Inflow lake water storage optimization calculation method considering flood control and ecological influence

Abstract

The invention discloses an internal flow lake water storage optimization calculation method considering flood control and ecological influence. The method comprises the following steps: step 1, lake water system connectivity analysis; 2, analyzing the water storage capacity of the lake; step 3, constructing a distributed hydrological model; 4, constructing and calculating a hydrology-water volume scheduling integrated model; step 5, constructing a water storage optimization model; and step 6, lake water storage optimization calculation. According to the internal flowing lake water storage optimization calculation method considering flood control and ecological influence, internal flowing lake water volume optimization scheduling considering ecological and flood control safety is realized, a scientific basis is provided for protecting the ecological and flood control safety of an internal flowing river basin under the current climate change condition, and the method has very high application value.

Description

Technical Field

[0001] The invention belongs to the technical field of water conservancy engineering, and in particular relates to an optimization calculation method for water storage in an inland lake taking into account flood control and ecological impacts. Background Art

[0002] The area of ​​inland drainage areas in my country accounts for about 36% of the country's total land area, mostly distributed in the northwest region and the arid climate zone in the central and northern Qinghai-Tibet Plateau. In the inland drainage areas, there are often tail lakes in the low-lying terrain of the basin without external drainage channels, such as Tuosu Lake in Qinghai, Jilantai Salt Lake in Inner Mongolia, and Caohai in Guizhou. With the influence of global warming, the water levels of many lakes in the inland drainage areas have continued to rise in recent years, and the lake shorelines have expanded as a whole during the rising water level, causing the surrounding grasslands, wetlands, houses and infrastructure to be flooded, forming flooding disasters, and even individual lakes have overflowed due to the continuous increase in water volume, causing unpredictable flood disasters. For example, Xiaochaidan Lake in Haixi Mongolian and Tibetan Autonomous Prefecture, Qinghai Province, has expanded rapidly since 2020, posing a threat to the safe operation of Liuge Expressway and Dexiao Expressway in the west and south of the lakeshore. The inland lakes in Coqen and Gegye in Tibet have been affected by factors such as rising temperatures in the basin, melting permafrost, increased precipitation, and accelerated melting of ice and snow. This has led to a continuous expansion of the water area and intensified swamping of land near the lakes, posing a significant threat to surrounding roads, houses and other facilities.

[0003] Through the planning, construction and rational use of various water projects, surface water can be regulated, controlled and distributed in time and space, thereby achieving multiple goals such as flood control and disaster reduction, ecological protection and comprehensive benefit improvement. Taking the Yangtze River Basin as an example, its optimized scheduling practice has achieved remarkable results in flood control, power generation, and water replenishment. Through the construction of reservoir projects such as the Three Gorges, Wudongde, and Baihetan, and the formulation of scientific scheduling plans, it has successfully responded to many major floods and effectively ensured the flood control safety of the middle and lower reaches of the Yangtze River; through the reasonable adjustment of reservoir water storage and power generation output, the power generation benefits have been maximized; through water replenishment scheduling, the production, living and ecological water conditions in the middle and lower reaches have been improved.

[0004] However, current research and practice on water optimization and scheduling mainly focus on outflow river basins, while relatively insufficient attention is paid to inland river basins. Inland rivers have completely different hydrological and hydraulic characteristics from outflow rivers, which is mainly reflected in the fact that the tail lake in the basin only receives water from the basin and has no natural way to discharge it. Water consumption mainly relies on evaporation and leakage. Climate change breaks the original balance of lake inflow and evaporation. The water volume of some lakes continues to increase, resulting in overflow risks at the low points of the lake shoreline, causing unconventional flood disasters. In addition, the unique hydrological characteristics and geographical environment of inland rivers determine their ecological fragility. On the one hand, the water source of inland rivers mainly comes from alpine ice and snow meltwater and mountain precipitation. Climate change, such as glacier retreat and changes in precipitation patterns caused by global warming, will directly affect the water volume of inland rivers and thus affect their ecosystems. On the other hand, the ecosystems of inland river basins are often relatively simple and have relatively low biodiversity. This simple ecosystem structure makes the system less resistant to external interference, and once it is damaged, it is more difficult to recover.

