CN115186483A - Water and soil resource mutual feedback mechanism identification method and system - Google Patents
Water and soil resource mutual feedback mechanism identification method and system Download PDFInfo
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Abstract
The invention provides a method and a system for identifying a water and soil resource mutual feedback mechanism, which comprise the following steps: acquiring hydrological data, meteorological data, geological data and remote sensing data of a target area; according to the obtained data, carrying out energy process simulation, evaporation and heat dissipation process simulation, vertical infiltration calculation, slope runoff generation calculation, slope confluence calculation, river confluence calculation and underground water movement calculation to obtain a distributed hydrological model; meanwhile, the surface flow rate, the precipitation amount and the evaporation heat dissipation amount of the drainage basin at different time scales and the net primary productivity of different land utilization types are combined to obtain the flow rate coefficient and the ratio of the evaporation heat dissipation to the net primary productivity at different time periods in the drainage basin space; and determining the interaction law of the water and soil resources according to the current generation coefficient and the ratio of the evaporative heat dissipation to the net primary productivity. The interaction rule of water and soil resources can be accurately obtained by obtaining the hydrological model based on the simulation of multiple processes and multiple elements of the drainage basin, and technical support is provided for comprehensive treatment and water and soil resource optimal allocation of the drainage basin.
Description
Technical Field
The invention relates to the technical field of basin water circulation simulation and emulation, in particular to a method and a system for identifying a water and soil resource mutual feedback action mechanism based on basin water circulation simulation.
Background
The problems of water and land contention of people and land restrict imbalance of balance relationship between a natural ecological system and a social economic system, the scales of water resource management and land resource management objects are inconsistent, and the water production and consumption processes and ecological effects on land patches are difficult to understand. The hydrological simulation of the drainage basin is a research means in the field of hydrological water resource major, and the hydrological process can be quantified through the hydrological simulation, and the change process of each hydrological cycle element along with time and the distribution rule of each hydrological cycle element on the space under different land utilization types can be quantitatively described. In order to better study the hydrological change law and the interaction law of water and soil resources, the simulation function of the basin hydrological model needs to be further enhanced, including process refinement and improvement of simulation equations.
At present, the hydrologists at home and abroad have made a lot of research and contribution in this respect, and some model software are concentrated on surface hydrological process simulation, underground water movement simulation, river course movement model, city rainfall flood simulation and the like, but from the perspective of the whole flow area, hydrological models considering whole-element hydrological process simulation from the surface to the underground and from the slope to the river course are rarely appeared. Aiming at the defects, a method for identifying a water and soil resource interaction feed mechanism based on basin water circulation simulation is provided.
Disclosure of Invention
The invention aims to provide a method and a system for identifying a water and soil resource mutual feed action mechanism, which are used for accurately obtaining the water and soil resource mutual feed action mechanism based on a basin refined simulation model considering multiple hydrological processes and multiple factors, expanding a basin hydrological research technical means and providing technical support for basin comprehensive treatment and water and soil resource optimal allocation.
In order to achieve the purpose, the invention provides the following scheme:
a method and a system for identifying a water and soil resource interaction feed mechanism comprise the following steps:
acquiring hydrological data, meteorological data, geological data and remote sensing data of a target area;
performing energy process simulation, evaporation and heat dissipation process simulation, vertical infiltration calculation, slope runoff generation calculation, slope confluence calculation, river confluence calculation and underground water movement calculation according to the hydrological data, the meteorological data, the geological data and the remote sensing data to obtain a distributed hydrological model; the energy process simulation comprises long wave radiation and short wave radiation calculation; the transpiration process simulation comprises vegetation transpiration, vegetation interception evaporation, water area evaporation, bare soil evaporation, urban surface evaporation and building evaporation;
calculating and counting the surface flow rates of different time scales of the drainage basin based on the distributed hydrological model, and obtaining flow rate coefficients of different time periods in the drainage basin space by combining precipitation;
calculating and counting the evaporation heat dissipation capacity of the basin at different time scales based on the distributed hydrological model, and determining the ratio of the evaporation heat dissipation capacity to the net primary productivity by combining the net primary productivity of different land utilization types;
and determining the interaction rule of the water and soil resources according to the flow generation coefficient and the ratio of the evaporative heat dissipation to the net primary productivity.
