A gis-based optimal selection calculation method for reservoir dam sites and reservoir capacity

Abstract

This invention discloses a GIS-based method for calculating the optimal selection of reservoir dam sites and storage capacity. The method includes: acquiring and preprocessing DEM data and river vector data of the target area; setting an initial dam site and adjusting its axis to be perpendicular to the river channel using a directional model; calculating the storage capacity and inundation range of the dam site at different water levels; constructing and applying a dam site translation function to automatically and systematically generate a series of candidate dam site sequences along the upstream direction of the river; batch calculating the storage capacity and inundation range of all candidate dam sites at various water levels to form a quantitative decision matrix; finally, based on the calculated data, with "maximum storage capacity and minimum inundation" and "maximum storage capacity-to-inundation ratio" as optimization objectives, automatically selecting the storage capacity priority scheme and the comprehensive optimal scheme. This invention achieves objective and systematic search and multi-objective quantitative optimization of dam site selection, effectively overcoming the subjectivity and limitations of traditional empirical methods, and significantly improving the scientific nature and decision-making quality of reservoir planning.

Description

Technical Field

[0001] This invention relates to the field of reservoir dam site and scale optimization selection technology in water conservancy projects, specifically a calculation method for optimal selection of reservoir dam site and reservoir capacity based on Git. Background Technology

[0002] As a core component of the water conservancy system, reservoirs are key infrastructure for ensuring regional water resource security and promoting sustainable economic and social development. Their construction and operation play an irreplaceable comprehensive role in flood control and disaster reduction, urban and rural water supply, agricultural irrigation, clean energy supply, and ecological environment improvement. However, the full realization of the benefits of reservoir projects depends heavily on the scientific and accurate planning in the early stages. Reservoir planning is essentially a complex system engineering project with multiple objectives and constraints. Its core challenge lies in how to achieve a scientific balance and optimized decision-making among multiple objectives such as reservoir capacity, project safety, economic benefits, social impact, and ecological protection.

[0003] Traditional methods for selecting dam sites and determining reservoir capacity primarily rely on engineers' experience and judgment. In practice, engineers typically use a Geographic Information System (GIS) platform, combined with qualitative analysis of the target area's topography, river systems, hydrological characteristics, and preliminary geological conditions, to subjectively select one or more suitable dam sites. Subsequently, for the selected dam sites, the GIS's hydrological analysis tools are used to simulate the reservoir's inundation range under different design water levels, and the corresponding reservoir capacity is estimated accordingly. While this method utilizes spatial information technology to some extent, its decision-making process still has significant limitations: First, the initial screening of dam sites relies too heavily on personal experience, lacking a systematic and objective search mechanism, and easily overlooking potential dam sites with better topography and hydropower conditions. Second, the assessment of reservoir capacity and inundation range is usually conducted only at a few pre-set points, failing to achieve continuous and automated scheme comparison along the river channel. Finally, planning decisions often focus on a single objective, making it difficult to systematically quantify and balance the sharp contradiction between reservoir capacity benefits and inundation losses, the latter being the focus of the current social and environmental challenges in reservoir construction, including resettlement of displaced persons and ecological compensation.

[0004] Furthermore, against the backdrop of global climate change, the frequency and uncertainty of extreme hydrological events are increasing, placing higher demands on the robustness and adaptability of reservoir design. Traditional planning methods based on limited locations and subjective experience are no longer sufficient to meet the scientific, systematic, and forward-looking needs of modern water conservancy projects. Therefore, there is an urgent need to develop a method for selecting reservoir dam sites and storage capacities that can automatically search, quantitatively evaluate, and optimize multiple objectives. This would improve the objectivity, systematicness, and decision-making quality of planning work from a technical perspective, and provide reliable tools to support the scientific planning of reservoirs in complex environments. Summary of the Invention

[0005] To address the problems of existing methods for reservoir dam site selection and capacity determination relying on subjective experience, lacking systematicity, and being difficult to achieve multi-objective optimization trade-offs, this invention proposes a Git-based calculation method for optimal selection of reservoir dam site and capacity. The aim is to achieve objective and systematic search and evaluation of dam sites through automated spatial analysis and multi-scheme iterative calculation.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a method for calculating the optimal selection of reservoir dam site and reservoir capacity based on Git, comprising the following steps:

[0007] Step S1: Obtain Geographic Information System (GIS) driving data, which includes the Digital Elevation Model (DEM), complete vector line features of the river where the reservoir is located, and the initial dam site location X1. Input the GIS driving data into the GIS model.

