CN115331215A - Three-dimensional identification and matching method and device for drought event - Google Patents
Three-dimensional identification and matching method and device for drought event Download PDFInfo
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Abstract
The invention provides a three-dimensional identification and matching method and a device for drought events, which relate to the technical field of drought management and correspondence and comprise the following steps: acquiring water volume data in a preset time period of a target area, and converting the water volume data into grid data; determining a drought event of a target area and characteristic parameters of the drought event based on a run length theory and grid data, wherein the drought event comprises the following steps: a hydrological drought event, an agricultural drought event, and an meteorological drought event; determining a target drought event based on the characteristic parameters of the drought event, and constructing a drought chain event based on the target drought event, wherein the target drought event is a drought event with an association relationship in the drought event, and the association relationship comprises a time association relationship and a space association relationship; the characteristic parameters of the drought chain event are determined based on the characteristic parameters of the target drought event corresponding to the drought chain event, and the technical problem that the matching accuracy of the existing meteorological, hydrological and agricultural drought events is low is solved.
Description
Technical Field
The invention relates to the technical field of drought management and handling, in particular to a three-dimensional identification and matching method and device for a drought event.
Background
The complex nature and wide impact of drought results in the lack of a proper definition, which allows different departments to further classify drought into different types, such as meteorological drought, agricultural drought, hydrological drought, and the like, from their respective perspectives. However, different types of drought are closely related, meteorological drought characterized by insufficient precipitation often triggers agricultural drought and hydrographic drought, and the agricultural drought and hydrographic drought have relatively complex transfer relationships, and the division of a complete drought transfer process is unscientific and incomplete. The three-dimensional identification and matching of the weather-hydrology-agricultural drought event from the three-dimensional space-time perspective has great significance for revealing the drought chain transfer characteristics and early warning of hydrology and agricultural drought.
Under the climate change background with global warming as a main characteristic, the frequency and the intensity of drought show an increasing trend, the drought monitoring index with month as a main time scale loses effectiveness on sudden drought events, and the time resolution of drought event analysis is urgently needed to be improved; the existing drought event identification method neglects the spatial continuity of the drought event, and the analysis of the drought event is urgently needed to be carried out from the perspective of three-dimensional time and space. In addition, the drought event matching research is mainly aimed at two types of weather-hydrology or weather-agriculture drought events, and the matching of the three types of weather-hydrology-agriculture drought events needs to be perfected and needs to be further researched. When matching different types of drought events is carried out, most of the existing methods identify the corresponding relation and the non-corresponding relation between meteorological drought and hydrological or agricultural drought events by drawing up assumed conditions. The assumed conditions comprise more parameters predefined according to experience, such as the requirement for artificially setting the starting time of the initiation of the hydrological drought event and the agricultural drought event, the requirement for artificially setting the overlapping time of the hydrological drought event and the agricultural drought event with the meteorological drought event, the requirement for artificially setting the lag time of the hydrological drought event and the agricultural drought event on the meteorological drought event, and the like. Although these methods can determine the corresponding relationship between weather drought and hydrological or agricultural drought events, various predetermined time parameters become one of the sources of uncertainty in the definition of the corresponding relationship. How to provide a three-dimensional identification and matching method for meteorological-hydrological-agricultural drought events, which is oriented to three drought types and gets rid of preset time parameters, is important content for quantifying field scale meteorological-hydrological-agricultural drought chain event transfer characteristics from a physical significance. The research result has theoretical significance in deepening the understanding of the water circulation water stripping process and has practical significance in early drought early warning and fine management.
Disclosure of Invention
In view of the above, the present invention provides a method and an apparatus for three-dimensional identification and matching of an drought event, so as to alleviate the technical problem of low matching accuracy of the existing meteorological, hydrological and agricultural drought events.
