KR20120000716A - Flood prevention system based on gis and method of the same - Google Patents

Abstract

PURPOSE: A flood protection system based on a geographic information system is provided to suggest flood defense measures using the vulnerability index of a local feature. CONSTITUTION: A flood defense system acquires a vulnerability index according to a lattice area. The flood defense system determines a usage level using the acquired vulnerability index. The flood defense system exhibits effective countermeasures. The flood defense system establishes the optimized method according to the effective countermeasures.

Description

Flood prevention system based on GIS and method of the same

The present invention relates to a system for presenting basic data for establishing a selective flood defense strategy by combining an abnormal flood vulnerability index and flood risk.

Unpredictable phenomena are appearing around the world so that the word climate change and abnormal climate are not awkward. For example, the heavy rains in South Asia, the heat waves in the eastern United States, storms and floods, together with the August heavy rains in Korea last year. These phenomena differ significantly from those in the 20th century, and in particular, they have not been observed in the past and generally do not occur according to a certain period or pattern, which is a major cause of great damage due to the lack of predictions and appropriate countermeasures. have. Accordingly, in order to analyze abnormal climates, that is, extreme events, in the existing studies based on annual data or average concepts, studies on long-term occurrence frequency and duration using daily data including definitions of extreme events are increasingly required.

Despite flood defense efforts over the last few decades, the magnitude of flood damage has not increased. The main reason for this may be the cause of the concentration of the damage factors caused by rapid urbanization and industrialization, and extreme weather such as torrential rain and sudden floods. The flood response efforts have been approached mainly from the structural point of view, but there are some limitations of structural measures along the riverside depending on the progress of urbanization, and there are limitations on establishing the perfect structural measures due to a large budget.

These structural measures are approached mainly from the concept of good along the river. However, recent flood damage patterns are not caused by primary problems such as simple levee flooding, and the magnitude of damages in flood occurrences also varies according to regional characteristics. Since there are limitations in structural measures that consider these complex causes and various damage factors, appropriate flood response measures are needed according to regional or regional importance.

It is necessary to design in accordance with the concept of disaster prevention where no damage occurs in critical facilities or in critical areas, and in some areas, the cost of reconstruction of the facilities is much higher than the damage, so other alternatives may be needed. When establishing countermeasures against flood defenses, it is necessary to find out which areas are vulnerable to flooding and to invest first and establish countermeasures, but there is a lack of research on the basis for objectively evaluating them.

Korea's disaster prevention policy is mainly focused on recovery and response, and does not put much budget on prevention and preparation. Rather than checking for administrative preventive measures, it is necessary to prepare for preventive actions against actual and useful disasters.

In the water long-term comprehensive plan, flood damage can be compared in order to establish the safety of flood control, and it is an index that can evaluate the dimension characteristics and socio-economic value of the unit area including not only hydrological elements but also socio-economic factors. Potential Flood Damage (PFD) was presented. The PFD is currently applied to various projects as a judgment index for understanding the dimensional characteristics of each unit area, calculating the dimensional investment priority among the unit areas, or establishing a comprehensive size plan for large scale units. However, the PFD quantitatively displays the potential and vulnerability of medium and small watersheds in managing watersheds, and does not provide a countermeasure or a practical flood response plan. It is true.

In terms of disaster management, disaster management is generally carried out in four stages: prevention, preparedness, response and recovery. In this context, prevention means structural measures such as dams and rivers, and countermeasures such as flooding, and contrast means establishing a countermeasure based on risk assessment, that is, risks through flood modeling or statistical methods. In general, the process of minimizing human injury through rapid evacuation or status reporting, and restoration means various activities to prepare for the next flood event or the next year's flood. The flood forecasting technique we speak of is a necessary technique for preparation, but as the paradigm shifts around the world recently, vulnerability assessment is emphasized along with risk assessment at the stage of preparation.

Flood hazards associated with flooding during natural disasters (hazards), the exposure to economic assets or lives in flood-hazardous areas, and vulnerability (lack of flood protection). The risk of flooding can be expressed by multiplying the three factors

Flood risk analysis refers to how much damage has occurred in the past and how often it has been exposed to flooding. Vulnerabilities, on the other hand, can be said to analyze the potential for potential disaster damage. In other words, the vulnerability assessment is a process necessary to prevent and respond to the weaknesses and strengths of current and future disasters based on past damages.

Therefore, there is a need for a method of establishing a flood response plan according to regional characteristics by quantitatively evaluating the strength and weakness of disasters in the region in terms of prevention and preparedness in such disaster management.

On the other hand, in the water resources sector, decision makers should develop and develop measures for the stable measures of the two dimensions, minimize the environmental damage or ecological change by development, seek the compromise of beneficiaries and victims by development, and cross-regional and group efficiency for distribution of development benefits. A plan must be developed that simultaneously meets the multi-valuation criteria, such as determining the optimal point between and equity.

In particular, in supporting the decision-making of flood response measures, various aspects such as the flood reduction effect of the flood countermeasures, the project cost, the environmental impacts thereof and the optimal location conditions for establishing the countermeasures should be considered. Therefore, it is also required to provide systematic information to support the complex decision making process as described above.

An object of the present invention is to solve the problems described above, considering that the existing flood safety potential (PFD), which is a conventional method for evaluating dimensional safety, only shows the potential risk between the watersheds, there is a limitation in the measures or applicability Therefore, it is to provide an evaluation system that can consider meteorological, social, economic, environmental, topographical and hydrological vulnerabilities by using the attribution information of the watershed unit and the attribution information of the administrative district unit.

Another object of the present invention is to provide a spatial information to the user by building in a GIS-based system, and to be able to determine the weight of the vulnerability evaluation index according to the user's purpose.

Another object of the present invention is to establish a function similar to the existing Flood Damage Potential (PFD) by presenting a vulnerability index, but the vulnerability of the area in the granular unit of the stream smaller than the watershed by the attribution data used to calculate the vulnerability index It is to provide a system that can check whether or not.

