Information processing device, water resources management method, information processing method, and program

Abstract

To solve a problem of a conventional information processing apparatus that cannot easily identify an important dominant factor for a water resource in each target area.SOLUTION: An information processing apparatus 1 includes: a calculation unit 151 which acquires a water balance calculation value on a balance of a water resource in a predetermined area, on the basis of values applied for each of two or more parameters on circulation state of the water resource in the predetermined area; an extraction unit 141 which causes the calculation unit 151 to acquire the water balance calculation values with modified values of the parameters to perform sensitivity analysis on the effect of the parameters on the water balance calculation values, and extracts a highly effective parameter which has a large effect on the water balance calculation values as the predetermined condition is satisfied; and an output unit 160 which outputs an identifier for identifying the highly effective parameter extracted by the extraction unit 141. The information processing apparatus can easily identify an important dominant factor for a water resource in each target area.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present invention relates to an information processing device, a water resources management method, an information processing method, and a program for identifying important control factors for managing water resources in a space having a certain spatial extent. [Background technology]

[0002] In recent years, when operating facilities such as factories, it is necessary to be aware of the amount of water resources in spatial units of a certain area, such as each facility or a river basin that includes the facility. For example, the amount of water resources in a target area is monitored, the monitoring results are analyzed, and the analysis results are used in production activities, water resource operation and management, water resource conservation activities, etc. For such activities, it is desirable to make future predictions that take into account the time scale so that effective future plans can be formulated and appropriate operation and management can be carried out.

[0003] That is, conventionally, when production activities are carried out in a factory or the like, regardless of the type of product being produced, large amounts of water resources are used for purposes such as boilers, raw materials, product processing, equipment cleaning, equipment cooling, temperature control equipment cleaning water, etc. Facilities that use water resources include facilities that own wells and draw water from them, and facilities that use tap water or industrial water purchased from the national or local government. In any water intake method, water resources in the river basin surrounding the facility or water resources in the vicinity are used.

[0004] Whether a facility can continue to operate depends on the sustainability of water resources in the basin around the facility. In order to increase the sustainability of water resources, it is important not only to improve the efficiency of water resource use at the facility, but also to develop an operation plan for the facility that minimizes the impact on water resources in the basin around the facility. Specifically, for example, when formulating an operation plan for a facility, it is necessary to pay close attention to various water-related indicators such as river water levels, groundwater levels, and spring water volume. In addition, if the sustainability of water resources in the basin around the facility is estimated to be low, it is necessary to develop an implementation plan for activities such as rice paddy cultivation and forest conservation activities to protect water resources.

[0005] However, it is not easy to accurately grasp the behavior of water in a certain geosphere environment with a certain extent. Water repeats various behaviors such as evaporation, transpiration, rainfall, snowfall, river flow, infiltration, groundwater flow, and springs between various systems such as the atmosphere, the earth's surface, and even underground, and is recharged and stored as groundwater or flows out from the area.

[0006] Therefore, in order to confirm the sustainability of water resource security at the facility level and at the basin level including the facility, it is necessary to monitor the water resource balance within the basin. It is also necessary to properly manage the flow, storage, and fluctuation of water resources at the facility level and at the basin level including the facility (hereinafter referred to as the water balance of the target area).

[0007] However, it is not realistic to grasp all the parameters related to the water balance of the target area at all points in the basin. In particular, when managing quantities that are difficult to directly observe, such as recharge quantities at points that are difficult to access, such as mountainous regions, or groundwater flow, it is difficult to manage them appropriately because it is not possible to obtain observed values ​​for these quantities.

[0008] In light of these problems, water cycle models have been used to manage water resources. These water cycle models are classified into centralized models and distributed water cycle models (see, for example, Non-Patent Document 1).

[0009] Lumped-scale models have the advantage that they require a small amount of data for calculation, are relatively easy to calculate, and are easy to systematize. However, it can be relatively difficult to reproduce or predict the water cycle with high accuracy using a lumped-scale model.

[0010] On the other hand, in a distributed water circulation model, the target space is divided into fine meshes, and the water circulation can be reproduced according to the physical laws of water circulation in each mesh. Therefore, it is possible to reproduce phenomena close to the real water circulation with a relatively high degree of accuracy. In other words, a distributed water circulation model is suitable for the purpose of managing the production capacity of a facility (see Non-Patent Documents 2 and 3). Examples of such distributed water circulation models include those described in Patent Document 1 and Non-Patent Document 4. [Prior art documents] [Patent documents]

[0011] [Patent Document 1] JP 2011-13753 A [Non-patent literature]

[0012] [Non-Patent Document 1] Nissui Consulting Co., Ltd., "Distributed Flood Forecasting Model | Nissui Consulting Co., Ltd. - Towards a Prosperous Future," [online], [Retrieved June 12, 2020], Internet<URL:http: / / www.nissuicon.co.jp / jigyou / kasen / kouzui-yosoku / > [Non-Patent Document 2] Hiroyuki Tosaka, Keiji Kojima, Akio Miki, Takeshi Chino, Development of a 3D Land-Water Simulation Method Coupling Surface and Groundwater Flows, Journal of the Japanese Society of Groundwater Hydrology, 1996, Vol. 38, No. 4, pp. 253-267 [Non-Patent Document 3] Koji Mori, Kazuhiro Tada, Takeshi Sato, Nobuko Kakizawa, Yoshimi Uchiyama, Naohide Yokoyama, Masanobu Yamane, Three-dimensional water circulation model of the water source area of ​​Kanagawa Prefecture, Kanagawa Prefectural Environmental Protection Society Report 10 (2013) 215-223. [Non-Patent Document 4] McDonald, Michael G. and Arlen W. Harbaugh. “A modular three-dimensional finite-difference ground-water flow model.” Techniques of water-resources investigations (1984) Summary of the Invention [Problem to be solved by the invention]

[0013] As mentioned above, in order to carry out production activities using water resources in a sustainable manner at each facility and at each watershed including the facility, it is necessary to properly manage the flow, storage, and fluctuation of water resources (hereinafter referred to as the water balance of the target area). In order to properly manage the water balance of the target area, it may be necessary to carry out water resource conservation activities in the target area as necessary.

[0014] There are many types of water resource conservation activities. In other words, there are many indicators of controlling factors that affect the water balance, such as understory vegetation, soil, riverbed, trees, surface geology, and deep geology. However, resources such as labor and costs for activities are limited, and it is difficult to carry out all conservation activities related to each of these controlling factors. Therefore, it is necessary to carry out effective conservation activities, such as prioritizing conservation activities for important controlling factors that are particularly likely to affect the water resources under management, in order to efficiently manage water resources.

[0015] In the past, it was difficult to easily identify the key controlling factors for water resources in each target region.

[0016] An object of the present invention is to provide an information processing device, a water resources management method, an information processing method, and a program that can easily identify important control factors for water resources in each target area. [Means for solving the problem]

[0017] The information processing device of the first invention is an information processing device comprising: a calculation unit that acquires a water balance calculated value regarding the balance of water resources in a specified area based on values ​​applied to each of two or more parameters related to the circulation state of water resources in the specified area; an extraction unit that performs a sensitivity analysis on the influence of each parameter on the water balance calculated value by changing the value of each parameter and having the calculation unit acquire a water balance calculated value, and extracts high-impact parameters that have a large influence on the water balance calculated value to the extent that they satisfy predetermined conditions; and an output unit that outputs an identifier that identifies the high-impact parameters extracted by the extraction unit.

[0018] With this configuration, it is possible to easily identify what the important controlling factors are for water resources in each target area.

[0019] In addition, the information processing device of the second invention is an information processing device in which, compared to the first invention, the extraction unit ranks each of the high-influence parameters to be extracted in order of the greatest influence each parameter has on the calculated water balance value, and the output unit outputs an identifier depending on the ranking result.