In a first aspect, an embodiment of the present invention provides a three-dimensional identification and matching method for a drought event, including: acquiring water volume data in a preset time period of a target area, and converting the water volume data into grid data, wherein the water volume data comprises: precipitation data, runoff data and soil water storage capacity data; determining a drought event of the target area and characteristic parameters of the drought event based on a run length theory and the grid data, wherein the drought event comprises: a hydrological drought event, an agricultural drought event, and an meteorological drought event; determining a target drought event based on the characteristic parameters of the drought event, and constructing a drought chain event based on the target drought event, wherein the target drought event is a drought event with an association relationship in the drought event, and the association relationship comprises a time association relationship and a space association relationship; and determining the characteristic parameters of the drought chain event based on the characteristic parameters of the target drought event corresponding to the drought chain event.
Further, target data of the target area at each time node is determined based on the water volume data in the preset time period, wherein the target data includes: the rainfall data comprises a climate accumulated value, a runoff data climate accumulated value and a soil water storage data climate average value; constructing the mesh data based on the target data, wherein the mesh data comprises: precipitation grid data, runoff grid data and soil water storage grid data.
Further, determining the drought event of the target area and the characteristic parameters of the drought event based on the run length theory and the grid data, including: determining drought grid points in the grid data based on the grid data and a preset quantile threshold value; merging target drought lattice points in the drought lattice points to obtain drought patches, wherein the target drought lattice points are adjacent drought lattice points; overlapping the drought patches of adjacent time nodes, determining the overlapping area of the overlapping area, and determining the drought patches with the overlapping area larger than the preset area as the same drought event; and performing feature extraction on the drought event based on the run length theory to obtain feature parameters of the drought event, wherein the feature parameters comprise: start time, end time, duration, average area, maximum area, and shroud area.
Further, determining drought grid points in the grid data based on the grid data and a preset quantile threshold value, including: determining the meteorological drought grid point based on the precipitation grid data and a preset quantile threshold value; determining the hydrological drought lattice point based on the runoff grid data and a preset quantile threshold value; and determining the agricultural drought grid point based on the soil water storage capacity grid data and a preset quantile threshold value.
Further, determining a target drought event based on the characteristic parameters of the drought event, and constructing a drought chain event based on the target drought event, wherein the method comprises the following steps: determining a first meteorological drought event corresponding to the hydrological drought event and a second meteorological drought event corresponding to the agricultural drought event based on the characteristic parameters, wherein the first meteorological drought event is a meteorological drought event with an end time between the start time and the end time of the hydrological drought event, and the second meteorological drought event is a meteorological drought event with an end time between the start time and the end time of the agricultural drought event; determining a first distribution of transit times between the first weather drought event and the hydrologic drought event, and determining a second distribution of transit times between the second weather drought event and the agricultural drought event; determining a median in the first distribution of transfer times as a first optimal transfer time and a median in the second distribution of transfer times as a second optimal transfer time; and determining the target drought event based on the first optimal transfer time, the second optimal transfer time and the characteristic parameters, and constructing a drought chain event based on the target drought event.
Further, determining the target drought event based on the first optimal delivery time, the second optimal delivery time and the characteristic parameters comprises: determining a first initial meteorological drought event of the first meteorological drought events that is time-correlated with the hydrological drought event based on the first optimal transfer time, the start time and the end time of the hydrological drought event, and determining a second initial meteorological drought event of the second meteorological drought events that is time-correlated with the agricultural drought event based on the second optimal transfer time, the start time and the end time of the agricultural drought event; determining a first intermediate weather drought event in the first initial weather drought event which has a spatial association with the hydrological drought event based on the covered area of the first initial weather drought event and the covered area of the hydrological drought event, and determining a second intermediate weather drought event in the second initial weather drought event which has a spatial association with the agricultural drought event based on the covered area of the second initial weather drought event and the covered area of the agricultural drought event; determining a target weather drought event in the first intermediate weather drought event and the second intermediate weather drought event, wherein the target weather drought event is a weather drought event contained in both the first intermediate weather drought event and the second intermediate weather drought event; and determining the target weather drought event, the hydrological drought event corresponding to the target weather drought event and the agricultural drought event as the target drought event.
Further, the characteristic parameters of the drought chain event comprise: beginning an event, ending an event, duration, response time of a corresponding hydrological drought event to the target meteorological drought event, response time of a corresponding agricultural drought event to the target meteorological drought event, lag time of a corresponding hydrological drought event to the target meteorological drought event, and lag time of a corresponding agricultural drought event to the target meteorological drought event.
