholar

Kohnová, S., Szolgay, J., Solin, L., Hlavčova, K., 2006. Regional Methods for Prediction in Ungauged Basins. Case Studies. KEY Publishing s.r.o. in cooperation with the Slovak Committee for Hydrology, Bratislava.Search in Google Scholar

Kruskal, W.H., Wallis, W.A., 1952. Use of ranks in onecriterion variance analysis. J. Am. Stat. Assoc., 47, 260, 583–621.10.1080/01621459.1952.10483441Search in Google Scholar

Leonard, R.A., Knisel, W.G., Still, D.A., 1987. GLEAMS: Groundwater loading effects of agricultural management systems. Trans. ASAE, 30, 5, 1403–1418.10.13031/2013.30578Search in Google Scholar

Levene, H., 1960. Robust tests for equality of variances. In: Olkin, I., Hotteling, H. et al. (Eds.): Contributions to Probability and Statistics: Essays in Honor of Harold Hotelling. Stanford University Press, pp. 278–292.Search in Google Scholar

Merz, R., Blöschl, G., 2005. Flood frequency regionalization - spatial proximity vs. catchment attributes. J. Hydrol., 302, 1–4, 283–306.10.1016/j.jhydrol.2004.07.018Search in Google Scholar

McCuen, R., 2002. Approach to confidence interval estimation for curve numbers. J. Hydraul. Eng., 7, 1, 43–48.10.1061/(ASCE)1084-0699(2002)7:1(43)Search in Google Scholar

Mishra, S.K., Tyagi, J.V., Singh, V.P., Singh, R., 2006. SCS-CNbased modeling of sediment yield. J. Hydrol., 324, 301–322.10.1016/j.jhydrol.2005.10.006Search in Google Scholar

Mishra, B.K., Takara, K., Tachikawa, Y., 2009. Integrating the NRCS runoff curve number in delineation of hydrologic homogeneous regions. J. Hydrol. Eng., 14, 10, 1091–1097.10.1061/(ASCE)HE.1943-5584.0000101Search in Google Scholar

Mockus, V., 1972. Chapter 21: Design hydrographs. In: McKeever, V., Owen, W., Rallison, R. (Eds.): National Engineering Handbook, Section 4, Hydrology. U.S. Department of Agriculture, Soil Conservation Service, Washington, DC.Search in Google Scholar

R Core Team, 2018. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org/.Search in Google Scholar

Rutkowska, A., Kohnová, S., Banasik, K., Szolgay, J., Karabová, B., 2015. Probabilistic properties of a curve number: a case study for small Polish and Slovak Carpathian Basins. J. Mt. Sci., 12, 3, 533–548. https://doi.org/10.1007/s11629-014-3123-010.1007/s11629-014-3123-0Search in Google Scholar

Rutkowska, A., Żelazny, M., Kohnová, S., Łyp, M., Banasik, K., 2010. Regional L-moment-based flood frequency analysis in the Upper Vistula River basin, Poland. Pure Appl. Geophys., 174, 2, 701–721. DOI: 10.1007/s00024-016-1298-810.1007/s00024-016-1298-8Search in Google Scholar

Sahu, R.K., Mishra, S.K., Eldho, T.I., 2010. An improved AMC-coupled runoff curve number model. Hydrol. Process., 24, 20, 2834–2839.10.1002/hyp.7695Search in Google Scholar

Scheffé, H., 1959. The Analysis of Variance. Wiley, New York. 477 p.Search in Google Scholar

Shi, Z.H., Chen, L.-D., Fang, N.-F., Qin, D.-F., CAI, C.-F., 2009. Research on the SCS-CN initial abstraction ratio using rainfallrunoff event analysis in the Three Gorges Area, China. Catena, 77, 1, 1–7. http://dx.doi.org/10.1016/j.catena.2008.11.006.10.1016/j.catena.2008.11.006Search in Google Scholar

Shapiro, S.S, Wilk, M.B., 1965. An Analysis of Variance Test for Normality, Biometrica, 52, 3–4, 591–611.10.1093/biomet/52.3-4.591Search in Google Scholar

