TWI802599B - Risk assessment system and risk assessment program - Google Patents
Risk assessment system and risk assessment program Download PDFInfo
- Publication number
- TWI802599B TWI802599B TW107135611A TW107135611A TWI802599B TW I802599 B TWI802599 B TW I802599B TW 107135611 A TW107135611 A TW 107135611A TW 107135611 A TW107135611 A TW 107135611A TW I802599 B TWI802599 B TW I802599B
- Authority
- TW
- Taiwan
- Prior art keywords
- unit
- risk assessment
- index
- area
- risk
- Prior art date
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01W—METEOROLOGY
- G01W1/00—Meteorology
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/02—Alarms for ensuring the safety of persons
- G08B21/10—Alarms for ensuring the safety of persons responsive to calamitous events, e.g. tornados or earthquakes
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B31/00—Predictive alarm systems characterised by extrapolation or other computation using updated historic data
Landscapes
- Environmental & Geological Engineering (AREA)
- Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Emergency Management (AREA)
- Business, Economics & Management (AREA)
- Life Sciences & Earth Sciences (AREA)
- Physics & Mathematics (AREA)
- Atmospheric Sciences (AREA)
- General Life Sciences & Earth Sciences (AREA)
- Geology (AREA)
- Biodiversity & Conservation Biology (AREA)
- Ecology (AREA)
- Environmental Sciences (AREA)
- Computing Systems (AREA)
- Alarm Systems (AREA)
- Emergency Alarm Devices (AREA)
- Pit Excavations, Shoring, Fill Or Stabilisation Of Slopes (AREA)
Abstract
特定出因降雨而產生人命相關之土石災害的可能性較高的地區。 Areas with a high probability of life-related earth and rock disasters due to rainfall are identified.
危險度評估系統係包含:土石產生性指標計算部,係將包含基礎建設上之危險評估單元與複數監視對象單元的區域作為土石崩落之監視區域,而依各該監視對象單元來計算出表示其土石產生性的土石產生性指標;到達可能性指標計算部,係依各該監視對象單元來計算出其崩落土石朝該危險評估單元的到達可能性;以及基礎建設風險指標計算部,係基於各該監視對象單元的該土石產生性指標及該到達可能性指標來計算出表示該危險評估單元會受到崩落土石之被害的可能性之基礎建設風險指標;比較該風險指標與閾值來評估該危險評價單元中之土石災害產生風險。 The risk assessment system includes: the soil and rock production index calculation department, which uses the area including the risk assessment unit on the infrastructure and multiple monitoring object units as the monitoring area for landslides, and calculates and expresses its value according to each monitoring object unit. Earth-rock generation index of earth-rock generation; arrival possibility index calculation part, which calculates the arrival possibility of landslides to the risk assessment unit according to each monitoring object unit; and infrastructure risk index calculation part, which is based on each monitoring object unit. Calculate the infrastructure risk index indicating the possibility that the risk assessment unit will be damaged by landslides from the earth and rock generation index and the arrival possibility index of the monitoring object unit; compare the risk index with a threshold to evaluate the risk assessment Earth-rock hazards in the unit generate risks.
Description
本發明係關於一種評估降雨所致土石崩落的危險度之技術。 The present invention relates to a technique for assessing the risk of landslides caused by rainfall.
降雨所致之土石崩落係有帶來人命相關之被害的情況。於是,為了減輕土石崩落之被害,便提議一種能特定出降雨所致之土石崩落的危險度,而會在危險度提高的情況下,通報情報之技術。 Landslides caused by rainfall may cause death-related injuries. Therefore, in order to reduce the damage caused by landslides, a technology is proposed that can specify the risk of landslides caused by rainfall, and report the information when the risk level increases.
例如,日本特開平10-232286號公報記載有處理裝置會以無線來接收設置於觀測地區之雨量計所測量出的雨量資訊,來計算出考量觀測地區之地理情況後的土中含水量,而基於計算出之含水量來進行通報的方法。 For example, Japanese Patent Application Laid-Open No. 10-232286 records that the processing device will wirelessly receive the rainfall information measured by the rain gauge installed in the observation area to calculate the moisture content in the soil after considering the geographical conditions of the observation area, and Method of notification based on calculated moisture content.
又,日本特開平2016-122239號公報記載有基於雨量來決定設定有土石災害產生的危險地區的上端部之水位,且為表示土石災害產生可能性高的土石災害水位,而比對指定地點所推斷出之水位,來特定出土石災害產生的高警戒區域的方法。 In addition, Japanese Patent Application Laid-Open No. 2016-122239 describes that the water level at the upper end of an area at risk of land-rock disasters is determined based on the amount of rainfall, and the water level at the upper end of the land-rock disaster area that is likely to occur with a high probability of land-rock disasters is compared. It is a method of specifying the high-alert area caused by excavation and rock disasters by inferring the water level.
在長時間持續降雨的情況,將接受降雨的全地區作為危險區域而成為土石崩落的監視對象,或是禁止人員進入至該等全區域之情況在風險與為了迴避風險的代價上欠缺平衡,而不現實。 In the case of continuous rainfall for a long time, the entire area receiving the rainfall is regarded as a dangerous area and becomes the monitoring object of landslides, or the situation of prohibiting people from entering such an entire area lacks a balance between the risk and the cost of avoiding the risk, and unrealistic.
若能特定出會產生人命相關之土石災害的可能性較高之地區的話,便可藉由集中監視該地區,或是只有該地區禁止人員進入,來有效率地迴避風險。 If an area with a high possibility of life-related earth-rock disasters can be identified, the risk can be avoided efficiently by focusing on monitoring the area, or only prohibiting personnel from entering the area.
本發明有鑑於上述情事,而提供一種,用以特定出因降雨而產生人命 相關之土石災害的可能性較高之區域的機構。 The present invention is in view of above-mentioned circumstances, and provides a kind of, is used for identifying the human life that produces because of rainfall. Institutions in areas with a high potential for related earth-rock hazards.