[0008] Step S2: Fill depressions in the terrain digital elevation model (DEM) and smooth the complete vector line features of the river where the reservoir is located;

[0009] Step S3: Set the initial dam site location X1 as the river confluence, and use the orientation model to adjust the orientation of the initial dam site location X1 so that the orientation of the initial dam site location X1 is perpendicular to the river channel orientation;

[0010] Step S4: Set the first initial water level y11 and the first highest water level y1m corresponding to the initial dam site location X1; start the Gis model and calculate the first reservoir capacity [V11, V1m] and the first inundation range [S11, S1m] corresponding to the first initial water level y11 to the first highest water level y1m at the initial dam site location X1.

[0011] Step S5: Based on the translation function, translate the current dam site location along the river direction to obtain the new dam site location;

[0012] Step S6: Repeat step S6 to obtain a series of dam site locations X2, X3, ..., Xn in sequence, where X2 is the second new dam site location, X3 is the third new dam site location, and Xn is the nth new dam site location.

[0013] Step S7: Set the corresponding nth initial water level yn1 and nth highest water level ynm for the nth new dam site location Xn; for the nth new dam site location Xn, start the Gis model to calculate the nth reservoir capacity [Vn1, Vnm] and the nth inundation range [Sn1, Snm] between the nth initial water level yn1 and the nth highest water level ynm;

[0014] Step S8: Based on the calculated total reservoir capacity V1 to Vn and the inundation range S1 to Sn, determine two optimal dam site locations Xp1 and Xp2, where: Xp1 is the dam site location with the smallest inundation range under the condition of the largest reservoir capacity, and Xp2 is the dam site location with the largest ratio of reservoir capacity to inundation range.

[0015] Step S9: Output the dam site location Xp1 with the smallest inundation range under the condition of maximum reservoir capacity and its corresponding optimal reservoir capacity, and the dam site location Xp2 with the largest ratio of reservoir capacity to inundation range and its corresponding optimal reservoir capacity.

[0016] Furthermore, in step S2, an adaptive smoothing model is used to smooth the complete vector line features of the river where the reservoir is located, and the smoothing range covers the entire section from the river's source to its confluence.

[0017] Furthermore, the formula for calculating the overall smoothness judgment value of the adaptive smoothing model is as follows:

[0018] ;

[0019] Where S(i) is the overall smoothness judgment value, For the corresponding weighting coefficients, A(i) is the rate of change of angle. For the corresponding weighting coefficients, C(i) is the curvature anomaly component. For the corresponding weighting coefficients, D(i) represents the context discontinuity component; when S(i) > 0.75, the complete vector line features of the river where the reservoir is located are smoothed, while other values ​​remain unchanged.

[0020] The formula for calculating the rate of change of angle is:

[0021] ;

[0022] in, The current inflection point The interior angle at that point, It is a straight angle. The angle weighting factor is calculated using the following formula: ;

[0023] The formula for calculating the curvature anomaly component is:

[0024] ;

[0025] in, For the current point The discrete curvature at a given point is calculated using the following formula: ;

[0026] The average curvature within the local window is calculated using the following formula: ;

[0027] For the local curvature standard deviation, This is the steepness parameter of the Sigmoid function. The curvature anomaly threshold, The coordinates of the current inflection point;

[0028] The formula for calculating the context discontinuity component is:

[0029] ;

[0030] in, Fit a straight line to the context using points arrive Linear regression yielded the result; Let be the distance from the point to the line. To prevent division by zero of small constants;

[0031] The trend discontinuity factor is calculated using the following formula: ;

[0032] This represents the current line segment direction angle. The overall orientation angle for the context.

[0033] Furthermore, in step S3, the orientation of the initial dam site X1 is adjusted using the orientation model, specifically through a vertical constraint function. This vertical constraint function is used to make the dam axis more perpendicular to the river channel orientation; specifically:

[0034] ;

[0035] in, For vertical constraint functions, The cosine function is a trigonometric function. This is the tolerance coefficient for deviation. This is the actual angle between the axis of the new dam and the direction of the river channel.

[0036] Further, in step S4, the first initial water level y11 and the first highest water level y1m corresponding to the initial dam site location X1 are set; the Gis model is started to calculate the first reservoir capacity [V11, V1m] and the first inundation range [S11, S1m] corresponding to the distance from the first initial water level y11 to the first highest water level y1m at the initial dam site location X1; specifically:

[0037] Step S41: After selecting the initial dam site location X1, the reservoir planning calculation module of the Gis model is used to calculate the corresponding first reservoir capacity V11 based on the input first initial water level y11, and then calculate the second reservoir capacity V12 corresponding to the second initial water level y12, until the m-th reservoir capacity V1m corresponding to the m-th initial water level y1m is calculated.

[0038] Step S42: Calculate the reservoir capacity and inundation range at different water levels using the Gis model's reservoir planning calculation module; the difference between adjacent calculated water levels is set to 1 unit, as shown in the following formula:

[0039] y1m = y11 + (m - 1);

[0040] Where y1m is the first highest water level, m is the number of water levels, and y11 is the first starting water level; y1m≤Max(DEMX1), that is, the highest water level must be less than or equal to the elevation value of the maximum topographic digital elevation model (DEM) where the dam site is located.

