JpGU-AGU Joint Meeting 2020

講演情報

[E] 口頭発表

セッション記号 A (大気水圏科学) » A-GE 地質環境・土壌環境

[A-GE43] 水文土壌学の普及-ヘンリー・リン教授を記念して

コンビーナ:登尾 浩助(Meiji University)、森 也寸志(岡山大学大学院環境生命科学研究科)

[AGE43-01] Performance of moisture release curves created using in situ measurements for estimating infiltration and runoff

★Invited Papers

*Colin Campbell1Alton Campbell2Neil Hansen2 (1.METER Group, Inc.、2.Dept. of Plant and Wildlife Sciences, Brigham Young University)

キーワード:Moisture release curves, water content, water potential, infiltration, sensors

The moisture release curve (MRC) has been described as the most critical information about an unsaturated soil and can be thought of as a soil’s fingerprint. It provides key information like water availability, infiltration, unsaturated hydraulic conductivity, and soil type. Despite the desirability of knowing the MRC, often it is simply estimated from soil type parameters. In the past, actually making an MRC was limited by long and sometimes complicated laboratory processes. While recent developments like the Wind Schindler method have improved this, it is still impractical to evaluate every soil of interest in the lab. The objective of this study was to investigate the quality of in situ MRCs created in-part using a newly-released, accurate soil matric potential sensor. Soil water content and matric potential sensors were collocated at multiple depths in three actively managed landscapes with different soils: loamy sand, sandy loam, and clay loam. An entire season of data was collected to include multiple drying and wetting events. Results were compared to MRCs created in the lab using a Wind Schindler method combined with a chilled mirror instrument. Curves showed good agreement between the two approaches. In situ-generated curves also provided good estimates of soil type as well. Roots in the loamy sand samples clearly shift moisture release curves and appear to be responsible for the largest disparity between lab (with roots dead or removed) and field data. In situ MRCs cannot substitute for the quality of curves generated in the lab, but they will produce good approximations that will help fill the MRC knowledge gap and be much improved from those estimated from soil type. Using this approach, it may be possible to partition infiltration and runoff in marginal areas like the contaminated forested areas around Iitate Village.