SYSTEM DYNAMICS MODELING AS A QUANTITATIVE-QUALITATIVE FRAMEWORK FOR SUSTAINABLE WATER RESOURCES MANAGEMENT: INSIGHTS FOR WATER QUALITY POLICY IN THE GREAT LAKES REGION

Early water resources modeling efforts were aimed mostly at representing hydrologic processes, but the need for interdisciplinary studies has led to increasing complexity and integration of environmental, social, and economic functions. The gradual shift from merely employing engineering-based simulation models to applying more holistic frameworks is an indicator of promising changes in the traditional paradigm for the application of water resources models, supporting more sustainable management decisions. This dissertation contributes to application of a quantitative-qualitative framework for sustainable water resources management using system dynamics simulation, as well as environmental systems analysis techniques to provide insights for water quality management in the Great Lakes basin. The traditional linear thinking paradigm lacks the mental and organizational framework for sustainable development trajectories, and may lead to quick-fix solutions that fail to address key drivers of water resources problems. To facilitate holistic analysis of water resources systems, systems thinking seeks to understand interactions among the subsystems. System dynamics provides a suitable framework for operationalizing systems thinking and its application to water resources problems by offering useful qualitative tools such as causal loop diagrams (CLD), stock-and-flow diagrams (SFD), and system archetypes. The approach provides a high-level quantitative-qualitative modeling framework for "big-picture" understanding of water resources systems, stakeholder participation, policy analysis, and strategic decision making. While quantitative modeling using extensive computer simulations and optimization is still very important and needed for policy screening, qualitative system dynamics models can improve understanding of general trends and the root causes of problems, and thus promote sustainable water resources decision making. Within the system dynamics framework, a growth and underinvestment (G&U) system archetype governing Lake Allegan's eutrophication problem was hypothesized to explain the system's problematic behavior and identify policy leverage points for mitigation. A system dynamics simulation model was developed to characterize the lake's recovery from its hypereutrophic state and assess a number of proposed total maximum daily load (TMDL) reduction policies, including phosphorus load reductions from point sources (PS) and non-point sources (NPS). It was shown that, for a TMDL plan to be effective, it should be considered a component of a continuous sustainability process, which considers the functionality of dynamic feedback relationships between socio-economic growth, land use change, and environmental conditions. Furthermore, a high-level simulation-optimization framework was developed to guide watershed scale BMP implementation in the Kalamazoo watershed. Agricultural BMPs should be given priority in the watershed in order to facilitate cost-efficient attainment of the Lake Allegan's TP concentration target. However, without adequate support policies, agricultural BMP implementation may adversely affect the agricultural producers. Results from a case study of the Maumee River basin show that coordinated BMP implementation across upstream and downstream watersheds can significantly improve cost efficiency of TP load abatement.

WATER RESOURCES, HEALTH, AND THE SUSTAINABILITY OF INTERVENTIONS TO ACHIEVE WATER AND SANITATION TARGETS OF THE MILLENNIUM DEVELOPMENT GOALS IN A CHANGING WORLD

