As recently shown in laboratory bench scale experiments, chemotaxis, i.e.the movement of microorganisms toward or away from the concentration gradient of a chemical species, could have a fundamental role in the transport of bacteria through saturated porous media. Chemotactic bacteria could enhance bioremediation by directing their own motions to residual contaminants in less conductive zones in aquifers. The aim of the present work is to develop a proper numerical scheme to define and to quantify the magnitude and the role of chemotaxis in the complex groundwater system framework. We present a new class of meshless Lagrangian particle methods based on the Smooth Particle Hydrodinamics (SPH) formulation of Vila & Ben Moussa, combined with a new Weighted Essentially Non-Oscillatory (WENO) reconstruction technique on moving point clouds in multiple space dimensions. The purpose of this new scheme is to fully exploit the advantages of SPH among traditional meshbased and meshfree schemes and to overcome its inapplicability for modeling chemotaxis in porous media. The key idea is to produce for each particle first a set of high order accurate Moving Least Squares (MLS) reconstructions on a set of different reconstruction stencils. Then, these reconstructions are combined with each other using a nonlinear WENO technique in order to capture at the same time discontinuities and to maintain accuracy and low numerical dissipation in smooth regions. The numerical fluxes between interacting particles are subsequently evaluated using this MLS-WENO reconstruction at the midpoint between two particles, in combination with a Riemann solver that provides the necessary stabilization of the scheme based on the underlying physics of the governing equations. We propose the use of two different Riemann solvers: the Rusanov flux and an Osher-type flux. The use of monotone fluxes together with a WENO reconstruction ensures accuracy, stability, robustness and an essentially non oscillatory solution without the artificial viscosity term usually employed in conventional SPH schemes. To our knowledge, this is the first time that the WENO method, which has originally been developed for mesh-based schemes in the Eulerian framework on fixed grids, is extended to meshfree Lagrangian particle methods like SPH in multiple space dimensions. In the first part, we test the new algorithm on two dimensional blast wave problems and on the classical one-dimensional Sod shock tube problem for the Euler equations of compressible gas dynamics. We obtain a good agreement with the exact or numerical reference solution in all cases and an improved accuracy and robustness compared to existing standard SPH schemes. In the second part, the new SPH scheme is applied to advection-diffusion equation in heterogeneous porous media with anisotropic diffusion tensor. Several numerical test case shows that the new scheme is accurate. Unlike standard SPH, it reduces the occurrence of negative concentration. In the third part, we show the applicability of the new scheme for modeling chemotaxis in porous media. We test the new scheme against analytical reference solutions. Under the assumption of complete mixing at the Darcy scale, we perform different two-dimensional conservative solute transport simulations under steady-state conditions with instant injection showing that chemotaxis significantly affect the quantification of field-scale mixing processes.

Through the last decades several nonlocal models of linear elasticity have been introduced as enhancements of the Cauchy-elastic model, often with the purpose of providing an improved mechanical description of solids at the microscale level. Although many efforts have been devoted to the analytical formulation of these advanced constitutive models, a definitive interpretation of the relevant static quantities is still incomplete and Finite Element (FE) solvers are practically unavailable. In this thesis, after providing a mechanical interpretation to the static quantities involved in strain gradient (of Mindlin type) elastic materials, an overview on the possible quadrilateral Hermitian finite elements is given to treat quasi-static plane problems. Beside the classical finite elements inspired by those adopted for modeling Kirchhoff plates, an alternative quadrilateral self-constrained finite element formulated through Lagrange multipliers is also proposed. With reference to a hexagonal lattice structure, for which the equivalent constitutive tensors have been recently derived as closed-form expressions, the developed FE codes are exploited to assess the reliability of modelling lattices through higher-order constitutive equations. These analyses are developed for one-dimensional and two dimensional problems, where the former are considered for both homogeneous layers (with a finite size in one direction) and rod-type structures (with a finite uniform cross section along one direction). It is confirmed that higher-order modelling improves the mechanical description. In particular, the macroscale response is shown to be strongly affected by higher-order contributions in the presence of extreme elastic contrast between microstructural elements. Indeed, in this last case, only higher-order modeling captures a non-null residual stiffness, which vanishes in the framework of classical models. Therefore, higher-order modeling becomes important not only to describe the mechanical response at a microlevel, but also for macrolevel modelling, when extreme mechanical properties are addressed. The presented results pave the way to a refined modelling of architected materials leading to improved design of microstructures displaying innovative mechanical features.

