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Design and key techniques of a collaborative virtual flood experiment that integrates cellular automata and dynamic observations

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Abstract

With the development of computer science, communications technology and environmental modeling, virtual geographic environments (VGEs) have been linked with field observations and geographic modeling. VGEs enable researchers in various fields to collaboratively perform computer-aided geographic experiments. This study proposes a collaborative environment to conduct a virtual flood experiment that integrates cellular automata and dynamic observations. Some of the key techniques, including a cellular automata flood modeling method, a real-time parameter similarity evaluation method, and a collaborative visualization and operation method, are explored. The proposed techniques are tested with a prototype system as part of a flood simulation case study of the Hunhe River in Liaoning Province. We conclude that a virtual experiment environment can provide effective technical support for flood research.

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References

  • Al-Fuagara A, Ahmed T, Ghazali AH, Zakaria S, Mahmud AR, Mansor S, Al-Mattarneh HMA (2008) The application of hydraulic model with GIS for visual floodplain mapping: a case study of Kuala Lumpur City, Malaysia. In: international conference on construction and building technologies (ICCBT), 2008-D, pp 273–282

  • Bates PD, de Roo APJ (2000) A simple raster-based model for flood inundation simulation. J Hydrol 236(1–2):54–77

    Article  Google Scholar 

  • Berndt D, Clifford J (1994) Using dynamic time warping to find patterns in time series. In: Fayyad UM (ed) UTHUR USA: MYR. AAAI-94 Workshop on Knowledge Discovery in Databases (KDD-94). Menlo Park, AAAI Press, pp 229–248

  • Bever AJ, Friedrichs MAM, Friedrichs CT et al (2013) Combining observations and numerical model results to improve estimates of hypoxic volume within the Chesapeake Bay, USA. J Geophys Res Oceans 118(10):4924–4944

    Article  Google Scholar 

  • Chen YG, Liu JS (2004) Main tasks and methods of geography. SCIENTIA GEOGRAPHICA SINICA 24(3):257–263

    Google Scholar 

  • Chen M, Lin M, Wen YN, He L, Hu MY (2012) Sino-VirtualMoon: a 3D web platform using Chang’e-1 data for collaborative research. Planet Space Sci 65(1):130–136

    Article  Google Scholar 

  • Chiggiato J, Jarosz E, Book JW et al (2012) Dynamics of the circulation in the Sea of Marmara: numerical modeling experiments and observations from the Turkish straits system experiment. Ocean Dyn 62(1):139–159

    Article  Google Scholar 

  • Ernst J, Coninx I, Dewals BJ, Detrembleur S, Erpicum S, Bachus K, Pirotton M (2009) Social flood impacts in urban areas: integration of detailed flow modelling and social analysis. In: Proceedings 33rd IAHR congress—water engineering for a sustainable environment. Vancouver, British Columbia, IAHR, pp 6820–6827

  • Evensen G (2003) The ensemble kalman filter: theoretical formulation and practical implementation. Ocean Dyn 53(4):343–367

    Article  Google Scholar 

  • Fiore SM, Harrison GW, Hughes CE, Rutström EE (2009) Virtual experiments and environmental policy. J Environ Econ Manag 57(1):65–86

    Article  Google Scholar 

  • Formetta G, Antonello A, Franceschi S (2014) Hydrological modelling with components: a GIS-based open-source framework. Environ Model Softw 55:190–200

    Article  Google Scholar 

  • Helbig C, Bauer HS, Rink K et al (2014) Concept and workflow for 3D visualization of atmospheric data in a virtual reality environment for analytical approaches. Environ Earth Sci 72(10):3767–3780

    Article  Google Scholar 

  • Kulkarni AT, Mohanty J, Eldho TI et al (2014) A web GIS based integrated flood assessment modeling tool for coastal urban watersheds. Comput Geosci 64:7–14

    Article  Google Scholar 

  • Li GY (2002) Construction of “Three Yellow Rivers”. Yellow River 24(7):1–3

    Google Scholar 

  • Li Y, Gong JH, Zhu J et al (2012) Efficient dam break flood simulation methods for developing a preliminary evacuation plan after the Wenchuan Earthquake. Nat Hazards Earth Syst Sci 12(1):97–106

    Article  Google Scholar 

  • Li Y, Gong JH, Zhu J et al (2013) Spatial-temporal simulation and risk analysis of dam-break flooding based on cellular automata. Int J Geogr Inf Sci 27(10):2043–2059

