CN115130396A - Distributed hydrological model modeling method for riverway type reservoir area - Google Patents
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Abstract
The invention provides a distributed hydrological model modeling method for a river channel type reservoir area, and belongs to the technical field of distributed hydrological modeling. Firstly, obtaining basic data required for building a reservoir area distributed hydrological model, including topographic and geomorphic data and hydrological meteorological data, seeking a proper grid scale and providing a basis for modeling the distributed hydrological model. And secondly, dividing the sub-watershed and the sloping surface watershed, and calculating the convergence. And finally, evaluating the forecasting performance of each flood according to the traditional evaluation indexes, and carrying out parameter calibration. According to the method, the reservoir area is divided into the sub-watersheds and the slope watershed through the establishment of the distributed hydrological model, the slope watershed is divided into the more refined slope hydrological response units, the spatial variation characteristics of the underlying surface of the slope unit can be fully reflected, and the inflow condition of the slope watershed can be simulated more accurately.
Description
Technical Field
The invention belongs to the technical field of distributed hydrological modeling, and relates to a distributed hydrological model modeling method for a river channel type reservoir area.
Background
The two side edges of the main river channel of the river channel type reservoir area are mainly Chongshan mountains and mountains, runoff can be directly and dispersedly converged into the main river channel from the slope surfaces of the two sides except for branch flow convergence, the slope surface area is small in water collection area, but large in space span, and strong in landform feature variability, so that the water volume spatial distribution converged into the main river channel is very uneven.
At present, the existing lumped hydrological model does not fully consider the spatial heterogeneity of a slope region, the slope region is divided into a large watershed to be processed, only the runoff at the outlet of the watershed can be simulated, the flow process of all places along the main river course in the slope watershed cannot be obtained, and the space-time variability of rainfall runoff in a reservoir area is difficult to accurately describe. Although the distributed watershed hydrological model can simultaneously consider the rainfall spatial distribution and the unevenness thereof and the influence of the underlying surface spatial variation on watershed production convergence, the degree of refinement of the modeling mode of the river channel type reservoir area is not enough, and the requirement of flood forecast of the river channel type reservoir area on the accuracy of the on-way important section is difficult to meet.
Therefore, according to the topographic features and features of the river channel type reservoir area, it is urgently needed to invent a distributed hydrological model capable of describing the production convergence process of the main river channel coastal slope surface drainage basin so as to fully reflect the spatial variation characteristics of the underlying surface of the slope unit and accurately simulate the inflow condition of the slope drainage basin.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a distributed hydrological model modeling method for a river channel type reservoir area.
The technical scheme adopted by the invention is as follows:
a distributed hydrological modeling method for a river channel type reservoir area is characterized in that the reservoir area is divided into sub-watersheds and a slope watershed, and meanwhile, in order to further meet fine modeling on the spatial scale of the slope watershed, the slope watershed is divided into finer slope hydrological response units. The method specifically comprises the following steps:
first, watershed partitioning of different geomorphic types
For the river channel type reservoir, the precipitation-production-confluence between the watershed sections can be divided into two cases according to the contact form with the main river channel (reservoir area), and the two cases are different in confluence mode. The sub-basin product confluence flows into the reservoir area in a point source mode, and the main river channel slope product confluence flows into the reservoir area in a distributed manner along the way.
1.1 division of sub-basins from slope basins
The invention divides the reservoir into two types of sub-watersheds and slope watersheds. The sub-watershed has a stable water system, hydraulic connection is generated between the sub-watershed and the main river channel in a contact point mode, the precipitation-runoff process of each position of the river channel in the sub-watershed is not required to be obtained according to a modeling mode aiming at the closed watershed, and only the runoff at the outlet of the sub-watershed is required to be output. The slope surface watershed is in direct contact with the main river channel in a surface form, a stable and complete water system does not exist in the slope surface watershed, and runoff dispersedly flows into the main river channel. The water collection area of the slope watershed is relatively small, but the slope watershed has large extension range on two sides of a main river channel, the landform and landform feature variability is strong, the slope watershed needs to be divided into slope hydrological response units with smaller scales, the spatial heterogeneity of the underlying surface of the slope watershed in rainfall spatial and temporal variability is fully considered, and the fine modeling on the spatial scale is met.
1.2 determining hydrological response unit threshold for a slope basin
Because the interaction modes and the confluence characteristics of the sub-watershed and the slope watershed and the main riverway are different, the requirement on the refinement degree of modeling is also different. In order to make the slope surface watershed more fine, the slope surface area needs to be divided into finer slope surface hydrological response units by setting soil types, land utilization types and gradient thresholds.