River/stream water temperature is one of the master water quality parameters as it controls several key iogeochemical, physical and ecological processes and river ecosystem functioning. Thermal regimes of several rivers have been substantially altered by climate change and other anthropogenic impacts resulting in deleterious impacts on river health. Given its importance, several studies have been conducted to understand the key processes defining water temperature, its controls and drivers of change. Temporal and spatial river temperature changes are a result of complex interactions between climate, hydrology and landscape/basin properties, making it difficult to identify and quantify the effect of individual controls. There is a need to further improve our understanding of the causes of spatiotemporal heterogeneity in river temperatures and the governing processes altering river temperatures. Furthermore, to assess the impacts of changing river temperatures on the river ecosystem, it is crucial to better understand the responses of freshwater biota to simultaneously acting stressors such as changing river temperatures, hydrology and river quality aspects (e.g. dissolved oxygen levels). So far, only a handful of studies have explored the impacts of multiple stressors, including changing river temperature, on river biota and, thus, are not well known. This thesis, thus, analysed the changes in river temperature behaviour at different scales and its effects on freshwater organisms. Firstly, at a regional scale, temporal changes in river temperature within long (25 years) and short time periods (10 years) were quantified and the roles of climatic, hydrological and landscape factors were identified for North German rivers. Secondly, at a reach scale, spatial temperature heterogeneity in a sixth-order lowland river (River Spree) was quantified and the role of landscape factors in inducing such heterogeneity was elucidated. Thirdly, at a site scale, short-term behavioural responses (namely drift) of three benthic invertebrate species to varying levels of water temperature, flow, and dissolved oxygen, and to combinations of those factors were experimentally investigated. Results from this thesis showed that, at a regional scale, the majority of investigated rivers in Germany have undergone significant annual and seasonal warming in the past decades. Air temperature change was found to be the major control of increasing river temperatures and of its temporal variability, with increasing influence for increasing catchment area and lower altitudes (lowland rivers). Strongest river temperature increase was observed in areas with low water availability. Other hydro-climatological variables such as flow, baseflow, NAO, had significant contributions in river temperature variability. Spatial variability in river temperature trend rates was mainly governed by ecoregion, altitude and catchment area via affecting the sensitivity of river temperature to its local climate. At a reach scale as well, air temperature was the major control of the temporal variability in river temperature over a period of nine months within a 200 km lowland river reach. The spatial heterogeneity of river temperature in this reach was most apparent during warm months and was mainly a result of the local landscape settings namely, urban areas and lakes. The influence of urban areas was independent of its distance from the river edge, at least when present within 1 km. Heat advected from upstream reaches determined the base river temperature while climatological controls induced river temperature variations around that base temperature, especially below lakes. Riparian buffers were not found to be effective in substantially moderating river temperature in reaches affected by lake warming due to the dominant advected heat from the upstream lake. Experimental investigation indicated that increasing water temperature had a stronger short-term effect on behavioural responses of benthic invertebrates, than simultaneous changes in flow or dissolved oxygen. Also, increases in water temperature was shown to affect benthic invertebrates more severely if accompanied by concomitant low dissolved oxygen and flow levels, while interactive effects among variables vary much among taxa. These results support findings of other studies that river warming, similar to climate change, might be a global phenomenon. Within Germany, lowland rivers are the most vulnerable to future warming, with reaches affected by urbanization and shallow lentic structures being more vulnerable and, therefore, requiring urgent attention. Furthermore, river biota in lowland rivers is particularly susceptible to short-term increases in river temperature such as heat waves. Plantation of riparian buffers, a widely recognized practice to manage climate change effects, in the headwater reaches can be suggested to mitigate and prevent future warming of lowland rivers in general and also throughout river basins, as river temperature response in lowland catchments is a culmination of local and upstream conditions. However, further river temperature increase in lowland river reaches within or close to urban areas and shallow lentic structures will be more difficult to mitigate only via riparian shading and would require additional measures

