An ecological water level regulation method and system based on the influence of annual evaporation

Abstract

This invention discloses an ecological water level regulation method and system based on the influence of annual evaporation, belonging to the field of water resource management technology. The method includes: acquiring water quality, hydrological, and environmental monitoring data of the target area; determining a suitable water level range based on historical baseline and change period water level data; determining an initial water level range based on a preset water level-water quality mapping table and water quality data; calculating the water body's self-purification capacity using hydrological data to obtain the target water level lower limit and updating the initial range; determining a base water level range by comparing the two types of ranges; calculating the total evaporation based on meteorological and environmental data for the next preset period; correcting the base water level range to obtain the actual water level range; and finally, controlling the gate to perform water level regulation operations based on this actual water level range. This invention integrates multiple constraints, and through multiple rounds of verification and dynamic correction, forms a scientific actual water level range and executes gate regulation, effectively improving the accuracy of water level regulation decisions.

Description

Technical Field

[0001] This invention belongs to the field of water resource management technology, specifically relating to an ecological water level regulation method and system based on the influence of annual evaporation. Background Technology

[0002] In the management of watersheds and water areas characterized by water scarcity, arid climates, and significant evaporation losses, ecological water level regulation based on annual evaporation is a highly targeted scheduling method. It is commonly applied to natural lakes, wetlands, inland rivers, and reservoirs and artificial ecological water areas controlled by dams in arid and semi-arid regions. It is particularly suitable for areas with high evaporation rates, water levels that are highly susceptible to climate changes, and ecologically sensitive and fragile environments. By dynamically adjusting water levels in conjunction with annual evaporation, it is possible to avoid water shrinkage and ecological degradation caused by excessive evaporation, as well as to prevent water waste caused by indiscriminate water replenishment. This has important practical significance for maintaining the ecological base flow of rivers and lakes, protecting aquatic habitats, ensuring the normal growth of wetland vegetation, and maintaining regional biodiversity. At the same time, it can also optimize the allocation of water resources in the basin, balance ecological water use with production and domestic water use, improve water resource utilization efficiency, and contribute to the stability of the aquatic ecosystem and the sustainable development of the basin.

[0003] Existing ecological water level control schemes typically rely on historical hydrological observation data and meteorological statistics to construct a basic water balance model. Annual evaporation is incorporated as a fixed water loss factor in the calculation, and then, combined with preset water level thresholds or reservoir capacity constraints, static water level control intervals and gate scheduling strategies are formulated. This approach has advantages such as simple model construction, intuitive scheduling logic, and ease of engineering application, and is therefore widely used in existing ecological water level control systems.

[0004] However, in the actual application of the above-mentioned ecological water level regulation methods, due to the continuous interference of human activities such as upstream reservoir scheduling and inter-basin water transfer, the natural hydrological situation of the water area has changed significantly. At the same time, problems such as water quality deterioration and pollutant accumulation are becoming increasingly prominent, posing multiple threats to the ecosystem. Existing schemes mostly take the restoration of the natural hydrological situation as the core objective, and only formulate static water level regulation ranges based on historical natural water level data and ecological water demand calculation results. They include environmental factors such as evaporation as a single water loss parameter in the basic calculation. This regulation logic based solely on the hydrological background will lead to the final determined water level range failing to meet the dual needs of water quality improvement and ecological water quantity guarantee, thereby affecting the health, stability and long-term sustainability of the aquatic ecosystem. Summary of the Invention

[0005] The purpose of this invention is to solve the problem that existing ecological water levels are difficult to comprehensively balance hydrological conditions, water quality protection and environmental dynamics, resulting in a mismatch between water level regulation and ecological health needs. Therefore, this invention proposes an ecological water level regulation method and system based on the influence of annual evaporation.

[0006] In a first aspect of this invention, an ecological water level regulation method based on the influence of annual evaporation is first proposed, the method comprising:

[0007] Acquire monitoring data for the target area; the monitoring data includes water quality data, hydrological data, and environmental data; the hydrological data includes upstream inflow, upstream pollutant concentration, outflow, actual water level, water area, and reservoir capacity;

[0008] Suitable water level ranges are determined based on historical baseline water level data and historical variation water level data; the historical baseline water level data represents the natural fluctuation of hydrological conditions during periods unaffected by upstream reservoir regulation; the historical variation water level data represents the response changes of hydrological conditions during periods affected by upstream reservoir construction and operation regulation.

[0009] Based on a preset water level and water quality mapping table, the initial water level range data is determined according to the water quality data.

[0010] The target water level lower limit is obtained by calculating the water self-purification capacity of the target area based on the hydrological data, and the target water level interval data is obtained by updating the initial water level interval data based on the target water level lower limit.

[0011] The water level range data is determined based on the comparison results between the suitable water level range data and the target water level range data.

[0012] Based on the meteorological data for the next preset period, the total evaporation of the target area for that preset period is calculated in combination with the environmental data. The water level interval data is then corrected according to the total evaporation to obtain the actual water level interval data. The gate is then controlled to perform water level regulation operations based on the actual water level interval data.

