論説頁
1
1931 年岩手県小国地震の被害に関する文献調査 ………………………………………… 水田敏彦・鏡味洋史
71901 年青森県東方沖地震の岩手・秋田の被害 …………………………………………… 鏡味洋史・水田敏彦
青森県階上町道仏震度観測点の特異性確認のための町内各地の地盤震動特性調査 ……………… 片岡俊一 13
東北地方中南部における臨時地震観測… 岡田知己・中山貴史・平原 聡・立岩和也・堀内茂木・勝俣 啓・大園真子・小菅正裕・前田拓人・
山中佳子・片尾 浩・松島 健・八木原寛・2011 年東北地方太平洋沖地震緊急観測グループ 19
中小地震の破壊伝播指向性と応力降下量－東北沖地震後に活発化した福島－茨城県境の地震活動の解析－………………………………………………………………………………… 池田里奈・吉田圭佑・松澤 暢 25
常時微動の地震波干渉法解析に基づく Rayleigh 波位相速度を用いた福島県における3 次元 S 波速度構造の逆解析 ……………………………… 土屋 隆・三浦賢太郎・山本英和・齊藤 剛 31
土粒子の間隙を流れる水の挙動に関する基礎的研究 ……… 柾谷みなみ・上野礼慈・中村優真・高瀬慎介 37
透明土粒子モデルを用いた浸透流の可視化手法に関する基礎的研究…………………………………………………………………… 中村優真・上野礼慈・高瀬慎介・金子賢治 43
地盤の液状化を加速度応答のみから推定するための特徴量の分析………………………………………………………………… 吉留大生・鳥屋部佳苗・加村晃良・風間基樹 47…………………………………………………………………………………松冨英夫 51
氾濫水密度の時間変化を考慮した津波遡上 ……………………………………………………………
氾濫流抵抗則の津波遡上への適用法 …………………………………………………………………… 松冨英夫 57
加速度センサを用いた漂流物の挙動に関する実験 ………………………… 望月良純・齋藤憲寿・渡辺一也 63
1804 年象潟地震による津波堆積物の層相 …………………… 長尾優樹・岡田里奈・梅田浩司・鎌滝孝信 69
数値シミュレーションを用いた雄物川河口域における塩水遡上の研究…………………………………………………………………… 神田智洋・谷口隼也・齋藤憲寿・渡辺一也 75
雄物川における出水後の河口砂州回復と波浪エネルギーの影響評価 … 谷口隼也・齋藤憲寿・渡辺一也 81
平面・鉛直方向における河床材料の粒度分布に関する検討 … 自見寿孝・谷口隼也・齋藤憲寿・渡辺一也 87
島根県江の川下流域における令和 3 年 8 月の氾濫について … 田上直弥・古田大智・岡本佳奈・鎌滝孝信 93
Estimation of Floodwater Depth in Quang Tri Province using Sentinel-1 Data………………………………
………………………Vuong
Tai CHI・Dinh Nhat QUANG・Nguyen Xuan TINH・Hitoshi TANAKA 99
Shoreline Change and Impacts of Coastal Protection Structures on Da Rang River Mouth
and Adjacent Coast, South Central of Vietnam……………………
………………Nguyen
Trong HIEP・Hitoshi TANAKA・Nguyen Xuan TINH・Nguyen Trung VIET 105
Assessment of River Mouth Variability After Jetty and Groyne Construction: A Case Study of The
Volta River Mouth, Ghana… Stephan Korblah LAWSON・Hitoshi TANAKA・Keiko UDO・Nguyen Trong HIEP・Nguyen Xuan TINH 111
数値シミュレーション結果を用いた災害リスク評価 ………………………………
…………………… 上野礼慈・中村優真・高瀬慎介 117
国内自然災害被害の確率分布に関する一考察 ……………………………………………………………………………
………………………………………………………… 奥村 誠 123
地形からみた山間部集落における豪雨時の適切な避難場所について ……………………………… 水本匡起 127
感染症拡大下での安否確認に特化した避難訓練の取り組み ………………………………………… 杉安和也 133……………………………………… 柴山明寛・Julia GERSTER 137
自然災害デジタルアーカイブの語彙に関する研究 ……………………………

ARTICLES

Page

Literature Survey on Damage due to the 1931 Oguni Earthquake of Iwate Prefecture1……………………………………………………………………………………… Toshihiko MIZUTA and Hiroshi KAGAMI
Damage in Akita and Iwate Prefectures due to the 1901 East off Aomori Earthquake
7……………………………………………………………………………………… Hiroshi KAGAMI and Toshihiko MIZUTA
On-site Study Around Hashikami-cho in Aomori Prefecture to Clarify the Singularity of Hashikami Station……………………………………………………………………………………………………………… Shunichi KATAOKA 13…………………………………………………………………………………………………………………
……… Tomomi OKADA, Takashi
Temporal Seismic Observation in the Central-southern Part of Tohoku District……………
NAKAYAMA, Satoshi HIRAHARA, Kazuya TATEIWA, Shigeki HORIUCHI, Kei KATSUMATA, Mako OHZONO,
Masahiro KOSUGA, Takuto MAEDA, Yoshiko YAMANAKA, Hiroshi KATAO, Takeshi MATSUSHIMA, Hiroshi
19
YAKIWARA, and Group for the aftershock observation of the 2011 off the Pacific coast of Tohoku earthquake
Simultaneous Estimation of Stress Drop and Rupture Directivity of Small Earthquakes Near the Fukushima-Ibaraki Border………………………………………………………………………
…………………………………………………………………………Rina
IKEDA, Keisuke YOSHIDA, Toru MATSUZAWA 25
An Inversion of a Three-dimensional S-wave Velocity Structure in Fukushima Prefecture using Phase Velocities ofRayleigh Wave Based on Seismic Interferometry Analysis of Microtremor………………………………………………………………… T. TSUCHIYA, K. MIURA, H.YAMAMOTO and T. SAITO 31……………………………………………………………………
Study on the Behavior of Water Flowing through the Gaps of Particle Swarms……………………………………………… Minami MASAYA, Reiji UWANO, Yuma NAKAMURA, Shinsuke TAKASE 37………
A Basic Study on Visualization Method of Seepage Flow Using Transparent Soil Model……………Yuma
NAKAMURA 43
Analysis of Feature Amount for Estimating Liquefaction Degree Based only on Seismic Data …
…… Taisei YOSHITOME 47
Tsunami Run-up Considering Time Variation of Density of Inundation Water……………………
………………… Hideo MATSUTOMI 51
Method for Applying Frictional Resistance Law of Inundation Flow Over a Movable Bed to Tsunami Run-up………………………………………………………………………………………………………………… Hideo MATSUTOMI 57
Experimental of the Behavior of Drifting Objects using an Acceleration Sensor…………………………………………………… Yoshizumi MOCHIZUKI, Noritoshi SAITO and Kazuya WATANABE 63………………………………………………………
Sedimentary Structure of Tsunami Deposits from the 1804 Kisakata Earthquake………………………………………………… Yuki NAGAO, Rina OKADA, Koji UMEDA and Takanobu KAMATAKI 69……………………………………………………
Study on Saline Water Run-up at Omono River Mouth using Numerical Simulation…………………………………… Tomohiro KANDA, Junya TANIGUCHI, Noritoshi SAITO and Kazuya WATANABE 75
Evaluation of Wave Energy Influence for Recovery of River Mouth Sandbar at Omono River………………………………………………………… Junya TANIGUCHI, Noritoshi SAITO and Kazuya WATANABE 81……………………………………………………………
Study on Grain Size Distribution of Riverbed Materials in the Horizontal and Vertical Direction…………………………………… Yoshitaka JIKEN, Junya TANIGUCHI, Noritoshi SAITO and Kazuya WATANABE 87
The Field Survey of Inundation in August 2021, from Gounokawa River, Shimane Prefecture……………………………………… Naoya TAGAMI, Daichi FURUTA, Kana OKAMOTO and Takanobu KAMATAKI 93
Estimation of Floodwater Depth in Quang Tri Province using Sentinel-1 Data…………………………………………… Vuong Tai CHI, Dinh Nhat QUANG, Nguyen Xuan TINH, Hitoshi TANAKA 99
Shoreline Change and Impacts of Coastal Protection Structures on Da Rang River Mouth and Adjacent Coast, South
Central of Vietnam…………………
……………… Nguyen Trong HIEP, Hitoshi TANAKA, Nguyen Xuan TINH, Nguyen Trung VIET 105
Assessment of River Mouth Variability after Jetty and Groyne Construction: a Case Study of the Volta River Mouth, Ghana…………… Stephan Korblah LAWSON, Hitoshi TANAKA, Keiko UDO, Nguyen Trong HIEP, Nguyen Xuan TINH 111………………………………………… Reiji UWANO 117
Disaster Risk Assessment using Numerical Simulation Results………………………………………………
Discussion on the Probabilistic Distribution of Japanese Disaster Damage Statistics…………… Makoto OKUMURA 123
Appropriate Evacuation Sites during Heavy Rainfall in Mountainous Areas based on Landform Analysis…… Tadaki MIZUMOTO 127
The Action of Evacuation Drills Specializing in Confirming Safety under the Spread of Infectious Diseases…… Kazuya SUGIYASU 133
The Vocabulary of Natural Disaster Digital Archives………………………… Akihiro SHIBAYAMA, Julia GERSTER 137

東北地域災害科学研究1

第58巻（2022） ᖺᒾᡭ┴ᑠᅜᆅ㟈ࡢ⿕ᐖ࡟㛵ࡍࡿᩥ⊩ㄪᰝ 㸨 ⛅⏣኱Ꮫ ᆅ᪉๰⏕ࢭࣥࢱ࣮ Ỉ⏣ ᩄᙪ໭ᾏ㐨኱Ꮫ ྡ㄃ᩍᤵ    㙾࿡ ὒྐ㸬ࡣࡌࡵ࡟ ➹⪅ࡽࡣᮾ໭ᆅ᪉ࡢ᫂἞௨㝆࡟Ⓨ⏕ࡋࡓ⿕ᐖᆅ㟈࡟ࡘ࠸࡚㸪ᙜ᫬ࡢᆅ᪉᪂⪺㸪㒓ᅵฟ∧≀㸪⾜ᨻ㈨ᩱ࡞࡝ࡢᩥ⊩ㄪᰝࢆ㐍ࡵ࡚࠸ࡿࠋᗈᇦ࡟⿕ᐖࢆࡶࡓࡽࡋࡓᆅ㟈ࡢ࡯࠿⿕⅏ᇦࡀ㝈ࡽࢀࡿᆅ㟈࡟ࡘ࠸࡚ࡶᩥ⊩ㄪᰝࢆ⾜࠸⿕ᐖࡢヲ⣽ࢆ㡰ḟ᫂ࡽ࠿࡟ࡋ࡚࠸ࡿ ౛࠼ࡤ㸯 㸪㸰 ࠋᒾᡭ┴ࡣἢᓊ㒊ࡢὠἼ⿕ᐖࡀ⏒኱࡛⧞ࡾ㏉ࡋⓎ⏕ࡋ࡚࠸ࡿࡀෆ㝣㒊࡛ࡶᆅ㟈ࡀⓎ⏕ࡋ࡚࠾ࡾ㸪᫂἞ᮇ௨㝆࡛ᒾᡭ┴ෆ㝣㒊࡟⿕ᐖࢆ⏕ࡌࡓᆅ㟈࡟ࡘ࠸࡚ᒾᡭ┴ᆅᇦ㜵⅏ィ⏬ 㸱㸧࠿ࡽ㑅ࡧ⾲㸯࡟♧ࡍࠋᑠㄽ࡛ࡣ㸪ࡇࢀࡽࡢ୰࠿ࡽ  ᖺᒾᡭ┴ᑠᅜᆅ㟈ࡢᩥ⊩ㄪᰝࢆ⾜࠸㸪⿕ᐖࡢ≧ἣࢆ᫂ࡽ࠿࡟ࡍࡿࠋ⿕⅏ᆅࡀ㝈ࡽࢀࡿᆅ㟈࡛࠶ࡿࡀ㸪ᙜヱᆅᇦࡢࡳ࡞ࡽࡎ┴ෆࡢᆅ㟈㜵⅏ࢆ⪃࠼ࡿୖ࡛ࡢᇶ♏㈨ᩱ࡜ࡋ࡚
㔜せ࡛࠶ࡿ࡜⪃࠼࡚࠸ࡿࠋ
㸬 ᖺᒾᡭ┴ᑠᅜᆅ㟈ࡢᴫせ ᮏᆅ㟈ࡢㅖඖࡣ᪥ᮏ⿕ᐖᆅ㟈⥲ぴ 㸲㸧 ࡟ࡼࢀࡤ㸪Ⓨ㟈᫬  ᖺ  ᭶  ᪥  ᫬  ศ㸪ᒾᡭ┴ᑠᅜ௜㏆㸪⤒ᗘ r͛(㸪⦋ᗘ r͛1㸪0 㸪K NP ࡛࠶ࡿࠋ⿕ᐖࡣࠗୗ㛢ఀ࣭ୖ㛢ఀ୧㒆ቃ⏺ࡢᒣ㛫࡛㐨㊰ࡢட⿣㸪▼ᇉࡢᔂቯ㸪ቨࡢட⿣࣭๤ⴠ࡞࡝ࡀ࠶ࡗࡓ࠘ࡇ࡜ࡀᥖ㍕ࡉࢀ࡚࠸ࡿࠋẼ㇟ᗇࡢ㟈ᗘࢹ࣮ࢱ࣮࣋ࢫ 㸳㸧 ࠿ࡽ㟈ᗘศᕸࢆ᳨⣴ࡋᅗ㸯࡟♧ࡍࠋ⾲㸯 ᒾᡭ┴ෆ㝣㒊ࡢ⿕ᐖᆅ㟈 㸱㸧㸦 ᖺ㹼 ᖺ㸧㹙 㸨 ༳ࡣࡇࢀࡲ࡛ᩥ⊩ㄪᰝࢆ⾜ࡗࡓᆅ㟈㹛ᖺ᭶᪥ᆅ㟈ྡ㡿ᇦ 0 㟈ᗘ㺃⿕ᐖ㸨  㝣⩚ᆅ㟈 ࿴㈡㒆࡛᭱ࡶ ⿕ᐖ ಽ ቯ ᐙ ᒇ ከ ᩘ࠶ࡾࠋ ᑠᅜᆅ㟈 ᑠᅜᮧ㝃㏆࡛ᆅ㟈 㟈ᗘ  ࠋᑠᅜᮧ㸪ୖ㛢ఀ㒆㔠ἑᮧᆅ᪉࡛▼ᇉᔂቯ㸪Ⅳࡀࡲ◚ቯ➼ࡢ⿕ᐖࠋ㸨 ⛅⏣┴༡㒊  ᮏ┴す㒊࡛㟈ᗘ 㹼㸪ᅜ㕲໭ୖ⥺
୍࡛᫬୙㏻ࠋᘓ≀ᦆቯ  Ჷ➼ࡢ⿕ᐖࠋ
୰㒊ἢᓊ 㟈ᗘ┒ᒸ㸪኱⯪Ώ 㸪ᐑྂ 㸪ὠἼ࡞ࡃ㸪ᘓ≀㸪ᅵᮌ᪋タ࡟⿕ᐖࠋෆ㝣໭㒊 㟈ᗘ㞸▼⏫㛗ᒣ  ᙅ㸪༓ⱉ⏣ 㸪㈇യ⪅  ྡ㹿ᅵᮌ᪋タ➼࡟኱ࡁ࡞⿕ᐖࠋ ᒾᡭᐑᇛ
 㟈ᗘዟᕞᕷ  ᙉࠋṚ⪅  ྡ㸪㔜㍍ෆ㝣ᆅ㟈യ⪅  ྡ㸪ᅵᮌ᪋タ㸪㎰ᯘᴗ㛵ಀ࡟኱ࡁ࡞⿕ᐖࠋ
 ἢᓊ໭㒊 㟈ᗘ㔝⏣ᮧ  ᙅࠋ㔜㍍യ⪅  ྡࠋᅵᮌ᪋タ㸪ᯘᴗ㛵ಀ࡟⿕ᐖࠋ ෆ㝣໭㒊 ┒ᒸᕷ࡛㟈ᗘ  ᙅࠋ㍍യ⪅  ྡࠋ᪂⪺グ஦࡟⿕
ᐖࡀᥖ㍕ࡉࢀ
࡚࠸ࡿ⏫ᮧྡ
ࢆేࡏ࡚♧ࡍࠋ

ᅗ㸯 ᒾᡭ┴ᑠᅜᆅ㟈ࡢ㟈ᗘศᕸẼ㇟ᗇ㟈ᗘ㺡㺼㺎㺞㺫㺼㺎㺛ࢆᇶ࡟సᡂ /LWHUDWXUH VXUYH\ RQGDPDJHGXHWR WKH 2JXQL HDUWKTXDNH RI ,ZDWHSUHIHFWXUH E\ 7RVKLKLNR0L]XWDDQG+LURVKL.DJDPL2㸬⿕ᐖࢆグ㍕ࡋࡓ㈨ᩱ
 ᖺᒾᡭ┴ᑠᅜᆅ㟈࡟㛵ࡍࡿㄪᰝሗ࿌㸪᪂⪺࡟⿕ᐖࡀグ㍕ࡉࢀ࡚࠸ࡿࡶࡢࢆ௨ୗ࡟♧ࡍࠋ⿕ᐖㄪᰝሗ࿌㸸୰ኸẼ㇟ྎࡀ  ᖺ  ᭶Ⓨ⾜ࡢẼ㇟せぴ࡟ࠕ ᪥  ᫬  ศ㡭ᒾᡭ┴ୗ㛢ఀ㒆ᑠᅜ௜㏆ࡢᆅ㟈ࠖ㸴㸧 ࡜㢟ࡋሗ࿌ࡋ࡚࠸ࡿࠋྛᆅࡢ㟈ᗘࡀ♧ࡉࢀ㸪┒ᒸೃᡤࡢሗ࿌࡟ᇶ࡙ࡃᒾ

ᡭ┴ࡢ⿕ᐖᴫせࡀグࡉࢀ࡚࠸ࡿࠋᑠᅜᮧࡢᅵⶶ࡜ᑠᅜᑠᏛᰯ▼ᇉࡢ⿕ᐖ෗┿  ᯛࡀᥖ㍕ࡉࢀ࡚࠸ࡿࠋࡲࡓ㸪 ᖺⓎ⾜ࡢᩪ⸨ሗᜠ఍◊✲ሗ࿌࡟ᮾ໭ᖇᅜ኱Ꮫ⌮Ꮫ㒊ࡢ⏣ᒣࡀࠕ᫛࿴  ᖺ ᭶  ᪥ࡢᑠᅜᆅ㟈ཬࡧࡑࡢ㟈ᇦᆅ᪉ࡢᆅᙧᆅ㉁␎ሗࠖ 㸵㸧 ࡜㢟ࡋሗ࿌ࡋ࡚࠸ࡿࠋᆅ㟈Ⓨ⏕࠿ࡽ ᪥ᚋࡢ  ᭶  ᪥ࡼࡾ  㐌㛫ㄪᰝࡀ⾜ࢃࢀ㸪ୗ㛢ఀ㒆ᑠᅜᮧ࡜ୖ㛢ఀ㒆㔠⃝ᮧࡢ⿕ᐖࡀグࡉࢀ㸪⿕ᐖศᕸᅗ࡜෗┿  ᯛ㸦⿕ᐖ≧ἣ  ᯛ㸪ᆅᙧ  ᯛ㸧ࡀᥖ㍕ࡉࢀ࡚࠸ࡿࠋ
᪂⪺㸸ᒾᡭ┴ࡢ௦⾲ⓗ࡞᪂⪺࡟ࠕᒾᡭ᪥ሗࠖࡀ࠶ࡾ㸪ᒾᡭ┴❧ᅗ᭩㤋࡛㜀ぴࢥࣆ࣮ࡋ㈨ᩱ࡜ࡋ
ࡓࠋグ஦ࡣᆅ㟈Ⓨ⏕⩣᪥࠿ࡽ⾲ࢀ㸪ヲ⣽ࡣḟ❶࡛㏙࡭ࡿࠋ㸬᪂⪺グ஦ᒾᡭࡢ௦⾲⣬࡛࠶ࡿᒾᡭ᪥ሗࡢ࣐࢖ࢡࣟࣇ࢕࣒ࣝࢆ㈨ᩱ࡜ࡋࡓࠋᆅ㟈࡟㛵ࡍࡿグ஦ࡣⓎ⏕⩣᪥ࡢ  ᭶  ᪥࠿ࡽ  ᪥௜ࡅࡢ⣬㠃ࡲ࡛⾲ࢀࡿࠋ⿕ᐖ࡟㛵㐃ࡍࡿグ஦ࡢࡳ㑅ࡧ௨ୗ࡟グࡍࠋ‫۔‬༳ࡣ኱ぢฟࡋ㸪‫  ࡣۑ‬ẁࡢᑠぢฟࡋ㸪ࠓ ࠔࡣグ஦ࡢせ⣙ࢆ♧ࡍࠋࡲࡓ㸪‫ࡣڹ‬グ஦ࡢ୰࡛౑ࢃࢀ
࡚࠸ࡿ‫ڹ‬༳࡛࠶ࡿࠋ࠙ ᭶  ᪥ࠚ 㠃㸸‫۔‬௒ᬡ┴ୗ୍ᖏᙉ㟈ᆅ㟈࡛ᒾ▼ᔂቯࡋᒣ⏣⥺࡛༴ࡃ஦ᨾⲡสࡾ⏨ࡀⓎぢ㎞
࠺ࡌ࡚ิ㌴೵ࡴᖹὠᡞᯇⲡ㥐㛫࡛ࠓ๓᭶  ᪥ᘏ㛗㛤ᴗࡋࡓࡤ࠿ࡾࡢᒣ⏣⥺ᖹὠᡞᯇⲡ㛫ࡢ⥺㊰
ഐࡢᓴࡼࡾከ㔞ࡢᅵ◁࡜ᒾ▼ᔂቯ㸪ᖹὠᡞⓎ  ᫬  ศࡢୖࡾ➨  ΰྜิ㌴೵㌴ࡋ༴ࡩࡃ஦࡞ࡁ
ࢆᚓࡓ㸪┤ࡕ࡟ᮧேཬࡧ௜㏆⥺㊰ᕤᡭࢆ⣕ྜࡋ⥺㊰  ࢭࣥࢳ⛣ືࡏࡋࡵ᚟ᪧࡋࡓࡀྠิ㌴ࡣ⣙ ศ⌧ሙ࡟೵㌴ࡋᑦ⥆࠸࡚ᔂቯࡢ៧ࡦ࠶ࡿࡢ࡛⌧ሙࡣ  ᫬㛫  ࢟ࣟࡢ㏿ຊ࡟࡚ᚎ⾜ࠔ ‫۔‬㟈ኸࡣᐑྂす༡ᑠᅜᕝὶᇦ㝃㏆ᮾ໭୍ᖏ࡟ரࡘ࡚࠶ࡘࡓ୰ኸẼ㇟ྎⓎ⾲ࠓṈࡢᆅ㟈ࡣእഃᆅ㟈ᖏࡢάື࡟ࡼࡿࡶࡢ࡛࠶ࡿࡀ௒ᅇࡢዴࡃ㝣ᆅ࡟㉳ࡁࡓࡢࡣྍ࡞ࡾ⌋ࡽࡋ࠸ࡇ࡜࡛࠶ࡿ⠊ᅖࡣྍ࡞ࡾ
ᗈ࠸ࡀከࡃࡣᒣᓅᆅᖏᆅ᪉࡛࠶ࡿ࠿ࡽ⿕ᐖࡣ࡞࠸ᶍᵝᮏᖺ  ᭶  ᪥㟷᳃┴ඵᡞᮾ᪉Ἀ࡟௒ᅇࡢ
ࡼࡾ⛮኱ࡁ࠸ᆅ㟈ࡀ࠶ࡘ࡚ከᑡ⿕ᐖࡶ࠶ࡘࡓࡀ௒ᅇࡣኵࡼࡾࡶᑠࡉࡃ⿕ᐖࡣ࡞࠸ࠔ ‫۔‬๓ᚋ ᅇ࡟ரࡾ㔩▼ᆅ᪉ᙉ㟈ື୙Ᏻ࡞୍ኪࢆ᫂࠿ࡍࠓ㔩▼ᆅ᪉ᡞࡀࡣ࡙ࢀᲴ࠿ࡽ≀ࡀⴠࡕ᫬ィ࡜ࡲࡿ➼୕㝣ὠἼ௨᮶ࡢ኱ᆅ㟈࡛ᝒ㬆ࢆୖࡆ࡚ᡞእ࡟㣕ࡧฟࡋ኱㦁ࡂࢆ₇ࡌࡓ㸪㔩▼㖔ᴗᡤࡢ↢⎰ሟࡀ⣙  㛫⛬ᔂቯࠔ ‫ۑ‬᫬ィࡢ᣺ᏊࡀṆࡲࡿỈ⃝ᆅ᪉࡟ࡶ࠿࡞ࡾࡢᙉ㟈ࠓỈ⃝ᆅ᪉࡟࠿࡞ࡾᙉ࠸
ᆅ㟈ࡀ࠶ࡾ᫬ィࡢ᣺ᏊࡀṆࡾᡞእ࡟㣕ฟࡓ⪅ࡶ࠶ࡘࡓỈ⃝⦋ᗘほᡤࡢᆅ㟈ィࡣࡇࢃࢀ࡚ࡋࡲ

ࡦุ↛ࡋࡓ஦ࡣุࡽ࡞࠸ࠔ ‫۔‬㟁⥺ษ᩿ࡉࡿᐑྂᆅ᪉ࡶ኱㦁ࡂࠓୗ㛢ఀ㒆ᐑྂᆅ᪉࡟㏆᮶⌋ࡽࡋ࠸ᙉ㟈࠶ࡾ㸪᫬ィࡢ᣺ࡾᏊࡀṆࡾ㟁⥺ࡀษ᩿ࡉࢀࡓࣨᡤ➼ࡶ࠶ࡾᒣ⏣㝃㏆ࡢዴࡁࡣᾏᓊ࡟ฟ࡚ὠἼࡢく᮶ࢆᜍࢀ࡚ⴙ୍ࡢሙྜ࡟ࡑ࡞࡬ࡿ➼኱㦁ࡂࢆ₇ࡌࡓ㸪ᐑྂ

ೃᡤࡢほ

࡟౫ࢀࡤ㟈

※ᆅࡣ᪩ụᓠᒣ㝃㏆࡛ᆅ㟈ィࡣ᭱኱㟈ᖜࡀࡣ࡙ࢀࡿ⛬ࡢࡶࡢ࡛࠶ࡘࡓࠔ ‫ۑ‬Ჴࡢჾ≀㌿ⴠ㐲㔝ᆅ᪉ᦆᐖࠓ㐲㔝⏫Ჴࡢჾ≀ࡣ㌿ⴠࡋ⏫Ẹࡣᡞእ࡟㣕ࡧฟࡋᒇ᰿⎰ࡣⴠࡕቨࡣ⬺ⴠ㸪ୖ㛢ఀ㒆ᯇᓮᮧ⚟Ἠᑎ▼ⅉ⡲ࡣ㌿ಽᔂቯ㸪㐲㔝⏫㦵ⴷရ㌿ⴠᔂቯ㸪ᅵⶶࡢቨ⬺ⴠ㸪ᯇᓮᮧ㔠ࣨ⃝቎ᆅ▼☃ᔂቯࠔ ‫ۑ‬࿴㈡㒆ୗࡣᡞእ࡟㣕ฟࡍࠓ࿴㈡㒆⣙  ศ㛫࡟ரࡘ࡚ᆅ㟈࠶ࡾ㯮ἑᑼ⏫ேࠎṤࢇ࡝ᡞእ࡟㣕ฟࡋࡓ⛬࡛᫬ィࡢ᣺ࡾᏊṆࡲࡘࡓࠔ  㠃㸸‫࡭ࡩࡺۑ‬ཪᆅ㟈వ㟈ࡋࡁࡾ ‫۔‬ಽ₽ᐙᒇ 3ᡞ㐨㊰ࡣỴ₽ࡋ஺㏻ᮭ⤯ࡍᑠᅜᮧࡼࡾࡢሗ࿌ࠓ ᪥༗ᚋ  ᫬┴ಖᏳㄢ࡟㐩ࡋࡓᑠᅜᮧᕠᰝ㥔ᅾᡤࡼࡾࡢሗ࿌࡟౫ࢀࡤᑠᅜᮧ⿕ᐖ⛬ᗘࡣྠᮧ඲ᡞ࡟ரࡾቨࡀⴠࡕᐙලᩓ஘ࡋಽ₽ᐙᒇ  ᡞ࠶ࡾ㸪ᆅ㟈ࡢࡓࡵࡢ࢟⿣ࡣ฿ࡿᡤ࡟ぢཷࡅࡽࢀ㐨㊰ࡢỴ₽  ࣨᡤ࠶ࡾ஺㏻ᮭ⤯ࡋἙᓊࡢỴ₽ࡢࡓࡵ㛢ఀᕝࡣⓑⰍ࡟ᅔ⃮ࡋᡈ⟠ᡤࡣ㯮࠸Ỉࢆᄇฟࡋ࡚ᒃࡿࠔ ‫ุۑ‬᫂ࡋࡓ⿕ᐖࠓୗ㛢ఀ㒆ᑠᅜᮧ᪂⏣㯄ᶫ㝿▼ᇉᔂቯ‫ྠڹ‬ᮧᑠᏛᰯ๓▼ᇉᔂቯ‫ࡢࡑڹ‬௚ྠᮧᙺሙ๓እ  ࣨᡤ▼ᇉᔂቯ‫ྠڹ‬ᮧ㐨ཪᶫ㝃㏆㐨㊰Ỵቯ‫ྠڹ‬኱⪺ᑎ㝃㏆㐨㊰⣙  ᑍチࡾࡢட⿣ࢆ⏕ࡌ〇Ⅳ❔ࡢᔂቯࡏࡿࡶࡢ  ࣨᡤ࡟ཬࡪ‫ྠڹ‬ᮧ㐨ཪ㒊ⴠ࡛ࡣேᐙࡢᡞ㞀Ꮚࡀ◚ࢀ㐨㊰ࡀỴቯட⿣⣙  ࣨᡤ‫ڹ‬ᑠᅜᕝࡢἙỈࡣⓑⰍ࡟ኚࡌ㐨ཪ㒊ⴠࡢᘬỈụ㝃㏆ࡣட⿣ࢆ⏕ࡌ㯮ⰍࡢỈࡀ‪ฟࡋࡓ‫ࡢࡑڹ‬௚ྠᮧෆྛၟᗑࡢᗑ⯒ࡢၟရࡀಽࢀ⟸➡ࡑࡢ௚ࡢᐙ㈈ࡀಽࢀᲷᮌᔂࢀࡓࡿࡶࡢ  ࣨᡤ࡟ཬࢇ࡛࠸ࡿࡀே␆࡟ࡣ⿕ᐖ
࡞࠸ᶍᵝࠔ࠙ ᭶  ᪥ࠚ 㠃㸸‫۔‬㟈ኸᑠᅜࢆゼࡩ  ศẖ࡟ᆅ㬆ࡾ⦪ᶓ↓ᑾࡢட⿣ᜍᛧ࡜୙Ᏻࡢ୍ኪࢆ᫂࠿
ࡍ඲ᮧ⏒ࡋ࠸᝺≧ࠓୖ㛢ఀ㒆᪩ụᓠᒣࢆ㟈※ᆅ࡜ࡋ࡚㉳ࡘࡓᆅ㟈ࡣ᫂἞  ᖺ୕㝣ᾏᓊࢆくࡩࡓ኱ᾏთࡢ㝿ࡼࡾࡎࡘ࡜ࡦ࡝࠿ࡘࡓ࡜⪺࠸ࡓグ⪅ࡣྠ༗ᚋ  ᫬༙⮬ື㌴࡛᭱ࡶ୰ᚰ࡟㏆࠸ᑠᅜᮧ࡟ྥࡘࡓ᪥ࡀᬽࢀᑠᅜᮧ࡟╔࠸ࡓ࡜ࡁࡣ  ᫬ࢆᘔࡘ࡚࠸ࡓ㸪᱌ෆᙺࡢヰ┿ኪ୰ࢻࢩࣥ࡜᮶ࡓᆅ
㟈ࡔ࡞࡜ᛮࡘࡓࡑࡢ▐㛫ࢢࣛࢢࣛ࡜᮶ࡓືࡃࡶṌࡃ஦ࡶฟ᮶࡞࠸ᡞ㞀Ꮚࡀእࢀ࡚ᆅ㠃࡟ࡓࡓࡁࡇࡣࢀࡿ㡢Ჴ࠿ࡽⴠࡕࡿ㡢℩ᡞ≀ࡢࡇࡣࢀࡿ㡢ᝒ㬆㸪వ㟈ࡣ㛫㧥࡞ࡃ⥆ࡁேࠎࡣᐙ࡟ධࡿ஦ࡶ
࡞ࡽࡎእ࡟↏ࡁⅆࡋ୍࡚ኪࡲࢇࡌࡾ࡜ࡶࡏࡎኪࡀ᫂ࡅ࡚ぢ࡚ࡑࡢ⿕ᐖࡢ኱ࡁ࠿ࡘࡓࡢ࡟㦫࠸ࡓᡞ㞀Ꮚࡣࡔࡽࡋ࡞ࡃᆅ㠃࡟ᢞࡆฟࡉࢀᲴ࠿ࡽⴠࡕࡓ℩ᡞ≀ࡢ◚∦⟸➡ࡸ㛗ᣢ࡜ࡀᐙࡢ୰࡟ಽࢀ
᭱ࡶ᝺ࡵ࡛࠶ࡘࡓࡢࡣၟᗑ࡛㝞ิᲴࡢୖ࠿ࡽᔂࢀⴠࡕࡓ⎼ワ㢮ࡀ୍ࡘṧࡽࡎቯࢀ㡹ᅛࢆ㄂ࡘ࡚
࠸ࡿ㸪ᅵⶶࡀࡔࡽࡋ࡞ࡃቨࡀᔂࢀⴠࡕཪᲷᮌࡣⴠࡕ࡚ഴࡁ࠿ࡅࡓᐙᒇࡸཪ▼ᇉࡢᔂቯࡋࡓࡶࡢ
㐨㊰ࡢỴቯࡋࡓࡶࡢᡈࡣ⦪ᶓ↓ᑾ࡟ட⿣ࢆ⏕ࡌࡓ⾤㊰➼ࠎ඲ࡃ㦫␗࡟್ࡍࡿࡶࡢチࡾ࡛࠶ࡘࡓ㸪ᑠᅜᮧࡣඖ᮶඲㎰࡛࠶ࡿࡀ෤ᮇ㛫ࡣ〇Ⅳࢆ௨࡚⏕ィࢆႠࡴ⪅ࡀከ࠸ࡢ࡛ᮧෆ࡟ⓒᩘ༑ಶࡢ〇❔
ࡀタࡅࡽࢀ࡚࠸ࡿࡀࡇࡢᙉ㟈࡟㐼ࡘ࡚ࡣࡦ࡜ࡓࡲࡾࡶ࡞ࡃᔂቯࡋ᫝ཪ᝺≧ࢆᴟࡵ࡚࠸ࡿᖾࡦ࡟
ே␆࡟⿕ᐖࡢ࡞࠿ࡘࡓ஦ࡀኳ♸࡛࠶ࡿ࡜ㄒࡿࠔ ‫۔‬㔠⃝ᮧࡶᆅ㟈⿕ᐖ⏒኱ᒣᔂࢀⅣ↝❔ಽ₽ࠓ኱ᵔὴฟᡤᕠᰝ㒊㛗ࡣ  ᪥ᮅ⌧ሙ࡟ᛴ⾜ᐇᆅㄪᰝࢆ⾜ࡘࡓࡀ㔠⃝ᮧᡞ⃝㸪୰ᒣ㒊ⴠ᭱ࡶᙉ㟈࡛▼ᇉᔂቯᩘࣧᡤᒣᔂࢀᩘࣧᡤ࠶ࡘࡓ㸪඲ᮧࡢⅣ↝ࡁ❔ࡢᔂቯࡏࡿࡶࡢࡸࡃ  ࣨᡤࠔ ‫ࡩࡢࡁۑ‬ࡶᮍࡔᆅ㬆ࡾṆࡲࡎᮧẸᡓࠎ᜗ࠎࠓ ᪥┴ᅵᮌㄢ࡟㐩ࡋࡓᑠᅜᮧᆅ᪉ࡢᆅ㟈⿕ᐖᑠᅜᮧ㐲㔝㸪ᕝ஭㛫㐨㊰ᔂቯ  ࣨᡤ㸪ᶫᱱᔂቯ  ࣨᡤ㸪㐨㊰ட⿣  ⟠ᡤ㸪Ⅳ↝❔ᔂ₽  㣾ಶ㸪ᅵⶶᔂቯ ࣨᡤࠔ ኤห  㠃㸸‫⤊۔‬᪥ᒣ㬆ࡾ᪩ụᓠᒣ㯄ᜍៃ௒ᬡࡶཪᙉ㟈࠶ࡘࡓࠓ㟈※ᆅ᪩ụᓠᒣࡢᒣ㯄ᆅ㔠⃝ᮧࡣ⤊᪥ࡈ࠺ࡈ࠺࡜ᒣ㬆ࡾࡀࡋ࡚Ⅳ↝ࡁ❔ࡀ኱㒊ศಽቯࡋ㐨㊰ࡣྛᡤ࡟ட⿣ࢆ⏕ࡌ಴ᗜࡸேᐙࡢቨࡣᔂࢀཪᒣࡀᔂቯ➼ࡀ㢖ฟࡋࡓࡀே␆࡟ࡣṚയࡀ࡞࠸㸪ᕝỈ㸪஭ᡞỈࡶ⃮ࡾ㣧ᩱỈࢆኻ࡞ࡘࡓ㒊ⴠẸࡣ኱ᜍៃࢆ᮶ࡋ࡚࠸ࡿࠔ࠙ ᭶  ᪥ࠚ 㠃㸸‫۔‬ᑠᅜᮧ㛗⪅᳃࡟᩿ᒙ↓ᩘⓎぢࡍᕵ  ᑍࡼࡾ  ᑻ఩ࡢࡶࡢ㥔ᅾᕠᰝࡢሗ࿌
ࠓᑠᅜᮧ㛗⪅᳃㝃㏆࡟᪊࡚ᕵ  ᑍ஀⮳  ᑻࡢ᩿ᒙࡀ↓ᩘ࡟࠶ࡿࡢࢆᑠᅜ㥔ᅾᡤᕠᰝࡀⓎぢࡋᐑྂ⨫࡟ሗ࿌ࠔ ‫۔‬వ㟈  ᅇ࡟ཬࡪ ‫⿕۔‬ᐖࡣ᝿ീ௨ୖᨭᗇ⃝⏣ᒓࡢሗ࿌ࠓ ᪥ᑠᅜᮧࡢᐇ᝟ㄪ
ᰝ࡟ྥࡘࡓୗ㛢ఀᨭᗇ⃝⏣ᒓࡣ  ᪥༗ᚋ  ᫬ᖐᗇ㸪ண᝿௨ୖࡢ⿕ᐖ࡟㦫࠸࡚᮶ࡓࡑࢀ࡛ྲྀᩒࡎ
Ⅳ↝❔ࡣྠᮧẸࡢ⏕࿨࡜ࡍࡿࡶࡢ࡛୎ᗘ㟂せᮇࢆࡦ࠿࡬࡚࠸ࡿ㛵ಀ࠿ࡽᮧẸࡣ┦஫ᢇຓ࡟౫ࡘ
࡚ྛࠎ⠏㐀ࡍࡿ஦࡟ࠔ

4

࠙ ᭶  ᪥ࠚ 㠃㸸‫۔‬Ⅳᑠᒇ  ᡞ㔠⃝ᮧ࡛↝ኻᑦవ㟈࠶ࡾᮧẸ⬣ࡺࠓୖ㛢ఀ㒆㔠⃝ᮧ㥔ᅾᡤࡢሗ࿌㸪Ⅳ↝❔  ࣨ₽ࢀྠ᫬࡟ⅆ⅏㉳ࡾⅣᑠᒇ  ᡞ↝ኻ㸪▼ᇉᩘࣨᡤᔂ₽㸪୰ᒣ㒊ⴠᅵⶶᔂቯ㸪Ꮠඖᮧ㸪୰ᒣ㸪ᡞ⃝ࡢዟᆅࡣ㐨㊰࡟ட⿣ࢆ⏕ࡌࡓእ஭ᡞỈࡀఱࢀࡶⓑⰍ࡟ኚࡌࡓࠔ ‫ۑ‬ᑠᅜᮧ㟈⅏⿕ᐖ┴࡟ሗ࿌ࠓୗ㛢ఀᨭᗇሗ࿌ࡀ  ᪥༗๓  ᫬༙┴࡟฿㐩㸪ᑠᅜᮧࡢⅣ↝ࡁ❔ࡀ  వࡶ◚ቯ㟷ᖺᅋࡢ᥼ຓ࡟౫ࡘ࡚  వ❔ࡣ᚟ᪧࠔ  㠃㸸‫۔‬෌ᗘᑠᅜࢆゼࡩ㇦㞵ᒣ㬆ࡾవ㟈ࡢࡓࡵᘬ㎸࡬ࡍࡅࡩ㟈※ᆅ࡬ྥࡩࠓᑠᅜᮧᙉ㟈ࡢࡓࡵᐙࡀഴࡁ୙Ᏻ࡟ໟࡲࢀ࡚ᒃࡿ㸪ྛ㒊ⴠ㟷ᖺᅋ➼༠ຊࡋ࡚㛤㐨ࡋࡓ┴㐨ࡣవ㟈ࡢࡓࡵཪࠎ↓ᩘࡢட⿣ࢆ⏕ࡌ⪔స⏿ᆅࡣ┤ᚄ  ࢭࣥࢳ௨ୖࡢ✰ࡀ⮳ࡿ⹦࡟࠶࠸࡚ᒃࡿ㸪Ỵ₽ࡋࡓⅣ↝ࡁ❔ࡣ↓᝺࡟ࡉࡽࡉࢀ࡚ᒃࡿ㸪㐨ཪ≟✰⃝࡟⮳ࡾ㟈※ᆅ㏆ࡃ࡟࡞ࢀࡤ  ⡿ᅄ᪉ࡢ኱ࡁ࡞ᒾ▼ࡀᔂ₽ࡋ  ㈏ࡢᒾ▼ࡀ↓ᩘ࡟㇂㛫࡟㌿ࡀࡘ࡚ᒃࡿࠔ ‫ۑ‬஭ᡞỈ⃮ࡿࠓᒾᡭ㍍㕲ࡢᑠᒣ⏣▮⃝୧㥐௜㏆ࡢẸᐙࡣᮏᖺ  ᭶㡭ࡼࡾྛ஭ᡞỈࡀ⃮ỈఫẸࡣ㣧ᩱỈ࡟ᅔᝨࡋ࡚࠸ࡓ࡜ࡇࢁᩘ᪥๓ࡢᆅ㟈┤ᚋ࠿ࡽྛ஭ᡞỈࡣⓑⰍ࡟ΰ⃮ࡋ౑⏝୙⬟࡜࡞ࡘࡓࠔ࠙ ᭶  ᪥ࠚ 㠃㸸‫۔‬኱ᆅ㟈ࡣගࢆⓎࡍᑠᅜ⃭㟈࡛☜ドᚓᏛ఍ࡢ㈗㔜࡞◊✲㈨ᩱ࡜࡞ࡿࢃࡀᅜ
஧ᗘ┠ࡢ⌧㇟ ‫۔‬㟈※ᆅࡣᑠᅜᮧጁ⃝ᒣࡼࡾ㛗⪅᳃࡟ࢃࡓࡿ㛫 ‫۔‬ᅛ࠸ᆅ┙ࡢⅭ⿕ᐖࡣᑩࡋ
ᐇᆅㄪᰝ࡟ྥࡘࡓ┒ᒸೃᡤ஧ᐑᢏᡭㄯ ‫ۑ‬ᮧẸ₞ࡸࡃᏳሚ ‫۔‬Ⅳ↝❔ᔂⴠࡣ᭱ࡶ኱ᡴᧁᦆᐖᐇ࡟  ୓  ༓෇✺◚ᑠᅜᮧẸᅔࡾษࡿࠓୗ㛢ఀ㒆ᑠᅜᮧࡢ⿕ᐖࡣࡑࡢ୺࡞ࡿࡶࡢࡣⅣ↝ࡁ❔ࡢᔂⴠ࡛෤ᮇ㛫ࡢ⏕ィࡣ〇Ⅳ࡟ࡼࡘ࡚❧࡚ࡽࢀ㎰స≀ࡢ୙స࡟ࡣࣅࢡ࡜ࡶࡏࡠᮧẸࡶ❔ࢆኻࡘࡓࡢ࡟ࡣᅔࡾษࡘ࡚࠸ࡿ㸪ᆅ㟈ᙜ᫬࡟ࡣ❔ࡢ୰࡟ࡣఱࢀࡶ  ಥ࠿ࡽከ࠸ࡢ࡛ࡣ  ಥศࡢⅣࡀฟ
᮶࠿࠿ࡘ࡚࠸ࡓࡀ❔ࡢᔂⴠ࡛඲㒊⇞࠼ᑾࡃࡋ࡚ࡋࡲࡘࡓ㸪ࡑࡢ௚ࡢ⿕ᐖࡣேᐙᅵⶶࡸఫᐙࡢቨ
ࡢⴠࡕࡓࡶࡢࡀ⣙  ෇㐨㊰ᶫᱱࡢ◚ᦆ➼ࡀ⣙  ༓  ⓒ෇ᐙ㈈≀ရࡢ◚ᦆࡑࡢ௚  ෇ෆእࠔ࠙ ᭶  ᪥ࠚ 㠃㸸‫۔‬ᑠᅜ࡟ཪᆅ㟈ὶゝ㣕ࡧᮧẸᜍᛧ ‫ۑ‬㔩▼࡟ᆅ㟈࠙ ᭶  ᪥ࠚ 㠃㸸‫۔‬᫖ኪ  ᅇ࡟ரࡾ㔠⃝ᮧ࡟ཪᆅ㟈ᮧẸࡢ୙Ᏻᑦ୍ᒙ
㸬⿕ᐖ࡜ࡑࡢศᕸ ᩪ⸨ሗᜠ఍◊✲ሗ࿌ 㸵㸧 ࡜᪂⪺グ஦࠿ࡽ⿕ᐖ࡟㛵ࡍࡿ㡯┠ࢆᪧᕷ⏫ᮧู࡟ᩚ⌮ࡋ⾲㸰࡟♧ࡍࠋࡲࡓ㸪⾲㸰࡟ࡼࡾ⿕ᐖࡢศᕸࢆᙜ᫬ࡢ㕲㐨࡜୺せ࡞㐨㊰࡜࡜ࡶ࡟♧ࡍ࡜ᅗ㸰ࡢࡼ࠺࡟࡞ࡿࠋ࡞
࠾㸪⏫ᮧࡣቃ⏺ࢆᐇ⥺࡛♧ࡋ㸪⾲㸰࡟グ㍕ࡉࢀ࡚࠸࡞࠸⏫ᮧྡࡣ㸦 㸧ෆ࡟♧ࡋࡓࠋ⿕ᐖࡣᑠᅜᮧ࡜㔠⃝ᮧ࡛኱ࡁࡃ㸪ᩪ⸨ሗᜠ఍◊✲ሗ࿌ࡢ⏣ᒣࡢሗ࿌ 㸵㸧 ࡟ࡣࠗ⿕ᐖࡣୗ㛢ఀ㒆ᑠᅜᮧ࡜ୖ
㛢ఀ㒆㔠⃝ᮧࡢ  ᮧ࡟ᒁ㝈ࡏࡽࢀࡑࡢ௚࡟᪊࡚ࡣ඲ࡃ⿕ᐖࡀ࡞࠸࠘࡜グ㍕ࡉࢀ࡚࠸ࡿࠋ〇Ⅳ❔
ࡢ⿕ᐖࡀ᭱ࡶከࡃ㸪ᑠᅜᮧ  ⟠ᡤ㸪㔠⃝ᮧ  ⟠ᡤ࡛ᔂቯࡋ㸪≉࡟ጁ⃝ᒣ㹼㛗⪅᳃㐃ᒣࡢ〇Ⅳ❔ࡣ඲㒊ᔂቯࡋࡓࡇ࡜ࡀグࡉࢀ࡚࠸ࡿࠋࡲࡓ㸪ᐙᒇ㺃ᅵⶶࡸ▼ᇉࡢ◚ᦆࡶⓎ⏕ࡋ㸪ᑠᅜᮧ࡟ࡘ
࠸࡚ࡣࠗ≉࡟ᮎゅ㸪ᅵ⃝࡟᪊࡚ኰ㸦࠾ࡧࡓࡓ㸧ࡋ࠸࠘࡜グ㍕ࡉࢀ࡚࠸ࡿࠋࡇࡢ௚㸪ᑠᅜᮧࡢᅵ
⃝ᓘ㹼㐨ཪ㛫㸪ᑠᓘ㹼኱ṇᶫ㛫㸪㔠⃝ᮧࡢᅵᆏᓘ㹼኱㈏ྎ㛫࡛㐨㊰ࡢட⿣ࡀⓎ⏕ࡋ࡚࠸ࡿࠋ
᪂⪺グ஦࡛ࡣ㸪ࡉࡽ࡟ᗈ࠸⠊ᅖ࡛࿘㎶⏫ᮧࡢ⿕ᐖࡀሗࡌࡽࢀ࡚࠸ࡿࠋ໭ࡣୗ㛢ఀ㒆㛛㤿ᮧ࠿ࡽ༡ࡣୖ㛢ఀ㒆㔩▼⏫ࡲ࡛㟈ኸ࠿ࡽ  ੊⛬ᗘࡢ⠊ᅖ࡛ቨࡢ⬺ⴠࡸ↢⎰ሟࡢᔂቯ㸪ᩳ㠃ᔂቯ࡞࡝ࡀሗࡌࡽࢀ࡚࠸ࡿࠋࡇࡢ௚㸪ᑠᅜᮧࡢ⿕ᐖ࡟ࡘ࠸࡚ࠗ඲ᡞ࡟ரࡾቨࡀⴠࡕᐙලᩓ஘ࡋಽ₽ᐙᒇ ᡞ࠘࡜グࡉࢀ㸪〇Ⅳ❔࡟ࡘ࠸࡚ࡣࠗⅣᑠᒇ  ᡞ㔠⃝ᮧ࡛↝ኻ࠘ࡋࡓࡇ࡜ࡀሗࡌࡽࢀ࡚࠸ࡿࠋ
ࡲࡓ㸪ᩳ㠃ᔂቯࡸⴠ▼ࡀᗈ⠊ᅖ࡛Ⓨ⏕ࡋ㐨㊰ࡢ୙㏻ࡀሗࡌࡽࢀ㸪๓᭶  ᪥ᘏ㛗㛤ᴗࡋࡓࡤ࠿ࡾ
ࡢᒣ⏣⥺ᖹὠᡞ㹼ᯇⲡ㛫࡛ࡣከ㔞ࡢᅵ◁࡜ⴠ▼࡟ࡼࡾิ㌴ࡀ೵㌴ࡋࡓࡇ࡜ࡀሗࡌࡽࢀ࡚࠸ࡿࠋ

5⾲㸰  ᖺᒾᡭ┴ᑠᅜᆅ㟈ࡢᕷ⏫ᮧู⿕ᐖ୍ぴ㒆 ᪧ⏫ᮧ ᩪ⸨ሗᜠ఍◊✲ሗ࿌ 㸵㸧 ᒾᡭ᪥ሗୗ ᑠᅜᮧ ᐙᒇᅵⶶቨࡢᔂⴠ  ⟠ᡤ㸪 ඲ᡞቨࡀⴠࡕಽ₽ᐙᒇ  ᡞᲷᮌᔂቯ  ࣨᡤே␆㛢▼ᇉᔂቯ  ⟠ᡤ㸪〇Ⅳ❔ᔂ ࡟ࡣ⿕ᐖ࡞࠸᪂⏣㯄ᶫ▼ᇉᔂቯᑠᏛᰯ๓▼ᇉᔂቯᙺሙ๓እ  ࣨᡤ▼ᇉᔂቯ࢟⿣฿ࡿᡤ࡟ぢཷࡅࡽࢀ㐨㊰ఀቯ  ⟠ᡤỴቯ  ࣨᡤ஺㏻ᮭ⤯㐨ཪᶫ㝃㏆㐨㊰Ỵቯ኱⪺ᑎ㝃㏆㒆㉥⃝㞟ⴠఫᐙഴᩳ  ᡞᅵ⃝㞟ⴠఫᐙഴᩳ  ᡞ㐨㊰ட⿣ 㸪 㐲㔝㸫ᕝ஭㛫㐨㊰ᔂቯ  ࣨᡤᶫᱱᔂቯ  ࣨᮎゅ㞟ⴠ኱ྠᑎᅵⶶட⿣ ᡤ㸪〇Ⅳ❔ᔂቯ  ࣨᡤἙᓊỴ₽㛢ఀᕝࡣⓑⰍ࡟ᅔ㐨㊰ட⿣ᅵ⃝ᓘ㹼㐨ཪ㛫㸪 ⃮ᘬỈụ㝃㏆ட⿣㯮࠸Ỉᄇฟ㸪㛗⪅᳃㝃㏆᩿ᒙ↓ᩘᑠᓘ㹼኱ṇᶫ㛫㛛㤿ᮧ 
ᒣ⏣⥺ᖹὠᡞ㸫ᯇⲡ㛫ከ㔞ࡢᅵ◁࡜ᒾ▼ᔂቯୖ 㔠⃝ᮧ ᐙᒇᅵⶶቨࡢᔂⴠ  ⟠ᡤ㸪 Ⅳ↝❔  ࣨ₽ࢀྠ᫬ⅆ⅏  ᡞ↝ኻ▼ᇉᩘࣨᡤᔂ₽▼ᇉᔂቯᩘ⟠ᡤ㸪〇Ⅳ❔ᔂ ୰ᒣ㒊ⴠᅵⶶᔂቯ୰ᒣ㒊ⴠ▼ᇉᔂቯᩘࣧᡤᒣᔂᩘࣧ
㛢ᡤ஭ᡞỈఱࢀࡶⓑⰍ࡟ኚࡌࡓቯ  ⟠ᡤఀ㐨㊰ட⿣ᅵᆏᓘ㹼኱㈏ྎ㛫㒆㐲㔝⏫ 
ᐙᒇᒇ᰿⎰ⴠࡕቨ⬺ⴠᅵⶶቨ⬺ⴠᯇᓮᮧ 
⚟Ἠᑎ▼ⅉ⡲㌿ಽᔂቯ㔠ࣨ⃝቎ᆅ▼☃ᔂቯ㔩▼⏫ 
㔩▼㖔ᴗᡤࡢ↢⎰ሟᔂቯ

