Abstract：With the rapid development of acoustic, optical, electrochemical, and other multi-type sensor technologies, in situ high-frequency monitoring has enabled continuous observations of water level, discharge, and multiple water quality parameters with high temporal and spatial resolution. This technological advancement has fundamentally transformed the traditional paradigms of hydrological and water quality monitoring, which have long been constrained by low sampling frequency, discontinuous data, and limited ability to capture shortterm hydrological events. As hydrological and water resources research increasingly emphasizes process-based mechanistic understanding and real-time management, in situ high-frequency monitoring has emerged as a critical tool for resolving rapid system dynamics and improving the accuracy of decision-making. This review systematically summarizes the evolution and applications of in situ high-frequency monitoring technology in the field of hydrology and water resources. The development of monitoring systems spans distinct technological stages, progressing from early manual observations and automated sampling to sensor-based, multi-parameter, and intelligent monitoring networks. Particular emphasis is placed on the pivotal role of advanced sensors in achieving long-term, high-resolution observations of hydrological and hydrochemical processes.A comprehensive synthesis of representative studies demonstrates that in situ high-frequency monitoring has significantly enhanced process characterization accuracy and response timeliness across a broad range of applications. These include watershed-scale hydrological process tracing and water source apportionment, analysis of solute transport and material migration mechanisms, water pollution control and early warning, refined water resources management, and forecasting of flash floods and mountain torrent disasters. High-frequency datasets effectively capture shortduration hydrological events, rapid water source transitions, and abrupt changes in pollutant fluxes—phenomena frequently missed by conventional low-frequency sampling—thereby providing essential data support for understanding complex hydrological and biogeochemical dynamics.Despite these notable advantages, current in situ high-frequency monitoring systems still face several challenges, including limited coverage of monitoring parameters, insufficient long-term sensor stability, performance degradation under complex environmental conditions, high costs for equipment deployment and maintenance, and the growing demand for efficient processing and interpretation of massive high-frequency datasets. Future development should prioritize the design of low-cost, multi-parameter integrated sensors and the deep integration of Internet of Things (IoT) technologies to improve data transmission efficiency and intelligent processing capabilities. These advancements will drive in situ high-frequency monitoring toward greater intelligence, precision, and operational efficiency, further consolidating its position as a core component of modern hydrological and water resources monitoring systems.