PROCESS SEDIMENTOLOGY OF THE GUADALUPIAN RADER LIMESTON, DELAWARE BASIN

An integrated LiDAR, XRF, Spectral Gamma Ray, and outcrop investigation was performed on the upper Guadalupian Rader Formation in the Delaware Basin of West Texas. The Rader Formation, is an upper slope carbonate submarine fan deposit that is divided into three units: the lower, middle and upper Rader intervals. The lower and upper Rader intervals are characterized by thin to thick, ungraded and graded skeletal and non-skeletal allochthonous deposits interpreted to be highstand carbonate apron deposits. These intervals are interpreted to have been deposited by grain flows and high density turbidite flows. The middle Rader unit has an erosive base and consists of ungraded matrix supported mega conglomerates and megabreccias as well as intervals of clast supported megabreccias representing a lowstand period which resulted in a catastrophic platform failure due to increasing stress of platform sediments as water level fell. The mega conglomerate and mega breccia of the middle Rader were deposited as debris flows. Lack of oiids, pisolites and fenestral fabrics within the Rader Formation indicate that more distant restricted back reef environments were not affected by the catastrophic platform failure, however, submarine cement coated grains and fusulinids observed in the middle Rader deposits indicate that the reef crest is the most proximal environment affected by the catastrophic slope failure. Of particular consequence is the presence of hummocky cross stratification observed within the Bull Head Turbidite which directly overlies the mega conglomerate deposits. The hummocky cross stratification is interpreted to be evidence of a tsunamiite generated by massive subaqueous debris flows caused by the platform failure responsible for the deposition of the mega conglomerate and mega breccia deposits

Multisensor Capacitance Probes for Simultaneously Monitoring Rice Field Soil-Water-Crop-Ambient Conditions

Multisensor capacitance probes (MCPs) have traditionally been used for soil moisture monitoring and irrigation scheduling. This paper presents a new application of these probes, namely the simultaneous monitoring of ponded water level, soil moisture, and temperature profile, conditions which are particularly important for rice crops in temperate growing regions and for rice grown with prolonged periods of drying. WiFi-based loggers are used to concurrently collect the data from the MCPs and ultrasonic distance sensors (giving an independent reading of water depth). Models are fit to MCP water depth vs volumetric water content (VWC) characteristics from laboratory measurements, variability from probe-to-probe is assessed, and the methodology is verified using measurements from a rice field throughout a growing season. The root-mean-squared error of the water depth calculated from MCP VWC over the rice growing season was 6.6 mm. MCPs are used to simultaneously monitor ponded water depth, soil moisture content when ponded water is drained, and temperatures in root, water, crop and ambient zones. The insulation effect of ponded water against cold-temperature effects is demonstrated with low and high water levels. The developed approach offers advantages in gaining the full soil-plant-atmosphere continuum in a single robust sensor

Assessment of Aquatic Weed in Irrigation Channels Using UAV and Satellite Imagery

Irrigated agriculture requires high reliability from water delivery networks and high flows to satisfy demand at seasonal peak times. Aquatic vegetation in irrigation channels are a major impediment to this, constraining flow rates. This work investigates the use of remote sensing from unmanned aerial vehicles (UAVs) and satellite platforms to monitor and classify vegetation, with a view to using this data to implement targeted weed control strategies and assessing the effectiveness of these control strategies. The images are processed in Google Earth Engine (GEE), including co-registration, atmospheric correction, band statistic calculation, clustering and classification. A combination of unsupervised and supervised classification methods is used to allow semi-automatic training of a new classifier for each new image, improving robustness and efficiency. The accuracy of classification algorithms with various band combinations and spatial resolutions is investigated. With three classes (water, land and weed), good accuracy (typical validation kappa >0.9) was achieved with classification and regression tree (CART) classifier; red, green, blue and near-infrared (RGBN) bands; and resolutions better than 1 m. A demonstration of using a time-series of UAV images over a number of irrigation channel stretches to monitor weed areas after application of mechanical and chemical control is given. The classification method is also applied to high-resolution satellite images, demonstrating scalability of developed techniques to detect weed areas across very large irrigation networks

Soil moisture forecasting for irrigation recommendation

This study integrates measured soil moisture sensor data, a remotely sensed crop vegetation index, and weather data to train models, in order to predict future soil moisture. The study was carried out on a cotton farm, with wireless soil moisture monitoring equipment deployed across five plots. Lasso, Decision Tree, Random Forest and Support Vector Machine modeling methods were trialled. Random Forest models gave consistently good results (mean 7-day prediction error from 8.0 to 16.9 kPA except in one plot with malfunctioning sensors). Linear regression with two of the most important predictor variables was not as accurate, but allowed extraction of an interpretable model. The system was implemented in Google Cloud Platform and a model was trained continuously through the season. An online irrigation dashboard was created showing previous and forecast soil moisture conditions, along with weather and normalized difference vegetation index (NDVI). This was used to guide operators in advance of irrigation water needs. The methodology developed in this study could be used as part of a closed-loop sensing and irrigation automation system

