References
- Asquith, W., 2022. lmomco---L-moments, censored L-moments, trimmed L-moments, L-comoments, and many distributions. R package version 2.4.7.
- Blöschl, G., Merz, R., 2008. Bestimmung von Bemessungshochwässern gegebener Jährlichkeit–Aspekte einer zeitgemäßen Strategie. Wasserwirtschaft, 11, 12–18.
- Brunner, M., Seibert, J., Favre, A., 2016a. Bivariate return periods and their importance for flood peak and volume estimation. WIREs Water, 3, 819–833. https://doi.org/10.1002/wat2.1173
- Brunner, M., Vannier, O., Favre, A., Viviroli, D., Meylan, P., Sikorska, A., Seibert, J., 2016b. Flood volume estimation in Switzerland using synthetic design hydrographs - a multivariate statistical approach. In: Proc. 13th Congress INTERPRAEVENT 2016, Luzern, pp. 468–476. https://doi.org/10.5167/uzh-124430
- Brunner, M., Viviroli, D., Sikorska, A., Vannier, O., Favre, A., Seibert, J., 2017. Flood type specific construction of synthetic design hydrographs. Water Resources Research, 53, 1390–1406. https://doi.org/10.1002/2016WR019535
- Brunner, M., Furrer, R., Favre, A., 2019. Modeling the spatial dependence of floods using the Fisher copula. Hydrology and Earth System Sciences, 23, 107–124. https://doi.org/10.5194/hess-23-107-2019
- Brunner, M., 2023. Floods and droughts: a multivariate perspective on hazard estimation: a multivariate perspective on hazard estimation. Hydrology and Earth System Sciences Discussions, 1–26. https://doi.org/https://doi.org/10.5194/hess-2023-20
- Campitelli, E., 2021. metR: tools for easier analysis of meteorological fields: tools for easier analysis of meteorological fields. R Package version 0.13.0. https://doi.org/10.5281/zenodo.2593516
- Carril-Rojas, D., Mediero, L., 2023. Bivariate analysis with synthetic hydrograph shapes for hydrological dam safety assessment. Environ. Sci. Proc., 25, 2.
- Czado, C., Nagler, T., 2022. Vine copula based modeling. Annual Review of Statistics and Its Application, 9, 453–477. https://doi.org/10.1146/annurev-statistics-040220-101153
- Danáčová, Z., Poórová, J., Blaškovičová, L., Liová, S., 2015. Instrumentation for surface water quantity monitoring and discharge measurements by ADCP. Acta Hydrologica Slovaca, 16, Thematic issue, 3–12.
- Dissmann, J., Brechmann, E., Czado, C., Kurowicka, D., 2013. Selecting and estimating regular vine copulae and application to financial returns. Computational Statistics & Data Analysis, 59, 52–69. https://doi.org/10.1016/j.csda.2012.08.010
- Drobot, R., Draghia, A., Ciuiu, D., Trandafir, R., 2021. Design floods considering the epistemic uncertainty. Water, 13. https://doi.org/10.3390/w13111601
- DWA, 2012. Merkblatt DWA-M 552: Ermittlung von Hochwasserwahrscheinlichkeiten. Deutsche Vereinigung für Wasserwirtschaft, Abwasser und Abfall e. V.
- Földes, G., Labat, M., Kohnová, S., Hlavčová, K., 2022. Impact of changes in short-term rainfall on design floods: Case study of the Hnilec River Basin, Slovakia. Slovak Journal of Civil Engineering, 30, 68–74. https://doi.org/10.2478/sjce-2022-0008
- Gaál, L., Szolgay, J., Kohnová, S., Hlavčová, K., Parajka, J., Viglione, A., Merz, R., Blöschl, G., 2015. Dependence between flood peaks and volumes: a case study on climate and hydrological controls. Hydrological Sciences Journal, 60, 968–984. https://doi.org/10.1080/02626667.2014.951361
- Gadek, W., Baziak, B., Tokarczyk, T., Szalińska, W., 2022. A novel method of design flood hydrographs estimation for flood hazard mapping. Water, 14, 12, 1856. https://doi.org/10.3390/w14121856
- Ganapathy, A., Hannah, D., Agarwal, A., 2022. Flood classification based on hydrograph characteristics. Authorea Preprints.
- Ganguli, P., Reddy, M., 2013. Probabilistic assessment of flood risks using trivariate copulas. Theoretical and Applied Climatology, 111, 341–360. https://doi.org/10.1007/s00704-012-0664-4
- Genest, C., Favre, A., 2007. Everything you always wanted to know about copula modeling but were afraid to ask. Journal of Hydrologic Engineering, 12, 4, 347–368. https://doi.org/10.1061/(ASCE)1084-0699(2007)12:4(347)
- Giani, G., Tarasova, L., Woods, R.A., Rico-Ramirez, M.A., 2022. An objective time-series-analysis method for rainfall-runoff event identification. Water Resources Research, 58, 2, e2021WR031283.
