Search

• Performance of 11 existing soil particle density estimating models were evaluated. • The modified Adams and some regression models gave reasonable estimates. • Particle density of subtropical soils was more affected by texture rather than SOM. • Particle density of subtropical soils was simply a linear function of clay content. Soil particle density (ρ s) is a basic soil physical property which is essential for soil pore volume estimation and sediment source discrimination. The measurement of soil ρ s is labor intensive and time-consuming. Pedotransfer functions (PTFs) have been developed for estimating ρ s from readily available soil properties during the past decades. Existing PTFs are developed mainly based on soil datasets covering wide ranges of soil organic matter (SOM) contents. For soils from subtropical regions with low SOM values the accuracy of previous PTFs remains unknown. In this study we evaluated the performance of existing ρ s PTFs by comparing model estimates to measurements of 175 soils from a subtropical region in China. The investigated soils had relatively low SOM contents (mostly<0.02 g g−1) and covered texture ranges from coarse sand to clayey soils. The Adams-based PTFs performed poorly, while the modified Adams PTFs and several simple linear or multiple regression PTFs produced relatively accurate ρ s estimates for the 175 soils with root mean square errors (RMSEs) around 0.05 g cm−3 and mean biases within ± 0.03 g cm−3. Further multiple regressions indicated that the ρ s of subtropical soils was simply a negative linear function of clay content. Despite conflicting several early reports, an independent dataset showed that the proposed linear model provided accurate ρ s estimates for soils with low SOM contents from subtropical regions with a RMSE of 0.030 g cm−3 and mean bias of −0.013 g cm−3. [ABSTRACT FROM AUTHOR]

Summary: Ponding tests were conducted in the Shiyang River Basin in Northwest China to assess canal leakage characteristics. Four anti-seepage constructions (concrete lining, pebble lining, clay lining plus compacted canal bed, compacted canal bed only) were performed on four canal sections, which were situated in multi-layered soils. The canal sections were tested using a two-stage approach: First, a stable water level was maintained; second, a stage where the water level in the canal section was permitted to drop. The canal seepage rate and the soil water content near the canal bed were monitored during each stage and in each canal section. Soil texture, bulk density and hydraulic conductivity were determined in each canal section and soil layer. Double ring infiltration tests were performed to investigate infiltration behaviour from the canal sections. The saturated–unsaturated flow model HYDRUS-2D was applied to simulate canal seepage and the local soil water response. The simulation results compared well with the monitored data, indicating that the model can reliably simulate canal seepage under these complex soil structures and different canal liners. Both experimental results and numerical modelling show that the clay lining plus compacted canal bed provides the best anti-seepage performance, followed by compacted canal bed only, then pebble and concrete lining. Simulation results also predicted that the soil water content was discontinuous at the interface of distinct soil layers, and that the range and form of wetting front varied greatly in the four canal sections, with a larger wetted area for the more permeable canal. Simulations were performed to study the sensitivity of canal seepage to the permeability of each soil layer and canal liner. The results, confirmed by the double-ring infiltration tests, indicated that the canal lining is not the only factor affecting canal seepage: The soil permeability can also influence the seepage, especially where there is a low permeability layer (e.g., compacted soil layer) close to the canal. [Copyright &y& Elsevier]