A method for diagnosing regional moisture conditions based on evaporative stress oscillation patterns

Abstract

A method for diagnosing regional moisture conditions based on evaporative stress oscillation patterns is presented. [Solution] The method includes the following steps: Step 1: acquiring data; Step 2: calculating the time series of the evaporative stress index; Step 3: calculating the evolution rate of the evaporative stress index; Step 4: determining the oscillation patterns of the evaporative stress index; Step 5: calculating the frequency or duration of each oscillation pattern; and Step 6: diagnosing the evaporative stress-driven pattern and regional moisture status. The method of the present invention effectively solves the problem of information leakage and failure to reflect the transition mechanism of the stress state due to smoothing of the long-term series in the process of diagnosing the current regional moisture status, and provides solid theoretical and technical support for the diagnosis and evaluation of the evaporative stress-driven pattern and regional moisture status.

Description

[Technical Field]

[0001] The present invention belongs to the field of eco-hydrology technology, and particularly relates to a method for diagnosing regional water conditions based on evaporative stress oscillation patterns. [Background technology]

[0002] The evaporative stress index is defined as the ratio of actual transpiration to potential transpiration. Actual transpiration is the amount of water actually lost at the soil surface, including evaporation and plant transpiration. Potential transpiration is the amount of water that can evaporate from the soil surface and be transpired by plants under ideal conditions, assuming no water is limited. The evaporative stress index can reflect the dynamic balance between water supply and demand. The oscillation pattern of the evaporative stress index is primarily affected by climate disturbances and can sensitively reveal the state of regional water stress. It is widely used as an indicator in drought research and has important implications for drought early warning. Therefore, studying the oscillation pattern of evaporative stress can reveal the main characteristics of water stress within a study area, determine the quality of regional water conditions, provide strong data support and decision-making basis for regional water resource management and agricultural production, and improve climate change and drought countermeasures.

[0003] Most current methods for assessing regional moisture conditions are based on calculating long-term averages of related hydrological or meteorological variables and drought indices. The differences lie in the choice of variables and indices, which reveal regional moisture conditions from different angles. For example, by calculating long-term average precipitation and combining it with a wet / dry regional classification criterion, regional moisture conditions can be diagnosed. If the long-term average precipitation exceeds 800 mm, the region is considered a humid region with favorable moisture conditions. However, such methods based on long-term averages smooth out short-term abnormal changes, resulting in the loss of potentially important information. They are unable to reflect seasonal and annual moisture changes and lack in-depth analysis of specific causes, which limits their ability to explore the dominant patterns of regional moisture stress and diagnose moisture conditions. Chinese patent publication number CN117058433A discloses an eco-hydrological partitioning method based on the Gaussian mixture clustering algorithm, which selects indicators that can reflect the hydrological, meteorological, ecological, land use, and socio-economic characteristics of a study area to establish an indicator system, determines the indicator weights using the entropy weight method, and diagnoses the eco-hydrological conditions of the area based on the output results of the Gaussian mixture model clustering algorithm, thereby dividing the study area into multiple eco-hydrological partitions. However, this method is still a statistical identification based on the long-term average state, and no diagnostic method based on the change mechanism has yet been proposed. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Chinese Patent Application Publication CN117058433A Summary of the Invention [Problem to be solved by the invention]

[0005] The objective of the present invention is to provide a method for diagnosing regional moisture conditions based on evaporative stress vibration patterns in order to solve the above technical problems. [Means for solving the problem]

[0006] To achieve the above object, the present invention provides the following technical solutions. [Technical solution of the present invention] The present invention discloses a method for diagnosing regional moisture conditions based on evaporative stress vibration patterns, the method comprising the following steps: Step 1, Data Acquisition: Obtain the actual transpiration time series ETa and potential transpiration time series ETp for the study area. Step 2, Calculation of the evaporative stress index time series: The evaporative stress index time series value ESI at time t is calculated based on equation (1). t and then obtain the evaporative stress index time series ESI, ESI t =ETa t / ETp t (1) In the formula: ESI t is the time series value of the evaporative stress index at time t, and ETa t is the actual transpiration time series value at time t, and ETp t is the time series value of potential transpiration at time t, Step 3, Calculation of the rate of development of the evaporative stress index: The development rate of the evaporative stress index is the change in the evaporative stress index per unit time, and the calculation formula is as follows: V=ΔESI / Δt (2) Where: V is the rate of evolution of the evaporative stress index, ΔESI is the change in the evaporative stress index over a certain period of time, and Δt is the time resolution. Step 4, Determining the oscillation pattern of the evaporative stress index: The oscillation pattern of the evaporative stress index is determined based on the relative magnitude of the development speed of the evaporative stress index at adjacent times and the relative magnitude of the evaporative stress index. The oscillation pattern of the evaporative stress index is divided into the following six types:

