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The precipitation data of the El Alto, Tambillo and Comanche stations are homogenous and consistent. The meteorological data from Irpa Chico, Collana and Viacha are consistent, but heterogeneous. The monthly precipitation in Viacha in December, January, March and April are better examples of a normal distribution in comparison to the months of October, November and February. The average annual precipitation in Viacha, in a thirty-four year time period, is 559 mm. Some 76% of this precipitation occurs in November to March. The minimum precipitation in Viacha, with an 80% probability of absence for the vegetative period, from October to April is 269mm. January is the month with the most precipitation (75 mm). The estimated potential of evaporation-transpiration with the Penmen-Monteith method is 1,168 mm a year. October constitutes the month with the greatest value of ETP (116mm). The maximum volume of food storage in the Calacalani Lagoon is 137,000 m3, with annual losses of 48,218 m3. 82% of these losses are due to evaporation and 18% due to infiltration. The usable water volume, taking into account the conservation of 30% of the total volume in order to maintain the aquatic fauna and flora, is 47,740 m3. With some exceptions, the quality of the water is suitable for livestock consumption and with an estimated irrigation capacity of 7-11 hectares per year. The Jacha Jahuira River- Pallina transports an average volume of 38.5x106 m3 annually. This presents serious restrictions for water use in agricultural irrigation and human consumption. The use of the River's water for agricultural purposes has been conditioned for special handling operations, which can reach an irrigational surface of 5,199-8,665 hectares/year. The ground water level may vary from 3,867-3,843 m over that of the ocean level. This presents a fluctuation of 1.2 m in the deep valley receptors of the Letanias hill country and 0.1 m in the community presented an average flow of 0.13 l/s, which represents a volume of 4,100 m3/year. The artesian or subterranean water represents an interesting potential for its quality as well as its availability of 788,000 m3/year of volume. With 12 hours of daily pumping of this water, some 53-88 hectares/year are suitable for irrigation. This is in spite of the fact that the lack of infrastructure has provoked the abandonment of deeply excavated wells, estimating an annual lose of 145,00 m3. Artesian water has no restriction in quality, for animal and human consumption or for irrigation purposes. Some ground water wells have been restricted for human use, due to bacterial contamination. The Choquenaira Community is located in the middle valley of the Jacha Jahuira-Pallina. In the high valley the reduction of vegetation coverage is being observed, that when combined with seasonal rains, provokes water erosion and the transportation of sediment through drainage; Estimating an average transportation of 104 TM of sediments in suspension, especially during the rainy seasons (December-March). In the lower valley severe biological contamination (for human consumption) has been detected. This is due to the discharge of service water from the Viacha City sewer system and the Laja population; and so the sediment accumulation, increasing the risk of overflow and flooding. Extreme events, such as flooding that exceed 50 million m3 of annual drainage, have happened four times in 52 years; which is approximately every 13 years. There is an annual 76% probability that a major event will not occur. The micro-region of the Choquenaria covers a total area of 2,126 hectares. Some 12% (262 hectares) are covered with pastures in a humid environment and temporarily or permanently flooded areas (bofedales, and fertile plains); 19% (401 hectares) are covered steeps, shrubs, and rocky outcrops with strong inclines; 69% (1,463 hectares) correspond to dry land cultivations, pastures, and or bushes that lack distinction. The highest quality springs are used for human consumption, which is estimated to be 10 liters/inhabitant/day, representing an overall community consumption of 594 m3/year (148 inhabitants). This level of consumption is low in comparison to that of the Bolivian, 30-50 l/habitant/day, which is due to the difficulty in accessing the water source. With an average cattle possession in a family being five bovines and 40 ovine, the average consumption is from 450 l/possession/day. This represents an annual consumption of 10,374 m3 used for livestock water in the Choquenaira Community. The surface that undergoes irrigation in the winter does not exceed 600 m2, which is a surface that needs 440 m3/year. The requirement or unitary demand for a cultivation system, consisting of barley (57%), potato (28.6%), and alfalfa (14.4%) in the Choquenaira Community is about 4,443 m3/hectares/year, assuming an irrigation efficiency of 100% and 7,405 m3/hectares/year with a 60% efficiency using a surface irrigation system. The