HydroChronos: Forecasting Long-Term Surface Water Dynamics from Multi-Modal Data

From Lumped to Spatially Distributed Hydrologic Modeling: A Data‐Driven Framework Evaluated Across North American Catchments

Data‐driven rainfall–runoff models have advanced rapidly, yet the majority of large‐scale applications still rely on lumped inputs that smooth out spatial variability in precipitation, temperature, and landscape properties. This simplification can introduce substantial biases in flood peaks, hydrograph timing, and wate...

Spatio-Temporal Dynamics and Environmental Drivers of Surface Chlorophyll-a in the Gulf of Guinea (2003–2022)

The mechanistic understanding of biogeochemical dynamics in the Gulf of Guinea (GoG) has historically been hindered by persistent cloud cover and reliance on static geographic boundaries. In this study, we analysed a 20-year (2003–2022) satellite-derived chlorophyll-a (Chl-a) dataset to overcome these observational lim...

Hapi: A Multivariable Land-Surface Transformer for Medium-Range Hydrological Forecasting at Continental Scale

Accurate flood forecasts several days in advance are essential for flood control, water-resource management, and emergency response. A central challenge is to produce high-resolution forecasts across continental domains where hydrological behavior varies widely from place to place. We developed Hapi, a U-Net Swin Trans...

Comparison and Analysis of Four Terrestrial Water Storage Monitoring Models: A Case Study of the Loess Plateau

Accurate estimation of terrestrial water storage change (TWSC) remains challenging in regions where hydrological variability interacts with complex geological conditions and intensive human activities. Taking the Loess Plateau (LP) in the middle Yellow River region as a case study, this work integrates GLDAS simulation...

Globally Applicable Discharge Reanalysis using SWOT observations

How Ocean Thermal Structure and Atmospheric Steering Govern Typhoon Evolution: Evidence from Interpretable Machine Learning

Reliable typhoon forecasting demands both predictive accuracy and physical transparency. This study develops a tree-based framework for simultaneous multi-step prediction of typhoon trajectory and intensity in Western North Pacific (WNP), and applies SHapley additive explanations (SHAP) to quantify the contribution o...