⌧ᅾ
ᐑྂᕷ

኱ᵔ⏫

㐲㔝ᕷ
㔩▼ᕷ




ᅗ㸰  ᖺᒾᡭ┴ᑠᅜᆅ㟈ࡢ⿕ᐖࡢࡲ࡜ࡵ
㹙‫ە‬ᐙᒇಽ₽ ‫۔‬ᐙᒇ◚ᦆ ‫ۑ‬ᅵⶶ◚ᦆ ‫ڦ‬Ⅳ↝❔ᔂቯ ‫▼ڸ‬ᇉ㺃↢⎰ሟ㺃▼ⅉ⡲㺃▼☃ᔂቯ 㐨㊰㺃㕲㐨⿕ᐖ㹛6㸬ࡲ࡜ࡵ  ᖺᒾᡭ┴ᑠᅜᆅ㟈࡟ࡘ࠸࡚㸪ᙜ᫬ࡢ⿕ᐖㄪᰝሗ࿌㸪᪂⪺ࢆ཰㞟ࡋグ㍕ࡉࢀ࡚࠸ࡿ⿕ᐖࢆᩚ⌮ࡋࡓࠋ᫂ࡽ࠿࡟ࡉࢀࡓ୺࡞㡯┠ࡣ௨ୗࡢ㏻ࡾ࡛࠶ࡿࠋ ୰ኸẼ㇟ྎ࡟ࡼࡿ⿕ᐖㄪᰝሗ࿌᭩㸪㛵㐃ㄽᩥࡀṧࡉࢀ࡚࠸ࡿࠋ୰ኸẼ㇟ྎሗ࿌࡟ࡣ㸪ྛᆅࡢ㟈ᗘ㸪┒ᒸೃᡤ࡟ࡼࡿ⿕ᐖᴫせࡢࡳグ㍕ࡉࢀ㸪ᑠᅜᮧࡢᅵⶶ࡜ᑠᏛᰯ▼ᇉࡢ⿕ᐖ෗┿  ᯛࡀṧࡉࢀ࡚࠸ࡿࠋ ᩪ⸨ሗᜠ఍◊✲ሗ࿌ࡢ⏣ᒣࡢㄽᩥ࡟ࡣ㸪ᑠᅜᮧ㸪㔠⃝ᮧࡢ⿕ᐖㄪᰝ⤖ᯝࡀグ㍕ࡉࢀ࡚࠸ࡿࠋ
ᐙᒇ㺃ᅵⶶࡸ▼ᇉࡢ◚ᦆ㸪〇Ⅳ❔ࡢᔂቯ㸪㐨㊰ட⿣ࡀⓎ⏕ࡋࡓࡇ࡜ࡀグࡉࢀ࡚࠸ࡿࠋࡲࡓ㸪୍㒊㞟ⴠࡢ⿕ᐖࡀグࡉࢀ࡚࠸ࡿࠋ ᪂⪺グ஦࡟ࡣ㸪⿕ᐖࡣ኱ࡁࡃሗࡌࡽࢀ㸪໭ࡣୗ㛢ఀ㒆㛛㤿ᮧ࠿ࡽ༡ࡣୖ㛢ఀ㒆㔩▼⏫ࡲ࡛㟈ኸ࠿ࡽ  ੊⛬ᗘࡢ⠊ᅖ࡛ቨࡢ⬺ⴠࡸ↢⎰ሟࡢᔂቯ㸪ᩳ㠃ᔂቯ࡞࡝ࡀⓎ⏕ࡋ࡚࠸ࡿࠋ⿕ᐖࡣ㟈※࡟㏆࠸ᑠᅜᮧ࡜㔠⃝ᮧ࡛኱ࡁࡃ㸪ᐙᒇࡸᅵⶶࡢᔂቯࡀሗࡌࡽࢀ࡚࠸ࡿࠋࡲࡓ㸪〇Ⅳ❔ࡢ⿕ᐖࡀ᭱ࡶከࡃ㸪ᩳ㠃ᔂቯࡸⴠ▼ࡀᗈ⠊ᅖ࡛Ⓨ⏕ࡋ㐨㊰ࡸ㕲㐨ࡢ୙㏻ࡀሗࡌࡽࢀ࡚࠸ࡿࠋ
ᒾᡭ┴ෆ㝣ࡢ⿕ᐖᆅ㟈ࡣ㏆ᖺከࡃⓎ⏕ࡋ࡚࠸ࡿࠋ௒ᚋࡣࡇࢀࡽ࡟ࡘ࠸࡚ࡶᩥ⊩ㄪᰝࢆ㐍ࡵ࡚࠸ࡁࡓ࠸ࠋ
ཧ⪃ᩥ⊩㸯㸧Ỉ⏣ᩄᙪ࣭㙾࿡ὒྐ㸸 ᖺ࠾ࡼࡧ  ᖺࡢ⛅⏣┴᳃ྜྷ࣭㜿ோࡢᆅ㟈࡟ࡼࡿ⿕ᐖ࡟㛵ࡍࡿᩥ⊩ㄪᰝ㸪ᮾ໭ᆅᇦ⅏ᐖ⛉Ꮫ◊✲㸪㸪SS㹼㸪
㸰㸧Ỉ⏣ᩄᙪ࣭㙾࿡ὒྐ㸸 ⛅⏣┴༡ᮾ㒊ᆅ㟈ࡢ⿕ᐖ࡟㛵ࡍࡿᩥ⊩ㄪᰝ㸪᪥ᮏᘓ⠏Ꮫ఍ᢏ⾡ሗ࿌㞟㸪㸪㸪SS㹼㸪
㸱㸧ᒾᡭ┴㸸ᆅᇦ㜵⅏ィ⏬㈨ᩱ⦅㸪SS㹼㸪
㸲㸧Ᏹబ⨾㱟ኵ࣭▼஭ᑑ࣭௒ᮧ㝯ṇ࣭Ṋᮧ㞞அ࣭ᯇᾆᚊᏊ㸸᪥ᮏ⿕ᐖᆅ㟈⥲ぴ㸪ᮾி኱Ꮫฟ∧఍㸪SS㸪㸳 㸧 Ẽ ㇟ ᗇ 㸸 㟈 ᗘ ࢹ ࣮ ࢱ ࣋ ࣮ ࢫ ᳨ ⣴ KWWSVZZZGDWDMPDJRMSVYGHTGEGDWDVKLQGRLQGH[KWPO
㸦 㜀ぴ㸧㸴㸧୰ኸẼ㇟ྎ㸸 ᪥  ᫬  ศ㡭ᒾᡭ┴ୗ㛢ఀ㒆ᑠᅜ௜㏆ࡢᆅ㟈㸪Ẽ㇟せぴ㸪㸪SS㹼㸪㸵㸧⏣ᒣ฼୕㑻㸸᫛࿴  ᖺ  ᭶  ᪥ࡢᑠᅜ ᒾᡭ┴ ᆅ㟈ཬࡧࡑࡢ㟈ᇦᆅ᪉ࡢᆅᙧᆅ㉁␎ሗ㸪ᩧ⸨ሗᜠ఍Ꮫ⾡◊✲ሗ࿌㸪㸪SS㸪 東北地域災害科学研究

7

第58巻（2022） ᖺ㟷᳃┴ᮾ᪉Ἀᆅ㟈ࡢᒾᡭ࣭⛅⏣ࡢ⿕ᐖ 㸨 ໭ᾏ㐨኱Ꮫ ྡ㄃ᩍᤵ    㙾࿡ ὒྐ⛅⏣኱Ꮫ ᆅ᪉๰⏕ࢭࣥࢱ࣮ Ỉ⏣ ᩄᙪ㸬ࡣࡌࡵ࡟
୕㝣Ἀ໭㒊࡛ࡣ ࣭࣭࣭ ᖺࡢᆅ㟈ࢆᅛ᭷ᆅ㟈࡜ࡋᾏ⁁ᆺᆅ㟈ࡢ㛗ᮇணࡀ⾜ࢃࢀ࡚࠸ࡿࠋ➹⪅ࡢ୍ேࡣ㸪ᅛ᭷ᆅ㟈ࡢ㛫ࡢ ࣭ ᖺ࡟Ⓨ⏕ࡋࡓ㟷᳃┴ᮾ᪉Ἀࡢᆅ㟈࡟ࡘ࠸࡚㟷᳃┴࣭໭ᾏ㐨ࡢᆅ᪉᪂⪺グ஦࠿ࡽ⿕ᐖࡢヲ⣽ࢆ᫂ࡽ࠿࡟ࡋ࡚࠸ࡿ 㸯㸧㸪㸰㸧ࠋ ᖺࡢᆅ㟈࡛ࡣ⿕ᐖࡣ୍㒊㸪ᒾᡭ┴࣭⛅⏣┴࡟࠾ࡼࢇ࡛࠸ࡿࠋᮏㄽ࡛ࡣ㸪ᒾᡭ┴࣭⛅⏣┴ࡢ⿕ᐖ࡟ࡘ࠸࡚ྛ┴ࡢ௦⾲⣬࡟ࡼࡿᩥ⊩ㄪᰝࢆ⾜࠸⿕ᐖࡢ≧ἣࢆ᫂ࡽ࠿࡟ࡍࡿࠋ
㸬୕㝣Ἀ໭㒊ࡢᾏ⁁ᆺᆅ㟈᪥ᮏᾏ⁁ἢ࠸ࡢ୕㝣Ἀ࠿ࡽᡣ⥲Ἀ࡟࠿ࡅ࡚ࡢᆅ㟈άືࡢ㛗ᮇホ౯ࡀ  ᖺ࡟ᆅ㟈ㄪᰝጤဨ఍࡟ࡼࡗ࡚࡞ࡉࢀࡓࠋ㟷᳃┴ᮾ᪉Ἀࢆྵࡴ୕㝣Ἀ໭㒊࡟ࡘ࠸࡚⾲㸯࡟♧ࡍ ࣭࣭࣭
 ᖺࡢᆅ㟈ࢆᅛ᭷ᆅ㟈࡜ࡋ࡚࠸ࡿࠋࡇࢀࡽࡢᆅ㟈ࡢᖹᆒⓎ⏕㛫㝸ࢆ  ᖺ࡜ࡋ㸪᭱ᚋࡢ ᖺ༑຾Ἀᆅ㟈࠿ࡽࡢ⤒㐣ᖺᩘࢆࡶ࡜࡟௒ᚋࡢⓎ⏕☜⋡ࢆ⟬ᐃࡋ࡚࠸ࡿࠋ ᖺ⌧ᅾ㸪௒ᚋ ᖺ௨ෆ࡟ 㹼㸣ࡢⓎ⏕☜⋡࡜ࡋ࡚࠸ࡿ㸦ᆅ㟈ㄪᰝ◊✲᥎㐍ᮏ㒊࣮࣒࣮࣍࣌ࢪ 㸱㸧㸧ࠋ⾲㸯 ୕㝣Ἀ໭㒊ࡢᆅ㟈㸦‫ڦ‬ᅛ᭷ᆅ㟈 ‫ࡢࡑ۔‬௚ࡢᆅ㟈 ‫ڸ‬ᮏㄽ࡛ᢅ࠺ᆅ㟈㸧Ⓨ⏕᪥0໭㡿ᇦ ༡㡿ᇦ ᪥ᮏ⿕ᐖᆅ㟈⥲ぴ 㸲㸧 ࡢグ㏙ ‫ڦ‬ඵᡞ㟈ᐖ࠶ࡾ㸪㟷᳃࣭௝ྎ↓⿕ᐖ㸪ὠἼ  ‫ڦ‬ඵᡞ࣭㟷᳃࣭㔝㎶ᆅ࣭⏣ྡ㒊࣭୐ᡞ㸪Ṛ  ₽  ‫ڦ‬ඵᡞ࣭㟷᳃㸪㟈ᐖᑡ࡞࠸㸪ὠἼ  ‫ڸ‬Ṛയ 㸪ᮌ㐀₽ 㸪ᐙᒇ◚ᦆ 㸪ඵᡞ࣭ᑠᆏ  ‫۔‬ඵᡞቨⴠୗ㸪ภ㤋↮✺◚ᦆ  ‫۔‬グ㏙࡞ࡋ 
 ‫۔‬ඵᡞ࡛ὠἼ  ‫۔‬㟷᳃࣭ᒾᡭ㺃ᒣᙧ┴࡟ࢃࡎ࠿࡞⿕ᐖ  ‫ڦ‬Ṛ⪅  ㈇യ 㸪඲ቯ  ༙ቯ 
 ‫۔‬ὠἼ FP ᮍ‶  ‫۔‬Ṛ⪅  ㈇യ 㸪ᘓ≀⿕ᐖ 㸪ᑠὠἼ 㸬 ᖺ㟷᳃┴ᮾ᪉Ἀᆅ㟈ࡢᴫせᮏᆅ㟈ࡢㅖඖࡣ᪥ᮏ⿕ᐖᆅ㟈⥲ぴ 㸲㸧 ࡟ࡼࢀࡤ㸪Ⓨ㟈᫬  ᖺ  ᭶  ᪥  ᫬  ศ㸪㟷᳃┴ᮾ᪉Ἀ㸪ᮾ⤒  ᗘ㸪໭⦋  ᗘ㸪0  ࡛㸪㟷᳃┴୕ᡞ㒆࡛⿕ᐖࡀ᭱኱࡛ୖ໭㒆ࡀࡇࢀ࡟ḟࡄ㸪⛅⏣┴࡛ࡣᑠᆏ࣭ẟ㤿ෆ࡛ᙉࡃ㸪ᒾᡭ┴࡛ࡣ஧ᡞ࣭஑ᡞ㒆ࡢ໭㒊ࡀᙉࡃ㸪኱᭦ᮧ㸪἟ᐑෆ㸪῰Ẹᮧࡢ⿕ᐖࢆᣲࡆ࡚࠸ࡿࠋ⿕ᐖศᕸࢆᅗ㸯࡟♧ࡍࠋ
'DPDJHLQ$NLWDDQG,ZDWHSUHIHFWXUHVGXHWRWKH(DVWRII$RPRULHDUWKTXDNHE\+LURVKL.DJDPLDQG7RVKLKLNR0L]XWD 8⿕ᐖ࠿ࡽぢࡓ
㟈ᗘศᕸ‫ە‬
‫۔‬
‫ۑ‬
‫ڹ‬


  ᪥ᮏ⿕ᐖᆅ㟈⥲ぴ㸲㸧࡟ࡼࡿ              㙾࿡  㸰㸧 ࡟ࡼࡿᅗ㸯  ᖺ㟷᳃┴ᮾ᪉Ἀᆅ㟈ࡢ⿕ᐖศᕸ㸬᪂⪺グ஦୧┴ࡢ௦⾲ⓗᆅ᪉⣬ࡢᒾᡭ᪥ሗ࣭⛅⏣㨥᪂ሗࡢ᪂⪺グ஦ࡣ୧┴❧ᅗ᭩㤋࡛㜀ぴ」෗ࡋ฼⏝ࡋࡓࠋᆅ㟈ࡢグ஦ࡣ  ᪥ᚋࡢ  ᭶  ௜ࡅࡢ⣬㠃࠿ࡽ⌧ࢀࡿࠋぢฟࡋࢆᩚ⌮ࡋ࡚⾲㸰࡟♧ࡍࠋ⾲㸰 ᪂⪺グ஦ぢฟ୍ぴ
᪥


㠃







㠃 ᒾᡭ᪥ሗ ‫۔‬᫖ᬡࡢᙉ㟈‫ྛ۔‬ᆅࡢ㟈ᐖ‫۔‬ᆅ㟈࡜➗ࡦヰ‫۔‬Ỷ㌴㐠㌿୰Ṇ ‫۔‬ภ㤋㟁ሗ‫۔‬ඵᡞ㟁ሗ ‫۔‬ᙜᕷ௨໭⃭㟈ูሗ‫ڸ‬ᆅ㟈࠙వ㟈ࠚ ‫۔‬ᆅ㟈⥆ሗ‫⚟۔‬ᓥ‫۔‬ᐑྂ‫▼۔‬ᕳ‫۔‬ᒣᙧ‫۔⏣⛅۔‬ภ㤋‫۔‬Ᏹ㒔ᐑ‫۔‬㟷᳃‫۔‬ᆅ㟈ほᐹ‫۔‬ᮏ┴ෆཬ㝃㏆ࡢヲሗࡣ  㠃࡟グࡍ࡭ࡋ ‫۔‬ᮏ┴ෆᆅ㟈వሗ‫ڸ‬ୗ㛢ఀ㒆ᒣ⏣ ‫ڸ‬Ẽ௝㒆┒㝃㏆‫ୖڸ‬㛢ఀ㒆㔩▼⏫‫ڸ‬࿴㈡㒆ἑෆᆅ᪉‫ڸ‬ᑠᆏ㖡ᒣ‫ڸ‬᫖᪥༗ᚋ㎾᥋ྲྀࡢሗ
 Ỷ㌴඲㏻ࡢᮅ
 ‫۔‬ᐑྂ ೃᡤሗ࿌ᆅ㟈ㄯ ‫۔‬㟷᳃┴㟈⅏⥆ሗ ‫۔‬ඵᡞᆅ㟈ㄯ



















‫۔‬Ỷ㌴඲㏻ᮇ‫۔‬㟷᳃┴㟈⅏⥆ሗ‫ڸ‬వ㟈⫼⛅⏣㨥᪂ሗ
‫୍ە‬᫖᪥ࡢᆅ㟈‫୍➨ڸ‬ᅇ┠ࡢᙉ㟈‫➨ڸ‬஧ᅇ┠ࡢᙉ㟈‫ە‬ᆅ㟈‫ە‬㟷᳃ภ㤋ࡢᆅ㟈











‫ە‬ᮾ໭኱ᆅ㟈ࠖ㸦᪥ᮏ㕲㐨◚ቯ㸧‫ە‬ᮾ໭ᆅ㟈ᴫほ‫⟶ە‬ෆᆅ㟈ᙡሗ‫ڸ‬኱᭤‫⯪ڸ‬㉺‫ڸ‬ส࿴㔝‫ڸ‬᳃ᓅ‫ڸ‬⬟௦‫ڸ‬ட⏣‫ڸ‬⡿ෆἑ‫ڸ‬㮚ᕢ‫ڸ‬ᡪ⏣‫ڸ‬஧ࢶ஭‫ڸ‬භ㒓‫ە‬ᡪ⏣ᆅ᪉࡟᪊ࡅࡿ㟈⅏9㸬⛅⏣࣭㟷᳃୧┴ࡢ⿕ᐖࡢࡲ࡜ࡵ ᕷ⏫ᮧู⿕ᐖ᪂⪺グ஦࡟⌧ࢀࡿ⿕ᐖ࡟㛵ࡍࡿグ஦ࢆᙜ᫬ࡢᕷ⏫ᮧู࡟ᩚ⌮ࡋ࡚⾲㸱࡟♧ࡍࠋᆅ㟈┤ᚋࡢ⿕ᐖㄪᰝሗ࿌࡟ụୖ 㸳㸧㸪㸴㸧 ࡀ࠶ࡾ୧┴ࡢ⿕ᐖࡶᥖࡆࡿࠋ⛅⏣┴࡛ࡣᑠᆏ㖔ᒣࡢ⿕ᐖࡢ࡯࠿㸪໭⛅⏣㒆ᡪ⏣⏫ࡢẸᐙࡢ⿕ᐖࡀሗࡌࡽࢀ࡚࠸ࡿࠋᒾᡭ┴ഃ࡛ࡣ㸪ᗈ࠸⠊ᅖࡢ⏫ᮧ࡛ᘓ≀⿕ᐖ㸪ၟရ⿕ᐖ࡞࡝ࡀሗࡌࡽࢀ࡚࠸ࡿࠋ┒ᒸᕷෆ࡛ࡣ⿕ᐖࡢ࡯࠿┒ࡾሙ࡛ࡢ≧ἣࡀሗࡌࡽࢀ࡚࠸ࡿࠋ
ᖺ୕㝣ὠἼᆅ㟈࠿ࡽࡢ᪥ࡶὸࡃ㸪ἢᓊ㒊ࡢ㔩▼࡞࡝࡛ࡢὠἼ㑊㞴ࡀሗࡌࡽࢀ࡚࠸ࡿࠋ┒ᒸᕷෆࡢ⿕ᐖࢆᅗ㸰࡟㸪ᒾᡭ┴࣭⛅⏣┴ࡢᕷ⏫ᮧู⿕ᐖࢆᅗ㸱࡟♧ࡍࠋ⾲㸱 ᕷ⏫ᮧู⿕ᐖ┴ 㒆ᒾ ┒ᒸᕷ
ᡭ
┴
ᒾᡭ㒆

ᪧᕷ⏫ᮧ
≴᳃
໭ᒣ
ඵᖭ⏫
἟ᐑෆ⏫
኱᭦ᮧ
஧ᡞ㒆
⚟ᒸ⏫
஑ᡞ㒆
ஂឿ⏫
㍍⡿ᮧ
ୗ㛢ఀ
ᐑྂ⏫
㔩▼⏫
ᑠᆏ⏫
⛅ 㮵ゅ㒆⏣ ໭⛅⏣㒆 ᡪ⏣⏫┴ ᒣᮏ㒆ᖖ┙ᮧ᪂⪺グ஦┘⊹↢⎰ሟட⿣ⴠୗ
ᮾ⚙ᑎ㛛๓⎰〇㐀ᡤ⎰⿕ᐖⰼ⾤ࡢ㞧㋃
㆙ᐹ⨫ቨⴠᖹᒇ  Ჷಽቯ
⚟ᒸ୰Ꮫᰯ஧㝵ቨⴠ㸪㓇⁄ὶ㸪ၟရ⿕ᐖ
㞧㈌㝡ჾᗑ⿕ᐖ
㞧㈌㝡ჾᗑ⿕ᐖ㞀ቨட⿣ὠἼ㑊㞴㸪㞧㈌㝡ჾᗑ⿕ᐖ኱↮✺ᢡᦆ㈇യ 㸪ᮏᒣ↮✺◚ᦆ㸪ᐙᒇቨⴠ
Ẹᐙቒⴠ 㸪ᅵⶶቨⴠ 
ᐙᒇഴᩳ

⌧ᕷ⏫ᮧ
┒ᒸᕷ

ᒾᡭ⏫
ඵᖭᖹᕷ
஧ᡞᕷ
ஂឿᕷ
㍍⡿⏫
ᐑྂᕷ
㔩▼ᕷ
ᑠᆏ⏫
኱㤋ᕷ
⬟௦ᕷ




ᅗ㸰 ┒ᒸᕷෆࡢ⿕ᐖ⟠ᡤ10‫ە‬ᑠ‖
‫ە‬ὸ⹸ ‫⊁ە‬ሙἑ‫ە‬㔝㎶ᆅ
㟷᳃‫ە ە‬㔝ෆ‫ە‬ᾆ⏫
‫ە‬எ౪

㸨 ୙㏻⟠ᡤ

‫ە‬἟ᓮ

㸨‫ྂە‬㛫ᮌ
㸨‫ە‬ୗ⏣㸨 ‫‖ە‬ᑼෆ‫ە ە‬ඵࣀᡞ㸨‫ە‬๢ྜྷ

ᑠᆏ⏫↮✺ᢡᦆ㈇യ 
ᐙᒇቨⴠ

㍍⡿ᮧ

‫ࣀ୕ە‬ᡞ

ᖖ┙ᮧ

ၟရ⿕ᐖ

ᐙᒇഴᩳ

኱᭦ᮧ
ᐙᒇಽቯ 

⚟ᒸ⏫
୰Ꮫቨⴠ
㓇⁄ὶ
ၟရ⿕ᐖ

ᡪ⏣⏫
ᐙᒇቨⴠ 
ᅵⶶቨⴠ 

ஂឿ⏫
ၟရ⿕ᐖ

἟ᐑෆ⏫
㆙ᐹ⨫ቨⴠ

ᐑྂ⏫
㞀ቨட⿣

┒ᒸᕷ
ᅗ㸰ཧ↷

㔩▼⏫
ၟရ⿕ᐖ
ὠἼ㑊㞴

ᅗ㸱 ᒾᡭ┴࣭⛅⏣┴ෆࡢ⿕ᐖ࡜᪥ᮏ㕲㐨⥺ࡢ୙㏻⟠ᡤ 㕲㐨ࡢ⿕ᐖᙜ᫬㸪ᮾ໭ᮏ⥺ࡣ⚾㕲ࡢ᪥ᮏ㕲㐨⥺࡜ࡋ࡚  ᖺ࡟㟷᳃ࡲ࡛ఙᘏࡋ࡚࠸ࡓࠋ⿕ᐖࡣ㟷᳃┴ෆ࡟㝈ࡽࢀࡓࡀ㸪ᙳ㡪ࡢ኱ࡁ࠸ᒾᡭ┴࡛ࡣ኱ࡁࡃሗ㐨ࡉࢀ࡚࠸ࡿࠋグ஦ࡢ౛ࢆᅗ㸲࡟♧ࡍࠋ


11


ᅗ㸲 㕲㐨⿕ᐖࡢ᪂⪺グ஦ࡢ౛㸦ᒾᡭ᪥ሗ  ᭶  ᪥  㠃㸧

㥐ྡ
୕ࣀᡞ
๢ྜྷ

ᑼෆ


ୗ⏣

ྂ㛫ᮌ

἟ᓮ

எ౪

㔝㎶ᆅ
⊁ሙἑ
ᑠ‖
ὸ⹸
㔝ෆ
ᾆ⏫

㟷᳃
ᑼෆ
ඵᡞ
‖

⾲㸲 㟷᳃┴ෆࡢ᪥ᮏ㕲㐨⥺ࡢ㥐࠾ࡼࡧ㥐㛫㊰⥺ࡢ⿕ᐖࡢ୍ぴ⌧㥐ྡ
୙㏻࣭᚟ᪧ᪥ ᮾዟ᪥ሗ᪂⪺グ஦ᒾᡭ᪥ሗ᪂⪺グ஦
୕ᡞ










ඵᡞ

ᶵ㛵ᗜ㸦↢⎰㐀㸧ࡣ኱◚ቯ㸪 ᶵ㛵ᗜᔂቯ㸪೵㌴ሙཬᙺᏯᒇ᰿ࡣⴠࡕᶵ㛵㌴  ྎࡣ◚ ኱◚ᦆࡏࡾ㸪▼Ⅳᗜࡶ኱◚ᦆ㸪♫Ꮿࡢ◚ᦆ᭱ࡶ⏒ࡋࡃ୰࡟ྜ
ᐟᡤࡣᲷᱱⴠࡕࡓࢀ࡝ࡶṚയ࡞ࡋ኱◚ᦆࡋ㧗⯓ᮧ㏆ഐࡢሐ㜵 ⥺㊰◚ᦆ  ࣨᡤ
㝗ⴠࡏࡾ


㈌≀ᗜࡣ⨯⅏ࡋࡑࡢ௚㥐ෆ ㈌≀ᗜᔂቯ㸪೵㌴ሙཬᙺᏯᘓ≀ࡢᦆᐖᑡ࡞࠿ࡽࡎ
኱◚


⥺㊰◚ᦆ  ࣨᡤ୕ἑ㥐⯋ከᑡࡢᦆᐖ
ᒇ᰿⎰ቨᔂቯ㸪❆◪Ꮚ◚ᦆ኱◚ᦆ⥺㊰◚ᦆ  ࣨᡤୖ໭⏫㥐⯋ከᑡࡢᦆᐖ
ቨⴠࡕ⥺㊰࡟ከᑡࡢᦆᐖከᑡᘓ≀࡟ᦆയ࠶ࡾ
⥺㊰࡟ከᑡࡢᦆᐖከᑡᘓ≀࡟ᦆയ࠶ࡾ
ᦆᐖᑡ࡞࠸
ᦆᐖᑡ࡞࠸
ᦆᐖᑡ࡞࠸ᘓ≀ࡣ኱ᴫቨட⿣ࡋཪࡣ๤ 
㞳ࡏࡾ
ᗫṆ

ᘓ≀ࡣ኱ᴫቨட⿣ࡋཪࡣ๤ 
㞳ࡏࡾ








ᮏ


೵㌴ሙཬᙺᏯ኱◚ᗫṆ೵㌴ሙཬᙺᏯ኱◚12㟷᳃┴ෆࡢ᪥ᮏ㕲㐨⥺ࡢ㥐࠾ࡼࡧ㥐㛫⥺㊰ࡢ⿕ᐖࡢ୍ぴࢆ⾲㸲࡟♧ࡍࠋᙜ᫬㸪㟷᳃┴ෆ࡟ࡣ༡ࡣ୕ࣀᡞ࠿ࡽ㟷᳃ࡲ࡛  㥐࠶ࡾ㸪⌧ᅾࡢࠕ㟷࠸᳃㕲㐨ࠖࡢ  㥐ࡢ༙ᩘ࡛࠶ࡿࠋ⌧ᅾࡢඵᡞ࣭
୕ἑ࣭ୖ໭⏫ࡣࡑࢀࡒࢀᑼෆ࣭ྂ㛫ᮌ࣭἟ᓮ࡛࠶ࡗࡓࠋᾆ⏫㥐ࡣ  ᖺࡢ」⥺㟁໬࡟క࠺࣮ࣝ
ࢺኚ᭦࡟ࡼࡾᗫṆ࡜࡞ࡗࡓࠋ㏵୰ᑼෆ࠿ࡽ㸪ඵᡞ㸦⌧㸸ᮏඵᡞ㸧ࢆ⤒࡚‖ࡲ࡛ࡢᨭ⥺ࡀ࠶ࡗࡓࠋ
‖㥐ࡣඵᡞ࡟᥋ࡋ࡚࠸ࡓࡀ  ᖺ᪑ᐈ㐠㌿୰Ṇ  ᖺ࡟ᗫ⥺࡜࡞ࡗࡓࠋᚋ࡟㛤㏻ࡢᅜ㕲ඵᡞ⥺ࡢ㝣ዟ‖࡜ࡣูࡢ㥐࡛࠶ࡿࠋ ᶵ㛵ᗜࡢ⿕ᐖࡣᑼෆ㥐࡛㸪㥐⯋ࡢ⿕ᐖࡣୗ⏣࣭ྂ㛫ᮌ࣭἟ᓮ࣭ඵࣀᡞ࣭‖࡞࡝ከࡃࡢ㥐࡛Ⓨ⏕ࡋ࡚࠸ࡿࠋ๢ྜྷ㸫἟ᓮ㛫࡛⥺㊰ࡢ⿕ᐖࡀ࠶ࡾ㸪」ᩘࡢ⟠ᡤ࡛୙㏻࡜࡞ࡗࡓࠋ๢ྜྷ̿ᑼෆ㸪ྂ㛫ᮌ̿἟ᓮ㛫ࡣ⩣᪥࡟㸪ୗ⏣̿ྂ㛫ᮌ㛫ࡣ  ᪥㸪ᑼෆ̿ୗ⏣㛫ࡣ  ᪥࡟᚟ᪧࡋ࡚࠸ࡿࠋ
㸬ࡲ࡜ࡵ
 ᖺ㟷᳃┴ᮾ᪉Ἀᆅ㟈ࡢᒾᡭ┴࣭⛅⏣┴ࡢ⿕ᐖ࡟ࡘ࠸࡚㸪ᙜ᫬ࡢᆅඖ᪂⪺ࢆ཰㞟ࡋグ㍕ࡉ
ࢀ࡚࠸ࡿ⿕ᐖࢆᩚ⌮ࡋࡓࠋᒾᡭ┴࡛ࡣ໭㒊ࡢᗈ࠸⠊ᅖ࡛㸪⛅⏣┴࡛ࡣ㮵ゅ㒆࡟⿕ᐖࡀ࠶ࡗࡓࡇ
࡜ࢆ᫂ࡽ࠿࡟ࡍࡿࡇ࡜ࡀ࡛ࡁࡓࠋ኱つᶍ࡞⿕ᐖᆅ㟈ࡢሙྜ㸪⿕ᐖ㞟୰ᆅ༊ࡢ⿕ᐖࡣヲ⣽࡟ㄪᰝࡀ㐍ࡵࡽࢀࡿࡀ㸪࿘㎶ࡢ⿕ᐖ࡟ࡘ࠸࡚ࡣྲྀࡾୖࡆࡽࢀࡿࡇ࡜ࡀᑡ࡞ࡃᛀࢀཤࡽࢀࡿࡇ࡜ࡀከ࠸ࠋ
㍍ᚤ࡛࠶ࡗ࡚ࡶ⅏ᐖᒚṔࡣᆅᇦ࡟࡜ࡗ࡚㈗㔜࡞㜵⅏᝟ሗ࡛࠶ࡿࡢ࡛ᚋୡ࡟ఏ࠼࡚࠾ࡁࡓ࠸ࠋཧ⪃ᩥ⊩㸯㸧㙾࿡ὒྐ㸸 ୕㝣Ἀ໭㒊㸦㟷᳃┴ඵᡞἈ㸧ࡢᆅ㟈ࡢ⿕ᐖ࡟㛵ࡍࡿᩥ⊩ㄪᰝ㸪᪥ᮏᘓ⠏Ꮫ఍ᢏ⾡ሗ࿌㞟㸪㸪㸪
㸰㸧㙾࿡ὒྐ㸸 ୕㝣Ἀ໭㒊㸦㟷᳃┴ඵᡞἈ㸧ࡢᆅ㟈ࡢ⿕ᐖ࡟㛵ࡍࡿᩥ⊩ㄪᰝ㸪᪥ᮏᘓ⠏Ꮫ఍ᢏ⾡ሗ࿌㞟㸪㸪㸪
㸱㸧ᆅ㟈ㄪᰝ◊✲᥎㐍ᮏ㒊࣮࣒࣮࣍࣌ࢪ㸪㟷᳃┴ᮾ᪉Ἀཬࡧᒾᡭ┴Ἀ໭㒊
KWWSVZZZMLVKLQJRMSUHJLRQDOBVHLVPLFLW\UVBNDLNRUVBDRPRULRNLBLZDWHRNL㸦 㜀ぴ㸧㸲㸧Ᏹబ⨾㱟ኵ࣭▼஭ᑑ࣭௒ᮧ㝯ṇ࣭Ṋᮧ㞞அ࣭ᯇᾆᚊᏊ㸸᪥ᮏ⿕ᐖᆅ㟈⥲ぴᮾி኱Ꮫฟ∧఍㸪㸪
㸳㸧ụୖ✄ྜྷ㸸ඵᡞᆅ᪉ࡢᙉ㟈㸪ᆅᏛ㞧ㄅ㸪㸪㸪㸴㸧ụୖ✄ྜྷ㸸ඵᡞᆅ᪉ࡢᙉ㟈㸦ᢎ๓㸧㸪ᆅᏛ㞧ㄅ㸪㸪㸪

東北地域災害科学研究

13

第58巻（2022）












!"##$%&'()*+,-./0123&(456*789(:;%&68'<=

.1>?6-2/$)@*7A.B2>C@D$EF

G'HI@J'<929(KL.M2NOKL*7APQ%&68'2$-R(2ST
2U@VA9(J'.<WX.92Y(Z[.\]^$- ` a  b

921$-.

cdefghYi(

321kl>[mknopqr$st%&

1$-  j%&R u,vw:;%&68'<xy $-.st

1XvwKLzL&'  u2{|}~$1k2k$7'(.2

Y\ 

(]_<

68'<

_.2KL-&6lC.

$2&2%-$J'<8'(.1k2{|-E1Xvw$(%&'EN$.2&22CY]
39$.

l861.mktY'2KY¢£¤Y:;_'<

-2)¥¦§±²

f»1-¼8<m1½2¾8Y¢_'¿%&68G8<!

R¥¨-©ª«d(2°(G?68'<­2g¬

68'K-

?62{|}~}¡$J¬_'<¦¨-­¥®

¯C.c³´1µY¶86-.·¸ª¹1$JC.º.1ÀpÁÂpÃ#$Ä]

68'm1½ÅÆ Y.WX$Ç
_

(@

\

_<

\^2 
-ÈÉ1



#

.2*ÊÈ

É1J'8-ËpÌÍ1$J'9(ÆK'<
-ÎH2Ï1
'<ÐÑÒ

2ÓÔ\

J

>'(.

]Õ-Ö%  2ËpÌÕ$JC.32X×ØÙ~ÚRÛÜ

ÝÞC×Yßà.ÕÖ  2áâÕ.Ù~ÚÕã% ä\ /22  !" #$ %#"""!&!'%!"%( !'#)( !"' #$  "*#%#  "$14 =$æç_'<xy $-ã%  =èé

$2  u,Y + (st8'<êYëì

6

ít

6î¿

 u2{|}~Y\ .

Eïðk-ñ , $J'9
('<"#$

/22¾8Y¢_'¿.ºf

ò8*óô1ÅIõö÷H\  2  #2øù

\ 
2m1½ÅÆY  - ` a  bKLõ`2 - a  b=$%ú6@L?

#(mk678- 

<  2m1½ÅÆ-ËpÌÍ1(%&68'
.ûü-ñ   $JC.2ûüñ   $J'2$.KGC»8
ý8

$J'<

-. a  b=$¥þÿ

2 ./ .32-õÿ2 ./  $J'<92$ð(G?

$J?

<Eh21

F86-.  $-âpoá



GK?

-

@

æ



p

1- 

../ . 

6$1kY4%ú'9($7
L2

Y\ 

\ å
9:

68'2$. 1
<3&

_<p

l²'st
1XvwKL u2{|}~- 0 KL 0 2$J'<  2ÇKLp21Çpnp$
J' /1  >CYî¿<32£¤Y

1³a:# KL52

(46\ 

_<\KL2-   >C@!t"*78<#$2ù%Y)&'()$î¿'(.  0-  0 (G?

<9

9$R (  -3&*&   (2
$J'<=.+2ª,-ñ 0 $J?

+2-.Yî¿'¿<.2 uKL%&6

8'  12ÇKL/ªkÇ20p1Á
23âá-Yî¿<62Ç2£¤Y\ 

456\ 2($7
2

1

15

\ $$7

124

_   $-8<&21$@_<;

, =ò_'.X;
8

_$-

68'<

\^>?- a  bô@g1A$B7\ å%& 1k2/ª  UÆp
1Á23âá<>- a  b21ô@g1N#R- a  b21¥NE#<

10#2@2$.CD2^$)*2$$- 0.  $- 0 $JC.#$2¾8-*7AG8<EN.?- - a  b¥NE$B7

10#2@2$.$- 0-.  $- 0 $JC.#$2¾8)@*78< 12ÇY4_'(. 

|*78<, WX2|*789(-.\  $456- , WX2
1F2{|G¤2HI(JL&'<- , =ò24à*78 9(KL.92k}~2¾8+
 

K

68'

2$JLM< a  b$-+@?(@&%8.  $ , =ò2|N*7

89(OP$JLM<%&'é21 #YQR$./  ST$mkY

<345 ÿ.60/XUÆ2à# ÍY  2V%ñ   2WôX½2Y(4Z7.]Ã^Ãk- 

2^Z
&(`

, (

.

_2

p

6.¥þÿ ./ / Yý86  UÆ2amkY W
nop

l>[[\2E

Y  DW<3, ]Ã^Ã$  Æ<pKL.2. )6b,Yî¿FKL1]=$2)*,2{|fgY_'2ë<]Õ   2ª,  u,-cd"eh$J'9(iL&68'<

EN$.uV   2b,% #-]Õ   2ª,  u, / #(·¸õÞh$J'9(jk"

iL&68'<39$.î¿b,KL % YlàmC.0$2{|

16

Y4
((@

<xy $ý8

_'9((

?KLõp

làm?

.] 

2Æno

h@Iqú6.\ rÆ²] mk2 %

6_








hYÇ_<$- % -  + $J'<

ò8  (   $-3&*&  -+R+ (
23&(¡G'R .  $-·¸õ2
h$JC.2 % }sGh(-tG8<=
1Y  -  -+ (]

?

uv

.









GK$

-)@,8<
%L

6./ªk2Mw 3 UÆ(XkUÆ(2Á23âá4Y\.amk2£¤(

 1$- 3 UÆ( 47 UÆ

_<Gl.992
2£¤Y>?$

6lC., =ò

3k@(õÞ , =ò

*7G¾8-xK?

<

yp3J'9('<  (   2yp
JC.|42h@ò8<>?6.

(õp2kYð_'1F-æç_'9('<}z-&68' % .k(@-.  -KL23&(òA{|ã8<  2Á23âá4-.3&W}22£¤(¡GC , KL , 2$ü8h(
G?68'<92k-.1k2k$J' , (K

68'(tq&'<% @B21(*7A¡G?6lC.92121Xvw-21Xvw(*7A¡
G'~%&'<Gl., =ò$(G?68'.9&-92kÁ23âá

68'

$-32

-

l86Xk2¿$J'<92-LK2c"Gki2HI(tq&'.

?68G8<()*2T"G@2$J'K./Y

6<32£¤.12-ºfe821A

(tq&'1J'9(ÆK?

l²'1(mk
45'(*78@22.õ

<+,:;2Mw1Ç24-.è*dOcd

h1°d2`(
@2$J'<1p@2Y$2[$6¡O(mkl>[32¡O-.YQ¿¢2  `£

d¤?

6¥?

<21Ç-KL¦§

Y¨²

<Ç

6©\Y_<-./0ª«¬E³­®1kÇe¯A

\ åmk2Xk(/ªk(2417/22]°â{|Rb1cd÷±xöR² ³R²  ´}ö´#R 
-R


6

pp¥g"°µ¶JG

2ST2-G·*78R  `  a  b6

3 -&_8¸32OP-¸R#&8++1110#$0"!09&+ ""!*(")++ 0#(R  `  a  b¹ºª«¬E` a  b»£

cdefgh212¼/22k}~RªU  `g¥g½¾  *d
Å1ÆÇr:;ÈR  R  jY¿sÀ^ËÁÂ3âcdÃÄ/-6÷É1AÊ1ËuÇÌªU  `  aÍW#6
ÎÏ+ÐÑÏ«ÒÓ½ÔEeÕ>'1½1FÆÖå ×ØØ^2vÙ(32ýR1cd÷Úå3"0 :&&0 R 6;<==.4/17 >:#&8++"0$$0)"09&+?$ # +9 +>11 >R  `  a  b¹ºÛÐ0a21Ük2=(¿1³a:#.
#&8++1110  09 0)"09&+>+@>+  +) $"+.  `  a  b¹º-^ÝÞ3âáÁ23âá

>'1k2{|}~PQ(32ëý.Úßd÷±xö.

3"0-+. .--#&8++"0"!)+ 0+9%90--0-A ÛÐYi'å8eàiá(32Üý.âãMú8. &.-- `6äåôæÏ«ÒÓçåèE-`éê¥NE12)*+,)*,

'1F}~2PQRbÒÙd÷vwë±x:;öR3"0R&&0 àL&R--0ìíî®Rª«¬Eo°pu2b,KL1F2ª,  u,Yïðst_'N)2¦ñRÚßd÷±xöR + ´:R`a東北地域災害科学研究

19

第58巻（2022）








ÐĲŀ×]cÏſ]ÜŜ]ŊÑ©fƥć¼]ĮƦ]
·ŢąƥP^SB>CUT^EƦ]zªƥ¼]ĮƦ]¼°ĿÀƥć¼³ƜłƧ¼]ĮƦ]ËŤēŪ]Ĳójƥã¼]ĮÔƦ]ÏctÀƥ¤Í¼]įºƦ]ĪÌġƥi¼ƒĨłƦ]ĈÒ~ƥeÓ¼]ĮƦ]ąÉƥƣ

Ò¼ÂƦ] Ýć³ý½ÜĞĚ³ƜŕìŰĤAY^Nƨ -3* ÆµľcƎ

ÏçľƎŅÒľƎ*%,Ɵ¶-ƧƏĴàŗüÎÚƧŅÒĺ³ŬŘüÎÚƧťüÎÚ)(,üÎÚūƙ*Ù%9%9ŧĭÏ5§¿Ï)(,ĦÏ4Ù_ý&Ƨ³Ɯğ-ć³ý,l³¶*Ė09'sż&ţ'4ś9'Ƨ)ĮŲ):%9'-ų)

9Ƨ³ƜŰĤŔĖƄĹ,¹¡Èá,ƢŰĤ<ũ'&êË³Ɯğ,òö<ũƧğüÎ',ÊëƑy)(<ċŵ9'-Č3%ăı
&9w.Ƨ¢Ć]lƥ

Ʀ-nØmƇ&,ŝĀ³ƜŰĤ<ũƧƏĴàüÎÚ,aĻ&ğķ)³Ɯğķİ%9'<Ů!

:1&ŰĤ]ĮŲñŨ"#!Ɵ¶,å'%ƧÆµľcƎ*%ŝĀ³ƜŰĤŔ<ú!

ÏçľƎ

ŅÒľƎ



ĆŇ&-ŰĤ,ß¸*$%ƈ09ƨ ŰĤčŭ¯  Ćłŉ&Åþ!ŰĤĩ,Ù Ë)ħš«ű-:o»,ÄÛ]ŝĀŰĤĩ
<ńƀŗ-ğüÎƧƀ`ű-ğĦÏ<ńĆŇ&-«ű&®#!Ō®*$

%ī*ċŵ<ũ#!

šm,d-ėžÞ_Ɯĥƥ  <ńƧš-Ģ<Ƨ¼-RA
LFV^K*Êë9ŰĤĩƐƗ-Ƨ³ƜķİÎ,ƥŏ'u%ŏ

-/ ņá'!

-/Ʀ<śïƧÿŷ,ÄÛŰĤŔ]ŝĀŰĤŔ

³ƜŴ- ; ) ; ,Ł¨Ą³ƜŴ<vı%9 I^E-÷ÚƛŸ¬ŗ<ı!
(/214$.5(,5/,&1%5(48$6,10,06+(&(064$.5176+(402$46 1)1+1-7 ,564,&6%:1/1/,-$'$$-$5+,
$-$:$/$$615+,,4$+$4$$;7:$$6(,9$+,*(-,14,7&+,(,$657/$6$$-1+;101$5$+,41157*$ $-761 $('$ "15+,-1 "$/$0$-$ ,415+, $6$1 $-(5+, $6575+,/$ ,415+, "$-,9$4$ $0'
4172)146+($)6(45+1&-1%5(48$6,101)6+(1))6+($&,),&&1$561)1+1-7($46+37$-(20

HZT^Eýâ*68pƉ:%9é7:!ƍœĝçI^E<ÄÛ³ƜŰĤŔ5l,ŝĀŰĤĩ'¡;%ƧŞĮ*68Ƨ³Ɯ,£ÄƧƜĥęÄ<ũ)#!

ƨ ŐĉÝ  Ă ŰĤŔ,ŷŚč+ÃgƧŞĮ,ùŠ4Ãg!Ƨ
ĄƐ*$%ƧƜĥęÄŐĉ)(,Ńź<ũ)#!

¯Ý.1&,
*ŰĤ:!³Ɯ,w<ń¯  ŰĤ:!³Ɯ,w ĝç<b7ƜƤ  ĝ] ĝ,Ż2

¾Ɓƚƞ*ń8):!ĝçƥŰĤĩƦ   &ń
:9ŰĤĩĆŇ*69ŰĤĩ&9 ƜĥÙ 
Ćłŉ&Åþ!ŝĀŰĤ6/ŞĮ*68£Ä:!>O\J<ŃźƧėžÞ_Ɯĥ@E[A*Ŷƅ:%)³Ɯ<Ńź! :7-ƧťüÎmƇ5ƏĴàŗüÎÚ^ŅÒĺ³ŬŘüÎÚ,6ŬƥaĻƦ,lƧ:7,Ɛ,Ɵ¶ƥÆµľƎƧdĊĴmƇƦ*4Ů7:9

 ³ Ɯ , Ɯ ¾  Ù ƥ

¯

 

  ÕŞĮƥ·]l )(Ʀ&é7:!Ɯĥ<ļů&ơ!4, ¯&ńėžÞ_Ɯĥ@E[A*¦1:9³Ɯ
o»*4³Ɯ<Ńź9'&!

Ƭ³Ɯƭš-ĢƧ¼-RA
LFV^K<ńƬĆłŉ,ŝĀŰĤĩ

ËƬ:o»,ŰĤĩ



bƬ:
Ù







:,RALFV^KƠá

21 T @LDSŲĆłŉ&Åþ!ŝĀŰĤ6/ŞĮ*68ƧÊžƟ¶&T@LDSŲ<õÄ!ƥ¯ Ʀ ýĜ- $4'(%(&-$0'+($4(4 &9 Đ:´)

ƊüÎ´&  Ƃ-ćŬ1!-Ŭćý
¥')9ć³ýƕƎ&,ë¹-w.Ƨ
"15+,'$(6$.

*68Ńź:%8Ƨ_ş*ā¼ĘÜ±řƂćŬ1!-Ŭćý¥&9ƊüÎ)Đ:üÎ

´,ë¹&

9č+,¥<øô

9 _ýƧaÏ³-ā¼ĘÜ±řƂý¥&9ƊüÎ)Đ:üÎ

´,ë¹ƧƓĔƖÏ³&-ēüÎ´,ë¹Ńź:%9Ƨ£ä*rŚ9æŹƟ¶*%-,6)Ķ)9¥Ńź:)#!

 ³ƜĝƋáĎƌ ¯  Ćłŉ/:1&,ŝĀŰĤ<ı ÊžƟ¶*%Ƨ³ƜĝƋáJUAW

ęÄ!T@LDSŲ/  Ƃ,Ù



M=#+$1(6$.   <ũ#!ƥ¯ Ʀ ĄƐ-9ĄĎƌ- -$'$(6$.

-

Ă

&

9

Ý

ÝćĚ³ƜķİoƔ&-/ 68Ġ³Ɯ&

9

Ģ



Ý  Ă*ķİ!  {,³Ɯ<vı!

Ćłŉ&Åþ!ŝĀŰĤ,I^E<ı9'&ÊžƟ¶,Ųáa9

'Ńź&!ƥ¯ Ʀ hĹ)ðĉ'%Ƨw. -$'$(6$.
ásƋá¶Ů":%9

*68ƧüÎÚĢƎ5Ɯĥ¶mƇ*³ƜĝƋƩƦƏĴàŗüÎÚ6/ŅÒĺ³ŬŘüÎÚ*ě#%Ƨ

aƎ]bƎ³ĕ*³ƜĝƋásƋáĶÛÙ9ƧƪƦŧĭÏ5§¿Ï,Ľb,ĢƎs¨ĝ³ƜƜĥ¶mƇ*-RARxőŎ*Êë9'ś7:9³ƜĝsƋá¶Á²9Ƨ'é7:%9 k¬,ÅI^E&4£ď,¥<é9'&!ƥ¯ƫƦ kèƧI^E,Ŧň*qƧƋáĎƌ,ùŠ<ũhÄ&9
1'3

ÆµľcƎ

ÏçľƎ

ŅÒľƎ*%,Ɵ¶-ƧƏĴàŗüÎÚƧŅÒĺ³ŬŘüÎÚƧťüÎÚ)(,üÎÚūƙ*Ù%9
ŰĤŔ<ĎōƧ,ăí*$%Ńź!

Ćłŉ&-ƧæŹƟ¶*9³Ɯ

³Ɯğás!3ƧkèŰĤ<ŒœƧ

22I^E<ŦňƧ,³¶,³Ɯğ',ŭ­<ũhÄ&

9ī*³Ɯğás­*$%ċŵ

¯  JUAWM=*ı!
Ɯĥ]ŰĤĩÙ ŖƝ-:Ģ

-/ 68ĠĢ

³Ɯ<ń

ħš«ű-Ć

:łŉ*69ŰĤĩƧĸ«ű:o»,ÄÛ]ŝĀŰĤĩ<ń

! -vı!AXG

K<ń

AXGK-Ģý¥*- -/ ƐƗ'!







¯  F?G@^Q^KHCJ,ĖƄ<ń
,|<ń

ÕƬŝĀĩ)ƧƬĢ -/ *9  ĝƋá}Ö

8,¹¡<ńŽƆĆłŉ-ĨÇƃģ,!3,³ƜĦÏŰĤłŉŴĵƥŋƪĒƦ,_į'%Åþ%1!ƧŰĤ*Ƙ!"!

