Inland arid region oasis water resource optimal configuration system based on big data analysis

Abstract

The invention relates to the field of big data analysis, in particular to an inland arid region oasis water resource optimal allocation system based on big data analysis, which comprises a water consumption accounting module, a water resource allocation module and a water resource allocation model construction module. The water consumption accounting module calculates and verifies regional water consumption by using various data sources; the water resource configuration module analyzes water resource changes from the two dimensions of ecological space and time, predicts ecological water consumption demands and evaluates the water resource carrying capacity; the water resource configuration model construction module constructs a series of water resource configuration models based on the bearing capacity, and integrates an intelligent algorithm and ecological constraint conditions. The system can accurately evaluate the regional water resource consumption condition, formulate a reasonable water resource allocation scheme, avoid water resource waste and excessive development, and maintain the stability and balance of an ecological system at the same time.

Description

Technical Field

[0001] The present invention relates to the field of big data analysis, and in particular to an inland arid oasis water resources optimization configuration system based on big data analysis. Background Art

[0002] Inland arid areas, as a unique natural environment type on the earth, have significant climatic and geographical characteristics. These areas usually have scarce precipitation, high evaporation, and extremely scarce water resources. At the same time, the topography is complex and diverse, including mountains, basins, deserts, oases and other landforms. As a gathering place for precious water resources in arid areas, oases are an important support for local agriculture, economy and ecology. However, the distribution of oases is often restricted by multiple factors such as topography, climate, and hydrology, showing scattered and discontinuous characteristics.

[0003] In inland arid areas, water shortage is a key factor restricting local economic and social development. Due to limited precipitation and scarce surface water resources, groundwater resources have become the main source of local water resources. However, the exploitation and utilization of groundwater resources are often restricted by geological conditions, hydrological environment and other factors. At the same time, due to the continuous increase in human activities, water pollution and over-exploitation are becoming increasingly serious, leading to an intensification of the contradiction between water supply and demand. In addition, the uneven distribution of water resources in time and space has also exacerbated the problem of water shortage.

[0004] Oasis areas in inland arid areas are an important support for local agriculture, economy and ecology. With the growth of population and economic development, the demand for water resources in oasis areas is increasing. Agricultural irrigation, industrial production, residents' lives and other aspects all require a large amount of water resources. However, due to the shortage and uneven distribution of water resources, the contradiction between water supply and demand in oasis areas has become increasingly prominent. Therefore, how to reasonably allocate and utilize water resources to meet social and economic needs has become an important issue facing local governments and relevant departments. The ecological environment in inland arid areas is fragile and easily affected and damaged by human activities. Excessive exploitation and utilization of water resources often lead to ecological problems such as groundwater level decline, water quality deterioration, and vegetation destruction. These problems will not only affect agricultural production and economic development in oasis areas, but also have long-term adverse effects on the local ecological environment. Therefore, how to protect the ecological environment and achieve sustainable use of water resources while ensuring social and economic needs has become an important issue that local governments and relevant departments need to solve. Therefore, this plan proposes an inland arid oasis water resource optimization allocation system based on big data analysis. Summary of the invention

[0005] To solve the above problems, the present invention provides an inland arid oasis water resource optimization configuration system based on big data analysis, which is used to improve the efficiency of water resource utilization and promote the stability and balance of the ecosystem.

[0006] In order to achieve the above-mentioned purpose, the technical scheme of the present invention is as follows: an inland arid oasis water resource optimization allocation system based on big data analysis includes a water consumption accounting module, which is used to use the irrigation area obtained from the land survey, the main bulk agricultural product output information recorded in the statistical yearbook, and the water and electricity fee data of the field survey to calculate and verify the regional water consumption and generate water consumption data;

[0007] Water resource allocation module: The water resource allocation module is used to use water consumption data and analyze the evolution relationship between water resource changes and ecological sensitive targets based on the two dimensions of ecological space and time, predict the ecological water demand of artificial oases and natural oases, and determine the consumption pattern of artificial oases and natural oases in combination with the water resource formation and consumption law of inland rivers and the principle of water balance in river basins, and obtain the water resource carrying capacity of artificial oases and natural oases;

[0008] Water resource allocation model construction module. The water resource allocation model construction module is used to establish a medium- and long-term water resource forecasting model, a cross-year groundwater resource optimization allocation model, a water resource optimization allocation model based on the joint allocation of plain reservoirs and mountain reservoirs, and a reservoir optimization scheduling model under ecological constraints based on the water resource carrying capacity of artificial oases and natural oases, combined with the elasticity of intelligent algorithms, cross-year groundwater, and joint allocation of plain reservoirs and mountain reservoirs.

