Development of groundwater flow pass detection method for landslides by resistivity monitoring with high time resolution

2019 Fiscal Year Final Research Report

• Project/Area Number: 17K01349
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Research Field: Natural disaster / Disaster prevention science
• Research Institution: National Agriculture and Food Research Organization
• Principal Investigator: Nakazato Hiroomi 国立研究開発法人農業・食品産業技術総合研究機構, 農村工学研究部門, 主席研究員 (00373225)
• Co-Investigator(Kenkyū-buntansha): 井上 敬資 国立研究開発法人農業・食品産業技術総合研究機構, 農村工学研究部門, 主任研究員 (60414455)
• Project Period (FY): 2017-04-01 – 2020-03-31
• Keywords: 地盤災害 / 地すべり / 物理探査 / 地下水流動 / 時系列探査

Outline of Final Research Achievements

In the resistivity monitoring method that detects the flow-down condition of the salt water tracer as a change in ground resistivity, the problem is that the time resolution is low because it takes 1 to several hours to measure one sequence. In order to establish the method of detecting the groundwater flow pass that influences the stability of landslide, we have attempted to improve the time resolution of exploration using a high-speed electrical survey system. For the analysis area of 120 m in length × 30 m in width × 40 m in depth, time series exploration was performed by acquiring 900 data at 10-minute intervals from 190 minutes before tracer injection to 180 minutes after injection　at Shimekake Landslide in Yamagata Prefecture. Then, from the results of the inversion analysis, we detected the part where the resistivity decreased due to the tracer injection. This result is the basis for establishing a method for detecting groundwater flow pass with high permeability.

Free Research Field

土木地質学

Academic Significance and Societal Importance of the Research Achievements

同時多点送信・多点受信による高速電気探査システムの現地適用性を検討し，1送信・多点受信の従来装置に対し，比抵抗モニタリングの時間分解能を向上させたが，時系列解析結果においてノイズデータによる偽像の発生が認められ，受信精度の向上が課題として残された．本研究により流動性の高い水みちの可視化手法が示され，大規模地すべりや深層崩壊等の斜面災害対策現場における成果の活用が期待される．