為了解決上述課題,本發明之第1態樣便提供一種危險度評估系統,係將包含危險評估單元與複數監視對象單元的區域作為土石崩落之監視區域,而基於各該監視對象單元的土石產生性以及各該監視對象單元的崩落土石朝該危險評估單元之到達可能性,來評估該危險評估單元中之土石災害產生風險。 In order to solve the above-mentioned problems, the first aspect of the present invention provides a risk assessment system, which uses the area including the risk assessment unit and a plurality of monitoring object units as the monitoring area for landslides, and based on the occurrence of earth and rocks in each of the monitoring object units The risk of earth-rock disasters in the risk assessment unit is evaluated based on the reliability and the possibility of the rockfall from each monitoring object unit reaching the risk assessment unit.
根據上述第1態樣相關之危險度評估系統,便可得知某地點的土石災害產生風險。 According to the risk assessment system related to the first aspect above, the risk of earth-rock disasters at a certain location can be known.
上述第1態樣相關之危險度評估系統中,可作為第2態樣來採用關於各該複數監視對象單元係將使用該監視對象單元之集水區域的面積所對應的分布與該監視對象單元之分布的比之指標作為表示各該監視對象單元之土石產生性的土石產生性指標來加以使用,該監視對象單元係將構成包含該監視區域之地區的複數單元之各分布與為供給會流進該單元之水的區域之集水區域的面積之關係依近似的回歸式來加以算出之構成。 In the risk assessment system related to the above-mentioned first aspect, the distribution corresponding to the area of the water collection area using the monitoring object unit and the monitoring object unit can be adopted as the second aspect. The ratio of the distribution ratio index is used as an indicator of soil and rock production for each monitoring object unit that combines the distribution of the plurality of units constituting the area including the monitoring area with the supply flow The relationship between the area of the water entering the unit and the area of the catchment area is calculated according to the approximate regression formula.
上述第1態樣相關之危險度評估系統中,可作為第3態樣來採用關於各該複數監視對象單元係將使用該監視對象單元與該危險評估單元之高度差,以及該監視對象單元與該危險評估單元之水平距離的比之指標作為表示各該監視對象的崩落土石朝該危險評估單元之到達可能性的到達可能性指標來加以使用之構成。 In the risk assessment system related to the above-mentioned first aspect, the height difference between the monitoring object unit and the risk assessment unit, and the height difference between the monitoring object unit and the monitoring object unit can be adopted as the third aspect. A configuration in which the ratio index of the horizontal distance of the risk assessment unit is used as an arrival possibility index indicating the possibility of arrival of landslides of the monitoring objects toward the risk assessment unit.
又,第2態樣相關之危險度評估系統中,可作為第4態樣來採用關於各該複數監視對象單元係將使用該監視對象單元與該危險評估單元之高度差,以及該監視對象單元與該危險評估單元之水平距離的比之指標作為表示各該監視對象的崩落土石朝該危險評估單元之到達可能性的到達可能性指標來加以使用之構成。 In addition, in the risk assessment system related to the second aspect, the height difference between the monitoring object unit and the risk assessment unit for each of the plurality of monitoring object units and the monitoring object unit can be adopted as the fourth aspect. A configuration in which a ratio index to the horizontal distance of the risk assessment unit is used as an arrival possibility index indicating the possibility of arrival of landslides of the monitoring objects toward the risk assessment unit.
上述第4態樣相關之危險度評估系統中,可作為第5態樣來以採用關於各該複數監視對象單元係基於使用該土石產生性指標與該到達可能性指標所計算出之指標的統計量,來評估該危險評估單元中之土石災害產生風險之構成。 In the risk assessment system related to the above-mentioned fourth aspect, it is possible to use as the fifth aspect the statistics of each of the plurality of monitoring target units based on the index calculated by using the soil and rock generation index and the arrival possibility index. Quantities to evaluate the composition of the risk of earth-rock disasters in the risk assessment unit.
根據上述第2至第5態樣相關之危險度評估系統,便可藉由包含監視區域之地區的數值標高模型來得知該地區內之某地點中的土石災害產生風險。 According to the risk assessment system related to the above-mentioned 2nd to 5th aspects, the risk of earth-rock disasters in a certain location in the area can be known through the numerical elevation model of the area including the monitoring area.
上述第1至第5中任一者態樣相關之危險度評估系統中,可作為第6態樣來採用關於基礎建設上之各複數單元係藉由評估出在該單元為該危險評估單元的情況下之該土石災害產生風險,來特定出該基礎建設上有危險的單元之構成。 In the risk assessment system related to any one of the above-mentioned
根據上述第6態樣相關之危險度評估系統,便可得知人員進出較多的基礎建設中土石災害產生風險較高的區域。 According to the risk assessment system related to the sixth aspect above, it can be known that the areas with higher risk of earth-rock disasters in the infrastructure construction with more people entering and leaving.
上述第1至第6中任一者態樣相關之危險度評估系統中,可作為第7態樣來採用基於包含該監視區域的地區中的降雨量之經時變化,來推定出該監視區域內的土石崩落的產生時刻之構成。 In the risk assessment system related to any one of the above-mentioned
根據上述第7態樣相關之危險度評估系統中,便可得知土石災害產生風險升高的時刻。 According to the risk assessment system related to the seventh aspect above, the moment when the risk of earth-rock disasters increases can be known.
又,本發明的第8態樣便提供一種程式,係讓電腦基於在包含危險評估單元與複數監視對象單元的土石崩落之監視區域中,表示各該監視對象單元之土石產生性的指標之土石產生性指標以及表示各該監視對象單元的崩落土石朝該危險評估單元之到達可能性的指標之到達可能性指標,來計算出表示該危險評估單元中的土石災害產生風險的指標。 In addition, the eighth aspect of the present invention provides a program that allows the computer to express the soil and rock production index of each monitoring object unit based on the earth and rock fall monitoring area including the risk assessment unit and the plurality of monitoring object units. The index indicating the occurrence risk of landslide disasters in the risk assessment unit is calculated by using the generation index and the arrival possibility index indicating the probability of arrival of landslides in each monitoring object unit to the risk assessment unit.
