CN110991702B - Method and device for calculating rainfall in mountainous area, computer equipment and storage medium - Google Patents
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Abstract
The application relates to a method and a device for calculating rainfall in a mountainous area, computer equipment and a storage medium, in particular to a method and a device for calculating the average monthly rainfall of each sub-target area in a preset time period, and determining a basic weight value of each rainfall data in a plurality of rainfall data in the sub-target area by utilizing a plurality of rainfall data, an altitude value and environmental data of the sub-target area in the target area; and then, calculating to obtain a target daily precipitation of the target area in the preset time period by using a plurality of precipitation data of the average monthly precipitation of each sub-target area in the preset time period and the basic weight value of each precipitation data, namely, increasing the weight occupied by the precipitation data with higher accuracy, reducing the weight occupied by the precipitation data with lower accuracy, and calculating the plurality of precipitation data based on the respective basic weight values to obtain the target daily precipitation with higher accuracy, thereby solving the problem of lower accuracy of the calculated precipitation in the mountainous area.
Description
Technical Field
The application relates to the technical field of hydrology, water resources and the like, in particular to a method and a device for calculating the rainfall in a mountainous area, computer equipment and a storage medium.
Background
Precipitation is one of the most important components of the water and energy cycle, and quantitative assessment of precipitation per area is crucial for many aspects of scientific and business applications.
At present, the method for determining the precipitation in a certain area mainly comprises the steps of ground station observation, ground radar observation, satellite observation and atmospheric reanalysis model to obtain precipitation data. However, when determining the rainfall amount in the mountainous area, the ground station observation is limited by station distribution (that is, the station distribution is less), and the acquired station data is less, so that the accuracy of the calculated rainfall amount is lower; the coverage range observed by the ground radar is limited to developed regions, and radar data in mountainous regions are less, because the calculated precipitation error is larger; satellite observation is easily affected by errors of an observation system (namely, the sensitivity to a slight rainfall event is low), so that the calculated rainfall error is large; atmospheric re-analysis models are well suited to simulate large scale weather system variations, but because of their relatively low resolution and inadequate sub-grid process parameterization, it is difficult to represent convection-related variations.
Therefore, how to improve the calculation accuracy of the rainfall amount in the mountainous area becomes a problem to be solved urgently.
Disclosure of Invention
In view of the above, it is desirable to provide a method, an apparatus, a computer device, and a storage medium for calculating the amount of rainfall in the mountainous area, which can improve the accuracy of calculating the amount of rainfall in the mountainous area.
A method for calculating precipitation in mountainous areas, the method comprising:
acquiring the average monthly rainfall of each sub-target area in the target area within a preset time period;
for each sub-target area in which the sites do not exist in the target area, determining a basic weight value of each precipitation data in the plurality of precipitation data in the sub-target area based on the plurality of precipitation data, the altitude value and the environmental data of the sub-target area;
and calculating the target daily precipitation of the target area within a preset time period by using the average monthly precipitation of each sub-target area, the plurality of precipitation data and the basic weight value of each precipitation data.
In one embodiment, if the sub-target region falls into an intra-region;
the acquiring the average monthly rainfall of each sub-target area in the target area in a preset time period comprises the following steps:
acquiring all the domestic daily precipitation of each sub-target area in the preset time period;
and calculating the average monthly rainfall of each sub-target area in a preset time period by using all the domestic daily rainfall.
In one embodiment, if the sub-target area falls into an overseas area;
when the altitude value of the sub-target area is greater than a preset threshold, the obtaining of the average monthly rainfall of each sub-target area in the target area within a preset time period includes:
acquiring all the domestic daily precipitation of each sub-target area in the preset time period;
and calculating the average monthly rainfall of each sub-target area in a preset time period by using all the domestic daily rainfall.
In one embodiment, when the altitude value of the sub-target area is less than or equal to a preset threshold, acquiring an average monthly rainfall of each of the sub-target areas in the target area within a preset time period includes:
acquiring all domestic daily precipitation and all overseas daily precipitation of each sub-target area within the preset time period;
and calculating the average monthly rainfall of each sub-target area in a preset time period by using all the domestic daily rainfall and all the overseas daily rainfall.
In one embodiment, the environmental data of the sub-target area includes the near-ground air pressure value, the near-ground air temperature and the near-ground wind speed value of the sub-target area;
the determining a basic weight value of each precipitation data in the plurality of precipitation data in the sub-target area based on the plurality of precipitation data, the altitude value and the environmental data of the sub-target area comprises:
inputting the plurality of precipitation data, the altitude value, the near-ground air pressure value, the near-ground air temperature and the near-ground wind speed value of the sub-target area into a pre-trained weight model to obtain a basic weight value of each precipitation data in the plurality of precipitation data in the sub-target area.
