JP2008050903A - Flood prediction method and flood prediction system - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To predict the outflow amount of water quickly by a little computer resource. <P>SOLUTION: A flood prediction system comprises a water-level gauge 1 and a server device 2. A river which is a target of evaluation is divided into a plurality of segments by a predetermined marker using a direction perpendicular to a center line of the river as division lines. The server device 2 comprises a catchment area extraction means for extracting a predetermined area centering on the river as the catchment area for each segment, a means for obtaining a short-lasting rainfall prediction value online, a precipitation amount prediction means for predicting precipitation at each catchment area based on the short-lasting rainfall prediction value, and an outflow amount prediction means for predicting the outflow amount of water flowing out of the catchment area to the river based on the precipitation predicted at each catchment area. <P>COPYRIGHT: (C)2008,JPO&INPIT

Description

  The present invention relates to a flood prediction method and a flood prediction system suitable for flood prediction of so-called small and medium rivers.

Although the term medium and small rivers does not have a strict definition, it usually refers to rivers with a catchment area of about 800 km ² or less, and larger rivers are larger rivers. Conventional flood forecasting technology has been used mainly for the purpose of river improvement planning for large river dams and dikes, and the typical procedure is a distributed flood runoff analysis method (for example, non-patent literature). 1, refer to Non-Patent Document 2).

  In this flood runoff analysis method, (I) watershed is determined based on elevation data, (II) watershed is determined with watershed as a boundary, (III) the inside of the watershed is divided into meshes of about 1 km, and (IV) due to rainfall Calculate the water collection for each mesh and also calculate the runoff between meshes based on the difference in elevation. (V) Calculate the runoff to the river, and (VI) Calculate the advection of the river channel after running into the river. It went through a huge process of going and predicting the water level.

Recently, for the purpose of creating a hazard map, a flooded area evaluation method has been proposed in which how the vicinity of a river is flooded when a river breaks (see Non-Patent Document 3, for example).
As a flood information providing means, a system for displaying on a screen in response to a request from an operator such as a computer or a portable terminal has been proposed (for example, see Non-Patent Document 4).

Megumi Mihori et al., “Application of Distributed Runoff Model Utilizing GIS to Ebi River Basin”, 2003, Hosei University Center for Computational Science, Internet, <http://www.cms.k.hosei.ac.jp/ pdf_vol16_28.pdf> Shingo Masuda et al., “Flood Runoff Analysis Using Distributed Runoff Model in Sekigawa Basin”, 2001, Nagaoka University of Technology, Internet, <http://globe.nagaokaut.ac.jp/yoshisyu/2001/kankyo/ taiki / kan02108.pdf> Hideto Kadozawa et al., “Prediction of flood inundation area in small and medium rivers: Case analysis of Horobetsu district in Noboribetsu”, Muroran Institute of Technology, <http://www.muroran-it.ac.jp/cea/ jabee / thesis2005 / 09.pdf> "Prefectural River Information System", 2003, River Information Center, <http://www.river.or.jp/pref/pamphlet.pdf>

The flood and runoff analysis methods disclosed in Non-Patent Documents 1 and 2 usually require detailed conditions such as detailed elevation along rivers and river cross-section data, so large-scale calculations are unavoidable. Therefore, there was a problem that it was not suitable for flood prediction of small and medium rivers where the time from precipitation to flood occurrence was short.
In addition, the flooded area evaluation method disclosed in Non-Patent Document 3 is a technique characterized in that the flooded area is evaluated based on highly accurate altitude data, and provides a simple and real-time water level prediction technique. It was not a thing.
Further, the river information system disclosed in Non-Patent Document 4 has no mechanism for quickly and automatically transmitting information to a preset notification destination by determining a water level threshold.

The present invention has been made in order to solve the above-mentioned problems, and in order to facilitate application to small and medium rivers, a flood that can quickly predict the amount of water runoff and the water level of a river with few computer resources. An object is to provide a prediction method and a flood prediction system.
In addition, the present invention provides a flood prediction method and a flood prediction system that can notify relevant parties immediately in order to promote actions to avoid and prepare for flood damage when the predicted water level exceeds the dangerous water level. For the purpose.

The present invention relates to a flood prediction method for predicting a flood in a computer having a CPU and a storage device. The river basin of an evaluation target is set in a direction perpendicular to the center line of the river based on map information. A dividing step for dividing the data into a plurality of segments with a predetermined index as a dividing line, a watershed extraction step for extracting a predetermined area centered on the river for each segment as a watershed, and an external input A precipitation prediction step for predicting precipitation for each catchment area based on a short-term predicted rainfall value, and a runoff amount of water flowing from the catchment area to the river based on the precipitation forecast for each catchment area. An outflow amount prediction step for predicting each catchment area is executed by the CPU according to a program stored in the storage device.
One of the characteristics of floods in small and medium rivers is that the water level rises within a short time due to torrential rain, and it is important to promptly predict the water level and use the information. The present invention provides a simple evaluation method that is easy to automate with a small programming scale when performing the water level prediction. The watershed is determined by a buffering operation along the river, and the prediction of precipitation falling there is obtained. It is characterized by predicting the outflow amount based on the amount.