[0041] Furthermore, the translation function f(x, y, z) in step S5 is a weighted combination of the vertical constraint function f1(x, y, z) and the translation distance function f2(x, z), and the calculation formula is as follows:

[0042] ;

[0043] in, These are the weighting coefficients of the level function. Let be the weight coefficients of the vertical function, and , The position corresponding to the translation function f(x, y, z) is selected as the new dam site.

[0044] Furthermore, the formula for calculating the translation distance function f2(x, z) is:

[0045] ;

[0046] in, This is a function to find the maximum value, specifically, to take the maximum value of the sequence of values ​​within the parentheses. This represents the actual translation distance from the original dam site to the new dam site. The preset distance threshold ranges from 0.5 to 2 kilometers.

[0047] Compared with the prior art, the present invention has the following beneficial effects:

[0048] This invention achieves objectivity and systematization in dam site selection, improving the comprehensiveness and optimality of the proposed solutions. Traditional methods rely on engineers' experience to make subjective preliminary selections at limited locations, easily overlooking potential dam sites with better topography, minimal inundation loss, and superior hydropower conditions. This invention establishes a mechanism that automatically and continuously generates a sequence of candidate dam sites starting from the river confluence and moving upstream along the river channel by constructing a data-driven dam site translation function. This method achieves a systematic and comprehensive search for possible dam site locations within the target river section, fundamentally avoiding the problem of overlooking potential optimal solutions due to limitations in human experience, and ensuring the scientific rigor and comprehensiveness of the optimization results.

[0049] This invention improves the computational efficiency and accuracy of reservoir capacity and inundation analysis, providing massive quantitative data support for decision-making. Traditional methods require manual settings and individual calculations for each candidate dam site, resulting in low efficiency and a large workload. This invention combines initial settings with automatic translation and batch calculation, leveraging the powerful spatial analysis capabilities of the Gis model to calculate the reservoir capacity and inundation range of dozens or even hundreds of candidate dam sites at different design water levels in a single operation. This significantly improves analysis efficiency and generates a detailed quantitative decision matrix covering the "location-water level" two-dimensional space, providing an unprecedented and refined data foundation for subsequent optimization decisions.

[0050] This invention innovatively introduces and quantifies core optimization indicators for reservoir capacity and inundation range, achieving a scientific balance between engineering benefits and social and environmental costs. It transcends the traditional single-objective optimization model that merely pursues maximum capacity or minimum investment, explicitly incorporating inundation loss—a crucial social and environmental cost—into the core decision-making framework. By defining and maximizing the capacity-to-inundation ratio, this invention can automatically identify the comprehensive optimal dam site scheme Xp2 that, under given technical conditions, achieves maximum capacity benefit per unit inundation cost. This provides decision-makers with a quantitative tool, enabling them to make precise and visual trade-offs between engineering benefits and inundation costs, effectively addressing the most sensitive and complex contradictions in modern reservoir planning, and making planning schemes more socially acceptable and environmentally friendly.

[0051] This invention provides multi-dimensional optimization results, enhancing the flexibility and relevance of decision-making. Instead of outputting a single optimal solution, it simultaneously offers two representative optimization results: a reservoir capacity priority scheme Xp1 and a comprehensive optimal scheme Xp2. Xp1 meets the engineering requirements prioritizing reservoir capacity benefits for water storage and power generation; Xp2 represents the optimal balance point for comprehensive benefits. This dual-objective output provides decision-makers with clear comparison anchors, enabling more targeted final decisions based on specific policy orientations, investment constraints, and social environmental sensitivity, greatly enhancing the adaptability of planning schemes and the flexibility of decision-making.

[0052] The method has a clear process and a high degree of automation, making it highly practical for engineering applications and worthy of promotion. The DEM and river vector data relied upon by this invention are common data in the field of geographic information, and the core functions called for filling depressions and calculating reservoir volume are standard or extended modules of mature GIS platforms. Therefore, this invention can be easily integrated into existing water conservancy engineering planning and design platforms or workflows, significantly improving the automation level and scientific decision-making ability of planning work, and has broad engineering application prospects and important promotional value. Attached Figure Description

[0053] Figure 1 This is a flowchart of the steps of the present invention;

[0054] Figure 2 This is a flowchart illustrating the steps of the present invention. Detailed Implementation

[0055] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that the following embodiments are only used to explain the invention and are not intended to limit the scope of the invention.

