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The authors study small disturbances to the periodic, plane Couette flow in the 3D incompressible Navier-Stokes equations at high Reynolds number Re. They prove that for sufficiently regular initial data of size $\\epsilon \\leq c_0\\mathbf {Re}^-1$ for some universal $c_0 > 0$, the solution is global, remains within $O(c_0)$ of the Couette flow in $L^2$, and returns to the Couette flow as $t \\rightarrow \\infty $. For times $t \\gtrsim \\mathbf {Re}^1/3$, the streamwise dependence is damped by a mixing-enhanced dissipation effect and the solution is rapidly attracted to the class of \"2.5 dimensional\" streamwise-independent solutions referred to as streaks.

Catchment‐scale hydrological models encountered dichotomies with the numerical hydrodynamic models when describing surface routing process. We propose a new modeling framework, the so‐called “Runoff‐On‐Grid” approach, for embedding distributed process‐based hydrological modeling into shallow water models, as an alternative to the traditional Fully Hydrodynamic Approach (also known as Rain‐On‐Grid). Antecedent Soil Moisture, subsurface dynamics, and other topsoil hydrological processes are implicitly integrated in the governing hydrodynamic equations via the proposed methodology. The resulting hydrological‐hydrodynamic coupling, based on the DREAM distributed hydrological model and the Iber+ shallow water model, enhances the capabilities of both reference models. Through introducing non‐negligible runoff generation sources, the Runoff‐On‐Grid approach extends the surface hydrodynamic modeling to medium‐sized vegetated and/or (semi)humid catchments, bypassing the limitations of the widespread hydrological losses' empirical formulations. Employed in an event‐based analysis within a High‐Performance Computing framework, the DREAM‐Iber model provides an efficient and reliable reconstruction of the November 2020 flood that occurred in Crotone (Italy), envisaging consequences of similar future scenarios. We show that the proposed modeling technique, nested within emerging environmental technologies and robust on‐site data, details the flood hazard inducing processes merging physical hydrology with advanced hydrodynamics. Plain Language Summary In this scientific contribution, the potential of combining two different operational tools, namely distributed rainfall‐runoff and flood models, is investigated. An hindcast procedure has been used as reference to assess both the hydrological processes and the inundations at the catchment‐scale. In this context, were exploited cutting edge computational and environmental technologies, which significantly quickened the simulations and enabled a high‐fidelity reconstruction of the extreme meteorological event. According to our findings, there is merit of the proposed approach for bridging the dichotomies between the hydrological and hydrodynamic simulators. This can favor of a more comprehensive method to reduce the limitation of the standalone models. Key Points The Runoff‐On‐Grid approach integrates subsurface hydrological processes, antecedent soil moisture and soil physics in shallow water models The Runoff‐On‐Grid approach expands the capabilities of the Rain‐On‐Grid approach introducing non‐negligible runoff generation sources The DREAM‐Iber model supported by enabling technologies provides a high‐fidelty reconstruction of the 2020 Esaro flood

Satellite remote sensing enhances model predictions by providing insights into terrestrial and hydrological processes. While data assimilation techniques have proven promising, there is a lack of standardized and effective approaches for integrating multiple observations simultaneously. This study presents a novel assimilation framework, the multi‐observation local ensemble‐Kalman‐filter (MoLEnKF), designed to effectively integrate multiple variables, even at scales different than the model. Evaluation of MoLEnKF in the Amazon River basin includes assimilation experiments with remote sensing data only, including water surface elevation (WSE), terrestrial water storage (TWS), flood extent (FE), and soil moisture (SM). MoLEnKF demonstrates improvements in a scenario where regions lack in‐situ hydroclimatic records and when assuming uncertainties of large‐scale hydrologic‐hydrodynamic models. Assimilating WSE outperforms daily discharge and water‐level estimations, achieving 38% and 36% error reduction, respectively. However, the monthly evapotranspiration estimate achieves the greatest error reduction by assimilating SM with 11%. MoLEnKF always remains in second position in a ranking of error and uncertainty reduction, providing an intermediate condition, being able to holistically outperform univariate experiments. MoLEnKF also outperform state‐of‐the‐art models in many cases. This study suggests potential improvements, urging exploration of correlations between assimilated variables and adaptive localization methods based on seasonality. The flexibility and the elegant way of expressing the LEnKF equations by MoLEnKF facilitates their application with different types of variables, compatible with large‐scale hydrologic‐hydrodynamic models and missions such as SWOT. Its robustness ensures easy replicability worldwide, facilitating hydrological reanalysis and improved forecasting, establishing MoLEnKF as a valuable tool for the scientific community in hydrological research.