Further, in one configuration example of the flood prediction method of the present invention, the watershed extraction step includes a typification table that stores in advance the landform and land use form and the distance reference value Lref for extracting the watershed in association with each other. And a reference value determination step for determining the reference value Lref for each segment from the segment and its nearby terrain and land use form, and when the river width in the segment is W, the watershed is extracted for this segment. A distance determination step for determining the distance L to be determined for each segment as L = Lref + W / 2, and an extraction step for extracting, for each segment, a region within the distance of L on both sides from the river center line as the catchment region Is included.
Moreover, in one structural example of the flood prediction method of this invention, the said river contains the sewer for rainwater.
In one configuration example of the flood prediction method of the present invention, the runoff prediction step predicts the runoff of water for each catchment area using a tank model based on precipitation predicted for each catchment area. It is what.
Further, one configuration example of the flood prediction method of the present invention further includes a water level prediction step of predicting the water level H (t) at the water level observation point at time t.
Moreover, one structural example of the flood prediction method of the present invention further includes a determination step of determining whether or not the water level prediction value obtained in the water level prediction step is equal to or higher than a threshold value to be notified, and the water level prediction value is equal to or higher than the threshold value. When the determination is made, the predetermined notification destination is notified that the water level of the river may exceed the threshold value.

Further, the flood prediction system of the present invention is installed at a water level observation point of a river to be evaluated, and a water level meter for measuring the water level of the river and the river basin with respect to the center line of the river based on map information. A catchment area extracting means for dividing the data into a plurality of segments with a predetermined index as a dividing line and extracting a predetermined area centered on the river as a catchment area for each segment; Means for obtaining rainfall prediction values online; Precipitation prediction means for predicting precipitation for each catchment area based on the short-term rainfall forecast value; and a catchment area based on precipitation predicted for each catchment area And an outflow amount predicting means for predicting the outflow amount of water flowing out into the river for each catchment area.
In addition, one configuration example of the flood prediction system of the present invention further includes water level prediction means for predicting the water level H (t) at the water level observation point at time t.
In addition, one configuration example of the flood prediction system according to the present invention further includes a determination unit that determines whether or not the water level prediction value obtained by the water level prediction unit is equal to or higher than a threshold value to be notified, and the water level prediction value is equal to or higher than the threshold value. A transmission means for notifying a predetermined notification destination that the water level of the river may exceed the threshold value when determined.

  According to the present invention, since it is possible to predict the outflow amount of water very easily, it is possible to mount at low cost. Moreover, in this invention, since it can implement | achieve by simple calculation, the outflow amount can be estimated in real time. Therefore, according to the present invention, it is possible to quickly predict the outflow amount of water with a small amount of computer resources, so that it can be easily applied to about 900 small and medium rivers existing in Japan.

  Further, according to the present invention, the water level of a river can be quickly predicted with a few computer resources, and therefore, it can be easily applied to about 900 small and medium rivers existing in Japan.

  Furthermore, according to the present invention, it is possible to provide quick and accurate information to related persons such as managers of small and medium rivers and on-site staffs who have a short time from rainfall to occurrence of flood. It is very useful because it can give the time necessary for preparatory actions such as evacuation. In the present invention, if the information notification destination is a mobile phone, it is possible to easily grasp whether or not the other party has received the information.

  Hereinafter, the embodiment of the present invention will be described first from the water extraction region. In the conventional determination of watersheds, watersheds were determined based on elevation data and used as watersheds. However, floods in small and medium rivers have short river lengths, and the time from rainfall to flooding is short, so a wide range of watersheds are evaluated. It is not always good to target. The tank model is often used for water runoff calculations, but if the area to be evaluated is large, the contribution of indirect runoff and groundwater runoff tends to be relatively large when runoff calculations are made, and it is directly related to floods. This is because direct outflow tends to be underestimated. Especially in the case of floods in small and medium rivers, the time from the rain to the occurrence of the flood is short, so it is simpler to build a model around direct runoff near the river and capture the essence of the phenomenon.

  Therefore, this embodiment has a first feature that, instead of evaluating the catchment area with a diversion basin, an area extracted at an appropriate distance L from the river is used as the catchment area. FIG. 1 is a diagram schematically showing a process of extracting a catchment area around a river. In FIG. 1, 100 is a river, 101 is a sea, and 102 is an extracted water collection area.