In order to determine a refined slope hydrological response unit, the watershed units are refined by setting a plurality of combination modes of different threshold values, namely, after the area threshold values, the soil type area threshold values and the gradient grade threshold values of different land utilization types are respectively set, the land utilization types, the soil type area threshold values and the gradient grade threshold values are arranged and combined, the influence of different threshold value combinations on the division of the hydrological response units is subjected to test analysis, finally, the threshold value combination which can give consideration to both simulation precision and calculation efficiency is obtained, the hydrological response unit threshold values of the slope watershed are determined, and the number of the slope watershed divided into the slope hydrological response units is finally determined.
Second, grid size selection
The distributed hydrological model can consider the spatial distribution difference of hydrological elements in the drainage basin, can truly simulate the spatial change of the drainage basin convergence process, and to embody the advantage, the construction of the distributed hydrological model needs to divide the drainage basin into a plurality of grids capable of reflecting the spatial heterogeneous characteristics of the drainage basin on the basis of the drainage basin DEM data. Meanwhile, the size of the grid dimension can greatly influence the production convergence simulation precision and the model calculation efficiency, and the invention provides a grid division method framework capable of meeting the simulation precision and the calculation efficiency at the same time.
2.1 different Scale grid construction
In the construction of the hydrological model, the selection of different grid scales often has a great influence on the simulation result of the hydrological model. The method is based on national digital elevation data with the precision of 30m multiplied by 30m, and original DEM data are resampled to different resolutions so as to establish DEMs with different grid scales.
The invention respectively resamples the original DEM by adopting three methods which are most commonly used in the prior resampling, wherein the three methods are respectively a nearest neighbor method, a two-line interpolation method and a cubic convolution method. Calculating the Root Mean Square Error (RMSE) of DEM data acquired after resampling, and finally selecting a resampling method according to the lowest value of RMSE, wherein the RMSE calculation formula is as follows:
in the formula, Z k For the grid elevation, z, of the DEM after resampling k And n is the number of the grids after resampling.
2.2DEM analytical processing
And further analyzing and processing the resampled DEM data to obtain watershed attribute data, and constructing a hydrological model on the basis of the watershed attribute data. And (3) for the obtained river basin water system, obtaining continuous river network data which accord with the surface water flow mechanism and have high matching degree with the actual river network through the steps of data correction, depression and flat land treatment, water flow direction determination, confluence accumulation amount calculation, water collection area threshold setting and river basin river network extraction. The method comprises the following specific steps:
correcting the DEM: and detecting and improving the surface elevation data precision of the DEM data by adopting an Agree method, and finely adjusting the surface elevation of the DEM to keep the DEM and the river channel vector diagram data in continuity and consistency, thereby completing the correction of the DEM data.
DEM depression and land leveling treatment: the presence of a large amount of depression information in DEM data can lead to flow discontinuities when flow analysis is performed. To ensure continuity of flow direction analysis, different treatments were used for each of the two types of puddles. Aiming at the independent depression with the elevation data of eight adjacent points around a certain point being larger than the data of the point, when at least one point of the eight adjacent points around the certain point is an outlet of a water collecting area, assigning the minimum value of the eight adjacent points around the point to the point; when no water collecting area outlet exists around, the minimum elevation point on the boundary line of the area is found, the filling point and the eight adjacent points are given to the value smaller than the minimum elevation point, and the filling work of the independent hollow is completed. For a composite depression area with a plurality of valley bottom points, starting from each valley bottom, determining positions of depression edge points and outlet points through reverse water flow, replacing elevations of the points with depression edge elevations smaller than the numerical value with elevations of the outlet points, and then giving elevation data to the points with the elevations of the outlet points lower than the numerical value of the adjacent depression area on the basis of the elevation data, so that the depression filling work of the composite depression is completed.
For a grid point with the same elevation as the eight surrounding grids, the flat ground needs to be treated to ensure that the water flow is directed out of the flat ground area. Searching a point with an elevation larger than that of an adjacent point on the boundary of the flat land area, marking the point as a safe point, marking the other points as points to be processed, performing small elevation increase on the points to be processed until all the points to be processed can be marked as safe points, so that flat land processing is completed, and finally enabling the DEM model to generate a continuous water system river;
thirdly, determining the direction of the water flow: in order to determine the flow direction of water flow in each cell, the invention firstly compares the slope between the grid cell to be processed and the adjacent 8 grid cells, connects the center of the grid cell to be processed with the center of the grid cell with the maximum slope in the adjacent 8 grid cells, and defines the connection direction as the water flow direction of the grid cell to be processed, namely, the D8 algorithm is used for determining the flow rate of the water flow;
determination of catchment area and water system: the cumulative amount of water flow at each grid point is the total number of all the grids flowing into the grid, i.e. the convergence cumulative matrix. Based on the water flow direction of the grids, the convergence cumulative matrix of each grid can be calculated, and the upstream convergence area of each unit grid can be obtained by multiplying the convergence cumulative matrix by the area of the grid.