Assessment of in-season cotton nitrogen status and lint yield prediction from unmanned aerial system imagery

The present work assessed the usefulness of a set of spectral indices obtained from an unmanned aerial system (UAS) for tracking spatial and temporal variability of nitrogen (N) status as well as for predicting lint yield in a commercial cotton (Gossypium hirsutum L.) farm. Organic, inorganic and a combination of both types of fertilizers were used to provide a range of eight N rates from 0 to 340 kg N ha−1. Multi-spectral images (reflectance in the blue, green, red, red edge and near infrared bands) were acquired on seven days throughout the season, from 62 to 169 days after sowing (DAS), and data were used to compute structure- and chlorophyll-sensitive vegetation indices (VIs). Above-ground plant biomass was sampled at first flower, first cracked boll and maturity and total plant N concentration (N%) and N uptake determined. Lint yield was determined at harvest and the relationships with the VIs explored. Results showed that differences in plant N% and N uptake between treatments increased as the season progressed. Early in the season, when fertilizer applications can still have an effect on lint yield, the simplified canopy chlorophyll content index (SCCCI) was the index that best explained the variation in N uptake and plant N% between treatments. Around first cracked boll and maturity, the linear regression obtained for the relationships between the VIs and both plant N% and N uptake was statistically significant, with the highest r2 values obtained at maturity. The normalized difference red edge (NDRE) index, and SCCCI were generally the indices that best distinguished the treatments according to the N uptake and total plant N%. Treatments with the highest N rates (from 307 to 340 kg N ha−1) had lower normalized difference vegetation index (NDVI) than treatments with 0 and 130 kg N ha−1 at the first measurement day (62 DAS), suggesting that factors other than fertilization N rate affected plant growth at this early stage of the crop. This fact affected the earliest date at which the structure-sensitive indices NDVI and the visible atmospherically resistant index (VARI) enabled yield prediction (97 DAS). A statistically significant linear regression was obtained for the relationships between SCCCI and NDRE with lint yield at 83 DAS. Overall, this study shows the practicality of using an UAS to monitor the spatial and temporal variability of cotton N status in commercial farms. It also illustrates the challenges of using multi-spectral information for fertilization recommendation in cotton at early stages of the crop

Toward Identifying the Next Generation of Superfund and Hazardous Waste Site Contaminants

Reproduced with permission from Environmental Health Perspectives."This commentary evolved from a workshop sponsored by the National Institute of Environmental Health Sciences titled "Superfund Contaminants: The Next Generation" held in Tucson, Arizona, in August 2009. All the authors were workshop participants." doi:10.1289/ehp.1002497Our aim was to initiate a dynamic, adaptable process for identifying contaminants of emerging concern (CECs) that are likely to be found in future hazardous waste sites, and to identify the gaps in primary research that cause uncertainty in determining future hazardous waste site contaminants. Superfund-relevant CECs can be characterized by specific attributes: they are persistent, bioaccumulative, toxic, occur in large quantities, and have localized accumulation with a likelihood of exposure. Although still under development and incompletely applied, methods to quantify these attributes can assist in winnowing down the list of candidates from the universe of potential CECs. Unfortunately, significant research gaps exist in detection and quantification, environmental fate and transport, health and risk assessment, and site exploration and remediation for CECs. Addressing these gaps is prerequisite to a preventive approach to generating and managing hazardous waste sites.Support for the workshop, from which this article evolved, was provided by the National Institute of Environmental Health Sciences Superfund Research Program (P42-ES04940)

Toward Identifying the Next Generation of Superfund and Hazardous Waste Site Contaminants

Reproduced with permission from Environmental Health Perspectives."This commentary evolved from a workshop sponsored by the National Institute of Environmental Health Sciences titled "Superfund Contaminants: The Next Generation" held in Tucson, Arizona, in August 2009. All the authors were workshop participants." doi:10.1289/ehp.1002497Our aim was to initiate a dynamic, adaptable process for identifying contaminants of emerging concern (CECs) that are likely to be found in future hazardous waste sites, and to identify the gaps in primary research that cause uncertainty in determining future hazardous waste site contaminants. Superfund-relevant CECs can be characterized by specific attributes: they are persistent, bioaccumulative, toxic, occur in large quantities, and have localized accumulation with a likelihood of exposure. Although still under development and incompletely applied, methods to quantify these attributes can assist in winnowing down the list of candidates from the universe of potential CECs. Unfortunately, significant research gaps exist in detection and quantification, environmental fate and transport, health and risk assessment, and site exploration and remediation for CECs. Addressing these gaps is prerequisite to a preventive approach to generating and managing hazardous waste sites.Support for the workshop, from which this article evolved, was provided by the National Institute of Environmental Health Sciences Superfund Research Program (P42-ES04940)

Systemic chemotherapy with or without cetuximab in patients with resectable colorectal liver metastasis (New EPOC): long-term results of a multicentre, randomised, controlled, phase 3 trial.