[0005] Therefore, how to achieve optimal calculation of water storage in inland lakes while taking into account both flood control and ecological impacts is a technical problem that needs to be solved urgently. Summary of the invention

[0006] The purpose of the present invention is to provide a method for optimizing the calculation of water storage in inland lakes taking into account flood control and ecological impacts, so as to solve the above-mentioned technical problems.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] The present invention discloses a method for optimizing the calculation of water storage in an inland lake taking into account flood control and ecological impacts, the method comprising the following steps:

[0009] Step 1: Analysis of lake water system connectivity: Collect DEM data, lake distribution data and remote sensing image data of the target basin; Based on the collected DEM data, obtain the river network water system distribution of the target basin through depression filling, flow direction analysis, flow calculation, and river network water system extraction; Based on the collected lake distribution data, compare and verify with the collected remote sensing image data to determine the distribution of lake depressions in the target basin; According to the river network water system distribution and lake depression distribution of the target basin, analyze the connectivity of the lakes, make a generalized map of lake connectivity, and determine the confluence path of each lake in the target basin;

[0010] Step 2: Analysis of lake water storage capacity: Based on the collected remote sensing image data, analyze the lake surface area at different time points and organize them into a sequence according to the area size, recorded as A_list = [A1, A2, ..., A i ,...,A N ], a total of N data, of which A iis the surface area of ​​the lake at the ith moment; based on the collected DEM data, the lake water level corresponding to each time point is obtained to form a water level sequence corresponding to the area sequence, recorded as H_list = [H1, H2, ..., H i ,...,H N ], a total of N data, of which H i is the lake water level at the i-th moment; according to the water level and area data at different time points, the volume calculation formula of the prism is used to estimate the water storage difference to form a water storage sequence corresponding to the area sequence, which is recorded as R_list=[V1,V1+ΔV2,...,V i-1 +ΔV i ,...,V N-1 +ΔV N ], a total of N data, where V1 is the initial storage capacity, when A1 is 0, V1 is equal to 0, ΔV i is the difference in water storage between the i-th and i-1-th values, and the calculation formula is:

[0011]

[0012] Among them, A i is the surface area of ​​the lake at the ith moment, H i is the lake water level at the ith moment;

[0013] According to the obtained area sequence, water level sequence and water storage sequence, the water level-water storage relationship curve and the water level-area relationship curve are fitted, where the lake area corresponding to the lake bottom water level is 0 and the lake water storage is 0;

[0014] Step 3: Distributed hydrological model construction: A distributed hydrological model is constructed, which is characterized by the use of grid-type computing units, and the computing grid can cover the entire basin; the model is constructed based on water balance and energy balance equations, comprehensively considering the interaction of climate, topography, soil properties, and vegetation, and supports runoff calculation. The hydrological and meteorological elements that can be calculated in the model include at least precipitation, ground evapotranspiration, water surface evaporation, surface runoff, and ground runoff;

[0015] Step 4: Construction and calculation of the integrated hydrological-water scheduling model: First, the target basin is generalized into three units: flow-generating zones, lakes, and sections. On this basis, the topological relationship of each unit in the basin is analyzed, and the construction and calculation of the integrated hydrological-water scheduling model are carried out, which specifically includes the following steps:

[0016] Step 4-1: Constructing a hydrological-water scheduling integrated model, including the following steps:

[0017] Step 4-1-1: Based on the river network and lake-depression distribution analyzed in step 1, the target watershed is divided into different runoff-generating sub-areas. The runoff of each runoff-generating sub-area unit flows into the lake or cross-section unit, and a generalized topological map of the watershed unit is produced;

[0018] Step 4-1-2: Based on the confluence paths of the lakes in the basin, associate each runoff zone with the distributed hydrological model calculation grid divided in step 3, and associate each runoff zone with several calculation grids;

[0019] Step 4-1-3, associate the lake with the distributed hydrological model calculation grid divided in step 3. The calculation grid covered by the lake surface does not perform runoff calculation, and only considers rainfall and evaporation;

[0020] Step 4-1-4, construct the basin topology relationship, which reflects the upstream and downstream relationship of each flow-generating partition, lake and section, and includes the association between the basin generalization unit and the distributed hydrological model calculation grid, and manages the basin topology relationship data in JSON files;

[0021] Step 4-1-5, manage the characteristic data of each lake unit in the basin in a JSON file; the characteristic data of each lake unit includes name, water level curve, area curve, water storage curve, lake overflow outlet elevation, lake overflow outlet width and initial water level elevation;

[0022] Step 4-2: Calculate the hydrological-water scheduling integrated model, including the following steps:

[0023] Step 4-2-1: Use the distributed hydrological model to simulate the hydrological process of the entire basin for several years. The time step of the model output is 1 day.