In one embodiment, for each sub-target area in which a site exists in the target area, calculating a correlation coefficient between each precipitation data in a plurality of precipitation data of the sub-target area and the site data;
taking the square value of the correlation coefficient as the basic weight value of the precipitation data of the sub-target area;
and the site data is the monthly rainfall of the sub-target area collected by the site.
In one embodiment, the calculating, by using the average monthly precipitation amount of each sub-target area, the plurality of precipitation data, and a basic weight value of each precipitation data, a target daily precipitation amount of the target area within a preset time period includes:
aiming at the basic weight value of each precipitation data in each sub-target area, taking the precipitation data as a dividend, taking the sum of the basic weight values of all the precipitation data in the sub-target area as a divisor, and taking the quotient value obtained by calculation as the relative weight value of the precipitation data;
and calculating the target daily precipitation of the target area within a preset time period by using the average monthly precipitation of each sub-target area, the plurality of precipitation data and the relative weight value of each precipitation data.
In one embodiment, the calculating, by using the average monthly precipitation amount of each sub-target area, the plurality of precipitation data, and the relative weight value of each precipitation data, a target daily precipitation amount of the target area within a preset time period includes:
calculating the target daily precipitation of the target area in a preset time period according to the following formula:
wherein, PrA target daily precipitation representing the target area; pyRepresenting the average monthly precipitation; dyRepresents the number of days encompassed in the month; piRepresenting one of the plurality of precipitation data; wiA relative weight value representing the precipitation data; n represents the total number of the plurality of precipitation data.
A device for calculating precipitation in mountainous areas, the device comprising:
the acquisition module is used for acquiring the average monthly rainfall of each sub-target area in the target area within a preset time period;
a determining module, configured to determine, for each sub-target area in which a site does not exist in the target area, a basic weight value of each of a plurality of precipitation data in the sub-target area based on the plurality of precipitation data, the altitude value, and the environmental data of the sub-target area;
and the calculation module is used for calculating the target daily precipitation of the target area within a preset time period by using the average monthly precipitation of each sub-target area, the plurality of precipitation data and the basic weight value of each precipitation data.
A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the following steps when executing the computer program:
acquiring the average monthly rainfall of each sub-target area in the target area within a preset time period;
for each sub-target area in which the sites do not exist in the target area, determining a basic weight value of each precipitation data in the plurality of precipitation data in the sub-target area based on the plurality of precipitation data, the altitude value and the environmental data of the sub-target area;
and calculating the target daily precipitation of the target area within a preset time period by using the average monthly precipitation of each sub-target area, the plurality of precipitation data and the basic weight value of each precipitation data.
A computer-readable storage medium, on which a computer program is stored which, when executed by a processor, carries out the steps of:
acquiring the average monthly rainfall of each sub-target area in the target area within a preset time period;
for each sub-target area in which the sites do not exist in the target area, determining a basic weight value of each precipitation data in the plurality of precipitation data in the sub-target area based on the plurality of precipitation data, the altitude value and the environmental data of the sub-target area;
and calculating the target daily precipitation of the target area within a preset time period by using the average monthly precipitation of each sub-target area, the plurality of precipitation data and the basic weight value of each precipitation data.
The method, the device, the computer equipment and the storage medium for calculating the rainfall in the mountainous area specifically acquire the average monthly rainfall of each sub-target area in the target area within a preset time period in advance; determining a basic weight value of each precipitation data in the plurality of precipitation data in the sub-target area by utilizing the plurality of precipitation data, the altitude value and the environmental data of the sub-target area in the target area; after the basic weight value of each precipitation data of each sub-target area is obtained, the target daily precipitation of the target area in the preset time period is calculated by using a plurality of precipitation data of the average monthly precipitation of each sub-target area in the preset time period and the basic weight value of each precipitation data, namely, the weight occupied by the precipitation data with higher accuracy is increased, the weight occupied by the precipitation data with lower accuracy is reduced, and the precipitation data are calculated based on the respective basic weight values, so that the target daily precipitation with higher accuracy is obtained, and the problem of lower accuracy of the calculated precipitation in the mountainous area is solved.
Drawings
FIG. 1 is a diagram of an exemplary embodiment of a method for calculating precipitation;
FIG. 2 is a schematic flow chart illustrating a method for calculating the precipitation amount according to an embodiment;
FIG. 3 is a flowchart illustrating the step of obtaining the average monthly rainfall for each sub-target area in the target area within a preset time period in one embodiment;
FIG. 4 is a schematic flowchart of the step of obtaining the average monthly rainfall of each sub-target area in the target area within a preset time period in another embodiment;
FIG. 5 is a flowchart illustrating the step of obtaining the average monthly rainfall for each sub-target area in the target area within a preset time period in one embodiment;
FIG. 6 is a schematic structural diagram illustrating a method for calculating the precipitation amount according to an embodiment;
FIG. 7 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The method for calculating the rainfall in the mountainous area can be applied to the application environment shown in fig. 1. Wherein the terminal 102 communicates with the server 104 via a network. The terminal 102 may be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, and portable wearable devices, and the server 104 may be implemented by an independent server or a server cluster formed by a plurality of servers.
