JP2019138742A - Runoff analyzer and runoff analysis parameter adjusting method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a spill analysis device and a spill analysis parameter adjustment method capable of more appropriately setting or adjusting the parameters of a spill analysis model constructed by using virtual parameters. An runoff analysis device of an embodiment includes a rainfall distribution input unit, a runoff analysis unit, an analysis accuracy evaluation unit, and a runoff analysis parameter adjustment unit. The rainfall distribution input unit inputs rainfall distribution information indicating the amount of rainfall for each mesh in the diagnosis target area. The runoff analysis unit performs runoff analysis that calculates the amount of storage of each mesh based on the rainfall distribution information. The analysis accuracy evaluation unit calculates the evaluation value for the accuracy of the runoff analysis for each mesh based on the result of the runoff analysis and the actual information on the actual runoff in the diagnosis target area, and the accuracy of the runoff analysis based on the evaluation value. To judge. The spill analysis parameter adjusting unit determines the diameter and slope of the virtual pipeline representing the pipeline existing in each mesh used for the spill analysis, depending on the accuracy of the spill analysis. [Selection diagram] FIG. 5

Description

  Embodiments described herein relate generally to an outflow analysis device and an outflow analysis parameter adjustment method.

  In recent years, there has been a lot of localized and short-term heavy rainfall (hereinafter referred to as “local heavy rain”), and the media refers to this local heavy rain as “guerrilla heavy rain” in the sense that it does not know when and where it occurs. Expressed in words, these words are now widely recognized by the general public. As a typical damage caused by local heavy rain, inundation floods occur frequently. In the past, the government has taken measures to prevent flooding, mainly in anticipation of flooding due to flooding or breakage of large rivers, such as embankments, river channel excavation, revetment construction and dam construction. River inundation is called outside water inundation. Conventionally, countermeasures against outside water inundation have been focused on, but in the future, it will be important to take into account inland water inundation. In fact, when we look at flood damage (outside water inundation, inland water inundation) in terms of damage amount, the damage amount of inland flooding accounts for about half of the total damage amount in the country, exceeding 90% of the total damage amount in Tokyo Yes. In this way, inundation is a new issue in urban areas where the development of dykes is relatively advanced.

  Distributed runoff analysis is widely used as a method for assessing such inundation risks throughout the city. Distributed runoff analysis is based on the use of land in a certain region, topographical information such as elevation, and civil engineering information such as the status of sewage pipe construction, and a combination of hydrological and hydraulic models as appropriate. This is a runoff analysis method that tracks the flow of rainfall (hereinafter referred to as “runoff”) using the constructed runoff analysis model. Specifically, the runoff situation for each mesh can be analyzed by applying the runoff analysis model and the rainfall data of each mesh to a plurality of meshes obtained by dividing the analysis target area. In practice, however, acquirable rainfall data is not always obtained in a mode suitable for such a runoff analysis model, and all necessary information is not necessarily obtained for civil engineering information. For this reason, labor has been required to adapt the available rainfall data and civil engineering information to the runoff analysis model. In order to solve such a problem, several methods for reducing labor when using the outflow analysis model have been proposed.

  On the other hand, a method for performing runoff analysis without using civil engineering information has also been proposed. For example, an analysis model (hereinafter referred to as “virtual tank model”) in which a virtual tank (hereinafter referred to as “virtual tank”) is assigned to each mesh and the outflow analysis is performed only by the balance of water between the virtual tanks has been proposed. Yes. However, in such a virtual tank model, since civil engineering information is not used, it is not possible to appropriately define the water level for calculating the hydrodynamic gradient, the depth of the depth, and the flow product. There was a possibility that analysis could not be performed.

  Even if the analysis model is properly constructed, it is difficult to obtain a highly accurate analysis result unless the parameters of the analysis model can be set appropriately. Furthermore, in a model using virtual parameters as described above, it may be particularly difficult to set parameters based on physical meaning. Therefore, when performing analysis with an analysis model simplified or simplified by aggregation or integration of actual physical structures, etc., a technology for appropriately setting or adjusting virtual parameters represented by the aggregation or integration Establishment of is desired.

JP 2009-8651 A JP 2005-128838 A Japanese Patent No. 4682178 Japanese Patent No. 4185910 Japanese Patent No. 4082686

  The problem to be solved by the present invention is to provide an outflow analysis device and an outflow analysis parameter adjustment method that can more appropriately determine the parameters of an outflow analysis model constructed using virtual parameters.

  The runoff analysis apparatus according to the embodiment includes a rainfall distribution input unit, a runoff analysis unit, an analysis accuracy evaluation unit, and a runoff analysis parameter adjustment unit. The rainfall distribution input unit inputs the rainfall distribution information indicating the rainfall amount for each mesh that is the rainfall amount in the diagnosis target area divided into a plurality of meshes. The runoff analysis unit performs a first runoff analysis for calculating a storage amount of each mesh by calculating a balance of flow rate between the meshes based on the rainfall distribution information. The analysis accuracy evaluation unit calculates an evaluation value for the accuracy of the outflow analysis for each mesh based on the result of the outflow analysis by the outflow analysis unit and the actual information about the actual outflow in the diagnosis target area, The accuracy of the outflow analysis is determined based on the evaluation value. The outflow analysis parameter adjustment unit determines a diameter and a gradient of a virtual pipe representing a pipe existing in each mesh used for the outflow analysis according to the accuracy of the outflow analysis evaluated by the analysis accuracy evaluation unit. To do.

The figure which shows the specific example of a structure of the outflow analysis apparatus of embodiment. The figure explaining the concept of the outflow analysis model which the outflow analysis apparatus 1 of embodiment uses. The figure which shows the relationship between a virtual water level, a pour, and a diameter depth. The figure which shows the relationship between a virtual water level, a dynamic water gradient, and a pipeline gradient. The block diagram which shows the specific example of a function structure of the outflow analysis apparatus 1 containing the function part regarding adjustment of an outflow analysis parameter. The figure which shows the specific example of the low precision mesh which exists locally. The figure which shows the specific example of the evaluation object mesh set according to the inundation attack area.

  Hereinafter, the outflow analysis device and the outflow analysis parameter adjustment method of the embodiment will be described with reference to the drawings.

First, the outflow analysis method performed by the outflow analysis device 1 of the embodiment will be described.
FIG. 1 is a diagram illustrating a specific example of the configuration of the outflow analysis apparatus according to the embodiment. In FIG. 1, only functional units related to outflow analysis are shown among the functional units included in the outflow analysis device 1. A functional unit relating to adjustment of parameters used in the outflow analysis (hereinafter referred to as “outflow analysis parameters”) will be described later.

  The outflow analysis device 1 includes a CPU (Central Processing Unit), a memory, an auxiliary storage device, and the like connected by a bus, and executes an outflow analysis device program. The runoff analysis device 1 has a rainfall distribution input unit 101, runoff coefficient calculation unit 102, runoff analysis unit 103, inundation risk evaluation unit 104, map information storage unit 105, mesh area setting unit 106, sewer management by executing the runoff analysis device program. A ledger data storage unit 107, a virtual sewage pipe diameter calculation unit 108, a virtual sewage pipe gradient calculation unit 109, a virtual sewage pipe roughness calculation unit 110, a manhole total area calculation unit 111, a capacity calculation unit 112, and a diagnosis result display unit 113 are provided. Functions as a device. All or some of the functions of the outflow analysis device 1 may be realized using hardware such as an application specific integrated circuit (ASIC), a programmable logic device (PLD), or a field programmable gate array (FPGA). . The outflow analysis device program may be recorded on a computer-readable recording medium. The computer-readable recording medium is, for example, a portable medium such as a flexible disk, a magneto-optical disk, a ROM, a CD-ROM, or a storage device such as a hard disk built in the computer system. The outflow analysis device program may be transmitted via a telecommunication line.

  The rain distribution input unit 101 inputs the rain distribution information to its own device. The rainfall distribution information is information indicating the distribution of rainfall in the target area, which is acquired from a rainfall radar or the like. Specifically, the rainfall distribution information is obtained as a set of information indicating the position of each mesh and the rainfall amount for the target area divided into meshes.