[0024] Step 4-2-2, read in the watershed topological relationship data in step 4-1-4 and the characteristic data of the lake unit in step 4-1-5;

[0025] Step 4-2-3: Based on the calculation results in step 4-2-1, as well as the relationship between the runoff generating zones, lakes and the distributed hydrological model calculation grid, calculate the multi-year average monthly runoff of each runoff generating zone, and calculate the multi-year average monthly precipitation and monthly evaporation of each lake;

[0026] Step 4-2-4, perform water storage calculation for each unit in the basin; read the inflow data of each unit from upstream to downstream in sequence according to the basin topology, and synthesize the flow if there are multiple upstream flows; perform storage calculation for lake units, analyze the lake's water storage capacity and discharge capacity based on the lake water level-storage capacity curve, as well as the bottom elevation and width of the overflow outlet, calculate the multi-year average monthly inflow, precipitation, evaporation, storage capacity, water level, overflow of each lake, and calculate the lake surface area change process based on the water level-area curve;

[0027] Step 4-2-5, traverse all units in the watershed and complete the calculation;

[0028] Step 5: Construction of water storage optimization model: The optimization algorithm is combined with the hydrology-water quantity scheduling integrated model constructed in step 4 to construct a water storage optimization model;

[0029] Step 6: Lake water storage optimization calculation: Use the water storage optimization model constructed in step 5 to perform optimization calculations to obtain the optimized overflow elevation of each lake in the basin.

[0030] Furthermore, the specific process of managing the watershed topology relationship data in a JSON file as described in step 4-1-4 is: managing the watershed generalization unit in the form of a JSON object, which includes "Name", "Id", "Type", "NextId", and "Grid" attributes; among which, the "Name" attribute stores the name of the unit; the "Id" attribute stores the unit code, which is unique among all units; the "Type" attribute stores the type of the unit, the runoff unit is "Watershed", the lake unit is "Reservoir", and the section unit is "Section"; the "NextId" attribute stores the code of the downstream unit of the unit, which is the "Id" of the first unit downstream of the unit according to the watershed topology relationship. When the unit is the most downstream unit in the watershed topology, that is, the tail lake, "NextId" is -1; when the unit is a runoff partition or lake type, it contains a "Grid" attribute, and "Grid" is an array type, which stores the distributed hydrological model calculation grid number associated with the unit.

[0031] Furthermore, the specific process of managing the characteristic data of each lake unit in the basin in a JSON file as described in step 4-1-5 is: managing the lake unit in the form of a JSON object, which includes the attributes "Name", "H_list", "A_list", "R_list", "E", "B", and "E_ini"; among them, the "Name" attribute saves the name of the unit; the "H_list" attribute saves the water level curve obtained in step 2; the "A_list" attribute saves the area curve obtained in step 2; the "R_list" attribute saves the water storage curve obtained in step 2; the "E" attribute saves the lake overflow elevation; the "B" attribute saves the lake overflow width; and the "E_ini" attribute saves the initial water level elevation calculated for lake storage.

[0032] Furthermore, the optimization algorithm adopted in step 5 is a genetic algorithm, a particle swarm algorithm or a SCE-UA algorithm.

[0033] Furthermore, the optimization variable of the water storage optimization model constructed in step 5 is the overflow elevation of other lakes in the basin except the tail lake, and the variable range is set to be from the current overflow elevation to the top elevation of the discharge project within the feasible range of the project;

[0034] The constraint condition of the water storage optimization model is that the water level of the tail lake does not exceed the overflow level;

[0035] In the lake unit in step 4-1-4, add the adaptability index attribute of plants and animals in the flooding affected area of ​​the lake, and name the different adaptability indexes of plants and animals in sequence as "Index_1, Index_2...", with the value range of 0 to 1, where 1 represents the strongest adaptability;

[0036] The optimization objective function of the water storage optimization model is set to minimize the weighted sum of the suitability indexes of the relative areas of each lake in the basin, that is, the increase in the flooded area of ​​the lake has the least impact on the suitability of the species, as shown in the following formula:

[0037]

[0038] Where Area i is the area of ​​the ith lake in the basin; Area_Max i is the maximum area of ​​the i-th lake in the basin under current conditions, that is, the lake area corresponding to the overflow outlet elevation; N' is the number of lakes in the basin; M is the number of species considered for suitability; Index_i_j is the suitability index of the j-th species in the inundation impact area of ​​the i-th lake.

