## 2 Materials and Methods
### Data Analyses  
For the high-frequency data collected on Feeagh buoy (AWQMS), a QA/QC was applied to account for data gaps, calibration periods or any sensor problems [74]. Data was then transformed from sub-daily (recorded every few minutes) to daily data (daily averages) using the subdaily2 daily function from the hydroTSM package in R [90]. Schmidt stability was calculated using lake water temperature profile data, Feeagh bathymetry and wind speed as input files to the rLakeAnalyzer package in R [91]. Schmidt stability was used as a physical index indicative of the resistance of Lough Feeagh to mixing (e.g., a value of 0 implies that a water column is fully mixed with units of amount of energy required to fully mix a water column per lake area) [92]. Mixed layer depth (MLD) was defined as the depth where the water density was 0.1 km\(\cdot\)m\({}^{-3}\) greater than the shallowest sensor depth, which, based on the findings from [PERSON] et al. (2020), is a robust method for temporal analysis in Lough Feeagh [93]. Quantifying the changes of the estimated MLD of Lough Feeagh over the study period was used to better characterise the physical impacts of the extreme-weather-related events in the lake which, in turn, had implications for chemical and planktonic community dynamics [94]. Based on the summer 2018 lake stability pattern, the period under study was divided into three phases (pre-, intermediate and post-Storm Hector). Pre-storm conditions were delineated by the initial heat wave (28 th May-13 th June); this was followed by an intermediate period dominated by the arrival and aftereffects of Storm Hector (14 th June-3 rd July) and, finally, the post-storm period was represented by a return to stable conditions, with high Schmidt stability values (4 th-15 th of July). Metabolic estimates were calculated using the maximum likelihood estimation method (mle) from the LakeMetabolizer package in R [95]. Two-minute time step changes of Lough Feeagh epilimnetic DO (0.9 m), water temperature, photosynthetic active radiation (PAR) and wind speed for the study period (April-October 2018) were used for producing daily GPP (positive values), R (negative values) and NEP (GPP + R) metabolism estimates. Daily values of air-water oxygen exchange velocity (k600) were calculated following [PERSON] and [PERSON] (1998) [96]. Regarding daily metabolic estimates calculated from DO values at 0.9 m of Lough Feeagh, only the sub-period from the 28 th May to the 15 th July was used, comprising similar days for the pre-, intermediate and post-storm event phases. Days with negative values of GPP or positive values of R were removed from the dataset. The non-parametric Kruskal-Wallis test and a following pairwise multiple comparison Dunn's test for determining which groups differ from others [97; 98] were performed to test for statistical differences between periods (pre-, intermediate and post-storm event) on metabolic estimates using the FSA package in R [99]. Point loadings (\(L\)) from the main inflow rivers were calculated by multiplying the concentration from the biweekly grab sampling nutrient concentrations by the daily average flow on the day the sample was collected [100] (Equation (1)). In turn, biweekly nutrient ratios of total inflow loadings were calculated as the sum of the Glenamong and Black rivers' nutrient loadings, converted to molar concentrations to make it possible to calculate nutrient ratios. \[L=K.V_{d}C_{d} \tag{1}\]where \(L\) is the nutrient loading in tonnes (t) or kilograms (kg) per day; \(K\) is the factor to convert milligram or microgram concentrations to t or kg; \(V_{d}\) is the daily cumulative streamflow in litres (flow in L\(\cdot\)s\({}^{-1}\) multiplied by 86,400 s-day\({}^{-1}\)); and \(C_{d}\) is the grab sampling nutrient concentration measured on the streams each specific day. [PERSON]'s rank correlation coefficient and significance of the correlation between inflow and in-lake TN:TP ratios were carried out with the Chart.correlation function of the PerformanceAnalytics package in R [101].