  For example, the rainfall distribution input unit 101 inputs rainfall distribution information acquired by a rainfall radar such as an X-band MP radar operated by the Ministry of Land, Infrastructure, Transport and Tourism. The rainfall distribution information acquired by the X-band MP radar is acquired as 250m square mesh data. Note that the rainfall distribution information may be acquired by other than the X-band MP radar. For example, the rainfall distribution information may be Amesh data (one of X-band radars), or data acquired by a phased array radar that can measure rainfall information in the vertical direction that is being put to practical use. It may be. From the viewpoint of runoff analysis, it is desirable that the rainfall distribution information be acquired with a fine mesh size like an X-band radar, but may be acquired with a 1-km square C-band radar. Rainfall distribution information is obtained by converting the radar reflection intensity measured by the rain radar using a radar equation, etc., but corrects the data obtained by the ground rain gauge installed in the target area. It may be what you did.

  The runoff coefficient calculation unit 102 calculates the runoff coefficient of each mesh based on the rain distribution information input by the rain distribution input unit 101. The runoff coefficient is a numerical value representing the ratio of rainwater (effective rainfall) that flows down the ground surface to the rainfall.

  For example, the runoff coefficient calculation unit 102 uses the GIS (Geographic Information System) data, which is electronic map information data acquired by an artificial satellite, to calculate the runoff coefficient for each mesh from which rainfall distribution information is acquired. For example, the outflow coefficient calculation unit 102 can calculate the outflow coefficient for each mesh by the following method. First, the runoff coefficient calculation unit 102 estimates the use form of each land using the color, the change in color, the shape, and the like indicated by the GIS data. For example, the correspondence relationship between the land use form and the color (specifically defined as a numerical value) indicated by the GIS data may be determined in advance. For example, a green part is defined as a mountain, a gray part as a road, and a square part having a predetermined size or less as a roof. The runoff coefficient calculation unit 102 calculates the proportion of land use forms in each mesh based on such correspondence. The runoff coefficient calculation unit 102 stores in advance a correspondence relationship between land use patterns and runoff coefficients. The runoff coefficient calculation unit 102 calculates, as the runoff coefficient of the mesh, a value obtained by adding the runoff coefficient associated with the land use form for each mesh with the above ratio as a weight.

  For example, based on the GIS data, it is assumed that the proportion of the usage pattern of the mesh land with the mountain proportion being 0.6, the road proportion being 0.3, and the roof proportion being 0.1 is calculated. The mountain runoff coefficient is 0.6, the road runoff coefficient is 0.8, and the roof runoff coefficient is 1. In this case, the outflow coefficient calculation unit 102 has an outflow coefficient of 0.7 (= 0.6 × 0.6 + 0.3 × 0.8 + 0.1 × 1). If information on land use forms cannot be obtained in detail, the target area is classified into rough use forms such as forests, fields, and urban areas, and the runoff coefficient is preliminarily determined for each of these rough use forms. You may define it.

  The runoff analysis unit 103 obtains effective rainfall information indicating the effective rainfall amount of each mesh by multiplying the runoff coefficient of each mesh calculated by the runoff coefficient calculation unit 102 by the rainfall amount for each mesh indicated by the rainfall distribution information. To do. The runoff analysis unit 103 calculates the change in the storage amount of each mesh by performing the runoff analysis with the effective rainfall information as an input.

  Specifically, the outflow analysis unit 103 performs outflow analysis using an outflow analysis model in which a virtual sewer pipe (virtual pipe line) described later is set for each mesh. In this respect, the outflow analysis model of the present embodiment is different from a conventional virtual tank model (see, for example, JP-A-2015-004245) in which a virtual tank is set for each mesh.

  Based on the outflow amount of each mesh analyzed by the outflow analysis unit 103, the inundation risk evaluation unit 104 determines whether or not the mesh is inundated and the degree of inundation (hereinafter referred to as “inundation risk”).

  The map information storage unit 105 is configured using a storage device such as a magnetic hard disk device or a semiconductor storage device. The map information storage unit 105 stores map information of the target area that is necessary for the calculation of the runoff coefficient by the runoff coefficient calculation unit 102. For example, it may be GIS data or map information obtained by another method.

  The mesh area setting unit 106 sets the area of each mesh necessary for the calculation of the outflow coefficient by the outflow coefficient calculation unit 102.

  The sewer management ledger data storage unit 107 is configured using a storage device such as a magnetic hard disk device or a semiconductor storage device. The sewer management ledger data storage unit 107 stores information (hereinafter referred to as “sewer management ledger data”) indicating the physical specifications of the sewer necessary for the processing of the outflow analysis unit 103 and the inundation risk evaluation unit 104.

  The virtual sewage pipe diameter calculation unit 108 calculates the pipe diameter of the virtual sewage pipe used for the outflow analysis by the outflow analysis unit 103 based on the sewer management ledger data.

  The virtual sewage pipe gradient calculation unit 109 calculates the gradient of the virtual sewage pipe used for the outflow analysis by the outflow analysis unit 103 based on the sewer management ledger data.

  The virtual sewage pipe roughness calculation unit 110 calculates the roughness of the virtual sewage pipe used for the outflow analysis by the outflow analysis unit 103 based on the sewer management ledger data.

  The manhole total area calculation unit 111 calculates the total manhole area used for the outflow analysis by the outflow analysis unit 103. The total manhole area represents the total area of each manhole mesh existing in the target area.

  The capacity calculation unit 112 calculates the maximum storage amount and the upper limit storage amount used by the outflow analysis unit 103 and the inundation risk evaluation unit 104. The maximum storage amount is the total capacity for each mesh of pipelines existing in the target area. The upper limit storage amount is the sum of the total capacity of each manhole mesh existing in the target area and the maximum storage amount.

  The diagnosis result display unit 113 displays information on the processing result of each functional unit for each mesh.

FIG. 2 is a diagram illustrating the concept of the outflow analysis model used by the outflow analysis device 1 of the embodiment. FIG. 2 schematically shows a state in which two adjacent meshes (mesh i and mesh j) are connected to the sewer pipe P via manholes (manhole i and manhole j) existing in the respective meshes. FIG. These manhole shown in FIG. 2 are virtual in that the cross-sectional area A _h of the manhole is represented by the total cross-sectional area of the manhole present in each mesh (i.e. manhole total area). Similarly, the sewer pipe P shown in FIG. 2 is also virtual, and the capacity of the pipe corresponding to each mesh is the total capacity of the pipes existing in each mesh (that is, the maximum storage amount). expressed.

  In the model that assumes such a virtual manhole and sewer pipe, when the virtual sewer pipe is full, the overflowed water does not immediately flow to the ground surface, but temporarily flows into the virtual manhole. It is possible to simulate the situation of being stored and being discharged to the ground surface when the virtual manhole is full. That is, in the runoff analysis model of the embodiment, the water level, which is a parameter necessary for calculating the hydrodynamic gradient, diameter depth, and flow product, is calculated as a value that considers the runoff path (sewage pipe and manhole) of rainwater. can do. According to such a runoff analysis model, an actual hydraulic phenomenon can be simulated more accurately than a conventional virtual tank model.

  In FIG. 2, the connection relationship between two meshes is shown for the sake of simplicity, but actually, there are four meshes that are vertically and horizontally adjacent to one mesh, and four meshes that are diagonally adjacent to each other. There are a total of 8 meshes. Therefore, when the outflow analysis is actually performed using the model as shown in FIG. 2, the outflow analysis is performed by applying the same connection relation as that of FIG.

  For example, the relationship between the flow rate balance between the mesh i and the mesh j and the virtual water level is expressed by the following equations (1) to (3).

In Expressions (1) to (3), H (i, j) represents the virtual water level of the mesh i adjacent to the mesh j. S (i) represents the storage amount in mesh i, S _lim (i) represents the upper limit storage amount of mesh i, and S _max (i) represents the maximum storage amount of mesh i. D (i, j) represents the pipe diameter (diameter) of the virtual sewer pipe connecting the mesh i and the mesh j. A h _(i) is a manhole total area of the mesh i, A _m respectively represent the area of each mesh (hereinafter referred to as "mesh area".).

Formula (1) is a formula for calculating the virtual water level when the storage amount of a certain mesh does not exceed the capacity of the virtual sewer pipe. Equation (1) indicates that the virtual water level in a certain mesh i is the actual storage amount relative to the pipe diameter D (i, j) of the virtual sewer pipe and the maximum storage capacity S _max (i) that can be stored in the sewer pipe of the mesh i. It is obtained by the product with the ratio of. That is, the virtual water level in a certain mesh i is obtained by dividing the pipe diameter D (i, j) of the virtual sewer pipe by the fullness ratio of the virtual sewer pipe in the mesh i. In this case, the virtual water level takes a value in the range of 0 to D (i, j) until the storage amount in the mesh i exceeds the maximum storage capacity S _max (i). Therefore, if an appropriate pipe diameter is set as D (i, j), the virtual water level can be calculated as an approximate value of the actual water level of the sewer pipe.

