# Investigating the Impact of Wildfires on Lake Water Quality Using Earth Observation Satellites
## 3 Results
### Determination of Peaks in Chl-a and Turbidity Concentrations  
Among all lake hydro-morphological parameters considered (listed in the Section 2) we found that mean depth was a significant factor to group lakes according to water quality responses to wildfire occurrence. In the 106 lakes analyzed, Chl-a concentration (both as annual mean concentration and maximum peak concentration) was greater in shallow lakes than in medium and deep lakes (Figure 4). We found that maximum peak concentrations of Chl-a were significantly higher in shallow lakes (median = 24.8 mg m\({}^{-3}\); N = 164;) than in medium depth lakes (19.9 mg m\({}^{-3}\); N = 124) and deep lakes (median = 12.2 mg m\({}^{-3}\); N = 136) (\(p<\) 0.001; Figure 4b) (where N represents the number of lakes for each year analyzed from 2017 to 2020). A Stepwise Multiple Linear Regression (SMLR) was performed in order to investigate factors that were significant in determining maximum annual Chl-a and turbidity peaks in the selected lakes (Table 3). These factors included lake geo-morphological characteristics, burned areas, the ratio BA/A calculated in the whole catchment and in the closest part of a lake (level 0-4), and SPI variation. The SMLR results confirmed that lake depth (\(-\); \(p<\) 0.001) was the most significant factor to predict maximum Chl-a peaks, followed by lake latitude (\(+\); \(p<\) 0.001). Mean values of BA/A (\(+\)) and mean SPI (\(-\)) improved the regression to a final R\({}^{2}\) = 19.5%. Multiple linear regression analysis to predict maximum turbidity peaks revealed mean SPI as a significant parameter (\(+\); \(p<\) 0.05), but explained a very small amount of variation (1.2%), with no additional significant variables in the analysis. Figure 4: Chlorophyll-a mean annual concentration (**a**) and maximum peak concentration (**b**) in lakes separated into three groups according to lake mean depth. S = shallow (\(<\)7 m), M = medium (7–15 m), D = deep (\(>\)15 m). We also restricted SMLR analysis to lakes having a significant regular annual burning and a high BA/A annual ratio in their catchment, located mainly in the African continent (cluster IV as reported in Table 1, N = 24; Table 3 right part). For Chl-a, SMLR performed on this restricted group of lakes confirmed that lake depth was the principal factor in predicting maximum peak concentration (\(-\); \(p\) \(<\) 0.001), followed by water residence time (+; \(p\) \(<\) 0.001), burned area closest to the lake (level 0-4) (\(-\); \(p\) \(<\) 0.001), and SPI (90 th percentile) (+; \(p\) = 0.028), resulting in a final R\({}^{2}\) = 45.8%. SMLR analysis for predicting turbidity maximum peaks, performed in the same restricted lakes group, resulted in lake elevation (\(-\); \(p\) \(<\) 0.001), log ratio catchment area/lake area (+; \(p\) \(<\) 0.001), and mean SPI (+; \(p\) \(<\) 0.001) as significant factors giving a final R\({}^{2}\) = 42.3%. Graphical analysis of time series data provides example lake cases to examine in more detail for our global findings. Figure 5 shows the time series for two lakes with the most extensive burned areas in their catchment (BA annual mean over 10,000 km\({}^{2}\)), located in the Sub-Saharan belt in Africa and having a regular annual burning frequency. Lake Volta (Ghana) is a large (6045 km\({}^{2}\)) and deep lake (average depth = 24.5 m), and Lake Chad (Chad/Niger) is very large (18,751 km\({}^{2}\)) and very shallow (average depth = 0.1 m). The two lakes have comparable wildfire frequency and intensity, with high BA/A ratio (0.14 to 0.38) and similar SPI range. General patterns of smoothed fit of turbidity and Chl-a showed that concentrations were more stable and with moderate concentration peaks (mean peaks: turbidity = 5.6 NTU; Chl-a = 14.8 mg m\({}^{-3}\)) in the deeper Lake Volta, and more variable with more pronounced peaks in the shallow Lake Chad (mean peaks: turbidity = 17.3 NTU; Chl-a = 20.7 mg m\({}^{-3}\)).