Use of hydroclimatic forecasts for improved water management in central Texas

Accurate seasonal to interannual streamflow forecasts based on climate information are critical for optimal management and operation of water resources systems. Considering most water supply systems are multipurpose, operating these systems to meet increasing demand under the growing stresses of climate variability and climate change, population and economic growth, and environmental concerns could be very challenging. This study was to investigate improvement in water resources systems management through the use of seasonal climate forecasts. Hydrological persistence (streamflow and precipitation) and large-scale recurrent oceanic-atmospheric patterns such as the El Niño/Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), the Atlantic Multidecadal Oscillation (AMO), the Pacific North American (PNA), and customized sea surface temperature (SST) indices were investigated for their potential to improve streamflow forecast accuracy and increase forecast lead-time in a river basin in central Texas. First, an ordinal polytomous logistic regression approach is proposed as a means of incorporating multiple predictor variables into a probabilistic forecast model. Forecast performance is assessed through a cross-validation procedure, using distributions-oriented metrics, and implications for decision making are discussed. Results indicate that, of the predictors evaluated, only hydrologic persistence and Pacific Ocean sea surface temperature patterns associated with ENSO and PDO provide forecasts which are statistically better than climatology. Secondly, a class of data mining techniques, known as tree-structured models, is investigated to address the nonlinear dynamics of climate teleconnections and screen promising probabilistic streamflow forecast models for river-reservoir systems. Results show that the tree-structured models can effectively capture the nonlinear features hidden in the data. Skill scores of probabilistic forecasts generated by both classification trees and logistic regression trees indicate that seasonal inflows throughout the system can be predicted with sufficient accuracy to improve water management, especially in the winter and spring seasons in central Texas. Lastly, a simplified two-stage stochastic economic-optimization model was proposed to investigate improvement in water use efficiency and the potential value of using seasonal forecasts, under the assumption of optimal decision making under uncertainty. Model results demonstrate that incorporating the probabilistic inflow forecasts into the optimization model can provide a significant improvement in seasonal water contract benefits over climatology, with lower average deficits (increased reliability) for a given average contract amount, or improved mean contract benefits for a given level of reliability compared to climatology. The results also illustrate the trade-off between the expected contract amount and reliability, i.e., larger contracts can be signed at greater risk.

Berry-Esseen bounds for nonlinear statistics, and asymptotic relative efficiency between correlation statistics

Four papers, written in collaboration with the author’s graduate school advisor, are presented. In the first paper, uniform and non-uniform Berry-Esseen (BE) bounds on the convergence to normality of a general class of nonlinear statistics are provided; novel applications to specific statistics, including the non-central Student’s, Pearson’s, and the non-central Hotelling’s, are also stated. In the second paper, a BE bound on the rate of convergence of the F-statistic used in testing hypotheses from a general linear model is given. The third paper considers the asymptotic relative efficiency (ARE) between the Pearson, Spearman, and Kendall correlation statistics; conditions sufficient to ensure that the Spearman and Kendall statistics are equally (asymptotically) efficient are provided, and several models are considered which illustrate the use of such conditions. Lastly, the fourth paper proves that, in the bivariate normal model, the ARE between any of these correlation statistics possesses certain monotonicity properties; quadratic lower and upper bounds on the ARE are stated as direct applications of such monotonicity patterns.

Effect of high order interpolation in the stability and efficiency of the time-integration process in vorticity-velocity CFD algorithms

