JKSCE - KSCE JOURNAL OF CIVIL AND ENVIRONMENTAL ENGINEERING RESEARCH

1

"Bates, P. D. and De Roo, A. P. J. (2000). “A simple raster-based model for flood inundation simulation.” Journal of Hydrology, Elsevier, Vol. 236, Nos. 1-2, pp. 54-77, https://doi.org/10.1016/S0022-1694(00)00278-X."

2

"Bates, P. D., Horritt, M. S. and Fewtrell, T. J. (2010). “A simple inertial formulation of the shallow water equations for efficient two-dimensional flood inundation modelling.” Journal of Hydrology, Elsevier, Vol. 387, Nos. 1-2, pp. 33-45, https://doi.org/10.1016/j.jhydrol.2010.03.027."

3

"Berkhahn, S., Fuchs, L. and Neuweiler, I. (2019). “An ensemble neural network model for real-time prediction of urban floods.” Journal of Hydrology, Elsevier, Vol. 575, pp. 743-754, https://doi.org/10.1016/j.jhydrol.2019.05.066."

4

"Brunner, G. W. (1995). HEC-RAS River Analysis System hydraulic reference manual, CPD-69, Hydrologic Engineering Center, Davis, CA. "

5

"Burrichter, B., Hofmann, J., Koltermann da Silva, J., Niemann, A. and Quirmbach, M. (2023). “A spatiotemporal deep learning approach for urban pluvial flood forecasting with multi-source data.” Water, MDPI, Vol. 15, No. 9, 1760, https://doi.org/10.3390/w15091760."

6

"Chen, W., Li, Y., Xue, W., Shahabi, H., Li, S., Hong, H., Wang, X. Bian, H., Zhang, S. Pradhan, B. and Ahmad, B. B. (2020). “Modeling flood susceptibility using data-driven approaches of naïve bayes tree, alternating decision tree, and random forest methods.” Science of the Total Environment, Elsevier, Vol. 701, 134979, https://doi.org/10.1016/j.scitotenv.2019.134979."

7

"Clark, C. O. (1945). “Storage and the unit hydrograph.” Transactions of the American Society of Civil Engineers, ASCE, Vol. 110, No. 1, pp. 1419-1446, https://doi.org/10.1061/TACEAT.0005800."

8

"DHI Software (2003). MIKE SHE user guide and reference manual, DHI A/S. "

9

"Dottori, F. and Todini, E. (2011). “Developments of a flood inundation model based on the cellular automata approach: testing different methods to improve model performance.” Physics and Chemistry of the Earth, Parts A/B/C, Elsevier, Vol. 36, Nos. 7-8, pp. 266-280, https://doi.org/10.1016/j.pce.2011.02.004."

10

"Innovyze (2012). InfoWorks ICM Help v3.0. "

11

"Islam, A. R. M. T., Talukdar, S., Mahato, S., Kundu, S., Eibek, K. U., Pham, Q. B., Kuriqi, A. and Linh, N. T. T. (2021). “Flood susceptibility modelling using advanced ensemble machine learning models.” Geoscience Frontiers, Elsevier, Vol. 12, No. 3, 101075, https://doi.org/10.1016/j.gsf.2020.09.006."

12

"Ivanov, V. Y., Xu, D., Dwelle, M. C., Sargsyan, K., Wright, D. B., Katopodes, N., Kim, J., Tran, V. N., Warnock, A., Fatichi, S., Burlando, P., Caporali, E., Restrepo, P., Sanders, B. F., Chaney, M. M., Nunes, A. M. B., Nardi, F., Vivoni, E. R., Istanbulluoglu, E., Bisht, G. and Bras, R. L. (2021). “Breaking down the computational barriers to real‐time urban flood forecasting.” Geophysical Research Letters, AGU, Vol. 48, No. 20, e2021GL093585, https://doi.org/10.1029/2021GL093585."

