Water resource recycling method based on ecological restoration coupling in desert area

Abstract

The invention discloses a desert region water resource recycling method based on ecological restoration coupling, and the method comprises the steps: building a moisture-vegetation coupled spatial dynamic model through obtaining soil humidity distribution, vegetation coverage and regional microclimate data, and recognizing a suspected water resource retention region; the water resource circulation potential is evaluated in combination with microclimate fluctuation characteristics and earth surface characteristics, and an actual water resource optimal utilization area is screened; according to the water resource circulation potential, the vegetation planting density, variety and irrigation mode are dynamically adjusted, the ecological restoration gain coefficient is calculated, and collaborative optimization of the water resource utilization efficiency and the ecological restoration effect is achieved. Water resource management and ecological restoration are organically coupled, accurate utilization and efficient circulation of water resources are achieved, and the restoration capacity and sustainability of an ecological system in the desert area are remarkably improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of ecological environment restoration and water resource management, and more particularly, relates to a water resource recycling method based on ecological restoration coupling in a desert area. BACKGROUND

[0002] As an important part of the global ecosystem, the desert area has special ecological value and environmental significance. However, due to natural factors such as drought climate, rare precipitation, and strong evaporation, combined with unreasonable human intervention, the desert area is generally facing severe challenges such as water resource scarcity and ecological system degradation. As a key limiting factor of the desert ecosystem, the rational use and recycling of water resources play a decisive role in the ecological restoration and sustainable development of the desert area.

[0003] The traditional water resource management method generally adopts a static and single management mode, which fails to fully consider the complex interaction between water and vegetation in the desert environment, resulting in low water resource utilization efficiency and limited ecological restoration effect. Due to the lack of comprehensive analysis of regional microclimate, soil characteristics, and vegetation distribution characteristics, the design of the irrigation system is seriously out of touch with the actual demand, which not only causes waste of valuable water resources, but also may cause secondary salinization problems. The existing technology lacks sufficient accuracy in identifying the natural water retention area in the desert region, and lacks a scientific spatial dynamic model to capture the synergistic relationship between water accumulation and vegetation growth, so that the ecological restoration project often selects an inappropriate site, and the input-output ratio is unbalanced. In addition, the irrigation strategy usually adopts a rough mode of fixed cycle and fixed water volume, which fails to fine-tune according to the evaporation amount daily variation characteristics and real-time soil humidity conditions, and the water resource utilization efficiency is particularly low during the peak period of drought. More importantly, the existing technology lacks an index system to quantitatively correlate water resource recycling with ecological restoration effect, which cannot realize dynamic decision optimization based on data driving, resulting in the difficulty of forming a virtuous cycle for the desert ecosystem restoration project, and the long-term ecological benefit cannot be sustained. In the face of climate change and extreme weather events, the desert ecosystem shows vulnerability, which seriously restricts the sustainable development and ecological safety of the desert area. SUMMARY

[0004] The main purpose of the present application is to provide a water resource recycling method based on ecological restoration coupling in a desert area to overcome the above-mentioned defects of the prior art.

[0005] To achieve the above-mentioned application purposes, the present application provides the following technical solutions.

[0006] Some embodiments of the present application provide a water resource recycling method based on ecological restoration coupling in a desert area, comprising:

[0007] Obtain soil moisture distribution data, vegetation coverage data and regional microclimate data of each time node in the monitoring range of the desert area;

[0008] According to the spatio-temporal variation characteristics of the water gradient in the soil moisture distribution data and the spatial distribution characteristics of the vegetation in the vegetation coverage data, a water-vegetation coupled spatial dynamic model is constructed to obtain a suspected water resource retention area;

[0009] According to the fluctuation characteristics of rainfall, evaporation and wind speed of adjacent time nodes in the analysis period of each time node in the regional microclimate data, combined with the terrain slope, soil permeability and surface roughness of the suspected water resource retention area, the water resource circulation potential of each suspected water resource retention area is obtained; based on the water resource circulation potential, an actual water resource optimization utilization area is screened;

[0010] According to the water resource circulation potential of the actual water resource optimization utilization area of each time node, the vegetation planting density, vegetation species and irrigation mode of the actual water resource optimization utilization area are dynamically adjusted to obtain the ecological restoration gain coefficient of the corresponding area; based on the ecological restoration gain coefficient, the water resource utilization efficiency and ecological restoration effect of the water resource circulation system are optimized.

[0011] In one embodiment, the construction of the water-vegetation coupled spatial dynamic model to obtain the suspected water resource retention area comprises:

[0012] The soil moisture distribution data is spatio-temporally interpolated to obtain the soil moisture gradient field of each time node; according to the direction and amplitude of the water gradient in the soil moisture gradient field, the water convergence area is extracted;

[0013] According to the spatial distribution characteristics of the vegetation in the vegetation coverage data, the local aggregation degree of vegetation coverage is calculated; based on the local aggregation degree and the spatial overlap degree of the water convergence area, a water-vegetation coupled spatial dynamic model is constructed;

[0014] In the water-vegetation coupled spatial dynamic model, the water convergence area with a spatial overlap degree greater than a preset overlap threshold is recorded as a suspected water resource retention area.

[0015] In one embodiment, the water resource circulation potential of each suspected water resource retention area is obtained, comprising:

[0016] The rainfall, evaporation and wind speed of adjacent time nodes in the analysis period of each time node in the regional microclimate data are time-series decomposed to obtain the corresponding rainfall fluctuation component, evaporation fluctuation component and wind speed fluctuation component;

[0017] According to a difference between the rainfall fluctuation component and the evaporation fluctuation component, and a disturbance effect of the wind speed fluctuation component on water migration, a water dynamic balance index of the suspected water resource retention area is calculated;

[0018] According to a terrain slope, a soil permeability, and a surface roughness of the suspected water resource retention area, a surface water retention resistance coefficient is constructed.

[0019] A product of the water dynamic balance index and the surface water retention resistance coefficient is normalized to obtain a water resource circulation potential of each suspected water resource retention area.

[0020] In one embodiment, the water resource circulation potential is used to screen an actual water resource optimized utilization area, including:

[0021] Water resource circulation potentials of all suspected water resource retention areas are sorted, and a suspected water resource retention area with a water resource circulation potential greater than a preset potential threshold is recorded as a candidate water resource optimized utilization area.

[0022] A time stability of a water resource circulation potential of each candidate water resource optimized utilization area is calculated, and the time stability is an inverse of a standard deviation of the water resource circulation potential in an analysis period.

[0023] A weighted sum of the water resource circulation potential and the time stability is used as a screening index, and a candidate water resource optimized utilization area with a screening index greater than a preset screening threshold is recorded as an actual water resource optimized utilization area.

[0024] In one embodiment, the vegetation planting density, the vegetation type, and the irrigation mode of the actual water resource optimized utilization area are dynamically adjusted, including:

[0025] According to a water resource circulation potential of the actual water resource optimized utilization area, an initial value of the vegetation planting density is determined.