The numerical solution of the incompressible Navier-Stokes Equations offers an effective alternative to the experimental analysis of Fluid-Structure interaction i.e. dynamical coupling between a fluid and a solid which otherwise is very complex, time consuming and very expensive. To have a method which can accurately model these types of mechanical systems by numerical solutions becomes a great option, since these advantages are even more obvious when considering huge structures like bridges, high rise buildings, or even wind turbine blades with diameters as large as 200 meters. The modeling of such processes, however, involves complex multiphysics problems along with complex geometries. This thesis focuses on a novel vorticity-velocity formulation called the KLE to solve the incompressible Navier-stokes equations for such FSI problems. This scheme allows for the implementation of robust adaptive ODE time integration schemes and thus allows us to tackle the various multiphysics problems as separate modules. The current algorithm for KLE employs a structured or unstructured mesh for spatial discretization and it allows the use of a self-adaptive or fixed time step ODE solver while dealing with unsteady problems. This research deals with the analysis of the effects of the Courant-Friedrichs-Lewy (CFL) condition for KLE when applied to unsteady Stoke’s problem. The objective is to conduct a numerical analysis for stability and, hence, for convergence. Our results confirmthat the time step ∆t is constrained by the CFL-like condition ∆t ≤ const. hα, where h denotes the variable that represents spatial discretization.

Functional ZnO nanostructures for electronic and energy applications

ZnO has proven to be a multifunctional material with important nanotechnological applications. ZnO nanostructures can be grown in various forms such as nanowires, nanorods, nanobelts, nanocombs etc. In this work, ZnO nanostructures are grown in a double quartz tube configuration thermal Chemical Vapor Deposition (CVD) system. We focus on functionalized ZnO Nanostructures by controlling their structures and tuning their properties for various applications. The following topics have been investigated: 1. We have fabricated various ZnO nanostructures using a thermal CVD technique. The growth parameters were optimized and studied for different nanostructures. 2. We have studied the application of ZnO nanowires (ZnONWs) for field effect transistors (FETs). Unintentional n-type conductivity was observed in our FETs based on as-grown ZnO NWs. We have then shown for the first time that controlled incorporation of hydrogen into ZnO NWs can introduce p-type characters to the nanowires. We further found that the n-type behaviors remained, leading to the ambipolar behaviors of hydrogen incorporated ZnO NWs. Importantly, the detected p- and n- type behaviors are stable for longer than two years when devices were kept in ambient conditions. All these can be explained by an ab initio model of Zn vacancy-Hydrogen complexes, which can serve as the donor, acceptors, or green photoluminescence quencher, depend on the number of hydrogen atoms involved. 3. Next ZnONWs were tested for electron field emission. We focus on reducing the threshold field (Eth) of field emission from non-aligned ZnO NWs. As encouraged by our results on enhancing the conductivity of ZnO NWs by hydrogen annealing described in Chapter 3, we have studied the effect of hydrogen annealing for improving field emission behavior of our ZnO NWs. We found that optimally annealed ZnO NWs offered much lower threshold electric field and improved emission stability. We also studied field emission from ZnO NWs at moderate vacuum levels. We found that there exists a minimum Eth as we scale the threshold field with pressure. This behavior is explained by referring to Paschen’s law. 4. We have studied the application of ZnO nanostructures for solar energy harvesting. First, as-grown and (CdSe) ZnS QDs decorated ZnO NBs and ZnONWs were tested for photocurrent generation. All these nanostructures offered fast response time to solar radiation. The decoration of QDs decreases the stable current level produced by ZnONWs but increases that generated by NBs. It is possible that NBs offer more stable surfaces for the attachment of QDs. In addition, our results suggests that performance degradation of solar cells made by growing ZnO NWs on ITO is due to the increase in resistance of ITO after the high temperature growth process. Hydrogen annealing also improve the efficiency of the solar cells by decreasing the resistance of ITO. Due to the issues on ITO, we use Ni foil as the growth substrates. Performance of solar cells made by growing ZnO NWs on Ni foils degraded after Hydrogen annealing at both low (300 °C) and high (600 °C) temperatures since annealing passivates native defects in ZnONWs and thus reduce the absorption of visible spectra from our solar simulator. Decoration of QDs improves the efficiency of such solar cells by increasing absorption of light in the visible region. Using a better electrolyte than phosphate buffer solution (PBS) such as KI also improves the solar cell efficiency. 5. Finally, we have attempted p-type doping of ZnO NWs using various growth precursors including phosphorus pentoxide, sodium fluoride, and zinc fluoride. We have also attempted to create p-type carriers via introducing interstitial fluorine by annealing ZnO nanostructures in diluted fluorine gas. In brief, we are unable to reproduce the growth of reported p-type ZnO nanostructures. However; we have identified the window of temperature and duration of post-growth annealing of ZnO NWs in dilute fluorine gas which leads to suppression of native defects. This is the first experimental effort on post-growth annealing of ZnO NWs in dilute fluorine gas although this has been suggested by a recent theory for creating p-type semiconductors. In our experiments the defect band peak due to native defects is found to decrease by annealing at 300 °C for 10 – 30 minutes. One of the major future works will be to determine the type of charge carriers in our annealed ZnONWs.