The invention also provides a water and soil resource interaction feed mechanism recognition system, which comprises:
the data acquisition module is used for acquiring hydrological data, meteorological data, geological data and remote sensing data of a target area; the distributed hydrological model simulation module is used for performing energy process simulation, evaporation and heat dissipation process simulation, vertical infiltration calculation, slope runoff calculation, slope confluence calculation, river confluence calculation and underground water movement calculation according to the hydrological data, the meteorological data, the geological data and the remote sensing data to obtain a distributed hydrological model; the energy process simulation comprises long-wave radiation and short-wave radiation calculation; the transpiration process simulation comprises vegetation transpiration, vegetation interception evaporation, water area evaporation, bare soil evaporation, urban surface evaporation and building evaporation;
the runoff yield coefficient calculation module is used for calculating and counting the surface runoff yields of the watershed at different time scales based on the distributed hydrological model and obtaining the runoff yield coefficients of the watershed at different time periods by combining precipitation;
the ratio calculation module of the evaporative heat dissipation and the net primary productivity is used for calculating and counting the evaporative heat dissipation capacity of different time scales of a basin based on the distributed hydrological model and determining the ratio of the evaporative heat dissipation capacity to the net primary productivity by combining the net primary productivity of different land utilization types;
and the water and soil resource interaction rule acquisition module is used for determining the water and soil resource interaction rule according to the runoff yield coefficient and the ratio of the evaporative heat dissipation to the net primary productivity.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the invention provides a method and a system for identifying a water and soil resource mutual feedback mechanism, which comprise the following steps: acquiring hydrological data, meteorological data, geological data and remote sensing data of a target area; according to the obtained data, carrying out energy process simulation, evaporation and heat dissipation process simulation, vertical infiltration calculation, slope runoff generation calculation, slope confluence calculation, river confluence calculation and underground water movement calculation to obtain a distributed hydrological model; calculating and counting surface flow rates of different time scales of a drainage basin based on a distributed hydrological model, and obtaining flow rate coefficients of different time periods in a drainage basin space by combining precipitation; calculating and counting the evaporation heat dissipation capacity of the basin at different time scales based on a distributed hydrological model, and determining the ratio of the evaporation heat dissipation capacity to the net primary productivity by combining the net primary productivity of different land utilization types; and determining the interaction rule of the water and soil resources according to the current generation coefficient and the ratio of the evaporative heat dissipation to the net primary productivity. A hydrological model obtained based on multi-process and multi-element refined simulation of the drainage basin can accurately obtain the interaction rule of water and soil resources, and technical support is provided for comprehensive treatment of the drainage basin and optimal allocation of the water and soil resources.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a flowchart of a method for identifying a water and soil resource interaction feed mechanism according to embodiment 1 of the present invention;
fig. 2 is a hydrologic analysis process of a Sihewa zone provided in example 1 of the present invention;
fig. 3 is topography data of a Sihefu river basin provided in example 1 of the present invention;
fig. 4 is weather data of a Sihewa region provided in example 1 of the present invention;
FIG. 5 is a mutation test of the Sihefu region provided in example 1 of the present invention;
FIG. 6 shows the vertical and horizontal structures of the basin hydrological model provided in example 1 of the present invention;
fig. 7 is a calibration and verification of the Sihefu area provided in example 1 of the present invention;
fig. 8 is a spatial distribution of the flow coefficient of the Sihefu river basin provided in example 1 of the present invention;
fig. 9 shows the spatial distribution of NPP/ET in the Sihefu area provided in example 1 of the present invention;
FIG. 10 is a schematic view of the water balance in the grid provided in example 1 of the present invention;
fig. 11 is a schematic view of a split aquifer system provided in embodiment 1 of the present invention;
fig. 12 is a perspective view of the peripheral grid and the central grid according to embodiment 1 of the present invention;
fig. 13 is a plane positional relationship between the peripheral grid and the central grid according to embodiment 1 of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention aims to provide a method and a system for identifying a water and soil resource mutual feedback mechanism, which are used for accurately acquiring the water and soil resource mutual feedback mechanism based on a basin refined simulation model considering multiple hydrologic processes and multiple elements, expanding the technical means of basin hydrologic research and providing technical support for basin comprehensive treatment and water and soil resource optimal allocation.
In order to make the aforementioned objects, features and advantages of the present invention more comprehensible, the present invention is described in detail with reference to the accompanying drawings and the detailed description thereof.
Example 1
As shown in fig. 1, the present embodiment provides a method and a system for identifying a water and soil resource interaction mechanism, including:
the scheme of this example is summarized first: taking the Sihefu river basin as an example, the basin refinement simulation method based on the coupling distributed hydrological model and the groundwater model provided by the embodiment is described as follows:
(1) Model input data preparation.
The concrete expression is as follows:
firstly, basin hydrological analysis, namely performing depression calculation, flow direction calculation, confluence accumulation amount calculation and basin generation by means of a hydrological analysis tool in ArcGIS on the basis of DEM, and taking the basin boundary at the moment as a boundary for preparing later-stage input data, as shown in FIG. 2;
secondly, preparing topographic and geomorphic data, taking the watershed range generated in the previous step as a boundary file, cutting the DEM, the soil type data, the soil thickness data, the land utilization type data in each period and the river network data, and converting all the cut files into ASCII files as input files, as shown in figure 3;
thirdly, preparing meteorological data, selecting meteorological stations and rainfall stations in and around the basin range, numbering the meteorological stations and the rainfall stations in sequence, and drawing the Thiessen Polygons of the meteorological stations and the rainfall stations respectively by means of a Thiessen polygon creating tool (Create Thiessen Polygons) in ArcGIS. And converting the drawn Thiessen polygons into raster files according to the site serial numbers by taking the basin range as a boundary, and converting the raster files into ASCII files. Extracting the weather data and precipitation data, preparing TXT files according to the format of ' year-month-1 st station-2 nd station- \8230and ' nth station ', as shown in figure 4;
and finally, preparing other basic data and parameters, namely latitude and elevation of a meteorological station, change rate of rainfall along with elevation, vegetation coverage data of each month, area index data of each month, reflectivity of various land utilization ground surfaces to short wave radiation, saturated water content of various kinds of soil, field water retention rate of various kinds of soil, withering coefficients of various kinds of soil, depression storage capacity of various land utilization types, transverse-longitudinal-vertical permeability coefficients of various soil layers, a slope Manning coefficient and a river Manning coefficient.
