Advective Conditions Research Articles

Nanoparticle transport in partially saturated porous media: Attachment at fluid interfaces

Like the solid-water interface (SWI), air-water and oil-water interfaces (AWI and OWI) also act as collectors for nano-sized particles in porous media. The attachment of hydrophobic nanoparticles, which is often favorable and irreversible, is of particular interest because the transport and retention of such particles is closely linked to the fate of nanoplastics in unsaturated subsurface environments and the success of nanoremediation practices. Here, we show how a pore-network model (PNM) can be used to upscale the kinetics and extent of irreversible nanoparticle attachment at a single fluid-fluid interface under conditions of advection and dispersion in a sphere packing. By focusing on a trapped (immobile) non-wetting phase, we highlight a fundamental difference between the single-collector contact efficiency of AWI/OWI and SWI. Namely, AWI/OWI collectors, which are largely by-passed by the flowing aqueous phase, are exposed to a hydrodynamic environment dominated by diffusion. This difference has profound implications for the modelling of nanoparticle transport in porous media at the continuum (Darcy) scale. This study reveals the potential of pore network modelling as an essential complement to continuum models for upscaling the behavior of nanocolloids in porous media.

Evaluation of accurate measurement methods for radon exhalation rate with advection effect and application in field

In decommissioning of a uranium tailings pond, radon exhalation rates on a beach surface should meet regulatory standards. Accurate measurements of the radon exhalation rate are demanded. However, current studies fail to consider the impact of advection under temperature variations or pressure gradients caused by gas movement on measurements using an accumulation chamber. Two proposed methods were therefore evaluated to accurately measure radon exhalation rates on the loose medium surface under advective conditions. Repeated experiments were conducted on a laboratory experimental platform filled with uranium tailings sand under advective flow rates of 0.03 and 0.3 L/min to validate the stability and reliability. Deviations between measured and true values were 0.1–6.1 % and 6.3–29.2 % for the two methods, respectively. Subsequently, numerical simulation was used to analyze defects of traditional methods and mechanisms of the new methods. In a field study, all methods were compared, and a predictive map of radon exhalation rates was created using interpolated data from 20 random sites using the new method. Results from the proposed methods, compared with traditional ones, were closer to true values under advective conditions, and accurate assessment of beach surface treatment was expected.

Improving prediction accuracy of CSM-CERES-Wheat model for water and nitrogen response using a modified Penman-Monteith equation in a semi-arid region

Context or problemThe implementation of crop models for water and nitrogen management are important in preserving water resources and reducing groundwater pollution. The Decision Support System for Agrotechnology Transfer (DSSAT) is a collection of field-scale process-based crop models that simulate crop growth and yield in response to water and nitrogen management as well as many other factors. Objective or research questionThe objective of this study was to improve the simulation of irrigation and nitrogen fertilizer effects on growth and yield of winter wheat using locally modified Penman-Monteith (PM) equation. Specifically, we focused on improving the estimation of ETo using a locally modified Penman-Monteith (PM) equation in the CSM-CERES-Wheat model. MethodsField measured data from a two-year experiment (2009–2010 and 2010–2011) in a semi-arid region were used to calibrate and evaluate the CSM-CERES-Wheat model in a region with strong advective condition. In this experiment, the irrigation treatments were 1.2, 1.0, 0.8, 0.5 times by full irrigation requirements and rain-fed, and nitrogen treatments were 0, 46, 92, and 136 kg N ha−1. ResultsUsing the CSM-CERES-Wheat model with the unmodified PM equation resulted in some growth variables such as: aboveground dry matter, grain yield, and grain nitrogen uptake with high normalized root mean square error (NRMSE) of 0.51, 0.35, and 0.32, respectively. However, using the modified PM equation for ETo module under semi-arid condition improved the soil water content estimation and the model outputs, such as the above ground dry matter, grain yield and grain nitrogen uptake with NRMSE of 0.2, 0.15 and 0.16, respectively, that are accurate. This modification provided more accurate estimations, particularly in our experimental site in semi-aid region with strong advective conditions. ConclusionsThe findings of this study indicated that the locally modified PM equation in the CSM-CERES-Wheat model enhanced the accuracy of estimating irrigation and nitrogen fertilizer on the growth and yield of winter wheat. By improving the estimation of ETo value, the model's performance in simulating crop responses to water and nitrogen management was significantly enhanced. Implications or significanceThe utilization of the accurately estimated ETo value of the modified PM equation has significant importance in the practical application of the CSM-CERES-Wheat model. Furthermore, this modification greatly enhances the accuracy of model outputs, particularly at our experimental site located in a semi-arid region with robust advective conditions.

