Results 171 to 180 of about 183,921 (351)

Sugar Cube Karst [PDF]

The purpose of this activity is to explore the way water moves through a porous, soluble substance and to observe the development of pits and channels as the substance dissolves in water. Students learn what karst is and how it is formed.
Barb Mieras
core  

Karst

Le mot karst est le toponyme germanisé de Kras, une région de plateaux calcaires appartenant aux Alpes dinariques (Slovénie). L’ouvrage de Jovan Cvijic [Das Karstphänomen, 1893] a fait rentrer ce terme dans le vocabulaire scientifique. Il désigne désormais tous les modelés superficiels et souterrains issus de la dissolution par l’eau des roches ...
Vanara, Nathalie, Bigot, Jean-Yves
openaire   +1 more source

Genetic and Iterative Metaheuristics‐Informed Algorithms for Precision Shallow Groundwater Modeling and Drought Inference

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 1, February 2026.
Abstract Cokriging is a widely used geostatistical method for modeling the shallow groundwater table, often incorporating digital elevation models (DEMs) as secondary variables. However, existing approaches rarely include robust validation procedures to reduce local uncertainty or iteratively improve spatial predictions.
Massimiliano Schiavo, Daniele Pedretti
wiley   +1 more source

Progress and Prospects of Research on Microhabitat Scale Characterization and Utilization in Chinese Karst Area. [PDF]

Ecol Evol
Huang H, Yu Y, Yang S, Yang Y, Fu Y.
europepmc   +1 more source

Carbonate rocks and karst water resources in the Mediterranean region [PDF]

Julian Xanke, Nico Goldscheider, Michel Bakalowicz, Juan Antonio Barberá, Stefan Broda, Zhao Chen, Mohamed Ghanmi, Andreas Günther, Andreas Hartmann, Hervé Jourde, Tanja Liesch, Matías Mudarra, Marco Petitta, Nataša Ravbar, Zoran Stevanović   +14 more
openalex   +1 more source

A Causal‐Spatial Explainability Framework for Geological Hazard Susceptibility Modeling

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 1, February 2026.
Abstract Data‐driven susceptibility models often act as black boxes, predicting where hazards may occur without explaining why. To address this gap, we propose a Causal‐Prior (CP) framework that integrates validated causal knowledge into training while yielding spatially grounded explanations.
Bo‐Fan Yu, Huai‐Xue Xing, Hong‐Hu Zhu, Wei‐Ya Ge, Cong‐Xuan Kang, Mu‐Hua Zhao, Zheng‐Da Zhang   +6 more
wiley   +1 more source

Vegetation Restoration in Karst Southwest China: Effects of Plant Community Diversity and Soil Physicochemical Properties on Soil Cadmium. [PDF]

Toxics
Xing Y, Zhang L, Mei Z, Wang X, Li C, Li Z, Li Y.   +6 more
europepmc   +1 more source

The Files: Legal Controls Over the Accuracy and Accessibility of Stored Personal Data [PDF]

, 1966
Karst, Kenneth L.
core   +1 more source

A Diagnostic Framework and Data Inventory to Analyze Human Intervention on Streamflow

Water Resources Research, Volume 62, Issue 2, February 2026.
Abstract Growing recognition of human impacts on streamflow regimes has driven efforts to integrate water‐management modules into hydrological models to improve simulation accuracy. Yet data constraints often force simplifying assumptions, which may introduce unintended biases and obscure true human influences.
Anav Vora, Ximing Cai
wiley   +1 more source

Numerical simulation study on inferring the location of subsurface karst water channels using shallow geothermal field data. [PDF]

PLoS One
Zhang Q, Zeng R, Chen Z, Li Y, Ge W, Lu Y, Qiu J.   +6 more
europepmc   +1 more source