[0020] With this configuration, it is possible to identify important control factors for water resources in each target region in order of their influence on the calculated water balance.

[0021] In addition, the information processing device of the third invention is an information processing device according to the first or second invention, in which the extraction unit acquires observation data regarding one or more parameters and the balance of water resources, and sets the value of each parameter corresponding to the acquired observation data and the values ​​of other parameters so that the water balance calculated value corresponds to the acquired observation data regarding the balance of water resources, and a post-change calculation unit changes the value of the parameter set by the parameter setting unit for each parameter to acquire a post-change calculated value regarding the balance of water resources, and extracts highly impacted parameters based on the post-change calculated value calculated by the post-change calculation unit for each parameter.

[0022] With this configuration, it is possible to reliably extract parameters that are highly sensitive to the calculated water balance value.

[0023] Furthermore, the information processing device of the fourth invention is an information processing device in which, compared to the third invention, the post-change calculation unit changes the value of the parameter set by the parameter setting unit by a predetermined rate to obtain a post-change calculated value for each parameter, and the extraction unit extracts the parameter as a high-influence parameter when the difference or ratio between the water balance calculated value obtained using the value set by the parameter setting unit and the post-change calculated value for each parameter is equal to or greater than a predetermined threshold value.

[0024] With this configuration, it is possible to reliably extract parameters that are highly sensitive to the calculated water balance value.

[0025] Furthermore, the information processing device of the fifth invention is an information processing device in which, compared to the third invention, the post-change calculation unit changes the value of each parameter set by the parameter setting unit to the maximum and minimum values ​​of the possible range to obtain two post-change calculated values, and the extraction unit extracts, for each parameter, the parameter as a high-influence parameter when the difference or ratio between the two post-change calculated values ​​is equal to or greater than a predetermined threshold value.

[0026] With this configuration, it is possible to reliably extract parameters that are highly sensitive to the calculated water balance value.

[0027] In addition, the information processing device of the sixth invention is an information processing device relative to any of the first to fifth inventions, wherein the extraction unit extracts a high-influence parameter from among two or more parameters that are determined to have a property that can change depending on the activity of the worker.

[0028] With this configuration, it is possible to extract parameters that are highly sensitive to the calculated water balance value from among parameters that can be affected by human activities.

[0029] In addition, an information processing device of the seventh invention is an information processing device according to the sixth invention, in which the extraction unit is configured to determine parameters relating to elements located above a point at a predetermined depth from the earth's surface as parameters having properties that can change in response to the activity of a worker.

[0030] With this configuration, parameters that are easily influenced by human activity can be extracted.

[0031] In addition, the information processing device of the eighth invention is an information processing device that, compared to the sixth or seventh invention, further includes a reception unit that receives from a user a designation operation specifying whether or not a parameter in a specified area can be a target of a worker's activity, and associates the designation operation with each parameter, and the extraction unit is configured to determine that the parameter designated as being a target of a worker's activity by the designation operation received by the reception unit is a parameter having a property that can change depending on the worker's activity.

[0032] With this configuration, it is possible to extract parameters that exist on-site.

[0033] In addition, the information processing device of the ninth invention is an information processing device relative to any of the first to eighth inventions, in which the water balance calculation value relates to the flow volume, storage volume, or fluctuations of water resources in a specified area.

[0034] With this configuration, it is possible to easily identify what are the important controlling factors for the flow volume, storage volume, or fluctuations of water resources in each target area.

[0035] In addition, the information processing device of the tenth invention is an information processing device relative to any of the first to eighth inventions, in which the water balance calculated value relates to the groundwater flow volume, storage volume, or fluctuations thereof in a specified area.

[0036] With this configuration, it is possible to easily identify the important controlling factors for the groundwater flow volume, storage volume, or fluctuations therein in each target area.

[0037] An information processing device according to an eleventh aspect of the present invention is an information processing device according to any one of the first to eighth aspects of the present invention, wherein the water balance calculation value relates to an amount of groundwater recharge in a predetermined area.

[0038] With this configuration, it is possible to easily identify what the important controlling factors are for groundwater recharge in each target area.

[0039] In addition, the information processing device of the twelfth invention is an information processing device relative to any of the first to eleventh inventions, wherein the calculation unit obtains a water balance calculation value using a distributed water circulation model constructed using a parameter group including two or more parameters, which models the circulation state of water resources in a specified area.

[0040] With this configuration, it is possible to easily identify what the important controlling factors are for water resources in each target area.

[0041] In addition, the water resources management method of the thirteenth invention is a water resources management method for managing water resources in a specified area, which includes the steps of acquiring an identifier output by an output unit of an information processing device configured to acquire a water balance calculation value relating to the balance of water resources in the specified area, and changing the state of the controlling element in the specified area corresponding to the acquired identifier.

[0042] With this configuration, effective conservation activities can be carried out in each target area, and water resources can be managed efficiently. Effect of the Invention

[0043] According to the information processing device of the present invention, it is possible to easily identify what are the important controlling factors for water resources in each target area. [Brief description of the drawings]

[0044] [Figure 1] FIG. 1 is a diagram for explaining an example of a distributed water circulation model according to one embodiment of the present invention. [Diagram 2] Flowchart explaining the use of the distributed water cycle model [Diagram 3] Block diagram of the information processing device [Figure 4] A flowchart showing an operation of the information processing device for extracting high-influence parameters. [Diagram 5] A flowchart showing an example of an extraction process performed by the information processing apparatus. [Figure 6] A flowchart showing a water resource management method using the information processing device. [Figure 7] Overview of the computer system according to the above embodiment. [Figure 8] Block diagram of the computer system [Figure 9] FIG. 1 is a diagram for explaining vegetation distribution in this embodiment. [Figure 10] FIG. 1 is a diagram for explaining geological divisions in this embodiment. [Figure 11]A comparison of the specific flow rate and effective precipitation estimated from mesh normal values ​​in this example. [Figure 12] FIG. 1 shows an image of the hydraulic conductivity setting in this embodiment. [Figure 13] FIG. 1 is a diagram for explaining the results of sensitivity analysis in this embodiment. [Figure 14] Diagram explaining the effects of management measures DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0045] Hereinafter, an embodiment of an information processing device and the like will be described with reference to the drawings. Note that, in the embodiments, components with the same reference numerals perform similar operations, and therefore repeated description may be omitted.

[0046] The terms used below are generally defined as follows. The meanings of these terms should not always be interpreted as shown here, but rather, when they are explained individually below, they should be interpreted in light of that explanation.

[0047] Water resources include, for example, groundwater, river water, stored water such as lake water, spring water, etc., but are not limited to these.

[0048] An identifier for an item is a character or code that uniquely identifies the item. Codes are, for example, alphanumeric characters or other symbols, but are not limited to these. An identifier is, for example, a code string that does not indicate a specific meaning in itself, but any type of information is acceptable as long as it can identify the corresponding item. In other words, an identifier may be the name of the thing it indicates, or a combination of codes that uniquely correspond to the thing. A combination of two or more pieces of information (for example, attribute values ​​of records recorded in a database) may be used as an identifier.

[0049] The term "acquisition" may include acquiring items input by a user or the like, or may include acquiring information stored in one's own device or another device (which may be information stored in advance or information generated by information processing performed in the device). Acquiring information stored in another device may include acquiring information stored in the other device via an API or the like, or may include acquiring the contents of a document file provided by another device (including the contents of a web page, etc.).

[0050] Also, a so-called machine learning technique may be used to acquire information. The machine learning technique can be used, for example, as follows. That is, a classifier that receives a specific type of input information as an input and outputs a type of output information to be acquired is configured using the machine learning technique. For example, two or more sets of input information and output information are prepared in advance, and the two or more sets of information are provided to a module for configuring a machine learning classifier to configure the classifier, and the configured classifier is stored in a storage unit. The classifier can also be called a learning device. Note that the machine learning technique may be, for example, deep learning, random forest, SVR, or the like. For machine learning, functions in various machine learning frameworks such as fastText, tinySVM, random forest, and TensorFlow, and various existing libraries can be used.

