CN115132054A - Environmental water flow and habitat demand simulation model based on river food net - Google Patents
Environmental water flow and habitat demand simulation model based on river food net Download PDFInfo
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Abstract
The invention discloses an environmental water flow and habitat demand simulation model based on a river food network, which comprises a flow and habitat suitable area relation module, a habitat suitable level space estimation module and a potential resource amount estimation module of aquatic organisms, wherein the flow and habitat suitable area relation module is connected with the habitat suitable level space estimation module; the flow and habitat suitable area relation module is used for analyzing the requirements of habitat organisms to obtain a habitat suitability curve of a target species; the space estimation module of the habitat suitability level is used for estimating a comprehensive suitability index value of the habitat; the potential resource quantity estimation module of the aquatic organisms multiplies the measured biomass according to the analysis data of the flow and habitat suitable area relation module and the habitat suitable grade space estimation module to calculate the potential resource quantity of the aquatic organisms; the invention realizes the simulation of the relationship between the flow of each river section and the suitable area of the habitat, and the estimation of the suitable level of the habitat and the potential resource amount of aquatic organisms.
Description
Technical Field
The invention relates to the technical field of hydrological ecological simulation models, in particular to an environmental water flow and habitat demand simulation model based on a river food net.
Background
Water is an essential precious natural resource for human survival and production activities. In addition to meeting the requirement of human water supply, the river hydrologic ecology in the natural ecological environment needs to be paid attention to all the time, the existing research on the river hydrologic ecology can not be comprehensively analyzed based on a demand model of habitat organisms and a simulation model of habitat environment, and the influence of the demand characteristics and environmental parameters of species on the river hydrologic ecology can not be comprehensively considered; meanwhile, on the basis of considering the demand characteristics of species and the environmental characteristics of environmental parameters, the relation between the flow and the suitable area of the habitat cannot be established for ecological flow decision, and the suitable level of the habitat and the potential resource amount of aquatic organisms cannot be effectively estimated.
Disclosure of Invention
The invention aims to provide an environmental water flow and habitat demand simulation model based on a river food net so as to solve the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: the simulation model comprises a flow and habitat suitable area relation module, a habitat suitable grade space estimation module and a potential resource amount estimation module of aquatic organisms;
the flow and habitat suitable area relation module is used for analyzing the requirements of habitat organisms to obtain a habitat suitable degree curve of a target species, simulating the habitat environment to obtain the flow speed, the water depth and the water body area distribution of river sections under different flows, researching the flow speed, the water depth and the water body area distribution of the river sections by the flow and habitat suitable area relation module according to the different flows obtained by simulating the habitat environment, calculating the suitable habitat area by combining the habitat suitable degree curve of the target species, and analyzing to obtain a proper habitat area duration curve of plants;
the space estimation module of the habitat suitability level is used for estimating a comprehensive suitability index value of the habitat;
the potential resource quantity estimation module of the aquatic organisms multiplies the measured biomass to calculate the potential resource quantity of the aquatic organisms according to the analysis data of the flow and habitat suitable area relation module and the habitat suitable level space estimation module.
Further, the flow and habitat suitable area relation module comprises a habitat biological demand model establishing unit;
the habitat biological demand model establishing unit acquires biomass of an environment where a target species is located, monitors corresponding environmental parameters, and utilizes a formula:
HIS＝Ni/N
calculating a habitat suitability index, wherein Ni represents the biomass of the target species observed within different environmental parameter ranges, and N is the total biomass of the target species within the study area; and 0 ≦ HIS ≦ 1, where 0 represents a habitat condition completely unsuitable for the target species and 1 represents a habitat condition most suitable for the target species;
and quantifying the sampled data according to the habitat suitability index HIS to obtain habitat suitability indexes HIS in different environmental parameter ranges, and obtaining a habitat suitability curve of the target species according to the habitat suitability indexes HIS in different ranges.