[0039] The beneficial effects of the present invention are as follows: the method for optimizing the calculation of water storage in inland lakes taking into account flood control and ecological impacts described in the present invention realizes the optimal scheduling of water volume in inland lakes that takes into account both ecological and flood control safety, provides a scientific basis for protecting the ecology and flood control safety of inland river basins under the current climate change conditions, and has very high application value.

[0040] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific implementation methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 is a flow chart of the method of the present invention;

[0042] Figure 2 This is the DEM data map of the inland river basin in Example 1;

[0043] Figure 3 This is a data map of lake distribution in the inland river basin in Example 1;

[0044] Figure 4 The remote sensing image data diagram of the inland river basin in Example 1;

[0045] Figure 5 The river network distribution map of the basin extracted based on DEM data in Example 1;

[0046] Figure 6 is a generalized diagram of lake connectivity in Example 1;

[0047] Figure 7 to Figure 17 They are respectively the water level-water storage-area relationship curves of Lakes 1 to 11 in the basin in Example 1;

[0048] Fig.18 A grid distribution map for calculating the distributed hydrological model in the first embodiment;

[0049] Fig.19 It is a generalized diagram of the watershed unit topology in Example 1;

[0050] Fig. 20 This is a relationship diagram between the watershed flow generation zones, lakes and computing grids in Example 1. DETAILED DESCRIPTION

[0051] The present invention discloses a method for optimizing the calculation of water storage in an inland lake taking into account flood control and ecological impacts. Figure 1 As shown, the method comprises the following steps:

[0052] Step 1. Lake water system connectivity analysis: Collect DEM data, lake distribution data and remote sensing image data of the target basin. Based on the collected DEM data, obtain the river network water system distribution of the target basin through depression filling, flow direction analysis, flow calculation, and river network water system extraction. Based on the collected lake distribution data, compare and verify with the collected remote sensing image data. If necessary, conduct field surveys to determine the distribution of lake depressions in the target basin. According to the distribution of river network water systems and lake depressions in the target basin, analyze the connectivity between lakes, make a generalized map of lake connectivity, and determine the confluence path of each lake in the target basin.

[0053] Step 2: Analysis of lake water storage capacity: Based on the collected remote sensing image data, analyze the lake surface area at different time points and organize them into a sequence according to the area size, recorded as A_list = [A1, A2, ..., A i ,...,A N ], a total of N data, of which A i is the surface area of ​​the lake at the i-th moment. Based on the collected DEM data, the lake water level corresponding to each time point is obtained to form a water level sequence corresponding to the area sequence, which is recorded as H_list = [H1, H2, ..., H i ,...,H N ], a total of N data, of which H i is the lake water level at the i-th moment. According to the water level and area data at different time points, the volume calculation formula of the prism is used to estimate the water storage difference, forming a water storage sequence corresponding to the area sequence, recorded as R_list=[V1,V1+ΔV2,...,V i-1 +ΔV i ,...,V N-1 +ΔV N ], a total of N data, where V1 is the initial storage capacity, when A1 is 0, V1 is equal to 0, ΔV i is the difference in water storage between the i-th and i-1-th values, and the calculation formula is as follows:

[0054]

[0055] Among them, A i is the surface area of ​​the lake at the ith moment, H i is the lake water level at the ith moment.

[0056] According to the obtained area sequence, water level sequence and water storage capacity sequence, the water level-water storage capacity relationship curve and the water level-area relationship curve are fitted, where the lake area corresponding to the lake bottom water level is 0 and the lake water storage capacity is 0.

[0057] Step 3: Construct a distributed hydrological model: Construct a distributed hydrological model, which is characterized by the use of grid-type computing units. The computing grid can cover the entire river basin. The model is constructed based on water balance and energy balance equations. It can comprehensively consider the interaction between climate, topography, soil properties, and vegetation, and support runoff calculation. The hydrological and meteorological elements that can be calculated in the model include at least precipitation, ground evapotranspiration, water surface evaporation, surface runoff, and groundrunoff.

[0058] Step 4: Construction and calculation of the integrated hydrological-water scheduling model: The target basin is generalized into three units: flow-generating zones, lakes, and sections. On this basis, the topological relationship of each unit in the basin is analyzed to construct and calculate the integrated hydrological-water scheduling model, which specifically includes the following steps:

[0059] Step 4-1: Constructing a hydrological-water scheduling integrated model, including the following steps:

[0060] Step 4-1-1: Based on the river network and lake-depression distribution analyzed in step 1, divide the target watershed into different flow-generating zones. The runoff of each flow-generating zone unit flows into the lake or cross-section unit, and a generalized topological map of the watershed unit is produced.

