In response to the challenges of detecting and forecasting adverse geological bodies and water inrush risks in long tunnels, this paper, based on the comprehensive analysis of seismic reflection waves and electroseismic effect coupling, has achieved a long-distance tunnel construction process, adverse geological detection, and early warning, and has realized precise forecasting of the scale and location of adverse water-containing bodies. Meanwhile, the transient electromagnetic theory and technology for detecting the position and scale of water-containing bodies have been proposed, achieving medium-distance water inrush risk detection. Finally, for water-containing bodies that are close, ground penetrating radar methods are used for detection and forecasting to achieve the purpose of close-range detection and forecasting. Ultimately, a comprehensive detection and forecasting theory and technology for adverse geological bodies and water inrush in long tunnels using electromagnetic, seismic wave, and electroseismic multi-means at long, medium, and short distances have been established. This technology has been applied to the detection and forecasting of adverse geology and water inrush in a tunnel in Fuzhou, and good application effects have been achieved through on-site excavation verification. By multi-means comprehensive forecasting technology and early warning systems, fine detection of adverse geology and water inrush during the tunnel construction process can be achieved, providing guidance and support for the safe construction of tunnels.

Subalpine meadow soil is widespread in the steep valleys of the eastern Tibetan Plateau. Owing to its unique structure and climatic conditions, rainfall can trigger extensive ecohydrological disaster, characterized by soil disintegration and shallow landsliding. This phenomenon leads to significant soil erosion and degradation of meadow ecosystems, highlighting the ecological vulnerability of the region. Field investigations have identified porewater pressure from infiltrated rainwater and gravitational pressure on saturated meadow soil as the primary drivers of the landsliding. Building on this understanding, efforts were made to assess the risk of subalpine meadow soil erosion induced by extreme rainfall near Xinduqiao County using the TRIGRS model and the coupled TRIGRS-TOPMODEL (TOP-TRIGRS). Validation of the simulated results against observed erosion events revealed that TOP-TRIGRS tends to predict unstable areas more accurately, particularly in the lower to mid-sections of slopes with gentler gradients, in line with theoretical models of shallow landslide. Specifically, while TRIGRS identified 50.31% of actual shallow landslides, TOP-TRIGRS reached 80.35%. Moreover, the AUC values for TRIGRS and TOP-TRIGRS were 0.787 and 0.896, respectively, indicating the superior predictive performance of TOP-TRIGRS. Accurate prediction of shallow landslides in subalpine meadow soil is vital for informing ecological management regulations and advancing soil and water conservation efforts in the eastern Tibetan Plateau.