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.

DEVELOPMENT OF AN OPTIMIZATION MODEL FOR BIOFUEL FACILITY SIZE AND LOCATION AND A SIMULATION MODEL FOR DESIGN OF A BIOFUEL SUPPLY CHAIN

A range of societal issues have been caused by fossil fuel consumption in the transportation sector in the United States (U.S.), including health related air pollution, climate change, the dependence on imported oil, and other oil related national security concerns. Biofuels production from various lignocellulosic biomass types such as wood, forest residues, and agriculture residues have the potential to replace a substantial portion of the total fossil fuel consumption. This research focuses on locating biofuel facilities and designing the biofuel supply chain to minimize the overall cost. For this purpose an integrated methodology was proposed by combining the GIS technology with simulation and optimization modeling methods. The GIS based methodology was used as a precursor for selecting biofuel facility locations by employing a series of decision factors. The resulted candidate sites for biofuel production served as inputs for simulation and optimization modeling. As a precursor to simulation or optimization modeling, the GIS-based methodology was used to preselect potential biofuel facility locations for biofuel production from forest biomass. Candidate locations were selected based on a set of evaluation criteria, including: county boundaries, a railroad transportation network, a state/federal road transportation network, water body (rivers, lakes, etc.) dispersion, city and village dispersion, a population census, biomass production, and no co-location with co-fired power plants. The simulation and optimization models were built around key supply activities including biomass harvesting/forwarding, transportation and storage. The built onsite storage served for spring breakup period where road restrictions were in place and truck transportation on certain roads was limited. Both models were evaluated using multiple performance indicators, including cost (consisting of the delivered feedstock cost, and inventory holding cost), energy consumption, and GHG emissions. The impact of energy consumption and GHG emissions were expressed in monetary terms to keep consistent with cost. Compared with the optimization model, the simulation model represents a more dynamic look at a 20-year operation by considering the impacts associated with building inventory at the biorefinery to address the limited availability of biomass feedstock during the spring breakup period. The number of trucks required per day was estimated and the inventory level all year around was tracked. Through the exchange of information across different procedures (harvesting, transportation, and biomass feedstock processing procedures), a smooth flow of biomass from harvesting areas to a biofuel facility was implemented. The optimization model was developed to address issues related to locating multiple biofuel facilities simultaneously. The size of the potential biofuel facility is set up with an upper bound of 50 MGY and a lower bound of 30 MGY. The optimization model is a static, Mathematical Programming Language (MPL)-based application which allows for sensitivity analysis by changing inputs to evaluate different scenarios. It was found that annual biofuel demand and biomass availability impacts the optimal results of biofuel facility locations and sizes.