13

"Ghimire, B., Chen, A. S., Guidolin, M., Keedwell, E. C., Djordjević, S. and Savić, D. A. (2013). “Formulation of a fast 2D urban pluvial flood model using a cellular automata approach.” Journal of Hydroinformatics, IWA, Vol. 15, No. 3, pp. 676-686, https://doi.org/10.2166/hydro.2012.245."

14

"Gude, V., Corns, S. and Long, S. (2020). “Flood prediction and uncertainty estimation using deep learning.” Water, MDPI, Vol. 12, No. 3, 884, https://doi.org/10.3390/w12030884."

15

"Guidolin, M., Chen, A. S., Ghimire, B., Keedwell, E. C., Djordjević, S. and Savić, D. A. (2016). “A weighted cellular automata 2D inundation model for rapid flood analysis.” Environmental Modelling & Software, Elsevier, Vol. 84, pp. 378-394, https://doi.org/10.1016/j.envsoft.2016.07.008."

16

"Guo, Z., Moosavi, V. and Leitão, J. P. (2022). “Data-driven rapid flood prediction mapping with catchment generalizability.” Journal of Hydrology, Elseiver, Vol. 609, 127726, https://doi.org/10.1016/j.jhydrol.2022.127726."

17

"He, Q. P. and Wang, J. (2007). “Fault detection using the k-nearest neighbor rule for semiconductor manufacturing processes.” IEEE Transactions on Semiconductor Manufacturing, IEEE, Vol. 20 No. 4, pp. 345-354, https://doi.org/10.1109/TSM.2007.907607."

18

"Hu, R. L., Pierce, D., Shafi, Y., Boral, A., Anisimov, V., Nevo, S. and Chen, Y. F. (2022). “Accelerating physics simulations with tensor processing units: An inundation modeling example.” The International Journal of High Performance Computing Applications, Sage Journals, Vol. 36, No. 4, pp. 510-523, https://doi.org/10.1177/10943420221102873."

19

"Huff, F. A. (1967). “Time distribution of rainfall in heavy storms.” Water Resources Research, AGU, Vol. 3, No. 4, pp. 1007-1019, https://doi.org/10.1029/WR003i004p01007."

20

"Jamali, B., Bach, P. M., Cunningham, L. and Deletic, A. (2019). “A Cellular Automata fast flood evaluation (CA-ffé) model.” Water Resources Research, AGU, Vol. 55, No. 6, pp. 4936-4953, https://doi.org/10.1029/2018WR023679."

21

"Jamali, B., Löwe, R., Bach, P. M., Urich, C., Arnbjerg-Nielsen, K. and Deletic, A. (2018). “A rapid urban flood inundation and damage assessment model.” Journal of Hydrology, Elsevier, Vol. 564, pp. 1085-1098, https://doi.org/10.1016/j.jhydrol.2018.07.064."

22

"Jeong, D. K. and Lee, B. H. (2010). “Development of urban flood water level forecasting model using regression method.” Journal of Korea Water Resources Association, KWRA, Vol. 43, No. 2, pp. 221-231, https://doi.org/10.3741/JKWRA.2010.43.2.221 (in Korean)."

23

"Jeong, J. and Kim, J. (2022). “Improved practical methods for considering climate change in design flood estimation.” Journal of the Korean Society of Hazard Mitigation, KOSHAM, Vol. 22, No. 6, pp. 301-309, https://doi.org/10.9798/KOSHAM.2022.22.6.301 (in Korean)."

24

"Kabir, S., Patidar, S., Xia, X., Liang, Q., Neal, J. and Pender, G. (2020). “A deep convolutional neural network model for rapid prediction of fluvial flood inundation.” Journal of Hydrology, Elsevier, Vol. 590, 125481, https://doi.org/10.1016/j.jhydrol. 2020.125481."

25

"Kabir, S., Wood, D. and Waller, S. (2023). “A deep learning model for generalized surface water flooding across multiple return periods.” Engineering Proceedings, MDPI, Vol. 39, No. 1, 94, https://doi.org/10.3390/engproc2023039094."

