Satellite Observations for Hydrology Modelling

Dear Colleagues,

Hydrological modelling has traditionally relied on ground-based observations, which are often sparse and limited in spatial coverage. Satellite remote sensing has emerged as a powerful alternative to traditional ground-based observations, offering high-resolution and spatially comprehensive data over vast areas. This capability is exemplified by numerous space-based hydrology missions, including ECOSTRESS, GCOM-W, GPM, GRACE-FO, NISAR, MetOp, TRMM, TOPEX, SMAP, SMOS, and SWOT. This has revolutionized hydrological research, providing a window into the intricate workings of the water cycle and enabling scientists to observe and measure key hydrological variables with unprecedented accuracy and spatial coverage. This transformation has empowered us to better understand and predict water resources at local, regional, and global scales, ultimately shaping the future of water resource management in a changing climate. Also, data assimilation techniques allow the systematic merging of these observations with model outputs, creating an estimate superior to either method alone. This combined approach helps bridge spatiotemporal scales and overcome limitations inherent to both observations and models.

This Special Issue seeks to explore the latest advancements and applications of satellite observations in hydrological modelling and data assimilation to enhance our understanding of the spatial and temporal dynamics of the terrestrial water cycle and freshwater resources. We also welcome research and case studies on the application of these data in hydrological models.

We welcome original research papers that address the following topics:

• Extracting hydrological variables: utilizing satellite-derived data for key hydrological variables such as precipitation, evapotranspiration, soil moisture, snow depth, groundwater storage changes (from gravity missions), and surface water discharge.
• Data assimilation techniques: developing and applying data assimilation techniques to integrate diverse satellite data into hydrological models, improving model accuracy and efficiency.
• Tailored satellite products: encouraging the development of new satellite-based products specifically designed for hydrological modeling applications.
• Impact evaluation: evaluating the impact of satellite data on hydrological simulations and predictions, particularly in ungauged basins with limited ground observations.
• Hydrological extremes: conducting research on using satellite data to improve predictions of floods, droughts, and other extreme hydrological events.
• Climate change assessment: investigating how satellite data can be used to understand the impact of climate change on hydrological processes.
• Machine learning applications: exploring how machine learning and deep learning techniques can be used to integrate diverse satellite datasets and improve model predictions.
• Real-world applications: showcasing successful case studies that demonstrate the application of satellite observations for real-world hydrological problems.

Dr. Younghyun Cho
Dr. ​Taeil ​Jang
Dr. Won-Ho Nam
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 100 words) can be sent to the Editorial Office for announcement on this website.

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. Remote Sensing 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 2700 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.

• hydrological modelling
• satellite remote sensing
• earth observations
• data assimilation
• earth’s water cycle
• global hydrology
• hydrometeorological variables
• hydrological extremes
• climate change assessment
• machine learning applications