A method and system for analyzing drought propagation considering multi-dimensional characteristics of drought events

Abstract

The application provides a drought propagation analysis method and system considering multi-dimensional characteristics of drought events. The method comprises the following steps: calculating a drought duration propagation index based on a meteorological drought total duration and an agricultural drought total duration; calculating a drought intensity propagation index based on meteorological drought intensities of previous meteorological drought events and agricultural drought intensities of previous agricultural drought events; calculating a drought intensity trend propagation index based on meteorological drought intensity trends of previous meteorological drought events and agricultural drought intensity trends of previous agricultural drought events; calculating a drought fluctuation propagation index based on meteorological drought index fluctuation rates of previous meteorological drought events and agricultural drought index fluctuation rates of previous agricultural drought events; calculating a drought probability propagation index based on a meteorological drought occurrence probability and an agricultural drought occurrence probability of a target region within a given time period; and constructing a comprehensive drought propagation index by using a CRITIC objective weighting method. The application can accurately describe the propagation process between meteorological drought and agricultural drought.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a method and system for drought propagation analysis that considers the multidimensional characteristics of drought events. Background Technology

[0002] Drought propagation mainly refers to the process of drought spreading from meteorological drought to agricultural, hydrological, and socioeconomic drought types. Drought propagation is characterized by accumulation, attenuation, lag, and prolongation. It possesses both temporal and spatial dimensions, serving as an intermediate link in drought development and evolution, and a fundamental research direction in the field of drought. Previous studies on the propagation of drought characteristics have primarily focused on the propagation process of drought frequency, duration, and intensity. Existing drought propagation analysis indicators are singular and cannot comprehensively quantify the degree of propagation of different drought characteristics during the transition from meteorological to agricultural drought. Therefore, how to more accurately describe the drought propagation process has become an urgent problem to be solved in the current field of drought research. Summary of the Invention

[0003] To more accurately describe the drought propagation process, this invention provides a drought propagation analysis method and system that considers the multi-dimensional characteristics of drought events. This method can accurately describe the propagation process between different types of drought.

[0004] In a first aspect, the present invention provides a drought propagation analysis method that considers the multi-dimensional characteristics of drought events, including:

[0005] Calculate the propagation time from meteorological drought to agricultural drought in the target area, and select the standardized precipitation index SPI and standardized soil moisture index SSMI corresponding to the time scale based on the propagation time.

[0006] Based on the run theory, meteorological drought events and agricultural drought events in the target area are identified, the duration of meteorological drought events and the duration of agricultural drought events are calculated, and the total duration of meteorological drought and agricultural drought events are integrated to obtain the total duration of meteorological drought and agricultural drought.

[0007] Based on the selected SPI, the meteorological drought intensity, meteorological drought intensity trend, meteorological drought index volatility, and the probability of meteorological drought occurring in the target area within a given time period are calculated for each meteorological drought event.

[0008] Based on the selected SSMI, the agricultural drought intensity, agricultural drought intensity trend, agricultural drought index volatility, and the probability of agricultural drought occurring in the target area within a given time period are calculated for each agricultural drought event.

[0009] The drought duration propagation index is calculated based on the total duration of meteorological drought and the total duration of agricultural drought; the drought intensity propagation index is calculated based on the meteorological drought intensity of previous meteorological drought events and the agricultural drought intensity of previous agricultural drought events; the drought intensity trend propagation index is calculated based on the meteorological drought intensity trend of previous meteorological drought events and the agricultural drought intensity trend of previous agricultural drought events; the drought fluctuation propagation index is calculated based on the volatility of the meteorological drought index of previous meteorological drought events and the volatility of the agricultural drought index of previous agricultural drought events; and the drought probability propagation index is calculated based on the probability of meteorological drought occurrence and the probability of agricultural drought occurrence in the target area within a given time period.

[0010] Based on the drought duration propagation index, drought intensity propagation index, drought intensity trend propagation index, drought fluctuation propagation index, and drought probability propagation index, a comprehensive drought propagation index is constructed using the CRITIC objective weighting method.

[0011] Furthermore, the propagation time from meteorological drought to agricultural drought in the target area is calculated, including:

[0012] Hourly precipitation data are fused into 30-365 day precipitation data, and the standardized precipitation index sequence SPI-n is calculated using the 30-365 day precipitation data.

[0013] Hourly soil moisture data are fused into 30-day soil moisture data. Based on the 30-day soil moisture data, the 30-day standardized soil moisture index series SSMI is calculated.

[0014] Based on the standardized precipitation index series SPI-n with a scale of 30–365 days and the standardized soil moisture index series SSMI with a scale of 30 days, a joint probability distribution model between the standardized precipitation index and the standardized soil moisture index is established using the Copula function, thereby determining the propagation time from meteorological drought to agricultural drought.

