Regional moisture condition diagnosis method based on evaporation stress oscillation mode

Abstract

The invention discloses a regional moisture condition diagnosis method based on an evaporation stress oscillation mode. The method comprises the following steps: step 1, data acquisition; 2, calculating an evaporation stress index time sequence; 3, calculating the development speed of the evaporation stress index; 4, determining an oscillation mode of the evaporation stress index; 5, calculating the frequency or duration of each oscillation mode; and step 6, diagnosing the evaporation stress dominant mode and the regional moisture condition. The method provided by the invention effectively solves the problems that information is missed and a stress state evolution mechanism cannot be reflected by smoothing a long-term sequence in a current regional moisture condition diagnosis process, and provides reliable theoretical and technical support for the diagnosis and evaluation of an evaporation stress dominant mode and a regional moisture condition.

Description

Technical Field

[0001] The invention belongs to the technical field of ecohydrology, and in particular relates to a method for diagnosing regional water conditions based on an evaporation stress oscillation mode. Background Art

[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 surface, including evaporation and plant transpiration; while potential evapotranspiration is the amount of water that can be evaporated from the surface and transpired by plants under ideal conditions assuming that water is not restricted. The evaporation stress index can reflect the dynamic balance between water supply and demand. The oscillation pattern of the evaporation stress index is mainly affected by climate disturbances. It can sensitively reveal the state of regional water stress and is often used as an indicator for studying drought. It has important indicative significance for early warning of drought. Therefore, studying the evaporation stress oscillation pattern can reveal the main characteristics of water stress in the study area, judge the quality of regional water conditions, and 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 judging regional water conditions, the more 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 regional water conditions from different perspectives. For example, by calculating the average precipitation over many years and combining it with the dry and wet zone division criteria, regional water conditions can be diagnosed: if the average precipitation over many years exceeds 800 mm, the area is considered to be a humid area with good water conditions. However, this method based on long-term averages will smooth out short-term abnormal changes, resulting in the loss of potentially important information, and cannot reflect seasonal and interannual water changes. It also lacks in-depth analysis of specific causes, so it has limitations in exploring the dominant mode of regional water stress and diagnosing water conditions. The Chinese patent with publication number CN117058433A discloses an eco-hydrological zoning method based on a Gaussian mixture clustering algorithm. The patent selects indicators that can reflect the hydrological, meteorological, ecological, land use, and socio-economic characteristics of the study area, constructs an indicator system, determines the indicator weights through 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, and divides the study area into several eco-hydrological zones. However, this method is still based on statistical identification of long-term average states, and a diagnostic method based on evolutionary mechanisms has not yet been proposed. Summary of the invention

[0004] The object of the present invention is to provide a method for diagnosing regional water conditions based on an evaporative stress oscillation model to solve the above technical problems.

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

[0006] The present invention discloses a method for diagnosing regional water conditions based on an evaporative stress oscillation mode, the method comprising the following steps:

[0007] Step 1: Data acquisition: Obtain the actual evapotranspiration time series ETa and potential evapotranspiration time series ETp of the study 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 the evaporation stress index time series ESI is obtained;

[0009]

[0010] 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;

[0011] 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:

[0012]

[0013] 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 change of time;

[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 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:

[0015]

[0016] 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;

[0017] 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;

[0018] 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 study 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 study period; assuming that the time resolution of the data is Δt, the influence of the continuous occurrence of the oscillation mode is emphasized when calculating the duration D. For the labeled pattern sequence, when calculating the denominator of the duration D, if the pattern S1 appears multiple times in succession, it is counted as once; the specific calculation process is as follows:

[0019] 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:

[0020]

[0021] in, represents the sum of the number of occurrences of all patterns;

[0022] 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 , Δs is the time resolution of the data;

[0023] Mode S i The total duration T i Expressed as the sum of the times of all consecutive segments:

[0024]

[0025] Mode Si Duration D i Expressed as the total duration of the pattern T i Divide by the number of segments m i :

[0026]

[0027] 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;

[0028] 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.

[0029] Furthermore, 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.

[0030] Furthermore, the dominant mode of diagnosing evaporative stress in step 6 and further determining the regional water status are specifically:

[0031] 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;

[0032] 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;

[0033] 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;

[0034] 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;

[0035] 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;

[0036] 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.

[0037] The beneficial effect of the present invention is that the method of the present invention can determine the state change mechanism of regional evaporative stress that has mainly presented over the years, thereby analyzing whether the region has the ability to alleviate the evaporative stress state on a long-term scale, and then diagnosing the water condition of the region. The method of the present invention effectively solves the problem of missing information and failing to reflect the evolution mechanism of the stress state in the current regional water condition diagnosis process by smoothing long-term series, and provides reliable theoretical and technical support for the diagnosis and evaluation of the dominant mode of evaporative stress and regional water conditions.

