Dynamic behaviour of lagoon ecosystems

The dynamic behaviour of primary producers in coastal lagoons due to changes of external control parameters—phosphorous external load and maximum tidal flow rate—is investigated by using a eutrophication model. The eutrophication model allows the simulation of the temporal evolution of the concentration of the following species: a) in the water column: dissolved oxygen, vegetal organic carbon, particulate and dissolved organic carbon, dissolved phosphorous and hydrogen sulphide; b) in sediments: dissolved oxygen, particulate and dissolved organic carbon, dissolved and adsorbed phosphorous, hydrogen sulphide. The vegetal organic carbon is distinguished in three components related to the main groups of primary producers, namely eelgrass, macroalgae and microalgae, having different modalities of nutrient uptake and kinetics parameters depending on the S/V ratio. Diagrams representing the ecosystem dynamic response to the changes of the control parameters were constructed by simulations. The response diagrams suggest the existence of regime shifts which border different ecosystem stability ranges, characterized by the dominance of a specific group of primary producers and by different ecosystem vulnerability at summer water anoxia. A catastrophic bifurcation or abrupt regime shift—evidenced by Poincar`e sections obtained mapping, at a prefixed time period, the values of the concentration of the species—occurs for a critical value of the control parameter and manifests itself as an abrupt change of the dominant species from eelgrass to macroalgae. An analogous abrupt change from eelgrass to macroalgae occurs for a critical value of the tidal flowrate assumed as control parameter in simulations conducted for an assigned value of external phosphorous load

21st Century Projections of High Streamflow Events in the UK and Germany

Radiative effects of anthropogenic changes in atmospheric composition are expected to enhance the hydrological cycle leading to more frequent and intense floods. To explore if there will be an increased risk of river flooding in the future, 21st century projections under global warming scenarios of High Streamflow Events (HSEs) for UK and German rivers are carried out, using a model that statistically relates large-scale atmospheric predictors - 850 hPa Geopotential Height (GPH850) and Integrated Water Vapor Transport (IVT) - to the occurrence of HSEs in one or simultaneously in several streamflow gauges. Here, HSE is defined as the streamflow exceeding the 99th percentile of daily flowrate time series measured at streamflow gauges. For the common period 1960-2012, historical data from 57 streamflow gauges in UK and 61 streamflow gauges in Germany, as well as, reanalysis data of GPH850 and IVT fields, bounded from 90W to 70E and from 20N to 80N are used. The link between GPH850 configurations and HSEs, and more precisely, identification of the GPH850 states potentially able to generate HSEs, is performed by a combined Kohonen Networks (Self Organized Map, SOM) and Event Syncronization approach. Complex network and modularity methods are used to cluster streamflow gauges that share common GPH850 configurations. Then a model based on a conditional Poisson distribution, in which the parameter of the Poisson distribution is assumed to be a nonlinear function of GPH850 and IVT, allows for the identification of GPH850 state and threshold of IVT beyond which there is the HSE highest probability. Using that model, projections of 21st century changes in frequency of HSEs occurrence in UK and Germany are estimated using the simulated fields of GPH850 and IVT from selected GCMs belonging to the Coupled Model Inter-comparison Project Phase 5 (CMIP5). Among the different GCMs, those are selected whose retrospective predictor fields have consistent statistics with the corresponding reanalysis data

Novel stacking models for improved extreme rainfall predictions under climate change scenarios.

Future projections under global warming scenarios of local extreme precipitations by downscaling models is still open challenge. A number of downscaling statistical models have been proposed to link large scale atmospheric circulation features, as simulated by Global Circulation Models (GCMs) and/or Regional Circulation Models (RCMs), to the temporal and spatial distribution of local rainfalls. Despite the efforts, comparisons between simulations and observations show that statistical downscaling methods, although able to realistically reproduce most of the mean rainfall attributes as seasonal or monthly rainfall amount, fail to simulate extreme precipitation with acceptable accuracy. This is due to the difficulties to: (i) select the optimal set of atmospheric variables used as predictors; (ii) solve the non-linear dependencies that link the rains to the atmospheric variables; (iii) assess the temporal dependencies between wet and dry states. To overcome such criticalities, in order to improve extreme precipitation forecasting, in this study we introduce in rainfall downscaling a paradigm already known in other disciplines of data science: the "stacking models". Stacking models combine different simulations from multiple predictive models. According to this approach we used Random Forest, extreme gradient boosting and Non-homogeneous Hidden Markov Model (NHMM). The validation was performed first on the individual models, calibrating the parameters individually and evaluating them globally with a cross validation approach. The performance of the proposed stacking model is assessed by comparing the daily rainfall amount simulations with those obtained by a state-of-the-art NHMM model, in which the probability of the rainfall occurrence is just modeled using a logistic regression with parameters depending upon climatology variables. We show that the stacking model outperforms the latter model, especially in simulating the extreme precipitations. Furthermore, such performance improvement is obtained by using a minor number of atmospheric predictors. Once the downscaling model has been calibrated and validated, we evaluated changes of precipitation extremes under climate change scenarios. The simulations were performed using the variables obtained from a GCM, Community Climate System Model v4 - NCAR, whose scenario is defined by CMIP5 - RCP 8.5. To evaluate the confidence bands of the simulated rainfall it was used an ensemble of simulations obtained by running the latter GCM with different initial conditions. The Lazio region was chosen as a study case. The Lazio Region is located in Central Italy, whose hydrogeological features make it particularly vulnerable to eventual future changes of hydrological cycle such as those induced by climate change. The Mediterranean is made up of many of these vulnerable areas, which makes the application of the method to this case study of general interest

