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A Flood Forecasting Method Based on Spatiotemporal Database of Rainfall and Flood

A technology of spatiotemporal data and rainfall data, applied in geographic information databases, forecasting, data processing applications, etc., can solve problems such as early warning obstacles and achieve accurate forecasting effects

Active Publication Date: 2020-10-16
SHANGHAI NORMAL UNIVERSITY
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Problems solved by technology

There are many types of databases above, but there is a lack of a summary database that unifies disaster-causing factors, disaster space-time information and detailed data statistics functions, which hinders disaster analysis and early warning.

Method used

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  • A Flood Forecasting Method Based on Spatiotemporal Database of Rainfall and Flood
  • A Flood Forecasting Method Based on Spatiotemporal Database of Rainfall and Flood
  • A Flood Forecasting Method Based on Spatiotemporal Database of Rainfall and Flood

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Embodiment

[0048] In this embodiment, the spatio-temporal data integrated with major flood disasters and daily rainfall data since the founding of the People's Republic of China are used to detect and predict the laws of rainstorm and flood disasters, including the following steps:

[0049]1) Use the relational database PostgreSQL to establish a data model, establish a complete table that can show the dynamic changes in daily rainfall, collect daily rainfall data from 1951 to 2013 at 194 stations across the country, and merge the data of all stations by month (data source : The 1951-2010 data in the data set was developed based on the "1951-2010 Chinese National Ground Station Data Corrected Monthly Report Data File (A0 / A1 / A) Basic Data Set" archived by the ground basic meteorological data construction project. 2011 The data from January to May 2012 was developed based on the surface monthly report data file (A file) reported by each province to the National Meteorological Information Cen...

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Abstract

The invention relates to a flood forecasting method based on a rainfall flood space-time database. The flood forecasting method comprises the following steps that 1) the rainfall flood space-time database is constructed; 2) a dynamic space-time rainfall map is drawn according to the rainfall flood space-time database with combination of GIS map data; 3) the space-time data corresponding to all the heavy rain paths involved in the flood in the historical periods of time are acquired according to the rainfall flood space-time database, and the heavy rain paths are displayed on the space-time rainfall map; and 4) corresponding class models are acquired according to the space-time data corresponding all the heavy rain paths, and flood forecasting is performed according to the class models. Compared with the methods in the prior art, the flood forecasting method has the advantages of being connected in space and time, dynamic and visual and accurate in forecasting.

Description

technical field [0001] The invention relates to the field of flood forecasting, in particular to a flood forecasting method based on a rainfall flood spatio-temporal database. Background technique [0002] Based on the review of previous studies, natural disaster databases can be divided into five types, namely statistical, spatial relational, time-relational, element-relational and process-relational. At present, the research on the establishment and application of China's comprehensive natural disaster database mainly focuses on the following three aspects. [0003] 1) Comprehensive natural disaster database and space-time regularity research. The database is a statistical database, [0004] For example, the China Natural Disaster Database is a statistical database consisting of sub-databases such as the China Natural Disaster Causing Factor Database, the Chinese Press and Periodical Natural Disaster Information Database, the Chinese Historical Natural Disaster Database,...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/04G06F16/29
CPCG06F16/29G06Q10/04Y02A10/40Y02A90/10
Inventor 杨宇涵蒋静婷降瑞娇
Owner SHANGHAI NORMAL UNIVERSITY
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