研究目的
To evaluate the applicability of fiber-optic distributed temperature sensing (DTS) in remote field environments, to describe the spatial and temporal variability of soil temperature (Ts) in complex terrain characterized by contrasting landscape units (LUs), and to investigate the implications for modeling Ts and related processes.
研究成果
DTS provided accurate and high-resolution measurements of soil temperature variability in complex terrain. Ts variability is largely deterministic and controlled by landscape units defined by topography and vegetation, with within-unit variability low (SD < 1.5°C) and between-unit differences significant (up to 5.2°C mean annual difference). This suggests that discretizing landscapes into small-scale LUs is essential for effective Ts simulation, outperforming elevation-based or air temperature-based approaches.
研究不足
The study was limited by the remote and rugged terrain, making cable installation time-consuming and susceptible to damage (e.g., by cattle). Measurement precision could be affected by calibration drift and instrument temperature dependencies. The spatial resolution of 1 m may not capture all small-scale variations, and the study duration (one year) may not capture long-term variability.
1：Experimental Design and Method Selection:
The study used fiber-optic distributed temperature sensing (DTS) to measure soil temperature at high spatial and temporal resolution. A 771 m fiber-optic cable was installed at 10 cm depth in different landscape units (LUs) defined by vegetative cover. The DTS system measured temperature at 1 m intervals along the cable.
2：Sample Selection and Data Sources:
The research was conducted in the Upper Sheep Creek watershed in Idaho, with LUs including low sagebrush, mountain big sagebrush, and aspen areas. Complementary data included soil water content, snow depth, and meteorological measurements from existing profiles and stations.
3：List of Experimental Equipment and Materials:
Sensornet Oryx DTS instrument, AFL Telecommunications DNS-1566 dual 50-mm multimode fiber-optic cable, FLUKE temperature meter (Model 1502a) with platinum resistance thermometer (Model 5613), PT100 temperature sensors, ultrasonic depth gauge, weighing precipitation gauges, and calibration equipment like ice baths.
4：Experimental Procedures and Operational Workflow:
The cable was installed in a duplexed, single-ended configuration with calibration coils. Temperature measurements were taken at regular intervals (e.g., 1 min readings hourly), with periodic calibrations using ice baths. Data were collected from November 2009 to July 2010, with post-processing for cable length effects.
5：Data Analysis Methods:
Data were analyzed for accuracy, calibration drift, and spatial variability using statistical methods such as mean, standard deviation, and linear regression. Temperature data were compared across LUs and time periods.
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