Enhancement of heterologous expression of alkaline phytase in Pichia pastors

Phytic acid is the major storage form of phosphorus and inositol in seeds and legumes. It forms insoluble phytate salts by chelating with positively charged mineral ions. Non-ruminant animals are not able to digest phytate due to the lack of phytases in their GI tracks, thus the undigested phytate is excreted leading to environmental contamination. Supplementation with phytases in animal feed has proven to be an effective strategy to alleviate nutritional and environmental issues. The unique catalytic and thermal stability properties of alkaline phytase from lily pollen (LlALP) suggest that it has the potential to be useful as a feed supplement. Our goal is to develop a method for the production of substantial amounts of rLlALP for animal feed and structural studies. rLlALP2 has been successfully expressed in the yeast, Pichia pastoris. However, expression yield was modest (8-10 mg/L). Gene copy number has been identified as an important parameter in enhancing protein yields. Multicopy clones were selected using Zeocin-resistance-based vectors and challenging transformants to high Zeocin levels under different conditions. Data indicate that increasing selection pressure led to the generation of clones with amplification of both rLlAlp2 and Zeor genes and the two genes were not equally amplified. Additionally, clones generated by step-wise methods led to clones with greater amplification. The effects of transgene copy number and gene sequence optimization on expression levels of rLlALP2 were examined. The data indicate that increasing the copy number of rLlAlp2 in transformed clones was detrimental to expression level. The use of a sequence-optimized rLlAlp2 (op-rLlAlp2) increased expression yield of the active enzyme by 25-50%, suggesting that transcription and translation efficiency are not major bottlenecks in the production of rLlALP2. Lowering induction temperature to 20 oC led to an increase in enzyme activity of 1.2 to 20-fold, suggesting that protein folding or post-translational processes may be limiting factors for rLlALP2 production. Cumulatively, optimization of copy number, gene sequence optimization and reduced temperature led to increase of rLlALP2 enzyme activity by three-fold (25-30 mg/L). In an effort to simplify the purification process of rLlALP2, extracellular expression of phytase was investigated. Extracellular expression is dependent on the presence of an appropriate secretion signal upstream of the transgene native signal peptide(s) present in the transgene may also influence secretion efficiency. The data suggest that deletion of both N- and C-terminal signal peptides of rLlALP2 enhanced α-mating factor (α-MF)-driven secretion of LlALP2 by four-fold. The secretion signal peptide of chicken egg white lysozyme was ineffective in secretion rLlALP2 in P. pastoris. To enhance rLlALP2 secretion, effectiveness of the strong inducible promoter (PAOX1) was compared with the constitutive promoter (PGAP). The intracellular yield of rLlALP2 was about four-fold greater under the control of PGAP compared to PAOX1 and extracellular expression level of rLlALP2 was around eight-fold (75-100 mg/L) greater. The successful production of active rLlALP2 in P. pastoris will allow us to conduct the animal feed supplementation studies and structural studies.