26

"Kang, J. E. and Lee, M. J. (2015). “Analysis of urban infrastructure risk areas to flooding using neural network in Seoul.” KSCE Journal of Civil and Environmental Engineering Research, KSCE, Vol. 35, No. 4, pp. 997-1006, https://doi.org/10.12652/Ksce.2015.35.4.0997 (in Korean)."

27

"Kia, M. B., Pirasteh, S., Pradhan, B., Mahmud, A. R., Sulaiman, W. N. A. and Moradi, A. (2012). “An artificial neural network model for flood simulation using GIS: Johor River Basin, Malaysia.” Environmental Earth Sciences, Springer, Vol. 67, pp. 251-264, https://doi.org/10.1007/s12665-011-1504-z."

28

"Kim, H. I., Han, K. Y. and Lee, J. Y. (2020). “Prediction of urban flood extent by LSTM model and logistic regression.” KSCE Journal of Civil and Environmental Engineering Research, KSCE, Vol. 40, No. 3, pp. 273-283, https://doi.org/10.12652/Ksce. 2020.40.3.0273 (in Korean)."

29

"Kim, H. I., Lee, Y. S. and Kim, B. (2021). “Real-time flood prediction applying random forest regression model in urban areas.” Journal of Korea Water Resources Association, KWRA, Vol. 54, No. spc1, pp. 1119-1130, https://doi.org/10.3741/JKWRA. 2021.54.S-1.1119 (in Korean)."

30

"Kim, J. and Jeong, J. (2019). “Development of stream channel design program for stream channel improvement.” Magazine of the Korean Society of Civil Engineers, KSCE, Vol. 67, No. 8, pp. 48-52 (in Korean). "

31

"Kumar, M., Kumar, P., Kumar, A., Elbeltagi, A. and Kuriqi, A. (2022). “Modeling stage-discharge-sediment using support vector machine and artificial neural network coupled with wavelet transform.” Applied Water Science, Springer, Vol. 12, No. 5, 87, https://doi.org/10.1007/s13201-022-01621-7."

32

"Lee, S., Kim, B., Choi, H. and Noh, S. J. (2022). “A review on urban inundation modeling research in South Korea: 2001-2022.” Journal of Korea Water Resources Association, KWRA, Vol. 55, No. 10, pp. 707-721, https://doi.org/10.3741/JKWRA.2022.55.10.707 (in Korean)."

33

"Lee, J. and Kim, B. (2021). “Scenario-based real-time flood prediction with logistic regression.” Water, MDPI, Vol. 13, No. 9, 1191, https://doi.org/10.3390/w13091191."

34

"Löwe, R., Böhm, J., Jensen, D. G., Leandro, J. and Rasmussen, S. H. (2021). “U-FLOOD - Topographic deep learning for predicting urban pluvial flood water depth.” Journal of Hydrology, Elsevier, Vol. 603, 126898, https://doi.org/10.1016/j.jhydrol.2021.126898."

35

"Ministry of Environment(ME) (2019). Guidelines for estimating flood discharge (in Korean). "

36

"Ministry of Environment(ME) (2020). Guidelines for developing a flood danger alert map (in Korean). "

37

"Ministry of Land, Transport and Maritime Affairs(MLTMA) (2012). Design flood estimation guide (in Korean). "

38

"Ministry of the Interior and Safety(MOIS) (2020). Guidelines for mapping of the disaster hazard maps (in Korean). "

39

"Ministry of the Interior and Safety(MOIS) (2022). Establishment of disaster prevention performance targets by region (in Korean). "

40

"Ministry of Land, Infrastructure and Transport(MOLIT) (2014). The national river master plan for Jinwi watershed (in Korean). "

41

"Muñoz, D. F., Yin, D., Bakhtyar, R., Moftakhari, H., Xue, Z., Mandli, K. and Ferreira, C. (2022). “Inter-model comparison of Delft3D‐FM and 2D HEC-RAS for total water level prediction in coastal to inland transition zones.” Journal of the American Water Resources Association, AWRA, Vol. 58, No. 1, pp. 34-49, https://doi.org/10.1111/1752-1688.12952."

