Quantitative accuracy assessment of the revised sparse Gash model using distinct time-step climatic parameters

Rainfall interception (I) can considerably influence the transport process of water. The revised sparse Gash model (RSGM) is a tool for determining the I, which assumes that the two climate parameters in the model are equal for all storms. However, few studies have provided additional cases to reexamine the correctness of this assumption and investigated the response of I of single storms to the time-step variability in climatic parameters. Hence, running the RSGM separately on an event basis during the growing season in 2017 and using three time-step climatic parameters (storm-based, monthly, and fixed) to estimate I for the forest stands of Pinus tabuliformis, Platycladus orientalis, and Acer truncatum in Northern China. In summary, the modeling accuracy of both cumulative I and individual I was enhanced by increasing the time step of the climatic parameters in this study. These positively support the assumption in the RSGM. These results suggest that it is more appropriate to run the RSGM using fixed climate parameters to estimate I for these tree species during the growing season in northern China. Additionally, the assumption in the RSGM should be appealed to be further confirmed across the widest possible range of species, regions, and time scales.

Wet Deposition of Mercury and Dissolved Organic Carbon during Pre-Monsoon and Monsoon Periods at Sitapuri Site in Delhi (India)

This rainwater chemistry study was carried out during monsoon and pre-monsoon seasons in 2018. The rainwater samples were collected in the residential area of Sitapuri which is situated the southwest zone of city Delhi. The rainwater samples were collected with the help of the funnel and bottle assembly on event basis. To refrain any contamination from the ground, the assembly was mounted at 5m above the ground level on a terrace. The assembly was always installed on the onset of rain and retrieved soon after the rain stopped. The collected samples were filtered. The samples were analyzed for Mercury (Hg0), Total Nitrogen (TN) and Dissolved Organic Carbon (DOC). The Hg(o) determination was done using Differential Pulse Anodic Stripping Voltammetry through standard addition methods and DOC species and TN species were determined using DOC/TN analyzer (Shimadzu model LCPH/CPN). The average concentration of Hg0 was recorded as 54.9 μg/l, while that of DOC and TN as 160.2 mg/l and 12.6 mg/l respectively. The study indicated that Hg0 and DOC were not contributed by common emission sources. Also, the study indicated that pre-monsoon air was more contaminated with Hg (0), TN and DOC as compared to the monsoon season.

Impact of improved energy resolution on DUNE sensitivity to neutrino non-standard interactions

The full physics potential of the next-generation Deep Underground Neutrino Experiment (DUNE) is still being explored. In particular, there have been some recent studies on the possibility of improving DUNE’s neutrino energy reconstruction. The main motivation is that a better determination of the neutrino energy in an event-by-event basis will translate into an improved measurement of the Dirac C P phase and other neutrino oscillation parameters. To further motivate studies and improvements on the neutrino energy reconstruction, we evaluate the impact of energy resolution at DUNE on an illustrative new physics scenario, viz. non-standard interactions (NSI) of neutrinos with matter. We show that a better energy resolution in comparison to the ones given in the DUNE conceptual and technical design reports may significantly enhance the experimental sensitivity to NSI, particularly when degeneracies are present. While a better reconstruction of the first oscillation peak helps disentangling standard C P effects from those coming from NSIs, we find that the second oscillation peak also plays a nontrivial role in improving DUNE’s sensitivity.

Rainfall-Runoff Analysis using Runoff Coefficient and SCS-CN Methods under GIS Approach

Estimation of runoff in a watershed is very important to manage the water resources efficiently. In this regard, surface runoff quantification is an essential study. The main objective of this study is to quantify the surface runoff of the catchment area of a well located in AEC & RI, TNAU, Kumulur, Trichy District of Tamil Nadu State, India. An attempt also made to analyze the surface runoff by SCS-CN event and annual basis as well as by modified runoff-coefficient method. This study identified the variation of runoff volume within different approaches of SCS-CN method and runoff coefficient method. By using GPS and GIS techniques catchment area of a well and slope direction was delineated. With the help of GIS tools and remote sensing technology with ground truth verifications, the land use/ land cover and soil maps were delineated for the study area. Sandy loam and sandy clay loam type of soils are predominating and HSG ‘C’ was identified for the study area. The highest CN value is 92 and the maximum runoff coefficient value is 0.95 for the Built-up land, the lowest CN value is 71 and the lowest runoff coefficient is 0.11 for the area covered with trees. Three AMC conditions were considered while estimating runoff volume by SCS-CN event approach. Among 15 years of rainfall data from 2004 to 2018, the highest runoff 38452.36 m3 was generated in the year 2005 and the lowest runoff 8718.29 m3 was generated in 2018 by SCS-CN event basis method. From this study between two concepts of SCS-CN and runoff coefficient models, the SCS-CN model with an event basis approach is yielding productive results. For quantifying surface runoff and for planning water conservation structures event basis calculations are more effective.