[0013] Optionally, the data for determining suitable water level ranges based on historical baseline water level data and historical variation water level data include:

[0014] The average water level data for the historical baseline period and the average water level data for the historical change period are calculated by averaging the data respectively to obtain the average water level data for the baseline period and the average water level data for the change period;

[0015] Hydrological change features are extracted and integrated from the baseline period average water level data and the change period average water level data respectively to obtain water level feature data;

[0016] Using the average water level data during the baseline period and the average water level data during the change period as benchmark variables, a correlation analysis is performed between the benchmark variables and the water level characteristic data, and effective water level characteristic data is obtained by screening.

[0017] Effective joint density data is obtained by performing joint distribution modeling on the effective water level characteristic data; the effective joint density data includes base period joint density data and change period joint density data.

[0018] Hydrological variability data are obtained by performing non-overlapping area integration calculations on the base period joint density data and the change period joint density data.

[0019] Based on the hydrological variability data, the cumulative probability within the water level range is selected from the baseline period joint density data to obtain suitable water level range data.

[0020] This scheme conducts multi-dimensional feature analysis and quantitative modeling based on historical water level data, scientifically identifies hydrological change patterns and accurately delineates suitable water level intervals. It not only conforms to the ecological basic requirements of the baseline period but also adapts to the dynamic characteristics of hydrological changes, significantly improving the scientificity and adaptability of water level interval delineation and providing accurate and reliable quantitative basis for ecological water level regulation.

[0021] Optionally, the hydrological variability data can be obtained by performing non-overlapping region integration calculations on the base period joint density data and the change period joint density data, including:

[0022] pass Calculate hydrological variability data; among which, This represents the hydrological variability data corresponding to the i-th hydrological change feature. This represents the joint density data of the i-th effective water level characteristic data and the benchmark variable y in the baseline period. This represents the joint density data of the i-th effective water level characteristic data and the change period of the benchmark variable y.

[0023] Optionally, the process of generating the preset water level and water quality mapping table includes:

[0024] Obtain historical water quality data that meets the standards, filter the water quality data that meets the preset water quality conditions from the historical water quality data as water quality data that meets the standards, and extract the corresponding water level data to obtain water level data that meets the standards.

[0025] The water level data and the water quality data that meet the standards are aligned by time to obtain a water level and water quality data sequence;

[0026] A regression model between water level and water quality data is established based on the water level and water quality data sequence. The upper limit water level data and the lower limit water level data are obtained by solving the water level range that meets the preset water quality conditions through the regression model.

[0027] A water level change rate sequence is generated based on the historical water level data, and the lower and upper limits of the water level change rate are set using the preset quantiles of the water level change rate sequence to obtain change rate limit data.

[0028] The upper limit water level data, the lower limit water level data, and the rate of change limit data are jointly constrained to select water level values ​​that simultaneously satisfy the condition that the water level value is between the upper and lower limits and the rate of change of the water level is within the rate of change limit, thus obtaining an effective water level interval. Different preset water quality conditions are associated with the effective water level intervals in the form of a mapping table to obtain a water level and water quality mapping table.

[0029] Optionally, calculating the target water level lower limit based on the hydrological data to obtain the water body self-purification capacity of the target area includes:

[0030] The total amount of pollutants entering the area is calculated based on the upstream inflow rate and the concentration of pollutants in the upstream water.

[0031] Calculate the annual outflow volume based on the outflow volume;

[0032] Establish a functional relationship between the actual water level and the reservoir capacity based on the water area;

[0033] pass Calculate the self-purification capacity of the water body in the target area; wherein, To preset pollutant concentrations, The water level H corresponds to the reservoir capacity value in the aforementioned functional relationship. The degradation coefficient of pollutants, This refers to the annual outflow of water from the area.

[0034] The minimum water level required for the water body to dissipate the current pollutant load is determined based on the water body's self-purification capacity and the total amount of pollutants entering the area, and this is used as the lower limit of the target water level.

[0035] This plan calculates the total amount of pollutants entering the area, constructs the relationship between water level and reservoir capacity, and accurately derives the minimum target water level that meets water quality requirements by combining the formula of water body self-purification capacity. It achieves quantitative matching between pollutant load and water body self-purification capacity, effectively improves the scientificity and accuracy of water level regulation decisions, and provides reliable support for water environment management and water resource allocation.

[0036] Optionally, determining the water level range data based on the comparison result between the suitable water level range data and the target water level range data includes:

[0037] The upper limit of the suitable water level range data is taken as the first upper limit, and the lower limit is taken as the first lower limit;

[0038] The upper limit of the target water level range data is used as the second upper limit, and the lower limit is used as the second lower limit;

[0039] The result is obtained by performing an intersection operation between the suitable water level range data and the target water level range data.