{j]ƑyđƑ*îŽĳa1



1

23


¯  ÅI^E*69Ģ -/ *9Ƨ ĝƋá}ÖƥÕƦ] ĝƋá}ÖƥƦ ƏĴàŗüÎÚƥƦƧŅÒĺ³ŬŘüÎÚƥƦƧťüÎÚƥƦ
 5  ,aĻƥŬƦ,`ű&ńĦÏ,mƇ*sƋá¶Ńź&9 &®1:!Ɵ¶&4sƋá¶Ńź&9













û Ĭ

(9+,),*2#/,(9,9!  ,>,;/6+-69,;,940505.09:;
6;0656*(3,*/(50:4:<33#,0:463#6*4   A /;;7:+6069.      ]Rpruoen  [C_zDE^XGISvWF[sUSvJKLMHz[~  A
2(+($(;:<@(>($%4056&6:/0+((:,.(>(
$(2(/(:/0&(4(+($6:<.($(2,+($(;6.(9(:/0$ )(9(#(2(0##(0.(0+(2($>(:(20$09(;($:<4<9(&(4(5(2(&$,9(2(>($(2(40*/0 2<+($
6902(>(#(;(60<9($<)6(;:<:/04($6;60?(4(*/0  ?76*,5;,940.9(;065(5+*9<:;(3:,0:40*
=,36*0;?+0:;90)<;0656):,9=,+-69;/,053(5+,(9;/8<(2,:>(94:
05+<*,+)?;/,  $6/62< 20,(9;/8<(2,05(7(504730*(;065:24-69*9<:;(3-3<0++0:;90)<;065(5+*9<:;(37,94,()030;?,6-3<0+: A /;;7:+6069. 
.-3




&6:/0+((:,.(>( 2(+($  #7(;0(3=(90(;0656-:;9,::
690,5;(;065:05(7(59,=,(3,+)?+,5:,:,0:40*6):,9=(;065:
$,*;6567/?:0*: A  A /;;7:+6069.   1;,*;6    
YqZwRx{fPma`}kZgx{cVNj yBT
hldb\|O QHic[tU[~   A '/(6(:,.(>(690<*/0#  $646.9(7/0*04(.05.6-!(5+#>(=,=,36*0;?:;9<*;<9,),5,(;/569;/,(:;,95(7(5,67/?:
",: /;;7:+6069.     東北地域災害科学研究25

第58巻（2022）୰ᑠᆅ㟈ࡢ◚ቯఏ᧛ᣦྥᛶ࡜ᛂຊ㝆ୗ㔞㸫 ᮾ໭Ἀᆅ㟈ᚋ࡟άⓎ໬ࡋࡓ⚟ᓥ-Ⲉᇛ┴ቃࡢᆅ㟈άືࡢゎᯒ 㸫 *ᮾ ໭኱Ꮫ ụ⏣㔛ዉ㸪ྜྷ⏣ᆂభ㸪ᯇ⃝ᬸࡣࡌࡵ࡟
ᆅ㟈ࡣᆅẆෆ࡛ቑຍࡋࡓ೫ᕪᛂຊ࣭ṍ࢚ࢿࣝࢠ࣮ࢆゎᾘࡍࡿ⮬↛⌧㇟࡛࠶ࡿࠋᆅ㟈๓ᚋ࡛ࡢ᩿ᒙ㠃ୖࡢࡏࢇ᩿ᛂຊࡢῶᑡ㔞ࢆᛂຊ㝆ୗ㔞࡜࿧ࡪࠋᛂຊ㝆ୗ㔞ࡣ㸪ᆅ㟈◚ቯࢆグ㏙ࡍࡿࡓࡵࡢᇶ♏ⓗ࡞ࣃ࣓࣮ࣛࢱ࡜ࡋ࡚ᗈࡃ⏝࠸ࡽࢀࡿ࡜࡜ࡶ࡟㸪ᆅ㟈࡟ࡼࡿ㧗࿘Ἴᨺᑕ࢚ࢿࣝࢠ࣮ࡢ
኱ࡁࡉࡢᣦᶆ࡜ࡋ࡚ࡶὀ┠ࡉࢀ࡚ࡁࡓ (e.g., Boore, 1983)ࠋ
㏻ᖖ㸪୰ᑠᆅ㟈ࡢᛂຊ㝆ୗ㔞ࡣ㸪෇ᙧ᩿ᒙࡢᑐ⛠◚ቯࢆ௬ᐃࡋࡓࣔࢹࣝ (௨㝆㸪ᑐ㇟◚ቯࣔࢹࣝࠋ౛࠼ࡤ㸪Brune 1970; Sato & Hirasawa, 1973) ࡟ᇶ࡙ࡁ㸪◚ቯ⥅⥆᫬㛫࡜ᆅ㟈࣮࣓ࣔࣥࢺ
࠿ࡽ᥎ᐃࡉࢀ࡚࠸ࡿࠋᑐ⛠◚ቯࣔࢹ࡛ࣝࡣ㸪ほࡉࢀࡿ◚ቯ⥅⥆᫬㛫࡟ࡣᙉ࠸᪉ྥ౫Ꮡࡣ⏕ࡌ࡞࠸ࡇ࡜࡟࡞ࡿࠋ୍᪉㸪ᐇ㝿ࡢ◚ቯࡀ㠀ᑐ⛠࡛࠶ࡿሙྜ㸪ྛほⅬ࡛ほࡉࢀࡿࠕࡳ࠿ࡅࡢ◚ቯ⥅⥆᫬㛫ࠖࡣᙉ࠸᪉ྥ౫Ꮡᛶࢆᣢࡘࡇ࡜࡟࡞ࡿ (e.g., Ben-Menahem, 1962)ࠋ◚ቯఏ᧛ᣦྥᛶ
(rupture directivity) ࡣ㸪ࡳ࠿ࡅࡢ◚ቯ⥅⥆᫬㛫ࡔࡅ࡛ࡣ࡞ࡃᆅ㟈ືࡢ኱ࡁࡉ࡟ࡶᙳ㡪ࢆ୚࠼ࡿࠋࡑࡢຠᯝࡣ≉࡟ S Ἴ࡟ᑐࡋ࡚๻ⓗ࡛࠶ࡾ㸪◚ቯఏ᧛ᣦྥᛶࡣᆅ㟈ືࡢ⌮ゎࡢࡓࡵ࡟ᛂຊ
㝆ୗ㔞࡜࡜ࡶ࡟㔜せ࡞㔞࡛࠶ࡿ࡜࠸࠼ࡿࠋ
ࡇࢀࡲ࡛㸪୰ᑠᆅ㟈ࡢゎᯒ࡛ࡣ㸪◚ቯఏ᧛ᣦྥᛶࡢᏑᅾࢆ↓どࡋ㸪ᑐ⛠◚ቯࣔࢹࣝࢆ௬ᐃ
ࡍࡿࡇ࡜ࡀṤ࡝࡛࠶ࡗࡓࡀ (Abercrombie, 2021)㸪ࡇࡢ௬ᐃࡀㄗࡗ࡚࠸ࡓሙྜ㸪ᛂຊ㝆ୗ㔞ࡢ᥎ᐃ್࡟ࡶ኱ࡁ࡞ㄗᕪࡀຍࢃࡿࡇ࡜࡟࡞ࡿࠋ
ᮏ◊✲࡛ࡣ㸪୰ᑠᆅ㟈ࡢ◚ቯఏ᧛ᣦྥᛶࡢᵝ(a)  (b)Ꮚࢆㄪ࡭ࡿࠋ⚟ᓥ㸫Ⲉᇛ┴ቃ࿘㎶ࡢᆅ㟈άືࢆゎᯒᑐ㇟࡜ࡋࡓ (ᅗ 1)ࠋࡇࡢᆅᇦ࡛ࡣ㸪2011 ᖺ 3 ᭶ 11 ᪥ࡢᮾ໭ᆅ᪉ኴᖹὒἈᆅ㟈ᚋ࠿ࡽ㠀ᖖ࡟άⓎ࡟ṇ᩿ᒙᆅ㟈ࡀⓎ⏕ࡋ࡚࠾ࡾ㸪4 ᭶ 11 ᪥࡟ࡣ MJMA7.0 ࡢᆅ㟈ࡶⓎ⏕ࡋ࡚࠸ࡿ (ᅗ 1a ࡢᫍ༳)ࠋ
㸰. ࢹ࣮ࢱ࡜ᡭἲ
⚟ᓥ㸫Ⲉᇛ┴ቃ࿘㎶࡛ 2011 ᖺ 3 ᭶ 11 ᪥࠿ࡽ 2018 ᖺ 10 ᭶ 31 ᪥ࡲ࡛࡟Ⓨ⏕ࡋࡓᆅ㟈ࡢ࠺ࡕ㸪F-net ࡟ࡼࡾ࣓࢝ࢽࢬ࣒ゎࡀ᥎ᐃࡉࢀ࡚࠸ࡿ 348 ಶࡢᆅ㟈ࡢゎᯒࢆ⾜ࡗࡓࠋ㟈※ࡢ῝ࡉࡣ 40 km ௨ὸ࡛࠶

ᅗ 1 (a) ゎᯒᑐ㇟ᇦ (㟷ᯟ)࡜ 2011 ᖺ⚟ᓥ┴὾㏻ࡾࡢ M7 ᆅ㟈ࡢ㟈ኸ (ᫍ༳)ࠋ (b) ᑐ㇟ᆅ㟈ࡢ㟈ኸ (㟷୸)࡜ほ Ⅼࡢ఩⨨ (㉥୕ゅ)*Simultaneous estimation of stress drop and rupture directivity of small earthquakes near the FukushimaIbaraki border by Rina Ikeda, Keisuke Yoshida, Toru Matsuzawa

26ࡾ㸪ᆅ㟈ࡢつᶍࡣ 3.3ӌMwӌ5.2 ࡛࠶ࡿࠋᅗ 2 ࡟ᑐ㇟ᆅ㟈ࡢ㟈ኸ (㟷୸) ࡜㸪౑⏝ࡋࡓほⅬࡢ఩⨨ (㉥୕ゅ) ࢆ♧ࡍࠋ
2.1 ᆅ㟈◚ቯࣔࢹࣝ㠀ᑐ⛠◚ቯࢆ⪃៖ࡋࡓࣔࢹࣝ࡜ࡋ࡚㸪Dong & Papageorgiou(2003) ࢆ⏝࠸ࡓ (௨㝆㸪୍⯡◚ቯࣔࢹࣝ)ࠋࡇࡢࣔࢹࣝࡣ㸪Sato& Hirasawa (1973) ࡢ෇ᙧᑐ⛠◚ቯࣔࢹࣝࢆᣑᙇࡋࡓࡶࡢ࡛㸪ᴃ෇ᙧ᩿ᒙࡸ㠀ᑐ⛠◚ቯࡶ⪃៖࡛ࡁࡿࠋ◚ቯࡣᴃ෇ୖࡢ௵ពࡢ
Ⅼ CN ࡛㛤ጞࡋ㸪ᴃ෇୰ᚰࡀ C0 ࡟ྥ࠿ࡗ୍࡚ᐃ㏿ᗘ࡛⛣ືࡋ࡚࠸ࡃࠋᴃ෇ᙧࡢ◚ቯࣇࣟࣥࢺࡶ୍ᐃ࣮ࣞࢺ࡛ᣑ኱ࡋ࡚࠸
ࡃࠋࡇࡢࣔࢹࣝ࡟ᑐࡋ࡚ࡣ㸪௵ពࡢほᅗ 2 ୍⯡◚ቯࣔࢹࣝࡢᴫ␎ᅗࠋ
CN ࡣ◚ቯࡢ㛤ጞⅬ㸪C0 ࡣᴃ෇ࡢ୰ᚰⅬ࡛ࡢࡳ࠿ࡅࡢ㟈※᫬㛫㛵ᩘࡢゎᯒゎࡀᚓࡽࢀ࡚࠸ࡿࠋ௒ᅇࡣ (1) ◚ቯࡢ㛤ጞⅬ CN ࡀᴃ෇ࡢ↔Ⅼ࡟఩⨨ࡍࡿ(Savage, 1966)㸪(2) ᴃ෇ࣇࣟࣥࢺࡀ㛗㍈᪉ྥ࡟ᣑ኱ࡍࡿ㏿ࡉ ‫ݒ‬௥ ࡀ S Ἴ㏿ᗘ ‫ݒ‬௦ ࡜ ‫ݒ‬௥ Ȁ‫ݒ‬௦ ൌ ͲǤͻࡢ㛵ಀࢆ‶ࡓࡍ࡜࠸࠺ᣊ᮰᮲௳ࡶ୚࠼ࡓࠋ
2.2 㟈※᫬㛫㛵ᩘ࡜ࢥ࣮ࢼ࣮࿘Ἴᩘࡢ᥎ᐃ
୰ᑠᆅ㟈ࡢ◚ቯఏ᧛ᣦྥᛶࢆㄪ࡭ࡿࡓࡵ࡟㸪ྛほⅬ࡛ࡳ࠿ࡅࡢ㟈※᫬㛫㛵ᩘࢆồࡵࡓࠋලయⓗ࡞᪉ἲࡣ㸪Yoshida (2019), Yoshida et al. (2019) ࡜ྠᵝ࡛࠶ࡾ㸪ᆅ㟈ࡢ S ἼἼᙧࢆ⏝࠸ࡓࠋᑐ㇟ᆅ㟈ࡢ㏆ഐ࡛Ⓨ⏕ࡋࡓᑠᆅ㟈ࡢἼᙧࢆ⤒㦂ⓗࢢ࣮ࣜࣥ㛵ᩘ࡜ࡋ࡚⏝࠸࡚㸪
deconvolution ࡟ࡼࡾ㸪ᑐ㇟ᆅ㟈ࡢࡳ࠿ࡅࡢ㟈※᫬㛫㛵ᩘࢆ᥎ᐃࡋࡓࠋDeconvolution ࡟ࡣ㸪Kikuchi & Kanamori (1982) ࡢᡭἲࢆ⏝࠸ࡓࠋᚓࡽࢀࡓࡳ࠿ࡅࡢ㟈※᫬㛫㛵ᩘ࡜⤒㦂ⓗࢢ࣮ࣜࣥ㛵ᩘࡢ convolution Ἴᙧ࡟ࡼࡾ㸪ᑐ㇟ᆅ㟈ࡢἼᙧࢆ᚟ඖ⋡ࡀ 80 %௨ୖ෌⌧࡛ࡁࡓࡶࡢࡢࡳࢆಙ
㢗ᛶࡢ࠶ࡿ⤖ᯝ࡜ࡋ࡚᥇⏝ࡋ㸪ࡑࢀࡀ 15 ほⅬ௨ୖ࡛ᚓࡽࢀࡓᆅ㟈ࢆゎᯒᑐ㇟࡜ࡋࡓࠋᚓࡽ

ࢀࡓࡳ࠿ࡅࡢ㟈※᫬㛫㛵ᩘࡢࡑࢀࡒࢀ࡟ᑐࡋ㸪 Andrews (1986) ࡟ࡼࡾᐃ⩏ࡉࢀࡓࢥ࣮ࢼ࣮࿘
Ἴᩘࢆ᫬㛫㡿ᇦ࡛ồࡵࡓࠋ
2.3 ࣔࢹ࣭ࣝࣃ࣓࣮ࣛࢱࡢ᥎ᐃ
ᚓࡽࢀࡓࢥ࣮ࢼ࣮࿘Ἴᩘ࡜ࡑࡢ᪉ྥ౫Ꮡᛶ࠿ࡽ㸪ࣔࢹ࣭ࣝࣃ࣓࣮ࣛࢱࡢ᥎ᐃࢆ⾜ࡗࡓࠋᴃ෇᩿ᒙࡢ㛗㍈ ܽ଴ 㸪ᴃ෇⋡ ܾ଴ Ȁܽ଴ ࠾ࡼࡧ◚ቯࡢ㐍ᒎ᪉ྥ߮଴ࢆࢢࣜࢵࢻࢧ࣮ࢳࡋ࡚ほࡉࢀࡓࢥ࣮ࢼ࣮࿘Ἴᩘࢆ᭱ࡶⰋࡃㄝ᫂ࡍࡿࣃ࣓࣮ࣛࢱࢆồࡵࡓࠋࣇ࢕ࢵࢸ࢕ࣥࢢࡢ㝿࡟ࡣ㸪ࢥ࣮ࢼ࣮࿘
Ἴᩘࡢᖹᆒ஧஌ṧᕪ௡ଶ            ൌ ෍൫݂ୡ ୫୭ୢୣ୪ െ ݂ୡ ௜ ൯ ൗ݊             ሺͳሻ௜ୀଵࡀ᭱ᑠ࡜࡞ࡿࡼ࠺࡟ࡋࡓࠋࡇࡇ࡛ ݂ୡ ୫୭ୢୣ୪ࡣࢥ࣮ࢼ࣮࿘Ἴᩘࡢ⌮ㄽ್㸪݂ୡ ௜ ࡣྛほⅬࡢࢥ࣮ࢼ࣮࿘Ἴᩘ㸪݊ࡣࢹ࣮ࢱᩘ࡛࠶ࡿࠋᚓࡽࢀࡓṧᕪࢆ⏝࠸࡚㸪㉥ụ᝟ሗ㔞ᇶ‽ (AIC; Akaike, 1974)࡟ᇶ࡙ࡁ୍⯡◚ቯࣔࢹࣝ࡜ᑐ⛠◚ቯࣔࢹࣝ (ܽ଴ ൌ ܾ଴ ) ࡢẚ㍑ࢆ⾜ࡗࡓࠋ  ൌ ݊   െ݊൅ ʹ݉ ൅ ݊  ʹɎ
ʹ

ሺʹሻ

27

݉ࡣࣔࢹࣝࡢ⮬⏤ᗘ࡛࠶ࡿࠋ☜⋡ศᕸࡀṇつศᕸ࡟ᚑ࠺ࡇ࡜ࢆ௬ᐃࡋࡓࠋAIC ࡣ㸪ࡑࡢ್ࡀᑠ
ࡉ࠸ࣔࢹࣝࡢ᪉ࡀඃ఩࡛࠶ࡿࡇ࡜ࢆ♧ࡍᣦᶆ࡜ࡋ࡚⏝࠸ࡿࡇ࡜ࡀ࡛ࡁࡿࠋᮏ◊✲࡛ࡣᑐ⛠◚ቯࣔࢹࣝࡢ AIC ࠿ࡽ୍⯡◚ቯࣔࢹࣝࡢ AIC ࢆᘬ࠸ࡓ್ǼAIC ࢆ⏝࠸࡚ࣔࢹࣝࡢẚ㍑ࢆ⾜ࡗࡓࠋゎᯒ⤖ᯝࡢ౛ࢆ♧ࡍࠋ1 ࡘ┠ࡢ౛ࡣ 2011 ᖺ 4 ᭶ 8 ᪥࡟Ⓨ⏕ࡋࡓ Mw 4.0 ࡢᆅ㟈࡛࠶ࡿࠋᅗ
3(a) ࡣࡳ࠿ࡅࡢ㟈※᫬㛫㛵ᩘࢆほⅬࡢ᪉఩࡟ᇶ࡙ࡁ୪࡭ࡓࡶࡢ࡛࠶ࡿࠋ180-270r(༡す᪉ྥ) ࡛ࣃࣝࢫࡢ⥅⥆᫬㛫ࡀ▷࠸ഴྥ࡟࠶ࡿࡇ࡜࠿ࡽ㸪◚ቯࡀ༡す᪉ྥ࡟ఏ᧛ࡋࡓࡇ࡜ࡀ♧၀ࡉࢀࡿࠋᅗ 3(b) ࡣ㸪ࢥ࣮ࢼ࣮࿘Ἴᩘࡢほ್࡜ࣔࢹࣝ࡟ࡼࡿ⌮ㄽ್ࢆẚ㍑ࡋ࡚࠸ࡿࠋほ್(㯮୸)ࡣ㸪ᑐ⛠◚ቯࣔࢹ࡛ࣝィ⟬ࡉࢀࡓ⌮ㄽ್ (⅊Ⰽ⥺) ࡼࡾࡶ㸪୍⯡◚ቯࣔࢹ࡛ࣝィ⟬ࡉࢀࡓ⌮ㄽ್ (㉥⥺) ࡟Ⰻࡃྜ࠺ഴྥࡀぢࡽࢀࡿࠋǼAIC ࡣ 82.8 ࡛㸪ᑐ⛠◚ቯࣔࢹࣝࡼࡾࡶ୍⯡◚ቯࣔࢹࣝࡢ᪉ࡀඃ఩࡛࠶ࡗࡓࠋ
(a)

(b)

ᅗ 3 (a) ࡳ࠿ࡅࡢ㟈※᫬㛫㛵ᩘࡢ᪉఩౫Ꮡࡢ౛ࠋ(b) ⌮ㄽ࡜ほࡢࢥ࣮ࢼ࣮࿘Ἴᩘࡢẚ㍑ࠋ 㯮୸㸸ほ್㸪㉥⥺㸸୍⯡◚ቯࣔࢹࣝࡢ⌮ㄽ್㸪⅊Ⰽ⥺㸸ᑐ⛠◚ቯࡢሙྜࡢ⌮ㄽ್ࠋ

ᅗ 4 ࡟㸪ǼAIC ࡀప࠸ሙྜࡢ౛࡜ࡋ࡚㸪2011 ᖺ 5 ᭶ 5 ᪥࡟Ⓨ⏕ࡋࡓ Mw 4.4 ࡢᆅ㟈ࡢ⤖ᯝࢆ♧ࡍࠋࡳ࠿ࡅࡢ㟈※᫬㛫㛵ᩘ࡟㢧ⴭ࡞᪉ྥ౫Ꮡࡀぢࡽࢀ࡚࠸ࡿࡢ࡟ࡶᣊࢃࡽࡎ㸪ǼAIC ࡣ -4࡛㸪୍⯡◚ቯࣔࢹࣝࡼࡾࡶᑐ⛠◚ቯࣔࢹࣝࡢ᪉ࡀඃ఩࡜࡞ࡗ࡚࠸ࡿࠋࡇࡢᆅ㟈ࡢሙྜ࡟ࡣ㸪ࡳ࠿ࡅࡢ㟈※᫬㛫㛵ᩘ࡟ 2 ࡘࡢࣆ࣮ࢡࡀぢࡽࢀ㸪2 ࡘࡢ◚ቯࡀ㐃⥆ࡋ࡚Ⓨ⏕ࡋࡓ࡜⪃࠼ࡽࢀࡿ㸬ࡇࡢࡼ࠺࡞」㞧࡞㟈※᫬㛫㛵ᩘࢆᣢࡘᆅ㟈࡟ᑐࡋ࡚ࡣ㸪௒ᅇ㸪ࡳ࠿ࡅࡢ◚ቯ⥅⥆᫬㛫ࢆࡿᑻᗘ࡜ࡋࡓࢥ࣮ࢼ࣮࿘Ἴᩘࡸ㸪༢Ⓨᆅ㟈ࢆ௬ᐃࡋࡓࣔࢹࣝࡀ࠺ࡲࡃാ࠿࡞࠿ࡗࡓ࡜⪃࠼ࡽࢀࡿࠋ
(a)

(b)

ᅗ 4 (a) ࡳ࠿ࡅࡢ㟈※᫬㛫㛵ᩘࡢ᪉఩౫Ꮡࡢ౛ࠋ(b) ⌮ㄽ࡜ほࡢࢥ࣮ࢼ࣮࿘Ἴᩘࡢẚ㍑ࠋ 㯮୸㸸ほ㉥⥺㸸୍⯡◚ቯࣔࢹࣝࡢ⌮ㄽ್㸪⅊Ⰽ⥺㸸ᑐ⛠◚ቯࣔࢹࣝࡢ⌮ㄽ್ࠋ

್㸪

28

㸱 . ⤖ᯝ࣭㆟ㄽ ᅗ 5 ࡟㸪ゎᯒᑐ㇟࡜ࡋࡓ 348 ಶࡢᆅ㟈࡟ᑐࡋ࡚ᚓࡽ
ṇࡢࢹ࣮ࢱᩘ㸸306

ࢀࡓǼAIC ࡢ㢖ᗘศᕸࢆ♧ࡍࠋ306 ಶࡢᆅ㟈࡛ǼAIC >㈇ࡢࢹ࣮ࢱᩘ㸸42

0 ࡛࠶ࡾ㸪ከࡃࡢᆅ㟈◚ቯࡀ᭷ព࡞◚ቯఏ᧛ᣦྥᛶࢆ
᭷ࡋ࡚࠸ࡿࡇ࡜ࢆ♧ࡋ࡚࠸ࡿࠋࡇࡢ⤖ᯝࡣ㸪ᑠᆅ㟈ࡢሙྜ࡟ࡶ◚ቯఏ᧛ᣦྥᛶࡢᙳ㡪ࡀ↓ど࡛ࡁ࡞࠸ࡇ࡜ࢆ
♧၀ࡋ࡚࠸ࡿࠋᅗ 6 ࡟㸪᥎ᐃࡋࡓ᩿ᒙ㠃✚㸪ᛂຊ㝆ୗ㔞ǼȪ㸪ǼAIC ࡜࣐ࢢࢽࢳ࣮ࣗࢻࡢ㛵ಀࢆ♧ࡍࠋ᩿ᒙ㠃✚ࡀつᶍ࡜࡜ࡶ࡟ቑຍࡍࡿࡢ࡟ᑐࡋ㸪ᛂຊ㝆ୗ㔞ࡣつᶍ࡟࠶ࡲࡾ౫Ꮡࡋ࡚࠸࡞࠸ࠋࡇࡢഴྥࡣ㸪ᆅ㟈ࡢࢫࢣ࣮ࣜࣥࢢ๎࡜ㄪ࿴ⓗ࡛࠶ࡿ (Aki, 1967)ࠋǼAIC ࡶᙉ
࠸つᶍ౫Ꮡᛶࢆ♧ࡉࡎ㸪◚ቯఏ᧛ᣦྥᛶࡢᙉࡉࡶつᶍ࡟኱ࡁᅗ 5. ǼAIC ࡢ㢖ᗘศᕸࡃ౫Ꮡࡋ࡞࠸ࡇ࡜ࢆ♧၀ࡍࡿࠋ

(a)

(b)

(c)

ᅗ 6 (a) ᩿ᒙ㠃✚㸪(b) ᛂຊ㝆ୗ㔞㸪(c) Ǽ AIC ࡜つᶍࡢ㛵ಀࠋ ㉥୸ࡣつᶍࡈ࡜ࡢᖹᆒ್ࢆ♧ࡍࠋᅗ 7(a) ࡟◚ቯࡢఏ᧛᪉ྥࡢ⤖ᯝࢆ♧ࡍࠋ◚ቯࡀ᪉఩ 50-180r࡟ఏ᧛ࡋࡓᆅ㟈ࡀከ࠸ࡼ࠺࡟
ࡳ࠼ࡿࠋඛ⾜◊✲࡟ࡼࡾ㸪ᆅ㟈◚ቯ࡟ఏ᧛ࡋࡸࡍ࠸᪉ྥࡀᏑᅾࡍࡿྍ⬟ᛶࡀᣦ᦬ࡉࢀ࡚࠸ࡿࡀ
(Kane et al., 2013; Calderoni et al., 2015; Yoshida et al., 2022)㸪௒ᅇࡢ⤖ᯝࡣࡑࢀࡽ࡜ㄪ࿴ⓗ࡛࠶
ࡿࠋ
(a)

(b)



ᅗ 7 (a) ◚ቯࡢ㐍ᒎ᪉ྥࡢ㢖ᗘศᕸ, (b) ᛂຊ㝆ୗ㔞ࡢ㢖ᗘศᕸ

29ᚓࡽࢀࡓᛂຊ㝆ୗ㔞ࡢ್ࡣ 5-30 MPa ⛬ᗘࡢࡶࡢࡀከ࠿ࡗࡓ (ᅗ 7b)ࠋࡇࡢᆅᇦࢆྵࡴᮾ໭
᪥ᮏ࡛᥎ᐃࡉࢀ࡚࠸ࡿ᭱኱๧᩿ᛂຊࡢ್ࡣᩘ༑ MPa (Yoshida et al., 2015a and b)࡛࠶ࡾ㸪ᮏ◊✲࡛᥎ᐃࡉࢀࡓᛂຊ㝆ୗ㔞ࡢᖹᆒ್࡜ྠ⛬ᗘ࡛࠶ࡿࠋࡇࡢࡇ࡜ࡣ㸪᩿ᒙ㠃ୖࡢ๧᩿ᛂຊࡀᆅ㟈࡟ࡼࡾṤ࡝ゎᨺࡉࢀ࡚࠸ࡿࡇ࡜ࢆ♧ࡍࡢ࠿ࡶࡋࢀ࡞࠸ࠋ
୍᪉㸪ᮏ◊✲ࡢゎᯒ࡟ࡼࡾ㸪୰ᑠᆅ㟈ࡢ◚ቯఏ᧛ࡢ」㞧ᛶࡶ᫂ࡽ࠿࡟࡞ࡗ࡚ࡁࡓࠋᅗ 4 ࡟♧ࡋࡓᆅ㟈ࡣ㸪」ᩘࡢ◚ቯ࠿ࡽ࡞ࡿᆅ㟈ࡢ౛࡛࠶ࡿࠋᮏ◊✲࡛ࡣ㸪ከࡃࡢඛ⾜◊✲࡛↓どࡉࢀ࡚ࡁࡓ◚ቯఏ᧛ᣦྥᛶࢆ⪃៖ࡋࡓ୍⯡◚ቯࣔࢹࣝࢆ⏝࠸࡚◚ቯఏ᧛ᣦྥᛶ࡜ᛂຊ㝆ୗ㔞ࢆ᥎ᐃࡋࡓ㸬ࡋ࠿ࡋ㸪ࡇࡢࣔࢹ࡛ࣝࡉ࠼㸪ᅗ 4 ࡢࡼ࠺࡞ᆅ㟈ࡢ」㞧ᛶࢆ༑ศ࡟ㄝ࡛᫂ࡁ࡞࠸ࠋࡇࡢࡼ
࠺࡞」㞧࡞◚ቯࢆࣔࢹࣝ໬ࡍࡿࡓࡵ࡟ࡣ㸪኱ᆅ㟈 (M>6) ࡟ᑐࡋ࡚⾜ࢃࢀ࡚࠸ࡿ㟈※㐣⛬࢖ࣥࣂ࣮ࢪࣙࣥࡢࡼ࠺࡞ゎᯒࡀᚲせ࡛࠶ࡿࠋࡋ࠿ࡋ࡞ࡀࡽ㸪ࡑࡢࡼ࠺࡞ゎᯒ࡛ࡣ㸪ࢹ࣮ࢱࡢ㝈⏺࠿ࡽ⁥ࡾศᕸࡢ᫬㛫Ⓨᒎࡸᛂຊ㝆ୗ㔞ࢆ༑ศࡼࡃᣊ᮰࡛ࡁ࡞࠸ࡇ࡜ࡀከ࠸ࡔࢁ࠺ (Adams et al.,2016)ࠋ୍⯡࡟㸪◚ቯ⥅⥆᫬㛫࠿ࡽ᩿ᒙࢧ࢖ࢬࢆ㧗⢭ᗘ࡟ᣊ᮰ࡍࡿࡇ࡜ࡣ㞴ࡋࡃ㸪⿵ຓⓗ࡞௬ᐃࡀᚲせ࡛࠶ࡿ㸬ୖグࡢࡇ࡜ࢆ⪃࠼ࡿ࡜㸪ᑠᆅ㟈ࡢᛂຊ㝆ୗ㔞ࢆṇ☜࡟ぢ✚ࡶࡿࡇ࡜ࡣᐇ㝿ࡢ࡜ࡇࢁ㠀ᖖ࡟㞴ࡋ࠸ࡼ࠺࡟ᛮࢃࢀࡿࠋᑠᆅ㟈࡟ᑐࡋ࡚᥎ᐃࡉࢀ࡚࠸ࡿ͆ᛂຊ㝆ୗ㔞͆ࡣ㸪㧗࿘Ἴ࢚ࢿࣝࢠ࣮ᨺᑕࡢᑻᗘ࡜ࡋ࡚ࡣ᭷⏝࡛࠶ࡿࡶࡢࡢ㸪ࡑࡢᮏ᮶ࡢព࿡࡛࠶ࡿᆅ㟈᫬ࡢ᩿ᒙୖࡢ
ᛂຊゎᨺ㔞࡜ࡣᚲࡎࡋࡶ⤖ࡧࡘ࠿ࡎ (e.g., Boore, 1983)㸪ヲ⣽࡞≀⌮ⓗゎ㔘ࢆ⾜࠺ࡇ࡜ࡣ㞴ࡋ࠸࠿ࡶࡋࢀ࡞࠸ࠋ୍᪉㸪ᑠᆅ㟈ࡢ◚ቯఏ᧛᪉ྥ➼ࡢࣃ࣓࣮ࣛࢱࡣ㸪ࡇࢀࡲ࡛࠶ࡲࡾὀ┠ࡉࢀ࡚ࡇ࡞࠿ࡗࡓࡶࡢࡢ㸪ከࡃࡢᆅ㟈࡟ࡘ࠸࡚᫂░࡟ࡳࡽࢀࡿࠋᑠᆅ㟈࡟ᑐࡋ࡚ࡶ robust ࡟᥎ᐃࡍࡿࡇ࡜ࡀྍ⬟࡞㔞࡜ࡋ࡚᭷⏝࡜࡞ࡿ࠿ࡶࡋࢀ࡞࠸ࠋ
㸳 . ⤖ㄽ
⚟ᓥ㸫Ⲉᇛ┴ቃ࿘㎶࡛Ⓨ⏕ࡋࡓ୰ᑠᆅ㟈ࡢ◚ቯఏ᧛ᣦྥᛶࡢ᥎ᐃࢆ⾜ࡗࡓࠋࡑࡢ⤖ᯝ㸪ከࡃࡢᑠᆅ㟈ࡀ㢧ⴭ࡞◚ቯఏ᧛ᣦྥᛶࢆ♧ࡋ࡚࠾ࡾ㸪ᚑ᮶ࡢᑐ⛠◚ቯࣔࢹࣝࢆ⏝࠸ࡓᛂຊ㝆ୗ㔞᥎ᐃࡢ㝿ࡢ௬ᐃࡀ࠶ࡲࡾࡼࡃᡂ❧ࡋ࡚࠸࡞࠸ࡇ࡜ࡀศ࠿ࡗࡓࠋ ௒ᅇࡣඛ⾜◊✲࡛↓どࡉࢀ࡚ࡁࡓ◚ቯఏ᧛ᣦྥᛶࢆ⪃៖ࡋ࡚◚ቯఏ᧛᪉ྥ࡜ᛂຊ㝆ୗ㔞ࢆྠ᫬࡟᥎ᐃࡋࡓࡀ㸪௒ᅇ⏝࠸ࡓࣔࢹ࡛ࣝࡉ࠼ᐇ㝿ࡢᆅ㟈◚ቯࡢ」㞧ᛶࢆ༑ศ࡟ㄝ࡛᫂ࡁ࡚࠸࡞࠸ሙྜࡀࡳࡽࢀࡓࠋࡑࢀࡽ࡟ࡘ࠸
࡚ࡣᛂຊ㝆ୗ㔞ࢆ኱ᖜ࡟ㄗ᥎ᐃࡋ࡚࠸ࡿྍ⬟ᛶࡶ⪃࠼ࡽࢀࡿࠋ
ᑠᆅ㟈ࡢ◚ቯఏ᧛ᣦྥᛶ࡟㛵ಀࡍࡿࣃ࣓࣮ࣛࢱࡣ㸪ࡇࢀࡲ࡛࠶ࡲࡾὀ┠ࡉࢀ࡚ࡇ࡞࠿ࡗࡓ
ࡶࡢࡢ㸪௒ᅇ㸪ከࡃࡢᆅ㟈࡟ࡘ࠸࡚᫂░࡟☜ㄆࡉࢀࡓࠋᑠᆅ㟈ࡢ㟈※㐣⛬࡟㛵ࡋ࡚ robust ࡟᥎ᐃࡍࡿࡇ࡜ࡀྍ⬟࡞᝟ሗ࡜ࡋ࡚௒ᚋ᭷⏝࡟࡞ࡿ࠿ࡶࡋࢀ࡞࠸ࠋ
ᘬ⏝ᩥ⊩Abercrombie, R. E. (2021) Resolution and uncertainties in estimates of earthquake stress drop andenergy release. Philosophical Transactions Royal Soc 379.
Adams, M., Twardzik, C. & Ji, C (2016) Exploring the uncertainty range of coseismic stress drop
estimations of large earthquakes using finite fault inversions. Geophys J Int 208, 86 –100.
Akaike, (1974) A new look at the statistical model identification. IEEE Transactions on AutomaticControl, 19, pp. 716-723.

30

Aki, K. (1967) Scaling law of seismic spectrum. J Geophys Res 72, 1217–1231.
Andrews D. J. (1986) Objective determination of source parameters and similarity of earthquakes ofdifferent size. Earthq source Mech 37, 259–267.
Brune, J. N. (1970) Tectonic stress and the spectra of seismic shear waves from earthquakes. J Geophys
Res 75, 4997–5009.
Calderoni, G., Rovelli, A., Ben-Zion, Y. & Giovambattista, R. D. (2015) Along-strike rupture
directivity of earthquakes of the 2009 L’Aquila, central Italy, seismic sequence. Geophys J Int 203,
399–415.
Dong G, Papageorgiou AS (2003) On a new class of kinematic models: Symmetrical and asymmetricalcircular and elliptical cracks. Phys Earth Planet Inter 137, 129–151. doi: 10.1016/S00319201(03)00012-8
Savage J.C. (1966) Radiation from a realistic model of faulting. Bulletin of the Seismological Societyof America, 56, (2), 577–592.
Kane, D. L., Shearer, P. M., Goertz‐Allmann, B. P. & Vernon, F. L. (2013) Rupture directivity of small
earthquakes at Parkfield. J Geophys Res Solid Earth 118, 212–221.
Kikuchi M, Kanamori H (1982) Inversion of complex body waves. Phys Earth Planet Inter 72, 491–
506. doi: 10.1016/0031-9201(86)90048-8
Sato T, Hirasawa T (1973) Body wave spectra from propagating shear cracks. J Phys Earth 21, 415–
431. doi: 10.4294/jpe1952.21.415
Yoshida, K (2019) Prevalence of asymmetrical rupture in small earthquakes and its effect on theestimation of stress drop: a systematic investigation in inland Japan. Geoscience Lett 6, 16.
Yoshida K, Hasegawa A, Okada T (2015a) Spatial variation of stress orientations in NE Japan reveal ed
by dense seismic observations. Tectonophysics 647, 63–72. doi: 10.1016/j.tecto.2015.02.013
Yoshida K, Hasegawa A, Okada T (2015b) Spatially heterogeneous stress field in the source area of the2011 Mw 6.6 Fukushima-Hamadori earthquake, NE Japan, probably caused by static stress change.
Geophys J Int 201, 1062–1071. doi: 10.1093/gji/ggv068
Yoshida, K., Saito, T., Emoto, K., Urata, Y. & Sato, D (2019) Rupture directivity, stress drop, andhypocenter migration of small- and moderate-sized earthquakes in the Yamagata-Fukushima borderswarm triggered by upward pore-pressure migration after the 2011 Tohoku-Oki earthquake.
Tectonophysics 228184. doi:10.1016/j.tecto.2019.228184.
Yoshida, K., Uchida, N., Kubo, H., Takagi, R. & Xu, S (2022) Prevalence of updip rupture propagation
in interplate earthquakes along the Japan trench. Earth Planet Sc Lett 578, 117306.

東北地域災害科学研究31

第58巻（2022）ᖖ ᫬ᚤືࡢᆅ㟈Ἴᖸ΅ἲゎᯒ࡟ᇶ࡙ࡃ Rayleigh Ἴ఩┦㏿ᗘࢆ⏝࠸ࡓ⚟ᓥ┴࡟࠾ࡅࡿ 3 ḟඖ S Ἴ㏿ᗘᵓ㐀ࡢ㏫ゎᯒ㸨ᒾᡭ኱Ꮫ኱Ꮫ㝔⥲ྜ⛉Ꮫ◊✲⛉ ᅵᒇ㝯ᒾᡭ኱Ꮫ⌮ᕤᏛ㒊 ୕ᾆ㈼ኴ㑻 ᒣᮏⱥ࿴ 㰺⸨๛
1㸬 ࡣࡌࡵ࡟ ᡃࠎࡣ㸪2012 ᖺᗘ࠿ࡽ㸦බ㈈㸧ᆅ㟈ண▱⥲ྜ◊✲᣺⯆఍ࡢ༠ຊࡢࡶ࡜ᆅ㟈Ἴᖸ΅ἲゎᯒࢆ⏝࠸ࡓ⚟ᓥ┴┤ୗ࡟࠾ࡅࡿᆅୗᵓ㐀᥎ᐃࡢ◊✲ࢆ⾜ࡗ࡚ࡁࡓ㸦౛࠼ࡤ㸪ᒣᮏ࡯࠿㸪2015㸧ࠋᒣᮏ࡯࠿㸦2015㸧࡛ࡣ㸪⚟ᓥ┴ࡢ Hi-net ཬࡧᗈᖏᇦᆅ㟈ィࣜࢽ࢔࢔ࣞ࢖࡛ほࡉࢀࡓᖖ᫬ᚤືグ㘓࡟ᆅ㟈Ἴᖸ΅ἲゎᯒࢆ㐺⏝ࡋ࡚ 2 Ⅼ㛫ࡢ┦஫┦㛵㛵ᩘࢆ⟬ฟࡋ㸪ᚓࡽࢀࡓ┦஫┦㛵㛵ᩘ࠿ࡽ⩌㏿ᗘࢆ⟬ᐃࡋ࡚࠸ࡓࠋࡋ࠿ࡋ㸪ᅵᒇ࡯࠿㸦2020㸧࡛ࡣ㸪ᖖ᫬ᚤືグ㘓࠿ࡽᚓࡽࢀࡓ 2 Ⅼ㛫ࡢࢡࣟࢫࢫ࣌ࢡࢺࣝ࡟ Ekstöm et al.(2009)ࡀᥦ᱌ࡋࡓࢮࣟࢡࣟࢫἲࢆ㐺⏝ࡋ㸪Rayleigh Ἴ఩┦㏿ᗘࡢ⟬ᐃࢆ⾜ࡗࡓࠋࡲࡓ㸪ᅵᒇ࡯࠿㸦2020㸧ࡢࣃࢫᐦᗘࡣ୙ᆒ୍࡛㏫ゎᯒࢆࡍࡿୖ࡛༑ศ࡞ࡶࡢ࡜ࡣ
ゝ࠼࡞࠸ࡓࡵ㸪ᮏ◊✲࡛ࡣ⚟ᓥ┴࿘㎶ࡢ Hi-net ࡸ F-net ࡢほⅬࡶ㏣ຍࡋ࡚㸪༑ศ㧗࠸ࣃࢫᐦᗘ࡟ࡍࡿࠋࡑࡋ࡚㸪ᚓࡽࢀࡓ⚟ᓥ┴඲యࢆ⥙⨶ࡍࡿࣃࢫࡢ఩┦㏿ᗘศᩓ᭤⥺࡟ᇶ࡙࠸࡚㸪Fang
et al.(2015)࡟ࡼࡿࢺࣔࢢࣛࣇ࢕ゎᯒᡭἲࢆ฼⏝ࡋ㸪⚟ᓥ┴┤ୗࡢ 3 ḟඖ S Ἴ㏿ᗘᵓ㐀ࡢ᥎ᐃࢆヨࡳࡿࠋ2㸬 ౑⏝ほⅬ࡜஬࠿᭶㛫ᖹᆒࢡࣟࢫࢫ࣌ࢡࢺࣝࡢ⟬ᐃ ᅗ 1 ࡟ Hi-net ほⅬࡢ఩⨨ࢆ♧ࡍࠋᅗ 2 ࡟ F-net ほ౑⏝ࡋࡓ Hi-net ほⅬࡣ⚟ᓥ┴ཬࡧࡑࡢ࿘㎶࡟タ⨨ࡉࢀ࡚࠸ࡿ඲ 46 ほⅬཬࡧࣜࢽ࢔࢔ࣞ࢖

⥺ࡢ఩⨨ࢆ♧ࡍࠋⅬ࡛㸪౑⏝ࢹ࣮ࢱᮇ

㛫ࡣ 2012 ᖺ 9 ᭶࠿ࡽ 2013 ᖺ 1 ᭶ࡲ࡛ࡢ஬࠿᭶㛫࡛࠶ࡿࠋ౑⏝ࡋࡓ F-net ほ㸦ᕝᓮ㸧࡜ N.ASIF㸦㊊ᑿ㸧ࡢ 2 ほᮇ㛫ࡣᗈᖏᇦࣜࢽ࢔࢔ࣞ࢖ほⅬ࡛㸪౑⏝ࢹ࣮ࢱᮇ㛫ࡣ Hi-net ほⅬࡣ㸪N.KSKF

Ⅼ࡜ྠᵝ࡛࠶ࡿࠋࡇࡢ

ࡀ 2011 ᖺ 8 ᭶࠿ࡽ 2014 ᖺ 2 ᭶ࡲ࡛ᐇ᪋ࡉࢀ㸪඲ほᮇ㛫ࡢ࠺ࡕ୍࠿᭶ࢹ࣮ࢱࡀ㐃⥆ࡋ࡚඲࡚Ꮡᅾࡋ࡚࠸ࡿᮇ㛫࡛࠶ࡾ㸪ゎᯒᮇ㛫ࢆྠ୍࡟ࡋࡓ࠿ࡗࡓࡓࡵ࡛
࠶ࡿࠋࡲࡓ㸪ࣜࢽ࢔࢔ࣞ࢖

⥺ࡢ NO4 ࡜ NO10 ࡟㛵ࡋ࡚ࡣ㸪ࢹ࣮ࢱ୙㊊ࡢࡓࡵゎᯒᑐ㇟࠿ࡽ㝖࠸࡚࠸ࡿࠋᗈᖏᇦࣜࢽ࢔࢔ࣞ࢖ࡢヲࡋ࠸ほ ࡲࡓ㸪Hi-net ࡣ 100Hz ࡛ほࢩࢫࢸ࣒ࡣ㸪ᒣᮏ࡯࠿㸦2016㸧࡟♧ࡉࢀ࡚࠸ࡿࠋ

ࡀ⾜ࢃࢀ࡚࠸ࡿࡀ㸪ィ⟬ࡢ㈇Ⲵࢆῶࡽࡍࡓࡵ࡟ᮏ◊✲࡛ࡣ 20Hz࡟ࢲ࢘ࣥࢧࣥࣉࣜࣥࢢࡋࡓࠋࡉࡽ࡟㸪๓ฎ⌮࡜ࡋ࡚᫬㛫つ᱁໬㸪஧್໬㸪ࢫ࣌ࢡࢺࣝ࣍࣡࢖ࢺ
ࢽࣥࢢࢆ⾜ࡗࡓ (Bensen et al., 2007)ࠋ๓ฎ⌮ࢆ⾜ࡗࡓ 1 ᫬㛫Ἴᙧ࡟ᑐࡋ㸪FFT ฎ⌮࡟ࡼࡾࢡࣟ
ࢫࢫ࣌ࢡࢺࣝࢆ⟬ฟࡋࡓࠋᮏ◊✲࡛ࡣᇶᮏ༊㛫ࢆ 15 ศ࡜ࡋ㸪4 ࡘᖹᆒࡍࡿࡇ࡜࡛ 1 ᫬㛫ᖹᆒ࡜ࡋࡓࠋ౛࡜ࡋ࡚㸪Hi-net ほ

Ⅼ N.NMEH㸦ᾉỤ㸧࡜ H.TDMH㸦ྈぢ㸧ࡢ 2 Ⅼ㛫ࡢつ᱁໬ࢡࣟࢫ

*An inversion of a three-dimensional S-wave velocity structure in Fukushima Prefecture using phase velocities
of Rayleigh wave based on seismic interferometry analysis of microtremors by T. Tsuchiya, K. Miura, H.
Yamamoto and T. Saito32ࢫ࣌ࢡࢺࣝࡢᐇ㒊ࢆᅗ 3 ࡟♧ࡍࠋୖ࠿ࡽ㡰࡟୍᫬㛫㸪୍᪥㸪୍࠿᭶㸪஬࠿᭶㛫ᖹᆒࡋࡓࢡࣟࢫ
ࢫ࣌ࢡࢺࣝࢆ⾲ࡋ࡚࠸ࡿࠋ▷᫬㛫ᖹᆒ࡛ࡣぢࡽࢀ࡞࠿ࡗࡓ≉ᚩⓗ࡞᣺ືࡀ㛗᫬㛫ᖹᆒ࡟ࡼࡾ☜ㄆ࡛ࡁࡿࡼ࠺࡟࡞ࡗࡓࠋࡉࡽ࡟㸪⟬ฟࡋࡓࢡࣟࢫࢫ࣌ࢡࢺࣝ࡟ࣀ࢖ࢬ࡟ࡼࡿᑠࡉ࡞ᙳ㡪ࢆ㝖ࡃࡓࡵ࡟⛣ືᖹᆒ᧯సࢆ⾜࠸㸪ࢮࣟࢡࣟࢫⅬࢆ᳨ฟ࡛ࡁࡿࡼ࠺࡟ヨ⾜㘒ㄗࡋ࡚ᖹ⁥໬ࡋ࡚࠸ࡿࠋ
3㸬
㸬 ࢮࣟࢡࣟࢫἲ࡟ࡼࡿ఩┦㏿ᗘ᥎ᐃࡣࡌࡵ࡟㸪ࢡࣟࢫࢫ࣌ࢡࢺࣝࡢ㞽Ⅼ࠿ࡽ఩┦㏿ᗘࢆồࡵࡿࡓࡵ࡟㸪௨ୗࡢࢮࣟࢡࣟࢫἲࢆ⏝࠸ࡓࠋ➨ 1 ✀ 0 ḟ࣋ࢵࢭࣝ㛵ᩘࡀ n ᅇ┠࡟ 0 ࡜࡞ࡿ㞽Ⅼࢆܼ௡ 㸪࿘Ἴᩘࢆ݂௡ ࡜ࡍࡿ࡜ Rayleigh Ἴ఩┦㏿ᗘࡣ(1)ᘧ࡛⾲ࡉࢀࡿࠋ‫ܥ‬ሺ݂ሻ ൌࡋ࠿ࡋ㸪ほଶగ௙೙ ௥
௓೙

(1)ࡉࢀࡓࢡࣟࢫࢫ࣌ࢡࢺࣝࡣ୍⯡ⓗ࡟ࣀ࢖ࢬࢆྵࡳ୙Ᏻᐃ࡛࠶ࡿࠋᮏ᮶ࡢ㞽ⅬࡀḞዴࡍࡿሙྜࡸవศ࡞㞽Ⅼࢆㄞࡴሙྜࡀ࠶ࡿࠋࡑࡢࡓࡵ㸪࣋ࢵࢭࣝ㛵ᩘࡢ≉ᐃࡢ㞽Ⅼ࡜ࢡࣟࢫࢫ
࣌ࢡࢺࣝࡢ㞽Ⅼࢆᑐᛂࡉࡏࡿࡢࡀᅔ㞴࡛࠶ࡿࠋࡑࡇ࡛㸪㞽ⅬࡢḞዴ࡜వศ࡞㞽Ⅼࢆ⪃៖ࡋࡓ(2)ᘧࢆ⏝࠸࡚఩┦㏿ᗘࡢ᥎ᐃࢆ⾜࠺(Ekstöm et al., 2009)ࠋ

‫ܥ‬௠ ሺ݂ሻ ൌଶగ௙೙ ௥
௓೙శమ೘ሺ݉ ൌ Ͳǡ േͳǡ േʹሻ(2)ࡇࡇ࡛݉ࡣ㸪Ḟዴࡋࡓ㸪ࡶࡋࡃࡣవศ࡟ㄞࡴ㞽Ⅼࡢᩘࢆ⾲ࡍࠋᮏ◊✲࡛ࡣ㸪࠶ࡽ࠿ࡌࡵ n ࢆ௬ᐃࡋ࡚݊ െ Ͷ ࠿ࡽ݊ ൅ Ͷࡲ࡛ࡢ 5 ࡘࡢ఩┦㏿ᗘࢆ⟬ฟࡋࡓࠋ౛࡜ࡋ࡚㸪ᅗ 4 ࡟ほ

Ⅼ N.NMEH(ᾉỤ)࡜ H.TDMH(ྈぢ)ࡢࢡࣟࢫࢫ࣌ࢡࢺࣝ࡜ࢮࣟࢡࣟࢫἲ࠿ࡽ᥎ᐃࡋࡓ Rayleigh Ἴ఩┦㏿ᗘศᩓ᭤⥺ࢆ♧ࡍࠋྠ᫬࡟Ẽ㇟ᗇ୍ḟඖ㏿ᗘᵓ㐀࠿ࡽィ⟬ࡉࢀࡓ఩┦㏿ᗘศᩓ᭤⥺㸦ୖ㔝࡯࠿㸪2002㸧ࡶ♧ࡋ㸪0.1Hz ࠿ࡽ 0.2Hz ࡢ㛫࡛ẚ㍑ࡍࡿࡇ࡜࡟ࡼࡾ୍␒㏆࠸ศᩓ᭤⥺ࢆ㑅ᐃࡋࡓࡑࡢ⤖ᯝ㸪
0.1Hz ࡛⣙ 3200m/s㸪0.2Hz ࡛⣙ 3000m/s㸪0.3Hz ࡛⣙ 2800m/s ࡜࡞ࡗࡓࠋࡇࡢࡼ࠺࡟࿘Ἴᩘࡈ࡜
ࡢ఩┦㏿ᗘࢆㄞࡳྲྀࡾ㸪」ᩘࡢ⤌ࡳྜࢃࡏ࠿ࡽ࡞ࡿࣃࢫࡈ࡜ࡢ఩┦㏿ᗘศᕸᅗࢆసᡂࡋࡓࠋᮏ
◊✲࡛ࡣ㸪ほⅬ㛫㊥㞳ࡀ 100km ௨ୖࡢ⤌ࡳྜࢃࡏࡢࡳࢆ౑⏝ࡋ㸪ᶵჾ≉ᛶࡢ␗࡞ࡿ Hi-net ࡜ᗈᖏᇦᆅ㟈ィࡢ⤌ࡳྜࢃࡏࡣ౑⏝ࡋ࡞࠸ࠋᅗ 5 ࡟㸪࿘ᮇ 8 ⛊࡟࠾ࡅࡿࣃࢫࡈ࡜ࡢ఩┦㏿ᗘศᕸ㸪ᅗ 6 ࡟࿘ᮇ 3 ⛊࡟࠾ࡅࡿࣃࢫࡈ࡜ࡢ఩
┦㏿ᗘศᕸࢆࡑࢀࡒࢀ♧ࡍࠋ౑⏝ࡋ࡚࠸ࡿࣃࢫࡢᩘࡣࡑࢀࡒࢀ 275 ಶ࡜ 215 ಶ࡛࠶ࡿࠋᅗ 5 ࡛ࡣ㸪఩┦㏿ᗘࡀᴫࡡ 3000m/s ௨ୖࢆ♧ࡍ⤒㊰ࡀከࡃ㸪ࡲࡓᆅᇦࡈ࡜ࡢ㐪࠸ࡣุูࡋ࡟ࡃ࠸ࠋᅗ
6 ࡛ࡣ㸪ᅗ 5 ࡼࡾࡶ఩┦㏿ᗘࡀᖹᆒⓗ࡟㐜ࡃ࡞ࡗ࡚࠾ࡾ㸪⚟ᓥ┴ࡢᮾ㒊࡛ࡣ⣙ 3000m/s ࢆ♧ࡍ⤒㊰ࡀከࡃ㸪໭す㒊ࡸ༡㒊࡛ࡣ⣙ 2400m/s ࠿ࡽ⣙ 2800m/s ࢆ♧ࡍ⤒㊰ࡀከ࠸ࡇ࡜ࡀ☜ㄆ࡛ࡁࡓࠋ
4㸬 ┤᥋ 6 Ἴ㏿ᗘ㏫ゎᯒࡢᡭ㡰ᮏ◊✲࡛ࡣ㸪Fang et al.(2015)࡟ࡼࡿ⾲㠃Ἴࡢศᩓࢹ࣮ࢱࢆ┤᥋㏫ゎᯒࡋ࡚ 3 ḟඖ S Ἴ㏿ᗘᵓ㐀ࢆ⟬ฟࡍࡿ⾲㠃Ἴࢺࣔࢢࣛࣇ࢕ἲࢆ౑⏝ࡋࡓࠋ㏻ᖖࡢ S Ἴ㏿ᗘᵓ㐀ࡣ㸪ྛࢢࣜࢵࢻ࣏࢖ࣥࢺ
࡛ࡢ S Ἴ㏿ᗘࡢ 1 ḟඖࣉࣟࣇ࢓࢖ࣝࡢ 2 ḟඖ఩┦㏿ᗘ࣐ࢵࣉࢆ౑⏝ࡋࡓⅬࡈ࡜ࡢ㏫ゎᯒ࡟ࡼࡗ࡚ᵓ⠏ࡉࢀࡿࠋࡋ࠿ࡋ㸪Fang et al.(2015)࡛ࡣ఩┦㏿ᗘ஧ḟඖ࣐ࢵࣉࢆసᡂࡏࡎ࡟㸪┤᥋ 3 ḟඖ33