[0015] Furthermore, a joint probability distribution model between the standardized precipitation index and the standardized soil moisture index is established using the Copula function to determine the propagation time from meteorological drought to agricultural drought, including:

[0016] Determine the marginal distributions of the standardized precipitation index series SPI-n and the standardized soil moisture index series SSMI, including: using the Kolmogorov-Smirnov test to determine whether the standardized precipitation index series SPI-n or the standardized soil moisture index series SSMI conforms to a normal distribution; if it conforms to a normal distribution, use the normal distribution to calculate its cumulative distribution probability; otherwise, use kernel density estimation to calculate its cumulative distribution probability.

[0017] Based on the determined marginal distributions u and v, the joint probability distribution model between the standardized precipitation index and the standardized soil moisture index is established using the Copula function as follows:

[0018]

[0019] in, This represents the probability that the event SSMI≤-1 occurs when SPI≤-1; Let u and v represent the joint distribution function of u and v, where u represents the marginal distribution function of SPI and v represents the marginal distribution function of SSMI.

[0020] Using SPI index data from 30 to 365 days as a condition, the joint distribution of the SPI index and SSMI index is calculated based on the joint probability distribution model to obtain the probability of agricultural drought occurrence corresponding to the SPI index at different time scales. The time scale of the SPI index corresponding to the highest probability value is selected as the propagation time from meteorological drought to agricultural drought.

[0021] Furthermore, the calculation of the drought probability propagation index based on the probability of meteorological drought and the probability of agricultural drought in the target area within a given time period includes:

[0022]

[0023] Where DPP represents the drought probability propagation index; n represents the drought propagation time; AP SSMI-30 MP represents the probability of agricultural drought occurring over a specific time period, calculated based on the 30-day SSMI index; SPI-n This represents the probability of meteorological drought occurring over a certain period of time, calculated based on the n-day SPI index, when the propagation time is n.

[0024] Secondly, the present invention provides a drought propagation analysis system that considers the multi-dimensional characteristics of drought events, comprising:

[0025] The drought propagation module is used to calculate the propagation time from meteorological drought to agricultural drought in the target area, and select the standardized precipitation index SPI and standardized soil moisture index SSMI corresponding to the time scale based on the propagation time.

[0026] The drought duration calculation module is used to identify meteorological drought events and agricultural drought events in the target area based on the runs theory, calculate the meteorological drought duration of each meteorological drought event and the agricultural drought duration of each agricultural drought event, and integrate them to obtain the total meteorological drought duration and the total agricultural drought duration.

[0027] The meteorological drought analysis module is used to calculate the meteorological drought intensity, meteorological drought intensity trend, meteorological drought index volatility, and the probability of meteorological drought occurring in the target area within a given time period based on the selected SPI for each meteorological drought event.

[0028] The agricultural drought analysis module is used to calculate the agricultural drought intensity, agricultural drought intensity trend, agricultural drought index volatility, and the probability of agricultural drought occurring in the target area within a given time period based on the selected SSMI for each agricultural drought event.

[0029] The multidimensional drought propagation index calculation module is used to calculate the drought duration propagation index based on the total duration of meteorological drought and the total duration of agricultural drought; to calculate the drought intensity propagation index based on the meteorological drought intensity of previous meteorological drought events and the agricultural drought intensity of previous agricultural drought events; to calculate the drought intensity trend propagation index based on the meteorological drought intensity trend of previous meteorological drought events and the agricultural drought intensity trend of previous agricultural drought events; to calculate the drought fluctuation propagation index based on the volatility of the meteorological drought index of previous meteorological drought events and the volatility of the agricultural drought index of previous agricultural drought events; and to calculate the drought probability propagation index based on the probability of meteorological drought and the probability of agricultural drought occurring in the target area within a given time period.

[0030] The integrated drought analysis module is used to construct an integrated drought propagation index based on the drought duration propagation index, drought intensity propagation index, drought intensity trend propagation index, drought fluctuation propagation index, and drought probability propagation index, using the CRITIC objective weighting method.

[0031] Thirdly, the present invention provides an electronic device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the program, implements the method as described in the first aspect.

[0032] Fourthly, the present invention provides a non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the method described in the first aspect.

[0033] Fifthly, the present invention provides a computer program product, including a computer program that, when executed by a processor, implements the method described in the first aspect.

[0034] The beneficial effects of this invention are as follows:

[0035] Previous studies on drought propagation have largely focused on traditional factors such as drought frequency, duration, and intensity, failing to comprehensively reflect the complex dynamic changes of drought during its propagation. This invention designs a multi-dimensional drought propagation index, including a drought probability propagation index. The drought probability propagation index is specifically designed to characterize the degree to which the probability of meteorological drought in a given region propagates to the probability of agricultural drought, thus incorporating the triggering risk of drought propagation into the analytical framework. Simultaneously, this invention combines the drought probability propagation index, drought duration propagation index, drought intensity propagation index, drought intensity trend propagation index, and drought fluctuation propagation index to systematically characterize the propagation characteristics of drought from multiple dimensions, including probability transmission, duration, severity, long-term trends, and process fluctuations. Based on this, the CRITIC objective weighting method is employed to automatically assign appropriate weights to each index by measuring the comparative strength of each sub-index and their mutual conflicts, thereby constructing a comprehensive drought propagation index. This invention overcomes the shortcomings of traditional research that relies on single or a few indicators, which can easily lead to one-sided conclusions. Through multi-dimensional integration, it significantly enhances the ability to depict the full picture of drought propagation. In particular, the drought probability propagation index clarifies how meteorological drought risk is transmitted to agricultural drought, providing crucial evidence for early warning. Simultaneously, the CRITIC objective weighting method avoids subjective human intervention, enabling the comprehensive index to exhibit good adaptability and transferability across different regions, climatic backgrounds, and time scales. Ultimately, this comprehensive drought propagation index can more sensitively capture the propagation signals of drought from meteorological to agricultural systems, more accurately assess its actual impact intensity, and provide more scientific and reliable decision support for drought relief scheduling, water resource management, and ecological risk early warning than previous methods. Attached Figure Description

