CN114781713A - Rainfall station network optimization method and device based on satellite inversion precipitation product - Google Patents
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Abstract
The invention relates to the technical field of rainfall station network planning, and discloses a rainfall station network optimization method and device based on satellite inversion precipitation products, aiming at improving the representativeness of rainfall station arrangement, and the scheme mainly comprises the following steps: acquiring first rainfall data measured by a rainfall station network, wherein the rainfall station network comprises a plurality of rainfall stations, and the first rainfall data is obtained by detection of the plurality of rainfall stations; performing interpolation processing on the first rainfall data by a kriging method to obtain rainfall distribution data of the whole area of the rainfall station network; acquiring second rainfall data corresponding to the rainfall station network geographical position information based on the satellite inversion precipitation product; and respectively carrying out visualization processing on the first rainfall data and the second rainfall data after interpolation processing to obtain a first rainfall distribution diagram corresponding to the first rainfall data after interpolation processing and a second rainfall distribution diagram corresponding to the second rainfall data, and optimizing the rainfall station network according to the difference between the first rainfall distribution diagram and the second rainfall distribution diagram.
Description
Technical Field
The invention relates to the technical field of rainfall station network planning, in particular to a rainfall station network optimization method and device based on satellite inversion precipitation products.
Background
The rainfall station network is mainly widely applied to hydraulic engineering, hydroelectric engineering, disaster monitoring and early warning, flood control decision-making departments and meteorological departments. Planning and optimizing the rainfall station network are to discuss how to scientifically lay the regional rainfall station network. The distribution of the rainfall station network determines the accuracy and the representativeness of reflecting the real rainfall condition, so that disaster monitoring and early warning, flood forecasting precision, flood control decision and the like are directly influenced, the rainfall station network is scientifically planned and optimized, the rainfall data can reflect the actual rainfall condition of the area to the maximum extent, and huge benefits can be brought to the actual production of multiple fields.
A plurality of research methods are proposed and developed for planning and laying rainfall stations at home and abroad, wherein the research methods comprise a simulation approximation method, a correlation coefficient method, a rainstorm center method, a station extraction method and the like, the existing method can only solve the problem of density requirement on an area surface, and meanwhile, no method is widely used at present due to randomness of a rainfall process, complexity of terrain distribution and completeness of research data.
In the prior art, a lot of station pulling methods are used, which are that the average rainfall of a surface is calculated by using all rainfall data of a rainfall station network dense area to serve as an approximate true value of the average rainfall of the drainage basin surface, then a part of rainfall stations are pulled out according to a uniformly distributed station pulling principle, the average rainfall of the surface is calculated, the error is calculated by comparing with the approximate true value, the relation between the error and the factors such as station distribution density, statistical time interval, terrain and the like is sought, and the station distribution quantity meeting the precision requirement is discussed. The station-drawing method is visual in concept and is often used as a standard for measuring and testing other methods, but the station-drawing method has an obvious defect that a rainfall station is evenly drawn in the whole area to directly calculate the surface rainfall, and a network density formula of a matched rainfall station obtained by the station-drawing method only considers the overall characteristics of the area of average elevation in a general way without considering the influence of the terrain with a larger scale in the research area, so that the calculation result of the surface rainfall cannot well represent the actual underlying surface condition of a specific drainage basin. Meanwhile, the station extraction method is not only complex, but also the premise of the application is that the area has dense rainfall data of the rainfall station network, and the method cannot be applied to areas without data and areas with sparse data.
Disclosure of Invention
The invention aims to provide a rainfall station network optimization method and device based on satellite inversion precipitation products, so as to optimize the rainfall station network in areas without data or with little data, and further improve the representativeness of the arrangement of the rainfall stations.
