Distributed human-water relationship model construction method and simulator design method

Abstract

The invention discloses a distributed human-water relationship model construction method and a simulator design method, and relates to the field of hydrological models and intelligent water conservancy. Comprising information perception system design, human-water relationship database design, technical support system design, distributed human-water relationship model design, human-water relationship simulation system design, result display system design and application service system design. By integrating multi-source data, such as information of meteorology, hydrology, economy, society, ecology and the like, a high-precision distributed human-water relationship model is constructed, and dynamic simulation, visual analysis and optimization decision support of a human-water relationship evolution process are realized in combination with an efficient simulator design. The method can accurately reflect the mutual influence of human activities and water resources in different scenes, provides systematic and reliable decision basis for water resource management, and improves the scientificity and refinement level of water conservancy work.

Description

Technical Field

[0001] The present invention relates to the fields of hydrological models and smart water conservancy, and more particularly to a distributed human-water relationship model construction method and a simulator design method. Background Art

[0002] The "human-water relationship" encompasses the interactions between humans and water, a fundamental, eternal, and insurmountable relationship. In recent years, river basins and regions have generally seen a continuous expansion of human activity and a growing impact, significantly impacting the water cycle. On the one hand, accelerating urbanization and a more diversified population and industrial landscape have complicated water resource management processes, such as storage, withdrawal, supply, use, consumption, and discharge. This has led to a growing complexity in the formation and transformation of water resources within river basins. On the other hand, water conservancy project construction, inter-basin water transfers, and surface modification have altered the natural runoff cycle, shifting the pathways and modes of the water cycle. The natural and social water cycle fluxes in river basins are experiencing a trade-off, with the former decreasing while the latter increasing, and the non-steady-state nature of river basins is becoming increasingly pronounced.

[0003] Significant progress has been made in hydrological and water resource simulation technologies, including distributed hydrological models, hydrodynamic models, and water resource optimization and scheduling models, which can simulate water cycle processes influenced by human activities to a certain extent. However, these models still have limitations in simulating the coupled relationship between human and water systems, making it difficult to accurately describe the dynamic evolution of the social water cycle. Furthermore, they lack efficient computing architectures and visualization analysis tools, making them difficult to meet the needs of modern water resource management. Summary of the Invention

[0004] In light of this, this paper provides a method for constructing a distributed human-water relationship model and simulator design, suitable for the dynamic scheduling, allocation, and management of water resources. By constructing a high-precision distributed model and combining it with advanced simulator design, this paper can effectively reveal and predict the changing trends of the human-water relationship, providing scientific decision-making support for optimizing water resource allocation, protecting aquatic ecosystems, responding to flood disasters, and sustainably utilizing water resources.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] A method for constructing a distributed human-water relationship model includes the following steps:

[0007] Based on the multi-agent system, different hydrological regions are divided into multiple agent nodes. Each node independently simulates the water cycle process, material cycle process, biological process, and human process, and works in collaboration with other nodes through an information sharing mechanism to adapt to the analysis needs of different spatial and temporal scales.

[0008] Through distributed simulation of precipitation, evaporation, transpiration, groundwater infiltration and surface runoff, the temporal and spatial distribution and flow patterns of water resources are dynamically portrayed, reflecting the relationship between water supply and demand in different regions;

[0009] Simulate the impact of ecosystems on water quality, consider the role of organisms in water bodies on water resources, and quantify the long-term and short-term impacts of biological processes on water cycles and water quality by integrating ecological models;

[0010] Simulate the impact of human activities on water systems and provide decision makers with effective water resources management solutions.

[0011] Optionally, it also includes support for simulation analysis of influencing factors, evaluation of the evolution trend of the relationship between people and water under a changing environment, and provision of flexible interfaces for expanding the consideration of the role of other external factors in different scenarios.

[0012] A distributed human-water relationship simulator design method, using any one of the above-mentioned distributed human-water relationship model construction methods, includes the following steps:

[0013] Design information perception system, including data source, data collection, data transmission, and data preprocessing;

[0014] Design of human-water relationship database, including data classification storage, data standardization, data indexing and retrieval, data update and management, data security and backup;

[0015] Design a distributed human-water relationship model, including a distributed architecture base model, a water cycle process expression module, a material cycle process expression module, a biological process expression module, and a human process expression module;

[0016] Design a simulation system for the human-water relationship, including simulation of the evolution of the human-water system, simulation of the impact of human activities on the water system, simulation of the impact of water system changes on the human system, and simulation of the mutual influence between the human system and the water system;

[0017] Design result display system, including core display engine, display function module, user interaction and feedback module, report output and data export;

[0018] Design an application service system, including scientific and technological innovation services, information sharing services, resource guarantee services, government decision-making services, emergency management services, and public cultural services.

[0019] Optionally, the data source includes meteorological, hydrological, economic, social, and ecological data to comprehensively reflect the multi-dimensional information of the relationship between people and water;

[0020] The data collection adopts multiple methods such as real-time monitoring, remote sensing data acquisition, and social surveys to obtain data from different sources and time and space scales to ensure the breadth and diversity of the data;

[0021] The data transmission, through the Internet of Things and cloud computing, ensures that the data is transmitted to the data processing center in real time and efficiently after collection, thus ensuring the timeliness and accuracy of the data;

[0022] The data preprocessing includes denoising, filling missing values, data conversion, and data integration of the original data, using appropriate algorithms and methods to ensure the quality and consistency of the data.