However, not all the grids having the upstream catchment area may form the river network, and only when the catchment area is larger than a certain threshold, the grid is calculated as a grid in the river network, and the grid is connected according to the water flow direction to form the river network. In order to determine the confluence area threshold, the invention establishes a relation between the river network gradient and the catchment area to find out the change of the relation coefficient. Through trial calculation, when the catchment area threshold approaches to a certain numerical value, the relation coefficient tends to be stable, and the catchment area threshold corresponding to the stable relation coefficient is taken as the most appropriate catchment area threshold.
Thirdly, calculating the convergence of the sub-basin and the slope basin
3.1 calculation of runoff yield in sub-watersheds and slope watersheds
The runoff producing processes of the sub-watershed and the slope watershed are consistent, and based on the determination of the grid scale, the invention adopts a runoff producing model of a distributed hydrological model which can simultaneously consider two runoff producing mechanisms of full storage and super-seepage and the influence of temperature on a runoff simulation result for the sub-watershed and the slope watershed.
The runoff yield of the sub-watershed and the sloping surface watershed is calculated as follows:
the infiltration capacity of the lattice cell varies spatially and can be represented by the following formula:
f＝f m [1-(1-C) 1/B ] (2)
wherein f is the infiltration capacity, f m C is the area ratio of the infiltration capacity less than or equal to f, and B is the shape parameter of the infiltration capacity.
According to the formula of water balance, it can be deduced that in a given period of time P:
P＝R 1 (y)+R 2 (y)+ΔW(y) (3)
y＝R 1 (y)+ΔW(y) (4)
wherein p represents a time-interval rainfall; y represents a vertical depth; r 1 (y) denotes a full production stream; r 2 (y) represents the hyperosmotic flow; Δ w (y) represents a change amount of soil moisture content;
the full production stream (R) in the formulae (3) and (4) 1 ) And the soil moisture content variation (Δ W) may be expressed as:
wherein i m Representing a maximum water storage capacity; i.e. i 0 Indicating the water storage capacity at a certain point; b represents a water storage shape factor;
from the above formula, W can be deduced p ，R 2 The expression of (a) is:
wherein B represents the infiltration capacity shape coefficient; Δ t represents a calculation time step;
the ARNO model is adopted for the calculation of the basic flow, and the calculation formula is as follows:
in the formula, D m At maximum base flow, D s For the current base stream and D m The ratio of (a) to (b),
is the initial water content of the underlying soil,
maximum water content of the underlying soil, W s The water content of the lower soil, R b Is a base stream.
3.2 Convergence calculation of sub-basin and slope basin
The invention relates to a method for simulating the spatial evolution of rainfall-runoff of a river channel type reservoir, which adopts a converging mode of 'closing first and then performing' to calculate the converging process of a sub-watershed and a slope watershed and finely simulates the evolution process of runoff among grids.
For the sub-basin, the grids are divided into two types, namely slope grids (not including branch rivers) and channel grids (including branch rivers) according to whether the grids include the branch rivers or not. In the slope grid, runoff firstly converges into a nearby river channel grid according to the topological relation of the grid, the process is calculated by adopting a unit line method based on probability distribution, then the runoff evolvement process in the river channel grid is described by adopting a motion wave equation or an impulse response function, and the operation is carried out on the outlet section of the sub-basin step by step along the river channel grid unit until the runoff converges into a main river channel.
In sub-basin confluence, the topological relation among grids is determined according to the D8 flow direction algorithm introduced above, and the movement of runoff in each grid is calculated according to a slope confluence method.
In a slope surface flow domain, runoff is dispersed and directly converged into a main river channel and directly contacts the main river channel in a surface form, the process of calculation downwards along the river channel does not exist, and the process of converging a slope surface grid into the main river channel is described by adopting a unit line method based on probability distribution.
Slope surface convergence calculation
When the slope convergence calculation is carried out, the unit line is calculated by probability distribution.
The probability density function of the two-parameter lognormal distribution is:
wherein x is greater than 0, - ∞ < mu < ∞, and sigma is greater than 0.
t p ＝exp(μ-σ 2 ) (11)
The above formula is substituted into the probability density function to solve, and the following steps are included:
t p and f (t) p ) Multiplying by the formula to obtain:
taking the natural logarithm of the two sides of the formula to obtain:
ln(t p )＝μ-σ 2 (14)
then the
μ＝σ 2 +ln(t p ) (15)
Given a t p And q is p Then μ and σ can be solved by the formula. Besides the two-parameter lognormal distribution, a unit line can be obtained through probability distribution functions such as two-parameter Pareto distribution, two-parameter Weibull distribution and two-parameter Frechet distribution.
