What makes a good reservoir?

Project Summary

David Clancy, a Stats/Math/EnvSci major, and Tianyi Mu, an ECE/CompSci major, spent ten weeks studying the effects of weather, surroundings, and climate on the operational behavior of water reservoirs across the United States. They used a large dataset compiled by the U.S. Army Corps of Engineers, and they worked closely with Lauren Patterson from the Water Policy Program at Duke's Nicholas Institute for Environmental Policy Solutions. Project mentorship was provided by Alireza Vahid, a postdoctoral candidate in Electrical Engineering.

Themes and Categories
Energy & Environment
Data+
Year
2015
Contact
Paul Bendich
bendich@math.duke.edu

Project Results

Using sophisticated statistical machinery, the team showed that greater forestation and less-dense development increases the influence of rain on a reservoir. They also proposed a novel way to identify and characterize extreme reservoir events.

David explains the project at the Data+ poster session

Download the executive summary (PDF).

Disciplines Involved

  • Environmental Science
  • Statistics

Project Team

Undergraduates: Tianyi Mu and David Clancy

Clients:

Lead mentor: Alireza Vahid, post-doc, ECE

Graduate mentor: Hamza Ghadyali graduate student, Mathematics

Related People

Related Projects

Maximizing Data Communication for Faster Energy Access

Brooke Erikson (Economics/Computer Science), Alejandro Ortega (Math), and Jade Wu (Computer Science) spent ten weeks developing open-source tools for automatic document categorization, PDF table extraction, and data identification. Their motivating application was provided by Power for All’s Platform for Energy Access Knowledge, and they frequently collaborated with professionals from that organization.

Click here to read the Executive Summary

 

Data and the Global Corporate Bond Market

Jake Epstein (Statistics/Economics), Emre Kiziltug (Economics), and Alexander Rubin (Math/Computer Science) spent ten weeks investigating the existence of relative value opportunities in global corporate bond markets. They worked closely with a dataset provided by a leading asset management firm.

Click here for the Executive Summary

Construction Machinery and the Business Cycle

Maksym Kosachevskyy (Economics) and Jaehyun Yoo (Statistics/Economics) spent ten weeks understanding temporal patterns in the used construction machinery market and investigating the relationship between these patterns and macroeconomic trends.

They worked closely with a large dataset provided by MachineryTrader.com, and discussed their findings with analytics professionals from a leading asset management firm.

Click here to read the Executive Summary