Deep learning for spatiotemporal forecasting in Earth system science: a review

M Yu, Q Huang, Z Li - International Journal of Digital Earth, 2024 - Taylor & Francis
Deep learning (DL) has demonstrated strong potential in addressing key challenges in
spatiotemporal forecasting across various Earth system science (ESS) domains. This review …

Utilizing hybrid machine learning techniques and gridded precipitation data for advanced discharge simulation in under-monitored river basins

R Morovati, O Kisi - Hydrology, 2024 - mdpi.com
This study addresses the challenge of utilizing incomplete long-term discharge data when
using gridded precipitation datasets and data-driven modeling in Iran's Karkheh basin. The …

[HTML][HTML] Streamflow simulation with high-resolution WRF input variables based on the CNN-LSTM hybrid model and gamma test

Y Wang, J Liu, L Xu, F Yu, S Zhang - Water, 2023 - mdpi.com
Streamflow modelling is one of the most important elements for the management of water
resources and flood control in the context of future climate change. With the advancement of …

Evaluating distributed snow model resolution and meteorology parameterizations against streamflow observations: Finer is not always better

TB Barnhart, AL Putman, AJ Heldmyer… - Water Resources …, 2024 - Wiley Online Library
Estimating snow conditions is often done using numerical snowpack evolution models at
spatial resolutions of 500 m and greater; however, snow depth in complex terrain often …

Dissolving the mystery of subsurface controls on snowmelt–discharge dynamics in karst mountain watersheds using hydrologic timeseries

D Thurber, B Lane, T Xu, BT Neilson - Hydrological Processes, 2024 - Wiley Online Library
Streamflow generation in mountain watersheds is strongly influenced by snow accumulation
and melt as well as groundwater connectivity. In mountainous regions with limestone and …