JP2024080066A - Water level prediction device, rainfall amount estimation device, and water level prediction method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a water level prediction device, a rainfall amount estimation device, and a water level prediction method that predict water level changes of small-scale rivers with good accuracy.

SOLUTION: Provided is a water level prediction device 11 that predicts a predictive water level H of future at a prediction point of river by using a predictive rainfall amount X, geographical information G, and a river water level W at the prediction point. The water level prediction device comprises: a watershed extraction unit 5 that applies the geographical information G to the predictive rainfall amount X to extract a predictive watershed rainfall amount Xr in a watershed where rainfall flows into the prediction point; a first river model 4 whose internal state is determined by a plurality of state variables S; a water level acquisition unit 21 that acquires the river water level W at the prediction point; and an estimated rainfall amount computation unit 3 that estimates a rainfall amount flowing into the prediction point by using the river water level W. The first river model 4 calculates the predicted water level H in accordance with the computation result of the estimated rainfall amount computation unit 3.

SELECTED DRAWING: Figure 1

COPYRIGHT: (C)2024,JPO&INPIT

Description

The present invention relates to a water level prediction device, a precipitation estimation device, and a water level prediction method.

Many research institutes and companies have developed river water level forecasting methods to reduce flooding and landslides caused by rising river levels due to precipitation, etc. Most of these methods are aimed at large rivers (class 1 and class 2 rivers), and water level forecasting has rarely been done for small rivers that flow through mountainous areas or urban areas at the foot of mountains.

However, there are residential areas in the basins of small rivers as well, and floods still cause damage. For example, the two mudslides that struck the Suwa region of Nagano Prefecture in August and September 2021 both occurred from small streams less than 1m wide. The August mudslide claimed three precious lives, and the September mudslide damaged more than 60 houses. Given these circumstances, there is a need to predict water levels in mountainous areas and small rivers flowing at their foothills, and to provide highly accurate evacuation information.

The Japan Meteorological Agency provides precipitation measured by raincloud radar and forecast precipitation for the next two hours, dividing the country into 250m meshes. This is called high-resolution nowcasting. In addition, topographical information for the entire country can be obtained in 100m meshes from the Ministry of Land, Infrastructure, Transport and Tourism's internet server. Therefore, it is possible to use this information (precipitation and topographical information) to predict the water levels of small rivers.

As a method for predicting the water level of small rivers, for example, Non-Patent Document 1 discusses predicting the water level of small and medium-sized rivers using a rainfall-runoff-inundation (RRI) model. Analytical rainfall (precipitation in 1-km mesh units) calculated based on precipitation radar etc. is applied to the RRI model to predict water levels. Patent Document 1 also discloses a method for predicting the water level of small and medium-sized rivers by applying a runoff analysis model to precipitation radar information.

Kakinuma, T. and 8 others, "Research toward the development of a real-time water level forecasting system for floods in small and medium-sized rivers," River Technology Papers, Vol. 27, June 2021, pp. 105-110

JP 2019-045290 A

The precipitation radar used as input for water level predictions in these previous documents captures the state of rain clouds in the sky (around 2000m) and calculates precipitation. As a result, it may not be able to capture low-altitude rain clouds or localized heavy rain. Also, when the wind is strong, rain falls at an angle, so the precipitation observed on the ground is misaligned. These are corrected for in the analyzed precipitation, but localized heavy rain may still not be captured. There was an issue that if the precipitation amount input to the model was incorrect, the model's calculation results (predicted water levels) would also be inaccurate.

In light of this situation, the present invention aims to provide a water level prediction device, a precipitation estimation device, and a water level prediction method that can accurately predict water level changes in small rivers.

The water level prediction device of the present invention is a water level prediction device that predicts the future predicted water level at a prediction point of a river using predicted precipitation, which is the predicted future precipitation, topographical information, and the river water level at the prediction point, and includes a watershed extraction unit that applies the topographical information to the predicted precipitation to extract a watershed predicted precipitation in the watershed where precipitation flows into the prediction point, a first river model whose internal state is determined by a plurality of state variables, a water level acquisition unit that acquires the river water level at the prediction point, and an estimated precipitation calculation unit that estimates the watershed estimated precipitation flowing into the prediction point using the river water level, and the first river model calculates the predicted water level according to the calculation result of the estimated precipitation calculation unit.