[0009] The technical principles of the above scheme are as follows:

[0010] 1. Water consumption calculation module

[0011] Data source: This module mainly uses the irrigation area obtained from the land survey, the output information of major agricultural products recorded in the statistical yearbook, and the water and electricity fee data from the field survey.

[0012] Calculation method: By collecting and analyzing this data, the module can calculate the regional water consumption and generate water consumption data. This process involves analyzing the correlation between irrigation area, agricultural product output and water and electricity charges, so as to accurately assess the actual consumption of regional water resources.

[0013] Verification mechanism: In order to ensure the accuracy of the accounting results, the module will also use field survey data for verification to ensure the reliability and validity of water consumption data.

[0014] 2. Water resources configuration module

[0015] Analytical Dimensions: This module analyzes the relationship between water resource changes and the evolution of ecologically sensitive targets from the perspectives of ecological space and time. This helps to understand the dynamic changes of water resources in different ecosystems and time scales.

[0016] Demand forecasting: Based on the analysis of water resource changes, the module can predict the ecological water demand of artificial and natural oases. This helps to ensure the rationality and scientific nature of water resource allocation.

[0017] Carrying capacity assessment: Combining the water resource formation and consumption patterns of inland rivers with the principle of water balance in river basins, the module can determine the water resource carrying capacity of artificial and natural oases. This helps avoid overexploitation of water resources and maintain the stability and balance of the ecosystem.

[0018] 3. Water resources allocation model construction module

[0019] Model basis: This module builds a series of water resource allocation models based on the water resource carrying capacity of artificial oases and natural oases. These models include medium- and long-term water resource prediction models, cross-year groundwater resource optimization allocation models, water resource optimization allocation models based on the joint allocation of plain reservoirs and mountain reservoirs, and reservoir optimization scheduling models under ecological constraints.

[0020] Intelligent algorithm application: Intelligent algorithms, such as machine learning and optimization algorithms, are integrated into the module to improve the prediction accuracy and configuration efficiency of the model. These algorithms can automatically adjust model parameters based on historical data and real-time information to achieve dynamic optimization of water resources.

[0021] Ecological constraints: When constructing the model, the module fully considers ecological constraints to ensure that water resource allocation does not harm the health and stability of the ecosystem. This helps to achieve sustainable use of water resources and coordinated development of the ecological environment.

[0022] The above scheme has the following beneficial effects:

[0023] 1. This scheme can accurately evaluate the actual consumption of regional water resources through the water consumption accounting module, and provide data support for the efficient use of water resources. The water resource allocation module can formulate a reasonable water resource allocation plan based on the ecological sensitivity goals and carrying capacity assessment results to avoid waste and over-exploitation of water resources.

[0024] 2. This plan systematically analyzes the relationship between water resource changes and the evolution of ecological sensitive targets from the two dimensions of ecological space and time, which helps to maintain the stability and balance of the ecosystem. By predicting the ecological water demand of artificial oases and natural oases and formulating corresponding configuration plans, the rationality and scientificity of water resource configuration can be ensured, and negative impacts on the ecosystem can be avoided to a certain extent.

[0025] 3. In this solution, the medium- and long-term water resources prediction model and the cross-year groundwater resources optimization allocation model constructed by the system can provide a scientific basis for the sustainable use of regional water resources. Through the application of intelligent algorithms, the system can automatically adjust the model parameters to achieve dynamic optimization of water resources and adapt to changes in water resource demand at different time and space scales. Optimal reservoir scheduling under ecological constraints can ensure the rational use of water resources and the coordinated development of the ecological environment, providing strong support for the sustainable development of the region.

[0026] 4. The water consumption data and water resource allocation plan provided by the system can provide a scientific basis for the decision-making of the government and relevant departments. Through real-time monitoring and analysis of water resource data, the system can timely warn of water shortages and ecological risks, and provide strong support for the government to formulate emergency plans and take corresponding measures.

