Reservoir yield estimates with consideration of uncertainty in used data in Illinois

Reservoir yield estimates are necessary and required for better water supply to communities especially during a severe drought. This study provides a framework to estimate reservoir yields with consideration of associated uncertainties in used data. Errors exist in inflow, reservoir capacity, evaporation and precipitation data and contribute to the overall uncertainty in reservoir yield estimates. Before combining optimization with Monte Carlo simulation, errors of each data category are assumed to follow a certain normal distribution. The framework is applied to three reservoirs in Illinois. It is found that the 95% probability intervals surrounding the estimates of reservoir yields range between -29% and +42% of the best estimate and the range is a bit right-shifted; evaporation contributes the most to the overall uncertainty, followed by reservoir capacity of small reservoirs and inflow to large reservoirs.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Environ Engr in Civil Engr

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2019

Author dc:creator

• Zhang, Yu

Contributors dc:contributor

• Cai, Ximing

• yield estimates
• data uncertainty

Statement dc:rights

• Copyright 2019 Yu Zhang

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/105955

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/105955