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Comprehension of the long-term effects of irrigation on basic soil characteristics and quality is essential for sustainable land management and agricultural production, particularly in arid regions where water availability is limited. This study aimed to investigate long-term irrigation effects on soil quality, soil organic carbon (SOC), and nitrogen (N) stocks in the arid lands of Egypt. Seventy soil samples were collected and analyzed to determine various soil properties. A soil quality index (SQI), SOC, and N stocks were computed. ANOVA and PCA analyses were used to identify significant differences between alluvial soils in the southwest part of the investigated area and coastal marine soils in the northeast of the study area. The results demonstrated that most of the studied soil parameters had significantly greater values in alluvial compared to coastal marine soils. Long-term irrigation led to an 8.00% increase in SOC and 7.22% increase in N stocks compared to coastal marine soils production. Furthermore, a 39.53% increase was found in the SQI upon long-term irrigation practice. These results suggest that shifting from rain-fed in coastal marine areas to irrigated production systems in alluvial fields can improve soil quality, SOC, and N stocks. Therefore, further studies are required to investigate the impact of additional factors, such as irrigation method and salinity status of sub-surface soil layers, to enhance agricultural productivity and sustainable land use. [ABSTRACT FROM AUTHOR]

Estimating soil erodible fraction based on basic soil properties in arid lands is a valuable research topic in the field of soil science and land management. The Proximal Sensing (PS) technique offers a non-destructive and efficient method to assess wind erosion potential in arid regions. By using Partial Least Squares Regression (PLSR) and Support Vector Machine (SVM) models and combining soil texture and chemical properties, determined through Visible-Near Infrared (vis-NIR) spectroscopy in 96 soil samples, this study aims to predict soil erodibility, soil organic matter (SOM), and calcium carbonate equivalent (CaCO3) in arid lands located in Elkobaneyya Valley, Aswan Governorate, Egypt. Results showed that the soil erodibility fraction (EF-Factor) had the highest values and possessed a strong relationship between slope and SOM of 0.01% in determining soil erodibility. The PLSR model performed better than SVM for estimating SOM, CaCO3, and EF-Factor. Furthermore, the results showed that the spectral responses of CaCO3 were observed in separate places in the wavelengths of 570, 649, 802, 1161, 1421, 1854, and 2362 nm, and the wavelengths with SOM parameter were 496, 658, 779, 1089, 1417, 1871, and 2423 nm. The EF-factor shows the highest significant correlation with spectral reflectance values at 526, 688, 744, 1418, 1442, 2292, and 2374 nm. The accuracy and performance of the PLSR model in estimating the EF-Factor using spectral reflectance data and the distribution of data points for both the calibration and validation data-sets indicate a good accuracy of the PLSR model, with RMSE values of 0.0921 and 0.0836 Mg h MJ−1 mm−1, coefficient of determination (R2) values of 0.931 and 0.76, and RPD values of 2.168 and 2.147, respectively. [ABSTRACT FROM AUTHOR]