Comparative analysis of drop-size measurement in highly dense sprays using shadowgraphy, PDA, and SLIPI

Atomization is a physical phenomenon that is widely encountered in many engineering and industrial applications, such as in combustion engines, spray coating, spray dryers and many more. Spray characterization involves the determination of the droplet size and velocity distributions (both probability density function and spatial). To determine these parameters experimentally, traditionally, microscopic shadowgraphy and Phase Doppler Anemometry (PDA) are used, because of their relative ease of use and high accuracy. However, the application of these techniques is limited to relatively less dense sprays. In highly dense sprays, the strong multiple scattering effects cause significant errors in the determination of relevant parameters. Therefore, the Structured Laser Illumination Planar Imaging (SLIPI) technique is adopted. In this work, comparative measurements are reported to assess the capabilities of these techniques for drop-size measurements in a highly dense spray originating from a pressure swirl nozzle

Global groundwater droughts are more severe than they appear in hydrological models:an investigation through a Bayesian merging of GRACE and GRACE-FO data with a water balance model

Realistic representation of hydrological drought events is increasingly important in world facing decreased freshwater availability. Index-based drought monitoring systems are often adopted to represent the evolution and distribution of hydrological droughts, which mainly rely on hydrological model simulations to compute these indices. Recent studies, however, indicate that model derived water storage estimates might have difficulties in adequately representing reality. Here, a novel Markov Chain Monte Carlo - Data Assimilation (MCMC-DA) approach is implemented to merge global Terrestrial Water Storage (TWS) changes from the Gravity Recovery And Climate Experiment (GRACE) and its Follow On mission (GRACE-FO) with the water storage estimations derived from the W3RA water balance model. The modified MCMC-DA derived summation of deep-rooted soil and groundwater storage estimates is then used to compute standardized groundwater drought indices globally to show the impact of GRACE/GRACE-FO DA on a global index-based hydrological drought monitoring system. Our numerical assessment covers the period of 2003–2021, and shows that integrating GRACE/GRACE-FO data modifies the seasonality and inter-annual trends of water storage estimations. Considerable increases in the length and severity of extreme droughts are found in basins that exhibited multi-year water storage fluctuations and those affected by climate teleconnections

Global groundwater droughts are more severe than they appear in hydrological models: An investigation through a Bayesian merging of GRACE and GRACE-FO data with a water balance model

Realistic representation of hydrological drought events is increasingly important in world facing decreased freshwater availability. Index-based drought monitoring systems are often adopted to represent the evolution and distribution of hydrological droughts, which mainly rely on hydrological model simulations to compute these indices. Recent studies, however, indicate that model derived water storage estimates might have difficulties in adequately representing reality. Here, a novel Markov Chain Monte Carlo - Data Assimilation (MCMC-DA) approach is implemented to merge global Terrestrial Water Storage (TWS) changes from the Gravity Recovery And Climate Experiment (GRACE) and its Follow On mission (GRACE-FO) with the water storage estimations derived from the W3RA water balance model. The modified MCMC-DA derived summation of deep-rooted soil and groundwater storage estimates is then used to compute 0.5∘ standardized groundwater drought indices globally to show the impact of GRACE/GRACE-FO DA on a global index-based hydrological drought monitoring system. Our numerical assessment covers the period of 2003-2021, and shows that integrating GRACE/GRACE-FO data modifies the seasonality and inter-annual trends of water storage estimations. Considerable increases in the length and severity of extreme droughts are found in basins that exhibited multi-year water storage fluctuations and those affected by climate teleconnections

Improving drought simulations within the Murray-Darling Basin by combined calibration/assimilation of GRACE data into the WaterGAP Global Hydrology Model

Simulating hydrological processes within the (semi-)arid region of the Murray-Darling Basin (MDB), Australia, is very challenging specially during droughts. In this study, we investigate whether integrating remotely sensed terrestrial water storage changes (TWSC) from the Gravity Recovery And Climate Experiment (GRACE) mission into a global water resources and use model enables a more realistic representation of the basin hydrology during droughts. For our study, the WaterGAP Global Hydrology Model (WGHM), which simulates the impact of human water abstractions on surface water and groundwater storage, has been chosen for simulating compartmental water storages and river discharge during the so-called ‘Millennium Drought’ (2001–2009). In particular, we test the ability of a parameter calibration and data assimilation (C/DA) approach to introduce long-term trends into WGHM, which are poorly represented due to errors in forcing, model structure and calibration. For the first time, the impact of the parameter equifinality problem on the C/DA results is evaluated. We also investigate the influence of selecting a specific GRACE data product and filtering method on the final C/DA results. Integrating GRACE data into WGHM does not only improve simulation of seasonality and trend of TWSC, but also it improves the simulation of individual water storage components. For example, after the C/DA, correlations between simulated groundwater storage changes and independent in-situ well data increase (up to 0.82) in three out of four sub-basins. Declining groundwater storage trends - found mainly in the south, i.e. Murray Basin, at in-situ wells - have been introduced while simulated soil water and surface water storage do not show trends, which is in agreement with existing literature. Although GRACE C/DA in MDB does not improve river discharge simulations, the correlation between river storage simulations and gauge-based river levels increases significantly from 0.15 to 0.52. By adapting the C/DA settings to the basin-specific characteristics and reducing the number of calibration parameters, their convergence is improved and their uncertainty is reduced. The time-variable parameter values resulting from C/DA allow WGHM to better react to the very wet Australian summer 2009/10. Using solutions from different GRACE data providers produces slightly different C/DA results. We conclude that a rigorous evaluation of GRACE errors is required to realistically account for the spread of the differences in the results

