A method and system for detecting rapid temperature changes in lake water.

Abstract

This invention discloses a method and system for detecting abrupt temperature changes in lake water. The method includes: acquiring daily time-series data of lake water temperature and calculating the diurnal temperature variation range to obtain a maximum temperature rise sequence and a maximum temperature fall sequence; calculating the quantile thresholds corresponding to the maximum temperature rise and maximum temperature fall sequences to obtain a temperature rise threshold sequence and a temperature fall threshold sequence; and detecting two types of abrupt temperature change events—cold-to-warm and hot-to-cold—based on these sequences, calculating the frequency, duration, intensity, and speed of occurrence of each event, thereby achieving the detection of abrupt temperature changes in lake water. This invention can characterize the rapid change process of lake water temperature on a daily scale, enabling systematic detection and multi-dimensional feature quantification of abrupt temperature changes in lake water. As a method and system for detecting abrupt temperature changes in lake water, this invention can be widely applied in the field of water body monitoring technology.

Description

Technical Field

[0001] This invention relates to the field of water monitoring technology, and in particular to a method and system for detecting rapid temperature changes in lake water. Background Technology

[0002] Lake water temperature is a crucial factor influencing the structure and function of lake ecosystems, playing a key regulatory role in physical, chemical, and biological processes within lakes. Changes in water temperature not only affect the thermal stratification of lakes but also significantly impact dissolved oxygen distribution, nutrient cycling, and phytoplankton growth, thereby affecting water quality and ecosystem stability. With the continued impact of climate change, lake systems are increasingly affected by extreme hydrological and climatic events, leading to more complex characteristics of lake water temperature variations and an increased frequency of extreme high and low temperature events, significantly impacting terrestrial aquatic ecosystems.

[0003] Compared to single warming or cooling processes, rapid temperature transitions in lakes, occurring within a short period or from hot to cold, are more abrupt. These changes are characterized by large amplitude and short duration, often making it difficult for ecosystems and related management measures to respond promptly, thus generating more significant impacts. Such processes can be defined as abrupt temperature change events in lakes, i.e., rapid transitions in lake water temperature from low to high or from high to low within a short period (several days). However, current technologies primarily focus on detecting long-term trends in lake water temperature or single extreme high / low temperature events, and cannot effectively characterize these rapid transitions on short timescales. Summary of the Invention

[0004] To address the aforementioned technical problems, the present invention aims to provide a method and system for detecting rapid temperature changes in lake water, which can characterize the rapid temperature change process of lake water on a daily scale and achieve systematic detection and multi-dimensional feature quantification of rapid temperature changes in lake water.

[0005] The first technical solution adopted in this invention is: a method for detecting rapid temperature changes in lake water, comprising the following steps: Obtain daily time series data of lake water temperature and calculate the inter-day water temperature variation to obtain the maximum temperature rise and maximum temperature drop sequences; Construct a calendar-day sliding window, calculate the quantile thresholds corresponding to the maximum temperature rise and maximum temperature fall sequences, and obtain the temperature rise threshold sequence and the temperature fall threshold sequence. Based on the heating and cooling threshold sequences, two types of rapid temperature change events, namely cold-to-heat and hot-to-cold, are detected. The frequency, duration, intensity, and speed of these events are calculated to achieve the detection of rapid temperature change events in lake water.

[0006] Furthermore, the step of acquiring daily time-series data of lake water temperature and calculating the inter-day water temperature variation to obtain the maximum temperature rise sequence and the maximum temperature drop sequence specifically includes: Obtain daily time series data of lake water temperature within a target area within a preset time period; Based on a preset time window, the daily water temperature variation range of the lake is calculated using daily time series data, resulting in the maximum temperature rise and maximum temperature drop sequences.

[0007] Furthermore, the specific expression for calculating the diurnal temperature variation amplitude of the daily time series data of lake water temperature is as follows: In the above formula, Indicates the first The lake water temperature of the day, Indicates the number of days to look back. Indicates the preset time window length. This represents the sequence of maximum temperature increases. This represents the sequence of maximum temperature drop.

