Improving Hydrologic Predictions of Distributed Watershed Model via Uncertainty Quantification of Evapotranspiration Methods

Successful initialization and accurate estimation of evapotranspiration (ET) in the coastal plain landscapes are crucial for the prediction of hydrologic variables including streamflow, surficial aquifer lost and infiltration. The aim of this study is to examine the ability of Soil and Water Assessment Tool (SWAT) to accurately represent the characterization of three potential ET methods (Priestley-Taylor (P-T), Penman–Monteith (P-M) and Hargreaves (HG)) using the Sequential Uncertainty FItting (SUFI-2) algorithm during 2003-2005 and 2006-2007 as calibration and validation intervals. The study area was the Waccamaw River watershed, a low-gradient coastal plain watershed in the southeastern US. The results indicated that in estimating ET for a coastal plain landscape, P-T method bracketed more than 75% of daily streamflow during calibration period while both P-M and HG bracketed 57% and 69% of measured streamflow during calibration period, respectively. Model daily performance using P-T method was “very good” (calibration NSE = 0.77; validation NSE=0.90) but only “satisfactory” (P-M calibration NSE = 0.55; HG calibration NSE =0.61) to “good” (P-M validation NSE=0.75; HG validation NSE=0.70) in P-M and HG methods. The prediction mean square error (MSE) for P-T method was comparably low (57.88 and 325.68) compared to P-M (68.34 and 635.95) and HG (69.99 and 551.99) methods at upstream and downstream outlets, respectively. This result suggests that radiation based ET method performed significant results in forested wetland dominated ecosystem with wet and humid surfaces. Based on the water balance analysis, only about 21.2% of flow loss was consumed via stream evaporation and floodplains evapotranspiration, indicating that 78.8% of the loss within the entire study area represented land ET and shallow aquifer recharge. Furthermore, uncertainty quantification revealed that low flows are sensitive to the changes in ET process in dry period and at the beginning of the wet season, but insensitive at the end of the wet season due to nonlinear control of coastal plain soil on water movement. In particular, under conditions of so-called “deep uncertainty” in the coastal plain landscapes, uncertainty quantification of ET methods can lead to the identification of optimal land and water management strategies in the southeastern ecosystems

COSORE: A community database for continuous soil respiration and other soil‐atmosphere greenhouse gas flux data

Globally, soils store two to three times as much carbon as currently resides in the atmosphere, and it is critical to understand how soil greenhouse gas (GHG) emissions and uptake will respond to ongoing climate change. In particular, the soil‐to‐atmosphere CO2 flux, commonly though imprecisely termed soil respiration (RS), is one of the largest carbon fluxes in the Earth system. An increasing number of high‐frequency RS measurements (typically, from an automated system with hourly sampling) have been made over the last two decades; an increasing number of methane measurements are being made with such systems as well. Such high frequency data are an invaluable resource for understanding GHG fluxes, but lack a central database or repository. Here we describe the lightweight, open‐source COSORE (COntinuous SOil REspiration) database and software, that focuses on automated, continuous and long‐term GHG flux datasets, and is intended to serve as a community resource for earth sciences, climate change syntheses and model evaluation. Contributed datasets are mapped to a single, consistent standard, with metadata on contributors, geographic location, measurement conditions and ancillary data. The design emphasizes the importance of reproducibility, scientific transparency and open access to data. While being oriented towards continuously measured RS, the database design accommodates other soil‐atmosphere measurements (e.g. ecosystem respiration, chamber‐measured net ecosystem exchange, methane fluxes) as well as experimental treatments (heterotrophic only, etc.). We give brief examples of the types of analyses possible using this new community resource and describe its accompanying R software package

ngVLA Key Science Goal 5 Understanding the Formation and Evolution of Black Holes in the Era of Multi-Messenger Astronomy

The next-generation Very Large Array (ngVLA) will be a powerful telescope for finding and studying black holes across the entire mass range. High-resolution imaging abilities will allow the separation of low-luminosity black holes in the local Universe from background sources, thereby providing critical constraints on the mass function, formation, and growth of black holes. Its combination of sensitivity and angular resolution will provide new constraints on the physics of black hole accretion and jet formation. Combined with facilities across the spectrum and gravitational wave observatories, the ngVLA will provide crucial constraints on the interaction of black holes with their environments, with specific implications for the relationship between evolution of galaxies and the emission of gravitational waves from in-spiraling supermassive black holes and potential implications for stellar mass and intermediate mass black holes. The ngVLA will identify the radio counterparts to transient sources discovered by electromagnetic, gravitational wave, and neutrino observatories, and its high-resolution, fast-mapping capabilities will make it the preferred instrument to pinpoint electromagnetic counterparts to events such as supermassive black hole mergers. The National Radio Astronomy Observatory is a facility of the National Science Foundation operated under cooperative agreement by Associated Universities, Inc. Part of this research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries