A method for evaluating the spatial distribution of rainfall stations

Abstract

The present invention relates to the field of rain gauge technology, and more particularly to a method and medium for evaluating the spatial distribution of rain gauges. The method comprises: calculating a current information score for a target station; calculating a time-varying score for the target station; calculating a coverage score for the target station; calculating a weight; and calculating a comprehensive score for the target station by weighting the current information score, time-varying score, and coverage score. The present invention provides multiple scoring methods for different purposes, enabling multi-objective fusion evaluation based on different evaluation criteria, and is applicable to any rain gauge optimization scenario.

Description

Technical Field

[0001] The present invention relates to the technical field of rain gauges, and in particular to a method and medium for evaluating the spatial distribution of rain gauges. Background Art

[0002] Rain gauges are the most accurate measurement tools for rainfall data. In today's world where big data serves meteorology, various prediction models require accurate data from rain gauges. Therefore, the requirements for the distribution of rain gauges are becoming increasingly higher. The more data from rain gauges, the more accurate the data obtained when using interpolation methods. Of course, the installation and maintenance costs will also increase accordingly.

[0003] The rationality of the rain gauge network distribution is closely related to the real-time deployment strategy. For example, when the strategy aims to maximize efficiency with the fewest stations, the number of rain gauges per unit area is the primary evaluation factor; when the strategy aims to improve interpolation accuracy, the amount of information between adjacent stations is also a factor. Furthermore, factors such as maintenance optimization timelines and maintenance budgets must be considered. This has led to a constant shift in rain gauge evaluation methods, and currently, there is no single, scientifically sound, and long-term evaluation method that takes all these factors into account. Summary of the Invention

[0004] The present invention discloses a method for evaluating the spatial distribution of rainfall stations, and the specific method is as follows:

[0005] Obtain the current rainfall data measured at the target site and several adjacent sites, and calculate the current information score of the target site using the information entropy of the target site;

[0006] Retrieve the historical information volume score of the target site, and calculate the time-varying score of the target site based on the current information volume score of the target site and the change in the historical information volume score;

[0007] Obtain estimated rainfall data calculated by remote sensing satellites, circle adjacent spaces whose estimated rainfall data differ from the target site by a first preset value, and calculate the coverage area score of the target site based on the area of ​​the adjacent spaces and the location distribution of the target site in the adjacent spaces;

[0008] The current information score, time-varying score, and coverage score are weighted to calculate the comprehensive score of the target site.

[0009] The advantage of this embodiment is that different evaluation indicators are provided based on different evaluation criteria. In combination with actual conditions, multi-objective fusion evaluation can be completed by adjusting the weights of different scoring indicators. It is suitable for any rainfall station optimization scenario.

[0010] Furthermore, when the comprehensive scores of several rain gauges in the region are lower than the warning value, regional optimization of the rain gauge network is started. The specific method is as follows:

[0011] Taking the comprehensive score as the optimization goal, the optimization algorithm is used to adjust the position of each rain gauge in the rain gauge network so that the sum of the comprehensive scores of each rain gauge in the rain gauge network is maximized.

[0012] Furthermore, the optimization algorithm is a genetic algorithm, and the specific method is as follows:

[0013] The spatial coordinate distribution of the current rainfall stations in the rainfall station network is used as the initial population;

[0014] Calculate the comprehensive score and of the initialized population;

[0015] The population is selected, crossed, and mutated to generate several new spatial distributions of rainfall stations;

[0016] Calculate the comprehensive score sum of the new rainfall station spatial distribution to form the offspring population;

[0017] Merge the parent and offspring populations to select the next generation input population;

[0018] Repeat the selection, crossover, mutation, calculation and screening operations until the convergence conditions are met;

[0019] The spatial distribution of several new rain gauges at the final convergence is taken as the optimization result of the rain gauge network.

[0020] The advantage of this embodiment is that the comprehensive scoring can reflect whether the rain gauge network meets the current actual needs and provide a scoring basis for optimizing the rain gauge network.

[0021] Furthermore, the current information volume score of the target site is calculated as follows:

[0022] Preset several data intervals and assign interval numbers to each interval;

[0023] The current rainfall data measured at the target station and several adjacent stations are divided into corresponding intervals, and an array is constructed using the interval numbers;

[0024] Calculate the information entropy of the rainfall interval of the target station;

[0025] 1 is subtracted, and the absolute value of the difference between the information entropy of the target station's rainfall interval and the preset standard information entropy is divided by the quotient of the preset standard information entropy, and then multiplied by 100 to calculate the current information score.

[0026] The advantage of this embodiment is that the rainfall measured by a reasonably designed rain gauge should have a reasonable information entropy; if the information entropy is too high, it means that the information measured by the target station and the adjacent stations is highly disordered, and the accuracy is difficult to guarantee when the interpolation method is used later; if the information entropy is too low, it means that the similarity between the information measured by the target station and the adjacent stations is too high, the information value is low, and the information cost is increased; therefore, by presetting the standard information entropy, it is possible to evaluate whether the information measured by the target station is reasonable. The higher the information score, the more valuable the rainfall measured at the target station location.

[0027] Furthermore, the time-varying score of the target site is calculated as follows:

[0028] Obtain the information score of several consecutive rainfall events at the target site;

[0029] Calculate the standard deviation of the array composed of several rainfall information scores;

[0030] 1 minus the standard deviation divided by the preset maximum standard deviation, and then multiplied by 100 to calculate the time-varying score of the current target site.

[0031] The advantage of this embodiment is that as the climate changes, the information value of the rainfall measured at the same target site will also change. In particular, for target sites that need to be deployed locally for a long time, the value of their long-term deployment needs to be quantified. The higher the time-varying score of the target site, the smaller the deviation of the information value of the target site.

[0032] Furthermore, the coverage area score of the target site is calculated as follows:

[0033] Estimate the area of ​​adjacent space based on estimated rainfall data calculated by remote sensing satellites;

[0034] The number of target sites and several adjacent sites is divided by the area of ​​the adjacent space to calculate the current number of sites per unit area.

[0035] The coverage area score of the target site is calculated by dividing the current number of sites per unit area by the preset maximum number of sites per unit area and multiplying the result by 100.

[0036] The advantage of this embodiment is that the coverage area score can evaluate the cost-effectiveness of the target site setting. The larger the coverage area, the lower the setting cost, which can balance the cost increase caused by the information volume score.

[0037] Furthermore, the current information score, time-varying score, and coverage score are weighted. The specific method is as follows:

[0038] The product of the current first weight and the current information score, plus the product of the current second weight and the time-varying score, plus the product of the current third weight and the coverage area score.

[0039] Furthermore, the current first weight, the current second weight, and the current third weight are calculated as follows:

[0040] Initialize the first weight, the second weight, and the third weight;

[0041] Calculate the difference between the information entropy score of the target site and the average information entropy score of the adjacent sites. When the absolute value of the difference increases, reduce the historical first weight, otherwise increase the historical first weight.

[0042] Obtain the optimization adjustment plan of the rainfall station network. When the optimization adjustment plan period exceeds the average period, the historical second weight is increased, otherwise it is reduced.

[0043] Obtain the construction budget of the rain gauge station. If the construction budget exceeds the historical average cost, the historical third weight will be reduced, otherwise it will be increased.

[0044] The normalized and corrected historical first weight, historical second weight and historical third weight are used to calculate the current first weight, current second weight and current third weight.

[0045] The advantage of this embodiment is that it provides a way to fuse decisions through weights and provides a method for quantitatively adjusting weight settings for different objectives, making the fusion evaluation truly executable and applicable to the evaluation of any rain gauge.

[0046] The present invention also discloses a storage medium storing a plurality of instructions, and a processor loads the instructions to execute the above-mentioned rainfall station spatial distribution assessment method.

[0047] Similarly, the present invention also discloses a storage medium, wherein the storage medium stores a plurality of instructions, wherein the instructions are suitable for loading by a processor, using the above method.

[0048] Other advantages, objects, and features of the present invention will be described in part in the following description and, in part, will be apparent to those skilled in the art upon examination of the following description or may be learned from practice of the present invention. The objects and other advantages of the present invention may be realized and obtained through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The accompanying drawings of the present invention are described below.

[0050] Figure 1 It is a schematic diagram of the overall process of the present invention. DETAILED DESCRIPTION

[0051] The present invention will be further described below with reference to the accompanying drawings and examples.

[0052] A method for evaluating the spatial distribution of rainfall stations, such as Figure 1 The specific steps are as follows:

[0053] S1. Calculate the current information volume score of the target site. The specific steps are as follows:

[0054] S11. Obtain current rainfall data for the target site and current rainfall data measured at several adjacent stations In this embodiment, the number of adjacent sites is 8, and k is the number of the current rainfall data.

[0055] S12, preset several data intervals th1, th2, ..., th l , th l For the lth data interval point, each interval is numbered th 1,2 ,th 2,3 ,th l-1,l .

[0056] S13. By comparing the numerical values ​​of the site rainfall and the interval, the current rainfall data measured at the target site and several adjacent sites are divided into corresponding intervals, and an array {IN1, IN2, IN3, ..., IN9} is constructed with the interval number, where IN1 is the data interval interval where the rainfall data of the target site is located, and IN2 to IN9 are the data interval intervals where the rainfall data of the eight adjacent sites are located.

[0057] S14. Calculate the information entropy of the rainfall interval at the target station using the following formula:

[0058]

[0059] S15, 1 minus, the information entropy of the target station rainfall interval minus the preset standard information entropy H standard The absolute value of the difference is divided by the quotient of the preset standard information entropy, and then multiplied by 100 to calculate the current information score. The calculation formula is as follows:

[0060]

[0061] S2. Calculate the time-varying score of the target site. The specific steps are as follows:

[0062] S21, obtain the information score of several consecutive rainfall events at the target site {score1, score2, ..., score k};

[0063] S22. Calculate the standard deviation of the array composed of several rainfall information scores. The specific formula is as follows:

[0064]

[0065] Where, The average of the ratings array.

[0066] S23, 1 minus the standard deviation divided by the preset maximum standard deviation, and then multiplied by 100 to calculate the time-varying score of the current target site. The calculation formula is as follows:

[0067]

[0068] Where s max is the preset maximum standard deviation.

[0069] S3. Calculate the coverage area score of the target site. The specific steps are as follows:

[0070] S31. Estimate the area of ​​the adjacent space based on the estimated rainfall data calculated by remote sensing satellites.

[0071] S32. Divide the number of target sites and several adjacent sites by the area of ​​the adjacent space to calculate the current number of sites per unit area, that is,

[0072] S33. Divide the current number of sites per unit area by the preset maximum number of sites per unit area, and multiply by 100 to calculate the coverage area score of the target site. The calculation formula is as follows:

[0073]

[0074] Where, d max The preset maximum number of sites per unit area.

[0075] S4. Calculate the weight. The specific steps are as follows:

[0076] S41, initializing a first weight w1, a second weight w2, and a third weight w3;

[0077] S42. Calculate the difference between the information entropy score of the target site and the average information entropy score of the adjacent sites. When the absolute value of the difference increases, reduce the historical first weight, otherwise increase the historical first weight:

[0078] When it increases, it means that the amount of rainfall information measured at the target station is too much or too little compared to the adjacent stations, which reduces or increases w1, thereby reducing the comprehensive score. The specific reduction value can be adjusted and set manually.

[0079] S43, obtaining an optimization adjustment plan for the rainfall station network, and when the optimization adjustment plan period exceeds the average period, the historical second weight is increased, otherwise the historical second weight is decreased;

[0080] In this embodiment, the longer the adjustment period is, the higher the requirement on the time-varying stability of the site is, and the corresponding weight should be increased.

[0081] S44. Obtain the construction budget of the rain gauge station. If the construction budget exceeds the historical average cost, the historical third weight is reduced; otherwise, the historical third weight is increased.

[0082] S45. The normalized and corrected historical first weight, historical second weight, and historical third weight are used to calculate the current first weight, current second weight, and current third weight.

[0083] S5. Calculate the comprehensive score of the target site. The specific formula is as follows:

[0084] scorec=w1.scorein+w2.scoret+w3.scored

[0085] S6. Optimize the rainfall station network. The specific steps are as follows:

[0086] S61, using the spatial coordinate distribution of the current rainfall station in the rainfall station network as the initialization population;

[0087] S62, calculating the comprehensive score of the initialized population;

[0088] S63. Select, cross, and mutate the population to generate several new spatial distributions of rainfall stations;

[0089] S64. Calculate the comprehensive score sum of the spatial distribution of the new rainfall stations to form a progeny population;

[0090] S65, merge the parent and offspring populations to select the next generation input population;

[0091] S66, repeat the selection, crossover, mutation, calculation and screening operations until the convergence condition is met;

[0092] S67. The spatial distribution of several new rain gauges at the final convergence is used as the optimization result of the rain gauge network.

