# Assessing the Performance of the Multi-Beam Echo-Sounder Bathymetric Uncertainty Prediction Model
## 5 Conclusions  
Predicting the uncertainty of MBES bathymetric measurements is an important and almost standard step in the planning of MBES surveys. Models have been developed to fulfil such a purpose enabling one to assess whether the required survey standards can be met in a specific measurement campaign for a given combination of measurement equipment, MBES, and environmental settings. Since the development of the these models, the MBES systems have been significantly improved. Moreover, new insights into the uncertainty sources affecting the quality of depth measurements have been obtained, such as the contribution of the baseline decorrelation, Doppler effect, and additive noise. This paper focused on assessing the performance of the widely used bathymetric uncertainty prediction model by comparing the predicted uncertainties to those measured using different pulse lengths and water depths. To obtain the measured bathymetric uncertainties such that a fair comparison could be made with those modeled, a number of issues were found of importance as follows:  
1. The size of the bottom surface patches, used for the calculation of the measured bathymetric uncertainty accounting for the potential presence of the small-scale depth variations, has to be chosen carefully. If a too large surface patch is used, the bottom morphology might change within a patch to an extent that cannot be captured by the fitting process. Therefore, the derived bathymetric uncertainty does not solely depend on the uncertainties inherent to the MBES. On the other hand, if a too small surface patch is used, the number of soundings within a patch might not be enough to to give a robust estimate of the required statistics. The optimal size of the surface patch varies with water depth and was found by comparing the bathymetric uncertainty corresponding to different patch sizes. 2. The number of phase samples within each beam is required for the calculation of the bathymetric uncertainty induced due to the phase bottom detection technique. The comparison between the theoretical number of samples and those obtained in practice revealed large discrepancies, and thus, the latter was used for a realistic comparison between the measured and predicted bathymetric uncertainties. Based on the comparison between the measured and predicted uncertainties, the following conclusions could be drawn:  
* In general, the magnitude of the bathymetric uncertainties derived from the prediction model were in good agreement with those measured. However, discrepancies were observed with increasing water depth and for the outer beams. * The model tends to underestimate the measured uncertainties for the beams where the amplitude detection was used as the bottom detection method. As the pulse length increases, a larger range of beam angles around nadir uses this bottom detection method, and hence, the underestimation occurs for a wider portion of the swath. * The most dominant contributor to the depth uncertainty was found to be the echosounder contribution, and hence, as a first step toward improving the model, the contributions of the baseline decorrelation and Doppler effect were added to this contribution. The comparison between the situations with and without accounting for these error sources indicated a decrease in the contribution of the echosounder in the case of the former. The effect on the total bathymetric uncertainty depended also on the magnitude of the Doppler effect (as the reduction in the contribution of the baseline decorrelation with the beam angle was counteracted by an increase in the Doppler induced depth uncertainty). * Accounting for the contributions of the Doppler effect and baseline decorrelation in general improves the performance of the prediction model in capturing the variations of the uncertainty with the beam angle. The agreement between the modeled and measured uncertainties for the outer parts of the swath is further improved by accounting for the decreased SNR.