Another object of the present invention is not to select an index that will improve the Flood Damage Potential (PFD), especially in constructing the Flood Flood Vulnerability Assessment System (EFVS) using the Flood Flood Vulnerability Index (EFVI). The objective was to provide a range of information that could be the basis for the proper direction of flood defense and the basis for establishing a practical flood response strategy.

In order to achieve the above objectives, we first developed a vulnerability index for abnormal floods in the region as a quantitative technique for evaluating abnormal floods and built a GIS-based vulnerability assessment system using them. To this end, we conducted a study on the selection of vulnerability indicators to calculate the vulnerability index and the calculation method of the index, and at the same time, the methodology for quantitatively evaluating the selected indicators and the topographical and humanities that can reflect the characteristics of the region. In addition, economic data and facility data were converted into D / B. In addition, the constructed data was constructed in the form of spatial analysis so that it can be used as space-time data so that it can be used to analyze the damage status and type of damage, analysis of precipitation and meteorological extreme phenomena, and analysis of potential risk of the region. Through computerization of the technique, it can be used as the basic information for strengthening the design criteria of facilities for the preparation of abnormal weather and establishing flood defense measures.

The system and method according to an embodiment of the present invention, the step of superimposing the vulnerability index for each area separated by a grid; Ranking using the nested vulnerability indicators; Presenting a countermeasure for each grade; And setting an optimal alternative according to whether the condition of convergence of the survival method is met.

In addition, the system and method according to another embodiment of the present invention comprises the steps of superimposing the area mana vulnerability index divided by a grid; Ranking using the nested vulnerability indicators; Querying major facilities of a region where the vulnerability index is high; And presenting the current status of each facility by overlapping past or future flood information.

As described above, according to the present invention, it is possible to obtain an alternative flood defense that quantitatively reflects local characteristics using the vulnerability index.

1 is a diagram showing the flood vulnerability index of Japan
2 illustrates an approach for flood vulnerability assessment
3 is a diagram illustrating the classification of the flood vulnerability index according to the present invention.
4 is a diagram illustrating the selection and weight of abnormal flood vulnerability index
5 is a diagram illustrating an overlapping method of an abnormal flood vulnerability index.
6 is a schematic diagram of the superposition of abnormal flood vulnerability index
7 is a schematic diagram of the calculation of abnormal flood vulnerability index
8 is a diagram illustrating a result graph for each vulnerability element.
9 is a flow-flow simulation flow chart
10 is a schematic diagram of the flooding flood
FIG. 11 shows the tendency of maximum rainfall for five days in duration.
12 is a view showing the limit analysis result screen
Fig. 13 is a diagram showing the limit analysis result screen.
14 is a schematic diagram of the process of evaluating disaster risk impacts due to climate change
15 is a diagram illustrating an initial screen for inquiry according to an embodiment of the present invention.
16 is a view illustrating a weather observation point inquiry screen according to an embodiment of the present invention.
17 is a diagram illustrating a vulnerability analysis result according to an embodiment of the present invention.
18 is a diagram illustrating a weighted screen according to an embodiment of the present invention.
19 is a diagram illustrating a vulnerability analysis result chart and a screen for providing a countermeasure for each grade according to an embodiment of the present invention.
20 is a diagram schematically illustrating a structure for setting a selective flood alternative.
21 is a diagram illustrating a result derivation screen for each vulnerability element according to an embodiment of the present invention.
FIG. 22 is a view illustrating an evaluation screen for importance of important facilities according to an embodiment of the present invention. FIG.
FIG. 23 is a view illustrating a submerged trace diagram display screen for selective flood defense according to an embodiment of the present invention. FIG.
24 is a diagram illustrating a risk analysis result screen according to main facilities according to an embodiment of the present invention.
FIG. 25 is a diagram illustrating a dangerous facility status information inquiry screen according to a risk analysis result according to an embodiment of the present invention. FIG.
26 is a diagram comparing the results of EFVS step 1 and PFD
27 shows a comparison of EFVS and PFD.
28 is a diagram illustrating an alternative and scenario inquiry screen according to a decision according to an embodiment of the present invention.
29 is a diagram illustrating a screen for alternative flood defense presentation according to an embodiment of the present invention.
30 is a view showing an overseas response example inquiry screen according to an embodiment of the present invention.

The above and other objects and novel features of the present invention will become more apparent from the description and the accompanying drawings.

First, the concept of the present invention will be described.

In order to identify the safety of floods in an area, it is necessary to first define safety. Since the concept of safety is different for each user, it is difficult to define clearly, but it can be defined in four ways as follows. First, safety refers to the so-called 'fundamental safety' method that prevents any risk of any condition that can cause human and material damage by freedom from hazard. Second, safety refers to the installation of protective facilities and protective devices by `` protecting people and property from dangerous exposure ''. Third, safety means "prevention of accidents," which means prevention using education and public relations. Fourth, safety is "acception if risk," which is a scientific and objective way of reducing the probability and intensity of disasters to an acceptable level through risk assessment. to be. This means that quantified modern safety management is needed.

Flood hazards associated with flooding during natural disasters (hazards), the exposure to economic assets or lives in flood-hazardous areas, and vulnerability (lack of flood protection). The risk of flooding can be expressed by multiplying the three factors, and in particular, the combination of exposure and vulnerability resulting from the flood event is expressed in C as follows.

R = P X C

R = Risk

P = Hazard

CExposure X Vulnerability

As discussed earlier, flood risk analysis refers to how much damage has occurred in the past and how often it has been exposed. In order to assess local safety, the D & E Reference Center (1998) said, “To determine local hazard risks and vulnerability to estimate risk hazards and probability of occurrence in a region”. Benouar and Mimi (2001) also defined vulnerability as the weakness and strength of each factor of disaster hazard. In other words, vulnerabilities can be analyzed by analyzing the potential for potential disaster damage. In 2002, the UN report defined vulnerability as a condition or condition that results from physical, social, economic, and environmental factors about the effects of a continual increase in flooding in some regions and societies.