The extraction process of the catchment area 102 can be easily performed by using a map information processing function that is generally installed in a general-purpose GIS (geographic information system). In the case of the present embodiment, a region within a certain distance on each side from the center line of the river 100 may be extracted as the catchment region 102. At this time, the distance L from the center line of the river 100 is represented by the following equation, where W is the width of the river.
L = Lref + W / 2 (1)
Here, Lref is a reference value that is categorized according to terrain and land use and set in advance. It is useful to register the river width W in advance for each river segment as an attribute value of the river center line.

  In addition, when the area | region extracted by the distance L overlaps, or it overlaps with the area | region extracted from another nearby river, it is good to divide the overlap part equally. In addition, when the extraction region protrudes outside the basin range in the vicinity of the ridge or the like, it is also preferable to delete the protruding region to improve the accuracy.

  In general, rainfall in mountainous areas has a property that rainwater tends to flow from a wide range to a river in a valley from a wide range due to a steep slope. On the other hand, in the rainfall in the plains, the direct flow is only from the vicinity of the river at the most because the water collecting action due to the altitude difference is weaker than in the mountainous area. These are phenomena due to elevation and topography. On the other hand, with regard to land use, for example, paddy fields in the plains have low penetration of rainwater underground, and rainwater tends to flow into rivers. In addition, rainwater tends to flow into rivers even in densely populated areas covered with asphalt or buildings. However, in fields and orchards, rainwater tends to penetrate underground and the rate of flowing into rivers is small.

  In the present embodiment, the rainwater outflow characteristics described above are categorized, a reference value Lref corresponding to the landform or land use form is set in advance, and the reference value Lref for each landform or land use form is set in the typology table. It is characterized by keeping it in a form. It is useful to use the national land numerical information provided by the Ministry of Land, Infrastructure, Transport and Tourism (see http://w3land.mlit.go.jp/ksj/) to create a typographical table. National land numerical information on topography, soil quality, land usage, etc. includes elevation / gradient mesh, land use classification mesh, land use mesh, etc. The creation process of the type table can be facilitated. However, since the items and numerical values themselves in the categorized table have a character that can be subdivided or changed as much as possible, the present embodiment does not uniquely limit the categorized table.

  Usually, when performing flood prediction of rivers, unless the river is very small, the river is divided into segments in order to take into account the delay of river flow. A representative reference value Lref in the divided segment is determined. Specifically, a rough region is extracted from the river at a distance greater than or equal to the maximum value of the reference value Lref registered in the typification table, and for this region, for example, a standard third-order mesh (1 km mesh) using the national land numerical information. ) The distance L is evaluated every time, and the average value is obtained. Alternatively, only a standard tertiary mesh adjacent to the center of the river segment may be considered. The present embodiment is characterized in that rules for evaluation are defined, and is not limited to these specific methods.

  Dividing the river to be evaluated to obtain individual catchment areas includes dividing the catchment area at the branch point of the main river and tributaries, the reciprocal of the average flow velocity when the river is increased due to rainfall, That is, there is a method of dividing the catchment area based on the distance of rainwater movement per hour. Dividing the catchment area should be done with a time granularity less than that, as an indicator, as the site hopes to allow about 3 hours for the forecast reading time. For example, if the average flow velocity at the time of water increase is about 1 m / sec, the travel distance for 3 hours of rainwater will be 1 m / sec × 3600 × 3 = about 10 km. Necessary. Therefore, the river is divided using the distance along the river or the arrival time as an index.

  Next, it is useful to use the short-term rainfall forecast value announced by the Japan Meteorological Agency for the forecasted precipitation amount of each divided catchment area. Since the short-term rainfall forecast value is given as a mesh value, the precipitation in the catchment area can be calculated by taking the logical sum of the short-term rain forecast value and the catchment area. Alternatively, since the unit of the catchment area is relatively fine, the precipitation distribution is assumed to be uniform, and the precipitation at the catchment area is simply multiplied by the precipitation at the representative point in the catchment area and the area of the catchment area. May be calculated.

  Since this embodiment is intended to calculate the outflow of water with an emphasis on the direct flow flowing from the vicinity of the river, it is preferable to evaluate the inflow of rainwater near the river to the sewage. Especially in urban areas where the ratio of non-permeable covered ground such as asphalt is high, rainwater flows into the river through the sewer channel without much penetration into the underground, so the sewage network should be regarded as a river and extract the catchment area. Is preferred.

  There are various methods for calculating the amount of runoff in each divided catchment area, but in this embodiment, a well-known tank model method is used as a preferable calculation method. The tank model method models the water outflow mechanism by combining several storage tanks. As a tank model to be used, a two-tank model may be used. However, as a result of investigations by the inventors, a calculation result with higher accuracy was obtained with the three-tank model. Use.