[0008] Furthermore, the step of constructing a calendar-day sliding window and calculating the quantile thresholds corresponding to the maximum temperature rise and maximum temperature fall sequences to obtain the temperature rise threshold sequence and the temperature fall threshold sequence specifically includes: Within the climate baseline period, a sliding time window centered on that day is constructed based on the temperature change amplitude sequence to obtain a calendar-day sliding window; Based on a calendar-day sliding window, the quantile thresholds corresponding to the maximum temperature rise and maximum temperature fall sequences are calculated to obtain the temperature rise threshold sequence and the temperature fall threshold sequence.

[0009] Furthermore, the specific expressions for calculating the quantile thresholds corresponding to the maximum temperature rise sequence and the maximum temperature fall sequence are as follows: In the above formula, Represents the temperature rise threshold sequence. Represents the cooling threshold sequence. This indicates that the heating end is preset to a percentile. This indicates that the cooling end is preset to a percentile. Indicates the half width of the window. This represents the sequence of maximum temperature increases. This represents the sequence of maximum temperature drop. Indicates the day order within a calendar year. This indicates a sliding time window centered on the current calendar day. , This represents the conditional quantile function.

[0010] Furthermore, the step of detecting two types of abrupt temperature change events—cold-to-hot and hot-to-cold—based on heating and cooling threshold sequences, and calculating the frequency, duration, intensity, and speed of these events to achieve the detection of abrupt temperature change events in lake water, specifically includes: Based on the relationship between the quantile thresholds corresponding to the maximum temperature rise and maximum temperature fall sequences, two types of abrupt transition events, namely cold-to-heat and hot-to-cold, are detected to obtain independent cold-to-heat event sequences and independent hot-to-cold event sequences. For independent cold-to-hot event sequences and independent hot-to-cold event sequences, the occurrence frequency, duration, intensity of rapid change, and speed of rapid change of events are calculated to detect rapid cold-to-hot changes in lake water temperature.

[0011] Furthermore, the step of detecting two types of abrupt transition events—cold-to-hot and hot-to-cold—based on the relationship between the quantile thresholds corresponding to the maximum temperature rise sequence and the maximum temperature fall sequence, and constructing an independent event sequence, specifically includes: If the maximum temperature rise sequence is greater than the temperature rise threshold sequence, it is detected as a cold-to-hot abrupt change event; If the maximum temperature drop sequence is less than the temperature drop threshold sequence, it is detected as a rapid thermal-to-cold transition event. If the time interval between adjacent cold-to-hot rapid transition events or adjacent hot-to-cold rapid transition events is less than the event interval parameter, they are considered as the same rapid transition process, and only the first event is retained, resulting in independent cold-to-hot event sequences and independent hot-to-cold event sequences.

[0012] Furthermore, the step of calculating the occurrence frequency, duration, intensity, and speed of rapid temperature changes in lake water for both independent cold-to-hot and independent hot-to-cold event sequences, to detect rapid temperature changes in lake water, specifically includes: Based on the preset study period, the occurrence frequency of independent cold-to-hot event sequences and independent hot-to-cold event sequences is obtained by cumulative statistics. For each detected independent cold-to-hot event sequence and independent hot-to-cold event sequence, determine the time scale corresponding to when the event reaches its extreme value, and obtain the duration of the event; The intensity of the sudden change in events is determined by the interday water temperature variation range corresponding to the independent cold-to-hot event sequence and the independent hot-to-cold event. The abrupt change rate of an event is obtained by comparing the abrupt change intensity to the corresponding duration of an independent cold-to-hot event sequence with that of an independent hot-to-cold event. By combining the frequency, duration, intensity, and speed of the event, the characteristics of rapid temperature changes in lake water can be quantified.

[0013] The second technical solution adopted in this invention is: a detection system for rapid temperature changes in lake water, comprising: The first module is used to acquire daily time series data of lake water temperature and calculate the daily water temperature variation range to obtain the maximum temperature rise range sequence and the maximum temperature drop range sequence. The second module is used to construct a calendar-day sliding window, calculate the quantile thresholds corresponding to the maximum temperature rise and maximum temperature fall sequences, and obtain the temperature rise threshold sequence and the temperature fall threshold sequence. The third module is used to detect two types of rapid temperature change events: cold-to-hot and hot-to-cold, based on the heating threshold sequence and the cooling threshold sequence. It calculates the occurrence frequency, duration, intensity, and speed of the events, thereby enabling the detection of rapid temperature change events in lake water.