Underlying Climate Controls in Triple Oxygen (16 O, 17 O, 18 O) and Hydrogen (1 H, 2 H) Isotopes Composition of Rainfall (Central Pyrenees)

Studies of rainfall isotopic composition in the Iberian Peninsula are scarce, and to date, none of them have provided analyses of the triple oxygen isotopes, preventing from the complete understanding of current atmospheric processes in this region. We investigate the rainwater δ17O, δ18O, and δD and derived parameters 17O-excess and d-excess in a mountain site in the Central South Pyrenees (Villanúa, Huesca, Spain) to identify the main factors (regional and local) controlling the isotopic composition of precipitation at event scale. The samples were collected on a rainfall-event basis during 2 years (from July 2017 to June 2019), and meteorological variables [temperature, relative humidity (RH), and rainfall amount] were monitored at the sampling site. The δ17O, δ18O, and δD values were higher during summer and lower during the rest of the year. In contrast, the 17O-excess and d-excess were lower during summer and higher during the remaining months. We found that the isotopic parameters are weakly correlated with rainfall amount during each event, but they strongly depend on changes in air temperature and moderately on RH. We consider other factors affecting the isotopic composition of rainfall events that resulted to have an important role, such as the influence of the moisture source and trajectory throughout the variations in the synoptic pattern during rainfall events. This dataset can be useful for further comprehensive atmospheric and hydrological studies, with application to paleoclimatic investigations.

Deep Learning Based Impact Parameter Determination for the CBM Experiment

In this talk we presented a novel technique, based on Deep Learning, to determine the impact parameter of nuclear collisions at the CBM experiment. PointNet based Deep Learning models are trained on UrQMD followed by CBMRoot simulations of Au+Au collisions at 10 AGeV to reconstruct the impact parameter of collisions from raw experimental data such as hits of the particles in the detector planes, tracks reconstructed from the hits or their combinations. The PointNet models can perform fast, accurate, event-by-event impact parameter determination in heavy ion collision experiments. They are shown to outperform a simple model which maps the track multiplicity to the impact parameter. While conventional methods for centrality classification merely provide an expected impact parameter distribution for a given centrality class, the PointNet models predict the impact parameter from 2–14 fm on an event-by-event basis with a mean error of −0.33 to 0.22 fm.

Columnar data analysis with ATLAS analysis formats

Future analysis of ATLAS data will involve new small-sized analysis formats to cope with the increased storage needs. The smallest of these, named DAOD_PHYSLITE, has calibrations already applied to allow fast downstream analysis and avoid the need for further analysis-specific intermediate formats. This allows for application of the “columnar analysis” paradigm where operations are applied on a per-array instead of a per-event basis. We will present methods to read the data into memory, using Uproot, and also discuss I/O aspects of columnar data and alternatives to the ROOT data format. Furthermore, we will show a representation of the event data model using the Awkward Array package and present proof of concept for a simple analysis application.

Investigation of centrality dependence of dynamical fluctuations in narrow pseudo-rapidity interval on event-by-event basis

A detailed study of centrality dependence of event-by-event fluctuations of maximum particle density of the produced particles in narrow pseudo-rapidity interval in terms of the scaled variance [Formula: see text] has been carried out for [Formula: see text]O-emulsion interactions at 4.5[Formula: see text]AGeV/[Formula: see text]. Depending on the values of the total charges or sum of the charges of noninteracting projectile fragments, event samples were classified into four centrality classes. Presence of event-by-event fluctuations of maximum particle density is reflected in the multiparticle production process for different centrality classes. The event-by-event fluctuations are found to decrease with the increase of pseudo-rapidity interval. The event-by-event fluctuations are found to decrease with decreasing centrality of collisions. A comparison with the analyzed results of the total disintegration events has also been carried out. Experimental analysis results have been compared with those obtained from the analysis of Monte Carlo simulated (MC-RAND) events in order to extract the dynamical fluctuations.