(2) And (4) model simulation calculation.
Simulating an energy process, including calculation of long-wave radiation and short-wave radiation of different underlying surfaces; transpiration process simulation, including vegetation transpiration (Penman-Monteith), vegetation-trapped evaporation (Penman), water evaporation (Penman), bare soil evaporation (modified Penman), urban surface evaporation and building evaporation (Penman); vertical infiltration calculations (Green-Ampt); calculating slope runoff, including super-osmotic runoff (Hotten slope runoff) and full runoff (saturated slope runoff); slope convergence calculation (motion wave) and river convergence calculation (motion wave); the vertical and horizontal structures of the processes of the elements of the groundwater motion calculation (Darcy formula) and hydrologic cycle simulation are schematically shown in FIG. 5.
(3) And (5) calibrating and verifying the model.
Firstly, mutation point detection, namely performing mutation detection on rainfall data by using a Mann-Kendall method, wherein the time before a mutation point is used as a rate period, and the time after the mutation point is used as a verification period, as shown in figure 6;
secondly, calibrating the model, debugging various parameters, judging the simulation effect of the model through three indexes of a correlation coefficient, a Nash coefficient and a relative error, and adjusting the parameters until the three indexes meet the requirements, and ending the parameter adjustment;
and (3) model verification, namely fixing parameters on the basis of model calibration, and performing simulation verification on the calibration period, wherein if the three indexes pass, the model calibration passes, and the results of the model calibration and the verification are shown in FIG. 7.
(4) Research on water and soil resource interaction feed mechanism.
Firstly, calculating and counting the surface runoff yield and the precipitation yield of each grid of the drainage basin at different time scales by using the compiled and debugged distributed hydrological model, and further obtaining runoff yield coefficients at different time periods in the drainage basin space, as shown in fig. 8;
secondly, calculating and counting evapotranspiration of each grid in different time scales in the flow domain by using the written and debugged distributed hydrological model, obtaining spatial distribution of net primary productivity in the flow domain by using net primary productivity quota of different land utilization types and land utilization spatial distribution, and finally comparing NPP and ET in space to obtain spatial distribution of NPP/ET in different time scales, wherein the spatial distribution is shown in figure 9;
and finally, the runoff coefficient is used as an index for researching the influence of the land resources on water resources, the NPP/ET is used as an index for researching the influence of the water resources on the land resources, the results of the runoff coefficient and the NPP/ET are analyzed, and the mutual feedback effect of the water and soil resources is analyzed from two angles of time and space.
The following steps of the method of this example are performed in more detail:
step S1: acquiring hydrological data, meteorological data, geological data and remote sensing data of a target area;
wherein, step S1 specifically includes:
step S11: performing basin hydrological analysis, namely performing filling calculation, flow direction calculation, confluence cumulant calculation and basin generation by using a hydrological analysis tool in ArcGIS on the basis of DEM, and taking the basin boundary at the moment as a boundary for preparing later-stage input data;
step S12: preparing topographic and geomorphic data, namely cutting the DEM again by taking the basin range generated in the step S11 as a boundary file to be used as basin elevation data, cutting soil type data, soil thickness data, land utilization type data of each period and river network data, and converting all the cut files into ASCII files to be used as input files;
step S13: selecting weather stations and rainfall stations within the drainage basin range and the preset range, and numbering the weather stations and the rainfall stations in sequence;
step S14: respectively drawing Thiessen polygons of the weather station and the rainfall station by utilizing a Thiessen polygon creating tool;
step S15: respectively converting the drawn Thiessen polygon mounting weather station number and the drawn Thiessen polygon mounting weather station number into raster files by taking the drainage basin range as a boundary;
step S16: extracting meteorological data and precipitation data based on the raster file;
the steps S13 to S16 realize meteorological data preparation, select meteorological stations and rainfall stations in and around the basin range and sequentially number the stations, and draw the Thiessen Polygons of the meteorological stations and the rainfall stations respectively by means of a Thiessen polygon creating tool (Create Thiessen Polygons) in ArcGIS. And converting the drawn Thiessen polygons into raster files according to the site serial numbers by taking the basin range as a boundary, and converting the raster files into ASCII files. The method comprises the steps of extracting weather data and precipitation data to be acquired, and preparing TXT files according to a format of ' year-month-1 st station-2 nd station- \ 8230and ' nth station '.
