SY
santiago yepez
University of Concepcion
Concepción, Chile
About this Research Topic
Manuscript Extension Submission Deadline 30 October 2026
Background
Rivers and glacial-fed lake systems are dynamic and complex environments shaped by interactions among flow regime, sediment transport, water quality, and geomorphic processes. These interactions are driven by natural variability and increasingly altered by anthropogenic pressures such as urbanization, agriculture, mining activities, and climate-related extremes. Disturbances including wildfires, prolonged droughts, glacier retreat, and volcanic activity can significantly modify water chemistry, sediment fluxes, and channel or basin morphology, often leaving detectable spectral signatures in fluvial and lacustrine environments.
Recent advances in hyperspectral and multispectral remote sensing have transformed the observation and understanding of fluvial and glacial-lake systems. Data acquired from UAVs, airborne sensors, satellites (including Landsat and Sentinel-2), and laboratory spectroscopy enable detailed characterization of water optical properties, suspended sediment concentrations, riverbed and lakebed materials, and hydrochemical anomalies. Hyperspectral and multispectral observations are particularly powerful for detecting diagnostic absorption and reflectance features associated with iron-rich precipitates, sulfate minerals, nutrients, contaminants, and algal blooms, which are commonly linked to acidic waters and other forms of water quality degradation.
This Research Topic focuses on the integration of hyperspectral and multispectral remote sensing across spatial and temporal scales to improve monitoring of water quality, sediment dynamics, and environmental change in river and lake systems, including proglacial and glacial-fed lakes. Contributions are encouraged that explore the fusion of UAV, airborne, and satellite data to enhance spatial–temporal resolution, enabling the assessment of both short-term disturbances and long-term trends. Studies addressing post-fire impacts on river systems, including sediment mobilization, hydrochemical alteration, and the evaluation of remediation or restoration effectiveness, are particularly welcome, as are studies on suspended sediment dynamics in glacially influenced lakes and rivers.
Emphasis is also placed on applications targeting urban and agricultural pollution, where hyperspectral and multispectral indicators can be used to detect nutrient enrichment, contaminants, and algal blooms, supporting regulatory monitoring and ecological risk assessment. Contributions linking remote sensing observations with river and lake restoration strategies, habitat assessment, and environmental management frameworks are strongly encouraged.
Methodological innovation is a core component of this Research Topic. Relevant studies may integrate hyperspectral or multispectral remote sensing with in-situ water quality measurements, sediment sampling, hydroacoustic observations (e.g., ADCP), and high-resolution topographic data such as LiDAR-derived DTMs. The use of remote sensing to parametrize, calibrate, or validate numerical models of water flow, water quality, and sediment transport is also of particular interest, strengthening process-based understanding and predictive capacity.
Multi-temporal analyses capturing seasonal variability, extreme hydrological events, and long-term environmental change are especially encouraged, as are case studies spanning diverse climatic settings, river and lake types, and degrees of human impact. By consolidating advances in hyperspectral and multispectral remote sensing, hydrology, geomorphology, and hydrochemistry, this Research Topic aims to advance transferable frameworks for monitoring, assessing, and managing fluvial and lacustrine systems under increasing environmental pressure.
The Research Topic welcomes contributions on:
• Multi-scale remote sensing of river and lake morphology and geomorphic units
• Hyperspectral detection of acidic waters and hydrochemical anomalies
• Spectral characterization of iron-rich and sulfate secondary minerals
• Remote sensing of water optical properties and quality gradients
• Integration of RS with ADCP, sediment measurements, and water chemistry
• Sediment transport and connectivity in impacted river and lake systems
• Detection of submerged features and fluvial or lacustrine habitats
• Multi-temporal analysis of geomorphic and hydrochemical change
• Machine learning approaches for fluvial, lacustrine, and hydrochemical feature extraction
• Case studies in natural and human-impacted river and lake systems
• Impacts of droughts, glacier retreat, or volcanic activity on water chemistry and sediment fluxes detectable via hyperspectral or multispectral signatures
• Multispectral estimation of suspended sediment concentration in glacial and proglacial lakes using Landsat, Sentinel-2, and similar satellite platforms
• Use of remote sensing to parametrize, calibrate, or validate numerical models of water flow, quality and sediment flux
Article types and fees
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
- Brief Research Report
- Data Report
- Editorial
- FAIR² Data
- General Commentary
- Hypothesis and Theory
- Methods
- Mini Review
- Opinion
Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.
Keywords: hyperspectral, remote sensing, water quality, sediment transport, river morphology, hydrochemistry, UAV, multi-temporal, contaminants, machine learning
Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