[0056] like Figures 1 to 2 As shown, this embodiment proposes the following technical solution: a method for calculating the optimal selection of reservoir dam site and reservoir capacity based on Git, which includes the following steps:

[0057] Step S1: Obtain Geographic Information System (GIS) driving data, which includes the Digital Elevation Model (DEM), complete vector line features of the river where the reservoir is located, and the initial dam site location X1. Input the GIS driving data into the GIS model.

[0058] Step S2: Fill depressions in the terrain digital elevation model (DEM) and smooth the complete vector line features of the river where the reservoir is located;

[0059] Step S3: Set the initial dam site location X1 as the river confluence, and use the orientation model to adjust the orientation of the initial dam site location X1 so that the orientation of the initial dam site location X1 is perpendicular to the river channel orientation;

[0060] Step S4: Set the first initial water level y11 and the first highest water level y1m corresponding to the initial dam site location X1; start the Gis model and calculate the first reservoir capacity [V11, V1m] and the first inundation range [S11, S1m] corresponding to the first initial water level y11 to the first highest water level y1m at the initial dam site location X1.

[0061] Step S5: Based on the translation function, translate the current dam site location along the river direction to obtain the new dam site location;

[0062] Step S6: Repeat step S6 to obtain a series of dam site locations X2, X3, ..., Xn in sequence, where X2 is the second new dam site location, X3 is the third new dam site location, and Xn is the nth new dam site location.

[0063] Step S7: Set the corresponding nth initial water level yn1 and nth highest water level ynm for the nth new dam site location Xn; for the nth new dam site location Xn, start the Gis model to calculate the nth reservoir capacity [Vn1, Vnm] and the nth inundation range [Sn1, Snm] between the nth initial water level yn1 and the nth highest water level ynm;

[0064] Step S8: Based on the calculated total reservoir capacity V1 to Vn and the inundation range S1 to Sn, determine two optimal dam site locations Xp1 and Xp2, where: Xp1 is the dam site location with the smallest inundation range under the condition of the largest reservoir capacity, and Xp2 is the dam site location with the largest ratio of reservoir capacity to inundation range.

[0065] Step S9: Output the dam site location Xp1 with the smallest inundation range under the condition of maximum reservoir capacity and its corresponding optimal reservoir capacity, and the dam site location Xp2 with the largest ratio of reservoir capacity to inundation range and its corresponding optimal reservoir capacity.

[0066] Furthermore, in step S2, an adaptive smoothing model is used to smooth the complete vector line features of the river where the reservoir is located, and the smoothing range covers the entire section from the river's source to its confluence.

[0067] Furthermore, the formula for calculating the overall smoothness judgment value of the adaptive smoothing model is as follows:

[0068] ;

[0069] Where S(i) is the overall smoothness judgment value, For the corresponding weighting coefficients, A(i) is the rate of change of angle. For the corresponding weighting coefficients, C(i) is the curvature anomaly component. For the corresponding weighting coefficients, D(i) represents the context discontinuity component; when S(i) > 0.75, the complete vector line features of the river where the reservoir is located are smoothed, while other values ​​remain unchanged.

[0070] The formula for calculating the rate of change of angle is:

[0071] ;

[0072] in, The current inflection point The interior angle at that point, It is a straight angle. The angle weighting factor is calculated using the following formula: ;

[0073] The formula for calculating the curvature anomaly component is:

[0074] ;

[0075] in, For the current point The discrete curvature at a given point is calculated using the following formula: ;

[0076] The average curvature within the local window is calculated using the following formula: ;

[0077] For the local curvature standard deviation, This is the steepness parameter of the Sigmoid function. The curvature anomaly threshold, The coordinates of the current inflection point;

[0078] The formula for calculating the context discontinuity component is:

[0079] ;

[0080] in, Fit a straight line to the context using points arrive Linear regression yielded the result; Let be the distance from the point to the line. To prevent division by zero of small constants;

[0081] The trend discontinuity factor is calculated using the following formula: ;

[0082] This represents the current line segment direction angle. The overall orientation angle for the context.

[0083] Furthermore, in step S3, the orientation of the initial dam site X1 is adjusted using the orientation model, specifically through a vertical constraint function. This vertical constraint function is used to make the dam axis more perpendicular to the river channel orientation; specifically:

[0084] ;

[0085] in, For vertical constraint functions, The cosine function is a trigonometric function. This is the tolerance coefficient for deviation. This is the actual angle between the axis of the new dam and the direction of the river channel.

[0086] Further, in step S4, the first initial water level y11 and the first highest water level y1m corresponding to the initial dam site location X1 are set; the Gis model is started to calculate the first reservoir capacity [V11, V1m] and the first inundation range [S11, S1m] corresponding to the distance from the first initial water level y11 to the first highest water level y1m at the initial dam site location X1; specifically:

[0087] Step S41: After selecting the initial dam site location X1, the reservoir planning calculation module of the Gis model is used to calculate the corresponding first reservoir capacity V11 based on the input first initial water level y11, and then calculate the second reservoir capacity V12 corresponding to the second initial water level y12, until the m-th reservoir capacity V1m corresponding to the m-th initial water level y1m is calculated.

