We developed an automated miniature constant-head tension infiltrometer that measures very small infiltration rates at millimetre resolution with minimal demands on the operator. The infiltrometer is made of 2.9 mm internal radius glass tube, with an integrated bubbling tower to maintain constant negative head and a porous mesh tip to avoid air-entry. In the bubbling tower, bubble formation and release changes the electrical resistance between two electrodes at the air-inlet. Tests were conducted on repacked sieved sands, sandy loam soil and clay loam soil, packed to a soil bulk density ρd of 1200 kg m-3 or 1400 kg m-3 and tested either air-dried or at a water potential ψ of -50 kPa. The change in water volume in the infiltrometer had a linear relationship with the number of bubbles, allowing bubble rate to be converted to infiltration rate. Sorptivity measured with the infiltrometer was similar between replicates and showed expected differences from soil texture and ρd, varying from 0.15 ± 0.01 (s.e.) mm s-1/2 for 1400 kg m-3 clay loam at ψ = -50 kPa to 0.65 ± 0.06 mm s-1/2 for 1200 kg m-3 air dry sandy loam soil. An array of infiltrometers is currently being developed so many measurements can be taken simultaneously.
The extent (determined by the repellency indices RI and RIc) and persistence (determined by the water drop penetration time, WDPT) of soil water repellency (SWR) induced by pines were assessed in vastly different geographic regions. The actual SWR characteristics were estimated in situ in clay loam soil at Ciavolo, Italy (CiF), sandy soil at Culbin, United Kingdom (CuF), silty clay soil at Javea, Spain (JaF), and sandy soil at Sekule, Slovakia (SeF). For Culbin soil, the potential SWR characteristics were also determined after oven-drying at 60°C (CuD). For two of the three pine species considered, strong (Pinus pinaster at CiF) and severe (Pinus sylvestris at CuD and SeF) SWR conditions were observed. Pinus halepensis trees induced slight SWR at JaF site. RI and RIc increased in the order: JaF < CuF < CiF < CuD < SeF, reflecting nearly the same order of WDPT increase. A lognormal distribution fitted well to histograms of RIc data from CuF and JaF, whereas CiF, CuD and SeF had multimodal distributions. RI correlated closely with WDPT, which was used to develop a classification of RI that showed a robust statistical agreement with WDPT classification according to three different versions of Kappa coefficient.
Subtropical regions have clay-rich, weathered soils, and long dry periods followed by intense rainfall that produces large fluctuations in soil water content (SWC) and hydrological behavior. This complicates predictions of spatiotemporal dynamics, as datasets are typically collected at too coarse resolution and observations often represent a duration that is too short to capture temporal stability. The aim of the present study was to gain further insights into the role of temporal sampling scale on the observed temporal stability features of SWC order to aid the design of optimal SWC sampling strategies. This focused on both sampling frequency and total monitoring duration, as previous analyses have not considered both of these sampling aspects simultaneously. We collected relatively high resolution data of SWC (fortnightly over 3.5 years) for various soil depths and under contrasting crops (peanuts and citrus) at the red soil region of southeast China. The dataset was split into a three-year training period and a six-month evaluation period. Altogether 13 sampling frequencies (intervals ranging from 15 to 240 days) and eight monitoring duration periods (between three and 36 months) were derived from the training period to identify temporal stability features and the most time stable location (MTSL). The prediction accuracies of these MTSLs were tested using the independent evaluation data. Results showed that vegetation type did affect the spatio-temporal patterns of SWC, whereby the citrus site exhibited a stronger temporal variation and weaker temporal stability than the peanut site. However, the effects of both sampling frequency and observation duration were more pronounced, irrespective of the role of vegetation type or soil depth. With increasing sampling interval or decreasing monitoring duration, temporal stability of SWC was generally overestimated; by less than 10% when sampling interval increased from every 15 to 240 days and by up to 40% with duration decreasing from 36 to 3 months. Our results suggest that sampling strategies and trade-offs between sampling interval and duration should focus on capturing the main variability in hydro-climatological conditions. For subtropical conditions, we found that sampling once every 45 days over 24 months to be the minimum sampling strategy to ensure errors in SWC temporal stability of less than 10%.