[0027] Furthermore, it also includes a water quality monitoring and assessment module, which is used to monitor the water quality conditions in the oasis area in real time, assess whether the water quality meets the needs of agricultural irrigation, domestic water and ecological protection, and adjust the water resource allocation strategy according to the water quality assessment results.

[0028] Beneficial effects: This module can monitor the water quality of the oasis area in real time to ensure the timeliness and accuracy of the data. By evaluating whether the water quality meets the needs of agricultural irrigation, domestic water and ecological protection, water quality problems can be discovered in time and measures can be taken. According to the water quality assessment results, the system can dynamically adjust the water resource allocation strategy to ensure the rational use of water resources and the coordinated development of the ecological environment. This helps to avoid irreversible damage to the ecosystem caused by water pollution to a certain extent.

[0029] Furthermore, the water consumption accounting module includes a data verification and correction submodule, which is used to verify the water consumption data calculated through irrigation area, agricultural product output information and water and electricity fee data, and correct errors by comparing with satellite remote sensing data and meteorological data.

[0030] Beneficial effects: By comparing satellite remote sensing data and meteorological data, this submodule can verify and correct the water consumption data calculated from the irrigation area, agricultural product output information, and water and electricity fee information. This helps to improve the accuracy and reliability of the data and provide a scientific basis for water resource allocation. The data verification and correction submodule can promptly detect and correct errors in the data to ensure the accuracy and effectiveness of the water resource allocation plan. This helps to avoid decision-making errors caused by inaccurate data.

[0031] Furthermore, the water resource allocation module includes a climate change impact assessment submodule, which is used to analyze the impact of climate change on the balance of water resource supply and demand and dynamically adjust the water resource allocation plan.

[0032] Beneficial effects: This submodule can analyze the impact of climate change on the balance of water supply and demand, and dynamically adjust the water resource allocation plan based on the analysis results. This helps the system adapt to the uncertainty brought about by climate change and ensure the sustainable use of water resources. By assessing the impact of climate change, the system can formulate response measures in advance to reduce the negative impact of climate change on water resource allocation. This helps maintain the stability and balance of the ecosystem and ensure the sustainable development of the regional economy.

[0033] Furthermore, the water resources allocation model construction module includes a socio-economic factors examination submodule, which is used to consider the impact of socio-economic factors such as population growth, economic development and industrial structure adjustment on water resources demand, and incorporate socio-economic factors into the construction of the water resources allocation model.

[0034] Beneficial effects: This submodule incorporates socioeconomic factors such as population growth, economic development, and industrial structure adjustment into the construction of the water resource allocation model, making the water resource allocation plan more comprehensive and reasonable. By considering the impact of socioeconomic factors, the system can more accurately predict water resource demand and formulate more efficient water resource allocation plans. This helps to meet the water demand for regional economic and social development and promote the sustainable development of the regional economy.

[0035] Furthermore, it also includes a user interaction interface module, which is used to provide an operation interface, and the operation interface can input data, view water resource configuration results and adjust configuration parameters.

[0036] Beneficial effects: The module provides a friendly operation interface, allowing users to easily input data, view water resource configuration results and adjust configuration parameters. This helps users better understand and use the system and improves the usability of the system. The user interaction interface module can provide real-time feedback on the results and status of water resource configuration, helping users to understand the system's operating conditions and configuration effects in a timely manner. This helps users adjust configuration strategies based on feedback results and improve the efficiency and accuracy of water resource configuration.

[0037] Furthermore, it also includes an intelligent early warning and emergency response module, which is used to predict and identify potential water resource shortages and water pollution risks based on real-time monitored water resource data, water quality data and meteorological data, automatically generate early warning information, and trigger corresponding emergency response plans.

[0038] Beneficial effects: The module can predict and identify potential water shortage and water pollution risks based on real-time monitored water resources data, water quality data and meteorological data. With early warning, users can take timely measures to avoid risks. The intelligent early warning and emergency response module can automatically generate early warning information and trigger corresponding emergency response plans. This helps users respond quickly to risk events and reduce losses and impacts.

[0039] Furthermore, the intelligent early warning and emergency response module includes a risk level assessment submodule, which is used to automatically assess the risk level of potential water shortages and water pollution according to the severity of the early warning information, and trigger corresponding emergency response plans according to different risk levels.

