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Food contamination is responsible for thousands of deaths worldwide every year. Plants represent the most common pathway for chemicals into the human and animal food chain. Although existing dynamic plant uptake models for chemica...
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Food contamination is responsible for thousands of deaths worldwide every year. Plants represent the most common pathway for chemicals into the human and animal food chain. Although existing dynamic plant uptake models for chemicals are crucial for the development of reliable mitigation strategies for food pollution, they nevertheless simplify the description of physicochemical processes in soil and plants, mass transfer processes between soil and plants and in plants, and transformation in plants. To fill this scientific gap, we couple a widely used hydrological model (HYDRUS) with a multicompartment dynamic plant uptake model, which accounts for differentiated multiple metabolization pathways in plant's tissues. The developed model is validated first theoretically and then experimentally against measured data from an experiment on the translocation and transformation of carbamazepine in three vegetables. The analysis is further enriched by performing a global sensitivity analysis on the soil-plant model to identify factors driving the compound's accumulation in plants' shoots, as well as to elucidate the role and the importance of soil hydraulic properties on the plant uptake process. Results of the multilevel numerical analysis emphasize the model's flexibility and demonstrate its ability to accurately reproduce physicochemical processes involved in the dynamic plant uptake of chemicals from contaminated soils.
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Low-impact developments (LIDs), such as green roofs, have proven to be valuable alternatives for stormwater management and hydrological restoration. Mechanistic models are reliable and accurate tools for analysis of the hydrologic...
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Low-impact developments (LIDs), such as green roofs, have proven to be valuable alternatives for stormwater management and hydrological restoration. Mechanistic models are reliable and accurate tools for analysis of the hydrologic behavior of LIDs, yet only a few studies provide a comprehensive numerical analysis of the hydrological processes involved and test their model predictions against field-scale data. Moreover, more research is needed to determine the unsaturated hydraulic properties of the substrates used in LIDs. For these reasons, the aim of this study was to provide a comprehensive description of the hydrological behavior of an extensive green roof installed at the University of Calabria. The soil hydraulic properties were determined by using the simplified evaporation method. Both unimodal and bimodal soil hydraulic functions were used in the analysis. The estimated parameters were then used in the HYDRUS-3D model to simulate a 2-molong period. Precipitation, irrigation, evaporation, and root water uptake processes were included in the numerical analysis. The values of 0.74 and 0.8 of the Nash-Sutcliffe efficiency index for the model predictions using unimodal and bimodal functions, respectively, confirmed the good agreement between the modeled and measured outflows. The bimodal model was able to both accurately reproduce the hydrographs in both dry and wet periods and account for daily fluctuations of soil moisture. Finally, the validated model was used to carry out a hydrological analysis of the green roof and its hydrological performance during the entire simulated period as well as during single precipitation events.
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Transient measurements from soil water monitoring installments are frequently coupled with Richards-based solvers to inversely estimate soil hydraulic parameters (SHPs) and numerically describe vadose zone water fluxes, such as gr...
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Transient measurements from soil water monitoring installments are frequently coupled with Richards-based solvers to inversely estimate soil hydraulic parameters (SHPs) and numerically describe vadose zone water fluxes, such as groundwater recharge. To reduce model predictive uncertainty, the experimental setup should be designed to maximize the information content of observations. However, in practice, this is generally done by relying on the a priori expertise of the scientist/user, without exploiting the advantages of model-based exper-imental design. Thus, the main aim of this study is to demonstrate how model-based experimental design can be used to maximize the information content of observations in multiple synthetic scenarios encompassing different soil textural compositions and climatic conditions. The hydrological model HYDRUS is coupled with a Nested Sampling estimator to calculate the parameters' posterior distributions and the Kullback-Leibler divergences. Results indicate that the combination of seepage flow, soil water content, and soil matric potential measurements generally leads to highly informative designs especially for fine textured soils, while results from coarse soils are generally affected by higher uncertainty. Additionally, the propagation of parameter uncertainties in a con-trasting (dry) climate scenario strongly increased prediction uncertainties for sandy soil, not only in terms of the cumulative amount and magnitude of the peak, but also in the temporal variability of the seepage flow. A complementary real-world application with a sandy soil lysimeter identified a combination of seepage data and matric potential as the most informative design and confirmed findings of the synthetic scenarios, in which matric potential proved to be more informative than soil water content measurements.
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Green Roofs (GR) represent a sustainable technological solution for reducing the environmental footprint of urban areas. Despite their benefits, traditional GRs have been criticized regarding their economic feasibility, suggesting...