Reference Evapotranspiration Estimation Using Genetic Algorithm-Optimized Machine Learning Models and Standardized Penman–Monteith Equation in a Highly Advective Environment

Accurate estimation of reference evapotranspiration (ETr) is important for irrigation planning, water resource management, and preserving agricultural and forest habitats. The widely used Penman–Monteith equation (ASCE-PM) estimates ETr across various timescales using ground weather station data. However, discrepancies persist between estimated ETr and measured ETr obtained from weighing lysimeters (ETr-lys), particularly in advective environments. This study assessed different machine learning (ML) models in comparison to ASCE-PM for ETr estimation in highly advective conditions. Various variable combinations, representing both radiation and aerodynamic components, were organized for evaluation. Eleven datasets (DT) were created for the daily timescale, while seven were established for hourly and quarter-hourly timescales. ML models were optimized by a genetic algorithm (GA) and included support vector regression (GA-SVR), random forest (GA-RF), artificial neural networks (GA-ANN), and extreme learning machines (GA-ELM). Meteorological data and direct measurements of well-watered alfalfa grown under reference ET conditions obtained from weighing lysimeters and a nearby weather station in Bushland, Texas (1996–1998), were used for training and testing. Model performance was assessed using metrics such as root mean square error (RMSE), mean absolute error (MAE), mean bias error (MBE), and coefficient of determination (R2). ASCE-PM consistently underestimated alfalfa ET across all timescales (above 7.5 mm/day, 0.6 mm/h, and 0.2 mm/h daily, hourly, and quarter-hourly, respectively). On hourly and quarter-hourly timescales, datasets predominantly composed of radiation components or a blend of radiation and aerodynamic components demonstrated superior performance. Conversely, datasets primarily composed of aerodynamic components exhibited enhanced performance on a daily timescale. Overall, GA-ELM outperformed the other models and was thus recommended for ETr estimation at all timescales. The findings emphasize the significance of ML models in accurately estimating ETr across varying temporal resolutions, crucial for effective water management, water resources, and agricultural planning.

Passive-tracer modelling at super-resolution with Weather Research and Forecasting – Advanced Research WRF (WRF-ARW) to assess mass-balance schemes

Abstract. Super-resolution atmospheric modelling can be used to interpret and optimize environmental observations during top-down emission rate retrieval campaigns (e.g. aircraft-based) by providing complementary data that closely correspond to real-world atmospheric pollution transport and dispersion conditions. For this work, super-resolution model simulations with large-eddy-simulation sub-grid-scale parameterization were developed and implemented using WRF-ARW (Weather Research and Forecasting - Advanced Research WRF). We demonstrate a series of best practices for improved (realistic) modelling of atmospheric pollutant dispersion at super-resolutions. These include careful considerations for grid quality over complex terrain, sub-grid turbulence parameterization at the scale of large eddies, and ensuring local and global tracer mass conservation. The study objective was to resolve small dynamical processes inclusive of spatio-temporal scales of high-speed (e.g. 100 m s−1) airborne measurements. This was achieved by downscaling of reanalysis data from 31.25 km to 50 m through multi-domain model nesting in the horizontal and grid-refining in the vertical. Further, WRF dynamical-solver source code was modified to simulate the release of passive tracers within the finest-resolution domain. Different meteorological case studies and several tracer source emission scenarios were considered. Model-generated fields were evaluated against observational data (surface monitoring network and aircraft campaign data) and also in terms of tracer mass conservation. Results indicated agreement between modelled and observed values within 5 ∘C for temperature, 1 %–25 % for relative humidity, and 1–2 standard deviations for wind fields. Model performance in terms of (global and local) tracer mass conservation was within 2 % to 5 % of model input emissions. We found that, to ensure mass conservation within the modelling domain, tracers should be released on a regular-resolution grid (vertical and horizontal). Further, using our super-resolution modelling products, we investigated emission rate estimations based on flux calculation and mass-balancing. Our results indicate that retrievals under weak advection conditions (horizontal wind speeds < 5 m s−1) are not reliable due to weak correlation between the source emission rate and the downwind tracer mass flux. In this work we demonstrate the development of accurate super-resolution model simulations useful for planning, interpreting, and optimizing top-down retrievals, and we discuss favourable conditions (e.g. meteorological) for reliable mass-balance emission rate estimations.

