A distributed hydrological modeling method for river-type reservoir areas

Abstract

The present invention provides a distributed hydrological modeling method for a river-type reservoir area, and belongs to the technical field of distributed hydrological modeling. First, the basic information required for establishing a distributed hydrological model of the reservoir area is obtained, including topographic data and hydrological and meteorological data, and a suitable grid scale is sought to provide a basis for modeling the distributed hydrological model. Secondly, the sub-basins and slope basins are divided, and runoff calculations are performed. Finally, the forecast performance of each flood is evaluated according to traditional evaluation indicators, and parameter calibration is performed. The present invention divides the reservoir area into sub-basins and slope basins through the establishment of a distributed hydrological model, and divides the slope basins into more refined slope hydrological response units, which can fully reflect the spatial variation characteristics of the underlying surface of the slope unit, and thus more accurately simulate the inflow of the slope basin.

Description

Technical Field

[0001] The invention belongs to the technical field of distributed hydrological modeling, and relates to a distributed hydrological modeling method for a river-type reservoir area. Background Art

[0002] The banks of the main river channels in river-type reservoirs are mostly high mountains and steep hills. In addition to the confluence of tributaries, runoff will directly and dispersedly flow into the main river channel from the slopes on both sides. Although the catchment area of ​​the slope area is small, the spatial span is large and the terrain and landform characteristics are highly variable, which makes the spatial distribution of water entering the main river channel very uneven.

[0003] At present, the existing lumped hydrological models do not fully consider the spatial heterogeneity of the slope area. The slope area is divided into a large basin for treatment. It can only simulate the runoff at the outlet of the basin, but cannot obtain the flow process at various locations along the main river channel in the slope basin, making it difficult to accurately describe the spatiotemporal variability of rainfall runoff in the reservoir area. Although the distributed basin hydrological model can simultaneously consider the spatial distribution and unevenness of rainfall, as well as the impact of the spatial variation of the underlying surface on the runoff of the basin, the modeling method of the river-type reservoir area is not refined enough, and it is difficult to meet the accuracy requirements of flood forecasting for important sections along the river-type reservoir area.

[0004] Therefore, according to the topographic and geomorphic characteristics of river-type reservoir areas, it is urgent to invent a distributed hydrological model that can describe the runoff generation and confluence process of the slope basin along the main river channel, so as to fully reflect the spatial variation characteristics of the underlying surface of the slope unit and accurately simulate the inflow conditions of the slope basin. Summary of the invention

[0005] In view of the problems existing in the prior art, the present invention provides a distributed hydrological modeling method for a river-type reservoir area.

[0006] The technical solution adopted by the present invention is:

[0007] A distributed hydrological modeling method for a river-type reservoir area is key to dividing the reservoir area into sub-basins and slope basins. At the same time, in order to further meet the fine modeling of the slope basin spatial scale, the slope basin is divided into finer slope hydrological response units. Specifically, the following steps are included:

[0008] The first step is to divide the watershed into different landform types

[0009] For river-type reservoirs, the precipitation-flow-confluence between watersheds can be divided into two situations according to the contact form with the main river (reservoir area). The two situations differ in the confluence mode. The sub-basin flow is concentrated into the reservoir in the form of point source, and the strip-shaped slope flow along the main river is distributed along the way.

[0010] 1.1 Division of sub-basins and slope basins

[0011] The present invention divides the reservoir area into two types: sub-basins and slope basins. The sub-basins have a stable water system, which is hydraulically connected to the main river channel in the form of contact points. According to the modeling method for closed basins, it is not necessary to obtain the precipitation-runoff process at various places in the river channel inside the sub-basin, and it is only necessary to output the runoff at the outlet of the sub-basin. The slope basin is in direct contact with the main river channel in the form of a surface, and there is no stable and complete water system in the slope basin, and the runoff will be dispersedly merged into the main river channel. The catchment area of ​​the slope basin is relatively small, but the slope basin extends over a large range on both sides of the main river channel, and the terrain and geomorphic features are highly variable. It is necessary to divide the slope basin into smaller-scale slope hydrological response units, fully considering the spatial heterogeneity of the underlying surface of the temporal and spatial variability of rainfall in the slope basin, and satisfying the fine modeling on the spatial scale.