[0036] Figure 1 This is one of the flowcharts illustrating a drought propagation analysis method that considers the multidimensional characteristics of drought events, provided as an embodiment of the present invention.

[0037] Figure 2 The second flowchart illustrates a drought propagation analysis method that considers the multi-dimensional characteristics of drought events, as provided in an embodiment of the present invention.

[0038] Figure 3 Spatial distribution map of drought propagation index in Southwest China provided for embodiments of the present invention;

[0039] Figure 4 A schematic diagram of the structure of a drought propagation analysis system that considers the multidimensional characteristics of drought events, provided as an embodiment of the present invention;

[0040] Figure 5 This is a structural block diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0041] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of the embodiments of this invention will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0042] This invention aims to construct a comprehensive drought propagation index based on multiple drought propagation indices and the CRITIC objective weighting method, to fully reveal the propagation pattern of meteorological drought to agricultural drought characteristics in the region, enrich the theory and methods of drought characteristic propagation research, and provide scientific tools and decision support for effective drought prevention and control.

[0043] like Figure 1 and Figure 2 As shown, this embodiment of the invention provides a drought propagation analysis method that considers the multi-dimensional characteristics of drought events, including the following steps:

[0044] S101. Calculate the propagation time n from meteorological drought to agricultural drought in the target area, and select the corresponding n-day standardized precipitation index SPI and 30-day standardized soil moisture index SSMI based on the propagation time n.

[0045] Specifically, the process of calculating the propagation time includes the following sub-steps:

[0046] (1) Merge hourly precipitation data into 30-365 day precipitation data, and use the 30-365 day precipitation data to calculate the 30-365 day standardized precipitation index sequence SPI-n;

[0047] (2) The hourly soil moisture data is integrated into the 30-day soil moisture data. For example, the hourly soil moisture data is averaged to obtain the daily soil moisture data, and the daily soil moisture data is averaged to obtain the 30-day soil moisture data. Based on the 30-day soil moisture data, the 30-day standardized soil moisture index sequence SSMI is calculated.

[0048] (3) Based on the standardized precipitation index sequence SPI-n with a scale of 30 to 365 days and the standardized soil moisture index sequence SSMI with a scale of 30 days, a joint probability distribution model between the standardized precipitation index and the standardized soil moisture index is established using the Copula function, so as to determine the propagation time from meteorological drought to agricultural drought.

[0049] In this embodiment, a joint probability distribution model between the standardized precipitation index and the standardized soil moisture index is established using the Copula function to determine the propagation time from meteorological drought to agricultural drought, including the following sub-steps:

[0050] Determine the marginal distributions of the standardized precipitation index series SPI-n and the standardized soil moisture index series SSMI, including: using the Kolmogorov-Smirnov test to determine whether the standardized precipitation index series SPI-n or the standardized soil moisture index series SSMI conforms to a normal distribution; if it conforms to a normal distribution, use the normal distribution to calculate its cumulative distribution probability; otherwise, use kernel density estimation to calculate its cumulative distribution probability.

[0051] Based on the determined marginal distributions u and v, the joint probability distribution model between the standardized precipitation index and the standardized soil moisture index is established using the Copula function as follows:

[0052]

[0053] in, This represents the probability that the event SSMI≤-1 occurs when SPI≤-1; Let P(SPI≤-1, SSMI≤-1) represent the joint distribution function of u and v, where u represents the marginal distribution function of SPI and v represents the marginal distribution function of SSMI.

[0054] Using SPI index data from 30 to 365 days as a condition, the joint distribution of the SPI index and SSMI index is calculated based on the joint probability distribution model to obtain the probability of agricultural drought occurrence corresponding to the SPI index at different time scales. The time scale of the SPI index corresponding to the highest probability value is selected as the propagation time from meteorological drought to agricultural drought.

[0055] S102. Identify meteorological drought events and agricultural drought events in the target area based on the run theory, calculate the duration of meteorological drought events and the duration of agricultural drought events for each meteorological drought event, and integrate them to obtain the total duration of meteorological drought and the total duration of agricultural drought.

[0056] Specifically, drought events are identified based on runs theory, and drought events are merged and eliminated to obtain meteorological drought events and agricultural drought events in the target area.

