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Articles 1 - 3 of 3
Full-Text Articles in Geological Engineering
Reducing Uncertainty In Sea-Level Rise Prediction: A Spatial-Variability-Aware Approach, Subhankar Ghosh, Shuai An, Arun Sharma, Jayant Gupta, Shashi Shekhar, Aneesh Subramanian
Reducing Uncertainty In Sea-Level Rise Prediction: A Spatial-Variability-Aware Approach, Subhankar Ghosh, Shuai An, Arun Sharma, Jayant Gupta, Shashi Shekhar, Aneesh Subramanian
I-GUIDE Forum
Given multi-model ensemble climate projections, the goal is to accurately and reliably predict future sea-level rise while lowering the uncertainty. This problem is important because sea-level rise affects millions of people in coastal communities and beyond due to climate change's impacts on polar ice sheets and the ocean. This problem is challenging due to spatial variability and unknowns such as possible tipping points (e.g., collapse of Greenland or West Antarctic ice-shelf), climate feedback loops (e.g., clouds, permafrost thawing), future policy decisions, and human actions. Most existing climate modeling approaches use the same set of weights globally, during either regression or …
Assessing Slope Instabilities, Victoria Leffel, Joey Franzino
Assessing Slope Instabilities, Victoria Leffel, Joey Franzino
Purdue Road School
INDOT’s Geotechnical Services Section has recently implemented a slide ArcGIS Collector app to provide a systematic approach to collecting and managing unsafe or failed slopes/embankments needed for decision making. A brief background in Indiana landslide geology will be given, then we will review the process of how to inventory slopes through the Collector app and identify potentially hazardous slopes. The session will end with a discussion of current engineering practices INDOT is using to correct landslides.
Spatial And Temporal Storm Generation From A Stochastic View, Jiaxiang Ding, Josept D. Revuelta-Acosta, Engel Bernard
Spatial And Temporal Storm Generation From A Stochastic View, Jiaxiang Ding, Josept D. Revuelta-Acosta, Engel Bernard
The Summer Undergraduate Research Fellowship (SURF) Symposium
Precipitation is one of the most important parameters in the study of hydrology and most of the research has been done on daily storm generation. Current weather generation models are used to replicate daily or monthly time resolution, which is not able to show the variability within one day or one month. This project deals with sub-daily storm generation with finer resolution and more accurate estimation, which also requires an independent storm separation method. And the Monte Carlo correlated multivariate simulation is applied to compute the variables. The description is essential for soil erosion and water quality research. Another reason …