Call for Abstracts: AGU26 Session H074 – Geospatial Foundation Model & Remote Sensing for Hydrologic Prediction Across the Terrestrial Water Cycle

[Aashutosh Aryal]

Dear Colleagues,

We would like to invite you to submit an abstract to our session, "H074. Geospatial Foundation Model and Remote Sensing for Hydrologic Prediction Across the Terrestrial Water Cycle."

Session Overview

Hydrology is rapidly shifting toward a paradigm where satellite remote sensing, physics-based modeling, and AI foundation models converge. This session explores the integration of multi-sensor observations with next-generation AI—including geospatial foundation models, physics-informed machine learning, and differentiable modeling—to advance terrestrial water cycle prediction across scales.

We aim to bridge the hydrology, remote sensing, and AI communities to build seamlessly integrated learning systems for Earth system science.

Key Topics

We welcome contributions on:

• Physics-informed and hybrid AI for process representation.

• Earth Observation (EO) foundation models coupling satellite data with climate models.

• Advanced data assimilation and AI-driven observation operators.

• Uncertainty quantification and spatiotemporal error characterization.

• Monitoring hydrological extremes (e.g., fine-resolution drought and flood persistence) and land-atmosphere interactions.

We encourage studies leveraging missions such as SMAP, SMOS, MetOp, SWOT, GRACE-FO, NISAR, CYGNSS, GPM, Landsat, VIIRS, Sentinel, and commercial satellite constellations.

Submission Details

• Session Code: H074

• Submission Link: https://agu.confex.com/agu/agu26/prelim.cgi/Session/280895

• Abstract Deadline: 5 August 2026

Session Conveners

• Primary Convener: Hyunglok Kim (GIST)

• Co-Conveners: Kristen Marie Whitney (NASA Goddard), Ehsan Jalilvand (NASA Goddard), Venkataraman Lakshmi (Johns Hopkins University)

• Student/Early Career Conveners: Mohammad Saeedi, Ziyue Zhu, Gigi Pavur, Sophia Bakar, Aashutosh Aryal

Please feel free to forward this invitation to any students, postdocs, or colleagues who might be interested. We look forward to receiving your abstracts!

Best regards,

Aashutosh Aryal, PhD

On behalf of the H074 Convening Team