In one embodiment, as shown in fig. 2, a method for calculating the rainfall in the mountainous area is provided, which is described by taking the method as an example applied to the terminal in fig. 1, and includes the following steps:
step 201, obtaining the average monthly precipitation of each sub-target area in the target area in a preset time period.
In the specific implementation, the target area is a mountain area to be measured for precipitation. Considering that the area of the mountain area is large, the target area may be divided into a plurality of sub-target areas, for example, the target area may be divided according to a spatial resolution of 0.1 °, so as to obtain N × M area grids, where each grid corresponds to one sub-target area; the target area may also be divided according to the number of sites set in the target area, that is, the target area is divided into sub-target areas with the number of sites on average, and the like, which is not specifically limited in this embodiment of the present application.
After the rainfall of each sub-target area in the target area is obtained by ground radar observation and satellite observation, the average daily rainfall, the average monthly rainfall, the average annual rainfall and the like of each sub-target area and the target area in any time period can be calculated regularly or in real time and stored. Because the radar data processing steps are complicated, the coverage area in the mountainous area is limited, preferably, the average monthly rainfall of each sub-target area obtained by satellite observation in the preset time period can be acquired in real time according to the preset time period. It should be noted that, in a specific application, if necessary, the average monthly precipitation of each sub-target area obtained from the ground radar observation and the satellite observation in a preset time period can also be obtained simultaneously.
Step 202, for each sub-target area in which no site exists in the target area, determining a basic weight value of each precipitation data in the plurality of precipitation data in the sub-target area based on the plurality of precipitation data, the altitude value and the environmental data of the sub-target area.
In a specific implementation, there are fewer sites set in the mountainous area, and therefore, there may be sites in the sub-target areas in the target area, and there may be no sites.
Acquiring data of each sub-target area, which is obtained by ground radar observation and satellite observation, of the sub-target area aiming at each sub-target area without sites in the target area, namely a plurality of precipitation data of the sub-target area (the satellite observation can be performed by a plurality of different satellites at the same time), wherein each precipitation data is recorded and stored in a unit of day; acquiring elevation data of a sub-target area acquired by a spacecraft Radar terrain mapping Mission (SRTM), namely an altitude value of the sub-target area; and acquiring the environmental data including the sub-target areas in the global re-analysis data, wherein the value indicates that the spatial resolution of the re-analysis data is 0.75 degrees, and in order to ensure the calculation accuracy of the precipitation of the target area, the re-analysis data with the spatial resolution of 0.1 degrees is obtained by the nearest neighbor interpolation method. Similarly, a plurality of precipitation data of the sub-target area can be adjusted by a nearest neighbor interpolation method; wherein the elevation value is obtained by using a bilinear interpolation method.
After acquiring the plurality of precipitation data, the altitude value and the environmental data of the sub-target area, determining a basic weight value of each of the plurality of precipitation data in the sub-target area based on the plurality of precipitation data, the altitude value and the environmental data of the sub-target area. The environmental data of each sub-target area comprises the near-ground air pressure value, the near-ground air temperature and the near-ground wind speed value of the sub-target area.
The accuracy of each precipitation data is different, and therefore, the basic weight value of each precipitation data needs to be calculated to determine the weight occupied by the precipitation data in subsequent calculation, so that the calculation accuracy of the precipitation amount of the target area is improved. The values are explained in that since the accuracy of each precipitation data in different areas and different time periods is different, the weight values of the precipitation data corresponding to each sub-target area and each time period need to be calculated respectively to ensure the calculation accuracy of the precipitation amount of the target area.
And step 203, calculating the target daily precipitation of the target area in the preset time period by using the average monthly precipitation of each sub-target area, a plurality of precipitation data and the basic weight value of each precipitation data.
In a specific implementation, a plurality of precipitation data of each sub-target area, the average monthly precipitation of each sub-target area obtained in step 201, and the basic weight value of each precipitation data obtained in step 202 are used to perform specific calculation, so as to obtain a target daily precipitation of a target area within a preset time period.
Specifically, when calculating the target daily precipitation amount of a target area within a preset time period, firstly, regarding the basic weight value of each precipitation data of each sub-target area, taking the precipitation data as a dividend, taking the sum of the basic weight values of all the precipitation data of the sub-target areas as a divisor, and taking the calculated quotient as the relative weight value of the precipitation data; the range of the relative weight value of each precipitation data is greater than 0 and less than 1, and the sum of the relative weight values of all the precipitation data in the sub-target area is 1.