Braided rivers exhibit extremely complex and dynamic morphologies as their multiple channels are constantly re-worked. The research reported in this thesis explored a number of properties of braided river form and dynamics and some controlling factors through three individual but complementary research elements. The first research element was concerned with some of the controls on the transition between single thread and multi-thread channel patterns. Twenty-seven different flume experiments were conducted, supported by fourteen replicates. In these experiments, channel confinement (maximum possible channel width) and formative discharge were varied in a 25 x 2.9 m flume of constant slope (1%) and bed material (D50 = 1mm) with sediment supply constrained to match sediment output. As the maximum potential channel width increased, the channel pattern changed from a single channel with alternate bars, to the formation of mid-channel bars, and finally to a multi-thread braided pattern. Bed elevation frequency distributions showed distinct changes in their median, standard deviation, skewness and kurtosis as channel width and discharge increased, indicating the consequences of confining braided channels and regulating discharge on their bed elevation and morphology. The second and third parts of the research use remotely sensed data sets to explored (i) the degree to which a real river shows similar characteristics to those generated in the flume experiments and (ii) the variety in braiding patterns that are found in association with different boundary conditions of slope, width, discharge, and riparian vegetation. For the second research element, a Lidar survey of a 36 km reach of the lower Tagliamento river, Italy, was investigated. Within this reach, the river shows only small variations in slope and bed material size and is subject to the same flood flows. Analysis focused on thirty-six 1 km sub-reaches and demonstrated clear associations among the median, standard deviation, kurtosis and skewness of the bed and also clear downstream trends. Measures of vegetation cover showed statistically-significant associations with the median, standard deviation, kurtosis and skewness of the bed, particularly when only the 32 truly braided reaches were analysed. The measures of vegetation cover also showed downstream trends that corresponded with the trends in bed morphology. Overall, variations in bed morphology showed similar characteristics to those observed in the laboratory flume, but also they showed correspondence with riparian vegetation cover, indicating a topographic signature of vegetation on the bed morphology. The downstream trends appear to be associated with the changing vigour of the riparian vegetation and possibly variations in river baseflow characteristics associated with varying groundwater levels in the alluvial aquifer. The most mature patches of vegetation within the braid plain of the most downstream part of the 36 km reach appear to occur on remnants of braid plain isolated by river bed incision. The third and final research element considered the morphology of six European braided rivers of different slope, width, discharge and riparian vegetation type. Information extracted from Google Earth and other aerial imagery, and gauged river flow data supported an analysis of changes in braided river characteristics through time, and among the six European river sites. Four traditional planform indices were used to characterise the braiding pattern (Bi – braiding index, Ai and Ai2 –anastomosing indices; Si – main channel sinuosity) were combined with measures of stream power and its component variables (width, Q10, and slope). Robust data for bed material calibre was not available. Statistical analysis of the entire data set revealed a potential influence of riparian vegetation type on the relationship between unit stream power and braid channel width; and a trend of increasing Bi, Ai, Ai2, and Si with decreasing unit stream power. However, a larger and more complete data set is needed to confirm these general trends and to fully explore transitional rivers. This research has illustrated the morphological consequences of confining braided rivers and the dependence of the braiding pattern on stream power. It has also illustrated the role of vegetation in contributing to the morphological complexity of braided rivers and the potential role of riparian vegetation in constraining the relationship between stream power and braided river width.