[0057] S103. Based on the selected n-day scale SPI, calculate the meteorological drought intensity, meteorological drought intensity trend, meteorological drought index volatility, and the probability of meteorological drought occurring in the target area within a given time period for each meteorological drought event. Further, average the meteorological drought intensity and meteorological drought index volatility of all meteorological drought events to obtain the average meteorological drought intensity and average meteorological drought index volatility.

[0058] S104. Based on the selected 30-day SSMI scale, calculate the agricultural drought intensity, agricultural drought intensity trend, agricultural drought index volatility, and the probability of agricultural drought occurring in the target area within a given time period for each agricultural drought event. Further, average the agricultural drought intensity and agricultural drought index volatility of all agricultural drought events to obtain the average agricultural drought intensity and average agricultural drought index volatility.

[0059] Specifically, meteorological (or agricultural) drought intensity is the quotient of the meteorological (or agricultural) drought intensity of a given meteorological (or agricultural) drought event and the duration of the meteorological (or agricultural) drought; and within a run, the cumulative deficit between the SXI value that meets the screening criteria and the threshold is the meteorological (or agricultural) drought intensity S, mathematically expressed as:

[0060]

[0061] In the formula, S represents the intensity of meteorological (or agricultural) drought; T o and T t These represent the start and end times of meteorological (or agricultural) drought, respectively; SXI stands for SPI (or SSMI).

[0062] The drought intensity trend of a meteorological (or agricultural) drought event is characterized by the fitted slope k of the daily cumulative intensity from the start to the end of the drought. Furthermore, when the propagation time is n, the average meteorological drought intensity trend of all meteorological drought events within a certain time period is obtained based on the n-day SPI index, and the average agricultural drought intensity trend of all agricultural drought events within a certain time period is obtained based on the 30-day SSMI index.

[0063] The volatility of the drought index for a given meteorological (or agricultural) drought event is characterized by the coefficient of variation of the SPI index (or SSMI index) from the start to the end of the drought. Furthermore, when the propagation time is n, the average volatility of the meteorological drought index is represented by the average coefficient of variation of the SPI index for all meteorological drought events within a certain time period, calculated based on the n-day SPI index; similarly, the average volatility of the agricultural drought index is represented by the average coefficient of variation of the SSMI index for all agricultural drought events within a certain time period, calculated based on the 30-day SSMI index.

[0064] The Kolmogorov-Smirnov test is used to determine whether the SPI or SSMI sequences conform to a normal distribution. If they conform to a normal distribution, their cumulative distribution probability is calculated using the normal distribution method; otherwise, kernel density estimation is used to calculate their cumulative distribution probability. Furthermore, the probabilities of meteorological drought and agricultural drought occurrence are calculated separately.

[0065]

[0066] In the formula, P represents the probability of meteorological drought or agricultural drought; SXI represents SPI or SSMI.

[0067] S105. Calculate the drought duration propagation index based on the total duration of meteorological drought and the total duration of agricultural drought; calculate the drought intensity propagation index based on the meteorological drought intensity of previous meteorological drought events and the agricultural drought intensity of previous agricultural drought events; calculate the drought intensity trend propagation index based on the meteorological drought intensity trend of previous meteorological drought events and the agricultural drought intensity trend of previous agricultural drought events; calculate the drought fluctuation propagation index based on the fluctuation rate of the meteorological drought index of previous meteorological drought events and the fluctuation rate of the agricultural drought index of previous agricultural drought events; calculate the drought probability propagation index based on the probability of meteorological drought occurrence and the probability of agricultural drought occurrence in the target area within a given time period.

[0068] Specifically, the drought duration propagation index characterizes the degree to which meteorological drought duration propagates to agricultural drought duration in a certain region, and the formula is as follows:

[0069]

[0070] In the formula, DDP represents the drought duration propagation index; n represents the drought propagation time obtained based on the Copula function, ranging from 30 days to 365 days; AD SSMI-30 This represents the total duration of agricultural drought over a specific period, calculated based on the 30-day SSMI index; MD SPI-n This represents the total duration of meteorological drought over a certain period of time, calculated based on the n-day SPI index, when the propagation time is n.

[0071] The drought intensity propagation index characterizes the degree to which meteorological drought intensity propagates to agricultural drought intensity in a certain region. The formula is as follows:

[0072]

[0073] In the formula, DIP represents the drought intensity propagation index; n represents the drought propagation time obtained based on the Copula function, ranging from 30 days to 365 days; AI SSMI-30 This represents the average agricultural drought intensity over a specific period, calculated based on the 30-day SSMI index; MISPI-n This represents the average meteorological drought intensity over a certain period of time, calculated based on the n-day SPI index, when the propagation time is n.

[0074] The drought intensity trend propagation index characterizes the extent to which the increasing trend of meteorological drought intensity propagates to the increasing trend of agricultural drought intensity in a certain region. The formula for the drought intensity trend propagation index is as follows:

[0075]

[0076] In the formula, DSTP represents the drought intensity trend propagation index; n represents the drought propagation time obtained based on the Copula function, ranging from 30 days to 365 days; AST SSMI-30 MST represents the trend of average agricultural drought intensity over a specific period, calculated based on the 30-day SSMI index; SPI-n This represents the average meteorological drought intensity trend over a certain period of time, calculated based on the n-day SPI index, when the propagation time is n.