In a second aspect, an embodiment of the present invention further provides a device for three-dimensional identification and matching of a drought event, including: the device comprises an acquisition unit, a first determination unit, a construction unit and a second determination unit, wherein the acquisition unit is used for acquiring water volume data in a preset time period of a target area and converting the water volume data into grid data, and the water volume data comprises: precipitation data, runoff data and soil water storage capacity data; the first determining unit is configured to determine, based on a run length theory and the grid data, a drought event of the target area and characteristic parameters of the drought event, where the drought event includes: a hydrological drought event, an agricultural drought event, and an meteorological drought event; the constructing unit is used for determining a target drought event based on the characteristic parameters of the drought event and constructing a drought chain event based on the target drought event, wherein the target drought event is a drought event with an incidence relation in the drought event, and the incidence relation comprises a time incidence relation and a space incidence relation; the second determining unit is configured to determine the characteristic parameters of the drought chain event based on the characteristic parameters of the target drought event corresponding to the drought chain event.
In a third aspect, an embodiment of the present invention further provides an electronic device, which includes a memory and a processor, where the memory is used to store a program that supports the processor to execute the method in the first aspect, and the processor is configured to execute the program stored in the memory.
In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored.
In the embodiment of the present invention, water volume data in a preset time period of a target area is obtained, and the water volume data is converted into grid data, where the water volume data includes: precipitation data, runoff data and soil water storage capacity data; determining a drought event of the target area and characteristic parameters of the drought event based on a run length theory and the grid data, wherein the drought event comprises: a hydrological drought event, an agricultural drought event, and an meteorological drought event; determining a target drought event based on the characteristic parameters of the drought event, and constructing a drought chain event based on the target drought event, wherein the target drought event is a drought event with an association relationship in the drought event, and the association relationship comprises a time association relationship and a space association relationship; and determining the characteristic parameters of the drought chain event based on the characteristic parameters of the target drought event corresponding to the drought chain event, so that the aim of matching the weather, hydrology and agricultural drought event from time and space dimensions is fulfilled, the technical problem that the existing weather, hydrology and agricultural drought event has high matching uncertainty is solved, and the technical effect of improving the matching accuracy of the weather, hydrology and agricultural drought event is achieved.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a flow chart of a three-dimensional identification and matching method for drought events according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a three-dimensional identification and matching device for drought events according to an embodiment of the present invention;
fig. 3 is a schematic diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
To make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
The first embodiment is as follows:
in accordance with an embodiment of the present invention, there is provided an embodiment of a method for three-dimensional identification and matching of drought events, it is noted that the steps illustrated in the flowchart of the accompanying drawings may be performed in a computer system such as a set of computer-executable instructions, and that while a logical order is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in an order different than here.
Fig. 1 is a flowchart of a three-dimensional identification and matching method for a drought event according to an embodiment of the present invention, as shown in fig. 1, the method includes the following steps:
step S102, water volume data in a preset time period of a target area are obtained, and the water volume data are converted into grid data, wherein the water volume data comprise: precipitation data, runoff data and soil water storage capacity data;
step S104, determining a drought event of the target area and characteristic parameters of the drought event based on a run length theory and the grid data, wherein the drought event comprises the following steps: hydrological drought events, agricultural drought events, and meteorological drought events;
step S106, determining a target drought event based on the characteristic parameters of the drought event, and constructing a drought chain event based on the target drought event, wherein the target drought event is a drought event with an incidence relation in the drought event, and the incidence relation comprises a time incidence relation and a space incidence relation;
and S108, determining the characteristic parameters of the drought chain event based on the characteristic parameters of the target drought event corresponding to the drought chain event.