An independent framework-based evapotranspiration model (IFEM) for dual-source: From field to regional scale

The triangle/trapezoid framework model (TFM) is a widely used approach for mapping regional evapotranspiration (ET) based on thermal infrared remote sensing imagery. However, the homogeneity assumption for meteorological forcing and surface properties involved in TFM contradicts the characteristics of heterogeneous regions, leading to high uncertainty at regional scale, especially under energy-limited or strong advection conditions. Therefore, this study examined the linear relationship between soil moisture availability (ΛSM), evapotranspiration efficiency (ΛET) and radiation surface temperature (Trad), and developed an Independent Framework-based dual-source ET Model (IFEM) for heterogeneous regions. By fixing two key meteorological forcing variables, air temperature (Ta) and vapor pressure deficit (VPD), and three surface characteristic parameters, aerodynamic resistance (ra), albedo (α) and the ratio of soil heat flux to net radiation (Γ), the IFEM constructs a uniform fractional vegetation cover (fc)- Trad space. In this uniform fc-Trad space, isolines of ΛSM and ΛET are aligned with those of Trad, and an independent trapezoid framework is constructed for each pixel of RS images. It avoids the systematic bias caused by the distorted trapezoid space involved in traditional TFMs. The proposed model was applied in a hydrologically semi-enclosed irrigation area, the Hetao Irrigation District, with Landsat and MODIS datasets from 2016 to 2020 to evaluate its performance at the field and region scales. Firstly, the IFEM was capable of retrieving latent heat with a mean absolute error (MAE) of 34.43 W m−2 and a mean absolute percentage error (MAPE) of 8.68%, compared with the measurements from flux towers. Secondly, the IFEM reasonably separated the soil (MAPE = 21.33%) and canopy (MAPE = 14.33%) components from ET, compared with the soil evaporation observed by micro-lysimeters and the plant transpiration calculated by sap velocity upscaling technology. Thirdly, the IFEM showed high accuracy in estimating annual total ET with a percentage error range within ±3.0%, compared against the regional water balance calculations. Overall, the IFEM demonstrated high robustness and accuracy for field-scale and regional-scale applications, validating its potential as a reliable method for mapping regional ET in heterogeneous regions.

Formulation, calibration, and validation of hybrid and coupled models for the design of upflow anaerobic filters in multiple separated stages for organic matter removal from sanitary landfill leachates

AbstractIn this paper, the formulation, calibration, and validation of hybrid and coupled models for the design of upflow anaerobic filters in multiple separated stages were developed for organic matter removal from sanitary landfill leachates. Three novelties were presented, the type of reactor, design models, and kinetic coefficients. The upflow anaerobic filters were separated into two and three stages identified as UAF‐2SS (DI‐FAFS, in Spanish) and UAF‐3SS (TRI‐FAFS, in Spanish). The formulation, calibration, and validation of mathematical structures of hybrid models and five coupled models are proposed for each reactor. The hybrid models are based on the law of mass conservation, with the organic matter transformation component within the UAF‐2SS and UAF‐3SS reactors, being estimated from empirical equations that have been tested in aerobic culture reactors, adapted to the experimental factors, including among these, those under a non‐stationary—advective conditions based on Velz's Law, Phelps's Law, and Monod's equation. The coupled models combine the components of the molecular transport by biosorption and molecular diffusion processes, with adaptations of the Stack's equation and Fick's Law, as well as transformation of organic substrates by biomass, whose kinetic coefficients contribute to explain the fraction, in which, the processes of mobility and biochemical transformation of the organic matter are occurring in the biomass within the bioreactors.

