A method and system for determining a control target of a low water level of the Poyang Lake

Abstract

The present application provides a kind of Poyanghu low water level control target determination method and system, the method includes the following steps: step 1) field sampling and test analysis;Step 2) wetland vegetation water utilization mode determination;Step 3) the response of dominant vegetation to low water level change is researched, and the low water level control target for ensuring the safety of wetland vegetation ecosystem on the shoal is proposed.The present application considers the response of shoal wetland vegetation growth condition to water level change, and enriches the ecological water level research of large river-connected lake.

Description

Technical Field

[0001] This invention relates to the technical field of environmental protection, and in particular to a method and system for determining low water level control targets in Poyang Lake. Background Technology

[0002] Wetlands are among the most biodiverse ecological landscapes in nature, playing a vital role in the survival and development of organisms. As my country's largest freshwater lake, Poyang Lake's unique hydrological characteristics—resembling a lake at high water levels and a river at low water levels—provide favorable conditions for vegetation growth and a good habitat for rare wild animals, making it one of the internationally important wetlands. In recent years, extreme drought events have occurred frequently in the Poyang Lake area, especially since 2003. The shortened wet season, earlier and longer dry season, and lower water levels pose a significant threat to the dynamic stability of the Poyang Lake wetland ecosystem's structure and function. For example, during the dry season, vegetation cover in the Poyang Lake area drops by 15.9 km². 2 The trend is towards the center of the lake, with the degree of landscape fragmentation gradually decreasing and the landscape shape transforming from complex to simple. As an important component of the Poyang Lake wetland, the islands and shoals provide a favorable breeding and survival environment for wildlife. However, affected by extreme water conditions, the vegetation area of ​​the islands and shoals, especially the area of ​​tall grass islands, has decreased in recent years from 288.31 km² in 1997. 2 Decreased to 155.36 km in 2013. 2 The vegetation area is decreasing, threatening vegetation biodiversity and wildlife habitat. To ensure the healthy development of Poyang Lake wetlands and curb the reduction of vegetation area on sandbars and the trend of vegetation expansion into the lake center, it is urgent to study the low water level control targets for maintaining the health of the vegetation ecosystem of Poyang Lake sandbar wetlands.

[0003] Water level is a measure of changes in the water storage capacity of a lake. For lake ecosystems, there exists an ecological water level range within which vegetation in lake wetlands can survive and succeed normally, and the structure and function of the ecosystem can be maintained. In recent years, scholars both domestically and internationally have conducted extensive research on determining the ecological water level of lake wetlands. This research mainly focuses on determining the ecological water level with the goal of obtaining and restoring the hydrological conditions before wetland destruction, determining the ecological water level by comprehensively considering the correlation between wetland ecological functions and water level, and determining the ecological water level by calculating the amount of water required to meet specific ecological environmental functions of wetlands. However, there is little research on the ecological water level of lakes considering the vegetation ecosystem of sandbar wetlands. Changes in the pattern of lake water level fluctuations can affect the rate of decomposition and degradation of soil organic matter in sandbar wetlands, alter soil physicochemical properties, and further affect the absorption of plant nutrients and the activity of photosynthetic enzymes, thus impacting the health of sandbar vegetation ecosystems. In the event of frequent extreme low water levels, if the process of lake water level regulation only considers the ecological water level that ensures the health of the aquatic ecosystem while ignoring the water level requirements of sandbar wetland vegetation, the structure and function of the Poyang Lake sandbar wetland vegetation ecosystem may be further degraded.

[0004] Therefore, studying the response of Poyang Lake's sandbar wetland vegetation to low water level changes and determining low water level control targets that consider the health of the sandbar wetland vegetation ecosystem are important measures to ensure the health of the lake ecosystem. Currently, the response relationship between Poyang Lake's sandbar wetland vegetation and water level has been extensively studied, mainly through field monitoring and remote sensing interpretation to establish correlations between water level and biomass, and between soil moisture and vegetation species and root distribution characteristics. However, there is a lack of systematic research on the process by which river (lake) water affects vegetation growth through groundwater and soil water, making the research results somewhat random due to limitations in observation conditions. In contrast, by coupling groundwater and soil water movement models with physical mechanisms, and considering the influence of the soil environment (soil moisture and nutrients, etc.) on vegetation growth, the relationship between river (lake) water level and vegetation growth characteristics (such as biomass) can be indirectly established. This can accurately describe the growth status of sandbar wetland vegetation and its response to water level changes under any water level conditions.

[0005] Against this backdrop, this application takes typical sandbar wetlands of Poyang Lake as the research object, identifies the water absorption depth of vegetation roots, constructs an eco-hydrological model of typical sandbar wetlands, analyzes the impact of low water level changes on sandbar wetland vegetation, and determines the low water level control target of the lake considering the health of the sandbar wetland vegetation ecosystem, which is of great significance for guiding the water level regulation of Poyang Lake. Summary of the Invention

[0006] To address the technical problems existing in the prior art, this invention provides a method and system for determining the low water level control target of Poyang Lake. Taking the vegetation on the riverbanks as the research object, it proposes a lower limit value of the water level range suitable for vegetation growth, providing technical support for the comprehensive determination of the ecological water level of Poyang Lake.