Next, the river water level is evaluated at a predetermined observation point. In the present embodiment, the following formulas (2) and (3) are used as one calculation method for predicting the water level H (t) of a river at a certain time t.
H (t) = H0 + ΔH (t) (2)

  Here, ΔH (t) is a predicted amount of increase in river level due to rainfall at time t, α is a predetermined fitting parameter for converting water inflow into river level, and ΔT (i) is the i th The average flow delay time from the catchment area to the water level observation point (the time required for rainwater to reach the water level observation point from the catchment area), V (i, t−ΔT (i)) is the time (t−ΔT ( In i)), the amount of water flowing out from the i-th catchment area into the river, H0, is a predetermined reference water level.

  The calculation method using the equations (2) and (3) uses the minimum water level of the river observed during the dry season as H0, and the water level of the river caused by precipitation flowing into the river in a relatively short time By adding the increase amount to the reference water level H0 as ΔH (t), the water level H (t) at time t is obtained. In this calculation method, elements that have only a uniform effect over a long period, such as runoff of groundwater with a long time constant and infiltration into rivers, are regarded as elements constituting the reference water level H0 and modeling is omitted. It is a feature.

As another calculation method of the water level, there is a method of using the last observed water level instead of using a fixed value for the reference water level. In this case, the water level H (t) is calculated by the above equation (3) and the following equations (4) to (6).
H (t) = Hobs (t ′) + β × ΔH ′ (t) (4)
ΔH ′ (t) = ΔH (t) −ΔH (t ′) (5)

  Here, ΔH ′ (t) is a predicted amount of water level fluctuation of the river from time t ′ to time t, ΔH (t ′) is a predicted amount of water level increase of the river derived from rainfall at time t ′, and Hobs ( t ′) is the river water level observed at the water level observation point at time t ′, and β is a predetermined fitting parameter.

  In the calculation method using the equations (3) to (6), since the observed water level fluctuates, the fluctuation prediction amount of the water level change is added to the observed water level Hobs (t ′) as ΔH ′ (t). The water level H (t) of t is obtained. In this calculation method, even if a sudden event such as a weir adjustment or water discharge occurs, the element of this event is included in the water level Hobs (t ′), so the time (t−t ′) from time t ′ After the lapse of time, the event is reflected in the prediction, and there is an advantage that the prediction accuracy of the water level becomes high.

  Hereinafter, this embodiment will be described in more detail. In the present embodiment, it may be possible to make the computer calculate the water level independently and display the prediction result on the screen, or to be able to view the prediction result on the network using the Internet. However, more preferably, the system configuration is such that the water level gauge and the server are linked to each other, and the water level to be observed at regular intervals is handed over to the server online. It is preferable to construct a system that simultaneously evaluates the observed water level and the predicted water level.

  Furthermore, in this embodiment, when the predicted water level exceeds a preset threshold value to be notified, it is automatically sent to a preset notification destination such as a basin manager or a department in charge of the field such as a fire department. It preferably has a function of transmitting information. In particular, as a notification destination, a mobile phone is preferable as a means of transmitting information regardless of working hours, etc., and when displaying the observed water level and predicted water level in graphics, the error can be grasped intuitively, so the risk level Is easy to understand and convenient.

  FIG. 2 is a block diagram showing a configuration example of the flood prediction system according to the embodiment of the present invention. 1 is a water level meter that is installed at a predetermined water level observation point and measures the water level of the river, 2 is a server device that predicts the water level of the river and determines whether the predicted water level exceeds a threshold to be notified, and 3 is a network 4 The server device of the Japan Meteorological Agency connected to the server device 2 through 5, 5 is an input device for inputting parameters and the like to the server device 2, 6 is a display device for displaying the prediction result of the server device 2, When it is determined that the water level is equal to or higher than the threshold value, the transmission device notifies a predetermined notification destination that the river water level may exceed the threshold value.

  FIG. 3 is a block diagram illustrating a configuration example of the server device 2. The server device 2 includes a catchment area extraction unit 20, a precipitation amount prediction unit 21, a runoff amount prediction unit 22, a water level prediction unit 23, a determination unit 24, and a storage unit 25.

  FIG. 4 is a flowchart showing the operation of the flood prediction system of the present embodiment. First, the catchment area extraction means 20 of the server device 2 divides the river basin to be evaluated into segments based on map data registered in advance (step S100 in FIG. 4). In this embodiment, the time required for the prediction of the water level is 3 hours, the travel distance of rainwater for 3 hours is 5 to 10 km, and the river basin of the evaluation target is 5 to 10 km along the river center line. Divide by degree. Here, the river basin is divided into n (n is an integer of 2 or more), and the divided n segments are denoted as RV (1) to RV (n).

  Subsequently, the catchment area extraction means 20 extracts a catchment area for each segment RV (1) to RV (n) of the divided river (step S101 in FIG. 4). In this Embodiment, when calculating | requiring the distance L for extracting a catchment area for every segment RV (1) -RV (n), the land use mesh of the national land numerical information given with a standard tertiary mesh is used.