- Gómez, M., Ausín, M., Domínguez, M., 2018. Vine copula models for predicting water flow discharge at King George Island, Antarctica. Stochastic Environmental Research and Risk Assessment, 32, 2787–2807. https://doi.org/10.1007/s00477-018-1599-9
- Gräler, B., van den Berg, M., Vandenberghe, S., Petroselli, A., Grimaldi, S., De Baets, B., Verhoest, N., 2013. Multivariate return periods in hydrology: a critical and practical review focusing on synthetic design hydrograph estimation. Hydrology and Earth System Sciences, 17, 1281–1296. https://doi.org/10.5194/hess-17-1281-2013
- Grimaldi, S., Petroselli, A., Salvadori, G., De Michele, C., 2016. Catchment compatibility via copulas: A non-parametric study of the dependence structures of hydrological responses. Advances in Water Resources, 90, 116–133. https://doi.org/10.1016/j.advwatres.2016.02.003
- Größer, J., Okhrin, O., 2022. Copulae: An overview and recent developments. WIREs Computational Statistics, 14. https://doi.org/10.1002/wics.1557
- Hosking, J., 1990. L-moments: Analysis and estimation of distributions using linear combinations of order statistics. Journal of the Royal Statistical Society: Series B (Methodological), 52, 105–124. https://doi.org/10.1111/j.2517-6161.1990.tb01775.x
- Hu, C., Ran, G., Li, G., Yu, Y., Wu, Q., Yan, D., Jian, S., 2021. The effects of rainfall characteristics and land use and cover change on runoff in the Yellow River basin, China. Journal of Hydrology and Hydromechanics, 69, 1, 29–40. https://doi.org/10.2478/johh-2020-0042
- Hundecha, Y., Parajka, J., Viglione, A., 2017. Flood type classification and assessment of their past changes across Europe. Hydrology and Earth System Sciences Discussions, 1–29. https://doi.org/https://doi.org/10.5194/hess-2017-356
- Cheng, S., Tong, X., Illman, W., 2022. Evaluation of baseflow separation methods with real and synthetic streamflow data from a watershed. Journal of Hydrology, 613, Part A, 128279. https://doi.org/10.1016/j.jhydrol.2022.128279
- Jafry, N., Suhaila, J., Yusof, F., Mohd Nor, S., Alias, N., 2022. Preliminary study on flood frequency analysis in Johor River basin using vine copula. Proceedings of Science and Mathematics, 7, 52–55.
- Latif, S., Simonovic, S., 2022. Parametric vine copula framework in the trivariate probability analysis of compound flooding events. Water, 14, 14, 2214. https://doi.org/10.3390/w14142214
- Le Clerc, S., Sauquet, E., Lang, M., 2003. Scaling properties of flood hydrographs and their use to derive design flood hydro-graphs. WIT Transactions on Ecology and the Environment, 60.
- LfU BW, 2005. Festlegung des Bemessungshochwassers für Anlagen des technischen Hochwasserschutzes. Leitfaden. Karlsruhe, 92 p.
- Liová, A., Valent, P., Hlavčová, K., Kohnová, S., Bacigál, T., Szolgay, J., 2022. A methodology for the estimation of control flood wave hydrographs for the Horné Orešany reservoir. Acta Hydrologica Slovaca, 23, 52–61. https://doi.org/10.31577/ahs-2022-0023.01.0006
- Lorenz, P., Gattermayr, W., Kölbl, C., Krammer, C., Maracek, K., Mathis, C., Moser, J., Schatzl, R., Wiesenegger, H., Wimmer, M., Lorenz, P. (Eds.), 2011. Leitfaden: Verfahren zur Abschätzung von Hochwasserkennwerten, 113 p.
- Mediero, L., Jiménez-Álvarez, A., Garrote, L., 2010. Design flood hydrographs from the relationship between flood peak and volume. Hydrology and Earth System Sciences, 14, 2495–2505. https://doi.org/10.5194/hess-14-2495-2010
- Nagler, T., Schepsmeier, U., Stoeber, J., Brechmann, E., Graeler, B., Erhardt, T., 2022. VineCopula: Statistical Inference of VinCopulas. R package version 2.4.4.
- Narasimhan, B., Johnson, S., Hahn, T., Bouvier, A., Kiêu, K., 2023. cubature: Adaptive Multivariate Integration over Hypercubes. R package version 2.0.4.6.
- Nazeri Tahroudi, M., Ramezani, Y., De Michele, C., Mirabbasi, R., 2022. Trivariate joint frequency analysis of water resources deficiency signatures using vine copulas. Applied Water Science, 12, 67. https://doi.org/10.1007/s13201-022-01589-4
- Nelsen, R., 2006. An Introduction to Copulas. 2nd ed. Springer, New York.