Evolution of pore structure in nanoparticle deposits from unimodal to bimodal pore size distributions: Focus on structural features of dendritic structures

Nanoparticle deposits can exhibit various structures, including compact and dendritic structures, depending on the deposition conditions. While previous studies have characterized deposit structures using factors such as porosity and spatial autocorrelation index, the pore size distribution (PSD), which is an essential structural property, has only been explored in compact structures. In this study, we investigate the PSDs of the entire nanoparticle deposits, ranging from compact to dendritic structures. Deposits are formed using an off-lattice Monte Carlo simulation, and deposition conditions are represented by two dimensionless numbers (KnD, χF). The diffusive Knudsen number (KnD) ranges from 10−1.5 to 101.5, while the dimensionless translational energy of a particle (χF) ranges from 10−3 to 101.5. We use the Delaunay triangulation algorithm for fast PSD calculation, and validate the calculation method using theoretical values of ideal structures and experimental literature data. Our results show that bimodal PSDs appear under thermally-dominated conditions with high values of KnD, while unimodal PSDs with a constant mode radius (∼2.5 rp) are observed under highly advective conditions with high values of χF. We present the geometric mean radii and mode radii of pores as color-filled contours to show their variation trends with KnD and χF. Additionally, we propose a simple model that predicts dendrite width by combining the overall porosity and mode radii of pores. Our model's predictions reasonably match the dendrite width data obtained using a density-based clustering algorithm.

Investigation of sessile droplet evaporation using a transient two-step moving mesh model

The evaporation of droplets on surfaces is a ubiquitous phenomenon essential in nature and industrial applications ranging from thermal management of electronics to self-assembly-based fabrication. In this study, water droplet evaporation on a thin quartz substrate is analyzed using an unsteady two-step arbitrary Lagrangian-Eulerian (ALE) moving mesh model, wherein the evaporation process is simulated during the constant contact radius (CCR) and contact angle (CCA) modes. The numerical model considers mass transfer in the gas domain, flow in the liquid and gas domains, and heat transfer in the solid, liquid, and gas domains. Besides, the model also accounts for interfacial force balance, including thermocapillary stresses, to obtain the instantaneous droplet shape. Experiments involving droplet evaporation on unheated quartz substrates agree with model predictions of contact radius, contact angle, and droplet volume. Model results indicating temperature and velocity distribution across an evaporating water droplet show that the lowest temperatures are at the liquid-gas interface, and a single vortex exists for the predominant duration of the droplet's lifetime. The temperature of the unheated substrate is also significantly reduced due to evaporative cooling. The interfacial evaporation flux distribution, which depends on heat transfer across the droplet and advection in the surrounding medium, shows the highest values near the three-phase contact line. In addition, the model also predicts evaporation dynamics when the substrate is heated and exposed to different advection conditions. Generally, higher evaporation rates result from higher substrate heating and advection rates. However, substrate heating and advection in the surrounding gas have minimal effects on the relative durations of CCR and CCA modes for a given receding contact angle. Specifically, in this case, a 40× increase in substrate heating rate or 7.5× increase in gas velocity can only change these relative durations by 3%. This study also highlights the importance of surface wettability, which affects evaporation dynamics for all the conditions explored by the numerical model.

Using Orbiting Carbon Observatory-2 (OCO-2) column CO2 retrievals to rapidly detect and estimate biospheric surface carbon flux anomalies

Abstract. The global carbon cycle is experiencing continued perturbations via increases in atmospheric carbon concentrations, which are partly reduced by terrestrial biosphere and ocean carbon uptake. Greenhouse gas satellites have been shown to be useful in retrieving atmospheric carbon concentrations and observing surface and atmospheric CO2 seasonal-to-interannual variations. However, limited attention has been placed on using satellite column CO2 retrievals to evaluate surface CO2 fluxes from the terrestrial biosphere without advanced inversion models at low latency. Such applications could be useful to monitor, in near real time, biosphere carbon fluxes during climatic anomalies like drought, heatwaves, and floods, before more complex terrestrial biosphere model outputs and/or advanced inversion modelling estimates become available. Here, we explore the ability of Orbiting Carbon Observatory-2 (OCO-2) column-averaged dry air CO2 (XCO2) retrievals to directly detect and estimate terrestrial biosphere CO2 flux anomalies using a simple mass-balance approach. An initial global analysis of surface–atmospheric CO2 coupling and transport conditions reveals that the western US, among a handful of other regions, is a feasible candidate for using XCO2 for detecting terrestrial biosphere CO2 flux anomalies. Using the CarbonTracker model reanalysis as a test bed, we first demonstrate that a well-established mass-balance approach can estimate monthly surface CO2 flux anomalies from XCO2 enhancements in the western United States. The method is optimal when the study domain is spatially extensive enough to account for atmospheric mixing and has favorable advection conditions with contributions primarily from one background region. We find that errors in individual soundings reduce the ability of OCO-2 XCO2 to estimate more frequent, smaller surface CO2 flux anomalies. However, we find that OCO-2 XCO2 can often detect and estimate large surface flux anomalies that leave an imprint on the atmospheric CO2 concentration anomalies beyond the retrieval error/uncertainty associated with the observations. OCO-2 can thus be useful for low-latency monitoring of the monthly timing and magnitude of extreme regional terrestrial biosphere carbon anomalies.

