Information processing device, information processing method, and computer program

Abstract

An information processing device, an information processing method, and a computer program are provided for estimating the amount of inflow into a water storage facility. [Solution] The information processing device of this embodiment includes a processing unit that detects one or more first periods of precipitation based on meteorological observation data regarding precipitation in a target area including a river, determines the value of a model parameter related to the characteristics of the target area of ​​an estimation model regarding the amount of water inflow into a water storage facility that can accumulate water flowing in from the river and release the accumulated water downstream based on the meteorological observation data for the first period and the water inflow data for the first period into the water storage facility, and estimates the amount of water inflow into the water storage facility based on the meteorological data regarding the precipitation in the target area and the value of the model parameter.

Description

[Technical Field]

[0001] The present embodiment relates to an information processing device, an information processing method, and a computer program. [Background technology]

[0002] When large amounts of rain fall in a short period of time, such as when a typhoon passes or a linear rain band occurs, there is a risk that rivers will rise and cause flooding in downstream areas. To prevent or mitigate flood damage, flood control is carried out by temporarily storing water in dams built on rivers and adjusting the amount of water released downstream. When large amounts of rain are expected in the near future, for example within a few hours, preliminary or advance release of water from the dam is carried out to ensure the free space (flood control capacity) required for flood control. Preliminary or advance release requires highly accurate estimation of the amount of water that will flow into the dam due to rising river water levels.

[0003] There is a known technology that uses a pre-constructed physical model based on weather forecast data for the target area where the dam is located to estimate the inflow volume to a dam for the near future. To accurately estimate the inflow volume, it is necessary to consider not only the precipitation that falls directly into the river, but also the rainwater that seeps underground from the surrounding ground surface and flows into the river, and the rainwater that overflows onto the ground surface when a large amount of rain falls on the ground surface in a short period of time, saturating the soil moisture. Examples of when a large amount of rain falls on the ground surface include when a typhoon passes through or when a linear rain band occurs. Therefore, estimating the inflow volume is difficult. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Publication No. 2023-074629 Summary of the Invention [Problem to be solved by the invention]

[0005] The present embodiment aims to provide an information processing device, an information processing method, and a computer program for estimating the amount of inflow into a water storage facility. [Means for solving the problem]

[0006] The information processing device of this embodiment includes a processing unit that detects one or more first periods of precipitation based on meteorological observation data regarding precipitation in a target area including a river, determines the value of a model parameter related to the characteristics of the target area of ​​an estimation model regarding the amount of water inflow into a water storage facility that can accumulate water flowing in from the river and release the accumulated water downstream based on the meteorological observation data for the first period and the water inflow data for the first period into the water storage facility, and estimates the amount of water inflow into the water storage facility based on the meteorological data regarding the precipitation in the target area and the value of the model parameter.

[0007] The information processing method of this embodiment detects one or more first periods of precipitation based on meteorological observation data regarding precipitation in a target area including a river, determines the value of a model parameter related to the characteristics of the target area of ​​an estimation model regarding the amount of water inflow into a water storage facility that can accumulate water flowing in from the river and release the accumulated water downstream based on the meteorological observation data for the first period and the water inflow data for the first period into the water storage facility, and estimates the amount of water inflow into the water storage facility based on the meteorological data regarding the precipitation in the target area and the value of the model parameter.

[0008] The computer program of this embodiment is a computer program that is executed by a computer to detect one or more first periods of precipitation based on meteorological observation data regarding precipitation in a target area including a river, determine the values ​​of model parameters related to the characteristics of the target area of ​​an estimation model regarding the amount of water inflow into a water storage facility that can accumulate water flowing in from the river and release the accumulated water downstream based on the meteorological observation data for the first periods and the water inflow data for the first periods into the water storage facility, and estimate the amount of water inflow into the water storage facility based on the meteorological data regarding the precipitation in the target area and the values ​​of the model parameters. [Brief explanation of the drawings]

[0009] [Figure 1] 1 is a diagram illustrating a configuration of an information processing device according to a first embodiment. [Figure 2] FIG. 2 is a diagram showing an example of time-series data of precipitation included in meteorological observation data. [Figure 3] FIG. 10 is a diagram showing an example of time-series data of inflow into a dam included in inflow data. [Figure 4] FIG. 3 is a diagram illustrating a detailed configuration of a data extraction unit according to the first embodiment. [Figure 5] FIG. 10 is a diagram showing an example of a candidate period and a flood period. [Figure 6] 4 is a flowchart illustrating processing executed by the information processing device according to the first embodiment. [Figure 7] FIG. 10 is a diagram showing a modified example of selecting a flood period from candidate periods. [Figure 8] FIG. 10 is a diagram illustrating a configuration of an information processing system according to a second embodiment. [Figure 9] FIG. 2 is a diagram illustrating a hardware configuration of an information processing device according to each embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0010] Hereinafter, the present embodiment will be described with reference to the drawings. In the drawings, the same or corresponding elements are designated by the same reference numerals, and detailed descriptions thereof will be omitted as appropriate.