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Green Roofs (GR) represent a sustainable technological solution for reducing the environmental footprint of urban areas. Despite their benefits, traditional GRs have been criticized regarding their economic feasibility, suggesting to develop advanced hybrid engineering solutions able to simultaneously maximize their hydrological and energetic benefits. In this view, there is a need of numerical models able to describe their complete hygrothermal behavior. Thus, the main aim of this study was to assess the suitability of the one-dimensional mechanistic model HYDRUS-1D in providing an accurate and comprehensive description of the coupled water heat-vapor transport in a field-scale Non-Vegetated Green Roof (NVGR) in the south of Italy. A complete calibration framework, which encompassed the Particle Swarm Optimization (PSO) algorithm and the combined Global Sensitivity Analysis-Generalized Likelihood Uncertainty Estimation (GSA-GLUE) method, was used to estimate the substrate thermal properties and assess the model predictive uncertainty. The calibrated model was exploited to examine the cooling efficiency of a combined Stormwater Reuse-NVGR system in the warm season. The analysis revealed that deeper substrates are positively correlated with thermal lag and attenuation, and that the irrigation can be properly designed to trigger the evaporative and convective cooling of the NVGR. The Response Surface methodology was finally used to optimize the watering regime on an 8 cm-deep NVGR. The exploitation of the evaporative cooling effect of the NVGR by means of a model-based irrigation optimization led to a reduction of the average soil bottom temperature of 4 degrees C. The coupled system was able to maximize the energetic benefits of GR.
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This study presents a hybrid Finite Volume - Finite Element (FV-FE) model that describes the coupled surface-subsurface flow processes occurring during furrow irrigation and fertigation. The numerical approach combines a one-dimen...
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This study presents a hybrid Finite Volume - Finite Element (FV-FE) model that describes the coupled surface-subsurface flow processes occurring during furrow irrigation and fertigation. The numerical approach combines a one-dimensional description of water flow and solute transport in an open channel with a two-dimensional description of water flow and solute transport in a subsurface soil domain, thus reducing the dimensionality of the problem and the computational cost. The modeling framework includes the widely used hydrological model, HYDRUS, which can simulate the movement of water and solutes, as well as root water and nutrient uptake in variably-saturated soils. The robustness of the proposed model was examined and confirmed by mesh and time step sensitivity analyses. The model was theoretically validated by comparison with simulations conducted with the well-established model WinSRFR and experimentally validated by comparison with field-measured data from a furrow fertigation experiment conducted in the US.
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The increasing frequency of flooding events in urban catchments related to an increase in impervious surfaces highlights the inadequacy of traditional urban drainage systems. Low Impact Development (LID) techniques have proven to ...
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The increasing frequency of flooding events in urban catchments related to an increase in impervious surfaces highlights the inadequacy of traditional urban drainage systems. Low Impact Development (LID) techniques have proven to be a viable and effective alternative by reducing stormwater runoff and increasing the infiltration and evapotranspiration capacity of urban areas. However, the lack of adequate modeling tools represents a barrier in designing and constructing such systems. This paper investigates the suitability of a mechanistic model, HYDRUS-1D, to correctly describe the hydraulic behavior of permeable pavement installed at the University of Calabria. Two different scenarios of describing the hydraulic behavior of the permeable pavement system were analyzed: the first one uses a single porosity model for all layers of the permeable pavement; the second one uses a dual-porosity model for the base and sub-base layers. Measured and modeled month-long hydrographs were compared using the Nash-Sutcliffe efficiency (NSE) index. A Global Sensitivity Analysis (GSA) followed by a Monte Carlo filtering highlighted the influence of the wear layer on the hydraulic behavior of the pavement and identified the ranges of parameters generating behavioral solutions. Reduced ranges were then used in the calibration procedure conducted with the metaheuristic Particle swarm optimization (PSO) algorithm for the estimation of hydraulic parameters. The best fit value for the first scenario was NSE = 0.43; for the second scenario, it was NSE = 0.81, indicating that the dual-porosity approach is more appropriate for describing the variably-saturated flow in the base and sub-base layers. Estimated parameters were validated using an independent, month-long set of measurements, resulting in NSE values of 0.43 and 0.86 for the first and second scenarios, respectively. The improvement in correspondence between measured and modeled hydrographs confirmed the reliability of the combination of GSA and PSO in dealing with highly dimensional optimization problems. Obtained results have demonstrated that PSO, due to its easiness of implementation and effectiveness, can represent a new and viable alternative to traditional optimization algorithms for the inverse estimation of unsaturated hydraulic properties. Finally, the results confirmed the suitability and the accuracy of HYDRUS-1D in correctly describing the hydraulic behavior of permeable pavements. (C) 2016 Elsevier B.V. All rights reserved.
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Green Roofs (GRs) have proven to be a sustainable solution to stormwater management in urban areas. To boost their adoption at the large scale, there is a need to develop numerical models, which are accurate, computationally cheap...
