Irrigation regulation method and system based on plant growth and water use

Abstract

The application provides an irrigation control method and system based on plant growth and water utilization, and relates to the technical field of ecological restoration.The method comprises the following steps: monitoring the weather conditions and soil water content of a planting area; generating an irrigation control strategy and executing the strategy based on the weather parameters obtained through monitoring and the deviation between the current soil water content and a preset irrigation threshold; wherein the target native plant species contained in the planting area is not less than one, and the irrigation threshold is determined in advance based on the growth and water utilization characteristics of the target native plant.The technical scheme of the application realizes the goal of accurate irrigation in the process of vegetation ecological restoration in alpine regions by determining the irrigation threshold in advance by combining the growth and water utilization characteristics of plants and executing the irrigation strategy according to the real-time monitoring of soil water content and weather parameters.Compared with the traditional flood irrigation mode, the application significantly improves the utilization rate of water resources and is conducive to ensuring the efficiency of ecological restoration.

Description

Technical Field

[0001] This application relates to the field of ecological restoration technology, specifically to an irrigation regulation method and system based on plant growth and water use. Background Technology

[0002] In the process of realizing this invention, the inventors discovered that in vegetation ecological restoration, the survival of native plants and the stability of the community depend on the precise regulation of soil moisture. In high-altitude and cold ecological environments, relevant native plant species have strict water requirements; too little water leads to seedling death, while too much water damages the root microenvironment. In existing related technologies, irrigation techniques are extensive and lack dynamic response to the water requirement threshold of native plants. The amount of water often far exceeds the actual demand, which not only wastes water resources and exacerbates the supply-demand imbalance, but also induces slope erosion due to soil saturation, and even triggers disasters such as landslides, threatening engineering and ecological safety.

[0003] Therefore, for the above-mentioned vegetation ecological restoration application scenarios, proposing an intelligent irrigation technology that matches the water threshold of native plants and adapts to the geographical environment is the core support for improving restoration efficiency and an urgent need to ensure the effective implementation of the project. Summary of the Invention

[0004] To at least partially overcome the problems existing in related technologies, embodiments of this application provide an irrigation regulation method and system based on plant growth and water use, which precisely irrigates plants based on a predetermined irrigation threshold and in combination with the actual soil moisture content.

[0005] First aspect

[0006] Some embodiments of this application provide an irrigation regulation method based on plant growth and water use, the irrigation regulation method comprising:

[0007] Monitor the weather conditions and soil moisture content in the plant planting area;

[0008] Based on the weather parameters obtained from monitoring, and the deviation between the current soil moisture content and the preset irrigation threshold, an irrigation regulation strategy is generated and executed.

[0009] The planting area contains at least one target native plant species, and the irrigation threshold is predetermined based on the growth and water use characteristics of the target native plants.

[0010] Second aspect

[0011] Some embodiments of this application provide an irrigation control system based on plant growth and water use, the irrigation control system comprising:

[0012] The monitoring module is used to monitor the weather conditions and soil moisture content in the plant planting area;

[0013] The control execution module is used to generate and execute irrigation regulation strategies based on the weather parameters obtained from monitoring and the deviation between the current soil moisture content and the preset irrigation threshold.

[0014] The planting area contains at least one target native plant species, and the irrigation threshold is predetermined based on the growth and water use characteristics of the target native plants.

[0015] The irrigation control method based on plant growth and water use provided in this application includes: monitoring the weather conditions and soil moisture content of the planting area; generating and executing an irrigation control strategy based on the difference between the monitored weather parameters and the current soil moisture content and a preset irrigation threshold; the planting area contains at least one target native plant species, and the irrigation threshold is predetermined based on the growth and water use characteristics of the target plants. In this application's technical solution, by pre-determining the irrigation threshold based on the growth and water use characteristics of the target native plants, and by implementing a targeted irrigation strategy based on real-time monitored soil moisture content and weather parameters, the goal of precise irrigation in the ecological restoration of vegetation in high-altitude and cold regions is achieved. Compared to the traditional small-scale flood irrigation model, this invention significantly improves water resource utilization and is beneficial for ensuring the efficiency of ecological restoration. Attached Figure Description

[0016] Figure 1 A flowchart illustrating an irrigation regulation method based on plant growth and water use provided in one embodiment of this application;

[0017] Figure 2 This is a flowchart illustrating the process of determining the baseline irrigation threshold for a target native plant in one embodiment of this application.

[0018] Figure 3 A schematic diagram of the structure of an irrigation control system based on plant growth and water use provided in one embodiment of this application;

[0019] Figure 4 This is a fitting curve of a partial response model constructed based on planting experiment data in one embodiment of this application;

[0020] Figure 5 This is a fitting curve of a partial response model constructed based on planting experiment data in one embodiment of this application;

[0021] Figure 6 This is a fitting curve of a partial response model constructed based on planting experiment data in one embodiment of this application;

[0022] Figure 7This is a fitting curve of a partial response model constructed based on planting experiment data in one embodiment of this application. Detailed Implementation

[0023] To make the purpose, technical solution and advantages of this application clearer, the technical solution of this application will be described in detail below.