[0051] The classifier is not limited to one obtained by machine learning. The classifier may be, for example, a table showing the correspondence between an input vector based on input information and output information. In this case, output information corresponding to a feature vector based on input information may be obtained from the table, or a vector approximating a feature vector based on input information may be generated using two or more input vectors in the table and parameters for weighting each input vector, and final output information may be obtained using output information and parameters corresponding to each input vector used in the generation. The classifier may also be, for example, a function expressing the relationship between an input vector based on input information and information for generating output information. In this case, for example, information corresponding to a feature vector based on input information may be obtained by a function, and output information may be obtained using the obtained information.

[0052] Outputting information is a concept that includes displaying on a display, projecting using a projector, printing on a printer, outputting sound, transmitting to an external device, storing on a recording medium, passing the processing results to another processing device or another program, etc. Specifically, it includes, for example, enabling information to be displayed on a web page, transmitting as e-mail, etc., and outputting information to be printed.

[0053] The concept of accepting information includes the acceptance of information input from input devices such as a keyboard, mouse, or touch panel, the reception of information transmitted from other devices via wired or wireless communication lines, and the acceptance of information read from recording media such as optical disks, magnetic disks, and semiconductor memories.

[0054] (Embodiment)

[0055] In this embodiment, the information processing device has a function of calculating the flow rate and storage volume fluctuation of water resources using a distributed water circulation model that reproduces the circulation state of water resources in a spatial unit having a certain spatial extent. The information processing device extracts high-influence parameters that have a large influence on the flow rate and storage volume fluctuation of water resources from among the parameters that constitute the distributed water circulation model, and outputs an identifier that identifies the high-influence parameter. In this embodiment, the information processing device preferably outputs the high-influence parameters after ranking the flow rate and storage volume fluctuation of water resources in order of the greatest influence on the water balance.

[0056] In this embodiment, it is preferable to vary each parameter centering on the set value of the input parameter of the distributed water circulation model whose reproducibility has been confirmed by comparing the observation data of the water circulation elements with the calculated values ​​of the distributed water circulation model corresponding to the observation data, and extract the parameters in order of the rate at which the element related to the water resource of the target area changes due to the change of the parameter. In this case, for example, it is possible to vary the value of each parameter by a predetermined rate and extract the parameters that change by a certain rate or more, or to vary the value of each parameter within the possible range and extract the parameters that change by a certain rate or more. It is preferable that the extracted high influence parameters are limited to those corresponding to elements that can be influenced by human activities. It is also preferable that the extracted high influence parameters correspond to elements that are actually influenced by human activities in the target area.

[0057] The information processing device 1 configured in this manner will be described below.

[0058] FIG. 1 is a diagram illustrating an example of a distributed water circulation model according to an embodiment of the present invention.

[0059] As shown in FIG. 1, in this embodiment, the distributed water circulation model is a model of the circulation state of water resources in a predetermined area including forests, rivers, and other types of land. The predetermined area can be set, for example, in units of factories or in units of river basins including factories. In other words, the predetermined area can be set in spatial units having a certain spatial extent. In this embodiment, the distributed water circulation model can be, for example, a known model such as "GETFLOWS (registered trademark)" or "MODFLOW", and in this embodiment, "GETFLOWS (registered trademark)" is more preferable.

[0060] The distributed water circulation model is configured using a large number of meshes obtained by dividing a given area into a grid, each mesh being associated with location information that specifies a location, and a parameter group including two or more parameters that are applied to each mesh. For each mesh of the distributed water circulation model, parameter values ​​are set, making it possible to simulate the circulation state of water resources in the model. The parameters may be set to, for example, those related to elements such as weather, the ground surface, the shallow layer, and the deep layer (e.g., precipitation, temperature, topsoil, sediment, permeable layer, etc.), or those related to properties specific to the location. In other words, it can be said that the parameters are related to the governing elements that affect the circulation state of water resources. The parameters are related to the circulation state of water resources. In this embodiment, the parameter group constituting the distributed water circulation model includes parameters such as precipitation, evapotranspiration, air temperature, wind speed, sunshine duration, relative humidity, canopy coverage, canopy storage, litter coverage, litter storage, snow accumulation-snow melt temperature, albedo, bulk transport coefficient, soil evaporation efficiency, groundwater flow, equivalent roughness coefficient, groundwater flow, hydraulic conductivity, effective porosity, solid phase compressibility, relative permeability, capillary pressure, fluid properties, fluid density, air density, fluid viscosity coefficient, and air viscosity coefficient. Note that the parameters are not limited to these, and various parameters may be set. Note that the position information of each mesh may be information indicating a relative positional relationship with an adjacent mesh, or may be information indicating an absolute position, such as information indicating a position in a predetermined coordinate system.

[0061] FIG. 2 is a flowchart explaining the use of the distributed water cycle model.

[0062] Using the distributed water cycle model described above, users such as businesses can grasp information on the water balance for a target area. The distributed water cycle model can be used, for example, in the following way.

[0063] (Step S1) That is, first, a target area for which information on water balance should be grasped is determined. Specifically, for example, when grasping the water balance around a factory that uses water resources, a recharge area such as a forest upstream of the factory, an area downstream from which the factory takes in groundwater or river water, and an area further downstream thereof can be selected as the target area.

[0064] (Step S2) Collect information on the topography, geology, vegetation, etc. of the target area. Various methods can be used to collect information, such as conducting a reconnaissance survey or investigating documents or databases in which information is recorded.

[0065] (Step S3) Using the collected information, the target area is modeled as a distributed water cycle model.

[0066] (Step S4) For the created distributed water circulation model, meteorological external force data is input and the water balance is calculated.

[0067] (Step S5) Using the observation data, the reproducibility of the model is confirmed. Also, the information collection and the adjustment of the model are repeated to improve the reproducibility. Note that such operations may be performed as necessary.

[0068] (Step S6) Once the distributed water cycle model that can be used is completed, the water balance of the target area is calculated. The calculation can be performed using a computer by a known method depending on the configuration of the distributed water cycle model to be adopted.

[0069] (Step S7) Each parameter value for a predetermined period is input into the distributed water circulation model, and the water balance for that period is calculated.

[0070] (Step S8) This allows production activities and the like for a predetermined period in the target area to be planned using information on the calculated water balance (calculated water balance value).

[0071] In the present embodiment, the water balance calculation value can be calculated by the calculation unit 151 of the processing unit 140 of the information processing device 1, as described later, but is not limited to this.

[0072] Note that the method of using the distributed water circulation model shown in FIG. 2 is just one example, and various modifications are possible depending on the configuration and use of the distributed water circulation model.

[0073] As described below, in this embodiment, it is possible to identify the controlling factors that have a large influence on the calculated water balance value of the water resources in a specified area by using the information processing device 1. That is, by using the information processing device 1 to obtain identifiers of high-influence parameters output from the information processing device 1 as follows, and by performing an activity to change the state of the controlling factor corresponding to the obtained identifier in the specified area, it is possible to effectively manage the water resources in the specified area.

[0074] In this embodiment, the water balance calculated value relates to the flow rate, storage volume, or fluctuations of water resources in a specified region. More specifically, the water balance calculated value can relate to the flow rate, storage volume, or fluctuations of groundwater in a specified region. In other words, the water balance is a concept that refers to, for example, the flow rate, storage volume, and fluctuations of water resources in a target region. The water balance calculated value can be calculated, for example, for each mesh, but may also be calculated for each specific point or for each partial region based on the calculation results for each mesh.

