KR20190052484A - An early warning system and method for agrometeorological disaster - Google Patents

Abstract

The present invention provides an early warning system of agricultural meteorological disasters and a method thereof. The early warning system of agricultural meteorological disasters prevents the occurrence of continuously transmitting the same weather danger information to farmers who took various weather danger countermeasures so that the weather danger and countermeasure information which reflected a weather environment of individual farms and countermeasures of the farmers in real time are provided, by using weather information the weather information observed in individual farms without using the estimated weather information by a small-scale weather model to the farm which is equipped with an automatic weather system (AWS) facility directly observing the weather information of the individual farms.

Description

Technical Field [0001] The present invention relates to an early warning system and an agricultural warning system for agricultural land use,

The present invention judges the risk of a disaster of a crop in a semi-real time reflecting the past and future weather features of the individual farm and the growth characteristics of the crop cultivated on the farm, and measures the disaster risk level to the farmer The present invention relates to an early warning system and method for an agricultural meteorological disaster,

Climate-related disasters have been increasing rapidly due to the recent abnormal weather conditions due to climate change, and thus there is a great difficulty in stable farming activities such as low productivity of crops, supply-demand anxiety, and monetary damage.

At present, the Meteorological Agency is preliminarily detecting meteorological hazards by means of latest observation and forecasting technology, and the municipal government announces meteorological information in space units.

However, these services based on city / county units are disadvantageous in that the weather risks are expressed to the same extent in the same city / village area from the viewpoint of the farmer who is the consumer, and thus they do not disclose specific risks to various farming sites .

Since the given weather hazards do not work equally in all farms, crops, varieties and growing stages in the municipality, the situation of individual farmers (breed, growth stage, management skills, weather conditions, etc.) Sufficient management guidelines are needed, but these are not considered sufficiently in the current system.

Therefore, the RDA has established a preliminary forecasting and delivery service system that can be applied to individual farm units to provide services to the farmers in the 10 districts of the Seomjin River basin. However, The current weather conditions of the individual farms are not sufficiently taken into account, such as the continuous transmission of weather risk information to the farmers who have taken countermeasures against the weather risks.

Therefore, a system for solving such a problem is required.

The present invention is based on the fact that farmers equipped with an Automatic Weather System (AWS) facility that directly observes weather information of individual farms can use weather information observed on individual farms without using weather information estimated by small-scale models , The agricultural weather to prevent the phenomenon that the same weather risk information is continuously transmitted to the farmers who took various weather risk countermeasures so that the meteorological conditions of the individual farms and countermeasures of the farmers are reflected in real time And an object of the present invention is to provide an early warning system and method thereof.

In order to achieve the above object, the present invention provides a climatic diagram generation unit for generating a climatic diagram in accordance with each weather information for each individual farm (parcel) unit; A growth condition estimating unit configured to estimate a growing condition based on a biological seasonal prediction model constructed based on a biological experiment corresponding to the property of a parcel crop cultivated in each individual farm (parcel) unit; A disaster risk index generation unit for extracting a disaster risk index based on a parcel crop based on the weather information extracted from the generated climatic map, combining the vegetation condition and the weather information according to the parcel crop property; A corresponding instruction database unit for inputting a corresponding instruction corresponding to disaster information according to the property of each parcel crop; A disaster special report generation unit for determining the hazard risk of the parcels using the generated disaster risk index and generating the disaster special report; And a disaster notification unit for providing the generated disaster special information and corresponding corresponding instructions to each individual farmhouse; And an agriculture meteorological disaster early warning system.

According to the present invention, the same weather risk information is continuously transmitted to the farmers who have taken various weather risk countermeasures so that the weather conditions of the individual farms and countermeasures of the farmers are reflected in real time It is possible to improve the applicability and reliability of the farm site.

In addition, by applying the weather forecast disaster forecasting and delivery service on an individual farm (parcel) basis, it is possible to remarkably reduce damages caused by personalized disaster of individual farms (parcels).