  The land use mesh of the national land information provided by the Ministry of Land, Infrastructure, Transport and Tourism includes “field”, “field”, “orchard”, “other tree field”, “forest”, “wilderness”, “building land A” “Building site B”, “Mainland traffic site”, “Other sites”, “Lakes and marshes”, “Riverland A”, “Riverland B”, “Beach”, “Unknown”, etc. Is posted. The designer of the flood prediction system creates a classification table of Table 1 using these pieces of information, and registers it in the storage means 25 of the server device 2 in advance. As shown in Table 1, the typification table stores landforms, land usage forms, and reference values Lref in association with each other.

  In addition, “mountain area / forest, etc.” of landforms and land use forms registered in the typology table shall include “forest” and “wilderness” in the land use mesh classification, and “paddy field” in the typology table. Is equivalent to “field” in the land use mesh classification, and “field / orchard” in the classification table is “field”, “orchard” and “other tree fields” in the land use mesh classification. The “urban area” in the classification table includes “building land A”, “building land B”, “main land”, and “other land” in the classification of the land use mesh.

  FIG. 5 is a flowchart showing the operation of the catchment area extraction means 20. The catchment area extraction means 20 first extracts a rough area including the catchment area at a distance equal to or greater than the maximum value of the reference value Lref as a first extraction process by referring to the typification table registered in the storage means 25. (Step S200 in FIG. 5). FIG. 6 is a diagram for explaining the first extraction process of the catchment area extraction means 20. In the example of FIG. 6, the width of the river in the segment RV (i) is W (i), and the area AR (i) within the distance of W (i) +2 km on both sides from the river center line C is roughly extracted. To do. The catchment area extraction means 20 performs such area extraction for each of the segments RV (1) to RV (n). The river width W is registered in advance in the storage means 25 for each segment.

  Subsequently, the watershed extraction means 20 refers to the land use mesh of the corresponding area for the extracted area AR (i), and determines the area for each item of landform and land use form registered in the typification table. Is calculated (step S201 in FIG. 5). The catchment area extraction means 20 performs such an area calculation for each of the segments RV (1) to RV (n).

  And the catchment area extraction means 20 specifies the largest thing among the areas calculated for every item of the topography and land use form about area | region AR (i), The reference value Lref of the item where the area became the maximum is obtained. The representative value Lref (i) of the area AR (i) is determined (step S202 in FIG. 5). The catchment area extraction means 20 determines such a reference value Lref (i) for each of the segments RV (1) to RV (n). Thus, the watershed extraction means 20 determines the reference values Lref (1) to Lref (n) for each of the segments RV (1) to RV (n).

  The catchment area extraction means 20 refers to each reference value Lref for each item of landform and land use form registered in the typification table by multiplying each area ratio calculated for each item. An effective reference value Lref (i) may be calculated by averaging the values Lref.

Next, the catchment area extraction means 20 determines the distance L (i) for extracting the catchment area for the segment RV (i) as shown in the following equation (step S203 in FIG. 5).
L (i) = Lref (i) + W (i) / 2 (7)
The catchment area extraction unit 20 determines such a distance L (i) for each of the segments RV (1) to RV (n).

  And the catchment area extraction means 20 extracts the area | region which exists in the distance of L (i) on both sides from the river centerline C about a segment RV (i) as a catchment area, respectively (step S204 of FIG. 5). As described above, this watershed extraction process can be realized by using the map information processing function installed in a general-purpose GIS. The catchment area extraction means 20 performs such catchment area extraction for each of the segments RV (1) to RV (n).

  Finally, the catchment area extraction means 20 calculates the area S (i) for each catchment area extracted for each of the segments RV (1) to RV (n) (step S205 in FIG. 5). Above, the process (step S101) of the catchment area extraction means 20 is complete | finished.

  Next, the precipitation predicting means 21 predicts the precipitation in each catchment area extracted by the catchment area extracting means 20 (step S102 in FIG. 4). The precipitation predicting means 21 obtains a point near the center in the segments RV (1) to RV (n) divided by the catchment area extracting means 20 in order to predict precipitation, and performs short-term rainfall prediction including that point. The coordinate value of the mesh is obtained in advance.

  Short-term rainfall forecast values are announced every 30 minutes by the Japan Meteorological Agency, and forecasts are made up to 6 hours ahead using 1-hour values. The resolution of the short-term rainfall forecast value is about 1 km. The precipitation prediction means 21 fetches this prediction value from the server device 3 of the Japan Meteorological Agency and stores it in the storage means 25 every time a short-term rainfall prediction value is announced.

  Then, the precipitation prediction means 21 uses the mesh coordinate values determined in advance from the short-term rainfall prediction data stored in the storage means 25, and the time of the mesh including the central point of the segment RV (i). The rainfall amount at t is extracted, and the rainfall amount R (t) of the catchment area i is calculated by multiplying the rainfall amount by the area S (i) of the catchment area of the segment RV (i). The precipitation amount prediction unit 21 performs such precipitation prediction for each of the segments RV (1) to RV (n). Above, the process (step S102) of the precipitation prediction means 21 is complete | finished. The time t here means a time earlier than the present time. Further, as described above, since the short-term rainfall predicted value is provided up to the predicted value of 6 hours ahead, the precipitation is predicted from the current time to, for example, 6 hours ahead.