Further, the flow and habitat suitable area relation module further comprises a habitat environment simulation model establishing unit;
the habitat environment simulation model building unit builds a two-dimensional hydrodynamic model by applying water conservancy model software, and calculates the flow velocity, the water depth and the water area distribution of the research river reach under different flows; the hydrodynamic model mainly comprises a riverbed terrain establishing unit, a calculation grid dividing unit, an entrance and exit boundary condition determining unit and a rating and verification model establishing unit;
establishing a riverbed terrain unit, inputting a remote sensing image of a researched river reach into a model as a base map, drawing a simulation boundary of the researched river reach according to the remote sensing image, inputting terrain elevation data of the researched river reach and setting projection information, and loading the terrain elevation data onto the base map of the remote sensing image;
the division calculation grid unit performs grid division and terrain interpolation on terrain elevation data by using triangular grids or square grids in a simulation boundary of a research river reach on the basis of establishing a riverbed terrain unit;
determining an inlet-outlet boundary of an inlet-outlet boundary condition unit in a model, inputting a simulated flow value and a simulated water level value, setting the inlet boundary condition as a flow value to be simulated, and setting the outlet boundary condition as a corresponding simulated water level value;
after determining the boundary conditions of an inlet and an outlet, a calibration and verification model establishing unit respectively sets different vortex viscosity coefficients and Manning coefficients to operate a model according to a two-dimensional shallow water Saint-Venen equation, and simulates the flow velocity, the water depth and the water level under different flows; then comparing the simulated flow velocity, the water depth and the water level with the actually measured flow velocity, water depth and water level, and adjusting the vortex viscosity coefficient, the Manning coefficient, the boundary conditions and the like to minimize the error between the vortex viscosity coefficient and the Manning coefficient; setting a rated vortex-viscosity coefficient, a Manning coefficient and boundary conditions, comparing the error between the simulated value and the measured value by using another period of measured data, and if the error is smaller than a set threshold value, verifying the model;
the specific steps of calculating the flow velocity, the water depth and the water area distribution of the river section under different flows are as follows:
the habitat environment simulation model establishing unit applies the verified model, inputs the boundary conditions of the flow and the water level to be simulated, and operates the model to simulate the spatial distribution values of the flow speed, the water depth and the water level on each grid node under the flow condition; the habitat environment simulation model building unit counts the area of all grid units with the water depth larger than 0 area, and the area is the water area under the flow.
Further, the module for solving the relationship between the flow and the suitable area of the habitat also comprises a unit for solving the relationship between the flow and the suitable area of the habitat,
the flow and habitat suitable area relation solving unit utilizes a formula:
calculating and researching a weight value suitable habitat area WUA on the river reach, wherein delta Ai is the area of the ith grid unit, the area of the grid unit is set according to the size of a grid in a habitat environment simulation model building unit, and CHSIi is a comprehensive suitability index corresponding to the ith grid unit; if the grid size range in the hydrodynamic model is 50-150 square meters, calculating the grid unit area suitable for the habitat area and setting the grid unit area as a value in the range;
the flow and habitat suitable area relation solving unit repeats the process for each simulated flow to obtain a corresponding weight suitable habitat area WUA, and a relation curve Q-WUA of the target flow Q and the weight suitable habitat area WUA is constructed;
a flow and habitat suitable area relation solving unit acquires a flow duration curve Q-t, wherein the flow duration curve Q-t is daily average flow time sequence data; the flow and habitat suitable area relation solving unit finds a WUA value corresponding to each target flow Q on a Q-WUA curve through internal operation of curve interpolation according to the Q-WUA relation curve, so that daily average flow time series data are converted into WUA time series data, and finally a plant habitat suitable area duration curve WUA-t of a plant is obtained, wherein the WUA-t curve is WUA daily average time series data corresponding to daily average flow time series date.
Further, the calculation of the composite suitability index value comprises the following steps:
the habitat suitability level space estimation module utilizes the formula:
CHSIi＝HSI1×b1+HIS2×b2+...+HISn×bn
calculating a comprehensive suitability index CHSIi corresponding to the ith grid unit, wherein HIS1, a.... wherein HISn represents habitat suitability indexes corresponding to n environmental factors, and b1, a.... wherein bn represents the response weight of the target species to the n environmental factors; the weight determination method comprises the following steps:
bj represents the response weight of the target species to the j-th environmental factor, Rj represents the correlation coefficient of the target species and the j-th environmental factor, and j is {1, 2.
Further, the potential resource amount estimation module of the aquatic organisms comprises a vegetation resource amount calculation unit, a benthonic animal resource amount calculation unit, a phytoplankton resource amount calculation unit and a zooplankton resource amount calculation unit;
the vegetation resource amount calculation unit uses a formula:
calculating the wet plant resource quantity SH and the emergent aquatic plant resource quantity SE, wherein deltaSHk represents the difference between the areas of suitable habitats of adjacent months, BHk represents the biomass of a second february wet plant, SEk represents the intersection of the areas of 2-6 months of emergent aquatic plants, BEk represents the biomass of emergent aquatic plants in June, R is the ratio of plant leaves to the biomass of the whole plant, k represents month, and k is {1,2,....... multidot.12 };
the benthonic animal resource amount calculation unit utilizes a formula:
calculating the benthonic animal resource amount SB, Sk representing the area of a proper habitat in the kth month, B1 representing high proper biomass, the high proper biomass being the biomass when the flow rate of the research river section is less than or equal to a preset threshold value m1, B2 representing the moderate proper biomass, the moderate proper biomass being the biomass when the flow rate of the research river section is greater than a preset threshold value m1 and less than or equal to a preset threshold value m2, HSI1 representing a high proper region proper index, and HSI2 representing a moderate proper region proper index;
the phytoplankton resource amount calculation unit utilizes a formula:
Sp＝{0.66125×6.6×Copt×(1.7239×SD+0.1685)×Dirr×0.87)}×A×S×365×10 (-3)
calculating the phytoplankton production Sp in the whole research area, wherein Copt represents the chlorophyll concentration of the maximum carbon fixed rate depth, SD represents the transparency, Dirr represents the illumination period, A represents the calibration coefficient, and S represents the annual average water surface area;
the zooplankton resource amount calculation unit utilizes a formula:
and calculating the zooplankton resource amount Sz, wherein Pk represents the average water body surface area in the k th month, and B represents zooplankton biomass.