To present specific indicators of vulnerability, Pearce (1993) defines vulnerabilities as indicators for managing risk, including topographic-physical elements and various elements on the map, with topographic, geographic, traffic and social infrastructure, and important buildings. He also had to consider bridges, bridges, and humanities. In addition, there are various definitions of vulnerability, but their content is consistent with the extent to which we can roughly determine the magnitude of the damage that can occur when exposed to floods of the same intensity. For this reason, a variety of approaches and studies are underway around the world of potential, potentially vulnerable, factors. For example, the recent flooding phenomenon caused by frequent abnormal weather has been studied in terms of meteorological vulnerability, and the population growth due to rapid urbanization is being studied in terms of sociological vulnerability.

Risk assessments and vulnerability assessments are factors to be considered at the same time in assessing safety in a given area. The question of how often and how large was the damage? Was past-oriented, but what factors would most likely cause damage and aggravated the damage? In other words, the vulnerability assessment is a process necessary to prevent and respond to the weaknesses and strengths of current and future disasters based on past damages.

Japan is located in a climatic zone similar to ours, and has a similar life culture and urban formation process. In addition, many researches related to disasters have been conducted since they are exposed to various types of disasters such as typhoons, earthquakes, and tsunamis. There is a Flood Vulnerability Index (FVI) developed by the National Institute for Land and Infrastructure Management (NILIM) related to abnormal flood vulnerabilities. 1 is a flood vulnerability index of Japan, and the formula is as follows.

Flood Vulnerability Index (FVI) = C (Climatic Factor) + H (Hydrogeological Factor) + S (Socioeconomic Factor) -M (Response Factor)

In the present invention, the approach for the abnormal flood vulnerability evaluation was examined as an example of FIG.

One is the bottom-up approach, which is a vulnerability approach to the living space in which we live. This is a method of deriving meteorological vulnerabilities through extreme event analysis and evaluating the topographic, social, environmental and economic vulnerabilities based on them, and at the same time, evaluating the vulnerabilities reflecting the magnitude and probability of damage caused by past floods. The other is a top-down approach, which is an approach in terms of abnormal climate associated with abnormal floods. If the bottom-up approach is selected as the main target in our space, the top-down approach selects climate change scenarios, evaluates the effects of the downpours based on the simulation results, and then evaluates the volatility of the downpours in the target watershed. It is to evaluate the abnormal flood vulnerability.

Meanwhile, in the present invention, the flood vulnerability is classified into meteorological vulnerability, hydrologic-geometric vulnerability, socio-economic vulnerability, and flood defense vulnerability based on the above classification of the vulnerability. (See FIG. 3). Vulnerabilities are similar to those of the existing PFD, since the basic theory of flood vulnerability estimation of the present invention is presented based on Risk = Hazard x Vulnerability. The risk factors were considered by watershed slope, runoff coefficient, and the like, using past flooding traces, flooding history, and damage.

Looking at the equation according to the invention according to the above classification as follows.

Abnormal Flood Vulnerability Index (EFVI) = C (Climate component) + Hydro-Geological component (G) + Socio-Economic component (S)-Protection component (P)

The abnormal flood vulnerability estimation formula, which uses various indicators, may have different results depending on the weight of the indicator. This means that there is a risk that the overall analysis results may differ depending on the weighting method and the scoring of the indicators. In order to improve these problems, this study conducted a study by selecting representative indicators that could increase the damage in case of abnormal floods, rather than using too many indicators after consulting several practical experts. At this time, the weight was determined through AHP analysis (Saaty, 1980) in one embodiment of the present invention, in which priority was given by ideal distribution.

The analysis system using the abnormal flood vulnerability index requires the process of establishing and calculating a large number of databases, but this affects the speed of system operation and may not provide an appropriate value at the appropriate time in response to the abnormal flood. Therefore, in the present invention, the DB utilizes the data already established by using the data of the National Emergency Management Agency and the National Water Resources Management System (WAMIS), evaluates each data according to the above-described evaluation method, and maps the evaluation results in a layered map. The method was used to evaluate the overlapped layers of the analysis result of each vulnerability index. (See FIGS. 5 and 6).

Meanwhile, a method of calculating the final vulnerability index using the abnormal flood vulnerability index is shown in FIG. 7. In FIG. 7, the leftmost layer represents the attribute values of the vulnerability table for each watershed, and these values are normalized by dividing each subwatershed value by the maximum value of the vulnerability index layer. The value thus determined refers to the second figure, and the number of boxes shown in the second figure refers to the weights shown by the AHP analysis. This weight is multiplied by the standardized attribute values, and these values are superimposed to calculate the final vulnerability value. The computed vulnerability value is then divided by the watershed maximum of the final nested layer, resulting in a value between 0-1. This value is divided into intervals of 0-0.1, 0.1-0.2, 0.2-0.3, ..., and re-flooded to 1-10, which is the final anomaly vulnerability analysis value.

The abnormal Flood Vulnerability Index (EFVI) calculated through this process is calculated by using all the layer property values of each indicator. Therefore, each of the four factors of meteorological vulnerability, hydrologic-geometric vulnerability, socio-economic vulnerability, and flood defense vulnerability Estimates can also be obtained. The estimated value for each element has a value ranging from 0-1 through standardization process (see FIG. 8), and proposes a countermeasure for abnormal floods based on this value.

Table 1 shows the direction of this flood defense strategy. Reclassify watersheds in grades 1-10 into groups A, B, C, D, E, and F, depending on conditions, to ensure appropriate flood protection for the group. Proposed measures.