根據上述第8態樣相關之程式,便可藉由電腦來實現上述第1態樣相關之危險度評估系統。 According to the program related to the above-mentioned eighth aspect, the risk assessment system related to the above-mentioned first aspect can be realized by a computer.
1‧‧‧危險度評估系統 1‧‧‧Risk Assessment System
11‧‧‧末端裝置 11‧‧‧Terminal device
12‧‧‧伺服器裝置 12‧‧‧Server Device
圖1係顯示一實施形態相關之危險度評估系統的整體構成之圖式。 FIG. 1 is a diagram showing the overall composition of a risk assessment system related to an embodiment.
圖2係顯示作為一實施形態相關之末端裝置的硬體來使用之電腦的構成之圖式。 FIG. 2 is a diagram showing a configuration of a computer used as hardware of a terminal device according to an embodiment.
圖3係顯示作為一實施形態相關之伺服器裝置的硬體來使用之電腦的構成之圖式。 FIG. 3 is a diagram showing a configuration of a computer used as hardware of a server device according to an embodiment.
圖4係顯示一實施形態相關之末端裝置的機能構成之圖式。 FIG. 4 is a diagram showing the functional configuration of a terminal device related to an embodiment.
圖5係顯示一實施形態相關之末端裝置所特定出的危險評估單元與監視區域之關係的圖式。 FIG. 5 is a diagram showing the relationship between the risk assessment unit and the monitoring area specified by the terminal device related to an embodiment.
圖6係例示一實施形態相關的顯示部所顯示的資訊之圖式。 Fig. 6 is a diagram illustrating an example of information displayed on a display unit according to an embodiment.
圖7係例示一實施形態相關的顯示部所顯示的資訊之圖式。 Fig. 7 is a diagram illustrating an example of information displayed on a display unit according to an embodiment.
圖8係顯示一實施形態相關之末端裝置的機能構成之圖式。 FIG. 8 is a diagram showing the functional configuration of a terminal device related to an embodiment.
圖9係例示一實施形態相關的顯示部所顯示的資訊之圖式。 Fig. 9 is a diagram illustrating an example of information displayed on a display unit according to an embodiment.
[實施形態] [implementation form]
以下,便說明本發明實施形態相關之危險度評估系統1。危險度評估系統1係將對象地區內之鐵路等的基礎建設中因降雨所致土石災害產生風險較高的區域通知使用者,並將在土石災害產生風險較高之部分中推測出土石災害會產生的時刻通知使用者的系統。 Hereinafter, the
圖1係顯示危險度評估系統1之整體構成的圖式。危險度評估系統1係具備:藉由使用者來被加以使用,而生成會對使用者進行通知的資訊,並將所生成的資訊通知使用者的末端裝置11;以及會對末端裝置11發布表示對象地區中之降雨量的經時變化的實際值與推測值之降雨量數據的伺服器裝置12。末端裝置11與伺服器裝置12會透過網路來通訊連接。 FIG. 1 is a diagram showing the overall configuration of a
末端裝置11與伺服器裝置12之硬體係電腦。圖2係顯示作為末端裝置11的硬體來使用之電腦10的構成之圖式。圖3係顯示作為伺服器裝置12的硬體來使用之電腦20的構成之圖式。 The hardware system computer of the
電腦10係具備有:記憶各種數據的記憶體101;依照記憶體101所記憶的程式來進行各種數據處理的處理器102;與外部裝置之間進行數據通訊的通訊單元103;對使用者顯示各種資訊的顯示器104;以及接受使用者之數據輸入操作的鍵盤105。另外,顯示器104及鍵盤105的至少一者可不被內建於電腦,而是作為外接裝置來連接於電腦10。 The
電腦20係具備有:記憶各種數據的記憶體201;依照記憶體201所記憶 的程式來進行各種數據處理的處理器202;以及與外部裝置之間進行數據通訊的通訊單元203。 The
在處理器202依照記憶體201所記憶的程式進行各種數據處理時,電腦20會作為將降雨量數據發布於末端裝置11之伺服器裝置12來加以動作。由於伺服器12之機能構成係與進行通常數據發布之伺服器裝置的機能構成相同,故省略其說明。 When the
圖4係顯示末端裝置11之機能構成中進行用以將土石災害產生風險較高之場所通知使用者的處理之機能構成的圖式。以下便說明圖4所示之機能構成。 FIG. 4 is a diagram showing a functional configuration of a
記憶部11主要係藉由記憶體101來被加以實現,並會記憶各種數據。記憶部111係記憶有:預先顯示對象地區之數值標高模型的數值標高模型數據;以及顯示對象地區內之鐵路(基礎建設一範例)所通過的位置之路線數據。又,記憶部111係記憶有會藉由以下所說明之演算部110所生成的各種數據。 The
演算部110主要係藉由處理器102來被加以實現,並會進行各種演算。演算部110係具備有會就構成對象地區之各複數單元,來計算出該單元之集水面積的集水面積計算部1101。本發明中之單元係代表著將對象地區分割而得到的複數既定大小之各矩形區域。單元的集水面積係供給會流進該單元之水的區域之集水區域的面積。集水面積計算部1101係使用數值標高模型數據所表示的數值標高模型,並藉由習知的地形水文分析來計算出對象地區內之各單元的集水面積。表示藉由集水面積計算部1101所計算出的各單元的集水面積之數據會作為集水面積數據而被記憶於記憶部111。 The
演算部110係具備有會計算出對象地區內之各單元的分布之分布計算部1102。分布計算部1102會進行數值標高模型數據所表示的數值標高模型的空間微分,來計算出對象地區內之各單元的分布。表示藉由分布計算部1102所計算出之各單元的分布之數據係作為分布數據來被記憶於記憶部111。 The
演算部110係具備有會特定出表示帶來對象地區中之標準土石的剝落 容易性的集水面積與分布之組合的回歸式之回歸式特定部1103。回歸式特定部1103會就對象地區內之各單元來將集水面積數據所表示之集水面積與分布數據所表示的分布作對應配對,而就將對應配對好的集水面積與分布之組別作為樣本的母集團藉由回歸分析來特定出回歸式。 The
本實施形態中,回歸式特定部1103所特定出之回歸式係具備有下數式1之構造。 In this embodiment, the regression formula specified by the regression
其中,S係分布(單位:m/m),Af係集水面積(單位:m2)。又,B及p係以對象地區之土石特性所訂出之常數,而會藉由回歸分析來被加以特定出。 Among them, S refers to the distribution (unit: m/m), and Af refers to the catchment area (unit: m 2 ). In addition, B and p are constants determined based on the characteristics of soil and rock in the target area, and are specified through regression analysis.
