A method for diagnosing regional water status based on the evaporation stress oscillation mode

Abstract

The present invention discloses a method for diagnosing the regional water status based on the evaporation stress oscillation mode. The method comprises the following steps: Step 1, data acquisition; Step 2, calculating the time series of the evaporation stress index; Step 3, calculating the development speed of the evaporation stress index; Step 4, determining the oscillation mode of the evaporation stress index; Step 5, calculating the frequency or duration of each oscillation mode; Step 6, diagnosing the dominant mode of evaporation stress and the regional water status. The method of the present invention effectively solves the problems of information omission caused by smoothing the long-term sequence and the inability to reflect the evolution mechanism of the stress state in the current diagnosis process of the regional water status, and provides reliable theoretical and technical support for the diagnosis and evaluation of the dominant mode of evaporation stress and the regional water status.

Description

Technical Field

[0001] The present invention belongs to the technical field of eco - hydrology, and particularly relates to a method for diagnosing the regional water condition based on the evaporation stress oscillation mode. Background Technique

[0002] The evaporation stress index is defined as the ratio of actual evapotranspiration to potential evapotranspiration. Actual evapotranspiration is the amount of water actually lost from the earth's surface, including evaporation and plant transpiration; while potential evapotranspiration is the amount of water that can be evaporated from the earth's surface and transpired by plants under ideal conditions where water is not restricted. The evaporation stress index can reflect the dynamic balance between water supply and demand. The oscillation mode of the evaporation stress index is mainly affected by climate disturbances, can sensitively reveal the state of regional water stress, and is often used as an indicator for studying drought, which has important guiding significance for the early warning of drought. Therefore, studying the evaporation stress oscillation mode can reveal the main characteristics of water stress in the study area, judge the quality of regional water conditions, further provide strong data support and decision - making basis for regional water resources management and agricultural production, and improve the ability to cope with climate change and drought.

[0003] Regarding the judgment of regional water conditions, currently, most common methods are mostly based on calculating the long - term average values of relevant hydrological or meteorological variables and drought indicators. The difference lies in the selection of variables and indicators to reveal the regional water conditions from different perspectives. For example, by calculating the multi - year average precipitation and combining the dry - wet area division standard, the regional water conditions can be diagnosed: if the multi - year average precipitation exceeds 800 mm, the area is considered a humid area with good water conditions. However, this method based on long - term average values will smooth out short - term abnormal changes, resulting in the loss of potential important information, unable to reflect seasonal and inter - annual water changes, and lacking in - depth analysis of specific causes. Therefore, it has limitations in exploring the dominant mode of regional water stress and diagnosing water conditions. Chinese Patent with publication number CN117058433A discloses an eco - hydrological zoning method based on the Gaussian mixture clustering algorithm. This patent selects indicators that can reflect the characteristics of hydrology, meteorology, ecology, land use, and social economy in the study area, constructs an indicator system, determines the indicator weights by the entropy weight method, and diagnoses the eco - hydrological conditions of the area according to the output results of the Gaussian mixture model clustering algorithm, dividing the study area into several eco - hydrological zones. However, this method is still a statistical identification based on the long - term average state and has not proposed a diagnostic method based on the evolution mechanism. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for diagnosing the regional water condition based on the evaporation stress oscillation mode to solve the above - mentioned technical problems.

[0005] To achieve the above purpose, the present invention provides the following technical solutions:

[0006] The present invention discloses a method for diagnosing regional water status based on an evaporation stress oscillation mode, and the method includes the following steps:

[0007] Step 1, data acquisition: Obtain the actual evapotranspiration time series ETa and the potential evapotranspiration time series ETp of the research area;

[0008] Step 2, calculate the evaporation stress index time series: Calculate the evaporation stress index time series value ESI at time t according to formula (1) t , and then obtain the evaporation stress index time series ESI;

[0009]

[0010] In the formula: ESI t is the evaporation stress index time series value at time t; ETa t is the actual evapotranspiration time series value at time t; ETp t is the potential evapotranspiration time series value at time t;

