Predoctoral Fellow 2014-2015, Institute for Environmental Science and Policy
Developing Process-Based Distributed Hydrologic Models for Water Resources Management
Nicholas Haas is a second year PhD student in the Civil and Materials Engineering department. As a Co-Operative Student at the Argonne National Laboratory he has worked on and published research into hydropower operations which resulted in the creation of a new INstantaneous STreamflow Analysis Tool (INSTANT). At Argonne he modeled fish favorability in the Colorado River downstream of the Glenn Canyon Dam, conducted a statistical analysis on the relationship between remotely sensed data of desert land use and physical ground observations, and is currently exploring the statistical relationship between hyperspectral data and physical measurements of land use. Nick’s master’s research used log transformed OLS regression to backcalculate and formulate more accurate and predictive equations governing sediment transport of pebble-bed rivers. His dissertation research is focusing on creating a watershed scale, rainfall-runoff model that is parsimonious, relying on the least amount of data possible.
The end goal is to create a model that captures the dynamics of green stormwater infrastructure and a model that is intuitive and easy to use. Hopefully planners and decision makers can use it to better manage stormwater runoff in highly developed areas.