S Ἴ㏿ᗘࣔࢹࣝࢆ᥎ᐃ࡛ࡁࡿࡶࡢ࡛࠶ࡿࠋࡲࡓ㸪ࡇࡢᡭἲࡣ⾲㠃Ἴࡢ㉮᫬ࡢィ⟬࡟Ἴ⥺㏣㊧ἲࢆ฼⏝ࡋࡓ㧗㏿࣐࣮ࢳࣥࢢἲ(FMM) (Rawlinson and Sambridge, 2004)ࢆ౑⏝ࡋ࡚࠾ࡾ㸪࿘Ἴᩘ౫ᏑࡍࡿἼ⥺ࡢ᭤ࡆࢆ⪃៖ࡋ࡚࠸ࡿࠋ㏿ᗘࡀ኱ࡁࡃኚ໬ࡍࡿ」㞧࡞፹య࡛┤⥺ఏ᧛ࡢ௬ᐃࡣ㐺ษ࡛ࡣ࡞࠸ࡓࡵ㸪㏫ゎᯒ࡟࠾ࡅࡿἼ⥺ࡢ᭤ࡆࡢᙳ㡪ࢆ⪃៖ࡍࡿࡇ࡜ࡣ㐺ษ࡛࠶ࡿࠋ
ࢺࣔࢢࣛࣇ࢕ゎᯒࢆ⾜࠺࡟࠶ࡓࡾᮏ◊✲࡟࠾ࡅࡿゎᯒ᮲௳ࢆḟࡢࡼ࠺࡟タᐃࡋࡓࠋᑐ㇟⠊ᅖ
ࡣ໭⦋ 36.6 ᗘ࠿ࡽ 38.4 ᗘ㸪ᮾ⤒ 138.9 ᗘ࠿ࡽ 141.3 ᗘ࡜ࡋ㸪⚟ᓥ┴ࢆ༑ศ࡟そ࠺⠊ᅖ࡜ࡋࡓࠋ
⦋ᗘ⤒ᗘࡢศ๭ᩘࡣࡑࢀࡒࢀ 30 ಶ࡛࠶ࡿࠋ౑⏝ࡍࡿ఩┦㏿ᗘࡢ࿘ᮇࡢ⠊ᅖࡣ 3.0 ⛊࠿ࡽ 10.0⛊ࡢ㛫࡛ 0.5 ⛊㛫㝸࡜ࡋࡓࠋồࡵࡓ࠸῝ࡉࡣ㸪2.0km ࠿ࡽ 9.0km ࡢ㛫࡛ 1.0km 㛫㝸࡜ࡋࡓࠋ཯
᚟ᅇᩘࡣ 10 ᅇ⾜ࡗࡓࠋ࡞࠾㸪ゎᯒ࡟⏝࠸࡚࠸ࡿࣃࢫࡢᩘࡣ᭱኱ 275 ಶ࡛࠶ࡿࠋ S Ἴ㏿ᗘࢺࣔࢢࣛࣇ࢕ࡢึᮇࣔࢹࣝࡣ㸪඲㒊ࡢࣃࢫ࡛ᖹᆒࡋࡓ఩┦㏿ᗘࢆ 1.1 ಸࡋ࡚ᨃఝⓗ࡞ S Ἴ㏿ᗘ࡜ࡋ㸪Ἴ㛗ࡢ㸱ศࡢ㸯ࢆ῝ࡉ࡜ࡋࡓࠋ
ࡲࡓᮏ◊✲࡛ࡣ㸪㏫ゎᯒࢆ⾜࠺๓࡟࠶ࡽ࠿ࡌࡵಙ㢗࡛ࡁࡿ⠊ᅖࢆᢕᥱࡍࡿࡓࡵ࡟㸪ࢳ࢙ࢵ࣮࣮࢝࣎ࢻࢸࢫࢺࢆᐇ᪋ࡋࡓࠋs0.4km/s ࡢ㏿ᗘ೫ᕪࢆ୚࠼ࡓ S Ἴ㏿ᗘࡢึᮇࣔࢹࣝࢆసᡂࡋࡓࠋ
㏿ᗘࡢᖹᆒ್ࡣᮏ␒ࡢゎᯒ࡛౑⏝ࡍࡿ㏿ᗘ໙㓄࡜ྠࡌ್ࢆ౑⏝ࡋ㸪῝ࡉ࡜࡜ࡶ࡟ቑຍࡉࡏ࡚࠸
ࡿࠋᅗ 7 ࡟῝ࡉ 5km ࡟࠾ࡅࡿࢳ࢙ࢵ࣮࣮࢝࣎ࢻࢸࢫࢺࡢ⤖ᯝࢆ♧ࡍࠋᚓࡽࢀࡓ⤖ᯝࢆẚ㍑ࡋ࡚
ࡳࡿ࡜㸪୺࡟⚟ᓥ┴ෆࢆ୰ᚰ࡟᱁Ꮚᶍᵝࢆ᚟ඖࡍࡿࡇ࡜ࡀฟ᮶ࡓࠋࡇࢀࡣ௒ᅇࡢධຊࢹ࣮ࢱ࡛
ࡣಙ㢗ᛶࡀ㧗࠸ሙᡤ࡜ண᝿ࡉࢀࡿࠋ㸬 ᥎ᐃ 6 Ἴ㏿ᗘᵓ㐀࡜⪃ᐹ
5㸬
᥎ᐃࡋࡓ῝ࡉ 5km ࡢ S Ἴ㏿ᗘᵓ㐀ࢆᅗ 8 ࡟㸪῝ࡉ 3km ࡢ S Ἴ㏿ᗘᵓ㐀ࢆᅗ 9 ࡟ࡑࢀࡒࢀ♧ࡍࠋ῝ࡉ 5km ࡛ࡣ㸪⚟ᓥ┴ࡢᮾ㒊ࡸ༡す㒊࡟࠾࠸࡚ S Ἴ㏿ᗘࡀ⣙ 3.3km/s ࡜㏿࠸㏿ᗘࢆ♧ࡋ࡚࠸ࡿ୍᪉࡛㸪఍ὠᆅᇦ࡛ࡣ⣙ 2.8km/s ࡜㏿ᗘࡢ㐜࠸್ࢆ♧ࡋ࡚࠸ࡿࠋ῝ࡉ 3km ࡛ࡣ㸪ᮾ㒊ࡸ༡す㒊࡟࠾࠸࡚⣙ 3.0km/s ࡜౫↛࡜ࡋ࡚㏿ᗘࡢ㏿࠸್ࢆ♧ࡋ࡚࠸ࡿ ୍᪉࡛㸪఍ὠᆅᇦ࡛ࡣ ⣙2.6km/s ࡜ඛ࡯࡝࡜ྠᵝ࡟௚ᆅᇦ࡜ẚ࡭࡚㏿ᗘࡀ㐜࠸ᆅᇦ࡜࡞ࡗ࡚࠸ࡿࠋࡲࡓ఍ὠᆅᇦࢆ㏻ࡿ
ࡼ࠺࡞⦋ᗘ 37.56 ᗘ࡟࠾ࡅࡿᮾす᩿㠃ࡢ S Ἴ㏿ᗘศᕸࢆᅗ 10 ࡟♧ࡍࠋಙ㢗ᛶࡀ㧗࠸⚟ᓥ┴ෆ࡟ὀ┠ࡍࡿ࡜㸪ᮾ⤒ 139.5 ᗘ࠿ࡽ 140.0 ᗘ࡟఩⨨ࡍࡿ఍ὠᆅᇦ࡛ࡣᬮⰍ࡛♧ࡉࢀࡿ S Ἴ㏿ᗘࡢ㐜࠸ศᕸࡀ῝㒊ࡲ࡛⾲⌧ࡉࢀ࡚࠾ࡾ㸪୍᪉࡛㸪ᮾ㒊ࡸす㒊࡛ࡣᐮⰍ࡛♧ࡉࢀࡿ S Ἴ㏿ᗘࡢ㏿࠸ศᕸࡀ఍ὠᆅᇦࡼࡾࡶὸ㒊ࡲ࡛⾲⌧ࡉࢀ࡚࠸ࡿࡇ࡜ࡀศ࠿ࡗࡓࠋ
ࡉࡽ࡟ᮏ◊✲࡛ࡣ㸪῝ࡉ 3km ࡢ S Ἴ㏿ᗘᵓ㐀࡜⚟ᓥ┴ࡢᆅ㉁ศᕸ࡜ẚ㍑ࡍࡿࠋS Ἴ㏿ᗘࡀ
3.0km/s ⛬ᗘࢆ♧ࡍⓑⰍࡢศᕸࡣ๓ᮇ₞᪂ୡ௨๓ࡢᇶ┙ᒾ㢮࡜㸪S Ἴ㏿ᗘࡀ 2.6km/s ⛬ᗘࢆ♧ࡍ㉥Ⰽࡢศᕸࡣ๓ᮇ᭦᪂ୡ௨㝆ࡢሁ✚≀ࡸⅆᒣᒾ㢮࡜ࡑࢀࡒࢀ࡯ࡰ୍⮴ࡋ࡚࠸ࡿࡇ࡜ࡀ☜࠿ࡵࡽࢀࡓࠋ
6㸬 ࡲ࡜ࡵ
ᮏ◊✲࡛ࡣ㸪⚟ᓥ┴ཬࡧࡑࡢ࿘㎶࡛ほࡉࢀࡓᖖ᫬ᚤືࡢ 2 Ⅼ㛫ࡢࢡࣟࢫࢫ࣌ࢡࢺࣝࡢࢮࣟ

ࢡࣟࢫⅬ࠿ࡽồࡵࡽࢀࡓ఩┦㏿ᗘศᩓ᭤⥺ࢆ⏝࠸࡚㸪Fang et al.(2015)ࡢ㏫ゎᯒᡭἲࢆ㐺⏝ࡋ࡚S Ἴ㏿ᗘᵓ㐀ࢆ᥎ᐃࡋࡓࠋࡑࡢ⤖ᯝ㸪⚟ᓥ┴ࡢᮾ㒊ࡸ༡す㒊࡟࠾࠸࡚㸪῝ࡉ 5km ࡛ࡣ S Ἴ㏿ᗘࡀ⣙ 3.3km/s㸪῝ࡉ 3km ࡛ࡣ⣙ 3.0km/s ࡜㏿ᗘࡢ㏿࠸್ࢆ♧ࡋࡓࠋ୍᪉࡛㸪఍ὠᆅᇦ࡟࠾࠸࡚

34ࡣ㸪῝ࡉ 5km ࡛ࡣ S Ἴ㏿ᗘࡀ⣙ 2.8km/s㸪῝ࡉ 3km ࡛ࡣ⣙ 2.6km/s ࡜㐜࠸್ࢆ♧ࡋࡓࠋࡲࡓ㸪῝ࡉ 3km ࡢ S Ἴ㏿ᗘᵓ㐀࡜⚟ᓥ┴ࡢᆅ㉁ศᕸࢆẚ㍑ࡋࡓ࡜ࡇࢁ㸪S Ἴ㏿ᗘࡀ㏿࠸ᆅᇦ࡜㐜࠸ᆅ
ᇦࡣᆅ㉁ᖺ௦࡜㛵ಀࡋ࡚࠸ࡿࡇ࡜ࢆ☜ㄆࡍࡿࡇ࡜ࡀ࡛ࡁࡓࠋࡋ࠿ࡋ㸪⚟ᓥ┴ἢᓊᆅᇦࡢࣃࢫᐦ
ᗘࡀ௚ᆅᇦ࡜ẚ࡭࡚ప࠸ࡇ࡜࠿ࡽ㸪ὸ㒊ࡢἢᓊ㒊࡟࠾ࡅࡿゎᯒ⤖ᯝࡢಙ㢗ᛶࡀప࠸ࠋࡇࢀࡣ㸪
100km ௨ୗࡢ⤌ࡳྜࢃࡏࢆቑࡸࡍࡇ࡜࡛ἢᓊ㒊࡟࠾ࡅࡿ᥎ᐃゎീᗘࡀୖࡀࡿ࡜⪃࠼ࡽࢀࡿࠋ
ㅰ ㎡(ᅜ◊)㜵⅏⛉Ꮫᢏ⾡◊✲ᡤ࠿ࡽ㧗ឤᗘᆅ㟈ほ⥙(Hi-net)ࡲࡓࡣᗈᖏᇦᆅ㟈ほ⥙(F-net)ࡢࢹ

࣮ࢱࢆ౑⏝ࡉࡏ࡚࠸ࡓࡔ࠸ࡓࠋ(බ㈈)ᆅ㟈ண▱⥲ྜ◊✲᣺⯆఍࡟ࡼࡿᗈᖏᇦࣜࢽ࢔࢔ࣞ࢖࡛ほࡉࢀࡓࢹ࣮ࢱࢆ౑⏝ࡉࡏ࡚࠸ࡓࡔ࠸ࡓࠋ3 ḟඖ S Ἴ㏿ᗘᵓ㐀ゎᯒ࡟ࡣ Fang ༤ኈ࡟ࡼࡿゎᯒࣉࣟࢢ࣒ࣛ DSurfTomo ࢆ౑⏝ࡉࡏ࡚࠸ࡓࡔ࠸ࡓࠋ୍㒊ࡢᅗࡢసᡂ࡟ࡣ GMT(Wessel and Smith, 1998)ࢆ౑⏝ࡉࡏ࡚࠸ࡓࡔ࠸ࡓࠋグࡋ࡚ࡇࡇ࡟ㅰពࢆ⾲ࡋࡲࡍࠋཧ⪃ᩥ⊩Bensen, G. D., M. H. Ritzwoller, M. P. Barmin, A. L. Levshin, F. Lin, M. P. Moschetti, N. M. Shapiro
and Y. Yang (2007), Processing seismic ambient noise data to obtain reliable broad -band surface
wave dispersion measurements, Geophys. J. Int., 169, 1239-1260.
Ekström, G, Geoffrey A. Abers, and Spahr C. Webb (2009), Determination of surface-wave phasevelocities across USArray from noise and Aki’s spectral formulation, Geophys. Res. Lett., 36,
L18301, doi:10.1029/2009GL039131, 2009.
Fang, H, H. Yao, H. Zhang, Y. C. Huang, and van der R. D. Hilst (2015), Direct inversion of surface wave
dispersion for three-dimensional shallow crustal structure based on ray tracing: methodology andapplication, Geophys. J. Int., 201, 1251-1263.
୍ ⯡ ♫ ᅋ ἲ ே ᮾ ໭ ᆅ ㉁ ᴗ ༠ ఍ 㸪 ᮾ ໭ 6 ┴ ࡢ ᆅ ㉁ 㸪 ⚟ ᓥ ┴ ࡢ ᆅ ㉁ 㸪 https://tohokugeo.ne.jp/information/daichi/img/53/03.pdf ᭱⤊㜀ぴ᪥ 2022 ᖺ 1 ᭶ 6 ᪥
Rawlinson, N. and M. Sambridge (2004), Wave front evolution in strongly heterogeneous layered mediausing the fast marching method, Geophys. J. Int., 156, 631–647.
ᅵᒇ㝯㸪ᒣᮏⱥ࿴㸪㰺⸨๛ (2020)㸪⚟ᓥ┴ࡢ Hi-net ほⅬ࡛ほࡉࢀࡓᖖ᫬ᚤືࡢᆅ㟈Ἴᖸ΅ἲゎᯒ࡟ࡼࡿ Rayleigh Ἴ఩┦㏿ᗘࡢ஧ḟඖศᕸࡢ᥎ᐃ㸪௧࿴ 2 ᖺᗘᮾ໭ᆅᇦ⅏ᐖ⛉Ꮫ◊✲㞟఍㸪ㅮ₇ண✏㞟.
ୖ㔝ᐶ㸪␊ᒣಙ୍㸪᫂⏣ᕝಖ㸪⯪ᓮ῟㸪὾⏣ಙ⏕ (2002)㸪Ẽ㇟ᗇࡢ㟈※Ỵᐃ᪉ἲࡢᨵၿ㸫ὸ㒊㏿ᗘᵓ㐀࡜㔜ࡳ㛵ᩘࡢᨵⰋ㸫㸪㦂㟈᫬ሗ➨ 65 ᕳ㸪pp.123-124.
Wessel, P. and W. HF. Smith (1998), New, improved version of the Generic Mapping Tools released, EOS
Trans. AGU, 79, 579.
ᒣᮏⱥ࿴㸪⃝⏣⩏༤㸪㰺⸨๛ (2015)㸪⚟ᓥ┴ࡢᗈᖏᇦࣜࢽ࢔࢔ࣞ࢖࡛ほࡉࢀࡓᖖ᫬ᚤືࡢᆅ㟈Ἴᖸ΅ἲゎᯒ㸦ࡑࡢ 1㸧㸪➨ 132 ᅇ≀⌮᥈ᰝᏛ఍㸪Ꮫ⾡ㅮ₇఍ㅮ₇ㄽᩥ㞟㸪pp.28-31.
ᒣᮏⱥ࿴㸪బ⸨ྐె㸪㰺⸨๛ (2016)㸪⚟ᓥ┴ࡢᗈᖏᇦࣜࢽ࢔࢔ࣞ࢖࡛ほࡉࢀࡓᖖ᫬ᚤືࡢᆅ㟈Ἴᖸ΅ἲゎᯒ㸪ᖹᡂ 28 ᖺᗘᮾ໭ᆅᇦ⅏ᐖ⛉Ꮫ◊✲㸪➨ 52 ᕳㄽᩥ㞟㸪pp.263-268.

35

ᅗ1

౑⏝ࡋࡓ Hi-net ほ

ᅗ2

Ⅼࡢ఩⨨

౑⏝ࡋࡓ F-net ほࣜࢽ࢔࢔ࣞ࢖

ᅗ3

Hi-net ほ

Ⅼ N.NMEH(ᾉỤ)࡜

ᅗ4Hi-net ほ

Ⅼཬࡧ

⥺ࡢ఩⨨

Ⅼ N.NMEH(ᾉỤ)࡜

H.TDMH(ྈぢ)ࡢ 2 Ⅼ㛫ࡢつ᱁໬ࢡࣟࢫ

H.TDMH(ྈぢ)ࡢࢡࣟࢫࢫ࣌ࢡࢺࣝ᣺ᖜ࡜

ࢫ࣌ࢡࢺࣝࡢᐇ㒊᥎ᐃ఩┦㏿ᗘ

ᅗ5

࿘ᮇ 8 ⛊࡟࠾ࡅࡿ 275 ಶࡢࣃࢫ࠿ࡽ࡞ࡿ఩┦㏿ᗘศᕸ

ᅗ6

࿘ᮇ 3 ⛊࡟࠾ࡅࡿ 215 ಶࡢࣃࢫ࠿ࡽ࡞ࡿ఩┦㏿ᗘศᕸ

36

ᅗ7

῝ࡉ 5km ࡟࠾ࡅࡿࢳ࢙ࢵ࣮࣮࢝࣎ࢻࢸࢫࢺࠋ
ᕥᅗࡀึᮇࣔࢹࣝ㸪ྑᅗࡀ㏫ゎᯒࣔࢹࣝࠋ

ᅗ 9 ῝ࡉ 3km ࡢ᥎ᐃ S Ἴ㏿ᗘᵓ㐀

Depth(km)ᅗ 8 ῝ࡉ 5km ࡢ᥎ᐃ S Ἴ㏿ᗘᵓ㐀Longitude(°)

S-velocity(km/s)
ᅗ 10 ⦋ᗘ 37.56 ᗘ࡟࠾ࡅࡿᮾす᩿㠃ࡢS Ἴ㏿ᗘศᕸ

ᅗ 11 ⚟ᓥ┴ࡢᆅ㉁ᅗ

東北地域災害科学研究37

第58巻（2022）

ᅵ⢏Ꮚࡢ㛫㝽ࢆὶࢀࡿỈࡢᣲື࡟㛵ࡍࡿᇶ♏ⓗ◊✲  ඵᡞᕤᴗ኱Ꮫ ᰟ㇂ ࡳ࡞ࡳඵᡞᕤᴗ኱Ꮫ ୖ㔝 ♩ឿ  ඵᡞᕤᴗ኱Ꮫ ୰ᮧ ඃ┿   ඵᡞᕤᴗ኱Ꮫ 㧗℩ ៅ௓ 1ࡣࡌࡵ࡟
 ㏆ᖺࠊ㇦㞵࡟ࡼࡿ⅏ᐖࡀ⥆࠸࡚࠸ࡿࠋࡇࢀࡣᆅ⌫つᶍࡢẼೃኚື࡟ࡼࡗ࡚ࡉࡽ࡟ཝࡋࡃ࡞ࡾ㸪௒ᚋࡶ㇦㞵⅏ᐖࡣቑຍࡋ࡚࠸ࡃ࡜⪃࠼ࡽࢀࡿࠋ㇦㞵⅏ᐖࡢ୰࡛ᩳ
㠃ᔂቯࠊሐ㜵◚ሐࠊᆅ┙ᮦᩱࡢὶኻ࡞࡝ࡢ⌧㇟ࡀⓎ⏕ࡋ⅏ᐖࡢ⿕ᐖࢆᣑ኱ࡍࡿせᅉ࡜࡞ࡗ࡚࠸ࡿࠋࡇࢀࡽࡢ
ࣜࢫࢡࡢணࡸホ౯ࡢࡓࡵ࡟ࡣᅵ࡜Ỉࡢ┦஫స⏝ຊࡢࣔࢹࣝࡢ⢭ᗘྥୖࡀᚲ㡲࡛࠶ࡿ㸬⢏Ꮚ⩌ࡢ㛫㝽ࢆὶࢀࡿỈࡢᣲື࡟ࡘ࠸࡚ࡣࠊྂࡃ࠿ࡽᐇ㦂ࠊゎᯒࡢᵝࠎ࡞◊✲ࡀ࡞ࡉࢀ࡚࠸ࡿࠋ≉࡟㸪ᆅ┙ᕤᏛ࡟࠾ࡅࡿ㏱Ỉၥ෗┿㸫 ᩳ㠃ᔂቯ  㢟࡟ࡘ࠸࡚ࡣ Darcy ๎ࡀ᭱ࡶᇶ♏ⓗ࡞ࣔࢹ࡛ࣝ࠶ࡾ㸪ࡉࡽ࡟㧗ᗘ࡞≀⌮࡜࡞ࡿ㠀 Darcy ὶࢀࡢຠᯝࡢᑟධࡢᚲせᛶࡶ㆟ㄽࡉࢀ࡚࠸ࡿࠋࡋ࠿ࡋ㠀
Darcy ὶࢀ࡟ࡘ࠸࡚ࡣᩘ್ゎᯒࡢ୰࡛ᢅ࠺ࡓࡵࡢᇶ┙ࡀ༑ศ࡟ᵓ⠏ࡉࢀ࡚࠸࡞࠸ࠋᐇ㝿ࡢᆅ┙ᮦᩱ࡟ࡣ⢏ᗘศᕸࡀᏑᅾࡋ㸪኱ᑠᵝࠎ࡞⢏ᚄࡢ⢏Ꮚ⩌ࡢ㞟ྜయ࡛࠶ࡿࠋࡼࡾ⌧ᐇ࡟๎ࡋࡓ㠀
Darcy ὶࢀࡢࣔࢹࣜࣥࢢࡢ㧗ᗘ໬ࡣ௒ᚋࡢᆅ┙ᮦᩱࡢᩘ್ゎᯒࡢࡓࡵ࡟ゎᾘࡍ࡭ࡁㄢ㢟ࡢ୍ࡘ࡛࠶ࡿࠋᮏ◊✲࡛ࡣ┤᥋ᩘ್ࢩ࣑࣮ࣗࣞࢩࣙࣥࡼࡿᾐ㏱ὶࡢᩘ್ゎᯒࢆ⾜࠸㸪ᆅ┙ᮦᩱࡢ≉ᛶࢆࢩ࣑࣮ࣗࣞࢩࣙࣥࢆ㏻ࡋ࡚⌮ゎࡍࡿࡇ࡜ࡀ┠ⓗ࡛࠶ࡿࠋᩘ್ゎᯒᡭἲࡣ᭷㝈せ⣲ἲࢆ⏝࠸࡚ᐇ᪋ࡍࡿࠋᮏ◊✲࡛ࡣ㸪㣬࿴ᅵ୰ࡢ㛫㝽Ỉࢆᐦᗘߩ㸪⢓ᛶಀᩘߤࢆࢽ࣮ࣗࢺࣥὶయ࡜௬ᐃࡋࡓ
࠺࠼࡛ࠊ᫬㛫 t㸪㏿ᗘ‫ݑ‬௜ ൌ ሺ‫ݑ‬ǡ ‫ݑ‬ǡ ‫ݓ‬ሻ㸪࠾ࡼࡧᅽຊ p ࡟㛵ࡍࡿᨭ㓄᪉⛬ᘧ࡛࠶ࡿ 3 ḟඖ NavierStokes ᪉⛬ᘧ 2)
߲‫ݑ‬௜
߲‫ݑ‬௜
ͳ ߲‫ݑ߲ ߲ ߤ ݌‬௜൅ ‫ݑ‬௝ൌെ൅ቆ ቇ ൅ ݂௜߲‫ݐ‬߲‫ݔ‬௝ߩ ߲‫ݔ‬௜ ߩ ߲‫ݔ‬௝ ߲‫ݔ‬௝࠾ࡼࡧࠊ㐃⥆ࡢᘧ
߲‫ݑ‬௜
ൌͲ
߲‫ݔ‬௜
ࢆᩘ್ィ⟬࡟ࡼࡗ࡚ゎࡃࠋ

*Study on the behavior of water flowing through the gaps of particle swarms by Minami Masaya,Reiji
Uwano,Yuma nakamura,Shinsuke Takase382࣓ࢵࢩࣗࢧ࢖ࢬࡢ᳨ウ ᾐ㏱ὶࡢࢩ࣑࣮ࣗࣞࢩ࡛ࣙࣥ⏝࠸ࡿ࣓ࢵࢩࣗࢧ࢖
ࢬࡢỴᐃࡢࡓࡵ࡟㸪⢏ᙧ 1.0mm ࡢ⌫ 2 ࡘ㓄⨨ࡋࡓࣔࢹࣝ㸦ᅗ̿1㸧ࡢゎᯒࢆ⾜ࡗࡓࠋ⌫࿘ࡾࡣ㠀ࡍ࡭ࡾ㸪ቨቃ⏺ࡣࡍ࡭ࡾቃ⏺࡜ࡍࡿࠋ࣓ࢵࢩࣗࢧ࢖ࢬࡣࡑࢀࡒࢀ



0.1㸪0.05㸪0.025 ࡜ࡋ㸪ືỈ໙㓄ࡣࡑࢀࡒࢀ 0.1㸪0.5 ࢆ୚࠼ࡓࠋ㛫㝽ὶయࡢࣃ࣓࣮ࣛࢱࡣɏ ൌ ͳͲͲͲ ݇݃Τ݉ଷ㸪Ɋ ൌᅗ̿ ࢸࢫࢺࣔࢹࣝ

ͳǤͲ ൈ ͳͲିଷ࣭ࡢỈࢆ⏝࠸ࡿ࣓ࢵࢩࣗࢧ࢖ࢬࡈ࡜ࡢ
᩿㠃ὶ㏿ࢆ⾲̿1㸪⾲̿2 ࡟♧ࡍࠋ࡝ࡕࡽࡶ࣓ࢵࢩࣗࢧ࢖ࢬࡀ 0.05 ࡢ᫬Ⅼ࡛᩿㠃ὶ㏿ࡣ཰᮰ࡋ࡚࠸ࡓࠋᮏゎᯒࡢつ๎㓄⨨ࣔࢹࣝࡣ⌫ࡢ┤ᚄ 1mm ࡢ᫬࡟࣓ࢵࢩࣗࢧ࢖ࢬࡀ 0.05 ࡜ࡑࢀࡒࢀ┤ᚄ࡟ᑐࡋ࡚ 20 ศ๭࡜࡞ࡿࡼ࠺࡟࣓ࢵࢩࣗࢧ࢖ࢬࢆ୚࠼ࡿࠋ
⾲̿1 ືỈ໙㓄 0.1 ࡢ᩿㠃ὶ㏿⾲̿2 ືỈ໙㓄 0.5 ࡢ᩿㠃ὶ㏿࣓ࢵࢩࣗࢧ࢖ࢬ

᩿㠃ὶ㏿[m/s]࣓ࢵࢩࣗࢧ࢖ࢬ

᩿㠃ὶ㏿[m/s]

0.025

0.108420.025

0.02782

0.05

0.10756

0.05

0.027210.1

0.094190.1

0.02121
3.ゎᯒᴫせ㸦1㸧つ๎㓄⨨ࣔࢹࣝつ๎㓄⨨ࣔࢹࣝࢆ⏝࠸ࡓᾐ㏱ὶࡢࢩ࣑࣮ࣗࣞࢩࣙࣥࢆ⾜࠺ࠋᆅ┙ᮦᩱ࡟㛵ࡍࡿࣃ࣓࣮ࣛࢱ
ࡢኚ໬࡟ྜࢃࡏ࡚㸪ෆ㒊ࡢᾐ㏱ὶࡀኚ໬ࡋ࡚࠸ࡃ㐣⛬ࡢ෌⌧ࢆヨࡳࡿࠋつ๎㓄⨨ࣔࢹ࡛ࣝࡣ⢏ᚄࡢኚ໬ࡸືỈ໙㓄ࡢኚ໬࡟╔┠ࡋ࡚ゎᯒࢆ⾜࠺ࠋࣔࢹࣝࡣᅗ̿1 ࡢࡼ࠺࡟సᡂࡍࡿࠋ⥺࡛♧ࡋࡓ㒊ศࡀゎᯒᑐ㇟ࡢ✵㛫࡛࠶ࡾ㸪ෆ㒊ࡢ⌫యࡀᅵ⢏Ꮚࢆ♧ࡍࠋ㛫㝽ὶయࡢࣃࣛ
࣓࣮ࢱࡣɏ ൌ ͳͲͲͲ ݇݃Τ݉ଷ㸪Ɋ ൌ ͳǤͲ ൈ ͳͲିଷ ࣭ࡢỈࢆ⏝࠸ࡿࠋゎᯒࣔࢹࣝ࡟⢏ᚄ 2.0mm㹼0.08mm ࡢࢫࢣ࣮ࣝࢆ⏝࠸ࡿࠋືỈ໙㓄ࡣ୍ᚊ࡛ 1.0 ࡜ࡍࡿࠋࡑࢀࡒࢀᐃᖖ࡞ὶࢀࡀᚓࡽࢀࡿࡲ࡛
ᾐ㏱ὶࡢࢩ࣑࣮ࣗࣞࢩࣙࣥࢆ⾜࠸㸪ゎᯒ⤖ᯝ࠿ࡽືỈ໙㓄୍ᐃ᮲௳࡛ࡢ⢏ᙧኚ໬࡟ᑐࡍࡿ㏱Ỉಀᩘࡢኚ໬ࢆࡳࡿࠋ

ᅗ̿2 つ๎㓄⨨ࣔࢹࣝ㸦2㸧୙つ๎㓄⨨ࣔࢹࣝ ୙つ๎㓄⨨ࣔࢹࣝࢆ⏝࠸ࡓᾐ㏱ὶࡢࢩ࣑࣮ࣗࣞࢩࣙࣥࢆ⾜࠺ࠋࣛࣥࢲ࣒ࣃࢵ࢟ࣥࢢ࡟ࡼࡗ࡚
సᡂࡋࡓゎᯒࣔࢹࣝ 3 ࡘࢆ౑⏝ࡍࡿࠋ⢏Ꮚᩘ࡜㛫㝽ẚࢆ⾲̿3㸪⢏ᗘศᕸࢆ⾲̿4 ࡟♧ࡍࠋ㛫㝽ὶయࡢࣃ࣓࣮ࣛࢱࡣɏ ൌ ͳͲͲͲ㸪Ɋ ൌ ͳǤͲ ൈ ͳͲିଷ ࣭ࡢỈࢆ⏝࠸ࡿࠋࡑࢀࡒࢀࡢࣔࢹࣝ࡟ᑐ
ࡋ࡚ 0.1㸪0.5㸪1.0 ࡜ືỈ໙㓄ࢆ୚࠼ࡿࠋ㏱Ỉ᪉ྥࡣᅗ̿3 ࡟♧ࡍࠋ

39

⾲̿3 ゎᯒࣔࢹࣝࡈ࡜ࡢ⢏Ꮚᩘ㸪㛫㝽ẚ
ゎᯒࣔࢹࣝ

⢏Ꮚᩘ

㛫㝽ẚ

࣓ࢵࢩࣗࢧ࢖ࢬ

ձ

430

0.93

1/20

ղ

473

0.78

1/20

ճ

488

0.72

1/20

⾲̿4 ⢏ᚄࡢΰྜẚ
ᅗ̿3 ᾐ㏱᪉ྥ

⢏ᚄ

ΰྜẚ

0.80

20㸣

0.91

20㸣

0.99

15㸣

1.03

45㸣

ഃ㠃ࡣቨቃ⏺㸪⌫࿘ࡾࡣ㠀ࡍ࡭ࡾቃ⏺㸪ቨቃ⏺ࡣࡍ࡭ࡾቃ⏺࡜ࡋ࡚࠸ࡿࠋࣔࢹࣝձ㹼ճࡢ୙つ๎㓄⨨ࣔࢹࣝࡣ௨ୗࡢᅗ࡟♧ࡍࠋ]ᅗ̿4 ࣔࢹࣝձ

]

[





[

ᅗ̿5 ࣔࢹࣝղ

ᅗ̿6 ࣔࢹࣝճ

4.ゎ
ゎ ᯒ⤖ᯝ
㸦1㸧つ๎㓄⨨ࣔࢹࣝつ๎㓄⨨ࣔࢹ࡛ࣝࡑࢀࡒࢀ㸪ᐃᖖ࡞ὶࢀࡀᚓࡽࢀࡿࡲ࡛ᾐ㏱ὶࡢࢩ࣑࣮ࣗࣞࢩࣙࣥࢆ⾜ࡗࡓࠋྛゎᯒࣔࢹࣝ࡟࠾࠸࡚ὶ㏿ࡢ್ࡀ୍ᐃ್࡟཰᮰ࡋࡓẁ㝵࡛ᐃᖖ࡜ࡍࡿࠋᮏゎᯒ࡛ᚓࡽࢀࡓ㸪ゎᯒ⤖ᯝ࠿ࡽ㸪ᐃᖖ≧ែ࡟࠾ࡅࡿᖹᆒ㏿ᗘࡢ್ࢆ⏝࠸࡚㸪ࢲࣝࢩ࣮๎࡟ࡼࡗ࡚㏱Ỉಀᩘࢆồࡵࡓࠋࡑࡢ⤖ᯝࢆᅗ̿7 ࡟♧ࡍࠋHazen ᘧࡸ Kozeny Carman ᘧࡢࡼ࠺࡞ Darcyࡣᩚ⌮ࡍࡿ࡜ಀᩘ

⢏ᙧ஧஌ࡢ㡯ࡢẚ౛⣔ࡢᙧ࡟ᩚ⌮࡛ࡁ㸪ᩘ್ゎᯒࡢ⤖ᯝࡀࡇࡢᙧ࡟ࡑ࠺࡜⥺ᙧ㏱Ỉ࡛࠶ࡿ࡜ࡉ
ࢀࡿࠋ㟷⥺ࡢ 2 ஌ẚ౛ࡣ᭱ึࡢ୍Ⅼ࠿ࡽࡑࡢࡲࡲᘏ㛗ࡋ࡚࠸ࡿࠋ⢏ᙧࣔࢹࣝࡀ኱ࡁࡃ࡞ࡿ࡟ࡘ
ࢀࠊᖹᆒ㏿ᗘࡣ኱ࡁࡃ࡞ࡾ㸪ὶࢀࡢ཰᮰ࡣ㐜ࡃ࡞ࡿࠋ⢏ᙧࡀᑠࡉ࡞ᅵ⢏Ꮚࡢゎᯒ⤖ᯝ࡟࠾࠸࡚ࠊ
⢏ᚄࡢ 2 ஌࡟ᑐࡍࡿẚ౛࡜ྜ࠺⤖ᯝࡀᚓࡽࢀࡓࠋ୍᪉㸪⢏ᚄࡀ኱ࡁ࠸ᅵ⢏Ꮚࡢゎᯒ⤖ᯝࡣ⢏ᚄ
ࡢ 2 ஌࡟ᑐࡍࡿẚ౛࠿ࡽ㞳ࢀࡿ⤖ᯝ࡜࡞ࡗࡓࠋ⢏ᚄࡢ኱ࡁ࡞ᅵ⢏Ꮚࡢ㏱Ỉ⌧㇟࡛ࡣ㸪ෆ㒊࡟ఱࡽ࠿ࡢὶࢀࡀⓎ⏕ࡋ࡚࠸ࡿࡇ࡜ࡀศ࠿ࡿࠋ

40⾲̿5 ὶ㏿࡜㏱Ỉಀᩘ
ὶ㏿

㏱Ỉಀᩘ

㹙mm㹛

㹙cm/s㹛

㹙cm/s㹛

0.08

0.018

0.018

0.1

0.028

0.028

0.2

0.112

0.112

0.4

0.427

0.427

0.6

0.894

0.894

0.8

1.423

1.423

1.0

1.978

1.978

1.5

3.313

3.313

2.0

4.441

4.441


մੵ݃Վ



ಃਭ‫ ਼ܐ‬FPVᅵ⢏Ꮚ┤ᚄཽ‫ܚ‬͹৒ർྭ








ཽ‫ ܚ‬FPᅗ̿7 ㏱Ỉಀᩘᅗ̿8 ⢏ᚄ 2.0 ࡢὶ⥺ᅗ㸦ᕥ㸧㸪⢏ᚄ 0.08 ࡢὶ⥺ᅗ㸦ྑ㸧                        ⢏ᚄ 2.0mm ࡜ 0.08mm ࡢᐃᖖ࡞≧ែ࡛ࡢὶ⥺ᅗࢆୖࡢᅗ̿8㸪ᅗ̿9 ࡟♧ࡍࠋ⢏ᚄࡢ኱ࡁ࠸
2.0mm ࡢὶ⥺ࡣ

ࡀⓎ⏕ࡋ㸪஘ࢀ࡚࠸ࡿᵝᏊࡀศ࠿ࡿࠋ㸦 2㸧୙つ๎㓄⨨ࣔࢹࣝ ୙つ๎㓄⨨ࣔࢹ࡛ࣝࡑࢀࡒࢀ㸪ᐃᖖ࡞ὶࢀࡀᚓࡽࢀࡿࡲ࡛ᾐ㏱ὶࡢࢩ࣑࣮ࣗࣞࢩࣙࣥࢆ⾜ࡗࡓࠋࡑࢀࡒࢀࡢࣔࢹࣝࡢゎᯒ⤖ᯝࢆ௨ୗࡢ⾲ 6㹼8 ࡜ᅗ 10㹼12 ࡟♧ࡍࠋ

41⾲̿6 ゎᯒࣔࢹࣝձ

⾲̿7 ゎᯒࣔࢹࣝղ

ືỈ໙㓄ࣞ࢖ࣀࣝࢬᩘ

ὶ㏿(mm/s)ືỈ໙㓄ࣞ࢖ࣀࣝࢬᩘ

ὶ㏿(mm/s)

0.10

1.93561.93560.10

1.26491.26490.50

8.25138.25130.50

5.74455.74451.00

14.4040

14.4040

1.00

10.3629

10.3629ᅗ̿10 ゎᯒࣔࢹࣝձ

ᅗ̿11 ゎᯒࣔࢹࣝղ⥺ᙧࡣືỈ໙㓄ࡀ୍␒ᑠࡉ࡞ࢣ࣮ࢫࡢὶ㏿ࢆ⾲̿8 ゎᯒࣔࢹࣝճ
ືỈ໙㓄ࣞ࢖ࣀࣝࢬᩘ

ὶ㏿(mm/s)

0.10

1.6862

1.68620.50

7.42847.42841.00

13.1874

13.1874ືỈ໙㓄ࡢቑຍ࡟ྜࢃࡏ࡚ 5 ಸ㸪10 ಸ࡜ࡋ࡚ࣉ
ࣟࢵࢺࡋࡓࡶࡢ࡜࡞ࡗ࡚࠸ࡿࠋ
3 ࡘࡢゎᯒࣔࢹࣝࡢ⤖ᯝ࠿ࡽ㸪ືỈ໙㓄ࡀ኱ࡁ࠸್࡟࡞ࡿ࡟ࡘࢀ㸪⥺ᙧ࠿ࡽእࢀ࡚࠸ࡃࡇ࡜ࡀ
ศ࠿ࡿࠋ⥺ᙧ㛵ಀࡀᡂࡾ❧ࡘࡣࡎ࡛࠶ࡿࡇ࡜࠿

18
15

Ꮚᩘࡀከࡃ㸪㛫㝽ẚࡢ್ࡀ኱ࡁ࠸ࣔࢹࣝձࡢὶ

12㏿ࡀ୍␒㏿࠸⤖ᯝ࡜࡞ࡗࡓࠋ
ླྀଐ(mm/s)ࡽࠊ᝿ᐃࡋࡓᾐ㏱ὶ࡜ࡣ␗࡞ࡿ⤖ᯝ࡜࡞ࡗࡓࠋ⢏ϠυϩᶇϠυϩᶇʤત‫ܙ‬ʥ

9
6



3



0

0



0.5
ಊਭ‫ޱ‬ഓ

1

ᅗ̿12 ゎᯒࣔࢹࣝճ5⤊ࢃࡾ࡟

⢏ᙧࣔࢹࣝࡀ኱ࡁࡃ࡞ࡿ࡟ࡘࢀ㸪ᖹᆒ㏿ᗘࡣ኱ࡁࡃ㸪ὶࢀࡢ཰᮰ࡣ㐜ࡃ࡞ࡾ㸪ᐇ㦂ⓗ࡟▱ࡽࢀ࡚࠸ࡿ⤖ᯝ࡜ఝࡓᾐ㏱ὶࡢᣲື࡜࡞ࡗࡓࠋ⢏ᚄࡢ኱ࡁ࡞ࣔࢹࣝࡢゎᯒ⤖ᯝ࡟⮳ࡗ࡚ࡣ㸪㏱Ỉ

42ῶᑡ࡟ᑐࡍࡿ㸪᪤Ꮡࡢ᥎ᐃࣔࢹ࡛ࣝࡣ࡜ࡽ࠼ࡿࡇ࡜ࡢ࡛ࡁ࡞࠸ὶࢀࡀⓎ⏕ࡋࡓ࡜⪃࠼ࡽࢀࡿࠋ
Navier-Stokes ᪉⛬ᘧࡢᩘ್ィ⟬࡟ࡼࡗ࡚㸪ᾐ㏱ὶࡢᣲືࢆ෌⌧࡛ࡁࡓࠋ௒ᚋ࡜ࡋ࡚㏱Ỉࢩ࣑࣮ࣗࣞࢩࣙࣥࡢ⤖ᯝ࠿ࡽࣞ࢖ࣀࣝࢬᩘࢆ⏝࠸ᩚ⌮ࡋつ๎㓄⨨ࣔࢹࣝ࡜㸪୙つ๎㓄⨨ࣔࢹࣝࡢᾐ
㏱ᣲື࡟ࡘ࠸࡚ࡲ࡜ࡵ࡚࠸ࡃணᐃ࡛࠶ࡿࠋᮏ◊✲ࡢゎᯒࣔࢹࣝࡣ⡆᫆ⓗ࡞ࡶࡢ࡛࠶ࡿࡓࡵࠊෆ
㒊ᵓ㐀ࡀࡼࡾ」㞧࡞ᐇ㝿ࡢᆅ┙ᮦᩱࡢᵓ㐀ࡢゎᯒࢆ⾜࠺ᚲせࡀ࠶ࡿࠋ

6.ཧ
ཧ ⪃ᩥ⊩
1) ᑠᒣෆಙᬛ㸸ᩳ㠃⅏ᐖࡢ⿕⅏ᆅࡢᆅᙧ࣭ᆅ㉁࡜ᩳ㠃ᔂቯࡢ≉ᚩ ໭ᾏ㐨㔞ᢏ⾡ㅮ₇఍    

2019.01.31 https://www.gsi.go.jp/common/000208624.pdf
2) Ikkoh Tachibana ,Shuji Moriguchi , Shinsuke Takase , Kenjiro Terada , Takayuki Aoki , Kohji
Kamiya , Takeshi Kodaka㸸Characterization of transition from Darcy to non-Darcy flow with 3D porelevel simulations Soils and Foundations Vol.57 5 ྕ 2017.10 p709

東北地域災害科学研究43

第58巻（2022）㏱᫂ᅵࣔࢹࣝࢆ⏝࠸ࡓᾐ㏱ὶࡢྍど໬ᡭἲ࡟
㛵ࡍࡿᇶ♏ⓗ◊✲ 㸨 ඵᡞᕤᴗ኱Ꮫ ୰ᮧ ඃ┿ ඵᡞᕤᴗ኱Ꮫ ୖ㔝 ♩ឿ ඵᡞᕤᴗ኱Ꮫ 㧗℩ ៅ௓ ඵᡞᕤᴗ኱Ꮫ 㔠Ꮚ ㈼἞  ࡣࡌࡵ࡟ ᪥ᮏࡣୡ⏺࡛ࡶ᭷ᩘࡢ⮬↛⅏ᐖ኱ᅜ࡛࠶ࡾ, ࡇࢀࡲ࡛ᵝࠎ࡞⅏ᐖ࡟ࡼࡿ⿕ᐖࢆཷࡅ࡚ࡁࡓࠋ
≉࡟᭱㏆࡛ࡣ, Ẽೃኚື࡟ࡼࡾ▷᫬㛫ࡢ࠺ࡕ࡟ᛴ࡟㝆ࡿ኱㞵ࡀⓎ⏕ࡍࡿ㢖ᗘࡣቑຍഴྥ࡟࠶ࡾ
1), 2018 ᖺ 6 ᭶ୗ᪪࠿ࡽ 7 ᭶࡟࠿ࡅ࡚ྎ㢼 7 ྕ࠾ࡼࡧᱵ㞵๓⥺࡞࡝࡟ࡼࡗ࡚ᘬࡁ㉳ࡇࡉࢀࡓ㞟୰㇦㞵㸦ᖹᡂ 30 ᖺ 7 ᭶㇦㞵㸧࡟ࡼࡾࠊす᪥ᮏࢆ୰ᚰ࡟໭ᾏ㐨ࡸ୰㒊ᆅ᪉࡞࡝ᗈ࠸⠊ᅖ࡛Ἑᕝࡢỏ℃ࡸሐ㜵ࡢỴቯ, ᅵ◁⅏ᐖ࡞࡝⏒኱࡞⿕ᐖࡀⓎ⏕ࡋࡓࠋ㏆ᖺୖ㝣ࡍࡿྎ㢼ࡀᖺࠎ኱ᆺ໬࠿
ࡘప㏿໬ࡋ࡚࠸ࡿࡇ࡜࠿ࡽ, ௒ᚋࡶẼೃኚື࡟ࡼࡿ⮬↛⅏ᐖࡀⓎ⏕ࡍࡿ㢖ᗘࡣቑຍࡋ࡚࠸ࡃ࡜
⪃࠼ࡽࢀࡿࠋ
㟷᳃┴࡛ࡶ, ௧࿴ 3 ᖺ 8 ᭶࡟㞟୰㇦㞵࡟ࡼࡿᅵ◁ᔂࢀࡀⓎ⏕ࡋ, ኱ࡁ࡞⿕ᐖࢆཷࡅࡓࠋ㇦㞵࡟ࡼࡿᅵ◁⅏ᐖࡢཎᅉࡢ୍ࡘ࡜ࡋ࡚ᾐ㏱࡟ࡼࡿෆ㒊ᾐ㣗ࡀᣲࡆࡽࢀࡿࠋࡋ࠿ࡋ, ෆ㒊ᾐ㣗ࡢⓎ⏕࣭㐍⾜࣓࢝ࢽࢬ࣒࡟ࡘ࠸࡚ࡣ୙᫂࡞Ⅼࡀከ࠸ࠋෆ㒊ᾐ㣗ࡢྲྀࡾᢅ࠸ࡀ㞴ࡋ࠸⌮⏤࡜ࡋ࡚ࡣ, ┤᥋ほࡍࡿࡇ࡜ࡢ࡛ࡁ࡞࠸ᅵ୰࡛㉳ࡇࡿࡇ࡜ࡀᣲࡆࡽࢀࡿࠋࡑࡇ࡛, ᆅ┙ࡢෆ㒊ࢆྍど໬ࡍࡿ◊✲ࡀከࡃ࡞ࡉࢀ࡚࠸ࡿࠋ
ᮏ◊✲࡛ࡣ, ᒅᢡ⋡࣐ࢵࢳࣥࢢᢏ⾡࡛ไసࡋࡓ㏱᫂ᅵࣔࢹࣝࢆ⏝࠸࡚㖄┤୍ḟඖᾐ㏱◚ቯᐇ㦂ࢆ⾜࠸, ⢏Ꮚࡢ㛫㝽ࢆὶࢀࡿᾐ㏱ὶࡢྍど໬ࢆ┠ⓗ࡜ࡋࡓࠋ
2.

㏱᫂ᅵࣔࢹࣝࡢ㑅ᐃ ᒅᢡ⋡࣐ࢵࢳࣥࢢᢏ⾡࡜ࡣ㏱᫂⢏Ꮚ࡜㛫㝽ὶయࡢ 2 ࡘࡢᒅᢡ⋡ࢆ୍⮴ࡉࡏࡿࡇ࡜࡛, ┤᥋ぢ࠼࡞࠸ෆ㒊ࡢ᩿㠃ࢆྍどගࡢࡶ࡜࡛ほᐹྍ⬟࡟ࡍࡿᐇ㦂ᡭἲ࡛࠶ࡿࠋ㏱᫂⢏Ꮚ࡜㛫㝽ὶయࡢ✀㢮࡟ࡼࡗ࡚ࡉࡲࡊࡲ࡞ᆅ┙ࢆసᡂࡍࡿࡇ࡜ࡀฟ᮶ࡿࠋ௦⾲ⓗ࡞ࡶࡢࢆ⾲-㸯࡟♧ࡍࠋ ᮏᐇ㦂࡛ࡣᅵࡢ୰ࡢὶࢀࢆ෌⌧ࡍࡿࡢ࡟᭱㐺࡞࢔ࢡ࢔ࣅ࣮ࢬࢆ౑⏝ࡋᐇ㦂ࢆ⾜࠺ࠋసᡂࡋࡓ
⾲-1 ௦⾲ⓗ࡞㏱᫂ᅵ࡜≉ᛶ

ᒅᢡ⋡
᭱㐺ࣔࢹࣝ
㛫㝽ὶయ

࢔ࣔࣝࣇ࢓ࢫࢩࣜ࢝
1.442
⢓ᅵ

ࢩࣜ࢝ࢤࣝ
1.442
◁

㖔Ἔࣈࣞࣥࢻ
⮯໬࢝ࣝࢩ࣒࢘

㖔Ἔࣈࣞࣥࢻ
⮯໬࢝ࣝࢩ࣒࢘

࢔ࢡ࢔ࣅ࣮ࢬ
1.333
ᅵࡢ୰ࡢὶࢀ
࡜࡚ࡶᙅ࠸ỿẊ≀Ỉ* A Basic Study on Visualization Method of Seepage Flow Using Transparent Soil Model44

ᅗ-1 సᡂࡋࡓ㏱᫂ᅵࣔࢹࣝ
ᕥ㸸࢔ࢡ࢔ࣅ࣮ࢬ㸦10mm㸧୰㸸࢔ࢡ࢔ࣅ࣮ࢬ㸦0.5mm㸧ྑ㸸ࢩࣜ࢝ࢤࣝ 㸦1mm㸧
㏱᫂ᅵࣔࢹࣝࢆᅗ-1 ࡟♧ࡍࠋ࢔ࢡ࢔ࣅ࣮ࢬࡣ㛫㝽ὶయ࡟Ỉࢆ౑ࡗ࡚࠸ࡿࡓࡵ, 㧗࠸㏱᫂ᗘࢆ♧ࡋ࡚࠸ࡿࠋࢩࣜ࢝ࢤࣝࡣỈ࡜ᒅᢡ⋡ࡀ␗࡞ࡿࡓ
ࡵ㏱᫂࡟ࡣ࡞ࡽ࡞࠸ࠋ
ࡲࡓ, ࢔ࢡ࢔ࣅ࣮ࢬࡣ྾Ỉᛶ࣏࣐࣮ࣜ࡜ࡶ࠸
࠸య✚ࡢ 200 ಸࡢỈࢆ྾཰ࡍࡿࡇ࡜ࡀฟ᮶ࡿࠋ
㸦ᅗ-2㸧ᅗ-2 ࢔ࢡ࢔ࣅ࣮ࢬ
ୖ㸸⤥Ỉ๓
ୗ㸸⤥Ỉᚋ

 ࡲࡓ, ⢊○ࡍࡿࡇ࡜࡛㏱Ỉಀᩘࢆኚ໬ࡉࡏࡿ
ࡇ࡜ࡀྍ⬟࡛࠶ࡿࠋ
3.

ᐇ 㦂ᴫせ

 ᾐ㏱◚ቯᐇ㦂⿦⨨ࢆᅗ-3 ࡟♧ࡍࠋ౑⏝
ࡍࡿ㈨ᩱࡣ࢔ࢡ࢔ࣅ࣮ࢬ㸦10mm㸧࡜ࡋࡓࠋ࢔ࢡ࢔ࣅ࣮ࢬࡣ, 㓄⨨࡟ࡼࡿὶࢀࡢ㐪࠸ࢆぢࡿࡓࡵつ๎㓄⨨࡜஺஫㓄⨨ࡢ㸰ࢣ࣮ࢫ⏝ពࡍࡿࠋ ẼἻࡀΰධࡋ࡞࠸ࡼ࠺ៅ㔜࡟సᴗࢆ⾜࠺ᚲせࡀ࠶ࡿࠋ ᐇ㦂ࡣὶ㔞ࢆ୍ᐃ࡟ಖࡕヨ㦂ᶵෆ࡟୍ᐃࡢὶࢀࢆⓎ⏕ࡉࡏࡓࡢࡕ࢖ࣥࢡࡢᢞධ
ཱྀ࠿ࡽ࢖ࣥࢡࢆᢞධࡋ
⢏Ꮚࡢ㛫㝽ࢆὶࢀࡿᾐ㏱ὶࡢືࡁࢆࣅࢹ
࣓࢜࢝ࣛࢆ౑⏝ࡋ᧜ᙳࡋࡓࠋ౑⏝ࡋࡓ࢖ࣥࢡࡣ, ୓ᖺ➹⏝࢖ࣥࢡࣈࣛࢵࢡ࡛࠶
ࡿࠋ

ᅗ-3 ᾐ㏱◚ቯᐇ㦂⿦⨨ᐇ㦂⿦⨨ࡣὶධཱྀ࡟ࣂࣝࣈࢆタ⨨ࡋ࡚࠾ࡾ, ௵ពࡢὶ㔞࡟ಖࡘࡇ࡜ࡀྍ⬟࡛࠶ࡿࠋ

45

4.

