## 5 Discussion
### Performance of this Study's Most Accurate Predictor (KED-LN)  
The spatial distribution of the residuals from KED-LN predictions and the spatial distribution of the local (GW) correlations between the actual and predicted WD (presented in Figure 7b,c, respectively) shows a distinct spatial pattern linked to the general bay's geometry, topographic controls and bottom type. The local correlations are stronger and more consistent in the southern section, and in a smaller extent, in the northern section, both areas characterized by low complex topography and homogeneous fine-grained seabed type (classes 3 and 4). Weak correlation and higher residuals patterns are largely associated with high relief controls (Liffey channel) and the edges of the bay (very shallow waters or occasional hardgrounds in class 1).  
KED-LN's minor dependency on depth can be observed. Under-prediction occurs mainly in the Liffey channel (observe the red dots of negative residuals in Figure 7b and the points on the bottom left-hand quarter of Figure 7d). One possible explanation is that the signal reflected is largely absorbed, or scattered in the water column, with just a residual component (or inexistent) coming from the seafloor bottom albedo. Therefore, the water-leaving signal represents closely the maximum penetration in the water rather than true depth to bottom. Differences in water column properties could be the main cause for the increase in absorption or scattering effects in these locations. Under-prediction could also be caused by local changes in the seabed type.  
Seafloor bottom reflectance is an important component of the overall water-leaving signal in coastal waters [24]. The assumption of a uniform bottom type is generally not appropriate in coastal areas due to the dynamic environment near the shoreline characterised by complex sediment and oceanographic patterns. The inclusion in our models of seabed class, as a categorical predictor variable, provides some significant results to further enhance the debate and becomes an initial attempt to better constrain the contribution of the bottom reflectance in the overall scheme.  
The central Liffey channel is where the model presents larger uncertainties, larger residuals and reduced accuracy. The rough geomorphological characteristics of the channel and the high backscatterlevels indicating harder and/ or rougher seafloor can influence the bottom reflectance contribution to the water-leaving radiance becoming more complex and generally larger than the more homogenous surroundings. Additionally, higher turbidity due to strong sediment fluxes along the navigational channel might also play a role increasing local variability in the water column. This is to a certain extent captured in the conditional boxplots for SEABED class 2 in Figure 7e, with some large negative residuals reflecting large under-predictions.  
Rock outcrops and hard bottoms are present in the region approximately covering 5% of the study area. These hard seafloor patches, mostly falling in seabed class 1, should have a larger component from the seafloor bottom albedo than the surroundings primarily due to the greater optical contrast in the water-seabed interface. This is true in the rock outcrops from the northern sector, where the KED-LN predictions generally show consistently positive residuals (prediction is deeper than it should be).  
The southern half of the bay is where the KED-LN model preforms better with high (actual WD _versus_ predicted WD) correlation coefficients (r \(\geq\) 0.98), low residuals (residuals \(\pm\) 0.5 m) and the narrowest residual boxplot (class 3, in Figure 7e). This area is characterised by a smooth topography, largely featureless and with homogenous sediment type. Additionally, the area also benefits from a low dynamic environment compared to the other areas, linked to stable water properties. These conditions are all favourable for a robust model fit.