Assessment of Irrigation Physics in a Land Surface Modeling Framework Using Non-Traditional and Human-Practice Datasets

Irrigation increases soil moisture, which in turn controls water and energy fluxes from the land surface to the10 planetary boundary layer and determines plant stress and productivity. Therefore, developing a realistic representation of irrigation is critical to understanding land-atmosphere interactions in agricultural areas. Irrigation parameterizations are becoming more common in land surface models and are growing in sophistication, but there is difficulty in assessing the realism of these schemes, due to limited observations (e.g., soil moisture, evapotranspiration) and scant reporting of irrigation timing and quantity. This study uses the Noah land surface model run at high resolution within NASAs Land15 Information System to assess the physics of a sprinkler irrigation simulation scheme and model sensitivity to choice of irrigation intensity and greenness fraction datasets over a small, high resolution domain in Nebraska. Differences between experiments are small at the interannual scale but become more apparent at seasonal and daily time scales. In addition, this study uses point and gridded soil moisture observations from fixed and roving Cosmic Ray Neutron Probes and co-located human practice data to evaluate the realism of irrigation amounts and soil moisture impacts simulated by the model. Results20 show that field-scale heterogeneity resulting from the individual actions of farmers is not captured by the model and the amount of irrigation applied by the model exceeds that applied at the two irrigated fields. However, the seasonal timing of irrigation and soil moisture contrasts between irrigated and non-irrigated areas are simulated well by the model. Overall, the results underscore the necessity of both high-quality meteorological forcing data and proper representation of irrigation foraccurate simulation of water and energy states and fluxes over cropland

Effects of ecstasy/polydrug use on memory for associative information

Rationale Associative learning underpins behaviours that are fundamental to the everyday functioning of the individual. Evidence pointing to learning deficits in recreational drug users merits further examination. Objectives A word pair learning task was administered to examine associative learning processes in ecstasy/polydrug users. Methods After assignment to either single or divided attention conditions, 44 ecstasy/polydrug users and 48 non-users were presented with 80 word pairs at encoding. Following this, four types of stimuli were presented at the recognition phase: the words as originally paired (old pairs), previously presented words in different pairings (conjunction pairs), old words paired with new words, and pairs of new words (not presented previously). The task was to identify which of the stimuli were intact old pairs. Results Ecstasy/ploydrug users produced significantly more false-positive responses overall compared to non-users. Increased long-term frequency of ecstasy use was positively associated with the propensity to produce false-positive responses. It was also associated with a more liberal signal detection theory decision criterion value. Measures of long term and recent cannabis use were also associated with these same word pair learning outcome measures. Conjunction word pairs, irrespective of drug use, generated the highest level of false-positive responses and significantly more false-positive responses were made in the divided attention condition compared to the single attention condition. Conclusions Overall, the results suggest that long-term ecstasy exposure may induce a deficit in associative learning and this may be in part a consequence of users adopting a more liberal decision criterion value

Observational and Modeling Analysis of Land–Atmopshere Coupling over Adjacent Irrigated and Rainfed Cropland during the GRAINEX Field Campaign

The Great Plains Irrigation Experiment (GRAINEX) was conducted in the spring and summer of 2018 to investigate Land-Atmosphere (L-A) coupling just prior to and through the growing season across adjacent, but distinctly unique, soil moisture regimes (contrasting irrigated and rainfed fields). GRAINEX was uniquely designed for the development and analysis of an extensive observational dataset for comprehensive process studies of L-A coupling, by focusing on irrigated and rainfed croplands in a ~100 x 100 km domain in southeastern Nebraska. Observation platforms included multiple NCAR EOL Integrated Surface Flux Systems and Integrated Sounding Systems, NCAR CSWR Doppler Radar on Wheels, 1200 radiosonde balloon launches from 5 sites, the NASA GREX airborne L-Band radiometer, and 75 University of Alabama-Huntsville Environmental Monitoring Economic Monitoring Sensor Hubs (EMESH mesonet stations). An integrated observational and modeling approach to advance knowledge of L-A coupling processes and precipitation impacts in regions of heterogeneous soil moisture will be presented. Specifically, through observation of land surface states, surface fluxes, near surface meteorology, and properties of the atmospheric column, an examination of the diurnal planetary boundary layer evolving characteristics will be presented. Results from a hierarchy of modeling platforms (e.g. single column, large-eddy, and mesoscale simulations) will also be presented to complement the observational findings. The modeling effort will generate high spatiotemporal resolution datasets to: 1) generate a multi-physics ensemble to test the robustness and potentially advance physical parameterizations in high resolution weather and climate models, 2) comparison of prescribed forcing from observations and those from offline land surface model simulations and high resolution operational analyses, 3) determine the ability of model simulations to reproduce observed boundary layer evolution, with particular attention to the processes that compose the L-A coupling chain and metrics (e.g. mixing ratio diagrams), and 4) in combination with observations, isolate the impacts of soil moisture heterogeneity on planetary boundary layer characteristics, cloud development, precipitation, mesoscale circulation patters and boundary layer development. Initial results from the observational and modeling analysis will be presented

Further Observations on the Displacement of Pre-adsorbed Water from BPL Activated Carbon by Chloropicrin Vapour

The efficiency of adsorption of chloropicrin vapour from a flowing airstream by beds of BPL activated carbon has been measured as a function of the relative humidity and temperature. The results show that there is a complex relationship between the kinetic adsorption performance and environmental parameters. In particular, the displacement of pre-adsorbed water can be critical. In several situations that reflect practical usage the effluent airstream is not able to remove water from the filter bed as fast as it is displaced (because it quickly reaches saturation). In such cases there is a fine balance as to whether water accumulation in the transport pore structure of the carbon results in pore blockage and thereby prevents the system reaching thermodynamic equilibrium, or whether build-up occurs in the intergranular spaces where it has only a limited effect

Long-term effects of cannabis on brain structure

The dose-dependent toxicity of the main psychoactive component of cannabis in brain regions rich in cannabinoid CB1 receptors is well known in animal studies. However, research in humans does not show common findings across studies regarding the brain regions that are affected after long-term exposure to cannabis. In the present study, we investigate (using Voxel-based Morphometry) gray matter changes in a group of regular cannabis smokers in comparison with a group of occasional smokers matched by the years of cannabis use. We provide evidence that regular cannabis use is associated with gray matter volume reduction in the medial temporal cortex, temporal pole, parahippocampal gyrus, insula, and orbitofrontal cortex; these regions are rich in cannabinoid CB1 receptors and functionally associated with motivational, emotional, and affective processing. Furthermore, these changes correlate with the frequency of cannabis use in the 3 months before inclusion in the study. The age of onset of drug use also influences the magnitude of these changes. Significant gray matter volume reduction could result either from heavy consumption unrelated to the age of onset or instead from recreational cannabis use initiated at an adolescent age. In contrast, the larger gray matter volume detected in the cerebellum of regular smokers without any correlation with the monthly consumption of cannabis may be related to developmental (ontogenic) processes that occur in adolescence