Quantitative evaluation and diagnosis method for natural water balance in multi-circle layer region

Abstract

The invention relates to the technical field of environmental monitoring and ecological evaluation, in particular to a multi-layer regional natural water balance quantitative evaluation and diagnosis method, which comprises the following steps of: acquiring key index data of an atmospheric layer, a surface layer and an underground layer related to regional natural water balance, constructing a key index data set of natural water balance, and analyzing the key index data set to determine the natural water balance; the method comprises the steps of obtaining index parameters of natural water balance, further calculating an actual comprehensive value, carrying out mean value analysis based on the actual comprehensive value in a historical time period, calculating a reference value of the natural water balance, comparing the actual comprehensive value of the current natural water balance with the reference value, calculating a deviation value, and matching the deviation value with a corresponding deviation interval. According to the method, evaluation scores are determined, comprehensive calculation is carried out to obtain comprehensive evaluation scores of natural water balance, and corresponding health conditions are matched, so that accurate quantification of the natural water balance state and health condition evaluation are realized, and a scientific basis is provided for ecological environment monitoring and treatment.

Description

Technical Field

[0001] This invention relates to the field of environmental monitoring and ecological assessment technology, specifically a method for quantitative evaluation and diagnosis of natural water balance in multi-sphere regions. Background Technology

[0002] Natural water balance refers to the dynamic equilibrium between the input, storage, and output of water in the atmosphere, surface, and subsurface layers within a specific region. This balance is affected by various factors such as climate change, geographical environment, and human activities, and is directly related to the stability of the ecological environment, the sustainable use of water resources, and regional water security management. In recent years, with the intensification of global climate change and the enhancement of human activities, the natural water balance in many regions has undergone significant changes, posing a severe challenge to the regional water environment. Therefore, scientifically and quantitatively assessing the status of natural water balance and systematically diagnosing it in order to identify potential imbalances has become an important research topic for water resource management and ecological protection. Traditional methods for assessing natural water balance typically rely on data analysis from a single sphere, failing to fully consider the comprehensive interactions between the atmosphere, surface, and subsurface spheres. Furthermore, existing methods are subjective in their evaluation criteria and lack unified quantitative standards, making it difficult to meet the needs of refined water resource management and ecological environmental protection.

[0003] To address the aforementioned shortcomings, a technical solution is provided. Summary of the Invention

[0004] The purpose of this invention is to address the lack of systematic and quantitative evaluation and diagnosis in current regional water balance analysis, and to propose a quantitative evaluation and diagnosis method for natural water balance in multi-sphere regions.

[0005] The objective of this invention can be achieved through the following technical solutions: A method for quantitative evaluation and diagnosis of natural water balance in multi-sphere regions includes the following steps: Collect key indicator data on the natural water balance of the region and construct a dataset of key indicators for natural water balance. The key indicator dataset of natural water balance is analyzed to obtain the indicator parameters of natural water balance, which include the indicator parameters of the atmosphere, the surface layer and the subsurface layer. The index parameters of natural water balance are analyzed to obtain the actual comprehensive value of natural water balance; Obtain the actual comprehensive value of natural water balance within a historical time period and perform mean analysis on it to calculate the actual comprehensive mean of natural water balance, which serves as the benchmark value of natural water balance; The deviation value of natural water balance is obtained by calculating the difference between the actual comprehensive value of natural water balance and its corresponding benchmark value. Five deviation ranges of natural water balance are set, and evaluation scores are assigned to the five deviation ranges in sequence. The deviation value of natural water balance is matched with the corresponding deviation range, and the corresponding evaluation score is determined based on the matching result. All the matched evaluation scores are comprehensively calculated to obtain the comprehensive evaluation score of natural water balance. At the same time, it is matched with the corresponding health status.

[0006] Furthermore, the specific process for constructing the dataset of key indicators for natural water balance is as follows: Over a period of time, key indicator data of the atmosphere, surface and subsurface layers involved in the regional natural water balance are collected in real time to construct a key indicator dataset of natural water balance. The data collection relies on daily observations from monitoring stations within the region, and the average value of the monitoring values ​​at different times on each day is calculated to obtain representative key indicator data for each day.