The precipitation estimation device of the present invention is a precipitation estimation device that acquires the river water level at a water level prediction point and outputs a basin-estimated precipitation that fell in the basin of the river water level measurement point, and is characterized in that it comprises a second river model that outputs a model water level from the basin-estimated precipitation, and a difference calculation means that calculates the difference between the river water level and the model water level to calculate a difference water level, and the integration means repeats the calculation of the second river model so that the difference water level approaches 0.

The water level prediction method of the present invention is a water level prediction method that predicts a future predicted water level at a prediction point of a river using predicted precipitation, topographical information, and river water level, and is characterized by comprising a basin predicted precipitation extraction step of applying the topographical information to the predicted precipitation to extract a basin predicted precipitation in a basin where precipitation flows into the prediction point, a river water level acquisition step of acquiring the river water level at the prediction point, a basin estimated precipitation estimation step of estimating the basin estimated precipitation flowing into the prediction point from the river water level, and a predicted water level calculation step of calculating the predicted water level using the basin predicted precipitation and the basin estimated precipitation.

With the above configuration, the predicted precipitation, topographical information, and river water levels measured at the prediction point are input to obtain state variables for a river model with less error, making it possible to capture the effects of localized heavy rain. As a result, it is possible to accurately predict the water levels of small rivers, such as those flowing through mountainous areas.

The water level prediction device and water level prediction method of the present invention can also be used to calculate a soil precipitation index. For example, if a local government installs a water level prediction device to which the present invention is applied in a river where debris flows are a concern, the local government can provide residents in the river basin with more accurate evacuation advisory information than before.

FIG. 2 is a block diagram shown for explaining the configuration of a water level prediction device 11 according to the first embodiment. 2 is a diagram shown for explaining the configuration of a water level acquisition unit 21 of the water level prediction device 11 according to the first embodiment. FIG. 2 is a block diagram shown for explaining the configuration of an estimated precipitation amount calculation unit 3 of the water level prediction device 11 according to the first embodiment. FIG. 2 is a diagram shown for explaining the configuration of a watershed extraction unit 5 of the water level prediction device 11 according to the first embodiment. FIG. 2 is a diagram shown for explaining a first river model 4 of the water level prediction device 11 according to the first embodiment. FIG. FIG. 11 is a diagram shown for explaining a water level prediction method according to the second embodiment. FIG. 11 is a block diagram shown for explaining the configuration of a water level acquisition unit 22 according to a third embodiment. FIG. 11 is a block diagram shown for explaining the configuration of a water level prediction device 12 according to a fourth embodiment. FIG. 13 is a block diagram shown for explaining the configuration of a water level prediction device 13 according to a fifth embodiment. FIG. 13 is a block diagram for explaining the configuration of a precipitation estimation device 8 according to a sixth embodiment.

The following describes the form for carrying out the present invention (hereinafter, "embodiments"). The embodiments described below do not limit the invention according to the claims. Furthermore, not all of the elements and combinations thereof described in the embodiments are necessarily essential to the present invention. Furthermore, where explanations in the various embodiments overlap, explanations may be omitted.

[Embodiment 1]
FIG. 1 is a block diagram shown for explaining the configuration of a water level prediction device 11 according to the first embodiment. FIG. 2 is a diagram shown for explaining the configuration of a water level acquisition unit 21 of the water level prediction device 11 according to the first embodiment. FIG. 3 is a block diagram shown for explaining the configuration of an estimated precipitation amount calculation unit 3 of the water level prediction device 11 according to the first embodiment. FIG. 4 is a diagram shown for explaining the configuration of a drainage basin extraction unit 5 of the water level prediction device 11 according to the first embodiment. FIG. 5 is a diagram shown for explaining a first river model 4 of the water level prediction device 11 according to the first embodiment.

