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Full-Text Articles in Engineering
Remote Sensing Of High Latitude Rivers: Approaches, Insights, And Future Ramifications, Merritt E. Harlan
Remote Sensing Of High Latitude Rivers: Approaches, Insights, And Future Ramifications, Merritt E. Harlan
Doctoral Dissertations
High latitude rivers across the pan-Arctic domain are changing due to changes in climate and positive Arctic feedback loops. Understanding and contextualizing these changes is challenging due to a lack of data and methods for estimating and modeling river discharge, and mapping rivers. Remote sensing, and the availability of satellite imagery can provide ways to overcome these challenges. Through combining various forms of fieldwork, modeling, deep learning, and remote sensing, we contribute methodologies and knowledge to three key challenges associated with better understanding high latitude rivers. In the first chapter, we combine field data that can be rapidly deployed with …
From Probabilistic Socio-Economic Vulnerability To An Integrated Framework For Flash Flood Prediction, Sepideh Khajehei
From Probabilistic Socio-Economic Vulnerability To An Integrated Framework For Flash Flood Prediction, Sepideh Khajehei
Dissertations and Theses
Flash flood is among the most hazardous natural disasters, and it can cause severe damages to the environment and human life. Flash floods are mainly caused by intense rainfall and due to their rapid onset (within six hours of rainfall), very limited opportunity can be left for effective response. Understanding the socio-economic characteristics involving natural hazards potential, vulnerability, and resilience is necessary to address the damages to economy and casualties from extreme natural hazards. The vulnerability to flash floods is dependent on both biophysical and socio-economic factors. This study provides a comprehensive assessment of socio-economic vulnerability to flash flood alongside …
Ensemble Data Assimilation For Flood Forecasting In Operational Settings: From Noah-Mp To Wrf-Hydro And The National Water Model, Mahkameh Zarekarizi
Ensemble Data Assimilation For Flood Forecasting In Operational Settings: From Noah-Mp To Wrf-Hydro And The National Water Model, Mahkameh Zarekarizi
Dissertations and Theses
The National Water Center (NWC) started using the National Water Model (NWM) in 2016. The NWM delivers state-of-the-science hydrologic forecasts in the nation. The NWM aims at operationally forecasting streamflow in more than 2,000,000 river reaches while currently river forecasts are issued for 4,000. The NWM is a specific configuration of the community WRF-Hydro Land Surface Model (LSM) which has recently been introduced to the hydrologic community. The WRF-Hydro model, itself, uses another newly-developed LSM called Noah-MP as the core hydrologic model. In WRF-Hydro, Noah-MP results (such as soil moisture and runoff) are passed to routing modules. Riverine water level …
A Multivariate Modeling Approach For Generating Ensemble Climatology Forcing For Hydrologic Applications, Sepideh Khajehei
A Multivariate Modeling Approach For Generating Ensemble Climatology Forcing For Hydrologic Applications, Sepideh Khajehei
Dissertations and Theses
Reliability and accuracy of the forcing data plays a vital role in the Hydrological Streamflow Prediction. Reliability of the forcing data leads to accurate predictions and ultimately reduction of uncertainty. Currently, Numerical Weather Prediction (NWP) models are developing ensemble forecasts for various temporal and spatial scales. However, it is proven that the raw products of the NWP models may be biased at the basin scale; unlike model grid scale, depending on the size of the catchment. Due to the large space-time variability of precipitation, bias-correcting the ensemble forecasts has proven to be a challenging task. In recent years, Ensemble Pre-Processing …
Implementation Of A Sediment Transport Model For Ce-Qual-W2, Rachel Hanna
Implementation Of A Sediment Transport Model For Ce-Qual-W2, Rachel Hanna
Civil and Environmental Engineering Master's Project Reports
The CE-QUAL-W2 model, developed by Portland State University, simulates water quality and flow. Recommendations to expand on this model and have it include sediment transport are implemented in this report. Existing one-, two-, and three-dimensional models are reviewed and assessed for their sediment transport methodology. A laterally (width) averaged sediment concentration model is developed as an Upwind Center Space Scheme using CE-QUAL-W2 data. The scheme includes a method to calculate scour for sediment concentration and results of the model are shown for a simulated branch of the Spokane River.
Hydroclimatic Forecasting In The Western United States Using Paleoclimate Reconstructions And Data-Driven Models, Christopher Allen Carrier
Hydroclimatic Forecasting In The Western United States Using Paleoclimate Reconstructions And Data-Driven Models, Christopher Allen Carrier
UNLV Theses, Dissertations, Professional Papers, and Capstones
This thesis investigated climate variability and their associated hydrologic responses in the western United States. The western United States faces the problem of water scarcity, where the management and mitigation of available water supplies are further complicated by climate variability. Climate variability associated with the phases of oceanic-atmospheric oscillations has been shown to influence streamflow and precipitation, where predictive relationships have led to the possibility of producing long-range forecasts. Based on literature review, four oceanic-atmospheric oscillation indices were identified in having the most prominent influence over the western United States including the El Niño - Southern Oscillation (ENSO), Pacific Decadal …
Association Of Oceanic-Atmospheric Oscillations And Hydroclimatic Variables In The Colorado River Basin, Ajay Kalra
Association Of Oceanic-Atmospheric Oscillations And Hydroclimatic Variables In The Colorado River Basin, Ajay Kalra
UNLV Theses, Dissertations, Professional Papers, and Capstones
With increasing evidence of climatic variability, there is a need to improve forecast for hydroclimatic variables i.e., precipitation and streamflow preserving their spatial and temporal variability. Climatologists have identified different oceanic-atmospheric oscillations that seem to influence the behavior of these variables and in turn can be used to extend the forecast lead time. In the absence of a good physical understanding of the linkages between oceanic-atmospheric oscillations and hydrological processes, it is difficult to construct a physical model. An attractive alternative to physically based models are the Artificial Intelligence (AI) type models, also referred to as machine learning or data-driven …