TWI598840B - Method for optimizing database of two-dimensional flood potential map - Google Patents

Description

Optimization method of two-dimensional flooding potential map database

The invention relates to a technology for flooding situation simulation and image searching, and particularly relates to a method for optimizing a two-dimensional flooding potential map database.

The current flood disaster information providing system stores historical flooding data of a certain geographical area in its database, and the user can understand the flooding situation of the geographical area through the action of the query. However, the user cannot provide an instant understanding of the current flooding situation through the flooding disaster information providing system, and the flooding disaster information providing system cannot effectively provide an immediate flooding forecast.

Therefore, how to enable users to predict the flooding situation that may occur in a geographical area in an instant and accurate manner is the focus of the field.

It is an object of the present invention to provide an optimized method for a two-dimensional flooding potential map database that can expand the database as new rainfall events in the geographic area increase.

To achieve the above object, the present invention provides an optimization method for a two-dimensional flooding potential map database, comprising the following steps: a. Historical rainfall from a geographical area To simulate the group map of the rainfall event; b. use the group map of the rainfall event to simulate the flooding of the geographic area to generate a two-dimensional flooding potential map and store it in the database; c. Searching for the optimal flooding potential map from the database based on the instantaneous observation water level of each station in the geographic area; and d. adding new rainfall events to the historical rainfall events of the geographic area, and Repeat steps a through c.

In one embodiment of the invention, step a includes: extracting rainfall events from historical rainfall events of the geographic area, each rainfall event including parameters such as rainfall delay, rainfall, and rain type, the rainfall event being defined as a continuous rainfall period Rainfall, the rainfall delay of the rainfall event is defined as the duration of the rainfall event, the rain pattern of the rainfall event is defined as the distribution of rainfall rainfall over time or its simulation function; each rainfall event in the historical rainfall event of the geographic region Performing statistical analysis to obtain a statistical analysis result of the rainfall event in the geographical area; and simulating a group map of the rainfall event according to the statistical analysis result of the rainfall event in the geographical area, the group diagram of the rainfall event includes a Or multiple rainfall events.

In an embodiment of the present invention, the step of simulating the group map for generating the rain event according to the statistical analysis result of the rainfall event of the geographical area comprises: simulating the rain pattern according to the statistical analysis result of the rainfall event of the geographical area, Rainfall delay, rainfall and rainfall event interval, resulting in a group map of the rainfall event.

In an embodiment of the present invention, in the step of simulating the group map for generating the rain event according to the statistical analysis result of the rainfall event in the geographical area, the Monte Carlo simulation method is used to generate the group of the rain event. Figure.

In an embodiment of the present invention, step b includes: using the group map of the rainfall event, simulating rainfall at different locations or different ranges of the geographic region, generating multiple sets of different rainfall scenario simulation data; and utilizing the multiple groups of different The rainfall situation simulation data, combined with the hydrological and terrestrial data of the geographical area, simulates the flooded area, respectively generates multiple two-dimensional flooding potential maps, and stores them in the two-dimensional flooding potential map database. .

In an embodiment of the present invention, step c includes: c1. collecting the instantaneous observation water level of each station in the geographical area; c2. using the processor to calculate a set time of each station in the geographical area from the current time point The observed water level at the current time point and the index of difference in scale of the simulated water level in the two-dimensional flooding potential map database; c3. using the processor to calculate the geography The average of the scale difference indicators of all stations in the area, and sorted from small to large, and selects the flooding map corresponding to the predetermined number of groups in front; c4. Using the processor to calculate the setting of each station in the geographical area from the setting The observation of the water level from the time point to the current time point and the time-difference in time of the simulated water level of the predetermined number of flooding maps selected in step c3; c5. calculating the geography using the processor The average value of the time trend difference index of all stations in the area, and the flooding map corresponding to the smallest average of the time trend difference indicators is selected as the representative of the set time point. a potential map; c6. using the processor to calculate an average error value of the simulated water level of the station at the current time point and the simulated water level at the same time point in the geographic area; and c7. The set time point is gradually increased as a new set time point, and steps c2 to c6 are repeated, and the process is utilized. The average error value of the representative flooding potential map at each set time point is calculated, and the representative flooding potential map corresponding to the smallest one is selected as the optimal flooding potential map.