[0026] According to a ratio of a soil humidity average of the actual water resource optimized utilization area in the soil humidity distribution data to rainfall in the regional microclimate data, a water supply stability coefficient is obtained.

[0027] According to a product of the water supply stability coefficient and the water resource circulation potential, the vegetation planting density is dynamically adjusted.

[0028] According to a terrain slope and a soil permeability of the actual water resource optimized utilization area, a drought resistance grade of the vegetation type is determined, and the vegetation type is dynamically adjusted based on a matching degree of the drought resistance grade and the water resource circulation potential.

[0029] According to the daily variation characteristics of the evaporation amount in the regional microclimate data, the irrigation time period and the irrigation amount of the irrigation mode are determined; and the irrigation amount is dynamically corrected based on the water resource circulation potential.

[0030] In one embodiment, the ecological restoration gain coefficient of the corresponding region is obtained, including:

[0031] According to the change amount of the vegetation coverage of the actual water resource optimized utilization area in the vegetation coverage data at adjacent time nodes, a vegetation coverage gain value is obtained;

[0032] According to the change amount of the soil moisture mean value of the actual water resource optimized utilization area in the soil moisture distribution data at adjacent time nodes, a soil moisture improvement value is obtained;

[0033] According to the change amount of the wind speed mean value of the actual water resource optimized utilization area in the regional microclimate data at adjacent time nodes, an aeolian erosion inhibition value is obtained;

[0034] The weighted sum of the vegetation coverage gain value, the soil moisture improvement value and the aeolian erosion inhibition value is normalized to obtain the ecological restoration gain coefficient.

[0035] In one embodiment, the water resource utilization efficiency and the ecological restoration effect of the water resource circulation system are optimized based on the ecological restoration gain coefficient, including:

[0036] According to the ratio of the ecological restoration gain coefficient to a preset gain threshold value, the irrigation frequency of the irrigation mode of the actual water resource optimized utilization area is adjusted;

[0037] According to the product of the ecological restoration gain coefficient and the water resource circulation potential, the upper limit value of the vegetation planting density of the actual water resource optimized utilization area is dynamically adjusted;

[0038] According to the time variation trend of the ecological restoration gain coefficient, the future variation trend of the water resource circulation potential of the actual water resource optimized utilization area is predicted; and the water resource allocation strategy of the water resource circulation system is optimized based on the future variation trend.

[0039] In one embodiment, the local aggregation degree of the vegetation coverage is calculated, including:

[0040] The vegetation coverage data is grid divided to obtain the vegetation coverage mean value of each grid;

[0041] The standard deviation of the vegetation coverage mean value of each grid and the vegetation coverage mean value of its adjacent grid is calculated as the local fluctuation value of the vegetation coverage of the grid;

[0042] The reciprocal of the local fluctuation value of the vegetation coverage is taken as the local aggregation degree of the vegetation coverage of the grid.

[0043] In one embodiment, the building of the surface water retention resistance coefficient comprises:

[0044] According to the terrain slope of the suspected water resource retention area, a surface runoff resistance component is calculated;

[0045] According to the soil permeability of the suspected water resource retention area, a water infiltration resistance component is calculated;

[0046] According to the surface roughness of the suspected water resource retention area, a water retention resistance component is calculated;

[0047] The weighted sum of the surface runoff resistance component, the water infiltration resistance component and the water retention resistance component is normalized to obtain the surface water retention resistance coefficient.

[0048] In one embodiment, the determination of the irrigation time period and the irrigation amount of the irrigation mode according to the daily variation characteristics of the evaporation amount in the regional microclimate data comprises:

[0049] The evaporation amount in the regional microclimate data is subjected to time series analysis to obtain an evaporation amount daily variation curve of each time node;

[0050] In the evaporation amount daily variation curve, a time period in which the evaporation amount is less than a preset evaporation threshold value is extracted as a candidate irrigation time period;

[0051] According to the soil moisture average value of the soil moisture distribution data in the candidate irrigation time period, a water replenishment demand amount is calculated;

[0052] According to the ratio of the water replenishment demand amount to the water resource circulation potential, the irrigation amount of the irrigation mode is determined.

[0053] Compared with the prior art, the desert area water resource recycling method based on ecological restoration coupling provided by the present application realizes the organic integration of water resource management and ecological restoration, greatly improves the utilization efficiency of water resources in the desert area, reduces the loss of invalid evaporation and seepage, and makes the limited water resources play the maximum ecological benefit. In actual application, the vegetation coverage rate of the desert area can be significantly improved, the soil structure can be obviously improved, and the wind erosion phenomenon can be effectively controlled, forming a benign ecological circulation system. In addition, by accurately identifying and scientifically utilizing the natural water retention area, the input cost of the ecological restoration project can be reduced, the success rate and durability of the restoration can be improved, and the adaptability and resistance of the desert ecological system to climate change can be enhanced. In the long run, it will help to reverse the desertification expansion trend, restore regional biodiversity, and improve local climate conditions. BRIEF DESCRIPTION OF DRAWINGS

[0054] Figure 1 FIG. 1 is a schematic diagram of a water resource recycling method based on ecological restoration coupling in a desert area according to an embodiment of the present application. DETAILED DESCRIPTION

[0055] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the scope of protection of the present application.

[0056] The present embodiment provides a water resource recycling method based on ecological restoration coupling in a desert area, which utilizes multi-source data monitoring and analysis technology to realize the coupling of efficient recycling of water resources and ecological system restoration in the desert area, and solves the dual challenges of water scarcity and ecological fragility in the desert area. The execution subjects of the method include but are not limited to: regional environmental monitoring system, water resource management system, ecological restoration system, etc.

[0057] Specifically, the water resource recycling method based on ecological restoration coupling in the desert area includes the following steps:

[0058] Firstly, the soil moisture distribution data, vegetation coverage data and regional microclimate data at each time node within the monitoring range of the desert area are obtained through the regional monitoring network. The soil moisture distribution data come from the soil moisture sensor network distributed in the monitoring area, and the soil moisture content at different depths is measured by using time domain reflectometry (TDR) or frequency domain reflectometry (FDR). The vegetation coverage data come from multi-spectral remote sensing image analysis, combined with ground verification point data, and are obtained by calculating the normalized difference vegetation index (NDVI) or enhanced vegetation index (EVI). The regional microclimate data include rainfall, evaporation and wind speed, etc. parameters, which come from the automatic weather station network distributed in the monitoring area, and are recorded and transmitted according to the hourly to daily scale.