[0014] The beneficial effects of the method and system of this invention are as follows: This invention obtains daily time series data of lake water temperature and calculates the inter-day water temperature variation range to obtain the maximum warming range sequence and the maximum cooling range sequence. Based on the daily time series of lake water temperature, a temperature variation range index is constructed within a limited time window to characterize the maximum warming and cooling process of water temperature on a short time scale. Furthermore, a daily sliding window is constructed to calculate the quantile thresholds corresponding to the maximum warming range sequence and the maximum cooling range sequence, obtaining the warming threshold sequence and the cooling threshold sequence. This allows for the construction of a temperature variation range index. By combining the indicators with the daily moving quantile threshold, the system effectively detects cold-to-warm and hot-to-cold processes, overcoming the shortcomings of existing methods in characterizing rapid transitions over short timescales. Finally, based on warming and cooling threshold sequences, the system detects two types of abrupt transition events: cold-to-warm and hot-to-cold. It calculates the frequency, duration, intensity, and speed of these events, enabling the detection of abrupt cold-to-warm transition events in lake water temperature. This allows the system to characterize the rapid transition process of lake water temperature on a daily scale, achieving systematic detection and multi-dimensional feature quantification of abrupt cold-to-warm transition events in lake water temperature. Attached Figure Description

[0015] Figure 1 This is a flowchart of the steps of a method for detecting rapid temperature changes in lake water according to the present invention; Figure 2 This is a structural block diagram of a detection system for rapid temperature changes in lake water according to the present invention. Detailed Implementation

[0016] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments. The step numbers in the following embodiments are only for ease of explanation and do not limit the order of the steps. The execution order of each step in the embodiments can be adapted according to the understanding of those skilled in the art.

[0017] First, it should be noted that the embodiments of the present invention address the shortcomings of existing technologies, which mainly focus on detecting long-term trends in lake water temperature or single extreme high / low temperature events, and lack effective detection and quantification methods for rapid and significant temperature changes in lake water within a short period of time. The present invention proposes a method for detecting rapid temperature changes in lake water based on the diurnal temperature variation amplitude and the moving quantile threshold. This method enables the detection and quantitative characterization of different processes such as cold-to-hot and hot-to-cold transitions, thereby improving the ability to characterize rapid temperature change processes in lakes.

[0018] Reference Figure 1 This invention provides a method for detecting rapid temperature changes in lake water, the method comprising the following steps: S100. Obtain daily time series data of lake water temperature and calculate the inter-day water temperature variation to obtain the maximum temperature rise sequence and the maximum temperature drop sequence. S110. Obtain daily time series data of lake water temperature within a target range within a preset time period; In this embodiment, daily time series data of lake water temperature over a large area within a set time period are obtained. Specifically, the lake water temperature data is daily continuous time series data obtained based on numerical simulation or observation.

[0019] S120. Based on a preset time window, calculate the daily water temperature variation range of the lake's daily time series data to obtain the maximum temperature rise range sequence and the maximum temperature drop range sequence.

[0020] In this embodiment, the daily water temperature variation is calculated based on the daily water temperature sequence within a given time window to obtain the maximum temperature rise sequence and the maximum temperature drop sequence.

[0021] The water temperature variation range is calculated as follows, over a given time scale. Below, for any number of... Before the calculation The temperature difference within the day is calculated, and the maximum and minimum values ​​are taken respectively to obtain the sequence of maximum temperature rise. and the maximum cooling rate sequence Its expression is: in, Indicates the first The lake water temperature of the day, Indicates the number of days to look back. The preset time window length.

[0022] S200. Construct a calendar-day sliding window, calculate the quantile thresholds corresponding to the maximum temperature rise and maximum temperature fall sequences, and obtain the temperature rise threshold sequence and the temperature fall threshold sequence. S210. Within the climate baseline period, a sliding time window centered on that day is constructed based on the temperature change amplitude sequence to obtain a calendar-day sliding window. S220. Based on a daily sliding window, calculate the quantile thresholds corresponding to the maximum temperature rise sequence and the maximum temperature fall sequence to obtain the temperature rise threshold sequence and the temperature fall threshold sequence.

[0023] In this embodiment, a calendar-day sliding window is constructed based on the climate baseline period, and the corresponding quantile thresholds are calculated based on the maximum warming amplitude sequence and the maximum cooling amplitude sequence.

