Results 231 to 240 of about 79,529 (308)

Integrating Maximum Entropy Production Theory and Machine Learning to Improve Global Evapotranspiration Modeling

Water Resources Research, Volume 62, Issue 5, May 2026.
Abstract Accurate estimation of terrestrial evapotranspiration (ET) is vital for understanding global water and energy cycles. However, current global ET estimations are not well constrained. This study introduces an integrated framework combining the Maximum Entropy Production (MEP) theory with Random Forest (RF) model to improve global ET estimation.
Donghui Xu, Valeriy Ivanov, Vinh Ngoc Tran, Dongyu Feng, Gautam Bisht, Jingfeng Wang, L. Ruby Leung   +6 more
wiley   +1 more source

Movement patterns and habitat selection of Lahontan cutthroat trout during streamflow recession in a Great Basin stream. [PDF]

Mov Ecol
Flynn K, Rhoades S, Rossi G, Bess Z, Simmons J, Csank A, Hogan Z, Chandra S.   +7 more
europepmc   +1 more source

A Hybrid Empirical and Conceptual Model for Improving the Representation of Reservoirs With Limited Data in Hydrological Models

Water Resources Research, Volume 62, Issue 5, May 2026.
Abstract Numerous dams and reservoirs have fundamentally altered streamflow regimes and terrestrial hydrology. However, large‐scale hydrological models still depend on simplified and often unrealistic reservoir operation schemes due to limited understanding of real‐world operation complexities and inaccessibility of long‐term in situ operation data ...
Yanan Chen, Yi Zheng, Ximing Cai, Bin Yu, Zihan Zheng   +4 more
wiley   +1 more source

Copula-based multivariate analysis of hydrological drought over jiabharali sub-basin of Brahmaputra River, India. [PDF]

Sci Rep
Chakma B, Jhajharia D, Yurembam GS, Patle GT, Robert P, Saha S, Sharma APM, Singh SK.   +7 more
europepmc   +1 more source

An Integrated Modeling Framework for Sediment Dynamics During Urban Flooding: Application to Hurricane Harvey in Houston

Water Resources Research, Volume 62, Issue 5, May 2026.
Abstract Floodwater can mobilize and redistribute large volumes of sediment from upland to downstream urban areas, threatening infrastructure, water quality, and ecosystem health. However, existing modeling approaches often fail to capture sediment dynamics in urban floodplains due to the lack of integration between upland hydrological processes and ...
Dongyu Feng, Zeli Tan, Donghui Xu, Lingcheng Li, Gautam Bisht   +4 more
wiley   +1 more source

Disentangling climate and policy uncertainties for the Colorado River post-2026 operations. [PDF]

Nat Commun
Wang B, Bass B, Hall A, Rahimi S, Huang L.   +4 more
europepmc   +1 more source

Mechanisms of Vegetation Community Self‐Organization Driven by Water Availability in Arid Northwest China

Water Resources Research, Volume 62, Issue 5, May 2026.
Abstract Precipitation is scarce in arid regions, making water redistribution a key driver of vegetation patterns, especially for non‐zonal vegetation in oases. Nevertheless, the coupling and mutual feedback mechanism between water and vegetation distribution is complex, and it has not been fully addressed. Taking an arid region of Northwest China as a
Xing Li, Yong Wang, Yong Zhao, Long Yan, Fan He, Jiaqi Zhai, Jiaxin Li, Yuan Liu, Kuan Liu, Yajie Hu, Zhu Wang, Minjian Chen   +11 more
wiley   +1 more source

Changing dynamic phosphorus forms from field to stream during surface runoff events. [PDF]

J Environ Qual
Kreiling RM, Williamson TN, Fitzpatrick FA, Gierke KJ, Blount JD, Perner PM, Mevis IJ, Broerman HM, Merriman KR, Komiskey MJ.   +9 more
europepmc   +1 more source

Varying the Combination of Hydrological Models in Time and Space: Toward a More Accurate Representation of Streamflow in Large‐Sample Hydrology

Water Resources Research, Volume 62, Issue 5, May 2026.
Abstract Accurate predictions of streamflow are needed to manage water resources, evaluate flooding risks, and support agriculture and industry. Many hydrological studies rely on a single model structure and parameter set applied uniformly across space and held fixed over time, limiting their ability to represent spatiotemporal changes in hydrological ...
C. Thébault, W. J. M. Knoben, N. Addor, A. J. Newman, M. P. Clark   +4 more
wiley   +1 more source

Climate drives observational changes in hydrological extremes across most global regions. [PDF]

Innovation (Camb)
Wang N, Sun F, Liu W, Yang S, Wang H, Feng Y, Huang Q.   +6 more
europepmc   +1 more source