In the embodiment of the present invention, water volume data in a preset time period of a target area is obtained, and the water volume data is converted into grid data, where the water volume data includes: precipitation data, runoff data and soil water storage capacity data; determining a drought event of the target area and characteristic parameters of the drought event based on a run length theory and the grid data, wherein the drought event comprises: a hydrological drought event, an agricultural drought event, and an meteorological drought event; determining a target drought event based on the characteristic parameters of the drought event, and constructing a drought chain event based on the target drought event, wherein the target drought event is a drought event with an incidence relation in the drought event, and the incidence relation comprises a time incidence relation and a space incidence relation; and determining the characteristic parameters of the drought chain event based on the characteristic parameters of the target drought event corresponding to the drought chain event, so that the aim of matching the weather, hydrology and agricultural drought event from time and space dimensions is fulfilled, the technical problem that the existing weather, hydrology and agricultural drought event has high matching uncertainty is solved, and the technical effect of improving the matching accuracy of the weather, hydrology and agricultural drought event is achieved.
In the embodiment of the present invention, step S102 includes the following steps:
step S11, determining target data of the target area at each time node based on the water volume data in the preset time period, where the target data includes: the rainfall data comprises a climate accumulated value, a runoff data climate accumulated value and a soil water storage data climate average value;
step S12, constructing the grid data based on the target data, wherein the grid data comprises: precipitation grid data, runoff grid data and soil water storage grid data.
In the embodiment of the invention, precipitation, runoff and soil water storage data are collected, the precipitation, runoff and soil water storage data are respectively processed into a waiting accumulated value of the precipitation data at each time node in a preset time period, a waiting accumulated value of the runoff data and a waiting average value of the soil water storage data on a time scale, the waiting accumulated value of the precipitation data, the waiting accumulated value of the runoff data and the waiting average value of the soil water storage data are processed into higher-resolution gridded precipitation, runoff and soil water storage data on a space scale, and all the data are processed into a unified unit to obtain precipitation gridding data, runoff gridding data and soil water storage gridding data; the rainfall deficit is used for representing meteorological drought, runoff deficit is used for representing hydrological drought, and soil water storage deficit is used for representing agricultural drought.
In the embodiment of the present invention, step S104 includes the following steps:
s21, determining drought grid points in the grid data based on the grid data and a preset quantile threshold value;
s22, merging target drought lattice points in the drought lattice points to obtain drought patches, wherein the target drought lattice points are adjacent drought lattice points;
s23, overlapping the drought patches of the adjacent time nodes to determine the overlapping area of the overlapping areas, and determining the drought patches with the overlapping areas larger than the preset area as the same drought event;
step S24, extracting the characteristics of the drought event based on the run-length theory to obtain the characteristic parameters of the drought event, wherein the characteristic parameters comprise: start time, end time, duration, mean area, maximum area, and cage area.
In the embodiment of the invention, a certain fraction less than 50% is set as a threshold value, drought lattice points of rainfall, runoff and soil water storage at each time point are respectively screened out by relying on a run-length theory, an n x n grid is utilized to traverse a target area, and if elements corresponding to adjacent lattice points are still drought lattice points, drought patches are formed by combination; only the drought plaques with each time point larger than the preset minimum plaque area are reserved.
And overlapping the drought patches at the adjacent time points in space, and if the overlapping area is larger than the minimum overlapping area, determining that the two drought patches belong to the same drought event and assigning the same drought event number.
Extracting characteristics of the drought event, including the drought starting time, the drought ending time, the duration, the average area, the maximum area, the covering area and the like, by depending on a run-length theory, wherein the drought duration is the total time of the drought event from the beginning to the end; the average drought area is the average of the occupied areas of all time points within the duration of a drought event; the maximum drought area is the maximum value of the occupied area of each time point within the duration of one drought event; the drought cage area is the union area of the grid points occupied by each time point within the duration of a drought event.
It should be noted that the minimum overlapping area determines the following formula:
wherein 1 and 0 respectively represent the existence and nonexistence of spatial overlap between the local drought event and the last drought event;A t andA t-1 respectively representing the plaque areas of the current drought event and the last drought event;A ST represents the area of the study region;MinA t,t-1 representing the minimum coincidence area of the patch areas of the drought event and the last drought event;αrepresents the minimum percentage of overlap based on the area of the study region;βrepresents the minimum percentage of overlap based on the area of drought events.