ᐇ 㦂⤖ᯝ

 ᐇ㦂⤖ᯝࢆᅗ-4 ࡟♧ࡍࠋ⢏Ꮚࡢ㛫㝽㛫ࢆὶࢀࡿᾐ㏱ὶࢆᚤどⓗ࡞ὶ⥺࡛ྍど໬ࡍࡿࡇ࡜ࡀฟ
᮶ࡓࠋࡋ࠿ࡋ, つ๎㓄⨨࡜஺஫㓄⨨࡟ࡼࡿὶࢀࡢ㐪࠸࡟ࡘ࠸࡚ࡣぢࡿࡇ࡜ࡀฟ᮶࡞࠿ࡗࡓࠋᐇ
㦂⤊஢ᚋࡢࣅ࣮ࢬࡢ㓄⨨ࢆ☜ㄆࡋࡓ࡜ࡇࢁ, つ๎㓄ิࡀᔂࢀ஺஫㓄ิࡢࡼ࠺࡟࡞ࡗ࡚࠸ࡓࠋ
࢔ࢡ࢔ࣅ࣮ࢬࡣ⾲㠃ࡀ⁥ࡽ࠿ࡔࡗࡓࡓࡵὶࢀ࡟ᢲࡉࢀࡿᙧ࡛㓄⨨ࡀኚ໬ࡋࡓࡶࡢ࡜ᛮࢃࢀࡿࠋ ࡲࡓ, PIV ゎᯒࢆ⏝࠸࡚ὶ㏿ศᕸࢆྍど໬ࡋࡓ⤖ᯝࢆᅗ-5 ࡟♧ࡍࠋ⢏Ꮚࡢ࿘ࡾࡢὶ㏿ࡢศᕸࢆ⡆᫆ⓗ࡛ࡣ࠶ࡿࡀ⾲⌧ࡍࡿࡇ࡜ࡀฟ᮶ࡓࠋࡋ࠿ࡋ, ┠ど࡛ࡣ, ࢖ࣥࢡࡢὶࢀ࡚࠸࡞࠸⟠ᡤ࡟ࡶ▮༳ࡀࣉࣟࢵࢺࡉࢀ࡚࠸ࡓࠋࡇࢀࡣ, ẼἻࡸ↷᫂࡟ࡼࡿ཯ᑕ➼࡟ࡼࡗ࡚ࢸࣥࣉ࣮ࣞࢺ࣐ࢵࢳ
ࣥࢢࡀୖᡭࡃ⾜ࢃࢀ࡞࠿ࡗࡓࡇ࡜ࡀཎᅉࡔ࡜ᛮࢃࢀࡿࠋ

 
᧜ᙳ㛤ጞ

3 ⛊ᚋ

5 ⛊ᚋ

 

 

᧜ᙳ㛤ጞ

3 ⛊ᚋ

5 ⛊ᚋ

ᅗ-4 ᐇ㦂⤖ᯝ㸦ᕥ㸸つ๎㓄⨨ ྑ㸸஺஫㓄⨨㸧

46

᧜ᙳ㛤ጞ

 

᧜ᙳ㛤ጞ

3 ⛊ᚋ

 

3 ⛊ᚋ

5 ⛊ᚋ

 

5 ⛊ᚋ

ᅗ-5 PIV ゎᯒ⤖ᯝ㸦ᕥ㸸つ๎㓄⨨ ྑ㸸஺஫㓄⨨㸧
5.

⤊ ࢃࡾ࡟

 ⢏Ꮚ㛫ࢆὶࢀࡿᾐ㏱ὶࢆ⡆᫆ⓗ࡛ࡣ࠶ࡿࡀᚤどⓗ࡟ྍど໬ࡍࡿࡇ࡜ࡀฟ᮶ࡓࠋࡋ࠿ࡋ, PIV ゎᯒࡣ, ࢸࣥࣉ࣮ࣞࢺ࣐ࢵࢳࣥࢢࡀୖᡭࡃ⾜ࡗ࡚࠸࡞࠸⟠ᡤࡀ࠶ࡗࡓ, ࡇࢀࡣẼἻࡢΰධࡸ↷᫂ࡢࣇࣜࢵ࣮࢝࡟ࡼࡿㄗᕪࡔ࡜⪃࠼ࡽࢀࡿࠋ ௒ᅇࡣ, ୍ḟඖࡢᾐ㏱ὶࢆྍど໬ࡋࡓࡀ, ௒ᚋࡣ୕ḟඖⓗ࡞ᾐ㏱ὶࡢྍど໬ࢆ⾜࠸, ᾐ㏱ὶ࡬ࡢ⌮ゎࢆࡼࡾ῝ࡵ࡚࠸ࡃᚲせࡀ࠶ࡿࠋཧ⪃ᩥ⊩1) Ẽ㇟ᗇ㸸Ẽೃኚື┘ど࣏࣮ࣞࢺ 20172) Magued Iskander㸸Modelling with Transparent Soils2010

東北地域災害科学研究47

第58巻（2022）

ᆅ┙ࡢᾮ≧໬ࢆຍ㏿ᗘᛂ⟅ࡢࡳ࠿ࡽ᥎ᐃࡍࡿࡓࡵࡢ≉ᚩ㔞ࡢศᯒᮾ໭኱Ꮫ ྜྷ␃኱⏕㸪㫽ᒇ㒊ెⱑ㸪ຍᮧ᫭Ⰻ㸪㢼㛫ᇶᶞ
1㸬 ࡣࡌࡵ࡟
ᆅ┙ࡢᾮ≧໬ࢆண

ุ࣭ᐃࡍࡿᡭἲࡣ㸪ᆅ┙ㄪᰝ⤖ᯝ࡟ᇶ࡙ࡃ⡆ุ᫆ᐃἲ࠿ࡽ㸪ᐊෆヨ㦂ࡸᩘ್ゎᯒ࡟ࡼࡿヲ⣽ἲࡲ࡛✀ࠎᏑᅾࡍࡿ㸬ࡋ࠿ࡋ㸪ࡇࢀࡽࡢᡭἲࡣ㸪᭱ࡶ⡆౽࡞ࡶࡢ࡛࠶ࡗ࡚
ࡶཎ఩⨨ࡢᆅ┙᝟ሗࢆᚲせ࡜ࡍࡿࡓࡵ㸪ᗈᇦ࡛ࡢ༶᫬ⓗホ౯ࡸ㸪ᾮ≧໬ࣜࢫࢡࡢ୍ḟࢫࢡ࣮ࣜࢽࣥࢢ➼ࡢほⅬ࡛ㄢ㢟ࡀ࠶ࡿ㸬ࡇࡢࡼ࠺࡞⫼ᬒ࠿ࡽ㸪Kamura et al. 1)ࡣ㸪ᆅ㟈ືࡢຍ㏿ᗘグ㘓ࡢࡳ࠿ࡽᆅ┙ࡢᾮ≧໬ࢆணุᐃࡍࡿ῝ᒙᏛ⩦ᢏ⾡ࢆᥦ᱌ࡋ࡚࠸ࡿ㸬ࡉࡽ࡟㸪㫽ᒇ㒊ࡽ 2)ࡣ㸪ࡇࡢࣔࢹࣝ࡟ᑐࡋ࡚㸪K-NET ࠾ࡼࡧ KiK-net3㸧ほ⥙ࡢࢹ࣮ࢱࢆ฼⏝ࡋ㸪ᗈᇦ࡛ࡢ㐺⏝ᛶࢆ᳨ウࡋࡓ㸬ࡇࢀࡽᡂᯝ࡛ࡣ㸪ᾮ≧໬ุᐃ࡟㛵ࡋ୍࡚ᐃࡢጇᙜᛶࡣ♧ࡉࢀ࡚࠸ࡿࡶࡢࡢ㸪ྠ᫬࡟㸪ࡉࡽ࡞ࡿᩍᖌࢹ࣮ࢱ㸦ᾮ≧໬᫬ࡢຍ㏿ᗘࢹ࣮ࢱ㸧࡜≉ᚩ㔞ホ౯ࡢᚲせᛶࡀᣦ᦬ࡉࢀ࡚࠸ࡿ㸬ࡑࡇ࡛ᮏ◊✲࡛ࡣ㸪Kamura et al. 1)ࡀ⾜ࡗࡓ᣺ືྎᐇ㦂ࡢ 1 ḟࢹ࣮ࢱ࡟╔┠ࡋ㸪ᾮ≧໬᫬࡟᭷ព࡟ኚ
໬ࡍࡿྛ✀≉ᚩ㔞ࡢヲ⣽࡞ศᯒࢆᐇ᪋ࡋࡓ㸬2㸬 ᐇ㦂ࢹ࣮ࢱࡢྲྀᚓ࡜ศᯒᑐ㇟
ᮏ◊✲࡛ࡣ㸪3 ḟඖຍ㏿ᗘධຊ࡟ࡼࡿ㣬࿴ᆅ┙ࡢ᣺ືྎᐇ㦂 120 ࢣ࣮ࢫࡢ⤖ᯝ  ࡜௒ᅇᐇ᪋
ࡋࡓ 119 ࢣ࣮ࢫࡢ⤖ᯝࢆྜࢃࡏࡓ 239 ࢣ࣮ࢫࡢᐇ㦂⤖ᯝ࠿ࡽᚓࡽࢀࡓᆅ⾲㠃ᛂ⟅ຍ㏿ᗘࢹ࣮ࢱࢆศᯒᑐ㇟࡜ࡋࡓ㸬ධຊᆅ㟈ືࡣ㸪⾲ 1 ࡟♧ࡍࡶࡢࢆ౑⏝ࡋ㸪᣺ᖜࢆ௵ពಸࡍࡿࡇ࡜࡛␗࡞ࡿ
Ἴᙧࢆ」ᩘసᡂࡋࡓ㸬ᆅ㟈ືࡢ⥅⥆᫬㛫ࡣ㸪ຍ㏿ᗘࡢ᭱኱್ࡢ 5㸣ࡀ᭱ึ࡟⌧ࢀ࡚࠿ࡽ㸪᭱ᚋ࡟⌧ࢀࡿࡲ࡛ࡢ᫬㛫࡜ᐃ⩏ࡋࡓ㸬ࡇࡢᆅ㟈ືࡢ⥅⥆᫬㛫ࢆ 3 ➼ศࡋ㸪ᚋ༙ࡢ 2/3 ༊㛫࡟࠾࠸࡚㸪㐣๫㛫㝽Ỉᅽࡢ᫬้Ṕᖹᆒࡀ㧗࠸ࢹ࣮ࢱ࡜ప࠸ࢹ࣮ࢱ㸦ᚋ㏙㸧࡟ศࡅ㸪ࡑࢀࡽ≉ᛶࡢ㐪࠸ࢆศᯒࡋࡓ㸬ࡇࡢศ㢮ࡣཧ⪃ᩥ⊩ 1)ࡢᾮ≧໬ࡢศ㢮ᐃ⩏࡟ᑐᛂࡋ࡚࠸ࡿ㸬࡞࠾㸪ᅗ 1 ࡟ࡣᆅ㟈ືࡢධຊࢹ࣮ࢱ࡜㸪ࣛࣥࢽࣥࢢࢫ࣌ࢡࢺࣝゎᯒࡢኚ໬ࡢ౛ࢆ♧ࡍ㸬ࡇࡢࡼ࠺࡟ࡋ࡚ྲྀᚓࡋࡓ᣺ືྎᐇ㦂ࡢຍ㏿ᗘࢹ࣮ࢱ㸦 ḟࢹ࣮ࢱ㸧ࢆฎ⌮ࡍࡿࡇ࡜࡛㸪ձ᭱኱ຍ㏿ᗘ㸦3 ᪉ྥ㸧ղ1 ḟ༟㉺࿘Ἴᩘ㸦3 ᪉ྥ㸧㸪ճ㟈ᗘ㸪մᆅ㟈ື⥅⥆᫬㛫㸪յ᭱኱㏿ᗘ㸦3 ᪉ྥ㸧㸪նSI ್㸪շH/V ࢫ࣌ࢡࢺࣝẚࡢ᭱኱್ࢆ≉ᚩ㔞࡜ࡋ࡚ᚓ࡚࠸ࡿ㸬ࡲࡓձ᭱኱ຍ㏿ᗘ㸪ղ1ḟ༟㉺࿘Ἴᩘ㸪յ᭱኱㏿ᗘ㸪շH/V ࢫ࣌ࢡࢺࣝẚ࡟ࡘ࠸࡚ࡣ᫬้Ṕ 3 ศ๭ࡋࡓ༊㛫ẖࡢ᭱኱್ࢆྲྀᚓࡍࡿࡇ࡜࡛㸪᫬㛫ኚ໬ࡢホ౯ࡶ⾜ࡗࡓ㸬3㸬 ࣟࢪࢫࢸ࢕ࢵࢡᅇᖐศᯒࡢᴫせ
239 ࡢἼᙧࢹ࣮ࢱࢆศᯒᑐ㇟࡜ࡋ㸪┠ⓗኚᩘ࡟㐣๫㛫㝽Ỉᅽẚ 0.6 ௨ୖࡢࢹ࣮ࢱࢆࠕ1ࠖ㸪㐣๫㛫㝽Ỉᅽẚ 0.6 ᮍ‶ࡢࢹ࣮ࢱࢆࠕ0ࠖ࡜タᐃࡋࡓ㸬ࡇࡢㄝ᫂ኚᩘ࡟ࡣ㸪 ḟࢹ࣮ࢱࡢ≉ᚩ㔞࡟ຍ࠼㸪ձ᭱኱ຍ㏿ᗘ㸪ղ1 ḟ༟㉺࿘Ἴᩘ㸪յ᭱኱㏿ᗘ㸪շH/V ࢫ࣌ࢡࢺࣝẚࡢྛ≉ᚩ㔞ࡢኚ໬ẚ⋡ࡶ㏣ຍࡋࡓ㸬ࡇࡇ࡛㸪ኚ໬ẚ⋡ࡣྛ≉ᚩ㔞ࡀ  ༊㛫ࡢ࠺ࡕ࡟࡝ࡢ⛬ᗘኚ໬ࡋࡓ࠿ࢆ♧ࡍᣦᶆ࡜ᐃ⩏ࡋ㸪ྛ≉ᚩ㔞࡟ࡘ࠸࡚㸪㸦╔┠ࡍࡿ༊㛫ࡢ್㸧㸦╔┠ࡍࡿ༊㛫ࡢ๓ࡢ್㸧࡜ࡋࡓ㸬* Analysis of feature amount for estimating liquefaction degree based only on seismic data by Taisei Yoshitome

48⾲ 1 ᣺ືྎᐇ㦂 239 ࢣ࣮ࢫࡢධຊᆅ㟈ື㸦ཎἼᙧ㸧
ほ

ᆅⅬ

ほ

᪥

ᆅ㟈ྡ

▼ᕳ㸦ᐑᇛ㸧

2003. 5. 26

ᐑᇛ┴Ἀᆅ㟈

㛗ᒸ㸦᪂₲㸧

2004. 10. 23

᪂₲┴୰㉺ᆅ㟈᯽ᓮ㸦᪂₲㸧

2007. 7. 16

᪂₲┴୰㉺Ἀᆅ㟈ᾆᏳ㸦༓ⴥ㸧

2011. 3. 11

ᮾ໭ᆅ᪉ኴᖹὒἈᆅ㟈Ᏹᅵ㸦⇃ᮏ㸧

2016. 4. 14⇃ᮏᆅ㟈Ɫᑠ∾㸦໭ᾏ㐨㸧2018. 9. 6

໭ᾏ㐨⫹᣺ᮾ㒊ᆅ㟈㮵ᔱ㸦Ⲉᇛ㸧

2011.3.11

ᮾ໭ᆅ᪉ኴᖹὒἈᆅ㟈ᮾ໭ᆅ᪉ኴᖹὒἈᆅ㟈௒ᕷ㸦ᰣᮌ㸧

2011.3.11

ᑠྡ὾㸦⚟ᓥ㸧

2011.4.11⚟ᓥ┴὾㏻ࡾࡢᆅ㟈బ಴㸦༓ⴥ㸧

2011.3.11

ᮾ໭ᆅ᪉ኴᖹὒἈᆅ㟈


ᇹᵏғ᧓

ᇹᵐғ᧓

ᇹᵑғ᧓

ᵐᵎᵎᵎ
ᵏᵔᵎᵎ

ьᡮࡇ ᵆᵥᵿᶊᵇ

ᵏᵐᵎᵎ
ᵖᵎᵎ
ᵒᵎᵎ
ᵎ

ᵋᵒᵎᵎ

ᵎ

ᵏᵎ

ᵐᵎ

ᵑᵎ

ᵋᵖᵎᵎ

ᵋᵏᵐᵎᵎ
ᵋᵏᵔᵎᵎ
ᵋᵐᵎᵎᵎ

଺᧓ ᵆᶑᵇa) ᆅ㟈ື᫬⣔ิຍ㏿ᗘἼᙧࢢࣛࣇ

b) 2 ༊㛫ࣇ࣮࢚ࣜࢫ࣌ࢡࢺࣝ

c) 3 ༊㛫ࣇ࣮࢚ࣜࢫ࣌ࢡࢺࣝ

ᅗ 1 ᆅ㟈ື⥅⥆᫬㛫ࡢ 3 ༊㛫ศ๭࡜ࣛࣥࢽࣥࢢࢫ࣌ࢡࢺࣝࡢゎᯒ⤖ᯝࡢ౛4㸬
㸬 ศᯒ⤖ᯝ
 ḟࢹ࣮ࢱࡢᗘᩘศᕸ ḟࢹ࣮ࢱࡢᗘᩘศᕸࡢ୍౛ࢆᅗ 2 ࠿ࡽᅗ 4 ࡟♧ࡍ㸬ࡲࡎ㸪ᅗ 2 ࡟♧ࡍ㐣๫㛫㝽Ỉᅽẚ 0.6 ௨ୖࡢࢹ࣮ࢱ⩌ࡢ᭱኱ຍ㏿ᗘ࡟╔┠ࡍࡿ㸬➨ 1 ༊㛫࡛ 200 Gal ௨ୖࡢࢡࣛࢫࡀ༙ᩘ௨ୖࢆ༨ࡵ࡚
࠾ࡾ㸪➨ 2 ༊㛫࡟࠿ࡅ࡚ࡣ኱ࡁࡃኚ໬ࡏࡎ㸪➨ 3 ༊㛫࡛⣙༙ᩘࡀ 100 Gal ௨ୗࡢࢡࣛࢫ࡟Ꮡᅾ
ࡋ࡚࠸ࡿ㸬୍᪉㸪ᅗ 3 ࡟♧ࡍ㐣๫㛫㝽Ỉᅽẚࡀ 0.2 ᮍ‶ࡢࢹ࣮ࢱ⩌࡟╔┠ࡍࡿ࡜㸪➨ 1 ༊㛫࡛ࡣ⣙ 6 ๭ࡀ 100 Gal ࡲ࡛ࡢࢡࣛࢫ࡟Ꮡᅾࡋ࡚࠸ࡿࡇ࡜ࡀࢃ࠿ࡿ㸬ࡑࡋ࡚➨ 2 ༊㛫࡟࠿ࡅ࡚኱ࡁ
࠸ࢡࣛࢫ࡬࡜ቑຍࡋ㸪➨ 3 ༊㛫࡛⣙ 7 ๭ࡀ 100 Gal ௨ୗࡢᑠࡉ࠸ࢡࣛࢫ࡟Ꮡᅾࡋ࡚࠸ࡿ㸬ࡇࢀࡽഴྥࡣ㸪㐣๫㛫㝽Ỉᅽẚ㸦ᾮ≧໬ࡢᗘྜ࠸㸧ࡀ㧗ࡃ࡞ࡿ࡜㸪ᆅ┙ࡢ๛ᛶࡀపୗࡋ࡚㸪ຍ㏿ᗘᛂ⟅ࣞ࣋ࣝࡀୗࡀࡿࡇ࡜࡟ᑐᛂࡋ࡚࠸ࡿ㸬ࡇࢀࡽࡢࡇ࡜࠿ࡽ㸪ᾮ≧໬ࡢ๓ᚋ࡛᭷ព࡟ኚ໬ࡍࡿ
ᣦᶆࡣ㸪ኚ໬ẚ⋡࡜ࡋ࡚ࢹ࣮ࢱࢭࢵࢺ໬ࡍࡿࡇ࡜ࡀ᭷ព⩏࡛࠶ࡿ࡜⪃࠼ࡽࢀࡿ㸬ᅗ 4 ࡢ SI ್࡟ࡘ࠸࡚ࡳࡿ࡜㸪ᾮ≧໬ᗘࡢ㧗࠸ࢹ࣮ࢱ⩌ࡣᾮ≧໬ᗘࡢప࠸ࢹ࣮ࢱ⩌࡟ẚ࡭࡚㸪኱ࡁ࠸ࢡࣛࢫ࡟
Ꮡᅾࡍࡿഴྥࡀ࠶ࡿ㸬ࡇࢀࡣ㸪ࡑࡶࡑࡶࡢධຊᆅ㟈ືࡢ኱ࡁࡉ࡟ࡼࡿࡶࡢ࡛࠶ࡿ㸬

ᵎᵌᵖ
ᵎᵌᵖ

ᵎᵌᵖ
ᵎᵌᵖ

ᵎᵌᵕ

ᵎᵌᵕ
ᵎᵌᵕ

ᵎᵌᵕ
ᵎᵌᵕ

ᵎᵌᵔ

ᵎᵌᵔ
ᵎᵌᵔ

ᵎᵌᵔ
ᵎᵌᵔ

ᵎᵌᵓ

ᵎᵌᵓ
ᵎᵌᵓ

ᵎᵌᵓ
ᵎᵌᵓ

ᵎᵌᵒ
ᵎᵌᵒ

ᵎᵌᵒ
ᵎᵌᵒ
ᵎᵌᵑ
ᵎᵌᵑ

ᵎᵌᵑ

ᵎᵌᵑ
ᵎᵌᵑ

ᵎᵌᵐ

ᵎᵌᵐ
ᵎᵌᵐ

ᵎᵌᵐ
ᵎᵌᵐ

ᵎᵌᵏ

ᵎᵌᵏ
ᵎᵌᵏ

ᵎᵌᵏ
ᵎᵌᵏ

ᵎ

ᵎᵎ

ᵎ

ᵏᵎᵎ
ᵏᵎᵎ
ᵐᵎᵎ
ᵐᵎᵎ
ᵑᵎᵎ
ᵑᵎᵎ
ᵒᵎᵎ
ᵒᵎᵎ
ᵓᵎᵎ
ᵓᵎᵎ
ᵔᵎᵎ
ᵔᵎᵎ
ᵕᵎᵎ
ᵕᵎᵎ
ᵖᵎᵎ
ᵖᵎᵎ
ᵗᵎᵎ
ᵗᵎᵎ
ᵏᵎᵎᵎ
ᵏᵎᵎᵎ
ᵏᵏᵎᵎ
ᵏᵏᵎᵎ
ᵏᵐᵎᵎ
ᵏᵐᵎᵎ
ᵏᵑᵎᵎ
ᵏᵑᵎᵎ
ᵏᵒᵎᵎ
ᵏᵒᵎᵎ

ᵎ
ᵏᵎᵎ
ᵏᵎᵎ
ᵐᵎᵎ
ᵐᵎᵎ
ᵑᵎᵎ
ᵑᵎᵎ
ᵒᵎᵎ
ᵒᵎᵎ
ᵓᵎᵎ
ᵓᵎᵎ
ᵔᵎᵎ
ᵔᵎᵎ
ᵕᵎᵎ
ᵕᵎᵎ
ᵖᵎᵎ
ᵖᵎᵎ
ᵗᵎᵎ
ᵗᵎᵎ
ᵏᵎᵎᵎ
ᵏᵎᵎᵎ
ᵏᵏᵎᵎ
ᵏᵏᵎᵎ
ᵏᵐᵎᵎ
ᵏᵐᵎᵎ
ᵏᵑᵎᵎ
ᵏᵑᵎᵎ
ᵏᵒᵎᵎ
ᵏᵒᵎᵎ

᫁ࡇ

ᵎᵌᵒ

᫁ࡇ
᫁ࡇ

᫁ࡇ

ᵎᵌᵖ

ᵏᵎᵎ
ᵐᵎᵎ
ᵑᵎᵎ
ᵒᵎᵎ
ᵓᵎᵎ
ᵔᵎᵎ
ᵕᵎᵎ
ᵖᵎᵎ
ᵗᵎᵎ
ᵏᵎᵎᵎ
ᵏᵏᵎᵎ
ᵏᵐᵎᵎ
ᵏᵑᵎᵎ
ᵏᵒᵎᵎ

᫁ࡇ

49

ьᡮࡇ ᵆᵥᵿᶊᵇ
ьᡮࡇ
ᵆᵥᵿᶊᵇ
ьᡮࡇ
ᵆᵥᵿᶊᵇ
ьᡮࡇ ᵆᵥᵿᶊᵇьᡮࡇ ᵆᵥᵿᶊᵇ       (a)➨ 1 ༊㛫       (b)➨ 2 ༊㛫       (c)➨ 3 ༊㛫ᅗ 2 3 ༊㛫ẖ࡛ࡢ㐣๫㛫㝽Ỉᅽẚ 0.6 ௨ୖࡢ᭱኱ຍ㏿ᗘࣄࢫࢺࢢ࣒ࣛ

ᵎᵌᵖ

ᵎᵌᵕ

ᵎᵌᵕ

ᵎᵌᵔ

ᵎᵌᵔ

ᵎᵌᵔ

ᵎᵌᵓ

ᵎᵌᵓ

ᵎᵌᵓ

ᵎᵌᵒ

᫁ࡇ

ᵎᵌᵖ

᫁ࡇ

ᵎᵌᵖ
ᵎᵌᵕ

ᵎᵌᵒ

ᵎᵌᵒ

ᵎᵌᵑ

ᵎᵌᵑ

ᵎᵌᵐ

ᵎᵌᵐ

ᵎᵌᵐ

ᵎᵌᵏ

ᵎᵌᵏ

ᵎᵌᵏ

ᵎ

ᵎ

ᵎ
ᵏᵎᵎ
ᵐᵎᵎ
ᵑᵎᵎ
ᵒᵎᵎ
ᵓᵎᵎ
ᵔᵎᵎ
ᵕᵎᵎ
ᵖᵎᵎ
ᵗᵎᵎ
ᵏᵎᵎᵎ
ᵏᵏᵎᵎ
ᵏᵐᵎᵎ
ᵏᵑᵎᵎ
ᵏᵒᵎᵎ

ьᡮࡇ ᵆᵥᵿᶊᵇ

ᵎᵌᵑ

ᵏᵎᵎ
ᵐᵎᵎ
ᵑᵎᵎ
ᵒᵎᵎ
ᵓᵎᵎ
ᵔᵎᵎ
ᵕᵎᵎ
ᵖᵎᵎ
ᵗᵎᵎ
ᵏᵎᵎᵎ
ᵏᵏᵎᵎ
ᵏᵐᵎᵎ
ᵏᵑᵎᵎ
ᵏᵒᵎᵎ

ᵏᵎᵎ
ᵐᵎᵎ
ᵑᵎᵎ
ᵒᵎᵎ
ᵓᵎᵎ
ᵔᵎᵎ
ᵕᵎᵎ
ᵖᵎᵎ
ᵗᵎᵎ
ᵏᵎᵎᵎ
ᵏᵏᵎᵎ
ᵏᵐᵎᵎ
ᵏᵑᵎᵎ
ᵏᵒᵎᵎ

᫁ࡇ



ьᡮࡇ ᵆᵥᵿᶊᵇьᡮࡇ ᵆᵥᵿᶊᵇ

ᵎᵌᵔ

ᵎᵌᵔ

ᵎᵌᵓ

ᵎᵌᵓ

ᵎᵌᵒ

ᵎᵌᵒ

᫁ࡇ

᫁ࡇ

        (a)➨ 1 ༊㛫      (b)➨ 2 ༊㛫       (c)➨ 3 ༊㛫ᅗ 3 3 ༊㛫ẖ࡛ࡢ㐣๫㛫㝽Ỉᅽẚ 0.2 ᮍ‶ࡢ᭱኱ຍ㏿ᗘࣄࢫࢺࢢ࣒ࣛ

ᵎᵌᵑ

ᵎᵌᵑ

ᵎᵌᵐ

ᵎᵌᵐ

ᵎᵌᵏ

ᵎᵌᵏ

ᵎ

ᵎ

ᵓ ᵏᵎᵏᵓᵐᵎᵐᵓᵑᵎᵑᵓᵒᵎᵒᵓᵓᵎᵓᵓᵔᵎ

ᵓ ᵏᵎᵏᵓᵐᵎᵐᵓᵑᵎᵑᵓᵒᵎᵒᵓᵓᵎᵓᵓᵔᵎ

ᵱᵧ͌

ᵱᵧ͌

 (a)㐣๫㛫㝽Ỉᅽẚ 0.6 ௨ୖ (b)㐣๫㛫㝽Ỉᅽẚ 0.2 ᮍ‶ᅗ 4 ඲༊㛫࡛ࡢ SI ್ࣄࢫࢺࢢ࣒ࣛ
ࣟࢪࢫࢸ࢕ࢵࢡᅇᖐศᯒࡢ⤖ᯝ ࣟࢪࢫࢸ࢕ࢵࢡᅇᖐศᯒࡢ⤖ᯝࢆ⾲ 2 ࡟♧ࡍ㸬࢜ࢵࢬẚࡢ್ࡀ  ௨ୗࡢ㡯┠ࡣ㐣๫㛫㝽Ỉᅽࡢప࠸ࢣ࣮ࢫ࡟ᙳ㡪ࢆཬࡰࡋ࡚࠾ࡾ㸪್ࡀ  ௨ୖࡢ㡯┠ࡣ㐣๫㛫㝽Ỉᅽࡀ㧗࠸ࢣ࣮ࢫ࡟ᙳ
㡪ࢆཬࡰࡋ࡚࠸ࡿ࡜ㄞࡳྲྀࡿࡇ࡜ࡀ࡛ࡁࡿࡢ࡛㸪ࡇࢀࡽ⤖ᯝࡼࡾ㸪ຍ㏿ᗘ㸦Ỉᖹ㸪㖄┤ᡂศ㸧ࡸ㸪1 ḟ༟㉺࿘Ἴᩘ㸪㏿ᗘ㸦Ỉᖹ㸪㖄┤ᡂศ㸧ࡑࡢࡶࡢࡢ್ࡼࡾࡶ㸪ኚ໬ẚ⋡ࡢ᪉ࡀᆅ┙ࡢᾮ≧໬๓ᚋ࡛ኚ໬ࢆᤊ࠼ࡸࡍ࠸ࡇ࡜ࡀศ࠿ࡿ㸬ࡲࡓ㸪➨ 1 ༊㛫࠿ࡽ➨ 2 ༊㛫࡟࠿ࡅ࡚ࡢỈᖹ᪉ྥࡢຍ㏿ᗘࡢኚ໬ẚ⋡ࢆࡳࡿ࡜㸪್ࡀ኱ࡁࡃ࡞ࡿ࡜㐣๫㛫㝽Ỉᅽࡢప࠸ࢣ࣮ࢫ࡟ᙳ㡪ࢆཬࡰࡋ࡚࠸

50

ࡿ㸬ࡇࢀࡣ㸪ᆅ┙ࡢ๛ᛶࡀపୗࡋ࡚࠾ࡽࡎ㸪ຍ㏿ᗘᛂ⟅ࡀ኱ࡁࡃฟ࡚࠸ࡿࡓࡵ࡜ゎ㔘࡛ࡁࡿ㸬ࡉࡽ࡟㸪ྠ༊㛫ࡢ࿘Ἴᩘࡢኚ໬ẚ⋡࡟╔┠ࡍࡿ࡜㸪್ࡀ኱ࡁࡃ࡞ࡿ࡜㐣๫㛫㝽Ỉᅽẚࡢప࠸᪉࡟ᙳ㡪ࢆཬࡰࡋ࡚࠸ࡿࡇ࡜ࡀศ࠿ࡿ㸬ࡇࢀࡣ㐣๫㛫㝽Ỉᅽࡢ㧗࠸㸦ࡍ࡞ࢃࡕᾮ≧໬ࡋ࡚࠸ࡿ㸧ᆅ┙ࡣ㛗࿘ᮇ໬ࡍࡿࡇ࡜࡟ᑐᛂࡋ࡚࠸ࡿ㸬ࡲࡓ㸪㟈ᗘࡀ኱ࡁࡃ࡞ࢀࡤᾮ≧໬ᗘࡢ㧗࠸ᆅ┙࡟ᙳ㡪ࢆཬࡰࡋ࡚࠾ࡾ㸪୍⯡ⓗ࡞▱ぢ࡝࠾ࡾࡢഴྥࡶࡳࡽࢀࡿ㸬⾲ 2 ࣟࢪࢫࢸ࢕ࢵࢡᅇᖐศᯒ⤖ᯝ
㡯┠

࢜ࢵࢬẚ

➨1༊㛫Ỉᖹ᪉ྥࠉ᭱኱ຍ㏿ᗘ

0.984

㡯┠
࢜ࢵࢬẚ
1Ѝ2༊㛫ࠉỈᖹ1ḟ༟㉺࿘Ἴᩘࠉኚ໬ẚ⋡ 0.1௨ୗ

➨1༊㛫ୖୗ᪉ྥࠉ᭱኱ຍ㏿ᗘ

1.001

1Ѝ2༊㛫ࠉୖୗ1ḟ༟㉺࿘Ἴᩘࠉኚ໬ẚ⋡

6.508➨2༊㛫Ỉᖹ᪉ྥࠉ᭱኱ຍ㏿ᗘ

1.006

2Ѝ3༊㛫ࠉỈᖹ1ḟ༟㉺࿘Ἴᩘࠉኚ໬ẚ⋡

0.1௨ୗ

➨2༊㛫ୖୗ᪉ྥࠉ᭱኱ຍ㏿ᗘ

0.990

2Ѝ3༊㛫ࠉୖୗ1ḟ༟㉺࿘Ἴᩘࠉኚ໬ẚ⋡

0.371➨3༊㛫Ỉᖹ᪉ྥࠉ᭱኱ຍ㏿ᗘ

0.986

1Ѝ3༊㛫ࠉỈᖹ1ḟ༟㉺࿘Ἴᩘࠉኚ໬ẚ⋡

10௨ୖ
0.100

➨3༊㛫ୖୗ᪉ྥࠉ᭱኱ຍ㏿ᗘ

1.100

1Ѝ3༊㛫ࠉୖୗ1ḟ༟㉺࿘Ἴᩘࠉኚ໬ẚ⋡1Ѝ2༊㛫Ỉᖹຍ㏿ᗘࠉኚ໬ẚ⋡

0.264ᆅ㟈ື⥅⥆᫬㛫

0.989

1Ѝ2༊㛫ୖୗຍ㏿ᗘࠉኚ໬ẚ⋡

1.581

㟈ᗘ

10௨ୖ

2Ѝ3༊㛫Ỉᖹຍ㏿ᗘࠉኚ໬ẚ⋡10௨ୖ➨1༊㛫ࠉỈᖹ᪉ྥ᭱኱㏿ᗘ

1.019

2Ѝ3༊㛫ୖୗຍ㏿ᗘࠉኚ໬ẚ⋡

0.1௨ୗ

➨1༊㛫ࠉୖୗ᪉ྥ᭱኱㏿ᗘ

0.608

1Ѝ3༊㛫Ỉᖹຍ㏿ᗘࠉኚ໬ẚ⋡

0.1௨ୗ

➨2༊㛫ࠉỈᖹ᪉ྥ᭱኱㏿ᗘ

0.567

1Ѝ3༊㛫ୖୗຍ㏿ᗘࠉኚ໬ẚ⋡

0.400➨2༊㛫ࠉୖୗ᪉ྥ᭱኱㏿ᗘ

1.532➨1༊㛫Ỉᖹ᪉ྥࠉḟ༟㉺࿘Ἴᩘ

1.574➨3༊㛫ࠉỈᖹ᪉ྥ᭱኱㏿ᗘ

1.112➨1༊㛫ୖୗ᪉ྥࠉḟ༟㉺࿘Ἴᩘ

0.359➨3༊㛫ࠉୖୗ᪉ྥ᭱኱㏿ᗘ

0.418➨2༊㛫Ỉᖹ᪉ྥࠉḟ༟㉺࿘Ἴᩘ

1.362

1Ѝ2༊㛫ࠉỈᖹ᭱኱㏿ᗘࠉኚ໬ẚ⋡

2.369➨2༊㛫ୖୗ᪉ྥࠉḟ༟㉺࿘Ἴᩘ

1.473

1Ѝ2༊㛫ࠉୖୗ᭱኱㏿ᗘࠉኚ໬ẚ⋡

0.333➨3༊㛫Ỉᖹ᪉ྥࠉḟ༟㉺࿘Ἴᩘ

0.570

2Ѝ3༊㛫ࠉỈᖹ᭱኱㏿ᗘࠉኚ໬ẚ⋡

0.1௨ୗ
0.1௨ୗ

➨3༊㛫ୖୗ᪉ྥࠉḟ༟㉺࿘Ἴᩘ

0.999

2Ѝ3༊㛫ࠉୖୗ᭱኱㏿ᗘࠉኚ໬ẚ⋡➨1༊㛫ࠉH/Vࢫ࣌ࢡࢺࣝẚ

0.898

1Ѝ3༊㛫ࠉỈᖹ᭱኱㏿ᗘࠉኚ໬ẚ⋡

1.182➨2༊㛫ࠉH/Vࢫ࣌ࢡࢺࣝẚ2.519

1Ѝ3༊㛫ࠉୖୗ᭱኱㏿ᗘࠉኚ໬ẚ⋡10௨ୖ➨3༊㛫ࠉH/Vࢫ࣌ࢡࢺࣝẚ

0.492SI್Ỉᖹ᪉ྥ

1.282

H/Vࢫ࣌ࢡࢺࣝẚࠉኚ໬ẚ⋡

0.796




5㸬
㸬 ࡲ࡜ࡵ
3 ḟඖຍ㏿ᗘධຊ࡟ࡼࡿ᣺ືྎᐇ㦂ࡢ⤖ᯝ  ࢣ࣮ࢫࡢᆅ⾲㠃ᛂ⟅ຍ㏿ᗘ᫬้Ṕࢹ࣮ࢱࢆศ
ᯒࡋ㸪ᾮ≧໬㸦㐣๫㛫㝽Ỉᅽẚࡢୖ᪼㸧๓ᚋ࡛ኚ໬ࡍࡿ≉ᚩ㔞ࢆホ౯ࡋࡓ㸬ࣟࢪࢫࢸ࢕ࢵࢡᅇ
ᖐศᯒࡢ⤖ᯝ࠿ࡽ㸪ຍ㏿ᗘ㸦Ỉᖹ㸪㖄┤ᡂศ㸧㸪1 ḟ༟㉺࿘Ἴᩘ㸪㏿ᗘ㸦Ỉᖹ㸪㖄┤ᡂศ㸧࡟ࡘ࠸࡚ࡣ㸪ࡑࡢࡶࡢ⮬యࡢ್ࡼࡾࡶ㸪ኚ໬ẚ⋡ࡢ᪉ࡀᾮ≧໬ࡢᗘྜ࠸࡜⤖ࡧࡘࡅࡽࢀࡿࡇ࡜ࡢ࡛
ࡁࡿ≉ᚩ㔞࡜ࡋ࡚㸪᭷ព⩏࡛࠶ࡿࡇ࡜ࡀ♧ࡉࢀࡓ㸬௒ᚋࡢⓎᒎ࡜ࡋ࡚㸪౛࠼ࡤ Kamura et al. 1)ࡽ
ࡀᥦ᱌ࡋ࡚࠸ࡿᆅ㟈ືࡢࡳ࠿ࡽᾮ≧໬ࡢ⛬ᗘࢆุᐃࡍࡿᡭἲ࡟㐺⏝࡛ࡁࡿྍ⬟ᛶࡀ࠶ࡿ㸬
6㸬 ཧ⪃ᩥ⊩1) Kamura et al.: Exploring the possibility of assessing the damage degree of liquefaction based only on seismic records
by artificial neural networks, Soil and Foundations, Vol.61, Issue 3, pp.658 -674, 2021.
2) 㫽ᒇ㒊ెⱑ㸪ຍᮧ᫭Ⰻ㸪㢼㛫ᇶᶞ㸸ᙉ㟈ほ ࢹ࣮ࢱࡢࡳ࠿ࡽᆅ┙ࡢᾮ≧໬ࡢ⛬ᗘࢆุᐃࡍࡿ῝ᒙᏛ⩦ᢏ ⾡ࡢጇᙜᛶࡢ᳨ウ 㸫ᮾ໭ᆅ᪉ኴᖹὒἈᆅ㟈ࢆ஦౛࡜ࡋ࡚㸫㸪ᅵᮌᏛ఍(J1) AI࣭ࢹ࣮ࢱࢧ࢖࢚ࣥࢫ㸪➨ 2 ᕳ㸪➨
J2 ྕ㸪pp598-608㸪20213) 㜵 ⅏ ⛉ Ꮫ ᢏ ⾡ ◊ ✲ ᡤ 㸸 ᙉ 㟈 ほ⥙ 㸦 K-net, KiK-net 㸧 ᙉ 㟈 グ 㘓 㸦 2011 ᖺ 3 ᭶ 11 ᪥ 㸧㸪https://www.kyoshin.bosai.go.jp/kyoshin/quake/東北地域災害科学研究51

第58巻（2022）

ỏ℃Ỉᐦᗘࡢ᫬㛫ኚ໬ࢆ⪃៖ࡋࡓὠἼ㐳ୖ*୰ኸ኱Ꮫ◊✲㛤Ⓨᶵᵓ ᯇ෠ⱥኵ ࡣࡌࡵ࡟ ὠἼⲴ㔜ࡸṔྐ࣭᝿ᐃὠἼつᶍホ౯ࡢ㧗ᗘ໬ࡢどⅬ࡜ࡋ࡚ỏ℃Ỉᐦᗘρ㸪ỏ℃ὶࡢ㠀ᐃᖖᛶ㸪⛣ືᗋୗࡢỏ℃
ὶ㸦㠀ᐃᖖὶ㸧ࡢ᢬ᢠ๎࡞࡝ࡀ⪃࠼ࡽࢀࡿ1)ࠋ
 ᯇ෠ࡽ2) - 7)ࡣὠἼỏ℃Ỉᐦᗘρࡢධᑕࣇ࣮ࣝࢻᩘFriࡸᗏ㉁ᅵ◁⢏ᚄ㸦୰ኸ⢏ᚄd50㸧࡬ࡢ౫Ꮡᛶࢆᑠつᶍ⛣ືᗋᐇ㦂࡟ᇶ࡙࠸᳨࡚ウࡋ࡚࠸ࡿࠋᯇ෠8)ࡣ⛣ືᗋୗࡢὠἼỏ℃ὶࡢ᢬ᢠ๎ࢆୖグᐇ㦂ࡢࢹ࣮ࢱࢆ⏝࠸᳨࡚ウࡋ࡚࠸ࡿࠋᅗ1 ᐇ㦂Ỉ㊰ࡢᴫ␎ Ỉ㊰ഃቨࡣ┬␎ 㸪Ỉ㊰෗┿ ྑ➃ 㸪ᐃჾල࡞࡝ࡢ㓄⨨࡜ㅖグྕࡢᐃ⩏ࠋ᭤㠃࡛Ỉᖹὶࢆ☜ಖᯇ෠࣭᭷ᕝ9)ࡣỏ℃ỈᐦᗘࡢὠἼ㐳ୖ࡬ࡢᙳ㡪ࢆ⌮ㄽⓗ࡟᳨ウࡋ࡚࠸ࡿࠋ๓஧⪅ࡣᐇ㦂ࢹ࣮ࢱ㔞ࡀᑡ࡞࠸≧ἣୗ࡛ࡢ㸪ᚋ⪅ࡣỏ℃Ỉᐦᗘ࡜ࡋ࡚㐳ୖ㐣⛬ᖹᆒ10)ࢆ᝿ᐃࡋ
ࡓ᫬㛫ⓗ࡟୙ኚ࡞᮲௳ୗ࡛ࡢ᳨ウ࡛࠶ࡿࠋ ௨ୖࢆ⫼ᬒ࡟㸪ᮏ◊✲ࡣỏ℃Ỉᐦᗘᐇ㦂࡜ᅵ◁ࢆྵࡴ
ỏ℃ὶࡢ㐳ୖᐇ㦂ࢆ᪂ࡓ࡟⾜ࡗ࡚ᐇ㦂ࢹ࣮ࢱ㔞㸦⠊ᅖ㸧ࢆቑࡸࡋ㸦ᣑࡆ 㸪᪤ሗࡢỏ℃ὶࡢᦶ᧿ᦆኻಀᩘKࡸỏ
℃Ỉᐦᗘࡢホ౯ᐇ㦂ᘧ8)ࢆ᳨ドࡍࡿ࡜࡜ࡶ࡟㸪ᦶ᧿ᦆኻಀᩘࡔࡅ࡛࡞ࡃ㸪ỏ℃Ỉᐦᗘࡢ᫬㛫ኚ໬ࢆࡶ⪃៖ࡍࡿࡇ࡜࡛㸪᪤ሗࡢὠἼ㐳ୖ⌮ㄽ9)ࡢ㧗ᗘ໬ࢆᅗࡿࡇ࡜ࢆ┠ⓗ࡜ࡍࡿࠋᅗ2 ୧᪉ἲ࡟ࡼࡿධᑕỏ℃Ỉ῝hiࡢẚ㍑౛
 ỏ℃Ỉᐦᗘᐇ㦂࡜ỏ℃ὶ㐳ୖᐇ㦂(1) ᐇ㦂᪉ἲ᫬ኚ໬ࢆ ᐃࡍࡿࡓࡵ㸪ୖ࣭ୗὶ➃࡟㉸㡢ἼᘧỈ఩ィa) ᐇ㦂Ỉ㊰ ᐇ㦂Ỉ㊰ࡣ㸪⡆᫆࡟㧗ࢩ࣮ࣝࢬᩘࢆᚓࡿࡓࡵ㸪ᖜ0.3 㸦KEYENCE♫〇㸪UD-500㸧ࢆタ⨨ࡋࡓ ᅗ1ཧ↷ ࠋỈm ࡢࡍ࡭ࡾྎ≧ࡢ┤⥺㛤Ỉ㊰࡜ࡋࡓࠋࡓࡔࡋ㸪ࡍ࡭ࡾྎ ఩ィ㛫ࡢ㊥㞳ࡣ3.01 m㸪ྛỈ఩ィ఩⨨ࡢỈ㊰ᗏ㠃఩ࡣྠᩳ㠃ࡢୗ➃࡟ࡣᅵ◁ࢆᩜࡃࡓࡵ࡟㏱᫂ሷࣅᯈ〇ࡢỈᖹ㒊㸪ࡌ࡛㸪Ỉ఩ࡢࢧࣥࣉࣜࣥࢢ᫬㛫㛫㝸ࡣ0.01 s ࡛࠶ࡿࠋࡑࡢୗὶ➃࡟ࡣᅵ◁ࢆᕳ㎸ࢇࡔỏ℃ὶඛ➃㒊ࡢỏ℃Ỉ  Ỉᖹ㒊࡟࠾ࡅࡿὶἣほᐹ࡜ỏ℃ὶඛ➃⛣ື㏿ᗘ㸦ҫධ㸦ᅵ◁Ỉ㸧㔞ࢆㄪ⠇ࡋ࡚᥇Ỉࡍࡿࡓࡵ࡟⾲㠃ሬ⿦ࡋࡓྜ ᑕỏ℃ὶ㏿ui࡜௬ᐃ 㸪ึᮇᅵ◁ᒙᇦ୰ᚰ㒊࡟࠾ࡅࡿỏᯈ〇ࡢ▷ࡃ⦆࠸ୖࡾᩳ㠃㒊㸪ࡉࡽ࡟ỏ℃ὶ㐳ୖᐇ㦂࡛ࡣ ℃ὶ฿㐩ᚋࡢỏ℃Ỉ῝ࢆホ౯ࡍࡿࡓࡵ㸪Ỉᖹ㒊ࡢ୧ഃቨࡑࡢ▷ࡃ⦆࠸ୖࡾᩳ㠃㒊࡟⥆ࡅ࡚⾲㠃ሬ⿦ࡋ㸪⢏ᚄ0.85 ኳ➃࡜∦ഃቨ࡟ࢫࢣ࣮ࣝࢆ㓄⨨ࡋ㸪ୖ᪉࡜ഃ᪉࠿ࡽࣅࢹ
㹼2 mmࡢ◁ࢆ㈞௜ࡅࡓྜᯈ〇ࡢྠࡌ໙㓄ࢆᣢࡘᩳ㠃㒊 ࢜᧜ᙳࢆ⾜ࡗࡓࠋࢆタࡅࡓࠋᐇ㦂Ỉ㊰ࡢᴫ␎㸪ᚋ㏙ࡍࡿ ᐃჾල࡞࡝ࡢ㓄  ึᮇᅵ◁ᒙᇦ୰ᚰ㒊࡟࠾ࡅࡿධᑕỏ℃Ỉ῝hi࡜ධᑕࣇ⨨࡜ㅖグྕࡢᐃ⩏࡞࡝ࢆᅗ1࡟♧ࡍࠋᅗ୰㸪hDࡣỈᖹ㒊 ࣮ࣝࢻᩘFriࡣ2᪉ἲ࡛ホ౯ࡋࡓࠋ➨1ἲࡣࣅࢹ࢜᧜ᙳ࠿ࡽ
ࡢᗏ㠃࠿ࡽࡍ࡭ࡾྎୖ➃࡟Ỉᖹ࡟タ⨨ࡋࡓ㈓Ỉᵴ㸦㧗ࡉ ᚓࡽࢀࡿ᭱኱ධᑕỏ℃Ỉ῝hi1࡜ỏ℃ὶඛ➃⛣ື㏿ᗘuiࢆ2) - 7)
0.5 m㸪ᖜ0.3 m㸪㛗ࡉ1.7 m㸧ࡢᗏ㠃ࡲ࡛ࡢ㧗ࡉ㸪hUࡣ㈓Ỉ ⏝࠸ࡿ᪉ἲ 㸪➨2 ἲࡣึᮇᅵ◁ᒙᇦࡢୖ࣭ୗὶ➃࡟タ῝㸪LUࡣ㈓Ỉ㛗㸪S1ࡣࡍ࡭ࡾྎᩳ㠃ࡢ໙㓄㸪LSࡣỈᖹ㒊 ⨨ࡋࡓ㉸㡢ἼᘧỈ఩ィ࠿ࡽᚓࡽࢀࡿ᭱኱ධᑕỏ℃Ỉ῝ࡢึᮇᅵ◁ᒙᇦ㛗㸪hTࡣึᮇᅵ◁ᒙཌ㸪hS࡜S2ࡣ▷ࡃ⦆ hiu㸪hid ࢆᖹᆒࡋࡓධᑕỏ℃Ỉ῝him࡜ࣅࢹ࢜᧜ᙳ࠿ࡽᚓ
࠸ୖࡾᩳ㠃㒊ࡢỈᖹ㒊ᗏ㠃࠿ࡽࡢୖ➃㧗ࡉ࡜໙㓄࡛࠶ࡿࠋࡽࢀࡿỏ℃ὶඛ➃⛣ື㏿ᗘuiࢆ⏝࠸ࡿ᪉ἲ࡛࠶ࡿࠋᮏ◊ ὠἼỏ℃ὶࡣࢤ࣮ࢺᛴ㛤ὶࢀ࡛ᶍᨃࡋࡓࠋࢤ࣮ࢺࡣࡍ ✲ࡢᐇ㦂࡛ࡣ➨2ἲࢆ᥇⏝ࡋ㸪᪤ሗࡢᐇ㦂࡛᥇⏝ࡋࡓ➨1ἲࡣ➨2ἲࡢࢳ࢙ࢵࢡ࡟⏝࠸ࡿࠋᅗ2࡟➨1ἲ࡜➨2ἲ࡛࡭ࡾྎᩳ㠃ୖ➃ࡢ┤ࡄ⫼ᚋ࡟఩⨨ࡍࡿࠋホ౯ࡋࡓධᑕỏ℃Ỉ῝hi hi1㸪him ࡢẚ㍑౛ࢆ♧ࡍࠋ୧᪉b) Ỉ⌮㔞ࡢ ᐃ ึᮇᅵ◁ᒙᇦࡢୖ࣭ୗὶ➃࡟࠾ࡅࡿධᑕỏ℃Ỉ῝ࡢ⤒ ἲࡀ࡯ࡰྠࡌධᑕỏ℃Ỉ῝ࢆ୚࠼࡚࠸ࡿࡇ࡜ࡀุࡿࠋ
* Tsunami run-up considering time variation of density of inundation water by Hideo MATSUTOMI

52⾲1 ᐇ㦂᮲௳hS S2 MSDᐇ 㦂 hD LU hU S1 LS hTഛࢣ࣮ࢫ (m) (m) (m) (°) (m) (m) (m) (°) (kg)
⪃
Case1
82.8
Case2
88.8 ◡◁
Case3
84.8
Case4
35.5 ࢩࣝࢺ
Case5 0.34 1.7 0.25 5.1 3.01 0.06 0.11 7.4 85.2
Case6
82.4
Case7
73.0 ኳ↛◁
Case8
87.2
Case9
96.2
Case1082.8 ◡◁
Case1185.2
0.34 1.7 0.25 5.1 3.01 0.06 0.11 7.4
Case1282.4 ኳ↛◁Case13131
Case140ΎỈCase15 0.34 1.7 0.25 5.1 3.01 0 0.11 7.4
Case16ᐇ 㦂ࢣ࣮ࢫCase 1Case 2
Case 3
Case 4
Case 5
Case 6
Case 7
Case 8
Case 9Case 10
Case 11
Case 12Case 13
Case 14
Case 15
Case 16

d50

(mm)

0.16
0.76
0.29
0.21
0.23
0.11
0.22
0.50
0.16
0.21
0.23
0.50
-

⾲2 ᐇ㦂⤖ᯝᆒ➼ ᭤⋡ hiFriΡLR,LRWಀᩘ ಀᩘ (cm) (-) (g/cm3) (cm)1.55 0.90 5.14 2.19 1.134
1.96 0.90 4.08 2.50 1.024
2.62 0.73 5.16 2.23 1.112
4.61 2.36 1.077
1.92 0.87 4.75 2.28 1.128
2.00 0.76 4.85 2.22 1.121
5.65 2.20 1.110
2.08 0.85 4.65 2.19 1.105
2.08 1.03 4.93 2.26 1.042
1.55 0.90 5.46 2.02
207.0
1.92 0.87 5.84 1.99
185.5
2.00 0.76 4.43 2.40
196.5
2.08 1.03 4.78 2.42
241.6
3.61 3.44
242.2
3.55 3.43
250.4
3.49 3.48
250.3

LRS

(cm)