[0011] Step 3, calculate the development speed of the evaporation stress index: The development speed of the evaporation stress index is the change in the evaporation stress index per unit time, and the calculation formula is:

[0012]

[0013] In the formula: V is the development speed of the evaporation stress index; ΔESI is the change amount of the evaporation stress index over a period of time; Δt is the time resolution;

[0014] Step 4, determine the oscillation mode of the evaporation stress index: Determine the oscillation mode of the evaporation stress index according to the relative magnitude of the development speed of the evaporation stress index at adjacent times and the relative magnitude of the evaporation stress index. The oscillation mode of the evaporation stress index is divided into the following six categories:

[0015]

[0016] In the formula: S represents the number of the mode, including six oscillation modes from S1 to S6; V t represents the speed during the change process from ESI t-1 to ESI t ; V t+1 represents the speed during the change process from ESI t to ESI t+1 ; The mode S1 represents that the evaporation stress accelerates and then slows down, where V t+1 >V t The increase in speed represents acceleration, and ESI t+1 >ESI t>ESI t-1 An increase in the evaporation stress index indicates a slowdown in evaporation stress; similarly, pattern S2 indicates a decelerated slowdown in evaporation stress; pattern S3 indicates a reversal from a slowdown to an increase in evaporation stress; pattern S4 indicates a reversal from an increase to a slowdown in evaporation stress; pattern S5 indicates a decelerated increase in evaporation stress; pattern S6 indicates an accelerated increase in evaporation stress;

[0017] After determining the oscillation pattern at adjacent times, the evaporation stress index time series ESI is labeled, that is, the evaporation stress index time series is converted into a labeled pattern sequence;

[0018] Step 5: Calculate the frequency or duration of each oscillation pattern: The frequency F is defined as the proportion of the number of times a certain oscillation pattern appears during the entire research period to the total number of times all oscillation patterns appear; the duration D is defined as the duration of a certain oscillation pattern divided by the number of times that pattern appears, indicating the average duration of a certain oscillation pattern each time it appears during the research period; when calculating the duration D, the influence of consecutive appearances of the oscillation pattern is emphasized. For the labeled pattern sequence, when calculating the denominator of the duration D, if pattern S1 appears consecutively multiple times, it is counted as 1 time; the specific calculation process is as follows:

[0019] Suppose there are N types of oscillation patterns during the research period, N ≤ 6, pattern S i The number of times it appears during the research period is n i , then the frequency F i is:

[0020]

[0021] where represents the sum of the number of times all patterns appear;

[0022] The duration D i represents the average duration of a certain oscillation pattern S i each time it appears during the research period. Suppose the number of appearance segments of pattern S i is m i , and the total time of each segment of appearance is L k ×Δt, where L k is the number of consecutive appearances of pattern S i in the k-th segment;

[0023] Pattern S i The total duration T i is expressed as the sum of the times of all consecutive appearance segments:

[0024]

[0025] Pattern S i The duration D iExpressed as the total duration T of the pattern i Divided by the number of continuous segments m i :

[0026]

[0027] That is, when the pattern S i Appears continuously in a certain segment, when calculating the duration, the duration of this segment is only counted once;

[0028] Step 6, Diagnose the dominant pattern of evaporation stress and the regional water status: Count the maximum value of the frequency or duration of each oscillation pattern during the entire research period, so as to diagnose the dominant pattern of evaporation stress and further judge the regional water status.

[0029] Furthermore, the actual evapotranspiration time series ETa and the potential evapotranspiration time series ETp of the research area described in Step 1 are obtained through downloading network public data or actual meteorological data observations.