[0023] Optionally, the design of the human-water relationship database includes the following specific aspects:

[0024] The data classification storage is to classify and store different types of data by field or application scenario according to the source and function of the data;

[0025] The data standardization is to format data from different sources using a unified standard;

[0026] The data indexing and retrieval, establishing a data index structure;

[0027] The data updating and management mentioned above involves designing an automated data updating mechanism to automatically update relevant data in the database based on real-time monitoring results or preset time intervals;

[0028] The data security and backup mentioned above adopt multi-level security protection measures, including data encryption, permission control, identity authentication, and regular data backup.

[0029] Optionally, the design of the human-water relationship simulation system includes the following aspects:

[0030] The simulation of the evolution of the human-water system, within the framework of the human-water coupling system, simulates the co-evolution of the human-water system, comprehensively considers economic and social development factors, as well as the spatiotemporal distribution of water resources, water cycle processes, and water environment changes, depicts the interactions and feedback relationships within the human-water system, and reveals the evolution laws and coupling characteristics of the human-water relationship;

[0031] Simulate the effects of human activities on water systems, assess the impact of different human activities on water resource consumption and pollution, and analyze the specific impacts of various human activities on water quality, water quantity, and water resource allocation;

[0032] Simulate the impact of water system changes on the human system, analyze the impact of water resource changes on the economy and society, consider how changes in water resource supply affect agricultural production, industrial development, and urban water use, and assess the potential threats of water resource supply and demand imbalances to economic development, people's livelihood security, and social stability;

[0033] The mutual influence simulation between the human system and the water system analyzes the feedback relationship between the water system and the economic and social system, reveals how water resource management measures, policy adjustments and economic activities react to the stability and development of the water system, and studies the interaction mechanism between the human system and the water system through modeling of two-way influences.

[0034] Optionally, the design of the result display system includes the following aspects:

[0035] The core display engine uses efficient data rendering and display technology and optimized graphics processing and rendering algorithms;

[0036] The display function module supports multiple data display formats, and users can freely choose the display format according to different needs;

[0037] The user interaction and feedback module allows users to interact with the system, select data, switch views, zoom, and annotate through a graphical interface, and provide improvement suggestions to the system through a feedback mechanism;

[0038] The report output and data export support generating reports in various formats and exporting data to common formats.

[0039] Optionally, the design of the application service system includes the following services:

[0040] The scientific and technological innovation services are used to provide technical support and promote scientific and technological innovation in the field of water resources management;

[0041] The information sharing service is used to promote the sharing and exchange of data and information on human and water systems;

[0042] The resource assurance service is used to provide scientific water resource assessment and allocation plans through precise data analysis and model simulation, helping governments at all levels and relevant departments to formulate reasonable water resource management policies and ensure the sustainable supply and management of water resources;

[0043] The government decision-making service is used to provide scientific basis for the government to assist in decision-making;

[0044] The emergency management service is used to provide emergency response and treatment plans for sudden water resource incidents;

[0045] The public cultural services are used to raise public awareness of water resources management and environmental protection.

[0046] It can be seen from the above technical solutions that, compared with the prior art, the present invention provides a distributed human-water relationship model construction method and simulator design method, which have the following beneficial effects:

[0047] 1. Improving the scientific and refined level of water resource management: By constructing a highly accurate distributed model of the human-water relationship, this invention accurately simulates the interaction and evolution of human activities and water resources. This model can provide accurate water resource management solutions under complex and changing conditions, thereby improving the scientific and refined level of management and helping governments and businesses to achieve rational resource allocation.

[0048] 2. Enhanced Decision Support: This invention incorporates a highly efficient simulator and visualization analysis system that dynamically simulates the evolving relationship between people and water, enabling decision makers to intuitively understand the impact of different policies and measures on water resource management. This not only helps decision makers gain a deeper understanding of complex water issues but also provides a precise basis for optimizing decision-making, particularly when addressing emergencies such as water shortages and pollution, enabling more targeted solutions.

[0049] 3. Promoting the Development and Application of Smart Water Conservancy: This invention combines a distributed architecture with advanced technologies to provide technical support for the implementation of smart water conservancy. By building a flexible and scalable system architecture, it supports multi-level and multi-regional application needs, promoting the popularization and development of smart water management systems. The system can adapt to complex geographical environments and changing hydrological conditions, ensuring the refined management and precise scheduling of water conservancy projects.

[0050] 4. Efficient Multi-Source Data Integration and Analysis: By integrating heterogeneous data from multiple sources, including hydrological, meteorological, economic, and social data, this invention overcomes the traditional water resources management model's reliance on a single data source, enhancing the model's adaptability and operability. The system can rapidly process and analyze large amounts of data, providing more comprehensive and accurate information support for water resources management. This unique advantage is particularly evident in addressing the complex and ever-changing relationship between people and water. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0052] Figure 1 Schematic diagram of the overall process of the method of the present invention;

[0053] Figure 2 Design a structural diagram for the information perception system;

[0054] Figure 3 Design structure diagram for human-water relational database;

[0055] Figure 4Design a structural diagram for the technical support system;

[0056] Figure 5 Design a structural diagram for the distributed human-water relationship model;

[0057] Figure 6 Schematic diagram of the design structure of the human-water relationship simulation system;

[0058] Figure 7 Design a schematic diagram for the results display system;

[0059] Figure 8 Design a structural diagram for the application service system. DETAILED DESCRIPTION

[0060] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0061] This embodiment describes in detail a distributed human-water relationship model construction method and simulator design method, aiming to provide technical support for the establishment of big data models, the optimization management of human-water relationships, and the practical application of smart water conservancy. Figure 1 As shown in the figure, this method realizes the dynamic management and optimization of the human-water system through the design and integration of information perception system, data processing and storage, distributed model and simulation system, and comprehensive service system.

