An intelligent analysis method for basin water balance statistics

Abstract

The present invention discloses an intelligent analysis method for basin water balance statistics, belonging to the technical field of data analysis, which includes the following steps: S1. Obtain the soil parameters at the bottom of the reservoir and the parameters of the aquifer, determine the characteristic aquifer, and calculate the water conductivity weight of the reservoir; S2. Obtain the water storage regulation index according to the water conductivity weight of the reservoir and the actual water storage volume in the historical period, and use the water storage regulation index to obtain the predicted water storage volume; S3. Give an early warning when the predicted water storage volume is greater than the total reservoir capacity. By combining the water conductivity weight and the historical water storage volume, the present invention can dynamically adjust the water storage regulation index to meet the water volume statistics requirements of the reservoir under different conditions, and provide strong support for the scheduling and management of the reservoir in the basin.

Description

Technical Field

[0001] The present invention belongs to the technical field of data analysis, and particularly relates to an intelligent analysis method for basin water balance statistics. Background Art

[0002] Reservoirs play an important role in the allocation and management of water resources within a basin. With the increasing number of reservoirs globally, more and more hydrological models have begun to consider the impact of various reservoir parameters on the hydrological process, and the change in reservoir water volume has an important impact on the river ecosystem within the basin. However, traditional basin water volume statistics rely on manual observations and simple hydrological models, and these methods have limitations in dealing with large-scale data and predicting future trends. Summary of the Invention

[0003] In order to solve the above problems, the present invention proposes an intelligent analysis method for basin water balance statistics.

[0004] The technical solution of the present invention is: an intelligent analysis method for basin water balance statistics includes the following steps:

[0005] S1. Obtain the soil parameters at the bottom of the reservoir and the parameters of the aquifer, determine the characteristic aquifer, and calculate the water conductivity weight of the reservoir;

[0006] S2. Obtain the water storage regulation index based on the water conductivity weight of the reservoir and the actual water storage volume over the historical period, and use the water storage regulation index to obtain the predicted water storage volume;

[0007] S3. Issue a warning when the predicted water storage volume is greater than the total reservoir capacity.

[0008] Further, S1 includes the following sub-steps:

[0009] S12. Construct a water storage balance function for the soil according to the sedimentation degree value of the reservoir;

[0010] S13. Substitute each aquifer of the soil at the bottom of the reservoir into the water storage balance function to obtain the aquifer that minimizes the value of the water storage balance function, which is used as the characteristic aquifer;

[0011] S14. Calculate the water conductivity weight of the reservoir according to the characteristic aquifer.

[0012] The beneficial effects of the above further solutions are as follows: In the present invention, by obtaining the dry unit weight and the maximum particle size of the soil at the bottom of the reservoir, a comprehensive understanding of the soil characteristics at the bottom of the reservoir can be established. The calculation of the sedimentation degree value helps to evaluate the sedimentation situation of the soil at the bottom of the reservoir, understand the compactness degree and particle distribution of the soil; by constructing a water storage balance function, the water storage capacity of the soil at the bottom of the reservoir under different conditions can be described; the water storage balance function can be dynamically adjusted according to the actual operation of the reservoir; by calculating the value of the water storage balance function, the most suitable aquifer as the characteristic aquifer can be optimally selected, which has an important impact on the water storage and water conduction capacity of the reservoir.

[0013] Further, in S11, the calculation formula for the sedimentation degree value Q of the soil is:

[0014] ; where ρ max represents the density of the particles corresponding to the maximum particle size in the bottom soil, e represents the exponent, and m represents the dry unit weight of the bottom soil.

[0015] Further, in S12, the aquifer includes a shallow aquifer, a middle aquifer, and a deep aquifer.

[0016] The aquifers of the reservoir may include multiple layers with different depths and properties. These aquifers may be composed of different rocks, soils, or sediments, and have different water permeability, water storage capacity, and water quality characteristics.

[0017] The shallow aquifer is located near the surface and is mainly composed of soil and sediment. It has good water permeability and is easy to receive recharge from precipitation and surface water. These aquifers are usually closely related to the leakage and drainage systems of the reservoir.

[0018] The middle aquifer is located below the shallow aquifer and is composed of relatively hard rocks or soils. It has poor water permeability but strong water storage capacity. These aquifers may play a role in regulating and storing water during the operation of the reservoir.

[0019] The deep aquifer is located below the middle aquifer and is usually connected to the groundwater system.