FIG. 1 and FIG. 2 are schematic views showing the construction of an early warning system for an agricultural weather hazard according to an embodiment of the present invention.
3 and 4 are views for explaining a biological seasonal prediction model according to an embodiment of the present invention.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. Prior to this, terms and words used in the present specification and claims should not be construed as limited to ordinary or dictionary terms, and the inventor should appropriately interpret the concepts of the terms appropriately It should be interpreted in accordance with the meaning and concept consistent with the technical idea of the present invention based on the principle that it can be defined.

In addition, the same or corresponding reference numerals are given to the same or corresponding reference numerals regardless of the reference numerals, and redundant description thereof will be omitted. For convenience of explanation, the size and shape of each constituent member shown in the drawings are exaggerated or reduced .

Therefore, the embodiments described in this specification and the configurations shown in the drawings are merely the most preferred embodiments of the present invention and do not represent all the technical ideas of the present invention. Therefore, It is to be understood that equivalents and modifications are possible.

This invention judges the risk of a disaster of a crop in a semi-real time reflecting characteristics of past and future meteorological features of individual farms and the growth characteristics of crops grown on the farm, The present invention relates to an early warning system and method for an agricultural meteorological disaster,

According to the exemplary early warning system for agricultural weather accidents of the present invention, it is possible to continuously provide the farmers who have taken various countermeasures against meteorological hazards so that the weather conditions of the individual farms and countermeasures of farmers can be provided in real- It is possible to prevent the phenomenon of the same weather risk information from being transmitted, thereby improving the applicability and reliability of the farm site.

FIG. 1 and FIG. 2 are schematic views showing a configuration of an early warning system for agricultural weather hazards according to an embodiment of the present invention, and FIGS. 3 and 4 are views for explaining a growth condition estimating unit according to an embodiment of the present invention .

Hereinafter, an agricultural meteorological disaster early warning system and method according to an embodiment of the present invention will be described in detail with reference to FIGS. 1 to 4. FIG.

1 and 2, an agricultural weather-hazard early warning system 10 according to an embodiment of the present invention includes a climate diagram generation unit 100, a growth condition estimation unit 200, a disaster risk index generation unit 300, a corresponding guidance database unit 400, a disaster notification generating unit 500, and a disaster notifying unit 600.

More specifically, the climate map generator 100 of the present invention can generate a climate map according to individual weather information for each individual farm (parcel) unit.

Here, the term "individual farm (parcel) unit" refers to a cropland of a cadastral map that has the same purpose as the owner and has a continuous ground.

The climatic level generator 100 also includes a farm climate diagram generator (hereinafter referred to as " farm climate generator ") that generates a farm climate map by the weather data collected from the automatic weather observation equipment (AWS) 110).

Here, the weather data may include actual measured values of temperature, humidity, radiation amount, precipitation amount, wind speed, wind direction and soil moisture content, temperature, sunshine hours and wetting duration measured in real time, but the present invention is not limited thereto.

In addition, the climate map generator 100 may be configured to use a small-scale model (scale reduction) that takes into account the terrain conditions corresponding to individual farms (parcels) when the automatic weather observation equipment (AWS) And an electronic climatic diagram generation unit 120 for generating an electronic climatic diagram estimated by the above-described method.

Here, in the generation of the electronic climate, various information of the meteorological station according to the characteristics of the local space such as altitude, terrain, surface covering according to the individual farm (parcel) unit, for example, the middle weather forecast, the neighborhood forecast, the weather forecast, Can be generated in detail.

In particular, weather forecasting can collect data through ASOS (Automatic Synoptic Observation System), AWS (Automatic Weather System), KLAPS (Korea Local Analysis and Prediction System), and satellite / radar.

More specifically, the automatic weather observation equipment of the Meteorological Administration has two types of AWS and ASOS depending on the purpose of installation. The ASOS has the purpose of observing various weather information to improve the accuracy of the forecast, and AWS has a function of temperature, At least the weather element is observed to prevent the disaster.

