102 research outputs found
ACCOUNTING FOR SPATIAL CHARACTERISTICS OF WATERSHEDS IN EVALUATING WATER POLLUTION ABATEMENT POLICIES
This study evaluates three agricultural nonpoint pollution abatement policies: regulating the spatial pattern of agricultural activities, ambient tax, and abatement tax/subsidy. All three policies incorporate spatial characteristics of agricultural emission loading and movement for an agricultural watershed in the Midwest. The effects of spatial variation in natural conditions and landscape features on agricultural emissions and crop yield are evaluated using a newly developed biophysical simulation model and experimental data. While the policies are equally cost effective in reducing agricultural nonpoint source pollution, their implementation feasibility is quite different.atrazine, environmental policy, nonpoint pollution, simulation, watershed management, water quality, Environmental Economics and Policy,
Potential Impacts of and Adaptation to Future Climate Change for Crop Farms: A Case Study of Flathead Valley, Montana
Improved indexes for targeting placement of buffers of Hortonian runoff
Targeting specific locations within agricultural watersheds for installing vegetative buffers has been advocated as a way to enhance the impact of buffers and buffer programs on stream water quality. Existing models for targeting buffers of Hortonian, or infiltration-excess, runoff are not well developed. The objective was to improve on an existing soil survey–based approach that would provide finer scale resolution, account for variable size of runoff source area to different locations, and compare locations directly on the basis of pollutant load that could be retained by a buffer. The method couples the Soil Survey Geographic database with topographic information provided by a grid digital elevation model in a geographic information system. Simple empirical equations were developed from soil and topographic variables to generate two indexes, one for deposition of sediment and one for infiltration of dissolved pollutants, and the equations were calibrated to the load of sediment and water, respectively, retained by a buffer under reference conditions using the process-based Vegetative Filter Strip Model. The resulting index equations and analytical procedures were demonstrated on a 67 km2 (25.9 mi2) agricultural watershed in northwestern Missouri, where overland runoff contributes to degraded stream water quality. For both indexes, mapped results clearly mimic spatial patterns of water flow convergence into subdrainages, substantiating the importance of size of source area to a given location on capability to intercept pollutants from surface runoff. A method is described for estimating a range of index values that is appropriate for targeting vegetative buffers. The index for sediment retention is robust. However, the index for water (and dissolved pollutant) retention is much less robust because infiltration is very small, compared to inflow volumes, and is relatively insensitive to the magnitude of inflow from source areas. Consequently, an index of inflow volume may be more useful for planning alternative practices for reducing dissolved pollutant loads to streams. The improved indexes provide a better method than previous indexes for targeting vegetative buffers in watersheds where Hortonian runoff causes significant nonpoint pollution
Potential of Core-Collapse Supernova Neutrino Detection at JUNO
JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve
Detection of the Diffuse Supernova Neutrino Background with JUNO
As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO
Real-time Monitoring for the Next Core-Collapse Supernova in JUNO
Core-collapse supernova (CCSN) is one of the most energetic astrophysical
events in the Universe. The early and prompt detection of neutrinos before
(pre-SN) and during the SN burst is a unique opportunity to realize the
multi-messenger observation of the CCSN events. In this work, we describe the
monitoring concept and present the sensitivity of the system to the pre-SN and
SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is
a 20 kton liquid scintillator detector under construction in South China. The
real-time monitoring system is designed with both the prompt monitors on the
electronic board and online monitors at the data acquisition stage, in order to
ensure both the alert speed and alert coverage of progenitor stars. By assuming
a false alert rate of 1 per year, this monitoring system can be sensitive to
the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos
up to about 370 (360) kpc for a progenitor mass of 30 for the case
of normal (inverted) mass ordering. The pointing ability of the CCSN is
evaluated by using the accumulated event anisotropy of the inverse beta decay
interactions from pre-SN or SN neutrinos, which, along with the early alert,
can play important roles for the followup multi-messenger observations of the
next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure
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