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[0007] Furthermore, the actual transpiration time series ETa and the potential transpiration time series ETp of the research area in step 1 are obtained by downloading public data on the network or by observing actual meteorological data.

[0008] Furthermore, the step of diagnosing the dominant pattern of evaporative stress in step 6 and determining the local moisture situation specifically includes: If the dominant pattern is S1, it indicates that the region has a strong ability to mitigate evaporative stress on a long-term average scale and the moisture situation in the region is good. If the dominant pattern is S2, it indicates that the region has the ability to mitigate evaporative stress on a long-term average scale and that the moisture situation in the region is relatively good; If the dominant pattern is S3, it indicates that the region has the ability to alleviate evaporative stress in the short term on a long-term average scale, but the evaporative stress is still reversed and the moisture situation in the region is poor; If the dominant pattern is S4, it indicates that the region has a certain ability to mitigate evaporative stress from the weighted trend on a long-term average scale, and the moisture situation in the region is generally good. If the dominant pattern is S5, it indicates that the region does not have the ability to alleviate evaporative stress on a long-term average scale, and evaporative stress continues to increase, resulting in poor moisture conditions in the region. When the dominant pattern is S6, it indicates that the region does not fully have the ability to mitigate evaporative stress on a long-term average scale, and evaporative stress continues to accelerate and worsen, resulting in extremely poor moisture conditions in the region. [Effects of the Invention]

[0009] The beneficial effects of the present invention are as follows: The method of the present invention can determine the main change mechanism of regional evaporative stress over many years, thereby analyzing whether a region has the ability to alleviate evaporative stress over a long time scale and further diagnosing the regional moisture conditions. The method of the present invention effectively solves the problem of information leakage and failure to reflect the change mechanism of stress conditions due to smoothing of long-term series in the process of diagnosing the current regional moisture conditions, and provides solid theoretical and technical support for the diagnostic evaluation of evaporative stress-driven patterns and regional moisture conditions.

[0010] The invention will now be described in more detail with reference to the drawings and specific embodiments. [Brief explanation of the drawings]

[0011] [Figure 1] 1 is a flow chart of the method of the present invention. [Figure 2] Schematic diagram of the calculation process of the evolution rate of the evaporative stress index. [Figure 3] 1 is a schematic diagram of six types of oscillation patterns of the evaporative stress index. [Figure 4] FIG. 1 is a schematic diagram of an evaporative stress index time series converted into a labeled pattern sequence. DETAILED DESCRIPTION OF THE INVENTION

[0012] The present invention discloses a method for diagnosing regional water status based on evaporative stress vibration patterns, and the principle of the method is as follows.

[0013] The evaporative stress index is defined as the ratio of actual transpiration to potential transpiration. It directly quantifies the ratio of actual water supply to potential demand in a region and can reflect the regional water supply and demand situation. Combining the change in the evaporative stress index itself with the contrast between the rate of change before and after the change at adjacent times, six types of oscillation patterns can be identified: accelerating relaxation of evaporative stress, decelerating relaxation, reversal from relaxation to stress, reversal from stress to relaxation, decelerating stress, and accelerating stress. The dominant pattern of evaporative stress can be diagnosed by statistically identifying the pattern with the highest frequency and duration over a certain period. If the diagnosed dominant pattern is a "relaxation" pattern, it indicates that the region has a certain ability to mitigate evaporative stress during the long-term average evaporative stress transition, demonstrating that the region's water status is generally good; conversely, it indicates that the region's water status is poor. Therefore, the oscillation pattern of the evaporative stress index can be used to diagnose the water stress status of a region. In contrast, traditional diagnostic methods based on long-term average values ​​may not be able to reflect seasonal or annual changes, or may lack analysis of the causes of water stress. Therefore, using the leading mechanism of identifying evaporative stress based on evaporative stress oscillation patterns is advantageous for further diagnosing regional water stress situations and clarifying the main characteristics of regional water stress, and further providing strong support and decision-making basis for water resources assessment and management.

