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Geological hazard forecasting and early warning are crucial measures for preventing geological disasters and minimizing casualties. Since the initiation of geological hazard meteorological risk early warning in 2003, 80% of mountainous provinces, cities and counties in China have implemented such measures. However, the independent construction model at the provincial, city, and county levels is inadequate to meet the collaborative needs across ministries, provinces, and the integration of cities and counties. This paper presents the case of integrated construction of meteorological risk early warning for geological hazards in Zhejiang Province. Following the principle of “provincial forecast extends to county, municipal forecast to township, and county early warning to village (point)”, the integration and exploration of trend forecasting, daily forecasting, short-term forecasting, real-time early warning, and the ‘intelligent prevention of geological disaster’ app have been conducted. A full lifecycle control and prevention business system of geological disaster with visual supervision and closed-loop means of intelligent prevention of geological disaster APP application has been established. Additionally, a digital product system for geological hazard prediction and early warning, tailored to the characteristics of Zhejiang Province, has been developed.

The research results regarding the threshold values for slope disasters caused by rainfall are crucial for geological disaster prevention. In this study，landslides induced by long-term heavy rainfall occurred in five counties within the Gansu section of the Bailongjiang Basin between 2004 and 2019. Using the frequency method, the rainfall thresholds for early warning of rainfall type landslides with different rock characteristics were investigated. A relationship model between event rainfall and the duration of rainfall leading to landslides was constructed under different probability levels, and a lower threshold for critical cumulative rainfall was provided. Through verification of landslide characteristics and rainfall data resulting from a flash flood disaster in Wudu District in 2020，the accumulated rainfall measured by the rainfall gauge before the landslide is found to be consistent with the threshold given by the model. This finding is of guiding significance for early warning of landslide disasters caused by sustained heavy rainfall.

Currently, in the field of geological disaster monitoring, monitoring and early warning information is mainly released based on the threshold setting of various types of monitoring equipment. However, since the thresholds are established according to empirical values or expert evaluations, there is a lack of pertinence to different types of geological disasters and different environments. Once set, these thresholds remain unchanged for a long time, and even when adjusted, they only slightly float based on experience, lacking scientific data sample analysis. Additionally, monitoring equipment is susceptible to satellite signals and environmental factors, leading to false alarms and false negatives during operation. To address these issues, a method of dynamic adjustment of self-learning and self-correction early warning thresholds is proposed. This method introduces two variable thresholds and a new performance index optimization method for VTAS based on priority and gate and semi-Markov processes. The application of the semi-Markov process allows the method to consider industrial measurements with non-Gaussian distributions. Moreover, an optimization design process based on genetic algorithms is proposed to improve performance indicators by optimizing parameter settings. Three numerical examples are used to illustrate the effectiveness of this approach and compare it with previous studies. When applied at the measured point, the method effectively reduce false alarms and under-alarms compared to the use of fixed thresholds, improving the accuracy of geological disaster early warning and better protecting the safety of people's lives and property.

As a natural disaster prone to occur in mountainous areas, geological hazards cause serious economic losses to China every year. In order to reveal the factors influencing of geological hazards susceptibility in typical mountain valley, this paper takes Changdu City as the study area.Firstly, we analyze the spatial distribution of geological hazards, and then divides it into three major watersheds based on the differences of disaster-inducing environments in the study area, selects 10 indicators such as elevation, slope and terrain relief to build a evaluation index system of geological hazard susceptibility , and the weights of index determined based on the Random Forest. The spatial distribution of geological hazards in each watershed of Changdu City is obtained by overlaying with GIS, and it is found that: (1) The types of geological hazards in Changdu City are mainly small disasters, while the distribution of large disasters is relatively small but the hazards are huge and the danger level is high. (2) In general, the factors influencing geological hazards are more or less the same in each basin, but there are still some differences, with the factor of medium altitude and road being more prominent in the Jinsha River basin, the factor of density of settlements being more prominent in the Lancang River basin, and the factor of road being more prominent in the Nujiang River basin.(3) The Jinsha River basin has the largest area of low susceptibility, and the Lancang and Nujiang River basins have the largest area of medium susceptibility; all three basins have the smallest area of high susceptibility, but they are distributed in the whole basin, and mainly in areas with strong human activities and soft lithology.

Geological hazard susceptibility assessment is an important basis for territorial space planning and geological hazard prevention and mitigation. In order to explore the evaluation method suitable for the geological hazard susceptibility of low hills and gullies in Yunnan plateau, Wuhua District of Kunming, Yunnan Province, China was selected as a typical study area. Eight factors including the engineering geology groups, distance from faults, elevation, slope, direction, curvature, distance from roads and land use covers were selected, and the weight evidence method based on Bayesian theory was applied to evaluate the susceptibility of geological hazards. After performing the Student-T test of the comprehensive evidence weight of each factor, the classification scheme of factors were optimized. The results of vulnerability zoning based on the evaluation of the model established in this paper showed that 89.9% and 9.1% of the geological hazard points fall into high and medium susceptibility areas. The comparative analysis showed that the modeling results are highly consistent with the geological hazards distribution, which better reveals the characteristics of geological hazards susceptibility in the study area. It can provide reference for the planning of geological hazards prevention in Wuhua District and other low hills and gullies areas of Yunnan plateau.