[0012] 1.2 Determining the hydrological response unit threshold of the overland watershed

[0013] Due to the different interaction modes and confluence characteristics between sub-basins and slope basins and the main river, the requirements for the refinement of modeling are also different. In order to make the slope basin more refined, it is necessary to divide the slope area into more refined slope hydrological response units by setting soil type, land use type, and slope threshold.

[0014] In order to determine the refined slope hydrological response unit, the present invention refines the watershed unit by setting a combination of multiple and different threshold values, that is, after setting different land use type area thresholds, soil type area thresholds, and slope grade thresholds, they are arranged and combined, and the influence of different threshold combinations on the division of hydrological response units is experimentally analyzed, and finally a threshold combination that can take into account both simulation accuracy and calculation efficiency is obtained, and the hydrological response unit threshold of the slope watershed is determined, and then the number of slope hydrological response units into which the slope watershed is divided is finally determined.

[0015] Step 2: Grid scale selection

[0016] Distributed hydrological models can take into account the differences in the spatial distribution of hydrological elements in a watershed, and can realistically simulate the spatial changes in the runoff process in the watershed. To reflect this advantage, the construction of distributed hydrological models needs to be based on the watershed DEM data, and the watershed should be divided into several grids that can reflect the spatial heterogeneity of the watershed. At the same time, because the size of the grid will have a great impact on the simulation accuracy of runoff and the calculation efficiency of the model, this paper proposes a method framework for grid division that can simultaneously meet the simulation accuracy and calculation efficiency.

[0017] 2.1 Construction of grids at different scales

[0018] In the construction of hydrological models, the selection of different grid scales often has a great impact on the simulation results of hydrological models. Based on the national 30m×30m precision digital elevation data, the present invention resamples the original DEM data to different resolutions to establish DEMs of different grid scales.

[0019] The present invention adopts the three most commonly used resampling methods to resample the original DEM, namely the nearest neighbor method, the bilinear interpolation method and the cubic convolution method. Based on the DEM data obtained after resampling, the root mean square error (RMSE) is calculated, and finally the resampling method is selected according to the lowest RMSE value. The RMSE calculation formula is:

[0020]

[0021] In the formula, Z k is the grid elevation of the resampled DEM, z k is the elevation of the corresponding position of the benchmark data, and n is the number of grids after resampling.

[0022] 2.2DEM analysis and processing

[0023] The resampled DEM data is further analyzed and processed to obtain the basin attribute data, which is used as the basis for building a hydrological model. For the obtained basin water system, through data correction, depression filling and leveling, determining the flow direction, calculating the cumulative amount of confluence, setting the catchment area threshold, and extracting the basin river network, continuous river network data that conforms to the surface water flow mechanism and has a high degree of match with the actual river network is obtained. The specific steps are as follows:

[0024] ①DEM correction: The Agree method is used to detect and improve the accuracy of the surface elevation data of the DEM data. The surface elevation of the DEM is fine-tuned to maintain continuity and consistency with the river vector map data, thereby completing the correction of the DEM data.

[0025] ②DEM depression and flat land processing: The large amount of depression information in the DEM data will cause discontinuous water flow when conducting water flow analysis. In order to ensure the continuity of flow direction analysis, different processing methods are used to fill the two types of depressions. For an independent depression where the elevation data of the eight adjacent points around a point are all greater than the data of the point, when at least one of the eight adjacent points around the point is the outlet of the catchment area, the minimum value of the eight adjacent points around the point is assigned to this point; when there is no outlet of the catchment area around, find the point with the minimum elevation on the boundary line of the area, and assign its value to the filling point and eight adjacent points that are less than the value, so as to complete the filling of the independent depression. For a composite depression area with multiple valley bottom points, first start from each valley bottom, determine the position of the depression edge point and the exit point by reverse water flow, and then use the exit point elevation to replace the elevation of the point whose depression edge elevation is less than the value, and then assign this elevation data to the point whose exit point elevation is lower than the value, so as to complete the filling of the composite depression.

