A meteorological and hydrological data management system based on multi-source data

Abstract

The present application belongs to the technical field of meteorological and hydrological data management, and relates to a meteorological and hydrological data management system based on multi-source data. The present application unifies and fuses meteorological data and hydrological data of a target region from different data sources to obtain a meteorological and hydrological data set of the target region, forms a more comprehensive and accurate data set, helps to eliminate data redundancy and inconsistency, improves the overall quality of data, helps to provide a basis for scientific research and policy making, analyzes current risk indicators and future prediction risk indicators of various natural disasters in the target region, and performs current risk management, future early warning management and measure management, helps to provide a scientific basis for formulating disaster prevention and reduction planning and allocating rescue resources, helps relevant departments and the public to make disaster response preparations in advance, improves the efficiency and effect of disaster response, and reduces the impact of disasters on human society and the natural environment.

Description

Technical Field

[0001] This invention belongs to the field of meteorological and hydrological data management technology, and relates to a meteorological and hydrological data management system based on multi-source data. Background Technology

[0002] With the increasing frequency of climate change and natural disasters, the demand for meteorological and hydrological data is growing. Whether in scientific research, weather forecasting, disaster early warning, water resource management, or environmental protection, accurate and timely meteorological and hydrological data are essential. Furthermore, the sources of data in meteorology and hydrology are becoming increasingly diverse. The numerous data sources, with their varying formats, different spatiotemporal resolutions, and massive volumes, pose significant challenges to data collection, integration, and effective utilization. Therefore, a meteorological and hydrological data management system based on multi-source data is of paramount importance and plays a crucial role.

[0003] Existing technologies also include some solutions related to multi-source data management. For example, Chinese Patent Publication No. CN118279167B discloses a mine layer management system based on multi-source data, which relates to the field of layer management technology and includes: an image acquisition module, a layer database module, a feature extraction module, a cluster analysis module, and a layer fusion module. The image acquisition module is used to acquire multi-source mine image data; the layer database module is used to store mine design drawing data and multi-source mine image data; the feature extraction module is used to extract features from the mine design drawing data and multi-source mine image data; the cluster analysis module is used to perform cluster analysis on the feature point set; and the layer fusion module is used to perform coordinate reconstruction and layer fusion of the mine design drawing data and multi-source mine image data based on the classified feature point set. This application achieves the fusion of multi-source mine images by combining feature extraction, cluster analysis, coordinate reconstruction, and layer fusion technologies, reducing the difficulty of multi-source data integration, improving data utilization, and thus enhancing management and planning support.

[0004] While the above-mentioned solutions offer some solutions for managing multi-source data, they still have certain limitations. On the one hand, existing solutions mainly achieve the integration of multi-source data by combining feature extraction, cluster analysis, coordinate reconstruction, and layer fusion techniques, which reduces the difficulty of multi-source data integration, improves data utilization, and thus enhances the support for management and planning. However, existing solutions lack the ability to associate and merge multiple types of multi-source data, which is not conducive to providing a basis for subsequent scientific research and policy formulation.

[0005] On the other hand, existing solutions also lack further detection and analysis based on multi-source data. For example, in terms of meteorological and hydrological data, they cannot analyze the current risks and future predicted risks of various natural disasters, which is not conducive to the formulation of disaster prevention and mitigation plans and the allocation of relief resources. They also fail to improve the efficiency and effectiveness of disaster response and reduce the impact of disasters on human society and the natural environment. Summary of the Invention

[0006] In view of this, in order to solve the problems mentioned in the background technology, a meteorological and hydrological data management system based on multi-source data is proposed.

[0007] The objective of this invention can be achieved through the following technical solution: This invention provides a meteorological and hydrological data management system based on multi-source data, including: a dataset acquisition module, a dataset parsing module, a management terminal, and a database.

[0008] The dataset acquisition module is used to detect meteorological and hydrological data of the target area in real time. It integrates and fuses meteorological and hydrological data of the target area from different data sources to obtain a meteorological and hydrological dataset of the target area, which is stored in the database. The dataset includes meteorological and hydrological data.

[0009] The dataset parsing module analyzes the current risk indicators and future predicted risk indicators of various natural disasters in the target area based on the meteorological and hydrological dataset of the target area. These natural disasters include floods, droughts, cold waves, debris flows, and landslides.

