Distributed basin water cycle and water quality simulation system and method

Abstract

A distributed watershed water cycle and water quality simulation system is disclosed. The disclosed distributed watershed water cycle and water quality simulation system includes: a WRF-Hydro hydrological model comprising a surface model and a stream tracking model; a paddy field module directly linked to the surface model to simulate the irrigation, storage, and drainage processes of paddy fields; a reservoir hydrological module directly linked to the stream tracking model to simulate discharge volumes according to the shape and operating conditions of the reservoir hydrological gate; and a WRF-HydroQual water quality model that receives a simulation result file from the WRF-Hydro hydrological model and independently simulates one or more inflows, transformations, and behaviors selected from a group including carbon, nitrogen, and phosphorus. Accordingly, by adding water quality simulation functions to the surface model Noah-MP and the tracking model constituting the WRF-Hydro model and providing a WRF-HydroQual model suitable for domestic environmental conditions, it is possible to simulate and test accurate water cycles and water quality within a watershed.

Description

Technology Field

[0001] The present invention relates to a distributed watershed water circulation and water quality simulation system and method, and more specifically, to a distributed watershed water circulation and water quality simulation system and method capable of simulating water circulation and water quality within a watershed by including an improved water quality model. Background Technology

[0003] As temperatures rise and precipitation variability increases due to climate change, the frequency of floods and droughts is also projected to rise. According to forecast data from the Korea Meteorological Administration, high-temperature related indices such as heatwave days, tropical nights, and summer days are expected to increase on the Korean Peninsula, while low-temperature related indices such as cold waves, freezing days, and frost days are projected to decrease. Furthermore, due to increased precipitation variability, extreme precipitation phenomena such as droughts and heavy rainfall are expected to become more frequent.

[0004] Such climate change causes rising water temperatures and fluctuations in the flow and quality characteristics of stormwater runoff, acting as a factor that amplifies the direct and indirect impacts on the water quality of rivers and lakes as well as aquatic ecosystems. Specifically, changes in flow and quality caused by floods and droughts lead to disturbances in aquatic ecosystems, while rising water temperatures and increased nutrient runoff from non-point sources cause frequent eutrophication and the occurrence of harmful cyanobacteria in lakes, which can undermine the safety of water sources and the health of aquatic ecosystems.

[0005] Meanwhile, since 2012, the Ministry of Environment has been providing water quality forecasts for water temperature and chlorophyll-a concentrations for seven days starting from the day after the forecast for major points in the four major river systems, including the Han River, Nakdong River, Geum River, and Yeongsan River. The water quality prediction information is delivered to water management agencies via the water quality forecast website and text messages and is utilized for proactive water quality management.

[0006] However, the water quality prediction model constituting the water quality forecasting system is built and operated for each of the four major river basins by linking the watershed model HSPF (Hydrological Simulation Program-Fortran) and the river model EFDC (Environmental Fluid Dynamics Code). Currently, the water quality forecasting system is applied only to the main stream sections of the four major rivers, and the water quality forecasting items (water temperature, chlorophyll-a) and frequency (twice a week) are limited, so there are limitations in utilizing it for integrated water management purposes across various watershed scales.

[0007] In addition, the HSPF watershed model, which constitutes the water quality prediction model, has a structure that simulates hydrological, hydraulic, and water quality processes at the sub-watershed level, which is composed of irregular units rather than a square grid. Since it does not explicitly simulate major physical processes affecting water quality, such as organic matter transformation and behavior in soil within the watershed, and soil erosion and transport, it has limitations in supporting a three-dimensional understanding of the spatiotemporal variability of hydrological, hydraulic, and water quality processes within the watershed, as well as the establishment and evaluation of short- and long-term watershed management plans based thereon. The problem to be solved

[0009] The present invention was created to solve the problems of the prior art described above, and aims to provide a distributed watershed water cycle and water quality simulation system and method capable of simulating water cycles and water quality within a watershed, including the WRF-HydroQual water quality model.

[0010] Meanwhile, other unspecified objects of the present invention will be further considered to the extent that they can be easily inferred from the following detailed description and effects. means of solving the problem

[0012] A distributed watershed water cycle and water quality simulation system according to one embodiment may include: a WRF-Hydro (Weather Research and Forecasting Hydro) hydrological model comprising a surface model and a river tracking model; a paddy field module directly linked to the surface model to simulate the irrigation, storage, and drainage processes of a paddy field; a reservoir hydrological module directly linked to the river tracking model to simulate the discharge amount according to the shape and operating conditions of the reservoir hydrological gate; and a WRF-HydroQual (Weather Research and Forecasting Hydro Water Quality) water quality model that receives a simulation result file of the WRF-Hydro hydrological model and independently simulates one or more inflows, transformations, and behaviors selected from a group including carbon, nitrogen, and phosphorus.

[0013] The above water quality model receives hydrological and hydraulic variable values ​​from the results of the above hydrological model and simulates the processes of sediment erosion, transport, deposition, and resuspension in soil and rivers according to particle size, thereby simulating changes in water quality within the river.

[0014] The above-mentioned paddy field module may include a function in which the height and thickness of the paddy field dike are constant on all sides and a water gate is located in the downstream direction, so that the surface runoff is controlled according to the height of the water gate specified by the user, thereby maintaining or varying the water depth in the paddy field grid.

[0015] It may further include a point source module linked to the above hydrological model, which receives point source discharge flow rates and loads for each river section and simulates changes in flow rate and water quality within the river.

[0016] The above point source module defines the discharge from sewage treatment facilities and industrial wastewater treatment facilities as point sources and can simulate the impact on river water quality by receiving discharge flow rates and loads as input data.

[0017] The above point source pollution module can simulate behavior within a river by classifying the input load into items including carbon, nitrogen, and phosphorus, and classifying each item according to dissolved / particulate and non-biodegradable / biodegradable characteristics.

[0018] The above point source pollution module can calculate pollutant transport and water quality changes by downstream section based on time-series fluctuations in discharge load, based on the river section where discharge occurs.