[0088] Step S42: Calculate the reservoir capacity and inundation range at different water levels using the Gis model's reservoir planning calculation module; the difference between adjacent calculated water levels is set to 1 unit, as shown in the following formula:

[0089] y1m = y11 + (m - 1);

[0090] Where y1m is the first highest water level, m is the number of water levels, and y11 is the first starting water level. For example, the starting water level y11 = 100 meters and the ending water level y1m = 120 meters; y1m ≤ Max(DEMX1), that is, the highest water level must be less than or equal to the elevation value of the largest topographic digital elevation model (DEM) where the dam site is located.

[0091] Furthermore, the translation function f(x, y, z) in step S5 is a weighted combination of the vertical constraint function f1(x, y, z) and the translation distance function f2(x, z), and the calculation formula is as follows:

[0092] ;

[0093] in, These are the weighting coefficients of the level function. Let be the weight coefficients of the vertical function, and , Select The corresponding location will be used as the new dam site.

[0094] Furthermore, the formula for calculating the translation distance function f2(x, z) is:

[0095] ;

[0096] in, This is a function to find the maximum value, specifically, to take the maximum value of the sequence of values ​​within the parentheses. This represents the actual translation distance from the original dam site to the new dam site. The preset distance threshold ranges from 0.5 to 2 kilometers.

[0097] Furthermore, in step S1, the raster resolution of the terrain DEM data is between 8 meters and 30 meters; the river line features are continuous linear features that match the actual river location; the initial dam site features are line features with a length set to 1.3 to 1.5 times the corresponding river width; and the coordinate system of all input data is a projected coordinate system.

[0098] Furthermore, in step S9, the reservoir planning calculation module of the Gis model is used to calculate the reservoir capacity and inundation range at different water levels; the difference between adjacent calculated water levels is set to 1 unit.

[0099] Preferably, the smoothing of river line elements adopts an adaptive smoothing model. This model makes a comprehensive judgment based on the rate of change of angle, curvature anomaly, and contextual discontinuity at the river inflection point, and only smooths the local areas with excessively high irregularity, so as to eliminate digital noise while maintaining the overall characteristics of the river's natural morphology.

[0100] Preferably, the dam site translation function f(x, y, z) is composed of a linear weighted sub-function f1(x, y, z) of vertical constraint and a sub-function f2(x, z) of translation distance; wherein f1 is used to ensure that the direction of the new dam site axis is perpendicular to the river channel; f2 is used to constrain the translation distance within a preset reasonable threshold range; by setting weighting coefficients and setting the effective range of the total function value, such as [7,10], feasible new dam site locations that simultaneously satisfy the direction and distance constraints are selected.

[0101] Preferably, the initial dam site location is defined as a line element, and its length is dynamically set to 1.3 to 1.5 times the width of the river at the location to ensure that the dam model has a reasonable spatial scale.

[0102] Example 1: Data preparation and preprocessing steps: Obtain geographic information system driven data for the reservoir planning area, including digital elevation model (DEM), river line features, and an initially set dam site feature X1; perform depression filling processing on the DEM data to eliminate data depressions, and perform smoothing processing on the river line features to improve the accuracy of subsequent analysis; all input data must be unified into a projected coordinate system.

[0103] Initial calculation steps: Set the initial dam site location X1 at the river confluence and adjust the dam site line direction using the directional model to make it basically perpendicular to the local river channel direction; set an initial water level y11 and a maximum water level y1m for dam site X1; start the reservoir planning calculation module of the Gis model to calculate the reservoir capacity sequence [V11, V1m] and its inundation range sequence [S11, S1m] corresponding to a series of different water levels from y11 to y1m at dam site X1.

[0104] Automatic Dam Site Search Steps: Based on a preset translation function, the previous dam site location is used as a basis for spatial translation along the upstream or downstream direction of the river to automatically generate a new candidate dam site location X2. The translation function comprehensively considers the vertical relationship constraint between the dam site and the river channel as well as a reasonable translation distance range to ensure the engineering rationality and spatial continuity of the new dam site. This translation process is repeated to generate a series of candidate dam site locations X2, X3, ..., Xn in sequence.

[0105] Multi-scheme batch calculation steps: Set the corresponding water level calculation range for each newly generated dam site Xn, which is from the initial water level yn1 to the highest water level ynm; For each dam site Xn, restart the Gis model and batch calculate the reservoir capacity sequence [Vn1, Vnm] and inundation range sequence [Sn1, Snm] at different water levels [yn1, ynm].