[0077] The drought fluctuation propagation index characterizes the degree to which the volatility of meteorological drought index propagates to the volatility of agricultural drought index in a certain region. The formula for the drought fluctuation propagation index is as follows:

[0078]

[0079] In the formula, DVP represents the drought fluctuation propagation index; n represents the drought propagation time obtained based on the Copula function, ranging from 30 days to 365 days; AV SSMI-30 MV represents the average coefficient of variation of the SSMI index for all agricultural drought events within a certain time period, calculated based on the 30-day SSMI index; SPI-n This represents the average coefficient of variation of the SPI index for all meteorological drought events within a certain time period, calculated based on the n-day SPI index.

[0080] The drought probability propagation index characterizes the degree to which the probability of meteorological drought in a certain region propagates to the probability of agricultural drought. The formula for the drought probability propagation index is as follows:

[0081]

[0082] In the formula, DPP represents the drought probability propagation index; n represents the drought propagation time obtained based on the Copula function, ranging from 30 days to 365 days; AP SSMI-30 MP represents the probability of agricultural drought occurring over a specific time period, calculated based on the 30-day SSMI index; SPI-n This represents the probability of meteorological drought occurring over a certain period of time, calculated based on the n-day SPI index, when the propagation time is n.

[0083] S106. Based on the drought duration propagation index, drought intensity propagation index, drought intensity trend propagation index, drought fluctuation propagation index, and drought probability propagation index, a comprehensive drought propagation index is constructed using the CRITIC objective weighting method.

[0084] Specifically, constructing the comprehensive drought propagation index using the CRITIC objective weighting method includes the following sub-steps:

[0085] (1) Dimensionless processing. The CRITIC weighting method uses forward or reverse processing. This invention uses forward processing to perform dimensionless processing on the data;

[0086]

[0087] In the formula, and These are the exponent values ​​before and after normalization, respectively. and These are the minimum and maximum values ​​of the sample, respectively;

[0088] (2) Determination of weighting coefficients. Conflicts between different indices. Information content of a single index Represented as:

[0089]

[0090] In the formula, The degree of linear correlation between index i and index j; Let be the standard deviation of the j-th index. If the weighting coefficient is , then

[0091]

[0092] In the formula, m represents the number of individual indicators in the comprehensive drought index;

[0093] (3) Comprehensive drought propagation index. Based on (1) and (2), the comprehensive drought propagation index can be expressed as:

[0094]

[0095] In the formula, These are the normalized values ​​for DDP, DIP, DSTP, DVP, and DPP, respectively.

[0096] To verify the effectiveness and rationality of the present invention, this embodiment takes the Southwest region as an example to analyze the propagation pattern from meteorological drought to agricultural drought in the region.

[0097] The southwestern region is located between 20°~35°N and 96°~113°E, covering an area of ​​approximately 1.37 × 10⁻⁶. 6 km 2 The Southwest region has a complex topography, encompassing the southeastern part of the Qinghai-Tibet Plateau, the Hengduan Mountains, most of the Sichuan Basin, and the Yunnan-Guizhou Plateau, with a terrain distribution of "high in the northwest and low in the southeast." The Southwest region has diverse climate types, mainly tropical monsoon climate, subtropical monsoon climate, and plateau mountain climate, with warm and humid summers and cold and dry winters. The average annual temperature in the Southwest region ranges from 14 to 24°C, exhibiting a spatial pattern of "high in the south and low in the north." Annual precipitation in the region generally ranges from 600 to 2300 mm, with uneven seasonal distribution; precipitation is lower in spring and autumn and higher in summer and autumn. Furthermore, due to the complex topography, precipitation exhibits spatial heterogeneity, showing a spatial pattern of "more in the east and less in the west, more in the south and less in the north."

[0098] Research on the propagation patterns of meteorological drought to agricultural drought in Southwest China is of great significance for improving drought theory and analysis framework, as well as ensuring food security, socio-economic development and sustainable ecological environment in Southwest China.

[0099] The 3-hour precipitation data used came from the China Meteorological Forcing Dataset (CMFD). The 3-hour precipitation data were accumulated to form 30- to 365-day precipitation data. Using the 30- to 365-day precipitation data, the standardized precipitation index (SPI) series for the 30- to 365-day scale was calculated. The 3-hour soil moisture products from December 3, 1979 to December 31, 2014 from GLDAS-2.0 Noah (Global Land Data Assimilation System Version 2.0 - Noah Land Surface Model) and the 3-hour soil moisture products from January 1, 2015 to December 31, 2018 from GLDAS-2.1 Noah (Global Land Data Assimilation System Version 2.1 - Noah Land Surface Model) are merged to form a soil moisture data series from 1979 to 2018, and then bias correction is performed. Daily soil moisture data is obtained by averaging the 3-hour soil moisture data, and further averaging the daily soil moisture data yields 30-day soil moisture data. The 30-day standardized soil moisture index (SSMI) series is then calculated.