Step S17: and acquiring latitude and elevation of a meteorological station, change rate of rainfall along with elevation, vegetation coverage data of each month, leaf area index data of each month, reflectivity of various land utilization earth surfaces to short wave radiation, saturated water content of various soils, field water retention rate of various soils, wilting coefficients of various soils, depression storage amount of various land utilization types, transverse-longitudinal-vertical permeability coefficients of each soil layer, domatic Manning coefficient and riverway Manning coefficient based on the grid file.
Step S17 belongs to preparation of other basic data and parameters, namely latitude, elevation of a meteorological station, change rate of rainfall along with elevation, vegetation coverage data of each month, area index data of each month, reflectivity of various land utilization earth surfaces to short wave radiation, saturated water content of various soils, field water retention rate of various soils, withering coefficients of various soils, depressed reserve of various land utilization types, transverse-longitudinal-vertical permeability coefficients of various soil layers, slope Manning coefficients and river Manning coefficients.
Step S2: performing energy process simulation, evaporation process simulation, vertical infiltration calculation, slope runoff generation calculation, slope confluence calculation, river confluence calculation and underground water movement calculation according to the hydrological data, the meteorological data, the geological data and the remote sensing data to obtain a distributed hydrological model; the energy process simulation comprises long wave radiation and short wave radiation calculation; the transpiration process simulation comprises vegetation transpiration, vegetation interception evaporation, water area evaporation, bare soil evaporation, urban surface evaporation and building evaporation; and (4) calculating the slope runoff yield, including the hyper-osmotic runoff and the accumulation runoff yield. The evaporation calculation is a known penmanman formula, and the transpiration is a known penmanmontes formula.
The step S2 specifically includes:
step S21: finely classifying the types of the underlying surfaces according to the national standard 'classification of the current situation of land utilization'; the refined classification represents that the underlying surface type is divided into preset classification numbers;
step S21 belongs to fine simulation, the types of the underlying surfaces are refined into 25 types according to the national standard 'classification of the current land utilization', each grid corresponds to one type of land utilization, and an independent vertical hydrologic cycle process is provided. The 25 types of underlying surfaces can be changed, increased or decreased, and are adjusted according to simulation requirements.
Step S22: calculating long wave radiation and short wave radiation for each underlying surface to carry out energy process simulation;
and (4) energy process simulation, which comprises calculation of long-wave radiation and short-wave radiation of different underlying surfaces.
Step S23: simulating the evaporation and heat dissipation process according to the vegetation transpiration condition, the vegetation interception evaporation condition, the water evaporation condition, the bare soil evaporation condition, the urban landmark evaporation condition and the building evaporation condition;
and (3) simulating the evapotranspiration process, including vegetation transpiration, vegetation interception evaporation, water evaporation, bare soil evaporation, urban surface evaporation and building evaporation.
Step S24: calculating the variation of the soil water and the underground water according to infiltration and evaporation; namely, vertical infiltration calculation and slope runoff yield calculation are carried out in the process of calculating the variation of soil water and underground water;
specifically, step S24 specifically includes:
acquiring the net rainfall of the rainfall entering the soil through interception and depression filling;
acquiring a first water amount for supplying the soil with the net rainfall infiltration;
obtaining a second water amount evaporated to return to the atmosphere and a third water amount evaporated from the vegetation to the atmosphere;
obtaining a fourth amount of water that is finally retained in the soil;
and determining the exchange process of the surface water and the underground water according to the net rainfall of the soil, the first water amount, the second water amount, the third water amount and the fourth water amount, and further realizing the vertical infiltration calculation.
The earth's surface exchanges with the underground water volume, and precipitation gets into soil through holding and filling the hole, and water infiltration partly supplies groundwater to water in the soil, and partly evaporates and returns the atmosphere, and partly transpires to the atmosphere through the vegetation, and partly remains in soil, and the computational formula is as follows:
P n ＝P-W r -H(S24-1)
W g ＝W 0 +W i -W s -W e (S24-3)
in the formula: p is rainfall (mm); p is n Net rainfall (mm), i.e., production flow; w r Cut-off for vegetation (mm); h is depression reserve (mm); f is infiltration capacity (mm/t); w 0 Initial soil moisture content (mm); w i The soil infiltration amount (mm); w is a group of s Saturated water content (mm) of the soil; w is a group of e Is the evaporation (mm); w is a group of g The amount (mm) of groundwater for rainfall replenishment; q is the lateral inflow (m) 3 T); a is the area of the supply region (m) 2 ) (ii) a Δ t is the time interval (t); s is the water storage rate (1/m); Δ h is a water level variation (m); v is the volume (m) of the underground water control body 3 )。
The amount of infiltration is Wi in formula S24-2 and the amount of production is Pn in formula S24-1.
Step S25: and carrying out slope convergence and river convergence simulation by using the motion wave model.
