Intelligent analysis method for basin water balance statistics

Abstract

The invention discloses an intelligent analysis method for basin water balance statistics, and belongs to the technical field of data analysis, and the method comprises the following steps: S1, obtaining the soil parameters of the bottom of a reservoir and the parameters of an aquifer, determining a characteristic aquifer, and calculating the water guide weight of the reservoir; s2, obtaining a water storage regulation index according to the water guide weight of the reservoir and the actual water storage capacity of the historical duration, and obtaining the predicted water storage capacity by using the water storage regulation index; and S3, performing early warning when the predicted water storage capacity is greater than the total storage capacity of the reservoir. According to the method, the water diversion weight and the historical water storage are combined, so that the water storage adjustment index can be dynamically adjusted to adapt to the statistical requirements of the water volume of the reservoir under different conditions, and powerful support is provided for the scheduling and management of the reservoir in the drainage basin.

Description

Technical Field

[0001] The present invention belongs to the technical field of data analysis, and in particular 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 in a river basin. With the increase in the number of reservoirs around the world, more and more hydrological models have begun to consider the impact of various reservoir parameters on hydrological processes, and changes in reservoir water volume have an important impact on the ecosystem of rivers in the basin. However, traditional basin water volume statistics rely on manual observations and simple hydrological models, which have limitations in processing 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 comprises the following steps:

[0005] 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;

[0006] 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;

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

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

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

[0010] 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;

[0011] S14. Calculate the water conductance weight of the reservoir based on the characteristic aquifer.

[0012] The beneficial effects of the above further scheme are: in the present invention, by obtaining the dry bulk density and 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, and the calculation of the sedimentation degree value is helpful to evaluate the sedimentation of the soil at the bottom of the reservoir and understand the compactness 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 aquifer that is most suitable as the characteristic aquifer can be optimized and selected, which has an important impact on the water storage and water conduction capacity of the reservoir.

[0013] Furthermore, in S11, the calculation formula of the soil deposition degree value Q is:

[0014] ; In the formula, ρ max It represents the density of particles corresponding to the maximum particle size in the bottom soil, e represents the index, and m represents the dry bulk density of the bottom soil.

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

[0016] A reservoir's aquifer may consist of multiple layers of varying depth and nature. These aquifers may be composed of different rocks, soils, or sediments with varying permeability, storage capacity, and water quality characteristics.

[0017] Shallow aquifers are located near the surface and are mainly composed of soil and sediments. They are permeable and easily recharged by precipitation and surface water. These aquifers are usually closely related to the leakage and drainage system of the reservoir.

[0018] Intermediate aquifers are located below shallow aquifers and are composed of harder rock or soil with lower permeability but higher water storage capacity. These aquifers may play a role in regulating and storing water during reservoir operation.

[0019] Deep aquifers lie beneath the intermediate aquifers and are usually connected to the groundwater system.

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

[0021] ; 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 soil sedimentation degree value.

[0022] Permeability coefficient, also known as hydraulic conductivity coefficient, refers to the unit water volume under unit hydraulic gradient in an isotropic medium. Water yield refers to the amount of water that can be released from a saturated aquifer under the action of gravity or pressure from a unit volume of aquifer. The water 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 thickness of the aquifer when the water head of the aquifer changes by one unit. The overflow coefficient is a parameter that characterizes the ability of a weak permeable layer to conduct overflow 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 of the water diversion weight C of the reservoir is:

[0024] ; 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.

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

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

[0027] S21. Obtain the actual water storage capacity of the reservoir during the historical period;

[0028] 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;

[0029] S23. According to the water storage regulation index and the actual water storage of the reservoir in the historical period, the predicted water storage of the reservoir is obtained.

[0030] The beneficial effect of the above further scheme is that: in the present invention, the Manning roughness coefficient is used to describe the situation in which 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 capacity of the historical period, the water storage situation of the reservoir in 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 capacity of the reservoir) and the relationship between the actual water storage capacity and the total storage capacity, so as to more comprehensively predict the water storage capacity of the reservoir.

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

[0032] ; 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.

[0033] Furthermore, in S23, the water storage regulation index is averaged with the average of all actual water storage capacities over a historical period to obtain the predicted water storage capacity of the reservoir.

[0034] The beneficial effects of the present invention are as follows: by acquiring detailed soil and aquifer parameters at the bottom of the reservoir, the present invention can more accurately understand the hydrological conditions at the bottom of the reservoir, obtain a water storage regulation index based on the water conduction weight of the reservoir and the actual water storage capacity of the historical period, and use the water storage regulation index to obtain the predicted water storage capacity; by combining the water conduction weight and the historical water storage capacity, the present invention can dynamically adjust the water storage regulation index to adapt to the statistical needs of reservoir water volume under different conditions, and provide strong support for the scheduling and management of reservoirs in the basin. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 The flowchart is a smart analysis method for basin water balance statistics. DETAILED DESCRIPTION

[0036] The embodiments of the present invention will be further described below in conjunction with the accompanying drawings.

