An Affordable Streamflow Measurement Technique Based on Delay and Sum Beamforming.

At the local scale, environmental parameters often require monitoring by means of affordable measuring techniques and technologies given they need to be frequently surveyed. Streamflow in riverbeds or in channels is a hydrological variable that needs to be monitored in order to keep the runoff regimes under control and somehow forecast floods, allowing prevention of damage for people and infrastructure. Moreover, measuring such a variable is always extremely important for the knowledge of the environmental status of connected aquatic ecosystems. This paper presents a new approach to assessing hydrodynamic features related to a given channel by means of a beamforming technique that was applied to video sensing. Different features have been estimated, namely the flow velocity, the temperature, and the riverbed movements. The applied beamforming technique works on a modified sum and delay method, also using the Multiple Signal Classification algorithm (MUSIC), by acting as Synthetic Aperture Radar (SAR) post-processing. The results are very interesting, especially compared to the on-site measured data and encourage the use of affordable video sensors located along the channel or river course for monitoring purposes. The paper also illustrates the use of beamforming measurements to be calibrated by means of conventional techniques with more accurate data. Certainly, the results can be improved; however, they indicate some margins of improvements and updates. As metrics of assessment, a histogram of greyscale/pixels was adopted, taking into account the example of layers and curve plots. They show changes according to the locations where the supporting videos were obtained.

Video-Sensing Characterization for Hydrodynamic Features: Particle Tracking-Based Algorithm Supported by a Machine Learning Approach.

The efficient and reliable monitoring of the flow of water in open channels provides useful information for preventing water slow-downs due to the deposition of materials within the bed of the channel, which might lead to critical floods. A reliable monitoring system can thus help to protect properties and, in the most critical cases, save lives. A sensing system capable of monitoring the flow conditions and the possible geo-environmental constraints within a channel can operate using still images or video imaging. The latter approach better supports the above two features, but the acquisition of still images can display a better accuracy. To increase the accuracy of the video imaging approach, we propose an improved particle tracking algorithm for flow hydrodynamics supported by a machine learning approach based on a convolutional neural network-evolutionary fuzzy integral (CNN-EFI), with a sub-comparison performed by multi-layer perceptron (MLP). Both algorithms have been applied to process the video signals captured from a CMOS camera, which monitors the water flow of a channel that collects rain water from an upstream area to discharge it into the sea. The channel plays a key role in avoiding upstream floods that might pose a serious threat to the neighboring infrastructures and population. This combined approach displays reliable results in the field of environmental and hydrodynamic safety.

Spatial and temporal classification of coastal regions using bioclimatic indices in a Mediterranean environment.

Bioclimatic indices combine atmospheric parameters to provide analytical indication of climatic features and their evolution in space and time that can directly relate with natural resource availability, distribution, and related bio-physical processes. The availability of bioclimatic information can provide natural resource managers with analytical means to assess the magnitude and temporal evolution of drought and climate change parameters that could affect the availability, demand and use of natural resources for various sectors. This paper presents a methodology to process bioclimatic data in the space and time domains for assessing the moisture/dryness level and water requirements of a region, and inform water resource planning and management decisions related to drought, climate variability and change. The methodology relies on a modular assembly of statistical tests and methods, and utilizes point scale measurements of meteorological data to perform the analysis of the spatial behavior of derived bioclimatic indicators at the continuous regional scale, and evaluate the significance of the temporal trends. Also, the article presents an application of the proposed methodology to a coastal area of southern Italy (the Apulia Region) that is characterized by recurring water supply limitations, involving the use of the popular De Martonne bioclimatic aridity index. The methodology allowed to obtain qualitative and quantitative information about the aridity level of the Apulia region, the identification of main bioclimatic zones, and the evaluation of spatial pattern and time evolution of aridity. The determination of bioclimatic zones showed that nearly 40% of the regional territory is characterized by dry sub-humid (Mediterranean) climate, about 30% by sub-humid climate, while nearly 10% and 20% are characterized by semi-arid and humid climates, respectively. The temporal analysis revealed that the Salento and the Ionian coastal zone are areas at risk of increasing aridity, with resulting impacts on the water supply and demand for irrigated agriculture.

A methodology for rapid assessment of the environmental status of the shallow aquifer of "Tavoliere di Puglia" (Southern Italy).

Anticipating the European Water Framework Directive (2000/60/EC), the Italian Government issued Legislative Decree n.152/99 which sets out rules for classifying the environmental status of national water bodies in order to achieve specific qualitative objectives by 2016. The most recent European Groundwater Directive (2006/118/EC), which was only recognized by Italy in early 2009 (Legislative Decree 30/09), requires such resources to be characterized from a qualitative standpoint and the risk of their being polluted by individual pollutants or groups of pollutants to be evaluated. This paper reports a simple methodology, based on easy-to-apply rules, for the rapid classification of groundwater, and the results of its application to the shallow aquifer of the plain of Tavoliere delle Puglie located in south Italy. Data collected during well-water monitoring campaigns carried out from 2002 to 2003 made it possible to assess the environmental status of the Tavoliere which, unfortunately, was found to be characterized by "significant anthropic pressures on quality and/or quantity of groundwater and necessitating specific improvement actions".