[0024] The quantile threshold is calculated using a sliding time window, targeting the quantile threshold within the climatic baseline period. For each day, a sliding time window centered on that day is constructed based on the temperature change amplitude sequence, and the corresponding quantile threshold is calculated within the window to obtain the temperature rise threshold sequence. and cooling threshold sequence Its expression is: in, For preset percentiles, The width is half the width of the window.

[0025] S300, based on heating threshold sequences and cooling threshold sequences, detects two types of rapid temperature change events: cold-to-hot and hot-to-cold. It calculates the occurrence frequency, duration, intensity, and speed of these events to achieve the detection of rapid temperature change events in lake water.

[0026] S310. Based on the relationship between the quantile thresholds corresponding to the maximum temperature rise sequence and the maximum temperature fall sequence, detect two types of rapid transition events: cold to heat and hot to cold, and obtain independent cold to heat event sequences and independent hot to cold event sequences. Specifically, if the maximum temperature rise sequence is greater than the temperature rise threshold sequence, it is detected as a cold-to-hot rapid transition event; if the maximum temperature drop sequence is less than the temperature drop threshold sequence, it is detected as a hot-to-cold rapid transition event. An event interval parameter is set. If the time interval between adjacent cold-to-hot rapid transition events or adjacent hot-to-cold rapid transition events is less than the event interval parameter, they are regarded as the same rapid transition process. Only the first event is retained, resulting in independent cold-to-hot event sequences and independent hot-to-cold event sequences.

[0027] In this embodiment, based on the relationship between the maximum temperature rise sequence, the maximum temperature drop sequence and the corresponding quantile threshold, two types of rapid transition events, namely cold to heat and hot to cold, are detected, and independent event sequences are extracted.

[0028] The following criteria are used to detect sudden turning events: When a The temperature rise of the day meets the requirements When the temperature drops, it is detected as a rapid transition from cold to hot; when the temperature drop meets the following criteria... When the event is detected as a rapid transition from hot to cold, a daily event sequence is constructed.

[0029] By setting the event interval parameter The event sequence is merged: when the time interval between two adjacent events is less than 100 minutes... By considering the timing as a single abrupt change process, only the moment of its first occurrence is retained as the starting point of the event, while the remaining events are discarded, thus obtaining an independent sequence of abrupt change events.

[0030] S320. For independent cold-to-hot event sequences and independent hot-to-cold event sequences, calculate the occurrence frequency, duration, intensity of rapid change, and speed of rapid change of events respectively, so as to realize the detection of rapid cold-to-hot change events in lake water temperature.

[0031] Specifically, based on a pre-defined research period, the occurrence frequency of independent cold-to-hot and independent hot-to-cold event sequences is obtained by cumulatively analyzing them. For each detected independent cold-to-hot and independent hot-to-cold event sequence, the time scale corresponding to the event reaching its extreme value is determined, thus obtaining the event's duration. The intensity of the abrupt change in water temperature is determined based on the diurnal water temperature variation corresponding to the independent cold-to-hot and independent hot-to-cold event sequences. The abrupt change velocity is obtained based on the ratio of the abrupt change intensity to the corresponding duration of the independent cold-to-hot and independent hot-to-cold event sequences. By combining the event occurrence frequency, duration, abrupt change intensity, and abrupt change velocity characteristics, the features of abrupt cold-to-hot water temperature change events in lakes are quantified.

[0032] In this embodiment, based on the independent event sequence, the occurrence frequency, duration, speed of change, and intensity of change of the two types of sudden change events are calculated respectively.

[0033] The frequency of events was obtained by cumulatively analyzing the independent event sequences over the study period. The duration of an event is determined by the timescale corresponding to when the temperature change reaches its extreme value. For each moment detected as the start of an event, its duration is taken as the time interval between the occurrence of the corresponding extreme value. Specifically, a rapid transition from cold to hot corresponds to... The corresponding event of rapid change from hot to cold ; The intensity of a sudden change in event is defined as the maximum temperature change amplitude for a sudden change in event, where for the first event... The intensity of the abrupt transition from cold to hot weather detected by the weather system was: For the first The intensity of the rapid transition from heat to cold detected by the weather system was: ; The event spin rate is defined as the ratio of spin intensity to the corresponding duration.