[0026] When a grid point has the same elevation value as the eight surrounding grids, the flat land needs to be processed to ensure that the water can flow out of the flat land area in a directional manner. A point with an elevation greater than that of the adjacent points is searched at the boundary of the flat land area, and it is marked as a safe point. The remaining points are marked as points to be processed, and the elevation of the points to be processed is increased slightly until all the points to be processed can be marked as safe points. At this point, the flat land processing is completed, and finally the DEM model can generate continuous river systems;

[0027] ③ Determination of water flow direction: In order to clarify the water flow direction in each cell, the present invention first compares the slope between the processed grid cell and the adjacent 8 grid cells, connects the center of the processed grid cell with the center of the grid cell with the largest slope among the adjacent 8 grid cells, and defines the connection direction as the water flow direction of the processed grid cell, that is, the flow rate of the water flow is determined using the D8 algorithm;

[0028] ④ Determination of catchment area and water system: The accumulated water flow at each grid point is the total amount of all grids that flow into this grid, that is, the cumulative confluence matrix. Based on the water flow direction of the grid, the cumulative confluence matrix of each grid can be calculated. Multiplying the cumulative confluence matrix with the grid area can obtain the upstream confluence area of ​​each unit grid.

[0029] However, not all grids with upstream catchment areas can form a river network. Only when the catchment area is greater than a certain threshold value, the grid will be counted as a grid in the river network. After connecting these grids according to the direction of water flow, a river network can be formed. In order to determine the catchment area threshold, the present invention establishes a relationship between the slope of the river network and the catchment area to explore the change of the relationship coefficient. Through trial calculation, when the catchment area threshold approaches a certain value, the relationship coefficient tends to be stable, and the catchment area threshold corresponding to this stable relationship coefficient is used as the most suitable catchment area threshold.

[0030] Step 3: Calculation of runoff generation and confluence of sub-basins and slope basins

[0031] 3.1 Calculation of runoff generation in sub-basins and slope basins

[0032] The runoff generation process of the sub-basin and the slope basin is consistent. Based on the determination of the grid scale, the present invention adopts a runoff model of a distributed hydrological model for both the sub-basin and the slope basin, which can simultaneously consider the two runoff generation mechanisms of full storage and over-seepage as well as the influence of temperature on the runoff simulation results.

[0033] The flow calculation for sub-basins and overland basins is as follows:

[0034] The infiltration capacity of a grid cell varies with space and can be expressed as follows:

[0035] f=f m [1-(1-C) 1 / B ] (2)

[0036] Where f is the infiltration capacity, f m is the maximum infiltration capacity, C is the area ratio where the infiltration capacity is less than or equal to f, and B is the infiltration capacity shape parameter.

[0037] According to the water balance formula, within a given time period P, it can be deduced that:

[0038] P=R1(y)+R2(y)+ΔW(y) (3)

[0039] y=R1(y)+ΔW(y) (4)

[0040] Where p represents the rainfall in the period; y represents the vertical depth; R1(y) represents the full flow; R2(y) represents the excess flow; ΔW(y) represents the change in soil moisture content;

[0041] The full flow (R1) and the change in soil moisture content (ΔW) in equations (3) and (4) can be expressed as:

[0042]

[0043]

[0044] Among them, i m represents the maximum water storage capacity; i0 represents the water storage capacity at a certain point; b represents the water storage shape coefficient;

[0045] From the above formula, we can infer that W p , the expression of R2 is:

[0046]

[0047]

[0048] Where B represents the infiltration capacity shape coefficient; Δt represents the calculation time step;

[0049] The base flow is calculated using the ARNO model, and the calculation formula is:

[0050]

[0051] Where D m is the maximum base flow, D s is the current base flow and D m The ratio of is the initial moisture content of the lower soil layer, is the maximum water content of the lower soil, W s is the water content ratio of the lower soil, R b For base flow.