[0007] According to a first aspect of the present invention, the present invention provides a method for determining a low water level control target in Poyang Lake, comprising the following steps: Based on the topography and vegetation distribution characteristics of the sandbar wetlands, field sampling sections and sampling points were set up. Using hydrogen and oxygen as analytical elements, a root water absorption depth determination model was adopted to analyze the proportion of soil water at different depths in the stem water of vegetation, study the vegetation water use patterns at different times, and determine the root water absorption depth at different times. An eco-hydrological model of the sandbar wetland was constructed, the model parameters were assigned and calibrated, and the model was validated. By interpreting historical remote sensing images and combining them with historical field biomass monitoring data, a dominant vegetation biomass data sequence was established as an evaluation standard for vegetation growth status. Based on long-term hydrological data, this study analyzes the impact of different low water levels on groundwater and soil water in sandbar wetlands, as well as the water stress on vegetation growth, and proposes low water level control targets to ensure the safety of the vegetation ecosystem in sandbar wetlands.

[0008] Based on the above technical solution, the present invention can also be improved as follows.

[0009] Optionally, the field sampling includes soil sample collection and vegetation sample collection.

[0010] Optionally, the field sampling includes extracting plant stem water and soil water using a plant water and soil water vacuum extraction device; sealing the extracted water samples in bottles; and testing and analyzing the hydrogen and oxygen isotope composition of each water sample, including δD and δ¹². 18 O provides analytical data for determining water use patterns in wetland vegetation.

[0011] Optionally, the analysis of the proportion of soil water at different depths in the stem water of vegetation, the study of vegetation water use patterns at different stages, and the determination of root water absorption depth at different stages include: By analyzing the main contributions of soil water at different depths to stem water in vegetation, i.e. water use patterns, the maximum depth at which vegetation roots absorb water is identified; among them, a root water absorption depth determination model is used to identify vegetation water use patterns.

[0012] Optionally, the wetland eco-hydrological model includes a precipitation interception module, an evapotranspiration module, a model vegetation growth module, a soil water movement module, and a groundwater movement module. Its features are as follows: The eco-hydrological model of the sandbar wetland takes soil as its core and forms a continuous model of river water-groundwater-soil-vegetation-atmosphere in the sandbar wetland. The precipitation interception module describes the amount of precipitation that is intercepted by leaves and enters the topsoil after rainfall (source term); the evapotranspiration module describes the soil moisture loss at different depths due to evaporation and transpiration (sink term); the vegetation growth module describes the amount of soil moisture loss at different depths due to water absorption by vegetation roots (sink term); and the groundwater movement module describes the amount of soil moisture loss or increase during soil recharge of groundwater or groundwater recharge of soil water (sink / source term). Driven by these source and sink terms, the soil water movement module can describe the changes in soil moisture at different soil depths. In addition to its recharge relationship with soil water, the groundwater operation module can also describe the amount of groundwater loss or increase during the process of groundwater recharged by river water or vice versa. Considering both the recharge relationship with soil water and river water, the groundwater operation module can describe the groundwater level under different river water level conditions and its impact on soil water. Soil is the carrier of vegetation growth, and soil moisture conditions affect vegetation growth. The vegetation growth module can describe the changes in vegetation biomass under different humidity and atmospheric conditions. Vegetation growth status can also directly affect the soil water transport module and indirectly affect the groundwater movement module by influencing rainfall interception and root water uptake rate, thereby affecting soil water sinks.

[0013] Optionally, the assignment and calibration of model parameters includes assigning and calibrating model parameters based on monitoring data of groundwater depth, soil environment and vegetation growth variables, as well as the interpretation results of historical remote sensing images.

[0014] Optionally, establishing dominant vegetation biomass data sequences as evaluation criteria for vegetation growth status includes: Using dominant vegetation communities as the analysis object, and combining historical remote sensing image interpretation results with field biomass monitoring data, the extreme water level during the dry season was used as the baseline water level. The design water level was calculated by decreasing the design water level per unit area. X Compare with the upper limit of the biomass evaluation standard X 上 and lower limit value X 下 The relative deviation between the predicted values ​​and the evaluation criteria was calculated, and the safety level of the wetland vegetation ecosystem structure at each site was classified as "unsafe", "sensitive" and "safe".

[0015] Optional criteria for determining "insecure," "sensitive," and "secure" are as follows: when X <1.3 X下 -0.3 X 上 or X >1.3 X 上 -0.3 X 下 At that time, the structure of the vegetation ecosystem was in an unsafe state; When 1.3 X 下 -0.3 X 上 ≤ X ≤0.7 X 下 +0.3 X 上 Or 0.7 X 上 +0.3 X 下 ≤ X ≤1.3 X 上 -0.3 X 下 At that time, the structure of the vegetation ecosystem is in a sensitive state; When 0.7 X 下 +0.3 X 上 < X <0.7 X 上 +0.3 X 下 At that time, the vegetation ecosystem structure was in a safe state.

[0016] Optionally, the criteria for determining low water level are as follows: taking the river / lake shoreline as the starting point and the first sampling point as the ending point, the range between the two points is the control distance of the first sampling point; taking the first sampling point as the starting point and the second sampling point as the ending point, the range between the two points is the control distance of the second sampling point; and so on. When the sensitive or unsafe distance of the sampling section is close to 20% of the section length, the design water level is determined to be the control low water level.