In an embodiment of the invention, the method further comprises the step of: c8. correcting the optimal flooding potential map by using the observed water level observed by all stations in the geographical area.

In the embodiment of the present invention, the database can be expanded with the increase of new rainfall events in the geographical area, and becomes a level of huge amount of data, and this huge database also becomes the basis for searching for the best flooding potential map. . As the amount of data in the database increases, it is also expected to find a more accurate flooding potential map.

S10~S16‧‧‧Steps

S20~S24‧‧‧Steps

S30~S32‧‧‧Steps

S71~S81‧‧‧Steps

FIG. 1 is a flow chart showing an optimization method of a two-dimensional flooding potential map database in an embodiment of the present invention.

Fig. 2 is a flow chart showing a method of generating a two-dimensional flooding potential map in the embodiment of the present invention.

Fig. 3A shows an example of the rainfall amount of the rain event in the embodiment of the present invention.

Fig. 3B shows an example of a simulated rain pattern in the embodiment of the present invention.

Fig. 3C shows an example of a group diagram of a rain event in the embodiment of the present invention.

Fig. 4 shows an example of the water level data in the embodiment of the present invention.

Fig. 5 shows an example of a flooding situation in the embodiment of the present invention.

Fig. 6 shows an example of the simulated water level and the observed water level in the embodiment of the present invention.

Figure 7 shows the search for a two-dimensional flooding potential map database in the embodiment of the present invention. Schematic diagram of the process of flooding the map.

Figure 8 is a flow chart showing the search for a flooded map in a two-dimensional flooding potential map database in another embodiment of the present invention.

The present invention will be further described in detail below with reference to the drawings and embodiments.

In the embodiment of the present invention, for the construction of the two-dimensional flooding potential map database, the rainfall events in the geographical area (such as the watershed) are simulated to calculate various flooding conditions, and the calculation results are stored in the exclusive data. Library (two-dimensional flooding potential map database).

In the embodiment of the present invention, for the image searching of the two-dimensional flooding potential map database, a huge amount of data searching technology is adopted, and the optimal feature condition is obtained by observing the observation water level of each station in the geographical area and the flooding map. Match and find the best flooding potential map.

In the embodiment of the present invention, the two-dimensional flooding potential map database becomes a level of huge amount of data due to the update of the data and continuous learning, so that the two-dimensional flooding potential map database increases with time. The generation of a huge database can also be the basis for searching for the best flooding potential map.

Please refer to FIG. 1 , which is a flow chart showing an optimization method of a two-dimensional flooding potential map database in an embodiment of the present invention, the method comprising the following steps:

Step S10: Simulate a group map of the rain event from the historical rainfall event of the geographical area.

The embodiment of the invention can simulate the flooding situation of the area for a geographical area, and the rainfall data of the area needs to be obtained before simulating the flooding situation of the area. In this regard, historical rainfall events in this geographic area can be obtained from meteorological information providers (such as the Central Weather Service).

Here, a rainfall event is defined as rainfall during a continuous rainfall, and a population map of a rainfall event may contain one or more rainfall events.

For example, during the rainy season or during a typhoon, there may be multiple rainfalls. A continuous rainfall can be considered as a rainfall event, and a group map of a rainfall event can represent a rainy season or a typhoon.

The historical rainfall event of the geographical area can be statistically analyzed, and the rainfall law of the geographical area can be obtained, and the group map of the rainfall event can be simulated according to the simulation, and a group map of a large number of rainfall events can be generated by using the simulation method, thereby In the subsequent steps, a large number of flooding potential maps are simulated, which effectively increases the number of samples in the database.

Step S12: Using the group map of the rainfall event, performing flooding simulation of the geographic area to generate a two-dimensional flooding potential map and storing it in a database.