[0062] 1. Information perception system design, such as Figure 2 As shown in the figure, through efficient data collection and transmission, the system can obtain various types of data in real time, providing support for subsequent analysis and simulation.

[0063] Data sources: including remote sensing satellites, ground sensors, weather stations, flow monitoring stations, etc., providing multi-dimensional data on hydrology, meteorology, land use, agricultural activities, economy and society, ensuring the applicability of the model in a wide range of areas.

[0064] Data collection: High-precision sensors (such as groundwater monitoring sensors, meteorological data collectors, flow monitors, etc.) as well as drones and remote sensing technology are used to collect real-time data on hydrological changes, agricultural irrigation, climate change and other factors in the region; for important monitoring points, multi-point sampling and dynamic monitoring are used to ensure high spatial resolution and timeliness of the data.

[0065] Data transmission: Transmitted to the data center through high-speed data transmission networks such as IoT technology and 5G networks; a distributed architecture is used to combine edge computing with cloud computing, and data pre-processing is performed through edge nodes to reduce transmission delays and improve real-time performance and reliability.

[0066] Data preprocessing: Preprocess the collected data, including data cleaning, missing value filling, data fusion, denoising, etc.; use machine learning-based interpolation algorithms to fill missing data, and use anomaly detection algorithms to identify and correct outliers.

[0067] 2. Design of human-water relationship database, such as Figure 3 As shown, it is the core of data storage and management, involving a variety of technical means to ensure the integrity, validity and security of data.

[0068] Data classification storage: To adapt to the management needs of different data types, data is divided into multi-level sub-databases, including water resources data, meteorological data, land use data, economic and social data, etc.; multidimensional databases (such as OLAP models) and graph databases (such as Neo4j) are used to store spatial data and relational data for efficient query and analysis.

[0069] Data standardization and conversion: An extraction, conversion, and loading process is used to convert data from different sources into a unified format, unit, and coordinate system to ensure efficient data sharing and compatibility. All data is coded and labeled according to ISO standards to ensure data consistency across departments and regions.

[0070] Data indexing and retrieval: By establishing a multi-level indexing system based on B-tree, hash index, and R-tree, it supports efficient query and analysis of large-scale data; full-text search technology (such as Lucene) is used to index text data to quickly retrieve key indicators or water resource information within a specific time period.

[0071] Data update and management: Design an automated data update mechanism that supports scheduled synchronization and real-time update functions; synchronize data with external data sources (such as the Meteorological Bureau, traffic monitoring stations, etc.) through automated scripts and API interfaces to ensure the timeliness of database content; and ensure historical traceability and version management of data through strict data auditing and version control mechanisms.

[0072] Data security and backup: Use data encryption and access control mechanisms (such as role-based access control (RBAC)) to ensure data security; design a multi-level data backup system to regularly back up important data, and use a dual backup method of the cloud platform and local servers to ensure data recoverability.

[0073] 3. Design of technical support system, such as Figure 4As shown, it provides multi-dimensional support in computing, data, communication, algorithms, security, and operation to ensure efficient and stable operation of the system.

[0074] Computing support: Adopting a high-performance computing architecture based on cloud computing, it supports large-scale parallel computing and real-time processing of massive data. Through GPU acceleration technology, it improves the computing speed and processing power of model simulation. Through containerization technology (such as Docker, Kubernetes, etc.), it performs dynamic resource scheduling to ensure the efficient execution of computing tasks.

[0075] Data support: Use distributed data storage technologies (such as Hadoop, Spark and other big data frameworks) to store and process massive amounts of data, supporting fast data retrieval and real-time analysis; and use data stream processing platforms (such as Apache Kafka) to achieve real-time data flow.

[0076] Communication support: 5G, LoRa and other communication technologies are used to ensure high-frequency, large-scale real-time data transmission; MPLS (Multi-Protocol Label Switching) and SD-WAN (Software-Defined Wide Area Network) technologies are used to ensure low latency and high reliability of the network.

[0077] Algorithm support: The system integrates multiple algorithms such as water resource simulation, optimal scheduling, and climate change prediction, and uses numerical methods such as the finite element method (FEM) and the finite difference method (FDM) to accurately simulate the hydrological cycle and material cycle processes.

[0078] Security support: We use multiple security protection measures such as firewall technology, intrusion detection system (IDS), SSL encryption, etc. to encrypt all sensitive data end-to-end to ensure the security of data transmission.

[0079] Operational support: Microservice architecture and containerization technology are used to ensure the flexibility and scalability of system modules. Monitoring tools such as Prometheus and Grafana are used to monitor system performance and status in real time to ensure the stability of the system during operation.

[0080] 4. Design of distributed human-water relationship model, such as Figure 5 As shown in the figure, a human-water relationship model based on a distributed architecture is designed to simulate the dynamic changes and mutual influence of the human-water system.

