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Perez, Gabriel

Publications and source records attributed to Perez, Gabriel.

Advancing process-based flood frequency analysis for assessing flood hazard and population flood exposure

Recent studies have showcased the use of process-based hydrological models with Stochastic Storm Transposition (SST) techniques to conduct Flood Frequency Analysis (FFA). This framework, referred hereby FFA-SST, has proved to be a robust strategy to estimate peak flows of specific annual exceedance probability (e.g., 100-year peak flow) that can reflect natural and anthropogenic disturbances, including changes in land use and meteorological patterns. With the objective of advancing the FFA-SST framework, this study presents for the first time the use of an Integrated Surface-Subsurface Hydrological Model (ISSHM) to conduct FFA-SST by extending the analysis from peak flow responses to flood extent, enabling a unique view and analysis of flood hazard and population flood exposure at the basin scale. As a proof-of-concept, we used the ISSHM, Advanced Terrestrial Simulator (Amanzi-ATS) model, and the SST model, RainyDay, to conduct FFA-SST by simulating the flood response to 5,000 annual synthetic storm events in a 2,227 $km^2$ Southeast Texas watershed. We demonstrate that ATS, without site-specific calibration, provides a robust process-based representation of peak flows, flood extent, streamflow, evapotranspiration, soil moisture content, and water storage changes. Our results and analyses, covering frequency curves up to a 500-year return period for peak flows, basin inundation fractions, and the number of people exposed to flooding, offer a unique perspective to analyze flood impacts across spatial scales. Overall, this study provides critical insights for flood risk management by extending the FFA-SST framework to include both flood hazard and population flood exposure analyses at the basin scale. Such an approach will empower stakeholders and disaster emergency agencies with a more comprehensive understanding of flood impacts across the entire basin domain, facilitating informed decision-making for flood risk assessment and management.

58 GEOSCIENCES↗

Model data for Flood Frequency Analysis using Stochastic Storm Transposition and an Integrated Surface-Subsurface Hydrological Model

This archived provides scripts and input files used for the implementation of a novel approach to conduct process-based Flood Frequency Analysis using a Stochastic Storm Transposition (SST) and an Integrated Surface-Subsurface Hydrological Model (ISSHM). As a proof-of-concept, this study uses the ISSHM, Advanced Terrestrial Simulator (Amanzi-ATS) model, and the SST model, RainyDay, to conduct flood frequency analysis by simulating the flood response to 5,000 annual synthetic storm events in a ~2000 km2 Southeast Texas watershed.The Watershed Workflow package is implemented in Python3. The Jupyter notebooks can be executed through multiple open-source tools, for example, Anaconda Jupyter Lab, VS Studio Code, etc. Other data files include TXT, CSV, DAT, SBATCH, SHP, TIF, NetCDF, and HDF5 files, which can be read through Python scripts. The input files for the ATS model and RainyDay model have .XML and .SST extensions, respectively, and can be edited in any commonly used text editors.This archive contains:* Scripts and data files essential for generating the ATS model input. It uses the Watershed Workflow package to produce both mesh and ATS input files. * Jupyter notebooks designated for the ATS model evaluation, covering both long-term simulations and 40 rainfall-runoff events.* Input files required to simulate SST storm events using RainyDay.

54 ENVIRONMENTAL SCIENCES↗

Probing the early Milky Way with GHOST spectra of an extremely metal-poor star in the Galactic disc

ABSTRACT Pristine_183.6849 + 04.8619 (P1836849) is an extremely metal-poor ([Fe/H] = −3.3 ± 0.1) star on a prograde orbit confined to the Galactic disc. Such stars are rare and may have their origins in protogalactic fragments that formed the early Milky Way, in low-mass satellites accreted later, or forming in situ in the Galactic plane. Here, we present a chemo-dynamical analysis of the spectral features between 3700−11 000 Å from a high-resolution spectrum taken during Science Verification of the new Gemini High-resolution Optical SpecTrograph. Spectral features for many chemical elements are analysed (Mg, Al, Si, Ca, Sc, Ti, Cr, Mn, Fe, Ni), and valuable upper limits are determined for others (C, Na, Sr, Ba). This main sequence star exhibits several rare chemical signatures, including (i) extremely low metallicity for a star in the Galactic disc, (ii) very low abundances of the light α-elements (Na, Mg, Si) compared to other metal-poor stars, and (iii) unusually large abundances of Cr and Mn, where [Cr, Mn/Fe]NLTE > +0.5. A comparison to theoretical yields from supernova models suggests that two low-mass Population III objects (one 10 M⊙ supernova and one 17 M⊙ hypernova) can reproduce the abundance pattern well (reduced χ2 < 1). When this star is compared to other extremely metal-poor stars on quasi-circular, prograde planar orbits, differences in both chemistry and kinematics imply there is little evidence for a common origin. The unique chemistry of P1836849 is discussed in terms of the earliest stages in the formation of the Milky Way.

Dovgal, Anya↗