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JDR Vol.16 No.3 pp. 310-320
(2021)
doi: 10.20965/jdr.2021.p0310

Review:

Advances in Urban Stormwater Management in Japan: A Review

Yoshihiro Shibuo*,† and Hiroaki Furumai**

*Department of Urban Engineering, Graduate School of Engineering, The University of Tokyo
7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan

Corresponding author

**Research Center for Water Environment Technology, School of Engineering, The University of Tokyo, Tokyo, Japan

Received:
January 24, 2021
Accepted:
January 31, 2021
Published:
April 1, 2021
Keywords:
stormwater management, rainfall observation, integrated urban flood modelling, Internet of Things
Abstract

The series of annual flood disasters that struck Japan in recent years pose challenges to urban stormwater management. Japan has been implementing nation-wide hydrometeorological observation through a dense network of rain gauges. Since the recent decade, ground radars have been deployed to observe heavy rainfall with high spatiotemporal resolution as a countermeasure. While commercial software is popular in designing stormwater drainage systems, several integrated urban flood models have been developed domestically and are applicable in stormwater management. A paradigm shift with the rise of Internet of Things (IoT) provides an inexperienced opportunity in hydrological observation, and has been implemented for monitoring sewer network conditions. Despite this broad scope of research works and technological innovations, such advancement is not internationally recognized yet. The present study aims to review the development and role of science and technology in stormwater management in Japan, focusing specifically on rainfall observation, integrated urban flood modelling, and emerging technologies for stormwater monitoring. In addition, the possible future direction of stormwater management is envisioned. Considering the series of record-breaking rainfall events that struck Japan, we will have to face more severe challenges in urban flood management alongside the impact of global climate change. As compared to structural measures, which are subject to budgetary constraints, the relative importance of non-structural measures is increasing; therefore, effective application of numerical modeling techniques is required. A common weakness of the urban flood modeling framework is the limited availability of observations in sewer networks, which can be relaxed by emerging IoT based observations. The fusion of IoT based observations with an integrated urban flood modeling technique appears to the emerging technology for stormwater management.

Cite this article as:
Yoshihiro Shibuo and Hiroaki Furumai, “Advances in Urban Stormwater Management in Japan: A Review,” J. Disaster Res., Vol.16, No.3, pp. 310-320, 2021.
Data files:
References
  1. [1] S. Ohtomo, R. Kimura, Y. Kawata, and K. Tamura, “The Determinants of Residents’ Evacuation Behavior in the Torrential Rain in Western Japan in 2018: Examination of Survey Data of Victims in Okayama Prefecture,” J. Disaster Res., Vol.15, No.7, pp. 1011-1024, 2020.
  2. [2] T. Sayama, M. Yamada, Y. Sugawara, and D. Yamazaki, “Ensemble flash flood predictions using a high-resolution nationwide distributed rainfall-runoff model: case study of the heavy rain event of July 2018 and Typhoon Hagibis in 2019,” Progress in Earth and Planetary Science, Vol.7, No.1, Article No.75, 2020.
  3. [3] M. Takeda, D. Sato, K. Kawaike, and M. Toyota, “Inundation Analysis of the Dike Breach of the Chikuma River Taking Drainage Process and House Damage into Consideration,” J. Disaster Res., Vol.16, No.3, pp. 343-350, 2021.
  4. [4] Ministry of Land, Infrastructure, Transport and Tourism, “Recent rainfall and pluvial flood damages, and situation of sewer management 2018,” https://www.mlit.go.jp/mizukokudo/sewerage/content/001320996.pdf (in Japanese) [accessed September 1, 2020]
  5. [5] K. Fukumori, Y. Kurita, and H. Furumai, “Validation of Inundation Damage Reduction by a Pump Gate with the New Type of Horizontal Axial Submersible Pump,” J. Disaster Res., Vol.16, No.3, pp. 381-386, 2021.
  6. [6] M. Hayakawa, T. Nakajima, and R. Hakoda, “Examination of Flood Countermeasures Utilizing a Yokohama City Main Rainwater Pipeline and Public–Private Anti-Flood Measures,” J. Disaster Res., Vol.16, No.3, pp. 437-441, 2021.