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

[0038] 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;

[0039] 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;

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

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

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

[0043] 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;

[0044] S14. Calculate the water conductance weight of the reservoir based on the characteristic aquifer.

[0045] In the present invention, by obtaining the dry bulk density and 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, and the calculation of the sedimentation degree value is helpful to evaluate the sedimentation of the soil at the bottom of the reservoir and understand the compactness 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 aquifer that is most suitable as the characteristic aquifer can be optimized and 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 soil deposition value Q is:

[0047] ; In the formula, ρ max It represents the density of particles corresponding to the maximum particle size in the bottom soil, e represents the index, and m represents the dry bulk density 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] A reservoir's aquifer may consist of multiple layers of varying depth and nature. These aquifers may be composed of different rocks, soils, or sediments with varying permeability, storage capacity, and water quality characteristics.

[0050] Shallow aquifers are located near the surface and are mainly composed of soil and sediments. They are permeable and easily recharged by precipitation and surface water. These aquifers are usually closely related to the leakage and drainage system of the reservoir.

[0051] Intermediate aquifers are located below shallow aquifers and are composed of harder rock or soil with lower permeability but higher water storage capacity. These aquifers may play a role in regulating and storing water during reservoir operation.

[0052] Deep aquifers lie beneath the intermediate aquifers and are 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] ; 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 soil sedimentation degree value.

[0055] Permeability coefficient, also known as hydraulic conductivity coefficient, refers to the unit flow rate under unit hydraulic gradient in an isotropic medium. Water yield refers to the amount of water that can be released from a saturated aquifer per unit volume under the action of gravity or pressure. The water 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 thickness of the aquifer when the water head of the aquifer changes by one unit. The overflow coefficient is a parameter that characterizes the ability of a weak permeable layer to conduct overflow 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 of the water diversion weight C of the reservoir is:

[0057] ; 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.

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

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

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

[0061] 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;

[0062] S23. According to the water storage regulation index and the actual water storage of the reservoir in the historical period, the predicted water storage of the reservoir is obtained.

[0063] In the present invention, the Manning roughness coefficient is used to describe the influence of the roughness of the riverbed or channel wall on the water flow in a river or open channel. By obtaining the actual water storage capacity of the historical period, the water storage conditions of the reservoir in 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 capacity of the reservoir), and the relationship between the actual water storage capacity and the total storage capacity, so as to more comprehensively predict the water storage capacity of the reservoir.

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

[0065] ; 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 that the kth value is less than The actual water storage capacity, H represents the total storage capacity, K represents less than In the present invention, dimension removal can be performed when necessary.

[0066] In the embodiment of the present invention, in S23, the water storage regulation index is multiplied by the average of all actual water storage capacities over a historical period to obtain the predicted water storage capacity of the reservoir.

[0067] Those skilled in the art will appreciate that the embodiments described herein are intended to help readers understand the principles of the present invention, and should be understood that the protection scope of the present invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific variations and combinations that do not deviate from the essence of the present invention based on the technical revelations disclosed by the present invention, and these variations 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.

2. The intelligent analysis method for basin water balance statistics according to claim 1 is characterized in that: 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 conductance weight of the reservoir based on the characteristic aquifer.

3. The intelligent analysis method for basin water balance statistics according to claim 2 is characterized in that: In S11, the calculation formula of the soil deposition value Q is: ; In the formula, ρ max It represents the density of particles corresponding to the maximum particle size in the bottom soil, e represents the index, and m represents the dry bulk density of the bottom soil.

4. The intelligent analysis method for basin water balance statistics according to claim 2 is characterized in that: In the S12, the soil aquifer includes a shallow aquifer, a middle aquifer and a deep aquifer.

5. The intelligent analysis method for basin water balance statistics according to claim 2 is characterized in that: 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 soil sedimentation degree value.

6. The intelligent analysis method for basin water balance statistics according to claim 2 is characterized in that: 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.

7. The intelligent analysis method for basin water balance statistics according to claim 1 is characterized in that: 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. According to the water storage regulation index and the actual water storage of the reservoir in the historical period, the predicted water storage of the reservoir is obtained.

8. The intelligent analysis method for basin water balance statistics according to claim 7 is characterized in that: 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.

9. The intelligent analysis method for basin water balance statistics according to claim 7, 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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