CN-122022275-A - Reservoir ecological dispatching optimization method for drifting egg fish

CN122022275ACN 122022275 ACN122022275 ACN 122022275ACN-122022275-A

Abstract

The invention discloses a reservoir ecological dispatching optimization method for producing drifting oofish, which relates to the technical field of reservoir ecological dispatching and comprises the following steps: s1, constructing a dynamic coupling model which covers multidimensional ecological factors and spawning scales of water temperature layering state, flow velocity gradient distribution, dissolved oxygen dynamic change, water transparency and flow, establishing a specific mathematical equation which reflects dynamic association of factors and spawning scales, and determining cooperative association and interaction mechanisms of the factors and the spawning scales; according to the invention, the multi-dimensional ecological factor dynamic coupling model is constructed, the interaction among the factors is comprehensively considered, the limitation of traditional single factor scheduling is made up, multi-factor cooperative regulation and control is realized, the comprehensive sensing means of the ecological environment is perfected by means of a multi-parameter real-time monitoring network, the dynamic change of the ecological factors is accurately captured, reliable data support is provided for scheduling, the spawning ecological requirements of fishes are fully combined through a dynamic weight distribution mechanism, and the scheduling effect is accurately matched with the actual requirements of the fishes.

Inventors

DONG CHUN
YANG GUOSHENG
LI DEWANG
CHEN XIAOJUAN
YANG ZHI
ZHU QIGUANG
XU WEI
CAO JUN

Assignees

水利部中国科学院水工程生态研究所

Dates

Publication Date: 20260512
Application Date: 20260108

Claims (9)