[0017] According to a second aspect of the present invention, a low water level control target determination system for Poyang Lake is provided, used in the aforementioned method for determining a low water level control target for Poyang Lake, comprising: Sampling units are used to set up field sampling sections and sampling points based on the topography and vegetation distribution characteristics of the beach wetlands; The vegetation water use pattern determination unit is used to analyze the proportion of soil water at different depths in the stem water of vegetation by using hydrogen and oxygen as analytical elements and a root water absorption depth determination model. It studies the vegetation water use pattern at different times and determines the root water absorption depth at different times. The low water level control unit is used to construct an eco-hydrological model of the sandbar wetland, assign and calibrate the model parameters, and validate the model. By interpreting historical remote sensing images and combining them with historical field biomass monitoring data, a dominant vegetation biomass data sequence is established as an evaluation standard for vegetation growth. Combining long-term hydrological data, the impact of different low water levels on groundwater and soil water in the sandbar wetland and the water stress on vegetation growth are analyzed, and low water level control targets to ensure the safety of the sandbar wetland vegetation ecosystem are proposed.

[0018] The technical effects and advantages of this invention are as follows: This invention provides a method and system for determining low water level control targets in Poyang Lake. Based on research on the water use patterns of vegetation in sandbar wetlands, it determines the root absorption depth of vegetation, providing accurate parameters for key modules of vegetation growth and soil water movement in the eco-hydrological model of sandbar wetlands, and constructing a reasonable eco-hydrological model of sandbar wetlands. It analyzes the impact of low water level changes on sandbar wetland vegetation and proposes a new direction for determining the ecological water level of large lakes, considering the health of the sandbar wetland vegetation ecosystem. This invention enriches the research on ecological water levels of large lakes connected to the Yangtze River and provides technical support for determining the ecological water level of Poyang Lake.

[0019] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures pointed out in the description, claims and drawings. Attached Figure Description

[0020] Figure 1 This is a flowchart of the method for determining the low water level control target of Poyang Lake provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of a typical beach wetland eco-hydrological process provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of a typical beach wetland eco-hydrological model module provided in an embodiment of the present invention; Figure 4 This is a map showing the humidity and sampling point distribution of typical sandbars in Poyang Lake, provided in an embodiment of the present invention. Figure 5 This is a schematic diagram of the sampling and calculation cross-section provided in an embodiment of the present invention; Figure 6 This invention provides soil moisture content at different depths in sandbar wetlands at different times during various periods, as provided in the embodiments of the present invention. Figure 7 This is a simulation diagram of the daily variation process of soil moisture at different depths in a typical sandbar wetland provided in an embodiment of the present invention; Figure 8This is a simulation diagram of the daily variation process of vegetation primary productivity in a typical cross-section from 2015 to 2016, provided in an embodiment of the present invention. Figure 9 This is a cross-sectional diagram showing the average biomass variation of sedge during the dry season over the years, provided in an embodiment of the present invention. Figure 10 This is the lowest water level value of the Wucheng water level station of Poyang Lake from 1953 to 2013 provided in the embodiments of the present invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0022] Water level is a measure of changes in the water storage capacity of a lake. For lake ecosystems, there exists an ecological water level range within which vegetation in lake wetlands can survive and succeed normally, and the structure and function of the ecosystem can be maintained. In recent years, scholars both domestically and internationally have conducted extensive research on determining the ecological water level of lake wetlands. This research mainly focuses on determining the ecological water level with the goal of obtaining and restoring the hydrological conditions before wetland destruction, determining the ecological water level by comprehensively considering the correlation between wetland ecological functions and water level, and determining the ecological water level by calculating the amount of water required to meet specific ecological environmental functions of wetlands. However, there is little research on the ecological water level of lakes considering the vegetation ecosystem of sandbar wetlands. Changes in lake water level fluctuations affect the rate of organic matter decomposition and degradation in wetland soils, alter soil physicochemical properties, and further influence plant nutrient absorption and the activity of photosynthetic enzymes, thus impacting the health of wetland vegetation ecosystems. In cases of frequent extreme low water levels, if lake water level regulation only considers ecological water levels necessary for the health of aquatic ecosystems while neglecting the water level requirements of wetland vegetation, the structure and function of the wetland vegetation ecosystem may further degrade. Against this backdrop, this invention focuses on lake wetlands, identifies the root absorption depth of vegetation, constructs an eco-hydrological model of wetlands, analyzes the impact of low water level changes on wetland vegetation, and determines low water level control targets for lakes that consider the health of the wetland vegetation ecosystem. This is of great significance for guiding water level regulation of large lakes connected to rivers.

[0023] This invention first establishes field sampling sections and sampling points based on the topography and vegetation distribution characteristics of the sandbar wetlands. Plant stems, soil, aboveground and belowground parts of the vegetation are collected in the field, and the δD and δ¹⁸O values ​​of each water sample are tested and analyzed. 18The study analyzed soil texture, bulk density, water content, and nitrogen content, as well as aboveground and belowground biomass of vegetation. Using hydrogen and oxygen as analytical elements, a root water absorption depth determination model was employed to analyze the proportion of soil water at different depths in vegetation stem water, investigate vegetation water use patterns at different times, and determine root water absorption depths at different periods. An eco-hydrological model of the sandbar wetland was constructed to calculate the dominant vegetation biomass driven by lake water levels and meteorological conditions. Through historical remote sensing image interpretation results combined with historical field biomass monitoring data, a dominant vegetation biomass data sequence was established as an evaluation standard for vegetation growth status. Combining long-term hydrological data, the study analyzed the impact of different low water levels on groundwater and soil water in the sandbar wetland, as well as the water stress experienced by vegetation growth, and proposed low water level control targets to ensure the safety of the sandbar wetland vegetation ecosystem.