A Combined Atmospheric Rivers and Geopotential Height Analysis for the Detection of High Streamflow Event Probability Occurrence in UK and Germany

The role of atmospheric rivers (ARs) in inducing High Streamflow Events (HSEs) in Europe has been confirmed by numerous studies. Here, we assume as HSEs the streamflows exceeding the 99th percentile of daily flowrate time series measured at streamflow gauges. Among the indicators of ARs are: the Integrated Water Vapor (IWV) and Integrated Water Vapor Transport (IVT). For both indicators the literature suggests thresholds in order to identify ARs. Furthermore, local thresholds of such indices are used to assess the occurrence of HSEs in a given region. Recent research on ARs still leaves room for open issues: 1) The literature is not unanimous in defining which of the two indicators is better. 2) The selection of the thresholds is based on subjective assessments. 3) The predictability of HSEs at the local scale associated with these indices seems to be weak and to exist only in the winter months. In order to address these issues, we propose an original methodology: (i) to choose between the two indicators which one is the most suitable for HSEs predictions; (ii) to select IWT and/or IVT (IVT/IWV) local thresholds in a more objective way; (iii) to implement an algorithm able to determine whether a IVT/IWV configuration is inducing HSEs, regardless of the season. In pursuing this goal, besides IWV and IVT fields, we introduce as further predictor the geopotential height at 850 hPa (GPH850) field, that implicitly contains information about the pattern of temperature, direction and intensity of the winds. In fact, the introduction of the GPH850 would help to improve the assessment of the occurrence of HSEs throughout the year. It is also plausible to hypothesize, that IVT/IWV local thresholds could vary in dependence of the GPH850 configuration. In this study, we propose a model to statistically relate these predictors, IVT/IWV and GPH850, to the simultaneous occurrence of HSEs in one or more streamflow gauges in UK and Germany. Historical data from 57 streamflow gauges in UK and 61 streamflow gauges in Germany, as well as reanalysis data of the 850 hPa geopotential fields bounded from 90W to 70E and from 20N to 80N are used. The common period is 1960 to 2012. The link between GPH850 and HSEs, and more precisely, the identification of the GPH850 states potentially able to generate HSEs is performed by a combined Kohonen Networks (Self Organized Map, SOM) and Event Syncronization approach. Complex network and modularity methods are used to cluster streamflow gauges that share common GPH850 configurations. Then a model based on a conditional Poisson distribution is carried out, in which the parameter of the Poisson distribution is assumed to be a nonlinear function of GPH850 state and IVT/ IWV. This model allows for the identification of the threshold of IVT/IWV beyond which there is the HSE highest probabilit

Enhanced flood mapping using synthetic aperture radar (SAR) images, hydraulic modelling, and social media: A case study of Hurricane Harvey (Houston, TX)

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Recycling of Pre-Washed Municipal Solid Waste Incinerator Fly Ash in the Manufacturing of Low Temperature Setting Geopolymer Materials

In this work, three samples of municipal solid waste incinerators fly ash (MSWI-FA) have been stabilized in systems containing coal fly ash to create geopolymers through a polycondensation reaction. Monolithic products have been obtained with both MSWI fly ash as received and after the partial removal of chloride and sulfate by water washing. The polycondensation products have been characterized qualitatively by means of Fourier transform infrared spectroscopy, X-ray diffraction and scanning electron microscopy and quantitatively, through the determination of the volume of reacted water and silicate. Furthermore, the heavy metals and chloride releases together with the physico-mechanical properties have been evaluated on the hardened products. In conclusion, considering the technological and environmental performances of the obtained geopolymers, they could be suitable for many non-structural applications, such as backfilling of abandoned quarries, decorative materials or brick fireplaces, hearths, patios, etc

