Phosphorous (P) has been found to be the limiting nutrient in freshwater systems, directly affecting rates of planktonic growth. The P circulation is very complex, and its pathways through lake systems are difficult to determine. Motala Ström is the biggest watercourse in the south-east of Sweden and an important source of P to the Baltic Sea. The aim of this study is to conduct a P mass balance analysis of the lakes Roxen and Glan over a period of time. The analysis will also include a quality control of the concentrations data. The P concentration data used in this investigation were collected from the Motala Ström River Association, consisting of seasonal or monthly concentration data of Tot-P during the period 1960-2010. Daily water flow data used in this study were modelled by the Swedish Meteorological and Hydrological Institute (SMHI) using the S-HYPE model. P concentration deviations from monthly averages at each sampling station were calculated, followed by a seasonal Mann Kendall trend analysis. At five out of eight sampling stations, negative trends were detected, indicating decreasing concentrations. The exception was the outflow from lake Glan, Stångån and Finspångsån. Linear interpolation of P concentration data was performed to create daily data for the period 1980-2010. Following interpolation, daily transport values were calculated and summed up to annual values. Lake Roxen has acted as a source of P during the whole period 1980-2010, except for one year. Lake Glan has acted as a source during 22 of the 31 years. There is a tendency of Glan to become more of a source over the years, which is in line with the deviation observations, but variation between years makes it necessary to analyse also future data in order to establish any possible trend in P transports. Before construction of wastewater treatment plants, the lakes were certainly sinks of phosphorus. But at least for Roxen, the switch from sink to source was completed before 1980.

The objective of this study is to investigate land-use changes and water quality trends within the headwaters of the Alafia River watershed. Water quality data were obtained from the Environmental Protection Commission of Hillsborough County (EPCHC). Eleven water quality parameters selected for analysis included: temperature (˚C), dissolved oxygen (DO), percent saturation of DO, conductivity, pH, total phosphorous (TP), total nitrogen (TN), ammonium, chlorophyll-a (uncorrected), fecal coliforms, and enterococci. ArcMap® & SWFWMD data were used to map EPCHC sampling stations, calculate contributing watershed size, and determine land-use changes over the course of the sampling period; 17 stations were chosen for this study. The annual average for each of the water quality parameters was calculated along with a Mann-Kendall Trend Analysis in order to determine if any of the observed trends were statistically significant. A non-parametric Kendall’s tau-b correlation and stepwise multiple linear regression tests were conducted in SPSS to determine if any statistically significant relationships between water quality data, land-use and basin size exist. The land-use results showed every basin consisted of some percentage of Low Density Residential, Cropland & Pastureland, Reservoirs, and Streams & Lake Swamps. In addition, no basin comprised of more than 20% wetlands and often it appears urbanization was at the sacrifice of agricultural lands, as opposed to wetlands. The trends in water quality showed eight of the 17 basins had at least one statistically significant trend. Analysis of the data used for this study has shown instances where water quality measurements were in violation of state standards. Changes in water quality can be statistically related to changes in land-use and basin size as both the correlation and the regression showed consistent relationships between several LULC types and water quality parameters: increases in Commercial & Services causes increased nutrients (TP and TN); Cropland & Pastureland causes decreased DO and DO% Saturation; increases in Tree Crops causes a decrease in pH; increasing Other Open Lands Rural causes a decrease in temperature; and increases in Shrub & Brushland cause decreases in conductivity and pH. As these relationships are based on the results from both analyses, it would seem that these relationships are the most reliable, and are key results of the study. These key relationships might be areas that future water resource managers may want to focus on in order to more efficiently improve or regulate water quality within headwater streams.