scholarly journals Estimating Hydrothermal Properties and High-Frequency Fluxes From Geophysical Measurements in the Hyporheic Zone

2021 ◽  
Vol 3 ◽  
Author(s):  
Karina Cucchi ◽  
Nicolas Flipo ◽  
Agnès Rivière ◽  
Yoram N. Rubin
Keyword(s):  
High Frequency ◽  
Large Scale ◽  
Hyporheic Zone ◽  
Water Fluxes ◽  
Riverine Ecosystems ◽  
Hyporheic Zones ◽  
Data Points ◽  
Heat Exchanges ◽  
Dynamic Exchange

Located in the critical zone at the intersection between surface water and groundwater, hyporheic zones (HZ) host a variety of hydrological, biological and biogeochemical processes regulating water availability and quality and sustaining riverine ecosystems. However, difficulty in quantifying water fluxes along this interface has limited our understanding of these processes, in particular under dynamic flow conditions where rapid variations can impact large-scale HZ biogeochemical function. In this study, we introduce an innovative measurement assimilation chain for determining uncertainty-quantified hydraulic and thermal HZ properties, as well as associated uncertainty-quantified high-frequency water fluxes. The chain consists in the assimilation of data collected with the LOMOS-mini geophysical device with a process-based, Bayesian approach. The application of this approach on a synthetic case study shows that hydraulic and thermal HZ properties can be estimated from LOMOS-mini measurements, their identifiability depending on the Peclet number – summarizing the hydrological and thermal regime. Hydraulic conductivity values can be estimated with precision when greater than ~10−5m · s−1 when other HZ properties are unknown, with decreasing uncertainty when other HZ properties are known prior to starting the LOMOS-mini measurement assimilation procedure. Water fluxes can be estimated in all regimes with varying accuracy, highest accuracy is reached for fluxes greater than ~10−6m · s−1, except under highly conductive exfiltration regimes. We apply the methodology on in situ datasets by deriving uncertainty-quantified HZ properties and water fluxes for 2 data points collected during field campaigns. This study demonstrates that the LOMOS-mini monitoring technology can be used as complete and stand-alone sampling solution for quantifying water and heat exchanges under dynamic exchange conditions (time resolution < 15 min).

Tracing plant water fluxes in ecosystems by stable isotopes along the soil-plant and plant-atmosphere interfaces

2020 ◽  
Author(s):  
Christiane Werner
Keyword(s):  
Water Uptake ◽  
Large Scale ◽  
Temporal Dynamics ◽  
Root Water Uptake ◽  
Plant Water ◽  
Water Fluxes ◽  
Terrestrial Vegetation ◽  
Species Specific ◽  
The Impact

<p>Terrestrial vegetation is a main driver of ecosystem water fluxes, as plants mediate the water fluxes within the soil-vegetation-atmosphere continuum. Stable isotopologues of water are efficient tracer to follow the water transfer in soils, uptake by plants, transport in stems and release into the atmosphere through stomata. The development of in-situ methods coupled to isotope spectroscopy does now enable real-time in-situ water vapour isotopologue measurements revealing high spatial and temporal dynamics, such as adaptations in root water uptake depths (within hours to days) or the impact of transpirational fluxes on atmospheric moisture.</p><p>Examples will be given how isotopes can be used to inform the complex interplay between plant ecophysiological adaptations and hydrological processes. For example, root water uptake is not solely driven by soil water availability but has to be understood in the context of species-specific regulation of active zones in their rooting system determining the conductivity between soil and roots regulating uptake depths. The latter has also to be evaluated in context of the nutrient demand and the spatial nutrient availability. Similarly, plant water transport and losses are a fined tuned interplay between species-specific structural and functional adaptations and atmospheric processes.</p><p>Finally, first data of a large-scale ecosystem labelling experiment at the Biosphere 2 tropical rainforest of the B2 Wald, Atmosphere, and Live Dynamics (B2WALD) will be presented.</p>

Response of the North Atlantic circulation to the small-scale surface wind perturbations

2020 ◽  
Author(s):  
Shenjie Zhou ◽  
Xiaoming Zhai ◽  
Ian Renfrew
Keyword(s):  
Ocean Circulation ◽  
High Frequency ◽  
General Circulation ◽  
Large Scale ◽  
Sea Surface ◽  
Small Scale ◽  
Local Response ◽  
High Frequencies ◽  
Wind Variability