inhabitants of the community use an operational strategy of national resources (ground, water, cultivations, etc.) on the basis of availability and incidence of climatic resources, with the use of local ecological indicators to predict the climate. The commoners seek the reduction of agricultural risk, through specialization in hydric cultivation (dry farming) crops, the spatial operations (epochs), water conservation (water gathering) and the diversification of fountains/springs. There are oftentimes-distinct gender roles in the community. Agriculture is considered a productive activity, in which men play the dominant role. Whereas the women play a fundamental role in obtaining water, especially that which is used in human and animal consumption. The overall offering of the local hydraulic system, composed of the contribution of the Jacha Jahuira River, Calacalani Lagoon, the ground water, and artesian wells, is 39.3 million meters cubed per year. The actual demand of the community, that includes human and animal consumption as well as the irrigation in winter pastures, reaches 11,381m3/year. The potential demand, that includes both human and animal consumption, irrigation in winter pastures and the supplementary irrigation of dry farming, reaches 3.2 million meters cubed per year. The local hydraulic system offers volumes of water, sufficient enough to meet the community's actual and potential demand. However, its contamination and difficulty to access has caused the inhabitants to develop spatial and temporary strategies in order to access the water. The commoners consider the developments of these hydric resources, especially that of human consumption, as a short and long term necessity.

Global sea surface temperature (SST) anomalies have a demonstrable effect on terrestrial climate dynamics throughout the continental U.S. SST variations have been correlated with greenness (vegetation densities) and precipitation via ocean-atmospheric interactions known as climate teleconnections. Prior research has demonstrated that teleconnections can be used for climate prediction across a wide region at sub-continental scales. Yet these studies tend to have large uncertainties in estimates by utilizing simple linear analyses to examine chaotic teleconnection relationships. Still, non-stationary signals exist, making teleconnection identification difficult at the local scale. Part 1 of this research establishes short-term (10-year), linear and non-stationary teleconnection signals between SST at the North Atlantic and North Pacific oceans and terrestrial responses of greenness and precipitation along multiple pristine sites in the northeastern U.S., including (1) White Mountain National Forest - Pemigewasset Wilderness, (2) Green Mountain National Forest - Lye Brook Wilderness and (3) Adirondack State Park - Siamese Ponds Wilderness. Each site was selected to avoid anthropogenic influences that may otherwise mask climate teleconnection signals. Lagged pixel-wise linear teleconnection patterns across anomalous datasets found significant correlation regions between SST and the terrestrial sites. Non-stationary signals also exhibit salient co-variations at biennial and triennial frequencies between terrestrial responses and SST anomalies across oceanic regions in agreement with the El Nino Southern Oscillation (ENSO) and North Atlantic Oscillation (NAO) signals. Multiple regression analysis of the combined ocean indices explained up to 50% of the greenness and 42% of the precipitation in the study sites. The identified short-term teleconnection signals improve the understanding and projection of climate change impacts at local scales, as well as harness the interannual periodicity information for future climate projections. Part 2 of this research paper builds upon the earlier short-term study by exploring a long-term (30-year) teleconnection signal investigation between SST at the North Atlantic and Pacific oceans and the precipitation within Adirondack State Park in upstate New York. Non-traditional teleconnection signals are identified using wavelet decomposition and teleconnection mapping specific to the Adirondack region. Unique SST indices are extracted and used as input variables in an artificial neural network (ANN) prediction model. The results show the importance of considering non-leading teleconnection patterns as well as the known teleconnection patterns. Additionally, the effects of the Pacific Ocean SST or the Atlantic Ocean SST on terrestrial precipitation in the study region were compared with each other to deepen the insight of sea-land interactions. Results demonstrate reasonable prediction skill at forecasting precipitation trends with a lead time of one month, with r values of 0.6. The results are compared against a statistical downscaling approach using the HadCM3 global circulation model output data and the SDSM statistical downscaling software, which demonstrate less predictive skill at forecasting precipitation within the Adirondacks.