[0007] Furthermore, the key indicator data of the atmosphere are analyzed, specifically as follows: Extract the measured atmospheric humidity for each day and sort the atmospheric humidity in descending order of value to obtain an atmospheric humidity sequence. Extract the value of the atmospheric humidity corresponding to the mode from the atmospheric humidity sequence as the atmospheric humidity index value of the atmosphere. Extract the measured precipitation for each day, and take the precipitation of the first day as the initial precipitation, thereby calculating the precipitation index value of the atmospheric sphere; The daily precipitation is classified according to the corresponding month to obtain the monthly precipitation data. The average precipitation data of each month is calculated to obtain the monthly average precipitation, which is used as the monthly precipitation. By using the monthly precipitation as the vector modulus and the month as the vector angle, vector synthesis calculations are performed to obtain the precipitation concentration index value of the atmosphere. The atmospheric parameters consist of atmospheric humidity, precipitation, and precipitation concentration.

[0008] Furthermore, the key indicator data of the Earth's surface layers are analyzed, specifically as follows: Extract the measured runoff for each day to form a runoff dataset. Remove the maximum and minimum runoff from the runoff dataset and calculate the mean of the removed runoff to obtain the mean runoff value, which is used as the runoff index value of the Earth's surface sphere. The measured runoff for each day is classified according to the corresponding month to obtain the runoff dataset for each month. The runoff trend coefficient for each month is determined based on the runoff dataset for each month. The runoff trend coefficients of each month are compared and analyzed with the preset runoff trend thresholds to determine the runoff concentration month. The monthly values ​​corresponding to the runoff concentration month are extracted as the runoff concentration value. The runoff concentration values ​​of the months determined to be runoff concentration months are added together to obtain the total runoff concentration value, which is used as the runoff concentration index value of the surface sphere. Extract the measured water storage for each day to form a water storage dataset. Calculate the difference between water storage for adjacent days in the water storage dataset to obtain a daily variation sequence of water storage. Then, calculate the average of the daily variation sequence of water storage and use it as an indicator value of water storage change in the Earth's surface sphere. Extract the measured soil moisture for each day to form a soil moisture dataset, and calculate the average soil moisture in the soil moisture dataset to obtain the average soil moisture value, which is used as the soil moisture index value of the surface layer. The index parameters of the Earth's surface sphere consist of runoff index values, runoff concentration index values, water storage change index values, and soil moisture index values.

[0009] Furthermore, the key indicator data of the underground layers are analyzed, specifically as follows: Extract the measured water pollution concentration for each day and compare it with the preset water pollution concentration threshold. If the measured water pollution concentration on a certain day is greater than or equal to the preset water pollution concentration threshold, the day is judged as an abnormal state. Count the number of times the state is judged as abnormal to obtain the total number of abnormalities. Calculate the ratio of the total number of abnormalities to the total number of judgments to obtain the water quality abnormality ratio, which is used as the water quality index value of the underground sphere. A 3D surface model of the goaf is constructed, and a mesh is laid out on the 3D surface model of the goaf to obtain a goaf mesh cell network. At each monitoring time point within a unit time period, the volume of the goaf mesh cell is calculated, and the volumes of all mesh cells are accumulated to obtain the total volume of the goaf corresponding to each monitoring time point within a unit time period. The volume change rate of the goaf is then calculated. Boundary points are set up at the boundary of the goaf to obtain the boundary point set of the goaf. At each monitoring time point within a unit time period, the boundary point set of the goaf is obtained, and the expansion rate of the goaf is calculated based on the maximum movement distance of the boundary points. The influence coefficient is obtained by multiplying the numerical values ​​of the volume change rate and expansion rate of the goaf by their respective weighting coefficients and then summing them. The measured daily mining volume is extracted from the key indicator data of the underground sphere and multiplied by the corresponding influence coefficient to obtain the effective mining volume for each day. This effective mining volume is then compared with the preset over-mining range. If the effective mining volume of a certain day is within the preset over-mining range, that day is determined to be an over-mining day. All the data of the over-mining days are then statistically integrated to calculate the duration of over-mining and use it as the mining indicator value of the underground sphere. The measured groundwater level for each day is extracted from the key indicator data of the underground sphere, and the rock type of the aquifer is obtained at the same time. The rock type of the aquifer is matched with the permeable stratum type table to determine its permeability influence value. The measured groundwater level for each day is multiplied by the corresponding permeability influence value to obtain the effective groundwater level for each day. Then, the average value of all effective groundwater levels is calculated to obtain the average value of the effective groundwater level, and this average value is used as the groundwater depth index value of the underground sphere. The index parameters of the underground sphere consist of water quality index values, mining index values, and groundwater depth index values.