<p>High-frequency and small-scale processes in the atmosphere have an important influence on the evolution of the underlying ocean. They can not only introduce variability to the coupled systems but also have long-term ramification effects on the sea surface temperature, thermocline structure and large-scale ocean general circulation via nonlinear interactions.</p><p>Comparisons between the newly-released ECMWF fifth-generation global climate reanalyses (ERA5) wind product and satellite/in-situ observations show that the latest reanalyses winds still considerably underestimate wind variability at high-frequencies and small-scales. A novel approach, Cellular Automata (CA), is used here to stochastically perturb the ERA5 wind field. CA, originally introduced into the weather forecast model to mimic the near-grid-scale variability associated with convective cloud clustering, generates spatially and temporally coherent perturbation patterns. Results show that the CA-perturbed ERA5 wind field enjoys an improved wavenumber spectrum, especially over high wavenumber bands (scales <400 km), when compared to the QuikSCAT measurements. In addition, including CA patterns also brings the level of wind variability at high-frequencies (>1 cpd) closer to in-situ mooring measurements. The local response of the upper ocean properties is investigated by a Multi-Column K-Profile Parameterization (MC_KPP) ocean mixed layer model over Atlantic section. It is found that overall the sea surface temperature (SST) decreases and oceanic boundary layer (OBL) deepens to respond to the enhanced surface turbulent heat loss and shear instability generated at the base of surface OBL caused by the small-scale wind perturbations. In particular, SST tends to decrease the most over the summer hemisphere by up to 1°C locally and 0.1°C averaging across the basin, in correlation with shallower background OBL and smaller OBL heat capacity. </p><p>The ocean states under the forcing of stochastic wind perturbation as expressed by the local response are found rectified by a non-negilible magnitude. We argued that although the missed small-scale and high-frequency wind variability may be represented differently than our approach, our results highlighted the fact that these variabilities should take a singificant part in driving the current generation of coupled climate model. Furhtermore, the temproal and spatial variabilities of the local signals can pose significant influence on the large-scale ocean circulation in terms of their pathways, strengths and variabilities. The dynamical response of the ocean circulation is to be further understood with an eddy-resolving Massachusette Institute of Technology General Circulation Model (MITgcm).</p>

In-situ compaction and sintering of Al2O3 – GNP nanoparticles using a high-frequency induction system

2018 ◽  
Vol 60 (7-8) ◽  
pp. 727-732
Author(s):  
Uğur Çavdar ◽  
İ. Murat Kusoglu ◽  
Ayberk Altintas
Keyword(s):  
High Frequency ◽  
Induction System ◽  
High Frequency Induction

scholarly journals IMPROVING SYSTEM READINESS, STAFF PREPAREDNESS AND PATIENT SAFETY IN A NEW SINGLE FAMILY ROOM NICU THROUGH IN SITU SIMULATION

2018 ◽  
Vol 23 (suppl_1) ◽  
pp. e16-e16
Author(s):  
Ahmed Moussa ◽  
Audrey Larone-Juneau ◽  
Laura Fazilleau ◽  
Marie-Eve Rochon ◽  
Justine Giroux ◽  
...  
Keyword(s):  
Patient Safety ◽  
Repeated Measures ◽  
Large Scale ◽  
Multidisciplinary Teams ◽  
Single Family ◽  
In Situ Simulation ◽  
Ensure Patient Safety ◽  
System Readiness ◽  
Dependent Samples

Abstract BACKGROUND Transitions to new healthcare environments can negatively impact patient care and threaten patient safety. Immersive in situ simulation conducted in newly constructed single family room (SFR) Neonatal Intensive Care Units (NICUs) prior to occupancy, has been shown to be effective in testing new environments and identifying latent safety threats (LSTs). These simulations overlay human factors to identify LSTs as new and existing process and systems are implemented in the new environment OBJECTIVES We aimed to demonstrate that large-scale, immersive, in situ simulation prior to the transition to a new SFR NICU improves: 1) systems readiness, 2) staff preparedness, 3) patient safety, 4) staff comfort with simulation, and 5) staff attitude towards culture change. DESIGN/METHODS Multidisciplinary teams of neonatal healthcare providers (HCP) and parents of former NICU patients participated in large-scale, immersive in-situ simulations conducted in the new NICU prior to occupancy. One eighth of the NICU was outfitted with equipment and mannequins and staff performed in their native roles. Multidisciplinary debriefings, which included parents, were conducted immediately after simulations to identify LSTs. Through an iterative process issues were resolved and additional simulations conducted. Debriefings were documented and debriefing transcripts transcribed and LSTs classified using qualitative methods. To assess systems readiness and staff preparedness for transition into the new NICU, HCPs completed surveys prior to transition, post-simulation and post-transition. Systems readiness and staff preparedness were rated on a 5-point Likert scale. Average survey responses were analyzed using dependent samples t-tests and repeated measures ANOVAs. RESULTS One hundred eight HCPs and 24 parents participated in six half-day simulation sessions. A total of 75 LSTs were identified and were categorized into eight themes: 1) work organization, 2) orientation and parent wayfinding, 3) communication devices/systems, 4) nursing and resuscitation equipment, 5) ergonomics, 6) parent comfort; 7) work processes, and 8) interdepartmental interactions. Prior to the transition to the new NICU, 76% of the LSTs were resolved. Survey response rate was 31%, 16%, 7% for baseline, post-simulation and post-move surveys, respectively. System readiness at baseline was 1.3/5,. Post-simulation systems readiness was 3.5/5 (p = 0.0001) and post-transition was 3.9/5 (p = 0.02). Staff preparedness at baseline was 1.4/5. Staff preparedness post-simulation was 3.3/5 (p = 0.006) and post-transition was 3.9/5 (p = 0.03). CONCLUSION Large-scale, immersive in situ simulation is a feasible and effective methodology for identifying LSTs, improving systems readiness and staff preparedness in a new SFR NICU prior to occupancy. However, to optimize patient safety, identified LSTs must be mitigated prior to occupancy. Coordinating large-scale simulations is worth the time and cost investment necessary to optimize systems and ensure patient safety prior to transition to a new SFR NICU.

