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

HIGH BAY CAPACITY UTILIZATION TOOL

Northrop Grumman’s Space Park facility has many inefficiencies in their high bay scheduling processes. Additionally, it is very hard for project managers to figure out the capabilities of each high bay in order to schedule their specific project. The purpose of this project is to develop a tool that can be used across the facility to easily create projects, assign projects, view room capabilities, and view a master schedule of the rooms. After researching commercially available tools, our approach to designing this system was to use tools that are already utilized at the facility (Microsoft Suite and Tableau) and engineer the system to do exactly what we need it to do for this facility. The design is a relational database managed in Microsoft Access that links to Tableau for a detailed schedule for all the rooms along with facility layouts on Microsoft Visio to show each facility at any time. These three programs are tied together with a user interface in Microsoft Access and available across the entire network at the Space Park facility via SharePoint. While our system would have higher initial cost to train employees on, it would save significant operating costs each year. If this system were to be installed and utilized into Northrop Grumman’s current operations, we estimate a cost savings between $10,000 and$25,000 over a ten year period. However, we ran into problems with the implementation of our tool due to having to use assumed data for our project. Although it is possible to expand this system, it is a lengthy process to add parameters for rooms and change the base layout of our design. Our largest recommendation for this system is that Northrop Grumman uses the base layout of our system (including the relational database design, user interface, and data visualization) to create a new system that has actual parameters of the room. This will yield the same results as installing the system that we have developed

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 the 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 NASA’s Land 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 timescales. 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. Results 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 for accurate simulation of water and energy states and fluxes over cropland

Irrigation Signals Detected from SMAP Soil Moisture Retrievals

Irrigation can influence weather and climate, but the magnitude, timing, and spatial extent of irrigation are poorly represented in models, as are the resulting impacts of irrigation on the coupled land-atmosphere system. One way to improve irrigation representation in models is to assimilate soil moisture observations that reflect an irrigation signal to improve model states. Satellite remote sensing is a promising avenue for obtaining these needed observations on a routine basis, but to date, irrigation detection in passive microwave satellites has proven difficult. In this study, results show that the new Enhanced soil moisture product from the Soil Moisture Active Passive (SMAP) satellite is able to capture irrigation signals over three semi-arid regions in the western United States. This marks an advancement in earth-observing satellite skill and the ability to monitor human impacts on the water cycle

THC alters alters morphology of neurons in medial prefrontal cortex, orbital prefrontal cortex, and nucleus accumbens and alters the ability of later experience to promote structural plasticity

Psychoactive drugs have the ability to alter the morphology of neuronal dendrites and spines and to influence later experience‐dependent structural plasticity. If rats are given repeated injections of psychomotor stimulants (amphetamine, cocaine, nicotine) prior to being placed in complex environments, the drug experience interferes with the ability of the environment to increase dendritic arborization and spine density. Repeated exposure to Delta 9‐Tetrahydrocannabinol (THC) changes the morphology of dendrites in medial prefrontal cortex (mPFC) and nucleus accumbens (NAcc). To determine if drugs other than psychomotor stimulants will also interfere with later experience‐dependent structural plasticity we gave Long‐Evans rats THC (0.5 mg/kg) or saline for 11 days before placing them in complex environments or standard laboratory caging for 90 days. Brains were subsequently processed for Golgi‐Cox staining and analysis of dendritic morphology and spine density mPFC, orbital frontal cortex (OFC), and NAcc. THC altered both dendritic arborization and spine density in all three regions, and, like psychomotor stimulants, THC influenced the effect of later experience in complex environments to shape the structure of neurons in these three regions. We conclude that THC may therefore contribute to persistent behavioral and cognitive deficits associated with prolonged use of the drug.Both repeated exposure to Delta 9‐THC and housing in complex environments changes the morphology of dendrites in mPFC, OFC, and NAcc. Prior exposure to THC influenced the effect of later experience in complex environments to shape the structure of neurons in these three regions.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141383/1/syn22020.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/141383/2/syn22020_am.pd

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

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

The effects of concurrent cannabis use among ecstasy users: neuroprotective or neurotoxic?

The research evidence regarding the potential effects of ecstasy suggests that it may be neurotoxic and that its use is associated with cognitive impairment. In recent years evidence has emerged suggesting that cannabinoids, the active ingredients in cannabis, can be neuroprotective under certain conditions. Given that many ecstasy users also consume cannabis at the same time, the possibility emerges that these individuals might be less susceptible to ecstasy-related impairment. The present paper reanalyses the data from a number of previous studies, contrasting the performance of those individuals who generally consume cannabis and ecstasy at the same time with those who generally consume ecstasy on its own. The two ecstasy-using groups are compared with non-ecstasy users on a range of measures including processing speed, random letter generation, verbal and visuo-spatial working memory span, reasoning and associative learning. The two ecstasy user groups did not differ significantly from each other on any of the measures. Both user groups were significantly worse than non-ecstasy users on measures of associative learning, verbal and visuo-spatial working memory and reasoning. The results suggest that consuming cannabis at the same time as ecstasy does not reduce the likelihood of cognitive impairment. Copyright © 2006 John Wiley & Sons, Ltd