Civil and Environmental Engineering Commons^™

Evaluation Of Snow And Streamflow In The National Water Model With Analysis Using Machine Learning, Engela Sthapit

Dissertations and Theses

Snow has great influence on land-atmosphere interactions and snowmelt from the mountains is a vital water source for downstream communities dependent on snow fed lakes, rivers and streams. This study explored the snow and streamflow prediction capabilities of process-based numerical prediction and data-driven machine learning models.

The overall goal of this study was to understand the deficiencies in the NOAA’s National Water Model (NWM) to represent snow, subsequently streamflow, and recognize the areas where it could be improved for future model developments. The goal was also to evaluate if the recent advancements in machine learning techniques is useful for predicting …

Data Fusion And Synergy Of Active And Passive Remote Sensing; An Application For Freeze Thaw Detections, Zahra Sharifnezhadazizi

Dissertations and Theses

There has been a recent evolvement in the field of remote sensing after increase of number satellites and sensors data which could be fused to produce new data and products. These efforts are mainly focused on using of simultaneous observations from different platforms with different spatial and temporal resolutions. The research dissertation aims to enhance the synergy use of active and passive microwave observations and examine the results in detection land freeze and thaw (FT) predictions. Freeze thaw cycles particularly in high-latitude regions have a crucial role in many applications such as agriculture, biogeochemical transitions, hydrology and ecosystem studies. The …

Using Statistical Learning Approaches To Understand Trends And Variability Of Tornadoes Across The Continental United States, Niloufar Nouri

Dissertations and Theses

The annual frequency of tornadoes during 1950-2018 across the major tornado-impacted states were examined and modeled using anthropogenic and large-scale climate covariates in a hierarchical Bayesian inference framework. Anthropogenic factors include increases in population density and better detection systems since the mid-1990s. Large-scale climate variables include El Niño Southern Oscillation (ENSO), Southern Oscillation Index (SOI), North Atlantic Oscillation (NAO), Pacific Decadal Oscillation (PDO), Arctic Oscillation (AO), and Atlantic Multi-decadal Oscillation (AMO). The model provides a robust way of estimating the response coefficients by considering pooling of information across groups of states that belong to Tornado Alley, Dixie Alley, and Other …