Results 121 to 130 of about 77,835 (200)

Predictability of seasonal runoff in the Mississippi River basin [PDF]

open access: yes, 2003
Recent advances in climate prediction and remote sensing offer the potential to improve long-lead streamflow forecasts and to provide better land surface state estimates at the time of forecast.
Lettenmaier, Dennis P., Maurer, Edwin P.
core   +1 more source

Predicting Lake Surface Water Temperature With Transfer‐Based Physics‐Informed Deep Learning

open access: yesWater Resources Research, Volume 62, Issue 4, April 2026.
Abstract Ongoing climate change has intensified lake surface warming. Enhanced accuracy in lake temperature modeling can better assess the risk of ecosystems being harmed by thermal tipping points, informing more sustainable water management. Recent progress in physics‐informed deep learning (PIDL) has opened new avenues for improving such modeling ...
Muyuan Liu   +9 more
wiley   +1 more source

Agricultural tile drains increase the susceptibility of streams to longer and more intense streamflow droughts

open access: yesEnvironmental Research Letters
Streamflow droughts are receiving increased attention worldwide due to their impact on the environment and economy. One region of concern is the Midwestern United States, whose agricultural productivity depends on subsurface pipes known as tile drains to
Seth R Adelsperger   +6 more
doaj   +1 more source

Toward improved hydrologic prediction with reduced uncertainty using sequential multi-model combination [PDF]

open access: yes, 2008
The contemporary usage of hydrologic models has been to rely on a single model to perform the simulation and predictions. Despite the tremendous progress, efforts and investment put into developing more hydrologic models, there is no convincing claim ...
Hsu, K, Moradkhani, H, Sorooshian, S
core  

A Graph‐Based Deep Learning Approach for Daily Flash Flood Susceptibility Modeling in China

open access: yesWater Resources Research, Volume 62, Issue 4, April 2026.
Abstract Flash floods are sudden flood events triggered by intense rainfall, and often exacerbated by mountainous terrain that accelerates surface runoff. To support disaster mitigation and management, deep learning (DL) models have been widely applied to flash flood susceptibility (FFS) modeling. However, traditional deep learning (DL) models overlook
Jun Liu   +3 more
wiley   +1 more source

Global Parameter Sensitivity in Forecast‐Informed Reservoir Operations Using Model Predictive Control

open access: yesWater Resources Research, Volume 62, Issue 4, April 2026.
Abstract Hydrologic forecasts have demonstrated considerable benefits for flood risk reduction and water supply operations in specific basins. However, it remains unclear how these benefits depend on key parameters of the reservoir infrastructure and forecasts.
Alexander B. Chen   +4 more
wiley   +1 more source

Evaluating Drought Vulnerability of Small Community Surface Water Supply Systems in the Midwest [PDF]

open access: yes, 2009
This report presents approaches and data availability for evaluating the drought vulnerability of small community water supply systems in the Midwest that obtain water from surface water bodies, such as rivers, streams, natural lakes, and man-made ...
Hecht, Jory S., Knapp, H. Vernon
core  

Influence of Weather Fronts on Design Storm Profiles: Applied Event Partitioning and Comparative Analysis

open access: yesWater Resources Research, Volume 62, Issue 4, April 2026.
Abstract Current practices in hydrologic design are based on the exceedance probability of rainfall intensities, without considering the meteorological conditions that generate them. Atmospheric drivers, such as weather fronts, control the spatiotemporal characteristics of storm events, with implications for urban stormwater infrastructure design and ...
M. J. Burns, K. D. Good, O. Wani
wiley   +1 more source

Sediment management for Southern California mountains, coastal plains and shoreline [PDF]

open access: yes, 1977
The Environmental Quality Laboratory at Caltech and the Shore Processes Laboratory at Scripps Institution of Oceanography have jointly undertaken a study of regional sediment balance problems in coastal southern California (see map in Figure 1).
Brown, William M., III   +2 more
core   +1 more source

A Model‐Agnostic Representation of Prairie Pothole Hydrology: Enhancing Generality and Implementation Across Hydrological Models

open access: yesWater Resources Research, Volume 62, Issue 4, April 2026.
Abstract Modeling streamflow in low‐lying, flat, and pothole‐dominated prairie or Arctic regions is challenging due to variable non‐contributing areas that influence how runoff translates to streamflow. Several modeling approaches have been developed to represent these dynamics, but many (a) lump depressions and permit spill only after a fixed capacity
Mohamed Moghairib   +3 more
wiley   +1 more source

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