[0040] If the calculation result has an intersection, the larger value between the first lower limit and the second lower limit is taken as the final lower limit of the water level, and the smaller value between the first upper limit and the second upper limit is taken as the final upper limit of the water level. The water level interval formed by the final lower limit of the water level and the final upper limit of the water level is determined as the water level interval data.

[0041] If the calculation result is that there is no intersection, an interval conflict warning signal is generated, and the preset safe water level interval data is taken as the water level interval data.

[0042] This scheme decomposes the suitable water level range and the target water level range into upper and lower limits, respectively. It first performs an intersection calculation on the data from both ranges, and then determines the final water level range or triggers an early warning and adopts a preset safe water level range based on whether the intersection exists. This achieves a scientific integration and coordinated handling of dual water level constraints. This approach ensures that water level regulation meets both ecological suitability requirements and actual scheduling objectives. Furthermore, it provides timely warnings and switches to a safe water level range when conflicts arise between the two constraints, effectively mitigating the risks of water level scheduling. This significantly improves the scientific, safe, and accurate nature of water level regulation decisions, providing a stable and reliable technical guarantee for refined regional water resource scheduling and ecological water level management.

[0043] Optionally, the calculation of the total evaporation of the target area in the preset period, based on meteorological data for the next preset period and combined with the environmental data, includes:

[0044] Obtain historical annual evaporation data;

[0045] The meteorological data is spatially downscaled using the Kriging interpolation method to obtain gridded meteorological data that matches the spatial resolution of the target area.

[0046] The deviation coefficient of meteorological data is calculated based on the sliding window statistical method, and the deviation is corrected based on the deviation coefficient to obtain a fused meteorological dataset.

[0047] A regional evaporation coefficient matrix is ​​constructed based on the environmental data of the target area, and a calibrated evaporation coefficient matrix is ​​obtained by calibrating the regional evaporation coefficient matrix based on the historical annual evaporation data.

[0048] The total evaporation of the target area in the preset period is calculated by substituting the fused meteorological dataset into the calibration evaporation coefficient matrix and using a spatiotemporal weighted iterative algorithm.

[0049] This scheme acquires historical annual evaporation data and combines it with the Kriging interpolation method to achieve accurate spatial downscaling of meteorological data. It uses the sliding window statistical method to calculate and correct the deviation coefficient, ensuring the accuracy of the meteorological dataset. At the same time, it constructs and calibrates the evaporation coefficient matrix based on the environmental data of the target area. Finally, it uses a spatiotemporal weighted iterative algorithm to accurately calculate the total regional evaporation, effectively improving the accuracy and reliability of the total evaporation measurement.

[0050] In a second aspect of this invention, an ecological water level regulation system based on the influence of annual evaporation is proposed, comprising:

[0051] The data acquisition module is used to acquire monitoring data of the target area; the monitoring data includes water quality data, hydrological data and environmental data; the hydrological data includes upstream inflow, upstream pollutant concentration, outflow, actual water level, water area and reservoir capacity.

[0052] The first interval determination module is used to determine suitable water level interval data based on historical baseline water level data and historical change period water level data; the historical baseline water level data represents the natural fluctuation state of the hydrological situation during the period when it is not affected by the regulation of the upstream reservoir; the historical change period water level data represents the response change state of the hydrological situation during the period when it is affected by the construction and operation regulation of the upstream reservoir.

[0053] The second interval determination module is used to determine the initial water level interval data based on the water quality data according to the preset water level and water quality mapping table.

[0054] The third interval determination module is used to calculate the water self-purification capacity of the target area based on the hydrological data to obtain the target water level lower limit, and update the initial water level interval data based on the target water level lower limit to obtain the target water level interval data.

[0055] The fourth interval determination module is used to determine the water level interval data based on the comparison result between the suitable water level interval data and the target water level interval data;

[0056] The control module is used to calculate the total evaporation of the target area in the preset period based on meteorological data of the next preset period and the environmental data, correct the water level interval data according to the total evaporation to obtain the actual water level interval data, and control the gate to perform water level control operation according to the actual water level interval data.

[0057] The beneficial effects of this invention are as follows: This solution, through hierarchical verification and dynamic correction of multi-dimensional monitoring data, not only ensures that water level regulation is in line with the regional water quality standards and the ecological baseline of water body self-purification throughout the entire process, effectively avoiding water quality exceeding standards or insufficient ecological water demand due to water level deviation, but also corrects the water level regulation target in real time through quantitative calculation of total evaporation, offsetting the actual impact of meteorological changes on water body capacity, so that gate regulation commands are always executed based on real-time and multi-dimensionally verified water level data, significantly improving the accuracy and anti-interference ability of water level regulation. Attached Figure Description

[0058] The present invention will now be further described with reference to the accompanying drawings.