[0019] The above point source module can simulate point source discharge scenarios (discharge period, flow rate, load) for each river section by receiving them as time series data.

[0020] It further includes a water distribution module linked to the above hydrological model that simulates changes in flow rate and water quality due to water intake and discharge, and the water distribution module can calculate the water intake amount by considering the maximum capacity of the water intake facility and the total available water amount at the time of intake, and calculate the water intake load by reflecting the average water quality at that time.

[0021] The above-mentioned paddy module and reservoir hydrology module are tightly coupled with the hydrology model, whereas the above-mentioned water quality model has a loose coupling structure that is simulated independently of the hydrology model, and accordingly, it can respond flexibly even to upgrades and code changes of the hydrology model.

[0022] The above water quality model can simulate behavior by particle size by classifying sediment into clay, silt, fine sand, and coarse sand.

[0023] The above reservoir sluice gate module can calculate the discharge amount by reflecting at least one type among lifting, rotary, and tilting sluice gates.

[0024] In addition, a method for simulating distributed watershed water circulation and water quality by a processor according to one embodiment may include: a step of driving a WRF-Hydro hydrological model including a surface model and a river tracking model; a step of simulating the irrigation, storage, and drainage processes of a paddy field directly linked to the surface model; a step of simulating the discharge amount according to the shape and operating conditions of a reservoir hydrological gate directly linked to the river tracking model; and a step of driving a water quality model that receives a simulation result file of the hydrological model and independently simulates at least one inflow, transformation, and behavior selected from a group including carbon, nitrogen, and phosphorus.

[0025] Additionally, one or more non-transient computer-readable storage media according to one embodiment may store instructions that cause one or more computers to perform operations of the individual methods when executed by one or more computers. Effects of the invention

[0027] The distributed watershed water circulation and water quality simulation system and method according to the present invention can accurately simulate water circulation and water quality within a watershed by developing additional water quality simulation functions for the indicator model Noah-MP and the tracking model constituting the WRF-Hydro model, thereby providing the WRF-HydroQual model suitable for domestic environmental conditions.

[0028] In addition, according to the present invention, by further developing water quality simulation functions for the indicator model Noah-MP and the tracking model constituting the WRF-Hydro model, a WRF-HydroQual model suitable for domestic environmental conditions can be provided.

[0029] In addition, according to the present invention, it can help in developing a paddy field module, a sediment transport model, and an organic matter conversion and behavior model linked with the Noah-MP index model, and in developing a reservoir hydrology module, a sediment transport model, and an organic matter conversion and behavior model linked with the WRF-Hydro tracking model.

[0030] Furthermore, according to the present invention, the WRF-HydroQual model is used to divide the entire country into ultra-high-resolution grids and produce basic hydrological and water quality data necessary for the establishment and evaluation of integrated water management policies. The time-series and spatial data produced by the WRF-HydroQual model can provide a basis for scientific decision support at various spatial scales, from small watersheds to the entire country, through effective data analysis and visualization tools of the Digital Twin Korea-Water (DTK-W) system.

[0031] In addition, according to the present invention, by providing prediction data on short- and long-term flow rate and water quality changes resulting from climate change and development plans to relevant agencies such as the central government and local governments, it is possible to provide a foundation for efficient watershed management and water management policy formulation among agencies.

[0032] In addition, according to the present invention, by producing prediction data on short- and long-term flow rate and water quality changes nationwide through the WRF-HydroQual model, it is possible to provide a foundation for establishing a rapid and effective water disaster response system in the event of localized floods, droughts, massive proliferation of harmful algal blooms, water pollution accidents, etc. Brief explanation of the drawing

[0034] FIG. 1 is a block diagram illustrating the main elements constituting a distributed basin water circulation and water quality simulation system according to one embodiment. FIG. 2 is a diagram illustrating the connection relationships between key elements of a distributed basin water circulation and water quality simulation system according to one embodiment. FIG. 3 is a diagram illustrating the configuration of a subroutine of a WRF-hydro tracing model according to one embodiment. FIG. 4 is a diagram illustrating the call structure of a non-subroutine within a Noah-MP indicator model according to one embodiment. FIG. 5 is a diagram illustrating the structure of a subroutine of a reservoir tracking module according to one embodiment. FIG. 6 is a diagram showing independent simulated structures of a point source module and a water distribution module according to one embodiment. FIG. 7 is a diagram illustrating a simulated structure of a paddy field module according to one embodiment, showing a schematic diagram of the hydrological process in a paddy field (Fig. 7a) and the structure of a paddy field dike and a water gate (Fig. 7b), respectively. FIG. 8 is a diagram illustrating an example of a hardware implementation of a distributed basin water circulation and water quality simulation system according to one embodiment. It should be noted that the attached drawings are provided as examples for reference to help understand the technical concept of the present invention, and the scope of the rights of the present invention is not limited by them. Specific details for implementing the invention

[0035] The most preferred embodiment of the present invention is described below. In the drawings, thicknesses and spacings are depicted for convenience of explanation and may be exaggerated compared to their actual physical thicknesses. In describing the present invention, known components unrelated to the essence of the invention may be omitted. It should be noted that in assigning reference numbers to the components of each drawing, identical components are assigned the same number as much as possible, even if they are shown in different drawings.

[0036] Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the attached drawings.

[0037] FIG. 1 illustrates a block diagram of the main elements constituting a distributed watershed water circulation and water quality simulation system according to one embodiment. FIG. 2 is a diagram illustrating the connection relationships between the main elements of a distributed watershed water circulation and water quality simulation system according to one embodiment.

[0038] Referring to FIGS. 1 and 2, the distributed watershed water cycle and water quality simulation system may include a hydrological model (110), a paddy field module (120), a reservoir hydrological module (130), a water quality model (140), and a point source module (150).