[0059] According to the spatio-temporal variation characteristics of the water gradient in the soil moisture distribution data and the spatial distribution characteristics of the vegetation in the vegetation coverage data, a water-vegetation coupling spatial dynamic model is constructed to obtain the suspected water resource retention area. The water-vegetation coupling model analyzes the interaction relationship between water distribution and vegetation growth to identify the areas where water naturally converges. These areas usually have high soil moisture gradient variation and vegetation coverage aggregation characteristics, indicating that they have the potential for natural retention of water resources.

[0060] According to the fluctuation characteristics of rainfall, evaporation and wind speed in the regional microclimate data of adjacent time nodes within the analysis period of each time node, combined with the terrain slope, soil permeability and surface roughness of the suspected water resource retention area, the water resource circulation potential of each suspected water resource retention area is obtained. The water resource circulation potential quantifies the ability of the region to retain water and maintain water circulation, and is a key indicator for screening and optimizing the use area.

[0061] Based on the water resource circulation potential, the actual water resource optimization utilization area is screened. By sorting and screening the water resource circulation potential of the suspected water resource retention area, the area with the most water resource optimization potential is determined, which will be the priority implementation area for ecological restoration. The screening process not only considers the absolute value of the water resource circulation potential, but also considers its time stability, to ensure that the selected area has long-term stable water resource guarantee.

[0062] According to the water resource circulation potential of the actual water resource optimization utilization area at each time node, the vegetation planting density, vegetation species and irrigation mode of the actual water resource optimization utilization area are dynamically adjusted, and the ecological restoration gain coefficient of the corresponding area is obtained. The dynamic adjustment strategy optimizes the vegetation configuration and irrigation scheme in real time according to the change of the water resource circulation potential, maximizes the water resource utilization efficiency and ecological restoration effect. The ecological restoration gain coefficient quantifies the effect of the restoration measures, which is a key indicator for system optimization.

[0063] Based on the ecological restoration gain coefficient, the water resource utilization efficiency and ecological restoration effect of the water resource circulation system are optimized. By analyzing the change trend of the ecological restoration gain coefficient, the water resource allocation strategy and ecological restoration measures are adjusted, forming a positive feedback mechanism of water resource circulation and ecological restoration, and realizing the continuous optimization of the system.

[0064] In this embodiment, the detailed implementation steps for constructing a water-vegetation coupled spatial dynamic model for the suspected water resource retention area can include:

[0065] The soil moisture distribution data is spatio-temporally interpolated to obtain the soil moisture gradient field at each time node. The spatio-temporal interpolation adopts Kriging interpolation method or inverse distance weighted method (IDW) to convert discrete monitoring point data into continuous spatial distribution field. The spatial autocorrelation and time continuity of the monitoring points are considered in the interpolation process to ensure that the generated moisture gradient field has high accuracy. The interpolation parameters of spatio-temporal interpolation are dynamically adjusted by the combined weight of soil type data and terrain relief data to improve the adaptability of the interpolation results.

[0066] According to the direction and amplitude of the water gradient in the soil moisture gradient field, the water convergence area is extracted. The direction of the water gradient indicates the potential path of water flow, and the amplitude reflects the intensity of water change. Through the vector field analysis method, the gradient vector of each grid point is calculated, and the area where the gradient vectors converge is identified as the water convergence area. The identification of the water convergence area adopts the gradient divergence calculation method, and the area with negative divergence and absolute value greater than the preset threshold is marked as the water convergence area. The preset threshold is dynamically determined by monitoring the ratio of the average soil moisture change rate to the rainfall infiltration rate of the region, ensuring the sensitivity of the identification result to the hydrological characteristics of the region.

[0067] According to the spatial distribution characteristics of vegetation in the vegetation coverage data, the local aggregation degree of vegetation coverage is calculated. The local aggregation degree reflects the spatial concentration degree of vegetation distribution, and is an important indicator for identifying vegetation growth advantage areas. In the calculation process, spatial autocorrelation analysis methods such as local Moran's I index or Getis-Ord Gi* statistics are used to quantify the spatial aggregation characteristics of vegetation coverage. The size of the calculation window of the local aggregation degree is determined by the ratio of the distribution range of the vegetation roots to the soil water diffusion radius, ensuring that the analysis scale matches the spatial scale of the ecological process.

[0068] Based on the spatial overlap degree of local aggregation degree and water convergence area, a spatial dynamic model of water-vegetation coupling is constructed. The model regards water distribution and vegetation growth as two interacting subsystems, and reveals the coupling mechanism of water resources and vegetation growth by quantitatively analyzing the spatial coordination relationship between the two. The spatial overlap degree is calculated by the ratio of the spatial intersection and union of the high value area of the local aggregation degree of vegetation and the water convergence area, reflecting the spatial matching degree of water distribution and vegetation growth. The spatial dynamic model of water-vegetation coupling adopts a weighted network structure, where the nodes represent spatial units and the edge weights represent the strength of water flow and vegetation influence. The dynamic process of water-vegetation interaction is simulated through iterative calculation.

[0069] In the spatial dynamic model of water-vegetation coupling, the water convergence area with a spatial overlap degree greater than a preset overlap threshold is recorded as a suspected water resource retention area. The preset overlap threshold is determined by the correlation coefficient of stable vegetation area and water duration in historical monitoring data, ensuring that the identification result has ecological significance. The suspected water resource retention area represents spatial units with potential for natural accumulation of water resources, and serves as the basis for subsequent analysis.

[0070] In this embodiment, the detailed implementation steps for obtaining the water resource circulation potential of each suspected water resource retention area can include:

[0071] The rainfall, evaporation, and wind speed of the adjacent time nodes in the analysis period of each time node are time-series decomposed to obtain the corresponding rainfall fluctuation component, evaporation fluctuation component, and wind speed fluctuation component. The time-series decomposition adopts the empirical mode decomposition (EMD) or wavelet decomposition method to decompose the time series into fluctuation components of different frequencies, revealing the multi-scale variation characteristics of the data. The fluctuation component reflects the variation law of the microclimate elements at different time scales, and is an important basis for evaluating the dynamic balance of water resources. The number of decomposition layers is determined by the ratio of the climate period of the monitoring area to the ecological response time, ensuring that the decomposition result can capture the key climate-ecology interaction process.

[0072] According to the difference between the rainfall fluctuation component and the evaporation fluctuation component, and the disturbance effect of the wind speed fluctuation component on water migration, the water resource dynamic balance index of the suspected water resource retention area is calculated. The water resource dynamic balance index quantifies the dynamic balance state of the water input and output of the region, and reflects the stability of the water resources. The calculation formula is:

[0073] The water resource dynamic balance index=(rainfall fluctuation component-evaporation fluctuation component)×(1-α×wind speed fluctuation component); wherein, α is the influence coefficient of wind speed on water migration, which is determined by a combination function of the regional vegetation coverage and soil texture. The combination function considers the weakening effect of vegetation on wind speed and the water retention capacity of soil, dynamically adjusts the wind speed influence coefficient, and improves the calculation accuracy of the balance index.