scholarly journals Mapping High Spatiotemporal-Resolution Soil Moisture by Upscaling Sparse Ground-Based Observations Using a Bayesian Linear Regression Method for Comparison with Microwave Remotely Sensed Soil Moisture Products

2021 ◽  
Vol 13 (2) ◽  
pp. 228
Author(s):  
Jian Kang ◽  
Rui Jin ◽  
Xin Li ◽  
Yang Zhang
Keyword(s):  
Soil Moisture ◽  
Large Scale ◽  
Spatial Scales ◽  
Microwave Remote Sensing ◽  
In Situ Measurements ◽  
Spatial Density ◽  
Linear Regression Method ◽  
Spatiotemporal Resolution ◽  
Pixel Scale

In recent decades, microwave remote sensing (RS) has been used to measure soil moisture (SM). Long-term and large-scale RS SM datasets derived from various microwave sensors have been used in environmental fields. Understanding the accuracies of RS SM products is essential for their proper applications. However, due to the mismatched spatial scale between the ground-based and RS observations, the truth at the pixel scale may not be accurately represented by ground-based observations, especially when the spatial density of in situ measurements is low. Because ground-based observations are often sparsely distributed, temporal upscaling was adopted to transform a few in situ measurements into SM values at a pixel scale of 1 km by introducing the temperature vegetation dryness index (TVDI) related to SM. The upscaled SM showed high consistency with in situ SM observations and could accurately capture rainfall events. The upscaled SM was considered as the reference data to evaluate RS SM products at different spatial scales. In regard to the validation results, in addition to the correlation coefficient (R) of the Soil Moisture Active Passive (SMAP) SM being slightly lower than that of the Climate Change Initiative (CCI) SM, SMAP had the best performance in terms of the root-mean-square error (RMSE), unbiased RMSE and bias, followed by the CCI. The Soil Moisture and Ocean Salinity (SMOS) products were in worse agreement with the upscaled SM and were inferior to the R value of the X-band SM of the Advanced Microwave Scanning Radiometer 2 (AMSR2). In conclusion, in the study area, the SMAP and CCI SM are more reliable, although both products were underestimated by 0.060 cm3 cm−3 and 0.077 cm3 cm−3, respectively. If the biases are corrected, then the improved SMAP with an RMSE of 0.043 cm3 cm−3 and the CCI with an RMSE of 0.039 cm3 cm−3 will hopefully reach the application requirement for an accuracy with an RMSE less than 0.040 cm3 cm−3.

scholarly journals Global soil moisture data derived through machine learning trained with in-situ measurements

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Sungmin O. ◽  
Rene Orth
Keyword(s):  
Machine Learning ◽  
Soil Moisture ◽  
Large Scale ◽  
Short Term Memory ◽  
Temporal Dynamics ◽  
Soil Moisture Data ◽  
Wide Range ◽  
Global Soil

AbstractWhile soil moisture information is essential for a wide range of hydrologic and climate applications, spatially-continuous soil moisture data is only available from satellite observations or model simulations. Here we present a global, long-term dataset of soil moisture derived through machine learning trained with in-situ measurements, SoMo.ml. We train a Long Short-Term Memory (LSTM) model to extrapolate daily soil moisture dynamics in space and in time, based on in-situ data collected from more than 1,000 stations across the globe. SoMo.ml provides multi-layer soil moisture data (0–10 cm, 10–30 cm, and 30–50 cm) at 0.25° spatial and daily temporal resolution over the period 2000–2019. The performance of the resulting dataset is evaluated through cross validation and inter-comparison with existing soil moisture datasets. SoMo.ml performs especially well in terms of temporal dynamics, making it particularly useful for applications requiring time-varying soil moisture, such as anomaly detection and memory analyses. SoMo.ml complements the existing suite of modelled and satellite-based datasets given its distinct derivation, to support large-scale hydrological, meteorological, and ecological analyses.