After the relative weight value of all precipitation data of each sub-target area in the target area is determined, calculating the target daily precipitation of the target area in a preset time period by using the average monthly precipitation of each sub-target area, a plurality of precipitation data and the relative weight value of each precipitation data, specifically calculating according to the following formula 1 to obtain the target daily precipitation of the target area in the preset time period:
wherein, PrA target daily precipitation amount representing a target area; pyRepresents the average monthly precipitation; dyRepresents the number of days encompassed in the month; piRepresenting one of a plurality of precipitation data; wiA relative weight value representing precipitation data; n represents the total number of the plurality of precipitation data.
When the preset time period comprises a single month, e.g. the preset time period is 3 months, DyThe value in the above formula is 31; when the preset time period includes a plurality of months, the calculation can be performed according to the following two calculation modes: the first calculation method, if the preset time period is 3-4 months, can perform calculation for 3 months and 4 months respectively, that is, when calculating the target daily precipitation of 3 months, DyWhen the value in the above formula is 31 and the target daily precipitation of 4 months is calculated, DyThe value in the above equation is 30.
Similarly, according to the above calculation method, the target-time precipitation amount of the target area in the preset time period, that is, the precipitation amount of the target area in each hour in the preset time period, may be further calculated, specifically according to formula 2, to obtain the target-time precipitation amount of the target area in the preset time period:
wherein, PzA target-time precipitation amount representing a target area; dyRepresents the number of days encompassed in the month; prA target daily precipitation amount representing a target area; pyRepresents the average monthly precipitation; piRepresenting one of a plurality of precipitation data; wiRelative weight values representing precipitation data(ii) a n represents the total number of the plurality of precipitation data.
Similarly, the precipitation amount per 2 hours, the precipitation amount per 3 hours, and the like of the target region can be calculated by equation 2. It should be noted that, when the formula is used to calculate the precipitation amount in any time period, the precipitation data used by the formula have the same or corresponding time resolution to ensure the accuracy of the calculation result.
According to the embodiment of the application, a basic weight value of each precipitation data in a plurality of precipitation data in a sub-target area in the target area is determined by utilizing a plurality of precipitation data, altitude values and environment data of the sub-target area, and the basic weight value of each precipitation data is converted into a relative weight value; after the relative weight value of each precipitation data of each sub-target area is obtained, the target daily precipitation of the target area in the preset time period is calculated by utilizing a plurality of average monthly precipitation data of each sub-target area in the preset time period and the relative weight value of each precipitation data, namely, the weight occupied by the precipitation data with higher accuracy is increased, the weight occupied by the precipitation data with lower accuracy is reduced, and the precipitation data are calculated based on the respective relative weight values, so that the target daily precipitation with higher accuracy is obtained, and the problem of lower accuracy of the calculated precipitation in the mountainous area is solved.
At present, daily rainfall in the same region is collected both in the interior and in the abroad, and the daily rainfall in the interior (that is, the rainfall data collected by the set site) collected in the interior and the daily rainfall in the overseas collected in the overseas have a certain difference, so that if the target region covers the interior region and the overseas region, the average monthly rainfall in the covered interior region and the average monthly rainfall in the covered overseas region are calculated respectively. In addition, because the elevation values of the mountainous area are different, the indoor daily precipitation and the outdoor daily precipitation of the target area at the same elevation value are different.
Specifically, after the target area is divided into a plurality of sub-target areas, the plurality of sub-target areas may be calculated respectively. When performing the specific calculation, the calculation can be performed according to the following three cases:
in the first case: if the sub-target area falls into the internal area, calculating the average monthly rainfall according to the method shown in FIG. 3, which comprises the following steps:
step 301, acquiring all domestic daily precipitation of each sub-target area within a preset time period;
step 302, calculating the average monthly rainfall of each sub-target area in a preset time period by using all the daily rainfall in the environment.
In specific implementation, the accuracy of the indoor daily precipitation is higher than that of the overseas daily precipitation in the daily precipitation collected for the indoor areas, so that when the sub-target areas fall into the indoor areas, all the indoor daily precipitation of each sub-target area in a preset time period is directly obtained; then, the average monthly rainfall of each sub-target area in the preset time period is calculated according to the specific time point of the preset time period.
For example, if the preset time period is from 2019 year 1 month No. 1 to 2019 year 1 month No. 31, the daily rainfall amounts in the domestic environment of the sub-target areas which fall into the domestic environment and are collected from 2019 year 1 month No. 1 to 2019 year 1 month No. 31 are summed to obtain the monthly rainfall amounts from 2019 year 1 month No. 1 to 2019 year 1 month No. 31 (the preset time period), and the monthly rainfall amount can be directly used as the average monthly rainfall amount; the average value of the monthly rainfall amounts of all 1 months in 2015-2019 can be further used to calculate an average value, and the average value is used as the average monthly rainfall amount.