The technical scheme adopted by the invention for solving the technical problems is as follows:
on one hand, the rainfall station network optimization method based on the satellite inversion precipitation product comprises the following steps:
step 1, acquiring first rainfall data actually measured by a rainfall station network, wherein the rainfall station network comprises a plurality of rainfall stations, and the first rainfall data is obtained by detecting the plurality of rainfall stations;
step 2, carrying out interpolation processing on the first rainfall data through a kriging method to obtain rainfall distribution data of the whole area of the rainfall station network;
step 3, acquiring second rainfall data corresponding to the rainfall station network geographical position information based on the satellite inversion precipitation product;
step 4, respectively performing visualization processing on the first rainfall data and the second rainfall data after the interpolation processing to obtain a first rainfall distribution diagram corresponding to the first rainfall data after the interpolation processing and a second rainfall distribution diagram corresponding to the second rainfall data;
and 5, optimizing the rainfall station network according to the difference between the first rainfall distribution diagram and the second rainfall distribution diagram.
Further, step 4 is preceded by:
and extracting third rainfall data corresponding to the position information of each rainfall station from the second rainfall data, judging whether the consistency of the first rainfall data and the third rainfall data meets the requirement, if so, entering a step 4, otherwise, optimizing the laid rainfall stations and entering a step 1.
Further, judging whether the consistency of the first rainfall data and the third rainfall data meets the requirement, specifically comprising:
and judging whether the correlation coefficient of the first rainfall data and the third rainfall data is in a first preset range, whether the root mean square error is in a second preset range and whether the relative deviation is in a third preset range, if so, judging that the consistency of the first rainfall data and the third rainfall data meets the requirement, otherwise, judging that the consistency of the first rainfall data and the third rainfall data does not meet the requirement.
Further, the calculation formula of the correlation coefficient of the first rainfall data and the third rainfall data is as follows:
wherein CC represents a correlation coefficient, SiThird rainfall data corresponding to the ith rainfall station position information is represented,
an average value G of third rainfall data corresponding to the position information of each rainfall stationiFirst rainfall data measured at the ith rainfall station is represented,
the average value of the first rainfall data measured at each rainfall station is represented, and n represents the number of rainfall stations.
Further, the root mean square error of the first rainfall data and the third rainfall data is calculated according to the following formula:
where RMSE represents the root mean square error, SiThird rainfall data corresponding to the position information of the ith rainfall station, GiAnd the measured first rainfall data of the ith rainfall station is shown, and n is the number of the rainfall stations.
Further, the calculation formula of the relative deviation of the first rainfall data and the third rainfall data is as follows:
in the formula, BIAS represents a relative deviation, SiThird rainfall data, G, corresponding to the i-th rainfall station position informationiAnd the measured first rainfall data of the ith rainfall station is shown, and n is the number of the rainfall stations.
Further, the optimizing the rainfall station network according to the difference between the first rainfall distribution diagram and the second rainfall distribution diagram specifically includes:
and determining whether the interpolation result without the position of the rainfall station is accurate or not according to the difference between the first rainfall distribution diagram and the second rainfall distribution diagram, and arranging the rainfall station at the position with the inaccurate interpolation result.
Further, the first rainfall data, the second rainfall data and the third rainfall data are daily rainfall, weekly rainfall, monthly rainfall or annual rainfall.
Further, performing visualization processing on the first rainfall data and the second rainfall data after the interpolation processing respectively, specifically including:
and performing visualization processing on the first rainfall data and the second rainfall data after the interpolation processing through ArcGis software, unifying the annual rainfall color gradation change to a preset range, and determining the preset range according to the maximum rainfall in the first rainfall data and the second rainfall data.
In another aspect, a rainfall station network optimization device based on satellite inversion precipitation products is provided, including:
the rainfall station network comprises a plurality of rainfall stations, and the first rainfall data is obtained by detection of the plurality of rainfall stations;
the interpolation processing unit is used for carrying out interpolation processing on the first rainfall data through a Kriging method to obtain rainfall distribution data of the whole area of the rainfall station network;
the second acquisition unit is used for acquiring second rainfall data corresponding to the rainfall station network geographical position information based on the satellite inversion precipitation product;
and the visualization processing unit is used for respectively performing visualization processing on the first rainfall data and the second rainfall data after the interpolation processing to obtain a first rainfall distribution diagram corresponding to the first rainfall data after the interpolation processing and a second rainfall distribution diagram corresponding to the second rainfall data, and optimizing the rainfall station network according to the difference between the first rainfall distribution diagram and the second rainfall distribution diagram.