  Furthermore, when the virtual sewer pipe is assumed to be a rectangular pipe instead of a circular pipe, a clearer physical interpretation is possible with respect to the virtual water level. That is, when D (i, j) is the length of the side in the height direction (z-axis direction) of the rectangular tube, the water level of the rectangular tube matches the virtual water level calculated by Equation (1) (the gradient is 0). If). Equation (1) is an extension of this idea. In the conventional virtual tank model, the virtual water level is calculated using the parameter of the bottom area with respect to the maximum storage capacity and the storage amount. The virtual water level is calculated using the virtual sewer parameters defined based on the actual pipe line information called the pipe diameter of the water pipe (or the height of the virtual sewer pipe). Thereby, the numerical value of the virtual water level can be obtained within a realistic value range (0 to D (i, j)).

  Formula (2) represents a formula for calculating the virtual water level when the storage amount of a certain mesh exceeds the maximum storage amount of the virtual sewer pipe and does not exceed the upper limit storage amount. When the amount of storage exceeds the capacity of the sewage pipe, the sewage pipe can be handled as a pressure pipe because it is full. In the model of FIG. 2, when the virtual sewer pipe is considered as a pressure pipe, the head (water level) of the virtual sewer pipe is obtained as the height of the manhole. Expression (2) is an expression expressing the water head (water level) in such a case. By using such an expression, it is possible to more accurately represent a phenomenon from when a virtual sewage pipe of a certain mesh becomes full (pressure pipe state) until overflowing water flows out to the ground surface.

Formula (3) represents the calculation formula of the virtual water level when the storage amount of a certain mesh exceeds the upper limit storage amount of the virtual sewer pipe. Expression (3) is an expression that expresses a phenomenon after overflowing water flows out to the ground surface and water is actually generated. After rainwater flows out to the ground surface, the virtual water level is considered to rise slightly depending on the area of the ground surface. Mesh area A _m takes a much greater value than manhole total area A _h. Therefore, Formula (3) expresses that the water level does not rise rapidly after the ground surface runoff.

  Hereinafter, a method for calculating the balance of the amount of water between the meshes will be described using Expressions (1) to (3). The calculation method of the water amount balance in this embodiment is basically the same as the conventional virtual tank model. Specifically, the balance of the amount of water between each mesh should be calculated using the “continuous formula” expressed by the following formula (4) and the “Manning formula” expressed by the formula (5). Can do.

In Formula (4) and Formula (5), S represents the storage amount of a certain mesh. Here, the stored amount S is described by omitting mesh identifiers such as i and j. The same applies to other parameters described below. R _e represents effective rainfall Mesh. Q represents an outflow amount from a certain mesh to an adjacent mesh. A _d is in the virtual sewers, representing the cross-sectional area of a portion which water occupies (Nagareseki). R represents the diameter of the virtual sewer pipe. I _d represents the hydraulic gradient of virtual sewer. n represents the roughness of the virtual sewer pipe. Here, the following equation (6) is obtained by substituting equation (5) into equation (4). In equation (6), the flow product A _d , the radial depth R, and the dynamic water gradient I _d are parameters that depend on the water level of the virtual sewer pipe.

FIG. 3 is a diagram illustrating the relationship between the virtual water level, the flow volume, and the diameter depth. Here, assuming a rectangular tube having a square cross section of side length L virtual sewage pipe (FIG. 3 (A)), the Nagareseki A _d and hydraulic radius R follows using the water level H of the virtual sewer It represents like Formula (7) and Formula (8). Further, when the virtual sewer pipe assumes a circular tube having a diameter D (FIG. 3 (B)), Nagareseki A _d and hydraulic radius R by using the water level H of the virtual sewer following equation (9) to ( 11). Each parameter of Formula (7)-Formula (11) respond | corresponds to each parameter of FIG.

FIG. 4 is a diagram illustrating the relationship between the virtual water level, the dynamic water gradient, and the pipeline gradient. The pipe gradient represents the gradient of the virtual sewer pipe itself, and the dynamic water gradient represents the gradient of the water surface flowing down the virtual sewer pipe. From the relationship shown in FIG. 4, hydraulic gradient I _d can be approximated as the following equation (12) using a virtual water level H and line slope I _s. Each parameter of Expression (12) corresponds to each parameter in FIG.

In Expression (12), K represents the side length of the mesh, and the side length of the mesh represents the distance between adjacent meshes. H and H ′ represent the water level (H ′) of the virtual sewer pipe in a mesh adjacent to the water level (H ′) of the virtual sewer pipe in a certain mesh. H and H ′ are calculated by the above formulas (1) to (3). Note that the line gradient _{I s} and hydraulic gradient _{I d,} if it can be assumed that _{I s} is sufficiently small relative to the _{I d} may be a _{I s} ≒ 0.

  An outflow analysis model is obtained by combining the equations (6) to (12) described above. Here, as an example, an outflow analysis model when the virtual sewer pipe is assumed to be a circular pipe will be described. In the case of a circular pipe, equations (9) to (12) become basic equations, and when these are combined, an outflow analysis model represented by the following equation (13) is obtained. Specifically, Expression (13) is obtained by substituting Expression (9) to Expression (12) into Expression (6) and rearranging.

  Here, θ in the equation (13) is expressed by the above equation (11). The second term on the right side of Equation (13) represents the inflow / outflow amount between adjacent meshes. In terms of the water balance, the flow rate of water flowing out (or flowing in) from a mesh and the flow rate of water flowing (or flowing out) into an adjacent mesh have the same absolute value but different signs. Therefore, in order to improve the accuracy of the outflow analysis, the water balance between the meshes may be adjusted so as to satisfy the above relationship by performing an averaging process on the water depth angle θ between the meshes.

  In this embodiment, the Manning equation is used to construct the outflow analysis model, but another equation including a hydraulic gradient as a variable may be used instead of the Manning equation. For example, equations corresponding to the equations (11) and (13) may be derived using the Kutta equation.

In the above embodiment, the outflow analysis model when a circular pipe is assumed as a virtual sewer pipe has been described. Instead, an outflow analysis model when a rectangular pipe is assumed as a virtual sewer pipe is derived. Also good. Furthermore, for simplification of the model, the diameter depth and the flow product may be fixed values without using parameters that vary depending on the virtual water level. For example, it is good also as diameter depth = D / 4 and flow product = (pi) * D < ² > / 8.

  That is, a model that expresses that the dynamic water gradient is a parameter that changes according to the virtual water level, and that the virtual water level is obtained by a calculation formula according to the storage amount as in equations (1) to (3). If so, an expression different from Expression (11) and Expression (13) may be used for the outflow analysis model.

  In the above description, for the sake of simplicity, an example has been described in which an outflow analysis between a mesh and one mesh adjacent to the mesh is performed. However, when an actual analysis is performed, Therefore, it is necessary to consider the influence of all adjacent meshes. Specifically, it is necessary to add a term that considers all adjacent meshes (for example, all eight meshes that are diagonally up, down, left, and right) as the second term of Expression (13). For the runoff analysis model constructed as described above, the runoff amount (or inflow amount) of each mesh is calculated by calculating the flow rate balance with the effective rainfall amount of each mesh as an input.

  Parameters such as virtual sewage pipe diameter, virtual sewage pipe slope, virtual sewage pipe roughness, total manhole area, maximum storage volume, and maximum storage volume can be calculated using sewer management ledger data. is there. These parameters are determined by the virtual sewage pipe diameter calculation unit 108, the virtual sewage pipe gradient calculation unit 109, the virtual sewage pipe roughness calculation unit 110, the manhole total area calculation unit 111, the capacity calculation unit 112, and the like, or are adjacent to each other. It is calculated in advance for each mesh.

Next, the evaluation of flood risk will be described. The inundation risk evaluation unit 104 performs the following evaluation for each mesh based on the storage amount calculated for each mesh. For example, when the storage amount of a certain mesh exceeds the maximum storage capacity _Smax , the inundation risk evaluation unit 104 determines that “there is a possibility of inundation” for the mesh. Further, when the storage amount of a certain mesh exceeds the upper limit storage capacity _Slim , the inundation risk evaluation unit 104 determines that “the possibility of inundation is extremely high” for the mesh. Such criteria for judging inundation risk may be appropriately set according to the characteristics of the diagnosis target area.