Further, the potential resource amount estimation module of the aquatic organisms further comprises a fish potential estimation unit;
the fishing potential estimation unit calculates the result of the unit according to the vegetation resource amount by using a formula:
FH＝SH/80
FE＝SE/200
estimating the fishery potential FH provided by the hygrophyte and the fishery potential FE provided by the emergent aquatic plants;
the fish potential estimation unit calculates the result of the unit according to the amount of the benthonic animal resources by using a formula:
FB＝0.1×SB
estimating the fishing potential FB that the benthonic animals can provide;
the fishing potential estimation unit calculates the result of the unit according to the phytoplankton resource amount by using a formula:
Fp＝0.0515×Sp
estimating the fishery potential Fp provided by phytoplankton;
the fish potential estimation unit calculates the result of the unit according to the zooplankton resource amount, and utilizes the formula:
Fz＝1.17×Sz
estimating the potential Fz of fishery provided by zooplankton.
Further, the potential resource amount estimation module of the aquatic organisms further comprises a finless porpoise resource amount estimation unit;
the finless porpoise resource quantity estimation unit utilizes a formula:
T＝[(FH+FE+Fp+Fz+FB)×B×C×D]/(E×6％×365)
the number of potential finless porpoise sustainable in the study area, T, was estimated, where B represents the weight of fish with body length less than a preset length as a percentage of the total fish weight, C represents the percentage of fish with body length less than a preset length ingested by finless porpoise, D represents the conversion efficiency of finless porpoise into fish, E represents finless porpoise weight, 6% represents the average daily food intake of finless porpoise at about 6% of body weight, and 365 represents 365 days per year.
Compared with the prior art, the invention has the following beneficial effects: the invention establishes the relation between the flow and the suitable area of the habitat for ecological flow decision and introduces the food net concept for potential resource amount estimation of aquatic organisms on the basis of a habitat organism demand model and a habitat environment simulation model which are coupled with target species.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a finless fish energy flow food net of the present invention based on a river food net ambient water flow and habitat demand simulation model;
FIG. 2 is an exemplary graph of one-dimensional flow data in a Q-WUA program of the present invention based on a simulation model of the environmental current and habitat demand of a river food network;
FIG. 3 is an exemplary graph of species name data in the Q-WUA program of the present invention based on a simulation model of the environmental current and habitat demand of a river food network;
FIG. 4 is a two-dimensional flow tabulation format diagram in the WUA-2D program of the present invention based on a river food net ambient water flow and habitat demand simulation model;
FIG. 5 is a plot of species txt in the WUA-2D program of the present invention based on a model of the environmental current and habitat demand simulation of a river food network;
FIG. 6 is a running log graph in the WUA-2D program of the environmental current and habitat demand simulation model based on a river food network of the present invention;
FIG. 7 is a graph of the results of the operation of the WUA-2D program of the present invention based on a simulation model of the environmental current and habitat requirements of a river food network;
FIG. 8 is a diagram of the output file format in the WUA-2D program of the environmental current and habitat demand simulation model of the river food network of the present invention;
FIG. 9 is a schematic diagram of the input files in the Biomass estimation program of the simulation model of the environmental water flow and habitat demand based on the river food network of the present invention;
FIG. 10 is a schematic diagram of the success of the Biomass estimation program of the present invention based on a simulation model of the environmental current and habitat demand of the river food network;
FIG. 11 is a schematic representation of the results of the Biomass estimation procedure based on the simulation model of the environmental current and habitat demand of the river food network of the present invention;
FIG. 12 is a schematic representation of the number of Dolphin Daphne in the Biomass estimation program based on the simulation model of the environmental current and habitat demand of the river food network.
FIG. 13 is a diagram showing the number of Dolphin donut in the Biomass estimation program based on the simulation model of the environmental water flow and habitat demand of the river food network;
FIG. 14 is a graph of the Q-WUA relationship of aquatic weeds in a river food net based simulation model of ambient water flow and habitat demand 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.
Referring to fig. 1-13, the present invention provides a technical solution: the simulation model comprises a flow and habitat suitable area relation module, a habitat suitable grade space estimation module and a potential resource amount estimation module of aquatic organisms;
the flow and habitat suitable area relation module is used for analyzing the requirements of habitat organisms to obtain a habitat suitable degree curve of a target species, simulating the habitat environment to obtain the flow speed, the water depth and the water body area distribution of a river section under different flows, researching the flow speed, the water depth and the water body area distribution of the river section by the flow and habitat suitable area relation module according to the different flows obtained by simulating the habitat environment, calculating the suitable habitat area by combining the habitat suitable degree curve of the target species, and analyzing to obtain a suitable habitat area duration curve of plants;
the space estimation module of the habitat suitability level is used for estimating a comprehensive suitability index value of the habitat;
the potential resource quantity estimation module of the aquatic organisms multiplies the measured biomass to calculate the potential resource quantity of the aquatic organisms according to the analysis data of the flow and habitat suitable area relation module and the habitat suitable level space estimation module.