② river course conflux calculation
Aiming at the river channel type reservoir, the invention adopts the existing main stream efficient calculation confluence method to calculate confluence, namely, two river channel confluence schemes of a motion wave (KWT) and an Impulse Response Function (IRF) are adopted to calculate the river channel confluence, wherein the KWT method is used for the river channel with larger river bottom specific drop, and the IRF method is used for the common river channel. The two methods are calculated as follows:
a. sport wave method (KWT)
The KWT method can calculate the wave velocity or flow entering an independent river section from the hydrological response unit in each time interval, the approximate assumption is that the river channel is rectangular, the hydraulic power width and the wave velocity C are the width omega of the river channel, the Manning coefficient n and the river bottom ratio drop S 0 And a function of the flow rate q. The river bottom ratio drop can be calculated from river network data, and the flow q can be obtained from the slope convergence. The river channel width is determined by the following formula:
the calculation formula of the wave velocity in the river reach is as follows:
if the calculated expected outflow time is before the end of the time period, then the wave is flowing into the downstream river segment, otherwise it is considered to be stagnant in the current time period.
b. Impulse Response Function (IRF)
The IRF method is used for performing confluence calculation on the runoff output of the gridded land model, and a gridded river network or a vector river network can be used.
The mathematical development of the IRF method is a one-dimensional diffusion wave equation derived based on a one-dimensional Saint-Venn equation
In the formula, q is the flow of the water cross section, x is the distance along the river channel, C represents the flow velocity, and D represents the diffusion coefficient.
The formula can be solved by convolution integral
Wherein
In the formula, U (t-s) is the radial flow depth generated at the time t-s.
When the IRF method is used, the flow process can be obtained only by performing unit line integration on each upstream river section and then accumulating the confluence calculation flow of all the upstream river sections at the outlet river section, and compared with the KWT method, the method does not need to pay attention to the sequence of the river sections and is more convenient to calculate.
Fourthly, calibrating parameters of the distributed hydrological model
For the distributed hydrological model, in order to avoid falling into a local convergence point, a multi-objective optimization algorithm is adopted for parameter calibration. The core of the algorithm is to coordinate the relationship among the objective functions and find out the Pareto optimal solution set which enables the objective functions to be as large or small as possible. The present invention adopts NSGA-II algorithm for calibration.
The reservoir area flood forecasting focuses on the aspects of flood peak, flood volume, flood process lines, flood space-time distribution and the like, so when the flow generation model parameters of the distributed hydrological model are optimized, two objective functions are set in the NSGA-II algorithm, and the minimum of the mean values of the relative error absolute values of the flood runoff depth and the flood peak flow are respectively the objective functions.
Wherein n is the number of flood fields, R f (i) Simulated runoff depth, R, representing ith field flood m (i) Representing the measured runoff depth of the ith field flood. Q f (i) Flood peak, Q, representing a simulation of the ith field flood m (i) Representing the measured flood peak value of the ith field flood.
When the confluence model parameters are optimized, the mean value of field flood certainty coefficients (DC) is maximum of an objective function:
in the formula, Q if And Q im Respectively the simulated flow and the measured flow of the ith flood in the total flow process,
average measured flow of the total flow process.
Thus, parameters of the model are obtained, and the construction of the distributed hydrological model of the riverway type reservoir area is further completed.
The invention has the following effects and benefits: according to the method, the reservoir area is divided into the sub-watersheds and the slope watershed through the establishment of the distributed hydrological model, the slope watershed is divided into the more refined slope hydrological response units, the spatial variation characteristics of the underlying surface of the slope unit can be fully reflected, and the inflow condition of the slope watershed can be simulated more accurately.
Drawings
Figure 1 is a 30m resolution DEM elevation map of a three gorges reservoir region according to an embodiment of the present invention.
Fig. 2 is a diagram of the result of meshing the three gorges reservoir region according to the embodiment of the present invention.
Fig. 3 is an output node diagram of a distributed hydrological model in the three gorges reservoir area according to an embodiment of the present invention.
Fig. 4 is a schematic diagram of the watershed division of the present invention.
FIG. 5 is a schematic view of the converging process of the sub-basin and the sloping basin of the present invention.
Fig. 6 is a route diagram of the distributed hydrological model modeling technology of the reservoir area of the river channel type reservoir.
Detailed Description
The invention provides a distributed hydrological modeling method for a river channel type reservoir area on the basis of distributed hydrological modeling.
The present invention is further illustrated by the following examples.