[0039] A hydrological model (110) may be a tool that simulates and predicts the circulation and movement of water using mathematical equations and computer code. Such a hydrological model may be constructed based on physical laws governing the water circulation (conservation of mass, conservation of energy, etc.). For example, the hydrological model (110) may be a WRF-Hydro (Weather Research and Forecasting Hydro) hydrological model that includes a surface model (111) and a river tracking model (112).

[0040] The surface model (112) is an element that simulates the energy and water cycle between the surface and the atmosphere in the hydrological model, the WRF-Hydro hydrological model. The role of this surface model is to calculate the vertical movement of water and provide starting point data for subsequent horizontal flow (outflow).

[0041] The river tracking model (112) may be a model that simulates and predicts the process of water collected through the surface and underground moving downstream along the river network in the hydrological model, WRF-Hydro hydrological model. This river tracking model can handle the horizontal flow of water after the vertical water cycle (precipitation, infiltration, evapotranspiration) occurring in the watershed is completed.

[0042] The Rice Paddy Module (120) is a module capable of simulating the irrigation, storage, and drainage processes in a rice paddy, and is a hydrological model improved to suit the domestic watershed environment.

[0043] The paddy field module (120) may be a sub-module specifically designed to be integrated into an agricultural hydrological model or a water quality model to simulate the unique water cycle and water quality characteristics of a paddy field area. Unlike typical natural watersheds, a separate paddy field module may be required to accurately simulate the water cycle in paddy fields because human irrigation and drainage activities have a significant impact on the water cycle.

[0044] That is, the paddy module (120) can be directly linked to the aforementioned surface model to simulate hydrological and water quality processes of the paddy. Additionally, the paddy module may include a function in which the height and thickness of the paddy dike are constant in all directions and a water gate is located in the downstream direction, so that the surface runoff is controlled according to the height of the water gate specified by the user, thereby maintaining or changing the water depth in the paddy grid.

[0045] The reservoir sluice gate module (130) is an improved sluice gate module that can simulate the discharge amount according to the type of reservoir sluice gate (rotary, lifting, tilting type) and operation data.

[0046] The reservoir sluice gate module (130) can simulate the discharge volume by reflecting at least one of a lifting sluice gate, a rotary sluice gate, and a tilting sluice gate. The reservoir sluice gate module can calculate the discharge volume based on a physical formula by receiving the sluice gate opening height, the upstream and downstream water levels of the reservoir, and the sluice gate width as input data. The reservoir sluice gate module can simulate a situation in which multiple sluice gates are operated in parallel by reflecting changes in the water level within the reservoir in real time.

[0047] The water quality model (140) is integrated into the hydrological model, the WRF-Hydro hydrological model, to simulate and predict the movement, change, and concentration of various pollutants and nutrients dissolved or suspended in water (H2O). Here, while the aforementioned hydrological model focuses on 'how much water flows and where,' the water quality model focuses on 'what state the water is in and what it contains.'

[0048] This water quality model may be the WRF-HydroQual (Weather Research and Forecasting Hydro Water Quality) model, which receives the simulation result file of the aforementioned WRF-Hydro hydrological model as input and independently simulates the transformation and behavior of carbon (C), nitrogen (N), phosphorus (P), etc. In other words, the WRF-HydroQual water quality model reads hydrological and hydraulic variable values ​​from the results of the hydrological model and can simulate changes in water quality within rivers and reservoirs.

[0049] In particular, the WRF-HydroQual water quality model can simulate the inflow, transformation, and behavior processes of carbon, nitrogen, and phosphorus with hydrological models using a loose coupling method.

[0050] Carbon (C) conversion and behavior models classify organic and inorganic matter within soil, aquifers, groundwater, and water bodies (rivers / reservoirs) into characteristics such as particulate, dissolved, biodegradable, and recalcitrant based on their form of existence and decomposition rate, and can simulate the processes of carbon inflow, conversion, and behavior in conjunction with hydrological models. Nitrogen (N) conversion and behavior models classify organic and inorganic matter within soil, aquifers, groundwater, and water bodies (rivers / reservoirs) into characteristics such as particulate, dissolved, biodegradable, and recalcitrant based on their form of existence and decomposition rate, and can simulate the processes of nitrogen inflow, conversion, and behavior in conjunction with hydrological models. Phosphorus (P) Transformation and Behavior Model: Organic and inorganic matter in soil, aquifers, groundwater, and water bodies (rivers / reservoirs) are classified into characteristics such as particulate, dissolved, biodegradable, and recalcitrant based on their existence form and decomposition rate, and the processes of phosphorus inflow, transformation, and behavior can be simulated in conjunction with hydrological models.

[0051] Sediment transport models classify sediment particles into four particle sizes, such as clay, silt, fine sand, and coarse sand, and can simulate processes such as erosion, transport, deposition, and resuspension of sediment in soil and rivers primarily using physical equations.

[0052] A distributed watershed water circulation and water quality simulation system according to one embodiment may further include a point source module (150).

[0053] The point source module can simulate changes in flow rate and water quality resulting from point source discharges into rivers. In other words, the point source module can relate to pollution sources with specific discharge outlets, which are distinguished from non-point sources (e.g., agricultural land, roads, etc.) that are spatially spread out. For example, discharges from sewage treatment facilities and industrial wastewater treatment facilities can be defined as point sources.

[0054] The point source module can simulate and manage the pollution load flowing into rivers or water bodies from specific points within a distributed watershed water cycle and water quality simulation system. For example, the point source module can simulate changes in water quality within a river by receiving discharge volumes from sewage treatment facilities, industrial wastewater treatment facilities, and the like as input data. Additionally, the point source module can calculate the discharge load for each river section to estimate the impact on flow rate and water quality on a section-by-section basis.

[0055] In this invention, the water quality model (i.e., the WRF-HydroQual water quality model) is configured to operate in the following manner: First, it is operated as a standalone simulation without coupling with the weather model. Next, the paddy field module and the reservoir hydrology module are operated using a tight coupling method. Furthermore, the sediment transport model and the CNP model are operated using a loose coupling method through file sharing with the WRF-Hydro model.

