This dissertation presents a new methodology for the sustainable and optimal allocation of water for a river basin management area that maximizes sustainable net economic benefit over the long-term planning horizon. The model distinguishes between short and long-term planning horizons and goals using a short-term modeling component (STM) and a long term modeling component (LTM) respectively. An STM optimizes a monthly allocation schedule on an annual basis in terms of maximum net economic benefit. A cost of depletion based upon Hotelling’s exhaustible resource theory is included in the STM net benefit calculation to address the non-use value of groundwater. An LTM consists of an STM for every year of the long-term planning horizon. Net economic benefits for both use and non-use values are generated by the series of STMs. In addition output from the STMs is measured in terms of sustainability which is quantified using a sustainability index (SI) with two groups of performance criteria. The first group measures risk to supply and is based on demand-supply deficits. The second group measures deviations from a target flow regime and uses a modified Hydrologic Alteration (HA) factor in the Range of Variability Approach (RVA). The STM is a linear programming (LP) model formulated in the General Algebraic Modeling System (GAMS) and the LTM is a nonlinear programming problem (NLP) solved using a genetic algorithm. The model is applied to the Prescott Active Management Area in north-central Arizona. Results suggest that the maximum sustainable net benefit is realized with a residential population and consumption rate increase in some areas, and a reduction in others.

Characterization of petroleum spill site source zones directly influences the selection of corrective action plans and frequently affects the success of remediation efforts. For example, simply knowing whether or not nonaqueous phase liquid (NAPL) is present, or if there is chemical storage in less hydraulically accessible regions, will influence corrective action planning. The overarching objective of this study was to assess if macroscopic source zone features can be inferred from dissolved concentration vs. time data. Laboratory-scale physical model studies were conducted for idealized sources; defined as Type-1) NAPL-impacted high permeability zones, Type-2) NAPL-impacted lower permeability zones, and Type-3) dissolved chemical matrix storage in lower permeability zones. Aquifer source release studies were conducted using two-dimensional stainless steel flow-through tanks outfitted with sampling ports for the monitoring of effluent concentrations and flow rates. An idealized NAPL mixture of key gasoline components was used to create the NAPL source zones, and dissolved sources were created using aqueous solutions having concentrations similar to water in equilibrium with the NAPL sources. The average linear velocity was controlled by pumping to be about 2 ft/d, and dissolved effluent concentrations were monitored daily. The Type-1 experiment resulted in a source signature similar to that expected for a relatively well-mixed NAPL source, with dissolved concentrations dependent on chemical solubility and initial mass fraction. The Type-2 and Type-3 experiments were conducted for 320 d and 190 d respectively. Unlike the Type-1 experiment, the concentration vs. time behavior was similar for all chemicals, for both source types. The magnitudes of the effluent concentrations varied between the Type-2 and Type-3 experiments, and were related to the hydrocarbon source mass. A fourth physical model experiment was performed to identify differences between ideal equilibrium behavior and the source concentration vs. time behavior observed in the tank experiments. Screening-level mathematical models predicted the general behavior observed in the experiments. The results of these studies suggest that dissolved concentration vs. time data can be used to distinguish between Type-1 sources in transmissive zones and Type-2 and Type-3 sources in lower permeability zones, provided that many years to decades of data are available. The results also suggest that concentration vs. time data alone will be insufficient to distinguish between NAPL and dissolved-phase storage sources in lower permeability regions.