In the embodiment of the present invention, step S106 includes the following steps:
step S31, determining a first weather drought event corresponding to the hydrological drought event and a second weather drought event corresponding to the agricultural drought event based on the characteristic parameters, wherein the first weather drought event is the weather drought event of which the ending time is between the starting time and the ending time of the hydrological drought event, and the second weather drought event is the weather drought event of which the ending time is between the starting time and the ending time of the agricultural drought event;
step S32, determining a first transmission time distribution between the first weather drought event and the hydrologic drought event, and determining a second transmission time distribution between the second weather drought event and the agricultural drought event;
step S33, determining the median in the first transmission time distribution as a first optimal transmission time, and determining the median in the second transmission time distribution as a second optimal transmission time;
and S34, determining the target drought event based on the first optimal transfer time, the second optimal transfer time and the characteristic parameters, and constructing a drought chain event based on the target drought event.
It should be noted that step S34 includes the following steps: determining a first initial meteorological drought event of the first meteorological drought events that is time-correlated with the hydrological drought event based on the first optimal transfer time, the start time and the end time of the hydrological drought event, and determining a second initial meteorological drought event of the second meteorological drought events that is time-correlated with the agricultural drought event based on the second optimal transfer time, the start time and the end time of the agricultural drought event;
determining a first intermediate weather drought event in the first initial weather drought event which has a spatial association with the hydrological drought event based on the covered area of the first initial weather drought event and the covered area of the hydrological drought event, and determining a second intermediate weather drought event in the second initial weather drought event which has a spatial association with the agricultural drought event based on the covered area of the second initial weather drought event and the covered area of the agricultural drought event;
determining a target weather drought event in the first intermediate weather drought event and the second intermediate weather drought event, wherein the target weather drought event is a weather drought event contained in both the first intermediate weather drought event and the second intermediate weather drought event;
and determining the target weather drought event, the hydrological drought event corresponding to the target weather drought event and the agricultural drought event as the target drought event.
In the embodiment of the invention, a first meteorological drought event and a second meteorological drought event are screened within the period of a hydrological drought event and an agricultural drought event, and the transmission time distribution from the first meteorological drought event and the second meteorological drought event to each field of the hydrological drought event and the agricultural drought event is calculated according to the end time of the hydrological drought event and the agricultural drought event and the latest end time of the first meteorological drought event and the second meteorological drought event obtained by screening; and taking the median of the transfer times as the optimal transfer times from the meteorological drought event to the hydrological drought event and the agricultural drought event, thereby determining the first optimal transfer time and the second optimal transfer time.
Screening meteorological drought events which are time-correlated with the hydrological drought events and the agricultural drought events in each field according to the starting time, the ending time and the optimal transmission time of the hydrological drought events and the agricultural drought events; according to the contact ratio of the meteorological drought event, the hydrological drought event and the agricultural drought event to the area of the cage, further screening the meteorological drought event which has sufficient spatial overlap with the hydrological drought event and the agricultural drought event in each field, and thus establishing the three-dimensional corresponding relationship of the meteorological drought event, the hydrological drought event and the agricultural drought event;
when the meteorological drought event corresponding to the hydrological drought event overlaps with the meteorological drought event corresponding to the agricultural drought event (i.e., the target meteorological drought event), the hydrological drought event and the agricultural drought event are considered to have a water exchange and correspondence relationship, thereby establishing a three-dimensional correspondence relationship of the meteorological-hydrological-agricultural drought event.