[0040] Beneficial effects: This submodule can automatically assess the level of potential water shortage and water pollution risks according to the severity of the early warning information. This helps users to understand the size and urgency of the risk more scientifically and formulate more reasonable response measures. According to the different risk levels, the system can trigger the corresponding emergency response plan. This helps users to take different levels of response measures according to the actual situation of the risk and improve the pertinence and effectiveness of the emergency response.

[0041] Furthermore, the climate change impact assessment submodule includes an extreme climate event prediction submodule, which is used to use big data analysis technology to predict extreme climate events and formulate response measures in advance.

[0042] Beneficial effects: This submodule can use big data analysis technology to predict extreme climate events. By predicting in advance, users can formulate countermeasures in advance to reduce the negative impact of extreme climate events on water resource allocation. By predicting extreme climate events and formulating corresponding countermeasures, the system can enhance its ability to resist extreme climate events and improve the resilience and reliability of water resource allocation.

[0043] Furthermore, the evolutionary relationship between water resource changes and ecologically sensitive targets is analyzed based on the two dimensions of ecological space and time. The ecological space dimension includes the relationship between water resource distribution and ecosystem, identification of ecologically sensitive areas, and the impact of water resource changes on ecosystems; the time dimension includes analysis of water resource change trends, the temporal evolution of ecologically sensitive targets, and the temporal matching of water resource allocation with ecological needs.

[0044] Beneficial effects: Based on the water resources allocation module, the relationship between water resources changes and the evolution of ecological sensitive targets is analyzed from the two dimensions of ecological space and time, which can fully reveal the interaction between water resources and ecosystems. This helps users to have a deeper understanding of the dynamic changes of water resources and the response mechanism of ecosystems. Based on the analysis results of ecological space and time dimensions, users can formulate more scientific water resources allocation plans. This helps to meet the water demand of the ecosystem, maintain the stability and balance of the ecosystem, and promote the sustainable development of the regional economy.

[0045] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 This is a structural diagram of an embodiment of an inland arid oasis water resources optimization configuration system based on big data analysis of the present invention;

[0047] Figure 2 It is a flow chart of an embodiment of the inland arid oasis water resources optimization configuration system based on big data analysis of the present invention; DETAILED DESCRIPTION

[0048] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0049] In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", and "third" are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance.

[0050] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0051] The following is further described in detail through specific implementation methods:

[0052] As attached Figure 1 and attached Figure 2 As shown: The water resource optimization allocation system for oases in inland arid areas based on big data analysis includes a water consumption accounting module, which is used to calculate and verify regional water consumption and generate water consumption data by using the irrigation area obtained from the land survey, the main bulk agricultural product output information recorded in the statistical yearbook, and the water and electricity fee data from the field survey. The water consumption accounting module includes a data verification and correction submodule, which is used to verify the water consumption data calculated by the irrigation area, agricultural product output information and water and electricity fee data, and correct the error by comparing with satellite remote sensing data and meteorological data.

[0053] Water resource allocation module: The water resource allocation module is used to use water consumption data and analyze the evolution relationship between water resource changes and ecological sensitive targets based on the two dimensions of ecological space and time, predict the ecological water demand of artificial oases and natural oases, and combine the water resource formation and consumption laws of inland rivers with the principle of water balance in river basins to determine the consumption pattern of artificial oases and natural oases, and obtain the water resource carrying capacity of artificial oases and natural oases. The water resource allocation module includes a climate change impact assessment submodule, which is used to analyze the impact of climate change on the balance of water resource supply and demand and dynamically adjust the water resource allocation plan. The climate change impact assessment submodule includes an extreme climate event prediction submodule, which is used to use big data analysis technology to predict extreme climate events and formulate response measures in advance.

[0054] The water resource allocation model construction module is used to establish a medium- and long-term water resource forecasting model, a cross-year groundwater resource optimization allocation model, a water resource optimization allocation model based on the joint allocation of plain reservoirs and mountain reservoirs, and a reservoir optimization scheduling model under ecological constraints based on the water resource carrying capacity of artificial oases and natural oases, combined with the elasticity of intelligent algorithms, cross-year groundwater, joint allocation of plain reservoirs and mountain reservoirs, and reservoir optimization scheduling under ecological constraints. The water resource allocation model construction module includes a submodule for examining socioeconomic factors. The submodule for examining socioeconomic factors is used to consider the impact of socioeconomic factors such as population growth, economic development, and industrial structure adjustment on water resource demand, and incorporate socioeconomic factors into the construction of the water resource allocation model.

