arXiv:2606. 02791v1 Announce Type: new Abstract: Watershed networks exhibit convergent topologies in which multiple tributaries merge into downstream channels,integrating diverse upstream hydrological processes.
Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.
arXiv:2607. 02437v1 Announce Type: new Abstract: Time series forecasting remains challenging when the underlying data contain rare but critical extreme events.
arXiv:2607. 03217v1 Announce Type: new Abstract: Uncertainty quantification of hydrological predictions is necessary to inform operational decisions.
arXiv:2510. 02605v2 Announce Type: replace Abstract: While many modern studies are dedicated to ML-based large-sample hydrologic modeling, these efforts have not necessarily translated into predictive improvements that are grounded in enhanced physical-conceptual understanding.
arXiv:2601. 01558v2 Announce Type: replace-cross Abstract: Predicting river flow in places without streamflow records is challenging because basins respond differently to climate, terrain, vegetation, and soils.
arXiv:2606. 04143v1 Announce Type: cross Abstract: Accurate flood forecasting is essential for mitigating disaster risks and protecting communities.
arXiv:2602. 16579v2 Announce Type: replace-cross Abstract: Reliable global streamflow forecasting is essential for flood preparedness and water resource management, yet data-driven models often suffer from a performance gap when transitioning from historical reanalysis to operational forecast products.