Method and system for compiling water ecological data of rivers, lakes and reservoirs

Abstract

The invention relates to a river, lake and reservoir water ecological data compilation method and system, and relates to the field of water ecological environment monitoring. According to the technical scheme, through multi-source heterogeneous data collection and Excel automatic integration, the problem of scattered data analysis management is effectively solved, original data standardization arrangement is achieved, unified data storage and resource application services are provided, and the water ecological data informatization management level and utilization efficiency are greatly improved. Moreover, through a high-order implementation normal form of species naming matching, accurate association retrieval of species and Compendium family information is realized, manual discrimination deviation is avoided, and data accuracy is ensured; a result engine reorganization generation mechanism replaces manual operation, the reorganization efficiency is remarkably improved, and the error rate is reduced. In addition, self-defined evaluation parameters are supported to generate adaptive results, complex scene analysis is adapted, the scheme is high in replicability and extensibility, the method can be popularized and applied to the same type of water bodies throughout the country, and reliable technical support is provided for water ecological planning protection decision making.

Description

Technical Field

[0001] This invention relates to the field of water ecological environment monitoring technology, and in particular to a method and system for compiling and organizing water ecological data of rivers, lakes and reservoirs. Background Technology

[0002] Water ecological monitoring is a prerequisite and crucial foundation for various water conservancy projects, including ensuring ecological flow in rivers and lakes, assessing river and lake health, ecological scheduling of watershed reservoirs, designing and constructing fish passage facilities in water conservancy projects, connecting and ecologically restoring river and lake systems, and ensuring water supply security. This invention aims to overcome the technical bottlenecks in data compilation and application during water ecological monitoring, providing reliable data support for the comprehensive management and application of water ecological data. Currently, my country has numerous rivers and lakes, and the aquatic species in various water bodies are extremely diverse. The classification relationships of species at the phylum, class, order, family, and genus levels are complex and varied, and aquatic organisms use a unique Latin nomenclature system, making the information integration of water ecological monitoring data extremely difficult.

[0003] Currently, aquatic species data management largely relies on fragmented databases and manual Excel processing, which presents several problems: First, data naming and identification are difficult. Latin names and synonyms lead to strong subjectivity and bias in manual identification, and the matching of end-point species with phylum, class, order, family, and genus is complex, making verification and application difficult. Second, the data is heterogeneous and scattered, with diverse record formats, inconsistent formats, and missing historical data, making effective integration difficult. Third, compilation efficiency is low; manual summarization, proofreading, and entry are time-consuming and have a high error rate. The root causes of these technical deficiencies can be analyzed from two aspects: Objectively, aquatic species are diverse and have unique names, making it impossible for human experience to handle the identification and verification of massive amounts of data; technically, existing management can only achieve basic storage, lacking intelligent cleaning and correlation analysis capabilities, unable to establish a usable information database, and lacking an effective management engine, resulting in a broken data processing chain, difficulty in querying and calling, and difficulty in carrying out results-oriented applications. Furthermore, existing general data analysis tools (such as Python and R language tools) require professionally customized scripts, which are difficult to use and have poor reusability.

[0004] In summary, the technical challenges in compiling and organizing aquatic ecological data are: firstly, aquatic ecological data itself has the objective characteristics of being diverse in species types, data formats, and being scattered; and secondly, there is a lack of unified and effective data analysis and organization methods and application frameworks. Summary of the Invention

[0005] The purpose of this invention is to provide a method and system for compiling and integrating ecological data of rivers, lakes and reservoirs, so as to solve the problems existing in the prior art.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows: In a first aspect, the present invention provides a method for compiling and integrating river, lake, and reservoir water ecological data, the method comprising: Based on an Excel-based automated integration tool, the original water ecology record data is integrated into a standardized data table, and the fields are standardized. A storage management framework is built using a domestically developed data management engine, combined with the EasyExcel data parsing engine, to parse and read the standardized data tables and achieve engine-based aggregated management. Based on the standardized data collected and managed by the engine, a water ecological data compilation engine is built, and the built-in water ecological evaluation algorithm and evaluation process are integrated to complete the data preparation. The water ecological data compilation engine generates a water ecological data compilation result table and a raw record result table based on preset query conditions, thereby realizing the compilation and output of water ecological data.