The three gorges reservoir belongs to a typical large river channel type reservoir, the water flow in the reservoir area presents an unsteady flow state, the water surface of the reservoir is not in a horizontal state under the influence of reservoir water blockage and warehousing flow, the wedge-shaped reservoir capacity (movable reservoir capacity) formed by backwater above the horizontal plane also has a regulating effect on flood, and the flood regulating effect of the three gorges reservoir is usually larger than that of a static reservoir capacity below the horizontal plane. Meanwhile, the three gorges reservoir area belongs to a humid subtropical monsoon climate, the climate is influenced by the topography of canyons very obviously, the rainfall is abundant all the year round, the average rainfall for many years reaches 1150mm, rivers in the reservoir area are vertically and horizontally, water systems develop and branch flows are numerous, besides the main flow of the overlong river and two major branch flows of the Jialing river and the Wujiang river, branch flows of the big flood river, the canal river, the dragon river, the small river, the Xiangxi river and the like are converged into the main river continuously, the added runoff can be dispersed from the slope surface around the reservoir and flows into the reservoir, and the stormy and flood law of the reservoir area is very complex. Therefore, by taking the area as an example, a refined production convergence theory and a related distributed hydrological model modeling method of the three gorges reservoir area are explored, and rainfall runoff space-time evolution of the three gorges reservoir area is accurately simulated. The method comprises the following specific steps:
the first step is as follows: basic data such as basic hydrological meteorological data and topographic and geomorphic data required by reservoir area hydrological modeling need to be collected firstly to drive a hydrological model to carry out fine modeling on the production convergence process of the three gorges reservoir area. The DEM elevation data of the three gorges reservoir area is selected from DEM elevation data with the resolution of 30m, as shown in figure 1, 0.05 degrees is used as the horizontal resolution of a distributed hydrological model grid, and then the whole three gorges reservoir area is divided into 2854 orthogonal grids with the resolution of 0.05 degrees multiplied by 0.05 degrees, and the orthogonal grids are used as calculation units of a runoff generating model of a drainage basin. As shown in fig. 2.
The second step is that: on the basis of DEM elevation data of the three gorges reservoir area, information such as boundaries of a research area, river networks and sub-river areas in the area is extracted and obtained through processes of hole filling, flow direction generation, accumulated flow calculation, sub-river area division and the like by utilizing an ArcGIS tool. And aiming at the sub-watershed, performing convergence calculation by adopting a method of combining the slope and river convergence.
The third step: through the constructed distributed hydrological model, a flow process including 54 nodes of inflow of 26 sub-watersheds and 28 main riverways along the slope and the sub-watershed interval is output at the same time, as shown in fig. 3. When calculating the flow process of the watershed nodes, the watershed nodes are divided, which is schematically shown in fig. 4, and include 6 sub watersheds and 2 slope watersheds (including 6 and 3 hydrologic response units, respectively). The specific details are as follows:
for sub-basin 1 and sub-basin 2: the runoff of the sub-watershed 1 is converged into the main river channel through a node 6, and the sub-watershed 2 interacts with the main river channel through a node 9;
② for slope watershed: the main river course traverses the slope hydrology response unit, the slope watershed 1 is divided into 6 slope hydrology response units, and the slope watershed 2 is divided into 3 slope hydrology response units. Runoff of the slope watershed hydrological response units 1-6 is converged into a main river channel through nodes 1-6 in sequence, and runoff of the slope watershed hydrological response units 7-9 is converged into the main river channel through nodes 7-9 in sequence;
and thirdly, the runoff simulation value indicating the nodes 1-9 in the drainage basin can be used as a hydrological model to be output continuously in space.
Subsequently, a confluence calculation was performed, with the following details:
the confluence process of the sub-watershed and the slope watershed is shown in fig. 5 (in this example, compared with fig. 4, the slope watershed is divided into more response units, which are 10 in total), and the specific details are as follows:
sub-basin confluence
a. The runoff of the grid A firstly flows to a nearby river channel grid H through the slope grid D, E, G, and after entering the river channel in the grid H, the runoff is calculated downstream along the river channel according to the mode of river channel confluence, and finally enters the main river channel through the node 10.
b. Runoff of the grid B flows into the river grid H through the slope grid C, F.
The confluence paths of the grids, namely the topological relation among the grids, are determined according to a D8 flow direction algorithm, and the movement of radial flow in each grid is calculated according to a slope confluence method.
② slope basin (hydrology response unit)
The slope surface watershed is divided into 10 slope surface hydrology response units, and in the slope surface hydrology response units 3, 4, 9 and 10, runoff flows into the main river channel grid J, K, L, M along the slope surface and flows out directly through the nodes 3, 4, 9 and 10 in the grid J, K, L, M.
Finally, the flow process can be obtained by using the river confluence calculation introduced in the invention.
