A review of hydrological monitoring and early warning technologies and equipment for geological hazards

Abstract

Geological hazards are frequent and highly destructive, with hydrological factors acting as the primary triggers. Constructing an efficient and precise hydrological monitoring and early warning system is crucial for active hazard prevention and control. Breaking away from the traditional review model based on technology types, this paper innovatively takes the "equipment development timeline" as the main thread, dividing the evolution of monitoring and early warning technologies into four core stages for in-depth analysis. The germination stage relied on manual inspections and empirical thresholds, suffering from monitoring blind spots and a lack of mechanistic understanding. The development stage achieved electronic automated data collection but was limited by point-based observation and "black box" models. The integration stage relied on "Space-Air-Ground" integration to achieve three-dimensional monitoring, yet faced conflicts between multi-source data fusion and spatiotemporal resolution. The current intelligent stage is evolving towards smart systems driven by the Internet of Things (IoT) and artificial intelligence (AI), but still faces challenges in hardware maintenance, data quality, and model interpretability. Based on the above diachronic analysis, this paper reveals the internal logic of technological iteration and innovatively proposes a next-generation technological roadmap centered on "full-area perception, intelligent fusion, and resilient early warning." The aim is to promote the deep integration of emerging technologies with hydrological and physical mechanisms in future research, constructing a more integrated, reliable, and intelligent disaster prevention and mitigation system framework.