Tribology is known as the science of surfaces in relative motion and involves complex interactions over multiple length and time scales. Therefore, friction, lubrication and wear of materials are intrinsically highly multiphysics and multiscale phenomena. Several modelling and simulation tools have been developed in the last decades, always requiring a trade-off between the available computational power and the accurate replication of the experimental results. Despite nowadays it is possible to model with extreme precision elastic problems at various scales, further eorts are needed for taking into account phenomena like plasticity, adhesion, wear, third-body friction and boundary and solid lubrication. The situation becomes even more challenging if considering non-conventional nano-, as in the case of polymer surfaces and interfaces, or microstructures, as for the hierarchical organisations observed in biological systems. Specically, biological surface structures have been demonstrated to present exceptional tribological properties, for instance in terms of adhesion (e.g., the gecko pad), superhydrophobicity (e.g., the lotus leaf) or fluid-dynamic drag reduction (e.g., the shark skin). This has suggested the study and development of hierarchical and/or bio-inspired structures for applications in tribology. Therefore, by taking inspiration from Nature, we investigate the effect of property gradients on the frictional behaviour of sliding interfaces, considering lateral variations in surface and bulk properties. 3D finite-element simulations are compared with a 2D spring-block model to show how lateral gradients can be used to tune the macroscopic coefficients of friction and control the propagation of detachment fronts. Complex microscale phenomena govern the macroscopic behaviour also of lubricated contacts. An example is represented by solid lubrication or third-body friction, which we study with 3D discreteelement simulations. We show the effects of surface waviness and of the modelling parameters on the macroscopic coefficient of friction. Many other natural systems present complex interfacial interactions and tribological behaviour. Plant roots, for instance, display optimised performance during the frictional penetration of soil, especially thanks to a particular apex morphology. Starting from experimental investigations of different probe geometries, we employ the discrete-element method to compute the expended work during the penetration of a granular packing, conrming the optimal bio-inspired shape. This has allowed to follow also an integrated approach including image acquisition and processing of the actual geometries, 3D printing, experiments and numerical simulations. Finally, another interesting example of advanced biological interface with optimised behaviour is represented by biosensing strucviii tures. We employ fluid-structure interaction numerical simulations for studying the response of spiders' trichobothria, which are among the most sensitive biosensors in Nature. Our results highlight the role of the fluid-dynamic drag on the system performance and allow to determine the optimal hair density observed experimentally. Both the third-body problem and the possibility to tune the frictional properties can be considered as the next grand challenges in tribology, which is going to live a "golden age" in the coming years. We believe the results discussed in this Doctoral Thesis could pave the way towards the design of novel bio-inspired structures with optimal tribological properties, for the future development of smart materials and innovative solutions for sliding interfaces.

The turbulent properties of flow in rivers are of fundamental importance to aquatic organisms yet are rarely quantified during routine river habitat assessment surveys or the design of restoration schemes due to their complex nature. This thesis uses a detailed review of the literature to highlight the various ways in which plants and animals modify the flow field, how this can deliver beneficial effects; and how turbulence can also generate threats to growth and survival. The thesis then presents the results from detailed field assessments of turbulence properties undertaken on low, intermediate and high gradient rivers to advance scientific understanding of the hydrodynamics of rivers and inform effective habitat assessment and restoration. A reach-scale comparison across sites reveals spatial variations in the relationships between turbulent parameters, emphasising the need for direct measurement of turbulence properties, while a geomorphic unit scale assessment suggests that variations in turbulence at the scale of individual roughness elements, and/or within the same broad groupings of geomorphic units (e.g. different types of pools) can have an important influence on hydraulic habitat. The importance of small-scale flow obstructions is further emphasised through analysis of the temporal dynamics of turbulence properties with changes in flow stage and vegetation growth. The highest magnitude temporal changes in turbulence properties were associated with individual boulders and vegetation patches respectively, indicating flow intensification around these sub-geomorphic unit scale features. Experimental research combining flow measurement with underwater videography reveals that more sophisticated turbulence parameters provide a better explanation of fish behaviour and habitat use under field conditions, further supporting direct measurement of turbulent properties where possible. The new insights into interactions between geomorphology, hydraulics and aquatic organisms generated by this work offer opportunities for refining habitat assessment and restoration design protocols to better integrate the important role of turbulence in generating suitable physical habitat for aquatic organisms.

The water-energy nexus holds paramount relevance in the context of the transition to a carbon free energy system, being water the only renewable energy source with reliable storage capacity. Modelling hydropower production in a large domain over a long time window represents an open challenge due to a variety of reasons: firstly, high-resolution, large-scale hydrological modelling in a context of uncertainty needs calibration, thus representing a computationally intensive task due to the large domain and time window over which calibration is needed; secondly, as stated by many works in literature, hydropower production modelling and in particular reservoir modelling is a very information-demanding procedure, and excessive simplifications adopted to face the lack of information might lead to consistent bias in the predictions. This thesis can be subdivided into three main parts: firstly, the model that was used to perform every analysis, HYPERstreamHS, will be presented. The model is a continuous, large-scale hydrological model embedding a dual-layer MPI framework (i.e. Message Passing Interface, a common standard in parallel computing) that ensures optimal scalability of the model, greatly reducing the computation time needed. Explicit simulation of water diversions due to hydropower production is also included in the model, and adopts only publicly available information, making the model widely applicable. Secondly, a first validation of the model will be presented, and the adopted approach will be compared with some other approaches commonly found in literature, showing that the inclusion of a high level of detail is crucial to ensure a reliable performance of the model; this first application was performed on the Adige catchment, where extensive information on human systems was available, and allowed to effectively assess which information were indispensable and which, in turn, could be simplified to some extent while preserving model performance. Finally, the model setup has been applied on a relevant portion of the Western Italian Alps; in this case, two different meteorological input forcing data sets were adopted, in order to assess the differences in their performance in terms of hydropower production modelling. This latter study indeed represents a preliminary analysis and will provide stepping stone to extend the modelling framework to the Italian Alpine Region.