[0059] Figure 1 A flowchart of an ecological water level regulation method based on the influence of annual evaporation provided in an embodiment of the present invention. Detailed Implementation

[0060] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0061] Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0062] This invention provides an ecological water level regulation method based on the influence of annual evaporation. See also... Figure 1 , Figure 1 A flowchart illustrating an ecological water level regulation method based on the influence of annual evaporation, provided as an embodiment of the present invention. The method includes the following steps:

[0063] S101, acquire monitoring data for the target area;

[0064] S102, determine suitable water level range data based on historical baseline water level data and historical change period water level data;

[0065] S103, Based on the preset water level and water quality mapping table, determine the initial water level range data according to the water quality data;

[0066] S104. Calculate the self-purification capacity of the water body in the target area based on hydrological data to obtain the lower limit of the target water level, and update the initial water level interval data based on the lower limit of the target water level to obtain the target water level interval data.

[0067] S105, determine the water level interval data based on the comparison results between the suitable water level interval data and the target water level interval data;

[0068] S106, based on the meteorological data of the next preset period, combined with environmental data, calculate the total evaporation of the target area in the preset period, correct the water level interval data according to the total evaporation to obtain the actual water level interval data, and control the gate to perform water level regulation operation according to the actual water level interval data.

[0069] The monitoring data includes water quality data, hydrological data, and environmental data;

[0070] Hydrological data include upstream inflow, upstream pollutant concentration, outflow, actual water level, water area, and reservoir capacity;

[0071] Historical baseline water level data characterizes the natural fluctuations in hydrological conditions during periods unaffected by upstream reservoir regulation.

[0072] Historical water level data characterize the response and change of hydrological conditions during periods affected by the construction and operation of upstream reservoirs.

[0073] This invention provides an ecological water level regulation method based on the impact of annual evaporation. The method first integrates multi-source monitoring data on water quality, hydrology, and environment in the target area. Based on historical baseline and changing period water level data, it determines ecologically suitable water level ranges. An initial water level range is derived using a water quality mapping table. Then, the target water level lower limit is calculated and updated by combining the water body's self-purification capacity. A baseline water level range is determined by comparing the two ranges. Subsequently, total evaporation is calculated using meteorological and environmental data, and the actual water level range is dynamically corrected and used for gate regulation. This method integrates multi-source monitoring data, incorporating multiple constraints such as ecological suitability, water quality safety, water body self-purification capacity, and evaporation dynamics. Through multiple rounds of verification and dynamic correction, a scientific actual water level range is formed and gate regulation is implemented. This method achieves a fusion of static constraints and dynamic environmental factors, ensuring that water level regulation aligns with hydrological changes and adapts to actual scheduling and evaporation losses. This effectively improves the accuracy of water level regulation decisions and provides comprehensive and highly reliable technical support for refined regional water resource scheduling and water environment management.

[0074] In one implementation, the preset period is in months or quarters, which can be flexibly selected according to the meteorological characteristics and hydrological scheduling needs of the target area.

[0075] In one implementation, after obtaining the total evaporation amount for the target area in the next preset period, the total evaporation amount is first converted into the water level drop rate within the period based on the correspondence between evaporation amount and water level change. This is used to dynamically correct the previously determined water level range data, and finally obtain the actual water level range data that fits the future hydrological dynamics.

[0076] In one embodiment, determining suitable water level intervals based on historical baseline water level data and historical variation water level data includes:

[0077] The average water level data for the base period and the average water level data for the change period are calculated by averaging the historical base period water level data and the historical change period water level data respectively.

[0078] Hydrological change characteristics were extracted and integrated from the baseline period average water level data and the change period average water level data respectively to obtain water level characteristic data;

[0079] The average water level data during the baseline period and the average water level data during the change period are used as baseline variables. Correlation analysis is performed between the baseline variables and the water level characteristic data, and effective water level characteristic data are obtained by screening.

[0080] Effective joint density data are obtained by performing joint distribution modeling on effective water level characteristic data; effective joint density data includes base period joint density data and change period joint density data.

[0081] Hydrological variability data are obtained by integrating the base period joint density data and the change period joint density data in non-overlapping areas.

[0082] Based on the hydrological variability data, the cumulative probability is selected from the base period joint density data to obtain suitable water level range data within the water level range.

[0083] In one implementation method, the extraction and integration of hydrological change features involves extracting corresponding hydrological change feature indicators from the baseline period average water level data and the change period average water level data, including monthly average water levels, extreme maximum or minimum water levels for different durations, the time of occurrence of extreme water levels, the number and duration of water level pulses, the rate of rise or fall of water levels, and the number of reversals. Then, all the hydrological change feature indicators extracted from the two periods are systematically integrated, duplicate indicators are eliminated, and the indicator dimensions and statistical calibers are unified, ultimately forming a complete and unified set of water level feature data that comprehensively represents the hydrological situation characteristics of water levels in the baseline period and the change period.

