Special Issue "Remote Sensing Data Assimilation in Hydrology: Towards an Improved Understanding of the Global Water Cycle and Human Impacts"
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Geology, Geomorphology and Hydrology".
Deadline for manuscript submissions: 31 July 2021.
Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA
Interests: hydrometeorology; surface water dynamics; computational modeling; water cycle; remote sensing
Interests: land surface modeling; hydrology; data assimilation; remote sensing; optimization
Special Issues and Collections in MDPI journals
Interests: regional climate processes; watershed hydrology; remote sensing; water resources; impacts of climate variability and change
Special Issues and Collections in MDPI journals
In the last decades, the hydrological science research has enabled significant advances in the understanding of water storage and fluxes over the continents using remote sensing data. Satellite missions such as GRACE and GRACE-FO has provided us with unprecedented information on the global water cycle and impacts of human activities on the spatial and temporal water storage variability. The GPM mission has been delivering us global hourly estimates of precipitation rates, and SMAP and SMOS has been retrieving surface soil moisture globally. The data from these missions are important not only for improving our understanding of the hydrological processes, but also for enhancing representation of extremes such as droughts and floods. Radar altimetry has been a gamechanger in surface water monitoring, measuring water levels of rivers, lakes, reservoirs and wetlands in the past 30 years. Combining water elevation change with digital elevation models or satellite-based water masks derived from Landsat and MODIS allows us to determine surface water storage change and reservoir operation impacts on river systems. The SWOT mission will further contribute to a two dimensional and temporally continuous monitoring of water bodies. Satellite-based leaf area index and evapotranspiration estimates can also inform us on plant stress and irrigation activities globally.
As a result of its global coverage at reasonable temporal resolution, hydrologists have been exploring ways to use multi-sensor satellite data to improve computational models. Data assimilation and optimization techniques have become popular tools, improving model parameters and states at different scales. Such techniques have also contributed to representations of anthropogenic activities, forecast initialization and the improvement of water resource monitoring systems.
The aim of this special issue is to gather a collection of latest developments and innovative applications of remote sensing data assimilation and integration into hydrological models. We invite contributions using the ample range of remotely sensed information through data assimilation, optimization and other innovative merging techniques to improve the numerical representation of hydrological processes, impacts of human activities on the water cycle and extreme hydrological event (e.g., droughts and floods) monitoring and forecast.Dr. Augusto Getirana
Dr. Sujay Kumar
Dr. Benjamin Zaitchik
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 papers will be 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 2200 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.