Here, ASOS is a synoptic meteorological instrument, and KLAPS is a meteorological analysis and prediction system on a local scale, which means weather data, weather forecast data and neighborhood forecast data of 5km grid provided by Korea Meteorological Administration.

On the other hand, the growth condition estimating unit 200 of the present invention can estimate and predict the growth conditions according to the properties of the parcels cultivated in each individual farm (parcel) unit.

More specifically, the growth state can be estimated by a biological seasonal prediction model constructed based on biological experiments corresponding to the properties of the parcels cultivated in each individual farm (parcel) unit.

That is, it is possible to estimate and predict the growth state by the biological seasonal prediction model constructed based on the biological experiment corresponding to each parcel crop property.

In addition, the growth condition estimating unit 200 may further include a parcels database storing the results of the bio-experiments corresponding to the properties of the parcels cultivated in each individual farm (parcel) unit.

Here, the biological experiment is for developing a model for estimating and predicting a biological season, and means a model for estimating and predicting a biological stage, for example, a flowering stage and a mature stage of a greenhouse in detail.

In the above example, a non-crop crop is taken as an example, but the present invention is not limited thereto.

In particular, since the meteorological conditions for determining a meteorological disaster differ depending on the growth period of an organism, the present invention can produce more precise and accurate prediction information by estimating and predicting a biological season.

More specifically, the model estimating and predicting the biological season is a linear or nonlinear model based on the temperature (temperature), the GDD (Growing Degree Days) model as the linear model, the Beta function model as the nonlinear model, the Cilldays Model, and a DVS (development rate) model.

For example, the GDD model selects the base temperature for each crop or variety and sets the GDD criterion that reaches each growth stage based on the field data.

Estimate the growth stage of crops or cultivars according to GDD, which is calculated by integrating daily average temperature [(maximum temperature + minimum temperature) / 2-reference temperature] above the reference temperature.

For example, the growth stage of rice is divided into seedling, transplanting, spinning, spreading, heading, and harvesting. The model for estimating the growth stage of rice is GDD, and the reference temperature is 10 ° C to be.

Rice crops can be divided into early, middle, and middle-breeding depending on the growing season. In this example, breeds belonging to middle-breed are described as an example.

 As shown in Fig. 3, in order to start the elongation period in rice midwifery, the GDD should be above 1,160 DEG C, and the GDD should be above 2,180 DEG C for the harvest to start.

4 is a graph showing the reference temperature for each stage of growth for judging the risk (warning, warning) of cold weather in a meteorological disaster.

Therefore, when the GDD is above 1,160 ℃ based on the past temperature and the future temperature is predicted to be below 17 ℃, information about the cold alarm can be provided to the farm A .

Here, the model for estimating and predicting the biological season is selected by selecting the model with the highest accuracy through testing of various estimation models for each tree, and the same model can be used for various varieties within the tree.

That is, rice varieties can use the GDD model selected as the model with the highest accuracy, but the GDD values at each growth stage are formed differently.

For example, in the GDD model, the reference temperature needs to be selected, and since the temperature at which the growth starts is different for each crop, the results of various prior studies can be examined and used.

Meanwhile, the disaster risk index generation unit 300 of the present invention extracts disaster risk index based on the parcels based on the weather information extracted from the generated climatic map, combining the growth conditions and the weather information according to the parcel property of the parcels .

Here, the disaster risk index means a numerical value of the possibility of damages that may occur depending on the reaction of the items exposed to the dangerous weather.

In particular, long - term meteorological observations of some farms are listed in order of magnitude, which is similar to the normal distribution curve (mean + variance). Overlapping this year 's weather can determine relative risk relative to normal.

That is, as described above, the attributes of the crops being cultivated per individual farm (parcel) units are grasped in advance, and the agricultural meteorological risk index indicating what kind of damages to be caused by the meteorological risks known by the detailed weather information is expressed .

In other words, the actual disaster risk index can be calculated by combining the plant attributes (crop, varieties, growth stage) and meteorological data for each individual farm (parcel) prepared in advance and compared with the baseline risk for normal disasters.

