P. Dimitriadis, A. Tegos, A. Oikonomou, V. Pagana, A. Koukouvinos, N. Mamassis, D. Koutsoyiannis, and A. Efstratiadis, Comparative evaluation of 1D and quasi-2D hydraulic models based on benchmark and real-world applications for uncertainty assessment in flood mapping, Journal of Hydrology, 534, 478–492, doi:10.1016/j.jhydrol.2016.01.020, 2016.
[doc_id=1596]
[English]
One-dimensional and quasi-two-dimensional hydraulic freeware models (HEC-RAS, LISFLOOD-FP and FLO-2d) are widely used for flood inundation mapping. These models are tested on a benchmark test with a mixed rectangular-triangular channel cross section. Using a Monte-Carlo approach, we employ extended sensitivity analysis by simultaneously varying the input discharge, longitudinal and lateral gradients and roughness coefficients, as well as the grid cell size. Based on statistical analysis of three output variables of interest, i.e. water depths at the inflow and outflow locations and total flood volume, we investigate the uncertainty enclosed in different model configurations and flow conditions, without the influence of errors and other assumptions on topography, channel geometry and boundary conditions. Moreover, we estimate the uncertainty associated to each input variable and we compare it to the overall one. The outcomes of the benchmark analysis are further highlighted by applying the three models to real-world flood propagation problems, in the context of two challenging case studies in Greece.
Full text is only available to the NTUA network due to copyright restrictions
Our works referenced by this work:
1. | D. Koutsoyiannis, N. Mamassis, and A. Tegos, Logical and illogical exegeses of hydrometeorological phenomena in ancient Greece, Water Science and Technology: Water Supply, 7 (1), 13–22, 2007. |
2. | D. Koutsoyiannis, N. Mamassis, A. Efstratiadis, N. Zarkadoulas, and Y. Markonis, Floods in Greece, Changes of Flood Risk in Europe, edited by Z. W. Kundzewicz, Chapter 12, 238–256, IAHS Press, Wallingford – International Association of Hydrological Sciences, 2012. |
3. | V. Pagana, Elaboration of flood inundation maps in Rafina basin, Postgraduate Thesis, 180 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, March 2012. |
4. | S.M. Papalexiou, D. Koutsoyiannis, and C. Makropoulos, How extreme is extreme? An assessment of daily rainfall distribution tails, Hydrology and Earth System Sciences, 17, 851–862, doi:10.5194/hess-17-851-2013, 2013. |
5. | A. Oikonomou, P. Dimitriadis, A. Koukouvinos, A. Tegos, V. Pagana, P. Panagopoulos, N. Mamassis, and D. Koutsoyiannis, Floodplain mapping via 1D and quasi-2D numerical models in the valley of Thessaly, Greece, European Geosciences Union General Assembly 2013, Geophysical Research Abstracts, Vol. 15, Vienna, EGU2013-10366, doi:10.13140/RG.2.2.25165.03040, European Geosciences Union, 2013. |
6. | V. Pagana, A. Tegos, P. Dimitriadis, A. Koukouvinos, P. Panagopoulos, and N. Mamassis, Alternative methods in floodplain hydraulic simulation - Experiences and perspectives, European Geosciences Union General Assembly 2013, Geophysical Research Abstracts, Vol. 15, Vienna, EGU2013-10283-2, European Geosciences Union, 2013. |
7. | A. Oikonomou, Investigation of hydraulic simulation software function in the evolution of flood plains. Apply to a study area located at Thessaly, Postgraduate Thesis, 99 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, Athens, June 2013. |
8. | A. Efstratiadis, A. D. Koussis, D. Koutsoyiannis, and N. Mamassis, Flood design recipes vs. reality: can predictions for ungauged basins be trusted?, Natural Hazards and Earth System Sciences, 14, 1417–1428, doi:10.5194/nhess-14-1417-2014, 2014. |
Our works that reference this work:
1. | P. Dimitriadis, A. Tegos, A. Petsiou, V. Pagana, I. Apostolopoulos, E. Vassilopoulos, M. Gini, A. D. Koussis, N. Mamassis, D. Koutsoyiannis, and P. Papanicolaou, Flood Directive implementation in Greece: Experiences and future improvements, 10th World Congress on Water Resources and Environment "Panta Rhei", Athens, European Water Resources Association, 2017. |
2. | G. Papaioannou, A. Efstratiadis, L. Vasiliades, A. Loukas, S.M. Papalexiou, A. Koukouvinos, I. Tsoukalas, and P. Kossieris, An operational method for Floods Directive implementation in ungauged urban areas, Hydrology, 5 (2), 24, doi:10.3390/hydrology5020024, 2018. |
3. | G.-F. Sargentis, P. Dimitriadis, and D. Koutsoyiannis, Aesthetical issues of Leonardo Da Vinci’s and Pablo Picasso’s paintings with stochastic evaluation, Heritage, 3 (2), 283–305, doi:10.3390/heritage3020017, 2020. |
4. | G.-F. Sargentis, T. Iliopoulou, S. Sigourou, P. Dimitriadis, and D. Koutsoyiannis, Evolution of clustering quantified by a stochastic method — Case studies on natural and human social structures, Sustainability, 12 (19), 7972, doi:10.3390/su12197972, 2020. |
5. | G. Papaioannou, L. Vasiliades, A. Loukas, A. Alamanos, A. Efstratiadis, A. Koukouvinos, I. Tsoukalas, and P. Kossieris, A flood inundation modelling approach for urban and rural areas in lake and large-scale river basins, Water, 13 (9), 1264, doi:10.3390/w13091264, 2021. |
6. | A. Efstratiadis, P. Dimas, G. Pouliasis, I. Tsoukalas, P. Kossieris, V. Bellos, G.-K. Sakki, C. Makropoulos, and S. Michas, Revisiting flood hazard assessment practices under a hybrid stochastic simulation framework, Water, 14 (3), 457, doi:10.3390/w14030457, 2022. |
7. | P. Dimas, G. Pouliasis, P. Dimitriadis, P. Papanicolaou, P. Lazaridou, and S. Michas, Comparison of mudflow simulation models in an ephemeral mountainous stream in Western Greece using HEC-RAS and FLO-2D, Euro-Mediterranean Journal for Environmental Integration, doi:10.1007/s41207-023-00409-8, 2023. |
8. | M.J. Alexopoulos, P. Dimitriadis, T. Iliopoulou, N. Bezak, M. Kobold, and D. Koutsoyiannis, Effects of Digital Elevation Model resolution on Rain-on-Grid simulations: a case study in a Slovenian watershed, Hydrological Sciences Journal, doi:10.1080/02626667.2024.2378487, 2024. |
Works that cite this document: View on Google Scholar or ResearchGate
Other works that reference this work (this list might be obsolete):
1. | Apel, H., O. Martínez Trepat, N. N. Hung, D. T. Chinh, B. Merz, and N. V. Dung, Combined fluvial and pluvial urban flood hazard analysis: concept development and application to Can Tho city, Mekong Delta, Vietnam, Natural Hazards and Earth System Sciences, 16, 941-961, doi:10.5194/nhess-16-941-2016, 2016. |
2. | Papaioannou , G., A. Loukas, L. Vasiliades, and G. T. Aronica, Flood inundation mapping sensitivity to riverine spatial resolution and modelling approach, Natural Hazards, 83, 117-132, doi:10.1007/s11069-016-2382-1, 2016. |