[0011] (Embodiment 1) FIG. 1 is a diagram illustrating a configuration of an information processing device 100 according to a first embodiment. Based on meteorological observation data on precipitation in a target area including a river, the information processing device 100 determines model parameters for an estimation model of the amount of water flowing from a river into a water storage facility, particularly values ​​of model parameters related to the characteristics of the target area. Based on the model parameter values ​​and meteorological data on precipitation in the target area, the information processing device 100 estimates the amount of water inflow into the water storage facility during a target period (target period) based on the model parameter values ​​and meteorological data on precipitation in the target area. In particular, when a large amount of precipitation occurs in a short period, such as when a typhoon passes or a linear rain band occurs, precipitation flows into the river from the surrounding land underground and also flows over the land surface. In order to accurately estimate the amount of inflow into the water storage facility, in this embodiment, the inflow of precipitation into the river is also accurately reflected in the estimation model. The following description assumes that the precipitation is rain, but precipitation is not limited to rain and may include solid precipitation such as snow, hail, and hail.

[0012] In the first embodiment, a water storage facility is defined as a structure that can block a river, store water, and release the stored water downstream, regardless of the height of the levee. In the following explanation, a dam is used as an example of a water storage facility, but it may also be called a reservoir or other name. A dam may be used for flood control purposes, or for water utilization or power generation purposes.

[0013] The target area is an area that includes a river and the surrounding land, and will be referred to as the target area below. The target area may also include a dam. The target area is, for example, an area with a radius of about 10 km.

[0014] Weather data includes weather observation data, which includes weather values ​​observed currently or in the past (weather observation values), and weather forecast data, which includes weather values ​​predicted for the future (weather forecast values) calculated by numerical calculation based on current or past weather observation values. Weather forecast data may also be called weather forecast data. Weather observation data may include not only the values ​​actually observed (observed values) themselves, but also values ​​obtained by processing the observed values ​​(e.g., analyzed rainfall by the Japan Meteorological Agency), or values ​​estimated from the observed values ​​using any model (e.g., analyzed snow depth by the Japan Meteorological Agency).

[0015] In this embodiment, estimating the inflow into a dam may include not only estimating future inflow into a dam but also estimating past inflow into a dam. For example, an estimation model can be evaluated by estimating past inflow into a dam using past meteorological data. Estimating future inflow into a dam may also be referred to as predicting inflow into a dam. The following description will discuss the case of estimating (forecasting) future inflow into a dam, but as mentioned above, this embodiment may also be used to estimate past inflow into a dam.

[0016] The information processing device 100 includes a model storage unit 10 that stores a physical model 11 that forms the basis of the estimation model, a data storage unit 20, a data extraction unit 30, a parameter adjustment unit 40, a data acquisition unit 50, an inflow estimation unit 60, and an output unit 70. Some or all of these elements 10 to 70 constitute a processing unit that executes the processing according to the first embodiment.

[0017] First, the physical model 11 will be described, and then each part will be described.

[0018] The physical model 11 is a model that describes a group of calculation formulas (such as equations) for estimating the inflow amount to a dam located in the target area using meteorological data for the target area as input. In detail, the physical model 11 is a model that simulates the process in which precipitation (e.g., rainwater) that falls on the target area flows through the ground surface and underground soil into a river, and then flows from the river into a dam, thereby estimating the inflow amount to the dam. The physical model 11 is, for example, a distributed model that subdivides the target area into a mesh and, based on the precipitation (e.g., rainfall) included in the meteorological data, simulates the movement of water and materials between the elements based on physical processes (e.g., snowmelt, surface runoff, underground runoff, and river channel runoff) in accordance with the law of conservation of water balance in each element (cell) of the mesh, thereby estimating the inflow amount to the dam.

[0019] The physical model 11 may be a dedicated model or an existing model may be used. For example, existing physical models include the Rainfall Runoff Inundation model (RRI model) developed by the International Centre for Water Hazard Risk Management under the auspices of UNESCO (ICHRM) and the WRF-Hydro model developed by the National Science Foundation - National Center for Atmospheric Research (NSF-NCAR). These physical models are publicly available as open source software (OSS) and can be used free of charge.

