A Comprehensive Approach for Estimating Hydraulic Quantities in a Multi-branched Estuarine System

Despite many previous investigations, there is no theoretically justifiable equation to determine the freshwater discharge, tidal velocity, and salinity in a complex estuary that contains several branches. In this study, the longitudinal distributions of freshwater and salinity concentration in multi-branched estuaries are investigated using a mathematical model, considering the energy balance by frictional head loss and the salt balance by diffusion and advection in a one-dimensional steady-state condition. We attempt to obtain the time-mean freshwater discharge rate quantitatively at a junction where the main flow separates into two branches. The salinity distribution along each branch is calculated by following the dispersion coefficient equation previously proposed for a single estuary. The salinity field is divided into the near-coast region and the upstream region, because in each segment the inland velocity varies according to the tidal flux. For computing the tidal velocity, we propose the Burgers equation and the Hoph-Cole transformation. The theoretical results obtained by these equations were found to be in good agreement with a set of observed data in the Red River estuary system.     

Output feedback stabilization of a clamped-free beam

We consider a Euler–Bernoulli beam, clamped at one extremity and free at the other, to which are attached a piezoelectric actuator and a collocated sensor touching the clamped extremity. We provide an output feedback law and characterize the sensor/actuator lengths for which the strong stabilization holds. Finally, we prove that the energy decreases to zero in a polynomial way for almost all lengths, and in an exponential way for lengths admitting a certain coprime factorization.     

Reference spectra to classify Amazon water types

Reference spectra extracted from spectral libraries can distinguish different water types in images when associated with limnological information. In this study, we compiled available databases into a single spectral library, using field water reflectance spectra and limnological data collected by different researchers and campaigns in the Amazonian region. By using an iterative clustering procedure based on the combination of reflectance and optically active components (OACs), reference spectra representative of the major Amazonian water types were defined from this library. Differences between the resultant limnological classes were also evaluated by paired t-tests at significance level 0.05. Finally, reference spectra were tested for Spectral Angle Mapper (SAM) classification of waters in Hyperion/Earth Observing-One (EO-1) and Medium Resolution Imaging Spectrometer (MERIS)/Environment Satellite (Envisat) images acquired simultaneously as the field campaigns. Results showed highly variable concentrations of OACs due to the complexity of the Amazonian aquatic environments. Ten classes were defined to represent this complexity, broadly grouped into four limnological characteristics: clear waters with low concentrations of OACs (class 1); black waters rich in dissolved organic carbon (DOC) (class 2); waters with large concentrations of inorganic suspended solids (ISSs) (classes 3–7); and waters dominated by chlorophyll-a (chl-a) (classes 8–10). Using the ten reference spectra, SAM classification of the field water curves produced an overall accuracy of 86% with the highest values observed for classes 3, 4, 6 and 7 and the lowest accuracy for classes 1 and 2. The results of paired t-tests confirmed the class differences based on the concentrations of OACs. SAM classification of the Hyperion and MERIS images using ground truth information resulted in overall classification accuracies of 48% and 67%, respectively, with the highest errors associated with specific portions of the scenes that were not adequately represented in the spectral library.     

A generalization of spatial and temporal fusion methods for remotely sensed surface parameters

Remotely sensed surface parameters, such as vegetation index, leaf area index, surface temperature, and evapotranspiration, show diverse spatial scales and temporal dynamics. Generally the spatial and temporal resolutions of remote-sensing data should match the characteristics of surface parameters under observation. These requirements sometimes cannot be provided by a single sensor due to the trade-off between spatial and temporal resolutions. Many spatial and temporal fusion (STF) methods have been proposed to derive the required data. However, the methodology suffers from disorderly development. To better inform future research, this study generalizes the existing methods from around 100 studies as spatial or temporal categories based on their physical assumptions related to spatial scales and temporal dynamics. To be specific, the assumptions are related to the scale invariance of the temporal information and temporal constancy of the spatial information. The spatial information can be contexture or spatial details. Experiments are conducted using Landsat data acquired on 13 dates in two study areas and simulated Moderate Resolution Imaging Spectroradiometer (MODIS) data. The results are presented to demonstrate the typical methods from each category. This study concludes the following. (1) Contexture methods depend heavily on how components maps (contexture) are defined. They are not recommended except when components maps can be estimated properly from observed images. (2) The spatial and temporal adaptive reflectance fusion model (STARFM) and enhanced STARFM (ESTARFM) methods belong to the temporal and spatial categories, respectively. Thus, STARFM and ESTARFM should be better applied to temporal variance – dominated and spatial variance – -dominated areas, respectively. (3) Non-linear methods, such as the sparse representation-based spatio-temporal reflectance fusion model, can successfully address land-cover changes in addition to phonological changes, thereby providing a promising option for STF problems in the future.     