198
174
177
-

(2) ゎᯒ᪉ἲa) ỏ℃Ỉᐦᗘᐇ㦂 ỏ℃Ỉࡣࡍ࡭ࡾྎࢆὶୗࡋ㸪Ỉᖹ㒊࡟ᩜ࠸ࡓᅵ◁ࢆᕳ㎸ࢇ࡛ୗὶ➃ࡢ▷ࡃ⦆࠸ୖࡾᩳ㠃ࢆ㥑ࡅୖࡀࡾ㸪✵୰࡟㣕ฟࡍࠋ㣕ฟࡋࡓỏ℃Ỉࡣࡑࡢⴠୗᇦ࡟タ⨨ࡉࢀࡓ❧᪉యࡢỈᵴ⩌㸦㎶㛗30 cm㸪Ỉᵴᯈཌ0.3 cm㸪⛗㔞29.4×29.4×
29.7ҫ2.57×104 cm3 ࡢࡶࡢࢆὶࢀ᪉ྥ࡟2ಶ㸪Ỉ㊰ᶓ᩿᪉ྥ࡟2ಶࡢィ4ಶࠋᅗ1ཧ↷㸧࡬㣕㎸ࡴࠋ࠶ࡽ࠿ࡌࡵྛỈᵴࡢ㔜㔞ࢆ㔞ࡾ㸪ỏ℃Ỉࡀ㣕㎸ࢇࡔᚋࡢྛỈᵴࡢ㔜㔞ࢆ㔞ࢀࡤ㸪ỏ℃Ỉࡢయ✚ࡣỈᵴᅄ㝮ࡢ‣Ỉ῝ࢆ ࡿࡇ࡜࡛ホ౯࡛ࡁࡿࡢ࡛㸪ỏ℃Ỉᐦᗘρࡀホ౯࡛ࡁࡿࡇ࡜࡟࡞ࡿࠋb) ỏ℃ὶ㐳ୖᐇ㦂 Ỉᖹ㒊࡛ᅵ◁ࢆᕳ㎸ࢇࡔỏ℃ὶࡣ୍ᵝ໙㓄ᩳ㠃㒊ࢆ㐳ୖࡍࡿࠋᩳ㠃㐳ୖᇦࡣ㐳ୖඛ➃ࡢᖹ㠃ᙧࡀ⯉≧ࡢᅵ◁ሁ✚ᇦ࡜ࡑࡢ㧗ᡤഃࡢỏ℃Ỉࡀᩳ㠃ࢆởࡍ⛬ᗘࡢ㡿ᇦ࡟኱
ูࡉࢀࡿ4)ࠋึᮇᅵ◁ᒙᇦୗὶ➃ࢆ㉳Ⅼ࡜ࡋ࡚㸪๓⪅ࡢ᭱኱㐳ୖ㊥㞳ࢆᅵ◁ሁ✚ᇦ㊥㞳LRS㸪ᚋ⪅ࡢᩳ㠃ᶓ᩿ᖹ

ᅗ3 ධᑕࣇ࣮ࣝࢻᩘFri ࡜ỏ℃Ỉᐦᗘρࡢ㛵ಀ㸦◚⥺ࡣᐇ㦂⤖ᯝ࡟ࡼࡃ㐺ྜࡍࡿᘧ(1)ࡢ⡆᫆ホ౯ࣔࢹࣝ᭤⥺ࠋK್ࡣࡑ
ࡢ࡜ࡁࡢᦶ᧿ᦆኻಀᩘ㸧ᆒ㐳ୖ㊥㞳ࢆ㐳ୖ㊥㞳LR㸦ΎỈࡢሙྜࡣLRW㸧࡜ࡍࡿࠋ(3) ᐇ㦂᮲௳ ᐇ㦂᮲௳ࢆ⾲1࡟♧ࡍࠋ⾲୰㸪MSDࡣỏ℃Ỉᐦᗘᐇ㦂Case 1㹼9 ࡜ỏ℃ὶ㐳ୖᐇ㦂 Case 10㹼13 ࡛౑⏝ࡋࡓᅵ◁ࡢ඲㉁㔞࡛࠶ࡿࠋCase 4ࡣࢩࣝࢺ࡛⢏ᚄࡀ୙᫂ බ⾲್࠶ࡾ ࡞ࡓࡵ㸪ཧ⪃ᐇ㦂࡜ࡍࡿࠋCase 13ࡣᩳ㠃㐳ୖᇦ࡟
3 cmཌࡢᅵ◁ࢆᩜ࠸࡚࠸ࡿࠋᐇ㦂ࡣྛࢣ࣮ࢫ1ᅇ࡛࠶ࡿࠋ ౑⏝ᅵ◁ࡣᕷ㈍ࡢ◡◁㸦ࢩࣝࢺࢆྵࡴ㸧࡜⛅⏣┴࡟࠿࡯ᕷᖹἑ11)࡞࡝ࡢ◁὾ᾏᓊ࡛᥇ྲྀࡋࡓኳ↛◁࡛㸪஝⇱ࡉࡏࡓࡶࡢࢆỈ㊰ࡢỈᖹ㒊࡟ᢞධࡋ㸪Ỉᖹ࡟ᆒࡋࡓࠋᐇ㦂ࢣ࣮ࢫẖࡢᐇ㦂๓ᅵ◁ࡢ⢏ᗘ≉ᛶ౛ࢆ⾲2࡟♧ࡍࠋ(4) ᐇ㦂⤖ᯝ࡜⪃ᐹ ⾲2࡟Ỉᵴ⩌࡬㣕㎸ࢇࡔỏ℃Ỉࡢ඲㔞࠿ࡽホ౯ࡋࡓᖹᆒࡢỏ℃Ỉᐦᗘρ㸪୍ᵝ໙㓄ᩳ㠃ࢆ㐳ୖࡋࡓỏ℃Ỉࡢ㐳ୖ㊥㞳LR㸪ΎỈࡢ㐳ୖ㊥㞳LRW࡜ᅵ◁ሁ✚ᇦ㊥㞳LRSࢆ♧ࡍࠋ⾲࠿ࡽ㸪᪤ሗ2) - 7)࡜ྠᵝ㸪ỏ℃Ỉᐦᗘࡀᗏ㉁ᅵ◁⢏ᚄd50࡟౫Ꮡࡋ࡚࠸ࡿࡇ࡜ࡀุࡿࠋ
 ᅗ3࡟᪤ሗᐇ㦂ࢹ࣮ࢱ㸦Exp. 1 2) - 7)࡜࡜ࡶ࡟ᮏ◊✲ᐇ㦂ࢹ࣮ࢱ㸦Exp. 2㸧ࡢධᑕࣇ࣮ࣝࢻᩘFri࡜ỏ℃Ỉᐦᗘρࡢ㛵ಀࢆ♧ࡍࠋᅗ୰ࡢρwࡣΎỈࡢᐦᗘ࡛㸪ᐇ㦂ࢹ࣮ࢱࡣᅵ◁ࢆᩜ࠸ࡓỈᖹ㒊ࡢᗏ㠃ࡀỏ℃ὶ࡛㟢ฟࡋ࡞࠸hTࡀ6 cmࡢሙྜ࡟㝈ᐃࡋ࡚࠸ࡿࠋᅗ୰࡟ࡣᮏ◊✲ᐇ㦂ࡢ3ᐇ㦂್࡟ᑐࡋ࡚㸪ᐇ㦂್࡟ࡼࡃ㐺ྜࡍࡿᚋ㏙ࡢᘧ(1)ࡢ᭤⥺㸦◚⥺㸧࡜ࡑࡢ࡜ࡁࡢᦶ᧿ᦆኻಀᩘKࡶ♧ࡉࢀ࡚࠸ࡿࠋᅗ࠿
ࡽ㸪ᮏ◊✲ᐇ㦂࡟࠾ࡅࡿỏ℃Ỉᐦᗘࡢኚᇦᖜࡀࡇࢀࡲ࡛
ࡼࡾࡶᗈ࠸ഴྥ࡟࠶ࡿࡇ࡜ࡀุࡿࠋ
 ỏ℃ὶ㐳ୖᐇ㦂⤖ᯝ࡟ࡘ࠸࡚ࡣᚋ㏙ࡍࡿ ᅗ12ཧ↷ ࠋ ᦶ᧿ᦆኻಀᩘ࡜ỏ℃Ỉᐦᗘࡢホ౯ᐇ㦂ᘧ ᯇ෠8)ࡣᤲὶᅵ◁࡜ᾋ㐟ᅵ◁ࢆศ㞳ࡏࡎ࡟඲ὶ㏦ᅵ◁ࢆᑐ㇟࡜ࡋ࡚⛣ືᗋୗࡢỏ℃ὶ࡟ࡼࡿỏ℃Ỉᐦᗘρ࡜ධᑕࣇ࣮ࣝࢻᩘFriࡢ㛵ಀ࡜ࡋ࡚ḟᘧࢆᑟฟࡋࡓࠋ
f
f(1)
1 1 M F2
1 1 r F2
1 1 KF 2
w

8

ri

1

8

ri

ri

ࡇࡇ࡛㸪fMࡣ⛣ືᗋୗࡢỏ℃ὶࡢᦶ᧿ᦆኻಀᩘ㸪fࡣ⛣ື53ᗋୗࡢᐃᖖὶࡢᦶ᧿ᦆኻಀᩘ㸪r1ࡣ⛣ືᗋୗࡢỏ℃ὶ࡜
ᐃᖖὶࡢᦶ᧿ᦆኻಀᩘẚfM /f㸪K㸦=fM /8=r1f /8㸧ࡣูᐃ⩏9)ࡢ⛣ືᗋୗࡢỏ℃ὶࡢᦶ᧿ᦆኻಀᩘ࡛㸪⛣ືᗋୗࡢᐃᖖ
ὶࡢ᢬ᢠ๎࡜ࡋ࡚ḟᘧࢆ᥇⏝ࡋ࡚࠸ࡿࠋ
8f

6.0 5.75 log10

2

hi
3d 50

(2)

 ࡲࡓ㸪ᯇ෠8)ࡣr1࡜ࡋ࡚ḟࡢᬻᐃᐇ㦂ᘧࢆᥦ♧ࡋ࡚࠸ࡿࠋ
0.234 Fri 1.05

r1

hi
3d 50

0.94

hi
d 50

0.083Fri 1.05

0.94

(3)
(a) ᗏ㉁ᅵ◁⢏ᚄd50ࢆࣃ࣓࣮ࣛࢱ࡜ࡋࡓሙྜ

ᘧ(3)࡟ᮏ◊✲ᐇ㦂ࢹ࣮ࢱ㸦Exp. 2㸧ࢆྵࡵࡓሙྜࡢᐇ㦂⠊ᅖ㸦2.18<Fri<6.29㸪54<hi/d50<513㸧ࡢୖ࣭ୗ㝈್ࢆ௦ධࡋ
࡚඲ᐇ㦂ࢹ࣮ࢱ࡜ẚ㍑ࡋࡓࡶࡢ㸦◚⥺㸧ࢆᅗ4࡟♧ࡍࠋᅗ୰࡟ࡣḟ❶ࡢ⌮ㄽゎᯒ࡟㐺⏝ྍ⬟࠿ࡘᘧ(3)࡜ྠ⛬ᗘࡢホ౯⢭ᗘࢆᣢࡘḟᘧ࡟ࡼࡿࡶࡢ ᐇ⥺ ࡶ♧ࡉࢀ࡚࠸ࡿࠋ
r1

0.327 Fri 1

hi
3d 50

0.807

0.135Fri 1

0.807

hi
d 50

(4)

ᅗ࠿ࡽ㸪ᘧ(3)ࡣ୍㒊ࡢᐇ㦂್ࡀ◚⥺࡟ᣳࡲࢀࡓ⠊ᅖእ࡜࡞ࡿࡀ㸪ᐇ㦂್ࢆࡼࡃㄝ᫂ࡋ࡚࠸ࡿ࡜ゝ࠼ࡿࠋ⌮ㄽゎᯒ࡛᥇⏝ணᐃࡢᘧ(4)ࡣᘧ(3)࡟ẚ࡭࡚ࡸࡸຎࡿࡀᐇ㦂್ࢆẚ
㍑ⓗࡼࡃໟྵࡋ࡚࠸ࡿ࡜ゝ࠼ࡿࠋࡼࡾ㐺ษ࡞ᘧࢆ┠ᣦࡋ࡚᪂ᐇ㦂ᘧࢆᥦ♧ࡍࡿࡇ࡜ࡶ⪃࠼ࡽࢀࡿࡀ㸪ᐇ㦂ࢹ࣮ࢱ㔞ࡀᑡ࡞࠸⌧≧࡛ࡣ↓㜌࡟ᥦ♧ࡍࡿࡇ࡜ࡣṆࡵ࡚࠾ࡃࠋ ᘧ(4)ࢆ᥇⏝ࡍࡿሙྜ㸪⛣ືᗋୗࡢỏ℃ὶࡢᦶ᧿ᦆኻಀ
ᩘKࡣḟᘧ࡜࡞ࡿࠋ
K

fM 8

r1 f 80.327 6.0 5.75 log100.00442 Fri 1

hi
3d 50

hi
3d 50

2

Fri 1

hi
3d 50

0 .5

0.00255 Fri 1

hi
d 50

0.807

(b) ධᑕࣇ࣮ࣝࢻᩘFriࢆࣃ࣓࣮ࣛࢱ࡜ࡋࡓሙྜ
ᅗ4 ᦶ᧿ᦆኻಀᩘẚr1㸦= fM/f 㸧ࡢᐇ㦂್࡜ྛᘧࡢẚ㍑

(5)

0 .5

ࡇࡇ࡛㸪ࡇࢀࡲ࡛ࡢᐇ㦂⠊ᅖ㸦54<hi/d50<513㸧࡟ᑐࡋ࡚㐺⏝࡛ࡁࡿࡶࡢ࡜ࡋ࡚ḟࡢ㏆ఝᘧࢆ⏝࠸࡚࠸ࡿࠋ
ᅗ5 ⛣ືᗋୗࡢᐃᖖὶࡢ᢬ᢠ๎㸦㯮ᐇ⥺㸧࡟ᑐࡍࡿ㏆ఝ᭤⥺
6.0 5.75 log10

hi
3d 50

2

0.0135

hi
3d 50

0.307

(6)

㸦㉥◚⥺㸧

ᘧ(7)ࡣρࡀධᑕỏ℃ὶ㏿ui࡜d50࡛Ỵࡲࡿࡇ࡜ࢆࡶ♧ࡍࠋ
ᘧ(6)ࡢ㏆ఝ⛬ᗘࢆᅗ5࡟♧ࡍࠋỴᐃಀᩘR ࡣ0.999࡛࠶ࡿࠋ ᅗ6࡟୧ᘧࡢẚ㍑ࢆᐇ㦂್࡜࡜ࡶ࡟♧ࡍࠋᅗ4࡜ྠᵝ ࡋࡓࡀࡗ࡚㸪ᘧ(1)࡜(5)࠿ࡽỏ℃Ỉᐦᗘρࡢ⡆᫆ホ౯ᐇ ࡟ྛࣃ࣓࣮ࣛࢱࡢ್࡜ࡋ࡚ᐇ㦂⠊ᅖࡢୖ࣭ୗ㝈್ࢆ᥇⏝ࡋ࡚࠸ࡿࠋ୍㒊ࡢᐇ㦂್ࡀྛᘧࡢ⥺࡟ᣳࡲࢀࡓ⠊ᅖእ࡜㦂ᘧ࡜ࡋ࡚ḟᘧࢆᚓࡿࠋ
࡞ࡿࡀ㸪୧ᘧࡣẚ㍑ⓗࡼ࠸ỏ℃Ỉᐦᗘࡢホ౯ᘧ࡜ゝ࠼ࡿࠋ
0 .5
h
(7)
w
1 0.00255Fri i ᅗ7࡟୧ᘧ࡟ࡼࡿホ౯್(ρ/ρw)m࡜ᐇ㦂್(ρ/ρw)eࡢẚ㍑ࢆ
d 50♧ࡍࠋ୧ᘧ࡜ᐇ㦂್ࡢ୍⮴ᗘࡣᚲࡎࡋࡶࡼࡃ࡞࠸ࡀ㸦R2
ࡣᘧ㡰࡟0.709࡜0.739 㸪୧ᘧࡣྠ⛬ᗘࡢ୍⮴ᗘ࡜ゝ࠼ࡿࠋ
ᘧ(1)㸪(2)㸪(3)࡜(6)࠿ࡽࡣḟᘧࢆᚓࡿࠋ
2w

1 0.00158Fri0.95

hi
d 50

0.633

(8)

 ỏ℃Ỉᐦᗘࡢ᫬㛫ኚ໬ࢆ⪃៖ࡋࡓ㐳ୖ⌮ㄽ ᗏ㉁ᅵ◁⢏ᚄd50ࡀ୍ᐃࢆ๓ᥦ࡟㸪ᦶ᧿ᦆኻಀᩘKࡣ᫬

54

ᅗ8 㐳ୖࡍࡿὠἼỏ℃ὶࡢึᮇ᮲௳࡜ㅖグྕࡢᐃ⩏9)

 1 㸪gࡣ㔜ຊຍ㏿ᗘ㸪h1ࡣึᮇࡢ㈓Ỉ῝㸦=ࡇࡇ࡛㸪c1= ghố⥺࡟࠾ࡅࡿධᑕẁἼ㧗 㸪a(t) ࡣỏ℃ὶඛ➃఩⨨ t ࡣ᫬㛫 i ࡣᩳ㠃໙㓄࡛࠶ࡿࠋ ᘧ(9)୰ࡢρw/ρ㸦ᘧ(11)୰ࡢࡶྵࡴ㸧ࢆධᑕỏ℃Ỉ῝hiࢆ
ỏ℃ὶඛ➃㒊ࡢᚋ➃Ỉ῝H࡜ࡋࡓᘧ(7)㸪ࡑࡢH࡜ᘧ(9)୰
ࡢᦶ᧿ᦆኻಀᩘKࢆࡑࢀࡒࢀḟᘧࢆ⏝࠸࡚᭩ࡁ┤ࡏࡤ㸪(a) ᗏ㉁ᅵ◁⢏ᚄd50ࢆࣃ࣓࣮ࣛࢱ࡜ࡋࡓሙྜ

1
c1
g

H

K

w

1

1
Fri2

1 da
2 dt

w

1

1
igt
2
2c1

2

(10)

da dt igt
2
4 da dt2(11)

ᘧ(12)ࢆᚓࡿࠋ
c1(b) ධᑕࣇ࣮ࣝࢻᩘFriࢆࣃ࣓࣮ࣛࢱ࡜ࡋࡓሙྜ
ᅗ6 ỏ℃Ỉᐦᗘρࡢᐇ㦂್࡜ྛᘧࡢẚ㍑

d 2a 1
1 da 10.00255da
1 da 1
igt t 2c1
igt
1dt
2 dt 22
2 dt 2gd50 dt 㸨ig c1

1 da 10.00255g
igt t
a
2 dt 2
gd50

2

3 da
da
c1 igt t
0
2 dt
dt

(12)
ᘧ(12)ࡣᅵ◁⢏ᚄd50࡟౫Ꮡࡍࡿᮏ◊✲ࡢᇶ♏ᘧ࡛㸪ρ/ρwࢆ୍ᐃ࡜ࡋࡓ᪤ሗ⌮ㄽ9)ࡼࡾᬑ㐢ⓗ࡜ゝ࠼ࡿࡶࡢ࡛࠶ࡿࠋ
ࡲࡓ㸪ᘧ୰ࡢῧᏐ㸨ࡀ௜࠸ࡓ㡯ࡣρ/ρw=1ࡢΎỈ࡛ࡣ࡞ࡃ࡞ࡾ㸪ࡇࢀࡣ௨ୗࡢᘧ࡛ࡶྠࡌ࡛࠶ࡿࠋ ᘧ(12)ࢆゎࡃ࡟࠶ࡓࡾḟࡢ↓ḟඖ㔞ࢆᑟධࡍࡿࠋ
1
1 2,(13, 14)g h1 t
2c t
igt a
h1

ᅗ7 ỏ℃Ỉᐦᗘρࡢᐇ㦂್(ρ/ρw)e࡜ࣔࢹࣝホ౯್(ρ/ρw)mࡢẚ㍑

12ࡇࢀࡽࡢᑟධ࡜0.00255
   h1 d50  ࡜⨨ࡃࡇ࡜࡟ࡼࡾ㸪ᘧ(12)ࡣḟᘧ࡜࡞ࡿࠋ
d2
d 2

d
d

1 d
4 d

2

d
4 d

2

2 i

d

㛫ኚ໬ࡍࡿࡀ㸪ỏ℃Ỉᐦᗘρࡣ୍ᐃ㸦㐳ୖ㐣⛬ᖹᆒ㸧࡜d 㸨 (15)9)ࡋࡓ㐳ୖ⌮ㄽࡣࡍ࡛࡟ᥦ♧ࡋࡓ ࠋᮏ◊✲࡛ࡣࡼࡾᐇ㝿
3 d
d
2
2 i
0
ⓗ࡛࠶ࡿᅵ◁⢏ᚄࡢࡳࡀ୍ᐃ࡛㸪ᦶ᧿ᦆኻಀᩘ࡜ỏ℃Ỉ
2 ddᐦᗘࡢ୧᪉ࡀ᫬㛫ኚ໬ࡍࡿ࡜ࡋࡓ㐳ୖ⌮ㄽࢆᒎ㛤ࡍࡿࠋ ࡉࡽ࡟㸪ḟࡢኚᩘኚ᥮ࢆ⾜࠺ࠋ ᅗ8࡟㐳ୖᑐ㇟ࡢ୍ᵝ໙㓄ᩳ㠃ᆅᙧ㸪ᗙᶆ⣔㸪㐳ୖࣔ,(16, 17)p d df ( p) df dp
ࢹࣝ࡜ㅖグྕࡢᐃ⩏ࢆ♧ࡍࠋࡇࡢሙྜࡢ㟼Ỉᅽ㏆ఝ࡟࠾
p≥0࡛㸪ࡇࡢኚ᥮࡟ࡼࡾḟࡢ㛵ಀᘧࢆᚓࡿࠋ
9)ࡅࡿᇶ♏ᘧࡣࡍ࡛࡟ᥦ♧ࡋ࡚࠾ࡾ 㸪ḟᘧ࡛࠶ࡿࠋ
pf
f,(18, 19)d 2 d 2 1 d 2 f dp 2
43
2
1 da 1
1 da 1
d a 1 wࡋࡓࡀࡗ࡚㸪ᘧ(15)ࡣḟࡢf࡟㛵ࡍࡿᖖᚤศ᪉⛬ᘧ࡜࡞ࡿࠋ
c1
igt t 2c1
igt
(9)
2 dt 22
2 dt 2
dt
1 2
pf
p f
p 2㸨 8 f 4 f p 2 if p f
0 (20)
ig c1

1 da
2 dt

3

1
igt t Kg a23 da
c1 igt t
2 dt

da
dt

2

0

4

4

 ᘧ(20)ࢆゎࡃ࡟࠶ࡓࡾf ࡟㛵ࡋ࡚pࡢ⣭ᩘゎࢆ௬ᐃࡍࡿࠋ

55

(21)

bn p nf ( p)n 0 ึᮇ᮲௳τ=0㸦t=0㸪p=0㸧ࡢ࡜ࡁ㸪α=dα/dt=0࠿ࡽ㸪b0=b1=0ࢆᚓࡿࠋࡇࢀࡽࢆ⪃៖ࡋ㸪ᘧ(21)ࢆᘧ(20)࡟௦ධࡍࢀࡤ㸪ࡿ᭱⤊ⓗ࡞ᜏ➼ᘧ࡜ࡋ࡚ḟᘧࢆᚓࡿࠋ
10b2 18b3 p 28b4 p 2
1㸨 16b2
4b2

40b5 p 3 54b6 p 4 .... p 2

20b3 p 24b4 p 2

12b3

2b2

28b5 p 3

32b6 p 4 ....

2
2

4ib p

(22)

6b3 18ib2 b3 p 2

24b4

p2

40b5 12b4 32ib2 b4 18ib32 p 3
60b6

20b5 50ib2 b5

0ᅗ9 ỏ℃ὶඛ➃఩⨨a(t)࡟㛵ࡍࡿ⣭ᩘゎᘧ(28)࡜(30)ࡢ཰᮰ᛶࡢ
᳨ウ౛㸦h1=0.09 m㸪i=0.05㸪h1/d50=300㸧

60ib3b4 p 4 ....

 ᘧ(22)࠿ࡽ౛࠼ࡤಀᩘb2㹼b6࡜ࡋ࡚ḟᘧ⩌ࡀᚓࡽࢀࡿࠋ
5 2 㸨
(23)
b
2

(24)

3 1㸨 16b2 1 3ib2 20 6b3 b2 2ib22 b3
12 1㸨 20b2 14

(25)

b3

b4

32

1㸨 16b2 1 2ib2 b2
2 3㸨 68b2 91㸨 16b2 6b4 16ib2b4 9ib32
60 1 3ib2 b32 24 1 2ib2 b2b4 384b3b4
4 5㸨 94b2 20

b5

(26)
ᅗ10 ỏ℃ὶඛ➃఩⨨a(t)࡜ᦶ᧿ᦆኻಀᩘK㸪ỏ℃Ỉᐦᗘρࡢ⤒᫬ኚ໬౛㸦h1=0.09 m㸪i=0.05㸪h1/d50=300ࠋ➨5ḟ㏆ఝ㸧

5 1㸨 16b2 2b5 5ib2b5 6ib3b4
20 6b4 16ib2b4 9ib32 b3
24 12b4 3b3 9ib2b3 b4
28 1 2ib2 b2b5 568b3b5
2 15㸨 272b2 27

b6

(27)

 ௨ୖ࠿ࡽ㸪௵ពࡢ୍ᐃ࡞h1㸪i㸪d50࡟ᑐࡍࡿỏ℃ὶࡢඛ➃఩⨨a(t)࡜ඛ➃㒊࡟࠾ࡅࡿỏ℃ὶ㏿U =da/dt ࡢ⣭ᩘゎ࡜ࡋ࡚ࡑࢀࡒࢀᘧ(28)㹼(30)ࡀᚓࡽࢀࡿࠋ
a

1 2
igt
2
2
h1 b2 p 2b3 p 3 3b4 p 4

U
t

(28)

2c1t

da dt

h1
2b2 p 3b3 p 2
g

4b5 p

5

5b6 p

6

....

(29)

2c1 igt c1 p
4b4 p 35b5 p 46b6 p 5 ....

(30)

 ᅗ9࡟ỏ℃ὶඛ➃఩⨨a(t)ࡢ⣭ᩘゎ࡛࠶ࡿᘧ(28)࡜(30)ࡢ
཰᮰ᛶࡢ᳨ウ౛ࢆ♧ࡍࠋᅗ࠿ࡽ㸪ಀᩘb6ࡲ࡛ࡢ➨5ḟ㏆ఝࢆ᥇⏝ࡍࢀࡤ㸪⣭ᩘゎࡀ༑ศ࡟཰᮰㸦➨4࡜5ḟ㏆ఝࡢᕪࡣ᭱኱㐳ୖ㊥㞳am࡛2.4%㸧ࡍࡿࡇ࡜ࡀุࡿࠋࡋࡓࡀࡗ
࡚㸪௨ୗࡢィ⟬౛࡛ࡣ➨5ḟ㏆ఝࢆ♧ࡍࠋ ᅗ10࡟ỏ℃ὶඛ➃఩⨨a(t)࡜ᦶ᧿ᦆኻಀᩘK㸪ỏ℃Ỉ
ᐦᗘρࡢ⤒᫬ኚ໬౛ࢆ♧ࡍࠋ┬␎ࡉࢀ࡚࠸ࡿࡀ㸪ึᮇࡢ
ỏ℃Ỉᐦᗘρ࡜᭱኱㐳ୖ㊥㞳am᫬ࡢᦶ᧿ᦆኻಀᩘKࡣ࡜ࡶ࡟↓㝈኱࡛࠶ࡿࠋᅗ࠿ࡽ㸪ᦶ᧿ᦆኻಀᩘ࡜ỏ℃Ỉᐦᗘࡀᅗ11 ྛ⌮ㄽ࡟ᇶ࡙ࡃỏ℃ὶඛ➃఩⨨a(t)ࡢẚ㍑౛㸦h1=0.09 m㸪
i=0.05㸪h1/d50=300㸪ρ/ρw=1.055㸪K=0.0034㸧

᫬㛫ኚ໬ࡋ࡚࠸ࡿࡇ࡜ࡀุࡿࠋ
 ᅗ11࡟᭱኱㐳ୖ㊥㞳am㸦ࡲࡓࡣ㐳ୖ㧗㸧ࢆྠࡌ࡜ࡋ
ࡓሙྜࡢᮏ⌮ㄽ ⣭ᩘゎ ࡜᪤ሗ⌮ㄽ9) ゎᯒゎ࡜⣭ᩘゎ࡟ࡼࡿỏ℃ὶඛ➃఩⨨a(t)ࡢẚ㍑౛ࢆ♧ࡍࠋ᪤ሗ⌮ㄽࡢゎᯒゎ࡜⣭ᩘゎࡣࡑࢀࡒࢀᘧ(31)࡜ᘧ(32)㹼(38)࡛࠶ࡿࠋ
1 w
1 2
(31)
a 2c t
igt 4
gt 2
1

a

2c1t

2

4

w

1 2
igt
2

h1
3b4 p 4K

(32)
4b5 p 5 5b6 p 6

6b7 p 77b8 p 8 ....

56

㸦ᘧ(28)࡜(30)㸧ࡢẚ㍑౛ࢆ♧ࡍࠋ୧⪅ࡣࡼࡃ୍⮴ࡋ࡚࠾ࡾ㸪⌮ㄽࡢ᭷⏝ᛶ࠾ࡼࡧࡑࡢึᮇỈ῝h1࡞࡝ࡢỴࡵ᪉ࡢጇᙜᛶࡀ☜ㄆࡉࢀࡓ࡜ゝ࠼ࡿࠋ

ᅗ12 㐳ୖ㊥㞳LR࡟㛵ࡍࡿᐇ㦂್LRe࡜⌮ㄽ್LRtࡢẚ㍑౛㸦➨5
ḟ㏆ఝ㸧
t

1
K

h1
(33)
4b4 p 3 5b5 p 4 6b6 p 5 7b7 p 6 8b8 p 7 ....
g

ࡇࡇ࡛㸪
b4

1
4 3
1,152
1,152b42
3,264b4 5 5

b5

w

(35)
w

64 9b42 102b4b5 70b52
12 15 w
8,832b4

b6(34)

288b43 i K (37) ཧ⪃ᩥ⊩1) ᯇ෠ⱥኵ㸸ὠἼⲴ㔜ホ౯㧗ᗘ໬࡬ࡢྲྀࡾ⤌ࡳ㸪⁺ ⁺ሙ⁺ᮧ◊ሗ㸪Vol.48, pp.4-7, 2020.
2
69b4b6 360b4 b7 35b5 370b5b6
2)
ᯇ෠ⱥኵ㸪ᕝᓥᓧ㸸ὠἼỏ℃ὶࡢᐦᗘ࡟㛵ࡍࡿᇶ♏ᐇ㦂㸪8474b5b7 240b62 24b42 6b4 49b5 i KᅵᮌᏛ఍ㄽᩥ㞟B2㸦ᾏᓊᕤᏛ 㸪Vol.71, No.2, pp.355-360, 2015.
(38)b83) ᯇ෠ⱥኵ㸪௒㔝ྐᏊ㸪㰻ᕝ⪷㸪㙊⁪Ꮥಙ㸪Ώ㑓୍ஓ㸸ὠἼ
4 7 w
3,648b4
ỏ℃Ỉᐦᗘࡢᅵ◁ሁ✚ࡸ㐳ୖ㧗࡬ࡢᙳ㡪㸪ᅵᮌᏛ఍ㄽᩥ㞟
ᅗ11࡛ࡣh1=0.09 m࡜i=0.05ࢆඹ㏻࡜ࡋ㸪ᮏ⌮ㄽࡢ⣭ᩘゎ
B2㸦ᾏᓊᕤᏛ 㸪Vol.72, No.2, pp.397-402, 2016.
➨5ḟ㏆ఝ ࡛ࡣh1/d50ࢆ300㸪᪤ሗ⌮ㄽࡢゎᯒゎ࡛ࡣρ/ρw 4) ᯇ෠ⱥኵ㸪௒㔝ྐᏊ㸪ᚋᮧ᫭ᇶ㸪௒⸨᫭ኴ㸪㙊⁪Ꮥಙ㸪Ώ㑓୍ஓ㸸ὠἼỏ℃Ỉᐦᗘ࡜ࡑࡢ㐳ୖ㊥㞳ࡸᅵ◁ሁ✚࡬ࡢᙳ
ࢆ1.055㸪᪤ሗ⌮ㄽࡢ⣭ᩘゎ ➨5ḟ㏆ఝ ࡛ࡣρ/ρw࡜Kࢆࡑ
10)
ࢀࡒࢀ1.055࡜0.0034ࡢ୍ᐃ ≠㐳ୖ㐣⛬ᖹᆒ ࡜ࡋ࡚࠸ࡿࠋ 㡪࡟㛵ࡍࡿᐃ㔞ᐇ㦂㸪ᅵᮌᏛ఍ㄽᩥ㞟B2㸦ᾏᓊᕤᏛ 㸪
Vol.73, No.2, pp.373-378, 2017.
ᅗ࠿ࡽ㸪ᮏ⌮ㄽࡢỏ℃ὶඛ➃఩⨨a(t)ࡣ᪤ሗ⌮ㄽࡢࡑࢀ5) ᯇ෠ⱥኵ㸪ᒸ⏣㞙ே㸪ஂಖ⏣཭ᐶ㸪௒㔝ྐᏊ㸸RC㐀ᘓ⠏≀ࡽࡢ㛫࡛࠶ࡿࡇ࡜ࡀุࡿࠋᅵ◁⢏ᚄd50ࡣΰྜ⢏ᚄࢆ᝿ᐃ࡟స⏝ࡍࡿὠἼⲴ㔜ࡢỏ℃Ỉᐦᗘ࡬ࡢ౫Ꮡ࡟㛵ࡍࡿᇶ♏ᐇࡋ࡞࠸㝈ࡾ᫬㛫ⓗ࡟୙ኚ࡛㸪ᮏ⌮ㄽࡣ3⌮ㄽࡢ୰࡛᭱ࡶ
㦂㸪ᅵᮌᏛ఍ㄽᩥ㞟B2㸦ᾏᓊᕤᏛ 㸪Vol.74, No.2, pp.265-270,ᐇ㝿ⓗ࡞ࡶࡢ࡜⪃࠼ࡽࢀ㸪ỏ℃Ỉᐦᗘ୍ᐃࡢ᪤ሗࡢゎᯒ
2018.
ゎࡣ㐳ୖࢆ᪩ 㧗 ࡵ࡟㸪ỏ℃Ỉᐦᗘ࡜ᦶ᧿ᦆኻಀᩘ୍ᐃ 6) ༓ⴥ⿱ኴ㸪୕ୖ㍤㸪ᯇ෠ⱥኵ㸸ὠἼỏ℃ỈᐦᗘࡢㅖỈ⌮㔞࡬ࡢ౫Ꮡᛶ㸪ᅵᮌᏛ఍ᮾ໭ᨭ㒊ᢏ⾡◊✲Ⓨ⾲఍ㅮ₇ᴫせࡢ᪤ሗࡢ⣭ᩘゎࡣ㐜 ప ࡵ࡟ホ౯ࡍࡿഴྥ࡜ゝ࠼ࡿࠋ
㞟㸪II-98, 2019 (CD- ROM).
 ḟ࡟ᮏ⌮ㄽࡢ᳨ド౛ࢆ♧ࡍࠋ᏶඲࡟ྠࡌ᮲௳ୗ࡛ࡢᐇ
7) ᯇ෠ⱥኵ㸪୕ୖ㍤㸪༓ⴥ⿱ኴ㸸ỏ℃Ỉᐦᗘ࡜Ἴ࿘ᮇࡢὠἼ
㦂࡜⌮ㄽࡢẚ㍑ࡣᐇ㦂ࡀ㞴ࡋࡃ㸪⌧≧࡛ࡣ࡛ࡁ࡞࠸ࠋᮏ
Ⲵ㔜࡬ࡢᙳ㡪㸪ᅵᮌᏛ఍ㄽᩥ㞟B2㸦ᾏᓊᕤᏛ 㸪Vol.75, No.2,⌮ㄽ࡟࠾ࡅࡿึᮇỈ῝h1ࡣึᮇᅵ◁ᒙᇦୗὶ➃࡛ࡢධᑕ
pp.397-402, 2019.
ỏ℃Ỉ῝hid ᅗ2ཧ↷ ࡟㏿ᗘỈ㢌ࢆຍ࠼ࡓࡶࡢ࡜ࡍࡿ10)ࠋ8) ᯇ෠ⱥኵ㸸ὠἼỏ℃Ỉᐦᗘࡢ⡆᫆ホ౯ἲ㸪ᅵᮌᏛ఍ㄽᩥ㞟
B2㸦ᾏᓊᕤᏛ 㸪Vol.75, No.2, pp.385-390, 2019.
㏿ᗘỈ㢌ࡢ㏿ᗘ࡜ࡋ࡚ධᑕࣇ࣮ࣝࢻᩘFriࢆホ౯ࡋࡓ࡜ࡁ
ࡢỏ℃ὶඛ➃⛣ື㏿ᗘuiࢆ᥇⏝ࡍࡿࠋࡑࡢ㏿ᗘࡣ⾲2࠿ 9) ᯇ෠ⱥኵ㸪᭷ᕝኴ㑻㸸ὠἼ㐳ୖ࡬ࡢỏ℃Ỉᐦᗘࡢᙳ㡪㸪ᅵᮌᏛ఍ㄽᩥ㞟B2㸦ᾏᓊᕤᏛ 㸪Vol.76, No.2, pp.391-396, 2020.
ࡽホ౯࡛ࡁࡿࠋᅵ◁⢏ᚄd50࡜ࡋ࡚㐳ୖᩳ㠃࡟㈞ࡾ௜ࡅࡓ
9) 10) ᯇ෠ⱥኵ㸸ỏ℃ὶ᢬ᢠ๎ࡢὠἼ㐳ୖ࡬ࡢ㐺⏝ἲ㸪ᮾ໭ᆅᇦ◁㸦⢏ᚄ0.85㹼2 mm㸧ࡢ௦⾲⢏ᚄ =┦ᙜ⢒ᗘks 1.0 mm⅏ᐖ⛉Ꮫ◊✲㸪➨58ᕳ㸪2022.㸦༳ๅ୰㸧Case 13࡛ࡣks=3d50=1.5 mm ࢆ᥇⏝ࡍࡿࠋᅗ12࡟㐳ୖ㊥ 11) ᯇ෠ⱥኵ㸪ᕤ⸨ᓫ㸪ụ⏣ṇே㸸⛅⏣┴༡㒊ᾏᓊ࡛ࡢ⁻◁ື㞳LR࡜LRW࡟㛵ࡍࡿᐇ㦂್LRe㸦Case 10㹼16㸧࡜⌮ㄽ್LRtྥ㸪ᾏᓊᕤᏛㄽᩥ㞟㸪➨39ᕳ㸪pp.341-345,1992.
b7

32 51b4b5

276b4b6 140b52 370b5b6
14 21 w
11,520b4(36)

 ࠾ࢃࡾ࡟ ᮏ◊✲࡛ᚓࡽࢀࡓ୺࡞⤖ᯝࡣḟࡢ㏻ࡾ࡛࠶ࡿࠋ
1) ᪂ࡓ࡟ỏ℃Ỉᐦᗘᐇ㦂࡜ỏ℃ὶ㐳ୖᐇ㦂ࢆ⾜ࡗ࡚ᐇ㦂ࢹ࣮ࢱ㔞㸦⠊ᅖ㸧ࢆቑࡸࡋ㸦ᣑࡆ 㸪⛣ືᗋୗࡢỏ℃ὶࡢᦶ᧿ᦆኻಀᩘK࡜ỏ℃Ỉᐦᗘρ࡟㛵ࡍࡿ᪤ሗࡢホ౯ᐇ㦂ᘧࡢጇᙜᛶࢆ☜ㄆࡍࡿ࡜࡜ࡶ࡟ὠἼ㐳ୖ⌮ㄽࡢ᳨ドࢹ࣮ࢱ㸦⾲2㸧ࢆᥦ౪ࡋࡓࠋ
2) ᗏ㉁ᅵ◁⢏ᚄ㸦୰ኸ⢏ᚄd50㸧࡟౫Ꮡࡋ㸪ᦶ᧿ᦆኻಀᩘ
࡜ỏ℃Ỉᐦᗘࡀ᫬㛫ኚ໬ࡍࡿࡼࡾᬑ㐢ᛶࡢ㧗࠸ὠἼ㐳ୖࡢ⌮ㄽゎࢆᥦ♧ࡋࡓ㸦ᘧ(28)㹼(30) ࠋ
3) ⛣ືᗋୗࡢΎỈ㸦ᅛᐃᗋୗࡢΎỈ࡜ࡶゝ࠼ࡿ㸧ࡢሙྜࢆྵࡵ࡚㸪ᐇ㦂್࡜ࡢẚ㍑᳨࣭ウࢆ㏻ࡋ࡚ὠἼ㐳ୖࡢ⌮ㄽゎ㸦ᘧ(28)࡜(30)㸧ࡢ᭷⏝ᛶࢆ☜ㄆࡋࡓ㸦ᅗ12 ࠋㅰ㎡㸸ᮏ◊✲ࡢ㐙⾜࡟࠶ࡓࡾ⛉Ꮫ◊✲㈝㸦ᇶ┙◊✲ C 㸪
20K05041㸪௦⾲㸸ᯇ෠ⱥኵ㸧ࡢ⿵ຓࢆཷࡅࡓࠋࡇࡇ࡟グࡋ࡚ㅰពࢆ⾲ࡍࡿࠋ東北地域災害科学研究

57

第58巻（2022）

ỏ℃ὶ᢬ᢠ๎ࡢὠἼ㐳ୖ࡬ࡢ㐺⏝ἲ*୰ኸ኱Ꮫ◊✲㛤Ⓨᶵᵓ ᯇ෠ⱥኵ ࡣࡌࡵ࡟
⌮ㄽࢆ⌮ㄽIII࡜ࡍࡿࠋࡇࡇ࡛㸪d50ࡣΰྜ⢏ᚄࢆ᝿ᐃࡋ࡞ ὠἼỏ℃ὶࡢඛ➃㒊࡟࠾࠸࡚ᦶ᧿ᦆኻಀᩘࡢ᫬㛫ኚ໬ ࠸㝈ࡾ୍ᐃ್࡛㸪ρ࡜Kࡣ㐳ୖ㐣⛬ᖹᆒࡢ୍ᐃ್࡛࠶ࡿࠋ
ࢆ⪃៖ࡍࡿࡇ࡜ࡢᚲせᛶࡀᣦ᦬ࡉࢀ࡚ஂࡋ࠸1)ࠋ
 ⌮ㄽI࡜⌮ㄽIIIࡣ⣭ᩘゎ࡛㸪⌮ㄽIIࡣゎᯒゎ࡛࠶ࡿࠋ⌮ ⛣ືᗋࡸὶࢀࡢ㠀ᐃᖖᛶࡣ᢬ᢠ๎࡟ᙳ㡪ࡋ2), 3)㸪ࡦ࠸࡚ ㄽII࠿ࡽ㐳ୖ㐣⛬ᖹᆒࡢρ࡜Kࢆh1࡜d50ࡢ㝧㛵ᩘ࡜ࡋ࡚ồࡣὠἼỏ℃Ỉᐦᗘρ 3) - 8)ࡸὠἼⲴ㔜9) - 13)㸪ὠἼつᶍ3), 14)ࡢホ ࡵࡿࡇ࡜ࡀ࡛ࡁࡿ㸦ᚋ㏙ ࠋࡇࡇ࡛㸪ඖࠎࡢρ࡜Kࡣධᑕ
ࣇ࣮ࣝࢻᩘFri࡜d50࡟౫Ꮡࡋ㸪i ࡢᙳ㡪ࡣ⪃៖ࡉࢀ࡚࠸࡞
౯࡞࡝࡟ᙳ㡪ࡍࡿࠋ ⛣ືᗋୗࡢ᢬ᢠ๎ࡢゎ᫂ࡣᐃᖖὶࡢሙྜ࡛ࡶ㞴ࡋ࠸15)ࠋ࠸ࠋࡇࡢ㐳ୖ㐣⛬ᖹᆒࡢρ࡜Kࢆ⌮ㄽIII࡟࠾ࡅࡿρ࡜Kࡢ㏆
ࡲࡋ࡚ࡸ㸪ὠἼỏ℃ὶࡢࡼ࠺࡟㠀ᐃᖖᛶࡀ࠿ࡽࡴ࡜ࡑࡢ ఝ್࡜ࡋ࡚⏝࠸ࡿࡇ࡜࡟ࡍࢀࡤ㸪3⌮ㄽࡣఱࢀࡶh1㸪i㸪㞴ࡋࡉࡣ࡞࠾ࡉࡽ࡛㸪ྛ✀ࡢỏ℃஦㇟ẖ࡟ᑐᛂࡏࡊࡿࢆ d50࡟౫Ꮡࡍࡿࡇ࡜࡟࡞ࡾ㸪ྛ⌮ㄽࡢ┤᥋ẚ㍑࡞࡝ࡢ᳨ウᚓ࡞࠸࠿ࡶࡋࢀ࡞࠸ࠋ
ࡸ㆟ㄽࡀ࡛ࡁࡿࡇ࡜࡟࡞ࡿࠋ ᅛᐃᗋୗࡢἢᓊᇦ௨῝ࡢὠἼ࡟ᑐࡍࡿ㠀ᐃᖖᛶࢆ⪃៖  ඛࡎ㸪ố⥺࡟࠾ࡅࡿධᑕẁἼ㧗h1㸪ᩳ㠃໙㓄i㸪ᅵ◁⢏ࡋࡓ᢬ᢠ๎㸦Ἴື᢬ᢠ๎㸧ࡣ⏣୰ࡽ16)࡟ࡼࡾ㆟ㄽࡉࢀ࡚ ᚄd50࡟౫Ꮡࡍࡿ⌮ㄽIࢆ⪃࠼ࡿࠋ࠸ࡿࠋ᢬ᢠ๎ࡲ࡛࡟ࡣ⮳ࡗ࡚࠸࡞࠸ࡀ㸪ἅ⃝ࡽ17)ࡣᅛᐃ  ⌮ㄽI࡛ࡣᬑ㐢ⓗ࡜⪃࠼ࡽࢀࡿḟᘧࢆ⏝࠸࡚࠸ࡿ2)ࠋ
ᗋୗࡢ୕ḟඖᩘ್ゎᯒ࡟ᇶ࡙ࡁ㸪ὠἼ㐳ୖᇦࢆྵࡵ࡚㸪(1)w
1 KFri2㛫᥋ⓗ࡟ὠἼࡢᢲࡋᘬࡁ㐣⛬ෆ࡛ᦶ᧿ᦆኻಀᩘࡀ᫬㛫ኚ໬ࡍࡿ࠿ࡶࡋࢀ࡞࠸ࡇ࡜ࢆ♧၀ࡋ࡚࠸ࡿࠋ
ࡇࡇ࡛㸪ρwࡣΎỈࡢᐦᗘ࡛࠶ࡿࠋලయⓗ࡟ࡣᘧ(1)ࢆ‶㊊
 ὠἼỏ℃ὶ࡟ᑐࡋ࡚⛣ືᗋ࡜㠀ᐃᖖᛶࡢ୧᪉ࢆ⪃៖ࡋ ࡍࡿḟࡢᐇ㦂ᘧ(2)࡜(3)ࢆ⏝࠸࡚࠸ࡿ3)ࠋ
ࡓ㆟ㄽࡀ㛤ጞࡉࢀࡣࡌࡵࡓࠋ౛࠼ࡤ㸪ᯇ෠2), 3)ࡣỈ⌮ᐇ㦂
0. 5
h
(2)
K 0.00255 Fri 1 i࡟ᇶ࡙࠸࡚ධᑕࣇ࣮ࣝࢻᩘFri࡜ᗏ㉁ᅵ◁⢏ᚄd50࡟౫Ꮡࡍd 50
ࡿỏ℃ὶ᢬ᢠ๎ࢆᬻᐃⓗ࡟ᥦ♧ࡋ࡚࠸ࡿࠋࡓࡔࡋ㸪ᗏ㠃໙㓄࡟ࡶ౫Ꮡࡍࡿ᢬ᢠ๎ࡲ࡛࡟ࡣ⮳ࡗ࡚࠸࡞࠸ࠋࡲࡓ㸪
0 .5
h
(3)
w
1 0.00255Fri i⛣ືᗋୗࡢỏ℃ὶࡢᦶ᧿ᦆኻಀᩘࡣ⛣ືᗋୗࡢᐃᖖὶࡢ
d 50
ࡶࡢ࡟ẚ࡭࡚኱ࡁ࠸ࡇ࡜ࢆᐇドࡋ㸪ὠἼ㐳ୖゎᯒ㸪ࡦ࠸࡚ࡣὠἼⲴ㔜ゎᯒ࡛ࡣᦶ᧿ᦆኻಀᩘ࡜ỏ℃Ỉᐦᗘࡢ᫬㛫 ࡇࡇ࡛㸪hi ࡣධᑕỏ℃Ỉ῝㸪Fri  247
 d 50 hi ࡛࠶ࡿࠋᘧ
(2)࡟ࡘ࠸࡚ࡣጇᙜᛶࡢ↷ᰝࡀ⾜ࢃࢀ࡚࠸ࡿ18)ࠋᘧ(2)࡜(3)ኚ໬ࢆ⪃៖ࡍࡿࡇ࡜ࡢᚲせᛶࢆᣦ᦬ࡋ࡚࠸ࡿࠋ ⛣ືᗋୗࡢὠἼỏ℃஦㇟ࡀ࿘ᮇ㸦つ๎Ἴ㸧㐠ື࡜ࡣ⪃ ࡢィ⟬ᅗࢆᅗ1࡜2࡟♧ࡍࠋ࠼࡟ࡃ࠸ࠋὠἼࡣ㐣ΏἼ࡛࠶ࡾ㸪ࡶ࡜ࡶ࡜࿘ᮇἼ࡛ࡣ࡞  ᘧ(2)ࡣ⛣ືᗋୗࡢỏ℃ὶඛ➃㒊࡟࠾ࡅࡿ✵㛫ᖹᆒࡢỏ࠸ࠋࡋ࠿ࡋ㸪ố⥺࠿ࡽ᭱኱㐳ୖ఩⨨ࡲ࡛ࡢỏ℃㐠ືࢆᅄ ℃Ỉᐦᗘࡢᐇ㦂್ࢆ⏝࠸࡚ᚓࡽࢀ࡚࠾ࡾ㸪ඛ➃㒊✵㛫ᖹ༙࿘ᮇࡢἼ㐠ື࡜௬ᐃࡋ㸪᪤Ꮡࡢ࿘ᮇἼࡢ᢬ᢠ๎࡟࠾ࡅ ᆒࡢ⛣ືᗋୗࡢỏ℃ὶ᢬ᢠ๎࡜ゝ࠼ࡿࠋ௒ᚋ㸪ᐇ㦂್ࡢࡿ⪃࠼᪉ࢆ㐺⏝ࡍࡿࡇ࡜࡛㸪Ἴ※ᇦ࠿ࡽ㐳ୖᇦࡲ࡛ࡢ඲ ⵳✚࡟ࡼࡾᐇ㦂ಀᩘࡀ᭦᪂ࡉࢀࡿࡇ࡜ࡀ࠶ࡿ࠿ࡶࡋࢀ࡞
ᇦ࡟࠾࠸୍࡚㈏ᛶࢆಖᣢࡉࡏࡓ⛣ືᗋୗࡢỏ℃ὶ᢬ᢠ๎ ࠸ࡀ㸪ᮏ◊✲ᑐ㇟ࡢὠἼ㐳ୖ⌮ㄽࡢ㏆ఝᗘࢆ⪃៖ࡍࢀࡤ㸪ࡢ㐺⏝ἲࢆ⌮ㄽⓗ࡟㆟ㄽ࡛ࡁࡿ࠿ࡶࡋࢀ࡞࠸ࠋ
ᘧᙧࡣ୙ኚ࡜⪃࠼ࡽࢀࡿࠋࡇࡢ≧ἣࡣᘧ(3)ࡶྠࡌ࡛࠶ࡿࠋ ᮏ◊✲ࡣ௨ୖࢆ⫼ᬒ࡟ᯇ෠3)ࡢ⛣ືᗋୗࡢỏ℃ὶ᢬ᢠ  ᘧ(2)࡜(3)ࡀᥦ᱌ࡉࢀࡓᐇ㦂࡜⌮ㄽࡢẚ㍑࡛ࡣ㸪⌮ㄽ࡟๎ࡢὠἼ㐳ୖ࡬ࡢ㐺⏝ᛶ࡜㐺⏝ἲࢆ㐳ୖᐇ㦂࡜ࡢẚ㍑࡞ ࠾ࡅࡿố⥺࡛ࡢධᑕẁἼ㧗h1ࢆḟᘧ࡛ホ౯ࡍࡿ3)ࠋࡇࢀ
࡝ࢆ㏻ࡋ࡚⌮ㄽⓗ࡟᳨ウࡍࡿࡇ࡜ࢆ┠ⓗ࡜ࡍࡿࠋࡣ3⌮ㄽ࡛ඹ㏻࡛࠶ࡿࠋ
2

ui
(4)
h1 hi
2g
 ὠἼ㐳ୖ࡬ࡢ㐺⏝ᛶ ᯇ෠ࡽ3), 14)ࡣỏ℃Ỉᐦᗘρࡢᙳ㡪ࢆ⪃៖ࡋࡓ3ࡘࡢὠἼ ࡇࡇ࡛㸪gࡣ㔜ຊຍ㏿ᗘ࡛㸪hi ࡟ࡣᐇ㦂࡟࠾ࡅࡿố⥺㐳ୖ⌮ㄽࢆᥦ♧ࡋ࡚࠸ࡿࠋố⥺࡟࠾ࡅࡿධᑕẁἼ㧗h1㸪 㸦㐳ୖᩳ㠃ጞⅬ㸧࡛ࡢධᑕỏ℃Ỉ῝hidࢆ㸪ධᑕỏ℃ὶ㏿
୍ᵝ࡞ᩳ㠃໙㓄 i㸪ᅵ◁⢏ᚄd50࡟౫Ꮡࡍࡿ⌧≧࡛ࡣ୍␒ ui࡟ࡣᐇ㦂࡟࠾ࡅࡿỏ℃ὶඛ➃⛣ື㏿ᗘࢆ⏝࠸ࡿ3)ࠋ
ᬑ㐢ᛶࡀ㧗࠸࡜ุ᩿ࡉࢀࡿ⌮ㄽࢆ⌮ㄽI㸪h1࡜i㸪ρ࡟౫Ꮡ  ⌮ㄽIࡢィ⟬࡛ࡣᅵ◁⢏ᚄd50ࡢ᝟ሗࡶᚲせ࡛㸪ᐇ㦂࡟ࡍࡿ⌮ㄽࢆ⌮ㄽII㸪h1࡜i㸪ρ㸪ᦶ᧿ᦆኻಀᩘK࡟౫Ꮡࡍࡿ ࠾ࡅࡿ㐳ୖᩳ㠃ࡣᅛᐃᗋ࡞ࡢ࡛3)㸪ᩳ㠃⢒ᗘ㸦┦ᙜ⢒ᗘ* Method for applying frictional resistance law of inundation flow over a movable bed to tsunami run-up by Hideo MATSUTOMI

58

ᅗ3 㐳ୖࡍࡿὠἼỏ℃ὶࡢึᮇ᮲௳࡜ㅖグྕࡢᐃ⩏

ᐇ 㦂
ࢣ࣮ࢫ

hi
(cm)

Case 10 5.46
Case 11 5.84
Case 12 4.43

ᅗ1 ỏ℃ὶᦶ᧿ᦆኻಀᩘKࡢホ౯ᐇ㦂ᘧ(2)ࡢィ⟬ᅗ⾲1 ᐇ㦂್3)࡜ィ⟬᮲௳
Fri LRe
h1
i
d50
ρ/ρw
K
(-) (cm) (cm)
(-)
(mm)
(-)
(-)
2.02 207 18.11 0.1296 1.00 1.036 0.00077
1.99 186 19.17 0.1296 1.00 1.037 0.00082
2.40 197 17.89 0.1296 1.00 1.035 0.00076