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

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

[0040] Figure 2 This is a schematic diagram of the calculation process of the development speed of the evaporative stress index;

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

[0042] Figure 4 Schematic diagram of converting the evaporative stress index time series into a labeled pattern series. DETAILED DESCRIPTION

[0043] The present invention discloses a method for diagnosing regional water conditions based on an evaporative stress oscillation mode, and the principle on which the method is based is as follows:

[0044] The evaporation stress index is defined as the ratio of actual evaporation to potential evaporation. The evaporation stress index directly quantifies the ratio of actual water supply to potential demand in the region, and can reflect the water supply and demand situation in the region. At adjacent moments, combined with the numerical changes of the evaporation stress index itself and the speed comparison of the changes before and after, there can be six types of oscillation modes at adjacent moments, namely, accelerated slowdown, deceleration slowdown, reversal from slowdown to aggravation, reversal from aggravation to slowdown, deceleration aggravation, and accelerated aggravation. By counting the patterns with the highest frequency and duration over a period of time, the dominant mode of evaporation stress can be diagnosed. If the dominant mode diagnosed is the "slowdown" mode, it means that the region has a certain ability to alleviate evaporation stress in the process of the evolution of evaporation stress on the multi-year average scale, proving that the regional water situation is still good, otherwise, the water situation is scarce. Therefore, the oscillation mode of the evaporation stress index can be used to diagnose the water stress situation in the region. However, traditional diagnostic methods based on long-term average values ​​cannot reflect seasonal or interannual changes, or lack analysis of the causes of water stress. Therefore, using the evaporation stress oscillation pattern to identify the dominant mechanism of evaporation stress and further diagnose the regional water stress status is conducive to revealing the main characteristics of regional water stress and further providing strong support and decision-making basis for water resources evaluation and management.

[0045] The specific steps include: Figure 1 As shown:

[0046] Step 1: Data acquisition: Obtain the actual evapotranspiration time series ETa and potential evapotranspiration time series ETp of the study area, which are generally obtained by downloading public data from the Internet or observing actual meteorological data, for example, they can be downloaded from the European Center for Medium-Range Weather Forecasts network.

[0047] 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;

[0048]

[0049] 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;

[0050] The smaller the value of the evaporation stress index, the more severe the evaporation stress situation is.

[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 speed of evaporation stress index; ΔESI is the change of evaporation stress index in a period of time; Δt is the change of time; Figure 2 shown.

[0054] 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:

[0055]

[0056] 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 DSI 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; Figure 3 shown.

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

[0058] Step 5. Calculate the frequency or duration of each oscillation mode: The frequency F is defined as the ratio of the number of times a certain oscillation mode appears during the entire study period to the total number of times all oscillation modes appear. The duration D is defined as the duration of a certain oscillation mode divided by the number of times the oscillation mode appears, which represents the average duration of a certain oscillation mode each time it appears during the study period. Since the time resolution of the data downloaded or observed is fixed, taking the data with a time resolution of Δt as an example, the calculation of the duration D emphasizes the influence of the continuous occurrence of the oscillation mode. 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 1 time. The specific calculation process is as follows:

[0059] Assume that there are N types of oscillation modes (N≤6) during the study period, mode S i The number of times it occurs during the study period is n i , then the frequency F i for:

[0060]

[0061] in, Represents the sum of the number of occurrences of all patterns.

[0062] Duration D i Indicates a certain oscillation mode S i The average duration of each occurrence during the study period. Assuming that the 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 , Δt is the time resolution of the data.

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

[0064]

[0065] Mode S i Duration D i It can be expressed as the total duration of the pattern T i Divide by the number of segments m i :

[0066]

[0067] This means that when mode S iWhen a pattern appears continuously in a certain segment, the duration of this segment is counted only once when calculating the duration. Therefore, the number of segments of the pattern is m. i It reflects the number of these uninterrupted segments, not the number of each individual occurrence.

[0068] Step 6. Diagnosis of the dominant mode of evaporation stress and regional water conditions: During the entire study period, the dominant mode of evaporation stress was diagnosed by counting the maximum value of the frequency or duration of each oscillation mode, and the regional water conditions were further judged. The oscillation mode can reflect whether the trend of evaporation stress is "increasing" or "reducing". Therefore, according to the oscillation mode with the highest frequency or the longest duration, the dominant mode of evaporation stress in the study area can be identified and the regional water conditions can be judged, as shown in Table 1. For example, if the statistical results show that the oscillation mode with the highest frequency or the longest duration is S1 (evaporation stress accelerated reduction mode), it means that 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.

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

[0070]

[0071]

[0072] Embodiment 1

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

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

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

[0076] The evaporation stress index time series on each grid in China was calculated based on the downloaded actual evapotranspiration and potential evapotranspiration time series. The values ​​of the series fluctuated continuously between 0.70 and 0.75.

[0077] By calculating the difference before and after the evaporation stress index time series and dividing it by the time resolution, i.e., 1 month, the development speed series of the monthly evaporation stress index is obtained, with values ​​ranging from -0.61 to 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 values ​​of the evaporation stress index and the development speed of the evaporation stress index at adjacent moments are compared to determine the oscillation pattern of the evaporation stress index, and then a labeled oscillation pattern sequence is obtained.

[0079] The frequency of each oscillation mode in the study area from 1950 to 2020 was calculated, and the oscillation mode with the highest frequency on each grid was counted and spatially distributed. According to the statistical results, about 79.6% of the study area from 1950 to 2020 had mode S3 (i.e., evaporation stress reversed from mitigation to aggravation) as the oscillation mode with the highest frequency, and this dominant mode was mainly distributed in areas with poor water conditions in the north; about 19.0% of the study area had mode S4 (i.e., evaporation stress reversed from aggravation to mitigation) as the oscillation mode with the highest frequency, and it was mainly distributed in the south or areas with dense forests with good water conditions.

[0080] The above examples demonstrate the effectiveness and accuracy of the method of the present invention in diagnosing the dominant mode of evaporative stress and regional water conditions.

[0081] Finally, it should be noted that the above is only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred arrangement scheme, a person skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents 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; WTp 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 change of time; 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 study 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 study period; assuming that the time resolution of the data is Δt, the influence of the continuous occurrence of the oscillation mode is emphasized when calculating the duration D. For the labeled pattern sequence, when calculating the denominator of the duration D, if the pattern S1 appears multiple times in succession, 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 , Δt is the time resolution of the data; 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.

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