[0100] A joint probability distribution model between standardized precipitation index and standardized soil moisture index was established using the Copula function to further determine the propagation time from meteorological drought to agricultural drought. Based on conditional probability, the propagation time from meteorological drought to agricultural drought in Southwest China ranged from 60 to 365 days, with an average of 125 days. Low propagation times were observed in northeastern Ganzi Tibetan Autonomous Prefecture, Aba Tibetan and Qiang Autonomous Prefecture, Chengdu City, western Deyang City, Chengkou County, Wuxi County, northeastern Kaizhou District, Fengjie County, Wanzhou District, Liangping County, northeastern Dianjiang County, Zhong County, Shizhu Tujia Autonomous County, and Nujiang Lisu Autonomous Prefecture in Yunnan Province.

[0101] Using the calculation methods described in the above embodiments, the drought duration propagation index, drought intensity propagation index, drought intensity trend propagation index, drought fluctuation propagation index, and drought probability propagation index for the Southwest region were statistically analyzed as follows:

[0102] The drought duration propagation index in Southwest China ranges from 0.56 to 1.34, with an average of 0.89. High values ​​of the drought duration propagation index are found in the northeastern part of Ganzi Tibetan Autonomous Prefecture in Sichuan Province and its southern border area with Aba Tibetan and Qiang Autonomous Prefecture; Aba Tibetan and Qiang Autonomous Prefecture; the central border area between Qiandongnan Miao and Dong Autonomous Prefecture in Guizhou Province and Guangxi Zhuang Autonomous Region; the southwestern part of Fangchenggang City in Guangxi Zhuang Autonomous Region; and Qujing City in Yunnan Province.

[0103] The drought intensity propagation index in Southwest China ranges from 0.80 to 2.69, with an average of 1.50. High values ​​of the drought intensity propagation index are found in the southeastern part of Ganzi Tibetan Autonomous Prefecture and the southwestern part of Meishan City, Sichuan Province.

[0104] The drought intensity trend propagation index in Southwest China ranges from 0.88 to 2.91, with an average of 1.58. High values ​​of the drought intensity trend propagation index are distributed in the southeastern part of Ganzi Tibetan Autonomous Prefecture, Ya'an City, and the southwestern part of Meishan City in Sichuan Province.

[0105] The drought fluctuation propagation index in Southwest China ranged from 0.77 to 1.83, with an average of 1.20. High values ​​of the drought fluctuation propagation index were distributed in southwestern and southeastern Ganzi Tibetan Autonomous Prefecture, southwestern Aba Tibetan and Qiang Autonomous Prefecture, northern Deyang City, Mianyang City, the border area between Zunyi City and Guiyang City in Guizhou Province, Wuzhou City and Guigang City in Guangxi Zhuang Autonomous Region, and Nujiang Lisu Autonomous Prefecture in Yunnan Province.

[0106] The drought probability propagation index in Southwest China ranges from 0.70 to 1.34, with an average of 0.95. High values ​​of the drought probability propagation index are distributed in the southern border area between Ganzi Tibetan Autonomous Prefecture and Aba Tibetan and Qiang Autonomous Prefecture in Sichuan Province, the southwestern and southeastern parts of Aba Tibetan and Qiang Autonomous Prefecture, and the northwestern part of Deyang City.

[0107] The comprehensive drought propagation index in Southwest China ranges from -1.73 to 3.64, with an average of 0. High values ​​of the comprehensive drought propagation index in Southwest China are distributed in the southern border area between Ganzi Tibetan Autonomous Prefecture and Aba Tibetan and Qiang Autonomous Prefecture in Sichuan Province, which shows a similar pattern to the distribution of high values ​​of other drought propagation indices.

[0108] A comprehensive drought propagation index was constructed based on the CRITIC objective weighting method, comprehensively analyzing the propagation process from meteorological drought to agricultural drought. This improves the drought theory and analytical framework, and can provide technical support for agricultural drought prediction and the formulation of water project scheduling plans. The analysis results are as follows: Figure 3 As shown.

[0109] like Figure 4 As shown, this embodiment of the invention also provides a drought propagation analysis system that considers the multi-dimensional characteristics of drought events, including a drought propagation module, a drought duration calculation module, a meteorological drought analysis module, an agricultural drought analysis module, a multi-dimensional drought propagation index calculation module, and a comprehensive drought analysis module;

[0110] The drought propagation module is used to calculate the propagation time from meteorological drought to agricultural drought in the target area, and selects the standardized precipitation index SPI and standardized soil moisture index SSMI corresponding to the time scale based on the propagation time.

[0111] The drought duration calculation module is used to identify meteorological drought events and agricultural drought events in the target area based on runs theory, calculate the meteorological drought duration of each meteorological drought event and the agricultural drought duration of each agricultural drought event, and integrate them to obtain the total meteorological drought duration and the total agricultural drought duration.