It should be noted that, the following formula is used to screen weather drought events having time correlation with each hydrological (agricultural) drought event:
wherein 1 and 0 represent the temporal association of the presence and absence, respectively, of a meteorological drought event and a hydrological (agricultural) drought event;MBT i andHBT j respectively representiWeather in the field drought event andjthe start time of a field hydrological (agricultural) drought event;MET i andHET j respectively representiWeather in the field drought event andjend time of a field hydrological (agricultural) drought event;BPTrepresents the optimal transfer time from a meteorological drought event to a hydrological (agricultural) drought event;
the following formula was screened for meteorological drought events with sufficient spatial overlap with each field of hydrological (agricultural) drought events:
wherein 1 and 0 represent the presence and absence of spatial overlap of the weather and hydrological (agricultural) drought events, respectively, on a time correlated basis;MUA i andEUA j respectively representiWeather in the field drought event andjcage area for field hydrological (agricultural) drought events;A ST represents the area of the study region;MinA i,j represents the minimum coincidence area of the area covered by the meteorological drought event and the hydrological (agricultural) drought event;αrepresents the minimum percentage of overlap based on the area of the study region;βrepresents the minimum percentage of overlap based on the area of drought events.
In addition, after determining the drought chain event, the characteristic parameters of the drought chain event and the characteristics of each single type of drought event need to be determined specifically as follows: the single type drought starting time is the minimum value of the starting time of each drought event; the single type drought ending time is the maximum value of the ending time of each drought event; the duration of the single type of drought is the sum of the durations of each drought event; the single type drought cage area is the union area of the grid points occupied by each time point within the duration of each drought event; the starting time of the drought chain event is the minimum value of the starting time of each type of drought; the end time of the drought chain event is the maximum value of the end time of each type of drought; the duration of the drought chain event is the difference between the ending time of the drought chain event and the starting time of the drought chain event; the response time of the hydrological (agricultural) drought to the meteorological drought in the drought chain event is the difference between the starting time of the hydrological (agricultural) drought and the starting time of the meteorological drought; the lag time of the hydrological (agricultural) drought to the meteorological drought in the drought chain event is the difference between the end time of the hydrological (agricultural) drought and the end time of the meteorological drought.
The embodiment of the invention provides a three-dimensional identification and matching method for drought events, which is oriented to three drought types and gets rid of preset time parameters, improves the space-time resolution of drought event identification, can quantify the transfer characteristics of field scale meteorological-hydrological-agricultural drought chain events from the physical significance, perfects the space-time granularity and the abundance of the drought event description, and has practical significance for early warning and fine management of hydrological and agricultural drought.
Example two:
the embodiment of the invention also provides a three-dimensional identification and matching device for the drought event, which is used for executing the three-dimensional identification and matching method for the drought event provided by the embodiment of the invention, and the following is a specific introduction of the device provided by the embodiment of the invention.
As shown in fig. 2, fig. 2 is a schematic diagram of the above three-dimensional identification and matching device for drought events, and the three-dimensional identification and matching device for drought events includes: an acquisition unit 10, a first determination unit 20, a construction unit 30 and a second determination unit 40.
The acquisition unit is used for acquiring water volume data in a preset time period of a target area and converting the water volume data into grid data, wherein the water volume data comprises: precipitation data, runoff data and soil water storage capacity data;
the first determining unit is configured to determine, based on a run length theory and the grid data, a drought event of the target area and characteristic parameters of the drought event, where the drought event includes: a hydrological drought event, an agricultural drought event, and an meteorological drought event;
the constructing unit is used for determining a target drought event based on the characteristic parameters of the drought event and constructing a drought chain event based on the target drought event, wherein the target drought event is a drought event with an association relationship in the drought event, and the association relationship comprises a time association relationship and a space association relationship;
the second determining unit is configured to determine the characteristic parameter of the drought chain event based on the characteristic parameter of the target drought event corresponding to the drought chain event.
In the embodiment of the present invention, water volume data in a preset time period of a target area is obtained, and the water volume data is converted into grid data, where the water volume data includes: precipitation data, runoff data and soil water storage capacity data; determining a drought event of the target area and characteristic parameters of the drought event based on a run length theory and the grid data, wherein the drought event comprises: a hydrological drought event, an agricultural drought event, and an meteorological drought event; determining a target drought event based on the characteristic parameters of the drought event, and constructing a drought chain event based on the target drought event, wherein the target drought event is a drought event with an incidence relation in the drought event, and the incidence relation comprises a time incidence relation and a space incidence relation; and determining the characteristic parameters of the drought chain event based on the characteristic parameters of the target drought event corresponding to the drought chain event, so that the aim of matching the weather, hydrology and agricultural drought event from time and space dimensions is fulfilled, the technical problem that the existing weather, hydrology and agricultural drought event has high matching uncertainty is solved, and the technical effect of improving the matching accuracy of the weather, hydrology and agricultural drought event is achieved.
