A method for simulating environmental exposure concentrations of chemical substances in lakes at a basin scale

Abstract

The present disclosure provides a method for simulating the environmental exposure concentration of chemical substances in lakes that meets the scale of a watershed, including: dividing the lake into regions according to a division rule to obtain multiple partitions, and recording the geometric parameters of each partition, the division rule including a first rule that the only water outlet and the water inlet of the lake are divided into different partitions and a second rule that the regional division meets the needs of chemical substance concentration management; calculating the calculated water flow rate between each partition on the same day and the calculated water outflow rate of the water outflow partition based on the daily hydrological data from the watershed hydrological model, the estimated value of the water level of each partition and the geometric parameters; optimizing and adjusting the partition by adjusting the water level or volume of the partition based on an optimization index, the optimization index including a first index related to the calculated water outflow rate of the water outflow partition on the same day and a second index related to the water flow rate between each partition on the same day; calculating the daily chemical concentration of the adjusted partition based on the chemical substance data from the watershed hydrological model.

Description

Technical Field

[0001] The present disclosure relates to the fields of chemical environmental risk analysis, environmental risk assessment, and environmental risk management, and more specifically, to a method for simulating the environmental exposure concentration of chemical substances in lakes at a basin scale. Background Art

[0002] High-precision simulation of toxic and hazardous chemicals is essential for exposure assessment and risk assessment of emerging chemical pollutants in the context of new pollutant control. Existing basin-scale chemical simulation models often adopt a holistic approach for lakes within a basin. This means that lakes are not regionalized and the behavior of chemicals within the lakes is assumed to be uniform across horizontal space. This is common in basin-wide multi-media chemical simulations. User requirements primarily focus on the distribution of chemical concentrations in soil, river sections, and air within different land units, with less attention paid to differences in chemical concentrations at different locations within a lake. This is often sufficient for small lakes, with rapid inflow and outflow, low water demand, and relatively simple ecosystem service functions. For example, the SWAT-KM model adheres to the design of the SWAT (Soil and Water Assessment Tool) basin hydrological model, taking a holistic view of lakes within a basin (including natural lakes, artificial lakes, and reservoirs). This model enables daily coordinated simulation of chemicals in the lake water and sediment phases and watershed units (sub-basins and river sections).

[0003] Numerous lake models exist for simulating lakes, a typical example being the Environmental FluidDynamics Code (EFDC) model. This model spatially grids lakes and constructs a hydrodynamic model of lake flow using a combination of mass and motion equations. This allows for high-precision simulations in both time (with very low time steps, such as seconds or minutes) and spatial locations (with grid resolution down to meters). Obviously, a lake model designed solely for lake simulations without integration with a watershed would struggle to capture the complex migration and transformation of chemicals within multiple spatial units and media within the basin. However, combining a lake model with a watershed hydrological model allows for daily coordinated simulation of chemical species in the lake's water phase (sometimes including the sediment phase) and watershed units (sub-basins, river sections). The technical bottleneck here lies in achieving spatiotemporal integration of the lake model with the watershed hydrological model.

[0004] Hydrodynamic lake models offer higher temporal precision, and ideally, they should be integrated with watershed hydrological models with the same high temporal resolution. However, the practical challenge is that high-precision chemical exposure simulations are often required only for lakes within larger watersheds. Using high temporal resolution for such large watersheds can be inefficient or even wasteful. This is because high temporal resolution requires high spatial resolution to be effective. High temporal and spatial resolution in large watershed simulations significantly increases the computational load, creating a computational resource barrier and making it impossible to meet the demands of large-scale watershed-scale chemical exposure assessments. Furthermore, for watershed hydrological models, high temporal and spatial resolution often refers to gridded models, such as the TOPKAPI-ETH model. These models are computationally intensive and suitable for simulating short-term precipitation events, but are not suitable for long-term large-scale watershed simulations (e.g., decades or decades). Furthermore, in many cases, their high temporal resolution advantage is not fully utilized. Given the same level of basic data, they do not necessarily outperform hydrological models with daily resolution, such as the SWAT model.

[0005] High-precision hydrodynamic lake models are coupled with daily-resolution hydrological models, such as the EFDC model coupled with the SWAT model. SWAT provides daily-resolution simulation values ​​(such as lake discharge and sediment inflow), which are then assumed to be evenly distributed throughout the day or to have a temporal distribution within a single day as boundary conditions for the EFDC model. However, this very practice of amortizing daily inputs to a higher temporal resolution introduces significant uncertainty, significantly obscuring the simulation capabilities and utility of high-precision hydrodynamic lake models. This apparent high accuracy, due to limited reliability, effectively results in lower-precision simulation results. Furthermore, in this coupled model, the slow computational speed of the lake model often becomes a bottleneck in the simulation process, hindering the long-term simulation of large-scale chemical substances in watersheds.

[0006] In summary, the lake models in related technologies can only meet basic simulation needs, and there are technical bottlenecks in how to connect the lake model with the basin hydrological model in time and space. If the temporal resolution of the basin hydrological model is improved for docking, there will be problems such as waste of computing resources, and it is not suitable for long-term simulation. Summary of the Invention

[0007] The purpose of the present disclosure is to provide a method for simulating the environmental exposure concentration of chemical substances in lakes that meets the basin scale, so as to solve at least one of the problems existing in the prior art.

[0008] To achieve the above objectives, the present disclosure adopts the following technical solutions:

[0009] The present disclosure provides a method for simulating the environmental exposure concentration of chemical substances in lakes that meets the watershed scale, comprising:

[0010] Divide the lake into zones according to a division rule to obtain multiple zones, and record geometric parameters of each zone. The division rule includes a first rule and a second rule. The first rule divides the lake's only outlet and the lake's inlet into different zones, and the second rule ensures that the zone division complies with chemical substance concentration management requirements.

[0011] Calculate the daily flow rate between each zone and the daily outflow rate of the outlet zone including the outlet based on the daily hydrological data from the watershed hydrological model, the estimated water level of each zone, and the geometric parameters of each zone;

[0012] Based on the optimization index, the partition is optimized and adjusted by adjusting the partition water level or the partition volume to obtain an adjusted partition, wherein the optimization index includes a first index related to the calculated value of the water outflow of the water outflow partition on the same day and a second index related to the water flow between each partition on the same day;

[0013] The chemical concentrations of each adjusted subarea were calculated based on the chemical data from the watershed hydrological model.

[0014] Optionally,

[0015] The first indicator is a ratio of a first value to a second value, wherein the first value is the difference between the calculated outflow flow of the outflow zone on the day and the actual outflow flow of the lake on the day, and the second value is the product of the first preset ratio value and the actual profit or loss value of the lake flow on the day; and / or,

[0016] The second indicator is the sum of the first weighted proportion values ​​of each partition, the first weighted proportion value of the partition is the product of the first proportion value of the partition and the weight, the first proportion value of the partition is the absolute value of the ratio of the daily flow profit and loss value of the partition to the daily inflow flow value of the partition, and the weight is the ratio of the daily inflow flow value of the partition to the sum of the daily inflow flow values ​​of each partition.

[0017] Optionally, the optimizing and adjusting the partition by adjusting the partition water level or the partition volume based on the optimization index includes:

[0018] Determine whether the first indicator is less than the first threshold and whether the second indicator is less than the second threshold:

[0019] If the first indicator is greater than or equal to the first threshold and the second indicator is less than the second threshold, the partition is optimized by adjusting the water level of the partition on that day. After the optimization and adjustment, the calculated water flow rate between the partitions on that day and the calculated outflow flow rate of the outflow partition on that day are recalculated and re-judged;

[0020] If the first indicator is less than the first threshold and the second indicator is greater than or equal to the second threshold, the partition is optimized by adjusting the partition volume. After the optimization and adjustment, the calculated water flow rate of the day between each partition and the calculated water flow rate of the water outlet zone on the day are recalculated and re-judged;

[0021] If the first indicator is greater than or equal to the first threshold and the second indicator is greater than or equal to the second threshold, then when the first indicator is greater than or equal to the second indicator, the partition is optimized by adjusting the partition water level; when the first indicator is less than the second indicator, the partition is optimized by adjusting the partition volume. After the optimization and adjustment, the calculated water flow rate of the day between each partition and the calculated water outflow rate of the water outflow zone are recalculated and re-judged;

[0022] If the first indicator is less than the first threshold and the second indicator is less than the second threshold, the optimization adjustment is ended.

[0023] Optionally, adjusting the partition water level includes:

[0024] Adjust the water level of the partition with the largest absolute value of daily flow profit or loss in each partition to lower the first indicator; or

[0025] Adjust the water level of each partition in batches to lower the first indicator.

[0026] Optionally, adjusting the partition volume includes:

[0027] The partition with the largest first weighted ratio value is selected as the first partition, and a partition that has water flow exchange with the first partition is selected as the second partition. The volume of the first set ratio of the first partition is divided into the second partition, or the volume of the first set ratio of the second partition is divided into the first partition.