  7. [7] R. Matsuoka and S. Oki, “Demonstration of Stormwater Management Technology by Short-Term Rainfall Prediction and Real-Time Runoff Analysis System Using Small X-Band Radar,” J. Disaster Res., Vol.16, No.3, pp. 403-409, 2021.
  8. [8] H. Mitamura and M. Fujie, “Evolutionary Transition of Stromwater Pump System in Tokyo,” J. Disaster Res., Vol.16, No.3, pp. 421-428, 2021.
  9. [9] H. Muroi, K. Mine, and Y. Eguchi, “Scenario Analysis of Sluice Gate Operations for Evaluating Inland Flood Damage,” J. Disaster Res., Vol.16, No.3, pp. 429-436, 2021.
  10. [10] M. Nakashima, S. Sameshima, Y. Kimura, and M. Yoshimoto, “Evaluation of Real-Time Water Level Prediction Technology Using Statistical Models for Reducing Urban Flood Risk,” J. Disaster Res., Vol.16, No.3, pp. 387-394, 2021.
  11. [11] K. Park, Y. Shibuo, J. Katayama, S. Baba, and H. Furumai, “Applicability of High-Resolution Geospatial Data Obtained by UAV Photogrammetry to Develop Drainage System Models for Pluvial Flood Analysis,” J. Disaster Res., Vol.16, No.3, pp. 371-380, 2021.
  12. [12] Y. Sakae, M. Endo, and Y. Nakayama, “Development and Evaluation of ICT Operation Support System for Urban Flood Control Facilities,” J. Disaster Res., Vol.16, No.3, pp. 395-402, 2021.
  13. [13] K. Yoshimi, M. Wada, and Y. Hiraoka, “Study on Water Level Prediction Using Observational Data from a Multi-Parameter Phased Array Weather Radar,” J. Disaster Res., Vol.16, No.3, pp. 410-414, 2021.
  14. [14] A. Kawamura, “Status Quo and Perspectives of Flood Runoff Analysis for Urban Watersheds,” J. of Japan Society of Hydrology and Water Resources, Vol.31, No.6, pp. 451-466, 2018.
  15. [15] K. E. Trenberth, A. Dai, R. M. Rasmussen, and D. B. Parsons, “The changing character of precipitation,” Bulletin of the American Meteorological Society, Vol.84, No.9, pp. 1205-1217, 2003.
  16. [16] D. Kamiya, H. Sakakibara, S. Morioke et al., “The Relationship between Disaster Prevention Weather Information and Evacuation Information and Evacuation Problems in Welfare Facilities,” J. of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering), Vol.75, No.1, pp. 370-377, 2019 (in Japanese).
  17. [17] Y. Shibuo, S. Lee, H. Sanuki et al., “Evaluating Characteristics of XRAIN and Numerical Rainfall Predictions for Urban Inundation Simulation,” J. of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering), Vol.74, No.4, pp. I_1381-I_1386, 2018 (in Japanese).
  18. [18] M. Ikeda, Y. Watanabe, and M. Ushiyama, “Regional meteorological observation from the Meteorological Agency,” J. of Japan Society of Hydrology and Water Resources, Vol.13, No.4, pp. 313-319, 2000 (in Japanese).
  19. [19] Japan Meteorological Agency, “Automated Meteorological Data Acquisition System 2020,” https://www.jma.go.jp/jma/en/Activities/amedas/amedas.html [accessed September 1, 2020]
  20. [20] Ministry of Land, Infrastructure, Transport and Tourism, “Water Information System 2020,” http://www1.river.go.jp/ (in Japanese) [accessed September 1, 2020]
  21. [21] X. Xue, Y. Hong, A. S. Limaye et al., “Statistical and Hydrological Evaluation of TRMM-Based Multi-Satellite Precipitation Analysis Over the Wangchu Basin of Bhutan: Are the Latest Satellite Precipitation Products 3B42V7 Ready for Use in Ungauged Basins?,” J. of Hydrology, Vol.499, pp. 91-99, 2013.
  22. [22] T. Dinku, C. Funk, P. Peterson et al., “Validation of the CHIRPS satellite rainfall estimates over eastern Africa,” Quarterly J. of the Royal Meteorological Society, Vol.144, No.S1, pp. 292-312, 2018.
  23. [23] I. Fujita and Y. Kunita, “Flash flood simulation of the Toga River caused by localized torrential rain in urbanized area,” Proc. of the Int. Conf. on Fluvial Hydraulics (River Flow 2010), pp. 1605-1613, 2010.
