AIMC Topic: Lakes

Clear Filters Showing 61 to 70 of 87 articles

Deep learning-based remote sensing estimation of water transparency in shallow lakes by combining Landsat 8 and Sentinel 2 images.

Environmental science and pollution research international
Water transparency is a key indicator of water quality as it reflects the turbidity and eutrophication in lakes and reservoirs. To carry out remote sensing monitoring of water transparency rapidly and intelligently, deep learning technology was used ...

Magnetic properties and its application in the prediction of potentially toxic elements in aquatic products by machine learning.

The Science of the total environment
Magnetic measurement was provided to substitute for time-consuming conventional methods for determination of potentially toxic elements. Both the concentrations of 12 elements and 9 magnetic parameters were determined in 700 muscle tissue samples fro...

Quantification of chlorophyll-a in typical lakes across China using Sentinel-2 MSI imagery with machine learning algorithm.

The Science of the total environment
Lake eutrophication has attracted the attention of the government and general public. Chlorophyll-a (Chl-a) is a key indicator of algal biomass and eutrophication. Many efforts have been devoted to establishing accurate algorithms for estimating Chl-...

Sustainable management of water demand using fuzzy inference system: a case study of Kenyir Lake, Malaysia.

Environmental science and pollution research international
Sustainable water demand management has become a necessity to the world since the immensely growing population and development have caused water deficit and groundwater depletion. This study aims to overcome water deficit by analyzing water demand at...

Application of machine learning to identify predators of stocked fish in Lake Ontario: using acoustic telemetry predation tags to inform management.

Journal of fish biology
Understanding predator-prey interactions and food web dynamics is important for ecosystem-based management in aquatic environments, as they experience increasing rates of human-induced changes, such as the addition and removal of fishes. To quantify ...

Lake water-level fluctuation forecasting using machine learning models: a systematic review.

Environmental science and pollution research international
Lake water-level fluctuation is a complex and dynamic process, characterized by high stochasticity and nonlinearity, and difficult to model and forecast. In recent years, applications of machine learning (ML) models have yielded substantial progress ...

Modelling of ecological status of Polish lakes using deep learning techniques.

Environmental science and pollution research international
Since 2000, after the Water Framework Directive came into force, aquatic ecosystems' bioassessment has acquired immense practical importance for water management. Currently, due to extensive scientific research and monitoring, we have gathered compre...

Photoautotrophic picoplankton - a review on their occurrence, role and diversity in Lake Balaton.

Biologia futura
Occurrence of the smallest phototrophic microorganisms (photoautotrophic picoplankton, APP) in Lake Balaton was discovered in the early 1980s. This triggered a series of systematic studies on APP and resulted in the setting of a unique long-term pico...

Vulnerability Indexing to Saltwater Intrusion from Models at Two Levels using Artificial Intelligence Multiple Model (AIMM).

Journal of environmental management
Unplanned groundwater exploitation in coastal aquifers results in water decline and consequently triggers saltwater intrusion (SWI). This study formulates a novel modeling strategy based on GALDIT method using Artificial Intelligence (AI) models for ...

Comparing artificial intelligence techniques for chlorophyll-a prediction in US lakes.

Environmental science and pollution research international
Chlorophyll-a (CHLA) is a key indicator to represent eutrophication status in lakes. In this study, CHLA, total phosphorus (TP), total nitrogen (TN), turbidity (TB), and Secchi depth (SD) collected by the United States Environmental Protection Agency...