[0061] Step 4-1-2: Based on the confluence paths of the lakes in the basin, each runoff zone is further associated with the distributed hydrological model calculation grid divided in step 3, and each runoff zone is associated with several calculation grids.

[0062] Step 4-1-3: Associate the lake with the distributed hydrological model calculation grid divided in step 3. The calculation grid covered by the lake surface does not perform runoff calculations, and only considers rainfall and evaporation.

[0063] Step 4-1-4, construct the basin topology relationship, which reflects the upstream and downstream relationship of each flow-generating partition, lake and section, and includes the association between the basin generalization unit and the distributed hydrological model calculation grid, and manages the basin topology relationship data in a JSON file. Specifically: manage the basin generalization unit in the form of a JSON object, which includes attributes such as "Name", "Id", "Type", "NextId", and "Grid". The "Name" attribute stores the name of the unit; the "Id" attribute stores the unit code, which is unique among all units; the "Type" attribute stores the type of the unit, the runoff unit is "Watershed", the lake unit is "Reservoir", and the cross-section unit is "Section"; the "NextId" attribute stores the code of the downstream unit of the unit, which is the "Id" of the first unit downstream of the unit according to the basin topology. When the unit is the most downstream unit in the basin topology, that is, the tail lake, "NextId" is -1; when the unit is a runoff partition or lake type, it contains the "Grid" attribute, "Grid" is an array type, which stores the distributed hydrological model calculation grid number associated with the unit.

[0064] Step 4-1-5, manage the characteristic data of each lake unit in the basin in a JSON file. Specifically: manage the lake unit in the form of a JSON object, which includes attributes such as "Name", "H_list", "A_list", "R_list", "E", "B", and "E_ini". The "Name" attribute saves the name of the unit; the "H_list" attribute saves the water level curve obtained in step 2; the "A_list" attribute saves the area curve obtained in step 2; the "R_list" attribute saves the water storage curve obtained in step 2; the "E" attribute saves the lake overflow elevation; the "B" attribute saves the lake overflow width; the "E_ini" attribute saves the initial water level elevation of the lake storage calculation.

[0065] Step 4-2: Calculate the hydrological-water scheduling integrated model, including the following steps:

[0066] Step 4-2-1: Use the distributed hydrological model to simulate the hydrological process of the entire basin for several years. The time step of the model output is 1 day.

[0067] Step 4-2-2, read in the basin topology relationship data prepared in step 4-1-4 and the characteristic data of the lake unit prepared in step 4-1-5;

[0068] Step 4-2-3: Based on the calculation results in step 4-2-1, as well as the relationship between the runoff generating zones, lakes and the distributed hydrological model calculation grid, calculate the multi-year average monthly runoff of each runoff generating zone, and calculate the multi-year average monthly precipitation and monthly evaporation of each lake;

[0069] Step 4-2-4, perform water storage calculations for each unit in the basin. According to the basin topology, read the inflow data of each unit from upstream to downstream in turn. If there are multiple upstream flows, synthesize the flow; perform storage calculations for lake units, analyze the lake's water storage capacity and discharge capacity based on the lake water level-reservoir capacity curve, as well as the bottom elevation and width of the overflow port, calculate the multi-year average monthly inflow, precipitation, evaporation, reservoir capacity, water level, overflow of each lake, and calculate the lake surface area change process based on the water level-area curve;

[0070] Step 4-2-5: Traverse all cells in the watershed to complete the calculation.

[0071] Step 5: Constructing a water storage capacity optimization model: Combine the optimization algorithm with the hydrological-water volume scheduling integrated model constructed in step 4 to construct a water storage capacity optimization model. The optimization algorithm used can be a commonly used optimization algorithm such as a genetic algorithm, a particle swarm algorithm, or an SCE-UA algorithm.

[0072] Specifically, the optimization variable of the water storage optimization model is the overflow elevation of other lakes in the basin except the tail lake, and the variable range is set from the current overflow elevation to the top elevation of the discharge project within the feasible range of the project. The constraint condition of the water storage optimization model is that the water level of the tail lake does not exceed the overflow level.

[0073] In order to consider the impact of lake regulation on ecology, the adaptability index attribute of plants and animals in the lake flooding area is added to the lake unit in step 4-1-4. Different plant and animal adaptability indexes are named "Index_1, Index_2..." in sequence, and the value range is 0 to 1, where 1 represents the strongest adaptability, that is, the increase in lake surface has a greater impact on their survival in the basin.