[0010] The management terminal is used to manage the current risks, future early warnings, and measures for various natural disasters in the target area based on current risk indicators and future predicted risk indicators.

[0011] The database is used to store meteorological and hydrological datasets for the target area. It stores the upper and lower limits of various meteorological parameters and hydrological parameters for the target area under the condition that no natural disasters occur. It also stores the current risk index range corresponding to each risk level of various natural disasters, and the future predicted risk index range corresponding to each predicted risk level of various natural disasters.

[0012] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. The present invention integrates and fuses meteorological and hydrological data from different data sources in the target area to obtain a meteorological and hydrological dataset of the target area, forming a more comprehensive and accurate dataset, which helps to eliminate data redundancy and inconsistency, improve the overall quality of the data, and help provide a basis for scientific research and policy formulation.

[0013] 2. By analyzing the current risk indicators and future predicted risk indicators of various natural disasters in the target area, this invention helps to provide a scientific basis for formulating disaster prevention and mitigation plans and allocating rescue resources. It also helps relevant departments and the public to prepare for disaster response in advance, improves the efficiency and effectiveness of disaster response, and reduces the impact of disasters on human society and the natural environment.

[0014] 3. This invention manages current risks, future early warnings, and measures for various natural disasters in the target area, and formulates targeted risk management measures to reduce casualties and property losses when disasters occur. It also helps relevant departments to plan ahead and prepare for possible future natural disasters, thereby reducing disaster losses. Attached Figure Description

[0015] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a schematic diagram of the system module connections of the present invention.

[0017] Figure 2 This is a flowchart illustrating the implementation steps of the module in this invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Please see Figure 1 As shown, this invention provides a meteorological and hydrological data management system based on multi-source data, with the following module distribution: a dataset acquisition module, a dataset parsing module, a management terminal, and a database. The modules are connected as follows: the dataset acquisition module is connected to the dataset parsing module, the dataset parsing module is connected to the management terminal, and the database is connected to the dataset acquisition module, the dataset parsing module, and the management terminal, respectively.

[0020] The dataset acquisition module is used to detect meteorological and hydrological data of the target area in real time. It integrates and fuses meteorological and hydrological data of the target area from different data sources to obtain a meteorological and hydrological dataset of the target area, which is stored in the database. The dataset includes meteorological and hydrological data.

[0021] It should be further explained that the flowchart for the implementation of the module steps is as follows: Figure 2 As shown.

[0022] It should be further explained that the methods for acquiring meteorological and hydrological data of the target areas from the different data sources include, but are not limited to, meteorological observation stations, hydrological stations, satellite remote sensing, radar, and ocean buoys.

[0023] As a preferred feasible example, the specific method for obtaining the meteorological and hydrological dataset of the target area is as follows: A1. Selecting the target data format: Taking into account the characteristics of meteorological and hydrological data of the target area from different data sources and the convenience of subsequent storage and use, a unified target data format is selected.

[0024] One specific example is that the characteristics include, but are not limited to, structured data, semi-structured data, unstructured data, time-series data, and spatial data.

[0025] The subsequent storage includes, but is not limited to, storage system compatibility and storage efficiency.

[0026] The ease of use includes, but is not limited to, ease of data access and query, ease of data processing and analysis, and ease of data sharing and exchange.

[0027] As a specific example, the data format includes, but is not limited to, NetCDF format and JSON format.

[0028] It should be further explained that if the meteorological and hydrological data of the target area from different data sources and in different formats are unstructured data, and the subsequent storage of the meteorological and hydrological data of the target area from different data sources and in different formats requires high storage efficiency, and the ease of use of the meteorological and hydrological data of the target area from different data sources and in different formats mainly considers the ease of data processing and analysis, then the NetCDF format can be selected as the unified target data format.

[0029] It should be noted that the advantages of the NetCDF format include, but are not limited to, unstructured data storage, efficient storage of multidimensional data, integrated storage of data and metadata, and good support for scientific computing and data processing.

[0030] A2. Data Format Conversion: Using data processing tools, convert the raw data formats of meteorological and hydrological data from different data sources in the target area into the target data format.