[0024] In the ecological restoration of vegetation in the high-altitude and ecologically fragile areas of western my country, the survival and community stability of native plants depend on the precise regulation of soil moisture. In the high-altitude ecological environment of the Qinghai-Tibet Plateau and surrounding areas, native plant species have strict water requirements; too little water leads to seedling death, while excessive water damages the root microenvironment. Existing irrigation technologies are crude and lack dynamic response to the water requirements of native plants, often resulting in water volumes far exceeding actual needs. This wastes water resources, exacerbates the supply-demand imbalance, and induces slope erosion due to soil saturation, even triggering landslides and other disasters, threatening project and ecological safety. Therefore, for the aforementioned vegetation ecological restoration application scenarios, proposing an intelligent irrigation technology that matches the water requirements of native plants and adapts to the geographical environment is a core support for improving restoration efficiency and an urgent need to ensure the effective implementation of projects.

[0025] Based on this, in one embodiment, such as Figure 1 As shown, the irrigation regulation method based on plant growth and water use proposed in this application includes:

[0026] Step S110: Monitor the weather conditions and soil moisture content of the planting area;

[0027] In practice, multiple soil moisture sensors can be buried at representative locations to monitor soil moisture content, based on the topography of the planting area and the distribution characteristics of the actual planted plants. Considering the characteristics of high-altitude and cold regions, low-temperature resistant sensor equipment needs to be selected.

[0028] Regarding weather monitoring, weather parameters can be monitored in real time by setting up weather stations in or near the planting area. Specifically, considering the characteristics of high-altitude and cold regions and the requirements of the technical solution in this application, the weather parameters here include, but are not limited to, rainfall intensity, photosynthetically active radiation, and wind speed.

[0029] Based on step S110, step S120 is performed, whereby an irrigation control strategy is generated and executed based on the weather parameters obtained from monitoring and the deviation between the current soil moisture content and the preset irrigation threshold. It should be noted that the planting area here contains no less than one type of target native plant, and the irrigation threshold is predetermined based on the growth and water use characteristics of the target native plants.

[0030] As described in the background section of this application, the target native plants refer to the native plants used in the ecological restoration of high-altitude and cold regions in this application scenario. These plants can effectively adapt to the environment of high-altitude and cold regions and meet the purpose of ecological restoration. For example, the target native plants in this application may include: white thorn flower, hairy wormwood, small blue plumbago, small-leaved vitex, etc.

[0031] Considering the high uncertainty and variability of many factors in the actual planting environment, such as rainfall and wind speed, making it difficult to accurately predict and handle changes in these variables, and taking into account the implementation costs of comprehensive engineering practice, this application can generate and execute irrigation regulation strategies based on fuzzy control.

[0032] As a further specific implementation method, in the implementation of fuzzy control logic, a fuzzy control rule base is constructed based on the deviation between the current soil moisture content and the irrigation threshold, combined with weather parameters, such as rainfall intensity, photosynthetically active radiation, and wind speed.

[0033] The technical solution of this application pre-determines irrigation thresholds by combining the growth and water use characteristics of the target native plants, and executes targeted irrigation strategies based on real-time monitored soil moisture content and weather parameters, achieving the goal of precise irrigation in the ecological restoration of vegetation in high-altitude and cold regions. Compared with the traditional small-scale flood irrigation mode, this invention significantly improves water resource utilization and reduces water waste caused by excessive irrigation. The introduction of fuzzy control logic to implement irrigation regulation strategies enables more flexible responses to complex environmental changes. Based on the deviation and rate of change between the current soil moisture content and the irrigation threshold, and combined with a fuzzy control rule base constructed from various weather parameters, irrigation decisions become more intelligent and refined, improving the system's adaptability and response speed.

[0034] To facilitate understanding of the technical solution of this application, the method for pre-determining the irrigation threshold in this application will be described below.

[0035] In this application's technical solution, the irrigation threshold is predetermined based on the growth and water use characteristics of the target native plants (such as *Nitraria tangutorum* and *Artemisia annua* mentioned above). In this application scenario, for ecological vegetation restoration considerations, there are generally multiple target native plants within a planting area, and the growth and water use characteristics of each target native plant may differ. To further achieve precise irrigation, in some embodiments, the process of pre-determining the irrigation threshold includes:

[0036] Water use characteristics planting experiments were conducted for each target native plant species to determine the threshold system data for the corresponding target native plant species. The threshold system data includes the baseline irrigation threshold range. When there are two or more target native plant species in the planting area, the baseline irrigation threshold range for the corresponding target native plant species was analyzed based on the actual species composition of the target native plants in the planting area. The common (threshold) interval of each baseline irrigation threshold range was selected as the irrigation threshold to ensure the implementation effect of the restoration project in the overall area.

[0037] Furthermore, such as Figure 2 As shown, in some embodiments, the process of conducting a water use characteristics planting experiment on any type of target native plant includes:

[0038] Step S210: The target native plants (such as white thorn flowers) are planted in greenhouses and pots, and multiple planting test groups are constructed based on the preset soil moisture content gradient distribution.