Hexavalent chromium is an extremely carcinogenic chemical that has been widely produced in the United States. This has led to major waste contamination and pollution throughout the country. According to the Environmental Working Group Hexavalent chromium has been found in 89% of city tap water. Most people believe they are safe using regular home filter systems however that is not true. A more expensive ion exchange water treatment unit is required. Therefore to protect yourselves from this carcinogenic metal a reliable test is required. In this study we have developed a Zinc Sulfide Manganese doped Quantum Rod technology to detect for presence of chromate and other harmful transitional metals in drinking water. Quantum Rods were synthesized using a hydrothermal reaction method. They were fully characterized using UV-visible absorption spectroscopy, fluorescence emission spectroscopy, X-ray Photoelectric Spectroscopy (XPS) and High Resolution Transmission Electron Microscopy (HRTEM). Quantum Rod metal detection studies were done with 28 different ions in a 96-well fluorescent plate reader. Results show that highest sensitivity to 8 ions including the toxic ions of chromate and mercury allowing us to create a sensor to detect these items.

Modern streamflow measuring equipment, water quality sampling techniques and a better understanding of pollutant washoff are continuously being developed as today's society is in critical need of improving water management, minimizing developmental impacts and preventing environmental hazards. In particular, the study of the spatial, temporal and volumetric characteristics of annual pollutant loading caused by variations in precipitation, land use and other anthropogenic factors is of great significance due to their relation to future global water demands. The research presented here falls in three parts. In the first part of the dissertation, an acoustical Doppler velocity profiler installed in a submerged concrete channel is proposed to continually measure the annual fluctuation in streamflow levels down to dry channel conditions. The tailwater influenced, intermittent streamflow conditions for the City of Kissimmee, Florida were selected for the evaluation of this approach under a 3-year study from 2006 to 2008. The performance of these concrete channels were systematically evaluated by comparisons with established field measurement techniques over various stream configurations and flow conditions. The second part of this research investigates the dynamics of flood wave detection with respect to enabling an automatic water quality sampler to start collecting samples. The main focus was on the accurate detection of flood waves in the absence of rainfall and the presence of fluctuating baseflows and stream stages. In the 3-year study, it was shown that a dual parameter trigger, utilizing independent measuring equipment, resulted in accurate flood wave detection with minimal false triggering of the autosampler. In addition, an incremental or percent deviation from a moving average of stage or flow proved to be a more consistent indicator for the presence of a flood wave. In the third part of this work, the frequency of water quality sampling and the associated level of detail for sampling of rainfall events were investigated with respect to accurately depicting annual pollutant loads. It was found that the seasonal variations in baseflow pollutant loads are not accurately represented by current 4-quarter grab sampling. Also, significant pollutant loading within rainfall events may not be captured by only performing grab sampling during baseflow conditions. In addition, although increased pollutant concentrations were observed within the initial 30 minutes of the flood wave, their actual loadings did not represent a significant impact on the annual pollutant loads. A biweekly grab sampling frequency was found to be adequate in many cases to depict the annual pollutant loads, but depending upon the targeted constituent and particular streamflow condition, rainfall event sampling might also be necessary. The results of this research complemented with other studies will promote better understanding of intermittent streamflows, accurate flood wave detection, and assessment of annual pollutant loads to our nation's waterbodies.