[0010] Furthermore, the index parameters of the atmosphere are analyzed, specifically as follows: The values ​​of atmospheric humidity, precipitation, and precipitation concentration were extracted from the index parameters of the atmosphere and normalized to obtain the actual comprehensive value of the atmosphere.

[0011] Furthermore, the index parameters of the Earth's surface layers are analyzed, specifically as follows: The values ​​of runoff, runoff concentration, water storage change, and soil moisture indices extracted from the surface layer are normalized to obtain the actual comprehensive value of the surface layer.

[0012] Furthermore, the index parameters of the underground layers are analyzed, specifically as follows: The values ​​of water quality, mining, and groundwater depth in the underground sphere are extracted and normalized to obtain the actual comprehensive value of the underground sphere.

[0013] Furthermore, the process of solving for the baseline value of natural water balance is as follows: The actual comprehensive values ​​of the atmosphere, surface sphere, and subsurface sphere in the natural water balance over a historical time period are obtained, and their average values ​​are calculated separately to obtain the actual comprehensive average values ​​of the atmosphere, surface sphere, and subsurface sphere, which are then used as the benchmark values ​​for the atmosphere, surface sphere, and subsurface sphere.

[0014] Furthermore, the process of calculating the comprehensive evaluation score for natural water balance is as follows: Calculate the deviation value of the atmosphere, that is, calculate the difference between the actual comprehensive value of the atmosphere and its reference value; Calculate the deviation value of the Earth's surface layers, that is, calculate the difference between the actual comprehensive value of the Earth's surface layers and its benchmark value; Calculate the deviation value of the underground layers, that is, calculate the difference between the actual comprehensive value of the underground layers and its benchmark value; The deviation values ​​of the atmosphere, surface layer, and subsurface layer are matched with their corresponding deviation intervals to determine the corresponding evaluation scores. All evaluation scores are then comprehensively calculated to obtain the comprehensive evaluation score of natural water balance.

[0015] The technical solution provided by this invention has the following advantages compared with the known prior art: 1. This invention constructs the index parameters of natural water balance by systematically analyzing the key indicators of each sphere, and further calculates the actual comprehensive value, so that the state of natural water balance can be accurately quantified, thereby avoiding the subjectivity and uncertainty brought about by the reliance on experience judgment in traditional methods. 2. This invention quantifies the natural water balance of the atmosphere, surface, and subsurface layers by using normalization and weighted calculation of influencing factors, and calculates a comprehensive evaluation score. This method can effectively reduce misjudgments that may be caused by fluctuations in a single indicator, making the evaluation results more accurate and reliable, and improving the scientific nature of natural water balance analysis. 3. This invention calculates the baseline value of natural water balance based on years of historical data, and calculates the difference between the actual comprehensive value of natural water balance and its corresponding baseline value to obtain the deviation value of natural water balance. Then, based on the set deviation range and evaluation score, it realizes the automatic classification of the health status of natural water balance. This quantitative assessment method can help governments, environmental protection agencies and related departments quickly identify areas with abnormal natural water balance, thereby formulating targeted ecological protection or restoration measures and improving the efficiency and scientific nature of environmental management. Attached Figure Description To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0016] Figure 1 This is a flowchart illustrating the overall process of the present invention. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, 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, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0018] like Figure 1 As shown, a method for quantitative evaluation and diagnosis of natural water balance in a multi-sphere region includes the following steps: A1: Collect key indicator data on the natural water balance of the relevant spheres in the region, and construct a key indicator dataset for natural water balance. The specific construction process is as follows: Over a period of time (on an annual scale), key indicator data of the atmosphere, surface and subsurface layers involved in the regional natural water balance are collected in real time to construct a key indicator dataset of natural water balance. Key indicators of the atmosphere include atmospheric humidity and precipitation. Key indicators of the Earth's surface include runoff, water storage, and soil moisture; Key indicators for the underground sphere include water pollution concentration, extraction volume, and groundwater level; Data collection relies on daily observations from monitoring stations (including meteorological stations, hydrological stations, satellite remote sensing, etc.) within the region, and the average value of the monitoring values ​​at different time points on each day is calculated to obtain representative key indicator data for each day; Specifically, for example, regarding atmospheric humidity, air humidity is measured at multiple times throughout the day (e.g., 00:00, 06:00, 12:00, 18:00), and the daily average is calculated using the following formula: , where H daily H represents the daily average atmospheric humidity. 00:00 -H 18:00 These are humidity values ​​measured at different time points; The calculated daily average atmospheric humidity value is used as the representative value of atmospheric humidity for that day.