[0075] For example, for the purpose of managing groundwater resources, there are cases where the amount of recharge, which is a parameter for water source conservation, is focused on as the flow rate of water resources. Here, recharge mainly refers to the supply of water from the ground surface to the groundwater table, and the amount of recharge refers to the amount of water supplied. When focusing on the amount of groundwater recharge in a specific area, the amount of water recharged as groundwater, the amount of water flowing into a specific area as groundwater, the groundwater level, etc. can be calculated and understood as water balance calculation values.

[0076] Note that the calculated water balance value is not limited to this, and the amount of water resources can be defined as appropriate depending on the purpose of understanding the water balance, etc.

[0077] For example, in order to manage surface water resources such as river water, attention may be paid to the flow rate during droughts. In such cases, the amount of water that flows out to the surface as spring water, the amount of water that flows into the river as river water, the amount of through-forest rain compared to outside-forest rain, the outflow rate of water compared to outside-forest rain, and the outflow rate of water compared to through-forest rain may be calculated and understood as water balance calculation values.

[0078] In addition, for example, there are cases where attention is paid to the amount of soil moisture for agriculture in order to manage soil water resources. In such cases, the amount of water that infiltrates as soil water can be calculated and understood as a water balance calculation value.

[0079] First, the configuration of the information processing device 1 will be described.

[0080] FIG. 3 is a block diagram of the information processing device 1. As shown in FIG.

[0081] 3, the information processing device 1 includes a storage unit 110, a reception unit 130, a processing unit 140, and an output unit 160. The information processing device 1 is, for example, a personal computer, but is not limited thereto, and may be a server device, a mobile information terminal, or the like. The information processing device 1 may be configured by one server, may be configured by multiple servers operating in cooperation with each other, or may be a computer or the like built into other equipment. The server may be a so-called cloud server, an ASP server, or the like, and the type is not important.

[0082] The storage unit 110 includes a model information storage unit 111, an observation data storage unit 113, and a property information storage unit 117. The storage unit 110 is preferably a non-volatile recording medium, but may also be a volatile recording medium. Each unit of the storage unit 110 stores, for example, information received by the reception unit 130 and information acquired by the processing unit 140, but the information stored in each unit of the storage unit 110 and the process by which the information is stored are not limited to this. For example, information may be stored in the storage unit 110 via a recording medium, information transmitted via a communication line or the like may be stored in the storage unit 110, or information inputted via an input device may be stored in the storage unit 110.

[0083] The model information storage unit 111 stores information about the distributed water circulation model. The information about the distributed water circulation model includes, for example, information about each mesh that constitutes the model. The values ​​of each parameter applied to each mesh are stored in the model information storage unit 111. In addition, the model information storage unit 111 stores information that can identify the position of each mesh.

[0084] The observation data storage unit 113 stores observation data on various parameters of the target area. The observation data is, for example, data obtained by reconnaissance, data obtained from an observation organization, etc., but is not limited to these. Each observation data is stored, for example, in association with an identifier that identifies the corresponding parameter. For example, observation data on precipitation is stored in association with an identifier of a parameter indicating precipitation. Note that observation data on the balance of water resources may be stored in association with an identifier that identifies that it is about the balance of water resources. The observation data is, for example, associated with location information corresponding to an observation point, but is not limited to this. The location information may be information indicating a position, or may be information that can identify a corresponding mesh. In addition, the observation data is, for example, associated with time information indicating the timing of observation, but is not limited to this. The observation data is, for example, not limited to each parameter, such as groundwater level and river flow rate. For example, geospatial information, such as the spatial distribution of spring points, may also be included.

[0085] The property information storage unit 117 stores information for identifying parameters that have a property that can change depending on the activity of the worker among the parameter group that configures the distributed water circulation model. For example, the amount of precipitation is not affected by the activity of the worker. On the other hand, the effective precipitation can change depending on the governing factors such as the amount of trees and vegetation at the point, so it can be said that it is a parameter that has a property that can change depending on the activity of the worker, such as thinning. In this manner, the property information storage unit 117 stores, for each parameter, a flag or the like indicating whether or not the parameter has a property that can change depending on the activity of the worker in association with an identifier that identifies the parameter. Note that the information stored in the property information storage unit 117 is stored depending on the setting operation of the user or the like received by the receiving unit 130 as described later, but is not limited to this. For example, it may be predetermined and stored.

[0086] The reception unit 130 receives, for example, information input using an input means connected to the information processing device 1, or information input by an input operation (including, for example, information read by a device) performed using a reading device (for example, a code reader, etc.) connected to the information processing device 1. The received information is stored, for example, in the storage unit 110. The input means that can be used to input information that can be received by the reception unit 130 may be any of a numeric keypad, keyboard, mouse, and menu screen. The reception unit 130 may be realized by a device driver for an input means such as a numeric keypad or keyboard, control software for a menu screen, and the like. The reception unit 130 may receive, for example, information such as voice input by a microphone.

[0087] In this embodiment, the reception unit 130 receives a designation operation by the user to designate whether or not each parameter has a property that can change depending on the activity of a worker. That is, the user can designate whether or not each parameter constituting the distributed water circulation model can be a target of worker activity in a predetermined area. When the reception unit 130 receives the designation operation, it associates an identifier that identifies the parameter with a flag or the like indicating whether or not the parameter has a property that can change depending on the activity of a worker, and stores the corresponding information in the property information storage unit 117. The user can, for example, perform a field survey of the predetermined area and then designate information regarding the above property for each parameter.

[0088] The processing unit 140 can usually be realized by an MPU, a memory, etc. The processing procedure of the processing unit 140 is usually realized by software, and the software is recorded in a recording medium such as a ROM. However, it may also be realized by hardware (dedicated circuit). The processing unit 140 performs various types of processing. The various types of processing are, for example, processing performed by each part of the processing unit 140 as follows.

[0089] In this embodiment, the processing unit 140 includes an extraction unit 141 , a calculation unit 151 , and a configuration unit 155 .

[0090] The extraction unit 141 extracts high influence parameters that have a large influence on the water balance calculation value as the high influence parameters satisfy a predetermined condition. The high influence parameters are extracted from a group of parameters used in the distributed water circulation model. The high influence parameters may be one or two or more.

[0091] Here, various conditions can be set as the predetermined condition. In this embodiment, the extraction unit 141 judges, for example, for each parameter, whether or not the result of the sensitivity analysis satisfies a predetermined extraction condition. As the extraction condition, for example, a ratio of the calculated value of the water balance before and after the value change is equal to or greater than a predetermined threshold value can be appropriately set. Note that the extraction unit 141 extracts a predetermined number (for example, it may be one or may be two or more) of top-ranked parameters as highly influential parameters in order of the influence on the calculated value of the water balance according to the result of ranking by the ranking setting unit 1415 described later.

[0092] In this embodiment, the extraction unit 141 extracts high-influence parameters from among the parameters constituting the distributed water circulation model that are determined to have a property that can change depending on the activity of the worker. The extraction unit 141 can determine that each parameter has a property that can change depending on the activity of the worker, for example, based on the information stored in the property information storage unit 117. That is, in this embodiment, the extraction unit 141 is configured to determine that a parameter designated as a possible target of the activity of the worker by a designation operation received by the reception unit 130 is a parameter that has a property that can change depending on the activity of the worker. The determination of whether or not a parameter has a property that can change depending on the activity of the worker may be performed after performing a sensitivity analysis of each parameter on the influence on the calculated water balance value as described below. Also, a sensitivity analysis of the influence on the calculated water balance value may be performed on only the parameters that have a property that can change depending on the activity of the worker.

[0093] In this embodiment, the extraction unit 141 extracts the highly influential parameters by performing a sensitivity analysis on the influence of each parameter on the water balance calculated value. The sensitivity analysis is performed by changing the value of each parameter and having the calculation unit 151 obtain the water balance calculated value.

[0094] The extraction unit 141 includes a parameter setting unit 1411 , a post-change calculation unit 1412 , and a ranking setting unit 1415 .