In the second case: if the sub-target area falls into the overseas area and the altitude value of the sub-target area is greater than the preset threshold, calculating the average monthly rainfall according to the method shown in fig. 4, and specifically comprising the following steps:
step 401, acquiring all domestic daily precipitation of each sub-target area within a preset time period;
and step 402, calculating the average monthly rainfall of each sub-target area in a preset time period by using all the domestic daily rainfall.
Here, the daily domestic precipitation and the daily overseas precipitation may be compared based on the altitude value to determine a preset threshold, which is a critical value, i.e., the daily overseas precipitation is generally overestimated when the altitude value is greater than the preset threshold, and the daily overseas precipitation is generally underestimated when the altitude value is less than or equal to the preset threshold. Therefore, when the sub-target areas fall into the overseas area and the altitude value of the sub-target areas is greater than the preset threshold, the average monthly rainfall of each sub-target area in the preset time period can be calculated by referring to the calculation method in the first case; the average monthly rainfall of each sub-target area in the preset time period can also be calculated by referring to the calculation method of the third case described below.
In the third case: if the sub-target area falls into the overseas area and the altitude value of the sub-target area is less than or equal to the preset threshold, calculating the average monthly rainfall according to the method shown in fig. 5, and the specific steps are as follows:
step 501, acquiring all domestic daily precipitation and all overseas daily precipitation of each sub-target area within a preset time period;
and 502, calculating the average monthly rainfall of each sub-target area in a preset time period by using all the domestic daily rainfall and all the overseas daily rainfall.
Here, when the altitude value is less than or equal to the preset threshold value, the overseas daily precipitation is an underestimated value compared to the actual daily precipitation, and therefore, the overseas daily precipitation needs to be corrected using the domestic daily precipitation.
Specifically, for the domestic daily precipitation and the overseas daily precipitation on the same day, the domestic daily precipitation is used as a dividend, the overseas daily precipitation is used as a divisor, a quotient obtained by division calculation is multiplied by the overseas daily precipitation, and the obtained product is used as the corrected overseas daily precipitation.
And performing the correction calculation on each day in a preset time period, and calculating the average monthly rainfall of each sub-target area by using all corrected overseas daily rainfall. For example, daily precipitation per day in five years is calculated, a summation algorithm is used to obtain a monthly precipitation per month in five years, and for an average monthly precipitation of 12 months, 5 monthly precipitations of 12 months included in five years are averaged to obtain an average monthly precipitation of 12 months in five years. The average monthly precipitation may be calculated for each sub-target area, that is, calculated using one or more precipitation data of each sub-target area.
Considering that a plurality of precipitation data in each sub-target area of the target area, in which the sites do not exist, are not collected by the sites, each precipitation data has a certain error. Therefore, in a specific implementation, a weight model to be trained is trained in advance by using a plurality of precipitation data samples of each of a plurality of sample regions falling within the interior, a basic weight value sample (obtained by manual calculation) of each precipitation data sample, an altitude value sample, a near-ground air pressure value sample, a near-ground air temperature sample and a near-ground wind speed value sample of the sample region. Inputting the plurality of precipitation data, the altitude value, the near-ground air pressure value, the near-ground air temperature and the near-ground wind speed value of the sub-target area into a pre-trained weight model to obtain a basic weight value of each precipitation data in the plurality of precipitation data in the sub-target area.
Specifically, a plurality of precipitation data, an altitude value, a near-ground air pressure value, a near-ground air temperature and a near-ground wind speed value of each sample area are respectively preprocessed, then a plurality of precipitation data, an altitude value, a near-ground air pressure value, a near-ground air temperature and a near-ground wind speed value of each sample area are input into a weight model to be trained, an error between an actual result (a weight value output by the weight model to be trained) and a theoretical result (a basic weight value sample of each precipitation data sample) is obtained, and when the error is larger than an allowable error threshold value, parameter adjustment is carried out on the weight model to be trained, and the next round of training is carried out; and stopping training until the error is less than or equal to the allowable error threshold.
Of course, the target area may include a sub-target area of the existing site. Calculating a correlation coefficient of each precipitation data and site data in a plurality of precipitation data of each sub-target area with the site aiming at each sub-target area with the site in the target area; taking the square value of the correlation coefficient as the basic weight value of the precipitation data of the sub-target area; wherein, the site data is the monthly rainfall of the sub-target area collected by the site. It is worth noting that the higher the correlation coefficient of the precipitation data with the site data, the higher the accuracy of the precipitation data.
It should be understood that although the various steps in the flow charts of fig. 2-5 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 2-5 may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternating with other steps or at least some of the sub-steps or stages of other steps.