The invention has the beneficial effects that: according to the rainfall station network optimization method and device based on the satellite inversion rainfall product, accurate rainfall data are obtained based on the existing satellite inversion rainfall product, the rainfall data are compared with the rainfall data determined by an interpolation method, and the position of a rainfall station is determined according to the comparison result, so that the representativeness and pertinence of the rainfall station are improved, unnecessary rainfall station construction resources are saved, and the method is simple and independent of historical rainfall data of the rainfall station network.
Drawings
Fig. 1 is a schematic flowchart of a rainfall station network optimization method based on satellite inversion precipitation products according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a second rainfall distribution according to the embodiment of the present invention;
FIG. 2 is a diagram illustrating a first rainfall distribution profile according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a rainfall station network optimization device based on satellite inversion precipitation products according to an embodiment of the present invention.
Detailed Description
Embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
The invention aims to provide a rainfall station network optimization method and device based on satellite inversion precipitation products, and the main technical concept is as follows: acquiring first rainfall data measured by a rainfall station network, wherein the rainfall station network comprises a plurality of rainfall stations, and the first rainfall data is obtained by detecting the plurality of rainfall stations; performing interpolation processing on the first rainfall data by a kriging method to obtain rainfall distribution data of the whole area of the rainfall station network; acquiring second rainfall data corresponding to the rainfall station network geographical position information based on the satellite inversion precipitation product; and respectively carrying out visualization processing on the first rainfall data and the second rainfall data after interpolation processing to obtain a first rainfall distribution diagram corresponding to the first rainfall data after interpolation processing and a second rainfall distribution diagram corresponding to the second rainfall data, and optimizing the rainfall station network according to the difference between the first rainfall distribution diagram and the second rainfall distribution diagram.
Specifically, a plurality of rainfall stations are distributed in the rainfall station network, the first rainfall data detected by each rainfall station can only reflect the rainfall data corresponding to the position of the rainfall station, and for the position where no rainfall station is distributed, the rainfall data of the position needs to be determined according to the first rainfall data collected by the adjacent rainfall stations and based on an interpolation method. Based on the above, the invention firstly carries out interpolation processing on the first rainfall data detected by each rainfall station based on a Krigin interpolation method, and accurate second rainfall data corresponding to the rainfall station network position information is obtained from the satellite inversion precipitation products, then performing visualization processing on the first rainfall data after interpolation processing to generate a corresponding first rainfall data distribution diagram, performing visualization processing on the second rainfall data to generate a corresponding second rainfall data distribution diagram, and finally optimizing the rainfall station network according to the difference between the first rainfall distribution diagram and the second rainfall distribution diagram, the rainfall station layout method comprises the steps of comparing first rainfall data determined based on an interpolation method in a first rainfall distribution diagram with second rainfall data corresponding to positions where rainfall stations are not laid in a second rainfall distribution diagram, and laying the rainfall stations according to comparison results.
Examples
The rainfall station network optimization method based on the satellite inversion precipitation product, disclosed by the embodiment of the invention, as shown in figure 1, comprises the following steps of:
step 1, acquiring first rainfall data actually measured by a rainfall station network, wherein the rainfall station network comprises a plurality of rainfall stations, and the first rainfall data is obtained by detecting the plurality of rainfall stations;
it can be understood that, for a rainfall station network, a set rainfall station generally cannot cover all areas, and in this embodiment, first rainfall data measured by the rainfall station network, that is, rainfall data obtained by the set rainfall station, is obtained first.
Step 2, performing interpolation processing on the first rainfall data through a Kriging method to obtain rainfall distribution data of the whole area of the rainfall station network;
it can be understood that, since the first rainfall data can only reflect the rainfall data of the position having the rainfall station and does not completely reflect the rainfall data of all the positions of the rainfall station network, for the rainfall data of the position not having the rainfall station, the embodiment performs interpolation determination by the kriging method, that is, the first rainfall data collected by the adjacent rainfall stations is determined based on the kriging method, and then the rainfall distribution data of the whole area of the rainfall station network is obtained.