[0095] The parameter setting unit 1411 acquires observation data relating to one or more parameters from the observation data storage unit 113. The parameter setting unit 1411 also acquires observation data relating to the balance of water resources from the observation data storage unit 113. The parameter setting unit 1411 can acquire corresponding observation data by using an identifier that identifies a parameter or a water balance.

[0096] The parameter setting unit 1411 sets the value of each parameter so that the water balance calculation value calculated by the processing unit 140 using the value of each parameter corresponding to the acquired observation data and the values ​​of other parameters corresponds to the acquired observation data regarding the balance of water resources. That is, the parameter setting unit 1411 sets the value of each parameter so that it is a reasonable value in light of the observation data. For example, for a parameter with corresponding observation data, a value corresponding to the observation data may be set, and the values ​​of the other parameters may be set within the range of possible values ​​of the parameter using an analysis method such as Newton's method so that the difference between the observation data of the water balance and the water balance calculation value is within a predetermined value.

[0097] The post-change calculation unit 1412 calculates the water balance by changing the parameter value set by the parameter setting unit 1411 for each parameter. The calculated value of the water balance calculated in this way is called a post-change calculated value. In other words, the post-change calculation unit 1412 acquires the post-change calculated value.

[0098] In this embodiment, the post-change calculation unit 1412 acquires a post-change calculated value by changing the parameter value set by the parameter setting unit 1411 by a predetermined rate for each parameter. Specifically, for example, the set value for one parameter is increased or decreased by 1 percent, and the post-change calculated value is calculated using the changed value. Note that the rate of change is not limited to this. Also, a value used for calculating the post-change calculated value may be obtained by adding or subtracting a change amount set in advance for each parameter to or from the set value.

[0099] The extraction unit 141 extracts a highly influential parameter based on the post-change calculated value calculated by the post-change calculation unit 1412 for each parameter. In this embodiment, the extraction unit 141 acquires a water balance calculated value for each parameter using a parameter group set by the parameter setting unit 1411. Then, the extraction unit 141 calculates the difference between the acquired water balance calculated value and the post-change calculated value calculated by the post-change calculation unit 1412. If the calculated difference is equal to or greater than a predetermined threshold, the extraction unit 141 extracts the parameter as a highly influential parameter. Note that the extraction unit 141 may extract the parameter as a highly influential parameter if the ratio between the water balance calculated value and the post-change calculated value is equal to or greater than a predetermined threshold.

[0100] Here, in this embodiment, the ranking setting unit 1415, for example, compares the difference between the water balance calculated value and the post-change calculated value obtained for each parameter between the parameters, and ranks the highly influential parameters. That is, the parameter with a larger difference (higher sensitivity) between the water balance calculated value and the post-change calculated value is ranked higher as having a larger influence on the water balance calculated value. In this way, the extraction unit 141 ranks the highly influential parameters in order of the influence each highly influential parameter has on the water balance calculated value. Note that information (for example, a flag) indicating whether each parameter has been extracted as a highly influential parameter, information indicating the result of the ranking by the ranking setting unit 1415, and the like may be stored in the storage unit 110 in association with an identifier or the like for identifying the parameter.

[0101] The extraction unit 141 performs sensitivity analysis by varying such values ​​for each parameter, and can extract highly influential parameters that have a large effect on the calculated water balance value, that is, parameters that are highly responsive to the water balance, to the extent that the predetermined condition is satisfied. The sensitivity analysis is performed using values ​​that are varied from the values ​​set by the parameter setting unit 1411, so that it is possible to confirm the sensitivity of the parameter in the vicinity of the values ​​that are considered to be likely to be actually taken by the parameter.

[0102] The extraction unit 141 may extract the high-influence parameters, for example, as follows. That is, the post-change calculation unit 1412 may change the value of each parameter set by the parameter setting unit 1411 to the maximum value and the minimum value of the possible range, and obtain two post-change calculated values. In this case, the extraction unit 141 may extract the parameter as a high-influence parameter when the difference or ratio between the two post-change calculated values ​​is equal to or greater than a predetermined threshold value for each parameter. Specifically, for example, when the ratio between the two post-change calculated values ​​is equal to or greater than 1 percent, the parameter can be extracted as a high-influence parameter, but the method of determining using the threshold value or the two post-change calculated values ​​is not limited to this. In addition, for example, a sensitivity analysis may be performed based on the post-change calculated value calculated using either the maximum value or the minimum value that the parameter can take, and the water balance calculated value obtained using the parameter group set by the parameter setting unit 1411.

[0103] The calculation unit 151 uses a distributed water circulation model to obtain a water balance calculation value based on the values ​​of the applied parameter set.

[0104] When the calculation unit 151 acquires a water balance calculation value, the configuration unit 155 configures output data using the water balance calculation value.

[0105] Furthermore, in this embodiment, when the extraction unit 141 extracts a high influence parameter as described above, the configuration unit 155 configures output data using an identifier for identifying the high influence parameter. The identifier for identifying the high influence parameter may be a code associated with each parameter, or may be the name of the parameter itself. Note that the configuration unit 155 may configure output data by sorting the identifiers of the high influence parameters in an order according to the ranking result by the ranking setting unit 1415 (for example, from highest to lowest).

[0106] In this embodiment, the output unit 160 outputs information by displaying the information on a display device provided in the information processing device 1, for example. In this embodiment, the output unit 160 outputs output data configured by the configuration unit 155, for example. That is, when a water balance calculation value is acquired, the output unit 160 can output the water balance calculation value. In addition, in this embodiment, when a high influence parameter is extracted, the output unit 160 outputs an identifier that identifies the extracted high influence parameter. At this time, the output unit 160 outputs the identifier according to the result of the ranking. Note that outputting according to the result of the ranking may be outputting information indicating the ranking and the identifier in association with each other, or may be outputting identifiers sorted in the order according to the result of the ranking as described above. Also, it may be outputting identifiers in order from the highest ranking, or may be outputting identifiers in order from the lowest ranking.

[0107] The output unit 160 may be configured to output information by transmitting information to another device via a network or the like using a transmission unit (not shown), for example. The output unit 160 may or may not include an output device such as a display or a speaker. The output unit 160 may be realized by driver software for an output device, or a combination of driver software for an output device and the output device, or the like.

[0108] In this embodiment, the determination by the extraction unit 141 as to whether each parameter has a property that can change depending on the activity of the worker may be performed, for example, as follows. That is, for example, the extraction unit 141 may be configured to determine, in each location, a parameter related to an element located above a point at a predetermined depth from the ground surface as a parameter having a property that can change depending on the activity of the worker. For example, by previously storing information indicating that the parameter has a property that can change depending on the activity of the worker in association with the parameter in the property information storage unit 117 or the like, the extraction unit 141 can make such a determination. In this way, the user of the information processing device 1 can obtain information indicating that the parameter corresponding to the controlling element that is likely to actually be influenced by the activity of the worker is a highly influential parameter.

[0109] Next, an example of the flow of operations related to extraction of high influence parameters performed by the information processing device 1 will be described.

[0110] FIG. 4 is a flowchart showing the operation of the information processing device 1 regarding extraction of high influence parameters.

[0111] (Step S11) The processing unit 140 identifies parameters determined to have properties that can change depending on the activity of the worker among the parameter group of the distributed water circulation model, i.e., among two or more parameters related to the circulation state of water resources in a predetermined area. As described above, this can be performed based on, for example, the information stored in the property information storage unit 117. The identified parameters are the targets of the sensitivity analysis.

[0112] (Step S12) The processing unit 140 performs a process of performing a sensitivity analysis on the identified parameters and extracting highly influential parameters. The flow of the extraction process will be described later.

[0113] (Step S13) The processing unit 140 ranks the extracted high influence parameters.

[0114] (Step S14) The determining unit 140 composes output data including an identifier for identifying the extracted high influence parameter. The composition is performed using the ranking result, but is not limited to this. The output unit 160 outputs the output data. As a result, the identifier for identifying the high influence parameter is output. After that, the series of processes ends.