[0028] Optionally, adjusting the partition volume further includes:

[0029] According to the volumes of the first partition and the second partition after the first set ratio of the volume of the first partition is divided into the second partition or the first set ratio of the volume of the second partition is divided into the first partition, the water levels of the first partition and the second partition and the geometric parameters including adjacent side lengths and plane areas are updated respectively.

[0030] Optionally, selecting a partition that exchanges water flow with the first partition as the second partition includes:

[0031] The zone with the largest water flow exchange value with the first zone on that day shall be the second zone; or

[0032] The partition that has the greatest impact on the daily flow profit and loss value of the first partition is used as the second partition.

[0033] Optionally, adjusting the partition volume includes:

[0034] The partition with the largest water flow exchange value with the first partition on that day is used as the second partition for iterative volume division until the second indicator is less than the third threshold or the number of iterations reaches the fourth threshold;

[0035] Execute the volume division cycle for the first set number of times. One volume division cycle includes: taking the partition that has the greatest impact on the daily flow profit and loss value of the first partition as the second partition and iterating the volume division for the second set number of times, and then taking the partition that has the largest daily water flow exchange value with the first partition as the second partition and iterating the volume division for the third set number of times.

[0036] Optionally, the volume value of a single volume division is set according to the maximum first weighted ratio value of each partition, and is reduced by a second set ratio when a first constraint condition is not satisfied, wherein the first constraint condition includes:

[0037] The volume value of a single volume division is less than or equal to the product of the second preset ratio value and the volume of the first partition and the product of the second preset ratio value and the volume of the second partition;

[0038] The volume of the first partition after volume division is greater than or equal to the product of the third preset ratio value and the volume of the first partition;

[0039] A water level change value of the first partition after volume division and a water level change value of the second partition after volume division are less than or equal to a fifth threshold.

[0040] Optionally, calculating the chemical substance concentration of each adjusted partition on the day includes:

[0041] Determine whether the actual value of lake outflow on that day is zero:

[0042] If not, the chemical concentrations in each adjusted partition are calculated based on the one-dimensional advection-diffusion equation;

[0043] If so, the chemical concentration of each adjusted partition is calculated according to a one-dimensional advection-diffusion equation based on the set number of reentry times and combined with the reentry flow attenuation.

[0044] The beneficial effects of the present disclosure are as follows:

[0045] The method provided by the present disclosure for simulating the environmental exposure concentration of chemical substances in lakes at a watershed scale can scientifically divide lakes into zones. The resulting zones are reasonable in terms of chemical substance migration and diffusion, meeting chemical substance concentration management requirements (including monitoring requirements, etc.). Even in the absence of lake information such as water level data, the zones can be optimized and adjusted to ensure the scientific and reasonable nature of the zone results, thereby accurately simulating the environmental exposure concentration of chemical substances in lakes. Based on the design of the present disclosure for chemical substance concentration management requirements, the lake model can be directly connected to the watershed hydrological model, allowing lake chemical substance concentration simulation to be performed without increasing the temporal resolution of the watershed hydrological model. This improves the calculation speed while ensuring the simulation quality of the zoned chemical substance concentration simulation, and facilitates long-term simulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The specific embodiments of the present disclosure will be further described in detail below with reference to the accompanying drawings.

[0047] Figure 1 A flow chart of a method for simulating environmental exposure concentrations of chemical substances in lakes that meets the watershed scale, provided by an embodiment of the present disclosure, is shown.

[0048] Figure 2 A schematic diagram of the overall process of the method for simulating the environmental exposure concentration of chemical substances in lakes that meets the watershed scale provided by an embodiment of the present disclosure is shown.

[0049] Figure 3 Schematic diagram showing the zoning plan distribution of lakes.

[0050] Figure 4 Show Figure 3 Schematic diagram of the quasi-rectangular flow setting and the equal-area circles between the lake partitions shown.

[0051] Figure 5 A schematic diagram showing a process of optimizing and adjusting partitions.

[0052] Figure 6 Schematic diagram showing the zoning plan distribution of the lake in the example.

[0053] Figure 7 The diagram shows the simulated daily concentration dynamic changes of a chemical substance in each zone of the lake in the example.

[0054] Figure 8 Schematic diagram showing the quarterly average concentration of a chemical substance in each lake section and the lake's inflow and outflow river sections in the example.

[0055] Figure 9A schematic diagram of the structure of a computer system of an apparatus for implementing the method for simulating the environmental exposure concentration of chemical substances in lakes that meets the watershed scale provided by an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0056] To more clearly illustrate the present disclosure, the present disclosure is further described below in conjunction with the embodiments and drawings. Similar components in the drawings are represented by the same reference numerals. Those skilled in the art should understand that the specific description below is illustrative rather than restrictive and should not be used to limit the scope of protection of the present disclosure.

[0057] In the description of the present disclosure, it should be noted that the orientation or positional relationship indicated by the terms "upper" and "lower" is based on the orientation or positional relationship shown in the accompanying drawings, and is only for the convenience of describing the present disclosure and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present disclosure. Unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be internal communication between two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present disclosure can be understood according to the specific circumstances.

[0058] It should also be noted that, in the description of the present disclosure, relational terms such as first and second, etc., are merely used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply the existence of any such actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variants thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further restrictions, an element defined by the statement "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or device comprising the element.

[0059] The present disclosure provides a method for simulating the environmental exposure concentration of chemical substances in lakes that meets the watershed scale, such as Figure 1 As shown, the method includes steps S1, S2, S3, and S4. Steps S1, S2, and S3 are lake area division steps, constituting a lake area division method. Step S4 is a step for simulating the daily chemical concentration of each lake area after the lake area division. Steps S1, S2, S3, and S4 are described as follows:

[0060] S1. Divide the lake into multiple zones according to the division rules, and record the geometric parameters of each zone. The division rules include a first rule and a second rule. The first rule divides the lake's only outlet and the lake's inlet into different zones. The second rule ensures that the zone division meets the requirements of chemical substance concentration management.

[0061] In a possible implementation, when the first rule and the second rule are satisfied, the division rule further includes:

[0062] The third rule is that the plane area of ​​the water inlet containing the lake should correspond to the water flow rate of the water inlet, that is, the plane area of ​​the water inlet zone with a larger water flow rate should be larger;

[0063] The fourth rule is that the water depth (lake depth) and lake bottom roughness data within the subarea are relatively uniform;

[0064] The fifth rule is that the plane shape of the partition should be as close to a circle or a square as possible.

[0065] It can be understood that the first and second rules are high-priority rules, and the third, fourth and fifth rules are low-priority rules. For the regional division of lakes, the high-priority rules must be met first, and then the low-priority rules can be considered on this basis.

[0066] In a specific example, the inventors found that, based on the actual needs analysis of chemical environmental exposure assessment and risk assessment, there is a need for differentiated levels of chemical concentrations in several areas of a lake. In this embodiment, the chemical concentration management needs of lake zoning include, for example: monitoring points are set up at different locations in a lake, and it is necessary to estimate and compare the daily changes in chemical concentrations in the waters where the monitoring points are located. Some areas of the lake have water use needs (agricultural, ecological, industrial, etc.), and it is necessary to focus on fluctuations in chemical concentrations in this area. A certain area of ​​the lake is a gathering place or habitat for a certain important species (aquatic organisms, waterfowl, etc.), and it is necessary to pay attention to the chemical concentration levels in this area, and so on.

[0067] In this embodiment, the chemical concentration management requirements for lake zones have the following characteristics:

[0068] The lake only needs to be divided into a small number of zones in plane, and the plane area of ​​each zone is not required to be close or even the same. The regional division does not require universal spatial high resolution.

[0069] For the chemical concentrations (or environmental exposure concentrations of chemical substances) in lake zones, daily concentrations (or daily simulations) are sufficient, without having to focus on hourly or finer time resolutions.

[0070] Chemical concentrations in lake subregions should vary in concert with the environmental behavior of chemicals in the watershed to enable long-term simulations.

[0071] Therefore, the aforementioned division rules established in step S1 balance scientific considerations with testing requirements. This ensures that the initial division of the lake area in step S1 is rational and easily integrates with the multimedia daily simulation results of chemicals in the watershed. The first rule ensures seamless integration between the zoning simulation and the watershed simulation, preventing chemicals introduced by individual inflowing sections from flowing directly out of the outlet without passing through other zones (i.e., avoiding "short-circuiting"), thus ensuring scientific validity. The second rule ensures that the zoning can serve practical management needs. This rule can, for example, be reflected in the establishment of zones at monitoring points and the division of areas where important species gather into zones. The third rule facilitates integration with the watershed simulation and facilitates the rapid optimization and adjustment of the zones later. The fourth rule ensures that differences within zones do not significantly affect the migration and diffusion of chemicals, thereby ensuring the rationality of the assumptions used in subsequent calculations. The fifth rule ensures that the zone flows and the migration and diffusion of chemicals based on zone flows in this embodiment are more reasonable.

