An insight into machine learning models era in simulating soil, water bodies and adsorption heavy metals: Review, challenges and solutions
ZM Yaseen - Chemosphere, 2021 - Elsevier
The development of computer aid models for heavy metals (HMs) simulation has been
remarkably advanced over the past two decades. Several machine learning (ML) models …
remarkably advanced over the past two decades. Several machine learning (ML) models …
An enhanced extreme learning machine model for river flow forecasting: State-of-the-art, practical applications in water resource engineering area and future research …
Despite the massive diversity in the modeling requirements for practical hydrological
applications, there remains a need to develop more reliable and intelligent expert systems …
applications, there remains a need to develop more reliable and intelligent expert systems …
[HTML][HTML] Mapping high resolution national soil information grids of China
Soil spatial information has traditionally been presented as polygon maps at coarse scales.
Solving global and local issues, including food security, water regulation, land degradation …
Solving global and local issues, including food security, water regulation, land degradation …
Modelling impacts of climate change and anthropogenic activities on inflows and sediment loads of wetlands: Case study of the Anzali wetland
Understanding the effects of climate change and anthropogenic activities on the
hydrogeomorpholgical parameters in wetlands ecosystems is vital for designing effective …
hydrogeomorpholgical parameters in wetlands ecosystems is vital for designing effective …
A rainfall‐runoff model with LSTM‐based sequence‐to‐sequence learning
Rainfall‐runoff modeling is a complex nonlinear time series problem. While there is still
room for improvement, researchers have been developing physical and machine learning …
room for improvement, researchers have been developing physical and machine learning …
Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling
We undertook a comprehensive evaluation of 22 gridded (quasi-) global (sub-) daily
precipitation (P) datasets for the period 2000–2016. Thirteen non-gauge-corrected P …
precipitation (P) datasets for the period 2000–2016. Thirteen non-gauge-corrected P …
Using machine learning models for predicting the water quality index in the La Buong River, Vietnam
For effective management of water quantity and quality, it is absolutely essential to estimate
the pollution level of the existing surface water. This case study aims to evaluate the …
the pollution level of the existing surface water. This case study aims to evaluate the …
Hydropower dams of the Mekong River basin: A review of their hydrological impacts
Hydropower production is altering the Mekong River basin's riverine ecosystems, which
contain the world's largest inland fishery and provide food security and livelihoods to …
contain the world's largest inland fishery and provide food security and livelihoods to …
A guideline for successful calibration and uncertainty analysis for soil and water assessment: a review of papers from the 2016 international SWAT conference
Application of integrated hydrological models to manage a watershed's water resources are
increasingly finding their way into the decision-making processes. The Soil and Water …
increasingly finding their way into the decision-making processes. The Soil and Water …
[HTML][HTML] A continental-scale hydrology and water quality model for Europe: Calibration and uncertainty of a high-resolution large-scale SWAT model
A combination of driving forces are increasing pressure on local, national, and regional
water supplies needed for irrigation, energy production, industrial uses, domestic purposes …
water supplies needed for irrigation, energy production, industrial uses, domestic purposes …