[0056] For example, the direct linkage method may be a method in which different modules are directly called within a single execution flow (code routine) to exchange data at the same time interval (time step) and in the same memory space. In the present invention, the non module (in the form of a subroutine within the indicator model) and the reservoir hydrology module (in the form of a subroutine within the tracking model) can be linked in this manner.

[0057] A loosely coupled method may be one in which different modules asynchronously exchange data through simulation result files or databases. That is, it may be a method in which a preceding module completes the calculation and saves the result, after which a succeeding module reads it and simulates it separately. The simulation process is separated into stages, and each module can be executed independently. In the present invention, the pseudo-movement model and the CNP model can be coupled in this manner.

[0058] More specifically, as illustrated in Figure 1 above, the linkage structure between the WRF-Hydro model and the WRF-HydroQual model is configured such that the paddy field module and the reservoir hydrology module are directly linked within the surface model and the tracking model (river tracking module), respectively, while the sediment transport model and the CNP model are structured to simulate independently of the WRF-Hydro model by reading the hydrological / hydraulic variable values ​​required in each subroutine from the WRF-Hydro simulation result file. This linkage method has the advantage of being able to flexibly respond to code changes, such as future upgrades of the WRF-Hydro model.

[0059] With reference to FIGS. 3 to 7 below, we will examine in more detail the operation of a distributed basin water circulation and water quality simulation system according to one embodiment.

[0060] FIG. 3 illustrates the configuration of a subroutine of a WRF-hydro tracking model according to one embodiment. FIG. 4 illustrates the call structure of a paddy field subroutine within a Noah-MP indicator model according to one embodiment. FIG. 5 illustrates the structure of a subroutine of a reservoir tracking module according to one embodiment (yellow boxes indicate modified subroutines). FIG. 6 illustrates the independent simulation structures of a point source module and a water distribution module according to one embodiment. FIG. 7 illustrates the simulation structure of a paddy field module according to one embodiment, showing a schematic diagram of the hydrological process in a paddy field ( FIG. 7a) and the structure of a paddy field dike and a water gate ( FIG. 7b), respectively.

[0061] First, watershed models can be classified into lumped models and distributed models depending on how the watershed is partitioned. Compared to lumped models, distributed models have the advantage of being able to represent spatial heterogeneity within the watershed because they divide the watershed into subdivided spatial units.

[0062]

[0063]

[0064] Among the distributed models subject to intensive review listed in Table 1 above, the Noah-MP model is evaluated to satisfy all four evaluation criteria in Table 2. Accordingly, the WRF-Hydro model including the Noah-MP model can be selected as the basic model.

[0065] The Noah-MP model may be a multi-parameter land surface model used to simulate atmosphere-land interactions.

[0066] However, since the surface model Noah-MP has a structure capable of only one-dimensional vertical simulation, an additional structure for simulating horizontal mass transport is required to simulate the movement of water and pollutants within the basin. The WRF-Hydro model can simulate vertical hydrological flow within the grid through Noah-MP, simulate horizontal movement within the basin and hydrological flow through rivers through a tracking model, and can also be equipped with a function for linking with a weather model.

[0067] As shown in Fig. 3, the WRF-Hydro model includes an indicator model, a trace model, and a subroutine, which are Noah-MP models, and the subroutine can perform data input / output and operation.

[0068] More specifically, the surface model is executed on a grid representing the surface, and the state variables of the surface model (soil moisture, temperature, and vegetation biomass, etc.) can be updated at each simulation time.

[0069] The WRF-Hydro tracking model may include two tracking models, for example, terrain routing modules and channel routing modules.

[0070] The WRF-Hydro tracking model receives simulated values ​​calculated from a surface model grid and can calculate the flow rate entering the river from land through a high-resolution tracking model grid.

[0071] As illustrated in Fig. 3, the WRF-Hydro tracking model can perform simulations in a total of six stages. That is, the WRF-Hydro tracking model can perform simulations by disaggregating variables from the surface model grid to the tracking model grid, calculating subsurface flow, which is the horizontal flow within the soil layer, calculating overland flow, which is the flow moving horizontally through the surface, calculating base flow, which is the flow moving through the underground aquifer, calculating channel and reservoir flow, which is the flow moving through the stream and reservoir, and aggregating variables from the tracking model grid to the surface model grid.

[0072] At this time, the detailed subroutines constituting the tracing model determine whether to simulate the corresponding process based on user-specified switches (SubRtSwcRT, OvRtSwcRT, GwBaseSwcRt, ChanRtSwcRt) and options (UDMP_OPT); if specified not to simulate, the simulation can be simplified or skipped. SubRtSwcRt represents the subsurface side flow tracing activation switch, OvRtSwcRt represents the surface runoff tracing activation switch, GwBaseSwcRt represents the base flow tracing activation switch, ChanRtSwcRt represents the river runoff tracing activation switch, and UDMP_OPT represents the watershed setting activation switch.

[0073] Next, we examine the WRF-HydroQual (Weather Research and Forecasting Hydro Water Quality) model, which is a basin water cycle and water quality simulation model according to one embodiment.

[0074] Meanwhile, as illustrated in FIG. 1 above, the linkage structure between the basic model, WRF-Hydro, and the basin water cycle and water quality simulation model, WRF-HydroQual, can be developed in a direct linkage manner within the paddy module (120) and the reservoir hydrology module (130) within the surface model and the tracking model (e.g., the river tracking module), respectively. Additionally, the sediment transport model and the CNP model (Carbon, Nitrogen, and Phosphorus Model) may be structured to simulate independently of the WRF-Hydro model by reading the hydrological / hydraulic variable values ​​required in each subroutine from the WRF-Hydro simulation result file. This linkage method has the advantage of being able to flexibly respond to code changes, such as future upgrades of the WRF-Hydro model.

[0075] Considering the partitioning and aggregation structure between the upper and lower grids of the WRF-Hydro model, as shown in Fig. 4, the non module can be developed as a subroutine that is directly called within the Noah-MP index model.