Equation of the present invention, even if the value of the abnormal flood vulnerability index is the same grade as shown in Table 1,

Structural and non-structural, depending on the distribution of vulnerability component values in “EFVI (Emergency Flood Vulnerability Index) = C (Climate component) + H (Hydro-Geological component) + S (Socio-Economic component) -P (Protection component)” The strength of the measures was configured to be different.

group Measures Rating A It is necessary to strengthen flood defense facilities and establish structural measures first. 10 Grade 10 overall 9 Flood Defense Vulnerability> 0.75 &
Hydrogeological Vulnerability> 0.75 B Reinforcement of flood defenses is needed, but structural measures are considered in consideration of local conditions compared to Group A 9 All 9 grades except Group A 8 Flood Defense Vulnerability> 0.75 or
Socioeconomic vulnerability> 0.75 or
Hydrogeological Vulnerability> 0.75 7 Flood Defense Vulnerability> 0.75 or
Hydrogeological Vulnerability> 0.75 or
Socioeconomic Vulnerability> 0.75 C It is necessary to strengthen flood defense facilities and establish structural and unstructured measures simultaneously. 8 All 8 grades except Group B 7 All 7 levels except Group B 6 6th grade 5 Flood Defense Vulnerability> 0.6 &
Socioeconomic Vulnerability> 0.6 4 Flood Defense Vulnerability> 0.6 &
Socioeconomic Vulnerability> 0.5 D Flood defense facilities are required but focus on unstructured measures 5 All 5 grades except C group 4 All 4 grades except C group 3 Hydrogeological Vulnerability> 0.5 or
Socioeconomic Vulnerability> 0.5 E Flood defense facility is sufficient, and there is unstructured countermeasure 3 All 3 levels except D group 2 Grade 2 overall F Watershed Management based on Nature-Friendly Urban Planning One Grade 1 overall

Meanwhile, the flood flood model was simulated and used as basic data for preparing disaster prevention measures and disaster information maps in areas where flooding is expected.

Flood Flood Map is a map that predicts the area where flooding is expected through previous flood traces and simulated flood flooding. It is used as basic data for preparing disaster prevention measures and disaster information maps. Therefore, in the present invention, in order to improve flood protection against abnormal floods caused by abnormal weather, scenarios such as rainfall events, bank collapses, and overflows exceeding the planned scale of rivers are generated, and mathematical and hydrological simulations and analysis are performed. Through this study, basic data used in the analysis of vulnerability and vulnerability analysis are presented.

In generating the frequency scale scenario, the frequency scale is the basic data structure for the flood analysis, and the frequency setting is a value representing the size of various flood events and data of the starting point and the end point of the target area. It can be seen to apply for the purpose. In the present invention, it is determined that the excess of the design frequency of the target watershed is an abnormal flood, and the overflow simulation and scenarios are prepared by applying the design frequency abnormality of a specific watershed.

The scenarios of breakwaters and overflows represent the situation where the mainstream flooding in the underland floods into the mines, and the flooding simulation by overflows creates flood flood maps at the point where natural overflows are applied by applying the event exceeding the planned frequency. In cities, flood simulations are conducted on the assumption that the banks will temporarily collapse to re-elevation.

It is very important to predict the collapse point due to breakage and overflow, but it is not practical to accurately predict the breakdown point. However, it is possible to select flood flood zones by analyzing the fragile parts of the hand structure, the geological form of the structure and the bottom of the levee, the form of the channel and the field survey.

In order to calculate the probability rainfall, the more data is available, the more stable the result is. In order to secure the reliability of the probability statistics processing, at least 20 ~ 30 years of data are required. The basic data is the probability rainfall information according to the time calculated from the quality observation station of the Meteorological Administration or the Ministry of Bridge.

Rainfall-runoff analysis is a method of tracking floods with a runoff model representing the physical characteristics of the watershed, using the probability rainfall set by frequency analysis of rainfall. In order to estimate the design flood volume of the target watershed, the flood tracking through the sewer and the flood hydrograph at the design reference point are applied by applying optimized parameters such as subwatershed segmentation, arrival time, and storage constant to reflect the spatial distribution of rainfall. The amount of flooding should be estimated through the synthesis of. Looking at the sequence of such a series of processes is generally as shown in FIG.

Based on the above process, effective rainfall, parameters, and floods are estimated. And through this, flood flood simulation of the watershed is carried out using HEC-RAS.

On the other hand, the Flood Inundation Map is one of the unstructured measures to protect the natural disasters caused by the flood and is a map displaying the information related to the flood. Flood flood maps are flood disaster maps that show the extent and magnitude of flooding in areas affected by past floods, and the extent, depth of flooding, flood duration, and flooding in the future. It can be divided into flood hazard map or flood risk map simulated by engineering analysis such as area. A flood flood map obtained through the work of the flood flood cap is as shown in FIG. 10, for example.

On the other hand, extreme climatic characteristics and definitions vary from region to region or country to country, which means that even if rainfall of the same size occurs, psychological and external factors, such as the ability to cope with past experiences and damages, or building social infrastructure in regions or watersheds This is because the risks and vulnerabilities you feel are relatively different.

Rainfall, for example, can be explained to the extreme of the storm event itself that emerged outside the previous period of rainfall. The fact that it rained after the rainy season, as well as the quantitative fact that it rained a lot compared to other years, means that extreme weather events can be interpreted in terms of period.

Therefore, this study presents definitions and methodologies for more objective and quantitative analysis of extreme climate change using rainfall, average temperature, high and low temperature observed in the past and presents the results. First, we analyze the results of an index analysis that can determine the extreme conditions of rainfall and temperature over a long period of time using daily rainfall, daily maximum, minimum, and average temperature data from 66 stations located in Korea. Based on the results, seasonal and spatial distribution patterns were identified.

