AIMC Topic: Rain

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Cluster-based downscaling of precipitation using Kolmogorov-Arnold Neural Networks and CMIP6 models: Insights from Oman.

Journal of environmental management Mar 20, 2025
Accurate precipitation predictions are crucial for addressing climate change impacts on water resources, especially in arid regions like Oman. Therefore, this study evaluates three machine learning models-Random Forest (RF), Multilayer Perceptron Neu...
Rain Oman Machine Learning Neural Networks, Computer Forecasting Models, Theoretical Seasons Climate Change
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Enhancement of standardized precipitation evapotranspiration index predictions by machine learning based on regression and soft computing for Iran's arid and hyper-arid region.

PloS one Mar 18, 2025
Drought is a climate risk that affects access to safe water, crop development, ecological stability, and food production. Therefore, developing drought prediction methods can lead to better management of surface and groundwater resources. Similarly, ...
Iran Droughts Soft Computing Rain Machine Learning Desert Climate Regression Analysis
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Flood resilience through hybrid deep learning: Advanced forecasting for Taipei's urban drainage system.

Journal of environmental management Mar 7, 2025
The escalating impacts of climate change have intensified extreme rainfall events, placing urban drainage systems under unprecedented pressure and increasing flood risks. Addressing these challenges requires advanced flood mitigation strategies, opti...
Neural Networks, Computer Forecasting Deep Learning Climate Change Floods Rain Cities Taiwan
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Assessing the impact of rainfall, topography, and human disturbances on nutrient levels using integrated machine learning and GAMs models in the Choctawhatchee River Watershed.

Journal of environmental management Jan 31, 2025
Nutrient pollution caused by excessive total nitrogen (TN) and total phosphorus (TP) is a significant environmental challenge globally, threatening water quality and ecosystem health. This study investigates the interplay between rainfall, topography...
Water Pollutants, Chemical Nitrogen Nutrients Machine Learning Environmental Monitoring Rivers Rain Phosphorus Water Quality Humans
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Informing Risk Hotspots and Critical Mitigations for Rainstorms Using Machine Learning: Evidence from 268 Chinese Cities.

Environmental science & technology Jan 16, 2025
Climate change is exacerbating rainstorms, increasing the risk of flooding and threatening urban sustainability, which could undermine climate action. Here, we propose a machine learning-based framework to assess heterogeneous risks and identify crit...
Machine Learning Climate Change China Rain Cities
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Deciphering the climate-malaria nexus: A machine learning approach in rural southeastern Tanzania.

Public health Dec 6, 2024
OBJECTIVES: Malaria remains a critical public health challenge, especially in regions like southeastern Tanzania. Understanding the intricate relationship between environmental factors and malaria incidence is essential for effective control and elim...
Cohort Studies Tanzania Rural Population Rain Machine Learning Temperature Seasons Humans Malaria Incidence Climate
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A predictive fuzzy logic and rule-based control approach for practical real-time operation of urban stormwater storage system.

Water research Sep 12, 2024
Predictive real-time control (RTC) strategies are usually more effective than reactive strategies for the intelligent management of urban stormwater storage systems. However, it remains a challenge to ensure the practicality of RTC strategies that us...
Rain Water Movements Fuzzy Logic Cities Floods Models, Theoretical
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Multimodal Social Sensing for the Spatio-Temporal Evolution and Assessment of Nature Disasters.

Sensors (Basel, Switzerland) Sep 11, 2024
Social sensing, using humans as sensors to collect disaster data, has emerged as a timely, cost-effective, and reliable data source. However, research has focused on the textual data. With advances in information technology, multimodal data such as i...
Spatio-Temporal Analysis Humans China Social Media Natural Disasters Disasters Neural Networks, Computer Rain Risk Assessment
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Deep learning insights into spatial patterns of stable isotopes in Iran's precipitation: a novel approach to climatological mapping.

Isotopes in environmental and health studies Sep 3, 2024
Stable isotope techniques are precise methods for studying various aspects of hydrology, such as precipitation characteristics. However, understanding the variations in the stable isotope content in precipitation is challenging in Iran due to numerou...
Climate Rain Iran Deep Learning Carbon Isotopes Oxygen Isotopes Isotopes Environmental Monitoring
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Association of precipitation extremes and crops production and projecting future extremes using machine learning approaches with CMIP6 data.

Environmental science and pollution research international Sep 2, 2024
Precipitation extremes have surged in frequency and duration in recent decades, significantly impacting various sectors, including agriculture, water resources, energy, and public health worldwide. Pakistan, being highly susceptible to climate change...
Agriculture Pakistan Crops, Agricultural Rain Climate Change Machine Learning Crop Production
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