[0074] The optimization objective function of the water storage optimization model is set to minimize the weighted sum of the suitability indexes of the relative areas of each lake in the basin, that is, the increase in the lake inundation range has the least impact on the suitability of species, as shown in the following formula.

[0075]

[0076] Where Area i is the area of ​​the ith lake in the basin; Area_Max iis the maximum area of ​​the i-th lake in the basin under current conditions, that is, the lake area corresponding to the overflow outlet elevation; N' is the number of lakes in the basin; M is the number of species considered for suitability; Index_i_j is the suitability index of the j-th species in the inundation impact area of ​​the i-th lake.

[0077] Step 6: Lake water storage optimization calculation: Use the water storage optimization model constructed in step 5 to perform optimization calculations to obtain the optimized overflow elevation of each lake in the basin.

[0078] Embodiment 1

[0079] This embodiment is an application example of the above method.

[0080] This embodiment discloses a method for optimizing the calculation of water storage in an inland lake taking into account flood control and ecological impacts, comprising the following steps:

[0081] Step 1: Lake system connectivity analysis: Collect DEM data, lake distribution data and remote sensing image data of an inland river basin. Figure 2 As shown in Figure 2, lake distribution data is as follows: Figure 3 As shown in Figure 4 shown.

[0082] Extract the river network distribution of the basin based on DEM data, such as Figure 5 As shown; and according to the distribution of lakes and water systems, the connectivity between lakes is analyzed, and a generalized map of lake connectivity is produced as shown Figure 6 As shown in the figure, a total of 4 confluence paths are obtained, namely: a) Lake 2—Confluence Path 1—Lake 1; b) Confluence Path 2—Lake 1; c) Lake 3—Lake 4—Confluence Path 3—Lake 1; d) Lake 5—Lake 6—Lake 7—Lake 8—Lake 9—Lake 10—Lake 11—Confluence Path 4—Lake 1. It can be seen that the lakes in the basin are finally converged into Lake 1 through four confluence paths, and Lake 1 is the tail lake of the basin.

[0083] Step 2: Analysis of lake water storage capacity: Analyze and obtain the water level-water storage capacity relationship curve and water level-area relationship curve of 11 lakes in the basin. Figures 7 to 17 shown.

[0084] Step 3: Distributed hydrological model construction: Construct a distributed hydrological model covering the entire basin. The model uses grid-type computing units, and the entire basin is divided into 682 computing grids, such as Fig.18 shown.

[0085] Step 4: Construction and calculation of the integrated hydrological-water scheduling model: According to the distribution of lakes and water systems in the basin, the inland river basin is divided into 16 flow-generating sub-areas, 3 sections are set, and the topological relationship of the 16 flow-generating sub-areas, 11 lakes and 3 sections in the basin is analyzed to make a generalized map as shown in the figure. Fig.19 As shown in the figure, the relationship between runoff generation zones, lakes and distributed hydrological model calculation grids is analyzed, as shown in the figure. Fig. 20 shown.

[0086] The watershed generalization unit is managed in the form of a JSON object as follows:

[0087]

[0088] The lake units are managed in the form of JSON objects as follows:

[0089]

[0090] The calculation results of runoff generation division and lake hydrology are as follows:

[0091]

[0092] The calculation results of lake water storage are as follows:

[0093]

[0094] Step 5: Construction of water storage optimization model: Combine the optimization algorithm with the hydrology-water scheduling integrated model constructed in step 4 to construct a water storage optimization model. In order to consider the impact of lake regulation on ecology, add a suitability index attribute to the lake unit, considering the suitability of two types of species, as shown below:

[0095]

[0096] Step 6. Lake water storage optimization calculation: After optimizing the calculation using the water storage optimization model constructed in step 5, the overflow elevations of each lake are obtained as shown in Table 1. It can be seen that by constructing water retaining projects in Lake 8 and Lake 11 and raising the overflow elevations by 1.2m and 3m respectively, the goal of preventing the tail lake in the basin from overflowing and minimizing the impact on the ecology can be achieved through upstream water storage.