[0052] 3.2 Calculation of sub-basin and slope basin flow

[0053] The present invention simulates the spatial evolution of precipitation-runoff in a river-type reservoir, adopts a "merge first, then perform" confluence method to calculate the confluence process of sub-basins and slope basins, and finely simulates the evolution process of runoff between grids.

[0054] For sub-basins, the grids are divided into two types: slope grids (excluding tributary rivers) and channel grids (including tributary rivers) according to whether the grid contains tributary rivers. In the slope grid, the runoff first flows into the nearby channel grid according to the topological relationship of the grid. This process is calculated using the unit line method based on probability distribution. Then the evolution of the runoff in the channel grid is described by the motion wave equation or impulse response function, and is calculated step by step along the channel grid unit to the sub-basin outlet section until it flows into the main river.

[0055] In the sub-basin confluence, the topological relationship between grids is determined according to the D8 flow direction algorithm introduced above, and the movement of runoff in each grid is calculated according to the slope confluence method.

[0056] In the slope watershed, the runoff is dispersed and directly merges into the main river channel, directly contacting the main river channel in the form of a surface. There is no process of calculation downward along the river channel. The process of the slope grid merging into the main river channel is described by the unit line method based on probability distribution.

[0057] ① Slope runoff calculation

[0058] When calculating the slope runoff, the present invention deduce the unit line from the probability distribution.

[0059] The probability density function of the two-parameter lognormal distribution is:

[0060]

[0061] In the formula, x>0, -∞<μ<∞, σ>0.

[0062] t p =exp(μ-σ 2 ) (11)

[0063] Substitute the above formula into the probability density function to solve it:

[0064]

[0065] t p With f(t p ) formula and multiply it to get:

[0066]

[0067] Taking the natural logarithm of both sides of the above equation, we get:

[0068] ln(t p )=μ-σ 2 (14)

[0069] but

[0070] μ=σ 2 +ln(t p ) (15)

[0071] Given t p and q p , we can solve μ and σ through the formula. In addition to the two-parameter lognormal distribution, we can also deduce the unit line through probability distribution functions such as the two-parameter Pareto distribution, the two-parameter Weibull distribution, and the two-parameter Frechet distribution.

[0072] ② Calculation of river confluence

[0073] The present invention aims at river-type reservoirs and adopts the existing mainstream efficient confluence calculation method to calculate the confluence, that is, the two river confluence schemes, kinematic wave (KWT) and impulse response function (IRF), are used to calculate the basin confluence. The KWT method is used for rivers with large bottom gradient, and the IRF method is used for general rivers. The calculation methods of the two methods are as follows:

[0074] a. Kinematic Wave Method (KWT)

[0075] The KWT method can calculate the wave velocity or flow rate from the hydrological response unit into an independent river section in each time period. It approximately assumes that the river channel is rectangular, and the hydraulic width and wave velocity C are functions of the river channel width ω, Manning coefficient n, riverbed gradient S0, and flow rate q. Among them, the riverbed gradient can be calculated from the river network data, and the flow rate q can be obtained from the above-mentioned slope confluence. The formula for determining the river channel width is as follows:

[0076]

[0077] The formula for calculating the wave speed in a river section is as follows:

[0078]

[0079] If the calculated estimated outflow time is before the end of the time period, then the wave flows into the downstream river section; otherwise, it is considered to be stranded in the current time period.

[0080] b. Impulse Response Function (IRF)

[0081] The IRF method is used to calculate the runoff output of a gridded land surface model, and can use either a gridded river network or a vector river network.

[0082] The mathematical development of the IRF method is based on the one-dimensional diffusion wave equation derived from the one-dimensional Saint-Venant equation.

[0083]

[0084] In the formula, q is the flow rate of the water section, x is the distance along the river channel, C represents the flow velocity, and D represents the diffusion coefficient.

[0085] The formula can be solved by convolution integral

[0086]

[0087] in

[0088]

[0089] Where U(ts) is the runoff depth generated at time ts.