42

"O'Brien, J. S., Julien, P. Y. and Fullerton, W. T. (1993). “Two- dimensional water flood and mudflow simulation.” Journal of Hydraulic Engineering, ASCE, Vol. 119, No. 2, pp. 244-261, https://doi.org/10.1061/(ASCE)0733-9429(1993)119:2(244)."

43

"Petaccia, G., Natale, L., Savi, F., Velickovic, M., Zech, Y. and Soares-Frazão, S. (2013). “Flood wave propagation in steep mountain rivers.” Journal of Hydroinformatics, IWA, Vol. 15, No. 1, pp. 120-137, https://doi.org/10.2166/hydro.2012.122."

44

"Piadeh, F., Behzadian, K. and Alani, A. M. (2022). “A critical review of real-time modelling of flood forecasting in urban drainage systems.” Journal of Hydrology, Elsevier, Vol. 607, 127476, https://doi.org/10.1016/j.jhydrol.2022.127476."

45

"Qi, W., Ma, C., Xu, H., Chen, Z., Zhao, K. and Han, H. (2021). “A review on applications of urban flood models in flood mitigation strategies.” Natural Hazards, Springer, Vol. 108, pp. 31-62, https://doi.org/10.1007/s11069-021-04715-8."

46

"Rezaeianzadeh, M., Tabari, H., Arabi Yazdi, A., Isik, S. and Kalin, L. (2014). “Flood flow forecasting using ANN, ANFIS and regression models.” Neural Computing and Applications, Springer, Vol. 25, pp. 25-37, https://doi.org/10.1007/s00521-013-1443-6."

47

"Rossman, L. A. (2010). Storm water management model user's manual version 5.0, U.S. Environmental Protection Agency, Washington, DC. "

48

"Saha, T. K., Pal, S., Talukdar, S., Debanshi, S., Khatun, R., Singha, P. and Mandal, I. (2021). “How far spatial resolution affects the ensemble machine learning based flood susceptibility prediction in data sparse region.” Journal of Environmental Management, Elsevier, Vol. 297, 113344, https://doi.org/10.1016/j.jenvman. 2021.113344."

49

"Soil Conservation Service(SCS). (1956). Hydrology. National Engineering Handbook, Supplement A, Section 4, Chapter 10, Soil Conservation Service, USDA., Washington. "

50

"Sun, A. Y., Li, Z., Lee, W., Huang, Q., Scanlon, B. R. and Dawson, C. (2023). “Rapid flood inundation forecast using Fourier neural operator.” Proceedings of 2023 IEEE/DVF International Conference on Computer Vision Workshops, IEEE, Paris, France, pp. 3733-3739, https://doi.org/10.1109/ICCVW60793.2023.00401."

51

"Suwon City (2014). The comprehensive plans for flood hazard reduction, Suwon City (in Korean). "

52

"XP Solutions (2013). XP-SWMM stormwater and wastewater management model: getting started manual, Newbury, UK. "

53

"Zhang, Y., Ragettli, S., Molnar, P., Fink, O. and Peleg, N. (2022). “Generalization of an Encoder-Decoder LSTM model for flood prediction in ungauged catchments.” Journal of Hydrology, Elsevier, Vol. 614, 128577, https://doi.org/10.1016/j.jhydrol. 2022.128577."

JKSCEKSCE JOURNAL OF CIVIL AND
ENVIRONMENTAL ENGINEERING RESEARCH

Journal of the Korean Society of Civil Engineers

ISO Journal TitleKSCE J. Civ. Environ. Eng. Res.

Journal Search

Journal XML

References

JKSCEKSCE JOURNAL OF CIVIL AND ENVIRONMENTAL ENGINEERING RESEARCH