Step 3, acquiring second rainfall data corresponding to the rainfall station network geographical position information based on the satellite inversion rainfall product;
in this embodiment, the satellite inversion precipitation product may be a cmorph (cpc moving technique) satellite inversion precipitation product of a climate prediction center of the american environment prediction center as research data. The CMORPH data download comes from a China meteorological data network, the spatial resolution is 0.1 degrees, and the time scale is 1 h. When the second rainfall data is annual rainfall, the downloaded time interval CMORPH data at the time interval of 1h can be merged into annual scale data, and then the second rainfall data is obtained.
The second rainfall data can accurately reflect rainfall data corresponding to each position in the rainfall station network.
In this embodiment, step 2 is followed by:
and (3) extracting third rainfall data corresponding to the position information of each rainfall station from the second rainfall data, judging whether the consistency of the first rainfall data and the third rainfall data meets the requirement, if so, entering the step 3, otherwise, optimizing the arranged rainfall stations and entering the step 1.
The first rainfall data in this step is rainfall data before interpolation processing, and specifically, whether the consistency of the first rainfall data and the third rainfall data meets the requirement is judged, which specifically includes:
and judging whether the correlation coefficient of the first rainfall data and the third rainfall data is in a first preset range, whether the root mean square error is in a second preset range and whether the relative deviation is in a third preset range, if so, judging that the consistency of the first rainfall data and the third rainfall data meets the requirement, otherwise, judging that the consistency of the first rainfall data and the third rainfall data does not meet the requirement.
The correlation coefficient is used for quantifying the linear correlation degree of the first rainfall data and the third rainfall data, the root-mean-square error is used for quantifying the discrete degree and the relative deviation between the first rainfall data and the third rainfall data, and the relative deviation is used for balancing the average trend of the third rainfall data to the first rainfall data error.
In this embodiment, a calculation formula of the correlation coefficient of the first rainfall data and the third rainfall data is as follows:
the calculation formula of the root mean square error of the first rainfall data and the third rainfall data is as follows:
the calculation formula of the relative deviation of the first rainfall data and the third rainfall data is as follows:
where CC denotes the correlation coefficient, RMSE denotes the root mean square error, BIAS denotes the relative deviation, SiThird rainfall data corresponding to the position information of the ith rainfall station is represented,
an average value G of third rainfall data corresponding to the position information of each rainfall stationiFirst rainfall data measured at the ith rainfall station is represented,
the average value of the first rainfall data measured at each rainfall station is represented, and n represents the number of rainfall stations.
It can be understood that when the consistency of the first rainfall data and the third rainfall data meets the requirement, it indicates that the rainfall data detected by the current rainfall station has high accuracy, the rainfall station network can be planned and optimized based on the satellite inversion precipitation product, and step 4 is entered, otherwise, it may be that the rainfall data detected by the current rainfall station has low accuracy, and at this time, the configuration of the currently deployed rainfall station can be optimized according to the third rainfall data, and step 1 is entered again after optimization.
Step 4, performing visualization processing on the first rainfall data and the second rainfall data after interpolation processing respectively to obtain a first rainfall distribution map corresponding to the first rainfall data after interpolation processing and a second rainfall distribution map corresponding to the second rainfall data;
in this embodiment, the first rainfall data and the second rainfall data after interpolation are visually processed through the ArcGis software, annual rainfall tone scale changes are unified to a preset range, and tone scales corresponding to the same rainfall are the same in the obtained first rainfall distribution map and the second rainfall distribution map, so that the difference between the two rainfall data is visually displayed. The preset range is determined according to the maximum rainfall capacity in the first rainfall data and the second rainfall data, for example, the preset range may be [1,2400 ].
In this embodiment, the first rainfall data, the second rainfall data and the third rainfall data may be a daily rainfall, a weekly rainfall, a monthly rainfall or an annual rainfall, etc.