3. | #Santillan, J. R., A. M. Amora, M. Makinano-Santillan, J. T. Marqueso, L. C. Cutamora, J. L. Serviano, and R. M. Makinano, Assessing the impacts of flooding caused by extreme rainfall events through a combined geospatial and numerical modeling approach, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XLI-B8, 2016, XXIII ISPRS Congress, Prague, doi:10.5194/isprs-archives-XLI-B8-1271-2016, 2016. |
4. | Cheviron, B. and R. Moussa, Determinants of modelling choices for 1-D free-surface flow and morphodynamics in hydrology and hydraulics: a review, Hydrology and Earth System Sciences, 20, 3799-3830, doi:10.5194/hess-20-3799-2016, 2016. |
5. | Anees, M.T., K. Abdullah, M.N.M. Nawawi, N. N. N. Ab Rahman, A. R. Mt. Piah, N. A. Zakaria, M.I. Syakir, and A.K. Mohd. Omar, Numerical modeling techniques for flood analysis, Journal of African Earth Sciences, 124, 478–486, doi:10.1016/j.jafrearsci.2016.10.001, 2016. |
6. | Skublics, D., G. Blöschl, and P. Rutschmann, Effect of river training on flood retention of the Bavarian Danube, Journal of Hydrology and Hydromechanics, 64(4), 349-356, doi:10.1515/johh-2016-0035, 2016. |
7. | Doong, D.-J., W. Lo, Z. Vojinovic, W.-L. Lee, and S.-P. Lee, Development of a new generation of flood inundation maps—A case study of the coastal City of Tainan, Taiwan, Water, 8(11), 521, doi:10.3390/w8110521, 2016. |
8. | #Cartaya, S., and R. Mantuano-Eduarte, Identificación de zonas en riesgo de inundación mediante la simulación hidráulica en un segmento del Río Pescadillo, Manabí, Ecuador, Revista de Investigación, 40(89), 158-170, 2016. |
9. | Javadnejad, F., B. Waldron, and A. Hill, LITE Flood: Simple GIS-based mapping approach for real-time redelineation of multifrequency floods, Natural Hazards Review, 18(3), doi:10.1061/(ASCE)NH.1527-6996.0000238, 2017. |
10. | Shrestha, A., M. S. Babel, S. Weesakul, and Z. Vojinovic, Developing intensity–duration–frequency (IDF) curves under climate change uncertainty: The case of Bangkok, Thailand, Water, 9(2), 145, doi:10.3390/w9020145, 2017. |
11. | Roushangar, K., M. T. Alami, V. Nourani, and A. Nouri, A cost model with several hydraulic constraints for optimizing in practice a trapezoidal cross section, Journal of Hydroinformatics, 19(3), 456-468, doi:10.2166/hydro.2017.081, 2017. |
12. | Papaioannou, G., L. Vasiliades, A. Loukas, and G. T. Aronica, Probabilistic flood inundation mapping at ungauged streams due to roughness coefficient uncertainty in hydraulic modelling, Advances in Geosciences, 44, 23-34, doi:10.5194/adgeo-44-23-2017, 2017. |
13. | Anees, M. T., K. Abdullah, M. N. M. Nawawi, N. N. N. Ab Rahman, A. R. Mt. Piah, M. I. Syakir, A. K. M. Omar, and K. Hossain, Applications of remote sensing, hydrology and geophysics for flood analysis, Indian Journal of Science and Technology, 10(17), doi:10.17485/ijst/2017/v10i17/111541, 2017. |
14. | Fuentes-Andino, D., K. Beven, S. Halldin, C.-Y. Xu, J. E. Reynolds, and G. Di Baldassarre, Reproducing an extreme flood with uncertain post-event information, Hydrology and Earth System Sciences, 21, 3597-3618, doi:10.5194/hess-21-3597-2017, 2017. |
15. | #Anees, M. T., K. Abdullah, M. N. M. Nordin, N. N. N. Ab Rahman, M. I. Syakir, and M. O. A. Kadir, One- and two-dimensional hydrological modelling and their uncertainties, Flood Risk Management, T. Hromadka and P. Rao (editors), Chapter 11, doi:10.5772/intechopen.68924, 2017. |
16. | #Papaioannou, G., A. Loukas, L. Vasiliades, and G. T. Aronica, Sensitivity analysis of a probabilistic flood inundation mapping framework for ungauged catchments, Proceedings of the 10th World Congress of EWRA “Panta Rhei”, European Water Resources Association, Athens, 2017. |
17. | Bangira, T., S. M. Alfieri , M. Menenti, A. van Niekerk, and Z. Vekerdy, A spectral unmixing method with ensemble estimation of endmembers: Application to flood mapping in the Caprivi floodplain, Remote Sensing, 9, 1013, doi:10.3390/rs9101013, 2017. |
18. | Carisi, F., A. Domeneghetti, M. G. Gaeta, and A. Castellarin, Is anthropogenic land subsidence a possible driver of riverine flood-hazard dynamics? A case study in Ravenna, Italy, Hydrological Sciences Journal, 62(15), 2440-2455, doi:10.1080/02626667.2017.1390315, 2017. |
19. | Podhoranyi, M., P. Veteska, D. Szturcova, L. Vojacek, and A. Portero, A web-based modelling and monitoring system based on coupling environmental models and hydrological-related data, Journal of Communications, 12(6), 340-346, doi:10.12720/jcm.12.6.340-346, 2017. |
20. | Bhuyian, N. M., A. Kalyanapu, and F. Hossain, Evaluating conveyance-based DEM correction technique on NED and SRTM DEMs for flood impact assessment of the 2010 Cumberland river flood, Geosciences, 7(4), 132; doi:10.3390/geosciences7040132, 2017. |
21. | Zin, W., A. Kawasaki, W. Takeuchi, Z. M. L. T. San, K. Z. Htun, T. H. Aye, and S. Win, Flood hazard assessment of Bago river basin, Myanmar, Journal of Disaster Research, 13(1), 14-21, doi:10.20965/jdr.2018.p0014, 2018. |
22. | #Siregar, R. I., Hydraulic modeling of flow impact on bridge structures: a case study on Citarum bridge, IOP Conference Series: Materials Science and Engineering, 309, 012015, doi:10.1088/1757-899X/309/1/012015, 2018. |
23. | Miranda, D., R. F. Camacho, S. Lousada, and R. A. Castanho, Hydraulic studies and their influence for regional urban planning: a practical approach to Funchal’s rivers, Revista Brasiliera de Planejamento e Desenvolvimento, 7(1), 145-164, doi:10.3895/rbpd.v7n1.7179, 2018. |
24. | Liu, W., and H. Liu, Integrating Monte Carlo and the hydrodynamic model for predicting extreme water levels in river systems, Preprints 2018, 2018030088, doi:10.20944/preprints201803.0088.v1, 2018. |
25. | #Indrawan, I., and R. I. Siregar, Analysis of flood vulnerability in urban area: a case study in Deli watershed, Journal of Physics Conference Series, 978(1), 012036, doi:10.1088/1742-6596/978/1/012036, 2018. |
26. | #Siregar, R. I., Land cover change impact on urban flood modeling (case study: Upper Citarum watershed), IOP Conference Series: Earth and Environmental Science, 126(1), 012027, doi:10.1088/1755-1315/126/1/012027, 2018. |
27. | #Ng, Z. F.., J. I. Gisen, and A. Akbari, Flood inundation modelling in the Kuantan river basin using 1D-2D flood modeller coupled with ASTER-GDEM, IOP Conference Series: Materials Science and Engineering, 318(1), 012024, doi:10.1088/1757-899X/318/1/012024, 2018. |
