Stable isotopes reveal groundwater to river connectivity in a mesoscale subtropical watershed

The Corumbataí River basin (São Paulo, Brazil) has a critical situation regarding water availability due to the intensive use to support agriculture and urbanization, requiring scientific information to face water demand. The aim of this study is to present a hydrological characterization based on the analysis of seasonal isotope variations (rainfall, groundwater, and surface water) and hydrometric data. Results indicate that baseflow contribution varies from 50 % to 70 % of the total flow, and water isotopic composition denotes a seasonal regime marked by the mixing of surface and groundwater in the wet period and groundwater discharge during the dry season. The results presented indicated the strong seasonal connection between atmospheric inputs and water movement across the basin, which poses an urgent need to diversify monitoring methods and create feasible regional and political regulations to control the effects on basin water resilience in the face of climate change and growing demand.

Controls over spatial and seasonal variations on isotopic composition of the precipitation along the central and eastern portion of Brazil

Based on Global Network Isotopes in Precipitation (GNIP) isotopic data set, a review of the spatial and temporal variability of δ¹⁸O and δ²H in precipitation was conducted throughout central and eastern Brazil, indicating that dynamic interactions between Intertropical and South Atlantic Convergence Zones, Amazon rainforest, and Atlantic Ocean determine the variations on the isotopic composition of precipitation over this area. Despite the seasonality and latitude effects observed, a fair correlation with precipitation amount was found. In addition, Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) air mass back trajectories were used to quantify the factors controlling daily variability in stable isotopes in precipitation. Through a linear multiple regression analysis, it was observed that temporal variations were consistent with the meteorological parameters derived from HYSPLIT, particularly precipitation amount along the trajectory and mix depth, but are not dependent on vapour residence time in the atmosphere. These findings also indicate the importance of convective systems to control the isotopic composition of precipitation in tropical and subtropical regions.

Compression of ECG signals by optimized quantization of discrete cosine transform coefficients

This paper presents an ECG compressor based on optimized quantization of Discrete Cosine Transform (DCT) coefficients. The ECG to be compressed is partitioned in blocks of fixed size, and each DCT block is quantized using a quantization vector and a threshold vector that are specifically defined for each signal. These vectors are defined, via Lagrange multipliers, so that the estimated entropy is minimized for a given distortion in the reconstructed signal. The optimization method presented in this paper is an adaptation for ECG of a technique previously used for image compression. In the last step of the compressor here proposed, the quantized coefficients are coded by an arithmetic coder. The Percent Root-Mean-Square Difference (PRD) was adopted as a measure of the distortion introduced by the compressor. To assess the performance of the proposed compressor, 2-minute sections of all 96 records of the MIT-BIH Arrhythmia Database were compressed at different PRD values, and the corresponding compression ratios were computed. We also present traces of test signals before and after the compression/decompression process. The results show that the proposed method achieves good compression ratios (CR) with excellent reconstruction quality. An average CR of 9.3:1 is achieved for PRD equal to 2.5%. Experiments with ECG records used in other results from the literature revealed that the proposed method compares favorably with various classical and state-of-the-art ECG compressors.