This dissertation addresses sustainability of rapid provision of safe water and sanitation required to meet the Millennium Development Goals. Review of health-related literature and global statistics demonstrates engineers' role in achieving the MDGs. This review is followed by analyses relating to social, environmental, and health aspects of meeting MDG targets. Analysis of national indicators showed that inadequate investment, poor or nonexistent policies and governance are challenges to global sanitation coverage in addition to lack of financial resources and gender disparity. Although water availability was not found to be a challenge globally, geospatial analysis demonstrated that water availability is a potentially significant barrier for up to 46 million people living in urban areas and relying on already degraded water resources for environmental income. A daily water balance model incorporating the National Resources Conservation Services curve number method in Bolivian watersheds showed that local water stress is linked to climate change because of reduced recharge. Agricultural expansion in the region slightly exacerbates recharge reductions. Although runoff changes will range from -17% to 14%, recharge rates will decrease under all climate scenarios evaluated (-14% to -27%). Increasing sewer coverage may place stress on the readily accessible natural springs, but increased demand can be sustained if other sources of water supply are developed. This analysis provides a method for hydrological analysis in data scarce regions. Data required for the model were either obtained from publicly available data products or by conducting field work using low-cost methods feasible for local participants. Lastly, a methodology was developed to evaluate public health impacts of increased household water access resulting from domestic rainwater harvesting, incorporating knowledge of water requirements of sanitation and hygiene technologies. In 37 West African cities, domestic rainwater harvesting has the potential to reduce diarrheal disease burden by 9%, if implemented alone with 400 L storage. If implemented in conjunction with point of use treatment, this reduction could increase to 16%. The methodology will contribute to cost-effectiveness evaluations of interventions as well as evaluations of potential disease burden resulting from reduced water supply, such as reductions observed in the Bolivian communities.

INTERACTIVE CONTROLS OF WATER TABLE POSITION AND PLANT FUNCTIONAL TYPES ON PEAT POREWATER CHARACTER IN NORTHERN BOG ECOSYSTEMS: IMPLICATIONS FOR CARBON CYCLING DYNAMICS

Northern wetlands, and particularly peatlands, have been shown to store around 30% of the world's soil carbon and thus play a significant role in the carbon cycle of our planet. Changes in climate are altering peatland hydrology and vegetation communities. These changes are possibly resulting in declines in the ability of peatlands to sequester carbon because losses through carbon oxidation and mineralization are likely to increase relative to C inputs from net primary production in a warmer, drier climate. However, the consequences of interactive effects of altered hydrology and vegetation on carbon storage are not well understood. This research evaluated the importance of plant species, water table, and their interactive effects on porewater quality in a northern peatland with an average pH of 4.54, ranging from 4.15 to 4.8. We assessed the effects of plant functional group (ericaceous shrubs, sedges, and bryophytes) and water table position on biogeochemical processes. Specifically, we measured dissolved organic carbon (DOC), total dissolved nitrogen (TDN), potential enzyme activity, organic acids, anions and cations, spectral indexes of aromaticity, and phenolic content. Our results indicate that acetate and propionate concentrations in the sedge-dominated communities declined with depth and water table drawdown, relative to the control and ericaceous treatments. DOC increased in the lowered water table treatments in all vegetation community types, and the peat porewater C:N ratio declined in the sedge-dominated treatments when the water table was lowered. The relationship between DOC and ferrous iron showed significant responses to vegetation type; the exclusion of Ericaceae resulted in less ferrous iron per unit DOC compared to mixed species treatments and Ericaceae alone. This observation was corroborated with higher mean oxidation redox potential profiles (integrating 20, 40, and 70 cm) measured in the sedge treatments, compared with the mixed and Ericaceae species treatments over a growing season. Enzymatic activities did not show as strong of a response to treatments as expected; the oxidative enzyme peroxidase and the hydrolytic enzyme phosphatase were the only enzymes to respond to water table, where the potential activity of both enzymes increased with water table drawdown. Overall, there were significant interactive effects between changes in vegetation and water table position on peat porewater composition. These data suggest that vegetation effects on oxidation reduction potentials and peat porewater character can be as important as water table position in northern bog ecosystems.

Perceptions of water conditions and management in the Sonora River Basin, Sonora, Mexico