Extreme weather events, caused by unusual climates, are unpredictable and unusual events that have not been observed in the past 30 years. It is characterized by not showing cycles or patterns such as the appearance and repeatability of a certain period of time. In addition, since it is not a phenomenon that has persisted since the past, it is difficult to infer a general conclusion. Therefore, in the present invention, it was determined that a statistical method should be applied to the trend analysis through indexing. In particular, how often again the extreme weather in the European Union, and what occurs in any size STARDEX (Sta tistical and R egional dynamical D ownscaling of Ex tremes for European regions) conducted over a period of about four years since 2002 to analyze the trends project Unlike other studies, the present invention judges that there is no great difficulty in applying the grading degree or trend grading by presenting an index for rainfall and temperature based on a relatively near-normal idea rather than a very extreme state such as 99th. Applied to.

Rainfall-related extreme index Torrential rain threshold Volume of 90% of rainfall occurrence days (mm / day)
90th percentile of rainy day amounts (mm / day) 5 days maximum rainfall Maximum rainfall for 5 days (mm)
Greatest 5-day total rainfall (㎜) max rainfall of 5-day duration Rainfall intensity on wet days Single rainfall intensity (rainfall on rainfall day)
Simple daily intensity (rainfall intensity of a rainy day) Drying duration Maximum number of days in consecutive rain
Maximum number of consecutive dry days Rainfall ratio above the heavy rainfall threshold Percentage of total rainfall over time> 90%
% of total rainfall from events> long-term 90th percentile Occurrences above the threshold of heavy rainfall Many events> 90% of long-term rainfall days
Number of events> long-term 90th percentile of raindays Temperature-related extreme indices Hot-day threshold Maximum temperature 90% (℃)-10% of the hottest day of the season
Tmax 90th percentile (℃) -the 10th hottest day per season Cold-night threshold Minimum temperature 10% (℃)-10% of the coldest night of the season
Tmin 10th percentile (℃) -the 10th coldest night per season Freezing days Freezing Day Minimum Temperature <0 ℃
Number of frost days Tmin <0 ℃ Maximum heat period Cold periods with values above a certain reference temperature
Heat wave duration (days)

The indexes presented in Table 2 are arranged in ascending or descending order of daily data (365 or 366 days) of the target area to be analyzed in order to calculate the value for a specific percentage. According to the condition suggested by each index, the value up to the tenth column is taken. They can compare and evaluate the relative values of physical factors such as terrain, land-use status, and area of the area being analyzed and the characteristics of social infrastructure.

In order to analyze the characteristics of Korea's weather events from the past until the extreme events began to be observed, the daily data of each station was used based on the above-mentioned indexes. There are 66 weather stations under the jurisdiction of Korea.

In order to calculate the index values of the 66 stations located in Korea, and to grasp the spatio-temporal distribution patterns, it is necessary to compare seasonally and to consider the spatial change of each index throughout Korea and to evaluate the trends relatively. Analyzed. At this time, depending on the tendency increase and decrease of the analyzed index values, they may be represented by “+” and “-” symbols, respectively (see FIG. 11). For example, when the index analysis result has a positive value, the tendency is increased. The symbol "+" is used to indicate that the symbol is larger, and the larger the symbol is, the more prominent it is compared to other observation points. However, the size of the symbol was calculated separately according to the seasonal characteristics according to each index, and the seasons were winter (December to February), spring (March to May), summer (June to August), and autumn (9). Month to November).

And the results are shown in tables and graphs as shown in Figs.

Increases in precipitation and strength due to climate change have a profound effect on hand structures such as dams, and if the dam collapses, it can cause enormous damage to the downstream waters of the dam. Preciptiation is considered. The maximum possible amount of precipitation is determined by the moisture content in the atmosphere and the dew point temperature, which typically increases by about 10% with a 1 ° C rise in temperature. If we assume that the temperature rises by 1 ° C ~ 2 ° C due to climate change, it would be possible to increase the maximum possible precipitation by more than 10%. As climate change changes the extreme hydrologic phenomena, the most important variable in the design of handicrafts, it is now becoming a reality for hydrotechnical engineers who plan and design handicraft infrastructure.

The most widely used tool for assessing the impact of climate change on the water cycle is the use of SCC-based GCM and RCM data, which is an IPCC recommended scenario, and is gradually applied to existing GCM data to extract local and detailed climate change information. In addition to applying the reduction technique, recent researches using RCM data with high resolution have been conducted. However, although RCM data are partially used in Korea, the applicability of the RCM data has not been tested enough, so it is limited to GCM data analysis.

In order to evaluate how future climate change affects extreme rainfall, the daily precipitation time series data per grid were simulated from the high-resolution (27km × 27km) Meteorological Agency RegCM3 RCM data using IPCC SRES A2 warming gas scenario. In addition, the probability rainfall amount was estimated for 24 hours of duration (fixed time) after reducing the temporal and temporal scale by the extreme rainfall data for each station point using shift correction and abnormality reduction techniques. In order to analyze the effect of climate change on the 24-hour probability rainfall in Korea (fixed period), we surveyed 66 stations in Korea.

In order to evaluate the effect of climate change on the probability rainfall, the present invention estimates the parameters by using the PWM, which is widely applied in Korea, test, Kolmogorov-Smirnov (KS) test, Cramer Von Using the Mises (CVM) test and the Probability Plot Correlation Coefficient (PPCC) test, the Gumbel distribution was found to be appropriate. When calculating the probability rainfall, the reproducing period is 2, 5, 10, 20, 30, 50, 70, 80, 100, 200, 300, 500 years using the rainfall analysis program FARD 2006. For each frequency, the probability rainfall was calculated.

Although many studies are underway to evaluate the impact of climate change on disaster risk, in the present invention, in the sense that climate change provides a local value rather than a local detailed value, in the present invention, the variability and Was attempted to assess the impact on disasters by using local disaster vulnerabilities. To evaluate this, the whole country was evaluated in 232 city and county districts. In order to consider the impact of disasters, we used population density and Gross Domestic Product as vulnerabilities. Extreme Volatility Index (EVI), Human Risk Index; HRI) and Disaster Impact Index (DII) were developed and evaluated, and this evaluation flow is shown in FIG. 14.