Projecting Changes in Tanzania Rainfall for the 21st century: Scenarios, Downscaling & Analysis

A Non-Homogeneous hidden Markov Model (NHMM) is developed using a 40-years record (1950-1990) of daily rainfall at eleven stations in Tanzania and re-analysis atmospheric fields of Temperature (T) at 1000 hPa, Geo Potential Height (GPH) at 1000 hPa, Meridional Winds (MW) and Zonal Winds (ZW) at 850 hPa, and Zonal Winds at the Equator(ZWE) from 10 to 1000 hPa. The NHMM is then used to predict future rainfall patterns under a global warming scenario (RCP8.5), using predictors from the CMCC-CMS simulations from 1950-2100. The model directly considers seasonality through changes in the driving variables thus addressing the question of how future changes in seasonality of precipitation can be modeled. The future downscaled simulations from NHMM, with predictors derived from the simulations of the CMCC-CMS CGM, in the worst conditions of global warming as simulated by RCP8.5 scenario, indicate that, Tanzania may be subjected to to a reduction of total annual rainfall; this reduction is concentrated in the wet seasons, OND, mainly as a consequence of decreasing of seasonal number of wet days. . Frequency and Intensity of extreme events don’t show any evident trend during the 21 century

A Three-Dimensional Numerical Study of Wave Induced Currents in the Cetraro Harbour Coastal Area (Italy)

In this paper we propose a three-dimensional numerical study of the coastal currents produced by the wave motion in the area opposite the Cetraro harbour (Italy), during the most significant wave event for the coastal sediment transport. The aim of the present study is the characterization of the current patterns responsible for the siltation that affects the harbour entrance area and the assessment of a project solution designed to limit this phenomenon. The numerical simulations are carried out by a three-dimensional non-hydrostatic model that is based on the Navier–Stokes equations expressed in integral and contravariant form on a time-dependent curvilinear coordinate system, in which the vertical coordinate moves in order to follow the free surface variations. The numerical simulations are carried out in two different geometric configurations: a present configuration, that reproduces the geometry of the coastal defence structures currently present in the harbour area and a project configuration, which reproduces the presence of a breakwater designed to modify the coastal currents in the area opposite the harbour entrance

Projections of climate extremes under potential climate change as represented by changing equator to pole temperature gradient and land ocean temperature contrast.

Under climate variability and anthropogenic forcing, the Equator-to-Pole Temperature Gradient (EPG) and the Ocean-Land Temperature Contrast (OLC) undergo systematic changes, which can be associated with the equatorial pacific circulation patterns via teleconnections, and with the Atlantic Meridional Overturning Circulation (AMOC) via ocean-atmosphere coupling. We couple the Lorenz ’84 atmospheric model, a Box AMOC model (after Roebber 1994), and an ENSO coupled ocean-atmosphere model (Tziperman et al, 1994) to explore the sensitivity of the strength, position and other statistics of the mid-latitude wind components to changes in the aforementioned systems and components. Sea ice and water balances are not explicitly modeled. We then develop and discuss projections of the changes in persistence, low frequency variability, and frequency of extremes in key climatic parameters, as specific climate changes, anticipated under anthropogenic forcing in the 21st century, are postulated

Analysis of changes in large-scale circulation patterns driving extreme precipitation events over the central-eastern China

To an extent, large-scale circulation situations and moisture transport are responsible for extreme precipitation occurrence. The aim of our study is to investigate the possible modifications of circulation patterns (CPs) in driving extreme precipitation over the central-eastern China (CEC). The self-organizing map (SOM) and event synchronization methods are used to link the extreme precipitation events with CPs. Results show that 23% of rain gauges have a significant change point (at the 90% confidence level) in annual extreme precipitation from 1960 to 2015. Based on the identified change points, we classified the data into two periods, that is, 1960–1989 and 1990–2015. Overall, CPs characterized by obvious positive anomalies of 500 hPa geopotential height over the Eastern Eurasia continent and negative values over the surrounding oceans are highly synchronized with extreme precipitation events. During 1990–2015, the predominant CPs are more related to the extreme precipitation with enhanced event synchronization. We found that the CP changes produce an increase in extreme precipitation frequency from 1960–1989 to 1990–2015