  Next, runoff is calculated in each catchment area. The runoff amount prediction means 22 predicts the runoff amount V (t + Δt) of water flowing into the river from the catchment area of the segment RV (i) at time t + Δt using the three-tank model with the precipitation R (t) as an input value. (Step S103 in FIG. 4). A three-tank model used in this embodiment is shown in FIG.

Moreover, the outflow amount prediction means 22 uses the following formula as a recurrence formula.
T1 (t + Δt) = T1 (t) + R (t) −E1 (t) −E2 (t) −E4 (t)
... (8)
T2 (t + Δt) = T2 (t) + E2 (t) −E3 (t) −E5 (t) (9)
T3 (t + Δt) = T3 (t) + E4 (t) + E5 (t) −E6 (t) −E7 (t)
... (10)
V (t + Δt) = E1 (t) + E3 (t) + E6 (t) (11)
E1 (t) = a1 × T1 (t) × Δt (12)
E2 (t) = a2 × T1 (t) × Δt (13)
E3 (t) = a3 × T2 (t) × Δt (14)
E4 (t) = a4 × T1 (t) × Δt (15)
E5 (t) = a5 × T2 (t) × Δt (16)
E6 (t) = a6 × T3 (t) × Δt (17)
E7 (t) = a7 × T3 (t) × Δt (18)

  In the equations (8) to (18), T1 (t) is the storage amount of the tank TA1 at time t, T2 (t) is the storage amount of the tank TA2 at time t, and T3 (t) is the storage amount of the tank TA3 at time t. The storage amount, E1 (t) is the outflow amount that flows out directly from the tank TA1 to the river at time t through the drain, etc., E2 (t) is the outflow amount that flows out from the tank TA1 to the tank TA2 at time t, and E3 (t) is The amount of outflow flowing from the tank TA2 to the river at the time t through the surface of the ground, E4 (t) is the amount of outflow flowing out from the tank TA1 to the tank TA3 at the time t, and E5 (t) is the tank TA2 from the tank TA2 at the time t. The outflow amount flowing out to TA3, E6 (t), the outflow amount flowing out from the tank TA3 to the river through the intermediate layer about 1 m deep from the ground at time t, E7 t) is an outflow amount flowing out from the tank TA3 to the groundwater vein at time t, a1, a2, a3, a4, a5, a6, a7 are fitting parameters registered in advance in the storage means 25, and Δt is a minute calculation step. It's time.

Here, for the sake of simplicity, the process of outflow from groundwater to rivers with a long time constant is ignored, but the tank design can be modified in various ways. Or overflow above the threshold.
In this way, the outflow amount prediction means 22 calculates the outflow amount V (t + Δt) using the equations (8) to (18). The outflow amount prediction means 22 performs such outflow amount calculation for each of the segments RV (1) to RV (n). Above, the process (step S103) of the outflow amount prediction means 22 is completed. As described above, since the short-term rainfall predicted value is provided up to a predicted value of 6 hours ahead, the outflow amount is predicted from the current time to, for example, 6 hours ahead.

  Next, the water level prediction means 23 inputs the outflow amount V (t) calculated by RV (i) as V (i, t), and predicts the water level H (t) at the water level observation point at time t (FIG. 4 step S104). First, the water level prediction means 23 calculates the total value SV (t) of the outflow amount at the water level observation point at time t by assuming that the water flowing out to the river is an equal flow as follows.

  As described above, ΔT (i) is the average arrival delay time from the catchment area of the segment RV (i) to the water level observation point, and is previously registered in the storage means 25 for each of the segments RV (1) to RV (n). ing.

And the water level prediction means 23 converts the total value SV (t) of the outflow amount into the water level H (t) at the water level observation point at time t by the following equation.
H (t) = H0 + ΔH (t) (20)
ΔH (t) = α × SV (t) (21)
α is a fitting parameter registered in advance in the storage means 25, and H0 is a predetermined reference water level.

Fitting parameters such as ΔT (i), α, a1 to a7 that minimize the error by comparing the water level value calculated by the prediction formulas of the equations (8) to (21) with a sufficient amount of actual observation data And is registered in advance in the storage means 25 of the server device 2. Thereafter, the server device 2 performs water level prediction using the fitting parameters registered in the storage unit 25. As the short-term rainfall forecast value announced by the Japan Meteorological Agency, the current state, the value up to 6 hours ahead is announced, so the water level prediction of this embodiment is also possible up to 6 hours ahead. Above, the process (step S104) of the water level estimation means 23 is complete | finished.
Note that the water level may be predicted using Equations (3) to (6) instead of Equations (19) to (21).