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Green Roofs (GRs) have proven to be a sustainable solution to stormwater management in urban areas. To boost their adoption at the large scale, there is a need to develop numerical models, which are accurate, computationally cheap, and as complex as needed to reproduce the hydrological behavior of GRs. Alternative conceptual and mechanistic approaches have been proposed and tested, however the most appropriate level of model complexity for GRs' analysis is still unknown. To cover this scientific gap, we provide a Bayesian comprehensive perspective of GR hydrological modeling, which includes a statistically rigorous Bayesian comparison of one conceptual and multiple Richards-based mechanistic GR models, and a probabilistic assessment of the information content of different observations. The analysis of the marginal likelihoods reveals that the conceptual and the unimodal van Genuchten - Mualem models are the most appropriate parameterizations, and that further layers of model complexity are not fully supported by the measurements. In addition to that, the estimated Kullback-Leibler divergences suggest that the measured volumetric water content outperforms the measured subsurface outflow and tracer concentrations in terms of informativeness, leading to the lowest model predictive uncertainty for the simulation of water fluxes. The findings of this study represent a first step to clarify the role of model complexity in GRs' analysis, and open new perspective on GRs' model-based experimental design. (C) 2020 The Authors. Published by Elsevier Ltd.
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Mechanistic models have proven to be accurate tools for the numerical analysis of the hydraulic behavior of Low Impact Development (LIDs) techniques. However, their widespread adoption has been limited by their computational cost....
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Mechanistic models have proven to be accurate tools for the numerical analysis of the hydraulic behavior of Low Impact Development (LIDs) techniques. However, their widespread adoption has been limited by their computational cost. In this view, surrogate modeling is focused on developing and using a computationally inexpensive surrogate of the original model. While having been previously applied to various water-related and environmental modeling problems, no studies have used surrogate models for the analysis of LIDs. The aim of this research thus was to investigate the benefit of surrogate-based modeling in the numerical analysis of LIDs. The kriging technique was used to approximate the deterministic response of the widely used mechanistic model HYDRUS-2D, which was employed to simulate the variably-saturated hydraulic behavior of a contained stormwater filter. The Nash-Sutcliffe efficiency (NSE) index was used to compare the simulated and measured outflows and as the variable of interest for the construction of the response surface. The validated kriging model was first used to carry out a Global Sensitivity Analysis of the unknown soil hydraulic parameters of the filter layer, revealing that only the shape parameter a and the saturated hydraulic conductivity Ks significantly affected the model response. Next, the Particle Swarm Optimization algorithm was used to estimate their values. The NSE value of 0.85 indicated a good accuracy of estimated parameters. Finally, the calibrated model was validated against an independent set of measured outflows with a NSE value of 0.8, which again corroborated the reliability of the surrogate-based optimized parameters. (C) 2017 Elsevier B.V. All rights reserved.
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Ground-Source Heat Pump (GSHP) systems represent one of the most efficient renewable energy technologies. Their efficiency is highly influenced by the thermal properties of the ground, which are often measured in-situ using the Th...
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Ground-Source Heat Pump (GSHP) systems represent one of the most efficient renewable energy technologies. Their efficiency is highly influenced by the thermal properties of the ground, which are often measured in-situ using the Thermal Response Tests (TRTs). While three-dimensional mechanistic models offer significant advantages over analytical solutions for the numerical interpretation of TRTs, their computational cost represents a limiting factor. Moreover, most of the existing models do not include a comprehensive description of hydrological processes, which have proven to strongly influence the behavior of GSHP. Thus, in this study, we propose a computationally efficient pseudo-3D model for the numerical analysis and interpretation of TRTs. The numerical approach combines a one-dimensional description of the heat transport in the buried tubes of the exchanger with a two-dimensional description of the heat transfer and water flow in the surrounding subsurface soil, thus reducing the dimensionality of the problem and the computational cost. The modeling framework includes the widely used hydrological model, HYDRUS, which can simulate the movement of water, heat, and multiple solutes in variably-saturated porous media. First, the proposed model is validated against experimental data collected at two different experimental sites in Japan, with satisfactory results. Then, it is combined with the Morris method to carry out a sensitivity analysis of thermal properties. Finally, the model is exploited to investigate the influence of groundwater and lithologic heterogeneities on the thermal behavior of the GSHP.
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In the last few decades, increasing research effort has focused on the design of telecommunication payload systems with advanced features and lower costs in space applications. In this context, photonic solutions have already prov...
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In the last few decades, increasing research effort has focused on the design of telecommunication payload systems with advanced features and lower costs in space applications. In this context, photonic solutions have already proven the potential to achieve additional functionalities, such as multiplexing or switching of RF or microwave signals, with consequent additional benefits in terms of size and mass reduction. In this paper, we report on the design of a 2 x 2 switching cell based on a thermo-optic interferometric configuration, whose key element is a sub-wavelength grating. We have theoretically demonstrated a broadband operation, with better performance in terms of operating wavelength range and compactness with respect to the existing interferometric cells. The switching cell shows a worst extinction ratio of about 13 dB, insertion loss of less than 2 dB, crosstalk of 12 dB, over a bandwidth of 150 nm, within a footprint as small as 240 mu m x 9 mu m. To demonstrate its potential use as a routing fabric in flexible telecommunication satellite payloads, as an example, the designed switching cell has been used as a building block of an 8 x 8 dilated Banyan matrix, where large bandwidth (150 nm), low crosstalk (-38 dB), small footprint (approximate to 1620 mu m x 576 mu m) and relatively low power consumption (276 mW) have been achieved.
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