Soulis, K.X., Valiantzas, J.D., 2012. SCS-CN parameter determination using rainfall-runoff data in heterogeneous watersheds - the two-CN system approach. Hydrol. Earth Syst. Sci. Discuss., 16, 1001–1015. DOI: 10.5194/hessd-8-8963-2011.10.5194/hessd-8-8963-2011Search in Google Scholar

Tedela, N.M., McCutcheon, S.C., Rasmussen, T.C., Tollner, E.W., 2008. Evaluation and Improvements of the Curve Number Method of Hydrological Analysis on Selected Forested Watersheds of Georgia. The University of Georgia, report submitted to Georgia Water Resources Institute. USA. Available at: http://water.usgs.gov/wrri/07grants/progress/2007GA143B.pdf (accessed on 6th February 2014).Search in Google Scholar

Ulrych, T.J., Velis, D.R., Woodbury, A.D., Sacchi, M.D., 2000. L-moments and C-moments. Stoch. Env. Res. Risk A., 14, 50–68.10.1007/s004770050004Search in Google Scholar

USDA, 2004. Estimation of direct runoff from storm rainfall. In: National Engineering Handbook, Chapter 10, part 630. Dept of Agriculture NRCS, Washington, DC, pp. 1–22.Search in Google Scholar

Verma, S., Verma, R.K., Mishra, S.K., Singh, A., Jayaraj, G.K., 2017. A revisit of NRCS-CN inspired models coupled with RS and GIS for runoff estimation. Hydrological Sciences Journal, 62, 12, 1891–1930. DOI: 10.1080/02626667.2017.133416610.1080/02626667.2017.1334166Search in Google Scholar

Viglione, A., 2018. nsRFA: Non-supervised Regional Frequency Analysis. R package version 0.7-14. https://cran.rproject.org/web/packages/nsRFA/nsRFA.pdfSearch in Google Scholar

Wang, Q.J., 1996. Direct sample estimators of L moments. Water Resour. Res., 32, 3617–3619.10.1029/96WR02675Search in Google Scholar

Wałęga, A., Cupak, A., Amatya, D.M., Drożdżal, E., 2017. Comparison of direct outflow calculated by modified SCSCN methods for mountainous and highland catchments in upper Vistula Basin, Poland and lowland catchment in South Carolina, U.S.A. Acta Scientiarum Polonorum Formatio Circumiectus, 16, 1, 187–207.10.15576/ASP.FC/2017.16.1.187Search in Google Scholar

Węglarczyk, S., 2010. Statystyka w inżynierii środowiska (Statistics in Environmental Engineering). Politechnika Krakowska, Cracow, Poland, 376 p.Search in Google Scholar

Woodward, D.E., Hawkins, R.H., Jiang, R., Hjelmfelt Jr., A.T., Van Mullem, J.A., Quang, D.Q., 2003. Runoff curve number method: examination of the initial abstraction ratio. In: Bizier, P., DeBarry, P. (Eds.): Proceedings of the World Water & Environmental Resources Congress 2003 and Related Symposia, EWRI, ASCE, 23–26 June, 2003, Philadelphia, Pennsylvania, USA, p. 10. DOI: 101061/40685(2003)308.10.1061/40685(2003)308Search in Google Scholar

Yang, T., Xu, C.-Y., Shao, Q.-X., Chen, X., 2010. Regional flood frequency and spatial patterns analysis in the Pearl River Delta region using L-moments approach. Stochastic Environmental Research and Risk Assessment, 24, 165–182. DOI: 10.1007/s00477-009-0308-0.10.1007/s00477-009-0308-0Search in Google Scholar

Yuan, Y., Nie, W., McCutcheon, S.C., Taguas, E.V., 2014. Initial abstraction and curve number for semiarid watersheds in Southeastern Arizona. Hydrol. Process., 28, 3, 774–783. http://dx.doi.org/10.1002/hyp.959210.1002/hyp.9592Search in Google Scholar