ABSTRACT Understanding photosynthetic processes under field conditions is critical for identifying physiological determinants of seed yield (SY) in soybean. This study evaluated leaf gas exchange and chlorophyll fluorescence traits in seven soybean cultivars grown under irrigated (IR) and rainfed (RF) environments in the Mississippi Delta.
Srinivasa R. Pinnamaneni +2 more
wiley +1 more source
ABSTRACT Menstrual justice is deeply interconnected with water justice, yet these topics remain largely siloed in policy and research—particularly in Canada, where water access is often assumed to be a non‐issue. However, existing literature reveals that inadequate water and infrastructure significantly affect menstrual hygiene, dignity, and health ...
Emma Cowman +4 more
wiley +1 more source
Impacts of a flash flood on drinking water quality: case study of areas most affected by the 2012 Beijing flood. [PDF]
Sun R +8 more
europepmc +1 more source
Trends in thunderstorm days, lightning activity, squalls and the environmental factors in Hong Kong
This study analyses trends in Hong Kong's convective weather using long‐term observer‐based and shorter‐term instrument‐based data. Annual thunderstorm days increased significantly by 1.9 days decade−1 in 1947–2024, notably in June–September, consistent with increasingly favourable warm‐season environments for thunderstorms.
Yuk Sing Lui +5 more
wiley +1 more source
Trends and Epidemiological Profile of Climate-Related Disasters in Spain between 1950 and 2024. [PDF]
Fernández García A +2 more
europepmc +1 more source
Abstract Past evaluation of artificial intelligence (AI) weather prediction has primarily relied on reanalyses, which can obscure important deficiencies due to prevailing biases in reanalyses themselves. Here, we present MAUSAM (Measuring AI Uncertainty during South Asian Monsoon), an evaluation of seven leading AI‐based prediction systems—FourCastNet,
Aman Gupta, Aditi Sheshadri, Dhruv Suri
wiley +1 more source
Learning 2D Shallow Water Equations With Physics‐Informed Neural Operator Networks
Abstract This study investigates the application of Physics‐Informed Neural Operators (PINOs) for solving the two‐dimensional shallow water equations (2D SWE) in the context of flood modeling. Unlike Physics‐Informed Neural Networks (PINNs), which require retraining for each new initial or boundary condition (BC), PINOs learn the solution operator ...
Robert Keppler +2 more
wiley +1 more source
Data-driven flood susceptibility assessment using hybrid machine learning and optimization techniques: case of the Sedrata Watershed, NE Algeria. [PDF]
Mechentel E +5 more
europepmc +1 more source
Climatology of Storm Characteristics for Sub‐Daily Heavy Precipitation in the Greater Alpine Region
Abstract Characterizing storms that generate heavy precipitation across different timescales is essential for parameterizing and assessing stochastic weather generators, evaluating climate models, enhancing risk management, and understanding climate change impacts.
Eleonora Dallan +4 more
wiley +1 more source
Strategic dam site selection and hazard mapping using remote sensing: insights from Wadi Araba, Egypt. [PDF]
Mesallam MA +4 more
europepmc +1 more source