[0084] In one implementation, the correlation analysis and screening process first determines the baseline variables as the average water level data during the baseline period and the average water level data during the change period, which reflect the overall water level and have an inherent physical and ecological relationship with various hydrological characteristics. The set of baseline variables is denoted as X={x1,x2}, where x1 is the average water level during the baseline period and x2 is the average water level during the change period. The set of water level characteristic data is denoted as Y={y1,y2,...,y n}, where y i For the i-th water level characteristic index, correlation analysis methods such as Pearson correlation coefficient method and principal component analysis are used to calculate the correlation coefficient between the benchmark variable and each water level characteristic index. This quantifies the degree of linear or nonlinear correlation between the two, where j takes values ​​of 1 and 2. Represents the benchmark variable With characteristic indicators covariance, , These are the standard deviations of the two values; then, a reasonable correlation screening threshold is set to retain those that satisfy | |Water level characteristic indicators that meet the correlation screening threshold, are significantly correlated with the baseline variable, can be effectively explained by the baseline variable, and have no obvious statistical redundancy are selected. Indicators with extremely low correlation and that cannot reflect the intrinsic relationship between the baseline variable and hydrological characteristics are removed. Finally, effective water level characteristic data that can accurately reflect the core changes in water level situation are obtained, which reduces the dimensional redundancy of subsequent modeling and improves the pertinence of analysis.

[0085] In one implementation, joint distribution modeling combines Gaussian kernel density estimation and Copula functions. First, for the effective water level characteristic data of the baseline period and the change period, the marginal probability density distribution of each characteristic index is fitted using the Gaussian kernel density estimation method. This accurately depicts the distribution law of a single effective water level characteristic and avoids the subjective problem of class division in the histogram method. Then, based on Sklar's theorem, a suitable Archimedean Copula function, such as Gumbel, Clayton, or Frank Copula, is introduced to couple the marginal distributions of each effective water level characteristic, constructing a joint probability density model among the effective water level characteristics of the baseline period and a joint probability density model among the effective water level characteristics of the change period. By solving the models, the baseline period joint density data that can characterize the joint distribution law of multiple features in the baseline period and the change period joint density data that characterizes the joint distribution law of multiple features in the change period are obtained. The two together constitute the effective joint density data, realizing the quantification of the coordinated change law of multiple hydrological characteristics.

[0086] In one implementation, the process of generating suitable water level interval data involves using the joint density data of the baseline period as a reference standard for natural hydrological conditions, and combining it with the degree of change in hydrological conditions reflected by hydrological variability data. First, the cumulative probability screening principle for suitable water levels is defined, namely, the cumulative probability range corresponding to water levels that conform to natural hydrological laws and can support the stability of the aquatic ecosystem. Then, the cumulative probability integral of the joint probability density function corresponding to the joint density data of the baseline period is calculated over the water level interval to extract the water level intervals whose cumulative probability falls within the preset suitable range. At the same time, the interval boundaries are corrected in combination with hydrological variability data. If the hydrological variability is mild, the interval range can be slightly widened; if it is moderate or severe, the interval is strictly determined according to the natural cumulative probability of the baseline period. Finally, suitable water level interval data that can provide a reference for ecological hydrological regulation and reservoir ecological scheduling is obtained. This data represents the reasonable water level range for maintaining the health of the aquatic ecosystem.

[0087] In one embodiment, hydrological variability data is obtained by integrating the base period joint density data and the change period joint density data over non-overlapping areas, including:

[0088] pass Calculate hydrological variability data; among which, This represents the hydrological variability data corresponding to the i-th hydrological change feature. This represents the joint density data of the i-th effective water level characteristic data and the benchmark variable y in the baseline period. This represents the joint density data of the i-th effective water level characteristic data and the change period of the benchmark variable y.

[0089] In one embodiment, the process of generating the preset water level and water quality mapping table includes:

[0090] Obtain historical water quality data that meets the standards, filter the water quality data that meets the preset water quality conditions from the historical water quality data as the water quality data that meets the standards, and extract the corresponding water level data to obtain the water level data that meets the standards.

[0091] The water level and water quality data that meet the standards are aligned by time to obtain a water level and water quality data sequence.

[0092] A regression model between water level and water quality data is established based on the water level and water quality data series. The upper limit water level data and the lower limit water level data are obtained by solving the water level range that meets the preset water quality conditions through the regression model.

[0093] A water level change rate sequence is generated based on historical water level data. The lower and upper limits of the water level change rate are set using the preset quantiles of the water level change rate sequence to obtain the change rate limit data.

[0094] By jointly constraining the upper limit water level data, lower limit water level data, and rate of change limit data, the effective water level intervals are selected by filtering out water level values ​​that simultaneously meet the conditions of being between the upper and lower limits and having a rate of change within the rate of change limit. Different preset water quality conditions are then associated with the effective water level intervals and stored in the form of a mapping table to obtain a water level and water quality mapping table.

[0095] In one implementation method, the preset water quality conditions are quantitative thresholds set for core water quality indicators such as dissolved oxygen, chemical oxygen demand, ammonia nitrogen, and total phosphorus, based on water environment quality standards and water ecological protection goals.