  The diagnosis result display unit 113 displays the inundation risk (including the result of the outflow analysis) of each mesh diagnosed in this manner in a visually identifiable manner. For example, the diagnosis result display unit 113 displays the inundation risk as a mesh distribution corresponding to each mesh. Specifically, a mesh whose stored amount exceeds the maximum stored amount may be displayed in yellow, and a mesh whose stored amount exceeds the upper limit stored amount may be displayed in red. Further, the full fill rate of the virtual sewer pipe may be calculated based on the maximum storage amount or the upper limit storage amount and the calculated storage amount, and each mesh may be displayed in a color corresponding to the full pipe rate. The diagnosis result display unit 113 may display any information as long as the information is obtained based on the result of the outflow analysis, the diagnosis result of the diagnosis risk, and the like. Also, the information display mode is not limited to the above-described color identification mode, but any other mode as long as it allows visual identification of characters, symbols, figures, graphs, etc. It may be.

  The flow analysis method performed by the flow analysis device 1 of the embodiment has been described above. Next, the outflow analysis parameter adjustment method used by the outflow analysis device 1 of the embodiment for use in the above outflow analysis will be described.

  FIG. 5 is a block diagram illustrating a specific example of a functional configuration of the outflow analysis apparatus 1 including a functional unit related to adjustment of outflow analysis parameters. In addition to the functional units shown in FIG. 1, the outflow analysis device 1 includes an outflow analysis parameter setting unit 114, an outflow analysis parameter adjustment unit 115, a performance information storage unit, a mesh-based actual data generation unit 117, a detailed analysis unit 118, A detailed data generation unit 119 for each mesh, an evaluation index calculation unit 120, and an analysis accuracy evaluation unit 121 are provided. Note that, in FIG. 5, among the functional units illustrated in FIG. 1, only functional units related to adjustment of outflow analysis parameters are illustrated, and other functional units are omitted. In FIG. 5, the mesh area setting unit 106, the virtual sewer pipe diameter calculation unit 108, the virtual sewer pipe gradient calculation unit 109, the virtual sewer pipe roughness calculation unit 110, the manhole total area calculation unit 111, and the capacity calculation unit 112 are included. The outflow analysis parameter calculation unit 130 is collectively described.

  The runoff analysis parameter setting unit 114 sets runoff analysis parameters for the runoff analysis model based on the effective rainfall information.

  The outflow analysis parameter adjustment unit 115 adjusts the outflow analysis parameter set by the outflow analysis parameter setting unit 114 so that a more accurate outflow analysis result can be obtained. Specifically, the outflow analysis parameter adjustment unit 115 identifies the outflow analysis parameter based on the result of the outflow analysis by the outflow analysis unit 103 and the actual result information on the actual outflow in the diagnosis target area. The outflow analysis parameter adjustment unit 115 updates the existing outflow analysis parameter with the identified outflow analysis parameter.

  The record information storage unit 116 is configured using a storage device such as a magnetic hard disk device or a semiconductor storage device. The record information storage unit 116 stores record information used for adjusting the outflow analysis parameters. The performance information is information indicating a more likely outflow situation or inundation situation with respect to the outflow analysis result by the outflow analysis apparatus 1. For example, the record information may be information on the actual water level and flow rate of a sewer pipe existing in the target area, or information on actual inundation.

  The mesh result data generation unit 117 generates mesh result data indicating the result information for each mesh. The mesh result data generation unit 117 generates mesh result data by processing such as organization of result information and data conversion.

  The detailed analysis unit 118 performs a more detailed runoff analysis (hereinafter referred to as “detailed analysis”) than the runoff analysis performed by the runoff analysis unit 103 based on the effective rainfall information. For example, the detailed analysis unit 118 performs an outflow analysis using a distributed outflow analysis model. By performing such a detailed analysis, it is possible to obtain an outflow analysis result having a finer granularity than the mesh unit. For example, it is possible to obtain an outflow analysis result in units of each sewer pipe or manhole.

  For example, in the detailed analysis, the initial runoff phenomenon until the rain flows into the sewer pipe is simulated hydrologically using a model that considers the initial seepage loss of the rain or a nonlinear reservoir model. Is analyzed by using a hydraulic model of the open channel called the so-called Saint-Bennan equation. The method of solving the Saint-Bennan equation most accurately is called a dynamic wave method, and a diffuse wave method in which the inertia term of the dynamic wave method is omitted can also be used. Detailed outflow analysis using such a model is provided as package software such as Information, MOUSE, and SWMM, and is widely used in the consulting industry and the like. The detailed analysis unit 118 may be realized using such package software.

  The detailed data generation unit 119 for each mesh generates detailed analysis data for each mesh indicating the detailed analysis result for each mesh. The detailed data generation unit 119 for each mesh generates detailed data for each mesh by organizing detailed analysis results, data conversion, and the like.

  The evaluation index calculation unit 120 calculates an index value for determining the accuracy of the outflow analysis by the outflow analysis unit 103 based on a predetermined evaluation criterion. The evaluation index calculation unit 120 calculates this index value for each mesh in the target area. Hereinafter, the index value calculated for this mesh is referred to as an index value for each mesh.

  The analysis accuracy evaluation unit 121 evaluates the analysis accuracy regarding the evaluation target area in the target area based on the index value for each mesh. For example, the analysis accuracy evaluation unit 121 calculates the sum of the index values for each mesh of the meshes included in the evaluation target area, and evaluates the analysis accuracy of the evaluation target area based on the total. The analysis accuracy may be evaluated by a value other than the sum of the index values for each mesh. For example, the analysis accuracy may be evaluated using an arbitrary statistical value such as an average value, maximum value, minimum value, median value, variance, or deviation of the index value for each mesh. The analysis accuracy may be evaluated by a value calculated by a predetermined calculation formula using the index value for each mesh.

Hereinafter, a method for setting outflow analysis parameters in the present embodiment will be described in detail. In order to perform the outflow analysis described with reference to FIGS. 1 to 4, the mesh area A _m , the mesh side length L, the total manhole area A _h , the maximum storage amount S _max , the upper limit storage amount S _lim , the roughness n, the virtual sewage pipe diameter D and the virtual sewer gradient I _s needs to be appropriately set. First, a method in which the outflow analysis parameter setting unit 114 sets initial values of these parameters will be described.

[1. Setting of mesh area _Am and mesh side length L]
Since the mesh area _Am and the mesh edge length L are parameters common to all meshes, the mesh area calculated by the mesh area setting unit 106 is set as a parameter common to all meshes. For example, when using the data acquired by the X-band MP radar as rainfall distribution information, since the mesh side length L is L = 250 meters, mesh area _{A m} is a 250m × 250m = 6.25ha.

[2. Maximum storage amount _{S max,} setting the upper limit accumulation amount _{S lim} and manhole total area _{A h]}
Parameters other than the mesh area A _m is set using the sewer management register data. S _max , S _lim and A _h are parameters defined for each mesh in the target area. In the above runoff analysis model, one virtual sewer pipe and one virtual manhole are set for each mesh. Therefore, it is desirable that the parameters related to the virtual sewage pipes and virtual manholes of each mesh be a comprehensive representation of the sewage pipes and manholes actually existing in each mesh.

For example, S _max , S _lim, and A _h are calculated based on the actual sewer pipe capacity, manhole capacity, number of manholes, and the like indicated by the sewer management ledger data. Specifically, the capacity calculation unit 112 calculates the maximum storage amount _Smax of the virtual sewer pipe of each mesh by calculating the total sum of the capacities of the existing sewer pipes for each mesh. Further, the capacity calculation unit 112 calculates the maximum storage amount of the virtual manhole of each mesh by calculating the sum of the capacities of the actual manholes for each mesh. The capacity calculation unit 112 calculates the upper limit storage amount S _lim of each mesh by taking the sum of the maximum storage amount S _max of the virtual sewer pipe and the maximum storage amount of the virtual manhole. Furthermore, manhole total area calculation unit 111 calculates the manhole total area A _h of each mesh by calculating the sum of the cross-sectional area of the real manhole for each mesh.