[0007] In some implementations, the automated integration tool based on Excel secondary programming, which integrates raw aquatic ecosystem records into standardized data tables, includes: Place the standardized Excel template, the original Excel data on aquatic ecology, and the Excel automated integration tool in the same folder; By defining the mapping relationship between fields in the canonical table and related similar fields in the original table through the program, it is possible to support one field in the canonical table corresponding to multiple similar fields in the original table; The Excel automation integration tool automatically converts raw data into a standardized data table and supports modifying mapping fields via text to ensure compatibility with newly added mapping objects.

[0008] In some implementations, the use of a domestically developed data management engine to build a storage management framework, combined with the EasyExcel data parsing engine, to parse and read the standardized data tables and achieve engine-based aggregated management includes: A water ecosystem data storage and management framework is built using a domestically developed data management engine, and the framework interface calls the EasyExcel data parsing engine to read standardized data tables. A high-order implementation paradigm for similar element retrieval in integrated generic sets is proposed. Based on the Java type parameterization mechanism, a type-safe container operation boundary is constructed to realize the retrieval and matching of aquatic species information and the associated output of phylum, class, order, family, and genus classification information. The domestically developed data management engine provides services for data import, addition, conditional query, modification and maintenance, and result export. During the data import process, it performs data verification and checks, and marks field issues.

[0009] In some implementations, the data import service includes multi-user sub-index entry of single species information and batch import of multiple species information from Excel, and the conditional query service includes query based on a combination of conditions such as species classification, phylum, class, order, family, genus, species, Latin name, and Chinese name.

[0010] In some implementations, the modification and maintenance service includes adding and deleting species association map information, modifying and deleting species information, and the result export service supports exporting query results in the form of Excel reports.

[0011] In some implementations, the integrated water ecological assessment algorithm and assessment process complete data preparation, including: The system includes a built-in aquatic organism status evaluation algorithm, which includes a fish retention index evaluation algorithm, a phytoplankton Shannon-Wiener diversity index or Margalef richness index evaluation algorithm, a zooplankton loss index evaluation algorithm, a benthic animal BMWP biological index or FBI biological index evaluation algorithm, and an aquatic vascular plant coverage evaluation algorithm. The built-in water eutrophication status assessment algorithm adopts the index method and includes the following steps: converting water quality item concentration values ​​into assigned values ​​through linear interpolation, calculating the eutrophication status index EI based on the assigned values, and determining the eutrophication status classification according to the eutrophication status index. It supports users to define water ecosystem types, monitoring station groups, and project groups to generate adaptive evaluation results.

[0012] In some implementations, the step of generating a water ecological data compilation result table and a raw record result table through the water ecological data compilation engine according to preset query conditions includes: Collect and classify paper reports on water ecological monitoring, extract data elements and summarize report text, establish multiple types of compiled report templates, and build a template repository. The water ecological data compilation engine provides filtering functions for compilation objects, compilation projects, and time conditions; Based on the screening criteria, standard data and evaluation analysis data are retrieved to generate a compiled result file including phytoplankton monitoring data result table, zooplankton monitoring data result table, benthic animal monitoring data result table, fish monitoring data result table, and raw data record result table. The compiled result files are imported into the water ecological data compilation system, which integrates the storage management framework built by the domestically produced data management engine and the water ecological data compilation engine, to form a compiled result database, supporting preview, detailed viewing, download, and printing operations.

[0013] In some implementations, the method further includes a batch import intelligent error correction step: During the batch data import process, data type errors and logical errors are marked in real time, and online editing functions are provided to correct erroneous data. The method also includes a data integration and exchange step: By adopting RESTful API or WebService data interface technology, we define standardized data interface standards, clarify interface functions, input and output parameters and data formats, and realize the sharing and interaction of water ecological data. The method also includes a data processing step: The collected raw data is cleaned to remove noisy data, outliers, and duplicate data; The cleaned data is then transformed and normalized to conform to the data format and standards required by the engine.

[0014] In some embodiments, the raw aquatic ecosystem record data includes at least one of plankton data, benthic organism data, fish data, and water quality monitoring data, and the data format includes database format, Excel format, and text format.