[0096] In one implementation, the commonly used specific values ​​for the preset quantiles are 25% and 75%, that is, the lower limit threshold is taken as the 25th quantile of the water level change rate sequence, and the upper limit threshold is taken as the 75th quantile.

[0097] In one implementation, the process of generating upper and lower limits for water levels involves first using water level and water quality data sequences as a basis, clearly defining water level data as the independent variable and water quality data as the dependent variable, and selecting regression analysis techniques such as linear regression, nonlinear regression, or generalized additive models that are suitable for the data distribution characteristics to construct a regression model between water level and water quality data. The quantitative correlation between the two is quantified through model fitting. Then, the preset water quality conditions are transformed into constraints for the model, that is, the water quality data is required to meet the preset compliance threshold range. By solving the regression model in reverse, all water level values ​​that allow the water quality data to fall within the constraint range are determined. Finally, the minimum value is extracted from these water level values ​​as the lower limit data and the maximum value is extracted as the upper limit data, thereby clarifying the boundary of the water level value range that meets the preset water quality requirements.

[0098] In one embodiment, calculating the target water level lower limit based on hydrological data includes:

[0099] The total amount of pollutants entering the area is calculated based on the upstream inflow rate and the concentration of pollutants in the upstream water.

[0100] Calculate the annual outflow volume based on the outflow volume;

[0101] Establish a functional relationship between the actual water level and the reservoir capacity based on the water area;

[0102] pass Calculate the self-purification capacity of the water body in the target area; where, To preset pollutant concentrations, It is the reservoir capacity value corresponding to the water level H in the functional relationship. The degradation coefficient of pollutants, This refers to the annual outflow of water from the area.

[0103] The minimum water level required to dissipate the current pollutant load is determined based on the water body's self-purification capacity and the total amount of pollutants entering the area, and this is used as the lower limit of the target water level.

[0104] In one implementation, the formula for calculating the self-purification capacity of the water body is based on the kinetic principles of a completely mixed reactor, objectively describing the variation of the water body's self-purification capacity with hydraulic retention time. In the formula, Q represents the annual outflow of water from the lake, which determines the potential for pollutant discharge. This refers to the hydraulic retention time; the higher the value, the more fully the pollutants are degraded in the water. When the water level approaches 1, the self-purification capacity reaches its upper limit. Introducing the impact of water level H on reservoir capacity V(H) allows for a quantitative assessment of the regulatory effect of ecological water level changes on pollution carrying capacity. This approach can quantitatively evaluate changes in self-purification capacity under different ecological water levels and... As a management constraint, the calculation results directly serve the total pollutant control and water level optimization scheduling.

[0105] In one implementation, the total amount of pollutants entering the area is calculated by multiplying the upstream inflow data for each time period with the corresponding upstream pollutant concentration data for that time period, and then summing them over time.

[0106] In one implementation, the functional relationship between water level and reservoir capacity is first based on the measured water area data of the target water area, combined with the water area planar mapping results under different water level elevations. Then, using the integration method, with water level H as the independent variable, the water area A(H) under the corresponding water level is integrated along the elevation direction.

[0107] In one embodiment, determining the water level interval data based on a comparison between suitable water level interval data and target water level interval data includes:

[0108] The upper limit of the appropriate water level range is taken as the first upper limit, and the lower limit is taken as the first lower limit.

[0109] The upper limit of the target water level range data is used as the second upper limit, and the lower limit is used as the second lower limit;

[0110] The result is obtained by intersecting the data of the suitable water level range with the data of the target water level range.

[0111] If the calculation results show an intersection, the larger value between the first lower limit and the second lower limit is taken as the final lower limit of the water level, and the smaller value between the first upper limit and the second upper limit is taken as the final upper limit of the water level. The water level interval formed by the final lower limit of the water level and the final upper limit of the water level is determined as the water level interval data.

[0112] If the calculation result is that there is no intersection, an interval conflict warning signal is generated, and the preset safe water level interval data is taken as the water level interval data.

[0113] In one implementation, the preset safe water level range data is determined by technical personnel.

[0114] In one embodiment, calculating the total evaporation of the target area for that preset period based on meteorological data from the next preset period, combined with environmental data, includes:

[0115] Obtain historical annual evaporation data;

[0116] Meteorological data is spatially downscaled using the Kriging interpolation method to obtain gridded meteorological data that matches the spatial resolution of the target area.

[0117] The deviation coefficient of meteorological data is calculated based on the sliding window statistical method, and the deviation is corrected based on the deviation coefficient to obtain the fused meteorological dataset.

[0118] A regional evaporation coefficient matrix is ​​constructed based on environmental data of the target area, and a calibrated evaporation coefficient matrix is ​​obtained by calibrating the regional evaporation coefficient matrix based on historical annual evaporation data.

[0119] By substituting the fused meteorological dataset into the calibrated evaporation coefficient matrix, the total evaporation of the target area in the preset period is calculated using a spatiotemporal weighted iterative algorithm.