[3. Setting of roughness n]
The parameters described above while a parameter that is set for each mesh, roughness n, virtual sewer diameter D and the virtual sewer gradient I _s is a parameter that is set between the meshes adjacent. The roughness n of the virtual sewer pipe is a parameter that appears only in the second term on the right side of Equation (13). The second term on the right side is a term indicating the flow rate represented by the Manning equation of equation (5). The roughness of the sewer pipe is usually determined by its material. For example, the roughness of a synthetic resin lining pipe is about 0.010, the roughness of a new concrete sewage pipe is about 0.013, and the roughness of an old sewage pipe made of concrete is about 0.015. Therefore, the roughness n is usually set in the range of 0.01 to 0.015, and is typically set to 0.013. The same applies to the distributed runoff analysis that performs detailed runoff analysis. Therefore, when the material variation of the sewer pipe is not large, a typical value such as 0.013 may be adopted as the roughness of the virtual sewer pipe. Moreover, when the roughness of an actual sewer pipe is acquirable, you may employ | adopt the average value of the roughness of the several sewer pipe which connects an adjacent mesh.

  On the other hand, when the material variation of the sewer pipe is large, the maximum value and the minimum value of the roughness of a plurality of sewer pipes connecting each mesh between all adjacent meshes are calculated in advance. The value obtained by the function defined in is set as the initial value of the roughness of each mesh. For example, the function may be a function for deriving one of the maximum value and the minimum value, or may be a function for deriving an average value of the maximum value and the minimum value.

[4. Setting of virtual sewage pipe diameter D]
The virtual sewage pipe diameter D is a parameter that appears not only in the second term (based on the Manning equation) on the right side of equation (13) but also in the water level calculation equations of equations (1) to (3). Expression (1) is an expression for deriving a value obtained by dividing the virtual sewage pipe diameter D by the storage amount and the maximum storage amount as a virtual water level. As described above, the virtual water level is a parameter that defines the dynamic water gradient, and is the parameter that has the greatest influence on the accuracy of the runoff analysis. Therefore, the virtual sewer pipe diameter D that affects the virtual water level needs to be set to an appropriate value.

This virtual sewage pipe diameter D is considered to be equal to or larger than the maximum pipe diameter among the pipe diameters of the actual plurality of sewage pipes connecting the meshes. For example, when a plurality of pipe diameters are given as d ₁ , d ₂ , d ₃ ,... And these sewer pipes are to be represented as one virtual sewer pipe, the flow rate of water flowing through the sewer pipe does not change. Therefore, the virtual sewer pipe diameter D is expressed as D = (d ₁ ² + d ₂ ² + d ₃ ² +...) ^1/2 . Therefore, the minimum value of the virtual sewer pipe diameter D is the maximum value among d ₁ , d ₂ , d ₃ . On the other hand, the virtual sewage pipe diameter D does not exceed the sum of d ₁ , d ₂ , d ₃ . Therefore, assuming that the maximum pipe diameter of the pipe diameters of the plurality of sewer pipes connecting the meshes is D _min and the sum of the pipe diameters of the plurality of sewer pipes connecting the meshes is D _max , the virtual sewer pipe diameter D The range of the value is D _min ≦ D ≦ D _max .

  The range of the value of the virtual sewage pipe diameter D can also be set based on the mathematical norm concept. For example, when assuming a virtual sewer pipe that is a circular pipe and has a constant gradient, the flow rate Q between meshes is expressed by the following equation (14) using the Manning equation of equation (5). In the formula (14), C is a constant calculated based on the roughness n and the gradient I.

Here, there Assuming the adjacent meshes are connected by two sewer, and the flow rate Q between adjacent meshes, the flow rate Q ₂ of the first sewer pipe flow Q ₁ and the second sewer pipe There should be a relationship of Q = Q ₁ + Q ₂ between them. This relationship is expressed as the following equation (15) when equation (14) is used.

In the equation (15), θ ₁ is an angle indicating the gradient of the first sewer pipe. D ₁ represents a pipe diameter of the first sewer pipe. θ ₂ is an angle indicating the gradient of the second sewer pipe. D ₂ represents a pipe diameter of the second sewer pipe. In order to express the virtual sewage pipe diameter D by only D ₁ and D _{2 according} to Expression (15), some assumptions are necessary for other parameters. For example, the following assumptions 1 to 3 can be placed.

<Assumption 1> The flow rate per sectional area of the virtual sewer pipe and the actual sewer pipe is constant.
This assumption is expressed by the following equation (16). Moreover, Formula (17) is formed from the relationship between Formula (16) and Q = Q ₁ + Q ₂ .

  Expression (17) is an expression that holds when two sewer pipes are assumed as the sewer pipes connecting between certain meshes. However, when this is expanded, when there are N sewer pipes connecting between certain meshes, The following equation (18) holds.

That is, under the assumption 1, the virtual sewer pipe diameter D can be expressed by the actual sewage pipe diameter _{D 1,} D _{2, · · ·,} with _{D N} the following equation (19).

<Assumption 2> The ratio of the actual flow rate to the maximum flow rate of each sewer pipe (flow rate ratio) is constant.
In general, it is known that the flow rate ratio is given by θ / 2π (1-sin θ / θ) ^ (5/3). Here, θ is an angle representing the gradient of each sewer pipe. The notation “A ^ B” represents A to the Bth power. In this case, Assumption 2 is expressed by the following equation (20).

  This equation (20) is an equation representing an assumption that the flow rate ratio between the virtual sewer pipe and the actual sewer pipe is constant. In this case, the following equation (16) is obtained from the equations (20) and (15).

  Here, as in the assumption 1, if the expression (21) is expanded to N sewer pipes, the following expression (22) is considered to be satisfied under the assumption 2.

In general, the p-norm (1 ≦ p ≦ ∞) of an n-order vector of X = [X ₁ , X ₂ ,..., X _n ] is mathematically defined as the following equation (23).

  Using this concept of norm, equation (19) representing the hypothetical sewer pipe diameter under assumption 1 means that the hypothetical sewer pipe diameter is given by 2 norms of the actual sewer pipe diameter. Equation (22) representing the virtual sewage pipe diameter below means that the virtual sewage pipe diameter is given by an 8/3 norm of the actual sewage pipe diameter.

<Assumption 3> The water level of the virtual sewer pipe is the same as the water level of the actual sewer pipe.
Assumption 3 is synonymous with assuming that the virtual sewer pipe diameter D is the sum _DMAX (= D ₁ + D ₂ +... + D _N ) of the sewer pipe diameters connecting adjacent meshes. In other words, assumption 3 is to assume that the virtual sewer pipe diameter D is one norm of the actual sewer pipe diameter.

  Although the assumptions 1 to 3 described above may be a relationship that does not strictly hold in an actual phenomenon, the hypothetical drainage pipe diameter D is set as the norm of the actual drainage pipe diameter by putting some assumptions in this way. Can be defined. In this way, the range of the value of the virtual sewage pipe diameter D can be defined as the range of the P (1 ≦ p ≦ ∞) norm of the actual sewage pipe diameter.

  The outflow analysis parameter setting unit 114 uses the value obtained by the function defined by the maximum value and the minimum value of the virtual sewer pipe diameter determined as described above as the initial value of the pipe diameter of the virtual sewer pipe connecting each mesh. Set. As in the case of the roughness n, the function may be a function for deriving one of the maximum value and the minimum value, or a function for deriving an average value of the maximum value and the minimum value. .

[5. Configuration of virtual sewer pipe slope _{I s]}
Given that a virtual sewage pipe is a virtual representation of a plurality of actual sewage pipes as a single sewage pipe, it is appropriate that the gradient represents a plurality of sewage pipes. Conceivable. Based on such an idea, the maximum value that can be taken by the virtual sewer pipe gradient (hereinafter referred to as “I _{s_max} ”) is set to the maximum value among the slopes of a plurality of sewer pipes connecting adjacent meshes. Conceivable.

On the other hand, in actual sewer pipes, the smaller the pipe diameter, the larger the gradient, and the larger the pipe diameter, the smaller the tendency is. Therefore, for example, the median value of the slopes of a plurality of sewer pipes connecting adjacent meshes may be _set as _{Is_max} . In this case, a relatively small gradient is adopted for I _{s_max} in an environment where a sewage pipe having a large pipe diameter is dominant, and a relatively large gradient is adopted for I _{s_max} in an environment where a sewage pipe having a small pipe diameter is dominant. become.