Specifically, step S25 specifically includes:
step 1: determining the topological relation and the calculation sequence of a slope surface grid and a river course grid through confluence cumulant and flow direction on the basis of a river network water system generated by the DEM;
and 2, step: and (3) constructing a water balance equation (equation S25-2) in the grid through a continuity equation (equation S25-1), substituting a Manning equation (equation S25-3) and a river section equation (S25-4) into the water balance equation, and digitizing the motion wave equation to obtain simulated slope convergence and simulated river convergence. At this time, the river channel is generalized into a rectangular river channel, the slope convergence is generalized into a wide-shallow channel, and the water balance in the grid is schematically shown in fig. 10.
Equation of continuity
Equation of water balance
Manning formula
River section equation A = b × h (formula S25-4)
In the above formula: a1 and A2 are the cross-sectional area (m) of water at the beginning and end of the grid period 2 ) (ii) a Qin is the upstream incoming water flow (m 3/s) of the grid (including the lateral incoming water flow Qside of the grid, such as the water quantity flowing into the river channel by the slope confluence and the self-generated flow of the grid); q1 and Q2 are the grid outflow water quantity (m) at the beginning and the end of the grid time period respectively 3 S); n is a Manning roughness coefficient of the grid surface; r is the hydraulic radius (m) of the grid river channel or the slope wide and shallow channel; s 0 Is a grid slope or a longitudinal slope of a river; b is the grid width (m); h is the depth of water (m) in the grid.
Step S26: and simulating the movement of the underground water according to the Darcy formula.
Step S26 specifically includes:
mesh generation is carried out on the underground water simulation area;
applying mass conservation and Darcy formula to a single grid to obtain the flow between two adjacent grids;
selecting a central grid in the grids, and determining a first flow rate of peripheral grids flowing into the corresponding central grid for each central grid according to the flow rate between two adjacent grids; the peripheral grid refers to a grid connected with the central grid, and the central grid is a grid surrounded by other grids;
calculating a second flow rate of any source of the aquifer to the central grid;
calculating a third flow rate of an aquifer multi-source flow to the central grid;
determining a difference equation of each grid according to the first flow, the second flow and the third flow in combination with the continuity equation;
and obtaining the water level condition of each grid according to the difference equation of each grid.
More specifically describing groundwater motion simulation: and calculating by adopting a Darcy formula. According to the simulation requirement, mesh generation is performed on the groundwater simulation area based on the grid division mode, as shown in fig. 11. The size of the underground water grid is consistent with that of the surface water simulation grid. The thickness of the underground aquifer is divided according to the local actual condition. A single grid calculation is related to its neighboring grids (up, down, left, right, front, back) as shown in fig. 12. Wherein i, j, k represent row, column, layer, respectively.
Applying the principle of conservation of mass and Darcy's law for cell (i, j, k) is:
in the formula: h is i,j,k ,h i,j-1,k The head values at nodes (i, j, k), (i, j-1, k), respectively. q. q.s i,j-1/2,k Is the traffic between node (i, j, k) and node (i, j-1, k); KR (Kr) i,j-1/2,k Is hydraulic conductivity coefficient; is the cross-sectional area; is the distance between two points.
The following can be obtained by the same way:
wherein KV, KR and KC are integral variables respectively representing vertical (vertical), row (row) and column (column) in each axis of xyz marked in FIG. 11.
Therefore, formula S26-2 can be written as:
wherein, CR, CC, CV are an integral variable, which respectively represents a vertical (vertical), a row (row), and a column (column), and these three variables are intermediate variables, which have no practical meaning and are used for simplifying the equation.
Equation S26-4 represents the flow from the adjacent 6 faces onto the junction (i, j, k). The flow from any source outside the aquifer to node (i, j, k) may be represented by the following equation:
a i,j,k,n ＝P i,j,k,n +q i,j,k,n (S26-5)
in the formula: supply (m) of the grid to the outside 3 D); the influence of the surface water circulation process on the underground water of the grid, such as river leakage replenishment and rainfall infiltration replenishment (m) 2 D), etc.; influence of artificial effect on the underground water of the grid, e.g. pumping capacity (m) 3 /d)。
In general, if there are N sources that have an effect on node (i, j, k), then the total flow from these N sources to node (i, j, k) is:
order to
Formula S26-6 can be written as:
QS i,j,k ＝P i,j,k h i,j,k +Q i,j,k (formula S26-7)
From the continuity equation:
in the formula: is the change of water level with time (L/t); the water storage rate (1/L) is the node (i, j, k); is the volume (L) of node (i, j, k) 3 )。
Equations S26-4 and S26-5 are substituted for equation 26-8 to obtain the finite difference equation at node (i, j, k) as follows:
wherein S is represented by the differentiated parameter, and the meaning is the water storage rate.
Differential after orientation method, equation S26-9 can be written as:
and obtaining a difference equation of each grid in the underground water simulation area in the same way, wherein the equation with the corresponding number is formed by the number of the grids.
