AIMC Topic: Climate Change

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Snow Height Sensors Reveal Phenological Advance in Alpine Grasslands.

Global change biology May 1, 2025
Long-term phenological data in alpine regions are often limited to a few locations and thus, little is known about climate-change-induced plant phenological shifts above the treeline. Because plant growth initiation in seasonally snow-covered regions...
Climate Change Switzerland Snow Grassland Plant Development Seasons Temperature
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Forecasting monthly runoff in a glacierized catchment: A comparison of extreme gradient boosting (XGBoost) and deep learning models.

PloS one Jan 1, 2025
Accurate monthly runoff forecasting is vital for water management, flood control, hydropower, and irrigation. In glacierized catchments affected by climate change, runoff is influenced by complex hydrological processes, making precise forecasting eve...
Forecasting Deep Learning Models, Theoretical Switzerland Climate Change Boosting Machine Learning Algorithms
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Artificial Intelligence for Climate Change Biology: From Data Collection to Predictions.

Integrative and comparative biology Sep 27, 2024
In the era of big data, ecological research is experiencing a transformative shift, yet big-data advancements in thermal ecology and the study of animal responses to climate conditions remain limited. This review discusses how big data analytics and ...
Climate Change Artificial Intelligence Microclimate Animals Big Data Data Collection
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[Multi-factor Impact Analysis of Grassland Phenology Changes on the Qinghai-Xizang Plateau Based on Interpretable Machine Learning].

Huan jing ke xue= Huanjing kexue Jun 8, 2024
The vegetation phenology of the Qinghai-Xizang Plateau is changing significantly in the context of climate change. However, there are many hydrothermal factors affecting the phenology, and few studies have focused on the effects of multiple factors o...
Soil China Machine Learning Temperature Seasons Poaceae Environmental Monitoring Remote Sensing Technology Grassland Rain Climate Change Altitude
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How AI is improving climate forecasts.

Nature Apr 1, 2024
Machine Learning Climate Change Climate Climate Models
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Environmental Sustainability and AI in Radiology: A Double-Edged Sword.

Radiology Feb 1, 2024
According to the World Health Organization, climate change is the single biggest health threat facing humanity. The global health care system, including medical imaging, must manage the health effects of climate change while at the same time addressi...
Radiology Climate Change Radiography Humans Artificial Intelligence Big Data
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Assessing the impacts of climate change on streamflow dynamics: A machine learning perspective.

Water science and technology : a journal of the International Association on Water Pollution Research Nov 1, 2023
This study investigates changes in river flow patterns, in the Hunza Basin, Pakistan, attributed to climate change. Given the anticipated rise in extreme weather events, accurate streamflow predictions are increasingly vital. We assess three machine ...
Water Resources Rivers Climate Change Neural Networks, Computer Machine Learning
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Deep learning based an effective hybrid model for water quality assessment.

Water environment research : a research publication of the Water Environment Federation Oct 1, 2023
Water, which is very important for life and civilizations on Earth, has been a source of life for all living things. However, freshwater resources gradually decrease due to climate change, pollution, and population growth. Water pollution is the qual...
Fresh Water Water Pollution Water Quality Climate Change Humans Deep Learning
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Climate and genetic data enhancement using deep learning analytics to improve maize yield predictability.

Journal of experimental botany Sep 3, 2022
Despite efforts to collect genomics and phenomics ('omics') and environmental data, spatiotemporal availability and access to digital resources still limit our ability to predict plants' response to changes in climate. Our goal is to quantify the imp...
Climate Change Climate Agriculture Deep Learning Zea mays
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Model predictive control based on artificial intelligence and EPA-SWMM model to reduce CSOs impacts in sewer systems.

Water science and technology : a journal of the International Association on Water Pollution Research Jan 1, 2022
Urbanization and an increase in precipitation intensities due to climate change, in addition to limited urban drainage systems (UDS) capacity, are the main causes of combined sewer overflows (CSOs) that cause serious water pollution problems in many ...
Cities Climate Change Urbanization Neural Networks, Computer Artificial Intelligence
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