Note that the minimum value (hereinafter referred to as “I _{s_min} ”) that can be assumed by the virtual sewer pipe gradient may be simply 0, or the minimum value of the gradients of a plurality of sewer pipes connecting adjacent meshes may be adopted. May be.

  The outflow analysis parameter setting unit 114 uses the value obtained by the function defined by the maximum and minimum values of the virtual sewer slope determined in this way as the initial value of the pipe diameter of the virtual sewer pipe connecting each mesh. Set. The function may be a function for deriving one of the maximum value and the minimum value, or a function for deriving an average value of the maximum value and the minimum value, similarly to the other parameters.

Subsequently, a method in which the outflow analysis parameter adjustment unit 115 adjusts each of the above parameters will be described. Here, as an example, a description will be given of a method of adjusting the virtual sewer diameter D and the virtual sewer gradient I _s of the above parameters. The adjustment method described below can also be used as an adjustment method for other parameters.

  First, the outflow analysis parameter adjustment unit 115 receives data from the mesh actual data generation unit 117 as data for comparison with the outflow analysis result by the outflow analysis unit 103 and the inundation risk evaluation result by the inundation risk evaluation unit 104. Get the data. For example, the result data for each mesh is generated as information indicating the storage amount in mesh units in time series (hereinafter referred to as “storage amount time-series data”).

  On the other hand, the outflow analysis parameter adjustment unit 115 acquires an index value for each mesh from the evaluation index calculation unit 120. This mesh-specific index value J is calculated by, for example, the following equations (24) and (25) as the mean square error of the storage amount time-series data.

  In Expression (24), T represents an arbitrary evaluation period. In Expression (25), S (t) represents the storage amount time series data of a certain mesh, and S ^ (t) represents the storage amount time series data of the mesh calculated by the outflow analysis unit 103. In addition, the index value J for each mesh may be represented by a value other than the mean square error (average error). For example, the index value J for each mesh may be represented by a peak flow rate error that seems to have the most influence on the inundation. In this case, the index value J for each mesh is expressed by the following equation (26), for example.

  Further, for example, the index value J for each mesh may be expressed as an error at the time when the actual value takes the peak value. In this case, the index value J for each mesh is expressed by, for example, the following expressions (27) and (28).

  For example, the index value J for each mesh may be represented by each value associated with the coincidence of the presence or absence of inundation. In this case, the index value J for each mesh is expressed by the following equation (29), for example.

  Further, for example, the index value J for each mesh may be represented by a difference in the amount of flooding. In this case, the index value J for each mesh is expressed by the following equation (30), for example.

In equation (30), sum (S _over (t)) represents the actual total amount of inundation, and sum (S ^{^} _over (t)) represents the total amount of inundation obtained from the analysis result of the outflow analysis unit 103.

  In the above, a specific example of the index value J for each mesh has been described, but any value can be used as the index value J for each mesh that can be calculated as an index value related to the accuracy of the outflow analysis based on the result information and the outflow analysis result. Various index values may be used. The analysis accuracy evaluation unit 121 calculates an index value (hereinafter referred to as “evaluation value”) indicating the accuracy of analysis for the evaluation target area based on the index value for each mesh calculated in this way. For example, the analysis accuracy evaluation unit 121 calculates the sum of the index values for each mesh included in the evaluation target area as the evaluation value. Note that the evaluation target area may be the whole or a part of the target area.

Runoff Analysis parameter adjustment unit 115, based on the evaluation value calculated in the above manner, minimize its evaluation value (optimized) adjusts the virtual sewer diameter D and the virtual sewer gradient I _s as To do. Specifically, runoff analysis parameter adjustment unit 115, the respective virtual sewer diameter D and the virtual sewer gradient I _s, one taking values ranging from 0 to 1 the parameter alpha (hereinafter referred to as "Adjust Parameters". ) To adjust. α is set for each virtual sewer diameter D and the virtual sewer gradient I _s. Hereinafter, the adjustment parameters are set for the virtual sewer pipe diameter D is described as alpha _1, an adjustment parameter to be set for the virtual sewer gradient I _s to as alpha _2. In addition, a parameter to be adjusted using the adjustment parameter α is hereinafter referred to as an adjustment target parameter. Adjusted parameters Here, specifically, a virtual sewer pipe diameter D and the virtual sewer gradient I _s.

  α is a parameter defined such that the adjustment target parameter takes the minimum value when α = 0, and the adjustment target parameter takes the maximum value when α = 1. The outflow analysis parameter adjustment unit 115 uses the adjustment parameter to vary the adjustment target parameter within the range from the maximum value to the minimum value, and causes the detailed analysis unit 118 to perform the detailed analysis, thereby obtaining a plurality of detailed analysis results. obtain. The outflow analysis parameter adjustment unit 115 sets the evaluation value calculated based on the result of the detailed analysis executed by the detailed analysis unit 118 and the result of the outflow analysis executed by the outflow analysis unit 103, as a plurality of detailed analysis results. Get every. The evaluation value acquired here is calculated by the same method as the above-described evaluation value calculated based on the result of the outflow analysis executed by the outflow analysis unit 103 and the actual data for each mesh. The outflow analysis parameter adjustment unit 115 adjusts the adjustment target parameter using the value determined by the adjustment parameter that gives the minimum value of the plurality of evaluation values obtained in this way as the adjusted parameter value. The maximum value and the minimum value that define the variation range of the adjustment target parameter are calculated by the outflow analysis parameter setting unit 114 by the above-described method.

For example, effluent analysis parameter adjustment unit 115, a virtual sewer diameter D and the virtual sewer gradient I _s, is varied based on the following equation (31) and (32).

  The runoff analysis device 1 of the embodiment configured as described above extends the conventional virtual tank model, and the virtual tank is represented by a virtual sewer pipe and a virtual manhole connecting the virtual sewer pipe and the ground surface. It has a configuration that performs runoff analysis using an analysis model. By providing such a configuration, it is possible to obtain a more realistic outflow analysis result while using a simple analysis model.

  Furthermore, the spill analysis device 1 of the embodiment is based on the spill analysis parameter setting unit 114 that sets the initial value of the spill analysis parameter within a range of probable values having a physical basis, based on the results information and the results of the detailed analysis. And an outflow analysis parameter adjusting unit 115 for adjusting the outflow analysis parameter. By providing such a configuration, the outflow analysis device 1 of the embodiment can further improve the accuracy of the above-described outflow analysis by including such a configuration.

In addition, a lot of meshes are often included in the area to be subjected to the runoff analysis, and the ordinary runoff analysis parameter adjustment method requires a lot of calculations for parameter adjustment. Specifically, there is a need to identify 2 × N number of parameters when the virtual pipe diameter D and the virtual sewer gradient I _s to be estimated independently for each mesh when the number of mesh was N. On the other hand, the outflow analysis apparatus 1 of the embodiment identifies each outflow analysis parameter by estimating one adjustment parameter α that varies each outflow analysis parameter within a range of probable values having a physical basis. To do. Therefore, the outflow analysis apparatus 1 of the embodiment can reduce the amount of calculation related to adjustment of the outflow analysis parameter, and can adjust the outflow analysis parameter in a shorter time.

  Also, in general, when there are a large number of parameters to be adjusted or when sufficient performance information for evaluation is not obtained, the result of parameter identification may vary greatly depending on the data used for identification. Known as. On the other hand, the outflow analysis device 1 of the embodiment sets the initial value of the outflow analysis parameter within a range of probable values having a physical basis. Therefore, each outflow analysis parameter is not identified as a value outside the range, and variations in parameter identification results can be reduced.

  Hereinafter, a modified example of the outflow analysis device 1 of the embodiment will be described.

<First Modification>
In the first modification, the outflow analysis parameter adjustment unit 115 adjusts the virtual sewer pipe diameter D based on the following equation (33) instead of the equation (31).