[0072] The first to fifth rules constitute rule set I, e.g. Figure 2 As shown, step S1 divides the lake into regions according to rule set I.

[0073] For example Figure 3 The lake shown has 4 inlets (i.e., the lake has 4 inlet river sections or rivers flowing into the lake, i.e., the upstream river sections of the lake, including the main stream) and 1 outlet (i.e., the lake has 1 outlet river section). Based on the rule set I, the lake is divided into 7 zones. The 4 inlets are divided into zones ①, ②, ④, and ⑥ respectively, the outlet is divided into zone ⑤, and zones ③ and ⑦ have no external water flow connection. It should be emphasized that, if Figure 3 As shown, although Figure 3 The water inlet and outlet at the middle and lower part (the outlet is Figure 3 The outlet weir position in the middle of the river, connecting to the downstream river section) is close to the river section, but it cannot be divided into the same zone. Figure 3 As shown in the figure, it is divided into partitions ⑥ and ⑤ respectively. Even if the plane area of ​​partition ⑥ is relatively small, it is necessary to do so. In addition, if Figure 3 As shown, the plane shapes of the seven partitions are relatively square, without any strange or narrow shapes.

[0074] S2. Calculate the calculated water flow rate between each zone and the calculated water flow rate of the outlet zone including the outlet based on the daily hydrological data from the watershed hydrological model, the estimated water level of each zone and the geometric parameters of each zone.

[0075] Continuing with the above example, this embodiment hopes to meet the needs of lake zone concentration simulation in the basin-scale chemical exposure simulation with the support of simple and easily available data. The application conditions and settings of this embodiment include: (1) It is used in conjunction with the basin-scale chemical exposure simulation model or the basin hydrological model, and the basin simulation results provide basic simulation data for lake zone simulation, such as the inflow river section (upstream river section) and outflow river section (downstream river section) when the lake is taken as a whole. The water flow, sediment content and content of various chemical forms of the inflow and outflow are clearly identifiable, and the inflow and outflow are simulated. (2) The lake has the characteristics of a shallow lake, that is, the "lake flipping" phenomenon is not obvious, and the vertical water flow movement is significantly weaker than the horizontal water flow movement. (3) The number of lake zones required is relatively small. (4) The time resolution of the lake zone simulation chemical exposure concentration is the same as that of the basin hydrological model, both of which are daily values. (5) The lake has basic geometric terrain data, including water depth distribution, water level value, water outlet form and its parameters (such as weir height, weir width, etc.), lake surface data (such as water surface map), etc. (6) The lake has only one outlet (or outflow section, outlet section).

[0076] The specific steps of step S2 include:

[0077] After obtaining multiple partitions in step S1, the geometric parameters and water levels of each partition are obtained. The basic assumptions include: the water depth and other hydrodynamic properties within each partition are the same, and the center position of each partition plane is stable and unchanged (even if the partition is subsequently optimized and adjusted, the center position of the partition plane remains unchanged). The geometric parameters of the partition mainly include:

[0078] Water depth of each zone, in d i Represents the water depth of the i-th partition, and the water depth set of each partition is represented by {d}.

[0079] Partition plan area, As i represents the plane area of ​​the ith partition, and the set of plane areas of each partition is represented by {As}. Figure 4 As shown, the partition is approximated by equal-area circles to obtain partition quasi-circles. According to the plane area As of the i-th partition i The radius R of the equal area circle of the i-th partition can be calculated i ,For example Figure 4 The radius R in is the radius of the equal-area circle of partition ⑦.

[0080] Partition volume (also known as water storage capacity), V i Represents the volume of the i-th partition, and the volume set of each partition is represented by {V}. The volume V of the i-th partition i For example, the water depth d of the i-th partition can be i and the plane area As of the i-th partition i The product of is approximated, that is (Ignoring the impact of shore slope and lake bottom inequality).

[0081] The distance between the center points of the partitions, Ds i,j It represents the center point distance between the i-th partition and the j-th partition. The center point distance between each partition can be expressed in the form of a matrix, with {Ds i,j} indicates that the matrix {Ds i,j The diagonal values ​​of} are all 0.

[0082] The length of the adjacent edges between partitions is expressed in Al i,j represents the length of the adjacent edge between the i-th partition and the j-th partition, where Al i,j = 0 means that the i-th partition and the j-th partition are not adjacent. The adjacent side lengths between partitions can be expressed in the form of a matrix, with {Al i,j} represents the matrix {Al i,j} diagonal value Al i,i is the plane perimeter of the i-th partition.

[0083] The above-mentioned geometric parameters should be obtained based on the actual lake information. Based on remote sensing data or surveying data, after directly determining the geometric center of each partition in GIS software or plane graphics software, the distance matrix {Ds i,j} and the adjacent edge length matrix between each partition {Al i,j For example, take the partition ② in Figure 3 as an example. This partition is determined by the connecting line of nodes ABCDA. AB, BC, and CD are the adjacent edges between partition ② and ①, ⑦, and ③, respectively. Suppose their lengths are 15 km, 20 km, and 25 km, respectively. Segment AD is the lakeshore adjacent to partition ②, and its length is 35 km. Then the matrix {Al i,j The value of the second row (and of course the second column, the adjacent edge length matrix is ​​a symmetric matrix) is: Al 2,1 =15,Al 2,2 =15+20+25+35=95, Al 2,3 =25,Al 2,4 =0,Al 2,5 =0,Al 2,6 =0,Al 2,7 =20.

[0084] It should be noted that the water depth d of each sub-area can be reasonably determined or estimated by referring to actual data. If a water depth distribution map of the lake or a lake bottom elevation map is available, the map can be read against the sub-area and the spatial average value within the sub-area plane range can be recorded as the sub-area depth. Related to the water depth d is the water level h of each sub-area (expressed in elevation, or using the same elevation base point as the weir height), expressed in h. iThe water level of the i-th partition is represented by {h}. The user should provide an initial estimate of the water level geometry {h} for each partition.

[0085] In addition, the geometric dimensions of the outlet of the outlet partition (such as partition ⑤ in Figure 3) can be obtained based on actual data. For example, when a weir is used as the outlet, the weir width and the head elevation of the outlet partition should be obtained (the head elevation of the outlet partition is the water level of the outlet partition, expressed in h). o Indicates that the outlet elevation h of the outlet zone 出 =h o -H, H is the weir height) to ensure that the water flow rate can be calculated.

[0086] It should be noted that the water depth set {d} of each partition, the water level set {h} of each partition and the height of the outlet weir h o There is a certain correlation between these data, which are key data for determining the water flow between partitions. In the subsequent step S3, when iteratively optimizing and adjusting the partitions, adjusting the water level is to adjust the water level set {h} of each partition, which is a correction and adjustment of the water level estimate; adjusting the volume is to adjust the water depth set {d} of each partition, the plane area set {As} of each partition, the volume set {V} of each partition, and the adjacent edge length matrix {Al} between each partition. i,j Systematic adjustments to multiple data sets, including {h}, will also adjust the water level set {h} for each subarea, subject to the constraint that the overall lake volume remains unchanged. To reduce the pressure of subsequent optimization and adjustment in step S3 and accelerate algorithm convergence, the inference or estimation of water depth, water level, and other data based on actual data should be as accurate as possible.

[0087] After obtaining the geometric parameters of the above partitions, the calculated water flow rate between each partition and the calculated water flow rate of the outlet partition including the outlet are calculated based on the Chezy Equation as follows:

[0088] The Xie Cai formula is a widely used formula for calculating flow velocity in open channels (non-confined). It ignores differences in velocity distribution across streamline cross sections and only expresses a uniform flow velocity u. When calculating the daily flow velocity (flow rate) between lake sections, the Xie Cai formula is used in its following form:

[0089]

[0090] in,

[0091] u is the flow velocity between lake partitions, in m / s;

[0092] n m is the Manning coefficient of water flow between lake partitions, which can be used as the value of smoother river sections in the basin, for example, around 0.05;

[0093] Rh is the hydraulic radius, in m;

[0094] Sl is the hydraulic gradient, dimensionless.

[0095] The plane shapes of each lake partition are basically irregular. In this embodiment, the water flow between the lakes in the source-sink partition (when calculating the water flow between partitions, the upstream partition is called the source partition and the downstream partition is called the sink partition) is set according to the pseudo-rectangular flow, that is,

[0096] For the i-th partition as a source partition and the j-th partition as a sink partition, the water flow between the source and sink partitions is as follows:

[0097] The distance Ds between the center points of the i-th partition and the j-th partition (i.e., the source-sink partition) i,j is the length of the adjacent side Al between the i-th partition and the j-th partition (i.e. the source-sink partition) i,j The geometric length and width of the pseudo-rectangle can be obtained from the center point distance matrix {Ds i,j}、The adjacent edge length matrix between each partition {Al i,j}Get it directly.