[0014] Specifically, the method includes the following steps 1 to 6. That is, as shown in FIG. Step 1, Data Acquisition: The actual transpiration time series ETa and potential transpiration time series ETp for the study area are obtained. These are generally obtained by downloading publicly available data from a network or by observing actual meteorological data, for example, from the European Centre for Medium-Range Weather Forecasts network.

[0015] Step 2, Calculation of the evaporative stress index time series: The evaporative stress index time series value ESI at time t is calculated based on equation (1). t and then obtain the evaporative stress index time series ESI, ESI t =ETa t / ETp t (1) In the formula: ESI t is the time series value of the evaporative stress index at time t, and ETa t is the actual transpiration time series value at time t, and ETp t is the time series value of potential transpiration at time t, The smaller the evaporative stress index value, the more severe the evaporative stress situation.

[0016] Step 3, Calculation of the rate of development of the evaporative stress index: The development rate of the evaporative stress index is the change in the evaporative stress index per unit time, and the calculation formula is as follows: V=ΔESI / Δt (2) where V is the rate of evolution of the evaporative stress index, ΔESI is the change in the evaporative stress index over a period of time, and Δt is the time resolution, which is shown in Figure 2.

[0017] Step 4, Determining the oscillation pattern of the evaporative stress index: The oscillation pattern of the evaporative stress index is determined based on the relative magnitude of the development speed of the evaporative stress index at adjacent times and the relative magnitude of the evaporative stress index. The oscillation pattern of the evaporative stress index is divided into the following six types:

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[0018] After determining the oscillation patterns of adjacent time periods, the evaporative stress index time series ESI can be labeled, i.e., the evaporative stress index time series can be converted into a labeled pattern series, as shown in Figure 4.

[0019] Step 5, Calculate the frequency or duration of each vibration pattern: Frequency F is defined as the ratio of the number of times a certain vibration pattern appears over the entire research period to the total number of times all vibration patterns appear. Duration D is defined as the time that a certain vibration pattern lasts divided by the number of times that vibration pattern appears, and represents the average duration of each time that a certain vibration pattern appears over the research period. Since the time resolution of downloaded data or data obtained through observation is fixed, data with a time resolution of Δt is used as an example to emphasize the influence of consecutive appearances of vibration patterns when calculating duration D. When calculating the denominator of duration D for a labeled pattern series, if pattern S1 appears multiple times consecutively, it is counted as one occurrence. The specific calculation process is as follows: During the study period, there were N types of vibration patterns (N≦6), and pattern S i occurs n times during the research period i Assuming that, the frequency F i is as follows:

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[0020] Duration D i is a vibration pattern S i represents the average duration of each occurrence during the study period. i The number of occurrences of is m i The total time for each stage is L k × Δt, where L k is the pattern S at the kth stage i is the number of consecutive occurrences of

[0021] Pattern S i The total duration of T i may be expressed as the sum of the times of all successive stages,

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[0022] Step 6, Diagnose evaporative stress-driven patterns and local moisture conditions: By collecting statistics on the maximum frequency or duration of each oscillation pattern over the entire study period, the dominant pattern of evaporative stress was diagnosed and the regional moisture status was further determined. The oscillation pattern can reflect whether the evaporative stress trend is "aggravated" or "relaxed." Therefore, the dominant pattern of evaporative stress in the study area can be identified and the regional moisture status determined based on the oscillation pattern with the highest frequency or longest duration, as shown in Table 1. For example, if the statistical results show that the oscillation pattern with the highest frequency or longest duration is S1 (an accelerated relaxation pattern of evaporative stress), this means that the area has a strong ability to alleviate evaporative stress on a long-term average scale and indicates a good moisture status in the area.

[0023] Table 1: Regional moisture conditions corresponding to different evaporative stress-driven patterns [Table 1]

[0024] Example 1 This embodiment is an application example of the above-mentioned method.