[0015] Secondly, the present invention provides a system for compiling and integrating river, lake, and reservoir water ecological data. This system is applied to the river, lake, and reservoir water ecological data compilation and integration method described above. The system includes: The data normalization and integration unit is used to integrate raw water ecology record data into a standardized data table based on an Excel-based automated integration tool, and to complete the field normalization process. The data parsing and engine-based aggregation unit is used to build a storage management framework using a domestically developed data management engine, and combined with the EasyExcel data parsing engine, to parse and read the standardized data table and achieve engine-based aggregation management. The water ecology assessment algorithm integration and data preparation unit is used to build a water ecology data compilation engine based on the standardized data collected and managed by the engine, and to complete the data preparation by integrating the built-in water ecology assessment algorithm and assessment process. The compilation result generation and output unit is used to generate a water ecological data compilation result table and a raw record result table according to preset query conditions through the water ecological data compilation engine, so as to realize the compilation and output of water ecological data.

[0016] Thirdly, the present invention provides a computer device, which includes a processor and a memory. The memory stores at least one instruction, at least one program, code set or instruction set. The processor can load and execute at least one instruction, at least one program, code set or instruction set to realize the method for compiling and integrating river, lake and reservoir water ecological data provided above.

[0017] The beneficial effects of the technical solution provided by this invention include at least the following: This technical solution effectively solves the challenges of managing and parsing fragmented data by aggregating heterogeneous data from multiple sources and automating integration with Excel. It achieves standardized organization of raw data, provides unified data storage and resource application services, and significantly improves the level of information management and utilization efficiency of aquatic ecological data. Furthermore, through a high-order implementation paradigm of species nomenclature matching, it enables precise association retrieval of species with phylum, class, order, family, and genus information, avoiding biases from manual screening and ensuring data accuracy. The results engine-based compilation and generation mechanism replaces manual operation, significantly improving compilation efficiency and reducing error rates. In addition, it supports the generation of adaptive results using custom evaluation parameters, adapting to complex scenario analysis. The solution is highly replicable and widely scalable, enabling its application in similar water bodies nationwide, providing reliable technical support for aquatic ecological planning and protection decisions. Attached Figure Description

[0018] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention and do not constitute a limitation thereof.

[0019] Figure 1 The diagram shows a flowchart of a method for compiling and integrating river, lake, and reservoir water ecological data according to an exemplary embodiment of the present invention.

[0020] Figure 2 The diagram illustrates the logical architecture of a method for compiling and integrating river, lake, and reservoir water ecological data, provided by an exemplary embodiment of the present invention.

[0021] Figure 3 This diagram illustrates the field standardization process of a method for compiling and integrating river, lake, and reservoir water ecological data, provided by an exemplary embodiment of the present invention.

[0022] Figure 4 The diagram shows a structural block diagram of a river, lake, and reservoir water ecological data compilation system provided by an exemplary embodiment of the present invention.

[0023] Figure 5 The diagram shows a schematic representation of the structure of a computer device for performing a method for compiling and organizing river, lake, and reservoir water ecological data, according to an exemplary embodiment of the present invention. Detailed Implementation

[0024] 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.

[0025] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0026] Figure 1 The diagram illustrates a flowchart of a method for compiling and integrating river, lake, and reservoir water ecological data according to an exemplary embodiment of the present invention. Figure 2 This diagram illustrates a logical architecture block diagram of a method for compiling and integrating river, lake, and reservoir water ecological data according to an exemplary embodiment of the present invention. The method includes: Step 101: Based on the Excel secondary programming automated integration tool, integrate the original water ecology record data into a standardized data table and complete the field standardization process.

[0027] In some embodiments, see Figure 3 Based on an Excel-based automated integration tool, this system integrates raw aquatic ecosystem records into standardized data tables. This includes: placing the standardized Excel template, the raw aquatic ecosystem Excel data, and the automated integration tool in the same folder; defining the mapping relationship between standardized table fields and related similar fields in the raw tables through a program, supporting one standardized table field corresponding to multiple similar fields in the raw tables; and executing the automated integration tool to automatically convert the raw data into standardized data tables, while also supporting text-based modification of mapping fields to ensure compatibility with newly added mapping objects.

[0028] In some embodiments, the raw aquatic ecosystem record data includes at least one of plankton data, benthic organism data, fish data, and water quality monitoring data, and the data format includes database format, Excel format, and text format.

[0029] In this embodiment, to address the issue of naming differences for similar indicators in the raw data submitted by different monitoring units, the mapping rules can automatically merge similar fields into standardized fields, reducing the workload of subsequent data verification. Furthermore, the output standardized data table is pre-adapted to the field recognition standards of the subsequent domestically produced data management engine, and its data structure can directly support the reserved association between species information and phylum, class, order, family, and genus classification information. Simultaneously, the text-modifiable mapping configuration mode provides convenience for grassroots monitoring personnel to complete localized data adaptation without requiring professional programming skills.