[0034] Finally, the embodiments of the present invention will be explained and illustrated with reference to specific examples: First, this embodiment of the invention acquires daily time series data of lake water temperature over a large area within a set time period; then, within a given time window, it calculates the inter-day water temperature change amplitude based on the daily water temperature sequence to obtain the maximum warming amplitude sequence and the maximum cooling amplitude sequence; further, it constructs a daily sliding window based on a climate baseline period, and calculates the corresponding quantile thresholds based on the maximum warming amplitude sequence and the maximum cooling amplitude sequence in S2; according to the relationship between the maximum warming amplitude sequence, the maximum cooling amplitude sequence and the corresponding quantile thresholds, it detects two types of abrupt change events: cold-to-warm and hot-to-cold, and extracts independent event sequences; finally, based on the independent event sequences, it calculates the occurrence frequency, duration, abrupt change intensity, and abrupt change speed characteristic indicators for the two types of abrupt change events respectively.

[0035] This invention proposes a method for detecting abrupt temperature changes in lake water, capable of characterizing rapid temperature transitions within a short period on a daily timescale. Compared to existing technologies that primarily focus on long-term trends or single extreme high / low temperature events, this invention, by constructing a temperature change amplitude index and combining it with a daily moving quantile threshold, effectively detects both cold-to-warm and hot-to-cold transitions, overcoming the shortcomings of existing methods in characterizing rapid transitions on short timescales. The abrupt temperature changes detected by this invention reflect sudden thermal changes in lake systems, providing technical support for monitoring, analyzing, and assessing abrupt changes in lake thermal states under climate change conditions. Furthermore, this method, based on daily time-series data, has a clear calculation process and well-defined parameter settings, is applicable to multi-source temperature data, and possesses good versatility and scalability.

[0036] Furthermore, lake surface water temperature data from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) phase 2b lake dataset were selected as input data, covering the period from 1980 to 2100, with a daily temporal resolution and a spatial resolution of 0.5° × 0.5°. This data was generated by the SimStrat-UoG lake model and driven by multiple bias-corrected climate models.

[0037] Then set the time window length Heaven. For any first... Calculate the water temperature difference over the previous 3 days, and take the maximum and minimum values ​​respectively to obtain the maximum temperature rise sequence. and the maximum cooling rate sequence Its expression is: in, Indicates the first The surface water temperature of the lake on that day, This indicates the number of days to look back. The time intervals corresponding to the reaching of the maximum temperature rise and fall are recorded synchronously and denoted as follows: and .

[0038] The period from 1991 to 2020 was selected as the climate baseline. For the first [year] of the year... The day is constructed with that day as the center and half its width as... A sliding time window of days is used to extract the corresponding data within that window. and Samples are analyzed, and their quantile thresholds are calculated. Quantile parameters are set. The heating threshold sequence was obtained. and cooling threshold sequence Its expression is: For any i Day, according to its corresponding calendar day Compare the temperature change amplitude with the threshold: when At that time, the detection indicated a rapid transition from cold to hot; when When the event is detected as a rapid transition from hot to cold, a daily event sequence is constructed.

[0039] Further configure the event interval parameters When the time interval between two adjacent events is less than 3 days, they are considered as the same abrupt change process, and only the moment of the first occurrence is retained as the starting point of the event, thus obtaining an independent abrupt change event sequence.

[0040] Statistical analysis was performed on the independent event sequences: The frequency of events is obtained by cumulatively counting the starting points of events within the study period; The duration of the event is determined by the time interval corresponding to when the temperature change reaches its extreme value, where for the first time interval... The duration of the sudden cold-to-hot transition event detected by the weather system is taken as the corresponding... For the first The duration of the rapid thermal-to-cold transition event detected by the weather system is taken as the corresponding... ; The intensity of a sudden change in event is defined as the maximum temperature change amplitude for a sudden change in event, where for the first event... The intensity of the abrupt transition from cold to hot weather detected by the weather system was: For the first The intensity of the rapid transition from heat to cold detected by the weather system was: ; The event rapidity is defined as the ratio of rapidity intensity to duration; that is, a cold-to-hot rapid event is... The event of a rapid shift from hot to cold is .