[0081] Base model of distributed architecture: Based on the multi-agent system (MAS), different hydrological areas are divided into multiple agent nodes. Each node independently simulates processes such as water cycle and material cycle, and works collaboratively with other nodes through an information sharing mechanism to adapt to analysis needs at different spatial and temporal scales.

[0082] Water cycle process expression module: simulates hydrological processes such as precipitation, evaporation, transpiration, groundwater infiltration and surface runoff, and dynamically depicts the spatiotemporal distribution and flow patterns of water resources. It not only considers the impact of natural factors (such as climate, topography, soil type, and vegetation cover) on hydrological processes, but also incorporates the interference of human activities (such as land use changes and water resource exploitation) on the water cycle. Through distributed simulation, it accurately reflects the relationship between water resource supply and demand in different regions, providing key hydrological driving data for other modules. Embedded formulas include but are not limited to:

[0083] a. Water balance equation:

[0084]

[0085] Where: S i is the water storage capacity of unit i, P i is the precipitation, E i is the evaporation amount, T i is the transpiration rate, R i is the surface runoff, G i is the groundwater infiltration rate.

[0086] b. Surface runoff calculation (SCS-CN method):

[0087]

[0088] Where: S i is the potential water storage capacity, which is related to soil type and land use.

[0089] c. Evaporation and transpiration calculation (Penman-Monteith equation):

[0090]

[0091] Where: ET i is the evaporation rate, R n is the net radiation, ρ a is the soil heat flux, c a is the air density, c p is the specific heat capacity, e s and e a are the saturated vapor pressure and the actual vapor pressure, r a is the aerodynamic drag, r s is the surface resistance.

[0092] d. Groundwater recharge equation:

[0093] G i =k i ·(S i -S gw,i )

[0094] Where: k i is the permeability coefficient, S gw,i For groundwater reserves.

[0095] Material Cycle Process Expression Module: This module simulates the migration, transformation, and accumulation of key substances such as nitrogen, phosphorus, and pollutants in water bodies, revealing the direct and indirect impacts of human activities on water quality. It focuses on the impacts of agricultural non-point source pollution (such as fertilizer and pesticide runoff), industrial point source pollution (such as wastewater discharge), and urban domestic sewage on water bodies, while also considering the purification effects of natural processes (such as sedimentation, degradation, and biological absorption) on pollutants. Embedded formulas include but are not limited to:

[0096] a. Nitrogen cycle equation:

[0097]

[0098] Where: N is the nitrogen reserve of unit i, N in,i is the input (such as fertilizer, precipitation), N out,i is the output (such as runoff loss), N uptake,i is the amount of vegetation absorption, N denit,i is the loss due to denitrification.

[0099] b. Pollutant migration equation:

[0100]

[0101] Where: C is the pollutant concentration, D is the diffusion coefficient, v is the flow velocity, and k is the degradation coefficient.

[0102] c. Sedimentation and resuspension equation:

[0103]

[0104] Where: S sed,i is the amount of sediment, v dep is the deposition rate, v res is the resuspension rate.

[0105] Biological Process Expression Module: Simulates the growth, succession, and feedback processes of biological communities in water bodies and surrounding ecosystems, and analyzes the interactions between ecosystems and water systems. It focuses on vegetation dynamics (such as the growth and degradation of forest, grassland, and wetland vegetation), changes in animal habitats (such as habitat suitability for fish and birds), and the evolution of ecological service functions (such as water conservation, water purification, and biodiversity maintenance). Embedded formulas include but are not limited to:

[0106] a. Single population growth rate equation, assuming that the number of a population at time t is N t, from t to t+Δt, the average population growth rate s and the average population relative growth rate r can be expressed as:

[0107]

[0108] Let Δt→0, and we can get the expressions of the single population growth rate s and relative growth rate r at time t:

[0109]

[0110] b. Vegetation dynamic equation:

[0111]

[0112] Where: B i is the vegetation biomass, r b is the growth rate, B max is the maximum biomass, m b For mortality rate.

[0113] c. Ecological service function equation:

[0114] ES i =c1·B i +c2·W i +c3·S i

[0115] Where: ES i is the ecological service function value, B i is the vegetation biomass, W i is the amount of water resources, S i is the soil quality, c1, c2, c3 are weight coefficients.

[0116] d. Animal habitat suitability equation:

[0117] H i =a·W i +b·B i +c·Q i

[0118] Where: H i is the habitat suitability index, W i is the amount of water resources, B i is the vegetation coverage, Q i is the water quality index, and a, b, and c are weight coefficients.

[0119] Human Process Expression Module: Simulates the impact of human activities on water resources and the ecological environment, focusing on water resource behaviors such as agricultural irrigation, industrial water use, urban water demand, and sewage treatment, as well as the feedback effects of policy implementation on water resource management and ecological restoration. By quantifying the pressure of human activities on water resources (such as water consumption and pollution emissions) and the response (such as water-saving technologies and pollution control), it reveals the dynamic evolution of the relationship between people and water. Embedded formulas include but are not limited to:

[0120] a. Population and economic indicator growth equation:

[0121] Growth rate equation expression:

[0122]

[0123] Where: H is the population or other specific economic and social indicators at time t, s t 、r t H at time t t growth rate, relative growth rate.