28. | Chang, M.-J., H.-K. Chang, Y.-C. Chen, G.-F. Lin, P.-A. Chen, J.-S. Lai, and Y.-C. Tan, A support vector machine forecasting model for typhoon flood inundation mapping and early flood warning systems, Water, 10, 1734, doi:10.3390/w10121734, 2018. |
29. | Dysarz, T., Application of Python scripting techniques for control and automation of HEC-RAS simulations, Water, 10(10):1382, doi:10.3390/w10101382, 2018. |
30. | Hdeib, R., C. Abdallah, F. Colin, L. Brocca, and R. Moussa, Constraining coupled hydrological-hydraulic flood model by past storm events and post-event measurements in data-sparse regions, Journal of Hydrology, 565, 160-175, doi:10.1016/j.jhydrol.2018.08.008, 2018. |
31. | Tan, F. J., E. J. R. Rarugal, and F. A. A. Uy, One-dimensional (1D) river analysis of a river basin in Southern Luzon Island in the Philippines using Lidar Digital Elevation Model, International Journal of Engineering & Technology, 7(3.7), 29-33, doi:10.14419/ijet.v7i3.7.16200, 2018. |
32. | Luo, P., D. Mu, H. Xue, T. Ngo-Duc, K. Dang-Dinh, K. Takara, D. Nover, and G. Schladow, Flood inundation assessment for the Hanoi Central Area, Vietnam under historical and extreme rainfall conditions, Scientific Reports, 8, 12623, doi:10.1038/s41598-018-30024-5, 2018. |
33. | Indrawan, I., and R. I. Siregar, Pemodelan Penerapan Terowongan Air (Tunnel) dalam Mengatasi Banjir Akibat Luapan Sungai Deli, Jurnal Teknik Sipil, 25(2), 113-120, doi:10.5614/jts.2018.25.2.4, 2018. |
34. | Petroselli, A., M. Vojtek, and J. Vojteková, Flood mapping in small ungauged basins: A comparison of different approaches for two case studies in Slovakia, Hydrology Research, 50(1), 379-392, doi:10.2166/nh.2018.040, 2018. |
35. | Agudelo-Otálora, L. M., W. D. Moscoso-Barrera, L. A. Paipa-Galeano, and C. Mesa-Sciarrotta, Comparison of physical models and artificial intelligence for prediction of flood levels, Water Technology and Sciences, 9(4), 209-236, doi:10.24850/j-tyca-2018-04-09, 2018. |
36. | Kaya, C. M., G. Tayfur, and O. Gungor, Predicting flood plain inundation for natural channels having no upstream gauged stations, Journal of Water and Climate Change, 10(2), 360-372, doi:10.2166/wcc.2017.307, 2019. |
37. | Liu, Z., V. Merwade, and K. Jafarzadegan, Investigating the role of model structure and surface roughness in generating flood inundation extents using 1D and 2D hydraulic models, Journal of Flood Risk Management, 12(1), e12347, doi:10.1111/jfr3.12347, 2019. |
38. | Tscheikner-Gratl, F., V. Bellos, A. Schellart, A. Moreno-Rodenas, M. Muthusamy, J. Langeveld, F. Clemens, L. Benedetti, M.A. Rico-Ramirez, R. Fernandes de Carvalho, L. Breuer, J. Shucksmith, G.B.M. Heuvelink, and S. Tait, Recent insights on uncertainties present in integrated catchment water quality modelling, Water Research, 150, 368-379, doi:10.1016/j.watres.2018.11.079, 2019. |
39. | Zeleňáková, M., R. Fijko, S. Labant, E. Weiss, G. Markovič, and R. Weiss, Flood risk modelling of the Slatvinec stream in Kružlov village, Slovakia, Journal of Cleaner Production, 212, 109-118, doi:10.1016/j.jclepro.2018.12.008, 2019. |
40. | Wang, P., G. Zhang, and H. Leung, Improving super-resolution flood inundation mapping for multispectral remote sensing image by supplying more spectral information, IEEE Geoscience and Remote Sensing Letters, 16(5), 771-775, doi:10.1109/LGRS.2018.2882516, 2019. |
41. | Tehrany, M. S., S. Jones, and F. Shabani, Identifying the essential flood conditioning factors for flood prone area mapping using machine learning techniques, Catena, 175, 174-192, doi:10.1016/j.catena.2018.12.011, 2019. |
42. | Škarpich, V., T. Galia, S. Ruman, and Z. Máčka, Variations in bar material grain-size and hydraulic conditions of managed and re-naturalized reaches of the gravel-bed Bečva River (Czech Republic), Science of The Total Environment, 649, 672-685, doi:10.1016/j.scitotenv.2018.08.329, 2019. |
43. | Yang, Z., K. Yang, L. Su, and H. Hu, The multi-objective operation for cascade reservoirs using MMOSFLA with emphasis on power generation and ecological benefit, Journal of Hydroinformatics, 21(2), 257-278, doi:10.2166/hydro.2019.064, 2019. |
44. | Dysarz, T., J. Wicher-Dysarz, M. Sojka, and J. Jaskuła, Analysis of extreme flow uncertainty impact on size of flood hazard zones for the Wronki gauge station in the Warta river, Acta Geophysica, 67(2), 661-676, doi:10.1007/s11600-019-00264-8, 2019. |
45. | Fleischmann, A., R. Paiva, and W. Collischonn, Can regional to continental river hydrodynamic models be locally relevant? A cross-scale comparison, Journal of Hydrology X, 3, 100027, doi:10.1016/j.hydroa.2019.100027, 2019. |
46. | Gyasi-Agyei, Y., Propagation of uncertainties in interpolated rain fields to runoff errors, Hydrological Sciences Journal, 64(5), 587-606, doi:10.1080/02626667.2019.1593989. 2019. |
47. | Langat, P. K., L. Kumar, and R. Koech, Identification of the most suitable probability distribution models for maximum, minimum, and mean streamflow, Water, 11, 734, doi:10.3390/w11040734, 2019. |
48. | Papaioannou, G., A. Loukas, and L. Vasiliades, Flood risk management methodology for lakes and adjacent areas: The lake Pamvotida paradigm, Proceedings, 7, 21, doi:10.3390/ECWS-3-05825, 2019. |
49. | Hosseini, D., M. Torabi, and M. A. Moghadam, Preference assessment of energy and momentum equations over 2D-SKM method in compound channels, Journal of Water Resource Engineering and Management, 6(1), 24-34, 2019. |
50. | Oubennaceur, K., K. Chokmani, M. Nastev, Y. Gauthier, J. Poulin, M. Tanguy, S. Raymond, and R. Lhissou, New sensitivity indices of a 2D flood inundation model using Gauss quadrature sampling, Geosciences, 9(5), 220, doi:10.3390/geosciences9050220, 2019. |
51. | Pinho, J. L. S., L. Vieira, J. M. P. Vieira, S. Venâncio, N. E. Simões, J. A. Sá Marques, and F. S. Santos, Assessing causes and associated water levels for an urban flood using hydroinformatic tools, Journal of Hydroinformatics, jh2019019, doi:10.2166/hydro.2019.019, 2019. |
52. | Saksena, S., V. Merwade, and P. J. Singhofen, Flood inundation modeling and mapping by integrating surface and subsurface hydrology with river hydrodynamics, Journal of Hydrology, 575, 1155-1177, doi:10.1016/j.jhydrol.2019.06.024, 2019. |
53. | #Fijko, R., and M., Zelenakova, Verification of the hydrodynamic model of the Slatvinec River in Kružlov, Air and Water Components of the Environment Conference Proceedings, 91-98, Cluj-Napoca, Romania, doi:10.24193/AWC2019_09, 2019. |
54. | Luppichini, M., M. Favalli, I. Isola, L. Nannipieri, R. Giannecchini, and M. Bini, Influence of topographic resolution and accuracy on hydraulic channel flow simulations: Case study of the Versilia River (Italy), Remote Sensing, 11(13), 1630, doi:10.3390/rs11131630, 2019. |
