{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T17:30:28Z","timestamp":1773423028772,"version":"3.50.1"},"reference-count":51,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2019,11,18]],"date-time":"2019-11-18T00:00:00Z","timestamp":1574035200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Dynamic visual simulation of flood risk is crucial for scientific and intelligent emergency management of flood disasters, in which data quality, availability, visualization, and interoperability are important. Here, a seamless integration of a spatio-temporal Geographic Information System (GIS) with one-dimensional (1D) and two-dimensional (2D) hydrodynamic models is achieved for data flow, calculation processes, operation flow, and system functions. Oblique photography-based three-dimensional (3D) modeling technology is used to quickly build a 3D model of the study area (including the hydraulic engineering facilities). A multisource spatio-temporal data platform for dynamically simulating flood risk was built based on the digital earth platform. Using the spatio-temporal computation framework, a dynamic visual simulation and decision support system for flood risk management was developed for the Xiashan Reservoir. The integration method proposed here was verified using flood simulation calculations, dynamic visual simulations, and downstream river channel and dam-break flood simulations. The results show that the proposed methods greatly improve the efficiency of flood risk simulation and decision support. The methods and system put forward in this study can be applied to flood risk simulations and practical management.<\/jats:p>","DOI":"10.3390\/ijgi8110520","type":"journal-article","created":{"date-parts":[[2019,11,18]],"date-time":"2019-11-18T11:18:48Z","timestamp":1574075928000},"page":"520","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["Dynamic 3D Simulation of Flood Risk Based on the Integration of Spatio-Temporal GIS and Hydrodynamic Models"],"prefix":"10.3390","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6829-053X","authenticated-orcid":false,"given":"Yongxing","family":"Wu","sequence":"first","affiliation":[{"name":"Institute of Remote Sensing and GIS, Peking University, Beijing 100871, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7050-8622","authenticated-orcid":false,"given":"Fei","family":"Peng","sequence":"additional","affiliation":[{"name":"Institute of Remote Sensing and GIS, Peking University, Beijing 100871, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yang","family":"Peng","sequence":"additional","affiliation":[{"name":"School of Renewable Energy, North China Electric Power University, Beijing 102206, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoyang","family":"Kong","sequence":"additional","affiliation":[{"name":"Institute of Remote Sensing and GIS, Peking University, Beijing 100871, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Heming","family":"Liang","sequence":"additional","affiliation":[{"name":"Institute of Remote Sensing and GIS, Peking University, Beijing 100871, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qi","family":"Li","sequence":"additional","affiliation":[{"name":"Institute of Remote Sensing and GIS, Peking University, Beijing 100871, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,11,18]]},"reference":[{"key":"ref_1","first-page":"14","article-title":"Analysis on the Basic Situation of Natural Disasters in 2018","volume":"5","author":"Liu","year":"2019","journal-title":"Disaster Reduct. 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