1. The ecological dispatching optimization method for the reservoir of the drifting egg fish is characterized by comprising the following steps of: S1, constructing a dynamic coupling model which covers multidimensional ecological factors and spawning scales of water temperature layering state, flow velocity gradient distribution, dissolved oxygen dynamic change, water transparency and flow, establishing a specific mathematical equation which reflects dynamic association of factors and spawning scales, and determining cooperative association and interaction mechanisms of the factors and the spawning scales; s2, building a multi-parameter real-time monitoring network, deploying a distributed sensor array, combining a satellite remote sensing technology with unmanned aerial vehicle inspection, and synchronously acquiring key ecological parameters of a reservoir area and a downstream river channel and acquiring data; S3, collecting historical scheduling data, ecological environment monitoring data and fish reproduction monitoring results, training a prediction model based on the data, and establishing an ecological response prediction mechanism; S4, adjusting the regulation weight of each ecological factor by referring to the spawning period ecological requirements of the drifting egg-producing fishes; S5, tracking the spawning state and ecological environment change of the fish according to the real-time monitoring data and the model prediction result, and adjusting reservoir dispatching parameters.
2. The reservoir ecological scheduling optimization method for the drift-producing oofish according to claim 1, wherein when a multidimensional ecological factor dynamic coupling model is constructed in the step S1, research documents of related fields are combed, in-situ investigation of at least one complete spawning period is carried out, influence thresholds and action rules of water temperature stratification, flow velocity gradient, dissolved oxygen dynamic change, water transparency and flow on spawning of the drift-producing oofish are clarified, the correlation strength of each ecological factor and spawning scale is identified by adopting Pearson correlation analysis and gray correlation analysis, the comprehensive influence degree of interaction among the factors on the spawning process is quantified by combining the coupling cooperative scheduling model, and a specific mathematical equation for reflecting dynamic correlation of the factors and spawning scale is established: wherein For the predicted value of the spawning scale, Respectively water temperature layering characteristic value, flow velocity gradient, dissolved oxygen content, water transparency and flow rate, As the linear coefficient of each factor, Is a constant term which is used to determine the degree of freedom, For the interaction coefficient among factors, a coupling model system with adjustable parameters is formed, and for accurately quantifying the contribution degree of the synergism among the factors to spawning, a synergism intensity calculation formula is introduced into the coupling model: , wherein, Is the first Personal ecological factor(s) The strength of the synergistic effect of the individual ecological factors, Is that 、 The Pearson correlation coefficient of two factors, 、 Respectively the first First, second The basic weight of the individual ecological factors, Total number of ecological factors.
3. The reservoir ecological scheduling optimization method for the drifting egg fishes is characterized in that when a multi-parameter real-time monitoring network is built in the step S2, a distributed sensor array is deployed according to a principle of uniformly distributing key sections of a water inlet and a water outlet of a reservoir area and a downstream river spawning site and combining encryption of a key area, the sensors synchronously acquire water temperature, flow velocity, dissolved oxygen, turbidity, pH value and flow, data acquisition frequency is set according to dynamic change characteristics of different ecological factors, high-frequency fluctuation factors shorten acquisition intervals, stable factor extension intervals, satellite remote sensing technology acquires overall thermal distribution of a water body and macroscopic indicators of the water body area of the reservoir area, and an unmanned aerial vehicle patrols and captures local ecological environment changes of the downstream river, wherein the two are complementary with microscopic data acquired by the sensors.
4. The reservoir ecological scheduling optimization method for the drifting egg fishes according to claim 3, wherein the deployment of the distributed sensor array avoids areas where a channel, a flood discharge channel and a ship berthing area are prone to being interfered by people, the measuring range, the precision and the response speed of the sensor are adapted to the monitoring requirements of all ecological factors, the data transmission adopts LoRa, NB-IoT low-power consumption wireless communication technology and data encryption transmission protocol, the data are transmitted to a monitoring platform, a regular calibration and maintenance plan is formulated, the sensors are calibrated with accuracy once a month, comprehensive maintenance is carried out once a quarter, and fault equipment is replaced.
5. The reservoir ecological scheduling optimization method for producing drifting egg fishes according to claim 1, wherein when an ecological response prediction mechanism is established in the step S3, collected historical scheduling data, ecological environment monitoring data and fish propagation monitoring results are preprocessed, a training set and a verification set are divided according to a preset ratio of 7:3, a random forest algorithm is selected as a core prediction model, the number of decision trees, the maximum depth, the node splitting feature number and other network structures and parameters of the model are optimized through a grid search method, the prediction precision of the model is checked through the verification set data by adopting root mean square error and a decision coefficient, and the model initial output result is corrected for further improving the accuracy of a prediction index value, wherein a correction formula is as follows: , wherein, For the modified predictive index value, For the initial predicted value of the model, Is the first The correction coefficient of the individual ecological factors, Is the first The real-time monitoring value of each ecological factor, Is the first in the historical data The average value of the individual ecological factors is calculated, Is the first in the historical data Standard deviation of individual ecological factors.
6. The reservoir ecological dispatching optimization method for the drift-producing oofish according to claim 5, wherein the fish reproduction monitoring results comprise drift-producing oofish species composition, spawning starting time, spawning peak time, spawning area specific distribution range and spawning amount of each area, the data are obtained through combination of a plurality of means of fixed-point shooting by underwater camera equipment, standardized fixed-point monitoring and water body environment DNA investigation, the results of different monitoring means are cross-validated, and contradictory data are removed.
7. The reservoir ecological scheduling optimization method of the drift-producing oofish according to claim 1, wherein when the ecological factor regulation weights are adjusted in the step S4, specific starting and ending nodes of the drift-producing oofish spawning period are determined through underwater acoustic monitoring, fish marking tracking and spawning site on-site exploration, and for realizing scientific allocation of spawning period factor weights, specific weights are calculated based on basic weights and spawning period sensitivity coefficients, and the calculation formula is as follows: , wherein, Is the first Stage of reproduction The regulating weight of each ecological factor, Is the first The basic weight of the individual ecological factors, Is the first Stage of reproduction The sensitivity coefficient of the individual ecological factors, The total number of ecological factors is the total number of the ecological factors, the spawning period takes the flow and the water temperature as core regulating factors, the total weight ratio of the flow and the water temperature is not lower than 60 percent, and the total weight is higher than the regulating weight of the transparency of the water body, the dynamic change of dissolved oxygen and the flow rate.
8. The method for optimizing ecological reservoir scheduling of fish spawning in drift as set forth in claim 1, wherein the step S5 of adjusting reservoir scheduling parameters includes: The real-time monitoring data is transmitted to a data processing center through a wireless communication network, and after data cleaning and standardization processing, the real-time monitoring data is compared with the range of the proper ecological factors output by the multidimensional ecological factor dynamic coupling model one by one; When all the core ecological factor values are in the corresponding proper ranges and the cooperative strength among factors meets the spawning requirement, judging that the adjustment of the dispatching parameters is not needed, maintaining the current reservoir running state, and when one or more factors exceed the proper ranges, combining the regulation and control suggestions output by the ecological response prediction mechanism, simultaneously considering the conventional functional requirements of flood control, power generation and water supply of the reservoir, and determining the adjustment direction and the specific amplitude of the core dispatching parameters of the drainage flow, the drainage water temperature and the drainage period; after parameter adjustment, the ecological factor change and spawning response of the fishes in the corresponding area are monitored, and the adjustment result is fed back to form a closed loop flow of monitoring, comparison, regulation and control and feedback.
9. The reservoir ecological scheduling optimization method for producing drifting oofish according to claim 1, wherein the multidimensional ecological factor dynamic coupling model is provided with a periodic updating mechanism, and when a complete fish breeding period is completed, the influence weight and interaction strength of each ecological factor are reevaluated by combining the latest monitoring data, fish breeding response results and scheduling practice feedback in the period, the associated parameters and factor weight reference values in the model are adjusted, and when the ecological environment of a water area is changed significantly or the fish breeding characteristics are fluctuant obviously, a model updating flow is started.