55. | Liu, Z., and V. Merwade, Separation and prioritization of uncertainty sources in a raster based flood inundation model using hierarchical Bayesian model averaging, Journal of Hydrology, 578, 124100, doi:10.1016/j.jhydrol.2019.124100, 2019. |
56. | #Huțanu, E., A. Urzică, L. E. Paveluc, C. C. Stoleriu, and A. Grozavu, The role of hydro-technical works in diminishing flooded areas. Case study: the June 1985 flood on the Miletin River, 16th International Conference on Environmental Science and Technology, Rhodes, 2019. |
57. | Chen, Y.-M., C.-H. Liu, H.-J. Shih, C.-H. Chang, W.-B. Chen, Y.-C. Yu, W.-R. Su, and L.-Y. Lin, An operational forecasting system for flash floods in mountainous areas in Taiwan, Water, 11, 2100, doi:10.3390/w11102100, 2019. |
58. | Shustikova, I., A. Domeneghetti, J. C. Neal, P. Bates, and A. Castellarin, Comparing 2D capabilities of HEC-RAS and LISFLOOD-FP on complex topography, Hydrological Sciences Journal, 64(14), 1769-1782, doi:10.1080/02626667.2019.1671982, 2019. |
59. | Papaioannou, G., G. Varlas, G. Terti, A. Papadopoulos, A. Loukas, Y. Panagopoulos, and E. Dimitriou, Flood inundation mapping at ungauged basins using coupled hydrometeorological-hydraulic modelling: The catastrophic case of the 2006 flash flood in Volos City, Greece, Water, 11, 2328, doi:10.3390/w11112328, 2019. |
60. | Liu, W.-C., and H.-M. Liu, Integrating hydrodynamic model and Monte Carlo simulation for predicting extreme water levels in a river system, Terrestrial, Atmospheric & Oceanic Sciences, 30(4), 589-604, doi:10.3319/TAO.2019.01.18.01, 2019. |
61. | Costabile, P., C. Costanzo, G. De Lorenzo, and F. Macchione, Is local flood hazard assessment in urban areas significantly influenced by the physical complexity of the hydrodynamic inundation model?, Journal of Hydrology, 580, 124231, doi:10.1016/j.jhydrol.2019.124231, 2020. |
62. | Stephens, T. A., and B. P. Bledsoe, Probabilistic mapping of flood hazards: depicting uncertainty in streamflow, land use, and geomorphic adjustment, Anthropocene, 29, 100231, doi:10.1016/j.ancene.2019.100231, 2020. |
63. | Papaioannou, G., C. Papadaki, and E. Dimitriou, Sensitivity of habitat hydraulic model outputs to DTM and computational mesh resolution, Ecohydrology, 13(2), e2182, doi:10.1002/eco.2182, 2020. |
64. | Saksena, S., S. Dey, V. Merwade, and P. J. Singhofen, A computationally efficient and physically based approach for urban flood modeling using a flexible spatiotemporal structure, Water Resources Research, 56(1), e2019WR025769, doi:10.1029/2019WR025769, 2020. |
65. | Annis, A., F. Nardi, E. Volpi, and A. Fiori, Quantifying the relative impact of hydrological and hydraulic modelling parameterizations on uncertainty of inundation maps, Hydrological Sciences Journal, 65(4), 507-523, doi:10.1080/02626667.2019.1709640, 2020. |
66. | Syafri, R. R., M. P. Hadi, and S. Suprayogi, Hydrodynamic modelling of Juwana river flooding using HEC-RAS 2D, IOP Conference Series Earth and Environmental Science, 412, 012028, doi:10.1088/1755-1315/412/1/012028, 2020. |
67. | Gergeľová, M. B., Ž. Kuzevičová, S. Labant, J. Gašinec, S. Kuzevič, J. Unucka, and P. Liptai, Evaluation of selected sub-elements of spatial data quality on 3D flood event modeling: Case study of Prešov City, Slovakia, Applied Sciences, 10(3), 820, doi:10.3390/app10030820, 2020. |
68. | Shaw, J., G. Kesserwani, and P. Pettersson, Probabilistic Godunov-type hydrodynamic modelling under multiple uncertainties: robust wavelet-based formulations, Advances in Water Resources, 137, 103526, doi:10.1016/j.advwatres.2020.103526, 2020. |
69. | Li, X., C. Huang, Y. Zhang, J. Pang, and Y. Ma, Hydrological reconstruction of extreme palaeoflood events 9000–8500 a BP in the Danjiang River Valley, tributary of the Danjiangkou Reservoir, China, Arabian Journal of Geosciences, 13, 137, doi:10.1007/s12517-020-5132-3, 2020. |
70. | Lousada, S., and L. Loures, Modelling torrential rain flows in urban territories: floods - natural channels (the case study of Madeira island), American Journal of Water Science and Engineering, 6(1), 17-30, doi:10.11648/j.ajwse.20200601.13, 2020. |
71. | Pariartha, G., A. Goonetilleke, P. Egodawatta, and H. Mirfenderesk, The prediction of flood damage in coastal urban areas, IOP Conference Series Earth and Environmental Science, 419, 012136, doi:10.1088/1755-1315/419/1/012136, 2020. |
72. | Lousada, S., Estudos hidráulicos e a sua influência no planeamento urbano regional: Aplicação prática às Ribeiras do Funchal – Portugal, Revista Americana de Empreendedorismo e Inovação, 2(2), 7-21, 2020. |
73. | Gan, B.-R., X.-G. Yang, H.-M. Liao, and J.-W. Zhou, Flood routing process and high dam interception of natural discharge from the 2018 Baige landslide-dammed lake, Water, 12(2), 605, doi:10.3390/w12020605, 2020. |
74. | Bellos, V., I. Papageorgaki, I. Kourtis, H. Vangelis, and G. Tsakiris, Reconstruction of a flash flood event using a 2D hydrodynamic model under spatial and temporal variability of storm, Natural Hazards, 101, 711-726, doi:10.1007/s11069-020-03891-3, 2020. |
75. | Yalcin, E., Assessing the impact of topography and land cover data resolutions on two-dimensional HEC-RAS hydrodynamic model simulations for urban flood hazard analysis, Natural Hazards, 101, 995-1017, doi:10.1007/s11069-020-03906-z, 2020. |
76. | Mateo-Lázaro, J., J. Castillo-Mateo, A. García-Gil, J. A. Sánchez-Navarro, V. Fuertes-Rodríguez, V. Edo-Romero, Comparative hydrodynamic analysis by using two−dimensional models and application to a new bridge, Water, 12(4), 997; doi:10.3390/w12040997, 2020. |
77. | Albu, L.-M., A. Enea, M. Iosub, and I.-G. Breabăn, Dam breach size comparison for flood simulations. A HEC-RAS based, GIS approach for Drăcșani lake, Sitna river, Romania, Water, 12(4), 1090, doi:10.3390/w12041090, 2020. |
78. | Pal, S., S. Talukdar, and R. Ghosh, Damming effect on habitat quality of riparian corridor, Ecological Indicators, 114, 106300, doi:10.1016/j.ecolind.2020.106300, 2020. |
79. | Sarchani, S. K. Seiradakis, P. Coulibaly, and I. Tsanis, Flood inundation mapping in an ungauged basin, Water, 12(6), 1532, doi:10.3390/w12061532, 2020. |
80. | Huţanu, E., A. Mihu-Pintilie, A. Urzica, L. E. Paveluc, C. C. Stoleriu, and A. Grozavu, Using 1D HEC-RAS modeling and LiDAR data to improve flood hazard maps’ accuracy: A case study from Jijia floodplain (NE Romania), Water, 12(6), 1624, doi:10.3390/w12061624, 2020. |