[0124] Malthusian Model of Growth:

[0125]

[0126] Where: H0 is the number of a certain indicator at time t0, t0 is the initial time, r is H t The constant value of relative growth rate.

[0127] Growth Logistic Model:

[0128]

[0129] Where: k is the index H t The maximum growth amount (constraint amount).

[0130] Considering the delayed growth Hutchinson model:

[0131]

[0132] Where: τ is the index H t delay time.

[0133] Two-index Lotka-Volterra model with competing relationships:

[0134]

[0135] Where: H 1,t 、H 2,tare the functions of indicators H1 and H2 with respect to t, r1 and r2 are the growth rates of indicators H1 and H2 respectively, K1 and K2 are the constraints of indicators H1 and H2 respectively, α is the competition intensity coefficient of indicator H2 to H1, and β is the competition intensity coefficient of indicator H1 to H2.

[0136] b. Agricultural irrigation water equation:

[0137] W agri,i =k agri ·A i ET crop,i

[0138] Where: W agri,i is the agricultural water consumption, k agri is the irrigation efficiency coefficient, A i is the irrigated area, ET crop,i The water requirement of crops.

[0139] c. Urban water use equation:

[0140] W urban,i =p i ·q per +I i ·q ind

[0141] Where: W urban,i is the urban water consumption, p i is the population, q per is the per capita water consumption, I i is the industrial output value, q ind The water consumption per unit output value.

[0142] d. Wastewater treatment and reuse equation:

[0143] W reuse,i =η·W waste,i

[0144] Where: W reuse,i is the amount of recycled water, η is the recycling efficiency, W waste,i The amount of sewage discharged.

[0145] e. Policy feedback equation:

[0146] ΔW i =α·(W target,i -W current,i )

[0147] In the formula: ΔW i is the water consumption adjustment value, α is the policy implementation intensity, W target,i is the target water consumption, W current,i is the current water consumption.

[0148] Other process expression modules: Considering the long-term impact of external factors such as climate change and population growth on water resources, the development trend of the human-water system is predicted through scenario analysis.

[0149] The construction of the distributed human-water relationship model based on the SWAT model is as follows:

[0150] ① Data preparation and preprocessing. Download the required data and perform preprocessing: splice the downloaded DEM data, clip the study area, project the coordinate system, and fill the depressions; splice the downloaded soil data, clip the study area, project the coordinate system, etc.; reclassify the soil data and create a soil index table, use SPAW software to calculate soil hydrological parameters and build a SWAT model soil database; splice the downloaded land use data, clip the study area, project the coordinate system, etc.; reclassify the land use types (cultivated land, forest land, grassland, water area, construction land, and unused land) and create a land use index table; downscale the meteorological data and extract the meteorological station data in the study area to create a meteorological data index table (relative humidity, rainfall, solar radiation, temperature, wind speed), use the SWATweather tool to process various meteorological data, and build the WGEN_user weather generator.

[0151] ② Model initialization. We integrated multiple modeling approaches, including the SWAT model, the system dynamics model, and the Invest model, and initialized each model. In the SWAT model, we set the watershed boundaries, sub-watershed divisions, and HRU divisions; in the system dynamics model, we set economic and social variables and their relationships; and in the Invest model, we set ecosystem service assessment parameters.

[0152] ③ Module Development. By coupling various tools and methods, such as SWAT and system dynamics, four modules of the distributed human-water relationship model were developed based on the "four major processes" of the human-water system. The water cycle process module: Based on the SWAT model, parameters for hydrological processes such as precipitation, evaporation, runoff, and groundwater are set. The material cycle process module: Combining SWAT and the system dynamics model, parameters for the migration and transformation of substances such as nitrogen and phosphorus are set. The biological process module: Combining SWAT and the Invest model, parameters for processes such as vegetation growth and biodiversity are set. The human process module: Based on the system dynamics model, parameters for processes such as population growth, economic development, and water resource management are set.

[0153] ④ Module coupling. Set the data exchange frequency and format to ensure data consistency and integrity. Couple the models through data exchange (e.g., the output of the SWAT model as the input of the system dynamics model) to ensure data exchange and collaborative operation between modules.

[0154] ⑤ Model operation. The SWAT model uses ArcSWAT, a specialized interface tool, in conjunction with ArcGIS software. The Invest model, based on Python, also uses ArcGIS for spatial data processing and model operation. The system dynamics model uses Vensim software for modeling and operation. The different modules (water cycle module, material cycle module, biological process module, and human process module) are coupled through data exchange to form a closed-loop system. Transmission and feedback mechanisms enable information flow and dynamic adjustment between modules, thereby solving the distributed human-water relationship model.

