CN-120580813-B - Intelligent meteorological early warning method based on portable traffic meteorological station

Abstract

The invention relates to the technical field of weather early warning, and particularly discloses an intelligent weather early warning method based on a portable traffic weather station, which comprises the steps of collecting weather data and rainfall data in real time through the traffic weather station and storing the weather data and the rainfall data into a database; the method comprises the steps of acquiring weather data and satellite cloud image information, predicting rainfall risks along with future time intervals according to the weather data and the satellite cloud image information acquired in real time to obtain predicted rainfall data, acquiring risk ponding points in an area, acquiring corresponding areas of each risk ponding point as risk areas, establishing a ponding risk model of each risk area according to the historical rainfall data in a database, and carrying out early warning on each ponding point through the rainfall data, the predicted rainfall data and the ponding risk model acquired in real time. The invention improves the accuracy of the early warning time point, is convenient for traffic departments to manage and control according to the judgment result, avoids the influence of road ponding on the life and property safety of people, and reduces the influence on traffic.

Inventors

• Liao Bijun
• WANG XINGMEI
• ZHANG XIAOWEI
• LI SHUANGSHUANG
• ZHA DAN
• WANG HENGBIN

Assignees

• 浙江蓝天气象科技有限公司

Dates

Publication Date

20260505

Application Date

20250424

Claims (3)

1. 1. An intelligent weather early warning method based on a portable traffic weather station is characterized by comprising the following steps: collecting meteorological data and rainfall data in real time through a traffic meteorological station and storing the meteorological data and the rainfall data into a database; Predicting rainfall risks along with future time periods according to weather data and satellite cloud image information acquired in real time to obtain predicted rainfall data; acquiring risk ponding points in the area, acquiring a corresponding area of each risk ponding point as a risk area, and establishing a ponding risk model of each risk area according to historical rainfall data in a database; early warning is carried out on each ponding point through rainfall data collected in real time, predicted rainfall data and ponding risk models; The process for establishing the ponding risk model comprises the following steps: Acquiring rainfall data when a ponding problem occurs in a historical risk area, fitting the rainfall data into a rainfall curve, and acquiring a rainfall value corresponding to a ponding occurrence time point in each ponding problem; Calculating the ground permeability value of the risk area when the water accumulation problem occurs each time; determining the ground penetration full load time of each water accumulation problem according to the rainfall curve and the ground penetration capacity value; Removing historical ponding problem corresponding data corresponding to a time point when the ground is fully penetrated and used and later than ponding occurs, and acquiring critical rainfall in a risk area according to the remaining historical ponding problem corresponding data; early warning the ponding risk according to the ground permeability value, the rainfall data, the predicted rainfall data and the critical rainfall of the risk area at the current time point; the process of calculating the ground penetration capacity value comprises the following steps: By the formula Calculating to obtain ground penetration capacity value of ponding problem corresponding to rainfall initial time point ; Wherein, the Is the ground penetration capacity value at the last rainfall end time point, T (T) is a temperature change curve, For the reference temperature value, H (t) is a humidity change curve, f is a soil moisture volatilization model function, For the last rainfall end time point, Corresponding to a rainfall starting time point for the current ponding problem; the calculation process when the ground penetration is fully loaded comprises the following steps: by establishing an equation Determining ground penetration loading ; Wherein, the Is the average value of the water seepage speed of the land, r (t) is a rainfall curve, Representation selection And the smaller of r (t); the process for acquiring critical rainfall in the risk area according to the corresponding data of the residual historical ponding problem comprises the following steps: acquiring rainfall values corresponding to the occurrence time points of the ponding in the residual historical ponding problem corresponding data; calculating variances of all rainfall values, and comparing the variances with preset error values: when the variance is less than or equal to a preset error value, the critical rainfall in the risk area is the average value of all rainfall values; When the variance is larger than the preset error value, sequentially removing the rainfall values according to the sequence of the difference between the rainfall value and the average value of all the rainfall values from large to small until the variance is smaller than or equal to the preset error value; the process of early warning each ponding point comprises the following steps: fitting a rainfall variation curve through rainfall data acquired in real time and predicted rainfall data ; Taking a rainfall initial time point as an origin, taking time as an x-axis, and taking rainfall as a y-axis to establish a plane coordinate system; By the formula Calculating the accumulated water quantity G (t) of the risk area, and carrying out weather early warning according to the accumulated water quantity G (t); Wherein, the For the judgment function, when x <0, When x is more than or equal to 0, R (t) is a rainfall variation curve, For the water-to-land ratio in the risk area, Representation selection And (3) with Q is critical rainfall of the risk area, and S is total area of the risk area.
2. 2. The intelligent weather early warning method based on the portable traffic weather station according to claim 1, wherein the weather early warning process according to the water accumulation amount G (t) comprises the following steps: When G (t) >0, judging that water accumulation occurs at the water accumulation point, and carrying out primary early warning; At the position of Judging that the accumulated water amount of the water accumulation point exceeds an alarm line and carrying out secondary early warning; Wherein A is a threshold value of the accumulated water quantity, Is the starting time point of the G (t) >0 period, , Is a preset fixed period of time.
3. 3. The intelligent weather early warning method based on the portable traffic weather station according to claim 2, wherein the process of early warning each water accumulation point further comprises: calculating the rainfall starting time point to Is the time difference of (2) ; At the position of Carrying out secondary early warning; Wherein, the Is a threshold time difference.