  24. [24] E. Nakakita, H. Sato, R. Nishiwaki, H. Yamabe, and K. Yamaguchi, “Early Detection of Baby-Rain-Cell Aloft in a Severe Storm and Risk Projection for Urban Flash Flood,” Advances in Meteorology, Vol.2017, pp. 1-15, 2017.
  25. [25] E. Nakakita, K. Yamaguchi, Y. Sumida et al., “Classification of Hydrometeors Using a C-band Polarimetric Radar and Validation by In-Situ Campaign Observation Synchronized with Video-Sonde,” Disaster Prevention Research Institute Annuals, Vol.51, pp. 519-533, 2007 (in Japanese).
  26. [26] K. Fukami, M. Kawasaki, S. Tsuchia, and H. Fujimaki, “History of ‘Radar Raingauges’ as the Precipitation Radar System of MLIT and its Future Direction,” Civil Engineering J., Vol.58, No.7, pp. 20-25, 2016 (in Japanese).
  27. [27] Bureau of Sewerage Tokyo Metropolitan Government, “Tokyo Amesh 2021,” https://tokyo-ame.jwa.or.jp/en/index.html [accessed September 1, 2020]
  28. [28] C. Kummerow, W. Barnes, T. Kozu, J. Shiue, and J. Simpson, “The Tropical Rainfall Measuring Mission (TRMM) Sensor Package,” J. of Atmospheric and Oceanic Technology, Vol.15, No.3, pp. 809-817, 1998.
  29. [29] T. Kubota, S. Shige, H. Hashizurne et al., “Global precipitation map using satellite-borne microwave radiometers by the GSMaP project: Production and validation,” IEEE Trans. on Geoscience and Remote Sensing, Vol.45, No.7, pp. 2259-2275, 2007.
  30. [30] Q. H. Sun, C. Y. Miao, Q. Y. Duan, H. Ashouri, S. Sorooshian, and K.-L. Hsu, “A Review of Global Precipitation Data Sets: Data Sources, Estimation, and Intercomparisons,” Reviews of Geophysics, Vol.56, No.1, pp. 79-107, 2018.
  31. [31] N. Mastrantonas, B. Bhattacharya, Y. Shibuo, M. Rasmy, G. Espinoza-Dávalos, and D. Solomatine, “Evaluating the Benefits of Merging Near-Real-Time Satellite Precipitation Products: A Case Study in the Kinu Basin Region, Japan,” J. of Hydrometeorology, Vol.20, No.6, pp. 1213-1233, 2019.
  32. [32] R. A. Acierto, A. Kawasaki, W. W. Zin, A. T. Oo, K. Ra, and D. Komori, “Development of a Hydrological Telemetry System in Bago River,” J. Disaster Res., Vol.13, No.1, pp. 116-124, 2018.
  33. [33] D. E. Alsdorf, E. Rodríguez, and D. P. Lettenmaier, “Measuring surface water from space,” Reviews of Geophysics, Vol.45, No.2, pp. 1-24, 2007.
  34. [34] Y. Kwak, S. H. Yun, and Y. Iwami, “A New Approach for Rapid Urban Flood Mapping Using ALOS-2/PALSAR-2 in 2015 Kinu River Flood, Japan,” 2017 IEEE Int. Geoscience and Remote Sensing Symp. (IGARSS), pp. 1880-1883, 2017.
  35. [35] J. C. Y. Guo, “Rational hydrograph method for small urban watersheds,” J. of Hydrologic Engineering, Vol.6, No.4, pp. 352-356, 2001.
  36. [36] L. Tolland, J. G. Cathcart, and S. O. D. Russell, “Estimating the Q100 in British Columbia: A practical problem in forest hydrology,” J. of the American Water Resources Association, Vol.34, No.4, pp. 787-794, 1998.
  37. [37] Y. Tanioka, S. Fukuoka, M. Taniguchi, and Y. Koyama, “Characteristics of Floods in Small Urban Rivers,” Proc. of JSCE, Vol.586, pp. 1-11, 1998 (in Japanese).
  38. [38] S. Tanaka, T. Sakakibara, S. Fujita, I. Tanaka, and K. Furukita, “Comparative Survey of Storm Runoff and Pollutant Load Models,” Japan Institute of Wastewater Engineering and Technology, 1994.