The group map of each simulated rainfall event can be used to simulate the flooding status of the geographical area. In this process, the hydrological and geologic data of the geographical area, water level data such as the water level and flow rate of the river, etc. Textual information such as contour maps or street and building locations.

The two-dimensional flooding potential map represents the grouping map using the rainfall event, and the two-dimensional water pattern is used to simulate the flooding situation of the geographical area. simulation The resulting two-dimensional flooding potential map is stored in a database, and subsequent searches can be performed in the database to predict possible flooding conditions in the geographic area.

Step S14: Searching for the optimal flooding potential map from the database according to the instantaneous observation water level of each station in the geographical area.

In this step, the difference between the instantaneous observation water level of each station in the geographical area and the simulated water level of each two-dimensional flooding potential map in the database can be analyzed, and the difference between the observed water level and the simulated water level at different time points can be compared. The degree and trend of change to find the optimal flooding potential map, which represents the possible flooding situation in the geographical area.

The search process of the aforementioned optimal flooding potential map can be implemented by a specific algorithm, which can be described below.

Step S16: adding a new rainfall event to the historical rainfall event of the geographical area, and repeating steps S10 to S14.

The geographic area is followed by a new rainfall event. The embodiment of the present invention can consider new rainfall events in the geographic area, thereby increasing the number of samples in the database and improving the accuracy of the flooding potential search.

Specifically, a new rainfall event in the geographic area may be added to its historical rainfall event, and a group map of the rainfall event is simulated through step S10, and a group map of the different rainfall events may be generated at this time; S12 generates a corresponding new two-dimensional flooding potential map, thereby amplifying the data amount of the database; and when the flooding potential search is performed in step S14, a more accurate flooding potential map can be found.

In the embodiment of the present invention, the database can be expanded with the increase of new rainfall events in the geographical area, and becomes a level of huge amount of data, and this huge database also becomes the basis for searching for the best flooding potential map. . As the amount of data in the database increases, it is also expected to find a more accurate flooding potential map.

In the construction of the two-dimensional flooding potential map database, rainfall events in geographical areas (such as watershed) can be simulated in advance, and a large number of rainfall events are derived. For example, the rainfall data collection in the geographical area can be integrated, the statistical analysis of the rainfall characteristics can be integrated, and the rainfall characteristic simulation mechanism developed by the Monte Carlo simulation method can be used to derive a large number of rainfall events in consideration of the spatial variability of the rainfall station. Various rainfall scenarios were simulated to simulate the two-dimensional flooding in the designated area, and the results were plotted as flooding potential maps and stored in the database as the basis for flooding potential data search.

An embodiment of the present invention provides a method for generating a two-dimensional flooding potential map. Referring to FIG. 2, a flow chart of a method for generating a two-dimensional flooding potential map according to an embodiment of the present invention is shown. The method includes the following steps. . It should be noted that, in the above step S10, the generation of the group map of the rain event may correspond to the steps S20 to S24 of the method; in the above step S12, the generation of the two-dimensional flooding potential map may correspond to the steps of the method. S30~S32.

Step S20: Extracting rainfall events from historical rainfall events in the geographic area, each rainfall event including parameters such as rainfall delay, rainfall, and rain patterns.

Historical rainfall events in a geographical area usually contain more than one rainfall event. Rain events are rainfall during a continuous rainfall. For example, there may be multiple rainfalls during the rainy season or during a typhoon. Each rainfall can be considered as a rainfall event.

Here, the rainfall delay of a rainfall event is defined as the duration of the rainfall event; the rain pattern of a rainfall event is defined as the distribution of rainfall rainfall over time or its simulation function; the rainfall of a rainfall event is defined as the total rainfall of the rainfall event.

Step S22: Perform statistical analysis on each rainfall event in the historical rainfall event of the geographical area, and obtain a statistical analysis result of the rainfall event in the geographical area.

The historical rainfall event of the geographical area can be statistically analyzed to obtain the rainfall law of the geographical area. For example, for a geographical area, the rainfall of each rainfall can be summarized, and the probability distribution of rainfall rainfall is obtained. The duration of each rainfall is summarized, and the probability distribution of rainfall duration is obtained. The probability of a rain pattern that occurs every time it rains.

