Results 151 to 160 of about 15,700 (307)

Response: Commentary: What We Know About Stemflow's Infiltration Area

open access: yesFrontiers in Forests and Global Change, 2021
Scott T. Allen   +2 more
doaj   +1 more source

Hydrologic resource assessment of upper Sabino Creek basin, Pima county, Arizona

open access: yes, 2001
A hydrologic resource assessment was performed for upper Sabino Creek basin, using data from a variety of local, state, and Federal agencies and organizations.
Peters, Christopher J., Bales, Roger C.
core  

Effects of Soil Physical Properties on Soil Infiltration in Forest Ecosystems of Southeast China

open access: yes
Soil infiltration properties (SIPs) are important components of forest hydrological responses; however, few studies have investigated the mechanisms through which soil physical properties affect SIPs.
Jinhong Chen   +3 more
core   +1 more source

Seasonal Variation in Carbon Dynamics in the Lower Tocantins River: Influence of Discharge and Environmental Drivers

open access: yesRiver Research and Applications, EarlyView.
ABSTRACT Tropical rivers play a key role in regional carbon budgets, yet greenhouse gas (GHG) dynamics in regulated systems remain poorly understood. This study investigates the seasonal variability of carbon dioxide (CO2) and methane (CH4) concentrations, isotopic composition (δ13C), and river‐atmosphere fluxes in the lower Tocantins River, a ...
Maria Gabriella da S. Araújo   +5 more
wiley   +1 more source

A Method for Identifying Rainfall‐Runoff Events at Sub‐Hourly Time Scales: Applications for Nature‐Based Solutions and Water Resources

open access: yesRiver Research and Applications, EarlyView.
ABSTRACT Understanding how changes in catchment conditions affect ecohydrology in response to rainfall‐runoff events is crucial when developing informed strategies to enhance flow resilience, restore natural habitats, interpret water quality data or reduce flood risk.
Josie Ashe   +7 more
wiley   +1 more source

Using Deep Learning AI to Detect Riparian Vegetation Recovery Following a Major Flood in the Brisbane River

open access: yesRiver Research and Applications, EarlyView.
ABSTRACT Post‐flood riparian vegetation recovery demands significant attention; however, the complexity of traditional remote sensing methods often hinders environmental managers from implementing rapid vegetation monitoring. This paper developed a model using a Deep Learning Model within ArcGIS to classify and detect recovery of vegetation with high ...
Sydney O'Hare, Jinghan Li, Yongping Wei
wiley   +1 more source

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