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Cosmic-ray neutron sensing (CRNS) is a non-invasive tool for measuring hydrogen pools such as soil moisture, snow or vegetation. The intrinsic integration over a radial hectare-scale footprint is a clear advantage for averaging out small-scale heterogeneity, but on the other hand the data may become hard to interpret in complex terrain with patchy land use.
This study presents a directional shielding approach to prevent neutrons from certain angles from being counted while counting neutrons entering the detector from other angles and explores its potential to gain a sharper horizontal view on the surrounding soil moisture distribution.
Using the Monte Carlo code URANOS (Ultra Rapid Neutron-Only Simulation), we modelled the effect of additional polyethylene shields on the horizontal field of view and assessed its impact on the epithermal count rate, propagated uncertainties and aggregation time.
The results demonstrate that directional CRNS measurements are strongly dominated by isotropic neutron transport, which dilutes the signal of the targeted direction especially from the far field. For typical count rates of customary CRNS stations, directional shielding of half-spaces could not lead to acceptable precision at a daily time resolution. However, the mere statistical distinction of two rates should be feasible.
Cosmic-ray neutron sensing (CRNS) is a non-invasive tool for measuring hydrogen pools such as soil moisture, snow or vegetation. The intrinsic integration over a radial hectare-scale footprint is a clear advantage for averaging out small-scale heterogeneity, but on the other hand the data may become hard to interpret in complex terrain with patchy land use.
This study presents a directional shielding approach to prevent neutrons from certain angles from being counted while counting neutrons entering the detector from other angles and explores its potential to gain a sharper horizontal view on the surrounding soil moisture distribution.
Using the Monte Carlo code URANOS (Ultra Rapid Neutron-Only Simulation), we modelled the effect of additional polyethylene shields on the horizontal field of view and assessed its impact on the epithermal count rate, propagated uncertainties and aggregation time.
The results demonstrate that directional CRNS measurements are strongly dominated by isotropic neutron transport, which dilutes the signal of the targeted direction especially from the far field. For typical count rates of customary CRNS stations, directional shielding of half-spaces could not lead to acceptable precision at a daily time resolution. However, the mere statistical distinction of two rates should be feasible.
Background:
Many authors regard counseling self-efficacy (CSE) as important in therapist development and training. The purpose of this study was to examine the factor structure, reliability, and validity of the German version of the Counselor Activity Self-Efficacy Scales-Revised (CASES-R).
Method:
The sample consisted of 670 German psychotherapy trainees, who completed an online survey. We examined the factor structure by applying exploratory and confirmatory factor analysis to the instrument as a whole.
Results:
A bifactor-exploratory structural equation modeling model with one general and five specific factors provided the best fit to the data. Omega hierarchical coefficients indicated optimal reliability for the general factor, acceptable reliability for the Action Skills-Revised (AS-R) factor, and insufficient estimates for the remaining factors. The CASES-R scales yielded significant correlations with related measures, but also with therapeutic orientations.
Conclusion:
We found support for the reliability and validity of the German CASES-R. However, the subdomains (except AS-R) should be interpreted with caution, and we do not recommend the CASES-R for comparisons between psychotherapeutic orientations.
Bumps in river profiles
(2017)
The analysis of longitudinal river profiles is an important tool for studying landscape evolution. However, characterizing river profiles based on digital elevation models (DEMs) suffers from errors and artifacts that particularly prevail along valley bottoms. The aim of this study is to characterize uncertainties that arise from the analysis of river profiles derived from different, near-globally available DEMs. We devised new algorithms quantile carving and the CRS algorithm - that rely on quantile regression to enable hydrological correction and the uncertainty quantification of river profiles. We find that globally available DEMs commonly overestimate river elevations in steep topography. The distributions of elevation errors become increasingly wider and right skewed if adjacent hillslope gradients are steep. Our analysis indicates that the AW3D DEM has the highest precision and lowest bias for the analysis of river profiles in mountainous topography. The new 12m resolution TanDEM-X DEM has a very low precision, most likely due to the combined effect of steep valley walls and the presence of water surfaces in valley bottoms. Compared to the conventional approaches of carving and filling, we find that our new approach is able to reduce the elevation bias and errors in longitudinal river profiles.
Within the field of species distribution modelling an apparent dichotomy exists between process-based and correlative approaches, where the processes are explicit in the former and implicit in the latter. However, these intuitive distinctions can become blurred when comparing species distribution modelling approaches in more detail. In this review article, we contrast the extremes of the correlativeprocess spectrum of species distribution models with respect to core assumptions, model building and selection strategies, validation, uncertainties, common errors and the questions they are most suited to answer. The extremes of such approaches differ clearly in many aspects, such as model building approaches, parameter estimation strategies and transferability. However, they also share strengths and weaknesses. We show that claims of one approach being intrinsically superior to the other are misguided and that they ignore the processcorrelation continuum as well as the domains of questions that each approach is addressing. Nonetheless, the application of process-based approaches to species distribution modelling lags far behind more correlative (process-implicit) methods and more research is required to explore their potential benefits. Critical issues for the employment of species distribution modelling approaches are given, together with a guideline for appropriate usage. We close with challenges for future development of process-explicit species distribution models and how they may complement current approaches to study species distributions.
