The fish, invertebrate, and macrophyte communities of Dumpert's Lake, a borrow pit located in northwest Delaware County, Indiana were studied in 1979 and 1980. Data obtained from this study were used to evaluate the potential for quality fishing, to identify sport fish production problems, to assess largemouth bass food habits and habitat utilization, and to consider management options.Bluegill dominated the July and September, 1980 fish collections at 69 and 84 percent, respectively. The growth rates for age II and older bluegill indicated mortality rates above 55 percent. Stocklength (3 in., 76 mm) was.attained at annulus 2 and quality-length (6 in., 152 mm) was reached at age III+. The overall average annual growth increment was 48 mm (1.9 in.). Bluegill were in good condition by overall average K at capture (2.05) and at annulus formation (1.91). Corresponding mean Relative Weight (Wr) values were 106 and 107, respectively.Largemouth bass comprised 23 and 14 percent, respectively, of the July and September, 1980 fish collections. Bass attained stock-length (8 in., 200 mm) by age II+ and an additional 1.5-2.0 years (age III+ or older) was required to attain quality-length (12 in., 300 mm). Growth rates and length-frequency distribution verified mortality rates in excess of 60 percent for all age groups of stock-size bass. Average yearly growth was 70 mm (2.8 in.). Condition was poor by overall average K at capture (1.27) and at annulus formation (1.22). The overall mean Wr was 89 for the respective K values.A stock structure index, Proportional Stock Density (PSD), indicated an unbalanced largemouth bass and bluegill population. Bluegill PSD was 78 with largemouth bass PSD at 27.Radio telemetry observations for two largemouth bass monitored from late May to mid-July, 1980 indicated relative inactivity by observed displacement (98 and 366 m) with respective home ranges of 0.01 and 0.12 ha. Extensive use of shoreline cattails was noted at 79 and 84 percent of the respective locations. All observations were over lake depths of 0.5-0.9 m. Two bass tracked from late July to mid-September, 1980 were more active by displacement (1401 and 1429 m) with home ranges of 0.92 ha for both fish, and similar utilization of submergent pondweeds (46 and 50 percent, respectively). One bass was always observed over lake depths of 1.0 m or greater. The other bass was observed in shallow water (0.5-0.9 m) for 50 percent of the observations.Fish occurred more frequently (71 percent) in stomachs of largemouth bass ranging from 195-247 mm than in stomachs (11 percent) of bass 253-347 mm total length. Insects dominated the diet of the larger fish by percent in volume and weight (66 percent) compared to the smaller stock-size bass (21-22 percent). Odonata was the most frequent insect taxa in the diet of the smaller bass at 29 percent and Ephemeroptera was the dominant insect taxa (33 percent) in the diet of the larger fish.Epifaunal macroinvertebrates were more diverse by taxa compared to macroinvertebrates from three benthic habitats which were about equal in diversity by taxa. Zooplankton diversity by taxa was also similar among the benthic habitats. Macroinvertebrate density showed a trend of seasonal increase for the 1979 summer period, while distinct biomodal peaks for zooplankton abundance occurred in early July and late August, 1979 for vegetated and nonvegetated littoral zones.Najas flexilis, Potamogeton nodosus, and P. pusillus dominated the submergent macrophyte community in 1979. The overall mean seasonal dry weight biomass of macrophytes was 110 g/m2 (114 g/m3 ). Macrophyte control was recommended for improving the sport fishery.Ball State UniversityMuncie, IN 47306

Indiana University-Purdue University Indianapolis (IUPUI) / Monitoring lake quality remotely offers an economically feasible approach as opposed to in-situ field data collection. Researchers have demonstrated that lake clarity can be successfully monitored through the analysis of remote sensing. Evaluating satellite imagery, as a means of water quality detection, offers a practical way to assess lake clarity across large areas, enabling researchers to conduct comparisons on a large spatial scale. Landsat data offers free access to frequent and recurring satellite images. This allows researchers the ability to make temporal comparisons regarding lake water quality. Lake water quality is related to turbidity which is associated with clarity. Lake clarity is a strong indicator of lake health and overall water quality. The possibility of detecting and monitoring lake clarity using Landsat8 mean brightness values is discussed in this report. Lake clarity is analyzed in three different reservoirs for this study; Brookeville, Geist, and Eagle Creek. In-situ measurements obtained from Brookeville Reservoir were used to calibrate reflectance from Landsat 8’s Operational Land Imager (OLI) satellite. Results indicated a correlation between turbidity and brightness values, which are highly correlated in algal dominated lakes.

Indiana University-Purdue University Indianapolis (IUPUI) / This thesis applies several different remote sensing techniques to data collected from 2005 to 2007 on central Indiana reservoirs to determine the best performing algorithms in estimating the cyanobacterial pigments chlorophyll a and phycocyanin. This thesis is a set of three scientific papers either in press or review at the time this thesis is published. The first paper describes using a curve fitting model as a novel approach to estimating cyanobacterial pigments from field spectra. The second paper compares the previous method with additional methods, band ratio and semi-empirical algorithms, commonly used in remote sensing. The third paper describes using a partial least squares (PLS) method as a novel approach to estimate cyanobacterial pigments from field spectra. While the three papers had different methodologies and cannot be directly compared, the results from all three studies suggest that no type of algorithm greatly outperformed another in estimating chlorophyll a on central Indiana reservoirs. However, algorithms that account for increased complexity, such as the stepwise regression band ratio (also known as 3-band tuning), curve fitting, and PLS, were able to predict phycocyanin with greater confidence.

Indiana University-Purdue University Indianapolis (IUPUI) / In this research, Environmental Fluid Dynamic Code (EFDC) and Adaptive- Networkbased Fuzzy Inference System Models (ANFIS) were developed and implemented to determine the spatial-temporal distribution of cyanobacterial metabolites: 2-MIB and geosmin, in Eagle Creek Reservoir, IN. The research is based on the current need for understanding algae dynamics and developing prediction methods for algal taste and odor release events. In this research the methodology for prediction of 2-MIB and geosmin production was explored. The approach incorporated a combination of numerical and heuristic modeling to show its capabilities in prediction of cyanobacteria metabolites. The reservoir’s variable data measured at monitoring stations and consisting of chemical/physical and biological parameters with the addition of calculated mixing conditions within the reservoir were used to train and validate the models. The Adaptive – Network based Fuzzy Inference System performed satisfactorily in predicting the metabolites, in spite of multiple model constraints. The predictions followed the generally observed trends of algal metabolites during the three seasons over three years (2008-2010). The randomly selected data pairs for geosmin for validation achieved coefficient of determination of 0.78, while 2-MIB validation was not accepted due to large differences between two observations and their model prediction. Although, these ANFIS results were accepted, the further application of the ANFIS model coupled with the numerical models to predict spatio-temporal distribution of metabolites showed serious limitations, due to numerical model calibration errors. The EFDC-ANFIS model over-predicted Pseudanabaena spp. biovolumes for selected stations. The predicted value was 18,386,540 mm3/m3, while observed values were 942,478 mm3/m3. The model simulating Planktothrix agardhii gave negative biovolumes, which were assumed to represent zero values observed at the station. The taste and odor metabolite, geosmin, was under-predicted as the predicted v concentration was 3.43 ng/L in comparison to observed value of 11.35 ng/l. The 2-MIB model did not validate during EFDC to ANFIS model evaluation. The proposed approach and developed methodology could be used for future applications if the limitations are appropriately addressed.