[0030] Step 102: Build a storage management framework using a domestically developed data management engine, and combine it with the EasyExcel data parsing engine to parse and read standardized data tables and achieve engine-based aggregated management.

[0031] In some embodiments, a storage management framework is built using a domestically developed data management engine, combined with the EasyExcel data parsing engine, to parse and read standardized data tables and achieve engine-based aggregated management. This includes: constructing an aquatic ecological data storage management framework using the domestically developed data management engine; calling the EasyExcel data parsing engine through the framework interface to read standardized data tables; integrating a high-order implementation paradigm for similar element retrieval in generic sets; constructing type-safe container operation boundaries based on Java type parameterization mechanisms to achieve retrieval and matching of aquatic species information and associated output of phylum, class, order, family, and genus classification information; providing data import, addition, conditional query, modification and maintenance, and result export services through the domestically developed data management engine, and performing data verification and checking during the data import process to mark field problems.

[0032] Furthermore, the data import service includes multi-user sub-index entry for single species information and batch import of multiple species information from Excel. The conditional query service includes queries based on combinations of species classification, phylum, class, order, family, genus, species, Latin name, and Chinese name. The modification and maintenance service includes adding and deleting species association map information and modifying and deleting species information. The result export service supports exporting query results in Excel report format.

[0033] In this embodiment, the high-order implementation paradigm of generic set retrieval, in addition to achieving species information matching, also avoids species classification errors caused by type mismatch in traditional retrieval through Java type parameterization mechanism. The multi-user, sub-index entry design in the data import stage implicitly considers adaptation to multi-departmental collaborative scenarios in water conservancy monitoring, enabling different monitoring groups to perform entry tasks separately and data to be aggregated in real time, solving the data redundancy and synchronization lag problems caused by traditional decentralized entry. Furthermore, the data verification and checking function goes beyond simply marking; its marking results can be back-linked to the front-end entry interface, providing precise error correction guidance for entry personnel, forming a closed loop of standardized and verified data quality control with the aforementioned Excel automation integration. In addition, the multi-dimensional design of combined condition queries is actually adapted to the needs of different business scenarios such as scientific research analysis, engineering evaluation, and regulatory decision-making. For example, scientific research scenarios require species queries accurate to the Latin name, while regulatory scenarios require summary data at the phylum, class, and order levels.

[0034] Step 103: Based on the standardized data collected and managed by the engine, build a water ecological data collection engine and integrate the built-in water ecological evaluation algorithm and evaluation process to complete the data preparation.

[0035] In some embodiments, data preparation is completed by integrating built-in aquatic ecological assessment algorithms and assessment processes, including: a built-in aquatic organism status assessment algorithm, which includes a fish retention index assessment algorithm, a phytoplankton Shannon-Wiener diversity index or Margalef richness index assessment algorithm, a zooplankton loss index assessment algorithm, a benthic BMWP bioindices or FBI bioindices assessment algorithm, and an aquatic vascular plant coverage assessment algorithm; a built-in eutrophication status assessment algorithm, which adopts an index method and includes steps such as converting water quality item concentration values ​​into assigned values ​​through linear interpolation, calculating the trophic status index EI based on the assigned values, and determining the trophic status classification according to the trophic status index; and supporting user-defined aquatic ecological types, station groups, and project groups to generate adaptive assessment results.

[0036] In this embodiment, the built-in evaluation algorithm fusion settings are used for comprehensive adaptation to the water ecological evaluation standards of the water conservancy industry. The selected algorithms, such as fish population index and various biodiversity / biological indices, all correspond to the main indicator systems of the current water ecological health evaluation. Furthermore, the algorithm fusion is not a simple superposition, but rather achieves data interoperability between algorithms through an engine. For example, water quality data required for eutrophication assessment can directly call related indicators from aquatic organism monitoring data, reducing redundant data processing steps. The user-defined function is used to adapt to the regionally differentiated evaluation needs of the water conservancy industry. Customizing the settings of water ecological types, monitoring station groups, and project groups allows for rapid adaptation to the evaluation needs of different scenarios such as southern river networks, northern lakes, and reservoirs, eliminating the need for repeated engine development for different scenarios and significantly improving the universality and implementation efficiency of the solution.

