Debris flows represent a persistent challenge for disaster prediction in mountainous regions due to their highly nonlinear and multivariate triggering mechanisms. This study proposes an explainable deep learning framework, the Improved Kepler Optimiz...
This study investigates the long-term influence of climate change on the spatiotemporal dynamics of harmful algal blooms in lakes larger than 10 km² across the Yangtze River Basin from 1985 to 2022. Using Landsat satellite imagery, we quantified bloo...
Aquatic toxicology (Amsterdam, Netherlands)
Jun 22, 2025
The Danube flows through various European regions, exposing its aquatic ecosystem to multiple stressors, including dams, canalization, and agricultural activities. Fertilizers, manures, pesticides, animal husbandry activities, irrigation practices, d...
Cryptosporidium is a waterborne pathogen which poses a major challenge to water utilities because of its resistance to chlorination and its infectivity at very low concentrations. The ability to make predictions of Cryptosporidium concentrations in r...
River runoff may be affected mainly by the natural climate or human activities, and runoff series present complex characteristics, such as non-stationarity, which makes accurate prediction of runoff challenging. To address the problem that the predic...
Habitat reduction is significantly threatening biodiversity, making ecological connectivity which facilitates species movement across habitat patches, essential for human impacts mitigation, promoting genetic exchange, and enabling colonization of ne...
Agricultural runoff leading to nitrate (NO-N) and orthophosphate (PO-P) contamination poses significant environmental and public health risks. This study integrates the Soil and Water Assessment Tool (SWAT) with eXtreme Gradient Boosting (XGBoost), o...
As regulations ban legacy PFASs, many emerging PFASs are being developed, leading to their release into the aquatic environment and drinking water. However, research studies on these emerging PFASs in drinking water are limited, and current standards...
This study examines the water environmental factors of the Cangshan stream and benthic animal communities by using random forest, gradient boosting decision tree, and support vector machine models to analyze the complex response mechanisms of benthic...
Recent achievements in the fields of deep learning and remote sensing have led to their application in monitoring river water quality. One of the most researched methods is the estimation of total suspended solid (TSS) concentrations using multispect...
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