As shown in FIG. 1, the water level prediction device 11 comprises a water level acquisition unit 21, an estimated precipitation calculation unit 3, a first river model 4, a watershed extraction unit 5, and model parameters P, and inputs predicted precipitation X, which is the amount of precipitation in the future, and topographical information G, which is information such as the altitude and latitude and longitude around the prediction point, and outputs a predicted future water level H at the prediction point of the target river and a soil precipitation index D, which is an index indicating the increased risk of landslides. Here, predicted precipitation X refers to the amount of precipitation that is expected to fall in a certain region or a certain area. For example, information on predicted precipitation provided by the Japan Meteorological Agency can be used as the predicted precipitation X. Below, each element that constitutes the water level prediction device 11 will be explained.

[Water level acquisition section]
The water level acquisition unit 21 is installed at a location where the water level of the target river is predicted, and measures the river water level W, which is the water level at the location where the water level of the target river is predicted.

As shown in FIG. 2, the water level acquisition unit 21 in the first embodiment includes one water level measurement means 50. The water level measurement means 50 includes a water level sensor 51, a cable 52, a circuit box 53, and a transmitting antenna 54. The circuit box 53 and the transmitting antenna 54 are installed next to the target river, and the water level sensor 51 is installed underwater in the target river to measure the river water level W.

The water level sensor 51 includes a semiconductor pressure sensor and outputs an electrical signal that changes according to the river water level W. A cable 52 transmits this electrical signal to a circuit box 53. The circuit box 53 converts the electrical signal into a digital signal and wirelessly transmits it as the river water level W from a transmitting antenna 54. The wirelessly transmitted river water level W is received by a receiving device (not shown).

[Estimated precipitation calculation section]
As shown in FIG. 3, the estimated precipitation calculation unit 3 includes a second river model 31, a model parameter P, a difference calculation means 32, and an integration means 33.

The estimated precipitation calculation unit 3 uses the river water level W to calculate the basin estimated precipitation Er that is estimated to have fallen in the basin of the target river. This makes it possible to accurately grasp the amount of precipitation in the basin of the target river at that time. Furthermore, the state of the target river at that time can be accurately reflected in the first river model 4, which will be described later.

The second river model 31 includes a model parameter P, which is a parameter that does not change over time, and a state variable S, which represents the water level change at the prediction point and changes over time. The second river model 31 may have the same configuration as the first river model 4, which will be described later.

The difference calculation means 32 calculates the differential water level Dh, which is the difference between the model water level M, which is the output of the second river model 31, which changes from moment to moment, and the measured river water level W. The estimated basin precipitation Er can be calculated as the input to the second river model 31 when the differential water level Dh becomes zero. If the differential water level Dh does not become zero, the differential water level Dh is accumulated by the accumulation means 33, and the output of the second river model 31 is recalculated while feeding back the accumulation result to the second river model 31. This feedback and recalculation loop is repeated until the differential water level Dh approaches zero.

In this way, when the output of the second river model 31 coincides with the river water level W, the basin estimated precipitation Er reflects the amount of precipitation that fell in the basin of the target river. Also, the state variable S inside the second river model 31 reflects the state of the target river. In this way, the estimated precipitation calculation unit 3 uses the river water level W to determine and output the basin estimated precipitation Er and state variable S.

[Watershed extraction section]
The watershed extraction unit 5 receives predicted precipitation X in the future (for example, 5 minutes, 10 minutes, 15 minutes, 2 hours later) as input, extracts the precipitation in the target watershed, and outputs it as predicted watershed precipitation Xr.

The watershed extraction unit 5 uses the topographical information G as shown in FIG. 4 to identify the watershed into which precipitation flows into the prediction point 100, and extracts the watershed mesh 101. For example, in FIG. 4, the topographical information G identifies a ridge line 103 located upstream of the prediction point 100, and the mesh included in the triangle formed by the ridge line 103 and the prediction point 100 is extracted as the watershed mesh 101.

The watershed extraction unit 5 integrates the predicted precipitation X for the watershed mesh 101 and outputs it as the watershed predicted precipitation Xr. In this way, the predicted value of the total precipitation flowing into the prediction point 100 (watershed predicted precipitation Xr) is obtained.