[0037] Step 104: Using the water ecological data compilation engine, generate a water ecological data compilation result table and a raw record result table according to preset query conditions, thereby realizing the compilation and output of water ecological data.

[0038] In some embodiments, the aquatic ecological data compilation engine generates aquatic ecological data compilation result tables and original record result tables based on preset query conditions. This includes: collecting and classifying aquatic ecological monitoring paper reports, extracting data elements and summarizing report text, establishing multiple types of compilation table templates, and building a template repository; providing filtering functions for compilation objects, compilation projects, and time conditions through the aquatic ecological data compilation engine; calling standardized data and evaluation analysis data based on the filtering conditions to generate compilation result files including phytoplankton monitoring data result tables, zooplankton monitoring data result tables, benthic animal monitoring data result tables, fish monitoring data result tables, and original data record result tables; and importing the compilation result files into the aquatic ecological data compilation system, which integrates a storage management framework built with a domestically developed data management engine and the aquatic ecological data compilation engine, to form a compilation result database, supporting preview, detailed viewing, download, and printing operations.

[0039] In this embodiment, the process of collecting and organizing paper reports on aquatic ecological monitoring and constructing a template repository addresses the industry pain point that historical aquatic ecological monitoring data is mostly stored in paper form and is difficult to reuse in information technology. By extracting data elements from paper and converting them into templates, seamless integration of old and new data is achieved, filling the gap in historical data in traditional digitization solutions. The generation of multiple types of compiled result tables is adaptable to the diverse business scenarios in the water conservancy industry. Detailed result tables for plankton, benthic animals, etc., correspond to different business needs such as aquatic organism-specific monitoring and watershed ecological health assessment. For example, environmental research scenarios require species monitoring result tables, while watershed management decision-making scenarios can quickly grasp the overall ecological status through the aggregated data of multiple types of result tables.

[0040] In this embodiment, the compiled results database can serve as a results module of the water ecological data resource center library, providing standardized results support for cross-departmental data sharing and long-term ecological change trend analysis. Meanwhile, convenient operations such as previewing, viewing, and downloading fully consider the actual usage habits of grassroots monitoring personnel, reduce the technical threshold for results application, and ensure that the value of engine-based compilation can be truly implemented in front-line water conservancy work.

[0041] In some embodiments, the method for compiling and integrating river, lake, and reservoir water ecological data further includes a batch import intelligent error correction step: during the batch data import process, data type errors and logical errors are marked in real time, and online editing functions are provided to correct erroneous data; the method for compiling and integrating river, lake, and reservoir water ecological data further includes a data integration and exchange step: using RESTful API or WebService data interface technology, defining standardized data interface standards, clarifying interface functions, input and output parameters, and data formats, to achieve water ecological data sharing and interaction; the method for compiling and integrating river, lake, and reservoir water ecological data further includes a data processing step: cleaning the collected raw data to remove noise data, outliers, and duplicate data; and converting and normalizing the cleaned data to make it conform to the data format and standards required by the engine.

[0042] Figure 4 This diagram illustrates a structural block diagram of a river, lake, and reservoir water ecological data compilation system provided by an exemplary embodiment of the present invention. This system is applied in the aforementioned river, lake, and reservoir water ecological data compilation method. The system includes: The data normalization and integration unit 401 is used to integrate the original water ecology record data into a standardized data table based on the Excel secondary programming automated integration tool, and complete the field normalization processing. The data parsing and engine-based aggregation unit 402 is used to build a storage management framework using a domestically produced data management engine, combined with the EasyExcel data parsing engine, to parse and read standardized data tables and achieve engine-based aggregation management. The water ecological assessment algorithm integration and data preparation unit 403 is used to build a water ecological data collection engine based on standardized data collected and managed by the engine, and to complete data preparation by integrating the built-in water ecological assessment algorithm and assessment process. The compilation result generation and output unit 404 is used to generate a water ecological data compilation result table and a raw record result table based on preset query conditions through the water ecological data compilation engine, so as to realize the compilation and output of water ecological data.