[0090] When using the IRF method, it is only necessary to perform a unit line integral on each upstream river section, and then accumulate the flow calculation flows of all upstream river sections at the outlet river section to obtain the flow process. Compared with the KWT method, this method does not need to pay attention to the order of river sections and is more convenient to calculate.

[0091] Step 4: Distributed hydrological model parameter calibration

[0092] For distributed hydrological models, in order to avoid falling into local convergence points, a multi-objective optimization algorithm is used for parameter calibration. The core of this algorithm is to coordinate the relationship between the objective functions and find the Pareto optimal solution set that makes each objective function as large or small as possible. The present invention uses the NSGA-II algorithm for calibration.

[0093] The reservoir flood forecast focuses on the flood peak, flood volume, flood process line and flood spatial and temporal distribution. Therefore, when optimizing the parameters of the distributed hydrological model runoff model, two objective functions are set in the NSGA-II algorithm, namely, the minimum mean of the absolute value of the relative error of the flood runoff depth and the peak flow.

[0094]

[0095]

[0096] Where n is the number of flood events, R f (i) represents the simulated runoff depth of the ith flood, R m (i) represents the measured runoff depth of the i-th flood. f (i) represents the simulated flood peak of the i-th flood, Q m (i) represents the measured peak flood value of the i-th flood.

[0097] When optimizing the parameters of the confluence model, the maximum mean value of the flood deterministic coefficient (DC) is taken as the objective function:

[0098]

[0099] In the formula, Q if and Q im are the simulated flow and measured flow of the ith flood in the total flow process, The average measured flow rate for the total flow process.

[0100] At this point, the model parameters were obtained, and the construction of a distributed hydrological model for the river-type reservoir area was completed.

[0101] The effects and benefits of the present invention are as follows: the present invention divides the reservoir area into sub-basins and slope basins through the establishment of a distributed hydrological model, and divides the slope basins into more refined slope hydrological response units, which can fully reflect the spatial variation characteristics of the underlying surface of the slope unit, and further more accurately simulate the inflow conditions of the slope basin. BRIEF DESCRIPTION OF THE DRAWINGS

[0102] Figure 1 It is a 30m resolution DEM elevation map of the Three Gorges Reservoir area according to the implementation scheme of the present invention.

[0103] Figure 2 This is a diagram showing the grid division results of the Three Gorges Reservoir area according to an implementation plan of the present invention.

[0104] Figure 3 It is the output node diagram of the distributed hydrological model of the Three Gorges Reservoir area according to the implementation scheme of the present invention.

[0105] Figure 4 It is a schematic diagram of watershed division of the present invention.

[0106] Figure 5 It is a schematic diagram of the confluence process of the sub-basin and the slope basin of the present invention.

[0107] Figure 6 It is a technical roadmap for modeling distributed hydrological models in river-type reservoir areas of the present invention. DETAILED DESCRIPTION

[0108] Based on distributed hydrological modeling, the present invention proposes a distributed hydrological modeling method for a river-type reservoir area.

[0109] The present invention will be further described below by way of examples.

[0110] The Three Gorges Reservoir is a typical large-scale river-type reservoir. The water flow in the reservoir area presents a non-steady flow state. Under the influence of reservoir backwater and inflow, the water surface of the reservoir is not horizontal. The wedge-shaped storage capacity (dynamic storage capacity) formed by the backwater above the horizontal plane also regulates floods, and its flood regulation effect is often greater than the role played by the static storage capacity below the horizontal plane. At the same time, the Three Gorges Reservoir area has a humid subtropical monsoon climate, which is significantly affected by the canyon terrain. The annual rainfall is abundant, and the average rainfall for many years reaches 1150mm. There are many rivers and streams in the reservoir area, and the water system is well developed. There are many tributaries. In addition to the main stream of the Yangtze River and the two major tributaries of the Jialing River and the Wujiang River, there are also tributaries such as the Dahong River, Quxi River, Long River, Xiaojiang River, and Xiangxi River that continuously flow into the main river channel. In addition, the runoff will also be dispersed from the slopes around the reservoir and flow into the reservoir. The law of rainstorm floods in the reservoir area is very complicated. Therefore, we take this area as an example to explore the refined runoff theory and related distributed hydrological modeling methods of the Three Gorges Reservoir area, and accurately simulate the temporal and spatial evolution of precipitation and runoff in the Three Gorges Reservoir area. The specific steps are as follows:

[0111] The first step is to collect the basic hydrological and meteorological data, topographic data and other basic data required for the hydrological modeling of the reservoir area to drive the hydrological model to carry out detailed modeling of the runoff generation and confluence process of the Three Gorges Reservoir area. The DEM elevation data of the Three Gorges Reservoir area is selected with a resolution of 30m, such as Figure 1 As shown in the figure, 0.05° is used as the horizontal resolution of the distributed hydrological model grid, and then the entire Three Gorges Reservoir area is divided into 2854 orthogonal grids with a resolution of 0.05°×0.05° as the calculation units of the flow generation model of the basin. Figure 2 shown.

[0112] Step 2: Based on the DEM elevation data of the Three Gorges Reservoir area, ArcGIS tools were used to extract the boundary of the study area and the river network and sub-basin information in the area through processes such as filling depressions, generating flow directions, calculating cumulative flow, and dividing sub-basins. For sub-basins, the confluence calculation was performed by combining slope and river confluence.

[0113] Step 3: Through the constructed distributed hydrological model, the flow process of 54 nodes including 26 sub-basins and 28 main river slopes along the main river and the inflow of sub-basin intervals is output simultaneously, such as Figure 3 When calculating the flow process of a watershed node, the watershed is first divided, as shown in the figure. Figure 4 As shown in the figure, it contains 6 sub-basins and 2 slope basins (containing 6 and 3 hydrological response units respectively). The details are as follows:

[0114] ① For sub-basin 1 and sub-basin 2: the runoff of sub-basin 1 flows into the main river through node 6, and sub-basin 2 interacts with the main river through node 9;

[0115] ② For slope basins: the main river runs through them, and slope basin 1 is divided into 6 slope hydrological response units, and slope basin 2 is divided into 3 slope hydrological response units. The runoff of slope basin hydrological response units 1 to 6 is sequentially merged into the main river through nodes 1 to 6, and the runoff of slope basin hydrological response units 7 to 9 is sequentially merged into the main river through nodes 7 to 9;

[0116] ③ It indicates that the runoff simulation values ​​of nodes 1 to 9 in the basin can be used as the spatially continuous output of the hydrological model.

[0117] Then, the confluence calculation is performed, the details are as follows:

[0118] The confluence process between sub-basins and slope basins is as follows Figure 5 As shown (this example is compared to Figure 4 , the slope watershed is divided into more response units, a total of 10), the details are as follows:

[0119] ① Sub-basin confluence

[0120] a. The runoff of grid A first flows through slope grids D, E, and G to the nearby river grid H. After the runoff enters the river in grid H, it flows downstream along the river in the manner of river confluence and finally enters the main river through node 10.

[0121] b. The runoff from grid B flows into river grid H through slope grids C and F.

[0122] The confluence path of each grid, that is, the topological relationship between grids, is determined according to the D8 flow algorithm, and the movement of runoff in each grid is calculated according to the slope confluence method.

[0123] ②Slope watershed (hydrological response unit)

[0124] The slope watershed is divided into 10 slope hydrological response units. In slope hydrological response units 3, 4, 9, and 10, the runoff flows along the slope into the main river grids J, K, L, and M, and flows out directly through nodes 3, 4, 9, and 10 in grids J, K, L, and M.

[0125] Finally, the flow process can be obtained by using the river confluence calculation introduced in the previous text of the present invention.

[0126] Step 4: A multi-objective genetic algorithm was used to calibrate the parameters of the distributed hydrological model of the Yandu River Basin in the reservoir area. 26 floods in the basin from 2014 to 2021 were selected, with a peak range of 104-903m. 3 / s, covering large, medium and small floods of various magnitudes, and having good representativeness. The parameter calibration results are shown in Table 1. This example can fully prove the accuracy and reliability of the simulation results of the distributed hydrological model for river-type reservoir areas of the present invention.