The formula S26-10 is arranged, and the underground water level (h) at the moment in the formula is compared with the underground water level at the moment m ) Puts the groundwater level at the previous moment and the known term to the right of the equation, as shown in equation S26-11.
Order to
Forming a matrix: [A] x { h } = { q }.
In the formula: a is a coefficient matrix; h is the water level of each grid at the moment and a variable matrix to be solved; q is a matrix of known terms.
The above equation is converted into a display format S26-13, and iterative solution is performed (the water level of the central grid at the time m is calculated by using the water levels of the peripheral grids at the time m-1, the upper limit of the iterative times is 10 times, and the iterative error is 0.01 m). Grid (i, j) and its surrounding grids are calculated as shown in FIG. 13.
And step S3: calculating and counting the surface flow rates of the watershed at different time scales based on the distributed hydrological model, and obtaining flow rate coefficients at different time periods in the watershed space by combining precipitation;
and step S4: calculating and counting the evaporative heat rejection of the basin at different time scales based on the distributed hydrological model and determining the ratio (NPP/ET) of the evaporative heat rejection to the net primary productivity in combination with the net primary productivity of different land use types.
Calculating and counting evapotranspiration of each grid in different time scales in the flow domain by using the written and debugged distributed hydrological model, obtaining spatial distribution of net primary productivity in the flow domain by using net primary productivity quota of different land utilization types and land utilization spatial distribution, and finally comparing NPP and ET in space to obtain spatial distribution of NPP/ET in different time scales.
Wherein, step S4 specifically includes:
calculating and counting evaporation heat dissipation amounts of different time scales of a watershed based on the distributed hydrological model;
obtaining a spatial distribution of net primary productivity within the territory using the net primary productivity quota of different land use types and the spatial distribution of land use;
determining a ratio between said heat rejected by evaporation and said net primary productivity spatially, resulting in a spatial distribution of said ratio of heat rejected by evaporation and said net primary productivity over different time scales.
Step S5: and determining the interaction law of water and soil resources according to the current generation coefficient and the ratio of the evaporative heat dissipation to the net primary productivity.
Step S5 specifically includes:
and taking the runoff yield coefficients of different time periods in the watershed space as indexes for researching the influence of the land resources on water resources, taking the spatial distribution of the ratio of the evaporation heat dissipation capacity to the net primary productivity in different time scales as indexes for researching the influence of the water resources on the land resources, and analyzing the mutual feeding effect of the water and soil resources from two angles of time and space.
It should be noted that after the distributed hydrological model is obtained, model calibration and verification are also included, which specifically includes:
mutation point inspection, namely performing mutation inspection on rainfall data by using a Mann-Kendall method, wherein the time before a mutation point is used as a rate period, and the time after the mutation point is used as a verification period;
calibrating the model, debugging various parameters, judging the simulation effect of the model through three indexes of a correlation coefficient, a Nash coefficient and a relative error, and adjusting parameters until the three indexes meet the requirements, and ending parameter adjustment;
and (3) model verification, namely fixing parameters on the basis of model calibration, and performing simulation verification on the calibration period, wherein if the three indexes pass, the model verification passes.
In the embodiment, a hydrological model for fine simulation of a watershed from the earth surface to the underground and from a slope to a river channel is compiled by using a Python language, and the hydrological model is applied to research on interaction of water and soil resources. Model input data preparation, including topographic and geomorphic data: elevation, slope, land utilization type, soil type and thickness, river network, meteorological data: weather station information, precipitation, temperature, wind speed, relative humidity, illumination time and other basic data and parameters; refined simulation, wherein the type of the refined underlying surface is 25 types, each simulation unit has a set of hydrological parameters, and independent vertical hydrological simulation is carried out; determining the rate period before the mutation point and determining the verification period after the mutation point by analyzing the mutation of rainfall data; model application, namely outputting precipitation, runoff, evapotranspiration and the like at different time and different spatial positions in the stream domain; and identifying the water and soil resource mutual feedback action. The basin multi-process multi-factor fine simulation can be realized, each simulation unit has one set of hydrological parameters, independent vertical hydrological simulation can be carried out, then the transverse relation is realized through the grid topological relation, the runoff quantity in the slope, the underground and the river channel is finally obtained, and technical support is provided for comprehensive treatment of the basin and optimal configuration of water and soil resources.