[0106] Multi-objective optimization decision-making steps: Summarize the reservoir capacity and inundation area calculation results of all candidate dam sites X1 to Xn under different water levels; based on this dataset, automatically select the optimal dam site according to the following two optimization objectives:

[0107] Maximum reservoir capacity - minimum inundation dam site Xp1: Among all calculated schemes, select the dam site that can achieve the maximum reservoir capacity. If there are multiple options, select the scheme with the smallest inundation area.

[0108] Optimal dam site with the highest reservoir capacity-to-inundation ratio Xp2: Calculate the ratio V / S of the reservoir capacity V to the inundation area S for all schemes, and select the dam site with the highest ratio as the scheme with the best overall benefits.

[0109] Output steps: Output the spatial location information of the two optimal dam sites Xp1 and Xp2, and their corresponding recommended design water level and reservoir capacity values.

[0110] Example 2: The core of this invention lies in providing an automated, systematic, and quantitatively balanced method for optimizing reservoir dam sites and storage capacity; the following describes the implementation steps of this invention in detail, using a typical watershed reservoir planning scenario.

[0111] Take a medium-sized reservoir planned for a river in a mountainous area as an example;

[0112] Step 1: Data preparation and input;

[0113] Obtain digital elevation model (DEM) data of the target watershed; this embodiment uses raster DEM data with a resolution of 10 meters, and its coordinate system has been unified to the Gauss-Kruger projection coordinate system to ensure the accuracy of distance and area calculations.

[0114] Obtain vector line feature data of the target river; this data is a continuous polyline that accurately depicts the complete river channel from the river's source to the planned section of interest, and its planar position matches the topography reflected by the DEM.

[0115] Define the initial dam site element X1; in this embodiment, the initial dam site is preset near the confluence of the downstream river; in the Gis software, draw a line segment intersecting the river channel as the dam axis; the length of the line segment is dynamically set to between 130 meters and 150 meters according to the average width of the river channel at that location, and ensure that its coordinate system is consistent with the aforementioned data.

[0116] Step 2: Data preprocessing and dam site initialization;

[0117] DEM Depression Filling Processing: The "Depression Filling" function in the Gis hydrological analysis toolset is used to process the input 10-meter DEM, eliminating tiny depressions in the data, ensuring the accuracy of water flow direction analysis, and generating a depression-free DEM.

[0118] River line element smoothing: The adaptive smoothing model defined in this invention is used to process the river vector line; the model reads the coordinate sequence of each inflection point of the river polyline; for any inflection point Pᵢ, the model calculates its angle change rate A(i), curvature anomaly C(i), and context discontinuity D(i); the comprehensive smoothness judgment value S(i) is calculated according to the preset weights α=0.4, β=0.3, γ=0.3; if S(i) > 0.75, the coordinates of the point are corrected by smoothing interpolation; otherwise, the original coordinates are retained; this process traverses the entire river segment and outputs a smoothed river line with a more natural shape that is beneficial to subsequent analysis.

[0119] Initialize the dam site orientation: Based on the smoothed river line, calculate the local orientation of the river channel at the location of the initial dam site X1; then, using the vertical constraint function f1 in the orientation model, adjust the orientation of the initial dam site line elements so that the angle β between them and the local river channel orientation approaches 90 degrees, allowing for small deviations, thereby determining an initial dam site scheme that conforms to engineering layout practices.

[0120] Step 3: Initial scheme calculation;

[0121] Set water level range: Set the calculated water level for the initial dam site X1; set the initial water level y11 as the lowest elevation of the riverbed at the dam site plus 10 meters, and set the highest water level y1m as the lowest elevation of the saddles or key features on both banks of the dam site; in this embodiment, y11 = 650 meters and y1m = 750 meters.

[0122] Reservoir capacity-inundation batch calculation: Start the reservoir simulation module of Gis or use the grid calculation function; with X1 as the dam axis, set the water level to 650 meters, 651 meters, 652 meters... up to 750 meters in sequence; for each water level, the module automatically simulates the inundation range and calculates the reservoir capacity and inundation area at that water level; finally, two sets of sequences are obtained: [V11, V12, ..., V1m] and [S11, S12, ..., S1m].

[0123] Step 4: Generate a sequence of candidate dam sites;

[0124] Application of translation function: Starting from the initial dam site X1, the dam site translation function f(x, y,z) constructed by this invention is applied; this function is composed of a weighted combination of the vertical constraint sub-function f1 and the translation distance sub-function f2.

[0125] Determine the translation direction and distance: Set the translation direction to the upstream of the river; the distance threshold z2 in function f2 is set to 1.0 km according to the watershed scale; function f will calculate the score f(x, y, z) of each potential new location within a certain distance range upstream; the system automatically selects the location with a score in the interval [7, 10] as the next candidate dam site X2; in this example, X2 is calculated to be located about 1.2 km upstream of X1, and its dam axis direction has been automatically adjusted to be perpendicular to the river channel at the new location by the constraint of f1.