The flow and habitat suitable area relation module comprises a habitat biological demand model establishing unit;
the habitat biological demand model establishing unit acquires the biomass of the environment where the target species are located, monitors corresponding environment parameters, and utilizes a formula:
HIS＝Ni/N
calculating a habitat suitability index, wherein Ni represents the biomass of the target species observed within different environmental parameter ranges, and N is the total biomass of the target species within the study area; and 0 ≦ HIS ≦ 1, where 0 represents a habitat condition completely unsuitable for the target species and 1 represents a habitat condition most suitable for the target species;
and quantizing the sampled data according to the habitat suitability index HIS to obtain habitat suitability indexes HIS in different environmental parameter ranges, and obtaining a habitat suitability curve of the target species according to the habitat suitability indexes HIS in different ranges.
The flow and habitat suitable area relation module further comprises a habitat environment simulation model establishing unit;
the habitat environment simulation model establishing unit establishes a two-dimensional hydrodynamic model by applying water conservancy model software, and calculates the flow velocity, the water depth and the water area distribution of a research river section under different flows; the hydrodynamic model mainly comprises a riverbed terrain establishing unit, a calculation grid dividing unit, an entrance and exit boundary condition determining unit and a rating and verification model establishing unit;
establishing a riverbed terrain unit, inputting a remote sensing image of a researched river reach into a model as a base map, drawing a simulation boundary of the researched river reach according to the remote sensing image, inputting terrain elevation data of the researched river reach and setting projection information, and loading the terrain elevation data onto the base map of the remote sensing image;
the division calculation grid unit performs grid division and terrain interpolation on terrain elevation data by using triangular grids or square grids in a simulation boundary of a research river reach on the basis of establishing a riverbed terrain unit;
determining an inlet-outlet boundary of an inlet-outlet boundary condition unit in a model, inputting a simulated flow value and a simulated water level value, setting the inlet boundary condition as a flow value to be simulated, and setting the outlet boundary condition as a corresponding simulated water level value;
after determining the boundary conditions of an inlet and an outlet, a calibration and verification model establishing unit respectively sets different vortex viscosity coefficients and Manning coefficients to operate a model according to a two-dimensional shallow water Saint-Venen equation, and simulates the flow velocity, the water depth and the water level under different flows; then comparing the simulated flow velocity, the water depth and the water level with the actually measured flow velocity, water depth and water level, and adjusting the vortex viscosity coefficient, the Manning coefficient, the boundary conditions and the like to minimize the error between the vortex viscosity coefficient and the Manning coefficient; setting a rated vortex-viscosity coefficient, a Manning coefficient and boundary conditions, comparing the error between the simulated value and the measured value by using another period of measured data, and if the error is smaller than a set threshold value, verifying the model;
the specific steps of calculating the flow velocity, the water depth and the water area distribution of the river section under different flows are as follows:
the habitat environment simulation model establishing unit applies the verified model, inputs the boundary conditions of the flow and the water level to be simulated, and operates the model to simulate the spatial distribution values of the flow speed, the water depth and the water level on each grid node under the flow condition; the habitat environment simulation model building unit counts the area of all grid units with the water depth larger than 0 area, and the area is the water area under the flow.
The flow and habitat suitable area relation module further comprises a flow and habitat suitable area relation solving unit,
the flow and habitat suitable area relation solving unit utilizes a formula:
calculating and researching a weight value suitable habitat area WUA on the river reach, wherein delta Ai is the area of the ith grid unit, the area of the grid unit is set according to the size of a grid in a habitat environment simulation model building unit, and CHSIi is a comprehensive suitability index corresponding to the ith grid unit; if the grid size range in the hydrodynamic model is 50-150 square meters, calculating the grid unit area suitable for the habitat area and setting the grid unit area as a value in the range;
the flow and habitat suitable area relation solving unit repeats the process for each simulated flow to obtain a corresponding weight suitable habitat area WUA, and a relation curve Q-WUA of the target flow Q and the weight suitable habitat area WUA is constructed;
the flow and habitat suitable area relation solving unit acquires a flow duration curve Q-t, wherein the flow duration curve Q-t is daily average flow time sequence data; the flow and habitat suitable area relation solving unit finds a WUA value corresponding to each target flow Q on a Q-WUA curve through internal operation of curve interpolation according to the Q-WUA relation curve, so that daily average flow time series data are converted into WUA time series data, and finally a plant habitat suitable area duration curve WUA-t of a plant is obtained, wherein the WUA-t curve is WUA daily average time series data corresponding to daily average flow time series date.