[0024] Based on this, this invention proposes a method for determining the low water level control target of Poyang Lake, specifically as follows: Figure 1 As shown, the method includes the following steps: (1) Field sampling and testing analysis; Based on the topography and vegetation distribution characteristics of the sandbar wetlands, reasonable field sampling sections and sampling points were set up. In the above technical solution, field sampling includes soil sample collection and vegetation sample collection.

[0025] Soil samples were collected by drilling a 1-meter-long hollow cylindrical iron drill at each sampling point, dividing the soil column at 0.1-meter intervals, and collecting three soil samples from each soil layer. To determine soil texture, soil bulk density, and soil nitrogen content, sampling was conducted three times: after the soil samples used for soil water collection were collected, the remaining soil was divided into two parts, one for testing soil nitrogen content and the other for determining soil texture; soil samples at different depths near the vegetation sampling points were collected using a ring cutter method to test soil bulk density. Plant sampling was conducted within a 10m radius of the soil sampling point, forming a vegetation sampling area. Five 50cm x 50cm sampling plots were set up, and three healthy plants were selected within each plot. Three samples of each type of vegetation were collected evenly and repeatedly, dividing the vegetation samples into leaf and stem portions. Simultaneously, the plants were cut, and both the aboveground and underground parts were collected.

[0026] The field sampling specifically includes collecting vegetation stems, soil, and aboveground and belowground parts of vegetation. The specific steps are as follows: for soil water and plant stem water, a vacuum extraction device is used to extract plant stem water and soil water; the extracted water samples are bottled and sealed, awaiting determination of the δ-ray concentration in the water samples. 18 O and δD; Test and analyze δD and δ of each water sample 18O provides analytical data for determining water use patterns in wetland vegetation.

[0027] (2) Determination of wetland vegetation water use patterns; Using hydrogen and oxygen as analytical elements, a root water absorption depth determination model was adopted to analyze the proportion of water in the stem of vegetation at different depths, study the water use patterns of vegetation at different times, and determine the root water absorption depth at different times. In the above technical solution, by analyzing the main contributions of soil water and groundwater at different depths to stem water in vegetation, i.e., water use patterns, the maximum depth at which vegetation roots absorb water can be identified. The root water absorption depth determination model is a key tool for identifying vegetation water use patterns, and its principle is as follows. The proportion of different water sources varies in different growing seasons. A root water absorption depth determination model based on the conservation of hydrogen and oxygen isotope mass can identify the contribution ratio of soil water at different depths to plant growth in different seasons. The root water absorption depth determination model can be described as follows: (1) (2) (3) in, For source i Middle elements D Isotopic composition (‰); For source i Middle elements 18 O isotope composition (‰); and respectively vegetation stem water P elements in D and 18 O isotope composition (‰); f i For source i Water on plant stems P Contribution percentage (%) n Water for plant stems P The number of water sources.

[0028] Step (3) Study on the response of dominant vegetation to low water level changes; An eco-hydrological model of the sandbar wetland was constructed, the model parameters were assigned and calibrated, and the model was validated. By interpreting historical remote sensing images and combining them with historical field biomass monitoring data, a dominant vegetation biomass data sequence was established as an evaluation standard for vegetation growth status. Based on long-term hydrological data, this study analyzes the impact of different low water levels on groundwater and soil water in sandbar wetlands, as well as the water stress on vegetation growth, and proposes low water level control targets to ensure the safety of the vegetation ecosystem in sandbar wetlands.

[0029] In the above technical solution, the wetland eco-hydrological model includes a precipitation interception module, an evapotranspiration module, a model vegetation growth module, a soil water movement module, and a groundwater movement module. The model principle is detailed in the appendix. Figures 2-3 The eco-hydrological model of sandbar wetlands, centered on soil, forms a continuum model of river water-groundwater-soil-vegetation-atmosphere. The precipitation interception module describes the amount of precipitation intercepted by leaves and entering the topsoil (source term); the evapotranspiration module describes soil moisture loss at different depths due to evaporation and transpiration (sink term); the vegetation growth module describes soil moisture loss at different depths due to root absorption (sink term); and the groundwater movement module describes soil moisture loss or increase during soil recharge of groundwater or groundwater recharge of soil water (sink / source term). Driven by these source and sink terms, the soil water movement module can describe changes in soil moisture at different depths.

[0030] In addition to its recharge relationship with soil water, the groundwater operation module can also describe the amount of groundwater loss or increase during the process of groundwater recharge by river water or river water recharge groundwater. Considering both the recharge relationship with soil water and river water, the groundwater operation module can describe the groundwater level under different river water level conditions and its impact on soil water.

[0031] Soil is the carrier of vegetation growth, and soil moisture conditions affect vegetation growth. The vegetation growth module can describe the changes in vegetation biomass under different humidity and atmospheric conditions. Vegetation growth status can also directly affect the soil water transport module and indirectly affect the groundwater movement module by influencing rainfall interception and root water uptake rate, thereby affecting soil water sinks.

[0032] The eco-hydrological model of the sandbar wetland takes soil as its core and forms a continuous model of river water-groundwater-soil-vegetation-atmosphere in the sandbar wetland.

[0033] The precipitation interception module describes the amount of precipitation that is intercepted by leaves and enters the topsoil after rainfall (source term); the evapotranspiration module describes the soil moisture loss at different depths due to evaporation and transpiration (sink term); the vegetation growth module describes the amount of soil moisture loss at different depths due to water absorption by vegetation roots (sink term); and the groundwater movement module describes the amount of soil moisture loss or increase during soil recharge of groundwater or groundwater recharge of soil water (sink / source term). Driven by these source and sink terms, the soil water movement module can describe the changes in soil moisture at different soil depths.

