Local Surrogate Relationships Between Soil Texture Fractions and Near-Surface Hydro-Structural Properties for Hydrological Parameterization in High-Andean Catchments

For hydrological parameterization in high-Andean catchments, it is necessary to understand whether near-surface hydro-structural soil properties can provide a surrogate signal of particle-size composition when direct texture information is sparse. This study evaluated the extent to which sand, silt, and clay fractions can be approximated from organic matter (OM), bulk density (ρb), and saturated hydraulic conductivity (Ksat) in the Zamora Huayco (ZH) and Irquis catchments, southern Ecuador. A harmonized dataset (n=44) was analyzed through exploratory statistics, compositional assessment, correlation analysis, PCA, fraction-wise regression, ILR-based modeling, AIC/BIC term reduction, sensitivity analysis excluding OM, nested LOOCV, and bootstrap-based uncertainty intervals. Among LULC classes, samples classified as paramo occupied a distinct high-Andean hydro-edaphic domain, characterized by a differentiated relationship between soil physical properties and hydrological behavior. PCA showed that the dominant covariance structure involved OM, ρb, Ksat, and the redistribution between sand and silt. The BIC-reduced ILR model provided the most balanced formulation, with positive nested LOOCV performance for sand, silt, and clay (RLOOCV2=0.147, 0.704, and 0.124, respectively) and exact 100% compositional closure after inverse transformation. Silt was the most stable predicted fraction, whereas sand and clay retained larger residual uncertainty, stronger tail departures, and partial compression of the observed variability. The proposed equations provide local hydro-pedotransfer support, although their predictive signal remains dependent on further refinement, uncertainty assessment, and external validation before regional application.