Prediction of Soil Infiltration Rate From Soil Color Parameters in a Brown Forest Soil of Transitional Climate Zone
Öz
Aim of the study: Forest vegetation exerts a significant influence on the physical and chemical characteristics of brown forest soils in transitional climate zones. Among soil physical properties, the infiltration rate (IR) is a key indicator of soil-water interactions, hydrological functioning, and ecosystem stability. However, direct measurement of IR across large spatial extents is labor-intensive and time-consuming, necessitating the development of reliable prediction approaches. This study aimed to quantify the relationship between soil infiltration rate and soil color parameters (L*: lightness, a*: redness, b*: yellowness) to evaluate whether color information can serve as a practical proxy for estimating IR Area of study: The research was conducted on brown forest soils located within the transitional climate zone of Tosya District, Kastamonu Province, Türkiye. Material and method: Field infiltration tests were carried out at 30 sampling points, and soil samples were collected from 90 GPS-referenced locations at a depth of 0-30 cm. The study area is predominantly covered by black pine (Pinus nigra) and oak (Quercus spp.) stands. Soil samples were analyzed for organic matter, particle-size distribution (sand, silt, and clay), electrical conductivity, pH, and CaCO₃ content. Infiltration rate and bulk density were measured on undisturbed soil cores, while soil color was determined using a chromameter in the CIE Lab* color system Main results: Multiple linear regression (MLR) analysis revealed that the a* and b* color parameters were strong predictors of soil infiltration rate, together explaining 92% of its total variation. The results indicate that numerical color parameters can be effectively utilized to estimate IR, with a* and b* values providing greater predictive reliability than L*. The Durbin-Watson test confirmed the absence of significant multicollinearity among variables Research highlights: The developed MLR model demonstrated a strong relationship between soil color parameters and infiltration rate, explaining 92% of the observed variability. These results suggest that soil color measurements may provide useful information for estimating infiltration characteristics and for identifying areas with contrasting infiltration behavior in forest soils.
Anahtar Kelimeler
Infiltration rate, Forest soil hydrology, Soil color parameters, Infiltration modeling
Kaynakça
- Aitkenhead, M. J, Coull, M., Towers, W., Hudson, G. & Black, H. I. J. (2013). Prediction of soil characteristics and colour using data from the National Soils Inventory of Scotland. Geoderma, 200: 99-107.
- Akbaş, F. (2014). Spatial variability of soil color parameters and soil properties in an alluvial soil. African Journal of Agricultural Research, 9(12), 1025-1035.
- Angelopoulou, T. (2022). Soil Reflectance Spectroscopy for Supporting Sustainable Development Goals. In Information and Communication Technologies for Agriculture Theme I: Sensors (pp. 17-42). Cham: Springer International Publishing.
- Barret, L. R. (2002). Spectrophotometric color measurement in situ in well drained sandy soils. Geoderma, 108:49-77.
- Ben-Dor, E., Ong, C. & Lau, I. C. (2015) Reflectance measurements of soils in the laboratory: Standards and protocols. Geoderma, 245:112-124
- Budak, M. & Gunal, H. (2016). Visible and near infrared spectroscopy techniques for determination of some physical and chemical properties in Kazova watershed. Advances in Environmental Biology, 10(5):61-73.
- Budak, M., Günal, H., Süer, M. & Akbaş, F. (2018). Sayısal renk parametreleri ile bazı fiziksel ve kimyasal toprak özelliklerinin tahmini. Harran Tarım ve Gıda Bilimleri Dergisi, 22(3), 376-389.
- CIE (Commission Internationale de l’Eclairage). (1986) Colorimetry-Technical Report, (CIE Pub. No. 15); Bureau Central de la CIE: Vienna, Austria.
- Cumming, G. (2009). Inference by eye: Reading the overlap of independent confidence intervals. Statistics in Medicine, 28(2), 205-220.
- Delgado, J., Nieto, J. M. & Boski, T. (2010). Analysis of the spatial variation of heavy metals in the Guadiana Estuary sediments (SW Iberian Peninsula) based on GIS-mapping techniques. Estuarine, Coastal and Shelf Science, 88(1), 71-83.