[0074] According to the terrain slope, soil permeability, and surface roughness of the suspected water resource retention area, the surface water retention resistance coefficient is constructed. The surface water retention resistance coefficient quantifies the influence of surface characteristics on water retention, and is an important part of evaluating the water resource circulation potential. The terrain slope data comes from digital elevation model (DEM) analysis, the soil permeability data comes from soil sample testing or soil type query table, and the surface roughness data comes from surface coverage classification and field investigation. After standardization processing, the three types of data are combined by weighting to form a comprehensive water retention resistance representation.

[0075] The product of the water resource dynamic balance index and the surface water retention resistance coefficient is normalized to obtain the water resource circulation potential of each suspected water resource retention area. The normalization processing adopts the Min-Max method to map the calculation results to the [0, 1] interval, which is convenient for comparison and sorting of different regions. The water resource circulation potential is a comprehensive index for measuring the sustainable utilization capacity of regional water resources. The higher the value, the more stable the regional water resource circulation system, and the more suitable it is as a priority area for ecological restoration. The reference range of the normalization processing is determined by statistical analysis of the historical data of all suspected water resource retention areas in the monitoring region, ensuring the regional applicability and time continuity of the evaluation results.

[0076] In this embodiment, the detailed implementation steps for screening the actual water resource optimization utilization area based on the water resource circulation potential can include:

[0077] The water resource circulation potentials of all suspected water resource retention areas are sorted, and the suspected water resource retention areas with a water resource circulation potential greater than a preset potential threshold are recorded as candidate water resource optimization utilization areas. The sorting process adopts descending arrangement, and the areas with high water resource circulation potential are preferentially selected. The preset potential threshold is determined by the ratio of the total amount of water resources to the ecological water demand of the monitoring area, to ensure that the selected area can meet the basic water resource demand for ecological restoration. The determination of the preset potential threshold also considers the type of regional ecosystem and the restoration target, and different threshold setting strategies are adopted for areas with different restoration targets.

[0078] The time stability of the water resource circulation potential of each candidate water resource optimization utilization area is calculated, and the time stability is the inverse of the standard deviation of the water resource circulation potential in the analysis period. The time stability reflects the fluctuation degree of the water resource circulation potential in the time dimension, and the area with high stability is more suitable for long-term ecological restoration. The standard deviation calculation adopts the weighted standard deviation method, and the weight of recent data is higher than that of long-term data, reflecting the latest trend of water resource circulation potential. The weighted method adopts an exponential decay weight function, and the weight decay rate is determined by the ratio of the climate change rate to the ecological response time of the monitoring area.

[0079] The weighted sum of the water resource circulation potential and the time stability is taken as the screening index, and the candidate water resource optimization utilization area with a screening index greater than a preset screening threshold is recorded as the actual water resource optimization utilization area. The weighted sum calculation formula is:

[0080] ZB=β×SX+(1-β)×SW;

[0081] Wherein, SX is the water resource circulation potential, ZB is the screening index, SW is the time stability, β is the weight coefficient, the value range is [0, 1], and the weight coefficient is determined by the ratio of the climate fluctuation characteristics to the ecological system restoration elasticity of the monitoring area. For areas with severe climate fluctuations or low ecological system restoration elasticity, the weight of time stability should be increased to ensure that the selected area has stable water resource guarantee; otherwise, the weight of water resource circulation potential can be increased to preferentially consider the area with the best water resource conditions. The preset screening threshold is determined by the screening index statistics of the historical ecological restoration success cases of the monitoring area, to ensure that the screening result has practical guiding significance.

[0082] The actual water resource optimization utilization area as the implementation area of ecological restoration will be subjected to vegetation configuration optimization and irrigation system design to realize the dual goals of efficient water resource utilization and ecological system restoration. In the screening process, the spatial connectivity of the actual water resource optimization utilization area is also considered, and the area combination with spatial aggregation or ecological corridor connection potential is preferentially selected to improve the overall effect of ecological restoration.

[0083] In this embodiment, the detailed implementation steps of dynamically adjusting the vegetation planting density, vegetation species, and irrigation mode of the actual water resource optimization utilization area can include:

[0084] According to the water resource circulation potential of the actual water resource optimization utilization area, the initial value of the vegetation planting density is determined. The vegetation planting density is the number of plants per unit area, which directly affects water resource consumption and ecological restoration effect. The initial value is determined by the ratio of the water resource circulation potential to the standard water demand of the target vegetation, ensuring that the initial vegetation configuration matches the water resource conditions. The standard water demand is calculated by the product of the transpiration coefficient of the target vegetation and the regional reference evaporation, reflecting the water consumption characteristics of the vegetation under standard conditions. The determination of the initial value also takes into account the succession stage of the regional ecosystem, and different initial density setting strategies are adopted for regions at different restoration stages.

[0085] According to the ratio of the average soil moisture of the actual water resource optimization utilization area in the soil moisture distribution data to the rainfall in the regional microclimate data, the water supply stability coefficient is obtained. The water supply stability coefficient reflects the reliability of the regional water source and is an important reference index for adjusting vegetation configuration. The calculation formula is:

[0086]

[0087] Where FC is the water supply stability coefficient, TS is the average soil moisture, JY is the rainfall; γ is the rainfall infiltration coefficient, determined by the function of soil texture and vegetation coverage; δ is the basic water supply constant, reflecting the contribution of non-rainfall water sources such as groundwater recharge. The higher the water supply stability coefficient, the more stable the regional water supply, and the more suitable for configuring high-density or high-water-consumption vegetation.

[0088] According to the product of the water supply stability coefficient and the water resource circulation potential, the vegetation planting density is dynamically adjusted. The adjustment process uses an iterative optimization method to gradually adjust the vegetation density according to changes in water resource conditions, avoiding ecological risks caused by drastic fluctuations. The frequency of dynamic adjustment is determined by the ratio of the water change rate of the region to the vegetation growth cycle, ensuring that the adjustment process matches the time scale of the ecological process. The adjustment range of the vegetation planting density is constrained by the stability of the ecosystem structure, avoiding the destruction of the community structure caused by excessive adjustment.

[0089] According to the topographic slope and soil permeability of the actual water resource optimization utilization area, the drought tolerance grade of the vegetation species is determined. The drought tolerance grade is a classification of the adaptability of vegetation to water stress, and is a key index for selecting suitable vegetation species. The drought tolerance grade is determined by a combination function of the topographic slope and soil permeability. In a region with a large slope and high permeability, vegetation species with strong drought tolerance need to be configured; in a region with a small slope and low permeability, vegetation species with weaker drought tolerance but stronger ecological function can be configured. The combination function considers the residence time of water on the ground and the water holding capacity of the soil, and comprehensively evaluates the water conditions of the region.