[0039] The use of greenhouse pot cultivation is primarily for rain protection, facilitating the study and confirmation of the target native plant's growth and water use characteristics. To facilitate subsequent data analysis, multiple planting experimental groups need to be constructed based on a pre-defined soil moisture content gradient distribution. Specifically, considering the potential range and accuracy requirements of soil moisture content in real-world scenarios, the soil moisture content gradient distribution is defined as 35% FC, 50% FC, 65% FC, 80% FC, and 95% FC, corresponding to five planting experimental groups. During the experiment, intelligent irrigation equipment is used for automatic water replenishment, combined with a soil moisture controller to ensure that the moisture content remains within the set gradient range.

[0040] Furthermore, to ensure that the obtained research data is more general, each experimental group has at least two planting pots, and each planting pot has at least two sample plants. For example, here we use five planting pots in one experimental group, with two sample plants in each planting pot.

[0041] Based on the planting sample group constructed in step 210, a planting experiment was conducted. Data was collected after the plants grew to a certain growth stage. It should be noted that plant growth stages generally include multiple stages, but the stage from seedling to growth stage has relatively stringent water requirements. Considering the actual engineering application needs, this application focuses on the research of the stage from seedling to growth stage, where irrigation requirements are relatively stringent in practice.

[0042] That is, corresponding to step S220, after the plant leaves have grown to mature leaves, water control treatment is carried out for each experimental group. When the treatment reaches the corresponding soil moisture content target, the sample plant leaves are measured to obtain the photosynthetic parameters of each sample in the corresponding group and to determine other target parameters based on the photosynthetic parameters.

[0043] For step S220, in practice, a portable photosynthesis measurement system (such as Li-6400) can be used to collect relevant photosynthetic parameters. Specifically, the photosynthetic growth parameters here include net photosynthetic rate (Pn), transpiration rate (Tr), stomatal conductance (Gs), intercellular CO2 concentration (Ci), etc. Other target parameters here include instantaneous water use efficiency (WUE, also known as WUEinst), intrinsic water use efficiency (WUEi), intercellular-environment CO2 concentration ratio (Ci / Ca), and stomatal limitation value (Ls).

[0044] In terms of specific operations, to ensure the usability of the measured data, the process of measuring relevant parameters of the sample plant leaves includes: for each of the five planting pots in each experimental group, for the two plants in each pot, one leaf is randomly selected from each plant and measured three times to determine the sample data. That is, each experimental group has 5 planting pots, 2 plants in each pot, 1 leaf is selected from each plant, and 3 readings are recorded for each leaf to obtain the required data (net photosynthetic rate, transpiration rate, etc.). In this process, the leaves should be healthy, sun-facing, and mature leaves. In this way, 30 sample data can be obtained for one experimental group.

[0045] For example, after a certain measurement, the relevant photosynthetic parameters of white thorn flower were obtained (the intensity of the photosynthetically active radiation was 1200 μmol·m⁻¹). -2 ・s -1 The environmental factor data are shown in Table 1 below:

[0046] Table 1. Summary Table of Partial Sample Data

[0047]

[0048] It should be noted that the data in Table 1 above are all directly measured data. Based on such data, other target parameters such as instantaneous water use efficiency (WUE), intrinsic water use efficiency (WUEi) (dimensionless), intercellular-environment CO2 concentration ratio (Ci / Ca) (ratio, dimensionless), and stomatal limitation value (Ls) (dimensionless) can be indirectly calculated and determined. Specifically, the calculation formulas involved in the determination process include WUE=Pn / Tr, WUEi=Pn / Gs, Ls=1-Ci / Ca, etc. The data of other target parameters obtained are shown in Table 2 below.

[0049] Table 2. Summary Table of Some Other Target Parameter Data

[0050]

[0051] After obtaining the above-mentioned relevant parameter data, step S230 is performed to construct sample datasets under various preset soil moisture content gradients based on the acquired and determined parameter data, and to determine the benchmark irrigation threshold range for the target native plant species based on the sample datasets.

[0052] In the technical scenario of this application, the net photosynthetic rate Pn is the rate at which plant leaves fix CO2 through photosynthesis minus the rate at which CO2 is released through respiration. It is a direct reflection of the plant's photosynthetic capacity, and a higher value indicates stronger photosynthesis.

[0053] Instantaneous water use efficiency (WUE) is the ratio of photosynthetic rate to transpiration rate in plant leaves. This index represents the amount of carbon fixation corresponding to a unit of transpiration water consumption, but it is easily affected by instantaneous environmental conditions (such as temperature and humidity).

[0054] Intrinsic water use efficiency (WUEi) is the ratio of plant leaf photosynthetic rate to stomatal conductance. It reflects the carbon-water tradeoff under stomatal constraints. This index eliminates the influence of environmental water vapor pressure difference and can more directly reflect the intrinsic regulatory efficiency of plant stomata on carbon-water exchange.

[0055] The stomatal limitation value Ls = 1 - Ci / Ca. Ci / Ca reflects the relative relationship between the internal CO2 supply and external CO2 demand of the leaf. Changes in this ratio are a key diagnostic tool for judging the decline in photosynthetic rate. Furthermore, Ls can quantify the degree of limitation on photosynthesis caused by stomatal closure. The larger the Ls value, the stronger the stomatal limitation.