[0055] Water quality monitoring and assessment module: The water quality monitoring and assessment module is used to monitor the water quality in the oasis area in real time, assess whether the water quality meets the needs of agricultural irrigation, domestic water use and ecological protection, and adjust the water resource allocation strategy based on the water quality assessment results.

[0056] The user interaction interface module is used to provide an operation interface, which can input data, view water resource configuration results and adjust configuration parameters.

[0057] Intelligent early warning and emergency response module, which is used to predict and identify potential water shortage and water pollution risks based on real-time monitored water resources data, water quality data and meteorological data, automatically generate early warning information, and trigger corresponding emergency response plans. The intelligent early warning and emergency response module includes a risk level assessment submodule, which is used to automatically assess the level of potential water shortage and water pollution risks based on the severity of the early warning information, and trigger corresponding emergency response plans based on different risk levels.

[0058] The evolutionary relationship between water resource changes and ecologically sensitive targets is analyzed based on the two dimensions of ecological space and time. The ecological space dimension includes the relationship between water resource distribution and ecosystem, identification of ecologically sensitive areas, and the impact of water resource changes on ecosystems; the time dimension includes analysis of water resource change trends, the temporal evolution of ecologically sensitive targets, and the temporal matching of water resource allocation and ecological needs.

[0059] The ecological space dimension includes the relationship between water resource distribution and ecosystem, identification of ecologically sensitive areas, and the impact of water resource changes on ecosystems. The relationship between water resource distribution and ecosystems is: analyzing the spatial distribution characteristics of water resources in the oasis area, including the distribution and storage of surface water and groundwater; exploring the relationship between water resource distribution and ecosystems, such as how water resources support plant growth, animal habitats, and the balance of the entire ecosystem in the oasis.

[0060] Identification of ecologically sensitive areas includes: identifying ecologically sensitive areas within oases, which are usually particularly sensitive to changes in water resources, such as wetlands and habitats of endangered species; analyzing the ecological needs and water resource needs of these ecologically sensitive areas, as well as their response mechanisms to changes in water resources.

[0061] The impact of water resource changes on ecosystems is to study the impact of water resource changes (such as increase or decrease in water volume, changes in water quality) on ecosystem structure and function; and to assess the potential impact of water resource changes on biodiversity, ecosystem health and stability.

[0062] The time dimension includes the analysis of water resource change trends, the temporal evolution of ecologically sensitive targets, and the temporal matching of water resource allocation with ecological needs. The analysis of water resource change trends is to collect and analyze historical water resource data, including precipitation, evaporation, river runoff, etc., to understand the temporal trend of water resources; and to predict the future trend of water resource changes, including long-term trends and seasonal changes.

[0063] The temporal evolution of ecologically sensitive targets is as follows: tracking and recording the temporal evolution of ecologically sensitive targets (such as specific species and ecological communities); analyzing the correlation and causal relationship between the evolution of these ecologically sensitive targets and changes in water resources.

[0064] The temporal matching of water resource allocation and ecological needs is as follows: according to the temporal evolution of ecologically sensitive targets, water resource allocation strategies are adjusted to meet the different temporal needs of the ecosystem; water resource allocation is ensured to be compatible with the seasonal and cyclical changes of the ecosystem to reduce the negative impact on the ecosystem.

[0065] The specific implementation process is as follows:

[0066] 1. System initialization and data preparation

[0067] System initialization:

[0068] Install and configure the software and hardware environment required by the system.

[0069] Set system parameters, such as time step, model parameters, etc.

[0070] Data preparation:

[0071] Land survey data: collect land survey data such as irrigation area, soil type, topography, etc.

[0072] Statistical Yearbook Data: Obtain production information of major agricultural products, demographic data, economic development indicators, etc.

[0073] Field research data: Collect field research data such as water and electricity charges, irrigation methods, and crop planting structure.

[0074] Satellite remote sensing data: Obtain satellite remote sensing data such as land cover, vegetation index, soil moisture, etc.

[0075] Meteorological data: collect meteorological data such as precipitation, evaporation, temperature, wind speed, etc.