Cellulose degradation products and high ionic strength enhance the retardation of strontium in hydrated cement paste

The present concept for the disposal of some low- and all intermediate-level radioactive waste in the United Kingdom involves grouting with cement in steel drums and placement in a geological facility. The vaults would then be backfilled with low strength, high porosity cement-based materials designed to promote a pervasive, alkaline environment in which many of the radioactive species present are sparingly soluble. This work investigates the interaction of strontium with such a backfill under both diffusive and advective conditions given the potential significance of the fission product 90Sr. An important characteristic of the United Kingdom waste inventory is the abundance of organic compounds, including cellulosic materials; consequently, the experiments were repeated with products of alkaline cellulose degradation. Additional experiments were performed at high ionic strength simulating anticipated changes in the salinity of the groundwater. The effective diffusivity (De) of strontium in the absence of the organic compounds ranged between 5.5 × 10−11 and 8.5 × 10−11 m2 s−1, with a distribution coefficient (Rd) of between 2.8 × 10−3 and 3.1 × 10−3 m3 kg−1. The presence of organic compounds and/or an increase of ionic strength enhanced the retardation of strontium. The results indicate that the retention of strontium by hydrated cement paste occurs via a reversible ion exchange mechanism rather than mineralisation and is promoted by decalcification of the calcium silicate hydrate phases.

Impact of Cloud Condensation Nuclei Reduction on Cloud Characteristics and Solar Radiation during COVID-19 Lockdown 2020 in Moscow

We used MODIS observations to retrieve number concentration of cloud droplets (Nd) at cloud lower boundary during spring 2018–2020 for the Moscow region. Looking through the similar synoptic situations of the northern clear air advection, we obtained Nd within the limits of 200–300 cm−3. During the lockdown period, with similar northern advection conditions, the reduction of Nd on 40–50 cm−3 (or 14–16%), with the increase in droplet effective radius by 8 ± 1% and cloud optical thickness reduction by 5 ± 2%, was observed in contrast to the values in typical conditions in 2018–2019. We used these values for setting up corresponding parameters in numerical simulations with the COSMO-Ru model. According to the numerical experiments, we showed that the observed reduction in cloud droplet concentration by 50 cm−3 provides a 5–9 W/m2 (or 9–11%) increase in global irradiance at ground in overcast cloud conditions with LWP = 200–400 g/m2.

Evapotranspiration uncertainty at micrometeorological scales: the impact of the eddy covariance energy imbalance and correction methods

Under ideal conditions, evapotranspiration (ET) fluxes derived through the eddy covariance (EC) technique are considered a direct measure of actual ET. Eddy covariance flux measurements provide estimates at a temporal frequency that allows examining sub-daily, daily, and seasonal scale processes and relationships between different surface fluxes. The Grape Remote Sensing Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX) project has collected micrometeorological and biophysical data to ground-truth new remote sensing tools for fine-tuning vineyard irrigation management across numerous sites since 2013. This rich dataset allows us to quantify the impact of different approaches to estimate daily ET fluxes, while accounting for energy imbalance. This imbalance results from the lack of agreement between the total available energy and turbulent fluxes derived by the EC technique. We found that different approaches to deal with this energy imbalance can lead to uncertainty in daily ET estimates of up to 50%. Over the growing season, this uncertainty can lead to considerable biases in crop water use estimates, which in some cases were equivalent to ~ 1/3rd of the total growing season applied irrigation We analyzed ET uncertainty relative to atmospheric meteorological, stability, and advective conditions, and highlight the importance of recognizing limitations of micrometeorological observational techniques, considered state of the art, to quantify ET for model validation and field-scale monitoring. This study provides a framework to quantify daily ET estimates’ uncertainty and expected reliability when using the eddy covariance technique for ground-truthing or model validation purposes.

