Pyrmnesium parvum, commonly known as golden algae, is an algal species that under certain circumstances releases toxins which can lead to fish kills and the death of other economically and ecologically important organisms. One of the major objectives of the study was to investigate whether a relationship exists between land use and Prymnesium parvum abundance in littoral sites of Lake Texoma, USA. Another objective was to investigate whether a relationship exists between other physical variables and counts of P. parvum. Lastly, developing a valid model that predicts P. parvum abundance was an objective of the study. Through stepwise regression, a small but highly significant amount of the variation in P. parvum counts was found to be explained by wetlands, soil erodibility and lake elevation. The developed model provides insight for potential golden algae management plans, such as maintaining wetlands and teaching land owners the relationship between soil erosivity and golden algae blooms.

The primary objective of this study was to develop and evaluate a system capable of rapid, continuous collection of water quality and locational data on Lake Texoma. Secondary objectives included developing monthly distribution maps for chlorophyll-a, turbidity, and specific conductivity in Lake Texoma and investigating the spatial and temporal relationships between these common water quality indicators. A modified YSI multiprobe was used to develop a system capable of surveying the lake within 4 days with samples at 330 to 400 meter intervals. Data generated with this system compared favorably with previous studies of Lake Texoma. Two sets of raster format maps were developed for the monthly distributions of chlorophyll-a, turbidity, and specific conductivity across the lake. Spatial and temporal relationships generally took the form of decreasing gradients running from the lake arms towards the Main Lake Zone in the case of chlorophyll-a and turbidity. Or, in the case of specific conductivity, a decreasing gradient from the Red River arm to the Washita River arm. All three water quality indicators were strongly influenced by river discharge levels.

The underwater optical climate of Lake Texoma was measured at eleven fixed stations from August 1996 to August 1997. Secchi transparency and submarine photometry characterized seasonal and spatial values of secchi depth (SD), vertical attenuation coefficient (η''), and depth of euphotic zone (Zeu). Indices of Zeu:SD and η'' × SD were compared with universally applied values derived from inland and coastal waters. Turbidity explained 76% of the variation (p = 0.0001) of η'' among water quality parameters, including chlorophyll-α. Using a spectroradiometer, spectral signatures of chlorophyll-α and turbidity were located. Stations with low turbidity exhibited a distinct green reflectance peak around 590-610 nanometers, indicating presence of chlorophyll-α. Stations with high turbidity exhibited a reflectance peak shift towards the red spectrum, making it difficult to detect the chlorophyll signature. Derivative analysis of the reflectance signal at 590-610, and 720-780 nanometers allowed discrimination of this chlorophyll signature from those of turbidity (0.66 ≤ r^2 ≤ 0.99).

A hydrologic model and watershed export model was used to estimate the loading of nutrients and total suspended solids from un-gaged local watersheds associated with Lake Texoma. Discharge to the reservoir from local watersheds was predicted using a modification of the curve number method in HEC Hydrologic Modeling System (HEC-HMS). Event mean concentrations were applied to land use to estimate loadings of nutrients and TSS. Total discharge from the local watersheds was estimated to be 3.02 x 107 cubic meters for a study window of March 1 to May 31, 1997, less than 10 percent of the input to the lake from the Red River and Washita River systems. Loadings were estimated to be 33,553 kg nitrogen, 4,401 kg phosphorus, and 3,423,140 kg TSS. The models and results obtained from their application appear to have potential utility for use in a water quality management decision support system for the reservoir.

Twenty-eight species of zooplankton were identified from Lake Texoma. Seasonal density of the overall microcrustacean community and seasonal cycles of individual species were compared with northern populations and any available literature from the Southwest. Cycles of occurrence and abundance were similar to those observed in northern populations but tended to occur earlier in the year due to higher temperatures. Spatial distributions within the reservoir were heavily influenced by nutrient and salt input from the Red River, which resulted in dense populations in the Red River Arm. In addition, during the summer, the microcrustacean community was restricted to the epilimnion due to anoxic conditions in the hypolimnion of the reservoir.

Seventy-one aquatic species including the copepodids and nauplii were identified from Lake Texoma from August 1996 to September 1997. Zooplankton community structure, abundance and spatial and temporal distributions were compared among five lake zones delineated a priori based on chloride concentration. The zones, in order of decreasing chloride concentration, are the Red River zone (RRZ), Red river Transition zone (RRTZ), Main Lake zone (MLZ), Washita River Transition zone (WRTZ) and Washita River zone (WRZ). Bray Curtis Similarity Index showed community structure was most similar in the two Red River arm zones, the two Washita River arm zones and the MLZ. Zooplankton abundance was greatest in the Red River arm (312 org/L), intermediate in the Washita River arm (217 org/L) and least in the Main Lake body (103 org/L). A significant increase in the abundance of a deformed rotifer, Keratella cochlearis, was observed mainly in the Red River arm during a second study from March 1999 to June 1999. Seasonal dynamics, rather than spatial dynamics, were more important in structuring the zooplankton community, especially in the two river arms. Spatial variance was solely attributed to station and zone effects independent of time for a few crustacean species and many of the water quality parameters supporting the presence of longitudinal gradients of differing water quality. Three independent models (Red River arm, Washita River arm, Main Lake body) rather than a single model for the entire reservoir, best describe patterns in the zooplankton community and its relationship to seasonal, physical and chemical factors. Statistical power, sample size and taxonomic resolution were examined. When monitoring seasonal and annuals trends in abundance, the greatest statistical power was achieved by analyzing count data at taxonomic levels above genus. Taxonomic sufficiency was assessed to determine if costs could be reduced for zooplankton identifications. For water quality monitoring purposes only, it is recommended that genus identifications are sufficient if supplemented with quarterly species identifications.

