Han et al. (2026) Remote Sensing Approaches to Track Climate-Induced Changes in Hydrological Systems

Identification

• Journal: Journal of Environmental & Earth Sciences
• Year: 2026
• Date: 2026-01-27
• Authors: Zhenghao Han, Zhigang Ye, Ying Zhou, Yin Cao
• DOI: 10.30564/jees.v8i1.12932

Research Groups

• College of Geographical Science, Inner Mongolia Normal University, Hohhot 010022, China

Short Summary

This review systematically synthesizes remote sensing technologies and analytical methods for monitoring climate-induced changes across various hydrological components, highlighting opportunities for multi-sensor data integration, machine learning, and high-resolution monitoring to enhance climate-responsive water resource management.

Objective

• To conduct an in-depth synthesis of remote sensing technologies, satellite missions, and analytical methods for tracking climate-induced changes in key hydrological variables (precipitation, soil moisture, snow cover, surface water processes, and groundwater variability).
• To identify new opportunities and outline future research directions for remote sensing-based hydrological analysis under changing climatic conditions.

Study Configuration

• Spatial Scale: Global to local (e.g., global precipitation, regional glacier retreat, local wetland hydrology).
• Temporal Scale: Near-real-time (e.g., flood monitoring) to long-term (e.g., multi-decadal changes in glacier extent, land use, and surface water).

Methodology and Data

• Models used: This paper is a systematic literature review and does not employ specific hydrological models itself. However, it discusses the application of remote sensing data as input for hydrological models (e.g., for flood prediction, water flow, and availability in river basins).
• Data sources:
  • Satellite Missions: Landsat, Sentinel-1, Sentinel-2, MODIS (Moderate Resolution Imaging Spectroradiometer), GPM (Global Precipitation Measurement), GRACE (Gravity Recovery and Climate Experiment), SMOS (Soil Moisture and Ocean Salinity), SMAP (Soil Moisture Active Passive), TRMM (Tropical Rainfall Measuring Mission), AMSR-E (Advanced Microwave Scanning Radiometer-Earth Observing System), WorldView, GeoEye.
  • Sensor Technologies: Multispectral (OLI), Synthetic Aperture Radar (SAR), Dual-frequency Precipitation Radar (DPR), Microwave Imager (GMI), Passive microwave radiometry, LiDAR (Light Detection and Ranging), Thermal infrared sensors.
  • Platforms: Satellite-based, Unmanned Aerial Vehicles (UAVs), Ground-based sensor networks (soil moisture sensors, piezometers, surface water sensors).
  • Methodology: Structured literature review focusing on recent peer-reviewed articles applying optical, microwave, radar, and gravimetric remote sensing methods. Analysis of regional case studies (Horn of Africa, Himalayas, Coastal Southeast Asia, Arctic Wetlands).

Main Results

• Remote sensing (RS) provides crucial, large-scale, and repetitive data for monitoring climate-induced hydrological changes, addressing the limitations of sparse ground-based observations.
• Key satellite missions offer diverse capabilities: optical sensors (Landsat, Sentinel-2, MODIS) for surface water extent, glacier mapping, and vegetation health; microwave/radar sensors (Sentinel-1 SAR, GPM, SMOS, SMAP, AMSR-E) for all-weather monitoring of precipitation, soil moisture, and flood dynamics; and gravimetric missions (GRACE) for large-scale groundwater storage changes.
• Case studies demonstrate RS utility in:
  • Drought monitoring and early warning (Horn of Africa) using SMOS, SMAP, and MODIS for soil moisture and vegetation stress.
  • Tracking glacier retreat and predicting river flow changes (Himalayas) with Landsat, Sentinel-2, and MODIS.
  • Monitoring coastal groundwater salinization and land subsidence (Coastal Southeast Asia) using Sentinel-1 SAR and GRACE.
  • Assessing wetland water levels and vegetation health (Arctic Wetlands) with Landsat, MODIS, and Sentinel-2.
• Future directions emphasize multi-sensor data integration, advanced analytical methods like machine learning, and high-resolution monitoring (e.g., UAVs, upcoming SWOT mission) to enhance hydrological analysis and overcome current limitations in spatial/temporal resolution and data accessibility.

Contributions

• Provides a comprehensive, systematic synthesis of diverse remote sensing technologies (optical, microwave, radar, gravimetric) and their applications across the entire hydrological cycle, filling a gap in existing reviews often focused on single variables or missions.
• Offers a comparative analysis of the capabilities, spatial-temporal resolutions, and practical applications of key satellite missions for climate-induced hydrological monitoring.
• Illustrates the practical utility and challenges of remote sensing through detailed regional case studies, demonstrating its role in water resource management and climate adaptation.
• Identifies new opportunities, such as multi-sensor data integration, machine learning, and high-resolution monitoring, and outlines future research directions to enhance climate-responsive water resource management.

Funding

• Inner Mongolia Autonomous Region Science and Technology Plan Project (No 2025YFHH0250)

Citation

@article{Han2026Remote,
  author = {Han, Zhenghao and Ye, Zhigang and Zhou, Ying and Cao, Yin},
  title = {Remote Sensing Approaches to Track Climate-Induced Changes in Hydrological Systems},
  journal = {Journal of Environmental & Earth Sciences},
  year = {2026},
  doi = {10.30564/jees.v8i1.12932},
  url = {https://doi.org/10.30564/jees.v8i1.12932}
}