[0120] In one implementation, the Kriging interpolation method is used to spatially downscale the original low-resolution meteorological data. By fitting the semi-variogram of meteorological elements to characterize the spatial autocorrelation structure, the large-scale meteorological data is interpolated and reconstructed into gridded data with the same resolution as the target area using the optimal linear unbiased estimation criterion, thus solving the problem of spatial scale mismatch in meteorological data.

[0121] In one implementation, a sliding window statistical method is used to traverse the gridded meteorological data with a set window length, calculate the deviation coefficient between the meteorological data and the measured observation values ​​within the window, quantify the systematic deviation of the data, and then perform pixel-by-pixel correction on the gridded meteorological data based on the deviation coefficient to eliminate the error introduced by spatial interpolation and form a fused meteorological dataset.

[0122] In one implementation, an evaporation coefficient matrix characterizing the spatial distribution of regional evaporation capacity is constructed by combining underlying surface environmental data such as land use, vegetation cover, and soil texture of the target area. Then, using historical annual evaporation measurement data as constraints, the parameters in the evaporation coefficient matrix are calibrated through an optimization inversion method, so that the calculation results of the evaporation coefficient matrix match the historical actual evaporation conditions, and a calibrated evaporation coefficient matrix that fits the actual situation of the region is obtained.

[0123] In one implementation, a fused meteorological dataset is used as the input driving variable. This dataset is substituted into the calibrated evaporation coefficient matrix. A spatiotemporal weighted iterative algorithm is then used to integrate the temporal variation characteristics of meteorological elements at different times with the differences in evaporation capacity of different underlying surface units. Through iterative updates, the algorithm gradually approximates the true total evaporation, thereby calculating the total evaporation of the target area within a preset period.

[0124] The foregoing has described one embodiment of the present invention in detail, but this content is merely a preferred embodiment and should not be considered as limiting the scope of the present invention. All equivalent variations and modifications made within the scope of the claims of this invention should still fall within the scope of the claims of this invention.

Claims

1. An ecological water level regulation method based on the influence of annual evaporation, characterized in that, The method includes: Acquire monitoring data for the target area; the monitoring data includes water quality data, hydrological data, and environmental data; the hydrological data includes upstream inflow, upstream pollutant concentration, outflow, actual water level, water area, and reservoir capacity; Suitable water level ranges are determined based on historical baseline water level data and historical variation water level data; the historical baseline water level data represents the natural fluctuation of hydrological conditions during periods unaffected by upstream reservoir regulation; the historical variation water level data represents the response changes of hydrological conditions during periods affected by upstream reservoir construction and operation regulation. Based on a preset water level and water quality mapping table, the initial water level range data is determined according to the water quality data. The target water level lower limit is obtained by calculating the water self-purification capacity of the target area based on the hydrological data, and the target water level interval data is obtained by updating the initial water level interval data based on the target water level lower limit. The water level range data is determined based on the comparison results between the suitable water level range data and the target water level range data. Based on the meteorological data for the next preset period, the total evaporation of the target area for that preset period is calculated in combination with the environmental data. The water level interval data is then corrected according to the total evaporation to obtain the actual water level interval data. The gate is then controlled to perform water level regulation operations based on the actual water level interval data.

2. The ecological water level regulation method based on the influence of annual evaporation according to claim 1, characterized in that, The data used to determine suitable water level intervals based on historical baseline water level data and historical variation water level data include: The average water level data for the historical baseline period and the average water level data for the historical change period are calculated by averaging the data respectively to obtain the average water level data for the baseline period and the average water level data for the change period. Hydrological change features are extracted and integrated from the baseline period average water level data and the change period average water level data respectively to obtain water level feature data; Using the average water level data during the baseline period and the average water level data during the change period as benchmark variables, a correlation analysis is performed between the benchmark variables and the water level characteristic data, and effective water level characteristic data is obtained by screening. Effective joint density data is obtained by performing joint distribution modeling on the effective water level characteristic data; the effective joint density data includes base period joint density data and change period joint density data. Hydrological variability data are obtained by performing non-overlapping area integration calculations on the base period joint density data and the change period joint density data. Based on the hydrological variability data, the cumulative probability within the water level range is selected from the baseline period joint density data to obtain suitable water level range data.

3. The ecological water level regulation method based on the influence of annual evaporation according to claim 2, characterized in that, Hydrological variability data are obtained by performing non-overlapping region integration calculations on the base period joint density data and the change period joint density data, including: By calculating hydrological variation degree data; wherein, denotes the hydrological variation degree data corresponding to the i-th hydrological variation feature, denotes the joint density data of the i-th effective water level feature data in the reference period and the reference variable y, denotes the joint density data of the i-th effective water level feature data in the variation period and the reference variable y.