And 5, optimizing the rainfall station network according to the difference between the first rainfall distribution diagram and the second rainfall distribution diagram.
In this embodiment, optimizing the rainfall station network according to the difference between the first rainfall distribution map and the second rainfall distribution map specifically includes: and determining whether the interpolation result without the position of the rainfall station is accurate or not according to the difference between the first rainfall distribution diagram and the second rainfall distribution diagram, and arranging the rainfall station at the position where the interpolation result is inaccurate.
Specifically, as shown in fig. 2, after the second rainfall distribution diagram and the first rainfall distribution diagram are obtained, the difference between the rainfall data determined based on the interpolation method in the first rainfall distribution diagram and the rainfall data corresponding to the position where the rainfall station is not arranged in the second rainfall distribution diagram can be determined through the color level difference between the two diagrams, and when the rainfall data difference between a certain position and the second rainfall distribution diagram is large, it indicates that the rainfall data determined by the interpolation method at the position is inaccurate, and the rainfall station arranged at the position needs to obtain the rainfall data at the accurate position, so that the optimization of the rainfall station network is realized.
In practical application, in order to improve the accuracy of optimizing the rainfall station network, the first rainfall data, the second rainfall data and the third rainfall data of continuous years can be obtained, the first rainfall distribution map and the second rainfall distribution map corresponding to each year are compared respectively, and the rainfall stations of the rainfall station network are optimized according to the comparison result corresponding to each year, so that the representativeness and pertinence of the distributed rainfall stations are improved, and unnecessary rainfall station construction resources are saved.
Based on the above technical solution, this embodiment further provides a rainfall station network optimization device based on satellite inversion precipitation products, as shown in fig. 3, including:
the system comprises a first acquisition unit, a second acquisition unit and a control unit, wherein the first acquisition unit is used for acquiring first rainfall data actually measured by a rainfall station network, the rainfall station network comprises a plurality of rainfall stations, and the first rainfall data is obtained by detecting the plurality of rainfall stations;
the interpolation processing unit is used for carrying out interpolation processing on the first rainfall data through a Kriging method to obtain rainfall distribution data of the whole area of the rainfall station network;
the second acquisition unit is used for acquiring second rainfall data corresponding to the rainfall station network geographical position information based on the satellite inversion precipitation product;
the visualization processing unit is used for respectively performing visualization processing on the first rainfall data and the second rainfall data after the interpolation processing to obtain a first rainfall distribution map corresponding to the first rainfall data after the interpolation processing and a second rainfall distribution map corresponding to the second rainfall data;
and the optimization unit is used for optimizing the rainfall station network according to the difference between the first rainfall distribution diagram and the second rainfall distribution diagram.
It can be understood that, since the rainfall station network optimization device based on satellite inversion precipitation products according to the embodiment of the present invention is a device for implementing the rainfall station network optimization method based on satellite inversion precipitation products according to the embodiment, for the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is simple, and for relevant points, reference may be made to the partial description of the method.
Claims (10)
1. The rainfall station network optimization method based on the satellite inversion precipitation product is characterized by comprising the following steps:
step 1, acquiring first rainfall data actually measured by a rainfall station network, wherein the rainfall station network comprises a plurality of rainfall stations, and the first rainfall data is obtained by detecting the plurality of rainfall stations;
step 2, performing interpolation processing on the first rainfall data through a Kriging method to obtain rainfall distribution data of the whole area of the rainfall station network;
step 3, acquiring second rainfall data corresponding to the rainfall station network geographical position information based on the satellite inversion precipitation product;
step 4, performing visualization processing on the first rainfall data and the second rainfall data after interpolation processing respectively to obtain a first rainfall distribution map corresponding to the first rainfall data after interpolation processing and a second rainfall distribution map corresponding to the second rainfall data;
and 5, optimizing the rainfall station network according to the difference between the first rainfall distribution diagram and the second rainfall distribution diagram.
2. The method of optimizing a network of rainfall stations based on satellite inversion precipitation products of claim 1 further comprising, prior to said step 4:
and extracting third rainfall data corresponding to the position information of each rainfall station from the second rainfall data, judging whether the consistency of the first rainfall data and the third rainfall data meets the requirement, if so, entering a step 4, otherwise, optimizing the laid rainfall stations and then entering a step 1.
