Wiley Online Library : Water Resources Research
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Isotope Hydrograph Separation Reveals Rainfall on the Glaciers Will Enhance Ice Meltwater Discharge to the Himalayan Rivers

Abstract The Indian Summer Monsoon (ISM) and meltwater from the Himalayan are the two most important sources of water in the Indian subcontinent. However, the impact of ISM on Himalayan glaciers and subsequent stream hydrology remains largely unknown. To provide new insight into the impact of rainfall on glacial hydrology, here we present hydro-meteorological...

Sat Jun 1, 2024 12:22
An Isotope Mass Balance Analysis of Evaporative Loss From Lake Turkana, Kenya Using δ18O and δD of Natural Waters

Abstract Measurements of oxygen and hydrogen stable isotope ratios (δ18O and δD) in meteoric waters provide insight to overlapping effects of evaporation, precipitation, and mixing on basin scale hydrology. This study of waters collected between 2016 and 2021 in the Turkana Basin, northern Kenya, uses δ18O and δD to understand water balance in Lake...

Fri May 31, 2024 13:14
Modeling the Effects of Artificial Drainage on Agriculture‐Dominated Watersheds Using a Fully Distributed Integrated Hydrology Model

Abstract In agriculture-dominated watersheds where natural drainage is poor, agricultural ditches (narrow engineered channels) and tile drains (perforated pipes) are widely employed to enhance surface and subsurface drainage, respectively. Despite their relatively small scale, these features exert substantial control over the hydro-biogeochemical function...

Fri May 31, 2024 13:14
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No abstract is available for this article.

Fri May 31, 2024 13:14
A Nonstationary Stochastic Rainfall Generator Conditioned on Global Climate Models for Design Flood Analyses in the Mississippi and Other Large River Basins

Abstract Existing stochastic rainfall generators (SRGs) are typically limited to relatively small domains due to spatial stationarity assumptions, hindering their usefulness for flood studies in large basins. This study proposes StormLab, an SRG that simulates precipitation events at 6-hr and 0.03° resolution in the Mississippi River Basin (MRB). The...

Sun May 26, 2024 12:01
A Novel Strategy for Automatic Selection of Cross‐Basin Data to Improve Local Machine Learning‐Based Runoff Models

Abstract Previous studies have shown that regional deep learning (DL) models can improve runoff prediction by leveraging large hydrological datasets. However, training a DL regional model using all data without screening may degrade local performance. This study focuses on constructing enhanced local models through the utilization of cross-basin data....

Sat May 25, 2024 13:03

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