81. | Fleischmann, A. S., R. C. D. Paiva, W. Collischonn, V. A. Siqueira, A. Paris, D. M. Moreira, F. Papa, A. A. Bitar, M. Parrens, F. Aires, and P. A. Garambois, Trade‐offs between 1D and 2D regional river hydrodynamic models, Water Resources Research, 56(8), e2019WR026812, doi:10.1029/2019WR026812, 2020. |
82. | Gralepois, M., What can we learn from planning instruments in flood prevention? Comparative illustration to highlight the challenges of governance in Europe, Water, 12(6), 1841, doi:10.3390/w12061841, 2020. |
83. | Rampinelli, C. G., I. Knack, and T. Smith, Flood mapping uncertainty from a restoration perspective: a practical case study, Water, 12(7), 1948, doi:10.3390/w12071948, 2020. |
84. | Kalinina, A., M. Spada, D. F. Vetsch, S. Marelli, C. Whealton, P. Burgherr, and B. Sudret, Metamodeling for uncertainty quantification of a flood wave model for concrete dam breaks, Energies, 13(14), 3685, doi:10.3390/en13143685, 2020. |
85. | Kitsikoudis, V., B. P. J., Becker, Y. Huismans, P. Archambeau, S. Erpicum, M. Pirotton, and B. Dewals, Discrepancies in flood modelling approaches in transboundary river systems: Legacy of the past or well-grounded choices?, Water Resources Management, 34, 3465-3478, doi:10.1007/s11269-020-02621-5, 2020. |
86. | Piacentini, T., C. Carabella, F. Boccabella, S. Ferrante, C. Gregori, V. Mancinelli, A. Pacione, T. Pagliani, and E. Miccadei, Geomorphology-based analysis of flood critical areas in small hilly catchments for civil protection purposes and early warning systems: The case of the Feltrino stream and the Lanciano urban area (Abruzzo, Central Italy), Water, 12(8), 2228, doi:10.3390/w12082228, 2020. |
87. | Arseni, M., A. Rosu, M. Calmuc, V. A. Calmuc, C. Iticescu, and L. P. Georgescu, Development of flood risk and hazard maps for the lower course of the Siret river, Romania, Sustainability, 12(16), 6588, doi:10.3390/su12166588, 2020. |
88. | Ahmed, M. I., A. Elshorbagy, and A. Pietroniro, A novel model for storage dynamics simulation and inundation mapping in the Prairies, Environmental Modelling & Software, 133, 104850, doi:10.1016/j.envsoft.2020.104850, 2020. |
89. | Bellos, V., V. K. Tsakiris, G. Kopsiaftis, and G. Tsakiris, Propagating dam breach parametric uncertainty in a river reach using the HEC-RAS software, Hydrology, 7(4), 72, doi:10.3390/hydrology7040072, 2020. |
90. | Demir, V., and A. Ü. Keskin, Obtaining the Manning roughness with terrestrial-remote sensing technique and flood modeling using FLO-2D: A case study Samsun from Turkey, Geofizika, 37, 131-156, doi:10.15233/gfz.2020.37.9, 2020. |
91. | Petroselli, A., J. Florek, D. Młyński, L. Książek, and A. Wałęga, New insights on flood mapping procedure: Two case studies in Poland, Sustainability, 12(20), 8454, doi:10.3390/su12208454, 2020. |
92. | Beden, N., and A. Ulke Keskin, Flood map production and evaluation of flood risks in situations of insufficient flow data, Natural Hazards, 105, 2381-2408, doi:10.1007/s11069-020-04404-y, 2020. |
93. | #Malakeel G. S., K. U. Abdu Rahiman, and S. Vishnudas, Flood risk assessment methods – A review, in: Thomas J., Jayalekshmi B., Nagarajan P. (eds), Current Trends in Civil Engineering. Lecture Notes in Civil Engineering, Vol. 104, Springer, Singapore, doi:10.1007/978-981-15-8151-9_19, 2021. |
94. | Musiyam, M., J. Jumadi, Y. A. Wibowo, W. Widiyatmoko, and S. H. Nur Hafida, Analysis of flood-affected areas due to extreme weather in Pacitan, Indonesia, International Journal of GEOMATE, 19(75), 27-34, doi:10.21660/2020.75.25688, 2020. |
95. | Ghimire, E., S. Sharma, and N. Lamichhane, Evaluation of one-dimensional and two-dimensional HEC-RAS models to predict flood travel time and inundation area for flood warning system, ISH Journal of Hydraulic Engineering, doi:10.1080/09715010.2020.1824621, 2020. |
96. | Lin, X., G. Huang, J. M. Piwowar, X. Zhou, and Y. Zhai, Risk of hydrological failure under the compound effects of instant flow and precipitation peaks under climate change: a case study of Mountain Island Dam, North Carolina, Journal of Cleaner Production, 284, 125305, doi:10.1016/j.jclepro.2020.125305, 2021. |
97. | Daksiya, V., P. V. Mandapaka, and E. Y. M. Lo, Effect of climate change and urbanisation on flood protection decision‐making, Journal of Flood Risk Management, 14(1), e12681, doi:10.1111/jfr3.12681, 2021. |
98. | Urzică, A., A. Mihu-Pintilie, C. C. Stoleriu, C. I. Cîmpianu, E. Huţanu, C. I. Pricop, and A. Grozavu, Using 2D HEC-RAS modeling and embankment dam break scenario for assessing the flood control capacity of a multi-reservoir system (NE Romania), Water, 13(1), 57, doi:10.3390/w13010057, 2021. |
99. | Elhag, M., and N. Yilmaz, Insights of remote sensing data to surmount rainfall/runoff data limitations of the downstream catchment of Pineios River, Greece, Environmental Earth Sciences, 80, 35, doi:10.1007/s12665-020-09289-5, 2021. |
100. | Hdeib, R., R. Moussa, F. Colin, and C. Abdallah, A new cost-performance grid to compare different flood modelling approaches, Hydrological Sciences Journal, 66(3), 434-449, doi:10.1080/02626667.2021.1873346, 2021. |
101. | Sharma, V. C., and S. K. Regonda, Two-dimensional flood inundation modeling in the Godavari river basin, India – Insights on model output uncertainty, Water, 13(2), 191, doi:10.3390/w13020191, 2021. |
102. | Santos, E. D. S., H. S. K. Pinheiro, and H. G. Junior, Height above the nearest drainage to predict flooding areas in São Luiz do Paraitinga, São Paulo, Floresta e Ambiente, 28(2), doi:10.1590/2179-8087-floram-2020-0070, 2021. |
103. | Chang, T.-Y., H. Chen, H.-S. Fu, W.-B. Chen, Y.-C. Yu, W.-R. Su, and L.-Y. Lin, An operational high-performance forecasting system for city-scale pluvial flash floods in the southwestern plain areas of Taiwan, Water, 13(4), 405, doi:10.3390/w13040405, 2021. |
104. | Naeem, B., M. Azmat, H. Tao, S. Ahmad, M. U. Khattak, S. Haider, S. Ahmad, Z. Khero, and C. R. Goodell, Flood hazard assessment for the Tori levee breach of the Indus river basin, Pakistan, Water; 13(5), 604, doi:10.3390/w13050604, 2021. |
105. | Zhu, Y., X. Niu, C. Gu, B. Dai, and L. Huang, A fuzzy clustering logic life loss risk evaluation model for dam-break floods, Complexity, 2021, 7093256, doi:10.1155/2021/7093256, 2021. |
106. | #Malakeel, G. S., K. U.Abdu Rahiman, and S. Vishnudas, Flood risk assessment methods—A review, In: Thomas J., Jayalekshmi B., Nagarajan P. (eds), Current Trends in Civil Engineering, Lecture Notes in Civil Engineering, Vol. 104. Springer, Singapore, doi:10.1007/978-981-15-8151-9_19, 2021, 2021. |
107. | Liu, W.-C., T.-H. Hsieh, and H.-M. Liu, Flood risk assessment in urban areas of southern Taiwan, Sustainability, 13(6), 3180, doi:10.3390/su13063180, 2021. |