[0076] Water quality monitoring data: Collect water quality monitoring data in the oasis area, including pH value, dissolved oxygen, ammonia nitrogen and other indicators.

[0077] 2. Water consumption calculation module

[0078] Data input:

[0079] The irrigation area obtained from the land survey, the output information of major agricultural products recorded in the statistical yearbook, and the water and electricity fee data from the field survey are input into the system.

[0080] Water consumption calculation:

[0081] The regional water consumption is estimated using crop water requirement models, irrigation efficiency coefficients, etc.

[0082] Data verification and correction:

[0083] The data verification and correction submodule is used to compare the estimated water consumption data with satellite remote sensing data and meteorological data to correct errors.

[0084] Verification data include irrigation water volume, crop transpiration, soil evaporation, etc.

[0085] 3. Water resources allocation module

[0086] Analysis of ecological space and time dimensions:

[0087] Analyze the relationship between water resources distribution and ecosystems, identify ecologically sensitive areas, and assess the impact of water resources changes on ecosystems.

[0088] Collect and analyze historical water resources data and predict future trends in water resources.

[0089] Track and record the temporal evolution of ecologically sensitive targets, and analyze their correlation and causal relationship with water resource changes.

[0090] Calculation of water resources carrying capacity:

[0091] The water resource carrying capacity of artificial and natural oases is determined based on the water resource formation and consumption patterns of inland rivers and the principle of water balance in river basins.

[0092] Water resources allocation plan formulation:

[0093] Utilize the climate change impact assessment submodule to analyze the impact of climate change on the balance of water supply and demand, and dynamically adjust the water resource allocation plan.

[0094] Utilize the extreme climate event prediction submodule to predict extreme climate events and formulate response measures in advance.

[0095] Model building and optimization:

[0096] Based on the water resources carrying capacity, combined with the elasticity of intelligent algorithms, cross-year groundwater, joint allocation of plain reservoirs and mountain reservoirs, and optimal scheduling of reservoirs under ecological constraints, we will establish a medium- and long-term water resources forecasting model and a cross-year groundwater resources optimization allocation model.

[0097] The submodule of socio-economic factors is considered, and the impact of socio-economic factors such as population growth, economic development and industrial structure adjustment on water resource demand is incorporated into the model construction.

[0098] 4. Water quality monitoring and assessment module

[0099] Real-time monitoring:

[0100] Use water quality monitoring equipment to monitor the water quality in the oasis area in real time.

[0101] Water Quality Assessment:

[0102] Based on water quality monitoring data, assess whether the water quality meets the needs of agricultural irrigation, domestic water and ecological protection.

[0103] Strategy Adjustment:

[0104] Adjust water resource allocation strategies based on water quality assessment results to ensure water quality safety.

[0105] 5. User interface module

[0106] Data input:

[0107] Provide an operation interface that allows users to input relevant data, such as irrigation area, agricultural product output, etc.

[0108] Results:

[0109] Display water resource allocation results, including water consumption, water resource carrying capacity, allocation plan, etc.

[0110] Parameter adjustment:

[0111] Allows users to adjust configuration parameters such as model parameters, time step, etc.

[0112] 6. Intelligent early warning and emergency response module

[0113] Risk prediction and identification:

[0114] Based on real-time monitoring of water resources data, water quality data and meteorological data, predict and identify potential risks of water shortage and water pollution.

[0115] Warning information generation:

[0116] Automatically generate warning information, including risk type, risk level, warning time, etc.

[0117] Emergency response plan trigger:

[0118] According to the results of the risk level assessment submodule, the corresponding emergency response plan is triggered.

[0119] The plan includes emergency measures, responsible persons, implementation time, etc.

[0120] 7. Data update and iterative optimization

[0121] Data update:

[0122] Regularly collect new land survey data, statistical yearbook data, field research data, etc., and update the system database.

[0123] Model iterative optimization:

[0124] According to the actual application results, the model is iteratively optimized to improve prediction accuracy and configuration efficiency.

[0125] System maintenance and upgrade:

[0126] Perform regular maintenance and upgrades on the system to ensure stable operation and continuous updates of the system.

[0127] Obviously, the above embodiments are merely examples for the purpose of clear explanation, and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived therefrom are still within the scope of protection of the present invention.