[0043] In some implementations, an automated integration tool based on Excel secondary programming is used to integrate raw aquatic ecosystem records into standardized data tables, including: Place the standardized Excel template, raw water ecology Excel data, and Excel automation integration tools in the same folder; By defining the mapping relationship between fields in the canonical table and related similar fields in the original table through the program, it is possible to support one field in the canonical table corresponding to multiple similar fields in the original table; The Excel automation integration tool automatically converts raw data into standardized data tables and supports modifying mapping fields via text to ensure compatibility with newly added mapping objects.

[0044] In some implementations, a storage management framework is built using a domestically developed data management engine, combined with the EasyExcel data parsing engine, to parse and read standardized data tables and achieve engine-based aggregated management, including: A water ecosystem data storage and management framework is built using a domestically developed data management engine, and the framework interface calls the EasyExcel data parsing engine to read standardized data tables. A high-order implementation paradigm for similar element retrieval in integrated generic sets is proposed. Based on the Java type parameterization mechanism, a type-safe container operation boundary is constructed to realize the retrieval and matching of aquatic species information and the associated output of phylum, class, order, family, and genus classification information. It provides data import, addition, conditional query, modification and maintenance, and result export services through a domestically developed data management engine, and performs data verification and checks during the data import process to mark field issues.

[0045] In some implementations, the data import service includes multi-user sub-index entry of single species information and batch import of multiple species information from Excel, and the conditional query service includes query based on a combination of conditions such as species classification, phylum, class, order, family, genus, species, Latin name, and Chinese name.

[0046] In some implementations, the modification and maintenance service includes adding and deleting species association map information, modifying and deleting species information, and the result export service supports exporting query results in the form of Excel reports.

[0047] In some implementations, data preparation is completed by integrating built-in water ecological assessment algorithms and assessment processes, including: The system includes built-in aquatic organism status assessment algorithms, which include fish retention index assessment algorithm, phytoplankton Shannon-Wiener diversity index or Margalef richness index assessment algorithm, zooplankton loss index assessment algorithm, benthic animal BMWP biological index or FBI biological index assessment algorithm, and aquatic vascular plant coverage assessment algorithm. The built-in water eutrophication status assessment algorithm adopts the index method, which includes the steps of converting water quality item concentration values ​​into assigned values ​​through linear interpolation, calculating the trophic status index EI based on the assigned values, and determining the trophic status classification according to the trophic status index. It supports users to define water ecosystem types, monitoring station groups, and project groups to generate adaptive evaluation results.

[0048] In some implementations, a water ecological data compilation engine generates a water ecological data compilation result table and a raw record result table based on preset query conditions, including: Collect and classify paper reports on water ecological monitoring, extract data elements and summarize report text, establish multiple types of compiled report templates, and build a template repository. The water ecology data compilation engine provides filtering functions for compilation objects, compilation projects, and time conditions; Based on the screening criteria, standard data and evaluation analysis data are retrieved to generate a compiled result file including phytoplankton monitoring data result table, zooplankton monitoring data result table, benthic animal monitoring data result table, fish monitoring data result table, and raw data record result table. The compiled output files are imported into the water ecological data compilation system, which integrates a storage management framework built with a domestically developed data management engine and a water ecological data compilation engine, to form a compiled output database that supports previewing, viewing details, downloading, and printing.

[0049] In some implementations, the method further includes a batch import intelligent error correction step: During the batch data import process, data type errors and logical errors are marked in real time, and online editing functions are provided to correct erroneous data. The method also includes a data integration and exchange step: By adopting RESTful API or WebService data interface technology, we define standardized data interface standards, clarify interface functions, input and output parameters and data formats, and realize the sharing and interaction of water ecological data. The method also includes data processing steps: The collected raw data is cleaned to remove noisy data, outliers, and duplicate data; The cleaned data is then transformed and normalized to conform to the data format and standards required by the engine.

[0050] In some implementations, the raw aquatic ecosystem record data includes at least one of plankton data, benthic organism data, fish data, and water quality monitoring data, and the data format includes database format, Excel format, and text format.

[0051] It should be noted that the river, lake and reservoir water ecological data compilation system provided in the above embodiments is only an example of the division of the above functional modules. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the equipment can be divided into different functional modules to complete all or part of the functions described above.

[0052] Figure 5 This diagram illustrates the structure of a computer device for performing a method for compiling and integrating river, lake, and reservoir water ecological data, according to an exemplary embodiment of the present invention. The computer device includes: The processor 501 includes one or more processing cores. The processor 501 executes various functional applications and data processing by running software programs and modules.