[0031] As a specific example, the data processing tools include, but are not limited to, the GDAL library.

[0032] A3. Spatiotemporal Registration: Based on the unified spatiotemporal resolution and target data format of meteorological and hydrological data from different data sources in the target area, further accurate registration of meteorological and hydrological data from different data sources in the target area in time and space is carried out. That is, data from different data sources at the same time correspond to the same spatial location, and data at the same spatial location are coherently matched in time series.

[0033] A concrete example is to accurately correlate the cloud image data of a target area acquired by satellite remote sensing at a certain moment with the temperature, precipitation and other data of the same area at the same moment from ground meteorological observation stations, so as to facilitate subsequent comprehensive analysis.

[0034] A4. Data Merging and Association: Based on the merging method, meteorological and hydrological data from different data sources in the target area are merged and associated to obtain meteorological and hydrological datasets from different data sources in the target area.

[0035] One specific example is that the merging method includes, but is not limited to, relational databases such as MySQL and Oracle.

[0036] A5. Multi-source data fusion: Based on the characteristics and fusion objectives of meteorological and hydrological datasets from different data sources in the target area, a suitable fusion algorithm is selected to fuse them to obtain the meteorological and hydrological dataset of the target area.

[0037] As a specific example, the fusion algorithm includes, but is not limited to, weighted average and Kalman filtering methods.

[0038] As a preferred feasible example, the meteorological data of the target area includes temperature, air pressure, wind speed, rainfall, snowfall and evaporation for the current time period, as well as temperature, air pressure, wind speed, rainfall, snowfall and evaporation for future time periods.

[0039] In one specific example, the future time period is within the next 48 hours.

[0040] It should be further explained that the specific method for obtaining the temperature, air pressure, wind speed, rainfall, snowfall, and evaporation for the future time period is as follows: the temperature, air pressure, wind speed, rainfall, snowfall, and evaporation for the future time period are obtained directly from the meteorological center of the target area.

[0041] The hydrological data for the target area include groundwater level, reservoir water level, flow rate, sediment content, soil moisture, runoff, and river ice thickness.

[0042] This invention integrates and fuses meteorological and hydrological data from different data sources in a target area to obtain a meteorological and hydrological dataset for that target area. This results in a more comprehensive and accurate dataset, which helps eliminate data redundancy and inconsistency, improves the overall quality of the data, and provides a basis for scientific research and policy making.

[0043] The dataset parsing module analyzes the current risk indicators and future predicted risk indicators of various natural disasters in the target area based on the meteorological and hydrological dataset of the target area. These natural disasters include floods, droughts, cold waves, debris flows, and landslides.

[0044] As a preferred feasibility example, the specific analysis method for the current risk indicators and future predicted risk indicators of flood disasters in the target area is as follows: extract the rainfall and evaporation, as well as the groundwater level, reservoir water level, and flow rate of the target area in the current time period, denoted as rain, eva, water1, water2, and flow, respectively, and analyze the current risk indicators of flood disasters in the target area. Where rain0, eva0, and water1′ are the maximum rainfall, minimum evaporation, and maximum groundwater level of the target area extracted from the database under the condition of no flooding, respectively, and water2′ and flow0 are the maximum water level and maximum flow of the reservoir in the target area extracted from the database, respectively.

[0045] Extract the rainfall and evaporation rates for the target area over a future time period.

[0046] By analyzing the current risk indicators of flood disasters in the target area, we can obtain the future predicted risk indicators of flood disasters in the target area.

[0047] As a preferred feasibility example, the specific analysis method for the current risk indicators and future predicted risk indicators of drought disaster in the target area is as follows: extract the current time period's temperature, rainfall, evaporation, groundwater level, and reservoir water level of the target area, denoted as T, rain, eva, water1, and water2, respectively, and analyze the current risk indicators of drought disaster in the target area. Where T0, rain′0, eva′0, and water1″ are the maximum temperature, minimum rainfall, maximum evaporation, and minimum groundwater level of the target area extracted from the database under non-drought conditions, respectively; μ1 is a set minimum value to prevent the denominator from being 0, and its unit is millimeters per minute; and e is a natural constant.