[0076] The paddy field module is configured to provide functions capable of simulating hydrological and water quality processes in paddy fields through tight coupling as an internal module of the surface model Noah-MP. In paddy fields, it must be possible to control water depth and surface water flow based on the dike and irrigation gate heights specified by the user; the irrigation gate height must be input by the user according to the farming season, and runoff must occur through the irrigation gate when the water depth is higher than the irrigation gate height. Furthermore, since it must be possible to explicitly simulate processes of sediment transport, such as erosion and deposition, and changes in surface water quality depending on the water depth, the paddy field module can be configured with these considerations in mind.

[0077] Hydrological processes in a paddy grid are divided into inflows such as precipitation and irrigation, and outflows such as evapotranspiration, surface runoff, intermediate runoff, and aquifer runoff, and hydrological processes within the grid, such as infiltration / permeability and aquifer filling, are simulated (see Fig. 7a).

[0078] In the model, the paddy field embankment has a constant height and thickness on all sides, and a water inlet is located in the downstream direction. The structure allows for controlling the outflow by adjusting the height of the water inlet (see Fig. 7b). The flow rate through the water inlet of the paddy field is calculated using the square weir overflow equation (Equation 1).

[0079]

[0080]

[0081]

[0082] Meanwhile, the runoff coefficient Cd is calculated using the following formula (Mathematical Formula 2).

[0083]

[0084]

[0085] A reservoir sluice gate module capable of simulating the installation and operation of various sluice gates can be applied by adding a discharge volume simulation function for structures such as radial gates, sluice gates, and bottom hinged flap gates to the reservoir tracking module of the WRF-Hydro model, and the subroutine structure of the reservoir tracking module may be as shown in Fig. 5. Instead of maintaining the subroutine call structure of the reservoir tracking module as before, three types of sluice gate simulation functions are applied by adding a list of call variables.

[0086] The reservoir sluice module applies three additional types of sluice simulation functions in addition to the fixed weir and orifice simulation functions provided by the reservoir tracking module of the WRF-Hydro model. The subroutine call structure of the WRF-Hydro model can be maintained identically.

[0087] The outflow can be simulated by receiving time-series data from the user to set the sluice gate opening height. In this case, the downstream water level (ZD) of the sluice gate is not high enough to increase the upstream water level (ZU), the water flow through the sluice gate is free flow without a backwater effect, and if the user does not provide time-series data for the sluice gate opening, it can be assumed that there is no sluice gate opening.

[0088] A sediment transport model is required to simulate sediment transport in the watershed in conjunction with the hydrological simulation results of the WRF-Hydro model. Since the sediment transport model relates to the simulation of sediment erosion and transport, it can be developed by introducing concepts such as critical unit flow rate and effective settling velocity.

[0089] This sediment transport model simulates sediment transport processes spatially by distinguishing between surface sediment transport and stream sediment transport processes; surface sediment transport (overland plane sediment routing) is simulated using the hydrological simulation results of the Noah-MP model, while stream sediment transport is simulated using the hydraulic simulation results of the WRF-Hydro stream tracking model, but can be operated independently.

[0090] The sediment transport model can be incrementally improved by setting the land cover of some grids within the test area of ​​the WRF-Hydro model to paddy fields, dry fields, and forests, and constructing a sediment transport model under various conditions to simulate the sediment transport process for each grid of each land cover. Here, the sediment transport process can be classified into sediment separation, erosion, deposition, runoff, aggregation, and changes in storage volume, and the sediment transport model can be verified by closely examining whether the simulation results of each process over a certain period (e.g., one year) are reasonable.

[0091] In addition, an organic matter conversion and behavior model (hereinafter referred to as the 'CNP model') is required to simulate the conversion and behavior of carbon, nitrogen, and phosphorus at the watershed scale in conjunction with the hydrological simulation results of the WRF-Hydro model.

[0092] This CNP model classifies organic matter in a watershed into particulate and dissolved forms based on its form of existence, and into labile and refractory forms based on its decomposition rate. The classification of carbon, nitrogen, and phosphorus reservoirs in a watershed by the CNP model may be as described in Table 3.

[0093]

[0094] The linkage structure between the basin water cycle and water quality simulation model and the basic model according to one embodiment may include a point source pollution module.

[0095] Here, the point source pollution module is a module with an integrated water distribution simulation function, as shown in FIG. 6. As described, it may be an integration of a point source module and a water distribution module having mutually independent simulated structures.

[0096] Below, a point source module according to one embodiment will be examined in more detail.

[0097] As it is necessary to integrate water distribution simulation capabilities into the point source module, the WRF-HydroQual model is improved by extending its point source simulation function and directly inputting the water intake facility operation records and wastewater treatment facility effluent (return water for domestic and industrial use) into the water distribution model, thereby simultaneously simulating changes in flow rate and water quality.

[0098] The point source pollution module can simulate changes in flow rate and water quality resulting from point source pollution discharge in a river, and the water distribution module can simulate changes in flow rate and water quality resulting from water intake and discharge in a river.

[0099] At this time, while the input data for point source pollution consists entirely of river inflow (discharge), the input data for water distribution may include both river inflow (discharge) and outflow (water intake). However, considering the problem that the amount of water intake must be determined based on the river flow rate at the time of intake, and that when the input period of the point source module and the input period of the water intake for the water distribution module overlap, the river flow rate cannot be known at the time of input data creation, thus making it impossible to create input data in a format that integrates point source-water distribution input data, the WRF-HydroQual model is improved by independently inputting the input data for the point source module and the water distribution module, and by independently calculating the flow rate and load.

[0100] Figure 6 conceptually illustrates the independent simulation structures of the point source module and the water distribution module, representing the concept in which the point source module and the water distribution module each function independently. That is, as shown in Figure 6, the improved WRF-HydroQual model may integrate the point source module and the water distribution module, which have independent simulation structures.

[0101] The input data for the point source module is a text file in the form of a breakpoint time series; the discharge date and time, flow rate, and load (sediment, carbon, nitrogen, and phosphorus items) for each rich are written and provided in the model input data folder.

