Session 5: Data-mining and methods for modeling and assessing state and fate of soil water

Organisers: Ioannis Daliakopoulos1, Yannis Markonis2, Konstantinos Andreadis3, and Aristeidis Koutroulis1

1School of Environmental Engineering, Technical University of Crete
2Department of Water Resources and Environmental Modeling, Faculty of Environmental Sciences, Czech University of Life Sciences
3Jet Propulsion Laboratory, California Institute of Technology


Soil water is a key component of the Earth System as it plays a vital role in modulating storage and runoff generation, both on-site and off-site, and by extension the ecohydrological and biogeochemical cycles, all the way from plant and plot to watershed and global scale. While the value of soil water has been appreciated since the advent to modern agriculture, many details are still partly understood, mainly due to the vast heterogeneity and the poor connectivity of soil properties across scales. Soil water monitoring has seen major advances, thus allowing the collection of large volumes of data across time and space, which have greatly advanced our understanding of the role of soil water in the Earth System. Beyond monitoring, by considering variability in space, time, and the interaction between the two, we can advance our comprehension of the processes that control the dynamics of soil water at each scale, as well as downscale or generalize. Improving the description of soil water fluxes from the subsurface to the atmosphere, will provide a firmer grasp of runoff sources and sinks, residence times and evaporation/transpiration partitioning. An extension of our knowledge about spatial variability, will provide new insight on monitoring and mapping possibilities from the point scale to the global earth observations sensors. Advances such as these are critical to tie the soil component into climate and earth system models, and to support integrated water management, food security, and hydrological risk mitigation goals.

Contributions to Session 5 may include novel distributed networks and sensors applications, machine learning methods, stochastic analysis, spatiotemporal statistics, advanced GIS and data visualization, telemetry and satellite/UAV remote sensing, network and connectivity analysis, multi-scale study designs, decision support and risk assessment systems. This list is not exhaustive and inquiries about possible submissions are welcome.

Format: Oral/Poster