Journal
AGRICULTURAL AND FOREST METEOROLOGY
Volume 290, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.agrformet.2020.107999
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Funding
- U.S.A. National Science Foundation Hydrologic Sciences Program [EAR-1416881]
- National Natural Science Foundation of China [51879172]
- National Science Foundation [EAR -0725019, EAR -1239285, EAR -1331726]
- NSF-supported Susquehanna Shale Hills Critical Zone Observatory
- Penn State College of Agriculture Sciences, Department of Ecosystem Science and Management
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Soil climate (soil moisture and temperature) affects many near-surface earth system processes and ecosystem functions. However, the challenge of acquiring reliable, high-resolution data has impeded the quantitative assessment of the spatial heterogeneity of soil climate at hillslope and catchment scales, namely, soil microclimate. Here, we examined three years of continuous soil micro-climate data to identify patterns in relation to slope aspect, position, and curvature in a 7.9-ha forested catchment in Pennsylvania, U.S.A. Mull-depth (5 to 162 cm) soil micro-climate data were collected by a sensor network consisting of 33 sites that were distributed throughout the catchment. Results showed a high degree of variability in time and space that alternated between wet-cold seasons (DJFMAM) and drywarm seasons (JJASON). Compared to dry-warm seasons, soil moisture was spatially more variable but temporally more stable in wet-cold seasons. Slope characteristics substantially mediated soil micro-climate distribution and variability, which were further influenced by the season and soil depth. With increasing soil depth, soil micro-climate became spatially more variable but more stable through time. The north (N)-facing aspect intensified the temporal variability of soil microclimate more than the south (S)-facing aspect. Swales and the valley floor dampened soil temperature fluctuations relative to planar slopes and the ridges. The N-facing slopes were significantly colder than the S-facing slopes but only in winter. The differences in slope insolation, vegetation cover, soil properties, and hydrology were used to explain soil micro-climate patterns. This study demonstrates the potential of sensor networks to investigate soil micro-climate at scales that are challenging for either point-scale measurements or remote sensing. These findings provide an enhanced understanding of localized soil micro-climate pattern and variability in forested headwater catchments, which can aide modeling water and energy budgets of the Critical Zone in temperate, humid region.
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