[0041] Therefore, this invention, based on daily time series of lake water temperature, constructs a temperature change amplitude index within a limited time window to characterize the maximum warming and cooling processes of water temperature on a short time scale. Building upon this, it establishes a seasonally varying quantile threshold system by combining a sliding statistical window for each calendar day. Furthermore, by comparing the temperature change amplitude with the corresponding threshold, it achieves the detection and quantitative characterization of rapid transitions in lake water temperature from cold to hot and from hot to cold. Compared to existing technologies that primarily focus on long-term trends or single extreme events, this invention can characterize the rapid transitions in lake water temperature on a daily scale, enabling systematic detection and multi-dimensional feature quantification of abrupt temperature changes in lake water.

[0042] In summary, the embodiments of this invention can characterize the rapid cooling and heating transitions of lake water temperature over a short period of time on a daily timescale. Compared to existing technologies that mainly focus on long-term trends in lake water temperature or single extreme high / low temperature events, this invention, by constructing a temperature change amplitude index and combining it with a daily moving quantile threshold, achieves effective detection of cold-to-warm and hot-to-cold processes, thus overcoming the shortcomings of existing methods in characterizing rapid transitions over short timescales. The abrupt cooling and heating events in lake water temperature detected by this invention can reflect the sudden thermal change processes in lake systems, providing technical support for the monitoring, analysis, and risk assessment of abrupt changes in lake thermal state under the background of climate change. Furthermore, this method, based on daily time series data, has a clear calculation process and well-defined parameter settings, is applicable to multi-source temperature data, and possesses good versatility and scalability.

[0043] Reference Figure 2 A detection system for rapid temperature changes in lake water, comprising: The first module 201 is used to acquire daily time series data of lake water temperature and calculate the daily water temperature change range to obtain the maximum temperature rise range sequence and the maximum temperature drop range sequence. The second module 202 is used to construct a calendar-day sliding window, calculate the quantile thresholds corresponding to the maximum temperature rise sequence and the maximum temperature fall sequence, and obtain the temperature rise threshold sequence and the temperature fall threshold sequence. The third module 203 is used to detect two types of rapid temperature change events, namely cold-to-hot and hot-to-cold, based on the heating threshold sequence and the cooling threshold sequence. It calculates the occurrence frequency, duration, intensity and speed of the events, and realizes the detection of rapid temperature change events in lake water.

[0044] The content of the above method embodiments is applicable to this system embodiment. The specific functions implemented in this system embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0045] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this is not intended to limit the scope of the embodiments of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the embodiments of the present application.

Claims

1. A method for detecting rapid temperature changes in lake water, characterized in that, Includes the following steps: Obtain daily time series data of lake water temperature and calculate the inter-day water temperature variation to obtain the maximum temperature rise and maximum temperature drop sequences; Construct a calendar-day sliding window, calculate the quantile thresholds corresponding to the maximum temperature rise and maximum temperature fall sequences, and obtain the temperature rise threshold sequence and the temperature fall threshold sequence. Based on the heating and cooling threshold sequences, two types of rapid temperature change events, namely cold-to-heat and hot-to-cold, are detected. The frequency, duration, intensity, and speed of these events are calculated to achieve the detection of rapid temperature change events in lake water.

2. The method for detecting rapid temperature changes in lake water according to claim 1, characterized in that, The step of acquiring daily time-series data of lake water temperature and calculating the inter-day water temperature variation to obtain the maximum temperature rise sequence and the maximum temperature drop sequence specifically includes: Obtain daily time series data of lake water temperature within a target area within a preset time period; Based on a preset time window, the daily water temperature variation range of the lake is calculated using daily time series data, resulting in the maximum temperature rise and maximum temperature drop sequences.

3. The method for detecting rapid temperature changes in lake water according to claim 2, characterized in that, The specific expression for calculating the inter-day water temperature variation amplitude based on the daily time series data of lake water temperature is as follows: In the above formula, Indicates the first The lake water temperature of the day, Indicates the number of days to look back. Indicates the preset time window length. This represents the sequence of maximum temperature increases. This represents the sequence of maximum temperature drop.

4. The method for detecting rapid temperature changes in lake water according to claim 3, characterized in that, The step of constructing a calendar-day sliding window and calculating the quantile thresholds corresponding to the maximum temperature rise and maximum temperature fall sequences to obtain the temperature rise threshold sequence and the temperature fall threshold sequence specifically includes: Within the climate baseline period, a sliding time window centered on that day is constructed based on the temperature change amplitude sequence to obtain a calendar-day sliding window; Based on a calendar-day sliding window, the quantile thresholds corresponding to the maximum temperature rise and maximum temperature fall sequences are calculated to obtain the temperature rise threshold sequence and the temperature fall threshold sequence.