Expression (33) is an expression in which the virtual sewage pipe diameter D is defined as the Nth-order p-norm of the pipe diameter of the existing sewage pipe. N is the total number of meshes, and p is a parameter that can be adjusted in the range of 1 to ∞. As described above, since the p-norm has a property of monotonously decreasing with respect to p (norm number), the virtual sewer pipe diameter D takes the value of D _max when p = 1, and the value of D _min when p = ∞. Takes a value. In this case, the outflow analysis parameter adjustment unit 115 uses p as an adjustment parameter instead of α, and searches for p that minimizes the evaluation value while varying p in the range of 1 to ∞. Thus, by using the p when the virtual sewer diameter D defined p-norm as an adjustment parameter, not by simple linear interpolation of the virtual sewer diameter D D _max and D _min, D _max and D It can be expressed by non-linear interpolation corresponding to p of _min . In such non-linear interpolation, the virtual sewer pipe diameter D can be finely adjusted finer as the virtual sewer pipe diameter D approaches _Dmin . Further, as described above, when the virtual sewer pipe diameter D is defined as the p-norm of the pipe diameter of the existing sewer pipe, it is assumed that the value of p varies depending on the assumption set based on hydraulics. Is done. Therefore, the value of p obtained by searching for the optimum value not only uniquely determines the virtual sewage pipe diameter D, but also hydraulically determines the result of the runoff analysis obtained using the determined virtual sewage pipe diameter D. It can be useful for proper consideration.

<Second Modification>
The second modification is a two-stage parameter adjustment method in which the first parameter adjustment is performed by the adjustment method described in the above embodiment, and the second parameter adjustment is performed by the following method. In actual outflow analysis, a situation may occur in which an analysis error of a specific mesh is larger than an analysis error of another mesh. The reason why such a situation occurs is not necessarily clear, but may be caused by a storage caused by a structural reason of the sewage pipe, such as a step joint of the sewage pipe in the vicinity of a specific mesh. The difference in analysis accuracy caused by such a reason can be grasped by comparing the index values for each mesh. Specifically, the outflow analysis parameter adjustment unit 115 identifies a mesh (hereinafter, referred to as “low-accuracy mesh”) whose analysis accuracy is partially reduced by the following equation (34).

In Expression (34), J _ij represents an index value for each mesh of the mesh identified by i and j (hereinafter referred to as “mesh (i, j)”), and J _all represents each mesh of each mesh in the evaluation target area. Indicates the average value of the index value. For example, J _all may be an average value or an intermediate value. σ _J represents the variance of the index value for each mesh of each mesh included in the evaluation target area. k is a parameter for adjustment, and is generally set to a value of about 2 to 3 statistically. That is, Expression (34) is an expression for determining whether or not the index value for each mesh of a certain mesh is significantly lower than the average index value based on the dispersion of the index values for each mesh.

FIG. 6 is a diagram illustrating a specific example of a low-precision mesh that exists locally. FIG. 6 shows an example of a diagnosis target area composed of M × N (M = 5, N = 5) meshes. For example, the outflow analysis parameter adjustment unit 115 identifies the mesh (2, 2) as a low-accuracy mesh by performing a determination using Expression (34) for each of 25 (= 5 × 5) meshes. Then, the outflow analysis parameter adjustment unit 115 uses the index value for each mesh of the mesh (hereinafter, referred to as “peripheral mesh”) located around the identified mesh (2, 2), to determine the mesh (2, 2). The local evaluation function J _local is calculated by the following equation (35).

In the equation (35), J _ij (i = 1, 2,..., J = 1, 2,...) Represents an index value for each mesh of the mesh (i, j). That is, the expression (35) is an expression having an average value of the index values for each mesh of the mesh (2, 2) and the surrounding mesh as an evaluation function. Here, the mesh (1, 2), the mesh (2, 1), the mesh (2, 3), and the mesh (3, 2) are the peripheral meshes of the mesh (2, 2). The mesh (1,1), mesh (1,3), mesh (3,1), and mesh (3,3) located in the diagonal direction of 2) may be included in the peripheral mesh. In addition, the peripheral mesh may be configured with a mesh in a wider range than the above located around the mesh (2, 2).

The outflow analysis parameter adjusting unit 115 identifies the virtual sewer pipe diameter D _ij and the virtual sewer pipe slope Is _(ij) of the surrounding mesh so as to minimize the value of the evaluation function J _total thus calculated. In this case, since there are eight parameters to be identified for one low-accuracy mesh, identification with a simple search method such as a binary search may be difficult. Therefore, the parameter identification method here includes data assimilation methods such as particle filter (particle filter), ensemble Kalman filter, Markov chain Monte Carlo method (MCMC), genetic algorithm (GA), particle swarm optimization (PSO), etc. Or a metaheuristic approach may be used. In the following, the parameter identification procedure when using the particle filter is shown.

First, a plurality of candidate values are generated for each of the eight parameters (D ₁₂ , D ₃₂ , D ₂₁ , D ₂₃ , I ₁₂ , I ₃₂ , I ₂₁ , I ₂₃ ) to be identified. The eight parameters are represented by the vector X = [X ₁ , X ₂ , X ₃ , X ₄ , X ₅ , X ₆ , X ₇ , X ₈ ] = [D ₁₂ , D ₃₂ , D ₂₁ , D ₂₃ , I ₁₂ , I ₃₂ , I ₂₁ , I ₂₃ ], candidate values are generated by the following equation (36).

In equation (36), X _now represents the current parameter value. That is, X _now is a parameter value adjusted by the first parameter adjustment method. X _sigma represents the standard deviation of each parameter value. In addition, since the standard deviation σ covers 99% of the population with 3σ, when calculation of X _sigma is difficult, for example, X _sigma = (X _max −X _min ) / 3 is simply set. May be. Here, X _max and X _min correspond to the maximum value and the minimum value of each parameter set by the first parameter adjustment method. Also, rand (0, 1) represents a normal random number having an average of 0 and a standard deviation of 1. P represents the number of particles in the particle filter. For example, when P = 100, 100 combinations of candidate parameter values are set based on X _now . P may be arbitrarily set as necessary.

  In addition, by replacing rand (0, 1) in equation (36) with diag (rand (0, 1), rand (0, 1),..., Rand (0, 1)) It is also possible to give a numerical value. Note that diag (element,...) Means a diagonal matrix having each element as a diagonal component.

After generating P parameter sets (= particles) according to the equation (36), the outflow analysis similar to the outflow analysis unit 103 is performed using the outflow analysis parameters of each parameter set. In general, in the particle filter, weighting is performed with the likelihood of the prediction error of the analysis result. However, for the sake of simplicity, the value of the evaluation function J _local shown in Expression (35) is used instead of the above likelihood. Define the goodness of fit. In this case, the fitness L is defined as the following equation (37).

In Expression (37), σ represents the standard deviation of J _local (k). For example, when the number of particles P = 100, the evaluation function J for each parameter set identified by k based on the result of the outflow analysis performed using 100 parameter sets generated by the equation (36). _local (k) is calculated in advance. Then, the weight W (k) of each particle is defined as the following equation (38) using the fitness L calculated by the equation (37).

  The weight W (k) of each particle k calculated by Expression (38) takes a value in the range of 0-1. After the weight W (k) is calculated, the particle X (k) is replicated as in the following equation (39) according to the weight ratio.

Equations (39) and (36) are similar, but differ in the following three points. One of the differences is that the first term on the right side is the value X (k) of the kth particle. Another difference is that the number of particles newly generated as X _new (l) is a number equal to or less than P corresponding to the weight ratio of each particle of the replication source. At this time, the sum total of the number of particles newly generated by Equation (39) for all k is P. Also one of the other difference is that the standard deviation is in the different X _'sigma and _{X simga.} Here, X ′ _sigma is a constant for giving fluctuation to each parameter, and is set to a value smaller than X _sigma . For example, X ′ _sigma = and X _sigma / 2 may be set.

This equation (39) generates P (= 100) new particles (parameter set) represented by X _new (l). By repeatedly executing such parameter set generation and outflow analysis using the generated parameter set, a parameter set that minimizes the value of the evaluation function J _local is finally obtained. The outflow analysis parameter adjustment unit 115 may be configured to repeat these processes until the variation in the fitness L becomes a predetermined value or less, or may be configured to repeat a predetermined number of times. Also good.

  The outflow analysis parameter adjustment unit 115 determines the updated parameter set by calculating the representative value of the P (= 100) particles (parameter set) thus obtained. An average value is typically used as the representative value calculated here, but if the influence of an outlier cannot be ignored, a median value may be used instead of the average value.

  The parameter adjustment method described as the second modification can partially improve the mesh outflow analysis parameter with insufficient analysis accuracy, although a certain amount of calculation load is required. In addition, although a certain amount of calculation load is required, the amount of calculation required for the parameter adjustment method of the second modification is sufficiently small as compared with the case where the outflow analysis parameters are individually estimated for all meshes. Therefore, the outflow analysis parameter can be adjusted in a shorter time and effectively.