Contamination of nano‐biothreats, such as viruses, mycoplasmas, and pathogenic bacteria, is widespread in cell cultures and greatly threatens many cell‐based bio‐analysis and biomanufacturing. However, non‐invasive trapping and removal of such biothreats during cell culturing, particularly many precious cells, is of great challenge. Here, inspired by the wake‐riding effect, a biocompatible opto‐hydrodynamic diatombot (OHD) based on optical trapping navigated rotational diatom (Phaeodactylum tricornutum Bohlin) for non‐invasive trapping and removal of nano‐biothreats is reported. Combining the opto‐hydrodynamic effect and optical trapping, this rotational OHD enables the trapping of bio‐targets down to sub‐100 nm. Different nano‐biothreats, such as adenoviruses, pathogenic bacteria, and mycoplasmas, are first demonstrated to be effectively trapped and removed by the OHD, without affecting culturing cells including precious cells such as hippocampal neurons. The removal efficiency is greatly enhanced via reconfigurable OHD array construction. Importantly, these OHDs show remarkable antibacterial capability, and further facilitate targeted gene delivery. This OHD serves as a smart micro‐robotic platform for effective trapping and active removal of nano‐biothreats in bio‐microenvironments, and especially for cell culturing of many precious cells, with great promises for benefiting cell‐based bio‐analysis and biomanufacturing. Inspired by the wake‐riding effect, this work reports a biocompatible opto‐hydrodynamic diatombot (OHD) based on optical trapping navigated rotational diatom for non‐invasive trapping and removal of nano‐biothreats with sizes down to sub‐100 nm such as adenoviruses, pathogenic bacteria, and mycoplasmas. This OHD can be directly used in cell cultures, without affecting culturing cells including precious cells such as hippocampal neurons.

Flash flooding has become more prominent under climate change, threatening people's life and property. Post‐event investigations of recent events emphasize the role of floating debris, such as vehicles, in exacerbating damage. Few modeling methods and tools have been developed to simulate the full‐process dynamics of floating debris driven by large‐scale flood waves in real world. In this work, a fully coupled model is developed for simulating the full‐process interactive movements of vehicles driven by flash flood hydrodynamics, from entrainment, transport to deposition. The proposed coupled modeling system consists of a finite volume shock‐capturing hydrodynamic model solving the 2D shallow water equations and a 3D discrete element method (DEM) model. The proposed two‐way coupling approach estimates the hydrostatic and hydrodynamic forces acting on solid objects using the water depth and velocity predicted by the hydrodynamic model; the resulting counter forces on the fluid flow are then considered by adding extra source terms in the hydrodynamic model. A multi‐sphere method is further embedded in the DEM model to better represent vehicle shapes. New calculation modules are further implemented to represent the vehicle entrainment, contact and stopping motions. The coupled model is applied to reproduce a flash flood event hit Boscastle in the UK in 2004. Over 100 vehicles were moved and carried downstream by the highly transient flood flow. The model well predicts the hydrodynamics, interactive transport process and the final locations of vehicles. The proposed coupled model provides a new tool for simulating large‐scale flash flooding processes, including debris dynamics. Key Points A new coupled model for simulation of entrainment, transport and deposition of vehicles driven by and interacting with flood hydrodynamics The model is used to reproduce a flash flood event that moved over 100 vehicles, with results consistent with post‐event report and survey Increasing number of floating vehicles alters flood hydrodynamics and intensifies debris‐debris and debris‐fluid interactions

Recently, non-reciprocal systems have become a focus of growing interest. Examples occur in soft and active matter, but also in engineered quantum materials and neural (brain) networks. Here, we investigate the impact of non-reciprocity on the collective behavior of a system of (dry) chiral active matter. Specifically, we consider a mixture of ‘circle swimmers’ with steric interactions and non-reciprocal alignment couplings. Based on hydrodynamic equations which we derive from a set of Langevin equations, we explore the interplay of non-reciprocity, finite size, and chirality. We first consider, as a reference, one-species systems with reciprocal couplings. Based on a linear stability analysis and numerical simulations, we here observe three different types of collective behavior, that is, flocking, motility-induced phase separation, and a combination of both. Turning then to a non-reciprocal system, we find that non-reciprocity can turn otherwise stationary instabilities into oscillatory ones, affect the relative orientation of flocks, and, crucially, change the general type of instability. This illustrates the drastic impact of non-reciprocity on the emergent collective dynamics of chiral active matter systems, with potentially far-reaching biological implications.

