Results 141 to 150 of about 1,749,217 (265)

Large Streamflow Differences Between Forested and Urbanized Watersheds in the Energy‐Limited Eastern United States: The Role of Evapotranspiration and Impervious Surfaces

Water Resources Research, Volume 62, Issue 2, February 2026.
Abstract Urban forests and other green infrastructures have been viewed as part of the “Nature‐based Solutions” (NbS) to mitigate emerging urban environmental change. This study focuses on the role of evapotranspiration (ET) in regulating water balances of small watersheds in the eastern United States.
Ge Sun, Zihao Bian, Kul Khand, Peter V. Caldwell, Johnny Boggs, Chen Wang, Yujuan Chen, Ning Liu, Yulong Zhang, Xi Chen, Gabriel B. Senay, Steven G. McNulty   +11 more
wiley   +1 more source

Evaporation‐Induced Hysteresis in Surface Water‐Groundwater Exchange in Wetlands

Water Resources Research, Volume 62, Issue 2, February 2026.
Abstract Evaporation is a major pathway of surface water loss in wetlands, yet its influence on subsurface feedbacks remains poorly understood. Using an integrated surface–subsurface hydrologic and solute transport model, we show that evaporation can induce hysteresis between evaporative demand and the upwelling of groundwater and solutes, with the ...
Chen Ding, Kewei Chen, Yang Zhan, Chunmiao Zheng, Zhilin Guo   +4 more
wiley   +1 more source

Comparison of Leaf Area Index, Surface Temperature, and Actual Evapotranspiration Estimated Using the METRIC Model and In Situ Measurements. [PDF]

Sensors (Basel), 2019
Reyes-González A, Kjaersgaard J, Trooien T, Reta-Sánchez DG, Sánchez-Duarte JI, Preciado-Rangel P, Fortis-Hernández M.   +6 more
europepmc   +1 more source

A remote sensing and modeling integrated approach for constructing continuous time series of daily actual evapotranspiration

Agricultural Water Management, 2022
H. Awada, S. Di Prima, C. Sirca, F. Giadrossich, S. Marras, D. Spanò, M. Pirastru   +6 more
semanticscholar   +1 more source

Human Interference Quantification and Representation in Hydrological Models—Introduction to the Special Collection on Quantifying Human Interferences in Hydrology

Water Resources Research, Volume 62, Issue 2, February 2026.
Abstract This article introduces papers published in the special collection of Water Resources Research on quantifying human interferences (or interventions in general) in hydrology and embedding them within large‐scale hydrological models. Starting with a list of instances of human interferences in various hydrologic processes, this article discusses ...
Ximing Cai
wiley   +1 more source

Comparison of the effectiveness of four Budyko-based methods in attributing long-term changes in actual evapotranspiration. [PDF]

Sci Rep, 2018
Ning T, Li Z, Feng Q, Liu W, Li Z.
europepmc   +1 more source

Evaluating the Performance of Uni‐ and Multivariate Bias Correction Techniques: Challenges in Preserving Temporal and Dependence Structures

Water Resources Research, Volume 62, Issue 2, February 2026.
Abstract Global Climate Models (GCMs) are essential for simulating past and future climates but suffer from systematic biases and coarse resolution, limiting direct applications. Bias correction (BC) and downscaling, using dynamical or statistical methods, address these issues. Quantile mapping (QM)‐based BC is widely used, yet it distorts dependencies,
Sachidananda Sharma, Akash Singh Raghuvanshi, Ankit Agarwal   +2 more
wiley   +1 more source

Soil water content effects on net ecosystem CO₂ exchange and actual evapotranspiration in a Mediterranean semiarid savanna of Central Chile. [PDF]

Sci Rep, 2018
Meza FJ, Montes C, Bravo-Martínez F, Serrano-Ortiz P, Kowalski AS.   +4 more
europepmc   +1 more source

Observation‐Driven Forecast of Global Terrestrial Water Storage and Evaluation for 2010–2024

Water Resources Research, Volume 62, Issue 2, February 2026.
Abstract Since 2002, the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow‐On (GRACE/‐FO) satellite missions have provided unprecedented measurements of terrestrial water storage changes (TWSC). These data are essential for monitoring the global water cycle, supporting drought and flood risk management, and informing water‐related ...
Fupeng Li, Jürgen Kusche
wiley   +1 more source

Bayesian-optimized machine learning boosts actual evapotranspiration prediction in water-stressed agricultural regions of China. [PDF]

Sci Rep
Elbeltagi A, Srivastava A, Cao X, Gautam VK, Zerouali B, Aslam MR, Salem A, Emami H, Elsadek EA.   +8 more
europepmc   +1 more source