AIMC Topic: Hydrology

Clear Filters Showing 41 to 49 of 49 articles

A fuzzy-logic based decision-making approach for identification of groundwater quality based on groundwater quality indices.

Journal of environmental management Oct 6, 2016
Due to inherent uncertainties in measurement and analysis, groundwater quality assessment is a difficult task. Artificial intelligence techniques, specifically fuzzy inference systems, have proven useful in evaluating groundwater quality in uncertain...
Groundwater Fuzzy Logic Decision Support Techniques Models, Theoretical Hydrology Iran Water Quality
View on PubMed DOI

Fuzzy logic-based assessment for mapping potential infiltration areas in low-gradient watersheds.

Journal of environmental management Apr 1, 2016
This paper gives an account of the design a logic-based approach for identifying potential infiltration areas in low-gradient watersheds based on remote sensing data. This methodological framework is applied in a sector of the Pampa Plain, Argentina,...
Drinking Water Hydrology Soil Pollutants Argentina Soil Agriculture Groundwater Fuzzy Logic Water Purification
View on PubMed DOI

An extreme learning machine model for the simulation of monthly mean streamflow water level in eastern Queensland.

Environmental monitoring and assessment Jan 16, 2016
A predictive model for streamflow has practical implications for understanding the drought hydrology, environmental monitoring and agriculture, ecosystems and resource management. In this study, the state-or-art extreme learning machine (ELM) model w...
Hydrology Queensland Neural Networks, Computer Indian Ocean Ecosystem Agriculture Water Supply Rivers Environmental Monitoring Water Water Movements
View on PubMed DOI

Improving forecasting accuracy of medium and long-term runoff using artificial neural network based on EEMD decomposition.

Environmental research Feb 12, 2015
Hydrological time series forecasting is one of the most important applications in modern hydrology, especially for the effective reservoir management. In this research, an artificial neural network (ANN) model coupled with the ensemble empirical mode...
Time Factors Forecasting Hydrology Models, Statistical China Water Resources Neural Networks, Computer
View on PubMed DOI

Intergenerational inequity from hydrological drought in a warming world.

Journal of environmental management Jul 1, 2025
As warmer temperatures enhance atmospheric moisture, hydrological droughts tend to intensify in most regions of the globe. Consequently, younger generations are expected to face a more severe risk of hydrological drought during their lifetimes, empha...
Droughts Hydrology Humans Climate Change
View on PubMed DOI

Exploring the morpho-tectonic nature, hydrological and physical characteristics of a watershed and prioritizing sub-watersheds surface runoff potentialities by integrating MCDM and ensemble machine learning models.

Journal of environmental management Jun 1, 2025
Much effective rainfall often leads to natural and human-induced hazards when unused. Therefore, monitoring and managing water resources by assessing comprehensive surface runoff (SR) potential is crucial instead of relying on broad sub-watershed (SW...
Hydrology Water Resources Machine Learning Models, Theoretical Rain
View on PubMed DOI

A comprehensive review of deep learning applications in hydrology and water resources.

Water science and technology : a journal of the International Association on Water Pollution Research Dec 1, 2020
The global volume of digital data is expected to reach 175 zettabytes by 2025. The volume, variety and velocity of water-related data are increasing due to large-scale sensor networks and increased attention to topics such as disaster response, water...
Climate Change Water Resources Deep Learning Hydrology
View on PubMed DOI

Hybrid wavelet-support vector machine approach for modelling rainfall-runoff process.

Water science and technology : a journal of the International Association on Water Pollution Research Jan 1, 2016
Because of the importance of water resources management, the need for accurate modeling of the rainfall-runoff process has rapidly grown in the past decades. Recently, the support vector machine (SVM) approach has been used by hydrologists for rainfa...
Support Vector Machine Hydrology Rivers Rain Neural Networks, Computer Water Resources Water Movements Models, Theoretical
View on PubMed DOI

Application of transit data analysis and artificial neural network in the prediction of discharge of Lor River, NW Spain.

Water science and technology : a journal of the International Association on Water Pollution Research Jan 1, 2016
Transit data analysis and artificial neural networks (ANNs) have proven to be a useful tool for characterizing and modelling non-linear hydrological processes. In this paper, these methods have been used to characterize and to predict the discharge o...
Rivers Models, Theoretical Neural Networks, Computer Water Pollutants, Chemical Hydrology Spain
View on PubMed DOI
Popular Topics
Recent Journals