Example three:
an embodiment of the present invention further provides an electronic device, including a memory and a processor, where the memory is used to store a program that supports the processor to execute the method described in the first embodiment, and the processor is configured to execute the program stored in the memory.
Referring to fig. 3, an embodiment of the present invention further provides an electronic device 100, including: the device comprises a processor 50, a memory 51, a bus 52 and a communication interface 53, wherein the processor 50, the communication interface 53 and the memory 51 are connected through the bus 52; the processor 50 is arranged to execute executable modules, such as computer programs, stored in the memory 51.
The Memory 51 may include a high-speed Random Access Memory (RAM) and may also include a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. The communication connection between the network element of the system and at least one other network element is realized through at least one communication interface 53 (which may be wired or wireless), and the internet, a wide area network, a local network, a metropolitan area network, and the like can be used.
The bus 52 may be an ISA bus, PCI bus, EISA bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one double-headed arrow is shown in FIG. 3, but this does not indicate only one bus or one type of bus.
The memory 51 is used for storing a program, the processor 50 executes the program after receiving an execution instruction, and the method executed by the apparatus defined by the flow process disclosed in any of the foregoing embodiments of the present invention may be applied to the processor 50, or implemented by the processor 50.
The processor 50 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware or instructions in the form of software in the processor 50. The Processor 50 may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; the Integrated Circuit may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, or discrete hardware components. The various methods, steps and logic blocks disclosed in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software modules may be located in ram, flash, rom, prom, or eprom, registers, etc. as is well known in the art. The storage medium is located in the memory 51, and the processor 50 reads the information in the memory 51 and completes the steps of the method in combination with the hardware thereof.
Example four:
the embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program performs the steps of the method in the first embodiment.
In addition, in the description of the embodiments of the present invention, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it should be understood by those skilled in the art that the following descriptions are only illustrative and not restrictive, and that the scope of the present invention is not limited to the above embodiments: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the embodiments of the present invention, and they should be construed as being included therein. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A three-dimensional identification and matching method for drought events is characterized by comprising the following steps:
acquiring water volume data in a preset time period of a target area, and converting the water volume data into grid data, wherein the water volume data comprises: precipitation data, runoff data and soil water storage capacity data;
determining a drought event of the target area and characteristic parameters of the drought event based on a run length theory and the grid data, wherein the drought event comprises: hydrological drought events, agricultural drought events, and meteorological drought events;
determining a target drought event based on the characteristic parameters of the drought event, and constructing a drought chain event based on the target drought event, wherein the target drought event is a drought event with an incidence relation in the drought event, and the incidence relation comprises a time incidence relation and a space incidence relation;
and determining the characteristic parameters of the drought chain event based on the characteristic parameters of the target drought event corresponding to the drought chain event.
2. The method of claim 1, wherein converting the water volume data into grid data comprises:
determining target data of the target area at each time node based on the water volume data in the preset time period, wherein the target data comprises: the rainfall data comprises a climate accumulated value of the rainfall data, a climate accumulated value of the runoff data and a climate average value of the soil water storage amount data;
constructing the mesh data based on the target data, wherein the mesh data comprises: precipitation grid data, runoff grid data and soil water storage grid data.
3. The method of claim 2, wherein determining the drought event of the target area and the characteristic parameters of the drought event based on run length theory and the grid data comprises:
determining drought grid points in the grid data based on the grid data and a preset quantile threshold value;
merging target drought lattice points in the drought lattice points to obtain drought patches, wherein the target drought lattice points are adjacent drought lattice points;
overlapping the drought patches of adjacent time nodes, determining the overlapping area of the overlapping areas, and determining the drought patches of which the overlapping areas are larger than a preset area as the same drought event;
and performing feature extraction on the drought event based on the run length theory to obtain feature parameters of the drought event, wherein the feature parameters comprise: start time, end time, duration, mean area, maximum area, and cage area.