[0056] The aforementioned different indicators are all key indicators reflecting plant function. In this application, in order to comprehensively judge the plant condition and the immediate "irrigation benefits", a comprehensive index is constructed to determine the benchmark irrigation threshold, so as to reduce the risk of a single indicator misleading irrigation decision-making bias.

[0057] Specifically, the sample dataset here includes data on net photosynthetic rate, instantaneous water use efficiency, intrinsic water use efficiency, and stomatal limitation values. The process of determining the baseline irrigation threshold range for this target native plant species based on the sample dataset includes:

[0058] Normalize the various parameter values ​​for each soil moisture content gradient in the sample dataset to obtain normalized parameters.

[0059] It should be noted here that, due to the different units and dimensions of the various parameters, the normalization process here aims to unify them to the range of 0 to 1 for easier subsequent weighting. For example, based on the following expression, the min-max normalization method is used for normalization.

[0060] (1)

[0061] In expression (1), This represents the normalized value. Represents the original value. and These represent the minimum and maximum values ​​in the corresponding type parameters, respectively.

[0062] Subsequently, based on the preset weighting coefficient system, the normalized parameters under each soil moisture content gradient are calculated using a weighted function to obtain comprehensive index parameter values ​​that characterize the overall condition of the plants.

[0063] The weighting coefficients reflect the relative importance of each parameter to the irrigation threshold decision. The weighting coefficient system in this application can be determined based on expert experience. Net photosynthetic rate (Pn), WUE, and WUEi are all positive indicators and should be assigned positive weights, while Ls has a negative impact and should be assigned negative weights or deducted during construction. For example, the comprehensive index parameters can be determined based on the following expression:

[0064] (2)

[0065] In expression (2), This represents the composite index parameter value determined for the j-th sample group. These represent the normalized parameter values ​​for instantaneous water use efficiency, intrinsic water use efficiency, net photosynthetic rate, and stomatal limitation in this sample group, respectively. to This represents the corresponding weight value, and the sum of the weight values ​​is 1.

[0066] For example, in the technical scenario of this application, the objective prioritizes water conservation, and the weighting used is... to The values ​​are 0.4, 0.3, 0.3, and 0.2, respectively.

[0067] Next, based on the data of each comprehensive index parameter, with the comprehensive index parameter as the dependent variable and the corresponding soil moisture content as the independent variable, a relationship response model is constructed. For example, the relationship response model can be constructed by regression fitting.

[0068] Based on this relational response model, the continuous soil moisture content range corresponding to a preset percentage where the comprehensive index value is not lower than its maximum value is determined as the baseline irrigation threshold range for the target native plant. Specifically, the highest comprehensive index value Smax is found using the curve corresponding to the relational response model, and then a percentage (e.g., 90%) is taken down. All continuous soil moisture content points corresponding to a comprehensive score greater than 0.9 * Smax constitute the baseline irrigation threshold range (range), serving as one of the threshold indicators in the threshold system data.

[0069] As in one embodiment, Figure 7 The legend in the figure is the fitted curve (line graph) of the relational response model constructed with the composite index parameter as the dependent variable. In this legend, the maximum value of the composite index corresponds to an RSWC of 0.65.

[0070] In one embodiment, the final determined baseline irrigation threshold range is as follows: for Plumbago spp., the baseline irrigation threshold range is 73.4%-85.5%FC; for Vitex negundo, the baseline irrigation threshold range is 78.8%-85.3%FC.

[0071] It should be noted that in the technical solution of this application, the benchmark irrigation threshold range determined by the above method, and the irrigation threshold for the planting area obtained therefrom, are essentially soil mass moisture content. However, in the implementation of the technical solution of this application, in order to ensure real-time control, the current soil moisture content is the soil volumetric moisture content data obtained by real-time monitoring through in-situ sensors. Based on this, the deviation between the current soil moisture content and the preset irrigation threshold in this application is determined by the following method: based on the soil bulk density parameter of the planting area, the soil volumetric moisture content data is converted into soil mass moisture content, such as by using the expression of volumetric moisture content = mass moisture content × soil bulk density ÷ water density; then, the difference between the soil mass moisture content and the irrigation threshold is calculated to determine the deviation between the two.

[0072] Based on the technical scenario of ecological vegetation restoration in this application, engineering practice generally requires various soil improvements to the planting area. During this process, the soil bulk density parameters need to be adjusted for the actual planting area to ensure the final irrigation effect. Furthermore, during the adjustment process, basic parameters can be measured based on laboratory tests and corrected according to the slope of the planting area to determine the actual soil bulk density parameters to be used.

[0073] On the other hand, as described in the previous embodiments, this application takes into account that many factors in the actual planting environment, such as rainfall and wind speed, have high uncertainty and variability, making it difficult to accurately predict and handle the changes in these variables. In addition, considering the actual implementation cost of the project, this application generates and executes irrigation control strategies based on fuzzy control. The overall framework for the implementation of fuzzy control is a publicly available technical principle in the prior art. This application only briefly describes some improvements that are closely related to the scenario of this application in the specific implementation.