[0048] Extract temperature, rainfall, and evaporation for the target area over a future time period.

[0049] By analyzing the current risk indicators of drought disasters in the same target area, we can obtain the future predicted risk indicators of drought disasters in the target area.

[0050] As a preferred feasibility example, the specific analysis method for the current risk indicators and future predicted risk indicators of cold wave disasters in the target area is as follows: extract the temperature, wind speed, snowfall, and river ice thickness of the target area for the current time period, denoted as T, V, snow, and thickness, respectively, and analyze the current risk indicators of cold wave disasters in the target area. Where T0′, V0, snow0, and thickness0 are the minimum temperature, maximum wind speed, maximum snowfall, and maximum river ice thickness of the target area extracted from the database under the condition of no cold wave, respectively, and μ2 is a set minimum value to prevent the denominator from being 0, and its unit is degrees Celsius.

[0051] Extract temperature, wind speed, and snowfall for the target area over a future time period.

[0052] By analyzing the current risk indicators of cold wave disasters in the target area, we can obtain the future predicted risk indicators of cold wave disasters in the target area.

[0053] As a preferred feasibility example, the specific analysis method for the current risk indicators and future predicted risk indicators of debris flow disasters in the target area is as follows: extract the rainfall, groundwater level, flow rate, sediment content, soil moisture, and runoff of the target area for the current time period, denoted as rain, water1, flow, sand, hum, and runoff, respectively, and analyze the current risk indicators of debris flow disasters in the target area. Among them, rain1 and water1 1 ,flow′0,sand0,hum0, andrunoff0 are the maximum rainfall, maximum groundwater level, maximum flow rate, maximum sediment content, maximum soil moisture, and maximum runoff of the target area extracted from the database under the condition that no debris flow occurs.

[0054] Extract the rainfall amount for the target area in the future time period.

[0055] By analyzing the current risk indicators of debris flow disasters in the same target area, we can obtain the future prediction risk indicators of debris flow disasters in the target area.

[0056] As a preferred feasibility example, the specific analysis method for the current risk indicators and future predicted risk indicators of landslide disasters in the target area is as follows: extract the rainfall, groundwater level, sediment content, and soil moisture of the target area for the current time period, denoted as rain, water, sand, and hum, respectively, and analyze the current risk indicators of landslide disasters in the target area. Among them, rain1′ and water1′ 1 Sand0′ and hum′0 represent the maximum rainfall, maximum groundwater level, maximum sediment content, and maximum soil moisture of the target area extracted from the database under the condition that no landslides occur.

[0057] Extract the rainfall amount for the target area in the future time period.

[0058] By analyzing the current risk indicators of landslide disasters in the same target area, we can obtain the future prediction risk indicators of landslide disasters in the target area.

[0059] This invention analyzes current and future predicted risk indicators of various natural disasters in the target area, which helps to provide a scientific basis for formulating disaster prevention and mitigation plans and allocating relief resources. It also helps relevant departments and the public to prepare for disaster response in advance, improves the efficiency and effectiveness of disaster response, and reduces the impact of disasters on human society and the natural environment.

[0060] The management terminal is used to manage the current risks, future early warnings, and measures for various natural disasters in the target area based on current risk indicators and future predicted risk indicators.

[0061] As a preferred feasible example, the specific operation of current risk management for various natural disasters in the target area is as follows: extract the current risk indicators of various natural disasters in the target area, match them with the current risk indicator range corresponding to each risk level of various natural disasters stored in the database, obtain the risk level of various natural disasters in the target area, and further carry out current risk management for various natural disasters in the target area accordingly.

[0062] It should be further explained that the risk levels mentioned include high risk, medium risk, and low risk.

[0063] It needs to be further explained that the current risk management of flood disasters in the target area includes: (1) High risk level: increase the frequency of meteorological and hydrological data observation in the target area, update and issue early warning information every 15-30 minutes or even less; and immediately activate the emergency plan, organize residents in dangerous areas to evacuate urgently according to the predetermined evacuation route; inspect and reinforce flood control and drainage engineering facilities such as dikes, sluices, and pumping stations; and urgently call for flood control and disaster relief materials such as sandbags and stones. (2) Medium risk level: maintain the regular frequency of meteorological and hydrological data observation in the target area, issue flood disaster early warning information on a regular basis every day; publicize and inform residents in areas near the warning water level and in low-lying and easily flooded areas, reminding them to prepare emergency escape supplies; and conduct a comprehensive inspection and maintenance of flood control and drainage engineering facilities. (3) Low risk level: carry out work according to the normal meteorological and hydrological data observation plan of the target area.