The effects of climate change are expected to be very severe in arid regions. The Sonora River Basin, in the northwestern state of Sonora, Mexico, is likely to be severely affected. Some of the anticipated effects include precipitation variability, intense storm events, higher overall temperatures, and less available water. In addition, population in Sonora, specifically the capital city of Hermosillo, is increasing at a 1.5% rate and current populations are near 700,000. With the reduction in water availability and an increase in population, Sonora, Mexico is expected to experience severe water resource issues in the near future. In anticipation of these changes, research is being conducted in an attempt to improve water management in the Sonora River Basin, located in the northwestern part of Sonora. This research involves participatory modeling techniques designed to increase water manager awareness of hydrological models and their use as integrative tools for water resource management. This study was conducted as preliminary research for the participatory modeling grant in order to gather useful information on the population being studied. This thesis presents research from thirty-four in-depth interviews with water managers, citizens, and agricultural producers in Sonora, Mexico. Data was collected on perceptions of water quantity and quality in the basin, thoughts on current water management practices, perceptions of climate change and its management, experience with, knowledge of, and trust in hydrological models as water management tools. Results showed that the majority of interviewees thought there was not enough water to satisfy their daily needs. Most respondents also agreed that the water available was of good quality, but that current management of water resources was ineffective. Nearly all interviewees were aware of climate change and thought it to be anthropogenic. May reported experiencing higher temperatures, precipitation changes, and higher water scarcity and attributed those fluctuations to climate change. 65% of interviewees were at least somewhat familiar with hydrological models, though only 28% had ever used them or their output. Even with model usage results being low, 100% of respondents believed hydrological models to be very useful water management tools. Understanding how water, climate change, and hydrological models are perceived by this population of people is essential to improving their water management practices in the face of climate change.

Human and embodied energy analysis applied to water source protection and household water treatment interventions used in Mali, West Africa

As water quality interventions are scaled up to meet the Millennium Development Goal of halving the proportion of the population without access to safe drinking water by 2015 there has been much discussion on the merits of household- and source-level interventions. This study furthers the discussion by examining specific interventions through the use of embodied human and material energy. Embodied energy quantifies the total energy required to produce and use an intervention, including all upstream energy transactions. This model uses material quantities and prices to calculate embodied energy using national economic input/output-based models from China, the United States and Mali. Embodied energy is a measure of aggregate environmental impacts of the interventions. Human energy quantifies the caloric expenditure associated with the installation and operation of an intervention is calculated using the physical activity ratios (PARs) and basal metabolic rates (BMRs). Human energy is a measure of aggregate social impacts of an intervention. A total of four household treatment interventions – biosand filtration, chlorination, ceramic filtration and boiling – and four water source-level interventions – an improved well, a rope pump, a hand pump and a solar pump – are evaluated in the context of Mali, West Africa. Source-level interventions slightly out-perform household-level interventions in terms of having less total embodied energy. Human energy, typically assumed to be a negligible portion of total embodied energy, is shown to be significant to all eight interventions, and contributing over half of total embodied energy in four of the interventions. Traditional gender roles in Mali dictate the types of work performed by men and women. When the human energy is disaggregated by gender, it is seen that women perform over 99% of the work associated with seven of the eight interventions. This has profound implications for gender equality in the context of water quality interventions, and may justify investment in interventions that reduce human energy burdens.

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.

AGENT BASED, DISTRIBUTED CONTROL STRATEGIES AND OPTIMIZATION OF PLUG-IN ELECTRIC VEHICLES ON SMART/MICROGRID ARCHITECTURES

This thesis will present strategies for the use of plug-in electric vehicles on smart and microgrids. MATLAB is used as the design tool for all models and simulations. First, a scenario will be explored using the dispatchable loads of electric vehicles to stabilize a microgrid with a high penetration of renewable power generation. Grid components for a microgrid with 50% photovoltaic solar production will be sized through an optimization routine to maintain storage system, load, and vehicle states over a 24-hour period. The findings of this portion are that the dispatchable loads can be used to guard against unpredictable losses in renewable generation output. Second, the use of distributed control strategies for the charging of electric vehicles utilizing an agent-based approach on a smart grid will be studied. The vehicles are regarded as additional loads to a primary forecasted load and use information transfer with the grid to make their charging decisions. Three lightweight control strategies and their effects on the power grid will be presented. The findings are that the charging behavior and peak loads on the grid can be reduced through the use of distributed control strategies.