About this Research Topic
Current state-of-the-art observation technologies and modeling capabilities pave a promising way to advance a predictive understanding of terrestrial ecohydrological processes. Real-time and high-density observational networks and measurements, including flux tower matrix, Wireless Sensor Networks (WSNs), Internet of Thing (IOT), Unmanned Aerial Vehicle (UAV) remote sensing, have been successfully established and widely utilized for monitoring ecohydrological and geophysical variables across scales (such as precipitation, evapotranspiration, soil moisture, streamflow, groundwater and vegetation). Via data-model integration, hyper-resolution computational ecohydrological models become powerful tools to improve predictivity based on high-quality datasets.
Computational models combined with data assimilation methods and physics-informed machine learning methods provide a promising numerical testbed to interpret field observations and analyze the complexity of the coupled processes. Sensitivity Analysis (SA) and Uncertainty Quantification (UQ) are also prominent to assess the performance of the numerical testbed and develop the next generation data-model platforms.
This Research Topic aims to call for original and innovative research related to cross-disciplinary studies that demystify the complexity of ecohydrological processes using high-density observations, multi-dimensional remote sensing and hyper-resolution ecohydrological models.
We welcome collaborative research that focus on:
• utilizing comprehensive monitoring data to address ecohydrological sciences questions
• data-driven modeling approaches to integrate field and remote sensing observations
• integrating comprehensive observation data with process-based ecohydrological models
• sensitivity analysis and uncertainty quantification.
Keywords: Terrestrial Ecohydrological Processes, Field observation, Remote sensing, Ecohydrological modeling, Data-model integration
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.