Scientists are continuously fascinated by the high degree of sophistication found in natural materials, arising from evolutionary optimisation. In living organisms, nature provides a wide variety of materials, architectures, systems and functions, often based on weak constituents at the lower scales. One of the most extensively studied natural materials is spider silk, renowned for its outstanding mechanical properties, which include exceptional strength and toughness. Owing to its wide range of properties, which vary depending on factors such as the type of silk (up to seven) that each spider can produce, and the species of spider, it can be considered a class of semi-crystalline polymeric material. Indeed, spider silk cleverly combines, depending on the application required, the great deformability of an amorphous phase with the stiffness and strength conferred by pseudo-crystals consisting of specific secondary structures of some of the proteins constituting the material. Based on the countless studies conducted on spider silk, it is now also clear that its remarkable performance are the result of a sophisticated optimisation of the material's hierarchical structure. Nevertheless, many of the multiscale mechanisms that give rise to the striking macroscopic properties are still unclear. Many open problems are also related to the relevant effects of environmental conditions and in particular on temperature and humidity, strongly conditioning the mechanical performances. In this thesis, aimed at unveiling some of these open problems, we introduce a multiscale model for the thermo-hygro-mechanical response, starting with the influence of water molecules modifying the microstructure, up to the effects at the macroscopic scale, including softening, increase in elongation at break and supercontraction, i.e. the shortening (up to half the initial length) of the spider threads in wet environments. Thereafter, we describe how the supercontraction effect can be adopted to obtain humidity-driven actuators, and in particular, we determine the maximum actuation force depending on the silk properties at the molecular scale and on the constraining system representing other silk threads or the actuated device. The spider silk actuation properties turned out to be extraordinary, making spider silk potentially the best performing humidity-driven actuator known to date in terms of work density. As observed in many natural materials, spider silks are characterized by a strong variability in both chemical and structural organization, as for example described in the recently published experimental database of properties at different scales of about a thousand different spider silks, where evident correlations among quantities are scarce. This large variability makes the theoretical understanding of the observed material behavior, in relation of the complex hierarchical structure, particularly intriguing. To address this novel amount of experimental data without losing sight of theoretical analytical modelling, we propose a new data modelling methodology to obtain simple and interpretable relationships linking quantities at different scales. In particular, we employ a symbolic regression technique, known as 'Evolutionary Polynomial Regression', which integrates regression capabilities with the Genetic Programming paradigm, enabling the derivation of explicit analytical formulas, finally delivering a deeper comprehension of the analysed physical phenomenon. Eventually, we provide insights to improve our multiscale theoretical model accounting for the humidity effects on spider silks. This approach may represent a proof of concept for modelling in fields governed by multiscale, hierarchical differential equations. We believe that the analytical description of the macroscopic behaviour from microscale properties is of great value both for the full understanding of biological materials, as well as in the perspective of bioinspired materials and structures.

