Geochemical and stable isotopic evolution of the Guarani Aquifer System in the state of São Paulo, Brazil

The purpose of this report is to explain geochemical and stable isotopes trends in the Brazilian unit of the Guarani Aquifer System (Botucatu and Piramboia aquifers) in S?o Paulo State, Brazil. Trends of dissolved species concentrations and geochemical modeling indicated a significant role of cation exchange and dissolution of carbonates in downgradient evolution of groundwater chemistry. Loss of calcium by the exchange for sodium drives dissolution of carbonates and results in Na–HCO₃ type of groundwater. The cation-exchange front moves downgradient at probably much slower rate compared to the velocity of groundwater flow and at present is located near to the cities of Sert?ozinho and águas de Santa Barbara (wells PZ-34 and PZ-148, respectively) in a shallow confined area, 50–70 km from the recharge zone. Part of the sodium probably enters the Guarani Aquifer System. together with chloride and sulfate from the underlying Piramboia Formation by diffusion related to the dissolution of evaporates like halite and gypsum. High concentrations of fluorine (up to 13.3 mg/L) can be explained by dissolution of mineral fluoride also driven by cation exchange. However, it is unclear if the dissolution takes place directly in the Guarani Aquifer System or in the overlying basaltic Serra Geral Formation. There is depletion in δ ²H and δ ¹⁸O values in groundwater downgradient. Values of δ ¹³C(DIC) are enriched downgradient, indicating dissolution of calcite under closed system conditions. Values of δ ¹³C(DIC) in deep geothermal wells are very high (>–6.0‰) and probably indicate isotopic exchange with carbonates with δ ¹³C about –3.0‰. Future work should be based on evaluation of vertical fluxes and potential for penetration of contamination to the Guarani Aquifer System. Electronic Publication     

Strategies to Make Methods Based on Flow Injection Analysis Greener

The implementation of flow injection analysis (FIA) systems and correlated techniques in the laboratory routine provides an increase of analytical throughput and the reduction of risks of analyte losses and contamination. Naturally, it contributes to the reduction of reagent consumption and minimization of waste generation. This paper presents and discusses an overview of the main strategies adopted to make methods based on FIA systems more environmentally friendly, and offers a review of these methods that covers the period from January 2002 to December 2019. Strategies based on reagent management (adoption of procedures without reagents, replacement of toxic reagents, recycling and reuse of reagents and, use of immobilized reagents), the online waste treatment, and the improvements of FIA systems (flow system configurations that avoid reagent wastage, use of green detectors, automation, and miniaturization) are approached in this perspective.     

Resampling of spatially correlated data with preferential sampling for the estimation of frequency distributions and semivariograms

Spatial data are commonly minimal and may have been collected in the process of confirming the profitability of a mining venture or investigating a contaminated site. In such situations, it is common to have measurements preferentially taken in the most critical areas (sweet spots, allegedly contaminated areas), thus conditionally biasing the sample. While preferential sampling makes good practical sense, its direct use leads to distorted sample moments and percentiles. Spatial clusters are a problem that has been identified in the past and solved with approaches ranging from ad hoc solutions to highly elaborate mathematical formulations, covering mostly the effect of clustering on the cumulative frequency distribution. The method proposed here is a form of resample, free of special assumptions, does not use weights to ponder the measurements, does not find solutions by successive approximation and provides variability in the results. The new method is illustrated with a synthetic dataset with an exponential semivariogram and purposely generated to follow a lognormal distribution. The lognormal distribution is both difficult to work with and typical of many attributes of practical interest. Testing of the new solution shows that sample subsets derived from resampled datasets can closely approximate the true probability distribution and the semivariogram, clearly outperforming the original preferentially sampled data.     

A regional water balance indicator inferred from satellite images of an Andean endorheic basin in central-western Argentina

In the Central Andes of Argentina (30–37°S), snowmelt is the main source of freshwater, an essential natural resource for ~2.2 million people in the adjacent arid lowlands. In this region, Laguna Llancanelo collects the water inputs from the Malargüe endorheic basin. Previous studies concerning the annual and intra-annual variations of this lagoon and its relationship with regional climate are rare. We obtained a monthly record for the Laguna Llancanelo area (LLA, 1984–2013) using the modified normalized difference water index derived from Landsat images. Monthly LLA ranges between 35 km² and 411 km² and is significantly related to variations of the Río Malargüe, the main snow-fed tributary to the lagoon. There is no long-term relationship between LLA and local rainfall, but rapid increases in LLA result from heavy rainfall around the lagoon. Conversely, rapid reductions in LLA encompass periods with both reduced discharge from the Río Malargüe and low local rainfall. The LLA integrates moisture of both Pacific (snowfall in the upper Andes) and Atlantic (lowland rainfall) origins; therefore, we propose using LLA as an indicator of regional water balance.     