[0074] As a specific implementation method, in the implementation of fuzzy control logic, based on the deviation e between the current soil moisture content and the lower limit of the irrigation threshold, a fuzzy control rule base is constructed in combination with weather parameters. According to the characteristics of the overall low and relatively stable temperature in the high-altitude cold region in this application scenario, the weather parameters here only include rainfall intensity P, photosynthetically active radiation R and wind speed W, without considering other weather factors such as temperature.

[0075] Based on the actual scenario of this application, the fuzzification configuration for the weather parameters is as follows:

[0076] Rainfall intensity P: categorized into {heavy rainfall (>10mm / h), moderate rain (5-10mm / h), light rain (1-5mm / h), no rain (<1mm / h)}, using a trapezoidal membership function; Photosynthetically active radiation R: categorized into {high radiation (>600W / m²)} 2 Medium radiation (200-600W / m) 2 Low radiation (<200W / m) 2 The Gaussian membership function is used for wind speed W: it is divided into {strong wind (>5m / s), moderate wind (2-5m / s), weak wind (<2m / s)}, and the Z-type and S-type combined membership functions are used.

[0077] In the corresponding implementation, the fuzzy control rule base can be flexibly selected according to the irrigation equipment. For example, in some implementation scenarios, the irrigation equipment includes sprinkler irrigation and drip irrigation equipment, and the fuzzy control rule base can contain the following core rules:

[0078] Rule 1: If e = negative (NB) and the predicted rainfall intensity P ≥ 8 mm / h in the next 3 hours, the pre-irrigation compensation mode is triggered: the irrigation amount is adjusted to 70% of the normal amount, and irrigation must be completed 1 hour before the start of rainfall;

[0079] Rule 2: If e = negative small (NS) and photosynthetically active radiation R = high radiation, then trigger the light-avoidance irrigation mode: turn off sprinkler irrigation and switch to drip irrigation; the single irrigation amount is corrected relative to the baseline irrigation amount as: Qadj = Qbase * [1 - 0.2 * (R - 600) / 400];

[0080] Rule 3: If the wind speed W = strong wind, the wind erosion protection mechanism will be forcibly activated: immediately terminate sprinkler irrigation operation and increase drip irrigation flow rate to 1.2 times.

[0081] Furthermore, in the process of executing fuzzy control decision-making, this application outputs irrigation duration and flow rate, and satisfies the following physical constraints:

[0082] (3)

[0083] Expression (3), Let be the soil hydraulic conductivity function. This represents the maximum permissible flow rate related to wind speed W. t represents the flow rate, and t represents the irrigation duration.

[0084] It should be noted that the maximum allowable flow rate refers to the dynamic upper limit of the flow rate set under different wind speed conditions to avoid the loss of irrigation water due to wind scattering, evaporation, or surface runoff.

[0085] The soil hydraulic conductivity function is a mathematical relationship describing the change of soil hydraulic conductivity K with soil volumetric water content θ. The soil hydraulic conductivity function is usually obtained by fitting experimental data. For example, it can be obtained by conducting experiments based on the van Genuchten-Mualem model according to the actual soil type. Through the constraint rules shown in the above expression (3), the upper limit of irrigation volume can be calculated according to the movement law of irrigation water in the soil to prevent runoff or waterlogging caused by insufficient hydraulic conductivity. Combined with the determined irrigation threshold, the irrigation strategy can be comprehensively optimized to match the water absorption characteristics of plant roots.

[0086] Based on the above embodiments, compared with the prior art, the technical solution of this application has the following technical advantages:

[0087] By pre-determining irrigation thresholds based on the growth and water use characteristics of target plants and dynamically adjusting irrigation strategies according to real-time monitoring of soil moisture content and weather parameters, this invention achieves precise irrigation for vegetation ecological restoration in high-altitude and cold regions. Compared to traditional flood irrigation, this invention significantly improves water resource utilization and reduces water waste caused by over-irrigation. Precise control of irrigation volume not only avoids soil erosion caused by over-irrigation but also effectively prevents geological disasters such as landslides, protecting the local ecological environment and infrastructure safety. Furthermore, scientific and rational irrigation management promotes healthy vegetation growth and helps accelerate the vegetation restoration process on bare slopes in high-altitude and cold regions. The introduction of fuzzy control logic to generate irrigation regulation strategies enables more flexible responses to complex environmental changes. Based on the deviation between current soil moisture content and irrigation thresholds, a fuzzy control rule base constructed using various weather parameters makes irrigation decisions more intelligent and refined, improving the system's adaptability and response speed. In the process of determining irrigation thresholds, multiple experimental groups were planted using greenhouse pot cultivation, and regression models were established based on the photosynthetic growth parameters of sample plants under different soil moisture gradients. These models provide a scientific basis for accurately setting irrigation thresholds, ensuring that irrigation strategies can meet the needs of plant growth without wasting resources.