[0097] Table 1 Calculation results of overflow elevation of each lake

[0098] Lake name Overflow height (m) Optimized overflow height (m) Overflow height (m) Lake 5 4828 4828 0 Lake 6 4804 4804 0 Lake 7 4799 4799 0 Lake 8 4647 4648.2 1.2 Lake 9 4646 4646 0 Lake 10 4551 4551 0 Lake 11 4550 4553 3.0 Lake 3 4672 4672 0 Lake 4 4561 4561 0 Lake 2 4663 4663 0 Lake 1 4544.64 4544.64 0

[0099] Finally, it should be noted that the above is only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred arrangement scheme, a person skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A method for optimizing the calculation of water storage in inland lakes considering flood control and ecological impacts, characterized in that: The method comprises the following steps: Step 1: Analysis of lake water system connectivity: Collect DEM data, lake distribution data and remote sensing image data of the target basin; Based on the collected DEM data, obtain the river network water system distribution of the target basin through depression filling, flow direction analysis, flow calculation, and river network water system extraction; Based on the collected lake distribution data, compare and verify with the collected remote sensing image data to determine the distribution of lake depressions in the target basin; According to the river network water system distribution and lake depression distribution of the target basin, analyze the connectivity of the lakes, make a generalized map of lake connectivity, and determine the confluence path of each lake in the target basin; Step 2: Analysis of lake water storage capacity: Based on the collected remote sensing image data, analyze the lake surface area at different time points and organize them into a sequence according to the area size, recorded as A_list = [A1, A2, ..., A i ,...,A N ], a total of N data, of which A i is the surface area of ​​the lake at the ith moment; based on the collected DEM data, the lake water level corresponding to each time point is obtained to form a water level sequence corresponding to the area sequence, recorded as H_list = [H1, H2, ..., H i ,...,H N ], a total of N data, of which H i is the lake water level at the i-th moment; according to the water level and area data at different time points, the volume calculation formula of the prism is used to estimate the water storage difference to form a water storage sequence corresponding to the area sequence, which is recorded as R_list=[V1,V1+ΔV2,...,V i-1 +ΔV i ,...,V N-1 +ΔV N ], a total of N data, where V1 is the initial storage capacity, when A1 is 0, V1 is equal to 0, ΔV i is the difference in water storage between the i-th and i-1-th values, and the calculation formula is: Among them, A i is the lake surface area at the i-th moment, H i is the lake water level at the i-th moment; According to the obtained area sequence, water level sequence and water storage sequence, the water level-water storage relationship curve and the water level-area relationship curve are fitted, where the lake area corresponding to the lake bottom water level is 0 and the lake water storage is 0; Step 3: Distributed hydrological model construction: A distributed hydrological model is constructed, which is characterized by the use of grid-type computing units, and the computing grid can cover the entire basin; the model is constructed based on water balance and energy balance equations, comprehensively considering the interaction of climate, topography, soil properties, and vegetation, and supports runoff calculation. The hydrological and meteorological elements that can be calculated in the model include at least precipitation, ground evapotranspiration, water surface evaporation, surface runoff, and ground runoff; Step 4: Construction and calculation of the integrated hydrological-water scheduling model: First, the target basin is generalized into three units: flow-generating zones, lakes, and sections. On this basis, the topological relationship of each unit in the basin is analyzed, and the construction and calculation of the integrated hydrological-water scheduling model are carried out, which specifically includes the following steps: Step 4-1: Constructing a hydrological-water scheduling integrated model, including the following steps: Step 4-1-1: Based on the river network and lake-depression distribution analyzed in step 1, the target watershed is divided into different runoff-generating sub-areas. The runoff of each runoff-generating sub-area unit flows into the lake or cross-section unit, and a generalized topological map of the watershed unit is produced; Step 4-1-2: Based on the confluence paths of the lakes in the basin, associate each runoff zone with the distributed hydrological model calculation grid divided in step 3, and associate each runoff zone with several calculation grids; Step 4-1-3, associate the lake with the distributed hydrological model calculation grid divided in step 3. The calculation grid covered by the lake surface does not perform runoff calculation, and only considers rainfall and evaporation; Step 4-1-4, construct the basin topology relationship, which reflects the upstream and downstream relationship of each flow-generating partition, lake and section, and includes the association between the basin generalization unit and the distributed hydrological model calculation grid, and manages the basin topology relationship data in JSON files; Step 4-1-5, manage the characteristic data of each lake unit in the basin in a JSON file; the characteristic data of each lake unit includes name, water level curve, area curve, water storage curve, lake overflow outlet elevation, lake overflow outlet width and initial water level elevation; Step 4-2: Calculate the hydrological-water scheduling integrated model, including the following steps: Step 4-2-1: Use the distributed hydrological model to simulate the hydrological process of the entire basin for several years. The time step of the model output is 1 day. Step 4-2-2, read in the watershed topological relationship data in step 4-1-4 and the characteristic data of the lake unit in step 4-1-5; Step 4-2-3: Based on the calculation results in step 4-2-1, as well as the relationship between the runoff generating zones, lakes and the distributed hydrological model calculation grid, calculate the multi-year average monthly runoff of each runoff generating zone, and calculate the multi-year average monthly precipitation and monthly evaporation of each lake; Step 4-2-4, perform water storage calculation for each unit in the basin; read the inflow data of each unit from upstream to downstream in sequence according to the basin topology, and synthesize the flow if there are multiple upstream flows; perform storage calculation for lake units, analyze the lake's water storage capacity and discharge capacity based on the lake water level-storage capacity curve, as well as the bottom elevation and width of the overflow outlet, calculate the multi-year average monthly inflow, precipitation, evaporation, storage capacity, water level, overflow of each lake, and calculate the lake surface area change process based on the water level-area curve; Step 4-2-5, traverse all units in the watershed and complete the calculation; Step 5: Construction of water storage optimization model: The optimization algorithm is combined with the hydrology-water quantity scheduling integrated model constructed in step 4 to construct a water storage optimization model; Step 6: Lake water storage optimization calculation: Use the water storage optimization model constructed in step 5 to perform optimization calculations to obtain the optimized overflow elevation of each lake in the basin.