Here, a reliable and sensitive method for the determination of 38 (modified) mycotoxins was developed. Using a QuEChERS-based extraction method [acetonitrile/water/formic acid (75:20:5, v/v/v)], followed by two runs of high performance liquid chromatography tandem mass spectrometry with different conditions, relevant mycotoxins in cereals were analyzed. The method was validated according to the performance criteria defined by the European Commission (EC) in Commission Decision no. 657/2002. Limits of quantification ranged from 0.05 to 150 μg/kg. Good linearity (R2 > 0.99), recovery (61–120%), repeatability (RSDr < 15%), and reproducibility (RSDR < 20%) were obtained for most mycotoxins. However, validation results for Alternaria toxins and fumonisins were unsatisfying. Matrix effects (−69 to +59%) were compensated for using standard addition. Application on reference materials gave correct results while analysis of samples from local retailers revealed contamination, especially with deoxynivalenol, deoxynivalenol-3-glucoside, fumonisins, and zearalenone, in concentrations up to 369, 58, 1002, and 21 μg/kg, respectively.
Global flood models (GFMs) are increasingly being used to estimate global-scale societal and economic risks of river flooding. Recent validation studies have highlighted substantial differences in performance between GFMs and between validation sites. However, it has not been systematically quantified to what extent the choice of the underlying climate forcing and global hydrological model (GHM) influence flood model performance. Here, we investigate this sensitivity by comparing simulated flood extent to satellite imagery of past flood events, for an ensemble of three climate reanalyses and 11 GHMs. We study eight historical flood events spread over four continents and various climate zones. For most regions, the simulated inundation extent is relatively insensitive to the choice of GHM. For some events, however, individual GHMs lead to much lower agreement with observations than the others, mostly resulting from an overestimation of inundated areas. Two of the climate forcings show very similar results, while with the third, differences between GHMs become more pronounced. We further show that when flood protection standards are accounted for, many models underestimate flood extent, pointing to deficiencies in their flood frequency distribution. Our study guides future applications of these models, and highlights regions and models where targeted improvements might yield the largest performance gains.
The aim of this study was the development and psychometric assessment of a questionnaire for functions of OCD (FFZ). The instrument was analyzed using factor and item analyses with a sample of 120 OCD patients within the first 5 weeks of an inpatient cognitive-behavioral treatment. The revealed scales were OCD as self-confirmation, emotion regulation, avoidance of responsibility, interpersonal regulation and OCD as occupation. The reliabilities of all subscales and the total value were satisfactory to nearly excellent. The factorial validity was good, content validity was excellent. The FFZ shows correlations with measures of interpersonal problems and emotional competence, but none with measures of self-reflection and therapy experience. No differences were found for gender or age. The results provide initial support for the reliability and validity of the FFZ.
Learning to regulate anger is an important task in childhood development, as maladaptive anger regulation has been linked to a variety of problems, including aggression and social rejection. To assess anger regulation in situ, in a previous study we developed a behavioural observation measure and demonstrated its cross-sectional construct and criterion validity in a sample of 599 children with a mean age of 8.1years. The present study further validated the measure by demonstrating its predictive validity. About 10months after the behavioural observation, participants were asked to imagine two anger-eliciting situations and report what they would do to get rid of their anger. Observed anger regulation strategies at T1 correlated significantly with self-reported regulatory behaviour at T2, suggesting that the behavioural observation measure is an ecologically valid approach for assessing anger regulation in middle childhood.
Contemporary drought impact assessments have been constrained due to data availability, leading to an incomplete representation of impact trends. To address this, we present a novel method for the comprehensive and near-real-time monitoring of drought socio-economic impacts based on media reports. We tested its application using the case of the exceptional 2018/19 German drought. By employing text mining techniques, 4839 impact statements were identified, relating to livestock, agriculture, forestry, fires, recreation, energy and transport sectors. An accuracy of 95.6% was obtained for their automatic classification. Furthermore, high levels of performance in terms of spatial and temporal precision were found when validating our results against independent data (e.g. soil moisture, average precipitation, population interest in droughts, crop yield and forest fire statistics). The findings highlight the applicability of media data for rapidly and accurately monitoring the propagation of drought consequences over time and space. We anticipate our method to be used as a starting point for an impact-based early warning system.