  39. [39] Japan Institute of Wastewater Engineering and Technology, “Runoff Analysis Model Application Manual: Operation Guidance of Runoff Analysis Model in Rainfall Management,” 2003.
  40. [40] P. M. Bach, W. Rauch, P. S. Mikkelsen, D. T. McCarthy, and A. Deletic, “A critical review of integrated urban water modelling – Urban drainage and beyond,” Environmental Modelling & Software, Vol.54, pp. 88-107, 2014.
  41. [41] Y. Yamagishi, T. Nonaka, and T. Nakamura, “Development of New Integrated Lowland Inundation Model,” Public Works Research Center, 2006.
  42. [42] M. Sunaguchi and M. Tsuchiya, “Study on the simulation of an inner water inundation and reduction measures of the water disaster for the drainage basin of storm water in an urban area,” Doboku Gakkai Ronbunshuu B, Vol.64, No.4, pp. 240-250, 2008 (in Japanese).
  43. [43] H. Yoneda, M. Satoh, I. Kawamura, M. Yamaguchi, K. Matsumoto, and T. Yamada, “The Risk Assessment of The Flood Damage By Inner and River Water Simultaneous Flood Analysis with Uncertainty of Rainfall and Runoff Analysis,” J. of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering), Vol.74, No.5, pp. I_1387-I_1392, 2018.
  44. [44] N. Koyama and T. Yamada, “A Proposed Simultaneous Calculation Method for Flood by River Water, Inland Flood, and Storm Surge at Tidal Rivers of Metropolitan Cities: A Case Study of Katabira River in Japan,” Water, Vol.12, No.6, p. 1769, 2020.
  45. [45] K. Kawaike, K. Inoue, K. Toda, H. Sakai, and R. Sagara, “Inundation Flow Analysis Due to Heavy Rainfall in Low-Lying River Basin and its Application to Neya River Basin,” Proc. of Hydraulic Engineering, Vol.46, pp. 367-372, 2002.
  46. [46] K. Kawaike, K. Inoue, K. Toda, and M. Noguchi, “Refinement of Inundation Flow Model Applied to Neya River Basin,” Proc. of Hydraulic Engineering, Vol.47, pp. 919-924, 2003.
  47. [47] J. A. Cunge and M. Wegner, “Numerical integration of Barré de Saint-Venant’s flow equations by means of an implicit scheme of finite differences,” La Houille Blanche, No.1, pp. 33-39, 1964 (in French).
  48. [48] M. Sekine, “Numerical Analysis of Inundation in the Region of Downtown Tokyo with Residence Area,” J. of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering), Vol.67, No.2, pp. 70-85, 2011.
  49. [49] M. Sekine and K. Kodama, “Evaluation of Inundation Risk During Heavy Rain in Tokyo 23 Wards and Pre-Flooding of Underpass,” J. of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering), Vol.74, No.4, pp. I_1543-I_1548, 2018 (in Japanese).
  50. [50] J. Akiyama, M. Shige-Eda, and T. Tanabe, “Numerical Simulation of Inundation Flow with Sewer Network in the Onga River Basin,” Annual J. of Hydraulic Engineering, Vol.53, pp. 829-834, 2009 (in Japanese).
  51. [51] J. Akiyama, M. Shige-Eda, and H. Kusano, “Economic Loss Estimation in Iizuka City Using Numerical Simulator for Rainfall-Runoff/Flood Inundation Process in Urban Area Wit River and Sewer Network,” J. of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering), Vol.68, No.4, pp. I_1063-I_1068, 2012 (in Japanese).
  52. [52] M. Takeda, M. Murase, R. Mouri, and N. Matsuo, “Numerical Analysis on Water Behaviour in Urban Area by Inudation Due to River Flood and Heavy Rain Considering the Origin,” J. of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering), Vol.74, No.5, pp. I_1465-I_1470, 2018 (in Japanese).
  53. [53] M. Takeda, M. Murase, Y. Nakajima, K. Komatsu, and N. Matsuo, “Numerical Analysis on Water Behaviour in Urban Area Due to Overlapping of Storm Surge and Flood Considering the Origin of the Inundation,” J. of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering), Vol.74, No.4, pp. I_1429-I_1434, 2018 (in Japanese).