Exploring the elevated water vapor signal associated with the free tropospheric biomass burning plume over the southeast Atlantic Ocean

Abstract. In southern Africa, widespread agricultural fires produce substantial biomass burning (BB) emissions over the region. The seasonal smoke plumes associated with these emissions are then advected westward over the persistent stratocumulus cloud deck in the southeast Atlantic (SEA) Ocean, resulting in aerosol effects which vary with time and location. Much work has focused on the effects of these aerosol plumes, but previous studies have also described an elevated free tropospheric water vapor signal over the SEA. Water vapor influences climate in its own right, and it is especially important to consider atmospheric water vapor when quantifying aerosol–cloud interactions and aerosol radiative effects. Here we present airborne observations made during the NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) campaign over the SEA Ocean. In observations collected from multiple independent instruments on the NASA P-3 aircraft (from near-surface to 6–7 km), we observe a strongly linear correlation between pollution indicators (carbon monoxide (CO) and aerosol loading) and atmospheric water vapor content, seen at all altitudes above the boundary layer. The focus of the current study is on the especially strong correlation observed during the ORACLES-2016 deployment (out of Walvis Bay, Namibia), but a similar relationship is also observed in the August 2017 and October 2018 ORACLES deployments. Using reanalyses from the European Centre for Medium-Range Weather Forecasts (ECMWF) and Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), and specialized WRF-Chem simulations, we trace the plume–vapor relationship to an initial humid, smoky continental source region, where it mixes with clean, dry upper tropospheric air and then is subjected to conditions of strong westward advection, namely the southern African easterly jet (AEJ-S). Our analysis indicates that air masses likely left the continent with the same relationship between water vapor and carbon monoxide as was observed by aircraft. This linear relationship developed over the continent due to daytime convection within a deep continental boundary layer (up to ∼5–6 km) and mixing with higher-altitude air, which resulted in fairly consistent vertical gradients in CO and water vapor, decreasing with altitude and varying in time, but this water vapor does not originate as a product of the BB combustion itself. Due to a combination of conditions and mixing between the smoky, moist continental boundary layer and the dry and fairly clean upper-troposphere air above (∼6 km), the smoky, humid air is transported by strong zonal winds and then advected over the SEA (to the ORACLES flight region) following largely isentropic trajectories. Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT) back trajectories support this interpretation. This work thus gives insights into the conditions and processes which cause water vapor to covary with plume strength. Better understanding of this relationship, including how it varies spatially and temporally, is important to accurately quantify direct, semi-direct, and indirect aerosol effects over this region.

Water vapor density and turbulent fluxes from three generations of infrared gas analyzers

Abstract. Fast-response infrared gas analyzers (IRGAs) have been widely used over 3 decades in many ecosystems for long-term monitoring of water vapor fluxes in the surface layer of the atmosphere. While some of the early IRGA sensors are still used in these national and/or regional eco-flux networks, optically improved IRGA sensors are newly employed in the same networks. The purpose of this study was to evaluate the performance of water vapor density and flux data from three generations of IRGAs – LI-7500, LI-7500A, and LI-7500RS (LI-COR Bioscience, Inc., Nebraska, USA) – over the course of a growing season in Bushland, Texas, USA, in an irrigated maize canopy for 90 d. Water vapor density measurements were in generally good agreement, but temporal drift occurred in different directions and magnitudes. Means exhibited mostly shift changes that did not impact the flux magnitudes, while their variances of water vapor density fluctuations were occasionally in poor agreement, especially following rainfall events. LI-7500 cospectra were largest compared to LI-7500RS and LI-7500A, especially under unstable and neutral static stability. Agreement among the sensors was best under the typical irrigation-cooled boundary layer, with a 14 % interinstrument coefficient of variability under advective conditions. Generally, the smallest variances occurred with the LI-7500RS, and high-frequency spectral corrections were larger for these measurements, resulting in similar fluxes between the LI-7500A and LI-7500RS. Fluxes from the LI-7500 were best representative of growing season ET based on a world-class lysimeter reference measurement, but using the energy balance ratio as an estimate of systematic bias corrected most of the differences among measured fluxes.