RESPONSE OF ECTOMYCORRHIZAL FUNGI TO INORGANIC AND ORGANIC FORMS OF NITROGEN AND PHOSPHORUS

The nutrient uptake response of ectomycorrhizal fungi (ECM) to different nutrient substrates is a driving force in ecosystem nutrient cycling. We hypothesized that taxa from low nitrogen (N) soils would be more likely to use organic N compared to taxa from high N soils, and that taxa from high N would be more likely to use organic phosphorus (P) sources when compared to the ECM dominant in low N soils. This study focuses on the growth response of ECM species collected over a N gradient to different forms of N and P nutrient substrates and whether ECM growth in a particular nutrient source can be related to how the ECM fungi have responded to elevated N in the field. This study found a mixed ECM response to organic and inorganic N and P treatments. High affinity N taxa expected to respond positively to inorganic N produced the phosphatase enzyme to take up organic phosphorus, but not all low affinity N taxa expected to negatively respond to organic P produced the protease enzyme to take up organic N. Interspecific variability was displayed by some high and low affinity N taxa responded and ECM intraspecific variability in response to N and P treatments was also noted. Future analysis of may show more evident ECM response patterns to inorganic and organic forms of N and P.

THE USE OF LIFE-CYCLE ANALYSIS TO REDUCE THE ENVIRONMENTAL IMPACT OF MATERIALS IN MANUFACTURING

This thesis is composed of three life-cycle analysis (LCA) studies of manufacturing to determine cumulative energy demand (CED) and greenhouse gas emissions (GHG). The methods proposed could reduce the environmental impact by reducing the CED in three manufacturing processes. First, industrial symbiosis is proposed and a LCA is performed on both conventional 1 GW-scaled hydrogenated amorphous silicon (a-Si:H)-based single junction and a-Si:H/microcrystalline-Si:H tandem cell solar PV manufacturing plants and such plants coupled to silane recycling plants. Using a recycling process that results in a silane loss of only 17 versus 85 percent, this results in a CED savings of 81,700 GJ and 290,000 GJ per year for single and tandem junction plants, respectively. This recycling process reduces the cost of raw silane by 68 percent, or approximately $22.6 and $79 million per year for a single and tandem 1 GW PV production facility, respectively. The results show environmental benefits of silane recycling centered around a-Si:H-based PV manufacturing plants. Second, an open-source self-replicating rapid prototype or 3-D printer, the RepRap, has the potential to reduce the environmental impact of manufacturing of polymer-based products, using distributed manufacturing paradigm, which is further minimized by the use of PV and improvements in PV manufacturing. Using 3-D printers for manufacturing provides the ability to ultra-customize products and to change fill composition, which increases material efficiency. An LCA was performed on three polymer-based products to determine the CED and GHG from conventional large-scale production and are compared to experimental measurements on a RepRap producing identical products with ABS and PLA. The results of this LCA study indicate that the CED of manufacturing polymer products can possibly be reduced using distributed manufacturing with existing 3-D printers under 89% fill and reduced even further with a solar photovoltaic system. The results indicate that the ability of RepRaps to vary fill has the potential to diminish environmental impact on many products. Third, one additional way to improve the environmental performance of this distributed manufacturing system is to create the polymer filament feedstock for 3-D printers using post-consumer plastic bottles. An LCA was performed on the recycling of high density polyethylene (HDPE) using the RecycleBot. The results of the LCA showed that distributed recycling has a lower CED than the best-case scenario used for centralized recycling. If this process is applied to the HDPE currently recycled in the U.S., more than 100 million MJ of energy could be conserved per annum along with significant reductions in GHG. This presents a novel path to a future of distributed manufacturing suited for both the developed and developing world with reduced environmental impact. From improving manufacturing in the photovoltaic industry with the use of recycling to recycling and manufacturing plastic products within our own homes, each step reduces the impact on the environment. The three coupled projects presented here show a clear potential to reduce the environmental impact of manufacturing and other processes by implementing complimenting systems, which have environmental benefits of their own in order to achieve a compounding effect of reduced CED and GHG.