Research into the use of LiDAR data for purposes other than simple topographic elevation determination, such as urban land cover classification and the identification of forest biomass, has become prominent in recent years. In many cases, alternative analysis methodologies conducted using airborne LiDAR data are possible because the raw data collected during a survey can include information other than the classically used elevation and coordinate points, the X, Y, and Z of the plane. In particular, intensity return values for each point in a LiDAR grid have been found to provide a useful data set for wet and dry channel classification. LiDAR intensity return data are, in essence, a numeric representation of the characteristic light reflectivity of the object being scanned; the more reflective the object is, the higher the intensity return will be. Intensity data points are collected along the course of the channel network and within the perceived banks of the channel. Intensity data do not crisply reflect a perfectly wet or dry condition, but instead vary over a range such that each location can be viewed as partially wet and partially dry. It is advantageous to assess problems of this type using the methods of fuzzy logic. Specifically, the variance in LiDAR intensity return data is such that the use of fuzzy logic to identify intensity cluster centers, and thereby assign wet and dry condition identifiers based on fuzzy memberships, is a possibility. Membership within a fuzzy data set is characterized by a value representing the degree of membership. Typically, membership values range from 0 (representing non-membership) through 1 (representing full membership), with many observations found to be not at either extreme but instead at some intermediate value representing partial membership. The ultimate goal of this research was to design and develop an automated algorithm to identify wet and dry channel sections, given a previously identified channel network based on topographic elevation, using a combination of intensity return values from LiDAR data and fuzzy logic clustering methods, and to implement that algorithm in such a way as to produce reliable multi-class channel segments in ArcGIS. To enable control of calculations, limiting parameters were defined, specifically including the maximum allowable bank slope, and a filtering percentage to more accurately accommodate the study area. Alteration of the maximum allowable bank slope has been shown to affect the comparative quantity of high and low intensity centroids, but only in extreme bank slope conditions are the centroids changed enough to hamper results. However, interference from thick vegetation has been shown to lower intensity values in dry channel sections into the range of a wet channel. The addition of a filtering algorithm alleviates some of the interference, but not all. Overall results of the tool show an effective methodology where basic channel conditions are identified, but refinement of the tool could produce more accurate results.

The following is a compilation of field data collected in 2011 and 2012 in Apalachicola, FL as part of a five year study assessing the ecological effects of sea level rise in the northern Gulf of Mexico. Many coastal communities, both natural and developed, will soon be working to mitigate the effects of sea level rise, if they are not already doing so. This thesis investigates the natural patterns of the Apalachicola estuarine system through the collection and analysis of in situ water, sediment, and biomass samples. Additionally, results of the field samples are presented and recommendations for additional sampling are given. The field methods and procedures developed in this study were designed to be repeated in other estuaries to build upon the work that has been conducted in Apalachicola. Water samples were tested for total suspended solids (TSS) and compared against hydrodynamic (tidal circulation and streamflow) and meteorological (wind and precipitation) characteristics. Streamflow was determined to influence a seasonal base level concentration of TSS. Wind strength and direction consistently influenced small TSS concentration fluctuations, an effect amplified by the shallow nature of the estuary. Tidal circulation appeared to have minor influences on TSS concentration fluctuations within the base level concentration range. Precipitation appeared to influence large TSS concentration fluctuations; however, due to limited data collection during storm events, more data is required to conclusively state this. Sediment cores throughout the lower Apalachicola River revealed that coarse particles settled out in upstream areas while fine particles tended to stay in suspension until low energy areas in the lower portions of the river or marsh system were reached. Finally, biomass samples were used to iv develop regression models utilizing remotely sensed data to predict biomass density in marsh areas with unprecedented accuracy. The documented patterns of this system are to be used as inputs and validation points to update an existing hydrodynamic model and to aid in the coupling and development of sediment transport and marsh equilibrium models. The field campaign developed and implemented here provides a foundation for this novel coupled modeling effort of estuarine systems. From the 2011 and 2012 sampling conducted, it is apparent that Apalachicola can be modeled as a closed system with river inflow and sediment influx as boundary conditions. Forcing local conditions should accurately represent the system. Ultimately, these models will be used to simulate future sea level rise scenarios and will provide useful decision making tools to coastal managers. Future work will include replicating water sampling in subsequent wet and dry seasons in Apalachicola, FL to confirm observed trends, in addition to implementing this sampling in Grand Bay, MS and Weeks Bay, AL. Additional biomass samples will be taken to validate the strong correlations found between remotely sensed data and in situ samples. In similar studies, it is recommended that water samples be taken to adequately represent influences from tidal cycles and riverine inflow. It is also recommended that spatially distributed biomass samples be taken to validate regression models.