[0064] The current risk management of drought disaster in the target area includes: (1) High risk level: increase the frequency of meteorological and hydrological data observation in the target area, issue drought warning information daily, and inform the public about the development and severity of drought; activate the emergency water resource allocation plan, prioritize the protection of domestic water use, and restrict or suspend the production water use of some high water-consuming industrial enterprises. (2) Medium risk level: maintain the normal observation frequency of meteorological and hydrological data in the target area, and issue drought warnings and reminders regularly; optimize the water resource allocation plan according to the water storage and water demand of the water source, and rationally arrange the allocation ratio of industrial, agricultural and ecological water use on the premise of ensuring domestic water use, appropriately reduce the part that can be saved in industrial and agricultural water use, and improve the efficiency of water resource utilization. (3) Low risk level: carry out work according to the normal meteorological and hydrological data observation plan of the target area.

[0065] The current risk management of cold wave disasters in the target area includes: (1) High risk level: increase the observation frequency of meteorological and hydrological data in the target area, update and issue cold wave warning information every 1-2 hours; remind residents to minimize going out, and if they need to go out, they must take precautions against the cold and avoid prolonged exposure to the cold environment; strengthen the inspection and maintenance of transportation infrastructure, promptly remove snow and ice from roads, spread de-icing agents and anti-skid sand on easily icy road sections, and ensure smooth and safe road traffic; organize power, communication and other departments to conduct comprehensive inspections and maintenance of power supply lines, communication base stations and other facilities, promptly repair any fault hazards found, and strengthen the cold protection measures for key equipment; coordinate energy supply companies to make energy reserves and allocation work in advance to ensure that the energy needs of residents for heating, electricity and gas during the cold wave are met. (2) Medium risk level: maintain the normal observation frequency of meteorological and hydrological data in the target area, and issue cold wave warning information regularly. (3) Low risk level: carry out work according to the normal meteorological and hydrological data observation plan of the target area.

[0066] The current risk management of debris flow disaster in the target area includes: (1) High risk level: increase the frequency of meteorological and hydrological data observation in the target area, and issue early warning information at least once per hour; immediately activate the emergency plan and organize residents, construction workers and others in the debris flow danger zone to evacuate quickly according to the predetermined emergency evacuation route; set up obvious warning lines and warning signs around the area that may be affected by debris flow; and promptly use simple measures such as sandbag stacking and geotextile covering to temporarily reinforce areas on the hillside where there are signs of unstable soil and rock, such as loose soil and cracks, to prevent further collapse of soil and rocks and trigger debris flow. (2) Medium risk level: maintain the normal observation frequency of meteorological and hydrological data in the target area, increase the number of patrols in areas prone to debris flow; conduct publicity and education for residents and units in areas with potential debris flow threats, inform them of the hazards of debris flow and key points of prevention, and remind them to prepare emergency escape supplies. (3) Low risk level: carry out work according to the normal meteorological and hydrological data observation plan for the target area.

[0067] The current risk management of landslide disasters in the target area includes: (1) High risk level: increase the frequency of meteorological and hydrological data observation in the target area; quickly activate the landslide emergency plan and organize personnel in the danger zone to evacuate according to the predetermined emergency evacuation route; set up obvious warning lines and warning signs around the landslide danger zone. (2) Medium risk level: maintain the normal observation frequency of meteorological and hydrological data in the target area; conduct extensive publicity and education for residents and staff in the potential landslide threat area, inform them of relevant knowledge about landslides, hazards and prevention points, and remind them to prepare necessary emergency escape supplies. (3) Low risk level: carry out work according to the normal meteorological and hydrological data observation plan for the target area.