2. The method for optimizing the calculation of water storage in inland lakes considering flood control and ecological impact according to claim 1 is characterized in that: The specific process of managing the watershed topology relationship data in JSON files as described in step 4-1-4 is as follows: manage the watershed generalization unit in the form of a JSON object, which includes the properties of "Name", "Id", "Type", "NextId", and "Grid". The "Name" property stores the name of the unit. The "Id" property stores the unit code, which is unique among all units. The "Type" property stores the type of the unit, which is "Watershed" for runoff units, "Reservoir" for lake units, and "Section" for cross-section units. The "NextId" property stores the code of the downstream unit of the unit, which is the "Id" of the first unit downstream of the unit according to the watershed topology. When the unit is the most downstream unit in the watershed topology, that is, the tail lake, "NextId" is -1. When the unit is a runoff partition or lake type, it contains the "Grid" property, which is an array type and stores the distributed hydrological model calculation grid number associated with the unit.

3. The method for optimizing the calculation of water storage in inland lakes considering flood control and ecological impact according to claim 1 is characterized in that: The specific process of managing the characteristic data of each lake unit in the basin in a JSON file as described in step 4-1-5 is: manage the lake unit in the form of a JSON object, which includes the attributes "Name", "H_list", "A_list", "R_list", "E", "B", "E_ini"; among them, the "Name" attribute saves the name of the unit; the "H_list" attribute saves the water level curve obtained in step 2; the "A_list" attribute saves the area curve obtained in step 2; the "R_list" attribute saves the water storage curve obtained in step 2; the "E" attribute saves the lake overflow elevation; the "B" attribute saves the lake overflow width; the "E_ini" attribute saves the initial water level elevation calculated for lake storage.

4. The method for optimizing the calculation of water storage in inland lakes considering flood control and ecological impact according to claim 1 is characterized in that: The optimization algorithm used in step 5 is a genetic algorithm, a particle swarm algorithm or a SCE-UA algorithm.

5. The method for optimizing the calculation of water storage in inland lakes considering flood control and ecological impact according to claim 2 is characterized in that: The optimization variable of the water storage optimization model constructed in step 5 is the overflow elevation of other lakes in the basin except the tail lake, and the variable range is set from the current overflow elevation to the top elevation of the discharge project within the feasible range of the project; The constraint condition of the water storage optimization model is that the water level of the tail lake does not exceed the overflow level; In the lake unit in step 4-1-4, add the adaptability index attribute of plants and animals in the flooded area of ​​the lake, and name the different adaptability indexes of plants and animals in sequence as "Index_1, Index_2...", with the value range of 0 to 1, where 1 represents the strongest adaptability; The optimization objective function of the water storage optimization model is set to minimize the weighted sum of the suitability indexes of the relative areas of each lake in the basin, that is, the increase in the flooded area of ​​the lake has the least impact on the suitability of the species, as shown in the following formula: Where Area i is the area of ​​the ith lake in the basin; Area_Max i is the maximum area of ​​the i-th lake in the basin under current conditions, that is, the lake area corresponding to the overflow outlet elevation; N' is the number of lakes in the basin; M is the number of species considered for suitability; Index_i_j is the suitability index of the j-th species in the inundation impact area of ​​the i-th lake.

Images