With advances in computer technology, organizations are able to store large amounts of data in data warehouses. There are two fundamental issues researchers must address: the dimensionality of data and the interpretation of multiple statistical tests. The first issue addressed by this research is the determination of the number of components to retain in principal components analysis. This research establishes regression, asymptotic theory, and neural network approaches for estimating mean and 95th percentile eigenvalues for implementing Horn's parallel analysis procedure for retaining components. Certain methods perform better for specific combinations of sample size and numbers of variables. The adjusted normal order statistic estimator (ANOSE), an asymptotic procedure, performs the best overall. Future research is warranted on combining methods to increase accuracy. The second issue involves interpreting multiple statistical tests. This study uses simulation to show that Parker and Rothenberg's technique using a density function with a mixture of betas to model p-values is viable for p-values from central and non-central t distributions. The simulation study shows that final estimates obtained in the proposed mixture approach reliably estimate the true proportion of the distributions associated with the null and nonnull hypotheses. Modeling the density of p-values allows for better control of the true experimentwise error rate and is used to provide insight into grouping hypothesis tests for clustering purposes. Future research will expand the simulation to include p-values generated from additional distributions. The techniques presented are applied to data from Lake Texoma where the size of the database and the number of hypotheses of interest call for nontraditional data mining techniques. The issue is to determine if information technology can be used to monitor the chlorophyll levels in the lake as chloride is removed upstream. A relationship established between chlorophyll and the energy reflectance, which can be measured by satellites, enables more comprehensive and frequent monitoring. The results have both economic and political ramifications.

A series of four stations for sampling the waters of the Red Rivers and Lake Texoma was established. Water samples from top, middle, and bottom levels of these four stations were taken on monthly intervals during periods of homothermousity and on two-week intervals during periods of thermal stratification. These samples were analysed for the cations sodium, potassium, calcium, and magnesium, and for the anions normal carbonate, bicarbonate, sulfate, chloride, nitrate, water hardness (expressed as calcium carbonate), and phosphates. Determinations for dissolved oxygen, carbon dioxide, pH, temperature, and specific conductance were performed. Using these data, vertical profiles of the lake at these four stations were established. From the study of these data it was concluded that the waters of the Red River improve in quality coincident with impoundment, and that these improvements are sufficient to warrant the use of these waters.

Phytoplankton productivity of Lake Texoma was measured for one year from August 1999 to August 2000 for four stations, using the oxygen change method and laboratory incubation. Mean values of the photosynthetic parameters, PBmax and alphaB ranged from 4.86 to 46.39 mg O2.mg Chl-1.hr-1 for PBmax and 20.06 to 98.96 mg O2.mg Chl-1.E-1.m2 for alphaB. These values were in the range to be expected for a highly turbid, temperate reservoir. Estimated gross annual areal productivity ranged from 594 g C.m2.yr-1 (P.Q. = 1.2), at a station in the Washita River Zone to 753 g C.m2.yr-1 at a station in the Red River Zone, of the reservoir. Gross annual areal productivity at Station 17, in the Main Lake Zone, was 708 g C.m2.yr-1. Gross areal and volumetric productivity showed distinct seasonal variation with Photosynthetically Available Radiation (PAR) and temperature. Trophic status estimated on a station-by-station basis, using net productivity values derived from gross productivity and respiration estimates, was mesotrophic for all the stations, though one station approached eutrophy. Net productivity values ranged from 0.74 to 0.91 g C. m-2.d-1. An algal bioassay conducted at two stations in August 2000, revealed that phosphorus was most likely the nutrient limiting photosynthesis at both these stations, although the more turbid riverine station was primarily light-limited.

From August 1996 through September 1997 eleven fixed stations were sampled monthly in January, March , April , July, August, September, and November and fortnightly in May and June for the purposes of establishing baseline conditions present in Lake Texoma as related to U.S. Army Corps of Engineers chloride control activities in the upper Wichita River, Texas. Five reservoir zones were identified a priori using historical chloride concentration data and include the Red River Zone (RRZ), Red River Transition Zone (RRTZ), Main Lake Body (MLB), Washita River Transition Zone (WRTZ), and Washita River Zone (WRZ) in order of decreasing chloride concentration. The existence of the WRTZ is not supported here, however the Big Mineral Arm in the RRTZ was observed to be highly independent of the mixing patterns observed in the RRTZ and was treated post priori separately from the RRTZ. Spatial and temporal comparisons between reservoir zones were performed on seventeen (17) physicochemical parameters from each of the eleven sampling stations and phytoplankton count data from one sampling station within each reservoir zone and physicochemical parameters were observed to exhibit a fixed spatial gradient. Strong density gradients throughout the reservoir were observed to occur in conjunction with vertical stratification of the water column. Stratification stability at individual stations was attributable to both thermal and salinity density gradients throughout the period of stratification with the degree to which stratification is thermally or chemically induced influenced by inter-annual variability in hydraulic residence time. Hypolimnetic oxygen depletion rates were also observed to be affected by changes in hydraulic residence time with a long-term trend of decreasing relative areal hypolimnetic oxygen rates detected between the 1970s and 1990s. The algal assemblage present in Lake Texoma is dominated by the Cyanophyta, which comprises 82.1 % of the assemblage total standing crop with one species, Microcystis incerta, comprising 57.0 % of the assemblage total standing crop and is typical of a temperate eutrophic lake. The algal assemblage was affected more by temporal dynamics rather than spatial dynamics with variance observed in the algal assemblage attributable to physicochemical factors which vary through time.