For example, in the unit for solving the relationship between the flow and the suitable area of the habitat, the water plant group in the Yichangjiang section is taken as an example to explain how to solve the WUA time series by applying the Q-WUA curve relationship of the water plants, as shown in FIG. 2;
the calculation of the composite suitability index value comprises the following steps:
the habitat suitability level space estimation module utilizes the formula:
CHSIi＝HSI1×b1+HIS2×b2+...+HISn×bn
calculating a comprehensive suitability index CHSIi corresponding to the ith grid unit, wherein HIS1, a.... the HISn represents habitat suitability indexes corresponding to n environmental factors, and b1, a.. the.. the.bn represents the response weight of the target species to the n environmental factors; the weight determination method comprises the following steps:
bj represents the response weight of the target species to the j-th environmental factor, Rj represents the correlation coefficient of the target species and the j-th environmental factor, and j is {1, 2.
As in the examples: if the environmental factors comprise flow velocity and water depth, b1 and b2 represent the response weights of the target species to the flow velocity and the water depth respectively; r1 and R2 represent the correlation coefficients of the target species with flow rate and water depth, respectively, so that b1 is R1/(R1+ R2), and b2 is R2/(R1+ R2).
The potential resource quantity estimation module of the aquatic organisms comprises a vegetation resource quantity calculation unit, a benthonic animal resource quantity calculation unit, a phytoplankton resource quantity calculation unit and a zooplankton resource quantity calculation unit;
the vegetation resource amount calculation unit uses a formula:
calculating the wet plant resource quantity SH and the emergent aquatic plant resource quantity SE, wherein deltaSHk represents the difference between the areas of suitable habitats of adjacent months, BHk represents the biomass of a second february wet plant, SEk represents the intersection of the areas of 2-6 months of emergent aquatic plants, BEk represents the biomass of emergent aquatic plants in June, R is the ratio of plant leaves to the biomass of the whole plant, k represents month, and k is {1,2,....... multidot.12 };
the method comprises the following steps of: for proclaim, Yichang and Daizhou as examples, the specific data of the biomass of the hydrophyte and the biomass of the emergent aquatic plant are as follows:
the benthonic animal resource quantity calculating unit utilizes a formula:
calculating benthonic animal resource quantity SB, Sk represents a proper habitat area of month k, B1 represents high proper biomass, the high proper biomass is biomass when the flow speed of a research river section is less than or equal to a preset threshold value m1, B2 represents medium proper biomass, the medium proper biomass is biomass when the flow speed of the research river section is greater than a preset threshold value m1 and less than or equal to a preset threshold value m2, HSI1 represents a high proper region proper index, and HSI2 represents a medium proper region proper index;
the method comprises the following steps of: for example, proclivity, Yichang and Daizhou, the specific data of high suitable biomass and medium suitable biomass are as follows:
the phytoplankton resource amount calculation unit utilizes a formula:
Sp＝{0.66125×6.6×Copt×(1.7239×SD+0.1685)×Dirr×0.87)}×A×S×365×10 (-3)
calculating the phytoplankton production Sp in the whole research area, wherein Copt represents the chlorophyll concentration of the maximum carbon fixed rate depth, SD represents the transparency, Dirr represents the illumination period, A represents the calibration coefficient, and S represents the annual average water surface area;
the method comprises the following steps of: for proclivity, Yichang, Daizhou, the specific data of phytoplankton production are as follows:
| name of river section | Phytoplankton production (g/m2) |
| Proctor | 0.0503 |
| Yichang tea | 0.0248 |
| Daihuai Daizhou | 0.0161 |
The zooplankton resource amount calculation unit utilizes a formula:
and calculating the zooplankton resource amount Sz, wherein Pk represents the average water body surface area in the k th month, and B represents zooplankton biomass.
The method comprises the following steps of: for proclaim, Yichang and Daizhou as examples, the specific data of zooplankton biomass are as follows:
| name of river section | Zooplankton biomass (g/m2) |
| Proctor | 0.0091 |
| Yichang tea | 0.0085 |
| Daihuai Daizhou | 0.0213 |
The potential resource quantity estimation module of the aquatic organisms further comprises a fishery potential estimation unit;
the fishing potential estimation unit calculates the result of the unit according to the vegetation resource amount by using a formula:
FH＝SH/80
FE＝SE/200
estimating fishery potential FH (free-standing) provided by a hygrophyte and fishery potential FE (free-standing) provided by an emergent aquatic plant;
the fish potential estimation unit calculates the result of the unit according to the amount of the benthonic animal resources by using a formula:
FB＝0.1×SB
estimating the fishing potential FB that the benthonic animals can provide;
the fishing potential estimation unit calculates the result of the unit according to the phytoplankton resource amount by using a formula:
Fp＝0.0515×Sp
estimating the fishery potential Fp provided by phytoplankton;
the fish potential estimation unit calculates the result of the unit according to the zooplankton resource amount, and utilizes the formula:
Fz＝1.17×Sz
estimating the fish potential Fz that zooplankton can provide.