Sea level rise (SLR) is posing a great risk of flooding and inundation to coastal areas in Florida. Some coastal nesting species, including sea turtle species, have experienced diminished habitat from SLR. In an effort to assess the economic and ecosystem service loss to coastal areas with respect to sea turtles Contingent Valuation Method (CVM) and Habitat Equivalency Analysis (HEA) were used. The CVM was used to measure the economic impacts of SLR on sea turtles. Open-ended and dichotomous choice CVM was used to obtain the willingness to pay (WTP) values of Florida residents to implement certain mitigation strategies which would protect Florida’s east coast sea turtle nesting areas. The problem of sample selection bias was reduced by surveying residents of two cities that would potentially have varying interest in coastal conservation due to their relative distance from the coast. The hypothetical WTP of Florida households to implement policies designed to protect sea turtle habitat from development encroachment was estimated to be between $21 and $29 per year for a maximum of five years. Characteristics of respondents were found to have statistically significant impacts on their WTP. Findings include a negative correlation between the age of a respondent and the probability of an individual willing to pay the hypothetical WTP amount. Counter intuitively, it was found that WTP of an individual was not dependent on prior knowledge of the effects of SLR on sea turtle habitat. As the level of this awareness increased, the probability to pay the hypothetical WTP value decreased. The greatest indicators of whether or not an individual was willing to pay to protect sea turtle habitat were the respondents’ perception regarding the importance of sea turtle population health to the ecosystem, and their confidence in the conservation methods used. iii Concepts of Habitat Equivalency Analysis were used in order to determine the ecosystem service lost due to SLR. The study area of Archie Carr National Wildlife Refuge (ACNWR) has a continually increasing sea turtle population due to various conservation efforts. However, how the inundation of the coastal area will injure this habitat was assessed, and if mitigation strategies to compensate for the loss are necessary. The carrying capacity (CC) of the refuge was chosen as the metric of the ecosystem service. Using the estimated area of ACNWR and the approximate area needed by a sea turtle to nest, the theoretical number of sea turtle nests possible on the refuge was calculated. This value was then projected to the year 2100 using the sea level rise scenarios provided by IPCC (2007) and NRC (2010). In order to quantify the injury caused by the decrease in the refuge’s CC, the number of sea turtle nests on the refuge was projected to the year 2100 using the data obtained over the past 30 years. The analysis concludes a potential loss of service to be experienced as early as 2060’s due to the carrying capacity of the refuge diminishing with the loss of the habitat due to the increase in the mean sea level.

Agriculture is the mainstay of the economy in Malawi and accounts for 40% of the Gross Domestic Product (GDP) and 90% of the export revenues. Corn (maize) is the major cereal crop grown as staple food under rainfed conditions, covers over 92% of the total agricultural area, and contributes 54% of the caloric intake. Corn production is the principle occupation and major source of income for over 85% of the total population in Malawi. Issues of hunger and food insecurity for the entire nation are associated with corn scarcity and low production. Global warming is expected to cause climate change in Malawi, including changes in temperature and precipitation amounts and patterns. These climate changes are expected to affect corn production in Malawi. This study evaluates the impacts of climate change on rainfed corn production in Malawi. Lilongwe District, with about 1,045 square miles of agriculture area, has been selected as a representative area. First, outputs of 15 General Circulation Models (GCMs) under different emission scenarios are statistically downscaled. For this purpose, a weather generator (LARSWG) is calibrated and validated for the study area and daily precipitation as well as minimum and maximum temperature are projected for 15 GCMs for three time horizons of 2020s, 2050s and 2090s. Probability assessment of bounded range with known distributions is used to deal with the uncertainties of GCMs’ outputs. These GCMs outputs are weighted by considering the ability of each model to simulate historical records. AquaCrop, a new model developed by FAO that simulates the crop yield response to water deficit conditions, is employed to assess potential rainfed corn production in the study area with and without climate change. Study results indicate an average temperature increase of 0.52 to 0.94oC, 1.26 to 2.20oC and 1.78 to 3.58oC in the nearterm (2020s), mid-term (2050s) and long-term (2090s) future, respectively. The expected changes in precipitation during these periods are -17 to 11%, -26 to 0%, and -29 to -3%. Corn iii yields are expected to change by -8.11 to 0.53%, -7.25 to -14.33%, and -13.19 to -31.86%, during the same time periods. The study concludes with suggestion of some adaptation strategies that the Government of Malawi could consider to improve national food security under climate change.