[0019] A2: The key indicator dataset of natural water balance is analyzed to obtain the indicator parameters of natural water balance. The indicator parameters of natural water balance include those of the atmosphere, the surface layer, and the subsurface layer. The specific analysis process is as follows: a: Analyze the key indicator data of the atmosphere, specifically as follows: The measured atmospheric humidity for each day is extracted from the key index data of the atmosphere, and the atmospheric humidity is sorted in descending order of value to obtain an atmospheric humidity sequence. The value of the mode corresponding to the atmospheric humidity is extracted from the atmospheric humidity sequence and used as the atmospheric humidity index value Dsd of the atmosphere. The measured daily precipitation was extracted from key atmospheric index data and denoted as js. r The precipitation on the first day is taken as the initial precipitation, denoted as js1, where r represents the number of each day; The atmospheric precipitation index value Djs is calculated using the following formula; Specific formula: Among them, jsz r The value represents the daily precipitation fluctuation, m represents the total number of daily labels, and m≤365. e and p are both set natural constants, and a1 and a2 are the set influencing factors corresponding to the degree of precipitation increase and decrease, respectively. The daily precipitation is classified according to the corresponding month to obtain the monthly precipitation data. The average precipitation data of each month is calculated to obtain the monthly average precipitation, which is used as the monthly precipitation. The monthly precipitation is used as the vector's modulus, and the month is used as the vector's angle. The angle is set according to the following rules: the angle of the vector corresponding to the first month is set to 0°, and for each additional month, the vector's angle increases counterclockwise by 30°, that is, the angle of the vector for the 12th month is 330°. Therefore, vector synthesis calculations are performed to obtain the atmospheric precipitation concentration index value Dsz, as shown in the following formula: In the formula: P total For total precipitation, P i Let P be the precipitation in the i-th month, where i represents the month number. X P is the sum of the horizontal components of the modulus of monthly precipitation. Y Let θ be the sum of the vertical components of the modulus of monthly precipitation vectors. i The angle of the vector precipitation in the i-th month The atmospheric parameters consist of atmospheric humidity, precipitation, and precipitation concentration. b: Analyze the key indicator data of the Earth's surface layers, specifically as follows: The measured runoff for each day is extracted from the key indicator data of the surface sphere to form a runoff dataset. The maximum and minimum runoff in the runoff dataset are removed, and the mean of the removed runoff is calculated to obtain the runoff mean, which is used as the runoff indicator value Bjk of the surface sphere. The measured runoff for each day is classified and divided according to the corresponding month to obtain the runoff dataset for each month. Based on the runoff dataset for each month, the runoff trend coefficient for each month is determined, including: sorting the runoff for each month in chronological order to obtain the runoff sequence for each month; performing time-series decomposition on the runoff sequence for each month based on the STL time-series decomposition method to obtain the slope of the trend term for each month, which is used as the runoff trend coefficient for each month. Among them, the Seasonal and Trend decomposition using Loess (STL) method is a time series decomposition method that uses robust local weighted regression as a smoothing method. It decomposes the time series into corresponding trend, seasonal and residual terms. The STL time series decomposition method is a well-known time series decomposition method in this field, and will not be described in detail here. In this embodiment of the invention, by performing STL time series decomposition on the runoff sequence of each month, the trend term curve corresponding to each month is obtained. Then, the slope of the trend term is used as the runoff trend coefficient. Since the trend term can characterize the overall trend of the corresponding time series, the slope of the trend term can characterize the runoff change trend of each month. That is to say, the runoff trend coefficient can characterize the runoff change trend. The runoff trend coefficient of each month is compared and analyzed with the preset runoff trend threshold. If the runoff trend coefficient of a certain month is greater than the preset runoff trend threshold, the month is determined to be a runoff concentration month. The corresponding monthly value is extracted as the runoff concentration value. The runoff concentration values ​​of the months determined to be runoff concentration months are added together to obtain the total runoff concentration value, which is used as the runoff concentration index value Bjz of the surface sphere. The measured water storage for each day is extracted from the key indicator data of the surface sphere to form a water storage dataset. The difference between the water storage of adjacent days in the water storage dataset is calculated to obtain the daily change sequence of water storage. The average value of the daily change sequence of water storage is then calculated and used as the water storage change index value Bjs of the surface sphere. The soil moisture measured on each day is extracted from the key indicator data of the surface layer to form a soil moisture dataset. The average soil moisture in the soil moisture dataset is calculated to obtain the average soil moisture value, which is used as the soil moisture index value Bjn of the surface layer. The index parameters of the Earth's surface sphere consist of runoff index values, runoff concentration index values, water storage change index values, and soil moisture index values. c: Analyze the key indicator data of the underground layers, specifically as follows: The measured water pollution concentrations for each day are extracted from the key indicator data of the underground sphere. The measured water pollution concentrations for each day are compared and analyzed with the preset water pollution concentration thresholds. If the measured water pollution concentration on a certain day is greater than or equal to the preset water pollution concentration threshold, the day is judged as an abnormal state; otherwise, the day is judged as a normal state. The number of times the state is judged as abnormal is counted to obtain the total number of abnormalities. The ratio of the total number of abnormalities to the total number of judgments is calculated to obtain the water quality abnormality ratio, which is used as the water quality indicator value Xsz of the underground sphere. A 3D surface model of the goaf was constructed using the Marching Cubes algorithm, and a mesh was laid out on the 3D surface model to obtain a goaf mesh cell network. At each monitoring time point within a unit time period, the volume of each mesh cell was calculated, and the volumes of all mesh cells were summed to obtain the total goaf volume v(t) at each monitoring time point within the unit time period. The volume change rate of the goaf was then calculated from this result. The specific calculation formula is as follows: Where t represents the number of each monitoring time point within a unit time period, h represents the total number of monitoring time point numbers within a unit time period, and Δt represents the time interval between adjacent monitoring time points. Boundary points are set up along the boundary of the goaf to obtain a set of boundary points. At each monitoring time point within a unit of time, the set of boundary points of the goaf is obtained. The specific expression is: ; Calculate the expansion rate of the goaf based on the maximum movement distance of the boundary points. The specific calculation formula is as follows: , where j represents the number of the boundary point; The influence coefficient is obtained by multiplying the numerical values ​​of the volume change rate and expansion rate of the goaf by their respective weighting coefficients and then summing them. The measured daily mining volume is extracted from the key indicator data of the underground sphere and multiplied by the corresponding influence coefficient to obtain the effective mining volume for each day. This effective mining volume is then compared with the preset over-mining range. If the effective mining volume of a certain day is within the preset over-mining range, that day is determined to be an over-mining day. All the data of the over-mining days are then statistically integrated to calculate the duration of over-mining and use it as the mining indicator value Xkc of the underground sphere. The measured groundwater level for each day is extracted from the key indicator data of the underground sphere, and the rock type of the aquifer is obtained at the same time. The rock type of the aquifer is matched with the permeable stratum type table to determine its permeability influence value. The measured groundwater level for each day is multiplied by the corresponding permeability influence value to obtain the effective groundwater level for each day. Then, the average value of all effective groundwater levels is calculated to obtain the average value of the effective groundwater level, and this average value is used as the groundwater depth index value Xss of the underground sphere. The index parameters of the underground sphere consist of water quality index values, mining index values, and groundwater depth index values. The parameters of natural water balance are composed of the parameters of the atmosphere, the surface layer, and the subsurface layer.