  Next, the determination unit 24 determines whether or not the water level prediction value calculated by the water level prediction unit 23 is equal to or higher than a preset threshold value to be notified (step S105 in FIG. 4), and if the water level prediction value is lower than the threshold value, Return to step S102. The threshold value may include, for example, a dangerous water level defined by the flood control law, a warning water level, a designated water level, and the like. However, since these are not always clearly specified in small and medium rivers, the threshold may be arbitrarily determined by the judgment of an administrator or an authorized person. There may be a plurality of threshold values. The precipitation amount predicting unit 21, the runoff amount predicting unit 22, the water level predicting unit 23, and the determining unit 24 repeat the processes of steps S102 to S105 at regular intervals.

  When the determination unit 24 determines that the predicted water level is equal to or higher than the threshold value in step S105, the determination unit 24 notifies the predetermined notification destination that the water level of the river may exceed the threshold value (FIG. 4). Step S106). The transmitting device 7 uses a mobile phone having a number registered in advance as a notification destination, and notifies the mobile phone by e-mail or voice call. At this time, it is desirable to transmit the current water level measured by the water level gauge 1 and the predicted water level to the notification destination. This is because an authorized person who can issue a flood warning usually issues a warning based on both the measurement data and the forecast data, so the current water level measurement is also required.

  As described above, according to the present embodiment, the outflow amount and the water level can be predicted extremely easily, and therefore can be implemented at a low cost. Moreover, according to this Embodiment, since it can implement | achieve by simple calculation, an outflow amount and a water level can be estimated in real time. Furthermore, the flood prediction system according to the present embodiment in cooperation with the water level gauge can provide quick and accurate information to managers and field personnel of small and medium rivers whose time from rainfall to flood occurrence is short. Therefore, it can give time necessary for preparatory actions such as countermeasures against floods and evacuation, which is extremely useful.

  Next, the effect of this embodiment will be described using data. FIG. 8 shows the result of predicting the water level by the flood prediction system of the present embodiment by dividing the river of less than about 30 km into four with the earthenware river in Kagawa Prefecture as the evaluation target. In the example of FIG. 8, instead of using short-term rainfall prediction data including an error, it is a result of optimizing parameters using an observation value (AMeDAS data) of precipitation as an input value, but drought as the reference water level H0. When a fixed value of 1.57m was used, the correlation between the predicted water level and the observed water level was R = 0.84 and standard deviation = 0.13m for one year of one-hour value data. was gotten. This fact indicates that the water collection process and the water level prediction model of the present embodiment are appropriate in the case of flood prediction of small and medium rivers.

  In addition, when the water level observation value Hobs is used as the reference water level, the parameter is optimized using the AMeDAS observation value after 6 hours in order to simulate the prediction after 6 hours, as shown in FIG. The correlation between the predicted water level and the observed water level was R = 0.97 and the standard deviation = 0.05 m for one year of 1 hour value data, and very good results were obtained. This shows that the error included in the simplified model in the present embodiment is absorbed by the observation value of the water level, and it is only possible to consider the amount of water collected in the vicinity of the river for the prediction about 6 hours ahead.

  The server device 2 according to the present embodiment can be realized by a computer having a CPU, a storage device, and an external interface, and a program for controlling these hardware resources. In such a computer, a program for realizing the flood prediction system of the present invention is provided in a state of being recorded on a recording medium such as a flexible disk, a CD-ROM, a DVD-ROM, or a memory card. The CPU writes the program read from the recording medium into the storage device, and executes the above-described processing according to the program.

  The present invention can be applied to flood prediction for small and medium rivers.

It is the figure which showed typically the process which extracts the catchment area around the river. It is a block diagram which shows the structural example of the flood prediction system which concerns on embodiment of this invention. It is a block diagram which shows the structural example of the server apparatus in the flood prediction system of embodiment of this invention. It is a flowchart which shows operation | movement of the flood prediction system of embodiment of this invention. It is a flowchart which shows operation | movement of the catchment area extraction means in the server apparatus of FIG. It is a figure for demonstrating the 1st extraction process of the catchment area extraction means in the server apparatus of FIG. It is a figure which shows the 3 tank model which the outflow amount prediction means in the server apparatus of FIG. 3 uses. It is a figure which shows one example of the prediction water level and observed water level at the time of using a fixed reference water level in the flood prediction system of embodiment of this invention. It is a figure which shows an example of the prediction water level and observation water level at the time of using an observed value for a reference water level in the flood prediction system of embodiment of this invention.

Explanation of symbols

  DESCRIPTION OF SYMBOLS 1 ... Water level meter, 2, 3 ... Server apparatus, 4 ... Network, 5 ... Input device, 6 ... Display apparatus, 7 ... Transmission apparatus, 20 ... Catchment area extraction means, 21 ... Precipitation prediction means, 22 ... Runoff prediction Means, 23 ... Water level prediction means, 24 ... Determination means, 25 ... Storage means.