[0030] Furthermore, the diagnosis of the dominant pattern of evaporation stress in Step 6 and the further judgment of the regional water status are specifically as follows:

[0031] If the dominant pattern is S1, the region has a strong ability to relieve evaporation stress on the multi-year average scale, indicating that the regional water status is good;

[0032] If the dominant pattern is S2, the region has the ability to relieve evaporation stress on the multi-year average scale, indicating that the regional water status is relatively good;

[0033] If the dominant pattern is S3, the region has the ability to relieve evaporation stress briefly on the multi-year average scale, but the evaporation stress still reverses and becomes aggravated, indicating that the regional water status is poor;

[0034] If the dominant pattern is S4, the region has a certain ability to relieve evaporation stress from the aggravating trend on the multi-year average scale, indicating that the regional water status is fair;

[0035] If the dominant pattern is S5, the region does not have the ability to relieve evaporation stress on the multi-year average scale, and the evaporation stress continues to increase, indicating that the regional water status is poor;

[0036] If the dominant pattern is S6, the region completely does not have the ability to relieve evaporation stress on the multi-year average scale, and the evaporation stress continues to accelerate and increase, indicating that the regional water status is extremely poor.

[0037] The beneficial effects of the present invention are as follows: The method of the present invention can determine the state change mechanism mainly presented by regional evaporation stress over the years, thereby analyzing whether the region has the ability to relieve the evaporation stress state on a long time scale, and further diagnosing the water condition of the region. The method of the present invention effectively solves the problems of information omission caused by smoothing long-term sequences and the inability to reflect the evolution mechanism of the stress state in the current diagnosis process of regional water conditions, and provides reliable theoretical and technical support for the diagnosis and evaluation of the dominant mode of evaporation stress and regional water conditions.

[0038] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 is a flowchart of the method of the present invention;

[0040] Figure 2 is a schematic diagram of the calculation process of the development rate of the evaporation stress index;

[0041] Figure 3 is a schematic diagram of six oscillation modes of the evaporation stress index;

[0042] Figure 4 is a schematic diagram of converting the evaporation stress index time series into a labeled pattern sequence. SPECIFIC EMBODIMENTS

[0043] The present invention discloses a method for diagnosing regional water conditions based on the oscillation mode of evaporation stress. The principle on which the method is based is as follows:

[0044] The evaporation stress index is defined as the ratio of actual evapotranspiration to potential evapotranspiration. The evaporation stress index directly quantifies the ratio of actual water supply to potential demand in a region and can reflect the water supply and demand situation in the region. At adjacent times, by combining the numerical change of the evaporation stress index itself and the comparison of the change speed before and after, there can be six types of oscillation modes at adjacent times, namely evaporation stress acceleration and deceleration, deceleration and deceleration, reversal from deceleration to aggravation, reversal from aggravation to deceleration, deceleration and aggravation, and acceleration and aggravation. By statistically analyzing the mode with the highest frequency and longest duration over a period of time, the dominant mode of evaporation stress can be diagnosed. If the diagnosed dominant mode is the "deceleration" mode, it indicates that the region has a certain ability to relieve evaporation stress during the evolution of evaporation stress on the multi-year average scale, proving that the water condition in the region is relatively good. On the contrary, the water condition is scarce. Therefore, the oscillation mode of the evaporation stress index can be used to diagnose the water stress condition in the region. The traditional diagnostic method based on long-term average values may either fail to reflect seasonal or interannual changes or lack an analysis of the causes of water stress. Therefore, using the evaporation stress oscillation mode to identify the dominant mechanism of evaporation stress and further diagnose the water stress condition in the region is conducive to revealing the main characteristics of regional water stress and providing strong support and decision-making basis for water resources evaluation and management.

[0045] Specifically, it includes the following steps, as Figure 1 shown:

[0046] Step 1, Data acquisition: Obtain the time series of actual evapotranspiration ETa and the time series of potential evapotranspiration ETp in the study area, generally through downloading publicly available network data or actual meteorological data observations. For example, it can be downloaded from the European Centre for Medium-Range Weather Forecasts network.

[0047] Step 2, Calculate the time series of the evaporation stress index: Calculate the time series value ESI of the evaporation stress index at time t according to formula (1) t , and then obtain the time series of the evaporation stress index ESI;

[0048]

[0049] In the formula: ESI t is the time series value of the evaporation stress index at time t; ETa t is the time series value of actual evapotranspiration at time t; ETp t is the time series value of potential evapotranspiration at time t;

[0050] The smaller the value of the evaporation stress index, the heavier the evaporation stress situation.