Example 2
The embodiment provides a water and soil resource interaction feed mechanism recognition system, which includes:
the data acquisition module M1 is used for acquiring hydrological data, meteorological data, geological data and remote sensing data of a target area;
the distributed hydrological model simulation module M2 is used for carrying out energy process simulation, evaporation and heat dissipation process simulation, vertical infiltration calculation, slope runoff calculation, slope confluence calculation, river confluence calculation and underground water movement calculation according to the hydrological data, the meteorological data, the geological data and the remote sensing data to obtain a distributed hydrological model; the energy process simulation comprises long-wave radiation and short-wave radiation calculation; the simulation of the evapotranspiration process comprises vegetation transpiration, vegetation interception and evaporation, water evaporation, bare soil evaporation, urban land surface evaporation and building evaporation;
the runoff yield coefficient calculation module M3 is used for calculating and counting the surface runoff yields of the watershed at different time scales based on the distributed hydrological model and obtaining the runoff yield coefficients of the watershed at different time periods by combining precipitation;
the ratio calculation module M4 of the evaporative heat dissipation to the net primary productivity is used for calculating and counting the evaporative heat dissipation of different time scales of the watershed based on the distributed hydrological model and determining the ratio of the evaporative heat dissipation to the net primary productivity by combining the net primary productivity of different land utilization types;
and the water and soil resource interaction rule acquisition module M5 is used for determining a water and soil resource interaction rule according to the runoff yield coefficient and the ratio of the evaporative heat dissipation to the net primary productivity.
The principle and the embodiment of the present invention are explained by applying specific examples, and the above description of the embodiments is only used to help understanding the method and the core idea of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.
Claims (9)
1. A method and a system for identifying a water and soil resource mutual feedback mechanism are characterized by comprising the following steps:
acquiring hydrological data, meteorological data, geological data and remote sensing data of a target area;
performing energy process simulation, evaporation heat dissipation process simulation, vertical infiltration calculation, slope runoff production calculation, slope confluence calculation, river confluence calculation and groundwater movement calculation according to the hydrological data, the meteorological data, the geological data and the remote sensing data to obtain a distributed hydrological model; the energy process simulation comprises long-wave radiation and short-wave radiation calculation; the transpiration process simulation comprises vegetation transpiration, vegetation interception evaporation, water area evaporation, bare soil evaporation, urban surface evaporation and building evaporation;
calculating and counting the surface flow rates of the watershed at different time scales based on the distributed hydrological model, and obtaining flow rate coefficients at different time periods in the watershed space by combining precipitation;
calculating and counting the evaporation heat dissipation capacity of the basin at different time scales based on the distributed hydrological model, and determining the ratio of the evaporation heat dissipation capacity to the net primary productivity by combining the net primary productivity of different land utilization types;
and determining the interaction law of water and soil resources according to the current generation coefficient and the ratio of the evaporative heat dissipation to the net primary productivity.
2. The method according to claim 1, wherein the acquiring of the hydrological data, meteorological data, geological data and remote sensing data of the target area specifically comprises:
on the basis of the digital elevation model DEM of the target area, performing filling calculation, flow direction calculation and confluence cumulant calculation by using a hydrological analysis tool to generate a basin, and obtaining basin hydrological analysis data;
cutting the digital elevation model DEM by taking a drainage basin range in the drainage basin water analysis data as a boundary condition to obtain drainage basin elevation data, soil type data, soil thickness data, land utilization type data and river network data;
selecting weather stations and rainfall stations within the drainage basin range and the preset range, and numbering the weather stations and the rainfall stations in sequence;
respectively drawing Thiessen polygons of the weather station and the rainfall station by utilizing a Thiessen polygon creating tool;
respectively converting the drawn Thiessen polygon mounting weather station number and the drawn Thiessen polygon mounting weather station number into raster files by taking the drainage basin range as a boundary;
extracting meteorological data and precipitation data based on the raster file;
acquiring latitude and elevation of a meteorological station, change rate of rainfall along with elevation, vegetation coverage data of each month, leaf area index data of each month, reflectivity of various land utilization earth surfaces to short wave radiation, saturated water content of various soils, field water retention rate of various soils, withering coefficients of various soils, depression storage amount of various land utilization types, transverse-longitudinal-vertical permeability coefficients of various soil layers, domatic Manning coefficients and riverway Manning coefficients based on the grid file.
3. The method according to claim 2, wherein the calculating and counting of the evaporative heat dissipation capacity of the basin on different time scales based on the distributed hydrological model and the determining of the ratio of the evaporative heat dissipation capacity to the net primary productivity in combination with the net primary productivity of different land use types comprises:
calculating and counting evaporation heat dissipation amounts of different time scales of a basin based on the distributed hydrological model;
obtaining a spatial distribution of net primary productivity within the territory using the net primary productivity quotients of the different land use types and the spatial distribution of land use;
determining a ratio between said heat rejected by evaporation and said net primary productivity spatially, resulting in a spatial distribution of said ratio of heat rejected by evaporation and said net primary productivity over different time scales.
4. The method of claim 3, wherein determining a water and soil resource interaction law from said current generation coefficient and said ratio of evaporative heat rejection to net primary productivity comprises:
and taking the runoff yield coefficients of different time periods in the watershed space as indexes for researching the influence of the land resources on water resources, taking the spatial distribution of the ratio of the evaporative heat dissipation capacity to the net primary productivity in different time scales as indexes for researching the influence of the water resources on the land resources, and analyzing the mutual feedback effect of the water and soil resources from two angles of time and space.