Energy Imbalance and Evapotranspiration Hysteresis Under an Advective Environment: Evidence From Lysimeter, Eddy Covariance, and Energy Balance Modeling

AbstractSurface energy imbalance problems have been underexplored especially under advective environments. Here, we present a novel analysis of surface energy fluxes from three distinct approaches—weighing lysimeter, eddy covariance (EC), and surface energy balance modeling for the 2014 sorghum and 2016 corn crop seasons in Bushland, Texas. Our results suggest that energy imbalance problems in the EC system were evidently associated with two opposite evapotranspiration (ET) hysteresis patterns with respect to net radiation and water vapor pressure deficit (VPD). The lysimeter ET had the smallest ET hysteresis while the eddy covariance ET results indicated the strongest hysteresis with respect to net radiation. Conversely, the lysimeter ET hysteresis related to water VPD was stronger than that of the eddy covariance method. This study provides understanding of ET hysteresis patterns, energy imbalance, and advective conditions associated with turbulent flux dynamics for both diel and crop growing seasonal timescales in Bushland, Texas.

Colloid-facilitated transport of 238Pu, 233U and 137Cs through fractured chalk: Laboratory experiments, modelling, and implications for nuclear waste disposal

The influence of montmorillonite colloids on the mobility of 238Pu, 233U and 137Cs through a chalk fracture was investigated to assess the transport potential for radioactive waste. Radioisotopes of each element, along with the conservative tracer tritium, were injected in the presence and absence of montmorillonite colloids into a naturally fractured chalk core. In parallel, batch experiments were conducted to obtain experimental sorption coefficients (Kd, mL/g) for both montmorillonite colloids and the chalk fracture material. Breakthrough curves were modelled to determine diffusivity and sorption of each radionuclide to the chalk and the colloids under advective conditions. Uranium sorbed sparingly to chalk (log Kd = 0.7 ± 0.2) in batch sorption experiments. 233U(VI) breakthrough was controlled primarily by the matrix diffusion and sorption to chalk (15 and 25% recovery with and without colloids, respectively). Cesium, in contrast, sorbed strongly to both the montmorillonite colloids and chalk (batch log Kd = 3.2 ± 0.01 and 3.9 ± 0.01, respectively). The high affinity to chalk and low colloid concentrations overwhelmed any colloidal Cs transport, resulting in very low 137Cs breakthrough (1.1–5.5% mass recovery). Batch and fracture transport results, and the associated modelling revealed that Pu migrates both as Pu (IV) sorbed to montmorillonite colloids and as dissolved Pu(V) (7% recovery). Transport experiments revealed differences in Pu(IV) and Pu(V) transport behavior that could not be quantified in simple batch experiments but are critical to effectively predict transport behavior of redox-sensitive radionuclides. Finally, a brackish groundwater solution was injected after completion of the fracture flow experiments and resulted in remobilization and recovery of 2.2% of the total sorbed radionuclides which remained in the core from previous experiments. In general, our study demonstrates consistency in sorption behavior between batch and advective fracture transport. The results suggest that colloid-facilitated radionuclide transport will enhance radionuclide migration in fractured chalk for those radionuclides with exceedingly high affinity for colloids.

Downscaling NLDAS-2 daily maximum air temperatures using MODIS land surface temperatures.

We have developed and applied a relatively simple disaggregation scheme that uses spatial patterns of Land Surface Temperature (LST) from MODIS warm-season composites to improve the spatial characterization of daily maximum and minimum air temperatures. This down-scaling model produces qualitatively reasonable 1 km daily maximum and minimum air temperature estimates that reflect urban and coastal features. In a 5-city validation, the model was shown to provide improved daily maximum air temperature estimates in the three coastal cities, compared to 12 km NLDAS-2 (North American Land Data Assimilation System). Down-scaled maximum temperature estimates for the other two (non-coastal) cities were marginally worse than the original NLDAS-2 temperatures. For daily minimum temperatures, the scheme produces spatial fields that qualitatively capture geographic features, but quantitative validation shows the down-scaling model performance to be very similar to the original NLDAS-2 minimum temperatures. Thus, we limit the discussion in this paper to daily maximum temperatures. Overall, errors in the down-scaled maximum air temperatures are comparable to errors in down-scaled LST obtained in previous studies. The advantage of this approach is that it produces estimates of daily maximum air temperatures, which is more relevant than LST in applications such as public health. The resulting 1 km daily maximum air temperatures have great potential utility for applications such as public health, energy demand, and surface energy balance analyses. The method may not perform as well in conditions of strong temperature advection. Application of the model also may be problematic in areas having extreme changes in elevation.