[0051] Step 3, Calculate the development speed of the evaporation stress index: The development speed of the evaporation stress index is the change of the evaporation stress index per unit time, and the calculation formula is:

[0052]

[0053] Where: V is the development rate of the evaporation stress index; ΔESI is the change in the evaporation stress index over a period of time; Δt is the time resolution; as Figure 2 shown.

[0054] Step 4. Determine the oscillation pattern of the evaporation stress index: Determine the oscillation pattern of the evaporation stress index according to the relative magnitudes of the development rates of the evaporation stress index at adjacent times and the relative magnitude of the evaporation stress index. The oscillation patterns of the evaporation stress index are divided into the following six categories:

[0055]

[0056] Where: S represents the pattern number, including six oscillation patterns from S1 to S6; V t represents the speed during the change process from ESI t-1 to ESI t ; V t+1 represents the speed during the change process from ESI t to ESI t+1 ; Pattern S1 indicates that the evaporation stress accelerates and then slows down, where V t+1 > V t an increase in speed indicates acceleration, and ESI t+1 > ESI t > ESI t-1 an increase in the evaporation stress index indicates that the evaporation stress slows down; similarly, pattern S2 indicates that the evaporation stress decelerates and then slows down; pattern S3 indicates that the evaporation stress changes from slowing down to increasing; pattern S4 indicates that the evaporation stress changes from increasing to slowing down; pattern S5 indicates that the evaporation stress decelerates and increases; pattern S6 indicates that the evaporation stress accelerates and increases; as Figure 3 shown.

[0057] After determining the oscillation pattern at adjacent times, the evaporation stress index time series ESI can be labeled, that is, the evaporation stress index time series is converted into a labeled pattern sequence, as Figure 4 shown.

[0058] Step 5: Calculate the frequency or duration of each oscillation mode. The frequency F is defined as the proportion of the number of occurrences of a certain oscillation mode during the entire research period to the total number of occurrences of all oscillation modes. The duration D is defined as the duration of a certain oscillation mode divided by the number of occurrences of that oscillation mode, representing the average duration of a certain oscillation mode each time it appears during the research period. Since the time resolution of the data obtained by downloading or observation is fixed, taking the data with a time resolution of Δt as an example, the impact of the continuous occurrence of the oscillation mode is emphasized when calculating the duration D. For the labeled mode sequence, when calculating the denominator of the duration D, if the mode S1 appears continuously multiple times, it is counted as 1 time. The specific calculation process is as follows:

[0059] Suppose there are N types of oscillation modes (N ≤ 6) during the research period, and the mode S i appears n i times during the research period. Then the frequency F i is:

[0060]

[0061] where represents the sum of the number of occurrences of all modes.

[0062] The duration D i represents the average duration of a certain oscillation mode S i each time it appears during the research period. Suppose the number of occurrence segments of the mode S i is m i , and the total time of each segment is L k ×Δt, where L k is the number of consecutive occurrences of the mode S i in the k-th segment.

[0063] The mode S i The total duration T i can be expressed as the sum of the times of all consecutive occurrence segments:

[0064]

[0065] The mode S i The duration D i can be expressed as the total mode duration T i divided by the number of consecutive segments m i :

[0066]

[0067] This means that when the mode S i appears continuously in a certain segment, when calculating the duration, the duration of this segment is only counted once. Therefore, the number of occurrence segments m iIt reflects the number of these uninterrupted segments, rather than the number of individual occurrences each time.

[0068] Step 6, diagnosing the dominant mode of evaporation stress and regional water status: During the entire research period, by statistically analyzing the maximum value of the frequency or duration of each oscillation mode, diagnose the dominant mode of evaporation stress, and further judge the regional water status. The oscillation mode can reflect whether the change trend of evaporation stress is "aggravating" or "mitigating". Therefore, according to the oscillation mode with the highest frequency or the longest duration, the dominant mode of evaporation stress in the research area can be identified, and the regional water status can be judged, as shown in Table 1. For example, if the statistical result shows that the oscillation mode with the highest frequency or the longest duration is S1 (the evaporation stress acceleration and mitigation mode), it means that the area has a strong ability to relieve evaporation stress on the multi-year average scale, indicating that the regional water status is good.