[0090] Based on the matching degree of the drought tolerance grade and the water resource circulation potential, the vegetation species is dynamically adjusted. The matching degree evaluation adopts a fuzzy logic method to fuzz the relationship between the drought tolerance grade and the water resource circulation potential, forming a decision rule for vegetation species selection. The decision rule not only considers the water conditions, but also considers the ecological functions of vegetation, such as wind prevention and sand fixation ability, soil improvement ability, and biodiversity contribution, etc., and preferentially selects vegetation species with strong ecological function under the premise of meeting the drought tolerance requirement. The adjustment of the vegetation species also considers the mutualistic symbiotic relationship between species, and preferentially selects the combination of species that can form a stable community structure.

[0091] According to the daily variation characteristics of evaporation in the regional microclimate data, the irrigation time period and irrigation amount of the irrigation mode are determined. The irrigation mode is a strategy for artificial replenishment of water resources, and directly affects the water resource utilization efficiency and vegetation growth condition. The selection of the irrigation time period is based on the analysis of the daily evaporation curve, and preferentially selects the period with low evaporation for irrigation to reduce water evaporation loss. The determination of the irrigation amount is based on the comprehensive analysis of soil water deficit and vegetation water requirement, which not only meets the vegetation growth demand, but also avoids the waste of water resources caused by excessive irrigation.

[0092] The irrigation amount is dynamically corrected based on the water resource circulation potential. The correction process adopts a proportional adjustment method. The irrigation amount in a region with high water resource circulation potential can be appropriately reduced to preferentially utilize natural water cycle; the irrigation amount in a region with low water resource circulation potential needs to be increased to ensure the survival of vegetation. The correction coefficient of dynamic correction is determined by the ratio of the water resource circulation potential to the regional evaporation, which reflects the satisfaction degree of natural water cycle to vegetation water requirement. The adjustment of the irrigation mode is cooperated with the adjustment of the vegetation species and density, forming a mutually adaptive water resource-vegetation system, maximizing the water resource utilization efficiency and ecological restoration effect.

[0093] In this embodiment, the detailed implementation steps of obtaining the ecological restoration gain coefficient corresponding to the region can include:

[0094] According to the change amount of the vegetation coverage in the actual water resource optimization utilization area in the vegetation coverage data at adjacent time nodes, a vegetation coverage gain value is obtained. The vegetation coverage gain value reflects the improvement degree of the vegetation growth condition and is a direct index for evaluating the ecological restoration effect. The calculation formula is:

[0095] Vegetation coverage gain value = (current time node vegetation coverage - last time node vegetation coverage) / last time node vegetation coverage

[0096] This relative change rate form eliminates the base effect, so that regions with different base vegetation coverages can be compared. The calculation of the vegetation coverage gain value considers the influence of seasonal fluctuations, and the seasonal factor is eliminated by comparison with historical data at the same period or seasonal adjustment to obtain the true restoration effect.

[0097] According to the change amount of the soil moisture mean value in the actual water resource optimization utilization area in the soil humidity distribution data at adjacent time nodes, a soil humidity improvement value is obtained. The soil humidity improvement value reflects the improvement of the water resource retention capacity and is an important index for evaluating the water cycle improvement. The calculation method is similar to that of the vegetation coverage gain value, and the relative change rate form is used to eliminate the base effect. The calculation of the soil humidity improvement value also considers the influence of rainfall variation, and the influence of climate fluctuations is eliminated by standardization processing of rainfall to obtain the true improvement degree of the soil moisture condition.

[0098] According to the change amount of the wind speed mean value in the actual water resource optimization utilization area in the regional microclimate data at adjacent time nodes, an aeolian erosion inhibition value is obtained. The aeolian erosion inhibition value reflects the improvement effect of the ecological restoration on the wind-sand environment and is a special evaluation index for ecological restoration in desert areas. The calculation formula is:

[0099] Aeolian erosion inhibition value = (last time node wind speed mean value - current time node wind speed mean value) / last time node wind speed mean value; the aeolian erosion inhibition value is positive, indicating that the wind speed is reduced and the ecological environment is improved; and the aeolian erosion inhibition value is negative, indicating that the wind speed is increased and protective measures need to be strengthened. The calculation of the aeolian erosion inhibition value considers the change of the regional meteorological background wind speed, and the influence of large-scale meteorological changes is eliminated by comparison with the reference point wind speed to obtain the actual adjustment effect of the vegetation on the wind speed.

[0100] The weighted sum of the vegetation coverage gain value, the soil humidity improvement value and the aeolian erosion inhibition value is normalized to obtain an ecological restoration gain coefficient. The calculation formula of the weighted sum is:

[0101] The original value of the ecological restoration gain coefficient is w1*the vegetation coverage gain value + w2*the soil moisture improvement value + w3*the wind erosion inhibition value; wherein w1, w2, and w3 are weight coefficients, and w1+w2+w3=1. The weight coefficients are determined according to the priority of the regional ecological restoration target. For a region where wind prevention and sand fixation is the main target, the weight of the wind erosion inhibition value is increased. For a region where vegetation restoration is the main target, the weight of the vegetation coverage gain value is increased. For a region where water resource protection is the main target, the weight of the soil moisture improvement value is increased. The original value is mapped to the interval [0, 1] by the Min-Max method for normalization processing, which facilitates comparison and evaluation of different regions and different periods.

[0102] The ecological restoration gain coefficient, as a comprehensive index for evaluating the restoration effect, reflects the coupling effect of water resource circulation and ecological restoration, and is an important basis for system optimization and adjustment. In the calculation process of the gain coefficient, the influence of the time scale is also considered, and short-term fluctuations and long-term trends are analyzed separately to ensure that the evaluation results accurately reflect the true effect of ecological restoration.

[0103] In this embodiment, the detailed implementation steps for optimizing the water resource utilization efficiency and the ecological restoration effect of the water resource circulation system based on the ecological restoration gain coefficient can include:

[0104] According to the ratio of the ecological restoration gain coefficient to the preset gain threshold value, the irrigation frequency of the irrigation mode of the actual water resource optimized utilization area is adjusted. The irrigation frequency is the number of irrigations per unit time, which directly affects the water resource input efficiency. The adjustment formula is:

[0105]

[0106] wherein GY is the adjusted irrigation frequency, YH is the original irrigation frequency, SN is the ecological restoration gain coefficient, SU is the preset gain threshold value, and η is the adjustment coefficient, which is determined by the ratio of the regional water resource scarcity degree to the ecological system restoration elasticity. When the ecological restoration gain coefficient is higher than the preset gain threshold value, it indicates that the restoration effect is good, and the irrigation frequency can be reduced to reduce water resource input; when it is lower than the preset threshold value, the irrigation frequency needs to be increased to strengthen water resource support. The preset gain threshold value is determined by the gain coefficient statistics of the historical ecological restoration projects in the region, which reflects the general level of regional ecological restoration.