Numeric benchmark study of plate vibration experiments in air and water

Numerous power generation technologies rely on plate geometry for the purpose of transporting heat through and across mediums. In the case of nuclear technology, this is relevant to that of plate-type-fuel and compact heat-exchangers; these components have high surface area to volume ratio provide ideal capacity for heat transfer to and through their respective parts. However, under highly advective conditions these plate-type geometries are susceptible to buckling and vibration which have possible safety-related implications associated with them. These complex phenomena occurring through fluid-structure-interactions have traditionally been quite difficult to predict using computational tools given their stiffly coupled nature. While recent efforts have demonstrated well aligned agreement with the use of advanced computational tools to predict flutter and buckling of unique mechanical geometries these tools have been found to consume significant computational resources not available to many within the community. This study investigates an industry tool's ability to compute the natural frequency of plates under various boundary conditions for the purpose of demonstrating relevance and limitations of its computing capacity when compared against experimental data to develop an objective basis for the use of such a tool in design and safety related predictions of components which comprise plate-type geometries. The goal of this study is to demonstrate a new method using an off-the-shelf software tool which is capable of operating on a standard desktop workstation and can readily predict the dynamic response of a mechanical structure in a fluid environment – a capability not previously demonstrated or otherwise shown to be successful in literature. A set of experimental plates were characterized to understand their dynamic response in both air and water. In an attempt to gain further insight into the vibration of the experimental test plates, a numeric benchmark study was performed to calculate their fundamental frequencies in both air and water, employing a novel modeling method to simulate submersion; one which allowed both the plate and the fluid domain to be modeled exclusively in a computational structural mechanics software package. Results show that the air simulation compares well with the analytic solutions; however comparison against experimental data is challenging, with no obvious trends present. Given the available experimental data, select air simulations are quite accurate, and careful selection of numeric boundary conditions yields representative results for alternative experimental boundary conditions. For simulations of plates submerged underwater, larger data sets for both experimental and numeric will be required to establish trends with a high degree of confidence; however preliminary results suggest the method can be accurate to a first order of magnitude approximation, requiring minimal computational resources.

A low‐cost underwater particle tracking velocimetry system for measuring in situ particle flux and sedimentation rate in low‐turbulence environments

AbstractWe describe a low‐cost three‐dimensional underwater particle tracking velocimetry system to directly measure particle settling rate and flux in low‐turbulence aquatic environments. The system consists of two waterproof cameras that acquire stereoscopic videos of sinking particles at 48 frames s−1 over a tunable sampling volume of about 45 × 25 × 24 cm. A dedicated software package has been developed to allow evaluation of particle velocities, concentration and flux, but also of morphometric parameters such as particle area, sinking angle, shape irregularity, and density. Our method offers several advantages over traditional approaches, like sediment trap or expensive in situ camera systems: (1) it does not require beforehand particle collection and handling; (2) it is not subjected to sediment trap biases from turbulence, horizontal advection, or presence of swimmers, that may alter particulate load and flux; (3) the camera system enables faster data processing and flux computation at higher spatial resolution; (4) apart from the particle settling rates, the particle size distribution, and morphology is determined. We tested the camera system in Lake Stechlin (Germany) in low turbulence and mean flow, and analyzed the morphological properties and settling rates of particles to determine their sinking behavior. The particle flux assessed from conventional sediment trap measurements agreed well with that determined by our system. By this, the low‐cost approach demonstrated its reliability in low turbulence environments and a strong potential to provide new insights into particulate carbon transport in aquatic systems. Extension of the method to more turbulent and advective conditions is also discussed.