[0068] As a preferred feasible example, the specific operation of future early warning management and measure management for various natural disasters in the target area is as follows: extract the future predicted risk indicators of various natural disasters in the target area, match them with the future predicted risk indicator ranges corresponding to each predicted risk level of various natural disasters stored in the database, obtain the predicted risk levels of various natural disasters in the target area, and further carry out future early warning management and measure management for various natural disasters in the target area accordingly.

[0069] It should be further explained that the specific operation of the future early warning management and measures management of various natural disasters in the target area is as follows: issue early warning information of different levels according to the predicted risk level of various natural disasters in the target area, and provide corresponding response suggestions.

[0070] This invention manages current risks, future early warnings, and measures for various natural disasters in a target area, and develops targeted risk management measures to reduce casualties and property losses when disasters occur. It also helps relevant departments plan ahead and prepare for possible future natural disasters, thereby reducing disaster losses.

[0071] The database is used to store meteorological and hydrological datasets for the target area, including the upper and lower limits of meteorological data parameters and hydrological data parameters for the target area under conditions where no natural disasters occur, the current risk index range corresponding to each risk level of various natural disasters, and the future predicted risk index range corresponding to each predicted risk level of various natural disasters.

[0072] The above content is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, and all such modifications and additions should fall within the protection scope of the present invention.

Claims

1. A meteorological and hydrological data management system based on multi-source data, characterized in that: include: The dataset acquisition module is used to detect meteorological and hydrological data of the target area in real time, and to integrate and fuse meteorological and hydrological data of the target area from different data sources to obtain a meteorological and hydrological dataset of the target area, which is stored in the database and includes meteorological and hydrological data. The dataset parsing module analyzes the current risk indicators and future predicted risk indicators of various natural disasters in the target area based on the meteorological and hydrological dataset of the target area. These natural disasters include floods, droughts, cold waves, debris flows, and landslides. The management terminal is used to manage the current risks, future early warnings, and measures for various natural disasters in the target area based on the current risk indicators and future predicted risk indicators of various natural disasters in the target area. The database is used to store meteorological and hydrological datasets for the target area. It stores the upper and lower limits of each parameter of meteorological data and each parameter of hydrological data for the target area under the condition that no natural disasters occur. It also stores the current risk index range corresponding to each risk level of various natural disasters and the future predicted risk index range corresponding to each predicted risk level of various natural disasters. The meteorological data for the target area includes the current temperature, air pressure, wind speed, rainfall, snowfall, and evaporation, as well as the future temperature, air pressure, wind speed, rainfall, snowfall, and evaporation. The hydrological data for the target area include groundwater level, reservoir water level, flow rate, sediment content, soil moisture, runoff, and river ice thickness; The specific analysis methods for the current risk indicators and future predicted risk indicators of flood disasters in the target area are as follows: Extract the rainfall and evaporation, as well as the groundwater level, reservoir water level, and flow rate of the target area for the current time period, and record them as follows: Analyze the current risk indicators of flooding in the target area. ,in These represent the maximum rainfall, minimum evaporation, and maximum groundwater level for the target area extracted from the database under conditions of no flooding. These are the maximum water level and maximum flow rate of the reservoir in the target area, extracted from the database, respectively. Extract the future rainfall and evaporation rates for the target area; By analyzing the current risk indicators of flood disasters in the target area, we can obtain the future predicted risk indicators of flood disasters in the target area.

2. The meteorological and hydrological data management system based on multi-source data according to claim 1, characterized in that: The specific method for obtaining the meteorological and hydrological dataset of the target area is as follows: A1. Select the target data format: Taking into account the characteristics of meteorological and hydrological data of the target area in different formats from different data sources, as well as the convenience of subsequent storage and use, select a unified target data format; A2. Data Format Conversion: Using data processing tools, convert the raw data formats of meteorological and hydrological data from different data sources in the target area into the target data format; A3. Spatiotemporal registration: Based on the unified spatiotemporal resolution and target data format of meteorological and hydrological data from different data sources in the target area, further accurate registration of meteorological and hydrological data from different data sources in the target area in time and space is carried out. That is, data from different data sources at the same time correspond to the same spatial location, and data at the same spatial location are coherently matched in time series. A4. Data Merging and Association: Based on the merging method, meteorological and hydrological data from different data sources in the target area are merged and associated to obtain meteorological and hydrological datasets from different data sources in the target area. A5. Multi-source data fusion: Based on the characteristics and fusion objectives of meteorological and hydrological datasets from different data sources in the target area, a suitable fusion algorithm is selected to fuse them to obtain the meteorological and hydrological dataset of the target area.