In the present invention, the Extreme Volatility Index (EVI) is based on the future climate change and the current rainfall variation using the difference between the probability rainfall amount by the reproduction time and the probability rainfall by the reproduction time using the current data. Developed. The calculation method of EVI can be expressed as follows.

EVI = RL (T) -RL (t)

where, RL (); Return level

RL (T); Actual value

RL (t); Design value

Using this data, the future rainfall was simulated by grid, and the data were constructed at 50, 100, 200, 300, and 500 years in terms of administrative districts, and the results were compared with the same current rainfall frequency. When calculated, the example was as Table 3.

The extreme rainfall fluctuation index may be used as a basis for strengthening the facility standard for future abnormal climate if approached from the concept of design frequency.

In the present invention, the human risk index (HRI) was evaluated in consideration of the calculated EVI and population density by selecting the fragility index roll as a part of urbanization. The reason for using population density is that the simulated results considering climate change are generally used as social and human vulnerabilities that are appropriate for 232 municipal scales because the results are spatially distributed rather than regionally clear.

HRI = EVI X Population

In general, the higher the financial independence, the higher the level of disaster safety in the region, which can be attributed to the local government's ability to invest in infrastructure and vulnerable facilities. If the results of the above-mentioned HRI approached weak areas of social vulnerability, considering the local government's financial index, it can be said to represent economic strength against disasters. In the present invention, the Disaster Impact Index (DII) is presented using the Gross Regional Domestic Product (GRDP).

DII = HRI / GRDP

EMBODIMENT OF THE INVENTION Hereinafter, the structure of this invention is demonstrated according to drawing.

The present invention provides a GIS-based flood defense analysis system as a system for presenting basic data for establishing a selective flood defense strategy by combining the above-mentioned flood vulnerability index and flood risk. The system was constructed based on GIS to express the results of meteorological, hydrogeological, socioeconomic and flood defense vulnerability analysis. Each layer on the GIS is constructed with vulnerability indicators, one layer represents the vulnerability indicators, and items corresponding to the vulnerable factors, such as meteorological, hydrogeological, socioeconomic and flood defense vulnerabilities, overlap each other. Express the results of the analysis.

Basically, the data used in the system of the present invention other than the various information such as the index, the indicator, the flood flooding schematic diagram generated by the novel method devised in the creative process described above separately, the Meteorological Agency, the National Emergency Management Agency and the Ministry of Education Accumulated by each organization such as GIS data, in particular, refers to data that are managed or can be added by the National Geographic Information System.

First, the flood defense method of the present invention in detail as follows.

[Watershed Status Inquiry Step]

According to an embodiment of the present invention, an initial screen as shown in FIG. 15 is provided.

The watershed status based on GIS information is retrieved based on the selection of a total of 21 watershed statuses. Here, the watershed specifications include watershed area, left eye area, right eye area, watershed circumference, watershed average width, watershed average slope, shape factor, shape factor, monolithic factor, circular ratio, elongation rate, water density, water frequency, water retention Includes constants, delicacies, ups and downs, relative ups and downs, ups and downs, and high water level elevation.

[Weather observation point inquiry step]

According to an embodiment of the present invention, the meteorological observation point is composed of a total of 76 observation points. As shown in Figure 16, if the weather observation point on the map is selected, it is possible to query the weather data. The weather data query inquires the information of rainfall, maximum temperature, average temperature and minimum temperature by period. The analysis of extreme weather events for each weather observation point described above can be executed and can be confirmed by viewing the results.

[Vulnerability Analysis Steps]

This is the step for vulnerability analysis by vulnerability indicator. Each analysis result is divided into 10 grades through GIS. And the information of each grade can be confirmed through the color legend window, for example.

According to an embodiment of the present invention, vulnerability analysis is performed with items as shown in Table 4 below.

division Vulnerability indicator Hazard Analysis ○ Watershed slope, impermeability, flood risk area (past), soil runoff (landslide) risk
Area, coastal water hazard area, flood damage scale map Social analysis ○ Population density, financial index Economic Analysis ○ Regional GDP (GRDP) Climatic Analysis ○ Frequency of extreme rainfall and daily rainfall

The calculation and analysis of the vulnerability index follow the method described above, and the result screen may be displayed as shown in FIG. 17.

On the other hand, according to the embodiment according to the present invention, the conventional method of calculating the abnormal flood vulnerability index was used to calculate the value for each subwatershed based on the largest value by applying the ideal distribution method through relative comparison. However, since the evaluation method is not discriminated depending on the characteristics of the indicator, or if the largest value is as large as an outlier, it may be affected too much. It is possible to calculate a new index using the normalization method.

In addition, depending on the analysis situation, it may be possible to classify the indicators newly by identifying which indicators have no discriminating power in the existing indicators and whose meanings overlap. For example, alternatively, the indicators commonly used in the present flood vulnerability and the future flood vulnerability according to the preferred embodiment of the present invention may include runoff coefficients, past damage scale indicators, watershed slope indicators, population density indicators, financial index indicators, and external waters. Six indicators of defensive capacity were used, and the selected indicators for setting up flood alternatives were fire stations, emergency facilities, water treatment plants, drainage pump stations, power generation facilities, and hospitals. In addition, the current flood vulnerability uses a maximum of five days of precipitation (summer) for observational data as a flood indices and meteorological vulnerability indicator. For the future flood vulnerability, the maximum of five days of rainfall simulated by climate change is used. Precipitation was to be used. In addition, the flood flood prediction map was used to use indicators using the estimated flood area ratio.