[0020] The estimation model in this embodiment is a model based on the physical model 11, and is a model that estimates the inflow amount to a dam located in the target area using meteorological data of the target area as input. The estimation model may be the same model as the physical model 11. However, the estimation model has unknown values ​​for the model parameters to be optimized, and the values ​​are determined by optimization. Details will be described later. The model parameters to be optimized include model parameters related to the characteristics of the target area, such as parameters related to soil characteristics and parameters related to the characteristics of the ground surface.

[0021] Model parameters relating to the characteristics of the target area (including, for example, parameters relating to soil characteristics and parameters relating to land surface characteristics) are adjusted to standard values ​​in the physical model 11 that match the average land surface and soil characteristics. Therefore, in order to accurately estimate the inflow volume into a dam into which river water in a specific region flows, the standard values ​​cannot be used directly in the estimation model. The model parameters must be adjusted to match the land surface and soil characteristics of that region. Specific examples of model parameters relating to the characteristics of the target area may represent specific characteristics of the land surface and soil (sediment quality), such as equivalent roughness, maximum storage height, saturated hydraulic conductivity, unsaturated hydraulic conductivity, and porosity, or may represent abstract characteristics of the land surface and soil, such as surface runoff coefficient, soil runoff coefficient, and soil infiltration coefficient.

[0022] During periods of heavy rainfall over a short period of time, such as during a typhoon or a linear rain band, rainwater that falls on the ground surface initially permeates the underground soil, then flows through the soil and into rivers. However, once the soil moisture reaches saturation, the rainwater overflows the ground surface and flows directly across the surface, eventually flowing into rivers. Therefore, to accurately reflect conditions in which heavy rainfall over a short period of time falls on the ground surface, it is particularly important to adjust not only model parameters related to soil characteristics but also model parameters related to ground surface characteristics to suit the characteristics of the target area. Specifically, it is important to appropriately adjust the equivalent roughness, maximum storage height, and surface runoff coefficient. Furthermore, the model parameters related to the characteristics of the target area are not limited to the soil and surface characteristics described above; other parameters that affect the amount of precipitation inflow into rivers during precipitation can also be used.

[0023] The data storage unit 20 stores weather data (weather observation data and weather forecast data) of the target area and inflow data of dams.

[0024] The weather data includes time-series data of at least precipitation (mm / h) for the target area, but may also include other weather values ​​such as wind direction and force, temperature, etc.

[0025] FIG. 2 shows an example of meteorological observation data in the meteorological data, specifically, an example of time-series data of precipitation. The meteorological data can be obtained, for example, from a database of the Japan Meteorological Agency. The weather forecast data may also be stored in the same format as that shown in FIG. 2, or in a different format. The weather forecast data can be obtained, for example, from the Japan Meteorological Agency in almost real time, and stored in the data storage unit 20 at any timing.

[0026] Inflow data is the inflow to the dam (m 3 / s) time series data. The unit of inflow volume can be mm / h, etc. Figure 3 shows an example of time-series data on inflow to a dam. Inflow data is held by the administrator of the dam or river, for example, and some of it is made publicly available in the Japanese Hydrological and Water Quality Database, etc.

[0027] The meteorological observation data and inflow data include not only data observed when large amounts of rain fall in a short period of time, such as when a typhoon passes or a linear rain band occurs, but also data observed on clear days and during normal rainfall. As mentioned above, in order to adjust model parameters related to the characteristics of the earth's surface, data observed during normal rainfall, i.e., data obtained when all rainwater falling on the ground surface permeates the soil, flows through the soil, and flows into rivers, is insufficient. Data obtained when the soil moisture is saturated, causing rainwater to overflow onto the ground surface and flow directly across the ground surface into rivers is required. Therefore, the data extraction unit 30 extracts such data.

[0028] The data extraction unit 30 detects one or more periods (first period or second period) suitable for adjusting model parameters related to the ground surface based on the meteorological observation data and inflow data stored in the data storage unit 20. For example, it detects a period (called a flood period) in which a large amount of rain falls on the ground surface in a short period of time, saturating the soil moisture and causing rainwater to overflow onto the ground surface. The period to be detected is, for example, a continuous period from the start to the end of rainfall. The data extraction unit 30 extracts the meteorological observation data and inflow data for the detected flood period for model learning.

[0029] 4 is a diagram showing the detailed configuration of the data extraction unit 30. The data extraction unit 30 includes a candidate period detection unit 31, a flood index calculation unit 32, a flood period selection unit 33, and an extraction unit .

