AIMC Topic: Rain

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Machine learning-based ensemble of Global climate models and trend analysis for projecting extreme precipitation indices under future climate scenarios.

Environmental monitoring and assessment Aug 12, 2025
Monitoring changes in climatic extremes is vital, as they influence current and future climate while significantly impacting ecosystems and society. This study examines trends in extreme precipitation indices over an Indian tropical river basin, anal...
Machine Learning Forecasting Rain Climate Models Pattern Analysis, Machine Environmental Monitoring Climate Change India
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Modeling impacts of climate-induced yield variability and adaptations on wheat and maize in a sub-tropical monsoon climate - using fuzzy logic.

Scientific reports Jul 16, 2025
Climate change is causing more frequent and extraordinary extreme weather events that are already negatively affecting crop production. There is a need for improved climate risk assessment by developing smart adaptation strategies for sustainable fut...
Temperature Zea mays Triticum Seasons Models, Theoretical Fuzzy Logic Adaptation, Physiological Bangladesh Climate Change Rain Crops, Agricultural
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Enhancing the resilience of urban drainage system using deep reinforcement learning.

Water research Apr 19, 2025
Real-time control (RTC) is an effective method used in urban drainage systems (UDS) for reducing flooding and combined sewer overflows. Recently, RTC based on Deep Reinforcement Learning (DRL) has been proven to have various advantages compared to tr...
Drainage, Sanitary Reinforcement Machine Learning Rain Deep Learning China Models, Theoretical Floods Cities
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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...
Oman Seasons Climate Change Rain Forecasting Models, Theoretical Neural Networks, Computer Machine Learning
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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, ...
Rain Soft Computing Iran Droughts 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...
Floods Rain Taiwan Climate Change Neural Networks, Computer Deep Learning Cities Forecasting
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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...
Machine Learning Environmental Monitoring Nitrogen Nutrients Water Pollutants, Chemical Humans Rivers Rain Phosphorus Water Quality
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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...
Cities Climate Change China Rain Machine Learning
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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...
Malaria Seasons Climate Cohort Studies Rural Population Temperature Incidence Tanzania Machine Learning Humans Rain
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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...
Water Movements Fuzzy Logic Cities Floods Models, Theoretical Rain
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