108. | Kumar, S., A. Agarwal, V. G. K. Villuri, S. Pasupuleti, D. Kumar, D. R. Kaushal, A. K. Gosain, A. Bronstert, and B. Sivakumar, Constructed wetland management in urban catchments for mitigating floods, Stochastic Environmental Research and Risk Assessment, 35, 2105-2124, doi:10.1007/s00477-021-02004-1, 2021. |
109. | Mourato, S., P. Fernandez, F. Marques, A. Rocha, and L. Pereira, An interactive Web-GIS fluvial flood forecast and alert system in operation in Portugal, International Journal of Disaster Risk Reduction, 58, 102201, doi:10.1016/j.ijdrr.2021.102201, 2021. |
110. | Dubey, A. K., P. Kumar, V. Chembolu, S. Dutta, R. P. Singh, and A. S. Rajawata, Flood modeling of a large transboundary river using WRF-Hydro and microwave remote sensing, Journal of Hydrology, 598, 126391, doi:10.1016/j.jhydrol.2021.126391, 2021. |
111. | de Arruda Gomes, M. M., L. F. de Melo Verçosa, and J. A. Cirilo, Hydrologic models coupled with 2D hydrodynamic model for high-resolution urban flood simulation, Natural Hazards, 108, 3121-3157, doi:10.1007/s11069-021-04817-3, 2021. |
112. | Gao, P., W. Gao, and N. Ke, Assessing the impact of flood inundation dynamics on an urban environment, Natural Hazards, 109, 1047-1072, doi:10.1007/s11069-021-04868-6, 2021. |
113. | Zhang, X., T. Wang, and B. Duan, Study on the effect of morphological changes of bridge piers on water movement properties, Water Practice and Technology, 16(4), 1421-1433, doi:10.2166/wpt.2021.08, 2021. |
114. | Fadilah, S., Istiarto, and D. Legono, Investigation and modelling of the flood control system in the Aerotropolis of Yogyakarta International Airport, IOP Conference Series Materials Science and Engineering, 1173(1), 012015, doi:10.1088/1757-899X/1173/1/012015, 2021. |
115. | Baran-Zgłobicka, B., D. Godziszewska, and W. Zgłobicki, The flash floods risk in the local spatial planning (case study: Lublin Upland, E. Poland), Resources, 10(2), 14, doi:10.3390/resources10020014, 2021. |
116. | Liang, C.-Y., Y.-H. Wang, G. J.-Y. You, P.-C. Chen, and E. Lo, Evaluating the cost of failure risk: A case study of the Kang-Wei-Kou stream diversion project, Water, 13(20), 2881, doi:10.3390/w13202881, 2021. |
117. | Uciechowska-Grakowicz, A., and O. Herrera-Granados, Riverbed mapping with the usage of deterministic and geo-statistical interpolation methods: The Odra River case study, Remote Sensing, 13(21), 4236, doi:10.3390/rs13214236, 2021. |
118. | Viquez, S. G., Mesurer le risque d’inondation en ville: Une modélisation sous contraintes, Terrains & Travaux, 38(1), 47-70, doi:10.3917/tt.038.0047, 2021. |
119. | Singh G., V. B. S. Chandel, and S. Kahlon, Flood hazard modelling in Upper Mandakini Basin of Uttarakhand, Current World Environment, 16(3), 880-889, doi:10.12944/CWE.16.3.18, 2021. |
120. | Liu, J., J. Wang, J. Xiong, W. Cheng, Y. Li, Y. Cao, Y. He, Y. Duan, W. He, and G. Yang, Assessment of flood susceptibility mapping using support vector machine, logistic regression and their ensemble techniques in the Belt and Road region, Geocarto International, doi:10.1080/10106049.2022.2025918, 2022. |
121. | Yang, S. Y., C. H. Chang, C. T. Hsu, and S. J. Wu, Variation of uncertainty of drainage density in flood hazard mapping assessment with coupled 1D–2D hydrodynamics model, Natural Hazards, 111, 2297-2315, doi:10.1007/s11069-021-05138-1, 2022. |
122. | Yoshida, K., S. Pan, J. Taniguchi, S. Nishiyama, T. Kojima, and T. Islam, Airborne LiDAR-assisted deep learning methodology for riparian land cover classification using aerial photographs and its application for flood modelling, Journal of Hydroinformatics, 24(1), 179-201, doi:10.2166/hydro.2022.134, 2022. |
123. | Kasprak, A., P. R. Jackson, E. M. Lindroth, J. W. Lund, and J. R. Ziegeweid, The role of hydraulic and geomorphic complexity in predicting invasive carp spawning potential: St. Croix River, Minnesota and Wisconsin, United States, PLoS ONE, 17(2), e026305, doi:10.1371/journal.pone.0263052, 2022. |
124. | Worley, L. C., K. L. Underwood, N. L. V. Vartanian, M. M. Dewoolkar, J. E. Matt, and D. M. Rizzo, Semi‐automated hydraulic model wrapper to support stakeholder evaluation: A floodplain reconnection study using 2D hydrologic engineering center's river analysis system, River Research and Applications, 38(4), 799-809, doi:10.1002/rra.3946, 2022. |
125. | Jiang, W., and J. Yu, Impact of rainstorm patterns on the urban flood process superimposed by flash floods and urban waterlogging based on a coupled hydrologic–hydraulic model: a case study in a coastal mountainous river basin within southeastern China, Natural Hazards, 112, 301-326, doi:10.1007/s11069-021-05182-x, 2022. |
126. | Mattos, T. S., P. T. S. Oliveira, L. de Souza Bruno, G. A. Carvalho, R. B. Pereira, L. L. Crivellaro, M. C. Lucas, and T. Roy, Towards reducing flood risk disasters in a tropical urban basin by the development of flood alert web application, Environmental Modelling & Software, 151, 105367, doi:10.1016/j.envsoft.2022.105367, 2022. |
127. | Papaioannou, G., V. Markogianni, A. Loukas, and E. Dimitriou, Remote sensing methodology for roughness estimation in ungauged streams for different hydraulic/hydrodynamic modeling approaches, Water, 14(7), 1076, doi:10.3390/w14071076, 2022. |
128. | Mishra, A., S. Mukherjee, B. Merz, V. P. Singh, D. B. Wright, G. Villarini, S. Paul, D. N. Kumar, C. P. Khedun, D. Niyogi, G. Schumann, and J. R. Stedinger, An overview of flood concepts, challenges, and future directions, Journal of Hydrologic Engineering, 27(6), doi:10.1061/(ASCE)HE.1943-5584.0002164, 2022. |
129. | Cea, L., and P. Costabile, Flood risk in urban areas: modelling, management and adaptation to climate change. A review, Hydrology, 9(3), 50, doi:10.3390/hydrology9030050, 2022. |
130. | #Karmakar, S., M. A. Sherly, and M. Mohanty, Urban flood risk mapping: A state-of-the-art review on quantification, current practices, and future challenges, Advances in Urban Design and Engineering. Design Science and Innovation, Banerji, P., Jana, A. (eds.), 125-156, Springer, Singapore, doi:10.1007/978-981-19-0412-7_5, 2022. |
131. | Kadir, M. A. A., M. R. R. M. A. Zainol, P. Luo, M. Kaamin, and S. N. H. S. Yahya, Advance flood inundation model toward flood nowcasting: A review, International Journal of Nanoelectronics and Materials, 15, 81-100, 2022. |
132. | Tegos, A., A. Ziogas, V. Bellos, and A. Tzimas, Forensic hydrology: a complete reconstruction of an extreme flood event in data-scarce area, Hydrology, 9(5), 93, doi:10.3390/hydrology9050093, 2022. |