In the subsequent step, when simulating the rainfall event in the geographical area, the probability distribution of the rainfall rainfall, the probability distribution of the rainfall duration, and/or the probability of occurrence of the rain pattern of each rainfall, or the like, or any combination thereof may be considered. In this way, when simulating a rain event, the rainfall situation in the geographical area can be closer. For example, the rainfall patterns of deserts and forests are completely different.

Step S24: Simulate the group map of the rain event according to the statistical analysis result of the rainfall event in the geographical area.

The statistical analysis results of rainfall events in geographical areas can be quantified, for example, by probability distribution as a quantification method, which can facilitate the simulation of rainfall events in the geographical area and facilitate the generation of a group map of rainfall events.

The statistical analysis of rainfall characteristics (ie, rainfall delay, rainfall and rain patterns of rainfall events) can be integrated, and the rainfall characteristics simulation mechanism developed by Monte Carlo simulation method can be used to derive a large number of rainfall events.

This step may include: simulating the rain pattern, the rainfall delay, the rainfall amount, and the interval interval of the rain event according to the statistical analysis result of the rainfall event in the geographical area, thereby generating a group map of the rainfall event. This step can utilize the Monte Carlo simulation method to generate a group map of the rainfall event.

For example, the two rainfall events shown in Figure 3A (ie, Rain Event 1 and Rain Event 2) can generate two rainfall events through the rain pattern simulated by the statistical analysis structure shown in Figure 3B, respectively. The rainfall distribution, which simulates a population map of a rainfall event containing two rainfall events as shown in Figure 3C.

Step S30: Using the group map of the rainfall event, simulating rainfall at different locations or different ranges of the geographic region, and generating multiple sets of different rainfall scenario simulation data.

The group map of the rainfall events simulated in step S24 can derive additional rainfall scenarios in consideration of the spatial variability of the heavy rainfall stations. That is to say, the rainfall according to the group map of the rainfall event can fall in different locations or different ranges of the geographical area, so that multiple sets of different rainfall situation simulation data can be generated.

For example, the simulated rainfall can be carried out upstream of a river, or it can be placed downstream of the river. Rainfall can fall in different locations or different ranges of the geographical area, and can be used as simulation data for different rainfall scenarios. This will cause subsequent flooding area simulations to produce different results.

Step S32: using the plurality of different rainfall situation simulation data, matching the hydrological and geotextuological data of the geographical area, performing flooding area simulation, respectively generating a plurality of two-dimensional flooding potential maps, and storing the two-dimensional flooding potential maps in two dimensions Flooding potential map database.

Each simulated multiple sets of different rainfall scenario simulation data, combined with the hydrological and geologic data of the geographical area, can be used to simulate the flooding status of the geographical area, and the two-dimensional hydraulic model can be used to simulate the geographical area. Out of the flooding situation. As shown in Figure 4, it displays hydrological data for a geographic area; as shown in Figure 5, it shows simulated flooding scenarios for a geographic area. The two-dimensional flooding potential map generated by the simulation is stored in the database, and the subsequent flooding can be predicted through the search.

In the embodiment of the present invention, the rainfall data collection in the geographical area can be integrated, the statistical analysis of the rainfall characteristics can be integrated, and the rainfall characteristic simulation mechanism developed by the Monte Carlo simulation method can be used to derive a large amount of the spatial variability of the rainfall station. Rainfall event. These large rainfall events can simulate a large number of flooding potential maps, thus enriching the data volume of the database and improving the accuracy of flooding prediction.

In the aspect of searching for the image of the two-dimensional flooding potential map database, the embodiment of the present invention applies data mining to search for the best flooding map from the two-dimensional flooding potential library to obtain suitable data. Flooding forecast information. After the initial establishment of the database, the observational water level information measured by the station in the real-time geographic area is used as a characteristic factor, and the flooding situation generated by using different hydrological and hydrological situation conditions in the database is compared, and the search is performed. The most matching flooding map.