[0115] FIG. 5 is a flowchart showing an example of the extraction process performed by the information processing device 1.

[0116] (Step S21) The processing unit 140 sets a counter i to zero.

[0117] (Step S22) The processing unit 140 increments the counter i.

[0118] (Step S23) The processing unit 140 selects the i-th parameter for which a sensitivity analysis is to be performed.

[0119] (Step S24) The processing unit 140 acquires the range of possible values ​​of the selected parameter. (Step S25) The processing unit 140 performs a sensitivity analysis by varying the values ​​of the selected parameters. (Step S26) The processor 140 judges whether the result of the sensitivity analysis satisfies a predetermined extraction condition. As the extraction condition, for example, as described above, it is possible to set that the ratio of the calculated values ​​of the water balance before and after the fluctuation is equal to or greater than a predetermined threshold. If the extraction condition is satisfied, the process proceeds to step S27, and if not, the process proceeds to step S28.

[0120] (Step S27) The processing unit 140 sets the selected parameter as an extraction target. That is, the processing unit 140 causes the selected parameter to be extracted as a highly influential parameter.

[0121] (Step S28) The processing unit 140 judges whether the counter i is equal to the total number of parameters for which the sensitivity analysis is performed. If it is equal, the extraction process ends. If it is not equal, the process returns to step S22.

[0122] In the example shown in Fig. 4, the information processing device 1 performs the sensitivity analysis after identifying the parameters to be subjected to the sensitivity analysis, but this is not limited to the above. For example, after the extraction process, the parameters that can be finally output as the highly influential parameters may be limited to those that have a property that can change depending on the activity of the worker. Also, the ranking process may be performed during the extraction process. In this case, the extraction condition may be set to be related to the result of the ranking.

[0123] As described above, in this embodiment, the information processing device 1 performs sensitivity analysis on each parameter, identifies highly influential parameters that have a large effect on the water balance calculation value to the extent that the parameters satisfy a predetermined condition, and outputs their identifiers. Therefore, a user of the information processing device 1 can use the water resources management method for managing water resources in a predetermined area by using the information processing device 1.

[0124] FIG. 6 is a flowchart showing a water resource management method using the information processing device 1.

[0125] (Step S51) First, as described above, a distributed water circulation model is created for a given target area.

[0126] (Step S52) Using a distributed water circulation model, the calculation unit 151 is caused to obtain a water balance calculation value and observation data, and the state of the water circulation in a predetermined area is grasped.

[0127] (Step S53) The information processing device 1 executes the above-mentioned process to obtain the identifier of the high influence parameter output by the output unit 160. This makes it possible to identify the controlling factor that has a large influence on the water balance calculation value of the water resource in the predetermined region.

[0128] (Step S54) In a predetermined area, an activity is carried out to change the state of the dominant element corresponding to the acquired identifier. This results in a substantial change in the value of the high-influence parameter. In other words, the process of steps S53 and S54 allows management of water resources.

[0129] (Step S55) Confirm the effect of changing the state of the control element. For example, in the same way as in step S52, obtain water balance calculation values ​​and observation data to confirm the changes in water resources after the activity in step S54.

[0130] In this way, it is possible to easily identify the controlling factors corresponding to the high-influence parameters that have a large influence on the water balance in a given region by using the information processing device 1. Therefore, when managing water resources, it is possible to effectively manage the water resources in a given region by performing an activity to change the state of the controlling factors.

[0131] The processing in this embodiment may be realized by software. This software may be distributed by software download or the like. This software may be recorded on a recording medium such as a CD-ROM and distributed. The software for realizing the information processing device 1 in this embodiment is the following program. That is, this program is executed by the computer of the information processing device 1, and causes the processor of the information processing device 1 to function as a calculation unit that acquires a water balance calculation value related to the balance of water resources in a predetermined area based on values ​​applied to each of two or more parameters related to the circulation state of water resources in the predetermined area, an extraction unit that performs a sensitivity analysis on the influence of each parameter on the water balance calculation value by changing each parameter and having the calculation unit acquire a water balance calculation value, and extracts a high-influence parameter that has a large influence on the water balance calculation value to the extent that it satisfies a predetermined condition, and an output unit that outputs an identifier that identifies the high-influence parameter extracted by the extraction unit.

[0132] Here, in the present embodiment, the information processing device 1 is configured to be able to acquire the water balance calculation value in a predetermined region using a distributed water circulation model, but may be configured to be able to acquire the water balance calculation value without using a distributed water circulation model. For example, the calculation unit may be configured to be able to acquire the water balance calculation value in a predetermined region using a water circulation model that is a so-called centralized model. Also, for example, the calculation unit may be configured to be able to acquire the water balance calculation value using a classifier configured to output the water balance calculation value based on the value of each parameter. As such a classifier, as described above, it is sufficient to adopt one obtained by using a machine learning technique, one using a table showing the correspondence between an input vector based on input information, etc. and output information, a function expressing the relationship between an input vector based on input information, etc. and information for generating output information, or the like.

[0133] (others)

[0134] Fig. 7 is a schematic diagram of a computer system 800 according to the above embodiment, and Fig. 8 is a block diagram of the computer system 800.

[0135] These figures show the configuration of a computer that executes the programs described in this specification to realize the information processing device 1 of the above-mentioned embodiment, etc. The above-mentioned embodiment can be realized by computer hardware and a computer program executed thereon.

[0136] Computer system 800 includes a computer 801 including a CD-ROM drive, a keyboard 802, a mouse 803, and a monitor 804.

[0137] In addition to the CD-ROM drive 8012, the computer 801 includes an MPU 8013, a bus 8014 connected to the CD-ROM drive 8012 etc., a ROM 8015 for storing programs such as a boot-up program, a RAM 8016 connected to the MPU 8013 for temporarily storing instructions of application programs and providing a temporary storage space, and a hard disk 8017 for storing application programs, system programs, and data. Although not shown here, the computer 801 may further include a network card for providing a connection to a LAN.

[0138] A program for causing computer system 800 to execute the functions of the information processing device or the like of the above-mentioned embodiments may be stored on CD-ROM 8101, inserted into CD-ROM drive 8012, and further transferred to hard disk 8017. Alternatively, the program may be transmitted to computer 801 via a network (not shown) and stored on hard disk 8017. The program is loaded into RAM 8016 at the time of execution. The program may be loaded directly from CD-ROM 8101 or the network.

[0139] The program does not necessarily include an operating system (OS) or a third party program that causes the computer 801 to execute the functions of the information processing device of the above-mentioned embodiment. The program only needs to include an instruction portion that calls appropriate functions (modules) in a controlled manner to obtain a desired result. How the computer system 800 operates is well known, and a detailed description will be omitted.

[0140] In addition, in the above program, the transmitting step of transmitting information and the receiving step of receiving information do not include processing performed by hardware, such as processing performed by a modem or interface card in the transmitting step (processing that is performed only by hardware).

[0141] The program may be executed by a single computer or a plurality of computers. That is, the program may be executed by a centralized processing or a distributed processing.

[0142] In the above-described embodiments, two or more components present in one device may be physically realized on one medium.

[0143] Furthermore, in the above embodiments, each process (each function) may be realized by centralized processing by a single device (system), or may be realized by distributed processing by multiple devices (in this case, the entire system made up of multiple devices performing distributed processing can be considered as a single "device").

[0144] In addition, in the above embodiments, the transfer of information between each component may be performed, for example, by one component outputting information and the other component receiving information if the two components transferring the information are physically different, or, if the two components transferring the information are physically the same, by shifting from a processing phase corresponding to one component to a processing phase corresponding to the other component.

[0145] In the above embodiment, information related to the processing performed by each component, such as information accepted, acquired, selected, generated, transmitted, or received by each component, and information such as thresholds, formulas, and addresses used by each component in processing, may be temporarily or long-term stored in a recording medium (not shown) even if not specified in the above description. Furthermore, each component or a storage unit (not shown) may store information in the recording medium (not shown). Furthermore, each component or a reading unit (not shown) may read information from the recording medium (not shown).