- O’Connor, K., Goswami, M., Faulkner, D., 2014. Flood Studies Update, Technical Research Report: Vol. III - Hydrograph Analysis.
- Okhrin, O., Ristig, A., Xu, Y. F., 2017. Copulae in high dimensions: an introduction. Applied Quantitative Finance, 247–277. https://doi.org/10.1007/978-3-662-54486-0_19
- Oppel, H., Mewes, B., 2020. On the automation of flood event separation from continuous time series. Frontiers in Water, 2, 18. https://doi.org/10.3389/frwa.2020.00018
- Pandi, G., 2010. The analysis of flood waves. Aerul si Apa. Componente ale Mediului, 35–44.
- Pramanik, N., Panda, R., Sen, D., 2009. Development of design flood hydrographs using probability density functions. Hydrological Processes, 24, 415–428. https://doi.org/10.1002/hyp.7494
- Pekárová, P., Mészáros, J., Miklánek, P., Pekár, J., Siman, C., Podolinská, J., 2021. Post-flood field investigation of the June 2020 flash flood in the upper Muráň River basin and the catastrophic flash flood scenario. Journal of Hydrology and Hydromechanics, 69, 3, 288–299. https://doi.org/10.2478/johh-2021-0015
- R Core Team, 2022. R: A language and environment for statistical computing. R Foundation for Statistical Computing.
- Requena, A., Mediero, L., Garrote, L., 2013. A bivariate return period based on copulas for hydrologic dam design: accounting for reservoir routing in risk estimation. Hydrology and Earth System Sciences, 17, 3023–3038. https://doi.org/10.5194/hess-17-3023-2013
- Rizwan, M., Guo, S., Yin, J., Xiong, F., 2019. Deriving design flood hydrographs based on copula function: A case study in Pakistan. Water, 11. https://doi.org/10.3390/w11081531
- Segers, J., Sibuya, M., Tsukahara, H., 2017. The Empirical Beta Copula. Journal of Multivariate Analysis, 155, 35–51. https://doi.org/10.1016/j.jmva.2016.11.010
- Schirmacher, D., Schirmacher, E., 2008. Multivariate dependence modeling using pair-copulas. Technical report.
- Szolgay, J., Gaál, L., Kohnová, S., Hlavčová, K., Výleta, R., Bacigál, T., Blöschl, G., 2015. A process-based analysis of the suitability of copula types for peak-volume flood relationships. Proceedings of the International Association of Hydrological Sciences, 370, 183–188. https://doi.org/10.5194/piahs-370-183-2015
- Škvarka, J., Bednárová, E., Miščík, M., Uhorščák, Ľ., 2021. The Domaša reservoir in the spectrum of climate change. Slovak Journal of Civil Engineering, 29, 9–15. https://doi.org/10.2478/sjce-2021-0009
- Thiesen, S., Darscheid, P., Ehret, U., 2019. Identifying rainfall-runoff events in discharge time series: a data-driven method based on information theory. Hydrology and Earth System Sciences, 23, 2, 1015–1034. https://doi.org/10.5194/hess-23-1015-2019
- Tootoonchi, F., Sadegh, M., Haerter, J., Räty, O., Grabs, T., Teutschbein, C., 2022. Copulas for hydroclimatic analysis: A practice‐oriented overview. WIREs Water, 9, 2, e1579. https://doi.org/10.1002/wat2.1579
- Tosunoglu, F., Gürbüz, F., İspirli, M., 2020. Multivariate modeling of flood characteristics using Vine copulas. Environmental Earth Sciences, 79, 459. https://doi.org/10.1007/s12665-020-09199-6
- Wickham, H., Averick, M., Bryan, J., Chang, W., McGowan, L. D. A., François, R., Grolemund, G., Hayes, A., Henry, L., Hester, J., Kuhn, M., Pedersen, T. L., Miller, E., Bache, S. M., Müller, K., Ooms, J., Robinson, D., Seidel, D. P., Spinu, V., Takahashi, K., Vaughan, D., Wilke, C., Woo, K., Yutani, H., 2019. Welcome to the Tidyverse. Journal of open source software, 4, 43, 1686. https://doi.org/10.21105/joss.01686
- Xiao, Y., Guo, S., Liu, P., Yan, B., Chen, L., 2009. Design flood hydrograph based on multicharacteristic synthesis index method. Journal of Hydrologic Engineering, 14, 1359–1364.
- Yue, S., Ouarda, T., Bobée, B., Legendre, P., Bruneau, P., 2002. Approach for describing statistical properties of flood hydro-graph. Journal of Hydrologic Engineering, 7, 147–153.
- Zhang, Q., Zhang, L., She, D., Wang, S., Wang, G., Zeng, S., 2021. Automatic procedure for selecting flood events and identifying flood characteristics from daily streamflow data. Environmental Modelling & Software, 145, 105180. https://doi.org/10.1016/j.envsoft.2021.105180