In the flooding map search, the embodiment of the present invention analyzes the difference between the instantaneous observation water level of each station in the geographical area and the simulated water level of each two-dimensional flooding potential map in the database, and the comparison and comparison principle are compared. Observe the difference degree and change trend between the water level and the simulated water level at different time points to find the optimal flooding potential map. From the observed water level and the simulated water level shown in Figure 6, the degree of difference and the trend of the observed water level and the simulated water level can be visually understood.

An embodiment of the present invention provides a method for searching for a flooded map in a two-dimensional flooding potential map database. Please refer to FIG. 7 , which shows a two-dimensional flooding potential map database in an embodiment of the present invention. A schematic diagram of a process for searching for flooded funds, the method comprising the following steps. It should be noted that, in the above step S14, searching for the optimal flooding potential map from the database may correspond to all steps of the method.

Step S71: Collecting the instantaneous observation water level of different stations (the number of stations is N _gage ) in the water collection area (or geographical area). In this step, and review the validity of the data, remove the invalid data.

Step S72: setting the data matching time T _b,i (i=1 to N _Tb , N _Tb is the number of matching data times).

Step S73: the station calculated for each time point - to present time t (t ^* T _b) ^* observed differences in level and flooding indicator scale potential library of simulated situations all flooding water level (Index of difference in scale ), as follows:

If [ θ _i -max( θ _{l ,min} )]=0, I =0; othrewise I =1

θ _max =max{ θ ₁ , θ ₂ , θ ₃ } where DS _i represents the scale difference index, H _obs,t and H _sim,t are the observed water level and the simulated water level, respectively, t ^* and T _b are the current time Point and forward matching data length, _{Hobs, P} and H _{sim, P} are the maximum observed and simulated water levels.

Step S74: Calculate the average value of the scale difference index of all the stations.

Step S75: Sort the average value of the scale difference index from small to large, and select the former n _best group flooding situation.

Step S76: calculated for each time point from the station - to the present time t ^* n _best observed water level and group level simulation time trend flood situations the difference index (Index of difference in time) ( t * T b), the following formula:

If [ θ _l -max( θ _l )]=0, I =0; othrewise I =1

θ _max =max{ θ ₄ , θ ₅ , θ ₆ } where DT _i represents the time trend difference indicator.

Step S77: Calculate the average value of the time trend difference index of all the stations.

Step S78: selecting the smallest average value of the time trend difference index in the n _best group flooding situation, that is, the data matching time T _{b, i} represents the flooding potential map F _{map(Tb, i)} .

Step S79: Calculate the water level of all stations at the current time point t ^* Simulated water level at the same time point as the representative flooding potential map F _map(Tb,i) Average error value , as follows: N _gage is the number of stations in the catchment area.

Step S80: Stepwise set the data matching time T _b,i+1 , and repeat steps S73-S79 to calculate the average error value of each representative flooding potential map F _map(Tb,i+1) . Select the matching time T _{b of} each data _, and the representative flooding potential map with the smallest average error value is the optimal flooding potential map.

Please refer to FIG. 8 , which shows a flow chart of searching for a flooded map in a two-dimensional flooding potential map database according to another embodiment of the present invention. The difference between the embodiment of FIG. 8 and the embodiment of FIG. 7 is that the embodiment of FIG. 8 further includes:

Step S81: Correcting the optimal flooding potential map by using the observed water level of all the stations. In this step, the observed water level observed in the geographical area or the catchment area can be used to correct the optimal flooding potential map obtained according to steps S71-S80, and further accurate flooding of the geographical area can be obtained. Happening.

In the embodiment of the present invention, in the aspect of flooding map searching, the principle of comparing the degree of difference between the water level and the simulated water level at different time points and the trend of change are used, and the observation water level and flooding map of each station in the geographical area are used. Make the best feature strip Match the pieces to find the best flooding potential map, which can improve the search accuracy of the flooding potential map.