3. A meteorological and hydrological data management system based on multi-source data according to claim 1, characterized in that: The specific analysis methods for the current risk indicators and future predicted risk indicators of drought disaster in the target area are as follows: Extract the current time period's temperature, rainfall, evaporation, groundwater level, and reservoir water level for the target area, and record them as follows: Analyze the current risk indicators of drought disasters in the target area. ,in These are the maximum temperature, minimum rainfall, maximum evaporation, and minimum groundwater level of the target area extracted from the database under conditions where drought does not occur. This is a minimum value set to prevent the denominator from being zero, and its unit is millimeters per minute. It is a natural constant; Extract temperature, rainfall, and evaporation rates for the target area over a future time period; By analyzing the current risk indicators of drought disasters in the target area, we can obtain the future predicted risk indicators of drought disasters in the target area.

4. A meteorological and hydrological data management system based on multi-source data according to claim 3, characterized in that: The specific analysis methods for the current risk indicators and future predicted risk indicators of cold wave disasters in the target area are as follows: Extract the current time period's temperature, wind speed, snowfall, and river ice thickness for the target area, and record them as follows: Analyze the current risk indicators of cold wave disasters in the target area. ,in These are the minimum temperature, maximum wind speed, maximum snowfall, and maximum river ice thickness for the target area extracted from the database under conditions where no cold wave occurs. This is a minimum value set to prevent the denominator from being zero, and its unit is degrees Celsius. Extract temperature, wind speed, and snowfall for the target area over a future time period; By analyzing the current risk indicators of cold wave disasters in the target area, we can obtain the future predicted risk indicators of cold wave disasters in the target area.

5. A meteorological and hydrological data management system based on multi-source data according to claim 4, characterized in that: The specific analysis methods for the current risk indicators and future predicted risk indicators of debris flow disasters in the target area are as follows: Extract the rainfall, groundwater level, flow rate, sediment content, soil moisture, and runoff for the target area in the current time period, and record them as follows: Analyze the current risk indicators of debris flow disasters in the target area. ,in These are the maximum rainfall, maximum groundwater level, maximum flow rate, maximum sediment content, maximum soil moisture, and maximum runoff of the target area extracted from the database under the condition that no debris flow occurs; Extract the rainfall forecast for the target area over a future time period; The analysis method of current risk indicators of debris flow disasters in the same target area is used to obtain future pre-prediction risk indicators of debris flow disasters in the target area.

6. A meteorological and hydrological data management system based on multi-source data according to claim 5, characterized in that: The specific analysis methods for the current risk indicators and future predicted risk indicators of landslide disasters in the target area are as follows: Extract the current time period's rainfall, groundwater level, sediment content, and soil moisture for the target area, and record them as follows: Analyze the current risk indicators of landslide disasters in the target area. ,in These are the maximum rainfall, maximum groundwater level, maximum sediment content, and maximum soil moisture of the target area extracted from the database under the condition that no landslides occur; Extract the rainfall forecast for the target area over a future time period; By analyzing the current risk indicators of landslide disasters in the target area, we can obtain the future prediction risk indicators of landslide disasters in the target area.

7. A meteorological and hydrological data management system based on multi-source data according to claim 1, characterized in that: The specific operations for current risk management of various natural disasters in the target area are as follows: Extract the current risk indicators of various natural disasters in the target area, and match them with the current risk indicator range corresponding to each risk level of various natural disasters stored in the database to obtain the risk level of various natural disasters in the target area, and further manage the current risk of various natural disasters in the target area accordingly.

8. A meteorological and hydrological data management system based on multi-source data according to claim 7, characterized in that: The specific operations for future early warning management and measure management of various natural disasters in the target area are as follows: Extract future predicted risk indicators for various natural disasters in the target area, and match them with the range of future predicted risk indicators corresponding to each predicted risk level of various natural disasters stored in the database to obtain the predicted risk level of various natural disasters in the target area. Based on this, further conduct future early warning management and measure management for various natural disasters in the target area.

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