[0107] According to the product of the ecological restoration gain coefficient and the water resource circulation potential, the upper limit value of the vegetation planting density of the actual water resource optimized utilization area is dynamically adjusted. The upper limit value of the vegetation planting density is a vegetation configuration constraint considering the water resource carrying capacity to prevent resource competition from intensifying due to overplanting. The adjustment formula is:

[0108] The upper limit of the adjusted vegetation planting density is equal to the upper limit of the basic vegetation planting density multiplied by (1 + θ × ecological restoration gain coefficient × water resource recycling potential); wherein θ is an adjustment coefficient determined by the ratio of the natural growth rate of regional vegetation to the change rate of water resources. The product of the ecological restoration gain coefficient and the water resource recycling potential reflects the level of coordinated development of the regional ecological-water resource system. A high product indicates that ecological restoration and water resource recycling form a virtuous cycle, which can support a higher density of vegetation. The upper limit of the basic vegetation planting density is determined by a function of the standard vegetation density of the regional climate zone and the soil carrying capacity, ensuring the scientificity of the upper limit value.

[0109] According to the time variation trend of the ecological restoration gain coefficient, the future variation trend of the water resource recycling potential of the actual water resource optimization utilization area is predicted. The prediction adopts a time series analysis method such as the exponential smoothing method or the ARIMA model to predict the future trend based on historical data. The time variation trend is determined by the first-order difference sequence analysis of the ecological restoration gain coefficient at a plurality of time nodes, capturing the change direction and rate of the gain coefficient. The time window of the prediction is determined by the ratio of the recovery characteristic time of the regional ecosystem to the climate period, ensuring that the prediction range is neither too short to cause frequent strategy adjustment nor too long to reduce the prediction accuracy.

[0110] Based on the future variation trend, the water resource allocation strategy of the water resource recycling system is optimized. The optimization process adopts a feedforward control method to adjust the water resource allocation in advance according to the predicted trend, preventing resource waste or ecological risks caused by system lag. The water resource allocation strategy includes a cross-regional water resource allocation scheme and a time series input plan, forming a spatial and temporal two-dimensional optimization strategy. The optimization goal of the allocation strategy is to maximize the product of the ecological restoration gain coefficient and the water resource utilization efficiency, realizing the dual maximization of ecological benefit and resource benefit.

[0111] During the implementation of the water resource allocation strategy, a dynamic feedback mechanism is established to monitor the changes of the ecological restoration gain coefficient and the water resource recycling potential in real time, adjust the implementation parameters of the allocation strategy, and ensure the adaptability and stability of the optimization process. The feedback mechanism adopts the proportional-integral-derivative (PID) control principle, which considers the current deviation, cumulative deviation and variation trend to realize accurate control of water resource allocation.

[0112] In this embodiment, the detailed implementation steps of calculating the local aggregation degree of vegetation coverage can include:

[0113] The vegetation coverage data is grid divided to obtain the average vegetation coverage of each grid. The grid division adopts a regular grid method to divide the monitoring area into grid units of the same size, and the arithmetic mean of the vegetation coverage in each grid is calculated. The grid size is determined by the ratio of the characteristic scale of the regional vegetation patch to the spatial resolution of the monitoring data, ensuring that the grid scale can capture the spatial variation of vegetation and not introduce excessive computational burden. The calculation of the average vegetation coverage takes into account the weighted contribution of various types of vegetation within the grid, and different types of vegetation are given different weights according to their ecological function importance, improving the ecological representativeness of the average value.

[0114] The standard deviation of the average vegetation coverage of each grid and the average vegetation coverage of its adjacent grid is calculated as the local fluctuation value of the vegetation coverage of the grid. The local fluctuation value reflects the spatial heterogeneity of vegetation distribution and is the basic index for calculating the aggregation degree. The definition of adjacent grid adopts Moore neighborhood or Von Neumann neighborhood, and the appropriate neighborhood structure is selected according to the spatial distribution characteristics of regional vegetation.

[0115] The reciprocal of the local fluctuation value of vegetation coverage is recorded as the local aggregation degree of vegetation coverage of the grid. The reciprocal relationship makes the area with small fluctuation value obtain high aggregation degree value, reflecting the spatial concentration characteristics of vegetation distribution. To avoid division by zero error caused by fluctuation value of zero, the actual calculation formula is:

[0116]

[0117] Where JGF is the local aggregation degree of vegetation coverage, BDJ is the local fluctuation value of vegetation coverage, and ε is a small positive number, usually 1% of the average vegetation coverage of the monitoring area. The calculation of local aggregation degree also considers the spatial autocorrelation between grids, and the calculation result is corrected by Moran's I index or Geary's C coefficient to improve the spatial consistency of aggregation degree evaluation.

[0118] The high value area of local aggregation degree of vegetation coverage represents the area with relatively uniform vegetation distribution and high coverage, which usually has stable vegetation community structure and good ecological function, and is the key area of water resources-vegetation coupling analysis. The spatial distribution map of local aggregation degree is generated by GIS interpolation method to generate continuous surface, which directly shows the spatial aggregation characteristics of vegetation distribution, supports the construction of water-vegetation coupling model and the identification of suspected water resources retention area.

[0119] In this embodiment, the detailed implementation steps for constructing the surface water retention resistance coefficient can include:

[0120] The surface runoff resistance component is calculated according to the terrain slope of the suspected water resource retention area. The terrain slope is the main factor affecting the speed and direction of surface water flow. The greater the slope, the shorter the residence time of water on the surface, and the lower the water retention capacity. The terrain slope data comes from digital elevation model (DEM) analysis, and the slope value of each spatial unit is calculated using the GIS slope analysis tool. The greater the slope, the smaller the resistance component, reflecting the negative impact of slope on water retention. The calculation of the resistance component also takes into account the influence of slope aspect, which has different evaporation conditions and vegetation cover on sunny and shady slopes, resulting in different water retention capacities.

[0121] The water infiltration resistance component is calculated according to the soil permeability of the suspected water resource retention area. Soil permeability determines the speed of precipitation moving to the deep soil, and the higher the permeability, the faster the water infiltration and the shorter the surface water retention time. Soil permeability data come from soil sample testing or soil type lookup table, reflecting the hydrodynamic properties of the soil. The higher the permeability, the smaller the resistance component, reflecting the negative impact of permeability on surface water retention. The calculation of the resistance component also takes into account the influence of soil moisture content, which reduces the permeability of soil with high moisture content. Dynamic correction of permeability through soil moisture data improves the accuracy of the calculation.

[0122] The water retention resistance component is calculated according to the surface roughness of the suspected water resource retention area. Surface roughness reflects the hindering effect of surface micro-topography and cover on water flow, and high roughness of the surface can slow down the water flow speed and increase the water retention time. Surface roughness data come from surface cover classification and field investigation, and different types of surface cover have different roughness values. The higher the roughness, the greater the resistance component, reflecting the positive contribution of roughness to water retention. The calculation of the resistance component also takes into account the influence of seasonal changes, with surface roughness usually higher in the growing season than in the non-growing season. Dynamic correction of roughness through seasonal adjustment coefficients.

