Unveiling soil temperature reached during a wildfire event using ex-post chemical and hydraulic soil analysis.

Wildfires affect different physical, chemical, and hydraulic soil properties, and the magnitude of their effects varies depending on intrinsic soil properties and wildfire characteristics. As a result of climate change, the frequency and intensity of wildfires have increased, and understanding their impact and predicting the temperature to which soils were exposed in previous events is becoming increasingly critical. Hence, the objectives of this study were to develop a soil-heating laboratory procedure to (a) identify changes in soil properties at different temperatures and (b) to infer the temperature ranges to which heated soils have been exposed. Saturated (Ks) and unsaturated (Ku) hydraulic conductivity, pH, electrical conductivity (EC), wet aggregate stability (WAS), soil water repellency index (RIm), and soil organic matter content (SOM) were measured in six laboratory heated (LH) soils at 300, 500, 700, and 900 °C for 2 h. Bulk density (BD) and soil texture were measured in unheated (UH) and wildfire-unheated (WH) samples. UH samples were used as baselines to quantify changes in soil properties, and WH and LH samples were compared to determine the temperatures to which WH soils were exposed. The results show that in the studied temperature range, WAS exhibited a U-shaped trend, opposite to that of pH and EC. Ks and Ku (negative tension of -3 cm) tend to increase with temperature, reaching a maximum of 1.27·10-4 and 5.62·10-5 (m/s) at 900 °C, respectively. RIm was highly dependent on texture; loam soils had an average minimum and maximum of 1.84 and 2.73, at 900 and 300 °C, respectively, while sandy loam soils had an average minimum and maximum of 1.29 and 2.08 at 300 and 900 °C, respectively. Finally, the parameters that provided laboratory variation and a temperature range consistent with the results observed in naturally heated soils were WAS, RIm, pH, and EC.

A comprehensive evaluation of pedotransfer functions for predicting soil water content in environmental modeling and ecosystem management.

Many pedotransfer functions (PTFs) have been developed for predicting the soil water content at different matric potentials. The use of these functions has been encouraged because of the time and work typically required for measuring it, while the PTFs require commonly measured soil properties such as sand, silt, clay, organic matter content, or bulk density for predicting water retention. In addition, several environmental and ecosystem management simulation models such as DRAINMOD, HYDRUS, EPIC, SPAW, and WEPP use PTFs for computing soil hydraulic properties. Because of the increasing use of the PTFs and their effect in many soil water simulation and transport models, this study revised and tested 13 different PTFs for predicting soil water content at -33 and -1500 kPa, values usually known as field capacity and wilting point. Three of these PTFs were derived from tropical soils while the rest were developed with soil samples collected across the United States. These PTFs were evaluated in Chilean soils as an independent dataset and their improvement after calibration was assessed with this new data. The results demonstrate that the PTFs performance depends on the soils used for their development as the estimates showed a significant improvement after calibration. When predicting water content, Rawls et al. (2004) was the best function before calibration (RMSE = 0.08 for -33 and -1500 kPa), while Gupta and Larson (1979) was the best after calibration (RMSE of 0.06 and 0.05, and r2 values of 0.69 and 0.66 at -33 and -1500 kPa, respectively). Nonlinear PTFs performed better than linear PTFs when predicting water content at field capacity. Finally, bulk density proved to be the key variable and can be used as footprint for soils changes through time. Organic matter content was also a significant input but improved the estimates for some specific matric potentials and PTFs.