數式1係由以下數式2所導出。
E=KA f m S n ...(式2) E = KA f m S n . . . (Formula 2)
其中,E係土石的侵蝕速度(單位:m/yr),K係土石的侵蝕效率(單位:例如yr-1(依存於指數m)。又,m及n係表示集水面積Af與分布S之加權的數值(m>0,n>0)。如數式2所示,土石的侵蝕速度已知在分布與集水面積的指數乘積上具有大致比例關係。另外,數式1之常數與數式2之常數係有以下數式3及數式4所示之關係。 Among them, the erosion rate of E-series soil and rock (unit: m/yr), the erosion efficiency of K-series soil and rock (unit: such as yr -1 (depending on the index m). In addition, m and n series represent the catchment area A f and distribution The weighted value of S (m>0, n>0). As shown in formula 2, the erosion rate of soil and rock is known to have a roughly proportional relationship in the exponential product of distribution and catchment area. In addition, the constant of
p=m/n...(式4) p = m / n. . . (Formula 4)
表示藉由回歸式特定部1103所特定出之回歸式的數據會作為回歸式數據而被記憶於記憶部111。 Data indicating the regression formula specified by the regression
演算部110係具備有會將從對象地區內之單元中鐵路會通過之單元作為危險評估單元而選出的危險評估單元選出部1104。危險評估單元選出部1104會基於路線數據來選出危險評估單元。表示藉由危險評估單元1104所選出之危險評估單元的數據會作為危險評估單元數據而被記憶於記憶部111。 The
演算部110係具備有就各危險評估單元,而將該危險評估單元之集水區域作為監視區域來特定出之監視區域特定部1105。監視區域特定部1105係使用數值標高模型數據所表示之數值標高模型來就各危險評估單元,藉由習知的地形水文分析來特定出集水區域,而將特定出之集水區域作為該危險評估單元之監視區域。以下,將監視區域內之單元稱為監視對象單元。 The
圖5係顯示對象地區U內之線路r上的1個危險評估單元Pi與危險評估單元Pi之監視區域Qi的圖式。表示藉由監視區域特定部1105所特定出之各危險評估單元的監視區域之數據會作為監視區域數據來被記憶於記憶部111。 FIG. 5 is a diagram showing one risk assessment unit P i and the monitoring area Q i of the risk assessment unit P i on the route r in the target area U. Data indicating the monitoring area of each risk assessment unit specified by the monitoring
演算部110(圖4)具備有土石產生性指標計算部1106,係就藉由危險評估單元選出部1104所選出之複數各危險評估單元,依藉由監視區域特定部1105所特定出之監視區域內的各監視對象單元,來計算出為表示土石產生性之指標的土石產生性指標。 Calculation unit 110 ( FIG. 4 ) is equipped with soil and rock generation
本實施形態中,土石產生性指標計算部1106係依照下數式5來計算出土石產生性指標SAI。 In this embodiment, the soil and rock production
其中,Slocal係分布數據所表示之監視對象單元的分布,Aflocal係集水面積數據所表示之監視區域的集水面積。又,S(Aflocal)係依照回歸式數據所表示之回歸式(數式1)所計算出的監視區域的集水面積Aflocal所對應的分布。 Among them, S local is the distribution of the monitoring object unit represented by the distribution data, and A flocal is the catchment area of the monitoring area represented by the catchment area data. Also, S(A flocal ) is a distribution corresponding to the water catchment area A flocal of the monitoring area calculated according to the regression formula (Expression 1) represented by the regression formula data.
表示藉由土石產生性指標計算部1106所計算出之各危險評價單元的各監視對象單元之土石產生性指標SAI的數據會作為土石產生性指標數據來被記憶於記憶部111。 Data indicating the soil and rock production index SAI of each monitoring target unit of each risk assessment unit calculated by the soil and rock production
演算部110具備有到達可能性指標計算部1107,係就藉由危險評估單元選出部1104所選出之複數各危險評估單元,依監視區域特定部1105所特定出之監視區域內的各監視對象單元,來計算出為表示崩落土石朝該危險評估單元之到達可能性的指標之到達可能性指標。
本實施形態中,到達可能性指標計算部1107係依照下數式6來計算出到達可能性指標IEFC。 In this embodiment, the reachability
其中,Hs係將數值標高模型數據所表示的以危險評估單元為基準的監視對象單元之高度(單位:m),亦即監視對象單元之高度減去危險評估單元之高度的數值。又,L係數值標高模型數據所表示之危險評估單元與監視對象單元的水平距離(單位:m)。 Among them, H s is the height (unit: m) of the monitoring object unit based on the risk assessment unit represented by the numerical elevation model data, that is, the value obtained by subtracting the height of the risk assessment unit from the height of the monitoring object unit. Also, the L coefficient value is the horizontal distance (unit: m) between the risk assessment unit represented by the elevation model data and the monitoring object unit.