133. | Stephens, T., and B. Bledsoe, Simplified uncertainty bounding: an approach for estimating flood hazard uncertainty, Water, 14(10), 1618, doi:10.3390/w14101618, 2022. |
134. | Iroume, J.Y.-A., R. Onguéné, F. Djanna Koffi, A. Colmet-Daage, T. Stieglitz, W. Essoh Sone, S. Bogning, J. M. Olinga Olinga, R. Ntchantcho, J.-C. Ntonga, J.-J. Braun, J.-P. Briquet, and J. Etame, The 21st August 2020 flood in Douala (Cameroon): A major urban flood investigated with 2D HEC-RAS modeling, Water, 14(11), 1768, doi:10.3390/w14111768, 2022. |
135. | Jiang, W., J. Yu, Q. Wang, and Q. Yue, Understanding the effects of digital elevation model resolution and building treatment for urban flood modelling, Journal of Hydrology: Regional Studies, 42, 101122, doi:10.1016/j.ejrh.2022.101122, 2022. |
136. | Singh, G., V. B. S. Chandel, and S. Kahlon, Flood hazard modelling in Upper Mandakini Basin of Uttarakhand, Current World Environment, 16(3), 880-889, doi:10.12944/CWE.16.3.18, 2022. |
137. | Li, Y., D. B. Wright, and Y. Liu, Flood-induced geomorphic change of floodplain extent and depth: A case study of Hurricane Maria in Puerto Rico, Journal of Hydrologic Engineering, 27(10), doi:10.1061/(ASCE)HE.1943-5584.0002199, 2022. |
138. | Iroume, J. Y.-A., R. Onguéné, F. Djanna Koffi, A. Colmet-Daage, T. Stieglitz, W. Essoh Sone, S. Bogning, J. M. Olinga Olinga, R. Ntchantcho, J.-C. Ntonga, J.-J. Braun, J.-P. Briquet, and J. Etame, The 21st August 2020 flood in Douala (Cameroon): A major urban flood investigated with 2D HEC-RAS modeling, Water, 14(11), 1768, doi:10.3390/w14111768, 2022. |
139. | Ahmad, N. S., and N. A. Ahmad, Propose design of new cross section by using one dimensional HEC-RAS at Maran River, Pahang, Journal of Advancement in Environmental Solution and Resource Recovery, 2(1), 51-59, 2022. |
140. | de Sousa, M. M., A. K. Beleño de Oliveira, O. M. Rezende, P. M. Canedo de Magalhães, A. C. Pitzer Jacob, P. C. de Magalhães, and M. G. Miguez, Highlighting the role of the model user and physical interpretation in urban flooding simulation, Journal of Hydroinformatics, 24(5), 976-991, doi:10.2166/hydro.2022.174, 2022. |
141. | Kaya, Ç. M., Taşkın Duyarlılık Haritalarının Oluşturulmasında Kullanılan Yöntemler, Turkish Journal of Remote Sensing and GIS, 3(2), 191-209, doi:10.48123/rsgis.1129606, 2022. |
142. | Li, Y., D. B. Wright, and Y. Liu, Flood-induced geomorphic change of floodplain extent and depth: a case study of hurricane Maria in Puerto Rico, Journal of Hydrologic Engineering, 27(10), doi:10.1061/(ASCE)HE.1943-5584.0002199, 2022. |
143. | Wibowo, Y. A., M. A. Marfai, M. P. Hadi, H. Fatchurohman, L. Ronggowulan and D. A. Arif, Geospatial technology for flood hazard analysis in Comal Watershed, Central Java, Indonesia, IOP Conference Series: Earth and Environmental Science, 1039, 012027, 2022. |
144. | Godwin, E., I. Kabenge, A. Gidudu, Y. Bamutaze, and A. Egeru, Differentiated spatial-temporal flood vulnerability and risk assessment in lowland plains in Eastern Uganda, Hydrology, 9(11), 201, doi:10.3390/hydrology9110201, 2022. |
145. | Zhou, Y., Z. Wu, H. Xu, and H. Wang, Prediction and early warning method of inundation process at waterlogging points based on Bayesian model average and data-driven, Journal of Hydrology: Regional Studies, 44, 101248, doi:10.1016/j.ejrh.2022.101248, 2022. |
146. | de Sousa, M. M., Ο. Μ. Rezende, A. C. P. Jacob, L. B. de França Ribeiro, P. M. C. de Magalhães, G. Maquera, and M. G. Miguez, Flood risk assessment index for urban mobility with the aid of quasi-2D flood model applied to an industrial park in São Paulo, Brazil, Infrastructures, 7(11), 158, doi:10.3390/infrastructures7110158, 2022. |
147. | Otmani, A., A. Hazzab, M. Atallah, C. Apollonio, and A. Petroselli, Using volunteered geographic information data for flood mapping – Wadi Deffa El Bayadh Algeria, Journal of Applied Water Engineering and Research, doi:10.1080/23249676.2022.2155716, 2022. |
148. | PhamVan, C., and H. Le, Estimation of the daily flow in river basins using the data-driven model and traditional approaches: an application in the Hieu river basin, Vietnam, Water Practice and Technology, 18(1), 215-230, doi:10.2166/wpt.2022.166, 2023. |
149. | Worley, L. C., K. L. Underwood, R. M. Diehl, J. E. Matt, K.S. Lawson, R. M. Seigel, and D. M. Rizzo, Balancing multiple stakeholder objectives for floodplain reconnection and wetland restoration, Journal of Environmental Management, 326(A), 116648, doi:10.1016/j.jenvman.2022.116648, 2023. |
150. | Xu, K., C. Wang, and L. Bin, Compound flood models in coastal areas: a review of methods and uncertainty analysis, Natural Hazards, 116, 469-496, doi:10.1007/s11069-022-05683-3, 2023. |
151. | Daniel, W. B., C. Roth, X. Li, C. Rakowski, T. McPherson, and D. Judi, Extremely rapid, Lagrangian modeling of 2D flooding: A rivulet-based approach, Environmental Modelling & Software, 161, 105630, doi:10.1016/j.envsoft.2023.105630, 2023. |
152. | Guirro, M. O., and G. P. Michel, Hydrological and hydrodynamic reconstruction of a flood event in a poorly monitored basin: a case study in the Rolante River, Brazil, Natural Hazards, doi:10.1007/s11069-023-05879-1, 2023. |
153. | Kohanpur, A. H., S. Saksena, S. Dey, J. M. Johnson, M. S. Riasi, L. Yeghiazarian, and A. M. Tartakovsky, Urban flood modeling: Uncertainty quantification and physics-informed Gaussian processes regression forecasting, Water Resources Research, 59(3), e2022WR033939, doi:10.1029/2022WR033939, 2023. |
154. | Rodas, M., L. Timbe, and L. Campozano, Sensibilidad del coeficiente de Manning en la estimación de los niveles de crecida para el mapeo de inundaciones en un río de la región interandina de Ecuador, Cuadernos de Geografía Revista Colombiana de Geografía, 32(1), doi:10.15446/rcdg.v32n1.94764, 2023. |
155. | Wu, S., and Y. Lei, Multiscale flood disaster risk assessment in the Lancang-Mekong river basin: A focus on watershed and community levels, Atmosphere, 14(4), 657, doi:10.3390/atmos14040657, 2023. |
156. | Viseh, H., and D. N. Bristow, Residential flood risk in metro Vancouver due to climate change using probability boxes, International Journal of River Basin Management, doi:10.1080/15715124.2023.2200006, 2023. |
157. | Moghim, S., M. A. Gharehtoragh, and A. Safaie, Performance of the flood models in different topographies, Journal of Hydrology, 620(A), 129446, doi:10.1016/j.jhydrol.2023.129446, 2023. |
158. | Makris, C., Z. Mallios, Y. Androulidakis, and Y. Krestenitis, CoastFLOOD: A high-resolution model for the simulation of coastal inundation due to storm surges, Hydrology, 10(5), 103, doi:10.3390/hydrology10050103, 2023. |