The present invention has been disclosed in the above preferred embodiments, and is not intended to limit the scope of the invention, and the invention may be modified and modified without departing from the spirit and scope of the invention. Therefore, the scope of the invention is defined by the scope of the appended claims.

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Claims (7)

An optimization method for a two-dimensional flooding potential map database includes the following steps: a. simulating a group map of a rain event from a historical rainfall event in a geographic area; b. using the group map of the rainfall event to perform the Flooding simulation of geographical areas to generate two-dimensional flooding potential maps and store them in the database; c. According to the instantaneous observation water level of each station in the geographical area, the most searched from the database a flooding potential map; and d. adding new rainfall events to historical rainfall events in the geographic area and repeating steps a through c. For example, in the method for optimizing the two-dimensional flooding potential map database described in claim 1, the step a includes: collecting rainfall events from historical rainfall events in the geographical area, each rainfall event including a rainfall delay, Rainfall and rain type parameters, the rainfall event is defined as rainfall during a continuous rainfall, the rainfall delay of the rainfall event is defined as the duration of the rainfall event, and the rain pattern of the rainfall event is defined as the distribution of rainfall rainfall over time or Simulating a function; performing statistical analysis on each rainfall event in the historical rainfall event of the geographical area, and obtaining a statistical analysis result of the rainfall event of the geographical area; and simulating the generation according to the statistical analysis result of the rainfall event of the geographical area A body map of a rainfall event, the body map of the rainfall event containing one or more rainfall events. The optimization method of the two-dimensional flooding potential map database described in claim 2, wherein the step of simulating the group map for generating the rain event according to the statistical analysis result of the rainfall event in the geographical area comprises: Based on the statistical analysis of the rainfall events in the geographical area, the rain pattern, rainfall delay, rainfall and rainfall event interval are simulated to generate a group map of the rainfall event. The method for generating a two-dimensional flooding potential map according to claim 2, wherein the step of simulating the group map for generating the rain event is based on a statistical analysis result of the rain event according to the geographical region The Monte Carlo simulation method produces a group map of the rainfall event. The method for optimizing a two-dimensional flooding potential map database according to claim 1, wherein the step b comprises: using the group map of the rainfall event to simulate rainfall at different locations or different ranges of the geographic region, Generate multiple sets of different rainfall situation simulation data; and use the different sets of different rainfall situation simulation data to match the hydrological and geologic data of the geographical area, simulate the flooded area, and generate multiple two-dimensional flooding potential maps respectively. And store it in the two-dimensional flooding potential map database. For example, in the method for optimizing the two-dimensional flooding potential map database described in claim 1, wherein the step c includes: c1. collecting the instantaneous observation water level of each station in the geographical area; c2. The observation water level of each station in the geographical area from a set time point before the current time point to the current time point and the two-dimensional flooding potential Index of difference in scale of the simulated water level of all flooded maps in the map database; c3. Using the processor to calculate the average value of the scale difference index of all stations in the geographic area, from small to large Sorting, selecting a flooding map corresponding to a predetermined number of groups in front; c4. using the processor to calculate an observation water level of each station in the geographical area from the set time point to the current time point and selecting in step c3 The index of difference in time of the simulated water level of the predetermined number of flooding maps; c5. using the processor to calculate an average value of time trend difference indicators of all stations in the geographic area, and selecting the time trend The flooding map corresponding to the smallest average of the difference indicators is used as the representative flooding potential map of the set time point; c6. Using the processor to calculate the observed water level of all the stations in the geographical area at the current time point The representative error value of the simulated water level at the same time point of the flooding potential map; and c7. gradually increasing from the set time point to the new set time point and repeating Steps c2 to c6, using the processor to calculate the average error value of the representative flooding potential map at each set time point, and selecting the representative flooding potential map corresponding to the smallest one as the optimal flooding potential map . For example, the optimization method of the two-dimensional flooding potential map database described in claim 6 of the patent scope further includes the steps of: C8. Correct the optimal flooding potential map by using the observed water level observed by all stations in the geographical area.