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Remote Sensing for Hydrogeological/Hydrological Modelling and Applications: Second Edition

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Remote Sensors".

Deadline for manuscript submissions: 15 September 2026 | Viewed by 808

Special Issue Editors


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Guest Editor
Department of Chemical and Physical Sciences, University of Toronto Mississauga, Mississauga, ON L5L 1C6, Canada
Interests: watershed hydrology; remote sensing of water resources; hydrologic data assimilation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Following the success of the previous Special Issue “Remote Sensing for Hydrogeological/Hydrological Modelling and Applications (https://www.mdpi.com/journal/sensors/special_issues/remote_hydrologeological_water) we are pleased to announce the next in the series, entitled “Remote Sensing for Hydrogeological/Hydrological Modelling and Applications: Second Edition”.

Water is essential for all life on Earth. Water security and sustainable water resource management are some of the most urgent challenges that the world faces today given that the water cycle behaviour and spatial and temporal patterns of water resources are being increasingly impacted by climate change. Recent advances in data collection from satellite-based remote sensing (Earth observation) have opened up new opportunities to better understand water cycle behaviour and how it is changing in response to climate change.

This Special Issue focuses on Earth observation applications to improve our understanding of variability in water cycle behaviour and water resources, a necessary step toward evidence-based sustainable water resources management and water security. We welcome submissions that are related, but not limited, to the following topics:

  • Development of retrieval algorithms for various types of satellite hydrologic products (precipitation, soil moisture, snow and ice, terrestrial water storage, evapotranspiration, streamflow, lake or river water levels, etc.);
  • Validation of satellite hydrologic products using ground measurements;
  • Monitoring of hydroclimatic extreme events (e.g., floods and droughts) from Earth observation;
  • Satellite detection of variability in regional or global surface water and groundwater resources as influenced by climate change and/or human activities;
  • Application of satellite hydrologic products in computational models (e.g., data assimilation, model calibration);
  • An integrated use of Earth observation, ground measurements, and computational modelling for advancing our understanding of the physical processes that govern water movement in the surface/subsurface domains of the Earth system.

Dr. Xiaoyong Xu
Dr. Amen Al-Yaari
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • earth observation
  • satellite hydrologic products
  • water cycle
  • water resources’ sustainability
  • water security
  • climate change
  • data assimilation

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Published Papers (1 paper)

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Research

24 pages, 19823 KB  
Article
Identification of the Dominant Rainfall Index and Evolution of Multi-Factor Driving Mechanisms for Landslide Activity in Hong Kong (1990–2024)
by Jiaqi Wu, Zelang Miao, Yaopeng Xiong, Zefa Yang and Xiangqian Shen
Sensors 2026, 26(5), 1430; https://doi.org/10.3390/s26051430 - 25 Feb 2026
Viewed by 542
Abstract
Revealing the spatiotemporal driving mechanisms of landslide activity is fundamental to improving long-term landslide hazard management and risk mitigation in mountainous cities. Focusing on landslide events in Hong Kong from 1990 to 2024, this study develops an integrated framework at the slope-unit scale [...] Read more.
Revealing the spatiotemporal driving mechanisms of landslide activity is fundamental to improving long-term landslide hazard management and risk mitigation in mountainous cities. Focusing on landslide events in Hong Kong from 1990 to 2024, this study develops an integrated framework at the slope-unit scale that combines rainfall index optimization with multi-factor spatiotemporal driving analysis. First, Grey Relational Analysis (GRA) is employed to systematically evaluate the spatiotemporal associations between landslide occurrences and six commonly used rainfall indices, aiming to obtain a consistent and robust representation of rainfall triggering conditions. Subsequently, the Optimal-Parameter Geographical Detector (OPGD) model is introduced to quantitatively assess the explanatory power of individual factors—covering geological, topographic, hydro-meteorological, and human-related variables—as well as their pairwise interactions, thereby revealing the spatiotemporal evolution of landslide driving factors and their multi-factor coupling mechanisms over a 35-year period. The results indicate that the maximum 3-day cumulative rainfall index (RX3day) consistently exhibits the strongest association across different resolution parameter settings and is identified as the dominant rainfall indicator representing dynamic landslide triggering. Geological conditions and topographic factors constitute a stable background controlling the spatial heterogeneity of landslides throughout the entire study period, whereas the explanatory power of RX3day increases markedly after around 2000, gradually emerging as a primary dynamic driving factor of landslide activity. Interaction detection further demonstrates that landslide occurrence is mainly governed by nonlinear enhancement effects among multiple factors, with “geology–topography” and “rainfall–topography/geology” interactions showing the highest explanatory power, and rainfall-related interactions exhibiting continuous strengthening over time. Overall, the spatiotemporal distribution of landslides in Hong Kong is jointly controlled by long-term stable geological–topographic conditions and increasingly intensified extreme rainfall forcing. Full article
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