[0098] Under the “quasi-rectangular” flow setting, the cross-sectional area Ax of water flow between the i-th partition and the j-th partition (i.e., the source-sink partition) is calculated as follows:

[0099]

[0100] During flow, the hydraulic radius Rh along the flow direction is calculated as follows:

[0101]

[0102] Among them, unlike other parameters, the hydraulic radius Rh needs to consider the impact of the lake shore on the partition of the adjacent lake shore, Ib i and Ib j They are binary variables of 0-1: If the i-th partition is adjacent to the lake shore, then Ib i The value is 1. If the i-th partition is not adjacent to the lake shore, Ib i The value is 0; if the jth partition is adjacent to the lake shore, Ib j The value is 1. If the jth partition is not adjacent to the lake shore, then Ib j The value is 0.

[0103] When the center position of each partition plane is stable, that is, the center position of each partition is fixed and the distance between the partitions is fixed and does not change with the partition optimization adjustment, when calculating the water flow based on the Xie Cai formula, the hydraulic gradient between the i-th partition and the j-th partition (i.e., the source-sink partition) is determined by the water level difference between the source-sink partitions:

[0104]

[0105] Under the above quasi-rectangular flow setting, the daily water flow rate u between the i-th partition and the j-th partition (i.e., the source-sink partition) can be calculated i,j and the water flow rate Q on that day i,j :

[0106]

[0107] The daily water flow between each partition can be expressed in the form of a matrix, with {Q i,j} indicates that the matrix {Q i,j} is an antisymmetric matrix with a diagonal of 0, that is, for any i, j, Q i,j = Q j,i .

[0108] For example, based on the simplified formula of the discharge flow of the rectangular thin-wall weir , where b is the weir width, h 出 =h o -H,h o is the outlet elevation of the outlet zone, H is the weir height, m ​​is the weir flow coefficient, and g is the acceleration of gravity (unit: m / s 2 ), the calculated value of the water discharge flow rate of the water discharge zone on the day Q can be calculated o .

[0109] In addition, the hydraulic radius Rh between the i-th partition and the j-th partition can also be combined i,j , hydraulic gradient Sl i,j and water flow rate u i,j , the turbulent diffusion coefficient generated by the water flow between the i-th partition and the j-th partition is calculated for the subsequent calculation of the chemical concentration of each partition. The turbulent diffusion coefficient generated by the water flow between the i-th partition and the j-th partition is:

[0110]

[0111] Among them, the turbulent diffusion coefficient D i,j Unit is m 2 / s, k is the von Karman constant (e.g. 0.40), dimensionless. The turbulent diffusion coefficient between each partition can be expressed in the form of a matrix, {D i,j}express.

[0112] S3. Based on the optimization index, the partition is optimized and adjusted by adjusting the partition water level or the partition volume to obtain the adjusted partition, wherein the optimization index includes a first index related to the calculated value of the water discharge flow of the water discharge partition on the same day and a second index related to the water flow between each partition on the same day.

[0113] In a possible implementation, in step S3,

[0114] The first indicator is a ratio of a first value to a second value, wherein the first value is the difference between the calculated outflow flow of the outflow zone on the day and the actual outflow flow of the lake on the day, and the second value is the product of the first preset ratio value and the actual profit or loss value of the lake flow on the day; and / or,

[0115] The second indicator is the sum of the first weighted proportion values ​​of each partition, the first weighted proportion value of the partition is the product of the first proportion value of the partition and the weight, the first proportion value of the partition is the absolute value of the ratio of the daily flow profit and loss value of the partition to the daily inflow flow value of the partition, and the weight is the ratio of the daily inflow flow value of the partition to the sum of the daily inflow flow values ​​of each partition.

[0116] The first indicator is that the daily flow surplus and deficit of the entire lake simulation must be consistent with the actual flow. Not only must the daily flow surplus and deficit of the entire lake simulation be consistent with the actual flow, but a reasonable lake area division result should also ensure that the daily flow surplus and deficit of each sub-area is consistent with its geometric dimensions (for example, the water depth d of the sub-area). i , the plane area of ​​the partition is As i , the sum of the lengths of the adjacent edges between the partition and other partitions Al i etc.) and water level h i This is essentially a process of solving the geometric shape of each partition - if a lake and its partitions have rich shape information, theoretically all parameters of all partitions and the daily flow between each partition can be solved. However, this embodiment is precisely aimed at insufficient lake information (for example, missing lake information such as water level data), or when it is not necessary to provide all lake information, the calculation requirements can also be met. In a reasonable lake area division result, the change in the water storage capacity of each partition in a daily average sense (that is, the flow profit and loss calculated by partition) should match the water inflow of the partition. There should not be a situation where some partitions store water quickly while other partitions store water slowly. This situation is a non-steady-state process and cannot be used as a representative state of each partition in a daily average sense. Therefore, this embodiment also designs the above-mentioned second indicator related to the daily water flow between each partition.

[0117] In step S3, two methods are provided for optimizing the partitions: adjusting the partition water level and adjusting the partition volume. The reason for proposing these two methods is that the partitions obtained by dividing the lake into regions in step S1 may have certain irrationalities in the plane division of the partitions (referring to the plane geometric properties, such as area size, etc.), or in the setting of the water level of each partition. As mentioned above, the water depth set {d} of each partition, the water level set {h} of each partition and the height of the outlet weir h o There is a certain correlation between these data, which are key data for determining the water flow between partitions. Adjusting the water level means adjusting the water level set {h} of each partition, which is a correction and adjustment of the water level estimate. When the first indicator does not meet the requirements, the water level is adjusted first. Adjusting the volume means adjusting the water depth set {d} of each partition, the plane area set {As} of each partition, the volume set {V} of each partition, and the adjacent edge length matrix {Al} between each partition. i,j}, under the constraint that the overall volume of the lake remains unchanged, the volume adjustment will also achieve the purpose of adjusting the water level set {h} of each partition. When the second indicator does not meet the requirements, the volume adjustment will be given priority.

[0118] Continuing with the above example, the optimization adjustment of the partitions performed in step S3 is a constrained partition optimization adjustment. The optimization adjustment should not violate the following basic constraints on water volume and water flow:

[0119] Optimization adjustment constraint 1: The inflow and outflow flows of the lake are consistent with the basin simulation results, that is, the upstream and downstream flow constraints;

[0120] Optimization adjustment constraint 2: If flow is formed between the i-th partition and the j-th partition, the water flow Q between these two partitions i,j The water level, location (center point distance), and geometric parameters (including depth, plane width, etc.) of these two partitions conform to Xie Cai's formula, i.e., hydraulic constraints;

[0121] Optimization adjustment constraint 3: The difference between all inflows of each partition (including inflows from the inflow section and inflows from other partitions) and all outflows (including outflows from the outlet and outflows to other partitions) is consistent with the water volume change of this partition, that is, the quality constraint.

[0122] For example Figure 5 As shown, the partition is being optimized and adjusted.

[0123] The first indicator is described as follows: after the geometric parameters of each partition are obtained in step S1, the daily water flow of each partition is calculated based on the Xie Cai formula, and the calculated daily flow profit and loss value of the entire lake simulation is summarized and compared with the actual daily flow profit and loss (i.e. , wQ kis the actual inflow of the k-th inlet of the lake on that day, InFSet is the number of inlets of the lake, wQ o The difference should be within a certain threshold, because the water flow between the zones on the same day does not involve the increase or decrease of the overall water volume of the lake on the same day. In fact, the overall flow profit or loss of the lake on the same day only needs to compare the calculated water flow value Q of the water outlet zone on the same day. o With the actual value wQ o Therefore, this embodiment designs the first indicator , and set a threshold of 10% of the actual flow surplus or deficit of the lake on that day (the first preset ratio value here is 10% as an example, which can be adjusted appropriately as needed):

[0124]

[0125] The second indicator is illustrated as follows: not only should the daily flow surplus and deficit of the entire lake simulation be consistent with the actual situation, but a reasonable lake area division result should also ensure that the daily flow surplus and deficit of each sub-area is consistent with its geometric dimensions (for example, the water depth d of the sub-area). i , the plane area of ​​the partition is As i , the sum of the lengths of the adjacent edges between the partition and other partitions Al i etc.) and water level h i This is essentially a process of solving the geometric shape of each partition - if a lake and its partitions have rich shape information, theoretically all parameters of all partitions and the flow between each partition can be solved. However, this embodiment is precisely aimed at insufficient lake information (for example, missing lake information such as water level data), or when it is not necessary to provide all lake information, the calculation needs can also be met. In a reasonable lake area division result, the change in the water storage capacity of each partition in a daily average sense (that is, the flow profit and loss calculated by partition) should match the water inflow of the partition. There should not be a situation where some partitions store water quickly while other partitions store water slowly. This situation is a non-steady-state process and cannot be used as a representative state of each partition in a daily average sense. For this reason, a second indicator is designed. :

[0126]

[0127] For each zone, the total inflow for the day is calculated based on the total inflow of all zones with which it is connected. and the total outflow for the day The indicator is calculated based on the ratio of the daily flow profit and loss to the total daily inflow. :

[0128]

[0129] Among them, wQi represents the daily inflow of the water inlet contained in the i-th partition, It represents the sum of the calculated daily inflow values ​​of all the partitions that have flow connections with the i-th partition to the i-th partition. Ie represents the sum of the calculated daily flow rates of all the partitions connected to the i-th partition; i It is a 0-1 binary variable, which takes the value of 1 when the i-th partition is the export partition, and 0 otherwise.