<Third Modification>
The third modification is a parameter adjustment method for calculating an evaluation value used for evaluation of analysis accuracy in the first parameter adjustment using an index value for each mesh of a part of meshes. This is based on the assumption that the outflow analysis parameter is to be adjusted by paying attention to a specific range of meshes, rather than being calculated only for a part of meshes having a certain index value for each mesh. In such a parameter adjustment method, for example, a case where attention is paid to a flooded area is assumed.

  FIG. 7 is a diagram illustrating a specific example of the evaluation target mesh set in accordance with the flooded area. In this case, it is possible to identify an outflow analysis parameter more suitable for evaluating the inundation risk by paying attention only to the index value for each mesh of the mesh corresponding to the inundation normal attack area (shaded portion in the figure).

<Fourth Modification>
The fourth modification is a parameter adjustment method that uses the result of the outflow analysis by the detailed analysis unit 118 instead of the performance information as information for evaluating the accuracy of the outflow analysis by the outflow analysis unit 103. In this case, the mesh result data generation unit 117 generates the mesh result data by organizing or converting the result of the outflow analysis by the detailed analysis unit 118 in the same manner as the result information. The outflow analysis parameter adjustment unit 115 adjusts the outflow analysis parameters by the same method as described above based on the result data for each mesh generated from the result of such detailed analysis.

  The outflow analysis parameter adjustment unit 115 may be configured to use the result of the detailed analysis when the actual information does not exist, or substitute the result of the detailed analysis for some information for which the actual information is not obtained. It may be configured to. When there is a large difference between the result information and the result of the detailed analysis, it is desirable that the outflow analysis parameter adjustment unit 115 adjust the result of the detailed analysis in advance so as to match the result information.

<Fifth Modification>
The fifth modification is a parameter adjustment method in the case where only information indicating the inundation state can be acquired as the result information. The information indicating the occurrence of inundation here is information indicating the correspondence between the presence / absence of inundation or the amount of inundation in each mesh and the inundation occurrence time. In such a case, the outflow analysis parameter adjustment unit 115 can adjust the outflow analysis parameter only by the information indicating the inundation performance by defining the evaluation value as in Expression (29) or Expression (30). For example, at the initial stage of flood control measures such as building a runoff analysis model for a new diagnosis target area, there is often little information that can be acquired about the target area, and the runoff analysis parameters are set with some accuracy and efficiency. Difficult to do. According to the parameter adjustment method of the fifth modification, it is possible to set the outflow analysis parameter with a certain degree of accuracy even in such an initial stage.

  According to at least one embodiment described above, an evaluation value related to the accuracy of the outflow analysis is calculated for each mesh based on the result of the outflow analysis and the actual information about the actual outflow in the diagnosis target area, and the calculated evaluation value An analysis accuracy evaluation unit that determines the accuracy of the spill analysis based on the analysis accuracy evaluation unit, and a virtual pipeline representative of the pipelines that exist in each mesh used in the spill analysis according to the accuracy of the spill analysis evaluated by the analysis accuracy evaluation unit By having the outflow analysis parameter adjusting unit that adjusts the diameter and the gradient, it is possible to more appropriately determine (set or adjust) the parameters of the outflow analysis model constructed using the virtual parameters.

  Although several embodiments of the present invention have been described, these embodiments are presented by way of example and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the spirit of the invention. These embodiments and modifications thereof are included in the invention described in the claims and their equivalents, as well as included in the scope and gist of the invention.

DESCRIPTION OF SYMBOLS 1 ... Runoff analysis apparatus, 101 ... Rainfall distribution input part, 102 ... Runoff coefficient calculation part, 103 ... Runoff analysis part, 104 ... Inundation risk evaluation part, 105 ... Map information storage part, 106 ... Mesh area setting part, 107 ... Sewer Management ledger data storage unit 108 ... virtual sewage pipe diameter calculation unit 109 ... virtual sewage pipe gradient calculation unit 110 ... virtual sewage pipe roughness calculation unit 111 ... manhole total area calculation unit 112 ... capacity calculation unit 113 ... Diagnosis result display unit, 114 ... Outflow analysis parameter setting unit, 115 ... Outflow analysis parameter adjustment unit, 116 ... Result information storage unit, 117 ... Result data generation unit for each mesh, 118 ... Detailed analysis unit, 119 ... Detailed data generation for each mesh , 120 ... Evaluation index calculation unit, 121 ... Analysis accuracy evaluation unit, 130 ... Outflow analysis parameter calculation unit

Claims (9)

A rainfall distribution input unit that inputs rainfall distribution information indicating the rainfall amount of each mesh that is the rainfall amount of the diagnosis target area divided into a plurality of meshes;
An outflow analysis unit for performing a first outflow analysis for calculating a storage amount of each mesh by calculating a balance of flow rate between the meshes based on the rainfall distribution information;
Based on the result of the outflow analysis by the outflow analysis unit and the actual information on the actual outflow in the diagnosis target area, the evaluation value related to the accuracy of the outflow analysis is calculated for each mesh, and based on the evaluation value An analysis accuracy evaluation unit for determining the accuracy of the outflow analysis;
An outflow analysis parameter adjusting unit for determining a diameter and a gradient of a virtual pipe representing the pipe existing in each mesh used in the outflow analysis according to the accuracy of the outflow analysis evaluated by the analysis accuracy evaluation unit; ,
An outflow analysis device comprising: The outflow analysis parameter adjustment unit sets a maximum value and a minimum value that can be taken by the diameter and the gradient of the virtual pipe, and changes the diameter or the gradient using an adjustment parameter that can be adjusted within a predetermined range. Identifying the diameter and gradient of the virtual conduit that optimizes the evaluation value,
The outflow analysis device according to claim 1. The adjustment parameter is a parameter that can be adjusted within a range of 0 to 1.
The outflow analysis device according to claim 2. The outflow analysis parameter adjustment unit represents the diameter of the virtual pipe line by the p-norm of the diameters of the actual plurality of sewage pipes connecting the adjacent meshes, and takes a value in the range of 1 to ∞ for the p-norm. By changing the diameter using the norm number p,
Identifying the diameter and slope of the virtual conduit that optimizes the evaluation value;
The outflow analysis device according to any one of claims 1 to 3. The outflow analysis parameter adjustment unit identifies the diameter and gradient of the virtual pipe line based on the evaluation value of the mesh in the range for the mesh in the range including the predetermined mesh determined based on the evaluation value.
The outflow analysis device according to any one of claims 1 to 4. The outflow analysis parameter adjustment unit uses as an index value an error in the peak flow rate of each mesh between the results information and the result of the outflow analysis, an average error of the peak flow rate, or an inundation occurrence state, Identifying the diameter and gradient of the virtual pipe for the mesh to be evaluated based on the index value of each mesh to be evaluated in the diagnosis target area;
The outflow analysis device according to any one of claims 1 to 5. Based on the rainfall distribution information, further comprising a detailed analysis unit for performing a second runoff analysis more detailed than the runoff analysis unit with respect to the diagnosis target area,
The outflow analysis parameter adjustment unit identifies the diameter and gradient of the virtual pipeline based on the result of the outflow analysis by the outflow analysis unit and the result information or the result of the second outflow analysis.
The outflow analysis device according to any one of claims 1 to 6. The information indicating the occurrence of the inundation is information indicating the correspondence between the occurrence of inundation or the amount of inundation in each mesh and the occurrence time of the inundation,
The outflow analysis device according to claim 6 or 7. A rainfall distribution input step for inputting rainfall distribution information indicating the rainfall amount of each of the meshes, which is information indicating the rainfall amount of the diagnosis target area divided into a plurality of meshes;
An outflow analysis step for calculating a storage amount of each mesh by calculating a balance of flow rate between each mesh based on the rainfall distribution information;
Based on the result of the outflow analysis by the outflow analysis unit and the actual information on the actual outflow in the diagnosis target area, the evaluation value related to the accuracy of the outflow analysis is calculated for each mesh, and based on the evaluation value An outflow analysis result evaluation step for determining the accuracy of the outflow analysis;
An outflow analysis parameter adjustment step for determining a diameter and a gradient of a virtual pipe representing a pipe existing in each mesh used for the outflow analysis according to the accuracy of the outflow analysis evaluated by the analysis accuracy evaluation unit; ,
A method for adjusting outflow analysis parameters.

Images