[0034] In addition to its recharge relationship with soil water, the groundwater operation module can also describe the amount of groundwater loss or increase during the process of groundwater recharge by river water or river water recharge groundwater. Considering both the recharge relationship with soil water and river water, the groundwater operation module can describe the groundwater level under different river water level conditions and its impact on soil water.

[0035] Soil is the carrier of vegetation growth, and soil moisture conditions affect vegetation growth. The vegetation growth module can describe the changes in vegetation biomass under different humidity and atmospheric conditions. Vegetation growth status can also directly affect the soil water transport module and indirectly affect the groundwater movement module by influencing rainfall interception and root water uptake rate, thereby affecting soil water sinks.

[0036] Root water absorption depth directly affects soil water movement, indirectly influencing evapotranspiration, groundwater movement, and vegetation growth. The principles of root water absorption and soil water movement are as follows: Vegetation primarily absorbs water from the soil through its roots to meet its growth, metabolic activities, and leaf transpiration needs. Assuming root water absorption... S ( z , t ) is evaporation E c ( t and effective root distribution Le ( z , t The function is used to constrain root water uptake by adding soil water constraints: (4) (5) (6) in, f (θ) is the soil water constraint coefficient; θ Soil moisture content, % θ w The soil moisture content during wilting is %; θ fc This represents the soil moisture content in the field, in percentages.

[0037] Soil water movement is not only a crucial part of the water cycle, but also plays a key role in vegetation transpiration, soil water evaporation, vegetation growth, and the biogeochemical cycles of ecosystems. The Richards equation for soil water movement is as follows: (7) in, θ Soil moisture content, % K ( θ () represents soil hydraulic conductivity, in m / d; D(θ) is the soil hydraulic diffusion coefficient, m 2 / d; SE The loss term includes water absorption by vegetation roots and water evaporation from the soil, 1 / d. The soil hydraulic property curves primarily use the Clapp-Homberger model, as detailed below: (8) (9) (10) (11) (12) (13) (14) in, θ s The saturated soil moisture content is %; K s Soil saturation hydraulic conductivity, m / d; ψ s Let m be the saturated matrix potential. a Let m be the saturated matrix potential parameter. b These are parameters related to soil properties; w ( sand )and w ( clay The numbers () represent the mass fractions of sand and clay particles in the soil, respectively.

[0038] The upper boundary condition is: (15) In the formula, R The net rainfall reaching the surface after deducting losses is expressed in m / d. S For water absorption by plant roots, 1 / day; E s The value represents soil water evaporation, measured in m / d. Compared to the upper boundary, the lower boundary shows a temporal variation with changes in the groundwater level. Nevertheless, it is assumed that the soil moisture content near the groundwater level is equivalent to the soil field capacity. θ fc Then the lower boundary condition is: (16) in, Z WT The water level is in meters (m).

[0039] Assigning and calibrating model parameters involves assigning and calibrating model parameters based on monitoring data of groundwater depth, soil environment and vegetation growth variables, as well as the interpretation results of historical remote sensing images.

[0040] The establishment of dominant vegetation biomass data sequences as a standard for evaluating vegetation growth status includes: Using dominant vegetation communities as the analysis object, and combining historical remote sensing image interpretation results with field biomass monitoring data, a vegetation biomass series was established for each sampling point during the dry season. The biomass values ​​with a P=10% guarantee rate and a P=90% guarantee rate were calculated as the upper limit value X of the evaluation standard. 上 and lower limit value X 下 .

[0041] Specifically, the extreme water level during the dry season was used as the baseline water level, and the design water level was decreased by 0.1m from the baseline water level. The biomass of dominant vegetation at different stations was calculated at the design water level. X Compare the upper and lower limits of the biomass evaluation criteria. X 上 and X 下 The relative deviation between the predicted values ​​and the evaluation criteria was calculated, and the safety level of the wetland vegetation ecosystem structure at each site was divided into three levels: "unsafe," "sensitive," and "safe," as detailed below: Safety: The vegetation community structure on the sandbar is stable, and the ecosystem functions normally. Sensitive: The vegetation community structure of the sandbar is in a critical state; if the water level drops further, the vegetation community structure of the sandbar will change. Unsafe: The vegetation on the sandbar is in an unstable state, and the community structure is evolving in a new direction.

[0042] The criteria for distinguishing between "insecure," "sensitive," and "secure" are as follows: when X <1.3 X 下 -0.3 X 上 or X >1.3 X 上 -0.3 X 下 At that time, the structure of the vegetation ecosystem was in an unsafe state; When 1.3 X 下 -0.3 X 上 ≤ X ≤0.7 X 下 +0.3 X 上 Or 0.7 X 上 +0.3 X下 ≤ X ≤1.3 X 上 -0.3 X 下 At that time, the structure of the vegetation ecosystem is in a sensitive state; When 0.7 X 下 +0.3 X 上 < X <0.7 X 上 +0.3 X 下 At that time, the vegetation ecosystem structure was in a safe state.

[0043] The analysis of the impact of different low water levels on groundwater and soil water in the sandbar wetlands, as well as the water stress experienced by vegetation growth, includes: The impact of low water levels on groundwater and soil water in sandbar wetlands is as follows: during periods of low water levels, there is less precipitation in wetlands, and the main source of soil water and groundwater replenishment is river water. Long-term low river water levels will lead to a continuous decrease in groundwater levels and a continuous reduction in soil water content.