表示藉由到達可能性指標計算部1107所計算出之各危險評估單元的各監視對象單元之到達可能性指標IEFC的數據會作為到達可能性指標數據來被記憶於記憶部111。 Data representing the arrival possibility index IEFC of each monitoring target unit of each risk assessment unit calculated by the arrival possibility
演算部110具備有災害指標計算部1108,係就藉由危險評估單元選出部1104所選出之複數各危險評估單元,依照監視區域特定部1105所特定出之監視區域內的各監視對象單元,來計算出為表示能夠到達危險評估單元之崩落土石的產生性之指標的災害指標。
本實施形態中,災害指標計算部1108係依照下數式7來計算處災害指標TGI。 In this embodiment, the disaster
TGI=SAI×IEFC...(式7) TGI = SAI × IEFC. . . (Formula 7)
表示藉由災害指標計算部1108所計算出之各危險評估單元的各監視對象單元的災害指標TGI的數據會作為災害指標數據來被記憶於記憶部111。 Data indicating the disaster index TGI of each monitoring target unit of each risk assessment unit calculated by the disaster
演算部110具備有基礎建設風險指標計算部1109,係就藉由危險評估單元選出部1104所選出之複數各危險評估單元,將藉由災害指標計算部1108所計算出之災害指標TGI統計量作為基礎建設風險指標來計算出。
本實施形態中,基礎建設風險指標計算部1109係將災害指標TGI的算術平均作為基礎建設風險指標SLPR來加以算出。表示藉由基礎建設風險指標計算部1109並依各危險評價單元所計算出之基礎建設風險指標SLPR的數據會作為基礎建設風險指標數據來被記憶於記憶部111。 In this embodiment, the infrastructure risk
顯示部112主要係藉由顯示器104來加以實現,並會顯示藉由演算部110所生成,而被記憶於記憶部111的各種數據所表示的資訊。圖6及圖7係例示顯示部112所顯示的資訊之圖式。 The
圖6係顯示顯示部112所顯示之災害地圖。圖6所例示的災害地圖係圖示有危險評估單元P1、P2、P3,來作為對象地區U內的線路r上的危險評估單元中基礎建設風險指標SLPR為既定閾值以上的危險評估單元。又,圖6所例示的災害地圖係以x印記來表示被包含在各危險評估單元P1、P2、P3所對應的監視區域Q1、Q2、Q3的監視對象單元中災害指標TGI為既定閾值以上的監視對象單元。 FIG. 6 shows a disaster map displayed on the
使用者可觀察災害地圖,來得知在線路r上容易遭受土石災害的場所,以及在對象地區內會帶來土石災害的土石崩落容易產生的場所。 The user can observe the disaster map to know the places that are prone to earth and rock disasters on the route r, and the places that are likely to cause landslides that cause earth and rock disasters in the target area.
圖7係顯示顯示部112所顯示的沿線風險線。沿線風險線係以從線路r的既定基準點到線路r上的危險評估單元之距離(沿著線路r的距離)為橫軸,以橫軸所示之距離所對應的危險評估單元的基礎建設風險指標SLPR為縱軸來描繪出的圖表。使用者可觀察沿線風險線,來得知在線路r上之各地點的土石災害的遭受容易度。 FIG. 7 shows the risk line along the line displayed on the
圖8係顯示在末端裝置11之機能構成中進行用以將推測出土石崩落會產生之時刻通知使用者的處理之機能構成的圖式。末端裝置11除了上述記憶部111、演算部110、顯示部112以外,還具備有從伺服器裝置12來接收降雨量數據的接收部113,以作為用以推測出土石崩落的產生時刻之構成部。接受部113主要會藉由通訊單元103來被加以實現。 FIG. 8 is a diagram showing a functional configuration of the functional configuration of the
演算部110係具備有壓力水面計算部1110、安定性指標計算部1111、產生時刻推測部1112,來作為用以推算出土石崩落之產生時刻的構成部。 The
壓力水面計算部1110係就對象地區內之各單元,依照下數式8,來計算出以降雨開始時刻為基準的時刻t(亦即,從降雨開始時刻開始經過時間t(單位:s)的時刻)中的壓力水面ψ的壓力水單位:m)。另外,下數式8係由Richard M.Iversony在2000年所發表之論文”Landslide triggering by rain infiltration”中所提議的模型方程式。 The pressure water
其中,t*係下數式9所表示之數值。 Wherein, t * is the numerical value represented by the following formula 9.
其中,D0係擴散係數(單位:m2/s),α係斜面傾斜角(單位:deg),Z係深度(單位:m)。 Among them, D 0 is the diffusion coefficient (unit: m 2 /s), α is the slope angle (unit: deg), and Z is the depth (unit: m).
又,T*係以下數式10所示的數值。 In addition, T * is a numerical value shown in the following
其中,T係降雨持續時間(單位:s)。 Among them, T is the duration of rainfall (unit: s).
又,ψ0係壓力水面的初期值,Iz係雨量強度(單位:m/s),Kz係深度方向之透水係數(m/s),R(t*)係將t*代入至下數式11之x的數值,R(t*-T*)係將(t*-T*)代入至下數式11之x的數值。 Also, ψ 0 is the initial value of the pressure water surface, I z is the rainfall intensity (unit: m/s), K z is the permeability coefficient in the depth direction (m/s), and R(t * ) is to substitute t * into the following For the value of x in
表示藉由壓力水面計算部1110所計算出之各單元的時刻t中的壓力水面ψ的壓力之數據會作為壓力水面數據來被記憶於記憶部111。 The data representing the pressure of the pressure water surface ψ in each cell at time t calculated by the pressure water
記憶部111係記憶有表示擴散係數D0的擴散係數數據、表示各單元的的斜面傾斜角數據、表示各單元之深度Z的深度數據、表示雨量強度Iz的雨量強度數據、表示深度方向之透水係數Kz的透水係數數據、表示降雨持續時間T的降雨持續時間數據,來作為壓力水面計算部1110為了計算出各單元之時刻t中的壓力水面ψ的壓力而使用的數據。 The
擴散係數數據所表示之擴散係數D0以及透水係數數據所表示之透水係數Kz係藉由對象地區內之代表點中的水文觀測值以及數式8所示的模型方程式的擬合來特定出之數值。 The diffusion coefficient D 0 represented by the diffusion coefficient data and the hydraulic permeability coefficient K z represented by the permeability coefficient data are specified by fitting the hydrological observation values in the representative points in the target area and the model equation shown in Equation 8 value.