[0030] The candidate period detection unit 31 detects candidates for flood periods (candidate periods or first periods) in the target area based on the meteorological observation data stored in the data storage unit 20. In detail, the candidate period detection unit 31 detects periods in which the cumulative rainfall (mm), which is the cumulative value of precipitation calculated from the meteorological observation data, is equal to or greater than a predetermined reference value, and sets these as candidate periods Di (i=1, 2, . . . , N).

[0031] The upper graph in Figure 5 shows a graph of cumulative rainfall over a certain period. Candidate periods D1 and D2 are shown, which are detected when the reference value for cumulative rainfall is set to 40 mm. Candidate periods D1 and D2 are continuous periods from the start to the end of rainfall, during which the cumulative rainfall is equal to or greater than the reference value of 40 mm.

[0032] The flood index calculation unit 32 calculates the surface runoff rate (mm / h) and the underground runoff rate (mm / h) for the candidate period Di (i=1, 2, . . . , N) detected by the candidate period detection unit 31 using a derivation formula for the surface runoff rate (mm / h) and the underground runoff rate (mm / h) included in the physical model 11. This formula includes parameters related to soil characteristics and parameters related to the characteristics of the ground surface. However, since high accuracy is not required when calculating the flood index, the standard values ​​used in the physical model 11 can be used as is. Specifically, the flood index calculation unit 32 inputs meteorological observation data corresponding to the candidate period Di and calculates the surface runoff rate (mm / h) and the underground runoff rate (mm / h) for the candidate period Di using the above formula. Then, it calculates a flood index Ii (i=1, 2, . . . , N) based on the relative relationship between the surface runoff rate (mm / h) and the underground runoff rate (mm / h).

[0033] For example, the flood index Ii may be a surface runoff ratio Ii, which is the ratio of the peak value of the surface runoff to the peak value of the underground runoff during the candidate period Di.

[0034]

number

[0035] In the above equation, qsurf(t) is the surface runoff during the candidate period Di, and qsoil(t) is the subsurface runoff during the candidate period Di.

[0036] Alternatively, the surface accumulation ratio Ii, which is the ratio of the accumulated value of the surface runoff to the accumulated value of the subsurface runoff during the candidate period Di, may be used as the flood index Ii.

[0037]

number

[0038] The flood period selection unit 33 selects a flood period (second period) from among the candidate periods based on the flood index. Specifically, the flood period selection unit 33 selects only candidate periods whose flood index satisfies a predetermined condition, for example, candidate periods whose flood index is equal to or greater than a threshold, from among the candidate periods, and sets these as flood periods (second periods). When the surface runoff ratio is used as the flood index, a flood index of 1.0 or greater means that the peak value of surface runoff exceeds the peak value of underground runoff. When the surface accumulation ratio is used as the flood index, a flood index of 1.0 or greater means that the cumulative value of surface runoff exceeds the cumulative value of underground runoff.

[0039] The bottom graph in Figure 5 shows a graph of the surface runoff and subsurface runoff for the same period as the top graph in Figure 5. Of the candidate periods D1 and D2, only candidate period D2, whose flood index is equal to or greater than the threshold value (1.0 in this example), is selected as the flood period. The selected flood period is referred to as flood period D2.

[0040] The extraction unit 34 extracts the meteorological observation data and inflow data corresponding to the flood period selected by the flood period selection unit 33 from the meteorological observation data and inflow data stored in the data storage unit 20. In the example of Figure 5, the meteorological observation data and inflow data corresponding to flood period D2 are extracted.

[0041] Returning to FIG. 1, the parameter adjustment unit 40 adjusts the model parameters of the estimation model for the amount of water inflow into the dam (water storage facility) using the meteorological observation data and inflow data for the flooding period extracted by the data extraction unit 30. The estimation model may be a model based on the physical model 11 as described above, and the model parameters to be optimized have unknown values. The estimation model may be the same as the physical model 11, but in this case too, the model parameters to be optimized are assumed to be replaced from the above-mentioned standard values ​​(initial values) with unknown values. The model parameters to be optimized include, for example, parameters related to soil characteristics and parameters related to earth surface characteristics. The estimation model is schematically shown by the following equation: x is an input variable, y is an output variable, a1 to aN are model parameters, and M is a symbol indicating the estimation model.

number

[0042] The parameter adjustment unit 40 estimates the inflow to the dam as an output variable y using meteorological observation data from the flood period as an input variable x (x can be a vector or a scalar), and determines (optimizes) the values ​​of model parameters a1 to aN so that the estimated inflow and the actual inflow match or approach each other. For example, the model parameter values ​​are determined so as to minimize the mean absolute error between them. The model parameters to be optimized include at least one of a parameter related to soil characteristics and a parameter related to land surface characteristics. Various well-known optimization methods, such as grid search or Bayesian optimization, can be used for optimization. An estimation model in which the model parameter values ​​are determined or adjusted using meteorological observation data and inflow data from the flood period is particularly suitable for highly accurate estimation of the inflow to the dam during flood periods, such as when a typhoon passes or a linear rain band occurs. Note that the meteorological values ​​used as input variables for the estimation model are not limited to precipitation, but may also include wind force and direction, temperature, etc.