The potential resource quantity estimation module of the aquatic organisms further comprises a finless porpoise resource quantity estimation unit;
the finless porpoise resource quantity estimation unit utilizes a formula:
T＝[(FH+FE+Fp+Fz+FB)×B×C×D]/(E×6％×365)
the number of potential finless porpoise sustainable in the study area, T, was estimated, where B represents the weight of fish with body length less than a preset length as a percentage of the total fish weight, C represents the percentage of fish with body length less than a preset length ingested by finless porpoise, D represents the conversion efficiency of finless porpoise into fish, E represents finless porpoise weight, 6% represents the average daily food intake of finless porpoise at about 6% of body weight, and 365 represents 365 days per year.
The value of B is between 16.5% and 63.4% according to a large amount of field survey data of Changjiang river trunk flow in 2019 of Chengfei and Gaoshan 2016-plus, and the value used by the formula is 40%. According to the results of the study on the ingestion of the finless porpoise by the Meishigang and the like, the C value is 40 percent, and the D value is 10 percent.
The river hydrological ecological simulation model is applied to the software process as follows:
the model software package is decompressed and stored in the hard disk, and the decompressed model folder comprises three subfolders which are respectively as follows: "bioglass", "wua", "wua 2 d", which are similar in structure and each contain a "cli.exe" file, an "in" folder, an "out" folder, and a "conf" folder. The method comprises the following steps that a 'cli.exe' file is an executable file of a calculation model, an input parameter file required by the model to be calculated is stored in an 'in' folder, a result file of model calculation is stored in an 'out' folder, and a configuration file required by the calculation model is stored in a 'conf' folder;
1. in the Q-WUA program, calculating the relationship between the flow and the suitability area;
the input files required by the input software to run are in an 'in' folder, and comprise: a one-dimensional flow data file and a species name data file;
one-dimensional flow data should be stored in a file named "flow. xlsx", which is illustrated in fig. 2; the file comprises two columns, and the names are respectively: date, flow (m 3/s);
secondly, the information data of the species with the suitable area to be calculated is stored in the file ' species name ' txt ', and the currently supported species are three types as follows: young fish, benthonic animals and flood plain vegetation. Inputting the id parameter corresponding to the above-mentioned species name (note: the first line # is the comment sign), and the calculated result is the suitability area of the species, which is shown in fig. 3;
operating and outputting files: the software running time depends on the period length of the simulation calculation, a 'cli.exe' file is clicked to trigger the model calculation, a new out folder appears after the cli.exe program is executed, and the calculation result is stored in the out folder;
WUA-2D program: inputting a flow space distribution result, selecting a target species, and outputting two-dimensional appropriate area space distribution;
the input files required by the software operation are in an 'in' folder and comprise: a one-dimensional flow data file and a species name data file. Are respectively defined as follows:
flow List, xlsx
The flow list stores the two-dimensional flow data of the past year, and the format is as shown in FIG. 4;
txt species
The species currently supported is shown in FIG. 5, please select the type of species that needs to be calculated ( input 1 or 2 or otherwise);
the software running duration depends on the period of the simulation calculation, the 'cli.exe' file is clicked to trigger the model calculation, and the running is successful as shown in a running log of FIG. 6 in the running process;
the results of the runs are saved in an "out" file. As shown in fig. 7;
the generated output file name is related to the name of the species selected by you, and the format of the output file is as shown in FIG. 8;
each column in FIG. 8 means langitude (latitude), latitude (longitude), hsi (fitness: low, mid, high, respectively);
biomass estimation program
The bioglass program has the function of calculating the number of finless porpoises in the designated river section according to the flow data and the model;
the input files required by the software operation are in the in folder, and the files contained in the in folder are as shown in FIG. 9:
the software running time depends on the period of the simulation calculation, the 'cli.exe' file is clicked to trigger the model calculation, and the running log shown in FIG. 10 shows that the running is successful in the running process;
the specific operation result is saved in the "out" folder, as in fig. 11;
the generated result file is related to the information of the section selected by you. The name of the output file indicates result information of model calculation, for example, the name of the result file is shown in fig. 12, which indicates that the result file is calculated by the number of finless porpoise calculated by the model in the section of the Daizhou river;
the specific content of the "number of finless porpoise. xlsx" file is shown in fig. 12.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. The model is characterized by comprising a flow and habitat suitable area relation module, a habitat suitable grade space estimation module and a potential resource amount estimation module of aquatic organisms;
the flow and habitat suitable area relation module is used for analyzing the requirements of habitat organisms to obtain a habitat suitable degree curve of a target species, simulating the habitat environment to obtain the flow speed, the water depth and the water body area distribution of a river section under different flows, researching the flow speed, the water depth and the water body area distribution of the river section under different flows obtained by simulating the habitat environment, calculating the suitable habitat area by combining the habitat suitable degree curve of the target species, and analyzing to obtain a habitat suitable area duration curve of the plants;
the space estimation module of the habitat suitability level is used for estimating a comprehensive suitability index value of the habitat;
and the potential resource quantity estimation module of the aquatic organisms multiplies the measured biomass according to the analysis data of the flow and habitat suitable area relation module and the habitat suitable grade space estimation module to calculate the potential resource quantity of the aquatic organisms.