[0155] ⑥ Model calibration and validation. The SWAT model used in the underlying model construction method can be calibrated using SWAT-CUP. This program can connect algorithms such as GLUE (maximum likelihood method), ParaSol, SUFI-2, MCMC and PSO with the SWAT model to perform sensitivity analysis, calibration, validation and uncertainty analysis of the SWAT model. The program has 11 model performance criteria (such as R 2 , Pbias, etc.), which can be used as the objective function for calibrating and validating the SWAT model. At the same time, the program has a graphical module for displaying simulation results, a dot plot for visualizing parameter sensitivity, a 95% prediction uncertainty (95PPU) for visualizing parameter sensitivity, and visualization functions such as p-factor and r-factor, sensitivity, etc. for quantifying uncertainty. In addition, the model results are verified using historical observation data, and the sensitivity of different input parameters to the model results is analyzed to determine which parameters have a greater impact on the model results, thereby optimizing the parameter settings. For the evaluation of model performance, the coefficient of certainty (R 2 ) and Nash efficiency coefficient (NSE) are used to evaluate the simulation accuracy of the constructed model. The calculation formula is as follows:

[0156]

[0157] Where: n is the total number of observations, i is the order of observations, Q s,i is the simulation value of the i-th time, is the average value of the simulation value, Q o,i is the i-th observation value, is the average value of the observed values. 2 , when R 2 =1, indicating that the change trend of the observed value is completely consistent with that of the simulated value; R 2 The further away from 1, the less consistent the observed and simulated values are. For NSE, the closer the NSE is to 1, the closer the simulated value is to the observed value; and the further the NSE deviates from 1, the further the simulated value deviates from the observed value.

[0158] 5. Design of human-water relationship simulation system, such as Figure 6 As shown in the figure, by simulating the evolution of the human-water system, the mutual influence between the human system and the water system is predicted.

[0159] Simulation of the evolution of the human-water system: Quantify changes in water supply and demand, and simulate changes in water supply and demand on short-term, medium-term and long-term time scales based on a distributed human-water relationship model; analyze influencing factors, comprehensively consider the impact of climate change (such as changes in precipitation patterns and rising temperatures) and economic and social activities (such as urbanization and industrialization) on water supply and demand; scenario simulation, evaluate the sustainability of water resources by setting different scenarios (such as extreme climate events and policy adjustments); trend forecast, use historical data and real-time monitoring data to predict future water supply and demand trends and generate a water supply and demand balance report.

[0160] Simulation of the impact of human activities on water systems: Land use change analysis, using remote sensing data and GIS technology to analyze land use change trends and their impact on water resources; agricultural activity simulation, combining hydrological models and material cycle models to evaluate the impact of agricultural irrigation water and non-point source pollution on water resource quantity and quality; industrial activity simulation, simulating the consumption and pollution of water resources by industrial water use and pollution emissions; management strategy formulation, based on simulation results, proposing management strategies such as water conservation, pollution control and ecological restoration.

[0161] Simulation of the impact of water system changes on human systems: Agricultural production impact analysis, using crop growth models to evaluate the impact of water shortages on agricultural output; drinking water safety impact analysis, using health risk assessment models to analyze the threat of water pollution to residents' health; ecological and environmental impact analysis, combining ecological models to evaluate the impact of water resource changes on ecosystem service functions; policy formulation support, based on simulation results, proposing water resource management policies (such as water price reform and ecological compensation).

[0162] Simulation of the mutual influence between human systems and water systems: Design of a two-way feedback mechanism, simulating the interaction between human activities and water systems through system dynamics models; simulation of the impact of human activities, simulating the impact of human water use behavior and pollution emissions on water resource distribution and water quality; water system feedback simulation, analyzing the feedback effect of water resource changes on the economic, social and ecological environment; scenario analysis and policy evaluation, identifying potential water resource crises and proposing response measures (such as water resource allocation and ecological restoration) by setting different scenarios.

[0163] 6. Design of result display system, such as Figure 7 As shown, by integrating the core display engine, display function module, user interaction and feedback module, report output and data export module, the effectiveness and operability of the system in practical applications are ensured.

[0164] Core display engine: Based on advanced visualization technologies such as WebGL and D3.js, it builds an efficient and interactive data display platform; it can render large-scale spatial data in real time and support users to select different analysis results for visualization according to their needs.

[0165] Implementation method: Dynamic map display, users can use dynamic maps to view key information such as water resource distribution, the impact of climate change on hydrological processes, and the progress of ecological restoration; multi-scale display, supporting multi-scale display such as region, watershed, and grid unit to meet analysis needs at different levels; rich visualization forms, providing heat maps, streamline maps, three-dimensional topographic maps and other visualization forms to help users intuitively understand the dynamics of complex human-water systems.

[0166] Functional effects: Realize real-time rendering and interactive display of large-scale spatial data; provide multi-scale and multi-dimensional visualization analysis functions to improve data understanding efficiency.

[0167] Display function module: supports the comprehensive display and analysis of multi-dimensional data such as water resources, economy, society, and ecosystem.

[0168] Implementation method: Data layer selection: users can select different data layers (such as precipitation, water consumption, pollutant concentration, and vegetation coverage) for dynamic overlay and comparative analysis; time series analysis: users can view the evolution trend of historical data and future forecast results, and analyze the long-term patterns of water resource changes; optimization scheduling tool: built-in water resource allocation plan generation tool and pollution control strategy optimization tool to help users quickly identify problems and provide optimization suggestions.

[0169] Functional effect: Realize comprehensive display and dynamic analysis of multi-dimensional data; provide optimization scheduling tools to support users to quickly generate solutions.

[0170] User interaction and feedback module: Improve user experience through friendly interface design and efficient interactive functions.

[0171] Implementation method: Interactive operation allows users to interact with data through operations such as dragging, zooming, and clicking, adjust parameters (such as time range, spatial range, and analysis indicators) in real time, and view changes in results; user feedback function allows users to annotate, comment, and share simulation results, promoting multi-party collaboration and decision optimization; intelligent prompt function automatically recommends relevant data and analysis tools based on user operations to improve usage efficiency.