Vulnerability assessments are classified in this way because they require a bottom-up and top-down approach to respond to abnormal floods, because climate change can be considered in top-down vulnerabilities. In top-down, the results of the current rainfall patterns and future analyzes can be compared to assess potential meteorological impacts.

The newly selected indices based on the above considerations are shown in Table 5.

[Weighting Steps by Evaluation Indicator]

This is the process of setting the weight for each evaluation index used for vulnerability analysis. 18 is an example of a screen for enabling such weighting. This weight is, of course, a value that can be changed depending on the purpose and environment of the analysis. The weight of each indicator is input and reflected in the vulnerability analysis.

[Vulnerability Analysis Result Charts and Levels of Countermeasures]

After executing the vulnerability analysis, click on the subwatershed to check the results of the vulnerability analysis. The results of the analysis of meteorological, hydrologic, topographical, socio-economic and flood defense vulnerabilities can be identified in charts, and countermeasures can be identified for each class of results. Countermeasures can be presented as in Table 1 above.

On the other hand, in the water resource field, multi-criteria decision-making is commonly used for evaluating alternatives for watershed projects. Multi-Criteria Decision Making (MCDM) is a decision where multiple criteria must be considered in the decision problem of selecting the best alternative. In the present invention, in order to perform such multi-criteria decision making, the optimal alternative is set according to the condition convergence of the survival method, and the selected alternative is compared with the foreign flood response case, and the method that can provide a reference to the decision is selected. .

In order to apply this method, the basic structure of flood alternative setting as shown in FIG. In the figure, the attributes are four attributes: meteorological, hydro-geologic, socio-economic, and flood defense vulnerabilities. The alternatives are the structural and non-structural alternatives mentioned above.

[Optional Flood Defense Stage]

Flood defense alternatives are basically structured and unstructured. Structural methods typically include dams, reservoirs, installations of reservoirs, and ways to improve within the channel. Recently, dams are difficult to set as an alternative due to environmental controversy, which can be considered as substantial reservoir improvement, installation of reservoirs, and improvement of the channel. The improvement of the roadway includes the excavation of roadway, festivals, dike promotion, and the expansion of the bank width.

In the present invention, the selected structural flood countermeasures to support the decision-making, embankment test, river reclamation, reservoir installation, control station installation, dam construction, drainage pump station installation and increase were selected. In addition to the structural countermeasures, three non-structural countermeasures were selected: the 30-minute evacuation plan (EAP), flooding, and migration measures. Indeed, 30-minute evacuation plans and migration measures are the best alternatives to reduce social vulnerability, while flooding affects both hydrogeographic and flood defense vulnerabilities.

In the present invention, this alternative was combined with the vulnerability analysis results to set the optimal alternative. The results of the system are shown as indices, but the indices contain the results of vulnerability analysis for each of the four groups (see Figure 21).

In the area where the last abnormal flood vulnerability was evaluated in light blue in FIG. 21, hydrologic-geographical vulnerability was not high but relatively high flood defense vulnerability. Therefore, capacity should be concentrated on structural flood defense measures such as river maintenance and drainage pump, and conversely in red. In the evaluated areas, flood defense vulnerability is low, but hydrologic-geometric and climate vulnerabilities are high. In this region, structural measures have already reached a certain level, and as such, it is understood that measures such as flooding and response planning, situation propagation and feng shui insurance should be applied as unstructured countermeasures.

It is suggested that the approach should be approached only by the result, but it should be calculated by analyzing which of the structural measures is better.

The most important thing in setting up flood defense alternatives is what is the alternative, but it is also important in which area the best alternatives are to be established. Existing watershed comprehensive dimensions have established dimensional safety to satisfy floodwaters at the watershed's final exit point. This approach does not actually consider the importance of critical facilities within the watershed.

Above, the results of the analysis of the meteorological vulnerability considering the climate change are explained. If we consider that abnormal floods, climate change, localized sudden floods, and heavy rainfall were words that were not mentioned well in the past, these phenomena have become frequent in recent years. It can be seen that this is happening.

If the current capacity of the facility has 100, most of the floods exceeded 100 when such a phenomenon occurred. In such cases, flooding is an inevitable risk. If the left eye of the river is flooded due to the flooding of 150 or so, if the left eye is flooded, and if the right eye is locked, the damage is 10 billion, focusing 100 on the left eye rather than 50 pulp capacity on the left and right eyes. It is necessary to minimize the damage. EFVI, calculated by the Flood Flood Vulnerability Analysis System, primarily represents vulnerability in subwatershed units.

However, the results of the EFVI shows the analysis results of the standard watershed or watershed size smaller than the standard watershed, which can only be used as a simple reference level in selecting a direct flood alternative. Therefore, based on the results of the EFVI, the appropriate flood alternatives were selected at the district level smaller than the watershed. In other words, by selecting a region with high EFVI value, the past damage history and various characteristics of the region were selected, this region was selected, and the system was selected to select a lot of flooding traces in the watershed.

To this end, first of all, we applied a method to evaluate the risks in the district by using the important facility indicators among the abnormal flood vulnerability indexes. First, by dividing the earth into a certain grid (in one embodiment of the present invention using a 30m grid size) the degree of risk in the grid was evaluated using the facility.

Here, the targets of the facilities that indicate the importance are the facilities that have an environmental and economic impact such as fire treatment facilities, emergency facilities, hospitals, schools, etc. to efficiently respond to flood occurrences and reduce damages, waste treatment facilities, landfills, water treatment plants, and power generation facilities. And lastly, the pulp facility was selected as the drainage pumping station.

22 is a method of expressing the importance of the facilities in color when the important facilities are located in one of the grids divided in this way, and evaluated by the same method for each dangerous facility in the district, and the value of the important facilities in the upstream, downstream, left and right eyes of the stream. Will be able to compare where is higher.