[0102] Meanwhile, in the water distribution module, intake and discharge flow rates and load can be calculated as follows: the intake flow rate is entered as a negative (-) number, and the discharge flow rate is entered as a positive (+) number. Intake flow rate (m 3 hr -1 ) is calculated as the smaller value between the maximum capacity of the water intake facility and 10% of the total available water volume of the river / reservoir at the time of intake. Water intake load (kg hr -1 The average water quality at the time of water intake of the relevant river / reservoir is applied and automatically calculated based on the intake flow rate. When water is drawn from within the basin and discharged within the basin, the user inputs the intake date and time, intake point, intake flow rate, discharge point, and the time (hr) required for the transfer-discharge process (input of the intake load is unnecessary as it is automatically calculated by reflecting the intake flow rate and water quality). When water is drawn from outside the basin and discharged into the basin, the user inputs the discharge date and time, discharge point, discharge flow rate, and discharge load for each item. It is assumed that there is no leakage or conversion during the transfer-discharge process for the discharge flow rate and load.

[0103] The input data for the water distribution module is a text file in the format of a breakpoint time series; for each rich, the intake-discharge dates, flow rates, and loads (sediment, carbon, nitrogen, and phosphorus items) are written and provided in the model input data folder.

[0104] (Example)

[0105] Pilot application of the WRF-HydroQual model

[0106] Pilot basin

[0107] The Geumho River basin was selected as a pilot basin to evaluate the performance and applicability of the WRF-HydroQual model according to the above-described embodiment. The Geumho River is one of the major tributaries of the Nakdong River, with a basin area of ​​2,092.6 km². It features an appropriate distribution of urban, agricultural, and forest areas, allowing for the examination of simulation results regarding various hydrological and water quality phenomena. Furthermore, river hydraulic structures such as the Yeongcheon Dam and Bohyeonsan Dam are located in the upstream area of ​​the basin, while agricultural areas receiving water through agricultural hydraulic facilities are distributed in the middle and downstream areas, making it a suitable region for evaluating the performance and applicability of the model. Additionally, the Geumho River basin is considered suitable as a pilot basin for the WRF-HydroQual model because it is possible to secure flow rate and water quality monitoring data for model validation, as well as discharge data from environmental infrastructure facilities that can be used as input data for the model.

[0108] The Geumho River basin includes 7 cities and counties, including Daegu Metropolitan City (24.7%), Gyeongsan City (18.9%), and Yeongcheon City (43.3%), and 18 major tributary streams, including Sinnyeongcheon, Jahocheon, Sincheon, and Omokcheon, flow into the main stream of the Geumho River.

[0109] Establishment of a model for the pilot watershed

[0110] The water quality models developed in this invention (sediment transport model, organic matter conversion and behavior model) were not yet linked with the tracking model of the WRF-Hydro model, so only the hydrological model was applied on a trial basis. To explicitly simulate hydrological / hydrological processes by land cover, both the surface model and the tracking model were constructed with the same grid network of 100m x 100m, and the total number of grids for the Geumho River basin model is 206,611.

[0111] Model construction for the pilot watershed was carried out by dividing it into two simulation periods as follows, depending on the purpose of the simulation. The simulation time interval for each model is 6 seconds, and the input / output time interval is 3600 seconds.

[0112] 15-day simulation: This was performed for the purpose of comparing and analyzing the simulation results of a model constructed using global data and a model constructed using domestic data.

[0113] 1-Year Simulation: This was conducted to evaluate the applicability of the model by comparing the flow rate simulation results of the model constructed using domestic data with the observed flow rate values ​​of the Geumho River.

[0114] The model for the Geumho River basin was constructed by updating domestic data into model input data generated using global data. The domestic data update items include spatial data such as land cover, soil texture, and topography (elevation), as well as time-series data such as temperature, wind speed, and solar radiation.

[0115] 15th mock

[0116] To evaluate the applicability of the WRF-HydroQual model, the simulation results of a model constructed using global data and a model constructed using domestic data were compared. The simulation period for each was 15 days, and the observed and simulated flow values ​​at four flow observation stations (Danpo Bridge, Geumchang Bridge, Ansim Bridge, and Gangchang Bridge) within the Geumho River basin were compared. Each model was simulated using default values ​​without parameter correction, and the evaluation indices NSE, RSR, and R2 were calculated by comparing the hourly flow simulation results of each model with the observed values.

[0117] The average values ​​of the evaluation indicators for four locations calculated for the simulation results of the global data model and the domestic data model were NSE 0.553 vs. 0.513, RSR 0.660 vs. 0.680, and R2 0.613 vs. 0.863. It was analyzed that, excluding NSE, the evaluation indicators of the domestic data model were somewhat better. The slightly higher R2 of the domestic data model in the uncorrected simulation results is believed to be due to the application of domestic meteorological data to reproduce rainfall patterns close to reality.

[0118] 1-year mock exam

[0119] The applicability of the WRF-HydroQual model, constructed using domestic data for the Geumho River basin, was evaluated based on one year of simulation results. The simulation results were obtained using default values ​​without parameter correction, and the evaluation indices NSE, RSR, and R2 were calculated by comparing the hourly flow rate simulation results with observed values.

[0120] The average values ​​of the evaluation indicators for the four flow observation stations were calculated as NSE 0.750, RSR 0.493, and R2 0.775, indicating that the simulated values ​​generally reproduce the observed values ​​well. Regarding peak flow, the simulated values ​​relatively well reproduce the magnitude and timing of the observed values. Although the base flow tends to show a slightly higher tendency in the simulated values ​​than in the observed values, these simulation results are considered very good given that no model calibration was performed. It is expected that the accuracy of the model can be further improved by performing calibration on the relevant parameters in the future.

[0121] conclusion

[0122] To enhance applicability to domestic watershed environments, some hydrological / hydrological simulation functions were added to the WRF-Hydro model (paddy field module, reservoir hydrological module), and a new water quality model was developed that can be simulated in conjunction with the WRF-Hydro model (sediment transport model, organic matter conversion and behavior model).