[0020] Further, in S12, the expression of the water storage balance function S is:

[0021] ; where α 1 represents the hydraulic conductivity of the aquifer, γ 1 represents the weight of the hydraulic conductivity of the aquifer, α 2 represents the specific yield of the aquifer, γ 2 represents the weight of the specific yield of the aquifer, α 3 represents the storage coefficient of the aquifer, γ 3The specific yield weight of the aquifer is denoted as S, the saturated water holding capacity is denoted as β, and the sedimentation degree value of the soil is denoted as Q.

[0022] The hydraulic conductivity, that is, the hydraulic conductivity coefficient, refers to the amount of water per unit under a unit hydraulic gradient in an isotropic medium. The specific yield refers to the amount of water that can be released from a unit volume of a saturated aquifer under the action of gravity or pressure. The storage coefficient represents the amount of water released (or stored) from a column with a bottom area of one unit and a height equal to the aquifer thickness when the aquifer head changes by one unit. The leakage coefficient is a parameter characterizing the ability of a semi-pervious layer to conduct cross-flow water in the vertical direction. The weights of several parameters can be determined using the analytic hierarchy process or the Delphi method.

[0023] Furthermore, in S14, the calculation formula for the water conductivity weight C of the reservoir is:

[0024] ; where s represents the water storage balance value of the characteristic aquifer, and q represents the specific yield of the characteristic aquifer.

[0025] The specific yield refers to the amount of water flowing into the wellbore per unit time when the water level drops by 1 m during a pumping test on the aquifer.

[0026] Furthermore, S2 includes the following sub-steps:

[0027] S21: Obtain the actual water storage volume of the reservoir over the historical period;

[0028] S22: Calculate the water storage regulation index based on the Manning roughness coefficient of the reservoir, the water conductivity weight, and the relationship between the actual water storage volume and the total storage capacity during the historical period;

[0029] S23: Obtain the predicted water storage volume of the reservoir based on the water storage regulation index and the actual water storage volume of the reservoir over the historical period.

[0030] The beneficial effects of the above further solution are: In the present invention, the Manning roughness coefficient is used to describe the situation where the water flow in a river or open channel is affected by the roughness of the riverbed or channel wall. By obtaining the actual water storage volume over the historical period, the water storage situation of the reservoir at different time periods can be understood, providing data support for subsequent water storage regulation and prediction; the present invention also comprehensively considers multiple factors, including the Manning roughness coefficient (a parameter reflecting the water flow resistance), the water conductivity weight (a parameter reflecting the water conductivity ability of the reservoir), and the relationship between the actual water storage volume and the total storage capacity, so as to be able to more comprehensively predict the water storage capacity of the reservoir.

[0031] Furthermore, in S22, the calculation formula for the water storage regulation index g is:

[0032] ; where n represents the Manning roughness coefficient of the reservoir, C represents the water conductivity weight of the reservoir, Yk represent the k-th actual water storage volume less than in the historical time period, H represents the total reservoir capacity, and K represents the number of actual water storage volumes less than in the historical time period.

[0033] Further, in S23, the water storage regulation index is averaged with the average value of all actual water storage volumes in the historical time period to obtain the predicted water storage volume of the reservoir.

[0034] The beneficial effects of the present invention are as follows: By obtaining the detailed soil and aquifer parameters at the bottom of the reservoir, the present invention can more accurately understand the hydrogeological conditions at the bottom of the reservoir. Based on the water conduction weight of the reservoir and the actual water storage volume in the historical time period, the water storage regulation index is obtained, and the predicted water storage volume is obtained by using the water storage regulation index. By combining the water conduction weight and the historical water storage volume, the present invention can dynamically adjust the water storage regulation index to meet the requirements of reservoir water volume statistics under different conditions, providing strong support for the scheduling and management of reservoirs in the basin. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 is a flowchart of an intelligent analysis method for basin water balance statistics. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0036] The embodiments of the present invention will be further described below with reference to the drawings.

[0037] As Figure 1 shown, the present invention provides an intelligent analysis method for basin water balance statistics, including the following steps:

[0038] S1. Obtain the soil parameters at the bottom of the reservoir and the parameters of the aquifer, determine the characteristic aquifer, and calculate the water conduction weight of the reservoir;

[0039] S2. Based on the water conduction weight of the reservoir and the actual water storage volume in the historical time period, obtain the water storage regulation index, and obtain the predicted water storage volume by using the water storage regulation index;

[0040] S3. Issue a warning when the predicted water storage volume is greater than the total reservoir capacity.

