Based on the record data of water disasters and the 5-min precipitation of 40 meteorological observation stations along the Shuozhou-Huanghua Railway from 2017 to 2019, the characteristics of railway water disasters and precipitation distribution were analyzed, then the three precipitation factors including continuous precipitation, the hourly maximum precipitation and the 24-hour precipitation were counted, the rainfall warning thresholds of no warning, patrol warning, speed limit warning and blockade warning of railway sections in plains and mountainous areas were formulated by using the mean-standard deviation method and the maximum value method. The results show that the water disasters of the Shuozhou-Huanghua Railway mainly occurred in July and August, and the duration of precipitation was mostly within 48 hours. The precipitation types causing water disasters were mainly local rainstorm, short-time heavy precipitation and long-duration precipitation, the railway water disasters in plain sections were mainly caused by local rainstorm, but the main cause of mountainous sections was long-duration precipitation. For railway section in the plain, the accuracy rate of patrol warning was 88.5%, the false rate was 11.5%, the accuracy rate of speed limit warning was 100%, for the railway section in the mountainous, the accuracy of patrols warning was 88.9% and the false rate was 11.1%. The rainfall warning threshold for railway sections in plains and mountainous areas could provide reference for safe running and efficient operation of railway.

Based on the traffic accidents data on expressway of Hebei Province and conventional observation data at 109 national weather stations from October 2015 to October 2018, the temporal variation characteristics of expressway traffic accidents and the relationship with meteorological factors in summer and winter half years were contrastively analyzed, firstly. Then, the meteorological factors which had obvious influence on traffic accidents were selected by principal component analysis method and the binary Logistic regression model was introduced to establish the meteorological early warning models of expressway traffic accidents in Hebei Province in summer and winter half years, respectively. Finally, the accuracy of two models was tested. The results show that the diurnal and monthly change characteristics of traffic accidents were obvious on expressway of Hebei Province. The frequency of traffic accident in summer half year was 1.4 times more than that in winter half year, and the monthly fluctuation in summer half year was weaker than that in winter half year. The diurnal variation of traffic accidents in summer and winter half years presented  ‘M’ pattern distribution. The traffic accidents in the daytime were more than that in the nighttime, the peak value appeared at 10:00 BST and 15:00 BST, and the traffic accidents at each time in summer half year (except from 18:00 BST to 20:00 BST) were higher than that in winter half year. The meteorological early warning model of expressway traffic accidents in Hebei integrated humidity, precipitation, wind speed and air pressure factors, while the temperature factor was also introduced in model in winter half year. The prediction accuracy of early warning model was above 99% to the samples less than or equal to the mode of traffic accidents, while that was lower to the samples above the mode, but the overall accuracy was still above 80%, which indicated that the model had a certain reference significance to expressway traffic early warning.

Based on traffic accidents and meteorological observation data from December 2015 to November 2018 in Hebei Province, the quantitative relationship between highway traffic accidents and meteorological conditions was analyzed. The highway traffic accidents happened more in summer and autumn than in spring and winter, and they happened more in the daytime than during nighttime. The peak value appeared in August and October, and it appeared during 09:00-11:00 and 14:00-17:00. Highway traffic accidents in Gaocheng of Shijiazhuang and Fengnan of Tangshan occurred most. Take the case of Shijiazhuang area, the response of the relative risk RR of highway traffic accidents to different meteorological elements was analyzed using the Spearman rank correlation and curve fitting method, it was found that there was a significant threshold effect of temperature on the frequency of highway traffic accidents, and the threshold of daily average temperature, the daily maximum temperature and daily minimum temperature  were 20 ℃, 25 ℃ and 15 ℃, respectively. When the daily minimum relative humidity exceeded 80%, the relative risk of accident increased by 3.77% for every 1% increase of relative humidity. When the maximum rain intensity increased 10 mm·h-1, the accident risk increased by 18.8%. When the visibility was less than 1000 meters, the risk of highway traffic accident decreased by 4.14% with the increase of 100 meters in the visibility.

The method of road surface temperature prediction for 2022 winter Olympic demonstration station (Beijing Huilongguan station) was discussed based on the METRo model. The artificial thermal parameters of iterative training fitting with a large number of sample data were added to the METRo model as the leading parameters in order to reduce the systematic error of the METRo model and the influence of human production and life on road surface temperature prediction. The results are as follows: (1) After introduction of artificial heat parameters, the simulation ability of the METRo model was improved significantly , especially at night, the root mean square error of road surface temperature prediction could be controlled at about 1 ℃. (2) The effect of artificial heat on road surface temperature presented negative feedback during daytime and positive feedback at night. (3) The simulated road surface temperature still had some errors due to influence of limitation of radiation prediction ability of meteorological models. In the mass, it was feasible to simulate the road surface temperature, especially for low temperature of road surface at the winter Olympic expressway demonstration station by using the METRo model with pre-set anthropogenic thermal parameters, which could support the prediction and early warning ability of highway road surface temperature and road icing in winter.

Based on the meteorological observation data at traffic weather stations along the highways of Hebei Province and the highway traffic accidents and closed-control data caused by the meteorological conditions during 2012-2017, the influence factors of the intensity of high impact weather, durations, risk zoning levels, single traffic flow, topography and occurrence period, etc. on the highway traffic passing were selected, firstly. Then the risk level forecast models of fog, road icing and heavy rainfall disasters were established by using the multifactor weighted method. And on this basis, the integrated risk level forecast model of highway traffic based on three weather conditions was built, and the grade standards were defined with the discrimination index of highway closed-control time caused by fog, road icing and heavy rainfall. Through testing, the accuracy rate of the forecast products of highway traffic integrated risk level model based on the meteorological conditions was 76.7%, which can meet the demand of daily traffic meteorological service.