[0123] The paddy field module was developed to allow users to maintain or vary the water level in the paddy field grid by adjusting the height of the water gate, thereby simulating hydrological and hydraulic processes. The reservoir water gate module was developed to simulate the reservoir discharge volume when users adjust the opening height for three types of gates: lifting, rotary, and tilting. The paddy field module and the reservoir water gate module were developed to be directly coupled (tight-coupled) as internal modules of the WRF-Hydro model.

[0124] The sediment transport model was developed to simulate soil erosion and sediment transport within the grid by linking with hydrological variables of the Noah-MP surface model, and to simulate sediment transport within the stream by linking with hydraulic variables of the WRF-Hydro stream tracking model. The organic matter conversion and behavior model was developed to simulate the conversion and behavior of carbon, nitrogen, and phosphorus in the soil layer and aquifer within the grid by linking with hydrological variables of the Noah-MP surface model, and to simulate the conversion and behavior of carbon, nitrogen, and phosphorus within the stream and reservoir by linking with hydraulic variables of the WRF-Hydro stream tracking model. Both the sediment transport model and the organic matter conversion and behavior model were developed using a loose coupling method, where variable values ​​are input via hydrological simulation result files. This coupling method has the advantage of being able to flexibly respond to code changes, such as future upgrades of the WRF-Hydro model.

[0125] Model verification is the process of confirming whether a designed conceptual model has been converted into a computer model with sufficient accuracy. In this invention, the WRF-HydroQual model was constructed using data from the Croton New York test area provided by NCAR, and verification was performed on the paddy module, sediment transport model, and organic matter conversion and behavior model over a one-year simulation period (simulation time interval of 1 hour). The rationality of the model response, such as the influence of rainfall events and seasonal variations in soil temperature, was thoroughly analyzed for individual hydrological / water quality processes in the paddy, dryland, and forest grids of the test area, and the magnitude and irregularity of mass balance calculation errors were confirmed. As a result, it was determined that the computer model functions accurately according to the algorithm of the conceptual model.

[0126] Since the water quality models developed in this invention (sediment transport model, organic matter conversion and behavior model) were not yet linked with the tracking model of the WRF-Hydro model, only the hydrological model was applied on a trial basis. The WRF-HydroQual model was constructed on a trial basis using a 100 m x 100 m grid for the Geumho River basin, and its applicability was evaluated. Domestic data is much more detailed and accurate than global data for model input data such as land cover, soil texture, topography, and weather in the Geumho River basin. As a result of comparing the simulation results over 15 days between the model constructed using global data and the model constructed using domestic data, the evaluation indicators of the domestic data model were analyzed to be somewhat better. The average values ​​of the evaluation indicators comparing one year of hourly flow simulations using a domestic data model with observed values ​​from four locations were calculated as NSE 0.750, RSR 0.493, and R2 0.775, indicating that the simulated values ​​for both peak and base flows accurately reproduce the observed values. Considering that no model calibration was performed, these simulation results are considered very good.

[0127] FIG. 8 is a diagram illustrating an example of a hardware implementation of a distributed watershed water circulation and water quality simulation system according to one embodiment. A distributed watershed water circulation and water quality simulation system (1000) according to one embodiment may include a processor (1010) and a memory (1020).

[0128] The processor (1010) can drive a WRF-Hydro hydrological model including a surface model and a river tracking model from 2D point cloud data continuously acquired by a 2D lidar. Additionally, the processor (1010) can simulate the irrigation, storage, and drainage processes of a paddy field by being directly linked to the surface model, and can simulate the discharge volume according to the shape and operating conditions of a reservoir sluice gate by being directly linked to the river tracking model. Furthermore, the processor (1010) can receive a simulation result file of the hydrological model and drive a water quality model that independently simulates at least one inflow, transformation, and behavior selected from a group including carbon, nitrogen, and phosphorus. However, the operation of the processor (1020) is not limited to this, and it may also perform the operations described in FIGS. 1 to 7.

[0129] The memory (1020) can store hydrological models, water quality models, etc. The memory (1020) can temporarily or permanently store data required to perform a distributed watershed water cycle and water quality simulation method according to one embodiment. For example, the memory (1020) can store simulation results by a paddy field module, simulation results by a reservoir hydrological module, simulation result files of a WRF-Hydro hydrological model, etc.

[0130] A distributed watershed water circulation and water quality simulation system (1000) according to one embodiment is equipped with a WRF-HydroQual model suitable for domestic environmental conditions by adding a water quality simulation function to the indicator model Noah-MP and the tracking model that constitute the WRF-Hydro model, thereby enabling accurate simulation testing of water circulation and water quality within the watershed.

[0131] The embodiments described above may be implemented as hardware components, software components, and / or combinations of hardware and software components. For example, the devices, methods, and components described in the embodiments may be implemented using a general-purpose computer or a special-purpose computer, such as, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable gate array (FPGA), a programmable logic unit (PLU), a microprocessor, or any other device capable of executing and responding to instructions. The processing unit may execute an operating system (OS) and software applications executed on said operating system. Additionally, the processing unit may access, store, manipulate, process, and generate data in response to the execution of the software. For ease of understanding, the processing unit may be described as being used as a single unit, but those skilled in the art will understand that the processing unit may include multiple processing elements and / or multiple types of processing elements. For example, the processing unit may include multiple processors or one processor and one controller. In addition, other processing configurations, such as parallel processors, are also possible.

[0132] Software may include computer programs, code, instructions, or a combination of one or more of these, and may configure a processing unit to operate as desired or command the processing unit independently or collectively. Software and / or data may be permanently or temporarily embodied in any type of machine, component, physical device, virtual equipment, computer storage medium or device, or transmitted signal wave so as to be interpreted by the processing unit or to provide instructions or data to the processing unit. Software may be distributed over networked computer systems and may be stored or executed in a distributed manner. Software and data may be stored on computer-readable recording media.