[0041] In the embodiments of the present invention, S1 includes the following sub-steps:

[0042] S12. Construct a water storage balance function for the soil according to the sedimentation degree value of the reservoir;

[0043] S13. Substitute each aquifer of the soil at the bottom of the reservoir into the water storage balance function to obtain the aquifer that minimizes the value of the water storage balance function as the characteristic aquifer;

[0044] S14. Calculate the water conduction weight of the reservoir according to the characteristic aquifer.

[0045] In the present invention, by obtaining the dry unit weight and the maximum particle size of the reservoir bottom soil, a comprehensive understanding of the characteristics of the reservoir bottom soil can be established. The calculation of the sedimentation degree value helps to evaluate the sedimentation situation of the reservoir bottom soil, understand the compactness and particle distribution of the soil; by constructing a water storage balance function, the water storage capacity of the reservoir bottom soil under different conditions can be described; the water storage balance function can be dynamically adjusted according to the actual operation of the reservoir; by calculating the water storage balance function value, the most suitable aquifer as the characteristic aquifer can be optimally selected, which has an important impact on the water storage and water conduction capacity of the reservoir.

[0046] In the embodiment of the present invention, in S11, the calculation formula of the sedimentation degree value Q of the soil is:

[0047] ; where ρ max represents the density of the particles corresponding to the maximum particle size in the bottom soil, e represents the exponent, and m represents the dry unit weight of the bottom soil.

[0048] In the embodiment of the present invention, in S12, the aquifer includes a shallow aquifer, a middle aquifer, and a deep aquifer.

[0049] The aquifers of the reservoir may include multiple layers with different depths and properties. These aquifers may be composed of different rocks, soils, or sediments, and have different water permeability, water storage capacity, and water quality characteristics.

[0050] The shallow aquifer is located near the surface, mainly composed of soil and sediment, with good water permeability and is easy to receive recharge from precipitation and surface water. These aquifers are usually closely related to the leakage and drainage systems of the reservoir.

[0051] The middle aquifer is located below the shallow aquifer, composed of relatively hard rocks or soils, with poor water permeability but strong water storage capacity. These aquifers may play a role in regulating and storing water during the operation of the reservoir.

[0052] The deep aquifer is located below the middle aquifer and is usually connected to the groundwater system.

[0053] In the embodiment of the present invention, in S12, the expression of the water storage balance function S is:

[0054] ; where α 1 represents the permeability coefficient of the aquifer, γ 1 represents the permeability coefficient weight of the aquifer, α 2 represents the specific yield of the aquifer, γ 2 represents the specific yield weight of the aquifer, α 3 represents the storage coefficient of the aquifer, γ 3The storage coefficient weight representing the aquifer is β, the saturated water holding capacity is β, and the sedimentation degree value of the soil is Q.

[0055] The permeability coefficient, that is, the hydraulic conductivity, refers to the unit flow rate under a unit hydraulic gradient in an isotropic medium. The specific yield refers to the amount of water that can be released from a unit volume of a saturated aquifer under the action of gravity or pressure. The storage coefficient represents the amount of water released (or stored) from a column with a bottom area of one unit and a height equal to the aquifer thickness when the aquifer head changes by one unit. The leakage coefficient is a parameter characterizing the ability of a semi-pervious layer to conduct cross-flow water in the vertical direction. The weights of several parameters can be determined using the analytic hierarchy process or the Delphi method.

[0056] In the embodiment of the present invention, in S14, the calculation formula for the water conduction weight C of the reservoir is:

[0057] ; where s represents the storage balance value of the characteristic aquifer, and q represents the specific yield of the characteristic aquifer.

[0058] The specific yield refers to the amount of water flowing into the wellbore per unit time when the water level drops by 1 m during a pumping test of the aquifer.

[0059] In the embodiment of the present invention, S2 includes the following sub-steps:

[0060] S21. Obtain the actual water storage volume of the reservoir during the historical period;

[0061] S22. Calculate the water storage regulation index according to the Manning roughness coefficient of the reservoir, the water conduction weight, and the relationship between the actual water storage volume and the total storage capacity during the historical period;

[0062] S23. Obtain the predicted water storage volume of the reservoir according to the water storage regulation index and the actual water storage volume of the reservoir during the historical period.