This is the second in a pair of works which study small disturbances to the plane, periodic 3D Couette flow in the incompressible Navier-Stokes equations at high Reynolds number

Turbulent heat fluxes are affected by and influence the temperature dynamics and ice conditions of lakes. Significant efforts have been made to develop operational hydrodynamic and ice models for large lakes such as the North American Great Lakes. However, the behavior of surface fluxes in these lakes has previously focused on the ice‐free season and has not yet been fully assessed during winter conditions in the presence of ice. Given the importance of navigation support and regional weather forecasting, we therefore analyze operational configurations of the Great Lakes for modeled fluxes to evaluate them for open water, ice‐covered, and partial ice conditions. We compare the modeled fluxes with eddy covariance‐based observed fluxes from the Great Lakes Evaporation Network. While observed latent heat fluxes have periods of high values both during ice‐free and ice‐covered periods, we find that elevated open water fluxes in early winter can be well modeled. However, the modeled fluxes during ice‐covered periods appear less accurate, where the errors are likely related to the simulated ice thickness. Thin ice has many small cracks, resulting in large fluxes nearly as high as over open water; very thick ice can reduce the latent fluxes to near zero, according to observations. Overall, the algorithms used in existing operational models show promise in resolving winter lake fluxes; however, further improvement may require adaptations to underlying ice and hydrodynamic model formulations.

Floodplain lakes are widespread and ecologically important throughout tropical river systems, however data are rare that describe how temporal variations in hydrological, meteorological and optical conditions moderate stratification and mixing in these shallow lakes. Using time series measurements of meteorology and water‐column temperatures from 17 several day campaigns spanning two hydrological years in a representative Amazon floodplain lake, we calculated surface energy fluxes and thermal stratification, and applied and evaluated a 3‐dimensional hydrodynamic model. The model successfully simulated diel cycles in thermal structure characterized by buoyancy frequency, depth of the actively mixing layer, and other terms associated with the surface energy budget. Diurnal heating with strong stratification and nocturnal mixing were common; despite considerable heat loss at night, the strong stratification during the day meant that mixing only infrequently extended to the bottom at night. Simulations indicated that the diurnal thermocline up and downwelled creating lake‐wide differences in near‐surface temperatures and mixing depths. Infrequent full mixing creates conditions conducive to anoxia in these shallow lakes given their warm temperatures. Key Points Diel thermal structure in a tropical floodplain lake was characterized by high‐resolution field measurements over two hydrological years State and process evaluation show that diel and seasonal stratification and mixing were simulated well by a 3‐D hydrodynamic model Diurnal heating with strong stratification and nocturnal mixing were common while mixing to the bottom was intermittent

Floods have always been associated with widespread devastation and destruction since the emergence of human civilization. The intensity of this disaster has been increasing due to accelerated impact of human activities. Flood vulnerability is very diverse in nature and is multidimensional and a topic of vital significance. Hence, flood vulnerability assessment assumes greater significance since magnitude of destructions varies over space and time. The study makes a credible attempt to present a coherent review on the approaches and methodologies used for assessing flood and its vulnerability. A time frame of 1990–2018 was chosen for analyzing varied works carried out flood vulnerability and susceptibility assessment. Articles from Scopus and other reputed journals were used to review the works on flood assessments. Methods and approaches were examined by considering most-cited authors and keywords used in their works. The study revealed a gap existing between methods and approaches for evaluating flood vulnerability which can be incorporated by using high-resolution data along with using multidimensional approach for assessing vulnerability. Furthermore, this study calls for comprehensive flood assessment using artificial neural network, hydrodynamic models and geospatial techniques to provide a vivid visualization of flood susceptibility. The study may prove helpful in analyzing different components of vulnerability and guiding research gaps in methodology to be used for assessing flood vulnerability at spatial scales.