Agape in Business:Policies and Actions beyond Caritas

Authors Harry Hummels, Yannick Bammens, Maike van Dijk, and Annelies van Uden argue in this chapter that agape means more than simply living up to the expectation of corporate social responsibility and creating shared value. It allows us to rethink the ways in which we do business, while aiming to achieve the mission and objectives of the business. Even though for many agape has roots in the Judeo-Christian tradition, it is a meaningful concept and can be applied in a secular business world that aims to create (long-term) value for its stakeholders, including shareholders

Non-stationary relationships between decadal water storage changes over Australia and climate variability of the El Niño Southern Oscillation and Indian Ocean Dipole

International audienceLarge-scale ocean-atmosphere interactions are hypothesized as the main drivers of water variations over the Australian continent. This study examines the relative contributions of the large-scale ocean-atmospheric processes in different time-scale variations of terrestrial water storage (TWS) over Australia. The aim is to determine whether the role of main climatic phenomena such as the El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) on water resources as appears to be a stationary relationship. The main analyses were performed on three decades (1982-2012) of: (i) TWS changes over Australia from the World Wide Water Resources Assessment (W3RA) hydrological model, and (ii) statistically reconstructed TWS changes from the Gravity Recovery And Climate Experiment (GRACE) products. Reconstructions were derived by applying low-degree autoregressive models to relate basin averaged TWS changes, over the nine major river drainage basins of Australia, to input values of precipitation minus evaporation as well as the ENSO and IOD indices. Our results indicate that both intra-annual and seasonal simulation and forecast of TWS water storage changes associated with ENSO cycles have increased during the last two decades of 1990 to 2010. The contribution of IOD to seasonal simulation and forecasts of TWS appears to have increased over the last decade. The long-term influence of IOD in TWS changes, however, appears to have decreased slightly. Our results demonstrate non-stationary behaviour of TWS in terms of variability and predictability due to the ENSO and IOD phenomena

Assessing sequential data assimilation techniques for integrating GRACE data into a hydrological model

The time-variable terrestrial water storage (TWS) products from the Gravity Recovery And Climate Experiment (GRACE) have been increasingly used in recent years to improve the simulation of hydrological models by applying data assimilation techniques. In this study, for the first time, we assess the performance of the most popular data assimilation sequential techniques for integrating GRACE TWS into the World-Wide Water Resources Assessment (W3RA) model. We implement and test stochastic and deterministic ensemble-based Kalman filters (EnKF), as well as Particle filters (PF) using two different resampling approaches of Multinomial Resampling and Systematic Resampling. These choices provide various opportunities for weighting observations and model simulations during the assimilation and also accounting for error distributions. Particularly, the deterministic EnKF is tested to avoid perturbing observations before assimilation (that is the case in an ordinary EnKF). Gaussian-based random updates in the EnKF approaches likely do not fully represent the statistical properties of the model simulations and TWS observations. Therefore, the fully non-Gaussian PF is also applied to estimate more realistic updates. Monthly GRACE TWS are assimilated into W3RA covering the entire Australia. To evaluate the filters performances and analyze their impact on model simulations, their estimates are validated by independent in-situ measurements. Our results indicate that all implemented filters improve the estimation of water storage simulations of W3RA. The best results are obtained using two versions of deterministic EnKF, i.e. the Square Root Analysis (SQRA) scheme and the Ensemble Square Root Filter (EnSRF), respectively, improving the model groundwater estimations errors by 34% and 31% compared to a model run without assimilation. Applying the PF along with Systematic Resampling successfully decreases the model estimation error by 23%.M. Khaki is grateful for the research grant of Curtin International Postgraduate Research Scholarships (CIPRS)/ORD Scholarship provided by Curtin University (Australia). This work is a TIGeR publication