  54. [54] T. Sayama and J. J. McDonnell, “A new time-space accounting scheme to predict stream water residence time and hydrograph source components at the watershed scale,” Water Resources Research, Vol.45, No.7, W07401, 2009.
  55. [55] H. Sanuki, Y. Shibuo, S. Lee et al., “Inundation Forecast Simulation in Urbanized Coastal Low-Lying Areas Considering Multiple Flood Causing Factors,” J. of Japan Society of Civil Engineers, Ser. B2 (Coastal Engineering), Vol.72, No.2, pp. I_517-I_522, 2016 (in Japanese).
  56. [56] L. Wang, T. Koike, D. Yang, and K. Yang, “Improving the hydrology of the Simple Biosphere Model 2 and its evaluation within the framework of a distributed hydrological model,” Hydrological Sciences J., Vol.54, No.6, pp. 989-1006, 2009.
  57. [57] K. Kawaike, A. Shimizu, Y. Baba, H. Nakagawa, and M. Takeda, “Verification of numerical model for urban inundation due to torrential rainfall using physical experimental flume with a sewer pipe,” J. of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering), Vol.67, No.4, pp. I_985-I_990, 2011 (in Japanese).
  58. [58] S. Lee, Y. Shibuo, and H. Furumai, “Change of Water Level and Electric Conductivity Using Monitoring Data at Combined Sewer Pipes in Tsurumi River Basin,” J. of Japan Society of Civil Engineers, Ser. G (Environmental Research), Vol.75, No.2, pp. 55-64, 2019 (in Japanese).
  59. [59] T. Adachi, K. Kusunoki, S. Yoshida, K. I. Arai, and T. Ushio, “High-Speed Volumetric Observation of a Wet Microburst Using X-band Phased Array Weather Radar in Japan,” Monthly Weather Review, Vol.144, No.10, pp. 3749-3765, 2016.
  60. [60] R. Uijlenhoet, A. Overeem, and H. Leijnse, “Opportunistic remote sensing of rainfall using microwave links from cellular communication networks,” Wiley Interdisciplinary Reviews: Water, Vol.5, No.4, e1289, 2018.
  61. [61] G. Kathiravelu, T. Lucke, and P. Nichols, “Rain Drop Measurement Techniques: A Review,” Water, Vol.8, No.1, p. 29, 2016.
  62. [62] M. Löffler-Mang and J. Joss, “An optical disdrometer for measuring size and velocity of hydrometeors,” J. of Atmospheric and Oceanic Technology, Vol.17, No.2, pp. 130-139, 2000.
  63. [63] P. Winder and K. S. Paulson, “The measurement of rain kinetic energy and rain intensity using an acoustic disdrometer,” Measurement Science and Technology, Vol.23, No.1, 015801, 2012.
  64. [64] J. Joss and A. Waldvogel, “A Spectrograph for Raindrops with Automatic Interpretation,” Pure and Applied Geophysics, Vol.68, No.3, 240-246, 1967.
  65. [65] M. Schönhuber, G. Lammer, and W. L. Randeu, “One decade of imaging precipitation measurement by 2D-video-distrometer,” Advances in Geosciences, Vol.10, pp. 85-90, 2007.
  66. [66] S. Onomura, K. Suzuki, and M. Nakayoshi, “Development of Image Disdrometer,” J. of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering), Vol.75, No.2, pp. I_1159-I_1164, 2019 (in Japanese).
  67. [67] S. Jiang, V. Babovic, Y. Zheng, and J. Xiong, “Advancing Opportunistic Sensing in Hydrology: A Novel Approach to Measuring Rainfall With Ordinary Surveillance Cameras,” Water Resources Research, Vol.55, No.4, pp. 3004-3027, 2019.
  68. [68] F. Meier, D. Fenner, T. Grassmann, M. Otto, and D. Scherer, “Crowdsourcing air temperature from citizen weather stations for urban climate research,” Urban Climate, Vol.19, pp. 170-191, 2017.
  69. [69] L. de Vos, H. Leijnse, A. Overeem, and R. Uijlenhoet, “The potential of urban rainfall monitoring with crowdsourced automatic weather stations in Amsterdam,” Hydrology and Earth System Sciences, Vol.21, No.2, pp. 765-777, 2017.
  70. [70] B. Strobl, S. Etter, I. van Meerveld, and J. Seibert, “Accuracy of crowdsourced streamflow and stream level class estimates,” Hydrological Sciences J., Vol.65, No.5, pp. 823-841, 2020.
