Date of Award:

2015

Document Type:

Dissertation

Degree Name:

Doctor of Philosophy (PhD)

Department:

Civil and Environmental Engineering

Advisor/Chair:

Richard C. Peralta

Abstract

Decision makers' conflicts about the validity of a single simulation model and inefficiencies of existing response matrix methods (RMM) hinder adopting successful groundwater management plans. We speed up the process by proposing a hybrid RMM that is most efficient for situations in which optimizable stimuli can vary through consecutive periods of uniform duration interspersed with periods of different duration. We use the hybrid RMM within Simulation-Optimization (S-O) models to develop optimal water management strategies. For the tested problems, the hybrid RMM requires as much or 63-89% less computation time than other RMMs.

Second, we propose Multi-Conceptual Model Optimization (MCMO) that can help stakeholders reach a compromise strategy instead of agreeing on the validity of a single model. MCMO computes optimal strategies that simultaneously satisfy analogous constraints and bounds in multiple numerical models differing by more than parameter values. Applying MCMO to Cache Valley (Utah, USA) reveals that protecting local ecosystem limits the increased groundwater pumping to satisfy only 40% of projected water demand increase using two models.

To successfully and sustainably manage Cache Valley aquifer, we evaluate sustained yield strategies (SYS) and quantify the resilience of a computed SYS. We maximize the number of new residents who can have their indoor and outdoor uses satisfied, subject to constraints on aquifer-surface waters conditions, and limiting new residents to projected increases in population (PIiP). furthermore, we examine the effect of optimization approach and sequiencing, temporally-lagged spatially distributed return flow that is a function of optimal groundwater use, and the acceptability time evaluation on the optimal yield strategy. Cache Valley aquifer can sustainably satisfy the outdoor water demand of 74%-83% and the indoor water demand of 83%-100% of the PIiP. We quantify deterministic resilience Rd(A,T,SV)=P to evaluate how completely an aquifer condition (SV) recovers after the end of climatic anomaly (A), by recovery time (T). Simulation predicts that Cache Valley aquifer system resiliences to a 2-year drought are Rd(2YD, 3 yrs, Overall) = 93% and Rd (2YD,≥8,Overall) ≥ 95%. Proportionally reducing pumping rates by 25% through the time horizon of the simulation increases the overall resilience to 96% within 3 years.

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