[0130] To speed up the second indicator The convergence speed of each partition in this embodiment is the index Add weight wt i The weight reflects the importance of the partition in terms of "sending and receiving" traffic, and is set as follows:

[0131]

[0132] in, Indicates the partitions sum.

[0133] In a possible implementation, in step S3, optimizing and adjusting the partition by adjusting the partition water level or the partition volume based on the optimization index includes:

[0134] Determine whether the first indicator is less than the first threshold and whether the second indicator is less than the second threshold:

[0135] If the first indicator is greater than or equal to the first threshold and the second indicator is less than the second threshold, the partition is optimized by adjusting the water level of the partition on that day. After the optimization and adjustment, the calculated water flow rate between the partitions on that day and the calculated outflow flow rate of the outflow partition on that day are recalculated and re-judged;

[0136] If the first indicator is less than the first threshold and the second indicator is greater than or equal to the second threshold, the partition is optimized by adjusting the partition volume. After the optimization and adjustment, the calculated water flow rate of the day between each partition and the calculated water flow rate of the water outlet zone on the day are recalculated and re-judged;

[0137] If the first indicator is greater than or equal to the first threshold and the second indicator is greater than or equal to the second threshold, then when the first indicator is greater than or equal to the second indicator, the partition is optimized by adjusting the partition water level; when the first indicator is less than the second indicator, the partition is optimized by adjusting the partition volume. After the optimization and adjustment, the calculated water flow rate of the day between each partition and the calculated water outflow rate of the water outflow zone are recalculated and re-judged;

[0138] If the first indicator is less than the first threshold and the second indicator is less than the second threshold, the optimization adjustment is ended.

[0139] Continuing with the previous example, Figure 5 As shown, in the process of iteratively adjusting the water level or volume for optimizing the partition, the first indicator should be reduced. and the second indicator As a goal, users can set the first indicator according to actual conditions The first threshold and the second indicator Considering that this embodiment is for lake zoning simulation under insufficient information, the simulated characteristics and required accuracy of each partition are set, for example, the first threshold and the second threshold are set to 0.1 respectively, in the first indicator and the second indicator When they are respectively less than 0.1, it can be considered that the partitioning level has been reached and the above-mentioned "constrained partitioning optimization adjustment" link is completed.

[0140] In a possible implementation, in step S3, adjusting the partition water level includes:

[0141] Adjust the water level of the partition with the largest absolute value of daily flow profit or loss in each partition to lower the first indicator; or

[0142] Adjust the water level of each partition in batches to lower the first indicator.

[0143] Continuing with the above example, if the setting or estimation of the water level of each zone is unreasonable, it will inevitably affect the simulated daily flow of each zone and cause the outflow of the lake on that day (that is, the outflow of the outlet zone on that day) to deviate from the actual value. In this case, adjusting the geometric properties of each zone will not be effective. Therefore, by reducing the first indicator As the main goal, adjusting the water level is used as the main iterative optimization operation.

[0144] For example Figure 5 As shown, in determining the first indicator Greater than or equal to the second index Specifically, the reason for incorrect (or inaccurate) water levels in each zone is uncertainty. If the user believes that the water levels in each zone are more accurate (for example, some of them are measured values ​​or estimates based on historical measured values), and the water elevation of the outlet zone is inaccurate (for example, it is only a rough estimate), the water level of each zone should be adjusted; otherwise, the water level of each zone should be adjusted in batches (increase or decrease together).

[0145] When the water level data is determined to be relatively accurate, the water level of individual partitions is adjusted;

[0146] When it is determined that the water level data is relatively inaccurate, the water levels of each partition are adjusted in batches.

[0147] Among them, the water level of individual zones can be adjusted by identifying the zones that need to adjust the water level according to the principle of the largest absolute value of the flow surplus or loss on that day, that is, .

[0148] Whether adjusting the water level of a single partition or adjusting the water level of all partitions in batches, the water level adjustment (increase or decrease) should be directed towards reducing the first indicator. The water level adjustment amount (or adjustment step) δh of each water level adjustment can be reasonably set based on the balance of iteration steps and stability according to actual experience. For example, the water level adjustment amount δh and the first indicator can be constructed. The empirical relationship is used to adaptively and dynamically determine the water level adjustment amount δh for each water level adjustment.

[0149] In a possible implementation, in step S3, adjusting the partition volume includes:

[0150] The partition with the largest first weighted ratio value is selected as the first partition, and a partition that has water flow exchange with the first partition is selected as the second partition. The volume of the first set ratio of the first partition is divided into the second partition, or the volume of the first set ratio of the second partition is divided into the first partition.

[0151] Continuing with the previous example, adjusting the partition volume is an effective way to change the partition size and thus improve the daily flow between adjacent partitions.

[0152] For example Figure 5 As shown, in determining the first indicator Less than the second index In the case of Specifically, incorrect (or inaccurate) partition volume, large differences between partition shape and equal area circle, etc. are all physical reasons for needing to adjust the volume. This embodiment proposes a practical strategy, namely, to select The partition with the largest value is used as the first partition mx, that is, Then, a partition that has water flow exchange (or flow connection) with the first partition mx is selected as the second partition mi, and the first set proportion of volume δV of the first partition mx is divided into the second partition mi, or the first set proportion of volume δV of the second partition mi is divided into the first partition mx, so as to reduce the second index. purpose.

[0153] In a possible implementation, in step S3, selecting a partition that exchanges water flow with the first partition as the second partition includes:

[0154] The zone with the largest water flow exchange value with the first zone on that day shall be the second zone; or

[0155] The partition that has the greatest impact on the daily flow profit and loss value of the first partition is used as the second partition.

[0156] In a possible implementation, in step S3, adjusting the partition volume includes:

[0157] The partition with the largest water flow exchange value with the first partition on that day is used as the second partition for iterative volume division until the second indicator is less than the third threshold or the number of iterations reaches the fourth threshold;

[0158] Execute the volume division cycle for the first set number of times. One volume division cycle includes: taking the partition that has the greatest impact on the daily flow profit and loss value of the first partition as the second partition and iterating the volume division for the second set number of times, and then taking the partition that has the largest daily water flow exchange value with the first partition as the second partition and iterating the volume division for the third set number of times.

[0159] Continuing with the previous example, Figure 5 As shown, this embodiment proposes two strategies for selecting the second partition mi: FM strategy and BM strategy.

[0160] Under the FM strategy, the dual partition with the maximum flow exchange value of the day with the first partition mx (the dual partition is the partition with flow exchange or flow connection) is selected as the second partition mi. For example, if the first partition mx itself is the water outlet partition, the second partition mi is selected as the maximum inflow source partition of the day of the first partition mx; otherwise, the second partition mi is selected as the maximum outflow sink partition of the day of the first partition mx (that is, the dual partition with the largest outflow of the first partition mx).

[0161] Under the BM strategy, the dual partition that contributes most to the daily flow profit or loss of the first partition mx is selected as the second partition mi. For example, if the outflow of the first partition mx itself is greater than the inflow, the second partition mi is selected as the sink partition with the largest outflow of the first partition mx on that day. Otherwise, the second partition mi is selected as the source partition with the largest inflow of the first partition mx on that day.

[0162] Through experiments, the inventors found that the FM and BM strategies, when used continuously or simply alternated during iteration, were ineffective, with limited effectiveness, slow convergence, and the potential for falling into local optima. Therefore, this embodiment proposes a strategy that randomly uses the FM and BM strategies according to a random mechanism II, which can achieve the good effect of increasing convergence speed and preventing falling into local optima. The design of random mechanism II is described as follows:

[0163] First, in the initial stage of iterative adjustment, the FM strategy is used to select the second partition mi and iteratively adjust the volume until the second index <0.3 or the number of iterations reaches 300;

[0164] Then, the BM strategy is used to select the second partition mi and iteratively adjust it 3 times, and then the FM strategy is used to select the second partition mi and iteratively adjust it 3 or 4 times. The above is iteratively executed 6-7 times in one cycle.