[0020] A3: The index parameters of natural water balance are analyzed to obtain the actual comprehensive value of natural water balance. The actual comprehensive value of natural water balance includes the actual comprehensive values ​​of the atmosphere, the surface sphere, and the subsurface sphere. The specific analysis is as follows: The values ​​of atmospheric humidity (Dsd), precipitation (Djs), and precipitation concentration (Dsz) from the atmospheric parameters are extracted and normalized according to the formula: The actual comprehensive value δ1 of the atmosphere is obtained, where η1, η2 and η3 represent the set index influence factors. The index influence factors are used to measure the relative contribution of different indicators to the actual comprehensive value of the atmosphere. They reflect the weight of each indicator in the comprehensive evaluation of the atmosphere and can be specifically set by those skilled in the art according to the actual situation. The values ​​of runoff index Bjk, runoff concentration index Bjz, water storage change index Bjs, and soil moisture index Bjn extracted from the surface sphere parameters are normalized according to the formula: The actual comprehensive value δ2 of the surface sphere is obtained, where η4, η5, η6 and η7 represent the set index influence factors, respectively. The values ​​of water quality index Xsz, mining index Xkc, and groundwater depth index Xss extracted from the underground strata are normalized according to the formula: The actual comprehensive value δ3 of the underground sphere is obtained, where η8, η9 and η10 represent the set index influence factors.

