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The Analysis of Support Systems of Underground Stormwater Basin Using a Multi-Criteria Analysis and Modeling

Mariame Bouchaqour, Ouadif Latifa, Bahi Lahcen

Ecological Engineering & Environmental Technology

2024

Vol. 25, iss. 1

101--114

This paper illustrates the importance of integrating buried stormwater ponds into underground development plans using a multi-criteria analysis and modeling for the selection of support in urban underground constructions, applied to the case study of buried stormwater ponds. This study underlines the importance of careful planning and the use of the technique for order of preference by similarity to ideal solution (TOPSIS) in the selection of support for underground stormwater basins in urban environments. The TOPSIS method led to the selection of diaphragm walls as the optimum solution, illustrating its effectiveness in evaluating alternatives based on a variety of criteria. diaphragm wall modeling using robot structural analysis (RSA) software validated this choice and accurately predicted the structure’s behavior, underlining the importance of numerical tools in engineering decision-making. The analysis of wall displacements, carried out using these tools, confirmed their compliance with standards, validating the choice of cast walls and highlighting the need for continuous monitoring to guarantee the stability of the structures.

Monitoring Land Use and Land Cover Changes Using Remote Sensing Techniques and the Precipitation-Vegetation Indexes in Morocco

Ait El Haj Fatiha, Ouadif Latifa, Akhssas Ahmed

Ecological Engineering & Environmental Technology

2023

Vol. 24, iss. 1

272--286

The study of land use and land cover change (LULC) is essential for the development of strategies, monitoring and control of the ecosystem. The present study aims to describe the dynamics of land cover and land use, and specially the impact of certain climatic parameters on the distribution of vegetation and land cover. For this study, multi-temporal remote sensing data are used to monitor land cover changes in Morocco, using a set of Landsat images, including Landsat 7 (ETM+), Landsat 5 (TM), and Landsat 8 (OLI), captured during the period 2000–2020, those changes were determined by adopting the maximum likelihood (ML) classification method. The classification results show good accuracy values in the range of 90% (2000), 80% (2007), 82% (2010), 93% (2020). The LU/LC change detection showed a decrease of agricultural and forest areas in the order of 5% between the year 2000 and 2020, and an increase of bare soil of 5% to 6%, and a notable change in urban area from 97.31 ha (0.03%) in 2000 to 2988.2637 ha (0.82%) in 2020. The overall results obtained from LULC show that the vegetation cover of the study area has undergone major changes during the study period. In order to monitor the vegetation status, an analysis of the precipitation-vegetation interaction is essential. The normalized difference vegetation index (NDVI) was determined from 2000 to 2020, to identify vegetation categories and quantify the vegetation density in the Lakhdar sub-basin. The obtained NDVI was analyzed using climatic index SPI (Normalized Precipitation Index) based on rainfall data from five stations. The correlation study between NDVI and SPI indices shows a strong linear relation between these two indicators especially while using an annual index SPI12 however, the use of NDVI index based on remote sensing provides a significant result while assessing vegetation. The results of our study can be used for vegetation monitoring and sustainable management of the area, since it is one of the largest basins in the country.