Description

Reservoir ecological dispatching optimization method for drifting egg fish Technical Field The invention relates to the technical field of reservoir ecological dispatching, in particular to a reservoir ecological dispatching optimization method for floating egg fish. Background The fish spawn producing drifting is characterized in that the produced spawn is required to be kept in a suspension state in a water flow environment, embryo development is completed until a hatched fish population is carried by water flow, the fish spawn producing drifting has irreplaceable effects on maintaining biological diversity of a water area, stabilizing a food chain structure and promoting substance circulation and energy flow, and meanwhile, part of species have important economic value and scientific research value, so that the fish spawn producing drifting is an important indicator organism of ecological health conditions of the water area. The water storage operation of the reservoir brings great economic benefit, and simultaneously produces adverse effects on the aquatic ecosystem, the hydrologic situation is changed, and the reduction of spawning sites, the delay of spawning time and the like of the drifting egg fishes are caused. The reservoir ecological dispatching for the fish producing the drifting eggs is characterized in that on the basis of conventional dispatching of reservoirs, the propagation biological characteristics and ecological hydrologic requirements of the fish producing the drifting eggs are combined, key factors such as the water leakage flow rate and the water temperature of the reservoirs are scientifically regulated and controlled, a proper hydrologic ecological environment dispatching mode is created for spawning, fish egg drifting incubation and fish fry survival of the fish, the change of reservoir construction on the hydrologic situation of a natural river channel can be effectively relieved by the dispatching mode, the adverse effect of hydraulic engineering on propagation of the fish producing the drifting eggs is reduced, and the method has important practical significance and long-term value for protecting fish resources and maintaining ecological balance of a water area and realizing collaborative development of hydraulic engineering and ecological protection. However, in the prior art, a certain defect still exists, reservoir ecological dispatching focuses on the regulation and control of a single ecological factor, the interaction among multiple factors such as water temperature layering, flow velocity gradient, flow dynamics and the like cannot be comprehensively considered, the association relation between each factor and spawning scale is not precisely quantified, the influence of ecological factor change on fish spawning cannot be precisely predicted, a dynamic weight distribution strategy is not formulated for the key stage of fish spawning period, so that dispatching emphasis is not highlighted, the core ecological requirements cannot be preferentially met, and comprehensive perception means for the ecological environment of a reservoir area and a downstream river channel are not available, so that the dispatching effect is not matched with the actual spawning requirements of fish. Therefore, the development of the reservoir ecological dispatching optimization method for the drifting egg fish has important significance. Disclosure of Invention The invention aims to make up the defects of the prior art and provides a reservoir ecological dispatching optimization method for producing drifting oofish, which can comprehensively consider the interaction among multiple factors by constructing a multidimensional ecological factor dynamic coupling model, realize the multi-factor cooperative regulation and control, perfect the comprehensive sensing means of ecological environment by means of a multi-parameter real-time monitoring network, accurately capture the dynamic change of ecological factors, provide reliable data support for dispatching, fully combine the spawning ecological requirements of fish through a dynamic weight distribution mechanism, enable the dispatching effect to be accurately matched with the actual requirements of fish, and provide a natural propagation suitable living environment for the fish. The invention provides a reservoir ecological dispatching optimization method for producing drifting oofish, which aims to solve the technical problems and comprises the following steps: S1, constructing a dynamic coupling model which covers multidimensional ecological factors and spawning scales of water temperature layering state, flow velocity gradient distribution, dissolved oxygen dynamic change, water transparency and flow, establishing a specific mathematical equation which reflects dynamic association of factors and spawning scales, and determining cooperative association and interaction mechanisms of the factors and the spawning scales; s2, building a multi-paramete