High-resolution aquifer analog of fluvial–aeolian sediments of the Guarani aquifer system

The Guarani aquifer system (GAS) represents one of the biggest aquifers in the world and is the most relevant groundwater resource in South America. For the first time, by combining field and laboratory measurements, a high-resolution aquifer analog model of fluvial–aeolian sediments of the GAS in São Paulo State (Brazil) is constructed. Three parallel sections of frontal outcrops, 28 m × 5.8 m, and two parallel sections of lateral outcrops, 7 m × 5.8 m, are recorded during open-pit mining of sandy sediments and describe in detail the three-dimensional distribution of the local lithofacies and hydrofacies. Variations of hydraulic conductivity, K, and porosity, n, are resolved on the centimeter scale, and the most permeable units of the fluvial–aeolian facies association are identified. The constructed aquifer analog model shows moderate hydraulic heterogeneity and a mean K value of 1.36 × 10^?4 m/s, which is greater than the reported range of K values for the entire GAS in São Paulo State. The results suggest that the examined sedimentary unit constitutes a relevant portion of the GAS in São Paulo State in the context of groundwater extraction and pollution. Moreover, the constructed aquifer analog is considered an ideal basis for future numerical model experiments, aiming at in-depth understanding of the groundwater flow and contaminant transport patterns at this GAS portion or at comparable fluvial–aeolian facies associations.     

Analyzing the spatial interactions between rainfall levels and flooding prediction in São Paulo

Rainfall is one of the primary triggers for many geological and hydrological natural disasters. While the geological events are related to mass movements in land collapse due to waterlogging, the hydrological ones are usually assigned to runoff or flooding. Studies in the literature propose predicting mass movement events as a function of accumulated rainfall levels recorded at distinct periods. According to these approaches, a two-dimensional rainfall levels feature space is segmented into the occurrence and non-occurrence decision regions by an empirical critical curve (CC). Although this scheme may easily be extended to other purposes and applications, studies in the literature need to discuss its use for flooding prediction. In light of this motivation, the present study is unfolded in (1) verifying that defining CCs in the rainfall levels feature space is a practical approach for flooding prediction and (2) analyzing how geospatial components interact with rainfall levels and flooding prediction. A database containing the rainfall levels recorded for flooding and non-flooding events in São Paulo city, Brazil, regarding the period 2015–2016, was considered in this study. The results indicate good accuracy for flooding prediction using only partial rain, which can be improved by adding physical characteristics of the flooding locations, demonstrating a direct correlation with spatial interactions, and rainfall levels.