[0126] Iterative generation sequence: Using the newly obtained X2 as the current dam site, repeat the above translation calculation process to obtain X3; iterate in this way until the preset search upper limit is reached or the function cannot find the next position that meets the conditions, and finally generate a candidate dam site sequence X1, X2, X3, ..., Xn.

[0127] Step 5: Batch evaluation of multiple options;

[0128] For each candidate dam site Xn in the sequence:

[0129] Based on the terrain of its location, reset its reasonable starting water level yn1 and maximum water level ynm.

[0130] Call the same Gis reservoir simulation module as in step three to calculate in batches the reservoir capacity Vnm and inundation area Snm corresponding to each water level from the initial water level yn1 to the highest water level ynm at the dam site.

[0131] Finally, a complete reservoir capacity matrix [Vn1, Vnm] and an inundation area matrix [Sn1, Snm] are obtained, where rows represent different dam sites and columns represent different water levels.

[0132] Step Six: Multi-objective optimization and decision output;

[0133] Identify "Reservoir Capacity Priority Scheme Xp1": The system traverses the reservoir capacity matrix [Vn1, Vnm] and finds the globally largest reservoir capacity value Max{Vnm}. There may be multiple locations that reach the same maximum reservoir capacity. Among these schemes, the corresponding inundation area Snm is compared, and the scheme with the smallest inundation area is selected. The dam site corresponding to this scheme is Xp1, and its water level and reservoir capacity are the optimal values.

[0134] Identify the "Comprehensive Optimal Solution Xp2": The system calculates the reservoir inundation ratio Rnm=Vnm / Snm for each solution; then, it finds the global maximum reservoir inundation ratio Max{Rnm}; the solution corresponding to this maximum value is the comprehensive optimal solution, its dam site location is denoted as Xp2, and its corresponding water level and reservoir capacity are output.

[0135] Results presentation: The system highlights the locations of the two optimal dam sites, Xp1 and Xp2, on the Gis map and lists in detail their corresponding recommended design water level, total reservoir capacity, inundation area, and reservoir capacity-to-inundation ratio in tabular form, for planning decision-makers to make final comparisons and decisions.

[0136] As can be seen from the above specific implementation methods, the present invention closely integrates Gis spatial analysis technology, automated algorithms and multi-objective optimization ideas, transforming a reservoir planning and site selection problem that originally relied on experience, was cumbersome and subjective into a standardized process that can be automatically executed, quantitatively evaluated and scientifically decided. This embodiment demonstrates the complete chain of the method from data input to result output, proving its feasibility and effectiveness in practical engineering applications.

[0137] It should be noted that the specific parameters in the above embodiments, such as DEM resolution, smoothing model weight, translation distance threshold, and water level step size, can be adjusted according to the specific conditions of different watersheds and engineering accuracy requirements. All such adjustments fall within the protection scope of this invention.

Claims

1. A method for calculating the optimal selection of reservoir dam site and reservoir capacity based on Git, characterized in that, Includes the following steps: Step S1: Obtain Geographic Information System (GIS) driving data, which includes the Digital Elevation Model (DEM), complete vector line features of the river where the reservoir is located, and the initial dam site location X1. Input the GIS driving data into the GIS model. Step S2: Fill depressions in the terrain digital elevation model (DEM) and smooth the complete vector line features of the river where the reservoir is located; Step S3: Set the initial dam site location X1 as the river confluence, and use the orientation model to adjust the orientation of the initial dam site location X1 so that the orientation of the initial dam site location X1 is perpendicular to the river channel orientation; Step S4: Set the first initial water level y11 and the first highest water level y1m corresponding to the initial dam site location X1; Start the Gis model and calculate the first reservoir capacity [V11, V1m] and the first inundation range [S11, S1m] corresponding to the first initial water level y11 to the first highest water level y1m at the initial dam site location X1. Step S5: Based on the translation function, translate the current dam site location along the river direction to obtain the new dam site location; Step S6: Repeat step S5 to obtain a series of dam site locations X2, X3, ..., Xn, where X2 is the second new dam site location, X3 is the third new dam site location, and Xn is the nth new dam site location. Step S7: Set the corresponding nth initial water level yn1 and nth highest water level ynm for the nth new dam site location Xn; for the nth new dam site location Xn, start the Gis model to calculate the nth reservoir capacity [Vn1, Vnm] and the nth inundation range [Sn1, Snm] between the nth initial water level yn1 and the nth highest water level ynm; Step S8: Based on the calculated total reservoir capacity V1 to Vn and the inundation range S1 to Sn, determine two dam site locations Xp1 and Xp2, where: Xp1 is the dam site location with the smallest inundation range under the condition of the largest reservoir capacity, and Xp2 is the dam site location with the largest ratio of reservoir capacity to inundation range. Step S9: Output the dam site location Xp1 with the smallest inundation range under the condition of maximum reservoir capacity and its corresponding optimal reservoir capacity, and the dam site location Xp2 with the largest ratio of reservoir capacity to inundation range and its corresponding optimal reservoir capacity.