斜面傾斜角數據所表示之各單元的斜面傾斜角α以及深度數據所表示的各單元之深度Z係基於數值標高模型數據來特定出之數值。 The slope angle α of each unit represented by the slope slope angle data and the depth Z of each cell represented by the depth data are numerical values specified based on the numerical elevation model data.
雨量強度數據所表示之雨量強度Iz以及降雨持續時間數據所表示之降雨持續時間T係基於接收部113從伺服器12所接收的降雨量數據來特定出之數值。 The rainfall intensity I z represented by the rainfall intensity data and the rain duration T represented by the rainfall duration data are values specified based on the rainfall data received by the receiving
另外,壓力水面計算部1110用於算出在時刻t中之壓力水面ψ之壓力的壓力水面之初期值ψ0係壓力水面數據所表示之降雨開始時刻中的壓力水面。 In addition, the pressure water
安定性指標計算部1111係就各對象地區內之各單元,依照下數式12來計算出時刻t中之斜面安定指標Fs。另外,下數式12係由A.W.Skempton與F.A.Delory在1957年所發表之論文”Stability of Natural Slopes in London Clay”所提議的計算式。 The stability
其中,c係土層之黏著力(單位:kPa),ΔΔ係樹根系統所致之黏著力的增加量(單位:kPa),γ係土層的飽和單位重量(單位:N/m3),γw係水的單位重量(單位:N/m3),h係土層厚(單位:m),α係斜面傾斜角(單位:deg),φ係剪切抵抗角(單位:deg)。 Among them, the adhesive force of the c-series soil layer (unit: kPa), the increase of the adhesive force caused by the ΔΔ-series root system (unit: kPa), and the saturated unit weight of the γ-series soil layer (unit: N/m 3 ) , γw is the unit weight of water (unit: N/m 3 ), h is the thickness of the soil layer (unit: m), α is the inclination angle of the slope (unit: deg), φ is the shear resistance angle (unit: deg) .
又,m係依照下數式13所計算出之地下水位參數(壓力水面相對於土層厚h的比)。 Also, m is the groundwater level parameter (ratio of the pressure water level to the thickness h of the soil layer) calculated according to the following formula 13.
斜面安定性指標Fs若為1以上的話,斜面便為安定,而表示土石崩落不會產生,若未達1的話則斜面為不安定,而表示土石崩落會產生。 If the slope stability index Fs is 1 or more, the slope is stable, indicating that landslides will not occur, and if it is less than 1, the slope is unstable, indicating that landslides will occur.
記憶部111係記憶有表示土層黏著力c的黏著力數據、表示樹根系統所致之土層的黏著力之增加量Δ致的黏著力增加量數據、表示土層的飽和單位重量γ的飽和單位重量數據、表示水的單位重量γw的單位重量數據、表示各單元之土層厚h的土層厚數據、表示各單元之斜面傾斜角α的斜面傾斜角數據、表示剪切抵抗角φ之剪切抵抗角數據,來作為安定性指標計算部1111為了計算出各單元之時刻t中的斜面安定性指標Fs而使用的數據。 The
黏著力數據所表示之土層黏著力c、飽和單位重量數據所表示之土層飽和單位重量γ、剪切抵抗角數據所表示之剪切抵抗角φ係藉由使用從對象地區內所採集的樣本來進行的剪切試驗等所特定出之數值。黏著力增加量數據所表示之土層的黏著力之增加量Δ驗係藉由作為土層中之深度函數的植物根系統的數量密度與根直徑分布及過去災害事例的逆分析,並以經驗來求得的數值。 The cohesion c of the soil layer represented by the adhesive force data, the saturated unit weight γ of the soil layer represented by the saturated unit weight data, and the shear resistance angle φ represented by the shear resistance angle data were obtained by using the data collected from the target area. The value specified by the shear test, etc. carried out on the sample. The increase in the adhesive force Δ of the soil layer represented by the adhesive force increase data is based on the inverse analysis of the number density and root diameter distribution of the plant root system as a function of the depth in the soil layer and past disaster cases, and based on experience to obtain the value.
斜面傾斜角數據所表示之各單元的斜面傾斜角α係基於數值標高模型數據來特定出之數值。 The slope inclination angle α of each unit indicated by the slope inclination angle data is a value specified based on the numerical elevation model data.
土層厚數據所表示之各單元的土層厚h係將基於數值標高模型數據來特定出之傾斜曲率C代入至下數式14而計算出之數值。 The soil layer thickness h of each unit represented by the soil layer thickness data is a value calculated by substituting the slope curvature C specified based on the numerical elevation model data into the following equation 14.
h=h 0 e aC ...(式14) h = h 0 e aC . . . (Formula 14)
其中,h0係傾斜曲率C為0之處的平板型斜面的土層厚,a係指數常數。 Among them, h 0 is the thickness of the flat slope where the slope curvature C is 0, and a is an exponential constant.