[First river model]
Various "river models" have been proposed for predicting the water level of a target river from the amount of precipitation. In the following explanation, a case where the "series three-stage tank model" shown in Fig. 5 is applied as the first river model 4 will be explained as an example. It goes without saying that river models other than the "series three-stage tank model" can also be suitably applied as the first river model 4.

The "series three-stage tank model 41" is configured with three stages of tanks stacked vertically, with horizontal holes on the sides of each tank and holes at the bottom so that water can be drained from each.

Rainfall pours into the first tank on the top level, and the amount of precipitation (r) is used as the input for the three-tank model in series. The outflow from the side hole of the first tank reflects the water flowing out from the surface of the river. Similarly, the outflow from the side hole of the second tank corresponds to the seepage outflow from the river surface, and the outflow from the side hole of the third tank corresponds to groundwater.

The first river model 4 is composed of a model parameter P that does not change and a state variable S that changes with rainfall in the river basin. The state variable S is the water storage volume of three tanks (S1, S2, S3).

The model parameters P include the following 12 parameters (u, _a0 , _a1 , _a2 , _a3 , _b1 , _b2 , _b3 , _z0 , _z1 , _z2 , _z3 ).

u … River runoff (normal water level when there has been no rain for a long period of time)
_a0 , _a1 , _a2 , _a3 ...size of the side hole of each tank; _b1 , _b2 , _b3 ...size of the pilot hole of each tank; _z0 , _z1 , _z2 , _z3 ...height of the side hole provided in each tank

[River model calculation]
In the model calculation, first, horizontal hole outflow rates q ₀ , q ₁ , q ₂ , and q ₃ are calculated from the water storage volumes of the three tanks (S1, S2, and S3).

Next, the amount of water stored in each tank (S1, S2, S3) is updated.

The flow rate calculation unit 42 adds the side hole outflow rates q ₀ , q ₁ , q ₂ , and q ₃ to the specified outflow rate u to determine the predicted flow rate Q(t).

Finally, the water level conversion unit 43 calculates the predicted water level H(t) according to the following formula (4) using the predicted flow rate Q(t) calculated by formula (3) and coefficients a and b.

Here, equation (4) is a characteristic generally known as the H-Q curve, which approximates the relationship between the water level (predicted water level) H and the flow rate (predicted flow rate) Q with a function using coefficients a and b. (The coefficients a and b can be determined, for example, by the least squares method using past observation results.)

The soil precipitation index extraction unit 44 calculates the soil precipitation index D by adding the water volumes (S1, S2, S3) of each tank as shown in equation (5).

In the conventional technology, the soil precipitation index D published by the Japan Meteorological Agency had a problem in that the error in the soil precipitation index D was large in places where the accuracy of precipitation radar is low, such as mountainous areas. In contrast, the water level prediction device 11 of embodiment 1 obtains the water storage volume (S1, S2, S3) of each tank from the river water level W, which has the effect of making the soil precipitation index D highly reliable.

[Embodiment 2]
FIG. 6 is a diagram shown for explaining the water level prediction method according to the second embodiment.

As shown in FIG. 2, the water level prediction method is a method for predicting a future predicted water level H of a river at a prediction point using predicted precipitation X, topographical information G, and river water level W, and includes a basin predicted precipitation extraction step S1, a river water level acquisition step S2, a basin estimated precipitation estimation step S3, and a predicted water level calculation step S4. The water level prediction method can be suitably implemented using the water level prediction device 11 according to the first embodiment. The water level prediction method according to the second embodiment will be described below with reference to FIGS. 1 to 6.

The basin predicted precipitation extraction process S1 is a process of applying topographical information G to predicted precipitation X to extract basin predicted precipitation Xr. Specifically, it is a process of applying topographical information G to predicted precipitation X to extract, from predicted precipitation X, basin predicted precipitation Xr in a basin where precipitation flows into a predicted point of a river.

The river water level acquisition process S2 is a process of acquiring the river water level W at the prediction point. The river water level W can be acquired by a water level acquisition unit 21 (see FIG. 2) installed at the location where the water level of the target river is predicted.

