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Because of the strategic importance of the Abydos archaeological site in Egypt as a source of wealth for Egyptian tourism, this study was concerned with carrying out geophysical measurements to detect subsurface succession and measure variations in the geotechnical engineering features of the soils/rocks in order to protect this significant area. The findings will assist geologists and seismologists in collaborating with archaeologists for future site development, revitalization, and investment. The primary objectives of this work were to determine the subsurface lithology, evaluate the engineering geotechnical properties of soils/rocks, identify the layer thicknesses, and identify the site class by calculating Vs30. To achieve these goals, seventeen (17) seismic refraction tomography (SRT) P- and S-wave measurements were executed in front of the Osirion location. SeisImager Software was used for the processing and interpretation of the outcomes. The results were the travel time–distance curves, which were used for building the 2D seismic models that exhibited the velocity and the depth of the layered models. These models were validated by our previous works using electric resistivity tomography and borehole data. The results indicated that this site consisted of three geoseismic subsurface layers. The first layer was the surface that was made up of wadi deposits, which were a mixture of gravel, sand, and silt and were characterized by incompetent to slightly competent materials. The second layer corresponded to the sand and muddy sand deposits of competent rock that was of fair to moderate quality. The third layer (clay deposits) had a higher velocity and was more compact and may be employed as a bedrock layer. The elastic moduli, Vs30, petrophysical, and geotechnical properties of the three geoseismic layers were appraised as essential parameters. Integration of petrophysical and geotechnical parameters and elastic moduli revealed that the third layer was composed of competent clays, which were characterized by low values of porosity, void ratio, Poisson ratio, and stress ratio. It also had a high rigidity, Young’s and bulk moduli, concentration and material indexes, N-value, ultimate bearing capacities, and high density values, and vice versa for the first layer. The standard NEHRP site class was B (rocks). These parameters are ordinarily used as key indications and serve as significant inputs for any future work.

Numerous farmers regularly irrigate their farms with inadequately treated sewage water pumped from the sewage system in the Arab El-Madabegh district of Assiut City, Egypt. According to previous studies, long-term irrigation with partially treated sewage water resulted in significant changes in the physicochemical properties of soil. The principal goals of this study are (1) to infer empirical equations between geoelectrical resistivity measurements and certain biophysicochemical parameters of some soil samples, and (2) to use these empirical equations to calculate the biophysicochemical parameters of the unknown samples for the same location. For this purpose, 27 soil samples at different depth levels (0 to 25, 25 to 60, and 60 to 90 cm) were collected from eleven locations at the sewage station. Physical properties including water content and particle size distribution, chemical properties including soil pH, electrical conductivity (EC), and the heavy metals concentrations, biological properties including total coliform counts, and geoelectrical resistivity measurements were estimated and analyzed for these samples. Electrical resistivity measurements and biophysicochemical properties were cross-correlated using the exponential trend line to fit the cross-correlated data, and the empirical relationships were obtained. These empirical relationships in conjunction with the measured electrical resistivity measurements were used to calculate the biophysicochemical values of the other three random soil samples. The biophysicochemical values of the former three samples were measured by the same normal procedures as 27 samples. Then, the calculated values were correlated with the measured ones. Good correlations between the estimated and the measured values for biophysicochemical features were obtained. Therefore, this method can be employed to calculate the biophysicochemical parameters for any unknown samples that have the same geological conditions for estimating and monitoring soil contamination.