[0043] The data acquisition unit 50 acquires weather data for a period (target period) to be estimated for the target area. The target period may be, for example, a continuous period from the start of rain to the end of rain in the weather data. Alternatively, it may be an arbitrarily determined period of several hours, one or several days, or several weeks. The target period may also be a period during which the cumulative rainfall is equal to or greater than a reference value.

[0044] The inflow estimation unit 60 estimates the inflow to the dam for the target period using an estimation model with adjusted model parameters, using the meteorological data for the target area acquired by the data acquisition unit 50 as input. The output unit 70 displays the inflow to the dam estimated by the inflow estimation unit 60.

[0045] The time at which estimation is performed may also be referred to as the current time. In the above example, the weather data used for estimation includes weather data for the estimation period after the current time, but as another example, it may also include weather observation data before the current time or weather data for a period after the current time but before the estimation period. In this case, it is sufficient to change the range of input variables in the estimation model.

[0046] Next, the process executed by the information processing device 100 according to the first embodiment will be described with reference to the flowchart of FIG.

[0047] Fig. 6 is a flowchart of the information processing method according to this embodiment. Steps S101 to S105 in Fig. 6 are processes related to adjusting the model parameters of the estimation model, and steps S106 to S108 in Fig. 6 are processes for estimating the inflow amount to the dam using the estimation model with the adjusted model parameters.

[0048] In step S101, the candidate period detection unit 31 detects a candidate flood period (candidate period or first period) for the target area based on previously observed meteorological observation data and dam inflow data for the target area stored in the data storage unit 20.

[0049] In step S102, the flood index calculation unit 32 calculates a flood index for each candidate period using model parameters related to the characteristics of the target area, in this example, parameters related to the soil characteristics and parameters related to the ground surface characteristics. When calculating the flood index, standard values ​​used in the physical model 11 can be used as the values ​​of these parameters.

[0050] In step S103, the flood period selection unit 33 selects a flood period (second period) from among the candidate periods based on the flood index.

[0051] In step S104, the extraction unit 34 extracts meteorological observation data and inflow data corresponding to each flood period from the meteorological observation data and inflow data stored in the data storage unit 20.

[0052] In step S105, the parameter adjustment unit 40 adjusts (optimizes) the model parameters used in the estimation model using meteorological observation data and inflow data from the flooding period. The model parameters to be adjusted include at least model parameters related to the characteristics of the target area. In this example, these parameters include at least one of parameters related to the soil characteristics and parameters related to the ground surface characteristics.

[0053] In step S106, the data acquisition unit 50 acquires weather data for the target area.

[0054] In step S107, the inflow estimation unit 60 estimates the inflow to the dam for the target period from the weather data for the target area using an estimation model with optimized model parameters. As an example, the weather forecast data for the target period is used as the period of weather data to be used. Alternatively, as described above, at least one of weather forecast data for a future period prior to the target period and past weather observation data may also be used. The weather data used may also be fictitious weather data. The fictitious weather data can also be used to carry out related use cases (e.g., discharge operation training during floods).

[0055] In step S108, the output unit 70 displays the estimated inflow amount to the dam to the user.

[0056] As described above, the information processing device 100 according to the first embodiment detects meteorological observation data and inflow data of the target area that correspond to a flood period from past meteorological observation data of the target area and inflow data of the dam, and adjusts the model parameters of the estimation model using this data. Due to these characteristics, the information processing device 100 according to the first embodiment can accurately estimate the inflow amount to the dam during flood periods when a large amount of rain falls in a short period of time, such as when a typhoon passes or a linear rainband occurs.

[0057] In the first embodiment, the time required for the parameter adjustment unit 40 to adjust the model parameters of the estimation model increases as the amount of flood period data used for adjustment increases. Therefore, if it is desired to shorten the time required for adjusting the model parameters, the flood period selection unit 33 may select only a predetermined number of flood periods from among candidate periods whose flood index satisfies a predetermined condition. For example, if the surface runoff ratio or surface accumulation ratio is used as the flood index, the flood period selection unit 33 may select only a predetermined number, for example, two, of candidate periods whose flood index is 1.0 or greater in descending order of the flood index as flood periods.