數式14之指數常數a係就從對象地區內隨機選擇的複數各單元,使用以基於數值標高模型數據所特定出之傾斜曲率C與土層厚h的實測值的組合為樣本的母集團,而藉由回歸分析來特定出之數值。另外,為了從傾斜曲率C來推測出土層厚h所使用的函數雖是藉由回歸分析來求得,但函數之種類並不限於數式14所例示的指數函數,只要能從傾斜曲率C來導出土層厚h的有意義的推測值的話,便可使用例如線性函數、多項式函數、指數函數等的任一種種類的函數。 The exponential constant a of Equation 14 is the parent group that uses the combination of the slope curvature C specified based on the numerical elevation model data and the actual measurement value of the soil layer thickness h as a sample for plural units randomly selected from the target area, And the value is specified by regression analysis. In addition, although the function used to estimate the thickness h of the soil layer from the slope curvature C is obtained by regression analysis, the type of function is not limited to the exponential function shown in Equation 14, as long as it can be obtained from the slope curvature C Any type of function such as a linear function, a polynomial function, or an exponential function can be used to derive a meaningful estimated value of the soil layer thickness h.
表示藉由安定性指標計算部1111所計算出之各單元的時刻t中的斜面安定性指標Fs之數據會作為斜面安定性指標數據來被記憶於記憶部111。 Data representing the slope stability index F s at time t of each unit calculated by the stability
產生時刻推測部1112係就被包含於基礎建設風險指標SLPR為既定閾值以上的各危險評估單元所對應的監視區域之各監視對象單元,而將斜面安定性指標數據為未達1的時刻推測為其監視對象單元中土石崩落會產生之時刻。 The generation
顯示部112係顯示藉由產生時刻推測部1112所推測出之土石崩落的產生場所及產生時刻。圖9係例示顯示部112所顯示之災害地圖的圖式。圖9所例示的災害地圖除了被包含於圖6所示之災害地圖的資訊以外,還顯示出推 測有土石崩落產生之場所與時刻。 The
使用者可觀察災害地圖,來得知在線路r上針對容易遭受土石災害之場所而有帶來崩落土石之可能性的監視區域內,在哪一場所及什麼時刻土石崩落會產生。 The user can observe the disaster map to know at which place and when the landslide will occur in the monitoring area on the route r that is likely to cause landslides for places that are prone to landslide disasters.
[變形例] [modified example]
本發明係可以與上述實施形態不同的形態來被加以實施。以下便顯示上述實施形態的變形例。又,以下變形例亦可各自組合。 The present invention can be implemented in different forms from the above-described embodiments. Modifications of the above-mentioned embodiment are shown below. In addition, the following modified examples may be combined respectively.
(1)上述實施形態中,雖基礎建設為鐵路,但基礎建設之種類並不限於鐵路,而可為道路、發電廠、變電所等的任一者。 (1) In the above embodiment, although the infrastructure is a railway, the type of infrastructure is not limited to the railway, but may be any of roads, power plants, and substations.
(2)上述實施形態中,雖表示各監視對象單元之土石產生性指標係使用數式5所定義的SAI,但只要為能表示各監視對象單元的土石產生性指標的話,亦可使用其他指標。 (2) In the above-mentioned embodiment, although the SAI defined by Equation 5 is used to represent the soil and rock generation index of each monitoring object unit, other indexes can also be used as long as it can represent the soil and rock generation index of each monitoring object unit .
(3)上述實施形態中,雖表示各監視對象單元的崩落土石朝危險評估單元的到達可能性指標係使用數式6所定義的IEFC,但只要為能表示各監視對象單元之崩落土石朝危險評估單元的到達可能性指標的話,亦可使用其他指標。 (3) In the above-mentioned embodiment, although the arrival possibility index of the assessment unit indicating the risk of landslides towards each monitoring object unit is defined by the IEFC defined in Eq. Other indicators may also be used for the evaluation unit's reachability indicator.
(4)上述實施形態中,雖表示各監視對象單元的可到達危險評估單元之崩落土石產生性指標係使用數式7所定義的TGI,但只要是使用表示各監視對象單元的土石產生性指標以及表示各監視對象單元之崩落土石朝危險評估單元之到達可能性指標來計算出的指標的話,亦可使用其他指標。 (4) In the above-mentioned embodiment, although TGI defined by Eq. As well as an index calculated to indicate the index of the possibility of arrival of landslides in each monitoring object unit toward the risk assessment unit, other indices may be used.
(5)上述實施形態中,雖表示基礎建設上之危險評估單元會受到崩落土石之被害的可能性之基礎建設風險指標SLPR係使用災害指標TGI之算數平均,但只要是使用表示各監視對象單元的土石產生性指標以及表示各監視對象單元之崩落土石朝危險評估單元的到達可能性指標來計算出之指標的統計量的話,亦可使用其他統計量來作為基礎建設風險指標SLPR。 (5) In the above-mentioned embodiment, although the infrastructure risk index SLPR, which indicates the possibility that the risk assessment unit on the infrastructure construction will be damaged by landslides, uses the arithmetic mean of the disaster index TGI, as long as it is used to represent each monitoring target unit If the soil and rock production index of each monitoring object unit is calculated from the index of the possibility of arrival of landslides towards the risk assessment unit, other statistics can also be used as the infrastructure risk index SLPR.