[0127] Table 1 Flood simulation results along the Duhe River Basin

[0128]

[0129]

[0130] The average relative error absolute value of flood volume is 13.86%, the average relative error absolute value of flood peak is 19.32%, and the flood peak error is not more than 20% of the measured value, which is qualified. There are 21 qualified flow production events in Yandu River Basin, with a qualified rate of 80.8%, and 16 qualified flood peak events in Yandu River Basin, with a qualified rate of 61.5%. The average deviation of the secondary flood peak time in Yandu River Basin is 1.38h, of which 17 peak time deviations are less than or equal to 1h, accounting for 65.38%. Therefore, the distributed hydrological model proposed in the present invention has a good simulation effect on the runoff and flood peak in Yandu River Basin.

[0131] The above-described embodiments merely express the implementation methods of the present invention, but they cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that for those skilled in the art, several modifications and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention.

Claims

1. A distributed hydrological modeling method for a river-type reservoir area, characterized in that it comprises the following steps: The first step is to divide the watershed into different landform types 1.1 Division of sub-basins and slope basins The reservoir area is divided into two types: sub-basin and slope basin; 1.2 Determining the hydrological response unit threshold of the overland watershed Step 2: Grid scale selection 2.1 Constructing grids of different scales Resample the original DEM data to different resolutions to create DEMs of different grid scales; 2.2DEM analysis and processing The resampled DEM data is further analyzed and processed to obtain basin attribute data, based on which the hydrological model is constructed; for the obtained basin water system, data correction, depression filling and leveling, water flow direction determination, flow accumulation calculation, catchment area threshold setting, and basin river network extraction are performed to obtain continuous river network data that conforms to the surface water flow mechanism and has a high degree of match with the actual river network; In the third step, the distributed hydrological model constructed was used to simultaneously output the flow process of 54 nodes including 26 sub-basins and 28 main river slopes along the main river and the inflow of sub-basin intervals; when calculating the flow process of the basin node, the basin was first divided, and then the confluence calculation was performed; sub-basin and slope basin flow generation and confluence calculation: 3.1 Calculation of runoff in sub-basins and slope basins The runoff generation process of sub-basins and overland basins is consistent. Based on the determination of the grid scale, a distributed hydrological model that can simultaneously consider the two runoff generation mechanisms of full storage and over-seepage as well as the influence of temperature on the runoff simulation results is used for both sub-basins and overland basins. 3.2 Calculation of sub-basin and slope basin flow In the sub-basin confluence, the topological relationship between grids is determined according to the D8 flow algorithm, and the movement of runoff in each grid is calculated according to the slope confluence method; In the slope watershed, the runoff is dispersed and directly merged into the main river channel, and is in direct contact with the main river channel in the form of a surface. There is no process of routing down along the river channel. The process of the slope grid merging into the main river channel is described by the unit line method based on probability distribution. ① Slope runoff calculation When calculating the slope runoff, the unit line is derived from the probability distribution; ② Calculation of river confluence For river-type reservoirs, two river confluence schemes, kinematic wave KWT and impulse response function IRF, are used to calculate basin confluence. The KWT method is used for rivers with large bottom gradient, and the IRF method is used for general rivers. Step 4: Distributed hydrological model parameter calibration When optimizing the parameters of the distributed hydrological model, two objective functions are set in the NSGA-II algorithm, namely, the minimum mean of the absolute value of the relative error of the flood runoff depth and the flood peak flow. Where n is the number of flood events, R f (i) represents the simulated runoff depth of the ith flood, R m (i) represents the measured runoff depth of the i-th flood; Q f (i) represents the simulated flood peak of the i-th flood, Q m (i) represents the measured peak flood value of the i-th flood; When optimizing the parameters of the confluence model, the maximum mean value of the flood deterministic coefficient DC is taken as the objective function: In the formula, Q if and Q im are the simulated flow and measured flow of the ith flood in the total flow process, The average measured flow rate of the total flow process; At this point, the model parameters were obtained, and the construction of a distributed hydrological model for the river-type reservoir area was completed.