[0058] FIG. 7 shows an example in which, out of candidate periods D2, D3, and D4 with flood indexes of 1.0 or more, only D3 and D2 are selected as flood periods because they have the top two flood indexes.

[0059] (Embodiment 2) 8 is a diagram showing the configuration of an information processing system 200 according to embodiment 2. The information processing system 200 includes an information processing device 101, a control device 202, and a dam 203. The control device 202 is an external device to the information processing device 101, but may be provided inside the information processing device 101 as a control unit. The control device 202 may be physically integrated with the information processing device 101 or may be a separate entity.

[0060] The information processing device 101 is the same as the information processing device 101 according to the first embodiment. The information processing device 101 acquires weather data (e.g., weather forecast data) for a target area where the dam 203 is located, for example, from the Japan Meteorological Agency, and stores the data in the data storage unit 20. The information processing device 101 estimates the amount of inflow into the dam 203 for a target period to be estimated based on the acquired weather data and an estimation model in which the model parameters have been adjusted. The dam 203 accumulates water flowing in from upstream of the river 206 and can release the accumulated water downstream by controlling the opening and closing of a gate 204. The river 206 is surrounded by land 207. During heavy rainfall such as a typhoon, rain moves over the surface of the land 207 and flows into the river 206, or rain that has infiltrated underground under the land 207 moves underground and flows into the river 206. The target period to be estimated may be, for example, a continuous period from the earliest rainfall in the future until the rain stops. The target period may also be a period during which cumulative rainfall satisfies a condition. The control device 202 generates a discharge plan necessary to ensure flood control capacity based on the inflow into the dam 203 estimated by the information processing device 101 and the current water storage volume or water storage rate of the dam 203. The control device 202 controls the sluice gates 204 of the dam 203 in accordance with the generated plan to perform discharge 205. Discharge 205 includes, for example, a preliminary discharge or advance discharge. The discharge plan may be generated, for example, so that the water storage volume or water storage rate of the dam 203 is equal to or lower than an upper limit value during a target period. The water volume of the river due to rainfall downstream may be estimated using at least one of weather forecast data and weather observation data for the area downstream of the dam 203 during or before the target period, and a discharge plan may be generated so that the water volume does not exceed a certain value.

[0061] (Hardware configuration) 9 is a diagram showing the hardware configuration of an information processing device 101 according to each embodiment. The information processing device 101 is configured by a computer device 600. The computer device 600 includes a CPU 601, an input interface 602, a display device 603, a communication device 604, a main memory device 605, and an external memory device 606, which are interconnected by a bus 607.

[0062] The CPU (Central Processing Unit) 601 executes a computer program on the main memory device 605. The computer program is a program that realizes each of the above-mentioned functional configurations of the information processing device 101. The computer program may be realized not as a single program, but as a combination of multiple programs or scripts. Each functional configuration is realized by the CPU 601 executing the computer program.

[0063] The input interface 602 is a circuit for inputting operation signals from input devices such as a keyboard, a mouse, and a touch panel to the information processing device 101.

[0064] The display device 603 displays data output from the information processing device 101. The display device 603 is, for example, but not limited to, an LCD (liquid crystal display), an organic electroluminescence display, a CRT (cathode ray tube), or a PDP (plasma display). Data output from the computer device 600 can be displayed on the display device 603. The display device 603 corresponds to the output unit 70 of the information processing device 101 according to each embodiment.

[0065] The communication device 604 is a circuit that enables the information processing device 101 to communicate with an external device wirelessly or via a wire. Data can be input from the external device via the communication device 604. The data input from the external device can be stored in the main memory device 605 or the external memory device 606. The communication device 604 corresponds to the data acquisition unit 50 of the information processing device 101 according to each embodiment.

[0066] The main memory device 605 stores computer programs, data required for executing the computer programs, data generated by executing the computer programs, etc. The computer programs are deployed and executed on the main memory device 605. The main memory device 605 is, for example, RAM, DRAM, or SRAM, but is not limited to these. The data storage unit 20 of the information processing device 101 according to each embodiment may be constructed on the main memory device 605.

[0067] The external storage device 606 stores computer programs, data required for executing the computer programs, and data generated by executing the computer programs. These computer programs and data are read into the main storage device 605 when the computer programs are executed. The external storage device 606 is, for example, but is not limited to, a hard disk, an optical disk, a flash memory, or a magnetic tape. The data storage unit 20 of the information processing device 101 according to each embodiment may be constructed on the external storage device 606.