[0088] Figure 3 This is a schematic diagram of the structure of an irrigation control system based on plant growth and water use provided in one embodiment of this application, as shown below. Figure 3 As shown, the irrigation control system 300 based on plant growth and water use includes:

[0089] The monitoring module 301 is used to monitor the weather conditions and soil moisture content of the planting area;

[0090] The control execution module 302 is used to generate and execute an irrigation control strategy based on the weather parameters obtained from monitoring and the deviation between the current soil moisture content and the preset irrigation threshold. The planting area contains at least one type of target native plant, and the irrigation threshold is predetermined based on the growth and water use characteristics of the target native plant.

[0091] Regarding the irrigation control system 300 based on plant growth and water use in the above-mentioned embodiments, the specific methods by which each module performs its operations have been described in detail in the embodiments of the relevant method, and will not be elaborated here.

[0092] Furthermore, in some embodiments, when there is only one target native plant species in the planting area, such as only *Rhizoma Cirsium japonicum*, based on the aforementioned planting experiment on the water use characteristics of the target native plant to obtain corresponding photosynthetic parameters and to determine other target parameters based on photosynthetic parameters, the relationship between a certain parameter and soil moisture content can be considered separately, and then comprehensively analyzed to determine the corresponding "threshold". A threshold system composed of multiple determined "thresholds" is then used to achieve refined irrigation control for the target native plant in this engineering scenario. Alternatively, when the planting area contains only one target native plant species, the threshold index is selected as the irrigation threshold from the threshold system data corresponding to the target native plant based on actual irrigation needs.

[0093] For example, based on experimental data of white thorn flower, the relationship between net photosynthetic rate Pn and RSWC is considered separately. That is, based on the data obtained from the planting experiment, with Pn as the dependent variable and the corresponding soil moisture content as the independent variable, a fitting method is used to obtain the relationship response model, as shown below. Figure 4 The response curve shown; similarly, considering the relationship between the stomatal limitation value Ls and RSWC alone, we can obtain the following: Figure 5 The response curve shown; considering the relationship between instantaneous water use efficiency (WUE) and RSWC separately, the following can be obtained: Figure 6 The response curve is shown.

[0094] comprehensive Figures 4 to 6 The curve shown can be analyzed as follows:

[0095] Physiologically effective thresholds and high-yield ranges are defined based on net photosynthetic rate (Pn). For example... Figure 4 As shown, a comprehensive characteristic analysis of the net photosynthetic rate response curve can establish two key critical points for plant survival and production. First, the intersection of the analytical curve and the horizontal axis (i.e., Pn=0) determines the relative soil moisture content (RSWC) of 0.2629 as the "theoretical survival baseline" for *Rhizoma Cypripedium spp.*. When soil moisture falls below this threshold, the plant's photosynthetic carbon assimilation rate cannot offset respiration consumption, leading to irreversible physiological mortality. Second, identifying the peak point of the curve, RSWC = 0.7393 is determined as the plant's "physiological high-yield saturation point." Exceeding this threshold, the marginal gain of photosynthetic rate disappears, accompanied by decreased soil aeration and the risk of deep seepage; this can be set as the "high-yield upper limit threshold" for irrigation management. Further calculations using the integral mean value theorem throughout the photosynthetic curve reveal the "effective production moisture range" to be 54.45% to 93.42% for maintaining above the average photosynthetic production level.

[0096] The water stress triggering threshold is defined based on the stomatal limitation value (Ls). When soil moisture content falls below this value (RSWC < 0.50), the stomatal limitation value shows a significant decreasing trend. This trend indicates that with the occurrence of severe drought, the dominant factor limiting photosynthesis has undergone a qualitative change: from simple "stomatal limitation" to "non-stomatal limitation." This judgment is highly coupled with the trend of net photosynthetic rate (Pn) being significantly inhibited in this range in Figure 4, indicating that plants have broken through the stomatal regulatory defense and face the risk of metabolic damage. Therefore, 0.50 is set as the "critical threshold for water stress" to initiate emergency irrigation decisions to avoid irreversible physiological damage to plants.

[0097] Defining high-efficiency water use points based on water use efficiency (WUE). Water use efficiency (WUE) characterizes the sensitivity of plants to short-term water changes and the productivity of a single unit of water (e.g., Figure 6 (As shown). Based on curve optimization, the "peak point of water-efficient use" for *Rhizoma Cirsium japonicum* was determined to be RSWC = 0.6288. This point represents the optimal water state for achieving maximum biomass output per unit of water input. Simultaneously, through integral calculation, the "high-efficiency regulation range" for maintaining average water use efficiency was determined to be 45.43% to 80.33%.

[0098] Furthermore, as mentioned earlier, in determining the baseline irrigation range using the weighted comprehensive evaluation method, the plant comprehensive index parameters were calculated by weighted summation of normalized parameters under different water gradients, and a line graph showing their variation with RSWC was plotted. Figure 7 The results showed that the comprehensive index reached its global maximum at RSWC = 0.65. The soil moisture content corresponding to this maximum value was defined as the target moisture point for maintaining optimal plant comprehensive function.

[0099] Based on this, a threshold system can be constructed for white thorn flower as shown in Table 3 below (excluding the benchmark irrigation threshold range index).