4. The method of claim 2, wherein determining drought lattice points in the lattice data based on the lattice data and a preset quantile threshold comprises:
determining the meteorological drought grid point based on the precipitation grid data and a preset quantile threshold value;
determining the hydrologic drought lattice point based on the runoff grid data and a preset quantile threshold value;
and determining the agricultural drought lattice point based on the soil water storage amount grid data and a preset quantile threshold value.
5. The method of claim 1, wherein determining a target drought event based on the characteristic parameters of the drought event and constructing a drought chain event based on the target drought event comprises:
determining a first meteorological drought event corresponding to the hydrological drought event and a second meteorological drought event corresponding to the agricultural drought event based on the characteristic parameters, wherein the first meteorological drought event is a meteorological drought event with an end time between the start time and the end time of the hydrological drought event, and the second meteorological drought event is a meteorological drought event with an end time between the start time and the end time of the agricultural drought event;
determining a first distribution of transit times between the first weather drought event and the hydrological drought event, and determining a second distribution of transit times between the second weather drought event and the agricultural drought event;
determining a median in the first distribution of transfer times as a first optimal transfer time and a median in the second distribution of transfer times as a second optimal transfer time;
and determining the target drought event based on the first optimal transfer time, the second optimal transfer time and the characteristic parameters, and constructing a drought chain event based on the target drought event.
6. The method of claim 5, wherein determining the target drought event based on the first optimal delivery time, the second optimal delivery time, and the characteristic parameters comprises:
determining a first initial meteorological drought event of the first meteorological drought events that is time-correlated with the hydrological drought event based on the first optimal transfer time, the start time and the end time of the hydrological drought event, and determining a second initial meteorological drought event of the second meteorological drought events that is time-correlated with the agricultural drought event based on the second optimal transfer time, the start time and the end time of the agricultural drought event;
determining a first intermediate weather drought event in the first initial weather drought event which has a spatial association with the hydrological drought event based on the covered area of the first initial weather drought event and the covered area of the hydrological drought event, and determining a second intermediate weather drought event in the second initial weather drought event which has a spatial association with the agricultural drought event based on the covered area of the second initial weather drought event and the covered area of the agricultural drought event;
determining a target weather drought event in the first intermediate weather drought event and the second intermediate weather drought event, wherein the target weather drought event is a weather drought event contained in both the first intermediate weather drought event and the second intermediate weather drought event;
and determining the target weather drought event, the hydrological drought event corresponding to the target weather drought event and the agricultural drought event as the target drought event.
7. The method of claim 6,
the characteristic parameters of the drought chain event comprise: beginning an event, ending an event, duration, response time of a corresponding hydrological drought event to the target meteorological drought event, response time of a corresponding agricultural drought event to the target meteorological drought event, lag time of a corresponding hydrological drought event to the target meteorological drought event, and lag time of a corresponding agricultural drought event to the target meteorological drought event.
8. A three-dimensional identification and matching apparatus for drought events, comprising: an obtaining unit, a first determining unit, a constructing unit and a second determining unit, wherein,
the acquiring unit is configured to acquire water volume data in a preset time period of a target area, and convert the water volume data into grid data, where the water volume data includes: precipitation data, runoff data and soil water storage capacity data;
the first determining unit is configured to determine a drought event of the target area and characteristic parameters of the drought event based on a run length theory and the grid data, where the drought event includes: a hydrological drought event, an agricultural drought event, and an meteorological drought event;
the constructing unit is used for determining a target drought event based on the characteristic parameters of the drought event and constructing a drought chain event based on the target drought event, wherein the target drought event is a drought event with an association relationship in the drought event, and the association relationship comprises a time association relationship and a space association relationship;
the second determining unit is configured to determine the characteristic parameters of the drought chain event based on the characteristic parameters of the target drought event corresponding to the drought chain event.
9. An electronic device comprising a memory for storing a program that enables a processor to perform the method of any of claims 1 to 7 and a processor configured to execute the program stored in the memory.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method according to any one of the claims 1 to 7.
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