[HTML][HTML] Groundwater level prediction using machine learning models: A comprehensive review
Develo** accurate soft computing methods for groundwater level (GWL) forecasting is
essential for enhancing the planning and management of water resources. Over the past two …
essential for enhancing the planning and management of water resources. Over the past two …
Deep learning for geophysics: Current and future trends
Recently deep learning (DL), as a new data‐driven technique compared to conventional
approaches, has attracted increasing attention in geophysical community, resulting in many …
approaches, has attracted increasing attention in geophysical community, resulting in many …
Climate change threatens terrestrial water storage over the Tibetan Plateau
Terrestrial water storage (TWS) over the Tibetan Plateau, a major global water tower, is
crucial in determining water transport and availability to a large downstream Asian …
crucial in determining water transport and availability to a large downstream Asian …
A comprehensive review of deep learning applications in hydrology and water resources
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 …
variety and velocity of water-related data are increasing due to large-scale sensor networks …
Impact of climate change on groundwater hydrology: a comprehensive review and current status of the Indian hydrogeology
Groundwater is the second largest store of freshwater in the world. The sustainability of the
ecosystem is largely dependent on groundwater availability, and groundwater has already …
ecosystem is largely dependent on groundwater availability, and groundwater has already …
Conceptualizing future groundwater models through a ternary framework of multisource data, human expertise, and machine intelligence
Groundwater models are essential for understanding aquifer systems behavior and effective
water resources spatio-temporal distributions, yet they are often hindered by challenges …
water resources spatio-temporal distributions, yet they are often hindered by challenges …
How can Big Data and machine learning benefit environment and water management: a survey of methods, applications, and future directions
Big Data and machine learning (ML) technologies have the potential to impact many facets
of environment and water management (EWM). Big Data are information assets …
of environment and water management (EWM). Big Data are information assets …
Machine learning for hydrologic sciences: An introductory overview
The hydrologic community has experienced a surge in interest in machine learning in recent
years. This interest is primarily driven by rapidly growing hydrologic data repositories, as …
years. This interest is primarily driven by rapidly growing hydrologic data repositories, as …
Reconstruction of GRACE data on changes in total water storage over the global land surface and 60 basins
Abstract Launched in May 2018, the Gravity Recovery and Climate Experiment Follow‐On
mission (GRACE‐FO)—the successor of the erstwhile GRACE mission—monitors changes …
mission (GRACE‐FO)—the successor of the erstwhile GRACE mission—monitors changes …
Improving AI system awareness of geoscience knowledge: Symbiotic integration of physical approaches and deep learning
Modeling dynamic geophysical phenomena is at the core of Earth and environmental
studies. The geoscientific community relying mainly on physical representations may want to …
studies. The geoscientific community relying mainly on physical representations may want to …