[0044] The water stress on vegetation growth caused by low water levels is as follows: the soil moisture content in wetlands is higher during periods of low water levels than during periods of high water levels, especially when river water levels are low for a long period of time. The topsoil, which is far from groundwater, will be in a state of water shortage, while most of the plant roots are in the topsoil. Long-term low water levels will affect the plants' ability to absorb water for photosynthesis and normal growth, resulting in plant death.

[0045] The criteria for determining low water levels are as follows: Starting from the river (lake) shoreline and ending at the first sampling point, the distance between these two points is the control distance for the first sampling point; starting from the first sampling point and ending at the second sampling point, the distance between these two points is the control distance for the second sampling point; and so on. When the sensitive or unsafe distance of the sampling section approaches 20% of the section length, the design water level is determined to be a low control water level.

[0046] Ultimately, a low water level control target was proposed to ensure the safety of the wetland vegetation ecosystem.

[0047] In summary, the steps of this invention are interconnected and can accurately reflect the impact of lake water level changes on the eco-hydrological processes of sandbar wetlands, thereby determining the target for low lake water level control.

[0048] Example The present invention will now be described using the example of determining the low water level control target of Poyang Lake. It also has guiding significance for determining the low water level control target of other large lakes connected to rivers with sandbar wetlands.

[0049] With the changes in elevation and water level of the sandbars in Poyang Lake, the ecological types of vegetation from the shore to the center of the lake (main lake and sub-lakes) show a regular ring-shaped change. The dominant vegetation communities are mainly: reeds + bulrushes - bermudagrass - sedge - artemisia - sedge - chrysanthemum-leaf potentilla community and sedge community.

[0050] (1) Sampling section setting Based on the seasonal alternation of sandbar appearances with wetland water levels and the distribution characteristics of dominant vegetation communities, and considering the influence of soil environment and vegetation type on vegetation water use patterns, cross sections were selected. S As the main research area, specifically such as Figures 4-5 As shown.

[0051] Section S The soil texture is similar across the various regions, but the vegetation type gradually changes from C4 plants such as *Imperata cylindrica* and *Cynodon dactylon* to C3 plants such as *Carex spp.*, *Artemisia argyi*, and *Gnaphalium affine*, based on the vegetation community distribution along the cross-section. Sampling points were set approximately every 150 m along the study cross-section. S A total of 6 sampling points were set up. The elevation and vegetation community information of each sampling point are shown in Table 1.

[0052] Table 1. Elevation and vegetation community information of sampling points

[0053] (2) Sample collection and testing 1) Sampling method ① Soil samples Section S The root system depth of the dominant vegetation ranges from 0.1 to 0.4 m. To comprehensively understand the contribution ratio of soil water at different depths to the vegetation's water source, a soil sampling depth of 1 m was set. At each sampling point, a 1 m long cylindrical hollow iron drill was used to drill a soil column, which was divided into sections at 0.1 m intervals. Three soil samples were collected from each soil layer.

[0054] To determine soil texture and bulk density, sampling was conducted twice: after the soil samples used for soil water collection were collected, the remaining soil was used to determine soil texture; soil samples at different depths near the vegetation sampling points were collected using the ring sampler method to test soil bulk density. Soil texture and bulk density samples were collected annually.

[0055] ② Plant samples Using the soil sampling point as the center, a 10m radius area was selected as the vegetation sampling area. A 50cm × 50cm sampling plot was set up, and three healthy plants were selected within each plot. Three samples of each type of vegetation were collected evenly and repeatedly, dividing the vegetation samples into leaf and stem portions. Simultaneously, the vegetation samples were cut, and both the aboveground and underground parts were collected.

[0056] 2) Sample testing ① Stable isotopic composition For soil water and plant stem water, a plant-soil moisture vacuum extraction device was used to extract water from the soil and plant stems. The extracted water samples were bottled and sealed, awaiting determination of the δ-ray concentration in the water samples. 18 O and δD.

[0057] Taking the MAT253 isotope ratio mass spectrometer connected to the Flash EA / HT as an example, the sample δ 18 O and δD were tested using this equipment. δ 18 The results of O and δD measurements were used in VSMOW (δ 18 O=0‰, δD=0‰) represent the per mille difference of the reference standard, with test accuracies of 0.2‰ and 2‰ respectively. The above measurement results δ R (‰) can be expressed as: (17) In the formula: R sample It indicates the relative abundance of a certain element's isotopes in a sample. R std This indicates the relative abundance of a certain element's heavy isotope in a standard substance. If δ... R A larger value of (‰) indicates that the sample is enriched with heavy isotopes; conversely, a smaller value indicates that the sample is enriched with light isotopes.

[0058] ② Meteorological and hydrological observation The official website of the Jiangxi Provincial Department of Water Resources updates river water levels and precipitation in the Poyang Lake basin hourly in real time. This invention primarily extracts the water levels at Yongxiu station at 8:00 AM and 8:00 PM on a given day, calculating their average as the daily average water level; it also records the total rainfall at Yongxiu station from 8:00 PM the previous day to 8:00 PM on the current day, as the daily rainfall. The groundwater depth in the riverbanks is manually observed using water gauges during each field sampling process.

[0059] ③ Soil environmental variables A. Soil texture Soil texture was determined using the Eye-Tech laser particle size analyzer from Ankersmid, Netherlands. Based on soil sample test results from October 2015 and April 2016, the vertical differences in soil texture were small at each sampling point, with silt content ranging from 93% to 98%, indicating that silt was the dominant soil type.