2. The river food net based ambient water flow and habitat demand simulation model of claim 1, characterized in that: the flow and habitat suitable area relation module comprises a habitat biological demand model establishing unit;
the habitat biological demand model establishing unit acquires biomass of an environment where a target species is located, monitors corresponding environmental parameters, and utilizes a formula:
HIS＝Ni/N
calculating a habitat suitability index, wherein Ni represents the biomass of the target species observed within different environmental parameter ranges, and N is the total biomass of the target species within the study area; and 0 ≦ HIS ≦ 1, where 0 represents a habitat condition completely unsuitable for the target species and 1 represents a habitat condition most suitable for the target species;
and quantizing the sampled data according to the habitat suitability index HIS to obtain habitat suitability indexes HIS in different environmental parameter ranges, and obtaining a habitat suitability curve of the target species according to the habitat suitability indexes HIS in different ranges.
3. The river food net based ambient water flow and habitat demand simulation model of claim 2, characterized in that: the flow and habitat suitable area relation module further comprises a habitat environment simulation model establishing unit;
the habitat environment simulation model establishing unit establishes a two-dimensional hydrodynamic model by applying water conservancy model software, and calculates the flow velocity, the water depth and the water area distribution of a research river section under different flows; the hydrodynamic model mainly comprises a riverbed terrain establishing unit, a calculation grid dividing unit, an entrance and exit boundary condition determining unit and a rating and verification model establishing unit;
the method comprises the steps that a riverbed terrain establishing unit inputs a remote sensing image of a researched river reach into a model as a base map, a simulation boundary of the researched river reach is sketched according to the remote sensing image, terrain elevation data of the researched river reach is input, projection information is set, and therefore the terrain elevation data are loaded on the base map of the remote sensing image;
the grid division and calculation unit carries out grid division and terrain interpolation on terrain elevation data by using triangular grids or square grids in a simulation boundary of a research river reach on the basis of establishing a riverbed terrain unit;
the method comprises the steps that an inlet boundary and an outlet boundary of an inlet boundary condition unit and an outlet boundary of a boundary condition unit in a model are determined, a simulated flow value and a simulated water level value are input, the inlet boundary condition is set to be a flow value to be simulated, and the outlet boundary condition is set to be a corresponding simulated water level value;
after determining the boundary conditions of an inlet and an outlet, the calibration and verification model establishing unit respectively sets different vortex viscosity coefficients and Manning coefficients to operate a model according to a two-dimensional shallow water Saint-Venen equation, and simulates the flow speed, the water depth and the water level under different flows; then comparing the simulated flow velocity, the water depth and the water level with the actually measured flow velocity, water depth and water level, and adjusting the vortex viscosity coefficient, the Manning coefficient, the boundary conditions and the like to minimize the error between the vortex viscosity coefficient and the Manning coefficient; setting the calibrated vortex viscosity coefficient, the Manning coefficient and the boundary conditions, comparing the error between the simulated value and the measured value by using another period of measured data, and if the error is smaller than a set threshold value, verifying the model;
the specific steps of calculating the flow velocity, the water depth and the water area distribution of the river section under different flows are as follows:
the habitat environment simulation model establishing unit applies the verified model, inputs the boundary conditions of flow and water level to be simulated, and operates the model to simulate the spatial distribution values of flow velocity, water depth and water level on each grid node under the flow condition; and the habitat environment simulation model establishing unit is used for counting the area of all grid units with the water depth larger than 0 area, namely the area of the water body under the flow.
4. The river food net based ambient water flow and habitat demand simulation model of claim 3, characterized in that: the flow and habitat suitable area relation module further comprises a flow and habitat suitable area relation solving unit,
the flow and habitat suitable area relation solving unit utilizes a formula:
calculating and researching a weight value suitable habitat area WUA on a river reach, wherein Delta Ai is the area of the ith grid unit, the area of the grid unit is set according to the size of a grid in the habitat environment simulation model building unit, and CHSIi is a comprehensive suitability index corresponding to the ith grid unit;
the flow and habitat suitable area relation solving unit repeats the process for each simulated flow to obtain a corresponding weight suitable habitat area WUA, and constructs a relation curve Q-WUA of a target flow Q and the weight suitable habitat area WUA;
the flow and habitat suitable area relation solving unit acquires a flow duration curve Q-t, wherein the flow duration curve Q-t is daily average flow time sequence data; the flow and habitat suitable area relation solving unit finds a WUA value corresponding to each target flow Q on a Q-WUA curve through internal operation of curve interpolation according to the Q-WUA relation curve, converts daily average flow time sequence data into WUA time sequence data, and finally obtains a plant habitat suitable area duration curve WUA-t of a plant, wherein the WUA-t curve is WUA daily average time sequence data corresponding to daily average flow time sequence date.