[0021] A4: Obtain the actual comprehensive value of natural water balance within the historical time period and perform mean analysis on it to calculate the actual comprehensive mean of natural water balance, which serves as the benchmark value for natural water balance. The specific analysis process is as follows: Obtain the actual comprehensive value of the atmosphere in the natural water balance within a historical time period, and calculate its mean to obtain the actual comprehensive mean value of the atmosphere, which serves as the benchmark value of the atmosphere. The actual comprehensive value of the surface sphere in the natural water balance within a historical time period is obtained, and its mean is calculated to obtain the actual comprehensive mean value of the surface sphere, which is used as the benchmark value of the surface sphere. Obtain the actual comprehensive value of the underground sphere in the natural water balance within a historical time period, and calculate its mean value to obtain the actual comprehensive mean value of the underground sphere, which serves as the benchmark value of the underground sphere. The baseline values ​​for natural water balance are composed of the baseline values ​​of the atmosphere, the surface layer, and the subsurface layer; In one specific embodiment, taking the determination of the baseline value of the atmosphere as an example, the actual comprehensive value of the atmosphere over the past 10 years is selected, and its average value is calculated to obtain the actual comprehensive average value of the atmosphere, which is used as the baseline value of the atmosphere.

[0022] A5: The deviation value of natural water balance is obtained by calculating the difference between the actual comprehensive value of natural water balance and its corresponding benchmark value. Five deviation intervals are set for the deviation value of natural water balance: the first deviation interval, the second deviation interval, the third deviation interval, the fourth deviation interval, and the fifth deviation interval. The first deviation interval, the second deviation interval, the third deviation interval, the fourth deviation interval, and the fifth deviation interval are sequentially increased by preset values. The five deviation intervals are assigned evaluation scores from 1 to 5. The deviation value of natural water balance is matched with the corresponding deviation interval, and the corresponding evaluation score is determined according to the matching result. All the matched evaluation scores are comprehensively calculated (the calculation method can be added) to obtain the comprehensive evaluation score of natural water balance. This comprehensive evaluation score can be used to evaluate the overall state of natural water balance. At the same time, it is matched with the corresponding health status to reflect the health level of natural water balance. Different comprehensive evaluation scores correspond to different health statuses. The higher the comprehensive evaluation score, the worse the health status. The health status is divided into excellent, good, and poor. In one specific embodiment, the deviation value of the atmosphere is calculated, that is, the difference between the actual comprehensive value of the atmosphere and its reference value is calculated; Calculate the deviation value of the Earth's surface layers, that is, calculate the difference between the actual comprehensive value of the Earth's surface layers and its benchmark value; Calculate the deviation value of the underground layers, that is, calculate the difference between the actual comprehensive value of the underground layers and its benchmark value; The deviation values ​​of the atmosphere, surface layer, and subsurface layer are matched with their corresponding deviation ranges to determine the corresponding evaluation scores. All evaluation scores are then comprehensively calculated to obtain a comprehensive evaluation score for natural water balance. Each comprehensive evaluation score corresponds to a specific health condition to reflect the overall health level of natural water balance.

