# Hazard Prediction of Water Inrush in Water-Rich Tunnels Based on Random Forest Algorithm
## 2 Construction of Evaluating Indicator System and Grading Standards  
### Construction of Evaluating Indicator System  
This article collected 101 actual accident cases; however, due to the high hazard of water inrush accidents recorded in this literature, the lack of cases with lower hazard, and the limited number of cases with relevant data, it was impossible to carry out subsequent data preprocessing work and establish prediction models. Based on this, this article collected 131 relevant studies from scholars on the prediction and evaluation of water  
Figure 1: Implementation process of hazard prediction of water inrush in a water-rich tunnel. inrush, and the results of these predictions and evaluations have been verified with high accuracy. In summary, the dataset applied to the model includes data regarding a total of 94 tunnels and 232 accident sections [14; 15; 16]. The construction of an evaluating indicator system can help evaluate the risk and hazard effects of water inrush in tunnels, thus enabling corresponding prevention and response measures and providing a scientific basis for the determination of the hazard level of water inrush in water-rich tunnels. Water inrush in a water-rich tunnel is influenced by various factors, mainly including hydrogeological conditions and human factors. Hydrogeological conditions are considered part of a disaster-prone environment, while human factors are considered to be inducing factors. This article focuses on the assessment of the hazard of water inrush in water-rich tunnel caused by the environment in which the tunnel is located. Therefore, the evaluating indicators established in this article all belong to hydrogeological conditions. This article conducts statistical analysis on accident sections where water inrush occurs. Based on the relevant hydrogeological conditions introduced by scholars [17; 18], the stratigraphic lithology, inadequate geology, and rock dip angle, which all have a significant impact on water inrush, are selected as evaluating indicators. Based on the evaluation and prediction of tunnel water inrush by various scholars [19; 20], the negative terrain area ratio, surrounding rock grade, and hydrodynamic zonation are three evaluating indicators that have high application frequency and are easy to collect. Finally, this article constructs an evaluation system for the hazard of water inrush in water-rich tunnels based on six evaluating indicators: stratigraphic lithology, inadequate geology, rock dip angle, negative terrain area ratio, surrounding rock grade, and hydrodynamic zonation. There is no obvious dependency relationship between various indicators, and their combination conditions jointly affect the risk of sudden water inrush, as shown in Figure 2.  
The impact mechanisms of the six evaluating indicators selected in this article are as follows. 1. Stratigraphic lithology B1: Stratigraphic lithology is one of the main material foundations that lead to karst development. Due to the different erosion and dissolution properties of rock minerals in groundwater, different rock types lead to different occurrence characteristics of water-bearing structures. Generally speaking, water inrush disasters in water-rich tunnels are more likely to occur in carbonate formations with higher solubility, such as limestone, dolomite, and other karst formations. 2. Inadequate geology B2: Inadequate geology refers to the channels and flow paths of underground water systems, including water storage structures, karst pipelines, underground rivers, fault fracture zones, and joint planes, which directly affect the scale of water inrush disasters in water-rich tunnels. The water-rich structural properties nurtured by these geological conditions determine the level of hazard when water inrush occurs in tunnels. Figure 2: Hazard evaluating indicator system of water inrush. Rock dip angle B3: The rock dip angle has a significant impact on the flow of groundwater.