In the case of the result of vulnerability analysis using the flooding trace, when the watershed in which the vulnerability is particularly high among the specific watersheds is selected in the system, it is zoomed in to the region as shown in FIG. 23 and the flooding trace of the region appears.

When the importance evaluation of the facility is made as shown in FIG. 23, it is possible to determine whether the facility is in the past inundation trace, and it is easy to determine where the facility is located around the river. After the analysis of the importance of facilities, the flood response plan for protecting the right eye of the river is established in FIG.

In FIG. 23, detailed specification information of rivers in the watershed can be confirmed, and the results of vulnerability analysis, flooding performance, and facility status of the watershed can be confirmed. Then, by selecting each evaluation index on the right side, you can check the vulnerability analysis result of the facility or the index. Through risk analysis, we can analyze the vulnerability according to the importance of each major facility. In addition, it is possible to analyze the status of major facilities in the analyzed area. The analysis results are shown in FIGS. 24 and 25.

Through this process, it is possible to determine which streams within the region and which of the left and right eyes of the streams should be selectively flooded.

In order to examine the adequacy of the EFVI developed in the present invention, it can be seen from FIG. 26 that a similar aspect is shown in some locations compared to the existing PFD analysis results of the Anseong stream basin. In the first-stage diagram of EFVS, we can see that the urban area's vulnerability is high due to the watershed segmentation and the high weight of the social vulnerability index. There is an advantage that you can check.

These advantages are divided into two stages of EFVI calculation and selective flood defense, and the user can input the weight of the vulnerabilities indicator for each stage. If you can judge this can be a big advantage. Comparison with PFD obtained based on these results is shown in FIG. 27.

[Decision support stage]

The abnormal flood vulnerability analysis system according to the present invention expresses the results of meteorological, hydro-geologic, socio-economic and flood defense vulnerability analysis, and presents the vulnerability analysis results for each element by overlapping items corresponding to the vulnerability. Based on the results of vulnerability analysis for each factor, we selected the appropriate flood response method according to the degree of vulnerability reduction by each flood alternative and suggested the best countermeasure, not optimal, through economic analysis on the selected alternatives.

The flood response method for decision making may include an economic analysis and a reduction effect due to hydrological analysis including structural increase of agricultural reservoirs, flood control reservoirs, and improvement of sewerage as structural measures.

This method is possible because this system uses GIS-based data, and the minimum scale of each data is composed of 30m grid, so the area can be divided into cities, urban and rural complexes, coastal and rural areas. This is because the presence of rivers, the amount of damage, and the degree of urbanization can be analyzed and expressed.

Referring to FIGS. 28 and 29, alternative flood protection alternatives may be suggested through decision making, and expected scenarios for each alternative may be identified. After identifying the forecast scenarios for each alternative, we provide decision support to select the best alternative in the watershed through weight analysis for each alternative.

On the other hand, in the decision-making, after the selective flood defense alternative search, the foreign response case by category for the selected flood defense alternative can be provided as a DB so that the foreign countermeasures can be inquired (see FIG. 30).

The system of the present invention includes a database storing the vulnerability assessment index, a GIS database, a database of various statistical data, a database storing information derived by an analysis method developed in accordance with the present invention, and data of the database. It consists of a server that contains a variety of analysis modules for the function of querying, calculating and storing, and a user terminal connected to the server. The analysis module is provided to perform the functions of the above-described steps, and the user terminal may be connected to the server at the same location or at a remote location.

The user requests to perform each of the above-mentioned steps by using a menu provided on the screen of the system provided according to the present invention, and the analysis module includes an algorithm for performing such a user request in advance. It is prepared to access various databases, collect necessary information, and then return the desired result to the user through an analysis process. Here, the contents of the algorithm include the process described in each step of the GS-based flood defense method according to the present invention.

The present invention can not only assess the overall vulnerability of various disaster types such as landslides, earthquakes, earthquakes and tsunamis, but also floods, as well as specific vulnerabilities that combine vulnerability indexes that are believed to directly affect each type of disaster. It can be applied as a system that can evaluate the value. This may mean that the value for this purpose can be calculated by expressing a specific value according to the type of disaster and by weighting the vulnerability index corresponding to the type of disaster in the overall vulnerability index.

Claims (10)

Superimposing and assigning a vulnerability index to each area separated by a grid;
Ranking using the nested vulnerability indicators;
Presenting a countermeasure for each grade; And
A method of flood control based on GS, characterized in that for setting the optimum alternative according to the condition of convergence of the survival measures. Superimposing and assigning a vulnerability index to each area separated by a grid;
Ranking using the nested vulnerability indicators;
Querying major facilities of a region where the vulnerability index is high; And
GIS-based flood defense method comprising the step of presenting the current status of each facility by overlapping the past or future flood information. 3. The method according to claim 1 or 2,
The vulnerability indicators are classified as climatic, hydro-geological, socio-economic and flood defense vulnerabilities. The method of claim 1,
GIS-based flood defense method further comprising the step of presenting an expected scenario for decision making after the step of setting the optimal alternative. The method of claim 2,
After presenting the status of each facility, the flood defense method based on the GS, characterized in that it further comprises the step of presenting the expected scenario for the decision. The method according to claim 4 or 5, wherein the predicted scenario for decision making is economic analysis, or structural measures, and hydrological analysis including agricultural reservoir increase, flood control reservoir, and sewer improvement, which includes a reduction effect. GS-based flood defense method characterized in that. 6. The method of claim 4 or 5, wherein the anticipated scenario for decision making includes a corresponding overseas response case. The method of claim 2,
The past or future flood information is a flood control method based on GS, characterized in that the inundation trace or flood intention. The method of claim 2,
The main facility is a GS-based flood defense method, characterized in that any one of the facility, the environmental and economic impact of the facility to reduce the damage and efficient response and flood damage. 3. The method according to claim 1 or 2,
The vulnerability indicator is a GS-based flood defense method further comprises the step of being weighted.

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