[0112] The meteorological drought analysis module is used to calculate the meteorological drought intensity, meteorological drought intensity trend, meteorological drought index volatility, and the probability of meteorological drought occurring in the target area within a given time period based on the selected SPI for each meteorological drought event.

[0113] The agricultural drought analysis module is used to calculate the agricultural drought intensity, agricultural drought intensity trend, agricultural drought index volatility, and the probability of agricultural drought occurring in the target area within a given time period based on the selected SSMI for each agricultural drought event.

[0114] The multidimensional drought propagation index calculation module is used to calculate the drought duration propagation index based on the total duration of meteorological drought and the total duration of agricultural drought; to calculate the drought intensity propagation index based on the meteorological drought intensity of previous meteorological drought events and the agricultural drought intensity of previous agricultural drought events; to calculate the drought intensity trend propagation index based on the meteorological drought intensity trend of previous meteorological drought events and the agricultural drought intensity trend of previous agricultural drought events; to calculate the drought fluctuation propagation index based on the volatility of the meteorological drought index of previous meteorological drought events and the volatility of the agricultural drought index of previous agricultural drought events; and to calculate the drought probability propagation index based on the probability of meteorological drought and the probability of agricultural drought occurring in the target area within a given time period.

[0115] The integrated drought analysis module is used to construct an integrated drought propagation index based on the drought duration propagation index, drought intensity propagation index, drought intensity trend propagation index, drought fluctuation propagation index, and drought probability propagation index, using the CRITIC objective weighting method.

[0116] It should be noted that the drought propagation analysis system provided in this embodiment of the invention is for implementing the above method, and its specific functions can be referred to the above method embodiment, which will not be repeated here.

[0117] Figure 5 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 5As shown, the electronic device may include: a processor 501, a communication interface 502, a memory 503, and a communication bus 504, wherein the processor 501, the communication interface 502, and the memory 503 communicate with each other through the communication bus 504. Processor 501 can call logical instructions in memory 503 to execute a drought propagation analysis method considering the multi-dimensional characteristics of drought events. This method includes: calculating the propagation time from meteorological drought to agricultural drought in a target area; selecting a standardized precipitation index (SPI) and a standardized soil moisture index (SSMI) for the corresponding time scale based on the propagation time; identifying meteorological drought events and agricultural drought events in the target area based on runs theory; calculating the duration of meteorological drought events and agricultural drought events for each meteorological drought event; and integrating these to obtain the total duration of meteorological drought and agricultural drought; calculating the meteorological drought intensity, meteorological drought intensity trend, meteorological drought index volatility, and the probability of meteorological drought occurring in the target area within a given time period based on the selected SPI; and calculating the agricultural drought intensity, agricultural drought intensity trend, and agricultural drought index volatility for each agricultural drought event based on the selected SSMI. The following criteria are used to calculate the drought propagation index: the probability of meteorological drought and agricultural drought occurring in the target area within a given time period; the drought duration propagation index; the drought intensity propagation index; the drought intensity trend propagation index; the drought fluctuation propagation index; the drought probability propagation index; and the comprehensive drought propagation index.

[0118] Furthermore, when the logical instructions in the aforementioned memory 503 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0119] This invention also provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium. The computer program includes program instructions, and when the program instructions are executed by a computer, the computer can execute a drought propagation analysis method considering the multi-dimensional characteristics of drought events provided in the above-described method embodiments.

[0120] This invention also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements a drought propagation analysis method considering the multi-dimensional characteristics of drought events provided in the above-described method embodiments.

[0121] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0122] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A drought propagation analysis method considering the multi-dimensional characteristics of drought events, characterized in that, include: Calculate the propagation time from meteorological drought to agricultural drought in the target area, and select the standardized precipitation index SPI and standardized soil moisture index SSMI corresponding to the time scale based on the propagation time. Based on the run theory, meteorological drought events and agricultural drought events in the target area are identified, the duration of meteorological drought events and the duration of agricultural drought events are calculated, and the total duration of meteorological drought and agricultural drought events are integrated to obtain the total duration of meteorological drought and agricultural drought. Based on the selected SPI, the meteorological drought intensity, meteorological drought intensity trend, meteorological drought index volatility, and the probability of meteorological drought occurring in the target area within a given time period are calculated for each meteorological drought event. Based on the selected SSMI, the agricultural drought intensity, agricultural drought intensity trend, agricultural drought index volatility, and the probability of agricultural drought occurring in the target area within a given time period are calculated for each agricultural drought event. The drought duration propagation index is calculated based on the total duration of meteorological drought and the total duration of agricultural drought; The drought intensity propagation index is calculated based on the meteorological drought intensity of previous meteorological drought events and the agricultural drought intensity of previous agricultural drought events. The drought intensity trend propagation index is calculated based on the meteorological drought intensity trend of previous meteorological drought events and the agricultural drought intensity trend of previous agricultural drought events. The drought fluctuation propagation index is calculated based on the volatility of the meteorological drought index and the volatility of the agricultural drought index for each meteorological drought event. The drought probability propagation index is calculated based on the probability of meteorological drought and the probability of agricultural drought in the target area within a given time period. Based on the drought duration propagation index, drought intensity propagation index, drought intensity trend propagation index, drought fluctuation propagation index, and drought probability propagation index, a comprehensive drought propagation index is constructed using the CRITIC objective weighting method.

