Calibration of channel depth and friction parameters in the LISFLOOD-FP hydraulic model using medium resolution SAR data and identifiability techniques

Single satellite synthetic aperture radar (SAR) data are now regularly used to estimate hydraulic model parameters such as channel roughness, depth and water slope. However, despite channel geometry being critical to the application of hydraulic models and poorly known a priori, it is not frequently the object of calibration. This paper presents a unique method to simultaneously calibrate the bankfull channel depth and channel roughness parameters within a 2-D LISFLOOD-FP hydraulic model using an archive of moderate-resolution (150 m) ENVISAT satellite SAR-derived flood extent maps and a binary performance measure for a 30 × 50 km domain covering the confluence of the rivers Severn and Avon in the UK. The unknown channel parameters are located by a novel technique utilising the information content and dynamic identifiability analysis (DYNIA) (Wagener et al., 2003) of single and combinations of SAR flood extent maps to find the optimum satellite images for model calibration. Highest information content is found in those SAR flood maps acquired near the peak of the flood hydrograph, and improves when more images are combined. We found that model sensitivity to variation in channel depth is greater than for channel roughness and a successful calibration for depth could only be obtained when channel roughness values were confined to a plausible range. The calibrated reach-average channel depth was within 0.9 m (16 % error) of the equivalent value determined from river cross-section survey data, demonstrating that a series of moderate-resolution SAR data can be used to successfully calibrate the depth parameters of a 2-D hydraulic model

Assimilation of Soil Moisture and Ocean Salinity (SMOS) brightness temperature into a large-scale distributed conceptual hydrological model to improve soil moisture predictions : the Murray-Darling basin in Australia as a test case

The main objective of this study is to investigate how brightness temperature observations from satellite microwave sensors may help to reduce errors and uncertainties in soil moisture and evapotranspiration simulations with a large-scale conceptual hydro-meteorological model. In addition, this study aims to investigate whether such a conceptual modelling framework, relying on parameter calibration, can reach the performance level of more complex physically based models for soil moisture simulations at a large scale. We use the ERA-Interim publicly available forcing data set and couple the Community Microwave Emission Modelling (CMEM) platform radiative transfer model with a hydro-meteorological model to enable, therefore, soil moisture, evapotranspiration and brightness temperature simulations over the Murray-Darling basin in Australia. The hydrometeorological model is configured using recent developments in the SUPERFLEX framework, which enables tailoring the model structure to the specific needs of the application and to data availability and computational requirements. The hydrological model is first calibrated using only a sample of the Soil Moisture and Ocean Salinity (SMOS) brightness temperature observations (2010-2011). Next, SMOS brightness temperature observations are sequentially assimi-lated into the coupled SUPERFLEX-CMEM model (20102015). For this experiment, a local ensemble transform Kalman filter is used. Our empirical results show that the SUPERFLEX-CMEM modelling chain is capable of predicting soil moisture at a performance level similar to that obtained for the same study area and with a quasi-identical experimental set-up using the Community Land Model (CLM). This shows that a simple model, when calibrated using globally and freely available Earth observation data, can yield performance levels similar to those of a physically based (uncalibrated) model. The correlation between simulated and in situ observed soil moisture ranges from 0.62 to 0.72 for the surface and root zone soil moisture. The assimilation of SMOS brightness temperature observations into the SUPERFLEX-CMEM modelling chain improves the correlation between predicted and in situ observed surface and root zone soil moisture by 0.03 on average, showing improvements similar to those obtained using the CLM land surface model. Moreover, at the same time the assimilation improves the correlation between predicted and in situ observed monthly evapotranspiration by 0.02 on average

Superparamagnetic cellulose fiber networks via nanocomposite functionalization

We present a simple and cost-effective method for rendering networks of cellulose fibers, such as paper, fabrics or membranes, superparamagnetic by impregnating the individual fibers with a reactive acrylic monomer. The cellulose fibers are wetted by a cyanoacrylate monomer solution containing superparamagnetic manganese ferrite colloidal nanoparticles. Upon moisture initiated polymerization of the monomer on the fiber surfaces, a thin nanocomposite shell forms around each fiber. The nanocomposite coating renders the cellulose fibers water repellent and magnetically responsive. Magnetic and microscopy studies prove that the amount of the entrapped nanoparticles in the nanocomposite shell is fully controllable, and that the magnetic response is directly proportional to this amount. A broad range of applications can be envisioned for waterproof magnetic cellulose materials (such as magnetic paper/tissues) obtained by such a simple yet highly efficient method

Biodegradazione della bagassa di guayule con "White-Rot Fungi" finalizzata alla produzione di zuccheri di 2° generazione per il progetto "ALBE"