[0165] In one possible implementation, in step S3, the volume value of a single volume division is set according to the maximum first weighted ratio value of each partition, and is reduced by a second set ratio if a first constraint condition is not satisfied, wherein the first constraint condition includes:

[0166] The volume value of a single volume division is less than or equal to the product of the second preset ratio value and the volume of the first partition and the product of the second preset ratio value and the volume of the second partition;

[0167] The volume of the first partition after volume division is greater than or equal to the product of the third preset ratio value and the volume of the first partition;

[0168] A water level change value of the first partition after volume division and a water level change value of the second partition after volume division are less than or equal to a fifth threshold.

[0169] In one possible implementation, in step S3, adjusting the partition volume further includes:

[0170] According to the volumes of the first partition and the second partition after the first set ratio of the volume of the first partition is divided into the second partition or the first set ratio of the volume of the second partition is divided into the first partition, the water levels of the first partition and the second partition and the geometric parameters including adjacent side lengths and plane areas are updated respectively.

[0171] Continuing with the previous example, Figure 5 As shown in the figure, the constraint design in the iterative volume adjustment process is as follows: after each iterative adjustment of the partition volume, the new and old volume ratio θ of the first partition mx and the second partition mi is calculated respectively, and the new and old volume ratio θ is calculated according to θ 1 / 3 The water depth d of the updated partition and the adjacent side length Al between the first partition mx and the second partition mi are scaled by mi,mx , according to θ 2 / 3 The updated partition's planar area As is scaled as follows:

[0172] , , , ,

[0173] After scaling the above, if the second partition mi and the first partition mx are still constructed based on equal-area circles, the sum of their volumes will not be consistent with the adjusted volume. The entire lake area can be treated as a whole and normalized based on the total volume of the lake area:

[0174]

[0175] in, It represents the sum of the volumes of all partitions before this adjustment. Indicates the sum of the volumes of all partitions except the first partition mx and the second partition mi before this volume adjustment.

[0176] In this way, the volume of the lake is ensured to remain consistent before and after various simulated assumptions and volume adjustment operations.

[0177] Dividing the volume δV of the first set ratio of the first partition mx to the second partition mi or dividing the volume δV of the second partition mi to the first partition mx will produce a systematic change of "volume division → volume change of the second partition mi and the first partition mx → water level change of the second partition mi and the first partition mx (water depth change will cause water level change) → flow change between the second partition mi and the first partition mx and their respective adjacent partitions → change of each partition". Therefore, the volume division amount δV should be reasonably set and can be dynamically adjusted. It can be adjusted according to the volume of the first partition mx. The initial value of the volume partition amount δV is set, and the value of the volume partition amount δV is lowered when the volume partition constraint condition is not met, for example Figure 5 Adjust the volume division amount δV value shown in the figure to 2 / 3 of the current value (for example, rounded to Figure 5 The volume division constraint conditions proposed in this embodiment are as follows:

[0178] Conditional formula (1), δV≤0.1min(V mx,old ,V mi,old ); Conditional formula (2), V mx,new =V mx,old -δV≥0.1V mx,original ; Conditional formula (3), max(|h mx,new -h mx,old |,|h mi,new -h mi,old |)≤0.01m.

[0179] That is, the single volume division amount δV shall not be greater than 10% of the original volume of the second partition mi and the first partition, and the new volume of the first partition mx after volume division shall not be less than the volume of the first partition when the partition was initially set (V mx,original) and must not cause the water level in the first and second partitions mx and mi to change by more than 1 cm. These three constraints reflect the requirements for robust volume adjustment, consideration of various realistic considerations for the partitioning in step S1, and robustness of the exchange flow between partitions.

[0180] S4. Calculate the chemical concentration of each adjusted zone on the day based on the chemical substance data from the watershed hydrological model.

[0181] In a possible implementation, in step S4, calculating the daily chemical concentration of each adjusted partition includes:

[0182] Determine whether the actual value of lake outflow on that day is zero:

[0183] If not, the chemical concentrations in each adjusted partition are calculated based on the one-dimensional advection-diffusion equation;

[0184] If so, the chemical concentration of each adjusted partition is calculated according to a one-dimensional advection-diffusion equation based on the set number of reentry times and combined with the reentry flow attenuation.

[0185] Continuing with the previous example, let's first explain the principle of the one-dimensional advection-diffusion equation:

[0186] The differential equation of the one-dimensional advection-diffusion equation (ADE) is as follows:

[0187]

[0188] Where C is the concentration of the chemical substance, which is a function of time t and spatial position x, and the unit is kg / m 3 ; u is the one-dimensional flow velocity, unit is m / s; D is the turbulent diffusion coefficient; k is the degradation rate constant, unit is 1 / s.

[0189] In the lake zoning simulation, the following boundary conditions apply:

[0190]

[0191]

[0192] Where C0 is the average chemical concentration of the delay process at time 0, in kg / m 3 ; C in is the average chemical concentration at the inlet section, in kg / m 3 .

[0193] The analytical expression of the one-dimensional advection-diffusion equation (ADE) under the above boundary conditions is:

[0194]

[0195] Where erfc is the error complement function.

[0196] The application of the one-dimensional advection-diffusion equation (ADE) in this embodiment is described below.

[0197] (1) One-dimensional advection-diffusion equation (ADE) for estimating the concentration of the partitioned water phase

[0198] In actual operation, the total concentration of water phase in this partition simulated yesterday is taken as the average concentration C0 of the time delay process at time 0, and the source of inflow to this partition (including the inflow river section and the flow matrix Q mat The total concentration of water-phase chemical substances in the zone (determined to flow into this zone) is taken as C in , by substituting the velocity u and turbulent diffusion coefficient D calculated according to Xie Cai's formula into the above analytical formula (d), the chemical concentration C(x,t) at each time and location in this zone can be calculated. Of course, in actual calculations, if the vertical mixing diffusion coefficient D of the lake caused by meteorological conditions is taken into account, m , then the turbulent diffusion coefficient D in the above analytical formula (d) should be the turbulent diffusion coefficient D caused by the water flow between the partitions and the vertical mixing diffusion coefficient D m Substitute the sum.

[0199] For example, you can continue to follow Figure 4 The equal-area circle approximates the partitioning method shown in the figure. The radius R of the equal-area circle of the partition is used as x, and C(R,t) is obtained as the concentration of the representative concentration of the partition at time t. Furthermore, a day is divided into 24 hours, and C(R,t) is calculated for each hour. The average value is taken as the average concentration of the partition on that day:

[0200]

[0201] Among them, C j represents the average chemical concentration of the jth partition on that day, R j The radius of the circle of equal area representing the jth partition.

[0202] Assuming that the flow velocity u and turbulent diffusion coefficient D and other parameters related to hydrodynamic conditions and the biodegradation rate k are relatively stable within a day, it is generally acceptable. Therefore, the formula (e) for the average concentration of the same day in the above partition is acceptable as the 24-hour average value. However, if the chemical substance has obvious photodegradation properties, it is not appropriate to set the average concentration of the chemical substance C in the jth partition on the same day based on the biodegradation rate k. j , but the biodegradation rate k should be allowed to change with time t in the above analytical formula - specifically, the hourly water surface incident light intensity, lake body extinction coefficient, etc. can be calculated in detail according to the calendar and geographical location. This embodiment does not make further settings for this.

[0203] 2. Estimation of dissolved concentration in the partitioned aqueous phase

[0204] With water flowing between partitions, not only can the chemical substances be approximated by the migration-diffusion equation, but the suspended solids (also called suspended sediment, Suspended Solids) in the water phase (watertable) can also be set by analogy with equations (a)-(d), except that the degradation rate constant here is not degradation, but the settling rate of suspended solids. In addition, the migration-diffusion equation of suspended solids between partitions is approximated based on the actual daily inflow of sediment wSed at the kth inlet of the lake from the daily hydrological data of the basin hydrological model. k Using S to represent the suspended solids concentration and ks to represent the suspended solids settling rate, we can list the concentration expression and daily average concentration expression for suspended solids:

[0205]

[0206]

[0207] Among them, S j is the suspended solids concentration of the jth partition on the day, S0 is the average suspended solids concentration of the time delay process at time 0, S in is the average suspended solids concentration at the inlet section.

[0208] The suspended solid concentration S in the jth zone on that day j With the support of j The dissolved concentration in the water phase of the partition can be further calculated by the equilibrium distribution method - using the organic carbon-water partition coefficient K of the chemical substance oc and the ratio of organic carbon in suspended solids f oc .

[0209] The following describes how to calculate the chemical concentrations in each partition using the one-dimensional migration-diffusion equation combined with return flow attenuation under the water storage mode (i.e., when the actual discharge flow of the lake on that day is zero).