2. The drought propagation analysis method considering the multi-dimensional characteristics of drought events according to claim 1, characterized in that, Calculate the propagation time from meteorological drought to agricultural drought in the target area, including: Hourly precipitation data are fused into 30-365 day precipitation data, and the standardized precipitation index sequence SPI-n is calculated using the 30-365 day precipitation data. Hourly soil moisture data are fused into 30-day soil moisture data. Based on the 30-day soil moisture data, the 30-day standardized soil moisture index series SSMI is calculated. Based on the standardized precipitation index series SPI-n with a scale of 30–365 days and the standardized soil moisture index series SSMI with a scale of 30 days, a joint probability distribution model between the standardized precipitation index and the standardized soil moisture index is established using the Copula function, thereby determining the propagation time from meteorological drought to agricultural drought.

3. The drought propagation analysis method considering the multi-dimensional characteristics of drought events according to claim 2, characterized in that, A joint probability distribution model between the standardized precipitation index and the standardized soil moisture index is established using the Copula function to determine the propagation time from meteorological drought to agricultural drought, including: Determine the marginal distributions of the standardized precipitation index series SPI-n and the standardized soil moisture index series SSMI, including: using the Kolmogorov-Smirnov test to determine whether the standardized precipitation index series SPI-n or the standardized soil moisture index series SSMI conforms to a normal distribution; if it conforms to a normal distribution, use the normal distribution to calculate its cumulative distribution probability; otherwise, use kernel density estimation to calculate its cumulative distribution probability. Based on the determined marginal distributions u and v, the joint probability distribution model between the standardized precipitation index and the standardized soil moisture index is established using the Copula function as follows: in, This represents the probability that the event SSMI≤-1 occurs when SPI≤-1; Let u and v represent the joint distribution function of u and v, where u represents the marginal distribution function of SPI and v represents the marginal distribution function of SSMI. Using SPI index data from 30 to 365 days as a condition, the joint distribution of the SPI index and SSMI index is calculated based on the joint probability distribution model to obtain the probability of agricultural drought occurrence corresponding to the SPI index at different time scales. The time scale of the SPI index corresponding to the highest probability value is selected as the propagation time from meteorological drought to agricultural drought.

4. The drought propagation analysis method considering the multi-dimensional characteristics of drought events according to claim 1, characterized in that, The calculation of the drought probability propagation index based on the probability of meteorological drought and the probability of agricultural drought in the target area within a given time period includes: Where DPP represents the drought probability propagation index; n represents the drought propagation time; AP SSMI-30 MP represents the probability of agricultural drought occurring over a specific time period, calculated based on the 30-day SSMI index; SPI-n This represents the probability of meteorological drought occurring over a certain period of time, calculated based on the n-day SPI index, when the propagation time is n.

5. A drought propagation analysis system considering the multi-dimensional characteristics of drought events, characterized in that, include: The drought propagation module is used to calculate the propagation time from meteorological drought to agricultural drought in the target area, and select the standardized precipitation index SPI and standardized soil moisture index SSMI corresponding to the time scale based on the propagation time. The drought duration calculation module is used to identify meteorological drought events and agricultural drought events in the target area based on the runs theory, calculate the meteorological drought duration of each meteorological drought event and the agricultural drought duration of each agricultural drought event, and integrate them to obtain the total meteorological drought duration and the total agricultural drought duration. The meteorological drought analysis module is used to calculate the meteorological drought intensity, meteorological drought intensity trend, meteorological drought index volatility, and the probability of meteorological drought occurring in the target area within a given time period based on the selected SPI for each meteorological drought event. The agricultural drought analysis module is used to calculate the agricultural drought intensity, agricultural drought intensity trend, agricultural drought index volatility, and the probability of agricultural drought occurring in the target area within a given time period based on the selected SSMI for each agricultural drought event. The multidimensional drought propagation index calculation module is used to calculate the drought duration propagation index based on the total duration of meteorological drought and the total duration of agricultural drought. The drought intensity propagation index is calculated based on the meteorological drought intensity of previous meteorological drought events and the agricultural drought intensity of previous agricultural drought events. The drought intensity trend propagation index is calculated based on the meteorological drought intensity trend of previous meteorological drought events and the agricultural drought intensity trend of previous agricultural drought events. The drought fluctuation propagation index is calculated based on the volatility of the meteorological drought index and the volatility of the agricultural drought index for each meteorological drought event. The drought probability propagation index is calculated based on the probability of meteorological drought and the probability of agricultural drought in the target area within a given time period. The integrated drought analysis module is used to construct an integrated drought propagation index based on the drought duration propagation index, drought intensity propagation index, drought intensity trend propagation index, drought fluctuation propagation index, and drought probability propagation index, using the CRITIC objective weighting method.

6. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method as described in any one of claims 1 to 4.

7. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1 to 4.

8. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 4.

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