Estimating sand concentrations using ADCP-based acoustic inversion in a large fluvial system characterized by bi-modal suspended-sediment distributions

Quantifying sediment flux within rivers is a challenge for many disciplines due, mainly, to difficulties inherent to traditional sediment sampling methods. These methods are operationally complex, high cost, and high risk. Additionally, the resulting data provide a low spatial and temporal resolution estimate of the total sediment flux, which has impeded advances in the understanding of the hydro-geomorphic characteristics of rivers. Acoustic technologies have been recognized as a leading tool for increasing the resolution of sediment data by relating their echo intensity level measurements to suspended sediment. Further effort is required to robustly test and develop these techniques across a wide range of conditions found in natural river systems. This article aims to evaluate the application of acoustic inversion techniques using commercially available, down-looking acoustic Doppler current profilers (ADCPs) in quantifying suspended sediment in a large sand bed river with varying bi-modal particle size distributions, wash load and suspended-sand ratios, and water stages. To achieve this objective, suspended sediment was physically sampled along the Paraná River, Argentina, under various hydro-sedimentological regimes. Two ADCPs emitting different sound frequencies were used to simultaneously profile echo intensity level within the water column. Using the sonar equation, calibrations were determined between suspended-sand concentrations and acoustic backscatter to solve the inverse problem. The study also analyzed the roles played by each term of the sonar equation, such as ADCP frequency, power supply, instrument constants, and particle size distributions typically found in sand bed rivers, on sediment attenuation and backscatter. Calibrations were successfully developed between corrected backscatter and suspended-sand concentrations for all sites and ADCP frequencies, resulting in mean suspended-sand concentration estimates within about 40% of the mean sampled concentrations. Noise values, calculated using the sonar equation and sediment sample characteristics, were fairly constant across evaluations, suggesting that they could be applied to other sand bed rivers. © 2018 John Wiley & Sons, Ltd.     

Kalman filtering of vessel motions for ocean wave directional spectrum estimation

This paper proposes a high-speed iterative procedure for estimating the ocean wave directional spectrum from vessel motion data. It uses as input data, the measurements from motion sensors that are commonly available on dynamically positioned vessels and which may easily be installed on any ship. Because the necessary sensors are relatively inexpensive or may already be installed, it becomes an ideal solution to provide initial estimates to offline estimation procedures and to give spectral updates under quickly changing weather conditions. The Kalman filtering algorithm, for iterative harmonic detection, and frequency domain vessel response data are used in the estimation procedure. The results and conclusions are still based on synthesized data, but very promising.     

Vulnerability of water resources,vegetation productivity and soil erosion to climate change in Mediterranean watersheds

Climate change is expected to increase temperatures and lower rainfall in Mediterranean regions; however, there is a great degree of uncertainty as to the amount of change. This limits the prediction capacity of models to quantify impacts on water resources, vegetation productivity and erosion. This work circumvents this problem by analysing the sensitivity of these variables to varying degrees of temperature change (increased by up to 6·4 °C), rainfall (reduced by up to 40%) and atmospheric CO₂ concentrations (increased by up to 100%). The SWAT watershed model was applied to 18 large watersheds in two contrasting regions of Portugal, one humid and one semi‐arid; incremental changes to climate variables were simulated using a stochastic weather generator. The main results indicate that water runoff, particularly subsurface runoff, is highly sensitive to these climate change trends (down by 80%). The biomass growth of most species showed a declining trend (wheat down by 40%), due to the negative impacts of increasing temperatures, dampened by higher CO₂ concentrations. Mediterranean species, however, showed a positive response to milder degrees of climate change. Changes to erosion depended on the interactions between the decline in surface runoff (driving erosion rates downward) and biomass growth (driving erosion rates upward). For the milder rainfall changes, soil erosion showed a significant increasing trend in wheat fields (up to 150% in the humid watersheds), well above the recovery capacity of the soil. Overall, the results indicate a shift of the humid watersheds to acquire semi‐arid characteristics, such as more irregular river flows and increasingly marginal conditions for agricultural production. Copyright © 2007 John Wiley & Sons, Ltd.     

Declustering of Clustered Preferential Sampling for?Histogram and Semivariogram Inference

Measurements of attributes obtained more as a consequence of business ventures than sampling design frequently result in samplings that are preferential both in location and value, typically in the form of clusters along the pay. Preferential sampling requires preprocessing for the purpose of properly inferring characteristics of the parent population, such as the cumulative distribution and the semivariogram. Consideration of the distance to the nearest neighbor allows preparation of resampled sets that produce comparable results to those from previously proposed methods. A clustered sampling of size 140, taken from an exhaustive sampling, is employed to illustrate this approach.     

Declustering of Clustered Preferential Sampling for Histogram and Semivariogram Inference

Measurements of attributes obtained more as a consequence of business ventures than sampling design frequently result in samplings that are preferential both in location and value, typically in the form of clusters along the pay. Preferential sampling requires preprocessing for the purpose of properly inferring characteristics of the parent population, such as the cumulative distribution and the semivariogram. Consideration of the distance to the nearest neighbor allows preparation of resampled sets that produce comparable results to those from previously proposed methods. A clustered sampling of size 140, taken from an exhaustive sampling, is employed to illustrate this approach.