[0100] Table 3. Summary of Partial Data from the Threshold System of *Rhizoma Cirsium japonicum*

[0101]

[0102] Similarly, a threshold system can be constructed for Artemisia annua as shown in Table 4 below:

[0103] Table 4. Summary of Partial Data for the Threshold System of Artemisia annua

[0104]

[0105] In other words, in one embodiment, the threshold system data shows that for *Rhizoma Cirsium japonicum*, the threshold index corresponding to its high-yield potential zone is 65.00%-93.42%; and for *Artemisia annua*, the threshold index corresponding to its high-efficiency regulation zone is 50%-65%.

[0106] In some embodiments, when the target native plant species included in the planting area is one (such as white thorn flower), a threshold index is selected from the threshold system data corresponding to the target native plant as the irrigation threshold according to the actual irrigation needs (for example, for white thorn flower, the threshold index corresponding to the high-yield potential area is selected, i.e., 65.00%-93.42% is the irrigation threshold).

[0107] Furthermore, based on the data in the two tables above, comparing the physiological and ecological characteristics of these two target plants, it can be seen that: *Artemisia annua*, limited by its relatively low upper limit of water tolerance (87.22%), does not possess the advantage of increased yield under high water conditions and is more suitable as a low-maintenance 'maintainer'; while *Rhizophora stylosa*, with its high photosynthetic peak and extremely strong flood tolerance (tolerating up to 93.42%), has the potential to be a 'pioneer' for rapidly establishing communities under high water input. Therefore, considering the irrigation needs in different scenarios in practice, this application further constructs the target plant functional classification and differentiated irrigation strategy based on physiological threshold characteristics, as shown in the table below, aiming to maximize water resource benefits through 'tailored policies for different plants'.

[0108] Table 5. Comparison of Target Plant Functional Type Classification and Differentiated Irrigation Strategies Based on Physiological Threshold Characteristics

[0109]

[0110] Based on Tables 3-5 above, this application further analyzed the hypothetical mixed planting application scenario of Artemisia annua and Rhizoma Cyathea rubra. It was found that the roles of the two plants (dominant species / companion species) vary depending on the engineering objectives, but the objective differences in their physiological tolerance characteristics (upper limits of moisture tolerance are 87.22% and 93.42%, respectively) always exist. Therefore, a single fixed irrigation standard cannot adapt to all configuration modes; that is, the irrigation adjustment method based on the baseline irrigation threshold range mentioned above is not refined enough. Accordingly, for the mixed planting of these two plants, this invention has formulated three differentiated synergistic regulation strategies guided by 'symbiotic balance', 'water conservation priority', and 'limited high yield', respectively, based on different community construction objectives (see Table 6 for details).

[0111] Table 6. Synergistic water regulation strategies in mixed communities of Artemisia annua and Rhizoma Cirsium japonicum based on interspecific competition-mutualism relationships.

[0112]

[0113] This allows for more precise control of irrigation thresholds based on actual scenario conditions (different mixed planting ratios and engineering objectives) when two target plants (white thorn flower and hairy wormwood) are used, thereby significantly improving water use efficiency and the synergy of crop growth response. It is easy to understand that a similar method can be used to determine irrigation thresholds based on actual conditions for any two target native plants mixed together; however, this application will not elaborate on these methods here.

[0114] The above description is merely a preferred embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0115] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0116] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. An irrigation regulation method based on plant growth and water use, applied to vegetation ecological restoration in high-altitude and cold regions, characterized in that, include: Monitor the weather conditions and soil moisture content in the planting area; Based on the weather parameters obtained from monitoring, and the deviation between the current soil moisture content and the preset irrigation threshold, fuzzy control logic is used to generate and execute irrigation regulation strategies. The planting area contains at least one type of target native plant; the irrigation threshold is predetermined based on the growth and water use characteristics of the target native plant. The predetermined process includes: conducting water use characteristic planting experiments for each type of target native plant to determine the threshold system data for the corresponding type of target native plant. The threshold system data includes a baseline irrigation threshold range. The target native plant species include: *Plumbago spp.*, *Vitex negundo*, *Hymenochloa chinensis*, and *Artemisia annua*. In the threshold system data: for *Plumbago spp.*, the baseline irrigation threshold range is 73.4%-85.5%FC; for *Vitex negundo*, the baseline irrigation threshold range is 78.8%-85.3%FC; for *Hymenochloa chinensis*, the threshold index corresponding to its high-yield potential zone is 65.00%-93.42%; and for *Artemisia annua*, the threshold index corresponding to its high-efficiency regulation zone is 50%-65%. When the target native plant species contained in the planting area is one, the threshold index is selected from the threshold system data corresponding to the target native plant as the irrigation threshold according to the actual irrigation needs; when the target native plant species contained in the planting area is two or more, the baseline irrigation threshold range of the corresponding target native plants is analyzed according to the actual species composition of the target native plants in the planting area, and the common interval of each baseline irrigation threshold range is selected as the irrigation threshold. The current soil moisture content is the soil volumetric moisture content data obtained in real time through in-situ sensor monitoring; the deviation between the current soil moisture content and the preset irrigation threshold is determined by the following method: based on the soil bulk density parameter of the planting area, the soil volumetric moisture content data is converted into soil mass moisture content, and the soil bulk density parameter is adjusted for the actual planting area; the deviation between the soil mass moisture content and the irrigation threshold is determined by calculating the difference between the two. The fuzzy control rule base is constructed based on the deviation between the current soil moisture content and the irrigation threshold, as well as weather parameters, which include only rainfall intensity, photosynthetically active radiation, and wind speed. During the execution of the fuzzy control decision, the irrigation duration and flow rate are output, satisfying the following physical constraints: in, Let be the soil hydraulic conductivity function. This represents the maximum permissible flow rate related to wind speed W. t represents the flow rate, and t represents the irrigation duration.