5. The method according to claim 2, wherein the performing energy process simulation, evaporative heat dissipation process simulation, vertical infiltration calculation, slope runoff calculation, slope confluence calculation, river confluence calculation, and groundwater movement calculation according to the hydrological data, the meteorological data, the geological data, and the remote sensing data to obtain the distributed hydrological model specifically comprises:
finely classifying the types of the underlying surfaces according to the national standard 'classification of the current situation of land utilization'; the refined classification represents that the types of the underlying surfaces are divided into preset classification numbers;
calculating long wave radiation and short wave radiation for each underlying surface to carry out energy process simulation;
simulating the evaporation and heat dissipation process according to the vegetation transpiration condition, the vegetation interception evaporation condition, the water evaporation condition, the bare soil evaporation condition, the urban landmark evaporation condition and the building evaporation condition;
vertical infiltration calculation and slope runoff calculation are carried out in the process of calculating the variation of the soil water and the underground water;
simulating slope convergence and river convergence by using a motion wave model;
and simulating the underground water movement according to the Darcy formula.
6. The method according to claim 5, wherein the vertical infiltration calculation and the slope runoff calculation are performed in the process of calculating the variation of the soil water and the groundwater, and specifically comprise:
acquiring the net rainfall of the rainfall entering the soil through interception and depression filling;
acquiring a first water amount for supplying the soil with the net rainfall infiltration;
obtaining a second water amount evaporated to return to the atmosphere and a third water amount evaporated from the vegetation to the atmosphere;
obtaining a fourth amount of water that is ultimately retained in the soil;
and determining the process of exchanging the surface water with the underground water according to the net rainfall of the soil, the first water amount, the second water amount, the third water amount and the fourth water amount, and further realizing vertical infiltration calculation and slope runoff yield calculation.
7. The method according to claim 5, wherein the simulating of slope convergence and river convergence by using the motion wave model specifically comprises:
determining the topological relation and the calculation sequence of a slope surface grid and a river course grid through confluence cumulant and flow direction on the basis of a river network water system generated by the DEM;
and (3) constructing a water balance equation in the grid according to the continuity equation, and quantifying the motion wave equation data by combining a Manning formula and a river course end surface equation to obtain simulated slope convergence and simulated river course convergence.
8. The method according to claim 5, wherein the simulating of groundwater movement according to Darcy's formula comprises:
mesh generation is carried out on the underground water simulation area;
applying mass conservation and Darcy formula to a single grid to obtain the flow between two adjacent grids;
selecting a central grid in the grids, and determining a first flow rate of peripheral grids flowing into the corresponding central grid for each central grid according to the flow rate between two adjacent grids; the peripheral grid refers to a grid connected with the central grid, and the central grid is a grid surrounded by other grids;
calculating a second flow rate of any source of the aquifer to the central grid;
calculating a third flow rate of an aquifer multi-source flow to the central grid;
determining a difference equation of each grid according to the first flow, the second flow and the third flow in combination with the continuity equation;
and obtaining the water level condition of each grid according to the difference equation of each grid.
9. A water and soil resource mutual feedback mechanism recognition system is characterized by comprising:
the data acquisition module is used for acquiring hydrological data, meteorological data, geological data and remote sensing data of a target area;
the distributed hydrological model simulation module is used for carrying out energy process simulation, evaporation and heat dissipation process simulation, vertical infiltration calculation, slope runoff calculation, slope confluence calculation, river confluence calculation and underground water movement calculation according to the hydrological data, the meteorological data, the geological data and the remote sensing data to obtain a distributed hydrological model; the energy process simulation comprises long-wave radiation and short-wave radiation calculation; the simulation of the evapotranspiration process comprises vegetation transpiration, vegetation interception and evaporation, water evaporation, bare soil evaporation, urban land surface evaporation and building evaporation;
the flow production coefficient calculation module is used for calculating and counting the surface flow production of the drainage basin at different time scales based on the distributed hydrological model and obtaining the flow production coefficient of the drainage basin at different time periods by combining precipitation;
the ratio calculation module of the evaporative heat dissipation and the net primary productivity is used for calculating and counting the evaporative heat dissipation capacity of the basin at different time scales based on the distributed hydrological model and determining the ratio of the evaporative heat dissipation and the net primary productivity by combining the net primary productivity of different land utilization types;
and the water and soil resource interaction rule acquisition module is used for determining the water and soil resource interaction rule according to the runoff yield coefficient and the ratio of the evaporative heat dissipation to the net primary productivity.
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| CN118297288A (en) * | 2024-06-05 | 2024-07-05 | 清华大学 | Full remote sensing watershed water resource quantity evaluation method and device |
| CN118332971A (en) * | 2024-06-13 | 2024-07-12 | 长江水利委员会长江科学院 | Optimization of distributed hydrologic model and determination method and device of hydrologic data |
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| CN118297288A (en) * | 2024-06-05 | 2024-07-05 | 清华大学 | Full remote sensing watershed water resource quantity evaluation method and device |
| CN118332971A (en) * | 2024-06-13 | 2024-07-12 | 长江水利委员会长江科学院 | Optimization of distributed hydrologic model and determination method and device of hydrologic data |
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