Remote Sensing for Distributed Hydrologic Models: New Satellite Data, Model Parametrization and Spatial Metrics to Calibrate and Evaluate Models
A special issue of Hydrology (ISSN 2306-5338).
Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 873
Special Issue Editors
2. Geological Survey of Denmark and Greenland, Øster Voldgade 10, 1350 Copenhagen, Denmark
Interests: hydrologic modeling; climate change; low flows; uncertainty analysis; spatial calibration
Special Issues, Collections and Topics in MDPI journals
Interests: hydrological modelling; remote sensing; machine learning; evapotranspiration
Special Issues, Collections and Topics in MDPI journals
Interests: hydrologic modeling and forecasting; land data assimilation; extreme events; climate change impact
Special Issues, Collections and Topics in MDPI journals
Interests: stochastic meteorology; hydrology; remote sensing; climate change
Special Issues, Collections and Topics in MDPI journals
Interests: The main research interests of the research group reside in the development of stochastic methods that characterize the spatial and temporal variability inherent to natural systems, in particular related to the water cycle. We use numerical techniques using high-order, nonparametric statistics. These allow us to analyze complex datasets such as remote sensing data or the outputs of complex models (climate models or flow/transport models). The work pursued is at the frontier between Earth modeling and computer science, with a strong emphasis on stochastic models, training images and example-based modeling.
Special Issues, Collections and Topics in MDPI journals
Interests: catchment hydrology; hydrological modelling; environmental change impacts; uncertainty analysis
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In this special issue of Remote Sensing we aim to collect contributions integrating satellite based remote sensing data into distributed hydrologic models using suitable or new spatial performance metrics (such as SSIM and SPAEF etc.) to evaluate spatial pattern agreement of satellite based estimations and hydrological predictions. Reviews and case studies reporting recent advancements in spatial metrics and remote sensing for precipitation, land surface temperature, actual evapotranspiration estimation, soil moisture, snow coverage, terrestrial water storage (MODIS, AMSR-E, Sentinel, SMOS, SMAP, GRACE etc.) are welcome. We are particularly interested in how satellite based data can improve spatial-temporal behavior of distributed hydrologic models and how they can be used in calibration and validation of hydrologic models. Also we aim to attract novel approaches for parameter regionalization and model parametrizations adding flexibility to the model structures to fit their outputs to the remote sensing data.
You may choose our Joint Special Issue in Remote Sensing.
Assoc. Prof. Mehmet Cüneyd Demirel
Dr. Julian Koch
Dr. Hongxiang Yan
Dr. Fabio Oriani
Prof. Dr. Gregoire Mariethoz
Assoc. Prof. Dr. ir Martijn J. Booij
Guest Editors
Manuscript Submission Information
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Keywords
- precipitation
- spatial hydrology
- soil moisture
- spatial calibration
- groundwater hydrology
- bias insensitive metrics
- evapotranspiration
- hydrologic model calibration
- spatial metrics
- SMAP
- GRACE
- MODIS
- Histogram match
- Spatial efficiency metric (SPAEF)
- Structural similarity index (SSIM)
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