Groundwater Geochemistry and Saltwater Intrusion in the Dakar Coastal Area, Senegal

Groundwater levels and water samples were collected from 20 drinking water pumping and piezometer wells in the urban area of Dakar coastal region in the year 2019. The pH-value, electrical conductivity, as well as calcium, magnesium, sodium, potassium, chloride, sulfate, bicarbonate, and nitrate concentrations were measured to assess the hydrochemical quality of the infrabasaltic aquifer in the area. The present work carried out a hydrochemical analysis to interpret the groundwater chemistry of the aquifer. The results of this chemical analysis indicate that Na+ > Mg2+ > Ca2+ > K+ was the most dominant cation sequence in the groundwater, while Cl- > HCO3- > SO42- > NO3- was the most dominant one for anions. The chemical analysis of our samples showed, that the Cl-Ca-Mg facies was dominant in the aquifer, while Cl-Na-K and HCO3-Na-K facies represent 20% and 10% of the groundwater sampled, respectively. A comparison of the measured groundwater quality in relation to WHO drinking water quality standards revealed that 80% of the water samples are suitable for drinking purposes. Ca enrichment, Simpson ratio, ratio of sodium chloride, and calculating Base Exchange (BEX) indices for the samples revealed that the groundwater is mainly affected by three factors: seawater intrusion due to aquifer overexploitation on one hand, and freshening processes and nitrate pollution, on the other, mainly caused by the groundwater flow from the unconfined aquifer.

Comparison of smoothness-constrained and geostatistically based cross-borehole electrical resistivity tomography for characterization of solute tracer plumes

Experiments using electrical resistivity tomography(ERT) have shown promising results in reducing the uncertainty of solute plume characteristics related to estimates based on the analysis of local point measurements only.To explore the similarities and differences between two cross-borehole ERT inversion approaches for characterizing salt tracer plumes,namely the classical smoothness-constrained inversion and a geostatistically based approach,we performed two-dimensional synthetic experiments.Simplifying assumptions about the solute transport model and the electrical forward and inverse model allowed us to study the sensitivity of the ERT inversion approaches towards a variety of basic conditions,including the number of boreholes,measurement schemes,contrast between the plume and background electrical conductivity,use of a priori knowledge,and point conditioning.The results show that geostatistically based and smoothness-constrained inversions of electrical resistance data yield plume characteristics of similar quality,which can be further improved when point measurements are incorporated and advantageous measurement schemes are chosen.As expected,an increased number of boreholes included in the ERT measurement layout can highly improve the quality of inferred plume characteristics,while in this case the benefits of point conditioning and advantageous measurement schemes diminish.Both ERT inversion approaches are similarly sensitive to the noise level of the data and the contrast between the solute plume and background electrical conductivity,and robust with regard to biased input parameters,such as mean concentration,variance,and correlation length of the plume.Although sophisticated inversion schemes have recently become available,in which flow and transport as well as electrical forward models are coupled,these schemes effectively rely on a relatively simple geometrical parameterization of the hydrogeological model.Therefore,we believe that standard uncoupled ERT inverse approaches,like the ones discussed and assessed in this paper,will continue to be important to the imaging and characterization of solute plumes in many real-world applications.

3D U-Net Segmentation Improves Root System Reconstruction from 3D MRI Images in Automated and Manual Virtual Reality Work Flows

Magnetic resonance imaging(MRI)is used to image root systems grown in opaque soil.However,reconstruction of root system architecture(RSA)from 3-dimensional(3D)MRI images is challenging.Low resolution and poor contrast-to-noise ratios(CNRs)hinder automated reconstruction.Hence,manual reconstruction is still widely used.Here,we evaluate a novel 2-step work flow for automated RSA reconstruction.In the first step,a 3D U-Net segments MRI images into root and soil in super-resolution.In the second step,an automated tracing algorithm reconstructs the root systems from the segmented images.We evaluated the merits of both steps for an MRI dataset of 8 lupine root systems,by comparing the automated reconstructions to manual reconstructions of unaltered and segmented MRI images derived with a novel virtual reality system.We found that the U-Net segmentation offers profound benefits in manual reconstruction:reconstruction speed was doubled(+97%)for images with low CNR and increased by 27%for images with high CNR.Reconstructed root lengths were increased by 20%and 3%,respectively.Therefore,we propose to use U-Net segmentation as a principal image preprocessing step in manual work flows.The root length derived by the tracing algorithm was lower than in both manual reconstruction methods,but segmentation allowed automated processing of otherwise not readily usable MRI images.Nonetheless,model-based functional root traits revealed similar hydraulic behavior of automated and manual reconstructions.Future studies will aim to establish a hybrid work flow that utilizes automated reconstructions as scaffolds that can be manually corrected.

