Physical Sciences and Mathematics Commons^™

Learning From Machines: Insights In Forest Transpiration Using Machine Learning Methods, Morgan Tholl

Dissertations and Theses

Machine learning has been used as a tool to model transpiration for individual sites, but few models are capable of generalizing to new locations without calibration to site data. Using the global SAPFLUXNET database, 95 tree sap flow data sites were grouped using three clustering strategies: by biome, by tree functional type, and through use of a k-means unsupervised clustering algorithm. Two supervised machine learning algorithms, a random forest algorithm and a neural network algorithm, were used to build machine learning models that predicted transpiration for each cluster. The performance and feature importance in each model were analyzed and compared …

Mass Capacity Analysis Of Stormwater Control Measures Using Synthetic Stormwater With Silica, Organic And Hydrocarbon Constituents, Craig Michael Fairbaugh

Dissertations and Theses

Stormwater control measure (SCM) performance is well studied regarding solids removal; however, analysis of mass loading capacity, long-term performance, and maintenance demands are challenging due to the variability and multiple constituents inherent in urban stormwater. This research examines the long-term water quality performance and sediment mass capacity of two common SCMs: high rate biofiltration (HRBF) and conventional bioretention (BRT). Pollutant removal trials were conducted in a laboratory setting per the New Jersey Department of Environmental Protection (NJDEP) filtration protocol in two phases: the first using inorganic sediment per the NJDEP protocol, the second phase with the addition of organic sediment …

Towards Simulation Of Complex Ocean Flows: Analysis And Algorithm For Computation Of Coupled Partial Differential Equations, Wenbin Dong

Dissertations and Theses

The hybrid CFD models which usually consist of 2 sub-models, develop our capability to simulate many emerging problems with multiphysics and multiscale flows, especially for the coastal ocean flows interacted with local phenomena of interest. For most cases, the sub-models are connected with direct interpolation which is easy and workable. It becomes urgently needed to investigate the inner mechanism of such model integration as this simple method does not work well if the two sub-models are different in governing equations, numerical methods, and computational grids. Also, it can not treat complex flow structures as well as the balance in mass …

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 …

A Citizen-Science Approach For Urban Flood Risk Analysis Using Data Science And Machine Learning, Candace Agonafir

Dissertations and Theses

Street flooding is problematic in urban areas, where impervious surfaces, such as concrete, brick, and asphalt prevail, impeding the infiltration of water into the ground. During rain events, water ponds and rise to levels that cause considerable economic damage and physical harm. The main goal of this dissertation is to develop novel approaches toward the comprehension of urban flood risk using data science techniques on crowd-sourced data. This is accomplished by developing a series of data-driven models to identify flood factors of significance and localized areas of flood vulnerability in New York City (NYC). First, the infrastructural (catch basin clogs, …