In one embodiment, as shown in fig. 6, there is provided a device for calculating rainfall in mountainous area, comprising: the device comprises an acquisition module, a determination module and a calculation module, wherein:
an obtaining module 601, configured to obtain an average monthly rainfall of each sub-target area in the target area within a preset time period;
a first determining module 602, configured to determine, for each sub-target area in which a site does not exist in a target area, a basic weight value of each of a plurality of precipitation data in the sub-target area based on a plurality of precipitation data, an altitude value, and environmental data of the sub-target area;
the calculating module 603 is configured to calculate, by using the average monthly precipitation amount of each sub-target area, a plurality of precipitation data, and a basic weight value of each precipitation data, a target daily precipitation amount of the target area within a preset time period.
In one embodiment, if the sub-target region falls within an intra-region; the obtaining module 601, when obtaining the average monthly rainfall of each sub-target area in the target area within a preset time period, includes:
acquiring all domestic daily precipitation of each sub-target area within a preset time period;
and calculating the average monthly rainfall of each sub-target area in a preset time period by using all the domestic daily rainfall.
In another embodiment, if the sub-target area falls into an overseas area; when the altitude value of the sub-target area is greater than the preset threshold, the obtaining module 601, when obtaining the average monthly rainfall of each sub-target area in the target area within the preset time period, includes:
acquiring all domestic daily precipitation of each sub-target area within a preset time period;
and calculating the average monthly rainfall of each sub-target area in a preset time period by using all the domestic daily rainfall.
In another embodiment, when the altitude value of the sub-target area is less than or equal to the preset threshold, the obtaining module 601, when obtaining the average monthly rainfall of each sub-target area in the target area within the preset time period, includes:
acquiring all domestic daily precipitation and all overseas daily precipitation of each sub-target area within a preset time period;
and calculating the average monthly rainfall of each sub-target area in a preset time period by using all the domestic daily rainfall and all the overseas daily rainfall.
In yet another embodiment, the environmental data of the sub-target area includes a near-ground air pressure value, a near-ground air temperature, and a near-ground wind speed value of the sub-target area; the first determining module 602, when determining the basic weight value of each of the plurality of precipitation data in the sub-target area based on the plurality of precipitation data, the altitude value, and the environmental data of the sub-target area, includes:
inputting the plurality of precipitation data, the altitude value, the near-ground air pressure value, the near-ground air temperature and the near-ground wind speed value of the sub-target area into a pre-trained weight model to obtain a basic weight value of each precipitation data in the plurality of precipitation data in the sub-target area.
In another embodiment, the device for calculating the amount of precipitation in the mountainous area further includes a second determining module 604 for determining the amount of precipitation in the mountainous area
Calculating a correlation coefficient of each precipitation data and site data in a plurality of precipitation data of each sub-target area with the site aiming at each sub-target area with the site in the target area;
taking the square value of the correlation coefficient as the basic weight value of the precipitation data of the sub-target area;
wherein, the site data is the monthly rainfall of the sub-target area collected by the site.
In another embodiment, the calculating module 603, when calculating the target daily precipitation of the target area within the preset time period by using the average monthly precipitation of each sub-target area, the plurality of precipitation data and the basic weight value of each precipitation data, includes:
aiming at the basic weight value of each precipitation data in each sub-target area, taking the precipitation data as a dividend, taking the sum of the basic weight values of all the precipitation data in the sub-target area as a divisor, and taking the quotient value obtained by calculation as the relative weight value of the precipitation data;
and calculating the target daily precipitation of the target area in the preset time period by using the average monthly precipitation of each sub-target area, a plurality of precipitation data and the relative weight value of each precipitation data.
In another embodiment, the calculating module 603, when calculating the target daily precipitation of the target area within the preset time period by using the average monthly precipitation of each sub-target area, the plurality of precipitation data and the relative weight value of each precipitation data, includes:
calculating the target daily precipitation of the target area in the preset time period according to the following formula:
wherein, PrA target daily precipitation amount representing a target area; pyRepresents the average monthly precipitation; dyRepresents the number of days encompassed in the month; piRepresenting one of a plurality of precipitation data; wiA relative weight value representing precipitation data; n represents the total number of the plurality of precipitation data.
The specific limitation of the computing device for the rainfall amount in the mountainous area can be referred to the limitation of the computing method for the rainfall amount in the mountainous area, and the detailed description is omitted here. All or part of each module in the computing device for the rainfall in the mountainous area can be realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as shown in fig. 7. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a method of calculating precipitation in mountainous areas. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.
Those skilled in the art will appreciate that the architecture shown in fig. 7 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the following steps when executing the computer program:
acquiring the average monthly rainfall of each sub-target area in the target area within a preset time period;
for each sub-target area in which the site does not exist in the target area, determining a basic weight value of each precipitation data in the plurality of precipitation data in the sub-target area based on the plurality of precipitation data, the altitude value and the environmental data of the sub-target area;
and calculating the target daily precipitation of the target area in the preset time period by using the average monthly precipitation of each sub-target area, a plurality of precipitation data and the basic weight value of each precipitation data.