[0146] In the above embodiment, if the information used by each component, such as the thresholds, addresses, and various setting values ​​used by each component in processing, may be changed by the user, the user may or may not be able to change the information as appropriate, even if not specified in the above description. If the information is changeable by the user, the change may be realized, for example, by a reception unit (not shown) that receives a change instruction from the user, and a change unit (not shown) that changes the information in response to the change instruction. The reception unit (not shown) may receive the change instruction from an input device, may receive information transmitted via a communication line, or may receive information read from a predetermined recording medium.

[0147] The present invention is not limited to the above-described embodiment, and various modifications are possible, and these modifications are also included within the scope of the present invention. In addition, some of the components and functions of the above-described embodiment may be omitted. In addition, various modifications may be made to the processes and procedures shown in the flowcharts above, such as adding, deleting, modifying, and changing the order of steps. EXAMPLES

[0148] An embodiment of the present invention will be described in detail below by way of an experimental example, but the present invention is not limited thereto.

[0149] In this example, a water circulation model was created to reproduce the circulation state of water resources in a spatial unit having a certain range of spatial extent, and a management index for groundwater recharge volume, one of the basic processes of water resources, was set. Then, the effect of managing the index was confirmed.

[0150] The target area is a designated area in Gifu prefecture. In this area, we set a management index for groundwater recharge, one of the basic processes of water resources, and confirmed the effect of managing the index.

[0151] First, a distributed water cycle model was created. From the national land water cycle model constructed by Geosphere Environmental Technology, areas covering approximately 250 ha and approximately 374 ha in the southeastern part of Gifu Prefecture were extracted, and the planar grid was subdivided into 100 m. The target period was the five years from 2011 to 2015. The year 2011 was used as a run-up period to transition from a steady state (background analysis) to an unsteady state (present-day reproduction analysis).

[0152] A transient analysis was performed on the equilibrium state given the average meteorological conditions of the region. From the calculation results, the reproduction of the water cycle in the target region and various quantities that represent the characteristics of the water source in the region were extracted.

[0153] The calculation conditions are as follows:

[0154] For precipitation, the background analysis used a constant precipitation amount that did not take into account temporal changes. For spatial distribution within the target area, multi-year daily average precipitation with a horizontal resolution of 1 km was used from the 2010 mesh normal. The calculation was done by subtracting the evapotranspiration amount (described below) from the precipitation amount to determine the effective precipitation amount, which was then assigned to the surface layer grid. For the present-day reproduction analysis, radar AMeDAS analysis precipitation was aggregated into daily data and used.

[0155] In the background analysis, potential evapotranspiration was calculated using the Harmon method (Harmon WR, 1961). Potential evapotranspiration is calculated using the following formula: In the formula below, "^" is the symbol indicating an exponent, and "_" is the symbol indicating a subscript.

[0156] Ep = 0.14 × (D_0)^2 × Pt Here, "Ep" is the daily average evapotranspiration (mm / d), "D_0" is the sunshine duration normalized to 12 hours, and "Pt" is the saturated absolute humidity (g / m^3). For the sunshine duration, the correction value of the day length for each latitude (Groundwater Handbook Editorial Committee, 1979) was used.

[0157] The effects of snow accumulation and snow melt were not taken into account in either the background analysis or the analysis reproducing current conditions.

[0158] Regarding vegetation, the background analysis did not take into account the effect of precipitation interception by vegetation. In the analysis of reproducing the current situation, the process of precipitation interception by the canopy and forest floor was considered. Rainfall outside the forest was assumed to be intercepted and stored by the canopy and forest floor, and the amount of water stored at each was assumed to flow out of the system by evapotranspiration calculated by the single-layer heat balance method. Only the remaining water passed through the canopy and reached the forest floor, and some of it passed through the forest floor and reached the ground surface. For the canopy and forest floor, the amount of storage and coverage rate corresponding to land use and vegetation classification were given as parameters. In this study, based on the existing vegetation map of the Basic Survey on Natural Environment Conservation, the vegetation distribution was reclassified into six categories: grassland / bare land, urban area, deciduous broadleaf trees, evergreen broadleaf trees, coniferous forest, and bamboo forest.

[0159] Fig. 9 is a diagram for explaining the vegetation distribution in this embodiment. Fig. 10 is a diagram for explaining the geological divisions in this embodiment.

[0160] The sensitivity analysis was carried out as follows. In other words, the parameters that may affect the recharge amount include boundary conditions such as effective precipitation and internal conditions such as hydraulic conductivity. Since the sensitivity analysis is a steady-state calculation, parameters that only affect the unsteady-state calculation (such as porosity) were excluded from the analysis. In addition, parameters with a very small range (such as water density) were excluded. The parameters that were ultimately used for the sensitivity analysis were effective precipitation, roughness coefficient, and hydraulic conductivity. The possible ranges of these parameters were assumed to be due to, for example, errors that occur when measuring rainfall, and the range of hydraulic conductivity set in the geological classification. For this reason, the range of boundary conditions and internal conditions was narrowed down by combining previous field data (rainfall observations, field surveys, hydraulic conductivity tests, hydrological observations, etc.), literature values, analysis results, etc. It is expected that the wider the parameter range is set, the larger the range of recharge amount will be, so it is desirable to narrow it down to a certain extent while leaving a sufficient range.

[0161] The range of effective precipitation is as follows. Specific flow was calculated from the river flow observation data around the target area, and it was confirmed that this roughly corresponded to the effective precipitation around the target area estimated using the Harmon method from the mesh average value 2010. The range of effective precipitation was then calculated from the difference between the two. Specifically, first, river flow points around the target area were selected where almost the entire amount of effective precipitation in the catchment area of ​​the point was thought to flow out based on topography, geology, etc., and where it is expected to occur over many years. The average specific flow was calculated for each selected point, and a range was set assuming the accuracy of the river flow to be plus or minus 10 percent. This was based on the knowledge that "Plot the flow rate on the existing water level and flow rate curve and check whether the value is far from the curve (approximately 10% is used as a guideline). If the value is far from the curve, investigate the cause" (described in Chapter 5, Flow Rate Data, Hydrological Observation (Public Works Research Institute), 2002 Edition). The largest difference between the range of specific flow rates obtained at each point and the effective precipitation estimated from the mesh average value for 2010 was taken as the range of average effective precipitation around the target area.

[0162] FIG. 11 is a diagram showing a comparison between the specific flow rate in this embodiment and the effective precipitation amount estimated from the mesh normal value 2010.

[0163] In Figure 11, the "Shirakawaguchi" was excluded from the calculation because it suggests the influence of water intake at the Nagura Dam. The difference between the final specific flow rate and the effective precipitation estimated from the mesh normal value for 2010 ranged from minus 114 mm / year to 402 mm / year.

[0164] The range of internal conditions was set as follows. In the quantitative evaluation of this embodiment, the reproducibility in steady-state calculations was confirmed and the parameter set was narrowed down. Since non-steady-state reproducibility was not considered, parameters such as porosity related to storage were not targeted. Therefore, the target parameters of the internal conditions were the permeability roughness coefficient and hydraulic conductivity. The permeability roughness coefficient was set in association with land use in the base case, and it was decided to continue to set it in association with land use in this embodiment. The possible range was set for each land use based on previous literature. The hydraulic conductivity was set in association with the stratum classification in the base case, and it was decided to continue to set it in association with the stratum classification.

[0165] FIG. 12 is a diagram showing an image of the setting of the hydraulic conductivity in this embodiment.