 ࡇࡢỏ℃ὶ㏿ࡣḟࡢ᫬㛫tmean࡟ᙧᡂࡉࢀࡿࠋ
c1
i 8X g

tmean

(10)

ࡋࡓࡀࡗ࡚㸪ỏ℃Ỉᐦᗘࡢᖹᆒ್ホ౯ᘧࡣḟᘧ࡜࡞ࡿࠋ
w

1 0.00255Fri
1 0.00255

ᅗ2 ỏ℃Ỉᐦᗘρࡢホ౯ᐇ㦂ᘧ(3)ࡢィ⟬ᅗks㸧ࡢd50㸦=1.0 mm14)㸧ࢆ⏝࠸ࡿࠋ ḟ࡟⌮ㄽIIࢆ⪃࠼ࡿࠋ⌮ㄽII࡟࠾࠸࡚ࡶᘧ(1)ࡢ㛵ಀࢆ⏝࠸࡚࠸ࡿࠋࡓࡔࡋ㸪⌮ㄽI࡟࠾ࡅࡿd50ࡢ௦ࢃࡾ࡟ỏ℃Ỉᐦᗘρࢆ⏝࠸࡚࠾ࡾ㸪ỏ℃Ỉᐦᗘࡣ㐳ୖ㐣⛬ᖹᆒࡢ୍ᐃ್࡜ࡋ࡚࠸ࡿࠋࡑࡢᖹᆒ್ホ౯ᘧࡣḟࡢࡼ࠺࡟ࡋ࡚ᑟฟࡉࢀࡿࠋ ᅗ3࡟♧ࡍ⌮ㄽࣔࢹࣝ࡟࠾ࡅࡿỏ℃ὶඛ➃㒊ࡢᚋ➃఩⨨x=ξ࡛ࡢỏ℃Ỉ῝H࡜ỏ℃ὶ㏿Uࡣྛࠎḟᘧ࡛࠶ࡿ14)ࠋ
1
c1
g

H

U

1
U
2

1
igt
2

2

2c1 igt 8 Xgt

(5)

(6)

(7)

2

H

16 X gtm

i 8X gh1
d 50

10.00255
U mean
gd 50

(11)

0 .5

ࡇࡇ࡛㸪d50ࡣ⌮ㄽI࡜ࡢ୍㈏ᛶ࠿ࡽᩳ㠃⢒ᗘࡢࡶࡢࢆ⏝࠸ࡿࠋ ⌮ㄽIIIࢆ⪃࠼ࡿࠋ⌮ㄽIII࡛ࡣᘧ(1)ࡢ㛵ಀࢆ⏝࠸࡚࠸࡞࠸ࠋࡍ࡞ࢃࡕ㸪ᦶ᧿ᦆኻಀᩘK࡜ỏ℃Ỉᐦᗘρࡣ㐃ືࡋ࡚࠸࡞࠸ࠋࡑࡢ௦ࢃࡾ࡟ᦶ᧿ᦆኻಀᩘ࡜ỏ℃Ỉᐦᗘࢆ㐳ୖ㐣⛬ᖹᆒࡢ୍ᐃ್࡜ࡋ࡚࠸ࡿࠋ⌮ㄽIIIࡢィ⟬࡛ࡣ㏆ఝ
ⓗ࡛࠶ࡿࡀ⌮ㄽII࡟ᇶ࡙ࡃᘧ(11)࠿ࡽᚓࡽࢀࡿỏ℃Ỉᐦᗘ࡜⌮ㄽII࡟ᇶ࡙ࡁḟࡢࡼ࠺࡟ࡋ࡚ᑟฟࡉࢀࡿᦶ᧿ᦆኻಀ
ᩘࡢᖹᆒ್ホ౯ᘧ㸦ᚋ㏙ࡢᘧ(14)㸧࠿ࡽᚓࡽࢀࡿᦶ᧿ᦆ
ኻಀᩘࢆ⏝࠸ࡿࡇ࡜࡟ࡍࡿࠋ 㐳ୖ㐣⛬࡟࠾ࡅࡿ௵ព᫬้t࡛ࡢධᑕࣇ࣮ࣝࢻᩘFriࡣ
ᘧ(6)࡜(7)࠿ࡽḟᘧ࡜࡞ࡿࠋ
U
c1
i 8X
(12)
F
ri

gH

2 Xgt

4X

 ᘧ(12)ࡢt࡟ᘧ(10)ࡢ㐳ୖ㐣⛬ᖹᆒࡢỏ℃ὶ㏿᫬tmeanࢆ௦ධࡍࢀࡤ㸪ḟࡢtmean᫬ࡢධᑕࣇ࣮ࣝࢻᩘFri meanࡀᚓࡽࢀࡿࠋ

X  1  w  4  w  ࡢ୍ᐃ್࡛࠶ࡿࠋࡇࡇ࡛㸪 ᘧ(5)࡜(6)࠿ࡽḟᘧࡀᚓࡽࢀࡿࠋ
2

0.5

hi
d 50

Fri mean

i 8X
4X

(13)

ࡋࡓࡀࡗ࡚㸪ᦶ᧿ᦆኻಀᩘࡢ㐳ୖ㐣⛬ᖹᆒ್Kmeanࡢホ౯ 㐳ୖ㛤ጞ᫬ࢆt=0࡜ࡍࢀࡤ㸪᭱኱㐳ୖ㊥㞳᫬ࡢ᫬㛫tmࡣ ᘧࡣḟᘧ࡜࡞ࡿࠋ
ỏ℃ὶ㏿U=0࡜ࡋ࡚ᚓࡽࢀ㸪ḟᘧ࡜࡞ࡿࠋ
0 .5
0 .5
2
h1
4X
h1
2
2c1
(8)
K
0
.
00255
F
0
.
00255
mean
ri
mean
t
d 50

i 8X

d 50

ࡋࡓࡀࡗ࡚㸪㐳ୖ㐣⛬ᖹᆒࡢỏ℃ὶ㏿Umeanࡣḟᘧ࡜࡞ࡿࠋ
(14)
1 t(9) ࡇࡇ࡛㸪⌮ㄽIࡸ⌮ㄽII࡜ࡢ୍㈏ᛶ࠿ࡽỏ℃Ỉᐦᗘࡸᦶ᧿
U
Udt c
m

mean

tm 0

1

ᦆኻಀᩘࡢホ౯࡟࠾ࡅࡿd50ࡣᩳ㠃⢒ᗘࡢࡶࡢࢆ⏝࠸ࡿࠋ59(a) Case 10(a) Case 10(b) Case 11(b) Case 11(c) Case 12
ᅗ4 ྛ⌮ㄽ࡟ࡼࡿỏ℃ὶඛ➃఩⨨a(t)ࡢẚ㍑౛

(c) Case 12
ᅗ6 ௬᝿ࡋࡓ㐳ୖᩳ㠃࡟࠾ࡅࡿྛ⌮ㄽ࡟ࡼࡿỏ℃ὶඛ➃఩⨨a(t)ࡢẚ㍑౛ᅗ5 ᐇ㦂㸪⌮ㄽII㸪⌮ㄽIIIࡢ⌮ㄽI࡜ࡢ㐳ୖ㊥㞳ẚ

 ௨ୖࡢࡼ࠺࡟ࡋ࡚ホ౯ࡉࢀࡿྛ⌮ㄽ࡟ࡼࡿỏ℃ὶඛ➃఩⨨a(t)ࡢẚ㍑౛ࢆᅗ4࡟♧ࡍࠋ⾲1࡟⌮ㄽィ⟬ࡢㅖ᮲௳࡜ࡑࡢ๓ᥦ࡜࡞ࡗࡓᐇ㦂್3)ࢆ♧ࡍࠋᅗࡣୖ࠿ࡽ㡰࡟
ỏ℃ὶᐇ㦂Case 10㹼12࡛࠶ࡿࠋࡲࡓ㸪㐳ୖ㊥㞳LR࡟㛵ࡋ࡚⌮ㄽI࡟ࡼࡿࡶࡢ࡜ᐇ㦂㸪⌮ㄽIIࡸ⌮ㄽIII࡟ࡼࡿࡶࡢ࡜
ࡢẚ㍑౛㸦RE/I=ᐇ㦂/⌮ㄽI㸪RII/I=⌮ㄽII/⌮ㄽI㸪RIII/I=⌮ㄽIII/⌮ㄽI㸧ࢆᅗ5ࡢComparison Case No. 1㹼3࡟♧ࡍࠋᅗ୰࡟
ࡣ௨㝆ࡢ᳨ウ⤖ᯝ㸦Comparison Case No. 4㹼12㸧ࡶ♧ࡋ࡚࠶ࡿࠋࡓࡔࡋ㸪᏶඲࡟ྠࡌ᮲௳ୗ࡛ࡢᐇ㦂࡜⌮ㄽࡢẚ㍑
ࡣᐇ㦂ࡀ㞴ࡋࡃ㸪⌧≧࡛ࡣ࡛ࡁ࡞࠸ࡇ࡜ࢆ᩿ࡗ࡚࠾ࡃ3)ࠋ

60 ୧ᅗ࠿ࡽ㸪1) ⌮ㄽII㸪⌮ㄽI㸪⌮ㄽIIIࡢ㡰࡟㐳ୖ㊥㞳ࡀ㛗ࡃ㸪ố⥺࠿ࡽ᭱኱㐳ୖ㊥㞳఩⨨ࡲ࡛࡟㐩ࡍࡿ᫬㛫ࡀ▷࠸㸪2) ⌮ㄽIIࡣ⌮ㄽIࡼࡾࡶ㸪⌮ㄽIࡣ⌮ㄽIIIࡼࡾࡶᐇ㦂࡜ࡢ㐺ྜᗘࡀࡼ࠸㸦ᖹᆒⓗ࡟ᐇ㦂್ࡣ⌮ㄽIIࡢ0.99ಸ㸪⌮ㄽIࡢ1.07ಸ㸪⌮ㄽIIIࡢ1.12ಸ 㸪3) 2)ࡢ⤖ᯝࡣึᮇ᮲௳ ᘧ(4) ࡢỴࡵ᪉ࡸỏ℃ὶ᢬ᢠ๎ࡀጇᙜ࡛࠶ࡿࡇ࡜ࢆ♧ࡋ࡚࠸ࡿ㸪4) ᬑ㐢ᛶࡀ᭱ࡶ㧗࠸⌮ㄽIࡣ3⌮ㄽࡢ୰࡛ᇶ‽࡜࡞ࡿ⌮ㄽ࡜⪃࠼ࡽࢀ㸪㐳ୖ㐣⛬ᖹᆒࡢỏ℃Ỉᐦᗘ୍ᐃࡣࡸ
ࡸ㛗ࡵࡢ㐳ୖ㊥㞳ࢆ୚࠼ࡿ㸪5) 㐳ୖ㐣⛬ᖹᆒࡢᦶ᧿ᦆኻ
ಀᩘ୍ᐃࡣỏ℃Ỉᐦᗘࡢ㛗ࡵࡢ㐳ୖ㊥㞳ࢆ୚࠼ࡿഴྥࢆ
ඃ࡟ᡴᾘࡍ࡯࡝ࡢ▷ࡵࡢ㐳ୖ㊥㞳ࢆ୚࠼ࡿࡇ࡜ࡀุࡿࠋ
 ⪃ᐹ1)࡜2)࡟࠾ࡅࡿ⌮ㄽIIIࡢ⤖ᯝ࡟ࡣᦶ᧿ᦆኻಀᩘ࡜
ỏ℃Ỉᐦᗘ࡜ࡋ࡚⌮ㄽII࡟ᇶ࡙ࡃ㐳ୖ㐣⛬ᖹᆒࡢࡶࡢࢆ
㏆ఝⓗ࡟⏝࠸࡚࠸ࡿࡇ࡜ࡀᙳ㡪ࡋ࡚࠸ࡼ࠺ࠋࡲࡓ㸪⪃ᐹ1)ࡣࡇࢀࡲ࡛ࡢᦶ᧿ᦆኻಀᩘࢆ᫬㛫ⓗ࡟୍ᐃ࡜ࡍࡿὠἼ
ᩘ್ィ⟬࡟ᨵၿࡢవᆅࡀ㸪≉࡟㐳ୖᇦ࡟࠾࠸࡚Ꮡᅾࡍࡿ
ࡇ࡜ࢆ♧၀ࡋ࡚࠸ࡿࠋ
 ⪃ᐹ1)ࡢ๓༙㒊㸪2)࡜4)ࡢ⌮⏤࡜ࡋ࡚㸪㐳ୖ㐣⛬ᖹᆒࡢᦶ᧿ᦆኻಀᩘࡸỏ℃Ỉᐦᗘࢆ⏝࠸࡚࠸ࡿࡇ࡜ࡀ⪃࠼ࡽࢀࡿࠋᮏ⌮ㄽࣔࢹ࡛ࣝࡣ㸪ỏ℃ὶࡀ㐳ୖࡍࡿ࡟ࡘࢀ࡚㸪ᦶ᧿ᦆኻಀᩘࡣ኱ࡁࡃ㸪ỏ℃Ỉᐦᗘࡣపࡃ࡞ࡾ3)㸪㐳ୖ㐣⛬ᖹᆒࡼࡾᑡࡋố⥺㸦ึᮇ㸧ഃࡢࡶࡢࢆ⏝࠸ࡿࡇ࡜࡛
⪃ᐹ1)ࡢ๓༙㒊㸪2)࡜4)ࡢ௳ࡣᨵၿࡉࢀࡿࠋ࡜ࡣゝ࠼㸪ఱࢀࡢ⌮ㄽࡶᐇ㦂࡜ࡢᕪࡀ㧗ࠎ12%௨ෆ࡛࠶ࡾ㸪⌮ゎࡢࡋ᫆ࡉࡸά⏝ࡢᐜ᫆ࡉࡢⅬ࠿ࡽ㐳ୖ㐣⛬ᖹᆒࡢ᥇⏝ࡀ᥎ዡࡉࢀࡿࠋࡑࡢ௚ࡢ⌮⏤࡜ࡋ࡚ᩳ㠃⢒ᗘd50ࡢ᥇⏝್ࡢጇᙜᛶࡀ⪃࠼ࡽࢀࡿࠋ
 ⪃ᐹ5)ࡢỏ℃Ỉᐦᗘࡼࡾᦶ᧿ᦆኻಀᩘࡢ᪉ࡀ㐳ୖ㊥㞳࡬ࡢᙳ㡪ࡀ኱ࡁ࠸ࡇ࡜ࡣ⌮ㄽIIIࡢ≉ᛶ᳨ウ࡟࠾࠸࡚ࡍ࡛
࡟☜ㄆ῭ࡳ࡛࠶ࡿ14)ࠋ
 ⌮ㄽIࡀᐇ㦂ࡢ㐳ୖ㊥㞳LRࢆࡼࡃㄝ࡛᫂ࡁࡿࡇ࡜ࢆ☜ㄆࡋࡓࠋࡑࡇ࡛㸪㐳ୖᩳ㠃ࡶố⥺ࡲ࡛࡜ྠࡌᅵ◁⢏ᚄࡢ⛣ືᗋ࡜௬᝿ࡋ㸪⌮ㄽIࡢ㐳ୖ㊥㞳ࢆ┿್࡜⪃࠼㸪௬᝿ࡋࡓሙྜ࡟࠾࠸࡚ࡶ⌮ㄽII࡜⌮ㄽIIIࡀᅗ4ࡸ5࡜ྠഴྥࢆ
♧ࡍ࠿࡝࠺࠿ࢆ᳨ウࡍࡿࠋࡇࡢሙྜ㸪ᩳ㠃⢒ᗘ㸦┦ᙜ⢒ᗘks㸧ࡣ3d50࡜࡞ࡿ3)ࠋ
 ᳨ウ⤖ᯝࢆᅗ6࡜ᅗ5୰ࡢComparison Case No. 4㹼6࡟♧ࡍࠋ୧ᅗ࠿ࡽ㸪1) ⌮ㄽIࡢ㐳ୖ㊥㞳ࡀ▷ࡵ㸦⣙9%ῶ㸧࡜࡞ࡗ࡚࠸ࡿࡇ࡜㸪2) 㐳ୖ㊥㞳ẚࡣᅗ4ࡢሙྜ࡜࡯ࡰྠࡌ
㸦ᖹᆒⓗ࡟⌮ㄽII࡜⌮ㄽIIIࡣ㡰࡟⌮ㄽIࡢ1.08ಸ࡜0.95ಸ㸧࡛࠶ࡿࡇ࡜ࡀุࡿࠋ1)ࡢ௬᝿ࡋࡓሙྜ࡟࠾࠸࡚㐳ୖ㊥㞳ࡀ▷ࡃ࡞ࡿࡇ࡜ࡣ᝿ീ࡟㞴ࡃ࡞࠸ࠋ2)ࡣ⌮ㄽI㸪⌮ㄽII㸪
⌮ㄽIIIࡢ㐳ୖ㊥㞳࡟㛵ࡍࡿ┦஫㛵ಀࡀ㐳ୖᩳ㠃ࡢ≧ἣ࡟౫Ꮡࡋ࡞࠸ࡇ࡜ࢆ♧ࡋ࡚࠸ࡿࠋ௒ᚋ㸪ࡇࢀࡽࡢุ᩿ࢆࡼ
ࡾ☜࠿࡞ࡶࡢ࡜ࡍࡿࡓࡵ㸪ࡇࡇ࡛௬᝿ࡋࡓ᮲௳࡟࠾ࡅࡿ
㐳ୖ㊥㞳LRࡢᐇ㦂್ྲྀᚓࡀᮃࡲࢀࡿ㸦1౛Ꮡᅾࡍࡿ3) ࠋ ὠἼ㐳ୖ࡬ࡢ㐺⏝ἲ ࠕᅵ◁⢏ᚄࡣd50࡜࠸࠺୍ᐃ⢏ᚄ࡛ࡼ࠸࠿ࠖ࡜࠸࠺␲ၥ
ࢆ㝖ࡅࡤ㸪⌮ㄽIࡢά⏝࡟≉ẁࡢၥ㢟ࡣ࡞࠸ࠋ⌮ㄽIࡣ3⌮ㄽࡢ୰୍࡛␒⌧ᐇⓗ࡛㸪ά⏝ࡀᐜ࡛᫆ࡶ࠶ࡿࠋ
 ⌮ㄽII࡛ࡣỏ℃Ỉᐦᗘρࢆ㸪⌮ㄽIII࡛ࡣỏ℃Ỉᐦᗘ࡜ᦶ᧿ᦆኻಀᩘKࢆ㐳ୖ㐣⛬ᖹᆒࡢ୍ᐃ್࡜ࡋ࡚࠸ࡿࠋ ࡜ࡇࢁ࡛㸪ᅛᐃᗋୗࡢ࿘ᮇἼࡢᦶ᧿ᦆኻಀᩘfwࡣᆅⅬẖࡢ᭱኱ᗏ㠃ࡏࢇ᩿ᛂຊ࡜Ἴືቃ⏺ᒙୖ➃࡟࠾ࡅࡿ᭱኱
ὶ㏿ࢆ⏝࠸࡚ᐃ⩏ࡉࢀࡿࡼ࠺࡛࠶ࡿ㸦ᐃ⩏ᘧ࡟࠾ࡅࡿᐃ
ᩘಀᩘࡀ࠸ࡃࡽ࠿㸪౛࠼ࡤ1/1㸪1/2㸪1/8࠿࡟せὀព 19)ࠋࡑࡢ᭱኱ᗏ㠃ࡏࢇ᩿ᛂຊ࡜᭱኱ὶ㏿ࡣἼᓠ఩┦࡛ᙧᡂࡉࢀࡿ࡜⪃࠼࡚ࡼ࠸ࡼ࠺࡛㸪fwࡣ᫬㛫ⓗ࡟୙ኚ㸦࿘ᮇ௦⾲್ ࡜ࡋ࡚ྲྀࡾᢅࢃࢀࡿࡼ࠺࡛ࡶ࠶ࡿࠋࡋࡓࡀࡗ࡚㸪㐳ୖ㐣⛬࡟࠾࠸࡚ࡶỏ℃Ỉᐦᗘࡸᦶ᧿ᦆኻಀᩘࡀ᫬㛫ⓗ࡟୙ኚ ୍ᐃ್ ࡛ࡼ࠸࡞ࡽࡤ㸪࿘ᮇἼ࡟࠾ࡅࡿྲྀᢅ࠸࡜ࡢ
୍㈏ᛶࢆ⪃៖ࡋ࡚㸪௨ୗࡢ⪃࠼᪉࡟ࡼࡾố⥺x=0 ึᮇt=0 ࡟࠾ࡅࡿࡑࢀࡽࡢホ౯್ࢆ⏝࠸ࡿࡇ࡜ࡀ᥎ዡࡉࢀࡼ࠺ࠋ ὠἼࡢ㐳ୖỏ℃⌧㇟ࢆố⥺఩⨨ࢆ୰ᚰ࡜ࡋࡓᅄ༙࿘ᮇ
ࡢ࿘ᮇἼ⌧㇟࡜௬ᐃࡍࡿࠋᮏ⌮ㄽࣔࢹࣝ3), 14)ࡢỏ℃ὶࡣố⥺࡛᭱኱ࡢධᑕỏ℃Ỉ῝hi࡜ỏ℃ὶඛ➃⛣ື㏿ᗘࢆᙧᡂࡋ㸪h1ࢆố⥺࡟࠾ࡅࡿὠἼࡢධᑕẁἼ㧗࡜ࡍࢀࡤ㸪୧
2 gh1࡛࠶ࡿ20)ࠋᯇ෠ࡀᥦ᱌ࡋ࡚࠸ࡿ
⪅ࡣࡑࢀࡒࢀ4h1/9࡜
⛣ືᗋୗࡢỏ℃ὶࡢᦶ᧿ᦆኻಀᩘK࡜ỏ℃Ỉᐦᗘρࡢホ౯ᐇ㦂ᘧ(2)࡜(3)࡛ࡣධᑕࣇ࣮ࣝࢻᩘFriࡢỏ℃ὶ㏿ui࡜ࡋ
࡚ỏ℃ὶඛ➃⛣ື㏿ᗘࡀ᥇⏝ࡉࢀ࡚࠾ࡾ㸪ố⥺࡟࠾ࡅࡿᯇ෠ᐃ⩏ࡢධᑕࣇ࣮ࣝࢻᩘࡣᖖ࡟3ࡢ᭷㝈್࡜࡞ࡿࠋࡋ
ࡓࡀࡗ࡚㸪࿘ᮇἼ࡟࠾ࡅࡿྲྀᢅ࠸࡜ࡢ୍㈏ᛶ࠿ࡽ㸪ὠἼࡢ㐳ୖỏ℃࡟ᑐࡋ࡚ố⥺࡟࠾ࡅࡿᯇ෠ࡢ⛣ືᗋୗࡢỏ℃ὶࡢᦶ᧿ᦆኻಀᩘࡸỏ℃Ỉᐦᗘࢆ᥇⏝ࡍࡿࡇ࡜࡟ࡍࢀࡤ㸪ࡑࢀࡽࡢホ౯ᐇ㦂ᘧࡣࡑࢀࡒࢀḟᘧ࡜࡞ࡿࠋ
Kx 0

0.00255 Fri 1
2 i 8X
9 4X

hi
d 50

x 0

2

w

0.000567

h1
d 50

0 .5

(15)

2

K mean1 0.00255Fri

w

0 .5

hi
d 50

0 .5

1 0.0051

h1
d 50

0 .5

(16)

1

ᘧ(15)࡜(16)࡟ࡣࡑࢀࡒࢀ㐳ୖ㐣⛬ᖹᆒࡢᘧ(14)࡜(11)࡜ࡢ
㛵ಀࡶ♧ࡉࢀ࡚࠸ࡿࠋ୧ᘧ࠿ࡽ㸪ࡑࢀࡒࢀᩳ㠃໙㓄iࡢ್ḟ➨㸦Հ2 3 2 4X 㸧࡛Kx=0࡜Kmeanࡢ኱ᑠ㛵ಀࡀỴࡲࡾ㸪
ỏ℃Ỉᐦᗘࡣố⥺࡛ࡢࡶࡢࡀᖖ࡟㧗࠸3)ࡇ࡜ࡀุࡿࠋỏ℃Ỉᐦᗘࡢࡇࡢഴྥࡣ㸪ố⥺࡛ࡢࡶࡢࢆ⏝࠸ࢀࡤ㸪㐳ୖ㊥㞳LRࡣᖖ࡟▷ࡵ࡟ホ౯ࡉࢀࡿࡇ࡜ࢆ♧ࡍࠋ ᘧ(15)࡜(16)࠿ࡽホ౯ࡉࢀࡿ್ࢆ㐳ୖ㐣⛬ࡢ௦⾲್࡜ࡋ࡚⏝࠸ࡓሙྜࡢྛ⌮ㄽ࡟ࡼࡿỏ℃ὶඛ➃఩⨨a(t)ࡢẚ㍑
౛ࢆᅗ7࡟♧ࡍࠋᅗ4࡜ྠࡌࡃୖ࠿ࡽ㡰࡟Case 10㹼12࡛61(a) Case 10(a) Case 10(b) Case 11(b) Case 11(c) Case 12(c) Case 12
ᅗ7 ྛ⌮ㄽ࡟ࡼࡿỏ℃ὶඛ➃఩⨨a(t)ࡢẚ㍑౛㸦ố⥺࡟࠾ࡅࡿ ᅗ8 ྛ⌮ㄽ࡟ࡼࡿỏ℃ὶඛ➃఩⨨a(t)ࡢẚ㍑౛㸦ố⥺࡟࠾ࡅࡿ⌮ㄽ࡟ᇶ࡙ࡃ᮲௳ࢆ౑⏝㸧ᐇ㦂࡟ᇶ࡙ࡃ᮲௳ࢆ౑⏝㸧࠶ࡿࠋࡲࡓ㸪㐳ୖ㊥㞳LR࡟㛵ࡋ࡚⌮ㄽI࡟ࡼࡿࡶࡢ࡜ᐇ  ᘧ(4)ࡢධᑕẁἼ㧗h1ࡀྠࡌ࡛ࡶධᑕỏ℃Ỉ῝hi࡜ධᑕ㦂㸪⌮ㄽIIࡸ⌮ㄽIII࡟ࡼࡿࡶࡢ࡜ࡢẚ㍑౛ࢆᅗ5ࡢ ỏ℃ὶ㏿uiࡢh1࡬ࡢ㈉⊩ᗘḟ➨࡛ὶ㔞ࡸẚຊ࡞࡝ࡀ␗࡞
Comparison Case No. 7㹼9࡟♧ࡍࠋ୧ᅗ࠿ࡽ㸪ᦶ᧿ᦆኻಀᩘ ࡿࡢ࡛㸪ố⥺㸦ึᮇ㸧࡟࠾ࡅࡿỏ℃Ỉᐦᗘࡸᦶ᧿ᦆኻಀ
ࡸỏ℃Ỉᐦᗘ࡜ࡋ࡚㐳ୖ㐣⛬ᖹᆒࡢ್ࢆ⏝࠸ࡓᅗ4ࡢሙ ᩘ࡜ࡋ࡚hi࡜uiࡢ୧ᐇ㦂್ࢆಶู࡟㝧࡟ά⏝ࡍࡿḟࡢ2ᘧ
ྜ࡟ẚ࡭࡚㸪⌮ㄽIIࡣ࠿࡞ࡾ▷ࡵ㸦⣙23%ῶ 㸪⌮ㄽIIIࡣ ࡛ホ౯ࡉࢀࡿࡶࡢࢆ⏝࠸ࡿሙྜࡢ᳨ウࡶ᭷┈࡜ᛮࢃࢀࡿࠋ
0.5
኱ᖜ࡟▷ࡵ㸦⣙39%ῶ㸧ࡢ㐳ୖ㊥㞳ࢆ୚࠼ࡿࡇ࡜ࡀุࡿࠋ
0.5
2ࡇࢀࡽࡢ⤖ᯝ࠿ࡽ㸪1) ᑡ࡞ࡃ࡜ࡶ㐳ୖ㐣⛬࡛ࡣᦶ᧿ᦆኻ
h
F
h
w
ri
1
1 0.00255Fri i
1 0.00255
1 2 d50d50
ಀᩘࡸỏ℃Ỉᐦᗘࡀ᭷ព࡟᫬㛫ኚ໬ࡍࡿࡇ࡜㸪2) ố⥺
x 0
Fri
1
2
㸦ึᮇ㸧࡟࠾ࡅࡿᦶ᧿ᦆኻಀᩘࡸỏ℃Ỉᐦᗘࡣ㐳ୖ㐣⛬(17)඲యࢆ⾲⌧ࡋᚓࡿࡶࡢ࡛ࡣ࡞࠸ࡇ࡜ࡀ᥎ᐹࡉࢀࡿࠋ

62

0.5
0.5

ཧ⪃ᩥ⊩

1) ᯇ෠ⱥኵ㸸㝣ୖ㐳ୖὠἼࡢඛ➃᮲௳࡜ඛ➃㒊ࡢ᢬ᢠಀᩘ㸪➨28ᅇᾏᓊᕤᏛㅮ₇఍ㄽᩥ㞟㸪pp.74-78, 1981.
2) ᯇ෠ⱥኵ㸸ὠἼỏ℃Ỉᐦᗘࡢ⡆᫆ホ౯ἲ㸪ᅵᮌᏛ఍ㄽᩥ㞟
B2㸦ᾏᓊᕤᏛ 㸪Vol.75, No.2, pp.385-390, 2019.
(18)3) ᯇ෠ⱥኵ㸸ỏ℃Ỉᐦᗘࡢ᫬㛫ኚ໬ࢆ⪃៖ࡋࡓὠἼ㐳ୖ㸪ᮾࡇࡇ࡛㸪ධᑕࣇ࣮ࣝࢻᩘFriࡣố⥺࡟࠾ࡅࡿධᑕỏ℃Ỉ῝໭ᆅᇦ⅏ᐖ⛉Ꮫ◊✲㸪➨58ᕳ㸪2022.㸦༳ๅ୰㸧hidࢆ⏝࠸ࡓ࡜ࡁࡢࡶࡢ㸪d50ࡣᩳ㠃⢒ᗘࡢࡶࡢ࡛࠶ࡿࠋ
4) ᯇ෠ⱥኵ㸪ᕝᓥᓧ㸸ὠἼỏ℃ὶࡢᐦᗘ࡟㛵ࡍࡿᇶ♏ᐇ㦂㸪ᅵᮌᏛ఍ㄽᩥ㞟B2㸦ᾏᓊᕤᏛ 㸪Vol.71, No.2, pp.355-360, 2015.
 ᘧ(17)࡜(18)࠿ࡽホ౯ࡉࢀࡿ್ࢆ㐳ୖ㐣⛬ࡢ௦⾲್࡜ࡋ
5)ᯇ෠ⱥኵ㸪௒㔝ྐᏊ㸪㰻ᕝ⪷㸪㙊⁪Ꮥಙ㸪Ώ㑓୍ஓ㸸ὠἼ࡚⏝࠸ࡓሙྜࡢྛ⌮ㄽ࡟ࡼࡿỏ℃ὶඛ➃఩⨨a(t)ࡢẚ㍑
ỏ℃Ỉᐦᗘࡢᅵ◁ሁ✚ࡸ㐳ୖ㧗࡬ࡢᙳ㡪㸪ᅵᮌᏛ఍ㄽᩥ㞟
౛ࢆᅗ8࡟♧ࡍࠋᅗࡣୖ࠿ࡽ㡰࡟Case 10㹼12࡛࠶ࡿࠋࡲ
B2㸦ᾏᓊᕤᏛ 㸪Vol.72, No.2, pp.397-402, 2016.
ࡓ㸪㐳ୖ㊥㞳LR࡟㛵ࡋ࡚⌮ㄽI࡟ࡼࡿࡶࡢ࡜ᐇ㦂㸪⌮ㄽII 6) ᯇ෠ⱥኵ㸪௒㔝ྐᏊ㸪ᚋᮧ᫭ᇶ㸪௒⸨᫭ኴ㸪㙊⁪Ꮥಙ㸪Ώࡸ⌮ㄽIII࡟ࡼࡿࡶࡢ࡜ࡢẚ㍑౛ࢆᅗ5ࡢComparison Case㑓୍ஓ㸸ὠἼỏ℃Ỉᐦᗘ࡜ࡑࡢ㐳ୖ㊥㞳ࡸᅵ◁ሁ✚࡬ࡢᙳ
No. 10㹼12࡟♧ࡍࠋ୧ᅗ࠿ࡽ㸪ỏ℃Ỉᐦᗘࡸᦶ᧿ᦆኻಀ
㡪࡟㛵ࡍࡿᐃ㔞ᐇ㦂㸪ᅵᮌᏛ఍ㄽᩥ㞟B2㸦ᾏᓊᕤᏛ 㸪ᩘ࡜ࡋ࡚㐳ୖ㐣⛬ᖹᆒࡢ್ࢆ⏝࠸ࡓᅗ4ࡢሙྜ࡟ẚ࡭࡚㸪 Vol.73, No.2, pp.373-378, 2017.
⌮ㄽIIࡣࡸࡸ▷ࡃ㸪⣙4%ῶ࡜࡞ࡗ࡚⌮ㄽI࡟㏆࡙ࡁ㸦⌮ 7) ༓ⴥ⿱ኴ㸪୕ୖ㍤㸪ᯇ෠ⱥኵ㸸ὠἼỏ℃ỈᐦᗘࡢㅖỈ⌮㔞࡬ࡢ౫Ꮡᛶ㸪ᅵᮌᏛ఍ᮾ໭ᨭ㒊ᢏ⾡◊✲Ⓨ⾲఍ㅮ₇ᴫせㄽIIࡀ⣙3%㛗࠸ 㸪⌮ㄽIIIࡣ㢧ⴭ࡟▷ࡃ㸪⣙44%ῶ࡜࡞ࡾ㸪
㞟㸪II-98, 2019 (CD- ROM).
ᅗ7ࡢධᑕỏ℃Ỉ῝hi࡜ධᑕỏ℃ὶ㏿uiࢆ⌮ㄽⓗ࡟Ỵࡵ 8) Matsutomi, H. and Konno, F.: Experiments on the density of tsunami inundationࡓሙྜ࡟ẚ࡭࡚ࡶࡸࡸ▷ࡃ㸪⣙8%ῶ࡜࡞ࡿࡇ࡜ࡀุࡿࠋ water and its influence on the tsunami run-up and deposit, Proc. of Intl. Conf. onࡋࡓࡀࡗ࡚㸪ố⥺࡟࠾ࡅࡿỏ℃Ỉᐦᗘࡸᦶ᧿ᦆኻಀᩘࢆCoastal Eng., No.36, Full Length papers: Paper.41, 2019.
⏝࠸ࡿሙྜࡣ㸪⌮ㄽII࡟㛵ࡋ࡚ࡣhi࡜uiࢆᐇ㦂ⓗ࡟Ỵࡵࡿ 9) ᯇ෠ⱥኵ㸪Ỵᚓඖᇶ㸪㰻⸨㞞኱㸸㛤ཱྀ㒊ࢆ᭷ࡍࡿ㕲➽ࢥࣥࢡ࣮ࣜࢺ㐀ᘓ≀࡟ാࡃὠἼὶయຊ࡟㛵ࡍࡿᇶ♏ᐇ㦂㸪ᅵᮌ᪉ࡀ㸪⌮ㄽIII࡟㛵ࡋ࡚ࡣ⌮ㄽⓗ࡟Ỵࡵࡿ᪉ࡀࡼ࠸࡜ゝ࠼Ꮫ఍ㄽᩥ㞟B2㸦ᾏᓊᕤᏛ 㸪Vol. 69, No. 2, pp.326-330, 2013.
ࡿࠋࡲࡓ㸪⌮ㄽIIࡢሙྜࡣ㸪ྠࡌධᑕẁἼ㧗h1࡛ࡶhi࡜ui10) ᯇ෠ⱥኵ㸪ᑠἨᣅஓ㸪↷஭⿱௓㸪ຍ⸨ᗈஅ㸪ᒾ℩ᾈஅ㸸ᐃࡢh1࡬ࡢ㈉⊩ᗘḟ➨࡛㸪ố⥺࡟࠾ࡅࡿỏ℃Ỉᐦᗘࢆ⏝࠸ᖖ࡜㠀ᐃᖖᐇ㦂ࡢ㐪࠸ࡀ⬚ቨ㉺ὶᚋࡢὠἼࡢỏ℃ὶࡸRC㐀࡚ࡶᐇ㦂࡜ࡢᑐᛂࡀࡼ࠸ሙྜࡀ࠶ࡿࡇ࡜ࢆ♧ࡋ࡚࠸ࡿࠋ
ᘓ⠏≀࡬ࡢἼຊ࡟ཬࡰࡍᙳ㡪㸪ᅵᮌᏛ఍ㄽᩥ㞟B1㸦ỈᕤᏛ 㸪Vol.74, No.5, pp.1225-1230, 2018.
 ௨ୖࡢ᳨ウ⤖ᯝ࠿ࡽ⥲ྜⓗ࡟ุ᩿ࡋ࡚㸪⌧≧࡛ࡣ㸪⌮
ㄽIIࡸ⌮ㄽIIIࡢά⏝࡟࠾࠸࡚ࡣ㐳ୖ㐣⛬ᖹᆒࡢỏ℃Ỉᐦ 11) ᯇ෠ⱥኵ㸪ᒸ⏣㞙ே㸪ஂಖ⏣཭ᐶ㸪௒㔝ྐᏊ㸸RC㐀ᘓ⠏≀࡟స⏝ࡍࡿὠἼⲴ㔜ࡢỏ℃Ỉᐦᗘ࡬ࡢ౫Ꮡ࡟㛵ࡍࡿᇶ♏ᐇᗘࡸᦶ᧿ᦆኻಀᩘࢆ⏝࠸ࡿࡇ࡜ࡀ᥎ዡࡉࢀࡿࠋᦶ᧿ᦆኻ
㦂㸪ᅵᮌᏛ఍ㄽᩥ㞟B2㸦ᾏᓊᕤᏛ 㸪Vol.74, No.2, pp.265-270,ಀᩘ࡟ᑐࡍࡿࡇࡢ⪃࠼᪉ࡣᇶᮏⓗ࡟ࡇࢀࡲ࡛ࡢὠἼ㐳ୖ
2018.
ᩘ್ゎᯒ࡟࠾ࡅࡿࡶࡢ࡜ྠࡌ࡜ゝ࠼ࡿࠋ12) ᯇ෠ⱥኵ㸪୕ୖ㍤㸪༓ⴥ⿱ኴ㸸ỏ℃Ỉᐦᗘ࡜Ἴ࿘ᮇࡢὠἼ
Ⲵ㔜࡬ࡢᙳ㡪㸪ᅵᮌᏛ఍ㄽᩥ㞟B2㸦ᾏᓊᕤᏛ 㸪Vol.75, No.2,
pp.397-402, 2019.
 ࠾ࢃࡾ࡟
13) ᮌ℩᫭࿘㸪᭷ᕝኴ㑻㸸ᅵ◁࣭ࢩࣝࢺࢆྵࢇࡔὠἼࡢἼຊ࡟ ᮏ◊✲࡛ᚓࡽࢀࡓ୺࡞⤖ᯝࡣḟࡢ㏻ࡾ࡛࠶ࡿࠋ
㛵ࡍࡿᐇ㦂ⓗ◊✲㸪ᅵᮌᏛ఍ㄽᩥ㞟B2㸦ᾏᓊᕤᏛ 㸪Vol.76,
1) ᪤ሗࡢὠἼ㐳ୖ࡟㛵ࡍࡿ⌮ㄽI 3)㸪⌮ㄽII 14)㸪⌮ㄽIII 14)࡬No. 2, pp.385-390, 2020.
ᯇ෠ࡢ⛣ືᗋୗࡢỏ℃ὶ᢬ᢠ๎ࢆ㐺⏝ࡋ㸪ྛ⌮ㄽ࡜ỏ℃14) ᯇ෠ⱥኵ㸪᭷ᕝኴ㑻㸸ὠἼ㐳ୖ࡬ࡢỏ℃Ỉᐦᗘࡢᙳ㡪㸪ᅵὶ᢬ᢠ๎ࡢ㐺⏝ᛶࢆᐇ㦂࡜ࡢẚ㍑ࡸ⌮ㄽ┦஫ࡢẚ㍑ࢆ㏻ᮌᏛ఍ㄽᩥ㞟B2㸦ᾏᓊᕤᏛ 㸪Vol.76, No.2, pp.391-396, 2020.
ࡋ᳨࡚ウࡋࡓࠋ3⌮ㄽࡢ୰࡛᭱ࡶᬑ㐢ᛶࡀ㧗࠸࡜⪃࠼ࡽ 15) ᅵᮌᏛ఍Ỉ⌮ጤဨ఍⛣ືᗋὶࢀࡢ᢬ᢠ࡜Ἑᗋᙧ≧◊✲ᑠጤဨ఍㸸⛣ືᗋὶࢀ࡟࠾ࡅࡿἙᗋᙧែ࡜⢒ᗘ㸪ᅵᮌᏛ఍ㄽᩥ
ࢀࡿ⌮ㄽIࡀᐇ㦂ࡢ㐳ୖ㊥㞳LRࢆࡼࡃㄝ࡛᫂ࡁࡿࡇ࡜㸪ሗ࿌㞟㸪➨210ྕ㸪pp.65-91, 1973.
⛣ືᗋୗࡢỏ℃ὶ᢬ᢠ๎ࡀጇᙜ࡛࠶ࡿࡇ࡜ࢆ☜ㄆࡋࡓࠋ2) ᦶ᧿ᦆኻಀᩘKࡸỏ℃Ỉᐦᗘρࡢố⥺x=0㸦ึᮇt=0㸧࡟ 16) ⏣୰ோ㸪Nguyen Xuan Tinh㸪Ᏽᩥୡ㸸ὠἼࡢୗ࡛ࡢᗏ㠃ቃ⏺
ᒙⓎ㐩࡜ᗏ㠃ࡏࢇ᩿ຊࡢ≉ᛶ㸪ᅵᮌᏛ఍ㄽᩥ㞟B2㸦ᾏᓊᕤ࠾ࡅࡿホ౯್ࡣ㸪ố⥺࡟࠾ࡅࡿධᑕỏ℃Ỉ῝hi࡜ධᑕỏᏛ 㸪Vol.74, No.2, pp.313-318, 2018.
℃ὶ㏿uiࡢᐇ㦂್ࢆಶู࡟㝧࡟ά⏝ࡍࡿሙྜࡢ⌮ㄽIIࢆ 17) ἅ⃝ భᶞ㸪Nguyen Xuan Tinh㸪Ώ㎶ ୍ஓ㸪⏣୰ ோ㸸஘ὶࣔࢹ㝖࠸࡚㸪㐳ୖ㐣⛬඲యࢆ⾲⌧ࡋᚓࡿࡶࡢ࡛ࡣ࡞࠸ࡇ࡜ࢆ
ࣝࢆ⏝࠸ࡓὠἼఏ᧛ࡢᩘ್ィ⟬㸪ᅵᮌᏛ఍ㄽᩥ㞟B2㸦ᾏᓊᕤᏛ 㸪Vol.74, No. 2, pp.163-168, 2018.
☜ㄆࡋࡓࠋ୍ᐃ್ࡢKࡸρ࡛㐳ୖ㐣⛬඲యࢆࡼࡾⓗ☜࡟⾲⌧ࡋࡼ࠺࡜ࡍࡿ࡞ࡽࡤ㸪⌧≧࡛ࡣ㐳ୖ㐣⛬ᖹᆒࡢ್ࢆ 18) ᯇ෠ⱥኵ㸸ỏ℃ὶ᢬ᢠ๎ᐇ㦂ᘧࡢ↷ᰝ㸪ᅵᮌᏛ఍ᮾ໭ᨭ㒊ᢏ⾡◊✲Ⓨ⾲఍ㅮ₇ᴫせ㞟㸪2022.㸦༳ๅ୰㸧⏝࠸ࡿࡇ࡜ࡀ᥎ዡࡉࢀࡿࡇ࡜ࢆ♧ࡋࡓࠋࡇࢀࡣ⛣ືᗋୗ19) ౛࠼ࡤ㸪⏣୰ோ㸪㤳⸨ఙኵ㸸୍᪉ྥὶࢆక࠺᣺ືὶ࡟㛵ࡍࡢỏ℃ὶ᢬ᢠ๎࡟㝈ࡿࡶࡢ࡛࡞࠸࡜ᛮࢃࢀࡿࠋ
ࡿᐇ㦂㸪➨29ᅇᾏᓊᕤᏛㅮ₇఍ㄽᩥ㞟㸪pp.259-263, 1982.
ㅰ㎡㸸ᮏ◊✲࡟࠶ࡓࡾ⛉◊㈝㸦ᇶ┙◊✲ C 㸪20K05041㸪20) ౛࠼ࡤ㸪ᯇ෠ⱥኵ㸸Ỉᖹᗋࡢ㈓Ỉ㒊ࢆᣢࡘࢲ࣒◚ቯὶࢀࡢ௦⾲㸸ᯇ෠ⱥኵ㸧ࡢ⿵ຓࢆཷࡅࡓࠋグࡋ࡚ㅰពࢆ⾲ࡍࡿࠋ ᩳ㠃㐳ୖ㸪ᮾ໭ᆅᇦ⅏ᐖ⛉Ꮫ◊✲㸪➨57ᕳ㸪pp.47-52, 2021.
Kx 0

0.00255 Fri

1

hi
d 50

0.00255Fri

11
h1
1 2 d 50
1
Fri
2

東北地域災害科学研究63

第58巻（2022）

ຍ㏿ᗘࢭࣥࢧࢆ⏝࠸ࡓ⁻ὶ≀ࡢᣲື࡟㛵ࡍࡿᐇ㦂㸨⛅⏣኱Ꮫ⌮ᕤᏛ㒊      ᮃ᭶Ⰻ⣧⛅⏣኱Ꮫ኱Ꮫ㝔⌮ᕤᏛ◊✲⛉ 㰻⸨᠇ᑑ⛅⏣኱Ꮫ኱Ꮫ㝔⌮ᕤᏛ◊✲⛉ Ώ㎶୍ஓ
1. ࡣࡌࡵ࡟
 2011 ᖺࡢᮾ᪥ᮏ኱㟈⅏࡟ࡼࡾ㸪ᚑ᮶ࡢ᝿ᐃࢆࡣࡿ࠿࡟㉸࠼ࡿつᶍࡢὠἼࢆཷࡅቯ⁛ⓗ࡞⿕ᐖࢆཷࡅࡓ¹⁾ࠋὠἼⓎ⏕᫬࡟࠾࠸࡚㸪ᾋయᘧὠἼ㑊㞴ࢩ࢙ࣝࢱ࣮࡞࡝ࡢ⁻ὶ≀ࢆ⏝࠸ࡓ㑊㞴᪉ἲࡀ᭷ຠ
࡛࠶ࡿࡇ࡜ࡀ♧ࡉࢀ࡚࠾ࡾ 2)3)㸪ᾋయᘧὠἼ㑊㞴ࢩ࢙ࣝࢱ࣮ࡢᏳ඲ᛶࡢ᳨ウࢆ⾜࠺ࡓࡵ㸪⁻ὶ≀ࡢᶍᆺࢆ⏝࠸ࡓᐇ㦂ࡀ⾜ࢃࢀ࡚࠸ࡿࠋࢩ࢙ࣝࢱ࣮ᶍᆺࢆᅛᐃࡋࡓ≧ែ࡛Ἴຊࢆィ ࡋࡓᐇ㦂 4)ࡸ㸪⁻ὶ≀࡟ᅽຊࢭࣥࢧࢆྲྀࡾ௜ࡅ࡚⛣ືྍ⬟࡞≧ែ࡛Ἴᅽࡢィ ࢆࡋࡓᐇ㦂 5)ࡀ⾜ࢃࢀ࡚ࡁࡓࡀ㸪ᅛᐃࡋࡓ≧ែ࡜ࡣ␗࡞ࡾ㸪⁻ὶ≀ࡢືᦂ࡟క࠺ഴᩳ࡟ࡼࡗ࡚Ỉ㠃࡜ᅽຊࢭࣥࢧ࡜ࡢ㊥㞳ࡀኚ໬ࡋ㸪ṇ☜࡟Ἴᅽࢆ ᐃࡍࡿ஦ࡣฟ᮶࡞࠿ࡗࡓࠋ
ࡑࡇ࡛ᮏ◊✲ࡣ㸪⁻ὶ≀ࡢഴᩳ࡟ࡼࡿἼᅽࡢኚ໬ࢆ⿵ṇࡍࡿࡓࡵ㸪ຍ㏿ᗘࢭࣥࢧࢆ⏝࠸ࡿࡇ࡜࡛
⁻ὶ≀ࡢゅᗘࢆ ᐃࡋ㸪ᐇ㝿࡟Ἴᅽࡢ⿵ṇࢆ⾜ࡗࡓࠋ2. ᐇ㦂ᴫせ(1)ᅽຊࢭࣥࢧ࠾ࡼࡧຍ㏿ᗘࢭࣥࢧ ᅽຊࢭࣥࢧࡣᅗ ࡟♧ࡍMeasurement Specialties 〇ࡢ MS5837-02BA
ࣔࢹࣝ㸪ຍ㏿ᗘࢭࣥࢧࡣᅗ ࡟♧ࡍInven Sense 〇ࡢ MPU-6050 ࣔࢹࣝࢆ౑⏝ࡋࡓࠋᅽຊࢭࣥࢧࡣ㜵Ỉᶵ⬟ࢆ᭷ࡋ࡚࠾ࡾ㸪ᐃ᱁ᐜ㔞 1,000㹼
200,000 Pa㸪ᑍἲ 3.3×3.3×2.75 mm ࡛࠶ࡿࠋࡲࡓ㸪ຍ㏿ᗘࢭࣥࢧࡣᐃ᱁
ᐜ㔞±2 g㸪ᑍἲ 4.0×4.0×0.9 mm ࡛࠶ࡿࠋ
ྛࢭࣥࢧࡣ 8 ࣅࢵࢺ࣐࢖ࢥ࣮ࣥ࣎ࢻ࡜ Processing/Wiring ゝㄒࢆᐇ⿦ᅗᅽຊࢭࣥࢧ

ࡋࡓ⤫ྜ㛤Ⓨ⎔ቃ࠿ࡽᵓᡂࡉࢀࡿࢩࢫࢸ࣒࡛࠶ࡿ Arduino ࡬᥋⥆ࡋࡓࠋ
࡞࠾㸪Arduino ࡣ࣮࢜ࣉࣥࢯ࣮ࢫࣁ࣮ࢻ࢙࢘࢔࡛࠶ࡿࡇ࡜࠿ࡽᢏ⾡ࣁ࣮ࢻࣝࡀపࡃ㸪ࢥࣥࣃࢡࢺ࡞ ᐃࢆྍ⬟࡜ࡋ࡚࠸ࡿࠋ
(2)⁻ὶ≀ᶍᆺ⁻ὶ≀ᶍᆺࡣὠἼ㑊㞴ࢩ࢙ࣝࢱ࣮ࠕsafe+ࠖ6)ࢆཧ⪃࡟㸪୍⯡ⓗ࡞⁻ὶ≀ࢆ⾲ࡍࡶࡢ࡜ࡋ࡚ 3D ࣉࣜࣥࢱ࣮࡛సࡽࢀࡓ┤᪉యࡢᾋయࢆ᥇⏝ࡋࡓࠋᶍᆺࡣᖜ 29.0 cm㸪㧗ࡉ 15.0 cm㸪㛗ࡉ 15.0 cm㸪㉁㔞 1,000 g ࡛࠶ࡾ㸪ᶍᆺෆ㒊࡟ࡣ㗽ࢆ 1,051 g ධࢀࡓࠋࡲࡓ㸪ᶍᆺࡢႚỈࡣᶍᆺᗏ㠃࠿㸨ᅗຍ㏿ᗘࢭࣥࢧ

Experimental of the Behavior of Drifting Objects using an Acceleration Sensor by Yoshizumi MOCHIZUKI㸪
Noritoshi SAITO and Kazuya WATANABE

64ᅗ ࢭࣥࢧࡢタ⨨఩⨨ࡢヲ⣽ᅗ⁻ὶ≀ᶍᆺᅗᐇ㦂Ỉ㊰
ࡽ 5 cm ࡛࠶ࡾ㸪ᅽຊࢭࣥࢧࡣᶍᆺᗏ㠃࠿ࡽ 2.5 cm ࡢ㧗ࡉ࡟タ⨨ࡋ㸪ຍ㏿ᗘࢭࣥࢧࡣ⁻ὶ≀ෆ㒊࡟タ⨨ࡋࡓࠋ⁻ὶ≀ᶍᆺࢆᅗ̾㸪ᅽຊࢭࣥࢧ࠾ࡼࡧຍ㏿ᗘࢭࣥࢧࡢ㓄⨨ࢆᅗ ࡟♧ࡍࠋ(3) ᐇ㦂Ỉ㊰Ỉ㊰ࡢᴫ␎ࢆᅗ ࡟♧ࡍࠋᖜ 0.30 m㸪㧗ࡉ 0.50 m㸪඲㛗 11.0 m ࡢ࠺ࡕ㸪ᾏഃࡢ㈓Ỉᵴࡀ 5.0 m㸪
㝣ഃ࡟ᩳ㠃໙㓄 1/26 ࡢᩳ㠃ࡀ࠶ࡿ㗰〇▴ᙧỈ㊰ࢆ౑⏝ࡋࡓࠋᮏ◊✲ࡣὠἼࡢ➨஧Ἴ┠௨㝆ࢆᑐ㇟࡜ࡋ࡚㸪ᾐỈ῝ hs=0.15 m㸪㈓Ỉ῝ h=0.3 m ࡜ࡋࡓࠋ
ᐇ㦂ᡭ㡰ࡣ㸪Ỉ㊰ࡢᾏഃ࡟࠶ࡿ㈓Ỉᵴ࡟Ỉࢆ㈓ࡵ㸪ᐇ㦂Ỉ㊰ࡢࢤ࣮ࢺࢆᛴ㛤ࡍࡿࡇ࡜࡟ࡼࡾᶍᨃ
ẁἼࢆⓎ⏕ࡉࡏࡓࠋẁἼࡣ୍ᵝỈ῝㒊㸪୍ᵝ໙㓄ᩳ㠃㒊ࢆఏ᧛ࡋࡓᚋ㸪⁻ὶ≀ᶍᆺ࡟⾪✺ࡍࡿࠋᮏ◊✲࡛ࡣᶍᆺᖜ࡜Ỉ㊰ࡢ㝽㛫ࢆ 1 cm ࡜ࡍࡿࡇ࡜࡛ᶍᆺࡢᅇ㌿㐠ືࢆᢚไࡋ㸪Ỉᖹ⛣ືࡢࡳホ౯ࡋࡓࠋࡲࡓ㸪ᶍᆺୖ㒊ࡢࢣ࣮ࣈࣝࡀỈᖹ⛣ື࡟ᙳ㡪ࡋ࡞࠸ࡼ࠺࡟ࢣ࣮ࣈࣝ㛗ࢆ 1 m ࡜ࡋࡓࠋᶍᆺࡢ
8 cm ๓᪉࡟㉸㡢ἼᘧỈ఩ィࢆタ⨨ࡋ㸪ὠἼࡢỈ఩ࡣ 0.01 s ẖ࡟ ᐃࡋ㸪⁻ὶ≀ᶍᆺ࡟ྲྀࡾ௜ࡅࡓ