[0068] The computer program may be pre-installed in the computer device 600, or may be stored on a storage medium such as a CD-ROM. The computer program may also be uploaded onto the Internet.

[0069] Furthermore, the information processing device 101 according to each embodiment may be configured as a single computer device 600, or may be configured as a system made up of a plurality of computer devices 600 connected to each other.

[0070] Although several embodiments have been described, these embodiments are presented as examples and are not intended to limit the scope of the embodiments. These embodiments can be implemented in various other forms, and various omissions, substitutions, modifications, combinations, etc. can be made without departing from the spirit of the embodiments. These embodiments and their modifications are included in the scope of the claims and their equivalents, as well as the scope and spirit of the embodiments.

[0071] This embodiment can also be configured as follows. [Item 1] detecting one or more first periods of precipitation based on meteorological observation data relating to precipitation in a region of interest that includes a river; determining model parameter values ​​related to characteristics of the target area of ​​a physical model relating to the amount of water inflow into the water storage facility based on the meteorological observation data for the first period and the water inflow data for the first period into the water storage facility that is capable of storing water flowing in from the river and discharging the stored water downstream; estimating the amount of water inflow into the water storage facility based on meteorological data related to the amount of precipitation in the target area and the values ​​of the model parameters; Processing section, An information processing device comprising: [Item 2] The first period is a period during which the cumulative value of the precipitation is equal to or greater than a reference value. Item 1. An information processing device according to item 1. [Item 3] the model parameters include parameters relating to the land surface and soil of the land surrounding the river; the processing unit calculates, for each of the one or more first periods, a surface runoff amount of the precipitation flowing on the ground surface and flowing into the river, and a subsurface runoff amount of the precipitation permeating from the ground surface into the underground and flowing into the river; selecting a second time period from the one or more first time periods based on the surface runoff and the subsurface runoff; determining values ​​of the model parameters based on the meteorological observation data and the inflow data for the second time period; Item 3. The information processing device according to item 1 or 2. [Item 4] the processing unit calculates an index indicating a relationship between the surface runoff amount and the underground runoff amount; selecting the second period based on the indicator; Item 3. An information processing device according to item 3. [Item 5] The index is a ratio of the peak value of the surface runoff to the peak value of the underground runoff, Item 5. An information processing device according to item 4. [Item 6] The index is a ratio of the cumulative value of the surface runoff to the cumulative value of the underground runoff, Item 5. An information processing device according to item 4. [Item 7] the processing unit selects, from the first periods, a first period in which the index is equal to or greater than a threshold as the second period; Item 7. The information processing device according to any one of items 4 to 6. [Item 8] the processing unit selects a predetermined number of the first periods having the highest indexes as the second periods; Item 7. The information processing device according to any one of items 4 to 6. [Item 9] the physical model is a distributed model in which the target area is divided into a plurality of mesh-like areas and the flow of the precipitation into the river is represented by a physical process; 9. The information processing device according to any one of items 1 to 8. [Item 10] The processing unit estimates the amount of water inflow into the water storage facility during the target period based on at least the meteorological data for the target area during the target period and the determined model parameters. 10. The information processing device according to any one of items 1 to 9. [Item 11] The target period is a continuous period from when precipitation occurs to when precipitation stops in the weather data. Item 11. An information processing device according to item 10. [Item 12] the processing unit calculates the surface runoff and the underground runoff using initial values ​​of parameters related to the ground surface of the land surrounding the river and initial values ​​of parameters related to soil; An information processing device according to any one of items 3 to 8, or any one of items 9 to 11 which cite item 3. [Item 13] a control unit that controls the discharge of the water storage facility based on the inflow amount of water estimated by the processing unit; 13. The information processing device according to any one of items 1 to 12, further comprising: [Item 14] detecting one or more first periods of precipitation based on meteorological observation data relating to precipitation in a region of interest that includes a river; determining model parameter values ​​related to characteristics of the target area of ​​a physical model relating to the amount of water inflow into the water storage facility based on the meteorological observation data for the first period and the water inflow data for the first period into the water storage facility that is capable of storing water flowing in from the river and discharging the stored water downstream; estimating the amount of water inflow into the water storage facility based on meteorological data related to the amount of precipitation in the target area and the values ​​of the model parameters; Information processing methods. [Item 15] detecting one or more first periods of precipitation based on meteorological observation data relating to precipitation in a region of interest that includes a river; determining model parameter values ​​related to characteristics of the target area of ​​a physical model relating to the amount of water inflow into the water storage facility based on the meteorological observation data for the first period and the water inflow data for the first period into the water storage facility that is capable of storing water flowing in from the river and discharging the stored water downstream; estimating the amount of water inflow into the water storage facility based on meteorological data related to the amount of precipitation in the target area and the values ​​of the model parameters; A computer program that is executed by a computer. [Explanation of symbols]