Remote sensing of phycocyanin pigment in highly turbid inland waters in Lake Taihu,China

Cyanobacterial blooms are an environmental issue that can cause health hazards by toxins and malodorous compounds. The pigment phycocyanin is indicative of cyanobacterial presence. In eutrophic inland waters in which nitrogen is not a limiting nutrient, the phycocyanin concentration (PC) is closely related to cyanobacterial biomass. This study proposes a simple semi-analytical four-band algorithm for PC estimation to overcome the deficiency of existing algorithms. This algorithm was calibrated using a data set collected from Lake Taihu in 2007. Optimal reference wavelengths for the algorithm were located through model tuning and accuracy optimization. The algorithm was evaluated for its accuracy against an independent data set collected in 2008. The performance of the algorithm was also compared with that of the nested band-ratio algorithm, which was developed for PC estimation in turbid waters.

Although both algorithms enabled the establishment of a linear relationship between measured and predicted PC, the nested band-ratio algorithm did not have a satisfactory performance with either data set, having a high level of uncertainty. Its mean relative error stands at 51.07% and 51% for the 2007 and 2008 data sets, respectively. It accounted for 68% and 74% of the variation in PC in the 2007 and 2008 data sets, respectively. The four-band algorithm worked well in PC estimation. It accounted for 87% of the variation in PC for the 2007 data set and 86% of the variation in the 2008 data set. Furthermore, it decreased estimation uncertainty, compared with the nested band-ratio algorithm, by more than 20%. The values of mean relative error for the correspondence data sets are 29.1% and 30%. Therefore, the proposed four-band algorithm holds great potential in estimating PC in highly turbid waters.     

The Pythagoras number of real sum of squares polynomials and sum of square magnitudes of polynomials

In this paper, we conjecture a formula for the value of the Pythagoras number for real multivariate sum of squares polynomials as a function of the (total or coordinate) degree and the number of variables. The conjecture is based on the comparison between the number of parameters and the number of conditions for a corresponding low-rank representation. This is then numerically verified for a number of examples. Additionally, we discuss the Pythagoras number of (complex) multivariate Laurent polynomials that are sum of square magnitudes of polynomials on the $n$ -torus. For both types of polynomials, we also propose an algorithm to numerically compute the Pythagoras number and give some numerical illustrations.     

New criteria for exponential stability of nonlinear difference systems with time-varying delay

General nonlinear time-varying difference systems with time-varying delay are considered. Some new explicit criteria for global exponential stability are given. Two examples are given to illustrate the obtained results.     

Dependable control of uncertain linear systems based on set-theoretic methods

This article concerns the feedback control of discrete-time systems subject to disturbances and uncertainties in both model parameters and signal measurements. The uncertainties are assumed to be unknown but bounded and thus characterised by closed intervals or sets. The main result is a new approach to design a feedback controller keeping the system state in a target set. First, a method is proposed that computes minimal enclosures of the set of reachable states, which are consistent with the uncertain input and output measurements and the system dynamics. Then, a control method to keep the current state set in the target set is developed, which extends control techniques based on invariant polyhedra. The method is illustrated by a mobile robot experiment.     

Potential of diffuse scatterer interferometry for monitoring CO2 storage sites in European contexts (land cover types)

This article proposes to test the feasibility of long-term surface deformation monitoring based on synthetic aperture radar (SAR) interferometry on carbon dioxide (CO₂) storage sites with land cover representative of potential European injection sites (agricultural or forests with minimum built-up land cover). Because no operational injection site is currently active in Europe, a SAR data set (based on EnviSAT–ASAR spaceborne data) is simulated by combining SAR scenes acquired over a potential future European injection site with deformation measurements from SAR analysis carried out on the In-Salah (Algeria) CO₂ injection demonstrator site. The study shows that under such conditions, both persistent scatterer interferometry (PSI) and diffuse scatterer (DS) interferometry appear insufficient to provide a sufficiently dense measurement network to characterize surface deformation correctly. Alternative solutions, to be investigated in further studies, include the use of data archives with shorter acquisition time spans (e.g. Sentinel-1 data when available) or installation of corner reflectors. The cost of the latter mixed space/ground solution must be evaluated with respect to conventional ground-based measurement methods in the proposed context.