Flood events are becoming more severe, causing significant problems to human communities, including physical, psychological, and material damage. For both flood forecasting in emergency response situations and flood mapping, georeferencing and data curation are paramount in the context of prevention or preparedness. Hence, data display, data management, and articulation with numerical simulation results must occur on GIS platforms. Our research is motivated by recent advances in Web and GIS technologies, social sensing and high-performance computing, and an envisaged wider availability of remote sensing data. This paper presents and discusses an innovative Web GIS platform named “RiverCure Portal” or “RCP” for short. This platform combines observations and hydrodynamic modelling tools to support various stages of the flood risk management cycle, including operational response, emergency preparedness, and risk assessment. RCP is a multi-organization, multi-context digital platform with flexible configuration features to define and support multiple sensor types and modelling options, satisfying the various needs of different organizations and stakeholders. In addition, this paper discusses the RiverCure Approach, which encompasses the following tasks directly supported by the RCP platform: defining the context and involved geometries, associating sensors to the context, pre-processing and generating the context mesh, defining the simulation event, running the simulation event, and analyzing the results from the simulation event. Thus, the RCP streamlines and simplifies data analysis and simulation procedures to meet decision-makers’ needs. The novelties discussed in this paper include the design and discussion of a Web GIS platform that allows (i) to manage flood data and results of simulations at several contextual levels by different stakeholders such as domain experts, decision-makers, researchers, or students; (ii) to process and curate sensed data obtained from physical and social sensors; and (iii) update the state and values of the parameters of simulation tools through continuous data assimilation techniques for forecasting purposes. Finally, this paper supports the explanation and discussion with a running example, “Águeda 2016 flood” event, which dataset is publicly available for further study and experimentation.

Channel bed morphology depends on bedload fluxes which are difficult to determine even in controlled laboratory conditions. Particle counting can provide time resolved bedload fluxes. Determination of particle rates by means of digital image processing is computationally expensive and the requirement for optical access is not always met. Weighing methods are limited by short dynamic ranges. To overcome these difficulties this paper presents a prototype of a particle counter device that works by detecting impacts on a sensitive surface. The accuracy of the device is validated, by means of laboratory experiments, contrasting its results against those obtained by means of digital image analysis. This device proved to be capable of measuring bedload fluxes, determining long time series of bedload transport rates, in particles per unit time, with high accuracy and with a much lower computation cost relatively to digital image processing. The device is also able to gather meaningful data in real-time, like particle arrival time-series and real-time lateral bedload distribution. The parameters involved in the detection criterion must be previously set through a heuristic procedure. However, the method itself is direct—it requires no calibration between the acquired signal and bedload transport rates. Particle counts can be transformed in bedload discharges by a simple binning process or by taking finite differences of the cumulative mass function. First and second order moments of bedload discharge are in agreement with the values obtained by direct counting. The low requirement for data storage, allowing for very large data series, the real time analysis capabilities, the low cost of such system when compared with a digital image acquisition system constitute the main advantages of the device for the study of integral scales of bedload and bedload intermittency.

We present novel velocimetry algorithms based on the hybridization of correlation-based Particle Image Velocimetry (PIV) and a combination of Lucas–Kanade and Liu–Shen optical flow (OpF) methods. An efficient Aparapi/OpenCL implementation of those methods is also provided in the accompanying open-source QuickLabPIV-ng tool enabled with a Graphical User Interface (GUI). Two different options of hybridization were developed and tested: OpF as a last step, after correlation-based PIV, and OpF as a substitute for sub-pixel interpolation. Hybridization increases the spatial resolution of PIV, enabling the characterization of small turbulent scales and the computation of key turbulence parameters such as the rate of dissipation of turbulent kinetic energy. The method was evaluated using both synthetic and real databases, representing flows that exhibit a variety of locally isotropic homogeneous turbulent scales. The proposed hybrid PIV-OpF results in a 3-fold increase in the PIV density for synthetic images. The analysis of power spectral density functions and auto-correlation demonstrated the impact of PIV image quality on the accuracy of the method and its ability to extend the turbulence range. We discuss the challenges posed by optical noise and tracer density in the quality of the vector map density.

A closed-form equation for the quality factor of CMOS or BiCMOS single-ended switched capacitor arrays (SSCAs), intended for radio-frequency (RF) and microwave switched tuning resonators, is presented and analyzed. This expression predicts accurately the SSCA quality factor (Qssca) with respect to the operation frequency and tuning control input. Important results arise from this equation, viz., Qssca shows a strong dependence on the reference cell electric parameters, presents a monotonically behavior with the tuning control input, is independent of the SSCA size (number of cells) and increases as the technology scales down. Besides that, new concepts are also introduced, namely, basic switch, reference switch, reference capacitor and reference cell. A 0.1 to 6 GHz SSCA, designed with standard 0.35 μm 2-poly 4-metal mixed-signal CMOS technology, is also described. The SSCA has a capacitive tuning range from 210 to 385 fF with a resolution capacitance of 25 fF. The theoretical results, obtained with the SSCA model, match the SSCA layout Spectre ^® RF simulation.