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Full-Text Articles in Physical Sciences and Mathematics
Identification And Evaluation Of Critical Transportation Infrastructure Resilience After Hydro-Meteorological Event, Herman Serrato
Identification And Evaluation Of Critical Transportation Infrastructure Resilience After Hydro-Meteorological Event, Herman Serrato
Open Access Theses & Dissertations
Modern civilization is dependent on essential infrastructure assets that allow society to function in today’s standards. Critical interdependent infrastructure such as transportation, communication, security, and public health are marvels of human innovation and an important aspect of civilization's evolution. Recent world events such as climate change have underlined the necessity to develop strategic plans to enhance the resilience of infrastructure. This study aimed to identify and evaluate the flooding potential of critical transportation infrastructure that will influence traffic flow and impact the economy. The technical workflow is based on observations, predictions, experiments, testing, and analysis to derive a resilience score …
Global Analysis Of The Hydrologic Sensitivity To Climate Variability, Marisol Dominguez
Global Analysis Of The Hydrologic Sensitivity To Climate Variability, Marisol Dominguez
Open Access Theses & Dissertations
Identifying the regions with greatest changes in their hydrologic behavior under extreme weather events in the 21st century, constitutes a study priority of global impact. Here, we present a global assessment assessing the sensitivity of the world’s water landscapes to climate variability during 2001-2016, using a new metric called the Hydrologic Sensitivity Index (HSi). This equation is based on the well-known Budyko curve that uses annual values of Potential and Actual Evapotranspiration (PET and AET), and Precipitation (P), to assess the hydrologic behavior of a location under a given climatic condition by plotting the Evaporative Index (AET/P) against the Dryness …
Application Of Machine Learning In Flood Depth Prediction, Armando Esquivel
Application Of Machine Learning In Flood Depth Prediction, Armando Esquivel
Open Access Theses & Dissertations
Machine learning technologies have helped provide answers for problems with a high degree of complexity. Machine learning has been utilized by various disciplines within the Civil Engineering profession and has proven to be efficient in solving complex problems. Although machine learning is being used in the Civil Engineering profession, a formal framework on developing and integrating machine learning has not been developed for flood depth prediction. The proposed word uses machine learning to predict the depth of flood at Houston, TX, due to a 100-year 24-hour storm. The proposed work can be used to collect, store and analyze data to …