[0093] 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 it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. A method for evaluating the spatial distribution of rainfall stations, characterized in that: The specific method is as follows: Obtain the current rainfall data measured at the target site and several adjacent sites, and calculate the current information score of the target site using the information entropy of the target site; Retrieve the historical information volume score of the target site, and calculate the time-varying score of the target site based on the current information volume score of the target site and the change in the historical information volume score; Obtain estimated rainfall data calculated by remote sensing satellites, circle adjacent spaces whose estimated rainfall data differ from the target site by a first preset value, and calculate the coverage area score of the target site based on the area of ​​the adjacent spaces and the location distribution of the target site in the adjacent spaces; The current information score, time-varying score, and coverage score are weighted to calculate the comprehensive score of the target site; Calculate the current information volume score of the target site as follows: Preset several data intervals and assign interval numbers to each interval; The current rainfall data measured at the target station and several adjacent stations are divided into corresponding intervals, and an array is constructed using the interval numbers; Calculate the information entropy of the rainfall interval of the target station; The current information score is calculated by subtracting the absolute value of the difference between the information entropy of the target station's rainfall interval and the preset standard information entropy, divided by the quotient of the preset standard information entropy, 1 minus the above quotient, and multiplying it by 100; Calculate the time-varying score of the target site. The specific method is as follows: Obtain the information score of several consecutive rainfall events at the target site; Calculate the standard deviation of the array composed of several rainfall information scores; The standard deviation is divided by the preset maximum standard deviation, the quotient is subtracted from 1, and the result is multiplied by 100 to calculate the time-varying score of the current target site.

2. The method for evaluating the spatial distribution of rainfall stations according to claim 1, wherein: When the combined scores of several rain gauges in a region are lower than the warning value, regional optimization of the rain gauge network is initiated. The specific method is as follows: Taking the comprehensive score as the optimization goal, the optimization algorithm is used to adjust the position of each rain gauge in the rain gauge network so that the sum of the comprehensive scores of each rain gauge in the rain gauge network is maximized.

3. The method for evaluating the spatial distribution of rainfall stations according to claim 2, wherein: The optimization algorithm is a genetic algorithm, and the specific method is as follows: The spatial coordinate distribution of the current rainfall stations in the rainfall station network is used as the initial population; Calculate the comprehensive score and of the initialized population; The population is selected, crossed, and mutated to generate several new spatial distributions of rainfall stations; Calculate the comprehensive score sum of the new rainfall station spatial distribution to form the offspring population; Merge the parent and offspring populations to select the next generation input population; Repeat the selection, crossover, mutation, calculation and screening operations until the convergence conditions are met; The spatial distribution of several new rain gauges at the final convergence is taken as the optimization result of the rain gauge network.

4. The method for evaluating the spatial distribution of rainfall stations according to claim 1, wherein: Calculate the coverage area score of the target site as follows: Estimate the area of ​​adjacent space based on estimated rainfall data calculated by remote sensing satellites; The number of target sites and several adjacent sites is divided by the area of ​​the adjacent space to calculate the current number of sites per unit area. The coverage area score of the target site is calculated by dividing the current number of sites per unit area by the preset maximum number of sites per unit area and multiplying the result by 100.

5. The method for evaluating the spatial distribution of rainfall stations according to claim 4, wherein: The weighted current information score, time-varying score, and coverage score are as follows: The product of the current first weight and the current information score, plus the product of the current second weight and the time-varying score, plus the product of the current third weight and the coverage area score.

6. The method for evaluating the spatial distribution of rainfall stations according to claim 5, wherein: The current first weight, current second weight, and current third weight are calculated as follows: Initialize the first weight, the second weight, and the third weight; Calculate the difference between the information entropy score of the target site and the average information entropy score of the adjacent sites. When the absolute value of the difference increases, reduce the historical first weight, otherwise increase the historical first weight. Obtain the optimization adjustment plan of the rainfall station network. When the optimization adjustment plan period exceeds the average period, the historical second weight is increased, otherwise it is reduced. Obtain the construction budget of the rain gauge station. If the construction budget exceeds the historical average cost, the historical third weight will be reduced, otherwise it will be increased. The normalized and corrected historical first weight, historical second weight and historical third weight are used to calculate the current first weight, current second weight and current third weight.

7. A storage medium, characterized in that: A plurality of instructions are stored, and a processor loads the instructions to execute the method for evaluating the spatial distribution of rainfall stations according to any one of claims 1 to 6.

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