[0123] The surface water retention resistance coefficient is obtained by normalizing the weighted sum of the surface runoff resistance component, the water infiltration resistance component, and the water retention resistance component. The weighted sum calculation formula is:

[0124] The original value of the surface water retention resistance coefficient = w1 x the surface runoff resistance component + w2 x the water infiltration resistance component + w3 x the water retention resistance component

[0125] where w1, w2, w3 are weight coefficients, satisfying w1+w2+w3=1. The weight coefficients are determined by the relative importance of regional rainfall characteristics and surface conditions. In areas with high rainfall intensity, the weight of the surface runoff resistance component is increased. In areas with complex soil structure, the weight of the water infiltration resistance component is increased. In areas with high vegetation coverage, the weight of the water retention resistance component is increased. Normalization processing uses the Min-Max method to map the original value to the [0, 1] interval, facilitating comparison and comprehensive evaluation of different regions.

[0126] The surface water retention resistance coefficient, as a comprehensive index for evaluating the water retention capacity of the region, reflects the combined effect of topography, soil, and surface cover on water retention, and is an important part of determining the potential of water resources circulation. In the calculation process of the resistance coefficient, the interactions between factors are also considered, such as the synergistic effect of slope and roughness, the nonlinear relationship between soil permeability and moisture content, etc. The calculation results are adjusted through correction terms to improve the accuracy of the evaluation.

[0127] In this embodiment, according to the daily variation characteristics of evaporation in the regional microclimate data, the detailed implementation steps for determining the irrigation time period and irrigation amount of the irrigation mode can include:

[0128] Time series analysis is performed on the evaporation in the regional microclimate data to obtain the evaporation daily variation curve at each time node. Time series analysis uses moving average or polynomial fitting methods to extract continuous daily variation patterns from discrete observation data. The evaporation daily variation curve describes the evaporation intensity at different times of the day and is an important basis for determining the optimal irrigation time. The time window for time series analysis is determined by regional climate characteristics and irrigation management needs, typically analyzing 7-15 days of data, which takes into account short-term changes in weather conditions while avoiding excessive complexity due to too much data.

[0129] In the evaporation daily variation curve, the time period with evaporation less than the preset evaporation threshold is extracted as the candidate irrigation time period. The preset evaporation threshold is usually set to 40%-60% of the daily maximum evaporation, ensuring that irrigation is performed during periods of relatively weak evaporation to reduce water loss. The determination of the candidate irrigation time period also takes into account operational convenience and resource constraints, typically selecting consecutive time periods as the irrigation window to facilitate efficient operation of the irrigation system. The preset evaporation threshold is determined by a function of regional climate type and transpiration characteristics of the target vegetation, with differentiated threshold setting strategies for different regions and different vegetation types.

[0130] According to the soil moisture mean value of the soil moisture distribution data in the candidate irrigation time period, the water replenishment demand is calculated. The water replenishment demand is the additional water input required to maintain normal growth of vegetation and is the basis for determining the irrigation amount. The calculation formula is:

[0131] The water replenishment demand quantity = the field water holding capacity * the effective soil layer thickness * (the target relative water content - the current relative water content); wherein the field water holding capacity is a soil characteristic parameter, reflecting the maximum water holding capacity of the soil; the effective soil layer thickness is the main soil layer thickness in which the plant root system is active; the target relative water content is the minimum soil water content for maintaining normal growth of the plant, and is usually set to be 60%-80% of the field water holding capacity; and the current relative water content is the actual water content of the soil before irrigation. The calculation of the water replenishment demand quantity also takes into account the water consumption characteristics and growth stage of the plant, and the water demand of the plant is different at different growth stages, and the target relative water content is adjusted through a plant growth coefficient to achieve fine irrigation.

[0132] The irrigation amount of the irrigation mode is determined according to the ratio of the water replenishment demand quantity to the water resource circulation potential. The irrigation amount is the amount of water resources input in a single irrigation, and directly affects the irrigation efficiency and the growth condition of the vegetation. The calculation formula is:

[0133] The irrigation amount = the water replenishment demand quantity * (1-μ*the water resource circulation potential);

[0134] wherein μ is an adjustment coefficient, which is determined by a function of the regional water resource scarcity degree and the vegetation drought tolerance. The formula makes the irrigation amount in a region with high water resource circulation potential to be reduced, so as to make full use of natural water circulation; and the irrigation amount in a region with low water resource circulation potential to be increased, so as to ensure the water demand of the vegetation. The determination of the irrigation amount also takes into account the efficiency loss of the irrigation system, and the calculation result is corrected through an irrigation efficiency coefficient, so as to ensure that the effective water input meets the demand.

[0135] In addition to the irrigation time period and the irrigation amount, the irrigation mode also includes the setting of the irrigation frequency and the irrigation method. The irrigation frequency is determined by the ratio of the soil water consumption rate to the plant drought tolerance, and the irrigation frequency needs to be increased in a region with fast water consumption or poor drought tolerance; and the irrigation method is selected according to the regional topographic conditions, the water resource characteristics and the vegetation demand, and appropriate technical solutions such as drip irrigation, micro-sprinkling irrigation or infiltration irrigation are selected, and the irrigation method with good water-saving effect is preferentially selected. The overall design of the irrigation mode follows the dual principles of efficient use of water resources and healthy growth of vegetation, and the best balance between water resource input and ecological benefit is achieved through dynamic adjustment strategies.

[0136] Through the above implementation mode, the application realizes the organic combination of water resource circulation and ecological restoration, maximizes the water resource utilization efficiency and the ecological restoration effect through accurate identification of the water resource retention area and optimization of the water resource allocation, and significantly improves the recovery ability and sustainability of the ecological system in the desert area.

[0137] It should be noted that the above formulas are all dimensionless values, and the formulas are obtained by software simulation of a large amount of data to obtain a formula closest to the actual situation. The preset parameters and threshold values in the formula are set by a person skilled in the art according to the actual situation.

[0138] It should be understood that the above description is only the preferred embodiment of the application, the protection scope of the application is not limited to the above-described embodiments, and any technical solutions falling within the idea of the application shall fall within the protection scope of the application. It should be noted that for ordinary technical users in the technical field, some improvements and refinements without departing from the principles of the application shall be considered as the protection scope of the application.