The basin estimated precipitation estimation process S3 is a process of estimating the basin estimated precipitation Er, which is the amount of precipitation flowing from the river water level W to the prediction point. In the basin estimated precipitation estimation process S3, the differential water level Dh between the river water level W and the output of the second river model 31 is obtained and fed back to the input to the second river model 31 for updating. The state variable S of the second river model 31 when the output of the second river model 31 matches the river water level W, and the basin estimated precipitation Er, which is the input to the second river model 31, are output (see Figure 3).

The predicted water level calculation step S4 is a step of calculating the predicted water level H using the basin predicted precipitation Xr and the state variable S, which is the output of the basin estimated precipitation estimation step S3. The predicted water level H is calculated by applying the basin predicted precipitation Xr and the state variable S to the first river model 4.

[Embodiment 3]
FIG. 7 is a diagram shown for explaining the water level acquisition unit 22 included in the water level prediction device according to the third embodiment.

As shown in FIG. 7, the water level acquisition unit 22 included in the water level prediction device according to the third embodiment is composed of a plurality of water level measurement means 50, for example, three water level measurement means 50A-50C, and a water level filter 55. Each of the water level measurement means 50A-50C has a similar configuration to the water level measurement means 50 described in the first embodiment. The water level information wa-wc measured by the water level sensors 51A-51C provided in each water level measurement means 50 is transmitted by a transmitting antenna 54 (see FIG. 2) and received by a receiving device (not shown).

Multiple water level measurement means 50A-50C may be installed at the same location of the target river 500, or at different locations along the flow. Furthermore, when three or more water level measurement means 50 are installed at different locations along the flow, the distance between adjacent water level measurement means 50 does not need to be constant, and they may be installed at any distance.

The flow of a river can shift, or the water depth can change locally due to small-scale cliff collapses. The water level information wa-wc measured by the water level sensors 51A-51C indicates different values depending on the conditions of the installation location (water depth at the installation location, river width, etc.). Therefore, in this invention, multiple water level measurement means 50A-50C are provided, and the measurement values are comprehensively judged by the water level filter 55, making it possible to measure the correct river water level W.

The water level filter 55 comprises flow rate conversion means 551A-551C, a flow rate filter 552, and a water level conversion means 553. The flow rate conversion means 551A-551C convert the water level information wa-wc into flow rate information qa-qc that is independent of the installation location conditions. The conversion from water level information to flow rate information can be achieved, for example, by determining the river width and flow speed at the locations where the water level sensors 51A-51C are installed, and determining and applying the inverse function of the H-Q curve shown as equation (4).

The flow rate filter 552 obtains the predicted flow rate Q by removing abnormal values from the multiple flow rate information qa to qc. Finally, the water level conversion means 553 converts the predicted flow rate Q into the river water level W and outputs it.

The flow rate filter 552 can obtain the predicted flow rate Q, for example, by averaging multiple pieces of flow rate information qa to qc. This makes it possible to remove disturbances that change randomly depending on the installation locations of the water level sensors 51A to 51C, and obtain a more accurate river water level W.

The flow rate filter 552 may also compare multiple pieces of flow rate information qa-qc, remove any flow rate information that deviates by more than a predetermined value, and then average the results to determine the predicted flow rate Q. Alternatively, the maximum and minimum values may be removed from the multiple pieces of flow rate information qa-qc, and the remaining value may be determined as the predicted flow rate Q. If, for example, heavy rain causes an increase in the flow rate of the river, and one of the water level sensors 51 is washed away or the cable 52 is damaged, resulting in abnormal water level information w being obtained from one of the three water level measurement means 50, the flow rate filter 552 can remove the abnormal value and obtain the correct river water level W.

As described above, the water level acquisition unit 22 according to the third embodiment has multiple water level measurement means 50 and a water level filter 55. This makes it possible to stably measure the river water level W even in the presence of various natural phenomena.

[Embodiment 4]
FIG. 8 is a block diagram shown for explaining the configuration of a water level prediction device 12 according to the fourth embodiment.

As shown in FIG. 8, the water level prediction device 12 includes a first estimated precipitation calculation unit 3A, a second estimated precipitation calculation unit 3B, a first river model 4A, and a third river model 4B. With this configuration, it is possible to output two predicted water levels Ha and Hb.

