Quantitative forecasts of hydrogeomorphic processes and topography are greatly valuable to prepare for and mitigate land-surface changes under climatic and environmental changes. They also enhance the basic understanding of the processes by measuring and quantifying “natural experiments” of climate-surface dynamics. The recent revolution in climate and topographic data availability, together with advances in computational resources and methodology, enables the “Earthcasting”, namely, forecasting testable hydrogeomorphic and topographic changes under various changing conditions.
This session aims to explore the mechanistic understandings and methodologies to translate paleo, modern, and projected (future) climate data sets to hydrogeomorphic processes and topographic changes across temporal and spatial scales.
We welcome scientific contributions that focus on phenomena driven by weather and climate, ranging from discrete events (such as rainfall extremes and heatwaves), multi-year to multi-centuries trends in climatic attributes (such as temperature/rainfall), and paleo climate changes. We cover a wide range of near-surface hydrological and geomorphic processes and landforms, including (but not restricted to) floods, river delta and coastal evolution, hillslope failures and landslides in mountain landscapes, fluvial erosion/aggradation, glacial and periglacial processes, wildfire-driven erosion, and soil loss. Our focus also extends to studies on changes in near-surface hydrological properties, ecosystems, and their linkages.
We invite contributions showing novel theoretical, conceptual, and computational approaches to analyzing local to regional scale climate data sets derived from field-installed instruments, remote sensing, climate models, and weather generators, and the integration of these products with measurements and/or models of hydrogeomorphic processes and topographic changes. Studies that present calibration and validation methodologies for Earth's surface forecasts are especially welcome. Also, studies that demonstrate the application and social value of the predictability of Earth surface systems and processes are well-received.
Giulia Sofia