Linking Water Temperature Variability to Water Quality Dynamics in Beck Lake, an Urban Inland Lake in Chicago (2020–2024)

Oscar Christopher Lee

Abstract
This study examines the effect of climate variability on water quality in Beck Lake, an inland urban lake in Chicago, Illinois, from 2020 to 2024. The lake is maintained by the Chicago Park District and contains aquatic life such as Bluegill, Largemouth Bass, and Northern Pike. To determine climate influence, satellite-derived water temperature data were analyzed using time series segmentation and non-parametric trend analysis in Python. Specifically, temperature trends were tested using Kendall’s τ (τ = −0.0188, p = 0.597), and correlations between water temperature and NDCI, TP, and EC were positive and statistically significant (r = 0.356, 0.166, and 0.329 respectively). Breakpoints representing statistically significant changes in water temperature were calculated, and corresponding trends in water quality metrics during these segments were examined. Water quality indicators, including the Normalized Difference Chlorophyll Index (NDCI), Normalized Difference Turbidity Index (NDTI), total phosphorus (TP), and electrical conductivity (EC), were extracted from Sentinel-2 imagery using Google Earth Engine. Temporal patterns in these metrics were analyzed in Python using non-parametric methods to find their response to water temperature shifts. Specifically, The results show chlorophyll and phosphorus were positively correlated with temperature, suggesting increased biological activity and nutrient loading. During warmer phases, change in turbidity and conductivity were also observed, indicating possible changes in physical and chemical processes within the lake. These results show strong seasonal co-variation between water temperature and water quality parameters. Based on these water quality shifts, fish species like Bluegill, Largemouth Bass, and Northern Pike that are commonly found in the lake may face periodic stress from lower oxygen levels, algal blooms, and reduced water clarity during warmer, nutrient-rich periods. These conditions can affect their feeding, spawning, and overall habitat suitability. This study demonstrates the value of integrating Earth observation data with climate-sensitive indicators and non-parametric analytics to improve understanding of how urban aquatic ecosystems and life respond to climate variability.