[0025] This study selected China as the study area. In recent years, the regional leaf area index (LAI) has increased significantly by 7.7%. Due to significant changes in the land environment and the impact of human activities, China's hydrological, vegetation, and climatic conditions have undergone significant changes. Therefore, regional water situation assessment must fully consider variability and change mechanisms, and smoothing long-term series in the water situation diagnosis process can solve the problems of information leakage and failure to reflect the change mechanisms of stress conditions.

[0026] Monthly time-resolution time series of actual and potential transpiration for the study area from 1950 to 2020 were downloaded. The data was publicly available through the European Centre for Medium-Range Weather Forecasts network. The downloaded data was grid data, and the method of the present invention was applied to each grid to verify the accuracy of the moisture situation assessment.

[0027] Based on the downloaded time series of actual and potential transpiration, the time series of evaporative stress index for each grid in the China region was calculated, and the value of the series fluctuated continuously between 0.70 and 0.75.

[0028] The difference between the time series of evaporative stress index before and after the calculation is divided by the time resolution, i.e., 1 month, to obtain the monthly evolution rate series of evaporative stress index, whose values ​​are between -0.61 and 0.73.

[0029] Based on the above steps, the time series of the evaporative stress index and the evolution rate series of the evaporative stress index in each grid are obtained, and the magnitude of the values ​​of the evaporative stress index and the evolution rate series of the evaporative stress index at adjacent times are compared to determine the oscillation pattern of the evaporative stress index, and a labeled oscillation pattern series is further obtained.

[0030] The frequency of occurrence of each oscillation pattern in the study area between 1950 and 2020 was calculated, and the oscillation pattern that appeared most frequently in each grid was statistically analyzed and spatially dispersed. The statistical results showed that pattern S3 (i.e., evaporative stress reversal from relaxation to stress) was the oscillation pattern that appeared most frequently in approximately 79.6% of the area between 1950 and 2020, and this dominant pattern was mainly distributed in northern areas with poor moisture conditions. In approximately 19.0% of the area, pattern S4 (i.e., evaporative stress reversal from stress to relaxation) was the oscillation pattern that appeared most frequently, and was mainly distributed in southern areas or densely forested areas with relatively good moisture conditions.

[0031] The above examples demonstrate the effectiveness and accuracy of the method of the present invention in diagnosing dominant patterns of evaporative stress and regional water status.