The fourth step: the parameters of the distributed hydrological model along the river-crossing basin in the reservoir area are calibrated by adopting a multi-target genetic algorithm, 26 fields of flood in 2021 of the basin 2014- 3 And/s covers flood of various magnitudes such as large, medium and small, and has better representativeness. The results of the parameter calibration are shown in Table 1. The accuracy and the reliability of the distributed hydrological model simulation result aiming at the reservoir area of the river channel type reservoir can be fully proved by the embodiment.
Table 1 flood simulation results along river crossing basin
The average absolute value of the relative error of the flood volume is 13.86 percent, the average absolute value of the relative error of the flood peak is 19.32 percent, the error of the flood peak is not more than 20 percent of the measured value, the qualified rate is up to 80.8 percent when the qualified rate of the runoff production along the river crossing basin is 21 fields, and the qualified rate is 61.5 percent when the qualified rate of the flood peak is 16 fields along the river crossing basin. The average deviation of the time of the secondary flood peak along the river crossing basin is 1.38h, the deviation of the time of the 17-field peak is less than or equal to 1h, and the percentage of the peak is 65.38%. Therefore, the distributed hydrological model provided by the invention has a good simulation effect on the runoff and the flood peak along the river crossing basin.
The above-mentioned embodiments only express the embodiments of the present invention, but not should be understood as the limitation of the scope of the invention patent, it should be noted that, for those skilled in the art, many variations and modifications can be made without departing from the concept of the present invention, and these all fall into the protection scope of the present invention.
Claims (5)
1. A distributed hydrological model modeling method for a river channel type reservoir area is characterized by comprising the following steps:
first, watershed segmentation of different landform types
For the river channel type reservoir, the precipitation-production-confluence between the watershed sections can be divided into two situations according to the contact form with the main river channel, and the two situations are different in confluence mode: converging the sub-basin products into the reservoir area in a point source mode, and converging the main river along the bank strip-shaped slope products into the reservoir area in an on-way distributed mode;
1.1 division of sub-basins from slope basins
Dividing the reservoir area into two types of sub-watershed and slope watershed; the sub-watershed has a stable water system, generates hydraulic connection with the main river channel in a contact point mode, and only needs to output runoff at an outlet of the sub-watershed without obtaining precipitation-runoff processes at all positions of the river channel in the sub-watershed according to a modeling mode aiming at the closed watershed; the slope surface watershed is in direct contact with the main riverway in a surface form, a stable and complete water system does not exist in the slope surface watershed, and runoff dispersedly converges into the main riverway;
1.2 determining hydrological response unit threshold for a slope basin
In order to determine refined slope hydrological response units, the watershed units are refined by setting a plurality of combination modes of different thresholds, namely, after area thresholds, soil type area thresholds and gradient grade thresholds of different land utilization types are respectively set, the area thresholds, the soil type area thresholds and the gradient grade thresholds are arranged and combined, the influence of different threshold combinations on the division of the hydrological response units is subjected to experimental analysis, threshold combinations capable of considering both simulation precision and calculation efficiency are obtained, the hydrological response unit thresholds of the slope watershed are determined, and the number of slope watershed divided slope hydrological response units is further determined;
second, grid size selection
Constructing a distributed hydrological model based on the data of the drainage basin DEM, and dividing the drainage basin into a plurality of grids capable of reflecting the spatial heterogeneous characteristics of the drainage basin; a method frame of grid division capable of meeting the requirements of simulation precision and calculation efficiency simultaneously is provided;
2.1 construction of different Scale meshes
Resampling the original DEM data to different resolutions, and establishing DEMs with different grid scales;
2.2DEM analytical processing
Further analyzing and processing the resampled DEM data to obtain watershed attribute data, and constructing a hydrological model on the basis of the watershed attribute data; for the obtained river basin water system, continuous river network data which accord with surface water flow mechanisms and have high matching degree with an actual river network are obtained through data correction, hole filling and flat land treatment, water flow direction determination, confluence cumulant calculation, water collection area threshold setting and river basin river network extraction;
firstly, correcting a DEM;