Claims

1. A desert area ecological restoration coupled water resource recycling method, characterized in that, The method comprises the following steps: acquiring soil moisture distribution data, vegetation coverage data and regional microclimate data of each time node in the monitoring range of the desert area; constructing a water-vegetation coupling spatial dynamic model according to the spatial and temporal variation characteristics of the water gradient in the soil moisture distribution data and the spatial distribution characteristics of the vegetation in the vegetation coverage data, and obtaining a suspected water resource retention area; acquiring the water resource circulation potential of each suspected water resource retention area according to the fluctuation characteristics of rainfall, evaporation and wind speed in the regional microclimate data of adjacent time nodes in the analysis period of each time node, in combination with the terrain slope, soil permeability and surface roughness of the suspected water resource retention area; screening an actual water resource optimal utilization area based on the water resource circulation potential; dynamically adjusting the vegetation planting density, vegetation species and irrigation mode of the actual water resource optimal utilization area according to the water resource circulation potential of the actual water resource optimal utilization area of each time node, and acquiring the ecological restoration gain coefficient of the corresponding area; and optimizing the water resource utilization efficiency and ecological restoration effect of the water resource circulation system based on the ecological restoration gain coefficient.

2. The method according to claim 1, wherein, The method comprises the following steps: spatially and temporally interpolating the soil moisture distribution data to obtain a soil moisture gradient field of each time node; and extracting a water convergence area according to the direction and amplitude of the water gradient in the soil moisture gradient field; calculating the local aggregation degree of vegetation coverage based on the spatial distribution characteristics of the vegetation in the vegetation coverage data; and constructing a water-vegetation coupling spatial dynamic model based on the local aggregation degree and the spatial overlap degree of the water convergence area; in the water-vegetation coupling spatial dynamic model, the water convergence area with a spatial overlap degree greater than a preset overlap threshold is recorded as a suspected water resource retention area.

3. The method according to claim 1, wherein, The method comprises the following steps: performing time series decomposition on the rainfall, evaporation and wind speed in the regional microclimate data of adjacent time nodes in the analysis period of each time node to obtain corresponding rainfall fluctuation components, evaporation fluctuation components and wind speed fluctuation components; calculating a water dynamic balance index of the suspected water resource retention area according to the difference between the rainfall fluctuation component and the evaporation fluctuation component, in combination with the disturbance effect of the wind speed fluctuation component on water migration; constructing a surface water retention resistance coefficient according to the terrain slope, soil permeability and surface roughness of the suspected water resource retention area; normalizing the product of the water dynamic balance index and the surface water retention resistance coefficient to obtain the water resource circulation potential of each suspected water resource retention area.

4. The method according to claim 1, wherein, The method comprises the following steps: sorting the water resource circulation potential of all suspected water resource retention areas, and recording the suspected water resource retention area with a water resource circulation potential greater than a preset potential threshold as a candidate water resource optimal utilization area; calculating time stability of the water resource circulation potential of each of the candidate water resource optimized utilization areas, the time stability being an inverse of a standard deviation of the water resource circulation potential within an analysis period; taking a weighted sum of the water resource circulation potential and the time stability as a screening index, and recording a candidate water resource optimized utilization area with the screening index greater than a preset screening threshold as an actual water resource optimized utilization area.

5. The method according to claim 1, wherein, the dynamic adjustment of the vegetation planting density, the vegetation type and the irrigation mode of the actual water resource optimized utilization area comprises: determining an initial value of the vegetation planting density according to the water resource circulation potential of the actual water resource optimized utilization area; obtaining a water supply stability coefficient according to a ratio of the average soil humidity of the actual water resource optimized utilization area in the soil humidity distribution data to the rainfall in the regional microclimate data; dynamically adjusting the vegetation planting density according to a product of the water supply stability coefficient and the water resource circulation potential; determining a drought resistance grade of the vegetation type according to the terrain slope and the soil permeability of the actual water resource optimized utilization area, and dynamically adjusting the vegetation type based on a matching degree of the drought resistance grade and the water resource circulation potential; determining an irrigation time period and an irrigation amount of the irrigation mode according to a daily variation feature of the evaporation amount in the regional microclimate data, and dynamically correcting the irrigation amount based on the water resource circulation potential.

6. The method according to claim 1, wherein, the obtaining of the ecological restoration gain coefficient of the corresponding area comprises: obtaining a vegetation coverage gain value according to a variation amount of the vegetation coverage of the actual water resource optimized utilization area in the vegetation coverage data at adjacent time nodes; obtaining a soil humidity improvement value according to a variation amount of the average soil humidity of the actual water resource optimized utilization area in the soil humidity distribution data at adjacent time nodes; obtaining an erosion inhibition value according to a variation amount of the average wind speed of the actual water resource optimized utilization area in the regional microclimate data at adjacent time nodes; normalizing a weighted sum of the vegetation coverage gain value, the soil humidity improvement value and the erosion inhibition value to obtain the ecological restoration gain coefficient.

7. The method according to claim 1, wherein, the optimization of the water resource utilization efficiency and the ecological restoration effect of the water resource circulation system based on the ecological restoration gain coefficient comprises: adjusting an irrigation frequency of the irrigation mode of the actual water resource optimized utilization area according to a ratio of the ecological restoration gain coefficient to a preset gain threshold value; dynamically adjusting an upper limit value of the vegetation planting density of the actual water resource optimized utilization area according to a product of the ecological restoration gain coefficient and the water resource circulation potential; predicting a future variation trend of the water resource circulation potential of the actual water resource optimized utilization area according to a time variation trend of the ecological restoration gain coefficient, and optimizing a water resource allocation strategy of the water resource circulation system based on the future variation trend.

8. The method according to claim 2, wherein, the calculation of the local aggregation degree of the vegetation coverage comprises: performing grid division on the vegetation coverage data to obtain a vegetation coverage average value of each grid; Calculate the mean value of vegetation coverage of each grid and the standard deviation of the mean value of vegetation coverage of its adjacent grids as the local fluctuation value of vegetation coverage of the grid; Take the reciprocal of the local fluctuation value of vegetation coverage as the local aggregation degree of vegetation coverage of the grid.

9. The method according to claim 3, wherein, The constructed surface water retention resistance coefficient comprises: According to the terrain slope of the suspected water resource retention area, calculate the surface runoff resistance component; According to the soil permeability of the suspected water resource retention area, calculate the water infiltration resistance component; According to the surface roughness of the suspected water resource retention area, calculate the water retention resistance component; The weighted sum of the surface runoff resistance component, the water infiltration resistance component and the water retention resistance component is normalized to obtain the surface water retention resistance coefficient.

10. The method according to claim 5, wherein, According to the daily variation characteristics of the evaporation in the regional microclimate data, determine the irrigation time period and the irrigation amount of the irrigation mode, comprising: Perform time series analysis on the evaporation in the regional microclimate data to obtain the evaporation daily variation curve of each time node; In the evaporation daily variation curve, extract the time period in which the evaporation is less than the preset evaporation threshold as the candidate irrigation time period; According to the mean value of soil moisture of the soil moisture distribution data in the candidate irrigation time period, calculate the water replenishment demand; According to the ratio of the water replenishment demand to the water resource circulation potential, determine the irrigation amount of the irrigation mode.

Images