5. The river food net based environmental current and habitat demand simulation model of claim 4, characterized by: the calculation of the composite suitability index value comprises the following steps:
the habitat suitability level space estimation module utilizes the formula:
CHSIi＝HSI1×b1+HIS2×b2+...+HISn×bn
calculating a comprehensive suitability index CHSIi corresponding to the ith grid unit, wherein HIS1, a.... wherein HISn represents habitat suitability indexes corresponding to n environmental factors, and b1, a.... wherein bn represents the response weight of the target species to the n environmental factors; the weight value determination method comprises the following steps:
bj represents the response weight of the target species to the j-th environmental factor, Rj represents the correlation coefficient of the target species and the j-th environmental factor, and j is {1, 2.
6. The river food net based environmental current and habitat demand simulation model of claim 5, characterized by: the potential resource quantity estimation module of the aquatic organisms comprises a vegetation resource quantity calculation unit, a benthonic animal resource quantity calculation unit, a phytoplankton resource quantity calculation unit and a zooplankton resource quantity calculation unit;
the vegetation resource amount calculation unit uses a formula:
calculating the wet plant resource quantity SH and the emergent aquatic plant resource quantity SE, wherein deltaSHk represents the difference between the areas of suitable habitats of adjacent months, BHk represents the biomass of a second february wet plant, SEk represents the intersection of the areas of 2-6 months of emergent aquatic plants, BEk represents the biomass of emergent aquatic plants in June, R is the ratio of plant leaves to the biomass of the whole plant, k represents month, and k is {1,2,....... multidot.12 };
the benthonic animal resource amount calculation unit utilizes a formula:
calculating the benthonic animal resource amount SB, Sk represents the area of a proper habitat in the kth month, B1 represents high proper biomass, the high proper biomass is the biomass when the flow speed of a research river section is less than or equal to a preset threshold value m1, B2 represents medium proper biomass, the medium proper biomass is the biomass when the flow speed of the research river section is greater than a preset threshold value m1 and less than or equal to a preset threshold value m2, HSI1 represents a high proper region proper index, and HSI2 represents a medium proper region proper index;
the phytoplankton resource amount calculation unit utilizes a formula:
Sp＝{0.66125×6.6×Copt×(1.7239×SD+0.1685)×Dirr×0.87)}×A×S×365×10 (-3)
calculating the phytoplankton production Sp in the whole research area, wherein Copt represents the chlorophyll concentration of the maximum carbon fixed rate depth, SD represents the transparency, Dirr represents the illumination period, A represents the calibration coefficient, and S represents the annual average water surface area;
and calculating the zooplankton resource amount Sz, wherein Pk represents the average water body surface area in the k th month, and B represents zooplankton biomass.
7. The river food net based environmental current and habitat demand simulation model of claim 6, characterized by: the potential resource amount estimation module of the aquatic organisms further comprises a fishery potential estimation unit;
the fishing potential estimation unit utilizes a formula according to the result of the vegetation resource amount calculation unit:
FH＝SH/80
FE＝SE/200
estimating fishery potential FH (free-standing) provided by a hygrophyte and fishery potential FE (free-standing) provided by an emergent aquatic plant;
the fishing potential estimation unit utilizes a formula according to the result of the benthonic animal resource amount calculation unit:
FB＝0.1×SB
estimating the fishing potential FB that the benthonic animals can provide;
the fishery potential estimation unit utilizes a formula according to the result of the phytoplankton resource amount calculation unit:
Fp＝0.0515×Sp
estimating the fishery potential Fp provided by phytoplankton;
the fishing potential estimation unit utilizes a formula according to the result of the zooplankton resource amount calculation unit:
Fz＝1.17×Sz
estimating the potential Fz of fishery provided by zooplankton.
8. The river food net based environmental current and habitat demand simulation model of claim 7, characterized by: the potential resource quantity estimation module of the aquatic organisms further comprises a finless porpoise resource quantity estimation unit;
the finless porpoise resource quantity estimation unit utilizes a formula:
T＝[(FH+FE+Fp+Fz+FB)×B×C×D]/(E×6％×365)
the number of potential finless porpoise sustainable in the study area, T, was estimated, where B represents the weight of fish with body length less than a preset length as a percentage of the total fish weight, C represents the percentage of fish with body length less than a preset length ingested by finless porpoise, D represents the conversion efficiency of finless porpoise into fish, E represents finless porpoise weight, 6% represents the average daily food intake of finless porpoise at about 6% of body weight, and 365 represents 365 days per year.
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