The biodegradation pretreatment of guayule bagasse by White Rot Fungi (WRF) using two lignin-lytic strains belonging to the Pleurotus ostreatus and Fomitiporia mediterranea species (Basidiomycotina) was studied under in vitro conditions for assessing the released 2nd-generation fermentable sugars suitable for producing bio-elastomers into “ALBE” Project (partnership among ENEA and VERSALIS). Guayule bagasse is an important and recalcitrant lignin-cellulosic co-product obtained from guayule crop, an alternative plant to caucciù tree for the industrial production of rubber, after industrial extraction of rubber and resin. In this research work were: 1) selected two strains of Pleurotus ostreatus and Fomitiporia mediterranea provided by the collection of University of Bari under laboratory condition on the basis of their growth performances; 2) analyzed guayule bagasse samples after resin extraction; 3) optimized the parameters of the biodegradation process by using liquid cultures under rotary shaking; 4) performed the releasing of fermentable sugars from guayule bagasse. The determination of glucose and other minor secondary metabolites were carried out by analytical standard methods after hydrolysis enzymatic of the crude cultural filtrates of each fungus. The results showed that the released sugars from guayule bagasse by biodegradation with WRF was significantly increased if compared to control, nevertheless more researches of this topic are needed.In questo lavoro, svolto nell’ambito del Progetto di Ricerca ENEA-VERSALIS “ALBE”, sono descritti la metodologia sperimentale e i risultati ottenuti su un processo di pretrattamento microbiologico della bagassa di guayule. Il guayule è una coltura alternativa al caucciù (albero della gomma) e può essere utilizzata per la produzione industriale di gomma naturale. Il residuo derivato (bagassa) è un materiale lignocellulosico che può essere valorizzato per la produzione di zuccheri di 2° generazione. In particolare il glucosio può essere utilizzato per la produzione di butandiolo, un building block, per ottenere elastomeri, obiettivo finale del progetto in esame. Nel merito di questo rapporto, il residuo lignocellulosico del guayule è stato caratterizzato e sottoposto ad un pretrattamento microbiologico con l’impiego di due ceppi di funghi Basidiomiceti ligninolitici, agenti della “carie bianca del legno” del tipo “WRF” e appartenenti alle specie Pleurotus ostreatus e Fomitiporia mediterranea. Essi sono stati selezionati in laboratorio per le loro prestazioni di crescita e utilizzati per pretrattare la bagassa di guayule. Dopo il pretrattamento è stata eseguita l’idrolisi enzimatica della cellulosa per l’ottenimento di un brodo zuccherino e di un residuo insolubile a base ligninica. Lo studio ha previsto sia una fase preliminare di ottimizzazione, consistita nel variare la durata del pretrattamento biologico (4-12 giorni) ed il dosaggio enzimatico, sia l’esecuzione di prove rappresentative su idonei quantitativi di bagassa con lo scopo di valutare i rendimenti in zuccheri fermentabili e i relativi flussi di massa. I risultati ottenuti, anche se richiedono un ulteriore approfondimento, hanno permesso di ottenere una preliminare valutazione dell’efficacia di questo tipo di pretrattamento, che ha riguardato una biomassa residuale particolarmente recalcitrante, come la bagassa del guayule, per la produzione di zuccheri di 2° generazione. Le attività sono state svolte in collaborazione con l’Università di Bari

Water-repellent cellulose fiber networks with multifunctional properties.

We demonstrate a simple but highly efficient technique to introduce multifunctional properties to cellulose fiber networks by wetting them with ethyl-cyanoacrylate monomer solutions containing various suspended organic submicrometer particles or inorganic nanoparticles. Solutions can be applied on cellulosic surfaces by simple solution casting techniques or by dip coating, both being suitable for large area applications. Immediately after solvent evaporation, ethyl-cyanoacrylate starts cross-linking around cellulose fibers under ambient conditions because of naturally occurring surface hydroxyl groups and adsorbed moisture, encapsulating them with a hydrophobic polymer shell. Furthermore, by dispersing various functional particles in the monomer solutions, hydrophobic ethyl-cyanoacrylate nanocomposites with desired functionalities can be formed around the cellulose fibers. To exhibit the versatility of the method, cellulose sheets were functionalized with different ethyl-cyanoacrylate nanocomposite shells..

Discharge and bed roughness estimation from water level data analysis

Water level data measured at the two ends of a reach are used to compute both the average n Manning roughness coefficient and the discharge hydrograph in the upstream section of the reach. The methodology is first introduced for the simple case of homogenous roughness and large slope, when the kinematic assumption holds for the momentum equation. In the more general case, when subcritical flow can occur along the channel, an approximation of the downstream boundary condition is required to make always identifiable the calibration problem. In this case, the calibration problem is solved by 1) associating to each possible n value the solution of a flow routing problem, with assigned upstream water level conditions, 2) selecting among all the feasible n values the optimal roughness coefficient that provides the best match between the computed and the measured water depths hydrograph in the downstream section, according to a selected functional error. The DORA diffusive model is adopted for the solution of the flow routing problem and the Brent algorithm is applied for the search of the minimum of the functional error. The choice and the computation of the initial conditions along the reach, for each possible n value, are discussed. An application to a set of data already available in literature and collected at two gauged sections in the Tiber river (Italy), follows

Conventional Point-Velocity Records and Surface Velocity Observations for Estimating High Flow Discharge

Flow velocity measurements using point-velocity meters are normally obtained by sampling one, two or three velocity points per vertical profile. During high floods their use is inhibited due to the difficulty of sampling in lower portions of the flow area. Nevertheless, the application of standard methods allows estimation of a parameter, α, which depends on the energy slope and the Manning roughness coefficient. During high floods, monitoring of velocity can be accomplished by sampling the maximum velocity, umax, only, which can be used to estimate the mean flow velocity, um, by applying the linear entropy relationship depending on the parameter, M, estimated on the basis of historical observed pairs (um, umax). In this context, this work attempts to analyze if a correlation between α and M holds, so that the monitoring for high flows can be addressed by exploiting information from standard methods. A methodology is proposed to estimate M from α, by coupling the “historical” information derived by standard methods, and “new” information from the measurement of umax surmised at later times. Results from four gauged river sites of different hydraulic and geometric characteristics have shown the robust estimation of M based on α