[0069] Table 1 Regional water status corresponding to different dominant modes of evaporation stress

[0070]

[0071]

[0072] Example 1

[0073] This example is an application example of the above method.

[0074] This example selects the Chinese region as the research area. In recent years, the regional leaf area index (LAI) has increased significantly by 7.7%. In the face of significant terrestrial environmental changes and the impact of human activities, the hydrological, vegetation and climate conditions in China have changed significantly. The assessment of regional water status needs to fully consider variability and evolution mechanisms, and improve the problem of information omission caused by smoothing long-term sequences and the inability to reflect the evolution mechanism of stress status during the water status diagnosis process.

[0075] Download the time series of actual evapotranspiration and potential evapotranspiration with monthly time resolution from 1950 to 2020 in the research area. The data is publicly available from the European Centre for Medium-Range Weather Forecasts network. The downloaded data is raster data, and the method described in the present invention is applied to each grid to verify the accuracy of water status assessment.

[0076] According to the downloaded time series of actual evapotranspiration and potential evapotranspiration, calculate the time series of evaporation stress index for each grid in the Chinese region. The values of this series fluctuate continuously between 0.70 and 0.75.

[0077] By calculating the difference before and after the time series of evaporation stress index and dividing it by the time resolution, which is 1 month, the development speed series of the evaporation stress index per month is obtained, and the values are between -0.61 and 0.73.

[0078] According to the above steps, the time series of the evaporation stress index and the development speed series of the evaporation stress index on each grid are obtained. The magnitudes of the evaporation stress index values and the development speed values of the evaporation stress index at adjacent times are compared to determine the oscillation mode of the evaporation stress index, and then the labeled oscillation mode series is obtained.

[0079] Calculate the frequency of occurrence of each oscillation mode in the study area during 1950 - 2020, count the oscillation mode with the highest frequency of occurrence on each grid, and perform spatial distribution. According to the statistical results, during 1950 - 2020 in the study area, about 79.6% of the area has the oscillation mode S3 (i.e., the evaporation stress changes from mitigation to aggravation) as the oscillation mode with the highest frequency of occurrence, and this dominant mode is mainly distributed in the areas with poor water conditions in the north; about 19.0% of the area in the study area has the oscillation mode S4 (i.e., the evaporation stress changes from aggravation to mitigation) as the oscillation mode with the highest frequency of occurrence, mainly distributed in the south or in the areas with good water conditions and dense forests.

[0080] The above embodiments prove the effectiveness and accuracy of the method described in the present invention in diagnosing the dominant mode of evaporation stress and the regional water conditions.