159. | Tarpanelli, A., B. Bonaccorsi, M. Sinagra, A. Domeneghetti, L. Brocca, and S. Barbetta, Flooding in the digital twin Earth: The case study of the Enza River levee breach in December 2017, Water, 15(9), 1644, doi:10.3390/w15091644, 2023. |
160. | Xafoulis, N., Y. Kontos, E. Farsirotou, S. Kotsopoulos, K. Perifanos, N. Alamanis, D. Dedousis, and K. Katsifarakis, Evaluation of various resolution DEMs in flood risk assessment and practical rules for flood mapping in data-scarce geospatial areas: A case study in Thessaly, Greece, Hydrology, 10(4), 91, doi:10.3390/hydrology10040091, 2023. |
161. | da Silva, A. A. C. L., and J. C. Eleutério, Identifying and testing the probability distribution of earthfill dam breach parameters for probabilistic dam breach modeling, Journal of Flood Risk Management, 16(3), e12900, doi:10.1111/jfr3.12900, 2023. |
162. | Hajihassanpour, M., G. Kesserwani, P. Pettersson, and V. Bellos, Sampling-based methods for uncertainty propagation in flood modeling under multiple uncertain inputs: Finding out the most efficient choice, Water Resources Research, 59(7), e2022WR034011, doi:10.1029/2022WR034011, 2023. |
163. | Biswal, S., B. Sahoo, M. K. Jha, and M. K. Bhuyan, A hybrid machine learning-based multi-dem ensemble model of river cross-section extraction: Implications on streamflow routing, Journal of Hydrology, 625(A), 129951, doi:10.1016/j.jhydrol.2023.129951, 2023. |
164. | Wienhold, K. J., D. Li, W. Li, and Z. N. Fang, Flood inundation and depth mapping using unmanned aerial vehicles combined with high-resolution multispectral imagery, Hydrology, 10(8), 158, doi:10.3390/hydrology10080158, 2023. |
165. | Aryal, A., and A. Kalra, Application of NEXRAD precipitation data for assessing the implications of low development practices in an ungauged basin, River, doi:10.1002/rvr2.55, 2023. |
166. | Bryant, S., H. Kreibich, and B. Merz, Bias in flood hazard grid aggregation, Water Resources Research, 59(9), e2023WR035100, doi:10.1029/2023WR035100, 2023. |
167. | Wang, W., G. Sang, Q. Zhao, and L. Lu, Water level prediction of pumping station pre-station based on machine learning methods, Water Supply, 23(10), 4092-4111, doi:10.2166/ws.2023.242, 2023. |
168. | Moraru, A., N. Rüther, and O. Bruland, Investigating optimal 2D hydrodynamic modeling of a recent flash flood in a steep Norwegian river using high-performance computing, Journal of Hydroinformatics, 25(5), 1690-1712, doi:10.2166/hydro.2023.012, 2023. |
169. | Dasari, I., and V. K. Vema, Assessment of the structural uncertainty of hydrological models and its impact on flood inundation mapping, Hydrological Sciences Journal, 68(16), 2404-2421, doi:10.1080/02626667.2023.2271456, 2023. |
170. | Rojpratak, S., and S. Supharatid, Regional-scale flood impacts on a small mountainous catchment in Thailand under a changing climate, Journal of Water and Climate Change, jwc2023527, doi:10.2166/wcc.2023.527, 2023. |
171. | Abbas, Z., M. Akhtar, S. Akram, S. Hafeez, and S. R. Ahmad, Flood inundation modeling and damage assessment in Lahore using remote sensing, International Journal of Innovations in Science & Technology, 5(4), 638-647, 2023. |
172. | Almeida, I. M., H. A. Santos, O. de Vasconcelos Costa, and V. B. Graciano, Uncertainty reduction in flood areas by probabilistic analyses of land use/cover in models of two-dimensional hydrodynamic model of dam-break, Stochastic Environmental Research and Risk Assessment, 38, 1335-1350, doi:10.1007/s00477-023-02635-6, 2024. |
173. | Stavi, I., S. Eldad, C. Xu, Z. Xu, Y. Gusarov, M. Haiman, and E. Argaman, Ancient agricultural terrace walls control floods and regulate the distribution of Asphodelus ramosus geophytes in the Israeli arid Negev, Catena, 234, 107588, doi:10.1016/j.catena.2023.107588, 2024. |
174. | Tilav, E. S., and S. Gülbaz, Investigation of flooding due to dam failure: A case study of Darlık dam, Journal of Natural Hazards and Environment, 10(1), 49-67, doi:10.21324/dacd.1327805, 2024. |
175. | Tunio, I. A., L. Kumar, S. A. Memon, A. A. Mahessar, A. W. Kandhir, Sediment transport dynamics during a super flood: A case study of the 2010 super flood at the Guddu Barrage on the Indus River, International Journal of Sediment Research, doi:10.1016/j.ijsrc.2024.03.002, 2024. |
176. | Sajjad, A., J. Lu, X. Chen, S. Yousaf, N. Mazhar, and S. Shuja, Flood hazard assessment in Chenab River basin using hydraulic simulation modeling and remote sensing, Natural Hazards, 120, 7679-7700, doi:10.1007/s11069-024-06513-4, 2024. |
177. | Ullah, A., S. Haider, and R. Farooq, Sensitivity analysis of a 2D flood inundation model. A case study of Tous Dam, Environmental Earth Sciences, 83, 213. doi:10.1007/s12665-024-11500-w, 2024. |
178. | #Ojasanya, K. A., and B. O. George-Kayode, A simplistic approach for evaluating urban flood risk through the integration of HEC-RAS 2D and GIS, World Environmental and Water Resources Congress 2024, 544-565, doi:10.1061/9780784485477.050, 2024. |
179. | Bănăduc, D., A. Curtean-Bănăduc, S. Barinova, V. L. Lozano, S. Afanasyev, T. Leite, P. Branco, D. F. Gomez Isaza, J. Geist, A. Tegos, H. Olosutean, and K. Cianfanglione, Multi-interacting natural and anthropogenic stressors on freshwater ecosystems: Their current status and future prospects for 21st century, Water, 16(11), 1483, doi:10.3390/w16111483, 2024. |
180. | Khatun, A., M.N. Nisha, S. Chatterjee, and V. Sridhar, A novel insight on input variable and time lag selection in daily streamflow forecasting using deep learning models, Environmental Modelling & Software, 179, 106126, doi:10.1016/j.envsoft.2024.106126, 2024. |
181. | Banupriy, R., N. M. Indumathi, A. Devendhiran, and C. Navamani, Mapping of high level remote sensing image features with pixel distribution and threshold computation, African Journal of Biological Sciences, 6(7), 703-711, doi:10.48047/AFJBS.6.7.2024.703-711, 2024. |
182. | Ma, J., J. Chen, and C. Xu, Hydraulic reconstruction of giant paleolandslide‐dammed lake outburst floods in high‐mountain region, eastern Tibetan Plateau: A case study of the Upper Minjiang River valley, Transactions in GIS, 28(6), 1793-1825, doi:10.1111/tgis.13218, 2024. |
183. | Yadav, A., R. M., Singh, M. K. Pandey, S. P. Maurya, and S. K. Singh, Hydrodynamic modelling of river training works for protection of group of villages on the left bank of Ramganga River: a case study, Natural Hazards, doi:10.1007/s11069-024-06888-4, 2024. |
Tagged under: Floods, Hydraulic models, Most recent works, Students' works, Uncertainty