In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of:
acquiring the average monthly rainfall of each sub-target area in the target area within a preset time period;
for each sub-target area in which the site does not exist in the target area, determining a basic weight value of each precipitation data in the plurality of precipitation data in the sub-target area based on the plurality of precipitation data, the altitude value and the environmental data of the sub-target area;
and calculating the target daily precipitation of the target area in the preset time period by using the average monthly precipitation of each sub-target area, a plurality of precipitation data and the basic weight value of each precipitation data.
In one embodiment, the computer program when executed by the processor further performs the steps of:
if the sub-target area falls into the internal area;
acquiring the average monthly rainfall of each sub-target area in the target area in a preset time period, wherein the average monthly rainfall comprises the following steps:
acquiring all domestic daily precipitation of each sub-target area within a preset time period;
and calculating the average monthly rainfall of each sub-target area in a preset time period by using all the domestic daily rainfall.
In one embodiment, the computer program when executed by the processor further performs the steps of:
if the sub-target area falls into the overseas area;
when the altitude value of the sub-target area is greater than a preset threshold, acquiring the average monthly rainfall of each sub-target area in the target area within a preset time period, wherein the method comprises the following steps:
acquiring all domestic daily precipitation of each sub-target area within a preset time period;
and calculating the average monthly rainfall of each sub-target area in a preset time period by using all the domestic daily rainfall.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
when the altitude value of the sub-target area is less than or equal to a preset threshold, acquiring the average monthly rainfall of each sub-target area in the target area within a preset time period, wherein the method comprises the following steps:
acquiring all domestic daily precipitation and all overseas daily precipitation of each sub-target area within a preset time period;
and calculating the average monthly rainfall of each sub-target area in a preset time period by using all the domestic daily rainfall and all the overseas daily rainfall.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
the environmental data of the sub-target area comprises the near-ground air pressure value, the near-ground air temperature and the near-ground wind speed value of the sub-target area;
determining a basic weight value of each precipitation data in the plurality of precipitation data in the sub-target area based on the plurality of precipitation data, the altitude value and the environmental data of the sub-target area, wherein the basic weight value comprises:
inputting the plurality of precipitation data, the altitude value, the near-ground air pressure value, the near-ground air temperature and the near-ground wind speed value of the sub-target area into a pre-trained weight model to obtain a basic weight value of each precipitation data in the plurality of precipitation data in the sub-target area.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
calculating a correlation coefficient of each precipitation data and site data in a plurality of precipitation data of each sub-target area with the site aiming at each sub-target area with the site in the target area;
taking the square value of the correlation coefficient as the basic weight value of the precipitation data of the sub-target area;
wherein, the site data is the monthly rainfall of the sub-target area collected by the site.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
calculating the target daily precipitation of the target area in a preset time period by using the average monthly precipitation of each sub-target area, a plurality of precipitation data and the basic weight value of each precipitation data, wherein the method comprises the following steps:
aiming at the basic weight value of each precipitation data in each sub-target area, taking the precipitation data as a dividend, taking the sum of the basic weight values of all the precipitation data in the sub-target area as a divisor, and taking the quotient value obtained by calculation as the relative weight value of the precipitation data;
and calculating the target daily precipitation of the target area in the preset time period by using the average monthly precipitation of each sub-target area, a plurality of precipitation data and the relative weight value of each precipitation data.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
calculating the target daily precipitation of the target area in a preset time period by using the average monthly precipitation of each sub-target area, a plurality of precipitation data and the relative weight value of each precipitation data, wherein the method comprises the following steps:
calculating the target daily precipitation of the target area in the preset time period according to the following formula:
wherein, PrA target daily precipitation amount representing a target area; pyRepresents the average monthly precipitation; dyRepresents the number of days encompassed in the month; piRepresenting one of a plurality of precipitation data; wiA relative weight value representing precipitation data; n represents the total number of the plurality of precipitation data.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A method for calculating rainfall in mountainous areas, comprising the following steps:
acquiring the average monthly rainfall of each sub-target area in the target area within a preset time period;
aiming at each sub-target area without sites in the target area, determining a basic weight value of each precipitation data in the sub-target area according to a preset weight model based on a plurality of precipitation data, altitude values and environment data of the sub-target area;
calculating the target daily precipitation of the target area within a preset time period by using the average monthly precipitation of each sub-target area, the plurality of precipitation data and the basic weight value of each precipitation data;
the environmental data of the sub-target area comprises the near-ground air pressure value, the near-ground air temperature and the near-ground wind speed value of the sub-target area;
the determining a basic weight value of each precipitation data in the plurality of precipitation data in the sub-target area according to a preset weight model based on the plurality of precipitation data, the altitude value and the environment data of the sub-target area comprises:
aiming at each sub-target area without sites in the target area, training a weight model to be trained by using a plurality of precipitation data samples of each sample area in the plurality of sample areas, a basic weight value sample, an altitude value sample, a near-ground air pressure value sample, a near-ground air temperature sample and a near-ground wind speed value sample of each precipitation data sample, inputting a plurality of precipitation data, altitude values, near-ground air pressure values, near-ground air temperatures and near-ground wind speed values of the sub-target area into a pre-trained weight model, and obtaining a basic weight value of each precipitation data in a plurality of precipitation data in the sub-target area, wherein the plurality of precipitation data samples are obtained through ground site observation, satellite observation and reanalysis data.