[0081] Finally, it should be noted that the above is only used to illustrate the technical solution of the present invention and not to limit it. Although the present invention has been described in detail with reference to the preferred arrangement, those of ordinary skill in the art should understand that the technical solution of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A method for diagnosing regional water conditions based on evaporative stress oscillation mode, characterized in that: The method comprises the following steps: Step 1: Data acquisition: Obtain the actual evapotranspiration time series ETa and potential evapotranspiration time series ETp of the study area; Step 2: Calculate the evaporation stress index time series: Calculate the evaporation stress index time series value ESI at time t according to formula (1): t , and then the evaporation stress index time series ESI is obtained; Where: ESI t is the time series value of the evaporation stress index at time t; ETa t is the actual evapotranspiration time series value at time t; ETp t is the time series value of potential evapotranspiration at time t; Step 3: Calculate the development speed of the evaporation stress index: The development speed of the evaporation stress index is the change of the evaporation stress index per unit time, and the calculation formula is: Where: V is the development speed of evaporative stress index; ΔESI is the change of evaporative stress index in a period of time; Δt is the time resolution; Step 4, determine the oscillation mode of the evaporation stress index: determine the oscillation mode of the evaporation stress index according to the relative size of the development speed of the evaporation stress index at adjacent moments and the relative size of the evaporation stress index. The oscillation mode of the evaporation stress index is divided into the following six categories: Where: S represents the mode number, including six types of oscillation modes from S1 to S6; V t Indicates that from ESI t-1 To ESI t The speed of the change process; V t+1 Indicates that from ESI t To ESI t+1 The speed of the change process; Mode S1 represents the acceleration and deceleration of evaporation stress, where V t+1 >V t Increased speed indicates acceleration, ESI t+1 >ESI t >ESI t-1 The increase of evaporation stress index indicates that evaporation stress is slowing down; similarly, mode S2 indicates that evaporation stress is slowing down; mode S3 indicates that evaporation stress changes from slowing down to aggravating; mode S4 indicates that evaporation stress changes from aggravating to slowing down; mode S5 indicates that evaporation stress is slowing down and aggravating; mode S6 indicates that evaporation stress is accelerating and aggravating; After determining the oscillation patterns of adjacent moments, the evaporation stress index time series ESI is labeled, that is, the evaporation stress index time series is converted into a labeled pattern sequence; Step 5, calculate the frequency or duration of each oscillation mode: the frequency F is defined as the ratio of the number of occurrences of a certain oscillation mode during the entire research period to the total number of occurrences of all oscillation modes; the duration D is defined as the duration of a certain oscillation mode divided by the number of occurrences of the oscillation mode, which represents the average duration of a certain oscillation mode each time it appears during the research period; when calculating the duration D, the influence of the continuous occurrence of the oscillation mode is emphasized. For the labeled pattern sequence, when calculating the denominator of the duration D, if the pattern S1 appears multiple times in a row, it is counted as once; the specific calculation process is as follows: Assume that there are N types of oscillation modes during the study period, N≤6, mode S i The number of times it occurs during the study period is n i , then the frequency F i for: in, represents the sum of the number of occurrences of all patterns; Duration D i Indicates a certain oscillation mode S i The average duration of each occurrence during the study period, assuming mode S i The number of segments is m i , the total time of each segment is L k ×Δt, where L k is the pattern S in the kth segment i The number of consecutive occurrences of Mode S i The total duration T i Expressed as the sum of the times of all consecutive segments: Mode S i Duration D i Expressed as the total duration of the pattern T i Divide by the number of segments m i : That is, when mode S i If a segment appears continuously in a certain period, the duration of this segment is counted only once when calculating the duration; Step 6. Diagnose the dominant mode of evaporation stress and regional water conditions: Count the maximum values ​​of the frequency or duration of each oscillation mode during the entire study period to diagnose the dominant mode of evaporation stress and further determine the regional water conditions.

2. A regional water status diagnosis method based on evaporative stress oscillation mode according to claim 1, characterized in that: The actual evapotranspiration time series ETa and the potential evapotranspiration time series ETp of the study area described in step 1 are obtained by downloading public data from the Internet or observing actual meteorological data.

3. The method for diagnosing regional water conditions based on evaporative stress oscillation mode according to claim 1, characterized in that: The dominant mode of diagnosing evaporative stress in step 6 and further determining the regional water status are as follows: If the dominant mode is S1, the region has a strong ability to alleviate evaporation stress on a multi-year average scale, indicating that the water conditions in the region are good; If the dominant mode is S2, the region has the ability to alleviate evaporation stress on a multi-year average scale, indicating that the water conditions in the region are good; If the dominant mode is S3, the region has the ability to alleviate evaporation stress in a short time on a multi-year average scale, but evaporation stress still turns to aggravation, indicating that the water condition in the region is poor; If the dominant mode is S4, the region has a certain ability to alleviate evaporation stress from the aggravating trend on a multi-year average scale, indicating that the water condition in the region is still good; If the dominant mode is S5, the region does not have the ability to alleviate evaporation stress on a multi-year average scale, and evaporation stress continues to increase, indicating that the water conditions in the region are poor; If the dominant mode is S6, the region has no ability to alleviate evaporation stress on a multi-year average scale, and evaporation stress continues to accelerate, indicating that the water conditions in the region are extremely poor.

Images