BACKGROUND: The interim analysis of the multicentre New EPOC trial in patients with resectable colorectal liver metastasis showed a significant reduction in progression-free survival in patients allocated to cetuximab plus chemotherapy compared with those given chemotherapy alone. The focus of the present analysis was to assess the effect on overall survival. METHODS: New EPOC was a multicentre, open-label, randomised, controlled, phase 3 trial. Adult patients (aged ≥18 years) with KRAS wild-type (codons 12, 13, and 61) resectable or suboptimally resectable colorectal liver metastases and a WHO performance status of 0-2 were randomly assigned (1:1) to receive chemotherapy with or without cetuximab before and after liver resection. Randomisation was done centrally with minimisation factors of surgical centre, poor prognosis cancer, and previous adjuvant treatment with oxaliplatin. Chemotherapy consisted of oxaliplatin 85 mg/m2 administered intravenously over 2 h, l-folinic acid (175 mg flat dose administered intravenously over 2 h) or d,l-folinic acid (350 mg flat dose administered intravenously over 2 h), and fluorouracil bolus 400 mg/m2 administered intravenously over 5 min, followed by a 46 h infusion of fluorouracil 2400 mg/m2 repeated every 2 weeks (regimen one), or oxaliplatin 130 mg/m2 administered intravenously over 2 h and oral capecitabine 1000 mg/m2 twice daily on days 1-14 repeated every 3 weeks (regimen two). Patients who had received adjuvant oxaliplatin could receive irinotecan 180 mg/m2 intravenously over 30 min with fluorouracil instead of oxaliplatin (regimen three). Cetuximab was given intravenously, 500 mg/m2 every 2 weeks with regimen one and three or a loading dose of 400 mg/m2 followed by a weekly infusion of 250 mg/m2 with regimen two. The primary endpoint of progression-free survival was published previously. Secondary endpoints were overall survival, preoperative response, pathological resection status, and safety. Trial recruitment was halted prematurely on the advice of the Trial Steering Committee on Nov 1, 2012. All analyses (except safety) were done on the intention-to-treat population. Safety analyses included all randomly assigned patients. This trial is registered with ISRCTN, number 22944367. FINDINGS: Between Feb 26, 2007, and Oct 12, 2012, 257 eligible patients were randomly assigned to chemotherapy with cetuximab (n=129) or without cetuximab (n=128). This analysis was carried out 5 years after the last patient was recruited, as defined in the protocol, at a median follow-up of 66·7 months (IQR 58·0-77·5). Median progression-free survival was 22·2 months (95% CI 18·3-26·8) in the chemotherapy alone group and 15·5 months (13·8-19·0) in the chemotherapy plus cetuximab group (hazard ratio [HR] 1·17, 95% CI 0·87-1·56; p=0·304). Median overall survival was 81·0 months (59·6 to not reached) in the chemotherapy alone group and 55·4 months (43·5-71·5) in the chemotherapy plus cetuximab group (HR 1·45, 1·02-2·05; p=0·036). There was no significant difference in the secondary outcomes of preoperative response or pathological resection status between groups. Five deaths might have been treatment-related (one in the chemotherapy alone group and four in the chemotherapy plus cetuximab group). The most common grade 3-4 adverse events reported were: neutrophil count decreased (26 [19%] of 134 in the chemotherapy alone group vs 21 [15%] of 137 in the chemotherapy plus cetuximab group), diarrhoea (13 [10%] vs 14 [10%]), skin rash (one [1%] vs 22 [16%]), thromboembolic events (ten [7%] vs 11 [8%]), lethargy (ten [7%] vs nine [7%]), oral mucositis (three [2%] vs 14 [10%]), vomiting (seven [5%] vs seven [5%]), peripheral neuropathy (eight [6%] vs five [4%]), and pain (six [4%] vs six [4%]). INTERPRETATION: Although the addition of cetuximab to chemotherapy improves the overall survival in some studies in patients with advanced, inoperable metastatic disease, its use in the perioperative setting in patients with operable disease confers a significant disadvantage in terms of overall survival. Cetuximab should not be used in this setting. FUNDING: Cancer Research UK

Bankless channel irrigation systems: irrigation performance assessment

Bankless Channel Irrigation Systems are being used by broadacre irrigators seeking to improve farm efficiencies. Evaluation of the irrigation performance of these systems has been difficult due to the operational nature of these systems. Using novel evaluation methods and tools an evaluation of the irrigation performance of a bankless system was achieved. These evaluations revealed the application efficiency at both the system and bay scale and will assist in the development of an irrigation evaluation technique and simulation model capable of simulating the performance of this system