[0210] When there is outflow from the lake, the concentration of chemical substances in each partition can be directly calculated using the one-dimensional advection-diffusion equation. However, if there is no outflow from the lake on a certain day (i.e., wQ o= 0, the lake is in "storage mode"), the results of directly solving the one-dimensional advection-diffusion equation may have significant deviations. This is because the simulation in this embodiment assumes that the flow between each sub-zone reaches a relatively stable state within a day, and the diffusion coefficient is estimated based on this state. The diffusion result is the concentration distribution of the chemical substances. However, in the storage mode (where the river inflow continues to flow), the flow carried by the river can easily reach the outlet sub-zone in a relatively short period of time (e.g., a few hours). If the flow reaches the outlet sub-zone but does not leak out, the diffusion of these chemical substances cannot fully reflect the results of one-dimensional advection-diffusion. However, the sub-zones near the inlet can still partially reflect the above-mentioned one-dimensional advection-diffusion results.

[0211] Therefore, this embodiment proposes to use “return decay virtual flow” to approximate the chemical diffusion estimation under the water storage mode. The chemical concentration distribution estimation of each partition is recorded as {C o=0}, where the subscript o=0 is short for out=0, which means there is no outflow from the lake or the flow is zero. The specific steps and design are as follows:

[0212] Based on the water level {h} of the previous day in the "water storage mode", the geometric parameters of the optimized partitions and the water flow matrix {Q i,j}, turbulent diffusion coefficient matrix {D i,j}, conventionally applying the aforementioned one-dimensional advection-diffusion equation, we obtain the estimated chemical concentration distribution in each partition {C}. To illustrate the characteristics of the water storage mode, the results of this round of calculations are marked with the subscript 0: {Q i,j}0、{D i,j}0, {C}0.

[0213] In the first round of return calculation, the flow between each partition is set to be completely "reverse" from the flow of the previous round marked as 0, and the flow is weakened. The calculation results of this round are marked with subscript 1. Based on experience and the principle of potential energy dissipation, it is more reasonable to calculate the return flow value of this round as 40% of the flow of the previous round, but in the opposite direction, that is,

[0214]

[0215] At the same time, the turbulent diffusion coefficient of this round is also converted to 40% of the previous round (no direction problem), that is,

[0216]

[0217] Then, with {C}0 as the initial state, the water flow matrix {Q i,j}1. Turbulent diffusion coefficient matrix after the first round of return calculation {D i,j}1 is substituted into the one-dimensional advection-diffusion equation to calculate the new chemical substance concentration distribution {C}1 in each partition.

[0218] In the second round of return calculation, the flow between each partition is set to be completely "reverse" from the flow of the previous round, and the flow is weakened. The return flow value of this round is calculated as 70% of the flow of the previous round, but in the opposite direction, that is,

[0219]

[0220] At the same time, the turbulent diffusion coefficient of this round is also converted to 70% of the previous round (no direction problem), that is,

[0221]

[0222] Then, with {C}1 as the initial state, the water flow matrix {Q i,j}2. Turbulent diffusion coefficient matrix after the second round of return calculation {D i,j}2 is substituted into the one-dimensional advection-diffusion equation to calculate the new chemical substance concentration distribution {C}2 in each partition.

[0223] After the first and second rounds of setting the return virtual flow and applying one-dimensional migration diffusion as mentioned above, better results can usually be obtained, that is, the concentration distribution of the partition far from the estuary into the lake is partially retained and the influence of the partition on the estuary into the lake gradually weakens and returns to a nearly completely mixed concentration distribution.

[0224] This type of return virtual flow uses a one-dimensional flow diffusion method. Since the water flow matrix {Q i,j}, turbulent diffusion coefficient matrix {D i,j}, the estimation of chemical concentration distribution in each partition {C} and its calculation logic are relatively simple in program implementation and have good application value.

[0225] The inventors have found that, generally, two rounds of excursions (as described above) are sufficient to meet this requirement. Further excursions may lose the ability to approximate the phenomenon of "the gradually diminishing influence of subregions beyond the lake estuary on the lake estuary." In this case, it may be preferable to simulate directly on the "water storage day" using a simplified fully mixed model (that is, abandoning the pursuit of subregional concentration distribution differences and returning to the single-unit simulation of the entire lake in watershed simulation). Of course, for specific simulation cases, the inventors believe that appropriately increasing the number of excursions may also be beneficial.

[0226] In summary, in the lake chemical concentration simulation method provided by this embodiment, the lake regional division can scientifically divide the lake into regions, and the resulting partitions are reasonable in terms of chemical migration and diffusion, meeting the chemical concentration management needs. In the case of missing lake information such as water level data, the partitions can be optimized and adjusted to ensure the scientific and reasonable results of the partitions, thereby accurately simulating the environmental exposure concentration of chemical substances in the lake. Based on the design of this embodiment for the chemical concentration management needs, the lake model can be directly connected to the basin hydrological model, and the lake chemical concentration simulation can be performed without improving the time resolution of the basin hydrological model. While ensuring the simulation quality of the partitioned chemical concentration simulation, the calculation speed can be improved, and it is conducive to long-term simulation.

[0227] The lake chemical substance concentration simulation method provided by this embodiment is further illustrated below through a specific example.

[0228] Take the simulation of a lake (denoted DL) in a pilot watershed (denoted YD) as an example. The method provided in this embodiment is implemented using Fortran code, forming a relatively independent module, Module LKZ, which is then integrated and interoperated with the SWAT-KM model, a watershed-scale environmental exposure simulation model. Using the SWAT-KM model, including Module LKZ, a zoned simulation of Lake DL in the YD watershed was performed, implementing all aspects of this embodiment and enabling systemic simulation of multiple media within the watershed, including soil, river sections, air, and vegetation.

[0229] Other watershed data (including meteorological data) and parameters required by SWAT-KM are omitted here. Only the input and output required for the DL lake zoning simulation involved in this embodiment are described.

[0230] like Figure 6 As shown, the DL Lake area is divided into seven zones based on inflow and outflow. These zones correspond to local monitoring sites and reflect the needs of lake chemical management. Zone 5 is the outlet zone, home to the lake's single outlet. Zones 2, 3, and 7 all have multiple inflows, while Zone 6 has neither inflow nor outflow. Zone sizes are designed to minimize the average annual inflow. With the exception of Zones 4 and 7, all other zones are relatively square.

[0231] The water depths of each DL lake zone are estimated based on publicly available data on the lake bed elevation, average water level, and water depth. Data such as the outlet weir elevation and width are publicly available. The water level elevations of each zone are set based on publicly available data on flow direction and measured data for certain locations and seasons. This allows for a certain degree of error, estimated to be no more than 10 cm, and is set at 0.05 m. Because outlet weir elevation data is more accurate, the water level adjustment strategy of this embodiment primarily utilizes batch adjustment.

[0232] Based on the above simple data settings, the SWAT-KM model including the LKZ Module can realize daily multi-media simulation of the YD Basin, including the DL lake zone simulation. For example, the simulation runs smoothly from the beginning of 2008 to the end of September 2024. The comparison curves of the simulated values ​​and actual values ​​of the daily concentration changes of a certain harmful chemical in each zone during the example period are as follows: Figure 7 The curve groups of Lake Zone #1, Lake Zone #2, Lake Zone #3, Lake Zone #4, LakeZone #5, Lake Zone #6 and Lake Zone #7 shown in the figure have seven curve groups: the colored curves are the simulated daily concentration values ​​of a certain chemical substance in the partition, and the gray curves are the simulated daily concentration values ​​of the corresponding chemical substances in other partitions (as a control, showing the coordinated and unequal concentration dynamics in different partitions of the lake). Figure 7 In the figure, the horizontal axis is day, and the vertical axis is the concentration of chemical substances, the unit is mg / m 3 .

[0233] After comparing with the actual monitoring results, the local concentration (indicated by the concentration of the sampling point in the sub-area and river section) simulated by this embodiment on the same day is consistent with the monitoring sampling concentration. Based on the daily simulation results of the lake sub-area and the daily simulation results of other units in the basin simulated in conjunction with it, the average value within a certain statistical period can be plotted. As an example, Figure 8 The quarterly average values ​​of water concentration in the YD Basin (including DL Lake and surrounding river sections) are shown in the table. Figure 8 As shown, the colors of the partitions and river sections represent the concentration values. The redder the color, the greater the concentration value. The numbers 16, 19, 20, 21, 43, 28, 39, 47, etc. are the unit numbers in the simulation.

