AIMC Topic: Hydrology

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Comparing linear and non-linear data-driven approaches in monthly river flow prediction, based on the models SARIMA, LSSVM, ANFIS, and GMDH.

Environmental science and pollution research international Nov 13, 2021
River flow variations directly affect the hydro-climatological, environmental, and ecological characteristics of a region. Therefore, an accurate prediction of river flow can critically be important for water managers and planners. The present study ...
Rivers Linear Models Hydrology Support Vector Machine Least-Squares Analysis
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Improving streamflow simulation by combining hydrological process-driven and artificial intelligence-based models.

Environmental science and pollution research international Jul 28, 2021
Accurate and timely monitoring of streamflow and its variation is crucial for water resources management in watersheds. This study aimed at evaluating the performance of two process-driven conceptual rainfall-runoff models (HBV: Hydrologiska Byråns V...
Rivers Water Movements Hydrology Artificial Intelligence Environmental Monitoring
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Reference evapotranspiration of Brazil modeled with machine learning techniques and remote sensing.

PloS one Feb 9, 2021
Reference evapotranspiration (ETo) is a fundamental parameter for hydrological studies and irrigation management. The Penman-Monteith method is the standard to estimate ETo and requires several meteorological elements. In developing countries, the nu...
Models, Statistical Remote Sensing Technology Hydrology Volatilization Reference Standards Machine Learning Brazil
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Exploring the multiscale hydrologic regulation of multipond systems in a humid agricultural catchment.

Water research Jul 11, 2020
Assessing the hydrologic processes over scales ranging from single wetland to regional is critical to understand the hydrologically-driven ecosystem services especially nutrient buffering of wetlands. Here, we present a novel approach to quantify the...
Ecosystem China Agriculture Artificial Intelligence Rivers Hydrology
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Artificial intelligence models versus empirical equations for modeling monthly reference evapotranspiration.

Environmental science and pollution research international May 23, 2020
Accurate estimation of reference evapotranspiration (ET) is profoundly crucial in crop modeling, sustainable management, hydrological water simulation, and irrigation scheduling, since it accounts for more than two-thirds of global precipitation loss...
Wind Algeria Neural Networks, Computer Artificial Intelligence Hydrology
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Leachate generation rate modeling using artificial intelligence algorithms aided by input optimization method for an MSW landfill.

Environmental science and pollution research international Dec 3, 2018
Leachate is one of the main surface water pollution sources in Selangor State (SS), Malaysia. The prediction of leachate amounts is elementary in sustainable waste management and leachate treatment processes, before discharging to surrounding environ...
Waste Management Gases Hydrology Artificial Intelligence Water Pollutants, Chemical Waste Disposal Facilities Algorithms Water Pollution, Chemical Malaysia Models, Theoretical Support Vector Machine
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Performance assessment of artificial neural networks and support vector regression models for stream flow predictions.

Environmental monitoring and assessment Nov 8, 2018
Water resources planning, development, and management need reliable forecasts of river flows. In past few decades, an important dimension has been introduced in the prediction of the hydrologic phenomenon through artificial intelligence-based modelin...
Neural Networks, Computer Artificial Intelligence Rivers Water Movements Hydrology Support Vector Machine Pakistan Algorithms Environmental Monitoring
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Modeling daily suspended sediment load using improved support vector machine model and genetic algorithm.

Environmental science and pollution research international Oct 24, 2018
Prediction of sediment volume and sediment load is always one of the important issues for decision-makers of watershed basins. The present study investigated the daily suspended sediment load in a watershed basin using the improved support vector mac...
Iran Geologic Sediments Hydrology Algorithms Support Vector Machine
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Priorization of River Restoration by Coupling Soil and Water Assessment Tool (SWAT) and Support Vector Machine (SVM) Models in the Taizi River Basin, Northern China.

International journal of environmental research and public health Sep 23, 2018
Identifying priority zones for river restoration is important for biodiversity conservation and catchment management. However, limited data due to the difficulty of field collection has led to research to better understand the ecological status withi...
China Environmental Monitoring Aquatic Organisms Soil Rivers Support Vector Machine Biodiversity Animals Environmental Restoration and Remediation Hydrology Seasons
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Assessment of groundwater vulnerability using supervised committee to combine fuzzy logic models.

Environmental science and pollution research international Feb 13, 2017
Vulnerability indices of an aquifer assessed by different fuzzy logic (FL) models often give rise to differing values with no theoretical or empirical basis to establish a validated baseline or to develop a comparison basis between the modeling resul...
Groundwater Hydrology Water Pollution Neural Networks, Computer Nitrates Geology Fuzzy Logic Iran Models, Theoretical
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