3. The satellite inversion precipitation product-based rainfall station network optimization method of claim 2, wherein determining whether the first rainfall data and the third rainfall data are consistent meets requirements comprises:
and judging whether the correlation coefficient of the first rainfall data and the third rainfall data is in a first preset range, whether the root mean square error is in a second preset range and whether the relative deviation is in a third preset range, if so, judging that the consistency of the first rainfall data and the third rainfall data meets the requirement, otherwise, judging that the consistency of the first rainfall data and the third rainfall data does not meet the requirement.
4. The method of optimizing a rain station network based on satellite inversion precipitation products of claim 3, wherein the correlation coefficient of the first rainfall data and the third rainfall data is calculated as follows:
wherein CC represents a correlation coefficient, SiThird rainfall data corresponding to the ith rainfall station position information is represented,
an average value G of third rainfall data corresponding to the position information of each rainfall stationiFirst rainfall data measured at the ith rainfall station is represented,
the average value of the first rainfall data measured at each rainfall station is represented, and n represents the number of rainfall stations.
5. The method of optimizing a rain station network based on satellite inversion precipitation products of claim 3, wherein the root mean square error of the first precipitation data and the third precipitation data is calculated as follows:
wherein RMSE represents the root mean square error, SiThird rainfall data corresponding to the position information of the ith rainfall station, GiAnd the measured first rainfall data of the ith rainfall station is shown, and n is the number of the rainfall stations.
6. The method of optimizing a rain station network based on satellite inversion precipitation products of claim 3, wherein the relative deviation of the first precipitation data and the third precipitation data is calculated as follows:
in the formula, BIAS represents a relative deviation, SiIndicating location information of the ith rain stationCorresponding third rainfall data, GiAnd the measured first rainfall data of the ith rainfall station is shown, and n is the number of the rainfall stations.
7. The method of optimizing a network of rainfall stations based on satellite inversion precipitation products of claim 1, wherein said optimizing the network of rainfall stations based on the difference between the first and second distribution profiles of rainfall comprises:
and determining whether the interpolation result without the position of the rainfall station is accurate or not according to the difference between the first rainfall distribution diagram and the second rainfall distribution diagram, and arranging the rainfall station at the position with the inaccurate interpolation result.
8. The method of any of claims 1 to 7, wherein the first, second and third rainfall data is daily rainfall, weekly rainfall, monthly rainfall or annual rainfall.
9. The satellite inversion precipitation product-based rainfall station network optimization method of claim 8, wherein the visualizing the interpolated first rainfall data and the interpolated second rainfall data comprises:
and performing visualization processing on the first rainfall data and the second rainfall data after the interpolation processing through ArcGis software, unifying the annual rainfall color gradation change to a preset range, and determining the preset range according to the maximum rainfall in the first rainfall data and the second rainfall data.
10. Rainfall station net optimizing device based on satellite inversion precipitation product, its characterized in that includes:
the system comprises a first acquisition unit, a second acquisition unit and a control unit, wherein the first acquisition unit is used for acquiring first rainfall data actually measured by a rainfall station network, the rainfall station network comprises a plurality of rainfall stations, and the first rainfall data is obtained by detecting the plurality of rainfall stations;
the interpolation processing unit is used for carrying out interpolation processing on the first rainfall data through a Kriging method to obtain rainfall distribution data of the whole area of the rainfall station network;
the second acquisition unit is used for acquiring second rainfall data corresponding to the rainfall station network geographical position information based on the satellite inversion rainfall product;
the visualization processing unit is used for respectively performing visualization processing on the first rainfall data and the second rainfall data after the interpolation processing to obtain a first rainfall distribution map corresponding to the first rainfall data after the interpolation processing and a second rainfall distribution map corresponding to the second rainfall data;
and the optimization unit is used for optimizing the rainfall station network according to the difference between the first rainfall distribution diagram and the second rainfall distribution diagram.
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