Other 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 …

Season-Ahead Forecasting Of Water Storage And Irrigation Requirements – An Application To The Southwest Monsoon In India, Arun Ravindranath, Naresh Devineni, Upmanu Lall, Paulina Concha Larrauri

Publications and Research

Water risk management is a ubiquitous challenge faced by stakeholders in the water or agricultural sector. We present a methodological framework for forecasting water storage requirements and present an application of this methodology to risk assessment in India. The application focused on forecasting crop water stress for potatoes grown during the monsoon season in the Satara district of Maharashtra. Pre-season large-scale climate predictors used to forecast water stress were selected based on an exhaustive search method that evaluates for highest ranked probability skill score and lowest root-mean-squared error in a leave-one-out cross-validation mode. Adaptive forecasts were made in the years …