[0053] The receiver 502 and transmitter 503 can be implemented as a communication component, which can be a communication chip. Optionally, this communication component can include signal transmission functionality. That is, the transmitter 503 can be used to transmit control signals to the image acquisition device and the scanning device, and the receiver 502 can be used to receive corresponding feedback commands.

[0054] The memory 504 is connected to the processor 501 via the bus 505.

[0055] The memory 504 can be used to store at least one instruction, and the processor 501 can execute the at least one instruction to implement the various steps in the above method embodiments.

[0056] This invention also provides a computer-readable storage medium storing at least one instruction, at least one program, code set, or instruction set, which can be loaded and executed by a processor to implement the above-described method for compiling and integrating river, lake, and reservoir water ecological data.

[0057] It is understood that the specific examples in this document are only intended to help those skilled in the art better understand this disclosure, and are not intended to limit the scope of the invention.

[0058] It is understood that in the various embodiments of this specification, the sequence number of each process does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of this disclosure.

[0059] It is understood that the various implementation methods described in this specification can be implemented individually or in combination, and this disclosure does not limit them.

[0060] Unless otherwise stated, all technical and scientific terms used in this disclosure have the same meaning as commonly understood by one of ordinary skill in the art. The terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the scope of this specification. The term "and / or" as used in this specification includes any and all combinations of one or more of the associated listed items. The singular forms "a," "the," and "the" as used in this disclosure and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise.

[0061] It is understood that the processor disclosed herein can be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method implementation can be completed by integrated logic circuits in the processor's hardware or by instructions in software form. The processor can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in this disclosure. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed herein can be directly implemented by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory; the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method.

[0062] It is understood that the memory in this disclosure can be volatile memory or non-volatile memory, or may include both. Non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory can be random access memory (RAM). It should be noted that the memory in the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0063] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this specification.

[0064] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems and units described above can be referred to the corresponding processes in the aforementioned method implementations, and will not be repeated here.

[0065] In the several embodiments provided in this specification, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the embodiments of the systems described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between systems or units may be electrical, mechanical, or other forms.

[0066] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0067] In addition, the functional units in the various embodiments of this specification can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0068] The above description is merely a specific embodiment of this specification, but the scope of protection of this invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this specification should be included within the scope of protection of this specification. Therefore, the scope of protection of this invention should be determined by the scope of the claims.

Claims

1. A method for compiling and integrating ecological data of rivers, lakes, and reservoirs, characterized in that, The method includes: Based on an Excel-based automated integration tool, the original water ecology record data is integrated into a standardized data table, and the fields are standardized. A storage management framework is built using a domestically developed data management engine, combined with the EasyExcel data parsing engine, to parse and read the standardized data tables and achieve engine-based aggregated management. Based on the standardized data collected and managed by the engine, a water ecological data compilation engine is built, and the built-in water ecological evaluation algorithm and evaluation process are integrated to complete the data preparation. The water ecological data compilation engine generates a water ecological data compilation result table and a raw record result table based on preset query conditions, thereby realizing the compilation and output of water ecological data.

2. The method for compiling and integrating river, lake, and reservoir water ecological data according to claim 1, characterized in that, The Excel-based automated integration tool integrates raw aquatic ecosystem records into standardized data tables, including: Place the standardized Excel template, the original Excel data on aquatic ecology, and the Excel automated integration tool in the same folder; By defining the mapping relationship between fields in the canonical table and related similar fields in the original table through the program, it is possible to support one field in the canonical table corresponding to multiple similar fields in the original table; The Excel automation integration tool automatically converts raw data into a standardized data table and supports modifying mapping fields via text to ensure compatibility with newly added mapping objects.

3. The method for compiling and integrating river, lake, and reservoir water ecological data according to claim 1, characterized in that, The storage management framework is built using a domestically developed data management engine, combined with the EasyExcel data parsing engine, to parse and read the standardized data tables and achieve engine-based aggregated management, including: A water ecosystem data storage and management framework is built using a domestically developed data management engine, and the framework interface calls the EasyExcel data parsing engine to read standardized data tables. A high-order implementation paradigm for similar element retrieval in integrated generic sets is proposed. Based on the Java type parameterization mechanism, a type-safe container operation boundary is constructed to realize the retrieval and matching of aquatic species information and the associated output of phylum, class, order, family, and genus classification information. The domestically developed data management engine provides services for data import, addition, conditional query, modification and maintenance, and result export. During the data import process, it performs data verification and checks, and marks field problems.