2. The computing method of claim 1, wherein if the sub-target region falls within an intra-region;
the acquiring the average monthly rainfall of each sub-target area in the target area in a preset time period comprises the following steps:
acquiring all the domestic daily precipitation of each sub-target area in the preset time period;
and calculating the average monthly rainfall of each sub-target area in a preset time period by using all the domestic daily rainfall.
3. The computing method of claim 1, wherein if the sub-target region falls into an out-of-bound region;
when the altitude value of the sub-target area is greater than a preset threshold, the obtaining of the average monthly rainfall of each sub-target area in the target area within a preset time period includes:
acquiring all the domestic daily precipitation of each sub-target area in the preset time period;
and calculating the average monthly rainfall of each sub-target area in a preset time period by using all the domestic daily rainfall.
4. The calculation method according to claim 3, wherein when the altitude value of the sub-target areas is less than or equal to a preset threshold, acquiring an average monthly rainfall of each of the sub-target areas in a preset time period comprises:
acquiring all domestic daily precipitation and all overseas daily precipitation of each sub-target area within the preset time period;
and calculating the average monthly rainfall of each sub-target area in a preset time period by using all the domestic daily rainfall and all the overseas daily rainfall.
5. The computing method of claim 1, further comprising:
calculating a correlation coefficient of each precipitation data and site data in a plurality of precipitation data of each sub-target area with the site for each sub-target area with the site in the target area;
taking the square value of the correlation coefficient as the basic weight value of the precipitation data of the sub-target area;
and the site data is the monthly rainfall of the sub-target area collected by the site.
6. The method of claim 5, wherein calculating the target daily precipitation for the target area within a preset time period using the average monthly precipitation for each sub-target area, the plurality of precipitation data, and a base weight value for each precipitation data comprises:
aiming at the basic weight value of each precipitation data in each sub-target area, taking the precipitation data as a dividend, taking the sum of the basic weight values of all the precipitation data in the sub-target area as a divisor, and taking the quotient value obtained by calculation as the relative weight value of the precipitation data;
and calculating the target daily precipitation of the target area within a preset time period by using the average monthly precipitation of each sub-target area, the plurality of precipitation data and the relative weight value of each precipitation data.
7. The method of claim 6, wherein calculating the target daily precipitation for the target area within a preset time period by using the average monthly precipitation for each sub-target area, the plurality of precipitation data, and the relative weight value of each precipitation data comprises:
calculating the target daily precipitation of the target area in a preset time period according to the following formula:
wherein, PrA target daily precipitation representing the target area; pyRepresenting the average monthly precipitation; dyRepresents the number of days encompassed in the month; piRepresenting one of the plurality of precipitation data; wiA relative weight value representing the precipitation data; n represents the total number of the plurality of precipitation data.
8. A device for calculating precipitation in mountainous areas, the device comprising:
the acquisition module is used for acquiring the average monthly rainfall of each sub-target area in the target area within a preset time period;
the determining module is used for determining a basic weight value of each precipitation data in the sub-target area according to a preset weight model based on the precipitation data, the altitude value and the environmental data of the sub-target area for each sub-target area without sites in the target area;
the calculation module is used for calculating the target daily precipitation of the target area within a preset time period by using the average monthly precipitation of each sub-target area, the plurality of precipitation data and the basic weight value of each precipitation data;
the environmental data of the sub-target area comprises the near-ground air pressure value, the near-ground air temperature and the near-ground wind speed value of the sub-target area;
the determining module is specifically configured to utilize, for each sub-target area of the target area where no site exists, a plurality of precipitation data samples for each of a plurality of sample areas, a base weight value sample, an altitude value sample, a near-ground air pressure value sample, a near-ground air temperature sample, and a near-ground wind speed value sample for each of the plurality of sample areas, training the weight model to be trained, inputting a plurality of precipitation data, altitude values, near-ground air pressure values, near-ground air temperatures and near-ground wind speed values of the sub-target area into the pre-trained weight model, obtaining a base weight value of each of the plurality of precipitation data in the sub-target region, wherein the plurality of precipitation data samples are obtained by ground site observation, satellite observation, and re-analysis of the data.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method of any of claims 1 to 7 are implemented when the computer program is executed by the processor.
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 of any one of claims 1 to 7.
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