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Document Type

Open Access Dissertation

Degree Name

Doctor of Philosophy (PhD)

Degree Program

Civil and Environmental Engineering

Year Degree Awarded

2018

Month Degree Awarded

September

First Advisor

Richard Palmer

Subject Categories

Other Civil and Environmental Engineering

Abstract

Fresh water is a resource strongly impacted by climactic conditions. Water supply systems in the northeastern United States will see the effects of climate change on their water quality and quantity in various ways, including changes in seasonality of flows, changes in the frequency and magnitude of extreme precipitation events, and changes in the variability of precipitation and water availability. Five northeastern water supplies examined are expected to maintain at least 95% monthly reliability over a range of climates wider than the current projections. However, model results indicate that turbidity levels in New York City's Ashokan Reservoir will change with changes in mean annual precipitation and temperature.

Through a series of linked models of stochastic weather, hydrologic processes, and the supply system, Chapter 2 demonstrates the robustness of several adaptations available to the New York City Water Supply System to mitigate drought and manage water quality under climate change projections through the end of the century. Results illustrate how reducing demand and managing storage and releases based on hydrologic forecasting reduce the frequency of drought warnings and emergencies and improve system reliability in all climate change scenarios investigated. Through operations that limit turbidity propagation through the system and improvements to the Catskill Aqueduct to lower the minimum flow under conditions with high turbidity, results demonstrate decreases lower turbidity loads and a reduction in emergency Alum use. These options demonstrate cumulative benefits when used in combination.

Chapter 3 seeks to quantify the amount of water supply system performance improvement that can be expected from improved forecasting in managing drought conditions. Using existing forecasts for Lancaster, PA, synthetic forecasts with varying quality, and a system model of the Baltimore, MD water supply system, this chapter demonstrated a method for quantifying improved system performance as a function of improved forecast quality, finding improvements in system performance to be approximately linear over a large range of forecast quality.

Chapter 4 tests a new method for the creation of statistical first-order autoregressive streamflow forecasts by conditioning the parameters and ensemble variance on a “hydrologic regime,” defined in several different ways. National Weather Service seasonal outlooks for precipitation are used as categorical forecasts of precipitation. The forecasts are found to have small positive skill, and for two of three sites, this skill is enough to result in small gains in the CRPSS of the ensemble hydrologic forecast. Utilizing perfect categorical forecasts indicates that adjusting the ensemble variance (rather than the autoregressive parameter) based on forecasted precipitation is responsible for the majority of improvements in skill for this method. The method is limited by the difficulty of long lead-time precipitation forecasting.

Available for download on Sunday, September 01, 2019

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