Here, the term "weather hazard" refers to the risk of potential damage to crops due to weather outside the standard deviation of 2 times from the normal average such as low temperature, high temperature, heavy rain, dew, humidity, drying, and strong wind.

The types of disasters may include frost damage, cold weather, high temperature, shortage and lack of sunshine, drought, rainfall, snow, snow, and damage due to strong winds.

That is, the risk of disasters according to each type of disaster can be indexed.

Meanwhile, the corresponding guidance data base unit 400 of the present invention can input corresponding guidance corresponding to the disaster information according to the property of each parcel crop.

That is, by inputting in advance a corresponding instruction corresponding to the disaster information corresponding to the disaster risk index, it can be converted into a database.

In addition, the disaster alert generator 500 of the present invention can determine the risk of disaster of the parcels using the generated disaster risk index, and generate the disaster alert.

In particular, the disaster special report generating unit 500 may be provided to generate different disaster special reports in accordance with each parcel crop property cultivated on an individual farm (parcel) basis.

For example, in an individual farm (parcel) unit, a farm A grows rice and a farm B grows apples, which can produce different disaster specials corresponding to the parcels crop.

Meanwhile, the disaster notification unit 600 of the present invention can provide the generated disaster special information and the corresponding guidance corresponding thereto to each individual farmhouse.

More specifically, the disaster notifying unit 600 receives the disaster information and the corresponding guidance from the individual farmers so that countermeasures are taken in accordance with the corresponding instructions, and when the disaster risk is removed, the measured weather information is reflected in the climate diagram generating unit in real time So as not to provide the same disaster warning and response guidance.

In other words, if countermeasures are taken by disaster information and response guidelines provided by individual farmers, the risk of disasters is eliminated, and the observed weather information is reflected in real time on the climate information generator, The same disaster alert and response guidance provided will not be provided.

In addition, the disaster notification unit may be provided to transmit the disaster special information and the corresponding instructions to the Internet, mobile phone text, the Web, and the application.

Here, the disaster notifying unit may be provided to receive at least one of the disaster notifications and the corresponding instructions in a desired manner among the Internet, mobile phone text, Web, and applications described above at individual farmhouses.

The present invention also provides an early warning method for agricultural weather accidents.

For example, the above-mentioned agricultural weather disaster early warning method relates to an agricultural weather accident early warning method using the above-described agricultural weather accident early warning system. Therefore, the details of the agricultural warning method of early warning of weather accidents to be described later can be applied equally to those described in the agricultural weather accident early warning system.

An exemplary agricultural meteorological disaster early warning method of the present invention includes a climate map generation step of generating a climate map in accordance with each weather information of each individual farm (parcel) unit.

It also includes estimating the growth conditions according to the properties of the parcels cultivated in each individual farm (parcel) unit.

The method also includes extracting a disaster risk index based on the parcel crop, based on the weather information extracted from the generated climatic map, combining the vegetation condition and the weather information according to the parcel crop property.

And inputting a corresponding instruction corresponding to the disaster information according to the property of each parcels to the corresponding instruction database unit.

Also, it includes a step of determining the risk of disaster of the parcels crop by using the generated disaster risk index, and generating the disaster special report.

The method also includes providing the generated disaster specialist and corresponding countermeasure instructions to each individual farmhouse.

In addition, the climatic level generating step includes generating the farm live climate map by the meteorological data collected from the automatic weather observation equipment (AWS), each of which is provided on an individual farm (parcel) unit for measuring the weather information.

In addition, the step of providing the disaster specialist and the corresponding guidance to the individual farmhouse is performed when the disaster specialist and the countermeasure instruction are provided to the individual farmhouse and the countermeasure is taken in accordance with the corresponding guidance, , And the same disaster notification and response guidelines are not provided.