[0072] 10 Storage section 11 Physical Model 20 Data storage unit 30 Data Extraction Section 31 Candidate period detection unit 32 Water level rise index calculation section 33 Flooding period selection section 34 Extraction part 40 Parameter Adjustment Section 50 Data Acquisition Section 60 Inflow amount estimation part 70 Output section 101 Information processing equipment 200 Information Processing Systems 202 Control device (control unit) 203 Dam (water storage facility) Gate 204 205 Release 206 Rivers 207 Land

Claims

1. Detecting one or more first periods of precipitation based on meteorological observation data relating to precipitation in a region of interest that includes a river; determining values ​​of model parameters relating to characteristics of the target area in an estimation model of the amount of water inflow into the water storage facility based on the meteorological observation data for the first period and the water inflow amount data for the first period into the water storage facility that is capable of accumulating water flowing in from the river and discharging the accumulated water downstream; estimating the amount of water inflow into the water storage facility based on meteorological data related to the amount of precipitation in the target area and the values ​​of the model parameters; Processing section, An information processing device comprising:

2. The first period is a period during which the cumulative value of the precipitation is equal to or greater than a reference value. The information processing device according to claim 1 .

3. the model parameters include parameters relating to the land surface and soil of the land surrounding the river; the processing unit calculates, for each of the one or more first periods, a surface runoff amount of the precipitation flowing on the ground surface and flowing into the river, and a subsurface runoff amount of the precipitation permeating from the ground surface into the ground and flowing into the river; selecting a second time period from the one or more first time periods based on the surface runoff and the subsurface runoff; determining values ​​of the model parameters based on the meteorological observation data and the inflow data for the second time period; The information processing device according to claim 1 .

4. the processing unit calculates an index indicating a relationship between the surface runoff amount and the underground runoff amount; selecting the second period based on the indicator; The information processing device according to claim 3 .

5. The index is a ratio of the peak value of the surface runoff to the peak value of the underground runoff, The information processing device according to claim 4 .

6. The index is a ratio of the cumulative value of the surface runoff to the cumulative value of the underground runoff, The information processing device according to claim 4 .

7. the processing unit selects, from the first periods, a first period in which the index is equal to or greater than a threshold as the second period; The information processing device according to any one of claims 4 to 6.

8. the processing unit selects a predetermined number of the first periods having the highest indexes as the second periods; The information processing device according to any one of claims 4 to 6.

9. the estimation model is a distributed model in which the target area is divided into a plurality of mesh-like areas and the flow of the precipitation into the river is represented by a physical process. The information processing device according to claim 1 .

10. The processing unit estimates the amount of water inflow into the water storage facility during the target period based on at least the meteorological data for the target area during the target period and the determined model parameters. The information processing device according to claim 1 .

11. The target period is a continuous period from when precipitation occurs to when precipitation stops in the weather data. The information processing device according to claim 10.

12. the processing unit calculates the surface runoff and the underground runoff using standard values ​​of parameters related to the ground surface and standard values ​​of parameters related to soil of the land surrounding the river; The information processing device according to claim 3 .

13. a control unit that controls the discharge of the water storage facility based on the inflow amount of water estimated by the processing unit; The information processing device according to claim 1 , further comprising:

14. Detecting one or more first periods of precipitation based on meteorological observation data relating to precipitation in a region of interest that includes a river; determining model parameter values ​​related to characteristics of the target area of ​​an estimation model for the amount of water inflow into the water storage facility based on the meteorological observation data for the first period and the water inflow amount data for the first period into the water storage facility that is capable of accumulating water flowing in from the river and discharging the accumulated water downstream; estimating the amount of water inflow into the water storage facility based on meteorological data related to the amount of precipitation in the target area and the values ​​of the model parameters; Information processing methods.

15. Detecting one or more first periods of precipitation based on meteorological observation data relating to precipitation in a region of interest that includes a river; determining model parameter values ​​related to characteristics of the target area of ​​an estimation model for the amount of water inflow into the water storage facility based on the meteorological observation data for the first period and the water inflow amount data for the first period into the water storage facility that is capable of accumulating water flowing in from the river and discharging the accumulated water downstream; estimating the amount of water inflow into the water storage facility based on meteorological data related to the amount of precipitation in the target area and the values ​​of the model parameters; A computer program that is executed by a computer.

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