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 …
[HTML][HTML] Marine waters assessment using improved water quality model incorporating machine learning approaches
In marine ecosystems, both living and non-living organisms depend on “good” water quality.
It depends on a number of factors, and one of the most important is the quality of the water …
It depends on a number of factors, and one of the most important is the quality of the water …
Interpretability of simple RNN and GRU deep learning models used to map land susceptibility to gully erosion
Gully erosion possess a serious hazard to critical resources such as soil, water, and
vegetation cover within watersheds. Therefore, spatial maps of gully erosion hazards can be …
vegetation cover within watersheds. Therefore, spatial maps of gully erosion hazards can be …
Research on the factors influencing nanofiltration membrane fouling and the prediction of membrane fouling
W Zheng, Y Chen, X Xu, X Peng, Y Niu, P Xu… - Journal of Water Process …, 2024 - Elsevier
The issue of membrane fouling poses a significant challenge to the extensive adoption of
nanofiltration membrane technology in public water supply systems. The occurrence of …
nanofiltration membrane technology in public water supply systems. The occurrence of …
Community-based watershed management (CBWM) for climate change adaptation and mitigation: Research trends, gaps, and factors assessment
N Ikhlas, BS Ramadan - Journal of Cleaner Production, 2023 - Elsevier
Appropriate watershed management must be implemented as an adaptation and mitigation
action for climate change. Therefore, community-based watershed management (CBWM) …
action for climate change. Therefore, community-based watershed management (CBWM) …
Anzali wetland crisis: unraveling the decline of Iran's ecological gem
The wetland loss rate in Iran is faster than the global average. Comprehending the
shrinkage rate in Iranian wetlands and identifying the underlying drivers of these changes is …
shrinkage rate in Iranian wetlands and identifying the underlying drivers of these changes is …
Contribution and behavioral assessment of physical and anthropogenic factors for soil erosion using integrated deep learning and game theory
Ensuring sustainable management of soil erosion is of utmost importance to prevent its
adverse effects. Unfortunately, this issue has received limited attention in the past, therefore …
adverse effects. Unfortunately, this issue has received limited attention in the past, therefore …
Machine learning prediction of wave characteristics: Comparison between semi-empirical approaches and DT model
Prediction of wave characteristics plays a crucial role in design and performance
assessment of various coastal projects. The computational complexity and time-consuming …
assessment of various coastal projects. The computational complexity and time-consuming …
Hybrid machine learning models for prediction of daily dissolved oxygen
Measuring water quality parameters is a significant step in many hydrological assessments.
Dissolved oxygen (DO) is one of these parameters that is an indicator of water quality …
Dissolved oxygen (DO) is one of these parameters that is an indicator of water quality …
Evaluation of water quality indexes with novel machine learning and SHapley Additive ExPlanation (SHAP) approaches
Water quality indexes (WQI) are pivotal in assessing aquatic systems. Conventional
modeling approaches rely on extensive datasets with numerous unspecified inputs, leading …
modeling approaches rely on extensive datasets with numerous unspecified inputs, leading …