Quantitative Multi-Layer Electromagnetic Induction Inversion and Full-Waveform Inversion of Crosshole Ground Penetrating Radar Data

Due to the recent system developments for the electromagnetic characterization of the subsurface, fast and easy acquisition is made feasible due to the fast measurement speed, easy coupling with GPS systems, and the availability of multi-channel electromagnetic induction（EMI） and ground penetrating radar（GPR） systems. Moreover, the increasing computer power enables the use of accurate forward modeling programs in advanced inversion algorithms where no approximations are used and the full information content of the measured data can be exploited. Here, recent developments of large-scale quantitative EMI inversion and full-waveform GPR inversion are discussed that yield higher resolution of quantitative medium properties compared to conventional approaches. In both cases a detailed forward model is used in the inversion procedure that is based on Maxwell＇s equations. The multi-channel EMI data that have different sensing depths for the different source-receiver offset are calibrated using a short electrical resistivity tomography（ERT） calibration line which makes it possible to invert for electrical conductivity changes with depth over large areas. The crosshole GPR full-waveform inversion yields significant higher resolution of the permittivity and conductivity images compared to ray-based inversion results.

Development and Validation of a Deep Learning Based Automated Minirhizotron Image Analysis Pipeline

Root systems of crops play a significant role in agroecosystems.The root system is essential for water and nutrient uptake,plant stability,symbiosis with microbes,and a good soil structure.Minirhizotrons have shown to be effective to noninvasively investigate the root system.Root traits,like root length,can therefore be obtained throughout the crop growing season.

One decade(2011–2020)of European agricultural water stress monitoring by MSG-SEVIRI:workflow implementation on the Virtual Earth Laboratory(VLab)platform

Cloud computing facilities can provide crucial computing support for processing the time series of satellite data and exploiting their spatio-temporal information content.However,dedicated efforts are still required to develop workflows,executable on cloud-based platforms,for ingesting the satellite data,performing the targeted processes,and generating the desired products.In this study,an operational workflow is proposed,based on monthly Evaporative Stress Index(ESI)anomaly,and implemented in cloud-based online Virtual Earth Laboratory(VLab)platform,as a demonstration,to monitor European agricultural water stress.To this end,daily time-series of actual and reference evapotranspiration(ETa and ET0),from the Spinning Enhanced Visible and Infrared Imager(SEVIRI)sensor,were used to execute the proposed workflow successfully on VLab.The execution of the workflow resulted in obtaining one decade(2011–2020)of European monthly agricultural water stress maps at 0.04˚spatial resolution and corresponding stress reports for each country.To support open science,all the workflow outputs are stored in GeoServer,documented in GeoNetwork,and made available through MapStore.This enables creating a dashboard for better visualization of the results for end-users.The results from this study demonstrate the capability of VLab platform for water stress detection from time series of SEVIRI-ET data.

Influences of perfluorooctanoic acid on the aggregation of multi-walled carbon nanotubes

The aggregation of multi-walled carbon nanotubes （MWCNTs） in the aqueous phase not only inhibits their extensive utilization in various aspects but also dominates their environmental fate and transport.The role of surfactants at low concentration in the aggregation of MWCNTs has been studied,however the effect of perfluorinated surfactants at low concentration is uncertain.To understand this interfacial phenomenon,the influences of perfluorooctanoic acid （PFOA）,and sodium dodecyl sulfate （SDS） as a control,on MWCNT aggregation in the aqueous phase were examined by the UV absorbency method.Influences of pH and cationic species on the critical coagulation concentration （CCC） value were evaluated.The CCC values were dependent on the concentration of PFOA,however a pronounced effect of SDS concentration on the CCC values was not observed.The CCC values of the MWCNTs were 51.6 mmol/L in NaCl and 0.28 mmol/L in CaCl 2 solutions,which suggested pronounced differences in the effects of Na＋ and Ca2＋ ions on the aggregation of the MWCNTs.The presence of both PFOA and SDS significantly decreased the CCC values of the MWCNTs in NaCl solution.The aggregation of the MWCNTs took place under acidic conditions and was not notably altered under neutral and alkaline conditions due to the electrostatic repulsion of deprotonated functional groups on the surface of the MWCNTs.