[0172] Functional effect: Provides intuitive and efficient interactive experience, enhances user participation; supports multi-party collaboration and decision optimization, and improves system practicality.

[0173] Report output and data export module: supports users to output analysis results and data in various forms to meet the needs of different scenarios.

[0174] Implementation method: Customized report generation allows users to choose to generate reports in formats such as PDF and Word, which include key charts, data analysis results, and optimization suggestions; the data export function supports exporting raw data, analysis results, and visual charts to common formats such as CSV, Excel, and GeoJSON for further analysis or integration with other systems; automated report generation allows users to simply select templates and parameters, and the system will automatically generate high-quality reports, significantly improving work efficiency.

[0175] Functional effect: Provides flexible report output and data export functions to meet diverse needs; significantly improves work efficiency through automated report generation.

[0176] 7. Application service system design, such as Figure 8 As shown, by integrating multiple service modules, the effectiveness and operability of the system in practical applications are ensured.

[0177] Technological Innovation Services: We are committed to promoting scientific and technological progress and innovative applications in the field of water resources management; by introducing cutting-edge technologies such as remote sensing interpretation, the Internet of Things, big data analysis, and artificial intelligence, we will improve the intelligence level of water resources monitoring, scheduling, and assessment.

[0178] Specific implementation: Application of remote sensing technology to monitor changes in surface water and groundwater in real time and generate high-precision water resource distribution maps; deployment of Internet of Things equipment to place water quality and water quantity monitoring equipment at key nodes to achieve real-time data collection and transmission; big data analysis to predict water resource supply and demand trends and generate supply and demand balance reports based on historical data and real-time monitoring data; development of intelligent tools to research and develop water resource scheduling optimization algorithms to support dynamic adjustment of water resource allocation plans.

[0179] Functional effect: Realize high-precision monitoring and prediction of water resources; improve the intelligence level of water resource scheduling and allocation.

[0180] Information sharing service: aims to build an efficient and open water resources information platform to promote cross-departmental and cross-regional sharing and exchange of data and resources.

[0181] Specific implementation: Data integration, integrating meteorological, hydrological, land use, economic and social data from multiple sources to build a watershed water resources information database; platform construction, developing a water resources information sharing platform to support data access and sharing from multiple departments and regions; data analysis, providing historical data archiving and trend analysis functions to generate water resources change trend reports; collaborative management, supporting cross-departmental and cross-regional collaborative management to improve water resources management efficiency.

[0182] Functional effect: Break down information silos and realize data interconnection and interoperability; provide comprehensive and real-time data support for decision makers.

[0183] Resource assurance service: Resource assurance service provides scientific water resource assessment and allocation solutions through precise data analysis and model simulation.

[0184] Specific implementation: Water resources assessment, based on a distributed human-water relationship model, evaluates the water supply and demand situation in the basin; allocation plan formulation, combining factors such as climate change, population growth, and economic development to formulate a scientific water resources allocation plan; policy optimization, puts forward suggestions for optimizing water resources utilization policies to avoid resource waste or over-exploitation.

[0185] Functional effect: Achieve accurate assessment and optimal allocation of water resources; ensure sustainable supply and management of water resources.

[0186] Government Decision-Making Services: Provide government departments with decision-making support tools based on a distributed human-water relationship model to help decision makers fully understand the current status and future trends of the human-water relationship.

[0187] Specific implementation: Scenario simulation, simulating changes in water supply and demand, regional distribution and ecological impacts under different policy scenarios; decision support, generating decision support reports and proposing scientific and reasonable water resource management strategies; policy evaluation, evaluating the effectiveness of existing policies and proposing optimization suggestions.

[0188] Functional effect: Provide scientific basis for government decision-making; enhance the foresight and operability of policies.

[0189] Emergency Management Services: Provide rapid response and scientific treatment solutions for sudden water resource incidents (such as floods, droughts, water pollution, etc.).

[0190] Specific implementation: Emergency plan generation, simulating emergency scenarios such as floods, droughts, and water pollution to generate emergency plans; emergency response, providing specific emergency measures to relevant departments and optimizing emergency resource allocation; drills and training, organizing emergency drills and training to enhance emergency response capabilities.

[0191] Functional effect: Improve the response speed and handling efficiency of emergencies; minimize disaster losses.

[0192] Public cultural services: Enhance public awareness and participation in water resources management and environmental protection through publicity and education, science popularization activities and information release.

[0193] Specific implementation: Science popularization activities, organizing water resources science lectures, exhibitions and practical activities to convey to the public the importance of water conservation and protection; information release, regularly updating water resources protection dynamics and policy interpretations through information release platforms; public participation, encouraging the public to participate in water resources protection and management, and creating a good atmosphere of common concern for the whole society.

[0194] Functional effect: Enhance public awareness and participation in water resource protection, and promote joint action by the whole society for the sustainable use of water resources.

[0195] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Reference can be made to the common and similar parts between the various embodiments. For the devices disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the method description.