2. The irrigation regulation method based on plant growth and water use according to claim 1, wherein, The process of conducting a water use characteristics planting experiment on any type of target native plant includes: planting the target native plant in a greenhouse using potted plants, and constructing multiple planting test groups based on a pre-set soil moisture content gradient distribution. After the plant leaves have grown to mature leaves, water control treatment is carried out for each experimental group. When the soil moisture content reaches the corresponding target, the leaves of the sample plants are measured to obtain the photosynthetic parameters of each sample in the corresponding group and other target parameters are determined based on the photosynthetic parameters. The photosynthetic parameters include net photosynthetic rate, transpiration rate, stomatal conductance and intercellular CO2 concentration. The other target parameters include instantaneous water use efficiency, intrinsic water use efficiency and stomatal limitation value. Based on the acquired and determined parameter data, a variety of sample datasets under preset soil moisture content gradients are constructed, and the baseline irrigation threshold range for the target native plant species is determined based on the sample datasets.

3. The irrigation regulation method based on plant growth and water use according to claim 2, wherein, The sample dataset includes data on net photosynthetic rate, instantaneous water use efficiency, intrinsic water use efficiency, and stomatal limitation value. The process of determining the baseline irrigation threshold range for this target native plant species based on the sample dataset includes: The various parameter values ​​under each soil moisture content gradient in the sample dataset are normalized to obtain normalized parameters. Based on a preset weighting coefficient system, a weighted function is calculated for the normalized parameters under each soil moisture content gradient to obtain comprehensive index parameter values ​​that characterize the overall plant condition. Based on the comprehensive index parameter values, a relational response model is constructed with the comprehensive index parameter as the dependent variable and the corresponding soil moisture content as the independent variable. Based on the aforementioned relationship response model, the continuous soil moisture content range corresponding to a preset percentage where the comprehensive index value is not lower than its maximum value is determined as the benchmark irrigation threshold range for the target native plant.

4. An irrigation regulation system based on plant growth and water use, applied to vegetation ecological restoration in high-altitude and cold regions, characterized in that, include: The monitoring module is used to monitor the weather conditions and soil moisture content in the planting area; The control execution module is used to generate and execute irrigation regulation strategies based on the weather parameters obtained from monitoring and the deviation between the current soil moisture content and the preset irrigation threshold, using fuzzy control logic. The planting area contains at least one type of target native plant; the irrigation threshold is predetermined based on the growth and water use characteristics of the target native plant. The predetermined process includes: conducting water use characteristic planting experiments for each type of target native plant to determine the threshold system data for the corresponding type of target native plant. The threshold system data includes a baseline irrigation threshold range. The target native plant species include: *Plumbago spp.*, *Vitex negundo*, *Hymenochloa chinensis*, and *Artemisia annua*. In the threshold system data: for *Plumbago spp.*, the baseline irrigation threshold range is 73.4%-85.5%FC; for *Vitex negundo*, the baseline irrigation threshold range is 78.8%-85.3%FC; for *Hymenochloa chinensis*, the threshold index corresponding to its high-yield potential zone is 65.00%-93.42%; and for *Artemisia annua*, the threshold index corresponding to its high-efficiency regulation zone is 50%-65%. When the target native plant species contained in the planting area is one, the threshold index is selected from the threshold system data corresponding to the target native plant as the irrigation threshold according to the actual irrigation needs; when the target native plant species contained in the planting area is two or more, the baseline irrigation threshold range of the corresponding target native plants is analyzed according to the actual species composition of the target native plants in the planting area, and the common interval of each baseline irrigation threshold range is selected as the irrigation threshold. The current soil moisture content is the soil volumetric moisture content data obtained in real time through in-situ sensor monitoring; the deviation between the current soil moisture content and the preset irrigation threshold is determined by the following method: based on the soil bulk density parameter of the planting area, the soil volumetric moisture content data is converted into soil mass moisture content, and the soil bulk density parameter is adjusted for the actual planting area; the deviation between the soil mass moisture content and the irrigation threshold is determined by calculating the difference between the two. The fuzzy control rule base is constructed based on the deviation between the current soil moisture content and the irrigation threshold, as well as weather parameters, which include only rainfall intensity, photosynthetically active radiation, and wind speed. During the execution of the fuzzy control decision, the irrigation duration and flow rate are output, satisfying the following physical constraints: in, Let be the soil hydraulic conductivity function. This represents the maximum permissible flow rate related to wind speed W. t represents the flow rate, and t represents the irrigation duration.

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