(6)上述實施形態中,雖用以推測出監視區域內的土石崩落產生時刻的指標係使用數式12所定義的斜面安定性指標Fs,但只要是基於對象地區中之降雨量的經時變化來計算出之表示各單元的斜面安定性之指標的話,亦可 使用其他指標。 (6) In the above embodiment, although the index for estimating the occurrence time of landslides in the monitoring area is the slope stability index F s defined by
(7)上述實施形態中,雖末端裝置11及伺服器裝置12係藉由讓電腦實行依照程式之處理來被加以實現者,但末端裝置11及伺服器12的至少一者亦可構成為專用裝置。 (7) In the above-mentioned embodiment, although the
1:危險度評估系統 1: Risk assessment system
11:末端裝置 11: Terminal device
12:伺服器裝置 12: Server device
Claims (9)
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
JP2017-196948 | 2017-10-10 | ||
JP2017196948A JP6941319B2 (en) | 2017-10-10 | 2017-10-10 | Risk assessment system |
Publications (2)
Publication Number | Publication Date |
---|---|
TW201928400A TW201928400A (en) | 2019-07-16 |
TWI802599B true TWI802599B (en) | 2023-05-21 |
Family
ID=66100616
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
TW107135611A TWI802599B (en) | 2017-10-10 | 2018-10-09 | Risk assessment system and risk assessment program |
Country Status (3)
Country | Link |
---|---|
JP (1) | JP6941319B2 (en) |
TW (1) | TWI802599B (en) |
WO (1) | WO2019073937A1 (en) |
Families Citing this family (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2020060078A (en) * | 2018-10-12 | 2020-04-16 | 日本信号株式会社 | System for estimating time landslide occurs |
CN109935054A (en) * | 2019-04-25 | 2019-06-25 | 成都星感智联科技有限公司 | A kind of landslide short period forecasting procedure |
CN111311879B (en) * | 2020-01-16 | 2021-04-20 | 广州地理研究所 | Debris flow early warning method and device |
CN111415065B (en) * | 2020-02-26 | 2023-05-12 | 广州地理研究所 | Mountain disaster ecological damage risk evaluation method based on action process |
CN112504624A (en) * | 2020-11-11 | 2021-03-16 | 华能澜沧江水电股份有限公司 | Hydrodynamic landslide multi-information multi-source fusion early warning method |
CN112464474B (en) * | 2020-11-26 | 2023-09-15 | 北京市地质灾害防治研究所 | Low-frequency debris flow early warning method based on risk evaluation |
CN115019478A (en) * | 2022-08-09 | 2022-09-06 | 中地宝联(北京)国土资源勘查技术开发集团有限公司 | Monitoring and early warning method applied to critical landslide |
CN116416762B (en) * | 2023-06-09 | 2023-08-15 | 四川川核地质工程有限公司 | Mud-rock flow early warning method and system based on artificial intelligence |
Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
TW200629183A (en) * | 2005-02-15 | 2006-08-16 | Univ Nat Pingtung Sci & Tech | Real-time mobile debris-flow disaster prevention and alert system |
JP2016122239A (en) * | 2014-12-24 | 2016-07-07 | エー・シー・エス株式会社 | Sediment disaster prediction system |
WO2017047061A1 (en) * | 2015-09-14 | 2017-03-23 | 日本電気株式会社 | Disaster prediction system, moisture prediction device, disaster prediction method, and program recording medium |
Family Cites Families (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP3656852B1 (en) * | 2004-07-22 | 2005-06-08 | 有限会社山口ティー・エル・オー | Disaster prevention business plan support method and system |
-
2017
- 2017-10-10 JP JP2017196948A patent/JP6941319B2/en active Active
-
2018
- 2018-10-05 WO PCT/JP2018/037473 patent/WO2019073937A1/en active Application Filing
- 2018-10-09 TW TW107135611A patent/TWI802599B/en active
Patent Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
TW200629183A (en) * | 2005-02-15 | 2006-08-16 | Univ Nat Pingtung Sci & Tech | Real-time mobile debris-flow disaster prevention and alert system |
JP2016122239A (en) * | 2014-12-24 | 2016-07-07 | エー・シー・エス株式会社 | Sediment disaster prediction system |
WO2017047061A1 (en) * | 2015-09-14 | 2017-03-23 | 日本電気株式会社 | Disaster prediction system, moisture prediction device, disaster prediction method, and program recording medium |
Also Published As
Publication number | Publication date |
---|---|
JP2019070961A (en) | 2019-05-09 |
WO2019073937A1 (en) | 2019-04-18 |
TW201928400A (en) | 2019-07-16 |
JP6941319B2 (en) | 2021-09-29 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
TWI802599B (en) | Risk assessment system and risk assessment program | |
JP6954425B2 (en) | Disaster prediction method, disaster prediction system, and disaster prediction program | |
KR101843007B1 (en) | Wireless sensor network measurring system and method for forcasting landslide | |
JP2020060078A (en) | System for estimating time landslide occurs | |
JP5875669B1 (en) | Earth and sand disaster prediction system | |
Yucel et al. | Evaluating a mesoscale atmosphere model and a satellite-based algorithm in estimating extreme rainfall events in northwestern Turkey | |
JP5731700B1 (en) | Sediment disaster prediction system based on water level prediction | |
JP2022047348A (en) | System for estimating occurrence possibility of landslide disaster at specific point | |
Ramon et al. | Kinetic energy estimation by rainfall intensity and its usefulness in predicting hydrosedimentological variables in a small rural catchment in southern Brazil | |
Lin et al. | Evaluation of soil erosion risk for watershed management in Shenmu watershed, central Taiwan using USLE model parameters | |
Yusof et al. | Use of statistical distribution for drought analysis | |
Sadeghi et al. | Conformity of MUSLE estimates and erosion plot data for storm-wise sediment yield estimation | |
JP6583529B2 (en) | Information processing apparatus, parameter correction method, and program | |
Marzolff et al. | Short to medium-term gully development: human activity and gully erosion variability in selected Spanish gully catchments | |
Klug et al. | A multi-purpose weather forecast model for the Mondsee Catchment | |
Jaiswal et al. | Rainfall-based temporal probability for landslide initiation along transportation routes in Southern India | |
TW201713925A (en) | Prediction device, prediction system, prediction method, and program recording medium | |
Caseri et al. | A space-time geostatistical approach for ensemble rainfall nowcasting | |
Bennett et al. | Selecting reference streamflow forecasts to demonstrate the performance of NWP-forced streamflow forecasts | |
Majlingová | Automated procedure to assess the susceptibility of forest to fire. | |
Kim et al. | Development and Application of GIS-based Information System of Landslide Hazard Map Induced by Earthquakes and Rainfall in Korea. | |
Abril et al. | Standardized Runoff Index (SRI) | |
Lee et al. | Risk-based analysis of monitoring time intervals for landslide prevention | |
Javelle et al. | Improving flash flood forecasting and warning capabilities. | |
Lu et al. | Rainfall and rainfall erosivity time series analysis of a small semi-arid watershed of the American Southwest |