Not many studies are currently devoted to the estimation of soil moisture from space-borne SAR data at the field scale. Superficial soil moisture is indeed generally estimated from SAR images at lower resolutions, rarely reaching the sub-kilometric scale. This is mainly due to the lack of in situ data, such as measured soil moisture and parameters indicative of the soil roughness and vegetation conditions. Moreover, when working at the kilometric scale, some hypothesis assumed while modelling the backscattered SAR signal over a vegetated area are more likely satisfied, whereas when working at higher resolutions such as the field scale, other interactions should be taken into account. Indeed, over a vegetated area the total backscattered SAR signal is usually modelled as the incoherent sum of the vegetation and the soil components, and only in the last years has been added a further contribution provoked from the presence of subsurface scatterers. In the present thesis, the just mentioned contributions are considered and modelled at the field scale for soil moisture estimation purposes. A long term Change Detection method is applied to copolarized Sentinel-1 data, with a focus on taking into account the component of the total backscattering coefficient due to the presence of subsurface scatterers, recently proposed in literature. By exploiting the strong relationships detected over the study area between the copolarized signal and the observed soil moisture, the inversion algorithm for soil moisture retrieval is adapted for considering the cases of dominant subsurface scattering mechanism. Moreover, the proper time scale of detection of subsurface scattering is identified at the field scale, providing helpful information for correcting retrieval algorithms based on SAR data also at lower spatial scales.

The design of a residential building to maximize comfort and energy savings is nowadays anchored in technical guidelines, although it is clear that individual preferences and subjective experiences play an undeniable role. Starting from this conflict, this study investigates the potential of new data sources (Internet of Things) and smart home technology as tools to better investigate and understand the real needs and preferences of individual inhabitants and, at the same time, to help the building adapt and respond to its occupants. In many countries, environmental energy monitoring systems for residential buildings remain unregulated and are not mandatory, a situation attributed to the high costs, perceived invasiveness, limited flexibility, and ambiguous benefits to the end-users; consequently, even in optimal scenarios, their application is confined primarily to building managers rather than the actual occupants. With smart homes, the ability to collect data and information has exploded, as the number of low-cost sensors now available on the market. This has also led to widespread automation, with the ability not only to monitor but also to "control" the built environment. Alongside these advancements, however, lies the risk of accumulating vast amounts of data that are unmanageable and useless, lacking tangible significance. Concerns over privacy and loss of control over one's private living space are raising, coupled with skepticism regarding the true efficacy of these systems. To truly optimize building performance, particularly within the residential sector, it is imperative to first gain an in-depth understanding of the intricate interplay between the built environment and its occupants, select the right aspect to optimize, and then provide the necessary information for optimization to stakeholders. Therefore, some questions arise: Is it possible, in the right situations, to use this less invasive and less expensive technology in place of more structured monitoring systems, the same ones also used in academic research? Is it a reliable technology? Can a monitoring system bring real benefits to the inhabitant and the building in terms of energy savings and quality of life improvement? Can it be adapted to the specific preferences and needs of both the building manager and the occupant? The present study begins by examining the concepts of indoor comfort and energy use in residential settings from a new perspective, incorporating a systematic literature review that delves into socio-cultural aspects. Adopting an interdisciplinary “learning by doing” approach, it deepens the topics of user-centered monitoring, the human-building interactions, and the wide-ranging resources and potential challenges that come with domestic environments. To concretely answer the theoretical and technical questions raised, the study paired its theoretical analysis with the design and prototyping from scratch of a plug-and-play, low-cost, and non-invasive monitoring and automation system called MOQA, which leverages smart home technologies. This process facilitated a comprehensive understanding of the data lifecycle  from its production and collection to its management, presentation to key stakeholders, and final evaluation by the end-users  essentially assessing its utility. The deployment of MOQA across different case studies, alongside its evaluation against more conventional monitoring systems, enabled an examination of the system’s acceptance, functionality, user interaction, stability, and overall performance. These experiences, despite some limitations, highlighted the user's pivotal role in effectively utilizing and truly benefiting from these systems. Support from individuals with in-depth knowledge of the system and its benefits is crucial, leading to satisfaction even among people who were initially skeptical. Over time, the system proved to be stable, accurate, accepted and, eventually, integrated into daily routines. Prioritizing hands-on solutions over theoretical debates about comfort and energy norms, the smart home system is perceived, in a personal parallel with the theory of salutogenesis in architecture, as a tool capable of connecting the inhabitant with the resources available in the building. Advancement in the spontaneous and beneficial exchange between humans and the environments they live in, spanning built and natural, leads to an uplift in the quality of life. Overall, the doctoral study contributed to exploring the potential of smart homes by merging the perspectives of research and users and broadening the strictly economic and business vision currently associated with the topic. Scientific, industrial, social, and environmental implications were addressed, suggesting future lines of research.