When the outputs of the two predicted water levels Ha and Hb are similar, it can be said that the prediction accuracy of the first river model 4A and the third river model 4B is sufficiently high.

In the water level prediction device 12, the first river model 4A and the third river model 4B can use different model parameters Pa and Pb. In this case, the estimated precipitation calculation units 3A and 3B will output different state variables Sa and Sb, respectively.

For example, the three tank water levels (S1, S2, S3) of the first river model 4A are set low to create state variable Sa, and the three tank water levels (S1, S2, S3) of the third river model 4B are set high to create state variable Sb. By intentionally inputting different parameters and state variables into the first river models 4A and 4B in this way and operating them simultaneously, the possible range of change in the predicted water level H can be expressed.

Similarly, for the soil precipitation index, by outputting two indices Da and Db using two different model parameters P and state variables S, if the respective outputs are close to each other, it can be said that the accuracy of the soil precipitation index is sufficiently high, and the user can get an idea of the reliability of the soil precipitation index.

[Embodiment 5]
FIG. 9 is a block diagram shown for explaining the configuration of a water level prediction device 13 according to the fifth embodiment.

As shown in FIG. 9, the water level prediction device 13 has a changeover switch 7 for switching between the basin estimated precipitation Er and the basin predicted precipitation Xr. In the water level prediction device 11 according to the first embodiment, the estimated precipitation calculation unit 3 calculates the state variable S, and the first river model 4 predicts the water level using the state variable S obtained as a result. The water level prediction device 13 has a changeover switch 7, and initially inputs the basin estimated precipitation Er to the first river model 4, but when input of the basin estimated precipitation Er up to the prediction start time has been completed and the state variable S has reached the desired value, the input to the first river model 4 is switched to the basin predicted precipitation Xr, and water level prediction is performed.

The water level prediction device 13 differs from the water level prediction device 11 according to the first embodiment in that the first river model 4 receives the basin estimated precipitation Er as an input and calculates the state variable S within the first river model 4. As a result, different models can be used for the first river model 4 and the second river model 31. For example, it is possible to apply a "series three-stage tank model" as the first river model 4 and an "RRI model" as the second river model 31 (see FIG. 3) included in the estimated precipitation calculation unit 3, so that more accurate water level predictions can be achieved by applying the optimal models for the estimation of the basin estimated precipitation Er and the prediction calculation of the predicted water level H.

[Embodiment 6]
FIG. 10 is a block diagram shown for explaining the configuration of a precipitation estimation device 8 according to the sixth embodiment.

As shown in FIG. 10, the precipitation estimation device 8 includes a second river model 31, model parameters P, a difference calculation means 32, and an integration means 33. The precipitation estimation device 8 inputs the river water level W measured at a specified point to the second river model 31, and outputs the basin estimated precipitation Er, which is the precipitation in the basin at that point. The precipitation estimation device 8 may have a similar configuration to the estimated precipitation calculation unit 3 (see FIG. 3) described in the first embodiment. The precipitation estimation device 8 of the sixth embodiment can estimate the basin estimated precipitation Er from the river water level W.

In the embodiment described above, the data input to the water level prediction devices 11 to 13 may be acquired collectively at a predetermined time interval.

The data input to the water level prediction devices 11 to 13 may include at least one of other information that affects the water level and precipitation, such as the discharge volume of a dam or floodgate installed in the watershed of the prediction point, the discharge time of the dam or floodgate, the amount of rainfall lost in the watershed of the prediction point, and the wind direction and speed in the watershed of the prediction point.

The water level prediction devices 11 to 13 may also be equipped with a warning unit that issues a warning to implement a disaster response plan according to the predicted water level H when the predicted water level H predicted by the first river model 4 exceeds a predetermined reference value. In addition, a warning may be issued to residents in the vicinity of the predicted location to implement an evacuation plan according to the predicted water level H as a disaster response plan.

Furthermore, the water level prediction devices 11 to 13 may have a function of comparing the predicted water level H predicted by the first river model 4 with the river water level W, and if there is a significant discrepancy, determining that some kind of abnormality has occurred in the river, such as a debris flow or a failure of the water level sensor 51.