scholarly journals Assessment of Automatically Monitored Water Levels and Water Quality Indicators in Rivers with Different Hydromorphological Conditions and Pollution Levels in Greece

Hydrology ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 86
Author(s):  
Angeliki Mentzafou ◽  
George Varlas ◽  
Anastasios Papadopoulos ◽  
Georgios Poulis ◽  
Elias Dimitriou
Keyword(s):  
Water Quality ◽  
Time Series ◽  
Quality Indicators ◽  
High Frequency ◽  
Automatic Monitoring ◽  
Water Levels ◽  
High Temporal Resolution ◽  
Water Quality Indicators ◽  
Pollution Levels ◽  
Riverine Ecosystems

Water resources, especially riverine ecosystems, are globally under qualitative and quantitative degradation due to human-imposed pressures. High-temporal-resolution data obtained from automatic stations can provide insights into the processes that link catchment hydrology and streamwater chemistry. The scope of this paper was to investigate the statistical behavior of high-frequency measurements at sites with known hydromorphological and pollution pressures. For this purpose, hourly time series of water levels and key water quality indicators (temperature, electric conductivity, and dissolved oxygen concentrations) collected from four automatic monitoring stations under different hydromorphological conditions and pollution pressures were statistically elaborated. Based on the results, the hydromorphological conditions and pollution pressures of each station were confirmed to be reflected in the results of the statistical analysis performed. It was proven that the comparative use of the statistics and patterns of the water level and quality high-frequency time series could be used in the interpretation of the current site status as well as allowing the detection of possible changes. This approach can be used as a tool for the definition of thresholds, and will contribute to the design of management and restoration measures for the most impacted areas.

scholarly journals Air-Sea Interactions over Eddies in the Brazil-Malvinas Confluence

2021 ◽  
Vol 13 (7) ◽  
pp. 1335
Author(s):  
Ronald Souza ◽  
Luciano Pezzi ◽  
Sebastiaan Swart ◽  
Fabrício Oliveira ◽  
Marcelo Santini
Keyword(s):  
Latent Heat ◽  
Large Scale ◽  
Surface Wind ◽  
Heat Fluxes ◽  
Lower Atmosphere ◽  
Meteorological Variables ◽  
Global Ocean ◽  
Study Region ◽  
Cold Core

The Brazil–Malvinas Confluence (BMC) is one of the most dynamical regions of the global ocean. Its variability is dominated by the mesoscale, mainly expressed by the presence of meanders and eddies, which are understood to be local regulators of air-sea interaction processes. The objective of this work is to study the local modulation of air-sea interaction variables by the presence of either a warm (ED1) and a cold core (ED2) eddy, present in the BMC, during September to November 2013. The translation and lifespans of both eddies were determined using satellite-derived sea level anomaly (SLA) data. Time series of satellite-derived surface wind data, as well as these and other meteorological variables, retrieved from ERA5 reanalysis at the eddies’ successive positions in time, allowed us to investigate the temporal modulation of the lower atmosphere by the eddies’ presence along their translation and lifespan. The reanalysis data indicate a mean increase of 78% in sensible and 55% in latent heat fluxes along the warm eddy trajectory in comparison to the surrounding ocean of the study region. Over the cold core eddy, on the other hand, we noticed a mean reduction of 49% and 25% in sensible and latent heat fluxes, respectively, compared to the adjacent ocean. Additionally, a field campaign observed both eddies and the lower atmosphere from ship-borne observations before, during and after crossing both eddies in the study region during October 2013. The presence of the eddies was imprinted on several surface meteorological variables depending on the sea surface temperature (SST) in the eddy cores. In situ oceanographic and meteorological data, together with high frequency micrometeorological data, were also used here to demonstrate that the local, rather than the large scale forcing of the eddies on the atmosphere above, is, as expected, the principal driver of air-sea interaction when transient atmospheric systems are stable (not actively varying) in the study region. We also make use of the in situ data to show the differences (biases) between bulk heat flux estimates (used on atmospheric reanalysis products) and eddy covariance measurements (taken as “sea truth”) of both sensible and latent heat fluxes. The findings demonstrate the importance of short-term changes (minutes to hours) in both the atmosphere and the ocean in contributing to these biases. We conclude by emphasizing the importance of the mesoscale oceanographic structures in the BMC on impacting local air-sea heat fluxes and the marine atmospheric boundary layer stability, especially under large scale, high-pressure atmospheric conditions.

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