[0234] Using the SWAT-KM model linked to the LKZ module, calculated based on the CPU-marked code start and end times on a personal computer (configuration: CPU Intel i7-10700 2.9 GHz, 4 cores, 16GB of RAM, 2TB of hard drive, Windows 10), reduced time by 93% compared to linking the SWAT-KM model to the EFDC model (with a time resolution set to 10 minutes). Simulation results from the SWAT-KM model linked to the EFDC model showed no significant advantage over those from the SWAT-KM model including the LKZ module, indicating no better agreement with the monitoring data. This demonstrates that, given limited input information, the lake zoning simulation method designed in this embodiment can achieve significantly faster computational speeds than algorithms linking a watershed model to a hydrodynamic model while maintaining simulation quality. This provides a better foundation for conducting long-term, continuous simulations, which is precisely what is required in environmental exposure assessments and environmental risk assessments of chemical substances.

[0235] like Figure 9 As shown, a computer system suitable for implementing the basin-scale simulation method for environmental exposure concentrations of chemical substances in lakes provided in the above-mentioned embodiments includes a central processing unit (CPU), which can perform various appropriate actions and processes based on programs stored in read-only memory (ROM) or programs loaded from a storage unit into random access memory (RAM). The RAM also stores various programs and data required for the operation of the computer system. The CPU, ROM, and RAM are connected to each other via a bus. An input / output (I / O) interface is also connected to the bus.

[0236] The following components are connected to the I / O interface: an input section including a keyboard and mouse, etc.; an output section including a liquid crystal display (LCD) and speakers, etc.; a storage section including a hard disk, etc.; and a communication section including a network interface card such as a LAN card and a modem. The communication section performs communication processing via a network such as the Internet. Drives are also connected to the I / O interface as needed. Removable media such as magnetic disks, optical disks, magneto-optical disks, and semiconductor memories are installed in the drives as needed, allowing computer programs read from these media to be installed in the storage section as needed.

[0237] In particular, according to this embodiment, the process described in the flowchart above can be implemented as a computer software program. For example, this embodiment includes a computer program product comprising a computer program tangibly embodied on a computer-readable medium, the computer program containing program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via a communication component and / or installed from a removable medium.

[0238] The flowcharts and schematic diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the system, method and computer program product of the present embodiment. In this regard, each box in the flowchart or schematic diagram can represent a module, program segment or part of code, and the part of the above-mentioned module, program segment or code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the schematic diagram and / or flowchart, and the combination of boxes in the schematic diagram and / or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0239] As another aspect, this embodiment further provides a non-volatile computer storage medium. This non-volatile computer storage medium may be the non-volatile computer storage medium included in the apparatus described in the above embodiment, or may be a standalone non-volatile computer storage medium not incorporated into a terminal. The non-volatile computer storage medium stores one or more programs. When executed by a device, the device implements the basin-scale method for simulating environmental exposure concentrations of chemical substances in lakes, as provided in the above embodiment.

[0240] As another aspect, this embodiment further provides a computer program product, including a computer program, which, when executed by a processor, implements the method for simulating the environmental exposure concentration of chemical substances in lakes that meets the watershed scale provided in the above embodiment.

[0241] Obviously, the above embodiments of the present disclosure are merely examples for clearly illustrating the present disclosure, and are not intended to limit the implementation methods of the present disclosure. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is impossible to enumerate all the implementation methods here. Any obvious changes or modifications derived from the technical solution of the present disclosure are still within the scope of protection of the present disclosure.

Claims

1. A method for simulating the environmental exposure concentration of chemical substances in lakes at a basin scale, characterized by: include: Divide the lake into zones according to a division rule to obtain multiple zones, and record geometric parameters of each zone. The division rule includes a first rule and a second rule. The first rule divides the lake's only outlet and the lake's inlet into different zones, and the second rule ensures that the zone division complies with chemical substance concentration management requirements. Calculate the daily flow rate between each zone and the daily outflow rate of the outlet zone including the outlet based on the daily hydrological data from the watershed hydrological model, the estimated water level of each zone, and the geometric parameters of each zone; Based on the optimization index, the partition is optimized and adjusted by adjusting the partition water level or the partition volume to obtain an adjusted partition, wherein the optimization index includes a first index related to the calculated value of the water outflow of the water outflow partition on the same day and a second index related to the water flow between each partition on the same day; Calculate the daily chemical concentrations for each adjusted subarea based on chemical data from the watershed hydrological model; The first indicator is a ratio of a first value to a second value, wherein the first value is the difference between the calculated outflow flow of the outflow zone on the day and the actual outflow flow of the lake on the day, and the second value is the product of the first preset ratio and the actual profit or loss value of the lake flow on the day; The second indicator is the sum of the first weighted proportion values ​​of each partition, the first weighted proportion value of the partition is the product of the first proportion value of the partition and the weight, the first proportion value of the partition is the absolute value of the ratio of the daily flow profit and loss value of the partition to the daily inflow flow value of the partition, and the weight is the ratio of the daily inflow flow value of the partition to the sum of the daily inflow flow values ​​of each partition.

2. The method according to claim 1, characterized in that The optimization adjustment of the partition by adjusting the partition water level or the partition volume based on the optimization index includes: Determine whether the first indicator is less than the first threshold and whether the second indicator is less than the second threshold: If the first indicator is greater than or equal to the first threshold and the second indicator is less than the second threshold, the partition is optimized by adjusting the water level of the partition on that day. After the optimization and adjustment, the calculated water flow rate between the partitions on that day and the calculated outflow flow rate of the outflow partition on that day are recalculated and re-judged; If the first indicator is less than the first threshold and the second indicator is greater than or equal to the second threshold, the partition is optimized by adjusting the partition volume. After the optimization and adjustment, the calculated water flow rate of the day between each partition and the calculated water flow rate of the water outlet zone on the day are recalculated and re-judged; If the first indicator is greater than or equal to the first threshold and the second indicator is greater than or equal to the second threshold, then when the first indicator is greater than or equal to the second indicator, the partition is optimized by adjusting the partition water level; when the first indicator is less than the second indicator, the partition is optimized by adjusting the partition volume. After the optimization and adjustment, the calculated water flow rate of the day between each partition and the calculated water outflow rate of the water outflow zone are recalculated and re-judged; If the first indicator is less than the first threshold and the second indicator is less than the second threshold, the optimization adjustment is ended.

3. The method according to claim 1 or 2, characterized in that The adjusting of the partition water level includes: Adjust the water level of the partition with the largest absolute value of daily flow profit or loss in each partition to lower the first indicator; or Adjust the water level of each partition in batches to lower the first indicator.

4. The method according to claim 1 or 2, characterized in that The adjusting the partition volume includes: The partition with the largest first weighted ratio value is selected as the first partition, and a partition that has water flow exchange with the first partition is selected as the second partition. The volume of the first set ratio of the first partition is divided into the second partition, or the volume of the first set ratio of the second partition is divided into the first partition.

5. The method according to claim 4, characterized in that The adjusting the partition volume further includes: According to the volumes of the first partition and the second partition after the first set ratio of the volume of the first partition is divided into the second partition or the first set ratio of the volume of the second partition is divided into the first partition, the water levels of the first partition and the second partition and the geometric parameters including adjacent side lengths and plane areas are updated respectively.

6. The method according to claim 4, characterized in that The selecting a partition that exchanges water flow with the first partition as the second partition includes: The zone with the largest water flow exchange value with the first zone on that day shall be the second zone; or The partition that has the greatest impact on the daily flow profit and loss value of the first partition is used as the second partition.

7. The method according to claim 6, characterized in that The adjusting the partition volume includes: The partition with the largest water flow exchange value with the first partition on that day is used as the second partition for iterative volume division until the second indicator is less than the third threshold or the number of iterations reaches the fourth threshold; Execute the volume division cycle for the first set number of times. One volume division cycle includes: taking the partition that has the greatest impact on the daily flow profit and loss value of the first partition as the second partition and iterating the volume division for the second set number of times, and then taking the partition that has the largest daily water flow exchange value with the first partition as the second partition and iterating the volume division for the third set number of times.

8. The method according to claim 6, characterized in that The volume value of a single volume division is set according to the maximum first weighted ratio value of each partition, and is reduced by a second set ratio when the first constraint condition is not met. The first constraint condition includes: The volume value of a single volume division is less than or equal to the product of the second preset ratio value and the volume of the first partition and the product of the second preset ratio value and the volume of the second partition; The volume of the first partition after volume division is greater than or equal to the product of the third preset ratio value and the volume of the first partition; A water level change value of the first partition after volume division and a water level change value of the second partition after volume division are less than or equal to a fifth threshold.

9. The method according to claim 1, characterized in that The calculation of the chemical substance concentration of each adjusted zone on the same day includes: Determine whether the actual value of lake outflow on that day is zero: If not, the chemical concentrations in each adjusted partition are calculated based on the one-dimensional advection-diffusion equation; If so, the chemical concentration of each adjusted partition is calculated according to a one-dimensional advection-diffusion equation based on the set number of reentry times and combined with the reentry flow attenuation.

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