[0133] The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded on a computer-readable medium. The computer-readable medium may store program instructions, data files, data structures, etc., either alone or in combination, and the program instructions recorded on the medium may be those specifically designed and configured for the embodiment or may be those known and available to those skilled in the art of computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tapes; optical recording media such as CD-ROMs and DVDs; magneto-optical media such as floptical disks; and hardware devices specifically configured to store and execute program instructions, such as ROM, RAM, and flash memory. Examples of program instructions include machine code, such as that generated by a compiler, as well as high-level language code that can be executed by a computer using an interpreter, etc.

[0134] The hardware device described above may be configured to operate as one or more software modules to perform the operation of the embodiment, and vice versa.

[0135] Although the embodiments have been described above with reference to the limited drawings, those skilled in the art can apply various technical modifications and variations based thereon. For example, suitable results may be achieved even if the described techniques are performed in a different order than described, and / or if the components of the described system, structure, device, circuit, etc. are combined or assembled in a form different from described, or replaced or substituted by other components or equivalents.

[0136] Therefore, other implementations, other embodiments, and equivalents to the claims also fall within the scope of the claims set forth below.

[0137] Although the technical concept of the present invention has been specifically described according to the preferred embodiments above, it should be noted that the above-mentioned embodiments are for illustrative purposes only and are not intended to be limiting. Furthermore, a person skilled in the art will understand that various embodiments are possible within the scope of the technical concept of the present invention. Explanation of the symbols

[0139] 100, 1000: Basin Water Cycle and Water Quality Simulation Prediction System 110 : Hydrological model, WRF-Hydro hydrological model 111 : Indicator model 112 : River Tracking Model 120 : Non-modular 130 : Reservoir Rumor Module 140 : Water quality model, WRF-HydroQual water quality model 150 : Point Source Module 1010 : Processor 1020 : Memory

Claims

Claim 1 A distributed watershed water cycle and water quality simulation system comprising: a WRF-Hydro hydrological model including a surface model and a stream tracking model; a paddy field module directly linked to the surface model to simulate the irrigation, storage, and drainage processes of paddy fields; a reservoir hydrological module directly linked to the stream tracking model to simulate the discharge volume according to the shape and operating conditions of the reservoir hydrological gate; and a WRF-HydroQual water quality model that receives a simulation result file of the WRF-Hydro hydrological model and independently simulates one or more inflows, transformations, and behaviors selected from a group including carbon, nitrogen, and phosphorus. Claim 2 In claim 1, the water quality model receives hydrological and hydraulic variable values ​​from the results of the hydrological model and simulates the processes of sediment erosion, transport, deposition, and resuspension in soil and rivers according to particle size, thereby simulating changes in water quality within the river, a distributed basin water cycle and water quality simulation system. Claim 3 In claim 2, the paddy field module comprises a distributed watershed water circulation and water quality simulation system in which the paddy field dike has constant height and thickness in all directions and a water gate is located in the downstream direction, so that the surface runoff is controlled according to the height of the water gate specified by the user, thereby maintaining or varying the water depth in the paddy field grid. Claim 4 A distributed watershed water cycle and water quality simulation system according to claim 1, further comprising a point source module linked to the hydrological model, which receives point source discharge flow rates and loads for each river section and simulates changes in flow rates and water quality within the river. Claim 5 In claim 4, the point source module defines the discharge of sewage treatment facilities and industrial wastewater treatment facilities as point sources, and is a distributed basin water cycle and water quality simulation system that receives discharge flow rates and loads as input data to simulate the impact on river water quality. Claim 6 In claim 5, the point source pollution module classifies the input load into items including carbon, nitrogen, and phosphorus, and classifies each item according to dissolved / particulate and non-biodegradable / biodegradable characteristics to simulate behavior within the river, thereby providing a distributed watershed water cycle and water quality simulation system. Claim 7 In claim 4, the point source module is a distributed basin water cycle and water quality simulation system that calculates pollutant transport and water quality changes by downstream section based on time-series fluctuations of discharge load, based on the river section where discharge occurs. Claim 8 In claim 7, the point source module is a distributed basin water cycle and water quality simulation system that receives point source discharge scenarios (discharge period, flow rate, load) for each river section as time series data and simulates them. Claim 9 A distributed basin water cycle and water quality simulation system according to claim 4, further comprising a water distribution module linked to the hydrological model to simulate changes in flow rate and water quality resulting from water intake and discharge, wherein the water distribution module calculates the amount of water intake by considering the maximum capacity of the water intake facility and the total available water quantity at the time of intake, and calculates the amount of water intake load by reflecting the average water quality at that time. Claim 10 In claim 1, the paddy field module and reservoir hydrology module are tightly coupled with the hydrology model, whereas the water quality model has a loose coupling structure in which it is simulated independently of the hydrology model, thereby enabling a distributed watershed water cycle and water quality simulation system that can flexibly respond to upgrades and code changes of the hydrology model. Claim 11 In claim 1, the water quality model is a distributed watershed water cycle and water quality simulation system that simulates behavior by particle size by classifying sediment into clay, silt, fine sand, and coarse sand. Claim 12 In claim 1, the reservoir sluice module is a distributed basin water circulation and water quality simulation system that calculates the discharge amount by reflecting at least one type among lifting, rotary, and tilting sluice gates. Claim 13 A method for simulating distributed watershed water cycle and water quality by a processor, comprising: a step of driving a WRF-Hydro hydrological model including a surface model and a stream tracking model; a step of simulating the irrigation, storage, and drainage processes of a paddy field directly linked to the surface model; a step of simulating the discharge amount according to the shape and operating conditions of a reservoir hydrological gate directly linked to the stream tracking model; and a step of driving a water quality model that receives a simulation result file of the hydrological model and independently simulates at least one inflow, transformation, and behavior selected from a group including carbon, nitrogen, and phosphorus. Claim 14 One or more non-transient computer-readable storage media storing instructions that, when executed by one or more computers, cause one or more computers to perform the operations of the individual methods of claim 13.

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