4. The ecological water level regulation method based on the influence of annual evaporation according to claim 1, characterized in that, The process of generating the preset water level and water quality mapping table includes: Obtain historical water quality data that meets the standards, filter the water quality data that meets the preset water quality conditions from the historical water quality data as water quality data that meets the standards, and extract the corresponding water level data to obtain water level data that meets the standards. The water level data and the water quality data that meet the standards are aligned by time to obtain a water level and water quality data sequence; A regression model between water level and water quality data is established based on the water level and water quality data sequence. The upper limit water level data and the lower limit water level data are obtained by solving the water level range that meets the preset water quality conditions through the regression model. A water level change rate sequence is generated based on the historical water level data, and the lower and upper limits of the water level change rate are set using the preset quantiles of the water level change rate sequence to obtain change rate limit data. The upper limit water level data, the lower limit water level data, and the rate of change limit data are jointly constrained to select water level values ​​that simultaneously satisfy the condition that the water level value is between the upper and lower limits and the rate of change of the water level is within the rate of change limit, thus obtaining an effective water level interval. Different preset water quality conditions are associated with the effective water level intervals in the form of a mapping table to obtain a water level and water quality mapping table.

5. The ecological water level regulation method based on the influence of annual evaporation according to claim 1, characterized in that, The target water level lower limit is obtained by calculating the self-purification capacity of the target area based on the hydrological data, including: The total amount of pollutants entering the area is calculated based on the upstream inflow rate and the concentration of pollutants in the upstream water. Calculate the annual outflow volume based on the outflow volume; Establish a functional relationship between the actual water level and the reservoir capacity based on the water area; By calculating the self-purification capacity of the water body in the target area; wherein, for a preset pollutant concentration, is the storage capacity value corresponding to the water level H in the function relationship, is the pollutant degradation coefficient, is the annual outflow. The minimum water level required for the water body to dissipate the current pollutant load is determined based on the water body's self-purification capacity and the total amount of pollutants entering the area, and this is used as the lower limit of the target water level.

6. The ecological water level regulation method based on the influence of annual evaporation according to claim 1, characterized in that, The water level range data is determined based on the comparison results between the suitable water level range data and the target water level range data, including: The upper limit of the suitable water level range data is taken as the first upper limit, and the lower limit is taken as the first lower limit; The upper limit of the target water level range data is used as the second upper limit, and the lower limit is used as the second lower limit; The result is obtained by performing an intersection operation between the suitable water level range data and the target water level range data. If the calculation result has an intersection, the larger value between the first lower limit and the second lower limit is taken as the final lower limit of the water level, and the smaller value between the first upper limit and the second upper limit is taken as the final upper limit of the water level. The water level interval formed by the final lower limit of the water level and the final upper limit of the water level is determined as the water level interval data. If the calculation result is that there is no intersection, an interval conflict warning signal is generated, and the preset safe water level interval data is taken as the water level interval data.

7. The ecological water level regulation method based on the influence of annual evaporation according to claim 1, characterized in that, Based on meteorological data for the next preset period, and in conjunction with the environmental data, the total evaporation of the target area for that preset period is calculated, including: Obtain historical annual evaporation data; The meteorological data is spatially downscaled using the Kriging interpolation method to obtain gridded meteorological data that matches the spatial resolution of the target area. The deviation coefficient of meteorological data is calculated based on the sliding window statistical method, and the deviation is corrected based on the deviation coefficient to obtain a fused meteorological dataset. A regional evaporation coefficient matrix is ​​constructed based on the environmental data of the target area, and a calibrated evaporation coefficient matrix is ​​obtained by calibrating the regional evaporation coefficient matrix based on the historical annual evaporation data. The total evaporation of the target area in the preset period is calculated by substituting the fused meteorological dataset into the calibration evaporation coefficient matrix and using a spatiotemporal weighted iterative algorithm.

8. An ecological water level regulation system based on the influence of annual evaporation, characterized in that, The system includes: The data acquisition module is used to acquire monitoring data of the target area; the monitoring data includes water quality data, hydrological data and environmental data; the hydrological data includes upstream inflow, upstream pollutant concentration, outflow, actual water level, water area and reservoir capacity. The first interval determination module is used to determine suitable water level interval data based on historical baseline water level data and historical change period water level data; the historical baseline water level data represents the natural fluctuation state of the hydrological situation during the period when it is not affected by the regulation of the upstream reservoir; the historical change period water level data represents the response change state of the hydrological situation during the period when it is affected by the construction and operation regulation of the upstream reservoir. The second interval determination module is used to determine the initial water level interval data based on the water quality data according to the preset water level and water quality mapping table. The third interval determination module is used to calculate the water self-purification capacity of the target area based on the hydrological data to obtain the target water level lower limit, and update the initial water level interval data based on the target water level lower limit to obtain the target water level interval data. The fourth interval determination module is used to determine the water level interval data based on the comparison result between the suitable water level interval data and the target water level interval data; The control module is used to calculate the total evaporation of the target area in the preset period based on meteorological data of the next preset period and the environmental data, correct the water level interval data according to the total evaporation to obtain the actual water level interval data, and control the gate to perform water level control operation according to the actual water level interval data.

Images