In the water level prediction devices 11 to 13, the watershed extraction unit 5 may extract the watershed using topographical information G that includes not only the watershed of the prediction point but also neighboring watersheds. In addition, when accumulating the predicted precipitation X for the watershed mesh 101, the watershed extraction unit 5 may calculate the watershed predicted precipitation Xr by accumulating the predicted precipitation X for the watershed mesh 101 while taking into account a time delay according to the distance from the watershed mesh 101 to the prediction point 100.

In the water level prediction devices 11 to 13, the river model used for the first river model 4 may be another model (e.g., the RRI model) that takes precipitation as input and water level as output, instead of the three-tank model in series.

This invention can be applied to predicting water levels in rivers.

11, 12, 13... Water level prediction device, 21, 22... Water level acquisition unit, 3... Estimated precipitation calculation unit, 4... First river model, 5... Watershed extraction unit, 7... Changeover switch, 8... Precipitation estimation device, 30... Model parameters, 31... Second river model, 32... Difference calculation means, 33... Integration means, 41... Three-stage tank, 42... Flow rate calculation unit, 43... Water level conversion unit, 44... Soil rainfall index extraction unit, 50... Water level measurement means, 51... Water level sensor, 52... Cable, 53... Circuit box, 54... Antenna, 55... Water level filter, 551... Flow rate conversion means, 552... Flow rate filter, 553... Water level conversion means, S... State variable, P... Model parameters

Claims (7)

A water level prediction device for predicting a future water level at a prediction point of a river using a predicted precipitation amount, which is a predicted future precipitation amount, topographical information, and a river water level at the prediction point, comprising:
a watershed extraction unit that applies the topographical information to the predicted precipitation to extract a watershed predicted precipitation in a watershed into which precipitation flows into the prediction point;
a first river model whose internal state is determined by a plurality of state variables;
a water level acquisition unit that acquires the river water level at the prediction point;
an estimated precipitation calculation unit that estimates a basin estimated precipitation flowing into the prediction point using the river water level,
The water level prediction device is characterized in that the first river model calculates the predicted water level according to a calculation result of the estimated precipitation calculation unit. the estimated precipitation calculation unit includes a second river model that outputs a model water level from the basin estimated precipitation, and a difference calculation means that calculates a difference between the river water level and the model water level to calculate a differential water level;
2. The water level prediction device according to claim 1, wherein the calculation of the second river model is repeated so that the differential water level approaches zero. The water level acquisition unit includes a plurality of water level measurement means and a water level filter,
The water level prediction device according to claim 1 or 2, characterized in that the water level filter removes water level information indicating abnormal values from the river water level information acquired by the multiple water level measurement means. a plurality of the estimated precipitation calculation units and a plurality of the first river models;
3. The water level prediction device according to claim 1, wherein a plurality of the predicted water levels are output. A changeover switch for changing over between the basin estimated precipitation amount and the basin forecast precipitation amount,
3. The water level prediction device according to claim 1, wherein the estimated precipitation amount in the river basin and the predicted precipitation amount in the river basin are input to the first river model while being switched between them. A precipitation estimation device that acquires a river water level at a water level prediction point and outputs a basin estimated precipitation that fell in the river basin at the measurement point of the river water level,
A second river model that outputs a model water level from the estimated precipitation in the river basin;
and a difference calculation means for calculating a difference between the river water level and the model water level to calculate a difference water level,
The precipitation estimation device according to claim 1, wherein the integration means repeats calculations of the second river model so that the differential water level approaches zero. A water level prediction method for predicting a future predicted water level at a predicted point of a river using predicted precipitation, topographical information, and river water level, comprising:
a basin predicted precipitation extraction step of extracting a basin predicted precipitation in a basin into which precipitation flows into the prediction point by applying the topographical information to the predicted precipitation;
a river water level acquisition step of acquiring the river water level at the prediction point;
a watershed estimated precipitation estimating step of estimating a watershed estimated precipitation flowing into the prediction point from the river water level;
A water level prediction method comprising: a predicted water level calculation step of calculating the predicted water level using the basin predicted precipitation and the basin estimated precipitation.

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