Taking Zemuhe fault zone (Puge section) as the study area, the control effect and development law of geological disasters in the study area are analyzed; Seven evaluation factors such as elevation, aspect and slope from fault are selected to construct the evaluation index system. The weighted information model coupled with deterministic coefficient model and information model is used to evaluate the susceptibility of geological disasters through ArcGIS. The results show that the development of geological hazards in the study area has fault distance effect, elevation and slope micro geomorphic effect and stratigraphic effect;The areas of extremely high, high, medium and low prone areas are 46.75 km2, 123.78 km2, 215.73 km2 and 285.34 km2 respectively, accounting for 6.96%, 18.43%, 32.12% and 42.49% respectively. The research results have important practical significance for guiding the land spatial planning and geological disaster prevention in Zemuhe fault zone and similar regions.

Wubao County is located in the northeastern part of the loess plateau in northern Shaanxi, geological disasters are developing in the area, which seriously threatens the life and property safety of local residents. On the basis of fully analyzing the geological disaster survey data in Wubao County, the evaluation indicators such as slope, slope aspect, and surface curvature were selected for the whole county scale, and the risk assessment was carried out based on the 25 m×25 m grid unit based on the information model based on the GIS platform. The evaluation results are divided into: extremely high risk area, high risk area, medium risk area and low risk area, accounting for 0.63%, 12.58%, 24.40% and 62.39% of the total area respectively. According to the scale of key areas, the factors of slope and slope height are selected, and the analytic hierarchy process model is used to carry out risk assessment of slope units divided by hydrological method based on GIS platform, including 19 extremely high-risk slopes, 69 high-risk slopes, 145 medium-risk slopes, 359 low-risk slopes. The same area (area A) under the two scales was selected to conduct variance analysis on the risk assessment results. It shows that at different scales and the same geographical location, the evaluation results of risk level may be inconsistent. At the county-wide scale, various mathematical statistical models with predictive functions should be used, but at the smaller key area scale, due to the insufficient number of samples used for training, it is not appropriate to use mathematical statistical models. Correspondingly, the grid unit based on GIS tools can be used as the evaluation unit at the county scale; the actual slope body can be used as the evaluation unit at the key area scale.

Gansu section of the Yellow River basin is the most concentrated area of geological disasters in Gansu Province. By the end of 2019, 12829 potential geological hazard points have been identified, accounting for 70.83% of the total number of disasters in Gansu Province. According to the distribution characteristics of water system, Weihe River basin, Jinghe River basin and the Yellow River basin are the most developed, followed by other water systems. According to the spatial distribution characteristics, it can be divided into three sections: the northern Yongdeng—Jingyuan debris flow area, the central and northern landslide debris flow concentrated section, the central and southern collapse landslide debris flow section, and the southern Maqu—Luqu geological disaster development section. In terms of time distribution, there are two high frequency periods: freezing and thawing period from February to May and main flood season from July to September. Geological disasters have the characteristics of small disaster and huge loss, mass damage and chain type huge loss. Single disaster is easy to form huge loss. The mass geological disaster caused by rainfall and earthquake often causes huge loss. At the same time, the risk of dammed lake formed by landslide flow blocking river channel often occurs.

This paper established the system of assessment in dex for regionalization of geological hazards in Bohai Sea with four aspects of hydrodynamic condition, engineering geological environment, disaster geological conditions and human engineering activities based on analytic hierarchy process, eight evaluation factors selected and the distribution characteristics of each geological hazard evaluation factor which were discussed in detail. The integrated geological disaster evaluation and regionalization were carried out combined with qualitative analysis and quantitative calculation. The risk level of submarine geological hazards in Bohai Sea are divided into four types: high, medium-high, medium-low and low.The study results can provide scientific basis for engineering construction and hazard prevention in Bohai Sea area.

The epicenter of the Ms6.0 earthquake occurred near Shuanghe Town in the southeast of Changning County, Yibin, Sichuan Province On June 17, 2019 is with the intensity of VIII degree. Immediately after the earthquake, field investigation of geological disasters were conducted, and it was found that Changning County and Gongxian County were greatly affected by the earthquake, while other districts and counties were slightly impacted. Based on the survey before and after the earthquake in three districts and seven counties in Yibin City, combined with the seismic intensity map and news articles issued by Sichuan Provincial Seismological Bureau, the development and distribution characteristics of post earthquake geological disasters in different seismic intensity areas, are as follows: ① The magnitude of the “6·17” earthquake in Changning, Yibin is 6.0, and the order of magnitude is 6.0. But there are many kinds of geological disasters. ②New geological hazards mainly distributed in Shuanghe Town, Changning County. The density of geological hazards in high intensity area is much larger than that in low intensity area. ③ The potential disaster points increased in high intensity areas, but slightly increase in medium intensity areas and had no change in low intensity areas. The conclusion of this paper could be reference for Sichuan Province, especially for the emergency relief, construction planning and geological disaster prevention and control.