Claims

1. The inland arid oasis water resources optimization allocation system based on big data analysis is characterized by: It includes a water consumption accounting module, which is used to calculate and verify regional water consumption and generate water consumption data by using the irrigation area obtained from the land survey, the output information of major agricultural products recorded in the statistical yearbook, and the water and electricity fee data from the field survey; Water resource allocation module: The water resource allocation module is used to use water consumption data and analyze the evolution relationship between water resource changes and ecological sensitive targets based on the two dimensions of ecological space and time, predict the ecological water demand of artificial oases and natural oases, and determine the consumption pattern of artificial oases and natural oases in combination with the water resource formation and consumption law of inland rivers and the principle of water balance in river basins, and obtain the water resource carrying capacity of artificial oases and natural oases; Water resources allocation model construction module. The water resources allocation model construction module is used to establish a medium- and long-term water resources forecasting model, a cross-year groundwater resources optimization allocation model, a water resources optimization allocation model based on the joint allocation of plain reservoirs and mountain reservoirs, and a reservoir optimization scheduling model under ecological constraints based on the water resources carrying capacity of artificial oases and natural oases, combined with the elasticity of intelligent algorithms, cross-year groundwater, and joint allocation of plain reservoirs and mountain reservoirs.

2. The inland arid oasis water resources optimization configuration system based on big data analysis according to claim 1 is characterized in that: It also includes a water quality monitoring and assessment module, which is used to monitor the water quality in the oasis area in real time, assess whether the water quality meets the needs of agricultural irrigation, domestic water use and ecological protection, and adjust the water resource allocation strategy based on the water quality assessment results.

3. The inland arid oasis water resources optimization configuration system based on big data analysis according to claim 2 is characterized in that: The water consumption accounting module includes a data verification and correction submodule, which is used to verify the water consumption data calculated based on the irrigation area, agricultural product output information and water and electricity fee data, and correct the error by comparing with satellite remote sensing data and meteorological data.

4. The inland arid oasis water resources optimization configuration system based on big data analysis according to claim 3 is characterized in that: The water resources allocation module includes a climate change impact assessment submodule, which is used to analyze the impact of climate change on the balance of water resources supply and demand and dynamically adjust the water resources allocation plan.

5. The inland arid oasis water resources optimization configuration system based on big data analysis according to claim 4 is characterized in that: The water resources allocation model construction module includes a socio-economic factors examination submodule, which is used to consider the impact of socio-economic factors such as population growth, economic development and industrial structure adjustment on water resources demand, and incorporate socio-economic factors into the construction of the water resources allocation model.

6. The inland arid oasis water resources optimization configuration system based on big data analysis according to claim 5 is characterized in that: It also includes a user interaction interface module, which is used to provide an operation interface. The operation interface can input data, view water resource configuration results and adjust configuration parameters.

7. The inland arid oasis water resources optimization configuration system based on big data analysis according to claim 6 is characterized in that: It also includes an intelligent early warning and emergency response module, which is used to predict and identify potential water shortages and water pollution risks based on real-time monitored water resources data, water quality data and meteorological data, automatically generate early warning information, and trigger corresponding emergency response plans.

8. The inland arid oasis water resources optimization configuration system based on big data analysis according to claim 7 is characterized in that: The intelligent early warning and emergency response module includes a risk level assessment submodule, which is used to automatically assess the risk level of potential water shortages and water pollution according to the severity of the early warning information, and trigger corresponding emergency response plans based on different risk levels.

9. The inland arid oasis water resources optimization configuration system based on big data analysis according to claim 8 is characterized in that: The climate change impact assessment submodule includes an extreme climate event prediction submodule, which is used to use big data analysis technology to predict extreme climate events and formulate response measures in advance.

10. The inland arid oasis water resources optimization configuration system based on big data analysis according to claim 9 is characterized in that: Based on the water resources allocation module, the evolutionary relationship between water resources changes and ecologically sensitive targets is analyzed according to the two dimensions of ecological space and time. The ecological space dimension includes the relationship between water resources distribution and ecosystems, identification of ecologically sensitive areas, and the impact of water resources changes on ecosystems; the time dimension includes analysis of water resources change trends, the temporal evolution of ecologically sensitive targets, and the temporal matching of water resources allocation and ecological needs.

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