Modelling Pollutant Dispersion in a Street Network

This study constitutes a further step in the analysis of the performances of a street network model to simulate atmospheric pollutant dispersion in urban areas. The model, named SIRANE, is based on the decomposition of the urban atmosphere into two sub-domains: the urban boundary layer, whose dynamics is assumed to be well established, and the urban canopy, represented as a series of interconnected boxes. Parametric laws govern the mass exchanges between the boxes under the assumption that the pollutant dispersion within the canopy can be fully simulated by modelling three main bulk transfer phenomena: channelling along street axes, transfers at street intersections, and vertical exchange between street canyons and the overlying atmosphere. Here, we aim to evaluate the reliability of the parametrizations adopted to simulate these phenomena, by focusing on their possible dependence on the external wind direction. To this end, we test the model against concentration measurements within an idealized urban district whose geometrical layout closely matches the street network represented in SIRANE. The analysis is performed for an urban array with a fixed geometry and a varying wind incidence angle. The results show that the model provides generally good results with the reference parametrizations adopted in SIRANE and that its performances are quite robust for a wide range of the model parameters. This proves the reliability of the street network approach in simulating pollutant dispersion in densely built city districts. The results also show that the model performances may be improved by considering a dependence of the wind fluctuations at street intersections and of the vertical exchange velocity on the direction of the incident wind. This opens the way for further investigations to clarify the dependence of these parameters on wind direction and street aspect ratios.     

Hydrogeological and mixing process of waters in deep aquifers in arid regions: south east Tunisia

This study addresses the hydrogeochemistry of thermal and cold waters from south east Tunisia. Temperature intervals are 38.5–68 °C and 22–27.8 °C for thermal water and cold water, respectively. Three distinct hydrogeological systems supply water either for irrigation or for drinking; they are: (1) the Continental Intercalaire geothermal aquifer (CI), (2) the Turonian aquifer and (3) the Senonian aquifer. A synthetic study including hydrochemical, hydrogeological and geothermal approaches have been applied in order to evaluate the inter-aquifers water transfer in south east of Tunisia. By using silica geothermometers and saturation indices for different solid phases, estimated thermal reservoir temperature varies between 52 and 87 °C and between 75 and 110 °C, respectively. Based on chemical and thermal data, mixing, which occurs between the ascending deep geothermal water and shallow cold water, is about 57 % cold water.     

Hydrochemical characterization of groundwater using multivariate statistical analysis: the Maritime Djeffara shallow aquifer (Southeastern Tunisia)

Worldwide, groundwater resources have been considered as the main sources of drinking, domestic uses, industrial and agriculture water demands, especially in arid and semiarid regions. Accordingly, the monitoring of the groundwater quality based on different tools and methods becomes a necessity. The aim of this study was to apply several approaches to assess the water quality and to define the main hydrochemical process which affect groundwater of the Maritime Djeffara shallow aquifer. In addition to the hydrochemical approach, two multivariate statistical analyses, hierarchical clusters analysis (HCA) and principal component analysis (PCA), were carried out to identify the natural and the anthropogenic processes affecting groundwater chemistry. Hydrochemical approach, based on 47 analyzed groundwater samples, shows that most of samples present a sulfate to mixed chloride, with sodi-potassic tendency facies. According to their chemically composition, the HCA revealed three different groups (C1, C2 and C3) according to their electrical conductivity (EC) values: C1 (average EC = 4500 µS/cm), C2 (average EC = 7040 µS/cm) and C3 (average EC = 9767 µS/cm). Furthermore, PCA results show two principal factors account 84.05% of the total variance: (1) F1 represents the natural component, and (2) F2 symbolizes the anthropic component. Moreover, the groundwater quality map of the Maritime Djeffara shows three categories: suitable, doubtful and unsuitable water for irrigation. These different results should be taken to protect water resources in arid and semiarid regions, especially at the alluvial coastal regions. Also, they help to make a suitable planning to manage and protect the groundwater resources.     

Soil salinization and critical shallow groundwater depth under saline irrigation condition in a Saharan irrigated land

In the arid irrigated lands, understanding the impact of shallow groundwater fluctuation on soil salinization has become crucial. Thus, investigation of the possible options for maintaining the groundwater depth for improving land productivity is of great importance. In this study, under saline irrigation condition, the effects of shallow groundwater depth on water and salt dynamics in the root-zone of date palms were analyzed through a particular field and modeling (SWAP) investigation in a Tunisian Saharan oasis (Dergine Oasis). The model was calibrated and validated against the measured soil water content through the date palm root-zone. The good agreement between measured and estimated soil water content demonstrated that the SWAP model is an effective tool to accurately simulate the water and salt dynamics in the root-zone of date palm. Multiple groundwater depth scenarios were performed, using the calibrated SWAP model, to achieve the optimal groundwater depth. The simulation results revealed that the shallow groundwater with a depth of ~80 cm coupled with frequent irrigation (20 days interval) during the summer season is the best practice to maintain the adequate soil water content (>0.035 (cm³ cm^?3) and safe salinity level (<4 dS m^?1) in the root-zone layer. The results of field investigation and numerical simulation in the present study can lead to a better management of lands with shallow water table in the Saharan irrigated areas.     

Hyperspectral image betweenness centrality clustering based adaptive spatial and spectral neighborhood approach for anomaly detection

Segmentation-based anomaly detectors proceeds to the clustering of the hyperspectral image as a first step. However, most of the well-known clustering methods cluster anomalous pixels as a part of the background. This paper presents a new hyperspectral image clustering approach based on the betweenness centrality measure. The proposed approach starts by the construction of an adaptive spatial and spectral neighborhood for each pixel. This neighborhood is based on the selection of the nearest spectral and spatial neighbors in multiple windows around each pixel to allow well-suited representation of the image features. In the next step, this neighborhood is clustered based on the edge betweenness measure algorithm that splits the image into regions sharing similar features. This approach (1) allows the reduction of intercluster relationship, (2) favors intracluster relations, and (3) preserves small clusters that can hold anomalous pixels. Experimental results show that the proposed approach is efficient for clustering and overcomes the state of the art approaches.