    Article  Google Scholar 

  • Li Y, Gong JH, Liu H et al (2015) Real-time flood simulations using CA model driven by dynamic observation data. Int J Geogr Inf Sci 29(4):523–535

    Article  Google Scholar 

  • Lin H, Huang FR, Lu GN (2009) Development of virtual geographic environments and the new initiative in experimental geography. Scientia Geographica Sinica 64(1):7–20

    Google Scholar 

  • Lin H, Chen M, Lu GN (2012) Virtual Geographic Environments—a workspace for computer-aided geographic experiments. Ann Assoc Am Geogr 103(3):465–482

    Article  Google Scholar 

  • Lin H, Chen M, Lu GN et al (2013) Virtual Geographic Environments (VGEs): a New Generation of Geographic Analysis Tool. Earth Sci Rev 126:74–84

    Article  Google Scholar 

  • Liu SK, Li XP, Li SG, Yu TY (1991) Numerical simulation of flood routing in the Xiaoqinghe flood plain. Adv Water Sci 2(3):188–193 (in Chinese)

    Google Scholar 

  • Lu GN (2011) Geographic analysis-oriented virtual geographic environment: framework, structure and functions. Sci China Ser D Earth Sci 54(5):733–743

    Article  Google Scholar 

  • Mackinder HJ (1987) On the scope and methods of geography. Proc R Geogr Soc Mon Rec Geogr 9(3):141–174

    Google Scholar 

  • Matthews JA, Herbert DT (2008) Geography: a very short introduction. Oxford University Press, New York

    Book  Google Scholar 

  • Ministry of water Resources of China (1995a) Test regulation for model of river (SL 99-95). China Water Power Press, Beijing (in Chinese)

    Google Scholar 

  • Ministry of water Resources of China (1995b) Test regulation for normal hydraulic model (SL 156-165-95). China Water Power Press, Beijing (in Chinese)

    Google Scholar 

  • Ramasundaram V, Grunwald S, Mangeot A, Comerford N, Bliss C (2005) Development of an environmental virtual field laboratory. Comput Educ 45(1):21–34

    Article  Google Scholar 

  • Rinaldi PR, Dalponte DD, Vénere MJ, Clausse A (2007) Cellular automata algorithm for simulation of surface flows in large plains. Simul Model Pract Theory 15(3):315–327

    Article  Google Scholar 

  • Rink K, Scheuermann G, Kolditz O (2014) Visualisation in environmental sciences. Environ Earth Sci 72(10):3749–3751

    Article  Google Scholar 

  • Soulis KX (2013) Development of a simplified grid cells ordering method facilitating GIS-based spatially distributed hydrological modeling. Comput Geosci 54:160–163

    Article  Google Scholar 

  • Torrens PM (2009) Process models and next-generation geographic information technology (GIS best practices: essays on geography and GIS, vol 2, pp 63–75). ESRI Press, Redlands

  • Van Der Knijff JM, Younis J, De Roo APJ (2010) LISFLOOD: a GIS-based distributed model for river basin scale water balance and flood simulation. Int J Geogr Inf Sci 24(2):189–212

    Article  Google Scholar 

  • Wang B, Zhou X, Zhu J (2000) Data assimilation and its applications. Proc Nat Acad Sci 97(21):11143–11144

    Article  Google Scholar 

  • Zhang Y, Li X, Liu X, Qiao J (2011) The CA model based on data assimilation. J Remote Sens 15(3):475–491

    Google Scholar 

Download references

Acknowledgments

This research is supported by the National Natural Science Foundation of China (41101363), the Key Knowledge Innovative Project of the Chinese Academy of Sciences (KZCX2-EW-318), the National Natural Science Foundation of China (41471341, 41201375), “135” Strategy Planning (Grant No. Y3SG1500CX) of the Institute of Remote Sensing and Digital Earth, CAS, the Young Scientists Foundation of RADI (Y5SJ1000CX), Tianjin Research Program of Application Foundation and Advanced Technology (14JCQNJC07900).

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Correspondence to Jianhua Gong.

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Li, Y., Gong, J., Song, Y. et al. Design and key techniques of a collaborative virtual flood experiment that integrates cellular automata and dynamic observations. Environ Earth Sci 74, 7059–7067 (2015). https://doi.org/10.1007/s12665-015-4716-9

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  • DOI: https://doi.org/10.1007/s12665-015-4716-9

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