"Soil Moisture Constants Induced Pedo-Transfer Function and Geographic Information System of Some Areas, Sohag Governorate, Egypt" | ||
| Journal of Sohag Agriscience (JSAS) | ||
| Volume 10, Issue 1, June 2025, Pages 28-38 PDF (1.81 M) | ||
| Document Type: Research and Review Papers | ||
| DOI: 10.21608/jsasj.2025.416648 | ||
| Authors | ||
| Asmaa Omar El-Sheikh* 1; Aly Abdel-Mawgoud2; Abdel-rahman A. Mustafa3 | ||
| 1Soil and Water department, faculty of Agriculture, Sohag university, Sohag, Egypt | ||
| 2Soils and Water Department Faculty of Agriculture Al-Azaher University Assuit Egypt | ||
| 3Soils and Water Department Faculty of Agriculture Sohag University Sohag Egypt | ||
| Abstract | ||
| Hydrological models are time-consuming to acquire, as they required huge soil data that might be unavailable under some conditions. So, pedo-transfer functions (PTFs) can be performed to assess some hydro-physical soil properties. Soil moisture constants, such as field capacity and permanent wilting point, are critical physical properties that determine the soil's water storage capacity and serve as essential input variables for agro-hydrological models. However, direct measurements of FC and PWP are often time-intensive, laborious, and costly. The current study aims to integrate GIS and pedo-transfer models to estimate field capacity and permanent wilting point values for some soils of Sohag Governorate. Total of 103 representative undisturbed soil samples (0-20 cm) were collected and examined for sand, silt and clay fractions as well as for soil organic matter (SOM) content. Initiated multiple linear and non-linear regression for FC and PWP by PTFs are based on soil particles distribution and SOM. The results showed that FC and PWP realized significant (P<0.001) negative correlations with sand, while there were positive correlations with silt, clay and SOM (P< 0.001). In general, PTFs performance was evaluated based on determination coefficient, root mean square error, and residual predication deviation and performance ratio to inter-quartile distance between the observed and predicted values. It might be concluded that these new PTFs technique can be applied with caution in other regions facing data scarcity but with similar ecosystem. Therefore, PTFs are essential tools to translate data that we have to data we need in agro-physical aspect and management applications. | ||
| Keywords | ||
| Geographic information system; Pedo-transfer functions; Field capacity; Wilting point; Residual predication deviation | ||
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