[0166] Field data such as permeability test data has not been collected for many stratum sections, such as mountain areas including the area of ​​interest (area surrounded by solid lines in Figure 9). Therefore, as shown in Figure 12, for all models, the permeability coefficient is basically set to decrease from the surface to the deeper layers, and this relative structure is maintained within about plus or minus one order. Therefore, a range was set in principle with the maximum value being the set value plus one order and the minimum value being the set value minus one order. However, if the value of the set value plus one order is considered to be too large, the maximum value was set to the set value and the minimum value was set to the set value minus two orders. Conversely, if the value of the set value minus one order is considered to be too small, the maximum value was set to the set value plus two orders and the minimum value was set to the set value.

[0167] FIG. 13 is a diagram for explaining the results of the sensitivity analysis in this embodiment.

[0168] The results of the sensitivity analysis were obtained as shown in Figure 13. For geology with weathered loosening zones, fresh areas, etc. set, sensitivity analysis was performed by simultaneously setting these to the maximum or minimum value. In addition, sensitivity analysis was performed by simultaneously setting all land uses to the maximum or minimum value for the roughness coefficient. The parameters that were determined to be sensitive to the amount of recharge in the area of ​​interest are as follows.

[0169] Effective precipitation, roughness coefficient, permeability coefficient of topsoil, permeability coefficient of sediments from the Late Pleistocene and Holocene, permeability coefficient of muddy parts of the Mesozoic layer, permeability coefficient of volcanic rocks from the Mesozoic to Neogene periods (including pyroclastic flow deposits)

[0170] The change in effective precipitation was found to be an important indicator, varying groundwater recharge by 31.2 percent. Effective precipitation was identified as an important indicator (high impact parameter) for managing water resources.

[0171] Based on these results, we decided to take management measures to increase effective precipitation, including thinning out densely packed trees.

[0172] FIG. 14 is a diagram illustrating the effect of the management measures in this embodiment.

[0173] The results of the confirmation of the effectiveness of the management measures are as follows. That is, in GHS2, where thinning of dense trees was carried out in December 2012, the ratio of rainfall within the canopy to rainfall outside the canopy increased from 2013 onwards, and in GHS2, where thinning of dense trees was carried out in May 2014, in 2014, and it was confirmed that the effective precipitation increased. Also, a trend of increasing base flow was confirmed during the same period. This suggests that the amount of recharge has increased. [Industrial Applicability]

[0174] INDUSTRIAL APPLICABILITY As described above, the information processing device of the present invention has the effect of making it possible to easily identify what are the important controlling factors for water resources in each target area, and is useful as an information processing device, etc. [Explanation of symbols]

[0175] 1. Information processing device 110 Storage area 111 Model information storage section 113 Observation Data Storage Unit 117 Property information storage section 130 Reception 140 Processing section 141 Extraction part 151 Calculation Department 155 Components 160 Output section 1411 Parameter setting section 1412 Post-change calculation unit 1414 Ranking Division

Claims

1. A calculation unit that obtains a water balance calculation value regarding the balance of water resources in a predetermined area based on values ​​applied to two or more parameters related to the circulation state of water resources in the predetermined area; an extraction unit that performs a sensitivity analysis on the influence of each of the parameters on the calculated water balance value by changing the value of each of the parameters and having the calculation unit obtain the calculated water balance value, and extracts high-influence parameters that have a large influence on the calculated water balance value to the extent that a predetermined condition is satisfied; an output unit that outputs an identifier that identifies the high influence parameter extracted by the extraction unit.

2. The extraction unit ranks each of the high influence parameters to be extracted in order of the influence each of the high influence parameters has on the water balance calculated value; The information processing device according to claim 1 , wherein the output unit outputs the identifier in accordance with a result of the ranking.

3. The extraction unit is a parameter setting unit that acquires one or more parameters and observation data related to the water resource balance, and sets values ​​of each parameter and other parameters corresponding to the acquired observation data so that the water balance calculation value corresponds to the acquired observation data related to the water resource balance; a post-change calculation unit that changes the value of each of the parameters set by the parameter setting unit to obtain a post-change calculated value related to the balance of water resources, The information processing apparatus according to claim 1 , wherein the highly influential parameters are extracted based on post-change calculated values ​​calculated by the post-change calculation unit for the respective parameters.

4. the post-change calculation unit changes the value of each of the parameters set by the parameter setting unit by a predetermined rate to obtain the post-change calculated value; 4. The information processing device according to claim 3, wherein the extraction unit extracts each of the parameters as the highly influential parameter when the difference or ratio between the water balance calculated value obtained using the value set by the parameter setting unit and the post-change calculated value is equal to or greater than a predetermined threshold value.

5. the post-change calculation unit changes the value of each of the parameters set by the parameter setting unit to a maximum value and a minimum value within a possible range, and obtains two of the post-change calculated values; The information processing apparatus according to claim 3 , wherein the extraction unit extracts, for each of the parameters, the parameter as the high-influence parameter when a difference or a ratio between the two post-change calculated values ​​is equal to or greater than a predetermined threshold value.

6. The information processing apparatus according to claim 1 , wherein the extraction unit extracts the high influence parameter from among the two or more parameters determined to have a property that can change depending on an activity of a worker.

7. The information processing device according to claim 6 , wherein the extraction unit is configured to determine a parameter related to an element located above a point at a predetermined depth from the earth's surface as a parameter having a property that can change depending on the activity of the worker.

8. a reception unit that receives from a user a designation operation that designates whether or not the predetermined area can be an activity target of a worker by associating the designation operation with each parameter, 8. The information processing device according to claim 6, wherein the extraction unit is configured to determine that a parameter designated as a possible target of a worker's activity by a designation operation accepted by the acceptance unit is a parameter having a property that can change depending on the activity of the worker.

9. The information processing apparatus according to claim 1 , wherein the water balance calculation value relates to a flow amount, a storage amount, or a fluctuation amount thereof of the water resource in the predetermined area.

10. The information processing device according to claim 1 , wherein the water balance calculation value relates to a groundwater flow rate, a storage amount, or a fluctuation amount thereof in the predetermined area.

11. The information processing apparatus according to claim 1 , wherein the water balance calculation value relates to an amount of groundwater recharge in the predetermined area.

12. 12. The information processing device according to claim 1, wherein the calculation unit obtains the water balance calculation value using a distributed water circulation model constructed using a parameter group including the two or more parameters, the distributed water circulation model modeling the circulation state of water resources in the specified region.

13. 1. A water resources management method for managing water resources in a given area, comprising: acquiring the identifier output by the output unit of the information processing device according to any one of claims 1 to 12, wherein the calculation unit is configured to obtain a water balance calculation value relating to a balance of water resources in the predetermined area; and changing a state of a controlling element corresponding to the acquired identifier in the specified area.

14. An information processing method realized by a calculation unit, an extraction unit, and an output unit, A calculation step in which the calculation unit obtains a water balance calculation value regarding the balance of water resources in a predetermined area based on values ​​applied to each of two or more parameters related to the circulation state of water resources in the predetermined area; an extraction step in which the extraction unit performs a sensitivity analysis on the influence of each of the parameters on the calculated water balance value by changing each of the parameters and causing the calculation unit to obtain the calculated water balance value, thereby extracting high-impact parameters that have a large influence on the calculated water balance value to the extent that a predetermined condition is satisfied; An information processing method comprising: an output step in which the output unit outputs an identifier that identifies the high-influence parameter extracted by the extraction unit.

15. A processor of the information processing device, A calculation unit that obtains a water balance calculation value regarding the balance of water resources in a predetermined area based on values ​​applied to two or more parameters related to the circulation state of water resources in the predetermined area; an extraction unit that performs a sensitivity analysis on the influence of each of the parameters on the calculated water balance value by causing the calculation unit to obtain the calculated water balance value while varying each of the parameters, and extracts high-influence parameters that have a large influence on the calculated water balance value to the extent that a predetermined condition is satisfied; A program for causing the program to function as an output unit that outputs an identifier for identifying the high-influence parameter extracted by the extraction unit.

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