Dissertations and Theses

Date of Award


Document Type



Civil Engineering

First Advisor

Naresh Devineni


Stochastic hydrology; Water policy; Streamflow reconstruction; Streamflow regimes; Water management; Risk assessment


The risks and vulnerabilities facing reservoir systems in river basins shift dynamically over time and space. These risks involve regime changes and shifts, throughout which one observes the transition of water availability from prolonged dry periods to prolonged wet periods. Ensuring reliability of water supply under these hydrological regime shifts involves understanding how these regime shifts can be identified, characterized, and quantified. This dissertation describes a dynamic risk management (DRM) framework for water management at the basin level whose main features are (1) a system of updating risk assessments and policy recommendations on a yearly basis, where the risk assessments themselves are multi-year projections for the purposes of long-term planning into the future, and (2) integration of water supply and water demand variables into a quantitative hydrological risk assessment and streamflow regime identification tool. The DRM framework expounded in this dissertation will be split into four parts. The first part is extending streamflow records using tree-ring chronology-based paleo-reconstruction techniques. Longer streamflow records have the advantage of containing more information about the past hydrological behavior than the much shorter observed records do. Chapter 2 details a novel streamflow reconstruction approach for river basins in which the streamflow gauges are organized as a network, in which one streamflow gauge feeds into another one downstream. The method is applied to reconstructing streamflow for eighteen streamflow gauges in the Upper Missouri River Basin (UMRB). The second part of the DRM system, discussed in chapter 3, introduces a set of metrics for identifying and quantifying hydrological regimes in streamflow records. The metrics developed here are applied to the streamflow reconstructions developed in chapter 2. A thorough analysis of the specific hydrological behavior identified along with a spatial analysis of the intensity of those hydrological phenomena as they appear in the UMRB, are presented. The third part of DRM is covered in Chapter 4, v which is a review of the entire history of the evolution of water policy and water consumption in the Delaware River Basin, specifically for the three reservoirs that serve New York City in this watershed, as a means of better understanding the demand side of water management and the factors that influence it. Finally, chapter 5 covers the fourth and final part of the DRM framework for the purposes of this dissertation, which is a constrained scenario-analysis model for determining the feasible demand space for future water management and water release policies. The constraints placed on this model are probabilistic constraints based on controlling the manifestation of risk factors to the reservoir system; namely, droughts and spills. The demand space is a set of water demand/release values that satisfy all constraints simultaneously while satisfying the needs of ecosystems and societies that demand on the water coming from the reservoir system.



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