2. The method for calculating the optimal selection of reservoir dam site and reservoir capacity based on Gis, as described in claim 1, is characterized in that: In step S2, the smoothing of the complete vector line features of the river where the reservoir is located adopts an adaptive smoothing model, and the smoothing range covers the entire section from the river source to the confluence.

3. The method for calculating the optimal selection of reservoir dam site and reservoir capacity based on Gis, as described in claim 2, is characterized in that: The formula for calculating the overall smoothness judgment value of the adaptive smoothing model is as follows: ； Where S(i) is the overall smoothness judgment value, For the corresponding weighting coefficients, A(i) is the rate of change of angle. For the corresponding weighting coefficients, C(i) is the curvature anomaly component. For the corresponding weighting coefficients, D(i) represents the context discontinuity component; when S(i) > 0.75, the complete vector line features of the river where the reservoir is located are smoothed, while other values ​​remain unchanged. The formula for calculating the rate of change of angle is: ； in, The current inflection point The interior angle at that point, It is a straight angle. The angle weighting factor is calculated using the following formula: ; The formula for calculating the curvature anomaly component is: ； in, For the current point The discrete curvature at a given point is calculated using the following formula: ; The average curvature within the local window is calculated using the following formula: ; For the local curvature standard deviation, This is the steepness parameter of the Sigmoid function. The curvature anomaly threshold, The coordinates of the current inflection point; The formula for calculating the context discontinuity component is: ； in, Fit a straight line to the context using points arrive Linear regression yielded the result; Let be the distance from the point to the line. To prevent division by zero of small constants; The trend discontinuity factor is calculated using the following formula: ; This represents the current line segment direction angle. The overall orientation angle for the context.

4. The method for calculating the optimal selection of reservoir dam site and reservoir capacity based on Gis, as described in claim 1, is characterized in that: In step S3, the orientation of the initial dam site X1 is adjusted using the orientation model. This is specifically achieved through a vertical constraint function, which makes the dam axis more perpendicular to the river channel orientation. Specifically: ； in, For vertical constraint functions, The cosine function is a trigonometric function. This is the tolerance coefficient for deviation. This is the actual angle between the axis of the new dam and the direction of the river channel.

5. The method for calculating the optimal selection of reservoir dam site and reservoir capacity based on Gis, as described in claim 1, is characterized in that: In step S4, the first initial water level y11 and the first highest water level y1m corresponding to the initial dam site location X1 are set; the Gis model is started to calculate the first reservoir capacity [V11, V1m] and the first inundation range [S11, S1m] corresponding to the distance from the first initial water level y11 to the first highest water level y1m at the initial dam site location X1; specifically: Step S41: After selecting the initial dam site location X1, the reservoir planning calculation module of the Gis model is used to calculate the corresponding first reservoir capacity V11 based on the input first initial water level y11, and then calculate the second reservoir capacity V12 corresponding to the second initial water level y12, until the m-th reservoir capacity V1m corresponding to the m-th initial water level y1m is calculated. Step S42: Calculate the reservoir capacity and inundation range at different water levels using the Gis model's reservoir planning calculation module; the difference between adjacent calculated water levels is set to 1 unit, as shown in the following formula: y1m = y11 + (m - 1); Where y1m is the first highest water level, m is the number of water levels, and y11 is the first starting water level; y1m≤Max(DEMX1), that is, the highest water level must be less than or equal to the elevation value of the maximum topographic digital elevation model (DEM) where the dam site is located.

6. The method for calculating the optimal selection of reservoir dam site and reservoir capacity based on Gis, as described in claim 1, is characterized in that: The translation function f(x, y, z) in step S5 is a weighted combination of the vertical constraint function f1(x, y, z) and the translation distance function f2(x, z), and the calculation formula is as follows: ； in, These are the weighting coefficients of the level function. Let be the weight coefficients of the vertical function, and , The position corresponding to the translation function f(x, y, z) is selected as the new dam site.

7. The method for calculating the optimal selection of reservoir dam site and reservoir capacity based on Gis, as described in claim 6, is characterized in that: The formula for calculating the translation distance function f2(x, z) is: ； in, This is a function to find the maximum value, specifically, to take the maximum value of the sequence of values ​​within the parentheses. This represents the actual translation distance from the original dam site to the new dam site. The preset distance threshold ranges from 0.5 to 2 kilometers.

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