Description

Intelligent meteorological early warning method based on portable traffic meteorological station Technical Field The invention relates to the technical field of weather early warning, in particular to an intelligent weather early warning method based on a portable traffic weather station. Background The portable traffic weather station is equipment integrating various sensors and is used for monitoring weather parameters such as temperature, humidity, air pressure, wind speed, wind direction, precipitation and the like of a traffic junction position, the traditional weather early warning method is mainly based on large weather station data, satellite cloud images and radar echoes, and the technologies are effective, but have the problem of delay, so that an alarm can be sent out only a few minutes before an extreme weather event occurs, the disaster prevention preparation can be not timely enough, the portable traffic weather station can monitor the weather state of the current position in real time through the arrangement of the portable traffic weather station, the weather state can be accurately judged through the monitored weather parameters in combination with the real-time satellite cloud images, the radar echoes and the like, early warning can be timely carried out when extreme weather occurs, the most frequent water accumulation problem in urban traffic can be timely early warned when serious water accumulation occurs on a road through timely judgment of the magnitude of the rainfall, and the harm caused by the extreme weather is reduced. The method for warning the ponding risk in the prior art mainly carries out rough judgment through the rainfall and the position points where the ponding occurs frequently in the urban road network, and because the drainage capacity of different position areas is difficult to directly measure, the judgment accuracy of the ponding risk is lower, when extreme weather occurs, the prior art can timely warn due to the fact that the rainfall is obviously large, but for the non-extreme weather, if the accuracy of the warning time cannot be ensured, adverse influence is caused on traffic management and control of the road network, and therefore, how to timely and accurately judge the road ponding risk is the fundamental problem to be solved by the method. Disclosure of Invention The invention aims to provide an intelligent weather early warning method based on a portable traffic weather station, which solves the following technical problems: and judging the road ponding risk timely and accurately. The aim of the invention can be achieved by the following technical scheme: an intelligent weather early warning method based on a portable traffic weather station, the method comprising: collecting meteorological data and rainfall data in real time through a traffic meteorological station and storing the meteorological data and the rainfall data into a database; Predicting rainfall risks along with future time periods according to weather data and satellite cloud image information acquired in real time to obtain predicted rainfall data; acquiring risk ponding points in the area, acquiring a corresponding area of each risk ponding point as a risk area, and establishing a ponding risk model of each risk area according to historical rainfall data in a database; and carrying out early warning on each ponding point through rainfall data acquired in real time, predicted rainfall data and ponding risk models. Through the technical scheme, the water accumulation risk model is analyzed and built for each water accumulation point, different standards of judgment can be carried out on different water accumulation points, the accuracy of judgment is guaranteed, traffic departments are convenient to manage and control according to the judgment result, influence of road water accumulation on life and property safety of people is avoided, and meanwhile influence on traffic is reduced. Further, the process for establishing the ponding risk model comprises the following steps: Acquiring rainfall data when a ponding problem occurs in a historical risk area, fitting the rainfall data into a rainfall curve, and acquiring a rainfall value corresponding to a ponding occurrence time point in each ponding problem; Calculating the ground permeability value of the risk area when the water accumulation problem occurs each time; determining the ground penetration full load time of each water accumulation problem according to the rainfall curve and the ground penetration capacity value; Removing historical ponding problem corresponding data corresponding to a time point when the ground is fully penetrated and used and later than ponding occurs, and acquiring critical rainfall in a risk area according to the remaining historical ponding problem corresponding data; And early warning the ponding risk according to the ground permeability value, the rainfall data, the predicted rainfall data and the critical rai