5. The method for detecting rapid temperature changes in lake water according to claim 4, characterized in that, The specific expressions for calculating the quantile thresholds corresponding to the maximum temperature rise and maximum temperature fall sequences are as follows: In the above formula, Represents the temperature rise threshold sequence. Represents the cooling threshold sequence. This indicates that the preset percentage for the heating end is... This indicates that the cooling end is preset to a percentile. Indicates half the width of the window. This represents the sequence of maximum temperature increases. This represents the sequence of maximum temperature drop. Indicates the day order within a calendar year. This indicates a sliding time window centered on the current calendar day. , This represents the conditional quantile function.

6. The method for detecting rapid temperature changes in lake water according to claim 5, characterized in that, The step of detecting abrupt temperature change events in lake water based on heating and cooling threshold sequences includes: calculating the frequency, duration, intensity, and speed of these events, and calculating characteristic indices such as frequency, duration, intensity, and speed. Based on the relationship between the quantile thresholds corresponding to the maximum temperature rise and maximum temperature fall sequences, two types of abrupt transition events, namely cold-to-heat and hot-to-cold, are detected to obtain independent cold-to-heat event sequences and independent hot-to-cold event sequences. For independent cold-to-hot event sequences and independent hot-to-cold event sequences, the occurrence frequency, duration, intensity of rapid change, and speed of rapid change of events are calculated to detect rapid cold-to-hot changes in lake water temperature.

7. The method for detecting rapid temperature changes in lake water according to claim 6, characterized in that, The step of detecting two types of abrupt transition events, namely cold-to-heat and hot-to-cold, and constructing independent event sequences based on the relationship between the quantile thresholds corresponding to the maximum temperature rise and maximum temperature fall sequences, specifically includes: If the maximum temperature rise sequence is greater than the temperature rise threshold sequence, it is detected as a cold-to-hot abrupt change event; If the maximum temperature drop sequence is less than the temperature drop threshold sequence, it is detected as a rapid thermal-to-cold transition event. If the time interval between adjacent cold-to-hot rapid transition events or adjacent hot-to-cold rapid transition events is less than the event interval parameter, they are considered as the same rapid transition process, and only the first event is retained, resulting in independent cold-to-hot event sequences and independent hot-to-cold event sequences.

8. The method for detecting rapid temperature changes in lake water according to claim 7, characterized in that, The step of detecting rapid temperature changes in lake water by calculating the occurrence frequency, duration, intensity, and speed of independent cold-to-hot and independent hot-to-cold event sequences, respectively, is as follows: Based on the preset study period, the occurrence frequency of independent cold-to-hot event sequences and independent hot-to-cold event sequences is obtained by cumulative statistics. For each detected independent cold-to-hot event sequence and independent hot-to-cold event sequence, determine the time scale corresponding to when the event reaches its extreme value, and obtain the duration of the event; The intensity of the sudden change in events is determined by the interday water temperature variation range corresponding to the independent cold-to-hot event sequence and the independent hot-to-cold event. The abrupt change rate of an event is obtained by comparing the abrupt change intensity to the corresponding duration of an independent cold-to-hot event sequence with that of an independent hot-to-cold event. Based on the frequency, duration, intensity, and speed of the event, the characteristics of rapid temperature changes in lake water are quantified.

9. A detection system for rapid temperature changes in lake water, characterized in that, Includes the following modules: The first module is used to acquire daily time series data of lake water temperature and calculate the daily water temperature variation range to obtain the maximum temperature rise range sequence and the maximum temperature drop range sequence. The second module is used to construct a calendar-day sliding window, calculate the quantile thresholds corresponding to the maximum temperature rise and maximum temperature fall sequences, and obtain the temperature rise threshold sequence and the temperature fall threshold sequence. The third module is used to detect two types of rapid temperature change events: cold-to-hot and hot-to-cold, based on the heating threshold sequence and the cooling threshold sequence. It calculates the occurrence frequency, duration, intensity, and speed of the events, thereby enabling the detection of rapid temperature change events in lake water.

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