[0023] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A method for quantitative evaluation and diagnosis of natural water balance in multi-sphere regions, characterized in that, Includes the following steps: Collect key indicator data on the natural water balance of the region and construct a dataset of key indicators for natural water balance. The key indicator dataset of natural water balance was analyzed to obtain the indicator parameters of natural water balance. These parameters include those for the atmosphere, the surface layer, and the subsurface layer. The index parameters of the atmosphere consist of atmospheric humidity index values, precipitation index values, and precipitation concentration index values; The index parameters of the Earth's surface layer consist of runoff index values, runoff concentration index values, water storage change index values, and soil moisture index values; The index parameters of the underground sphere consist of water quality index values, mining index values, and groundwater depth index values; The index parameters of natural water balance are analyzed to obtain the actual comprehensive value of natural water balance; Obtain the actual comprehensive value of natural water balance within a historical time period and perform mean analysis on it to calculate the actual comprehensive mean of natural water balance, which serves as the benchmark value of natural water balance; The deviation value of natural water balance is obtained by calculating the difference between the actual comprehensive value of natural water balance and its corresponding benchmark value, and the comprehensive evaluation score of natural water balance is determined accordingly.

2. The method for quantitative evaluation and diagnosis of natural water balance in a multi-sphere region according to claim 1, characterized in that, The specific process of constructing the dataset of key indicators for natural water balance is as follows: Over a period of time, key indicator data of the atmosphere, surface and subsurface layers involved in the regional natural water balance are collected in real time to construct a key indicator dataset of natural water balance. The data collection relies on daily observations from monitoring stations within the region, and the average value of the monitoring values ​​at different times on each day is calculated to obtain representative key indicator data for each day.

3. The method for quantitative evaluation and diagnosis of natural water balance in a multi-sphere region according to claim 1, characterized in that, The specific process for solving the index parameters of the atmosphere is as follows: Extract the measured atmospheric humidity for each day and sort the atmospheric humidity in descending order of value to obtain an atmospheric humidity sequence. Extract the value of the atmospheric humidity corresponding to the mode from the atmospheric humidity sequence as the atmospheric humidity index value of the atmosphere. Extract the measured precipitation for each day, and take the precipitation of the first day as the initial precipitation, thereby calculating the precipitation index value of the atmospheric sphere; The daily precipitation is classified according to the corresponding month to obtain the monthly precipitation data. The average precipitation data of each month is calculated to obtain the monthly average precipitation, which is used as the monthly precipitation. By using the monthly precipitation as the vector modulus and the month as the vector angle, vector synthesis calculations are performed to obtain the precipitation concentration index value of the atmosphere.

4. The method for quantitative evaluation and diagnosis of natural water balance in a multi-sphere region according to claim 1, characterized in that, The specific process for solving the index parameters of the Earth's surface layers is as follows: Extract the measured runoff for each day to form a runoff dataset. Remove the maximum and minimum runoff from the runoff dataset and calculate the mean of the removed runoff to obtain the mean runoff value, which is used as the runoff index value of the Earth's surface sphere. The measured runoff for each day is classified according to the corresponding month to obtain the runoff dataset for each month. The runoff trend coefficient for each month is determined based on the runoff dataset for each month. The runoff trend coefficients of each month are compared and analyzed with the preset runoff trend thresholds to determine the runoff concentration month. The monthly values ​​corresponding to the runoff concentration month are extracted as the runoff concentration value. The runoff concentration values ​​of the months determined to be runoff concentration months are added together to obtain the total runoff concentration value, which is used as the runoff concentration index value of the surface sphere. Extract the measured water storage for each day to form a water storage dataset. Calculate the difference between water storage for adjacent days in the water storage dataset to obtain a daily variation sequence of water storage. Then, calculate the average of the daily variation sequence of water storage and use it as an indicator value of water storage change in the Earth's surface sphere. The measured soil moisture data for each day were extracted to form a soil moisture dataset. The average soil moisture value was then calculated from the soil moisture data to obtain the average soil moisture value, which serves as the soil moisture index value for the Earth's surface layer.

5. The method for quantitative evaluation and diagnosis of natural water balance in a multi-sphere region according to claim 1, characterized in that, The specific process for solving the water quality index values ​​among the index parameters of the underground sphere is as follows: Extract the measured water pollution concentration for each day and compare it with the preset water pollution concentration threshold. If the measured water pollution concentration on a certain day is greater than or equal to the preset water pollution concentration threshold, the day is judged as an abnormal state. Count the number of times the state is judged as abnormal to obtain the total number of abnormalities. Calculate the ratio of the total number of abnormalities to the total number of judgments to obtain the water quality abnormality ratio, which is used as the water quality index value of the underground sphere.