[0063] In the present invention, the Manning roughness coefficient is used to describe the situation where the water flow in a river or open channel is affected by the roughness of the riverbed or channel wall. By obtaining the actual water storage volume during the historical period, the water storage situation of the reservoir at different time periods can be understood, providing data support for subsequent water storage regulation and prediction; the present invention also comprehensively considers multiple factors, including the Manning roughness coefficient (a parameter reflecting the water flow resistance), the water conduction weight (a parameter reflecting the water conduction ability of the reservoir), and the relationship between the actual water storage volume and the total storage capacity, so as to be able to more comprehensively predict the water storage capacity of the reservoir.

[0064] In the embodiment of the present invention, in S22, the calculation formula for the water storage regulation index g is:

[0065] ; where n represents the Manning roughness coefficient of the reservoir, C represents the water conduction weight of the reservoir, Yk denotes the k-th actual water storage volume less than , H denotes the total storage capacity, and K denotes the number of actual water storage volumes less than . In the present invention, dimensionality reduction processing can be performed when necessary.

[0066] In an embodiment of the present invention, in S23, the water storage regulation index is multiplied by the average value of all actual water storage volumes over the historical duration to obtain the predicted water storage volume of the reservoir.

[0067] Those of ordinary skill in the art will realize that the embodiments described herein are for helping readers understand the principles of the present invention, and it should be understood that the protection scope of the present invention is not limited to such specific statements and embodiments. Those of ordinary skill in the art can make various other specific deformations and combinations that do not depart from the essence of the present invention based on these technical revelations disclosed in the present invention, and these deformations and combinations are still within the protection scope of the present invention.

Claims

1. An intelligent analysis method for basin water balance statistics, characterized in that: The following steps are involved: S1. Obtain soil parameters at the bottom of the reservoir and parameters of the aquifer, determine the characteristic aquifer, and calculate the water conduction weight of the reservoir; S2. According to the water diversion weight of the reservoir and the actual water storage capacity of the historical period, a water storage regulation index is obtained, and the predicted water storage capacity is obtained using the water storage regulation index; S3. Issue an early warning when the predicted water storage volume is greater than the total storage capacity of the reservoir; The S1 comprises the following sub-steps: S11, obtaining the dry bulk density of the soil at the bottom of the reservoir and the maximum particle size of the particles contained in the soil at the bottom, and calculating the sedimentation degree value of the reservoir; S12, constructing a water storage balance function for the soil according to the sedimentation degree value of the reservoir; S13, substituting each aquifer of the soil at the bottom of the reservoir into the water storage balance function, and obtaining the aquifer that minimizes the value of the water storage balance function as the characteristic aquifer; S14. Calculate the water conduction weight of the reservoir according to the characteristic aquifer; In S11, the calculation formula of the soil deposition value Q is: ; In the formula, ρ max It represents the density of the particles corresponding to the largest particle size in the bottom soil, e represents the index, and m represents the dry bulk density of the bottom soil; In S12, the soil aquifer includes a shallow aquifer, a middle aquifer and a deep aquifer; In S12, the expression of the water storage balance function S is: ; In the formula, α1 represents the permeability coefficient of the aquifer, γ1 represents the permeability coefficient weight of the aquifer, α2 represents the water supply degree of the aquifer, γ2 represents the water supply degree weight of the aquifer, α3 represents the water storage coefficient of the aquifer, γ3 represents the water storage coefficient weight of the aquifer, β represents the saturated water holding capacity, and Q represents the sedimentation degree value of the soil; In S14, the calculation formula of the water diversion weight C of the reservoir is: ; In the formula, s represents the water storage balance value of the characteristic aquifer, and q represents the unit water yield of the characteristic aquifer; The S2 comprises the following sub-steps: S21. Obtain the actual water storage capacity of the reservoir during the historical period; S22. Calculate the water storage regulation index based on the Manning roughness coefficient of the reservoir, the water diversion weight, and the relationship between the actual water storage and the total storage capacity in the historical period; S23, obtaining the predicted water storage capacity of the reservoir according to the water storage regulation index and the actual water storage capacity of the reservoir in the historical period; In S22, the calculation formula of the water storage regulation index g is: ; In the formula, n represents the Manning roughness coefficient of the reservoir, C represents the water conduction weight of the reservoir, and Y k Indicates the kth time in the history that is less than The actual water storage capacity, H represents the total storage capacity, and K represents the historical length of time less than The actual water storage capacity.

2. The intelligent analysis method for basin water balance statistics according to claim 1 is characterized in that: In S23, the water storage regulation index and the average of all actual water storage capacities over a historical period are averaged to obtain the predicted water storage capacity of the reservoir.

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