DEM depression and land leveling treatment: in order to ensure the continuity of flow direction analysis, different treatment methods are respectively adopted for the independent hollow areas and the composite hollow areas for filling; aiming at the independent depression with the elevation data of eight adjacent points around a certain point being larger than the data of the point, when at least one point of the eight adjacent points around the certain point is an outlet of a water collecting area, assigning the minimum value of the eight adjacent points around the point to the point; when no water collecting area outlet exists around, finding out the minimum elevation point on the boundary line of the area, and assigning the value of the minimum elevation point to the hollow point and eight adjacent points which are smaller than the value, so as to finish the hollow filling work of the independent hollow; for a composite hollow area with a plurality of valley bottom points, firstly starting from each valley bottom, determining the positions of hollow edge points and outlet points through reverse water flow, then replacing the elevation of a point with the elevation of the hollow edge less than the numerical value with the elevation of the outlet point, and then giving the elevation data to the point with the elevation of the outlet point less than the numerical value of the adjacent hollow area on the basis of the elevation data, so that hollow filling work of the composite hollow area is completed;
for a grid point with the same elevation as the eight surrounding grids, the flat ground needs to be treated to ensure that the water flow can directionally flow out of the flat ground area; searching a point with an elevation larger than that of an adjacent point on the boundary of the flat land area, marking the point as a safe point, marking the other points as points to be processed, performing small elevation increase on the points to be processed until all the points to be processed can be marked as safe points, so that flat land processing is completed, and finally enabling the DEM model to generate a continuous water system river;
thirdly, determining the direction of the water flow: in order to determine the flow direction of the water flow in each cell, firstly, the slopes and the dips between the grid cell to be processed and the adjacent 8 grid cells are compared, the center of the grid cell to be processed and the center of the grid cell with the largest slope and the largest slope among the adjacent 8 grid cells are connected, and the connection direction is defined as the water flow direction of the grid cell to be processed, namely, the flow rate of the water flow is determined by using a D8 algorithm;
determination of catchment area and water system: the cumulative water flow on each grid point is the total number of all grids flowing into the grid, namely a confluence accumulation matrix; calculating a convergence accumulation matrix of each grid according to the water flow direction of the grid, and multiplying the convergence accumulation matrix by the area of the grid to obtain the upstream convergence area of each unit grid;
in order to determine the confluence area threshold, a relation between the river network gradient and the catchment area is established to find out the change of the relation coefficient; through trial calculation, when the catchment area threshold approaches to a certain numerical value, the relation coefficient tends to be stable, and the catchment area threshold corresponding to the stable relation coefficient is taken as the most appropriate catchment area threshold;
thirdly, calculating the convergence of the sub-basin and the slope basin
3.1 calculation of runoff yield in sub-watersheds and slope watersheds
The runoff producing processes of the sub-watershed and the slope watershed are consistent, and based on the determination of the grid scale, a runoff producing model of a distributed hydrological model which can simultaneously consider two runoff producing mechanisms of full storage and super-seepage and the influence of temperature on a runoff simulating result is adopted for the sub-watershed and the slope watershed;
the runoff yield calculation of the sub-watershed and the slope watershed is as follows:
the infiltration capacity of the grid cells varies with space and is represented by the following formula:
f＝f m [1-(1-C) 1/B ] (1)
wherein f is the infiltration capacity, f m C is the area ratio of the infiltration capacity less than or equal to f, and B is the shape parameter of the infiltration capacity;
according to the formula of water balance, deducing in a given time period P:
P＝R 1 (y)+R 2 (y)+ΔW(y) (2)
y＝R 1 (y)+ΔW(y) (3)
wherein p represents a period rainfall; y represents a vertical depth; r 1 (y) indicates a full production stream; r 2 (y) represents the hyperosmotic flow;
Δ w (y) represents a change amount of soil moisture content;
the full production flow R in the formulas (3) and (4) 1 And the soil moisture content variation amount aw may be expressed as:
wherein i m Representing a maximum water storage capacity; i.e. i 0 Indicating the water storage capacity at a certain point; b represents a water storage shape factor;
further obtain W p ，R 2 The expression of (a) is:
wherein, B represents the infiltration capacity shape coefficient; Δ t represents a calculation time step;
the ARNO model is adopted for the calculation of the basic flow, and the calculation formula is as follows:
in the formula, D m At maximum base flow, D s For the current base stream and D m The ratio of (a) to (b),
is the initial water content of the underlying soil,
maximum water content of the underlying soil, W s The water content of the lower soil, R b Is a base stream;
3.2 Convergence calculation of sub-basin and slope basin
In order to simulate the spatial evolution of the rainfall-runoff of the riverway type reservoir, the convergence process of the sub-watershed and the slope watershed is calculated in a convergence mode of 'first combination and then evolution', and the evolution process of the runoff among grids is simulated in a refined mode;
for the sub-watershed, dividing grids into a slope grid and a river grid according to whether the grids contain a tributary river or not, wherein the slope grid does not contain the tributary river, and the river grid contains the tributary river; in the slope grid, runoff firstly converges into a nearby river channel grid according to the topological relation of the grid, the process is calculated by adopting a unit line method based on probability distribution, then the evolution process of the runoff in the river channel grid is described by adopting a motion wave equation or an impulse response function, and the calculation is carried out to the outlet section of the sub-basin step by step along the grid cells of the river channel until the runoff converges into a main river channel;