[0032] Finally, it should be noted that the above description is for the purpose of illustrating the technical solution of the present invention and is not limiting, and although the present invention has been described in detail with reference to preferred arrangement means, it is understood by those skilled in the art that the technical solution of the present invention can be modified or equivalently substituted without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. 1. A method for diagnosing regional moisture conditions based on evaporative stress oscillation patterns, the method comprising the steps of: Step 1, Data Acquisition: Obtain the actual transpiration time series ETa and potential transpiration time series ETp for the study area. Step 2, Calculation of the evaporative stress index time series: The evaporative stress index time series value ESI at time t calculated based on equation (1) ｔ and further obtain the evaporative stress index time series ESI, ESI ｔ =ETa ｔ / ETp ｔ (1) In the formula: ESI ｔ is the time series value of the evaporative stress index at time t, and ETa ｔ is the actual transpiration time series value at time t, and ETp ｔ is the time series value of potential transpiration at time t, Step 3, Calculate the evolution rate of the evaporative stress index: The development rate of the evaporative stress index is the change in the evaporative stress index per unit time, and the calculation formula is as follows: V=ΔESI / Δt (2) where V is the rate of evolution of the evaporative stress index, ΔESI is the change in the evaporative stress index over a period of time, and Δt is the time resolution. Step 4, Determining the oscillation pattern of the evaporative stress index: The oscillation pattern of the evaporative stress index is determined based on the relative magnitude of the development speed of the evaporative stress index at adjacent times and the relative magnitude of the evaporative stress index. The oscillation pattern of the evaporative stress index is divided into the following six types: [Equation 1] In the formula: S represents the pattern number, and includes six types of vibration patterns S1 to S6, and V ｔ is ESI ｔ－１ From ESI ｔ represents the speed of the change process to ｔ＋１ is ESI ｔ From ESI ｔ＋１ , and pattern S1 represents the accelerated relaxation of evaporative stress, where V ｔ＋１ >V ｔ An increase in velocity represents acceleration, and ESI ｔ＋１ >ESI ｔ >ESI ｔ－１ An increase in the evaporative stress index represents a relaxation of evaporative stress; similarly, pattern S2 represents a decelerating relaxation of evaporative stress, pattern S3 represents a reversal of evaporative stress from relaxation to stress, pattern S4 represents a reversal of evaporative stress from stress to evaporative stress, pattern S5 represents a decelerating stress, and pattern S6 represents an accelerating stress of evaporative stress; After determining the oscillation patterns of adjacent time periods, label the evaporative stress index time series ESI, i.e., convert the evaporative stress index time series into a labeled pattern series; Step 5, Calculate the frequency or duration of each vibration pattern: The frequency F is defined as the ratio of the number of times a certain vibration pattern appears during the entire study period to the total number of times all vibration patterns appear, and the duration D is defined as the time that a certain vibration pattern lasts divided by the number of times that the vibration pattern appears, and represents the average duration of each time that a certain vibration pattern appears during the study period. When calculating the duration D, the influence of consecutive appearances of vibration patterns is emphasized. When calculating the denominator of the duration D for a labeled pattern sequence, if a pattern S1 appears multiple times consecutively, it is counted as one appearance in the statistics, and the specific calculation process is as follows: During the study period, there are N types of vibration patterns, N≦6, and pattern S ｉ appears n times during the research period ｉ Assuming that, the frequency F ｉ is as follows: [Equation 2] Here, the denominator on the right side of the above equation is [Equation 3] represents the total number of occurrences of all patterns, Duration D ｉ is a certain vibration pattern S ｉ represents the average duration of each occurrence during the study period, and pattern S ｉ The number of occurrences is m ｉ The total time for each stage is L ｋ × Δt, where L ｋ is the pattern S in the kth stage ｉ is the number of consecutive occurrences of Pattern S ｉ The total duration T ｉ is expressed as the sum of the times of all successive stages, [Equation 4] Pattern S ｉ Duration D ｉ is the total duration of the pattern T ｉ The number of stages m that continue ｉ It is expressed as a value divided by D ｉ =T ｉ / m ｉ (6) That is, pattern S ｉ appears consecutively in a certain stage, and when calculating the duration, the duration of this stage is counted only once, Step 6. Diagnose evaporative stress-driven patterns and local moisture conditions: Statistical analysis of the maximum frequency or duration of each oscillation pattern over the entire study period will be used to diagnose the dominant pattern of evaporative stress and further determine the regional moisture situation. A method for diagnosing regional moisture conditions based on evaporative stress vibration patterns, comprising the steps 1 to 6 above.

2. In step 1, the actual transpiration time series ETa and the potential transpiration time series ETp of the research area are obtained by downloading public data on the network or by observing actual meteorological data. The method for diagnosing regional moisture conditions based on evaporative stress vibration patterns according to claim 1.

3. The step of diagnosing the dominant pattern of evaporative stress in step 6 and determining the local moisture situation specifically includes: If the dominant pattern is S1, it indicates that the region has a strong ability to mitigate evaporative stress on a long-term average scale and the moisture situation in the region is good; If the dominant pattern is S2, it indicates that the region has the ability to mitigate evaporative stress on a long-term average scale and that the moisture situation in the region is relatively good; If the dominant pattern is S3, it indicates that the region has the ability to alleviate evaporative stress in the short term on a long-term average scale, but the evaporative stress is still reversed and the moisture situation in the region is poor; If the dominant pattern is S4, it indicates that the region has a certain ability to mitigate evaporative stress from the weighted trend on a long-term average scale, and the moisture situation in the region is generally good; If the dominant pattern is S5, it indicates that the region does not have the ability to alleviate evaporative stress on a long-term average scale, and evaporative stress continues to increase, resulting in poor moisture conditions in the region. If the dominant pattern is S6, it indicates that the region does not fully have the ability to alleviate evaporative stress on a long-term average scale, and evaporative stress continues to accelerate and worsen, resulting in an extremely poor moisture situation in the region. The method for diagnosing regional moisture conditions based on evaporative stress vibration patterns according to claim 1.

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