Affiliation:
1. School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China
2. Department of Water Resources Engineering, Center for Middle Eastern Studies, Lund University, SE-221 00 Lund, Sweden
Abstract
Soil physicochemical properties and macropore spatial structure affect saturated hydraulic conductivity (Ks). However, due to regional differences and long measurement time, Ks is tedious to quantify. Therefore, it is of great importance to find simplified but robust methods to predict Ks. One possibility is to use pedo-transfer functions (PTFs). Along this line, stratified sampling was carried out in six typical forestlands in the rocky mountain area of Northern China. Penetration experiments and industrial CT scanning were combined to explore the distribution characteristics of regional Ks and its influencing factors. Based on this, we compared three Ks PTF models by multiple linear regression for Ks prediction. The results indicated that: (1) Ks decreased with increasing soil depth, which followed the order coniferous forest < broad-leaved forest < mixed forest, and the change range of mixed forest was greater than that of homogeneous forest. (2) Soil bulk density, water content, sand, silt, organic matter, total nitrogen, total phosphorus, and total potassium were significantly correlated with Ks (p < 0.05). In addition, stand type and soil depth had a certain impact on soil physicochemical properties that affected Ks. (3) Soil macropore structure, such as number density, length density, surface area density, and volume density, all decreased with increasing soil depth. They were all significantly positively correlated with Ks (p < 0.001). (4) The best predictability and universality for PTFs was achieved for PTFs containing bulk density, organic matter content, and total phosphorus. Only PTFs containing parameters of macropore spatial structure did not yield high predictability of Ks. The findings of this study contribute to the understanding of forest hydrological infiltration processes in rocky mountain forests in Northern China, and provide theoretical support for the prediction and management of water loss and soil erosion and the enhancement of water conservation functions.
Funder
the National Natural Science Foundation of China
the National Key Research and Development Program of China
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