  71. [71] S. Etter, B. Strobl, I. van Meerveld, and J. Seibert, “Quality and timing of crowd-based water level class observations,” Hydrological Processes, Vol.34, No.22, 2020.
  72. [72] J. Seibert, B. Strobl, S. Etter, P. Hummer, and H. J. van Meerveld, “Virtual Staff Gauges for Crowd-Based Stream Level Observations,” Frontiers in Earth Science, Vol.7, Article No.70, 2019.
  73. [73] M. Mazzoleni, M. Verlaan, L. Alfonso et al., “Can assimilation of crowdsourced data in hydrological modelling improve flood prediction?,” Hydrology and Earth System Sciences, Vol.21, No.2, pp. 839-861, 2017.
  74. [74] P. M. Avellaneda, D. L. Ficklin, C. S. Lowry, J. H. Knouft, and D. M. Hall, “Improving Hydrological Models With the Assimilation of Crowdsourced Data,” Water Resources Research, Vol.56, No.5, e2019WR026325, 2020.
  75. [75] L. Atzori, A. Iera, and G. Morabito, “The Internet of Things: A survey,” Computer Networks, Vol.54, No.15, pp. 2787-2805, 2010.
  76. [76] H. Schaffers, N. Komninos, M. Pallot, B. Trousse, M. Nilsson, and A. Oliveira, “Smart Cities and the Future Internet: Towards Cooperation Frameworks for Open Innovation,” Lecture Notes in Computer Science: The Future Internet: Future Internet Assembly 2011: Achievements and Technological Promises Proc., pp. 431-446, 2011.
  77. [77] A. Zanella, N. Bui, A. Castellani, L. Vangelista, and M. Zorzi, “Internet of Things for Smart Cities,” IEEE Int. of Things J., Vol.1, No.1, pp. 22-32, 2014.
  78. [78] B. Kerkez, C. Gruden, M. Lewis et al., “Smarter Stormwater Systems,” Environmental Science & Technology, Vol.50, No.14, pp. 7267-7273, 2016.
  79. [79] B. P. Wong and B. Kerkez, “Real-Time Control of Urban Headwater Catchments Through Linear Feedback: Performance, Analysis, and Site Selection,” Water Resources Research, Vol.54, No.10, pp. 7309-7330, 2018.
  80. [80] A. Mullapudi, M. Bartos, B. Wong, and B. Kerkez, “Shaping Streamflow Using a Real-Time Stormwater Control Network,” Sensors, Vol.18, No.7, 11, 2018.
  81. [81] Y. Nakasaka and T. Ishigaki, “Vulnerability to Mega Underground Inundation and Evacuation Assuming Devastating Urban Flood,” J. Disaster Res., Vol.16, No.3, pp. 321-328, 2021.
  82. [82] W. Kobayashi, “Reliability Assessment in Wireless Apparatus Using LoRa and Sigfox in Catch Basin,” J. Disaster Res., Vol.16, No.3, pp. 363-370, 2021.
  83. [83] H. Minakawa, I. Azechi, M. Kimura, N. Okumura, N. Kimura, and D. Baba, “Utilization of simulated data for development of a deep learning flood prediction model as support of drainage pump operation,” Annual J. of Hydraulic Engineering, Vol.76, No.2, pp. I_349-I_354, 2020 (in Japanese).
  84. [84] L. Wu, Y. Tajima, D. Yamazaki, Y. Shibuo, H. Sanuki, and H. Furumai, “Development of Real-Time Assimilation Model for Prediction of Inundation on Urbanized Coastal Lowland,” Proc. of the 10th Int. Conf. on Asian and Pacific Coasts (APAC 2019), pp. 1343-1349, 2019.
  85. [85] Y. Shibuo, L. Wu, Y. Tajima, D. Yamazaki, H. Sanuki, and H. Furumai, “Application of Databank-Based Data Assimilation to Urban Inundation Model for Improved Accuracy and Sensitivity Analysis of Pumping Operation,” J. of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering), Vol.75, No.2, pp. I_199-I_204, 2019.
  86. [86] P. H. Whitfield, “Floods in future climates: a review,” J. of Flood Risk Management, Vol.5, No.4, pp. 336-365, 2012.

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