Abstract
This work represents one of the first successful applications of Autonomous Underwater Vehicles (AUVs) for interdisciplinary coastal research. A monitoring mission to study the shape and estimate the initial dilution of the S. Jacinto sewage outfall plume using an AUV was performed on July 2002. An efficient sampling strategy enabling greater improvements in spatial and temporal range of detection demonstrated that the sewage effluent plume can be clearly traced using naturally occurring tracers in the wastewater. The outfall plume was found at the surface highly influenced by the weak stratification and low currents. Dilution varying with distance downstream was estimated from the plume rise over the outfall diffuser until a nearly constant value of 130:1, 60 m from the diffuser, indicating the near field end. Our results demonstrate that AUVs can provide high-quality measurements of physical properties of effluent plumes in a very effective manner and valuable considerations about the initial mixing processes under real oceanic conditions can be further investigated.

Abstract
A monitoring mission to study the shape and estimate initial dilution of the S. Jacinto outfall plume using an autonomous underwater vehicle (AUV) was performed on July 30, 2002. In order to reduce the uncertainty about plume location and to concentrate the vehicle mission only in the hydrodynamic mixing zone, outputs of a near-field prediction model, based on effective real-time in situ measurements of current speed and direction and density stratification, were opportunistically used to specify in real time the mission transects. The surface characteristics of the outfall plume were found to be influenced strongly by the relatively weak stratification and low current velocities. Dilution was estimated using a tempera tu re-salinity (TS-) diagram with initial mixing lines between wastewater and ambient waters. Effluent dilutions were at least 30:1 in this study. In order to efficiently map the plume dispersion we applied the least-squares collocation method technique. Our results demonstrate that AUVs can provide high-quality measurements of physical properties of effluent plumes in a quite effective manner and valuable considerations about the initial mixing processes under real oceanic conditions can be further investigated.

Abstract
A seawater quality monitoring program for Foz do Arelho outfall has already started in May 2006 to evaluate the background seawater quality around the vicinity of the sea outfall and to follow the impacts of wastewater discharge in the area. Seven monitoring campaigns were already performed between 2006-2007 in which CTD and ADCP measurements were obtained in the vicinity of the wastewater discharge. Predictions of the plume behavior for several times of the year were obtained using a near field model with the monitoring data as input. The plume behavior was mostly influenced by density stratification. During stratified conditions the plume was trapped with dilutions always above 270 to 1. During unstratified conditions the plume was surfacing with dilutions above always 375 to 1. It is concluded that the outfall is behaving as expected.

Abstract
This paper describes an integrated application that performs a geostatistical analysis of data acquired by an AUV in monitoring missions to sewage outfalls. This comes as an effort for automating the procedures of a monitoring campaign from data acquisition to data processing. This application is based on the R statistical software and uses the Gstat package for the geostatistical prediction. R is a console based application that uses software packages developed by the community. The application interfaces with R guiding the user through several steps that perform the geostatistical analysis. It was not our intention to cover all geostatistical procedures but only the ones that are needed for the data processing concerned. The major advantage of this application is that the user does not need to be familiar with methods and data structures associated with the base software, allowing the processing and analysis to be more simple, fast and efficient which is particularly important for routine monitoring. This software application also enables us to give a quicker response in case of contamination to near-by beaches.

Abstract
This paper describes an integrated application that automates the procedure for sea outfall discharges data acquisition with an Autonomous Underwater Vehicle (AUV). Since most applications for this type of technology are research related, the used software tends to be more technical, oriented for engineers. This fact, allied with the bad sea conditions usually encountered at the portuguese coast, cause the mission execution to be extremely difficult at times. Before starting operating the AUV, a wide range of operations must be completed: we need to get data to estimate plume position, calculate mission path, transfer the AUV and acoustic buoys to the water, test communications and configure a variety of systems. So clearly there is a need to develop an application that fully automates a monitoring mission, allowing the operator with little to no experience to conclude it efficiently. Ultimately, by automating the procedure, there is the possibility of expanding the use of AUV's across several fields of study since no prior knowledge about the its systems is required. In summary this guides the user through a series of tasks and provides visual and audio information.

Abstract
The main purpose of this study was to examine the applicability of geostatistical modeling to obtain valuable information for assessing the environmental impact of sewage outfall discharges. The data set used was obtained in a monitoring campaign to S. Jacinto outfall, located off the Portuguese west coast near Aveiro region, using an AUV. The Matheron's classical estimator was used the compute the experimental semivariogram, which was fitted to three theoretical models: spherical, exponential and Gaussian. The cross-validation procedure suggested the best semivariogram model and ordinary kriging was used to obtain the predictions of salinity at unknown locations. The generated map shows clearly the plume dispersion in the studied area, indicating that the effluent does not reach the nearby beaches. Our study suggests that an optimal design for the AUV sampling trajectory from a geostatistical prediction point of view, can help to compute more precise predictions and hence to quantify more accurately dilution. Moreover, since accurate measurements of plume's dilution are rare, these studies might be very helpful in the future for validation of dispersion models.