in sub-basin confluence, the topological relation among grids is determined according to a D8 flow direction algorithm, and the movement of runoff in each grid is calculated according to a slope confluence method;
in a slope surface flow domain, runoff is dispersed and directly converged into a main river channel and directly contacts the main river channel in a surface form, the process of calculation downwards along the river channel does not exist, and the process of converging a slope surface grid into the main river channel is described by adopting a unit line method based on probability distribution;
slope surface convergence calculation
During slope convergence calculation, a unit line is calculated according to probability distribution;
② river course conflux calculation
Aiming at a river channel type reservoir, calculating river basin confluence by adopting two river channel confluence schemes of a motion wave KWT and an impulse response function IRF, wherein the KWT method is used for a river channel with a large river bottom ratio, and the IRF method is used for a common river channel;
fourthly, calibrating parameters of the distributed hydrological model
For the distributed hydrological model, in order to avoid falling into a local convergence point, a multi-objective optimization algorithm is adopted for parameter calibration; the core of the algorithm is to coordinate the relationship among the objective functions and find out a Pareto optimal solution set which enables the objective functions to be as large or small as possible; carrying out calibration by adopting an NSGA-II algorithm;
paying attention to flood peak, flood volume, flood process line and flood space-time distribution in reservoir area flood forecasting, and setting two objective functions in an NSGA-II algorithm when the optimal selection of the parameters of the distributed hydrological model runoff generation model is carried out, wherein the two objective functions are respectively the objective function with the minimum mean value of relative error absolute values of flood runoff depth and flood peak flow;
wherein n is the number of flood fields, R f (i) Simulated runoff depth, R, representing ith field flood m (i) The measured runoff depth of the ith flood is represented; q f (i) Simulated flood peak, Q, representing the ith field flood m (i) Representing the measured flood peak value of the ith flood;
when the parameters of the confluence model are optimized, the mean value of the field flood certainty coefficient DC is maximum to be an objective function:
in the formula, Q if And Q im Respectively the simulated flow and the measured flow of the ith flood in the total flow process,
average measured flow rate of the total flow rate process;
thus, parameters of the model are obtained, and further the construction of the distributed hydrological model of the river channel type reservoir area is completed.
2. The modeling method of the distributed hydrological model of the reservoir area of the river channel type reservoir according to claim 1, wherein in the second step 2.1), the resampling method is a nearest neighbor method, a two-line interpolation method and a cubic convolution method; calculating the root mean square error RMSE of the DEM data obtained after resampling, and finally selecting a resampling method according to the lowest value of the RMSE, wherein the RMSE calculation formula is as follows:
in the formula, Z k For the grid elevation, z, of the DEM after resampling k And n is the number of the grids after resampling.
3. The method for modeling the distributed hydrological model of the river channel type reservoir area according to claim 1, wherein in the step 2.2 r): and (3) detecting and improving the surface elevation data precision of the DEM data by adopting an Agree method, and finely adjusting the surface elevation of the DEM to keep the DEM and the river channel vector diagram data in continuity and consistency so as to finish the correction of the DEM data.
4. The method for modeling the distributed hydrological model of the reservoir area of the river channel type reservoir according to claim 1, wherein in the third step, step 3.2 r), a unit line is calculated by adopting two-parameter lognormal distribution, two-parameter Pareto distribution, two-parameter Weibull distribution, two-parameter Frechet distribution or other probability distribution functions.
5. The method for modeling a distributed hydrological model of a reservoir area of a river channel type reservoir according to claim 1, wherein in the third step, step 3.2), the method for calculating the motion wave KWT and the impulse response function IRF comprises the following steps:
a. moving wave method KWT
The KWT method can calculate the wave velocity or flow entering an independent river reach from the hydrological response unit in each time interval, the approximate assumption is that the river is rectangular, the hydraulic width and the wave velocity C are the width omega of the river, the Manning coefficient n and the river bottom ratio drop S 0 And, anda function of the flow q; wherein, the river bottom ratio drop can be calculated by river network data, and the flow q can be obtained by the convergence of the slope; the river channel width is determined by the following formula:
the calculation formula of the wave velocity in the river reach is as follows:
if the calculated predicted outflow time is before the end of the time interval, the wave flows into a downstream river section, otherwise the wave is regarded as staying in the current time interval;
b. impulse response function IRF
The IRF method is used for carrying out confluence calculation on the runoff output of the gridded land model, and can use a gridded river network or a vector river network; when the IRF method is adopted, the flow process can be obtained only by performing unit line integration on each upstream river section and then accumulating the confluence calculation flow of all the upstream river sections at the outlet river section, and the method does not need to pay attention to the sequence of the river sections.
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