Results 111 to 120 of about 7,970 (210)

In the Age of AI—Are National Models and Data Sets Still Important for Stream Flow Prediction?

Water Resources Research, Volume 62, Issue 10, October 2026.
Abstract Accurate streamflow prediction is critical for effective water resource management, and recent advances in deep learning and multi‐basin data sets have significantly improved model skill. Global deep‐learning models, trained on thousands of catchments have demonstrated strong generalization across diverse climates and continents.
Brett Snider, Ehsan Roshani
wiley   +1 more source

Physics-informed hybrid GR4J-XGBoost model for streamflow prediction: integrating conceptual states, SHAP interpretability, and uncertainty analysis. [PDF]

Sci Rep
Kisi O, Heddam S, Parmar KS, Külls C, Zounemat-Kermani M.   +4 more
europepmc   +1 more source

How Data Uncertainty Influences Estimates of Root Zone Water Storage Capacity

Water Resources Research, Volume 62, Issue 10, October 2026.
Abstract Root zone water storage capacity (SR ${S}_{R}$) sets the lower limit on the water available to plants and is critical for modeling terrestrial water and carbon fluxes. Due to subsurface heterogeneity in soils, roots, and geology, in‐situ measurements of SR ${S}_{R}$ are infeasible at regional to global scales.
Christopher J. Heckman, Lauren E. L. Lowman   +1 more
wiley   +1 more source

Unified multi-task learning for hydrological processes using a shared transformer framework. [PDF]

Sci Rep
Demiray BZ, Demir I.
europepmc   +1 more source

Spatiotemporal Dynamics of Active Root Zone Storage Revealed From Hybrid Machine Learning

Water Resources Research, Volume 62, Issue 10, October 2026.
Abstract Water within the root zone regulates water, energy, and carbon exchanges at the land‐atmosphere interface, yet the dynamically active portion of subsurface water that ecosystems mobilize for evapotranspiration (ET) remains unclear, because it represents only part of the total subsurface storage.
Georgios Blougouras, Shijie Jiang, Alexander Brenning, Mirco Migliavacca, Louise Slater, Jialiang Zhou, Rohini Kumar, Lu Tian, Chao Wang, Markus Reichstein   +9 more
wiley   +1 more source

Streamflow and water chemistry in cattle-impacted watersheds of the southern Coastal Plain, USA. [PDF]

J Environ Qual
Pisani O, Liebert D, Keel E, Coffin AW.
europepmc   +1 more source

Structure–Function Coherent Coarsening for Cross‐Resolution Ecohydrological Modeling

Water Resources Research, Volume 62, Issue 10, October 2026.
Abstract Ecohydrological models are increasingly applied in regional scenario‐based studies, yet their cross‐resolution application remains constrained by high computational costs of fine‐resolution simulations and by structural inconsistencies introduced during scale transfer.
Long Jiang, Yang Yang, Morgan Thornwell, Robert McKane, Sonali Chokshi, Huanfeng Duan, Tiantian Yang, Hoshin Vijai Gupta   +7 more
wiley   +1 more source

A comprehensive global dataset of river nutrient concentrations, loads and streamflow. [PDF]

Sci Data
Peters J, Noble A, Doscher C, McDowell R.   +3 more
europepmc   +1 more source

Time‐Varying Operation Policies With GRU‐Based Parameterization for Adaptive Multi‐Objective Reservoir Operation Under Climate Change

Water Resources Research, Volume 62, Issue 10, October 2026.
Abstract Designing reservoir operation policies that can adapt to non‐stationary hydroclimatic conditions is a major challenge for water resources management under climate change. This study develops an adaptive dynamic operation policy (ADOP), in which Gaussian radial basis functions (RBFs) are coupled with a gated recurrent unit (GRU)‐based ...
Yiming Wei, Renchao Wang, Lu Zhuo, Zengchuan Dong   +3 more
wiley   +1 more source

Uncertainty Estimation in Predicting River Discharge Using Probabilistic Machine Learning and Conformal Prediction. [PDF]

Sensors (Basel)
Abdi E, Sattari MT, Pal M, Milewski A, Apaydin H.   +4 more
europepmc   +1 more source