10: Agricultural weather disaster early warning system
100: Climate diagram generator
110: Farm climate formation section
120: Electronic Climate Map Generator
200: Growth condition estimating unit
300: Disaster Risk Index Generator
400: corresponding guidance database part
500: Disaster Annihilation Generator
600: Disaster notification section

Claims (12)

Climate diagrams for creating climate maps according to individual weather information for individual farms (parcels);
A growth condition estimating unit configured to estimate a growing condition based on a biological seasonal prediction model constructed based on a biological experiment corresponding to the property of a parcel crop cultivated in each individual farm (parcel) unit;
A disaster risk index generation unit for extracting a disaster risk index based on a parcel crop based on the weather information extracted from the generated climatic map, combining the vegetation condition and the weather information according to the parcel crop property;
A corresponding instruction database unit for inputting a corresponding instruction corresponding to disaster information according to the property of each parcel crop;
A disaster special report generation unit for determining the hazard risk of the parcels using the generated disaster risk index and generating the disaster special report; And
A disaster notification unit for providing the generated disaster special information and corresponding corresponding instructions to each individual farmhouse; An early warning system for agricultural meteorological disasters. The method according to claim 1,
The climate diagram generating section includes a farm climate diagram generating section for generating a farm live climate map by the weather data collected from the automatic weather observation equipment (AWS) provided for each individual farm (parcel) unit for measuring the weather information Agricultural Meteorological Hazard Early Warning System. 3. The method of claim 2,
Wherein the weather data includes measured values of real-time measured temperature, humidity, radiation amount, precipitation amount, wind speed, wind direction, soil moisture content, geothermal temperature, daylight hours and wetting duration. The method of claim 3,
The Climate Map Generator is responsible for estimating the size of the eclipsed area by using a small scale model (scale reduction method) that takes into account the terrain conditions corresponding to individual farms (parcels) when no automatic weather observation equipment (AWS) And an electronic climatic level generating section for generating a climatic map. The method according to claim 1,
The parcel crop property includes crops, cultivars and growing stages of the crops cultivated by each individual farm (parcel) unit. The method according to claim 1,
Wherein the growth condition estimating unit further includes a parcel crop database storing a biological experiment result corresponding to the property of the parcels cultivated in each individual farm (parcel) unit. 3. The method of claim 2,
The disaster alerting department, when the disaster alert is provided to individual farmers and response measures are taken in accordance with the corresponding guidelines, the observed weather information is reflected in the climate diagram generator in real time, and the same disaster alert and response guidelines An early warning system for agricultural weather disasters that is not provided. The method according to claim 1,
The disaster alert generator is configured to generate different disaster alarms according to the properties of each parcel crop cultivated on an individual farm (parcel) unit. The method according to claim 1,
The disaster alert department is an agriculture weather disaster early warning system that is designed to deliver disaster alert and response instructions to the Internet, mobile phone text, Web, and applications. Climate diagram generation phase that generates climate map according to each weather information of each farm (parcel) unit;
Estimating a growth condition by a biological seasonal prediction model constructed based on a biological experiment corresponding to the property of a parcel crop cultivated in each individual farm (parcel) unit;
Extracting a disaster risk index based on a parcel crop based on the weather information extracted from the generated climatic map, combining the vegetation information and the weather information according to the parcel crop property;
Inputting a corresponding instruction corresponding to disaster information according to an attribute of each parcel crop into a corresponding instruction database unit;
Determining the risk of disaster of the parcels crop by using the generated disaster risk index and generating the disaster special report; And
Providing the generated disaster specialist and corresponding countermeasure instructions to each individual farmhouse; An early warning method for an agricultural meteorological disaster. 11. The method of claim 10,
The climatic level generating step includes the step of generating the farm live climate map by the weather data collected from the automatic weather observation equipment (AWS) provided in each individual farm (parcel) unit to measure the weather information. . 12. The method of claim 11,
Providing disaster warning and response guidance to individual farmers is a process in which individual farmers are provided with disaster warning and response guidance and response measures are taken in accordance with the corresponding guidance, An early warning method for agricultural weather accidents, which is reflected in real time, so that the same disaster warning and response instructions are not provided.

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