6. The method for quantitative evaluation and diagnosis of natural water balance in a multi-sphere region according to claim 1, characterized in that, The specific process for solving the mining index values ​​among the index parameters of the underground strata is as follows: A 3D surface model of the goaf is constructed, and a mesh is laid out on the 3D surface model of the goaf to obtain a goaf mesh cell network. At each monitoring time point within a unit time period, the volume of the goaf mesh cell is calculated, and the volumes of all mesh cells are accumulated to obtain the total volume of the goaf corresponding to each monitoring time point within a unit time period. The volume change rate of the goaf is then calculated. Boundary points are set up at the boundary of the goaf to obtain the boundary point set of the goaf. At each monitoring time point within a unit time period, the boundary point set of the goaf is obtained, and the expansion rate of the goaf is calculated based on the maximum movement distance of the boundary points. The influence coefficient is obtained by multiplying the numerical values ​​of the volume change rate and expansion rate of the goaf by their respective weighting coefficients and then summing them. The measured daily mining volume is extracted from the key indicator data of the underground sphere and multiplied by the corresponding influence coefficient to obtain the effective mining volume for each day. This effective mining volume is then compared with the preset over-mining range. If the effective mining volume of a certain day falls within the preset over-mining range, that day is determined to be an over-mining day. All data from the days determined to be over-mining are then statistically integrated to calculate the duration of over-mining, which is then used as the mining indicator value for the underground sphere.

7. The method for quantitative evaluation and diagnosis of natural water balance in a multi-sphere region according to claim 1, characterized in that, The specific process for solving the groundwater depth index value among the index parameters of the underground strata is as follows: The measured groundwater level for each day is extracted from the key indicator data of the underground sphere, and the rock type of the aquifer is obtained at the same time. The rock type of the aquifer is matched with the permeability stratum type table to determine its permeability influence value. The measured groundwater level for each day is multiplied by the corresponding permeability influence value to obtain the effective groundwater level for each day. Then, the average value of all effective groundwater levels is calculated to obtain the average value of the effective groundwater level, and this average value is used as the groundwater depth index value of the underground sphere.

8. The method for quantitative evaluation and diagnosis of natural water balance in a multi-sphere region according to claim 1, characterized in that, The parameters of the natural water balance are analyzed, specifically as follows: The actual comprehensive value of the atmosphere is determined based on the atmospheric humidity, precipitation and precipitation concentration parameters. The actual comprehensive value of the surface sphere is determined based on the runoff index value, runoff concentration index value, water storage change index value and soil moisture index value among the index parameters of the surface sphere. The actual comprehensive value of the underground sphere is determined based on the water quality index, mining index, and groundwater depth index among the index parameters of the underground sphere. The actual comprehensive value of natural water balance is composed of the actual combined values ​​of the atmosphere, the surface layer, and the subsurface layer.

9. The method for quantitative evaluation and diagnosis of natural water balance in a multi-sphere region according to claim 8, characterized in that, The process of solving for the baseline value of natural water balance is as follows: The actual comprehensive values ​​of the atmosphere, surface sphere, and subsurface sphere in the natural water balance within a historical time period are obtained, and their average values ​​are calculated separately to obtain the actual comprehensive average values ​​of the atmosphere, surface sphere, and subsurface sphere, which are then used as the benchmark values ​​for the atmosphere, surface sphere, and subsurface sphere. The baseline values ​​for natural water balance are composed of the baseline values ​​of the atmosphere, the surface layer, and the subsurface layer.

10. The method for quantitative evaluation and diagnosis of natural water balance in a multi-sphere region according to claim 1, characterized in that, The process of calculating the comprehensive evaluation score for natural water balance is as follows: Calculate the deviation value of the atmosphere, that is, calculate the difference between the actual comprehensive value of the atmosphere and its reference value; Calculate the deviation value of the Earth's surface layers, that is, calculate the difference between the actual comprehensive value of the Earth's surface layers and its benchmark value; Calculate the deviation value of the underground layers, that is, calculate the difference between the actual comprehensive value of the underground layers and its benchmark value; The deviation values ​​of the atmosphere, surface layer, and subsurface layer are matched with their corresponding deviation intervals to determine the corresponding evaluation scores. All evaluation scores are then comprehensively calculated to obtain the comprehensive evaluation score of natural water balance.

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