2. The distributed hydrological modeling method for a river-type reservoir area according to claim 1 is characterized in that: In the second step 2.1), the resampling methods are the nearest neighbor method, the bilinear interpolation method and the cubic convolution method respectively; Based on the DEM data obtained after resampling, the root mean square error RMSE is calculated, and finally the resampling method is selected according to the lowest RMSE value. The RMSE calculation formula is: In the formula, Z k is the grid elevation of the resampled DEM, z k is the elevation of the corresponding position of the benchmark data, and n is the number of grids after resampling.

3. The distributed hydrological modeling method for a river-type reservoir area according to claim 1 is characterized in that: In the step 2.2: the Agree method is used to detect and improve the accuracy of the surface elevation data of the DEM data, and the surface elevation of the DEM is fine-tuned to maintain continuity and consistency with the river vector map data, thereby completing the correction of the DEM data.

4. The distributed hydrological modeling method for a river-type reservoir area according to claim 1 is characterized in that: In the third step 3.2①), the unit line is derived using a two-parameter lognormal distribution, a two-parameter Pareto distribution, a two-parameter Weibull distribution, a two-parameter Frechet distribution or other probability distribution functions.

5. The distributed hydrological modeling method for a river-type reservoir area according to claim 1 is characterized in that: In the third step 3.2②), the motion wave KWT and impulse response function IRF are calculated as follows: a. KWT The KWT method can calculate the wave velocity or flow rate from the hydrological response unit into an independent river section in each time period. It approximately assumes that the river channel is rectangular, and the hydraulic width and wave velocity C are functions of the river channel width ω, Manning coefficient n, riverbed gradient S0, and flow rate q; among them, the riverbed gradient can be calculated from the river network data, and the flow rate q can be obtained from the above-mentioned slope confluence; the formula for determining the river channel width is as follows: The formula for calculating the wave speed in a river section is as follows: If the calculated estimated outflow time is before the end of the time period, then the wave flows into the downstream river section, otherwise it is considered to be stranded in the current time period; b. Impulse response function IRF The IRF method is used to calculate the runoff output of the gridded land surface model. A gridded river network or a vector river network can be used. When using the IRF method, it is only necessary to perform a unit line integral on each upstream river section, and then accumulate the flow calculation flow of all upstream river sections at the outlet river section to obtain the flow process. This method does not need to pay attention to the order of river sections.

6. The distributed hydrological modeling method for a river-type reservoir area according to claim 1 is characterized in that: In step 3.1, the flow calculation of sub-basin and slope basin is as follows: The infiltration capacity of a grid cell varies with space and is expressed as follows: f=f m [1-(1-C) 1 / B ](2) Where f is the infiltration capacity, f m is the maximum infiltration capacity, C is the proportion of areas with infiltration capacity less than or equal to f, and B is the infiltration capacity shape parameter; According to the water balance formula, within a given time period P, it is deduced that: P=R1(y)+R2(y)+ΔW(y)(3) y=R1(y)+ΔW(y)(4) Where p represents the rainfall in the period; y represents the vertical depth; R1(y) represents the full flow; R2(y) represents the excess flow; ΔW(y) represents the change in soil moisture content; The full flow R1 and the change in soil moisture content ΔW in equations (3) and (4) can be expressed as: Among them, i m represents the maximum water storage capacity; i0 represents the water storage capacity at a certain point; b represents the water storage shape coefficient; Then we get W p , the expression of R2 is: Where B represents the infiltration capacity shape coefficient; Δt represents the calculation time step; The base flow is calculated using the ARNO model, and the calculation formula is: Where D m is the maximum base flow, D s is the current base flow and D m The ratio of is the initial moisture content of the lower soil layer, is the maximum water content of the lower soil, W s is the water content ratio of the lower soil, R b For base flow.

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