[0060] Table 2 Soil texture at each sampling point of the cross section

[0061] B. Soil bulk density Soil samples collected using the ring cutter method were dried in an oven at 105℃ to constant weight, and the bulk density of soil in different soil layers was calculated.

[0062] Table 3 Soil bulk density at each sampling point of the cross section

[0063] C. Soil moisture content Before performing the soil water vacuum extraction process, the mass of the soil sample was measured. After the extraction process was completed, the soil sample was weighed again to obtain the dry soil mass, and the soil (mass) water content was calculated. Figure 6 The data shows the soil moisture content at different depths in the sandbar wetlands at different times.

[0064] ④ Aboveground and underground biomass of vegetation The collected above-ground and underground parts of the vegetation were dried in an 80°C oven until constant weight, and then weighed.

[0065] Table 4. Aboveground and underground biomass of sedge from September to December

[0066] (2) Determination of wetland vegetation water use patterns According to the calculation results, the root water absorption depth of vegetation in the study area during the two growing seasons of February to May and September to December is 30 cm and 50 cm, respectively, which can be used as important parameters for the eco-hydrological model of typical sandbar wetlands.

[0067] Table 5. Water absorption depth of sedge roots

[0068] 3) Research on the response of dominant vegetation to low water level changes ①Establishment of a typical beach wetland eco-hydrological model Figure 7 This is a simulation of the average daily soil moisture change process during the calculation period of 2015-2016. As can be seen from the figure, the daily change process of soil moisture at 10 cm is more drastic than that at 20 cm, 30 cm, 40 cm and 50 cm. This is mainly because the root depth of wetland vegetation is between 0 and 40 cm, with the majority between 0 and 10 cm. Near-soil meteorological conditions and root water absorption have a greater impact on soil moisture at 0-10 cm.

[0069] Figure 8 This demonstrates the diurnal variation of vegetation primary productivity. Calculations show that the mature sedge biomass at the cross-section reaches 969.61 C / m². 2 The results are close to those in Table 4, indicating that the model principle and parameters can reflect the vegetation growth characteristics of typical sandbar wetlands.

[0070] ② Establishment of biomass standards For reference Figure 9 As shown, based on the annual dry season biomass monitoring results of the sampling section from 2001 to 2020, the biomass values ​​under the average conditions of P=10% guarantee rate and P=90% guarantee rate were statistically obtained as 1194.9 g / m³. 2 and 699.4g / m 2 At each sampling point, the biomass with a P=10% guarantee rate ranged from 779 to 1459 g / m³. 2 With a P=90% guarantee rate, biomass ranges from 454 to 854 g / m³. 2 .

[0071] Table 6. Carex biomass at different sampling points from September to December under different guarantee rates.

[0072] ③ Determination of basic water level value For reference Figure 10 As shown, based on the long-term daily water level monitoring results of the Wucheng water level station of Poyang Lake from 1953 to 2013, and considering the impact of hydrological variations on the water level process and related scientific research results, the lowest water level value of 11.1m in 2002 (Wusong elevation, the same below) was taken as the base water level.

[0073] ④ Simulation of sedge biomass under different low water levels and evaluation of the structural safety level of wetland vegetation ecosystem Based on the baseline water level, different design water levels were determined in increments of 0.1m, and the dominant vegetation biomass at different stations was calculated at the design water level. X .

[0074] Table 7. Moss biomass at various sampling points during the dry season under different design water levels.

[0075] According to the calculation results, when the water level of a typical sandbar wetland is greater than 8.0m during the dry season, the safe control distance for the structure of the sandbar wetland vegetation ecosystem is greater than 80%; when the wetland water level is 7.9m, the sensitive or unsafe control distance for the structure of the sandbar wetland vegetation ecosystem is greater than 20%. Based on the above criteria, 8.0m is the low control water level for the sandbar wetland where the calculation section is located.

[0076] This embodiment uses the low water level control target determination system of Poyang Lake described in this invention to analyze the low water level control target of typical sandbar wetlands in Poyang Lake. While enriching the research on ecological water level of large lakes connected to the Yangtze River, it can provide technical support for the determination of ecological water level in Poyang Lake.

[0077] The following describes the Poyang Lake low water level control target determination system provided by the present invention. The Poyang Lake low water level control target determination system described below can be referred to in correspondence with the Poyang Lake low water level control target determination method described above.

[0078] Additionally, embodiments of the present invention also provide a low water level control target determination system for Poyang Lake, used in the aforementioned method for determining a low water level control target for Poyang Lake, comprising: Sampling units are used to set up field sampling sections and sampling points based on the topography and vegetation distribution characteristics of the beach wetlands; The vegetation water use pattern determination unit is used to analyze the proportion of soil water and groundwater at different depths in vegetation stem water using hydrogen and oxygen as analytical elements and an isotope mixing model, to study vegetation water use patterns at different times and determine the root water absorption depth at different times. The low water level control unit is used to construct an eco-hydrological model of the sandbar wetland, assign and calibrate the model parameters, and validate the model. By interpreting historical remote sensing images and combining them with historical field biomass monitoring data, a dominant vegetation biomass data sequence is established as an evaluation standard for vegetation growth. Combining long-term hydrological data, the impact of different low water levels on groundwater and soil water in the sandbar wetland and the water stress on vegetation growth are analyzed, and low water level control targets to ensure the safety of the sandbar wetland vegetation ecosystem are proposed.