Claims (9)

A flood prediction method for predicting flood in a computer having a CPU and a storage device,
A division step of dividing the river basin of the evaluation target on the data based on the map information into a plurality of segments with a predetermined index with a direction perpendicular to the center line of the river as a dividing line;
A watershed extraction step for extracting a predetermined area around the river as a watershed for each segment;
A precipitation prediction step for predicting precipitation for each watershed based on short-term rainfall prediction values input from the outside;
An outflow amount prediction step for predicting, for each catchment area, an outflow amount of water flowing out from the catchment area to the river based on precipitation predicted for each catchment area, according to the program stored in the storage device; A flood prediction method characterized in that The flood prediction method according to claim 1,
The watershed extraction step includes
The reference value Lref is calculated from the typographical table that stores the terrain and land usage pattern and the reference value Lref of the distance for extracting the catchment area in association with each other, and the segment and the terrain and land usage pattern in the vicinity thereof. A reference value determination step for determining each segment;
When the river width in the segment is W, a distance determination step for determining the distance L for extracting the catchment area for this segment as L = Lref + W / 2 for each segment;
A flood prediction method comprising: an extraction step for extracting, for each of the segments, an area within a distance of L on both sides from a river center line as the catchment area. The flood prediction method according to claim 1,
The flood prediction method, wherein the river includes a sewer for rainwater. The flood prediction method according to claim 1,
The flood forecasting method, wherein the runoff forecasting step predicts the runoff of water for each catchment area using a tank model based on precipitation predicted for each catchment area. The flood prediction method according to claim 1,
Furthermore, the number of the segments is n (n is an integer of 2 or more), the predicted amount of increase in the water level of the river derived from rainfall at time t is ΔH (t), and the river derived from rainfall at time t ′ (t ′ <t) ΔH (t ′) is the predicted amount of increase in water level, ΔT (i) is the average delay time from the i-th (i is an integer of 1 to n) catchment area to the water level observation point, and time (t−ΔT ( In i)), the amount of water flowing into the river from the i th catchment area is V (i, t-ΔT (i)), the reference water level is H0, and the river level observed at the water level observation point at time t ′. Is Hobs (t ′), and the predetermined parameters are α and β, the water level H (t) of the water level observation point at time t is
H (t) = H0 + ΔH (t)

Or H (t) = Hobs (t ′) + β × (ΔH (t) −ΔH (t ′))

A flood forecasting method comprising a water level forecasting step for forecasting according to the above. The flood prediction method according to claim 5,
Further, a determination step for determining whether or not the water level prediction value obtained in the water level prediction step is a threshold value to be notified,
A flood prediction method comprising: a notification step of notifying a predetermined notification destination that there is a possibility that the water level of the river may exceed the threshold when the predicted water level is greater than or equal to the threshold. A water level meter installed at the water level observation point of the river to be evaluated and measuring the water level of the river;
Based on the map information, the river basin is divided on the data into a plurality of segments with a predetermined index, with the direction perpendicular to the river center line as the dividing line, and the river is centered for each segment. A catchment area extracting means for extracting a predetermined area as a catchment area;
A means of obtaining short-term rainfall forecasts online;
Precipitation prediction means for predicting precipitation for each watershed based on the short-term rainfall prediction value;
A flood prediction system comprising: an outflow amount predicting unit that predicts an outflow amount of water flowing out of a catchment area into the river based on a precipitation amount predicted for each catchment area. The flood prediction system according to claim 7,
Furthermore, the number of the segments is n (n is an integer of 2 or more), the predicted amount of increase in the water level of the river derived from rainfall at time t is ΔH (t), and the river derived from rainfall at time t ′ (t ′ <t) ΔH (t ′) is the predicted amount of increase in water level, ΔT (i) is the average delay time from the i-th (i is an integer of 1 to n) catchment area to the water level observation point, and time (t−ΔT ( In i)), the amount of water flowing out from the i th catchment area into the river is V (i, t−ΔT (i)), the reference water level is H0, and the water level observation point at time t ′ (t ′ <t). When the observed river water level is Hobs (t ') and the predetermined parameters are α and β, the water level H (t) at the water level observation point at time t is
H (t) = H0 + ΔH (t)

Or H (t) = Hobs (t ′) + β × (ΔH (t) −ΔH (t ′))

A flood forecasting system comprising a water level forecasting means for forecasting according to the above. The flood prediction system according to claim 8,
Further, a determination means for determining whether or not the water level prediction value obtained by the water level prediction means is greater than or equal to a threshold value to be notified
A flood prediction system comprising: a transmitting means for notifying a predetermined notification destination that the water level of the river may exceed the threshold when the predicted water level is determined to be equal to or greater than the threshold. .

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