4. The method for compiling and integrating river, lake, and reservoir water ecological data according to claim 3, characterized in that, The data import service includes multi-user sub-index entry of single species information and batch import of multiple species information from Excel. The conditional query service includes query based on a combination of conditions such as species classification, phylum, class, order, family, genus, species, Latin name, and Chinese name.

5. The method for compiling and integrating river, lake, and reservoir water ecological data according to claim 3, characterized in that, The modification and maintenance service includes adding and deleting species association map information, modifying and deleting species information, and the result export service supports exporting query results in the form of Excel reports.

6. The method for compiling and integrating river, lake, and reservoir water ecological data according to claim 1, characterized in that, The integrated water ecological assessment algorithm and assessment process complete the data preparation, including: The system includes a built-in aquatic organism status evaluation algorithm, which includes a fish retention index evaluation algorithm, a phytoplankton Shannon-Wiener diversity index or Margalef richness index evaluation algorithm, a zooplankton loss index evaluation algorithm, a benthic animal BMWP biological index or FBI biological index evaluation algorithm, and an aquatic vascular plant coverage evaluation algorithm. The built-in water eutrophication status assessment algorithm adopts the index method and includes the following steps: converting water quality item concentration values ​​into assigned values ​​through linear interpolation, calculating the eutrophication status index EI based on the assigned values, and determining the eutrophication status classification according to the eutrophication status index. It supports users to define water ecosystem types, monitoring station groups, and project groups to generate adaptive evaluation results.

7. The method for compiling and integrating river, lake, and reservoir water ecological data according to claim 1, characterized in that, The process of generating a water ecological data compilation result table and a raw record result table through the water ecological data compilation engine according to preset query conditions includes: Collect and classify paper reports on water ecological monitoring, extract data elements and summarize report text, establish multiple types of compiled table templates, and build a template repository. The water ecological data compilation engine provides filtering functions for compilation objects, compilation projects, and time conditions; Based on the screening criteria, standard data and evaluation analysis data are retrieved to generate a compiled result file including phytoplankton monitoring data result table, zooplankton monitoring data result table, benthic animal monitoring data result table, fish monitoring data result table, and raw data record result table. The compiled result files are imported into the water ecological data compilation system, which integrates the storage management framework built by the domestically produced data management engine and the water ecological data compilation engine, to form a compiled result database, supporting preview, detailed viewing, download, and printing operations.

8. The method for compiling and integrating river, lake, and reservoir water ecological data according to claim 1, characterized in that, The method also includes a batch import intelligent error correction step: During the batch data import process, data type errors and logical errors are marked in real time, and online editing functions are provided to correct erroneous data. The method also includes a data integration and exchange step: By adopting RESTful API or WebService data interface technology, we define standardized data interface standards, clarify interface functions, input and output parameters and data formats, and realize the sharing and interaction of water ecological data. The method also includes a data processing step: The collected raw data is cleaned to remove noisy data, outliers, and duplicate data; The cleaned data is then transformed and normalized to conform to the data format and standards required by the engine.

9. The method for compiling and integrating river, lake, and reservoir water ecological data according to claim 1, characterized in that, The original aquatic ecosystem data includes at least one of plankton data, benthic organism data, fish data, and water quality monitoring data, and the data format includes database format, Excel format, and text format.

10. A system for compiling and integrating ecological data of rivers, lakes, and reservoirs, characterized in that, The system is applied in the method for compiling and integrating river, lake, and reservoir water ecological data as described in any one of claims 1 to 9, and the system includes: The data standardization and integration unit is used to integrate raw water ecology record data into standardized data tables based on Excel secondary programming automated integration tools, and complete field standardization processing. The data parsing and engine-based aggregation unit is used to build a storage management framework using a domestically produced data management engine, and combined with the EasyExcel data parsing engine, to parse and read the standardized data table and realize engine-based aggregation management. The water ecology assessment algorithm integration and data preparation unit is used to build a water ecology data compilation engine based on the standardized data collected and managed by the engine, and to complete the data preparation by integrating the built-in water ecology assessment algorithm and assessment process. The compilation result generation and output unit is used to generate a water ecological data compilation result table and a raw record result table according to preset query conditions through the water ecological data compilation engine, so as to realize the compilation and output of water ecological data.

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