[0079] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0080] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for determining low water level control targets in Poyang Lake, characterized in that, Includes the following steps: Based on the topography and vegetation distribution characteristics of the sandbar wetlands, field sampling sections and sampling points were set up. Using hydrogen and oxygen as analytical elements, a root water absorption depth determination model was adopted to analyze the proportion of soil water at different depths in the stem water of vegetation, study the vegetation water use patterns at different times, and determine the root water absorption depth at different times. An eco-hydrological model of the sandbar wetland was constructed, the model parameters were assigned and calibrated, and the model was validated. By interpreting historical remote sensing images and combining them with historical field biomass monitoring data, a dominant vegetation biomass data sequence was established as an evaluation standard for vegetation growth status. Based on long-term hydrological data, this study analyzes the impact of different low water levels on groundwater and soil water in sandbar wetlands, as well as the water stress on vegetation growth, and proposes low water level control targets to ensure the safety of the vegetation ecosystem in sandbar wetlands.

2. The method for determining the low water level control target of Poyang Lake according to claim 1, characterized in that, Field sampling includes soil sampling and vegetation sampling.

3. The method for determining the low water level control target of Poyang Lake according to claim 2, characterized in that, Field sampling included soil water and plant stem water. Vacuum extraction devices were used to extract plant stem water and soil water. The extracted water samples were bottled and sealed, and the hydrogen and oxygen isotope composition, including δD and δ¹², was analyzed in each sample. 18 The O component provides analytical data for determining wetland vegetation water use patterns.

4. The method for determining the low water level control target of Poyang Lake according to claim 1, characterized in that, The analysis examined the proportion of soil water at different depths in the stem water of vegetation, studied vegetation water use patterns at different stages, and determined the root water absorption depth at different stages, including: By analyzing the main contributions of soil water at different depths to stem water in vegetation, i.e. water use patterns, the maximum depth at which vegetation roots absorb water is identified; among them, a root water absorption depth determination model is used to identify vegetation water use patterns.

5. The method for determining the low water level control target of Poyang Lake according to claim 1, characterized in that, The eco-hydrological model of the shoal wetland includes a precipitation interception module, an evapotranspiration module, a vegetation growth module, a soil water movement module, and a groundwater movement module.

6. The method for determining the low water level control target of Poyang Lake according to claim 1, characterized in that, The process of assigning and calibrating model parameters includes assigning and calibrating model parameters based on monitoring data of groundwater depth, soil environment and vegetation growth variables, as well as the interpretation results of historical remote sensing images.

7. The method for determining the low water level control target of Poyang Lake according to claim 1, characterized in that, The establishment of dominant vegetation biomass data sequences as a standard for evaluating vegetation growth status includes: Using dominant vegetation communities as the analysis object, and combining historical remote sensing image interpretation results with field biomass monitoring data, the extreme water level during the dry season was used as the baseline water level. The design water level was calculated by decreasing the design water level per unit area. X Compare with the upper limit of the biomass evaluation standard X 上 and lower limit value X 下 The relative deviation between the predicted values ​​and the evaluation criteria was calculated, and the safety level of the wetland vegetation ecosystem structure at each site was classified as "unsafe", "sensitive" and "safe".

8. The method for determining the low water level control target of Poyang Lake according to claim 7, characterized in that, The criteria for determining "insecure," "sensitive," and "secure" are as follows: when X <1.3 X 下 -0.3 X 上 or X >1.3 X 上 -0.3 X 下 At that time, the structure of the vegetation ecosystem was in an unsafe state; When 1.3 X 下 -0.3 X 上 ≤ X ≤0.7 X 下 +0.3 X 上 Or 0.7 X 上 +0.3 X 下 ≤ X ≤1.3 X 上 -0.3 X 下 At that time, the structure of the vegetation ecosystem is in a sensitive state; When 0.7 X 下 +0.3 X 上 < X <0.7 X 上 +0.3 X 下 At that time, the vegetation ecosystem structure was in a safe state.

9. The method for determining the low water level control target of Poyang Lake according to claim 1, characterized in that, The criteria for determining low water levels are as follows: taking the river / lake shoreline as the starting point and the first sampling point as the ending point, the range between the two points is the control distance of the first sampling point; taking the first sampling point as the starting point and the second sampling point as the ending point, the range between the two points is the control distance of the second sampling point; and so on. When the sensitive or unsafe distance of the sampling section reaches 20% of the section length, the design water level is determined to be a low water level.

10. A system for determining low water level control targets in Poyang Lake, used in the method for determining low water level control targets in Poyang Lake as described in any one of claims 1-9, characterized in that, include: Sampling units are used to set up field sampling sections and sampling points based on the topography and vegetation distribution characteristics of the beach wetlands; The vegetation water use pattern determination unit is used to analyze the proportion of soil water at different depths in the stem water of vegetation by using hydrogen and oxygen as analytical elements and a root water absorption depth determination model. It studies the vegetation water use pattern at different times and determines the root water absorption depth at different times. The low water level control unit is used to construct an eco-hydrological model of the sandbar wetland, assign and calibrate the model parameters, and validate the model. By interpreting historical remote sensing images and combining them with historical field biomass monitoring data, a dominant vegetation biomass data sequence is established as an evaluation standard for vegetation growth. Combining long-term hydrological data, the impact of different low water levels on groundwater and soil water in the sandbar wetland and the water stress on vegetation growth are analyzed, and low water level control targets to ensure the safety of the sandbar wetland vegetation ecosystem are proposed.

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