[0196] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for constructing a distributed human-water relationship model, characterized in that: The following steps are involved: Based on the multi-agent system, different hydrological regions are divided into multiple agent nodes. Each node independently simulates the water cycle process, material cycle process, biological process, and human process, and works in collaboration with other nodes through an information sharing mechanism to adapt to the analysis needs of different spatial and temporal scales. Through distributed simulation of precipitation, evaporation, transpiration, groundwater infiltration and surface runoff, the temporal and spatial distribution and flow patterns of water resources are dynamically portrayed, reflecting the relationship between water supply and demand in different regions; Simulate the impact of ecosystems on water quality, consider the role of organisms in water bodies on water resources, and quantify the long-term and short-term impacts of biological processes on water cycles and water quality by integrating ecological models; Simulate the impact of human activities on water systems and provide decision makers with effective water resources management solutions.

2. A distributed human-water relationship model construction method according to claim 1, characterized in that: It also includes support for simulation analysis of influencing factors, evaluation of the evolution trend of the relationship between people and water under a changing environment, and provides a flexible interface for expanding the consideration of the role of other external factors in different scenarios.

3. A distributed human-water relationship simulator design method, using a distributed human-water relationship model construction method according to any one of claims 1-2, characterized in that: The following steps are involved: Design information perception system, including data source, data collection, data transmission, and data preprocessing; Design of human-water relationship database, including data classification storage, data standardization, data indexing and retrieval, data update and management, data security and backup; Design a distributed human-water relationship model, including a distributed architecture base model, a water cycle process expression module, a material cycle process expression module, a biological process expression module, and a human process expression module; Design a simulation system for the human-water relationship, including simulation of the evolution of the human-water system, simulation of the impact of human activities on the water system, simulation of the impact of water system changes on the human system, and simulation of the mutual influence between the human system and the water system; Design result display system, including core display engine, display function module, user interaction and feedback module, report output and data export; Design an application service system, including scientific and technological innovation services, information sharing services, resource guarantee services, government decision-making services, emergency management services, and public cultural services.

4. A distributed human-water relationship simulator design method according to claim 3, characterized in that: The data sources mentioned above cover meteorological, hydrological, economic, social, and ecological data to comprehensively reflect the multi-dimensional information on the relationship between people and water; The data collection adopts multiple methods such as real-time monitoring, remote sensing data acquisition, and social surveys to obtain data from different sources and time and space scales to ensure the breadth and diversity of the data; The data transmission, through the Internet of Things and cloud computing, ensures that the data is transmitted to the data processing center in real time and efficiently after collection, thus ensuring the timeliness and accuracy of the data; The data preprocessing includes denoising, filling missing values, data conversion, and data integration of the original data, using appropriate algorithms and methods to ensure the quality and consistency of the data.

5. The method for designing a distributed human-water relationship simulator according to claim 3, characterized in that: The design of the human-water relationship database includes the following specific aspects: The data classification storage is to classify and store different types of data by field or application scenario according to the source and function of the data; The data standardization is to format data from different sources using a unified standard; The data indexing and retrieval, establishing a data index structure; The data updating and management mentioned above involves designing an automated data updating mechanism to automatically update relevant data in the database based on real-time monitoring results or preset time intervals; The data security and backup mentioned above adopt multi-level security protection measures, including data encryption, permission control, identity authentication, and regular data backup.

6. A distributed human-water relationship simulator design method according to claim 3, characterized in that: The design of the human-water relationship simulation system includes the following aspects: The simulation of the evolution of the human-water system, within the framework of the human-water coupling system, simulates the co-evolution of the human-water system, comprehensively considers economic and social development factors, as well as the spatiotemporal distribution of water resources, water cycle processes, and water environment changes, depicts the interactions and feedback relationships within the human-water system, and reveals the evolution laws and coupling characteristics of the human-water relationship; Simulate the effects of human activities on water systems, assess the impact of different human activities on water resource consumption and pollution, and analyze the specific impacts of various human activities on water quality, water quantity, and water resource allocation; Simulate the impact of water system changes on the human system, analyze the impact of water resource changes on the economy and society, consider how changes in water resource supply affect agricultural production, industrial development, and urban water use, and assess the potential threats of water resource supply and demand imbalances to economic development, people's livelihood security, and social stability; The mutual influence simulation between the human system and the water system analyzes the feedback relationship between the water system and the economic and social system, reveals how water resource management measures, policy adjustments and economic activities react to the stability and development of the water system, and studies the interaction mechanism between the human system and the water system through modeling of two-way influences.

7. The method for designing a distributed human-water relationship simulator according to claim 3, characterized in that: The design of the result display system includes the following aspects: The core display engine uses efficient data rendering and display technology and optimized graphics processing and rendering algorithms; The display function module supports multiple data display formats, and users can freely choose the display format according to different needs; The user interaction and feedback module allows users to interact with the system, select data, switch views, zoom, and annotate through a graphical interface, and provide improvement suggestions to the system through a feedback mechanism; The report output and data export support generating reports in various formats and exporting data to common formats.

8. The method for designing a distributed human-water relationship simulator according to claim 3, characterized in that: The design of the application service system includes the following services: The scientific and technological innovation services are used to provide technical support and promote scientific and technological innovation in the field of water resources management; The information sharing service is used to promote the sharing and exchange of data and information on human and water systems; The resource assurance service is used to provide scientific water resource assessment and allocation plans through precise data analysis and model simulation, helping governments at all levels and relevant departments to formulate reasonable water resource management policies and ensure the sustainable supply and management of water resources; The government decision-making service is used to provide scientific basis for the government to assist in decision-making; The emergency management service is used to provide emergency response and treatment plans for sudden water resource incidents; The public cultural services are used to raise public awareness of water resources management and environmental protection.

Images