65

ᅗゅᗘ࡜Ỉᅽࡢ㛵ಀᅗ ႚỈ࡜Ỉᅽࡢ㛵ಀᅽຊࢭࣥࢧࢆ⏝࠸࡚ὠἼࡢἼᅽࢆ ᐃ㸪ഴᩳࢆຍ㏿ᗘࢭࣥࢧ࡛ ᐃࡋࡓࠋ࡞࠾㸪Ἴᅽ࡜ഴᩳࡣ 0.05
s ẖ࡟ ᐃࡋ࡚࠸ࡿࠋὠἼ࡜ᶍᆺࡢᣲືࢆほᐹࡍࡿࡓࡵ࡟Ỉ㊰ഃ㠃࠿ࡽࣅࢹ࢜᧜ᙳࢆ⾜ࡗ࡚࠸ࡿࠋ
࡞࠾㸪ᾐỈ῝ࡣṆỈᯈࢆỈ㊰ୗ➃࡟タ⨨ࡍࡿࡇ࡜࡛⾲⌧ࡋ࡚࠸ࡿࠋ ᐇ㦂⤖ᯝ
3.
(1) ഴᩳ࡜Ỉᅽࡢ㛵ಀ⁻ὶ≀ࢆỈ࡟ᾋ࠿࡭㸪ຍ㏿ᗘࢆຍ࠼ࡎᕥྑ࡟ഴࡅࡓ⤖ᯝ࡜ࡋ࡚㸪ゅᗘ࡜Ỉᅽࡢ㛵ಀࢆᅗ ࡟♧
ࡍࠋゅᗘࡀ኱ࡁࡃ࡞ࡿ࡯࡝Ỉᅽࡀ኱ࡁࡃ࡞ࡿഴྥ࡛࠶ࡿࡀ㸪-20°㸦㝣ഃ࡟ 20°㸧ࡼࡾഴࡃ࡜ᅽຊࢭ
ࣥࢧࡀỈ㠃࠿ࡽ㟢ฟࡍࡿࡓࡵ㸪Ỉᅽࡀ୍ᐃ࡜࡞ࡗࡓࠋࡑࡇ࡛Ỉୖ࠿ࡽฟ࡚࠸ࡿ㒊ศࡢ-20°௨ୗࡢࢹ࣮ࢱࢆ┬ࡁ㸪3 ᅇศࡢᐇ㦂ࡢࢹ࣮ࢱࢆ⏝࠸࡚㏆ఝᘧࢆồࡵࡓࠋ(2)ႚỈ࡜Ỉᅽࡢ㛵ಀὠἼ࡟ࡼࡗ࡚ືᦂࡋ࡚࠸ࡿ⁻ὶ≀ࡢἼᅽࢆṇ☜࡟ᐃࡍࡿࡓࡵ࡟ࡣ㸪ഴᩳ࡟ࡼࡿἼᅽࡢ⿵ṇࡔࡅ࡛ࡣ࡞ࡃ㸪ႚỈࡢኚ໬࡟ࡘ࠸࡚ࡶ⪃៖ࡍࡿᚲせ࡛࠶ࡿࠋࡑࡇ࡛⁻ὶ≀ࢆ 1 cm ẖ࡟ᾋࡁỿࡳࡉࡏ㸪Ỉᅽࢆ ᐃࡋࡓࠋႚỈ࡜Ỉᅽࡢ㛵ಀࢆ♧ࡍᅗ ࢆぢࡿ࡜㸪ႚỈࡀ 1 cm ⛬ᗘኚ໬ࡍࡿ࡜Ỉᅽࡀ 100
Pa ⛬ᗘኚ໬ࡋ࡚࠾ࡾ㸪ࡇࢀࡣ㟼Ỉᅽࢆィ⟬࡛ồࡵࡿሙྜ࡜୍⮴ࡋ࡚࠸ࡓࠋ
(3)⁻ὶ≀ᶍᆺࢆ⏝࠸ࡓὠἼࡢ⾪✺ᐇ㦂ࡢ⤖ᯝ Ỉ఩㸪⁻ὶ≀ࡢἼᅽ࠾ࡼࡧゅᗘࡢ⤒᫬ኚ໬ࢆᅗ㸪Ỉ㊰ࡢഃ㠃࠿ࡽࣅࢹ࢜᧜ᙳࡋࡓἼᙧࡢኚ໬ࢆᅗ ࡟♧ࡍࠋỈ఩ࡣὠἼ⾪✺┤ᚋୖ᪼ࡋࡓᚋ㸪⦆ࡸ࠿࡟ୖୗࡋ࡞ࡀࡽ୍ᐃ࡜࡞ࡗ࡚࠸ࡿࠋ⾪✺࠿ࡽ⣙ 1.3s ᚋࡢỈ఩ࡢୖ᪼ࡣ㸪ࢤ࣮ࢺᛴ㛤᫬࡟Ⓨ⏕ࡋࡓ 2 ࡘ┠ࡢẁἼࡀཎᅉ࡛࠶ࡿ࡜⪃࠼ࡽࢀࡿࠋ Ἴᅽࡢ⤒᫬ኚ໬ࢆぢࡿ࡜㸪Ἴᅽࡣ⾪✺┤ᚋୖ᪼ࡋ㸪࣐࢖ࢼࢫࡢ್ࡀ ᐃࡉࢀࡓࠋࡑࡢᚋ෌ࡧἼᅽ
ࡣୖ᪼ࡋࣉࣛࢫࡢ್࡛ୖୗࢆ⧞ࡾ㏉ࡋࡓࠋἼᅽࡀ࣐࢖ࢼࢫ࡛࠶ࡿ⌮⏤࡜ࡋ࡚㸪⁻ὶ≀ࡀ㝣ഃ࡬ഴࡃ஦࡟ࡼࡗ࡚ᅽຊࢭࣥࢧ࡜Ỉ㠃ࡢ㊥㞳ࡀ▷ࡃ࡞ࡿࡇ࡜ࡀせᅉ࡜⪃࠼ࡽࢀࡿࠋ୍᪉㸪ᾏഃ࡟ഴࡃࡇ࡜࡟
ࡼࡗ࡚Ἴᅽࡀ኱ࡁࡃ ᐃࡉࢀࡓࠋ
ゅᗘࡢ⤒᫬ኚ໬ࢆぢࡿ࡜㸪⁻ὶ≀ࡣ⾪✺ᚋ 0.6 s ࠿ࡅ࡚㝣ഃ࡟ 9°⛬ᗘഴࡁ㸪ࡑࡢᚋ 0.4 s ࠿ࡅ࡚

66ᅗ Ỉ఩㸪Ἴᅽ㸪ゅᗘࡢ⤒᫬ኚ໬ᅗ Ỉ఩ࡢ⤒᫬ኚ໬ࡢ෗┿ᅗ
ᾏഃ࡟ 13°⛬ᗘࡲ࡛ഴ࠸࡚࠸ࡓࠋࡉࡽ࡟㸪ࢢࣛࣇࡢᒣ࡜㇂ࡢィ᫬㛫࡟ࡘ࠸࡚Ἴᅽ࡜ゅᗘࡢ⤒᫬ኚ໬ࢆẚ㍑ࡍࡿ࡜㸪ഴྥࡣᴫࡡ୍⮴ࡋ࡚࠾ࡾ㸪ࡇࢀࡣᅗ ࡢ⁻ὶ≀ࡢ⏬ീ࠿ࡽࡶ☜ㄆ࡛ࡁࡿࠋࡋ࠿ࡋ㸪
Ἴᅽ࡜ゅᗘࡢࣆ࣮ࢡࡢ ᐃ᫬㛫࡟ࡎࢀࡀ⏕ࡌ࡚࠸ࡿࠋࡇࢀࡣ⁻ὶ≀ࡢୖୗ㐠ື࡟ࡼࡿႚỈࡢኚ໬ࡀᙳ㡪ࡋ࡚࠸ࡿࡢ࡛ࡣ࡞࠸࠿࡜⪃࠼ࡽࢀࡿࠋ
(4)ഴᩳ࡟ࡼࡿἼᅽࡢ⿵ṇ⤖ᯝ ⿵ṇ࡟ࡘ࠸࡚ࡢㄝ᫂ࢆᅗ ࡟♧ࡍࠋὠἼ⾪✺ᐇ㦂࡟࠾࠸࡚㸪Ἴᅽ࡜ྠ᫬࡟ゅᗘࡶィࢆ⾜࠸㸪ᅗ ⁻ὶ≀ᶍᆺࡢᣲື

67ᅗゅᗘࡢ⿵ṇ࢖࣓࣮ࢪ

ᅗゅᗘ⿵ṇᚋࡢἼᅽࡢ⤒᫬ኚ໬ᅗ ႚỈࡢኚ໬(2.6s)

ᅗ \ ㍈ຍ㏿ᗘࡢ⤒᫬ኚ໬ࡇࡢ㏆ఝᘧ࡟ゅᗘࢆ௦ධࡋ㸪 ᐃࡉࢀࡓἼᅽ࠿ࡽ㏆ఝᘧ࡛ồࡵࡓἼᅽࢆᘬࡃࡇ࡜࡛⿵ṇࢆ⾜࠺ࠋ⿵ṇࢆ⾜࠺࡜ ᐃ್ࡣ㸪⁻ὶ≀ࡀ㝣ഃ࡟ഴࡃ࡜Ἴᅽࢆቑຍࡉࡏ㸪ᾏഃ࡟ഴࡃ࡜Ἴᅽࢆῶᑡࡉࡏࡿࠋ
ഴᩳ࡟ࡼࡿἼᅽࡢ⿵ṇࢆᅗ ࡟♧ࡍࠋ⾪✺┤ᚋࡢἼᅽࢆぢࡿ࡜㝣ഃ࡟ഴ࠸࡚࠸ࡿࡓࡵ㸪ഴࡁࡀ᭱኱࡜࡞ࡿ 2.6 s ࡲ࡛Ἴᅽࡣ᭱኱ 90 Pa ⛬ᗘࣉࣛࢫഃ࡟⿵ṇࡉࢀࡓࠋࡑࡋ࡚⁻ὶࡋ࡚࠸ࡿ≧ἣࢆぢࡿ࡜㸪ഴࡁࡀ 0°࡜࡞ࡿ 2.7 s ࠿ࡽᾏഃ࡬ࡢഴࡁ࡜࡞ࡿࡓࡵ㸪Ἴᅽࡣ࣐࢖ࢼࢫࡢ⿵ṇ࡜࡞ࡿࠋᾏഃ࡟
ഴࡃሙྜࡣ᭱኱࡛-150 Pa ⛬ᗘࡲ࡛⿵ṇࡉࢀࡿഴྥ࡟࠶ࡗࡓࠋḟ࡟⿵ṇࡢ๓ᚋࢆẚ㍑ࡍࡿ࡜㸪㝣ഃࡢഴࡁࡀ᭱኱࡜࡞ࡿ 2.5 s ࡲ࡛Ἴᅽࡀࣉࣛࢫࡢ್ࢆ♧ࡋ࡚࠸ࡓࡀ㸪Ἴᅽࡣ 2.6 s ௨㝆ࡶῶᑡࡋ⥆ࡅ
2.65 s ࡢ᫬㸪࣐࢖ࢼࢫࡢࣆ࣮ࢡࢆ㏄࠼࡚࠸ࡓࠋ
(5)ႚỈ࡟ࡼࡿἼᅽ
ႚỈࡢኚ໬࡟ࡘ࠸࡚ᅗ ࡟ 2.6 s ࡢႚỈ࡟ὀ┠ࡋࡓ⏬ീࢆ♧ࡍࠋࡇࡢ᫬㛫࡛ࡣ㸪1 cm ⛬ᗘࡢႚỈࡢኚ໬ࡀぢࡽࢀࡓࠋࡇࢀࡣ⁻ὶ≀ࡢୗ᪉࡟ࡶࡄࡾࡇࢇࡔἼࡀ⁻ὶ≀ࢆᢲࡋୖࡆࡓࡇ࡜࡟ࡼࡿႚ
Ỉࡢపୗࡀཎᅉ࡛࠶ࡿ࡜⪃࠼ࡿࠋᅗ ࡢ \ ㍈ࡢຍ㏿ᗘࡢ⤒᫬ኚ໬࠿ࡽࡶ㸪2.6 s ๓ᚋ࡛ \ ㍈ṇ᪉ྥ࡟㐠ືࡋ࡚࠸ࡿࡇ࡜ࡀࢃ࠿ࡿࠋࡇࡢ y ㍈ࡢຍ㏿ᗘࡢᛴୖ᪼ࡣ㸪⁻ὶ≀ࡢᅇ㌿࡜ୖ᪉ྥ࡬ࡢ⛣ືࡀᙳ㡪ࡋ࡚࠸ࡿࠋ
⁻ὶ≀ࡀഴ࠸࡚࠸࡞࠸≧ែ࡛࠶ࡿࡓࡵ㸪ഴᩳ࡟ࡼࡿᙳ㡪࡛ࡣ࡞࠸ࡇ࡜ࡀ☜ㄆ࡛ࡁ㸪ᅗ ࡢ 2.6 s
ࡢ᫬-100 Pa ࡣႚỈࡀᙳ㡪ࡋ࡚࠸ࡿࡶࡢ࡛࠶ࡿ࡜⪃࠼ࡿࠋႚỈࡢ⿵ṇ࡟ࡘ࠸࡚ㄝ᫂ࢆᅗ ࡟♧ࡍࠋ⿵ṇࢆ⾜࠺࡜ႚỈࡀపୗࡋࡓ᫬Ἴᅽࡀቑຍࡋ㸪ୖ᪼ࡋ

68ᅗ ႚỈࡢ⿵ṇ࢖࣓࣮ࢪ

ᅗ ٦ਭึਜ਼‫ޛ‬͹ഀѻ͹‫࣎ܨ‬รԿࡓ᫬ἼᅽࡣῶᑡࡍࡿࠋὠἼ⾪✺ᐇ㦂࡟࠾࠸࡚᧜ᙳࡋࡓື⏬ࢆ☜ㄆࡋ㸪ႚỈࡢኚ໬ࢆ┠ど࡛࡜ࡽ࠼㸪ᐃࡋࡓ್ࢆ㟼Ỉᅽࡢᘧ࡟௦ධࡍࡿࡇ࡜࡛⿵ṇࢆ⾜ࡗࡓࠋႚỈࡢኚ໬ࢆ⪃៖ࡋࡓἼᅽࡢ⤒᫬ኚ໬ࢆᅗ ࡟♧ࡍࠋႚỈࡣ㸪ὠἼ⾪✺ᚋࢃࡎ࠿࡟ୖ᪼ࡋ㸪ẁἼࡀࡶࡄࡾࡇࡴ㝿పୗࡍࡿࠋࡑࡢࡓࡵ㸪⿵ṇ๓ࡢἼᅽ࡜⿵ṇᚋࡢἼᅽࢆẚ㍑ࡍࡿ࡜㸪⾪✺┤ᚋࡣῶᑡࡀࡳࡽࢀࡿࡀ㸪ࣆ࣮ࢡࡢᐃ್ࡣቑຍࡋ㸪࣐࢖ࢼࢫࡢ ᐃࡀ⾜ࢃࢀ࡚࠸ࡓἼᅽࡀࣉࣛࢫࡢ ᐃ್࡜࡞ࡗࡓࠋ

4. ࠾ࢃࡾ࡟
ᮏ◊✲࡟ࡼࡾ௨ୗࡢࡇ࡜ࡀ᫂ࡽ࠿࡜࡞ࡗࡓࠋ
࣭⁻ὶ≀ᶍᆺࡣὠἼ⾪✺᫬࡟㝣ഃ࡬⣙ 10°ഴᩳࡋ㸪ࡑࡢᚋࡣ⣙ 15°ᾏഃ࡬ഴᩳࡋ࡚࠸ࡓࠋ
࣭Ἴ࡟ࡼࡗ࡚ືᦂࡍࡿ⁻ὶ≀࡟స⏝ࡍࡿᅽຊࡣ㸪ഴᩳ࡟ࡼࡿኚ໬ࡢ௚࡟㸪ႚỈࡢቑῶ࡛ࡶኚ໬ࡍࡿࠋ
࣭⁻ὶ≀ᶍᆺࡢഴᩳ࠾ࡼࡧႚỈࡢኚ໬ࢆ⪃៖ࡏࡎἼᅽࢆ࡟ホ౯ࡋ࡚࠸ࡓ㸬ᐃࡋࡓሙྜ㸪⾪✺┤ᚋࡣ㐣ᑠ㸪⁻ὶ୰ࡣ㐣኱௒ᚋࡢᒎᮃ࡟ࡘ࠸࡚㸪㈓Ỉ῝࡜ᾐỈ῝ࡢ᮲௳ࢆኚ᭦ࡋ㸪Ἴᅽࡢ⿵ṇࢆ⾜࠺ࡇ࡜ࡸ㸪ႚỈࡢኚ໬࡟ᑐࡍࡿ᳨ウࢆ῝ࡵࡿࡓࡵ࡟㸪ୖୗ᪉ྥࡢຍ㏿ᗘࡢ᳨ウࢆ⾜࠺ணᐃ࡛࠶ࡿࠋཧ⪃ᩥ⊩1) ෆ㛶ᗓ࣭ᮾ᪥ᮏ኱㟈⅏࡟ࡼࡿὒୖ⁻ὶ≀ Q&A(https://www8.cao.go.jp/ocean/policies/hyouryuu/q_and_a.html)㸦2021-12-9 ࢔ࢡࢭࢫ㸧2) 㔜ᯇᏕᫀ, ᫂▱㢧୕, ᑠụᩄஓ㸸ᾋయᘧὠἼ㑊㞴ࢩ࢙ࣝࢱ࣮࡟㛵ࡍࡿᇶ♏ⓗᐇ㦂, ᾏὒ㛤Ⓨㄽᩥ㞟, ➨ 24 ᕳ, pp. 105_ 110, 2008.
3) 㔜ᯇᏕᫀ㸪୰ᮾ኱㍜㸸஧㔜ᘧᾋయᘧὠἼ㑊㞴ࢩ࢙ࣝࢱ࣮ࡢ㐠ື≉ᛶ࡟㛵ࡍࡿᐇ㦂ⓗ◊✲,ᅵᮌᏛ఍ㄽᩥ㞟㸪B2㸦ᾏᓊᕤᏛ㸧, Vol. 67, No. 2, pp. l_751-l_755, 2011.
4) ⵗⱑ⣧, 㰻⸨᠇ᑑ, Ώ㎶୍ஓ㸸࣮ࣟࢻࢭࣝࢆ⏝࠸ࡓᾋయᘧὠἼ㑊㞴ࢩ࢙ࣝࢱ࣮ࡢἼຊ࡟㛵ࡍࡿ᳨ウ, ᮾ໭ᆅᇦ⅏ᐖ⛉Ꮫ◊✲, ➨ 55 ᕳ, No. 56, pp. 101_106, 2020.
5) 㰻⸨᠇ᑑ, Ώ㎶୍ஓ, ▼ሯ኱ᬛ㸸ᅽຊࢭࣥࢧࢆ⏝࠸ࡓ⁻ὶ≀ࡢἼຊ࡟㛵ࡍࡿ᳨ウ㸪ᾏὒ㛤Ⓨㄽᩥ㞟㸪➨ 77 ᕳ㸪pp. I_103-I_108㸪2021㸬
6) ࢱࢪ࣐ࡢᾋᥭᘧὠἼὥỈᑐ⟇⏝ࢩ࢙ࣝࢱ࣮SAFE+㸦ࢭ࣮ࣇࣉࣛࢫ㸧(https://www.tajima-motor.com/)㸦2021-5-23 ࢔ࢡࢭࢫ㸧東北地域災害科学研究

69

第58巻（2022） ᖺ㇟₲ᆅ㟈࡟ࡼࡿὠἼሁ✚≀ࡢᒙ┦ᘯ๓኱Ꮫ⌮ᕤᏛ㒊 㛗ᑿඃᶞᘯ๓኱Ꮫ኱Ꮫ㝔⌮ᕤᏛ◊✲⛉ ᒸ⏣㔛ዉᘯ๓኱Ꮫ኱Ꮫ㝔⌮ᕤᏛ◊✲⛉ ᱵ⏣ᾈྖᒸᒣ⌮⛉኱Ꮫ⌮Ꮫ㒊 㙊⁪Ꮥಙ㸯㸬 ࡣࡌࡵ࡟ ὠἼࡸὥỈ㸪㧗Ἴ㸪㧗₻࡜࠸ࡗࡓఱࡽ࠿ࡢእⓗ࡞஦㇟࡟ࡼࡾᆅ㉁Ꮫⓗ࡞᫬㛫ࢫࢣ࣮࡛ࣝࡣ
▐㛫ⓗ࡟ሁ✚ࡋࡓሁ✚≀ࢆ࢖࣋ࣥࢺሁ✚≀࡜࠸࠺ࠋࡇࡢ࠺ࡕ㸪ὠἼ࡟ࡼࡗ࡚ᾏᗏࡸἢᓊ㒊ࡢ὾ᥦ➼ࡢ◁ࡸἾ㸪♟ࡀ౵㣗ࡉࢀ㸪㐠ᦙࡉࢀ஧ḟⓗ࡟ሁ✚ࡋࡓࡶࡢࢆὠἼሁ✚≀࡜࠸࠺ࠋࡇࡢὠἼ
ሁ✚≀ࡢ≉᭷ࡢሁ✚ᵓ㐀ࡸෆ㝣᪉ྥ࡬ࡢᒙཌ㸪⢏ᗘࡢኚ໬࡜࠸ࡗࡓᕧどⓗ࡞≉ᚩࢆヲ⣽࡟グ㍕ࡍࡿࡇ࡜࡟ࡼࡗ࡚㸪௒ᚋࡢ◊✲࡛ࡢ࢖࣋ࣥࢺሁ✚≀ࡢㄆᐃ࡟ᙺ❧࡚ࡽࢀࡿࠋ᪂₲┴࠿ࡽ໭ᾏ㐨す᪉ࡲ࡛ࡢ᪥ᮏᾏἢᓊཬࡧࡑࡢἈྜ࠸ࡢ኱㝣ᩳ㠃࡟ࡣ➨ᅄ⣖࡟ከࡃࡢ㏫᩿ᒙࡀᙧᡂࡉࢀ㸪඲య࡜ࡋ࡚㛗ࡉ⣙ 1000km㸪ᖜ 100km ௨ୖ࡟㐩ࡍࡿ▷⦰ኚືᖏ㸦᪥ᮏᾏᮾ⦕ኚືᖏ㸧ࡀ࠶ࡿࠋࡇࡇ
࡛ࡣ㸪1983 ᖺࡢ᪥ᮏᾏ୰㒊ᆅ㟈ࡸ 1993 ᖺࡢ໭ᾏ㐨༡すἈᆅ㟈࡞࡝ࡀⓎ⏕ࡋ࡚࠸ࡿࠋࡉࡽ࡟㐣ཤࡢṔྐ᫬௦࡟㐳ࡿ࡜㸪1704 ᖺࡢᒾ㤋ᆅ㟈㸪1793 ᖺࡢすὠ㍍ᆅ㟈➼ࡀⓎ⏕ࡋἢᓊᆅᇦ࡟኱ࡁ
࡞⿕ᐖࢆࡶࡓࡽࡋࡓࠋ1804 ᖺ㸦ᩥ໬ඖᖺ㸧࡟Ⓨ⏕ࡋࡓ㇟₲ᆅ㟈㸦M=7.3㸧ࡶࡇࢀࡽࡢᆅ㟈ࡢ୍ࡘ࡛࠶ࡾ㸪ᬒ຾ᆅ“㇟₲”ࢆࡣࡌࡵ㸪ᗈ࠸⠊ᅖ࡛ᾏᓊ㝯㉳ࡀ⏕ࡌ࡚㇟₲௜㏆ࡢᾏᓊ㒊࡛᭱኱
1.8m ࡢ㝯㉳ࡀ⏕ࡌࡓ㸦ᖹ㔝࡯࠿㸪1979㸧ࠋࡇࡢ㝯㉳࡟ࡼࡗ࡚㇟₲†ࡀ㞳Ỉ࣭㝣໬ࡋࡓࠋࡲ
ࡓ㸪⛅⏣┴⬟௦࠿ࡽᒣᙧ┴୕℩ࡢἢᓊᇦ࡟ࡣὠἼࡀ฿᮶ࡋ㸪ᾐỈ㧗ࡣ㇟₲௜㏆ࡀ᭱኱࡛ 4㹼
5m ࡜᥎ᐃࡉࢀ࡚࠸ࡿ㸦⩚㫽㸪1986㸧ࠋࡋ࠿ࡋ࡞ࡀࡽ㸪ࡇࡢὠἼ࡟⏤᮶ࡍࡿ࢖࣋ࣥࢺሁ✚≀࡟ࡘ࠸࡚ࡣ㸪ࡇࢀࡲ࡛ヲ⣽࡞ሗ࿌ࡣ࡞ࡉࢀ࡚࠸࡞࠸ࠋࡑࡢࡓࡵ㸪➹⪅ࡽࡢࢢ࣮ࣝࣉ࡛ࡣࣁࣥࢹ࢕
ࢪ࢜ࢫࣛ࢖ࢧ࣮ࢆ⏝࠸ࡓὠἼሁ✚≀ࡢㄪᰝࢆ㇟₲࡛⾜ࡗࡓࠋᮏ✏࡛ࡣࡑࡢ⤖ᯝ࡟ࡘ࠸࡚ሗ࿌ࡍ
ࡿࠋ㸰㸬 ㄪᰝᆅᇦ࣭ᡭἲ
ㄪᰝࡣ 2021 ᖺ 10 ᭶࡟⛅⏣┴࡟࠿࡯ᕷ㇟₲⏫ࡢ⺡‶ᑎࡢᮾഃࡢỈ⏣࡟࠾࠸࡚㸪඲㛗 2m ࡢࣁࣥࢹ࢕ࢪ࢜ࢫࣛ࢖ࢧ࣮࡜඲㛗 1m ࡢࣁࣥࢻࢥ࢔࣮ࣛࢆ⏝࠸࡚⾜ࡗࡓࠋ௒ᅇࡣᾏᓊ࠿ࡽ⣙ 700m 㞳ࢀࡓᆅⅬ࠿ࡽᾏᓊ⥺࡟࡯ࡰ┤஺ࡍࡿ⣙ 500m ࡢ⥺㸦⥺ 1㸧࡟࠾࠸࡚㸪⣙ 40m 㛫㝸࡛ࢥ࢔ヨᩱࢆ᥇ྲྀࡋ㸪ᒙཌࡸሁ✚ᵓ㐀ࡢ≉ᚩࢆグ㍕ࡋࡓࠋࡲࡓ㸪⥺ 1 ࠿ࡽ༡᪉ྥ࡬⣙ 300m 㞳ࢀࡓ㧗Ἠᑎ௜㏆࡛ࡶࣁࣥࢹ࢕ࢪ࢜ࢫࣛ࢖ࢧ࣮࡟ࡼࡾ 3 ᮏࡢࢥ࢔ヨᩱࢆ᥀๐ࡋࡓࠋࡉࡽ࡟㸪᪥ᮏᾏᆅ
*Sedimentary structure of Tsunami deposits from the 1804 Kisakata Earthquake by Yuki Nagao, Rina
Okada, Koji Umeda and Takanobu Kamataki70㟈࣭ὠἼㄪᰝࣉࣟࢪ࢙ࢡࢺ㸦https://www.eri.u-tokyo.ac.jp/project/Japan_Sea/gaiyou.html㸧࡛᥀๐ࡉࢀࡓ῝ᗘ 8m ࡢ࣮࣎ࣜࣥࢢࢥ࢔ 2 ᮏ㸦KK1㸪KK2 ࢥ࢔㸧ࡢグ㍕ࡶ⾜ࡗࡓࠋ⢏ᗘศᯒ࡟ࡣᓥὠ〇సᡤ〇 SALD-3000J㸦࣮ࣞࢨᅇᯒᘧ⢏ᗘศᕸᅇᯒཬࡧ࣮ࣞࢨᩓ஘ἲࢆ⏝࠸ࡓᐃ⿦⨨㸧ࢆ⏝࠸ࡓࠋSALD-3000J ࡣ㸪࣮ࣞࢨᐃ᪉ᘧ࡛࠶ࡾ㸪ග※࡛࠶ࡿ༙ᑟయ࣮ࣞࢨࡢἼ㛗ࡣ 690nm ࡛࠶ࡿࠋཷග㒊ࡣ 76 ⣲Ꮚኚᙧྠᚰ෇ࢭࣥࢧ㸪ഃ᪉ࢭࣥࢧ㸪ᚋ᪉ࢭࣥࢧ㸦2 ⣲Ꮚ㸧࡟࡚ᵓᡂࡉࢀ
࡚࠸ࡿࠋࡇࢀ࡟ࡼࡾ㸪0.1㹼2,000μm ࡢ⠊ᅖࡢ⢏Ꮚࢆ▷᫬㛫࡛ṇ☜࡟ᐃࡍࡿࡇ࡜ࡀ࡛ࡁࡿࠋ

⢏ᗘศᯒ࡟⏝࠸ࡓヨᩱࡣྛ᥀๐ᆅⅬ࡟࠾࠸࡚㸪ὠἼሁ✚≀ࡢୖୗᒙࢆྵࡵ࡚ 1㹼2cm 㛫㝸࡛ሁ✚≀ࢆ᥇ྲྀࡋࡓࠋࡲࡓ㸪ᐃ⤖ᯝࡢ⢏ᚄຍ✚᭤⥺࠿ࡽ Folk and Ward㸦1957㸧࡟ᇶ࡙࠸࡚Ὲửᗘࢆ⟬ฟࡋࡓࠋ
ᅗ 1 ㄪᰝᆅᇦ࣭ㄪᰝ

⥺A㸸඲యᅗ. B㸸࡟࠿࡯ᕷ࿘㎶ᅗ. C㸸㇟₲࿘㎶ᅗ. D㸸᥀๐ᆅⅬ

71

㸱 㸬 ࢥ࢔ࡢᒙ┦ほᐹ࣭⢏ᗘศᯒ ᒙ┦ほᐹ࡟ࡼࡿ࡜㸪⪔సᅵࡢ┤ୗ࡟◁ᒙⱝࡋࡃࡣࢩࣝࢺΰࡌࡾࡢ◁ᒙࡀᏑᅾࡋ㸪ࡇࢀࡀ㈅Ẇΰࡌࡾࡢ◁࠾ࡼࡧࢩࣝࢺࢆ୺యࡍࡿ㇟₲ᒙࢆそࡗ࡚࠸ࡿࠋࡇࡇ࡛ࡣ KK22 ࢆ౛࡜ࡋ࡚㸪ὠἼሁ✚≀ࢆྵࡴ㇟₲ᒙࡢᒙ┦ࡢ≉ᚩࢆ♧ࡍ㸦ᅗ 2㸧ࠋKK22 ࡛ࡣ㸪ᆅ⾲㠃࠿ࡽ῝ᗘ 18cm ࡲ࡛ࡣ⪔సᅵ࠿ࡽ࡞ࡾ㸪ࡑࡇ࠿ࡽୗ఩ࡣ㈅Ẇࢆከࡃྵࡴ◁ཬࡧࢩࣝࢺࡀሁ✚ࡋ࡚࠸ࡿࠋ῝ᗘ 23㹼
37cm ࡟ࡣᴟ⣽⢏◁࠿ࡽ⣽⢏◁࠿ࡽ࡞ࡿ◁ᒙࡀᏑᅾࡍࡿࠋࡇࡢ◁ᒙ࡜ୗ఩ࡢ㇟₲ᒙࡢቃ⏺࡟ࡣ᫂░࡞౵㣗㠃ࡀㄆࡵࡽࢀࡿࡇ࡜㸪◁ᒙࡢୗ㒊࡟ࡣ㇟₲ᒙࡢഇ♟㸦ࣜࢵࣉ࢔ࢵࣉࢡࣛࢫࢺ㸧ࢆྵࡴࡇ࡜࠿ࡽ㸪ࡇࡢ◁ᒙࡣᙉ࠸Ỉὶୗ࡟࠾ࡅࡿ㐠ᦙ࣭ሁ✚స⏝࡟క࠺ὠἼሁ✚≀࡜⪃࠼ࡽࢀࡿࠋ
࡞࠾㸪㇟₲ᒙࡢୗ㒊ࡢ῝ᗘ 163cm ௨῝࡛ࡣ㸪◁ΰࡌࡾࡢࢩࣝࢺ࠿ࡽ᭷ᶵ㉁ࢩࣝࢺᒙ࡬࡜ኚ໬
ࡋ࡚࠸ࡿࠋ⢏ᗘศᯒࡢ⤖ᯝ㸪◁ᒙࢆᵓᡂࡋ࡚࠸ࡿ○ᒌ⢏Ꮚࡢ୰ኸ್㸦D50㸧ࡣ 2.07㸦ȭ㸧࡛࠶ࡾ㸪Ὲửᗘࡣ 1.02 ࡛࠶ࡗࡓ㸦῝ᗘ 30㹼31cm㸧ࠋ◁ᒙࡢୖ఩ࡢ◁ΰࡌࡾࢩࣝࢺᒙ࡛ࡣ㸪୰ኸ್
ࡣ 2.45㸦ȭ㸧࡛࠶ࡾ㸪Ὲửᗘࡣ 2.15 ࡛࠶ࡗࡓ㸦῝ᗘ 20㹼21cm㸧ࠋ◁ᒙࡢୗ఩ࡢ◁ΰࡌࡾࢩࣝ
ࢺᒙ࡛ࡣ୰ኸ್ 2.67㸦ȭ㸧࡛࠶ࡾ㸪Ὲửᗘࡣ 1.67 ࡛࠶ࡗࡓ㸦῝ᗘ 44㹼45cm㸧ࠋ୍᪉㸪◁ᒙ࡟ྵࡲࢀࡿഇ♟࡛ࡣ୰ኸ್ࡀ 2.78㸦ȭ㸧࡛࠶ࡾ㸪Ὲửᗘࡣ 2.03 ࡛࠶ࡗࡓࠋὠἼሁ✚≀࡜⪃࠼ࡽࢀࡿ◁ᒙࡢሁ✚ᵓ㐀ࡣ㇟₲ᒙ࡟ẚ࡭࡚ῈửࡀⰋࡃ㸪ྵࡲࢀࡿഇ♟ࡢ⢏ᗘศᕸࡣ㇟₲ᒙ࡜㢮ఝࡋ࡚࠸ࡿ࡜࠸࠺⤖ᯝࡀᚓࡽࢀࡓࠋ


ᅗ 2 KK22 ࡟࠾ࡅࡿᰕ≧ᅗ㸪ࢥ࢔෗┿

72

ᅗ 3 KK22㸦῝ᗘ 20~45cm㸧ࡢࢥ࢔෗┿㸪⢏ᗘศᯒ⤖ᯝ⢏ᗘศᯒ ᕥୖ㸸῝ᗘ 20㹼21cm ྑୖ㸸῝ᗘ 30㹼31cm ᕥୗ㸸῝ᗘ 44~45cm ྑୗ㸸ഇ♟㸲㸬 ᒙ┦ࡢ✵㛫ⓗ≉ᚩ
๓㏙ࡋࡓ⥺ 1㸦඲㛗⣙ 500m㸧ࡣ㸪ᶆ㧗ࡀ 1.2㹼1.6m ࡛ෆ㝣᪉ྥ࡬ࢃࡎ࠿࡟పࡃഴ࠸ࡓ࡯

ࡰᖹᆠ࡞ᆅᙧ࡟఩⨨ࡋ࡚࠾ࡾ㸪ࡇࡇ࡛ࡣ KK24 ࠿ࡽ KK37 ࡲ࡛ࡢ 14 ᮏࡢࢥ࢔ࢆ᥇ྲྀࡋࡓࠋὠ
Ἴሁ✚≀࡜⪃࠼ࡽࢀࡿ◁ᒙࡢᒙཌࡣ㸪⣙ 10cm ࡛㸪᭱኱ࡣ 23cm㸦KK30㸧࡛࠶ࡗࡓࠋ඲యⓗ࡟ෆ㝣᪉ྥ࡬ⷧᒙ໬ࡋ࡚࠸ࡃഴྥࡀㄆࡵࡽࢀ㸪ᾏᓊ࠿ࡽ⣙ 1300m ௜㏆࡛ࡏࢇ⁛ࡍࡿࠋ⢏ᗘศᯒ࡟ࡼࡿ࡜○ᒌ⢏Ꮚࡢᖹᆒ୰ኸ್ࡣ 1.91ȭ㸦KK2㸧㹼4.06ȭ㸦KK36㸧࡜୰⢏◁࠿ࡽࢩࣝࢺࢧ࢖
ࢬࡲ࡛ኚ໬ࡋ㸪ᾏᓊ࠿ࡽෆ㝣࡟ྥ࠿ࡗ࡚⣽⢏໬ࡋ࡚࠸ࡃ࡜࠸ࡗࡓഴྥࡀ㢧ⴭ࡛࠶ࡿࠋ

73

ᅗ4

⥺ 1 ࡢᒙཌኚ໬㸪⢏ᗘኚ໬㸳㸬 ⪃ᐹ ㇟₲ࡢὠἼሁ✚≀ㄪᰝࡢ⤖ᯝ㸪

⥺ 1 ࡛ࡣ඲యⓗ࡟ᾏᓊ࠿ࡽෆ㝣࡟ྥ࠿ࡗ࡚ὠἼሁ✚≀ࡢᒙཌࡀⷧࡃ࡞ࡾ㸪○ᒌ⢏Ꮚࡶ⣽⢏໬ࡋ࡚࠸ࡃഴྥࡀㄆࡵࡽࢀࡓࠋᒙཌࡀෆ㝣࡬ⷧᒙ໬ࡍࡿഴྥ
ࡣ㸪2011 ᖺᮾ໭ᆅ᪉ኴᖹὒἈᆅ㟈ࡢὠἼሁ✚≀࡟ࡶྠᵝ࡞ഴྥࡀㄆࡵࡽࢀࡿ㸦ᒣ⏣࣭⸨㔝㸪
2013㸧ࠋࡇࡢཎᅉ࡜ࡋ࡚ࡣ㸪ὠἼࡢὶࢀࡀῶ㏿ࡍࡿ࡟ᚑࡗ࡚⢏Ꮚࡀ㡰ḟሁ✚ࡍࡿࡇ࡜࡟ࡼࡾሁ
✚≀ࡢ౪⤥ࡀෆ㝣࡯࡝ᑡ࡞ࡃ࡞ࡿࡇ࡜ࡀ⪃࠼ࡽࢀࡿ㸦ᚋ⸨࣭⸨㔝㸪2008㸧ࠋࡲࡓ㸪○ᒌ⢏Ꮚࡢෆ㝣࡬ࡢ⣽⢏໬ࡶ 2004 ᖺ࢖ࣥࢻὒ኱ὠἼࡢሁ✚≀࡞࡝ࡢ◊✲࡛ሗ࿌ࡉࢀ࡚࠸ࡿ㸦౛࠼ࡤ㸪⸨㔝࡯࠿㸪2006㸧ࠋෆ㝣⣽⢏໬ࡀࡳࡽࢀࡿせᅉ࡜ࡋ࡚ࡣ㸪ὠἼࡀෆ㝣࡬࡜౵ධࡍࡿ࡟ࡘࢀ㸪⢒⢏ࢧ࢖ࢬࡢ○ᒌ⢏Ꮚࡀඃඛⓗ࡟ሁ✚ࡋ㸪ෆ㝣࡯࡝⢒⢏⢏Ꮚ࡟ஈࡋࡃ࡞ࡾ㸪┦ᑐⓗ࡟⣽⢏໬ࡋ࡚࠸ࡗࡓ࡜⪃࠼ࡽࢀࡿ㸦ᚋ⸨࣭⸨㔝㸪2008㸧ࠋࡉࡽ࡟㸪ࡇࡢ⌧㇟ࡣ㐳ୖ㊥㞳ࡀ▷࠸࡯࡝㢧ⴭ࡛࠶ࡿࡇ࡜ࡀᣦ᦬ࡉࢀ࡚࠸ࡿࡀ㸦౛࠼ࡤ㸪∦ᒣ࡯࠿㸪2015㸧㸪⥺ 1 ࡛ࡶྠᵝ࡞ഴྥࡀㄆࡵࡽࢀࡓࠋ ࡲࡓ㸪௒ᅇࡢㄪᰝ࡛ࡣὠἼሁ✚≀ࢆそ࠺⪔సᅵࡢ┤ୗ࡟ὠἼሁ✚≀ࡀฟ⌧ࡍࡿሙྜ࡜⪔సᅵ࡜ὠἼሁ✚≀࡜ࡢ㛫࡟◁ΰࡌࡾࢩࣝࢺᒙࢆᣳࡴሙྜࡀ࠶ࡗࡓࠋ๓⪅࡟ࡘ࠸࡚ࡣ㸪㝣໬ࡋࡓ㇟₲ࡢ᪂⏣㛤Ⓨࡢ㝿࡟㸪ὠἼሁ✚≀ࡢ୍㒊ࡀ๐ࡾྲྀࡽࢀࡓྍ⬟ᛶࡀ࠶ࡿࠋ୍᪉㸪ᚋ⪅ࡣỈᇦ࠶ࡿ࠸ࡣỈᇦ࡟㏆࠸⎔ቃ࡛ὠἼሁ✚≀ࡀሁ✚ࡋ㸪ࡑࡢᚋ࡟◁ΰࡌࡾࡢࢩࣝࢺࡀሁ✚≀ࢆそࡗࡓࡶࡢ࡛㸪ὠἼሁ✚≀ࡢேⅭⓗ࡞Ḟᦆࢆචࢀࡓࡇ࡜ࡀ⪃࠼ࡽࢀࡿࠋṔྐྐᩱ࡟ࡼࡿ࡜ 1804 ᖺࡢ㇟₲ᆅ㟈┤ᚋࡣ㸪㇟₲ࡢ༡ഃ࡛ࡣ᏶඲࡟㝣໬ࡋ࡚࠾ࡽࡎ㸪୍㒊࡟Ỉᇦࡀṧࡗ࡚࠸ࡓ࡜ࡉࢀ࡚࠸ࡿࡀ
㸦Ᏻ⏣㸪2021㸧㸪◁ΰࡌࡾࢩࣝࢺᒙࢆᣳࡴࢥ࢔ࡶ㇟₲ࡢ༡ഃ࡟ศᕸࡍࡿഴྥࡀ࠶ࡿࠋ㸴㸬 ࠾ࢃࡾ࡟
 1804 ᖺ㇟₲ᆅ㟈ࡢὠἼሁ✚≀ࢆㄪᰝࡋࡓ⤖ᯝ㸪ᾏᓊ࠿ࡽෆ㝣࡟ྥࡅ࡚ሁ✚ᵓ㐀ࡀኚ໬ࡍࡿ
ࡇ࡜ࡀ᫂ࡽ࠿࡟࡞ࡗࡓࠋࡋ࠿ࡋ࡞ࡀࡽ㸪㇟₲†ࡢ༡ഃ࡟ศᕸࡍࡿὠἼሁ✚≀ࢆそ࠺◁ΰࡌࡾࢩࣝࢺᒙࡢᡂᅉࡸᆅ㟈࡟క࠺ὠἼࡢᾐỈ⠊ᅖ➼ࡀㄢ㢟࡜ࡋ࡚ṧࡉࢀࡿࠋ௒ᚋࡣㄪᰝᆅⅬࢆቑࡸࡍ

74࡜࡜ࡶ࡟㸪○ᒌ⢏Ꮚࡢ᳨㙾ほᐹ㸪⌛⸴ศᯒࡸⅆᒣ࢞ࣛࢫࡢ୺ᡂศඖ⣲ศᯒ➼࡟ࡼࡗ࡚ከゅⓗ࡞᳨ウࢆ㐍ࡵ࡚࠸ࡃணᐃ࡛࠶ࡿࠋ

ㅰ㎡
 ᮏ◊✲ࡢ୍㒊࡟ࡣ⛉Ꮫ◊✲㈝㸦ᇶ┙◊✲㸦C㸧㸪ㄢ㢟␒ྕ㸸20K05042㸪௦⾲㸸㙊⁪Ꮥಙ㸧ࢆ౑⏝ࡋࡓࠋࡲࡓ㸪ᒸᒣ⌮⛉኱Ꮫ⌮Ꮫ㒊ᇶ♏⌮Ꮫ⛉ 4 ᖺ⏕ࡢ⏣ཎ⚈ከ㸪ὠᓮ᪦㝧㸪ྂ⏣ᐶᏘࡢྛẶ࡟ࡣ⌧ᆅㄪᰝ࡟༠ຊ࠸ࡓࡔ࠸ࡓࠋᆅᇦఫẸࡢ᪉ࠎ࡟ࡣㄪᰝ࡟㛵ࡋ࡚ᛌㅙࡋ࡚㡬࠸ࡓࠋࡇࡇ࡟
グࡋ࡚㛵ಀྛ఩࡟῝ࡃㅰពࢆ⾲ࡍࠋᘬ⏝ᩥ⊩Ᏻ⏣ᐜᏊ㸸ᆅ㟈๓࡜ᆅ㟈ᚋࡢ⤮⏬࠿ࡽࡳࡿ㇟₲ࡢኚ㑄. ௒஭೺ኴ㑻㸦⦅㸧, ஧ⓒᖺ๓࡟㇟₲࡛㉳ࡁࡓࡇ࡜, ⛅⏣ᩥ໬ฟ∧, pp.12-24, 2021.
ᖹ㔝ಙ୍࣭୰⏣㧗࣭௒Ἠಇᩥ㸸㇟₲ᆅ㟈㸦1804 ᖺ㸧࡟క࠺ᆅẆኚᙧ, ➨ᅄ⣖◊✲, 18, pp.17-30,
1979.
⩚㫽ᚨኴ㑻㸸ᩥ໬ඖᖺ㸦1804 ᖺ㸧㇟₲ᆅ㟈ࡢ㟈ᗘ࠾ࡼࡧὠἼㄪᰝ, ᆅ㟈◊✲ᡤᙡሗ,61,
pp.143-157, 1986.
∦ᒣ⿱அ࣭๓⏣ຬྖ࣭Ᏻ㔝ᾈ୍ᮁ࣭ྜྷἙ⚽㑻࣭㜰ཱྀ⚽࣭すᾆὈ௓㸸ὠἼሁ✚≀ࡢ⢏ᗘ೫ᯒ࣓࢝
ࢽࢬ࣒ࡢゎ᫂࡟㛵ࡍࡿᇶ♏ⓗ◊✲, ᅵᮌᏛ఍ㄽᩥ㞟 B3㸦ᾏὒ㛤Ⓨ㸧, 71, pp.641-646, 2015.
ᒣ⏣ᫀᶞ࣭⸨㔝⁠ᘯ㸸2011 ᖺᮾ໭ᆅ᪉ኴᖹὒἈᆅ㟈ὠἼ࡟ࡼࡾⲈᇛ┴࣭༓ⴥ┴ἢᓊపᆅ࡟ᙧ
ᡂࡉࢀࡓὠἼሁ✚≀ࡢሁ✚Ꮫⓗ≉ᚩ, ሁ✚Ꮫ◊✲, 72, pp.13-25, 2013.
Folk, R.L. and Ward, W.C., Brajos river bar: a study in the significance of grain-size parameters.
Journal of Sedimentary Petrology, 27, pp.3-27, 1957.
ᚋ⸨࿴ஂ࣭⸨㔝⁠ᘯ㸸2004 ᖺ࢖ࣥࢻὒ኱ὠἼᚋࡢὠἼሁ✚≀◊✲ࡢㄢ㢟࡜ᒎᮃ, ᆅ㉁Ꮫ㞧
ㄅ,12, pp.599-617, 2008.
⸨㔝⁠ᘯ࣭ᯇᮏᙎ࣭ᡂ℩ඖ࣭⸨⏣࿴ᙪ࣭Suphawajruksakul, A.࣭Jarupongsakul, T.㸸㝣ୖὠἼሁ✚≀ࡢሁ✚ᵓ㐀࡜ሁ✚㐣⛬㸫ࢱ࢖༡す㒊࡟࠾ࡅࡿ࢖ࣥࢻὒὠἼࡢ౛㸫, ᭶หᆅ⌫, 326,
pp.558-562, 2006.

東北地域災害科学研究75

第58巻（2022）ᩘ್ࢩ࣑࣮ࣗࣞࢩࣙࣥࢆ⏝࠸ࡓ㞝≀ᕝἙཱྀᇦ࡟࠾ࡅࡿሷỈ㐳ୖࡢ◊✲ ⛅⏣኱Ꮫ⌮ᕤᏛ㒊 ⚄⏣ᬛὒ⛅⏣኱Ꮫ኱Ꮫ㝔⌮ᕤᏛ◊✲⛉ ㇂ཱྀ㞙ஓ࣭㰻⸨᠇ᑑ࣭Ώ㎶୍ஓ1㸬 ࡣࡌࡵ࡟
Ἑཱྀ㒊ࡣἙᕝࡸᾏᓊ࠿ࡽࡢእຊ࡟ࡼࡿᙳ㡪ࢆ኱ࡁࡃཷࡅ࡚࠾ࡾ㸪≉࡟ῐỈ࡜ሷỈࡢ᥋ゐ࡟ࡼࡾࡁࢃࡵ࡚」㞧࡞ᵝ┦ࢆ࿊ࡋ࡚࠸ࡿ 1)ࠋᙅΰྜᆺἙᕝ࡛⏕ࡌࡿሷỈࡃࡉࡧࡣἙᕝỈࡢሷỈ໬ࢆᘬࡁ㉳ࡇࡋỈ㈨※฼⏝ࡢ㞀ᐖ࡜࡞ࡗ࡚࠾ࡾ㸪ࡇࡢᛶ㉁ࢆゎ᫂ࡍࡿࡇ࡜ࡣ㔜せ࡛࠶ࡿࠋࡇࡢࡼ࠺࡞Ἑᕝ࡛ࡢሷ
Ỉࡃࡉࡧࡢ㐳ୖ࡟ࡘ࠸࡚ࡣ㸪▼⊁ᕝἙཱྀ 2)ࡸ㜿㈡㔝ᕝ 3)➼࡛ᐇ㈨ᩱࢆࡶ࡜࡟◊✲ࡀ⾜ࢃࢀ࡚࠸ࡿࠋ

ࡲࡓ㸪⛅⏣┴࡛ࡣ⡿௦ᕝ 4)࡛◊✲ࡀ⾜ࢃࢀ࡚࠸ࡿࡀ㸪2019 ᖺࡢῬỈ⿕ᐖ 5)࡟క࠸ሷỈ㐳ୖࡀ☜ㄆࡉࢀࡓ㞝≀ᕝ࡟࠾࠸࡚㸪ሷỈ㐳ୖࡢせᅉࡣ᫂ࡽ࠿࡜࡞ࡗ࡚࠸࡞࠸ࠋ
ࡑࡇ࡛ᮏ◊✲࡛ࡣ㸪㞝≀ᕝἙཱྀᇦࢆᑐ㇟࡟⌧ᆅほ ࡜ሷỈ㐳ୖࡢᩘ್ࢩ࣑࣮ࣗࣞࢩࣙࣥࢆ⾜࠸㸪㞝≀ᕝࡢሷỈ㐳ୖ࡟ᙳ㡪ࢆࡶࡓࡽࡍせᅉࢆ᳨ウࡋࡓࠋ
2㸬 ◊✲ᑐ㇟ᅗ  ࡟㞝≀ᕝࡢ඲యᅗࢆ♧ࡍࠋ㞝≀ᕝࡣ⛅⏣┴ࢆὶࢀࡿ୍
⣭Ἑᕝ࡛࠶ࡿࠋὶᇦ㠃✚ࡣ 4,710 kଶ 㸪ᖿ⥺ὶ㊰ᘏ㛗ࡣ 133
km ࡜࡞ࡗ࡚࠸ࡿࠋᅗ  ࡟ほᆅⅬ࠾ࡼࡧィ⟬㡿ᇦࢆ♧ࡍࠋ

ほ ᆅⅬ࡟࠾࠸࡚ࡣ㸪ほ ᆅⅬ AB 㛫ࡢ㊥㞳ࡣ⣙ 50 m ࡜࡞ࡗ࡚࠸ࡿࠋほ ᆅⅬ C ࡣ㸪2019 ᖺ࡟ᅜᅵ஺㏻┬ࡀᐇ᪋ࡋࡓᅗ  㞝≀ᕝὶᇦᅗᅗ  ほ ᆅⅬ࣭ィ⟬㡿ᇦ(google map ࡼࡾᘬ⏝)*Study on Saline Water Run-up at Omono River Mouth using Numerical Simulation by Tomohiro KANDA,
Junya TANIGUCHI, Noritoshi SAITO and Kazuya WATANABE

76ሷศほ ᆅⅬ࡛࠶ࡾ㸪ほ ᆅⅬ A ࠾ࡼࡧ B࠿ࡽୖὶ᪉ྥ࡟⣙ 100 m ࡟఩⨨ࡋ࡚࠸ࡿࠋ
ᮏ◊✲࡛ࡣ㞝≀ᕝἙཱྀᇦࢆᑐ㇟࡟㸪⌧ᆅほ࡜ᩘ್ࢩ࣑࣮ࣗࣞࢩࣙࣥࢆ⾜ࡗࡓࠋ
㸬 ሷศほ
3㸬

⤖ᯝ

ሷศほ ࡟ࡣከ㡯┠Ỉ㉁ィ㸦ࢡࣟࣟࢸࢵ
ࢡ㸧ࢆ⏝࠸࡚㸪ሷศࡢ㖄┤ศᕸࢆ ᐃࡋࡓࠋሷศほ ࡢ⤖ᯝࢆᅗ  ࡟♧ࡍࠋ2021/6/17 ࡢᅗ  ሷศほ ⤖ᯝ࡛ࡣ㸪ᆅⅬ A ࡟࡚ሷỈࡢ㐳ୖࡣㄆࡵࡽ

ほࢀ࡞࠿ࡗࡓࡀ㸪2021/8/4 ࡢᆅⅬ A ࡛ࡣ㸪᭱኱ሷศ⃰ᗘ 31.510 psu ࢆ♧ࡋࡓࠋྠ᪥ࡢᆅ
Ⅼ B ࡛ࡣ㸪᭱኱ሷศ⃰ᗘ 31.416 psu ࢆ♧ࡋࡓࠋࡑࡋ࡚㸪2019 ᖺ࡟ᅜᅵ஺㏻┬࡟ࡼࡗ࡚ᆅⅬ C ࡟࡚ᐇ᪋ࡉࢀࡓほ16.300psu ࢆ♧ࡋࡓ⤖ᯝࡣ㸪6)ࠋᆅⅬ A ࠾ࡼࡧ B ࡟

ᑐࡋ࡚ᆅⅬ C ࡢሷศ⃰ᗘࡣ༙ศ⛬ᗘ࡜࠸࠺⤖ᯝࢆ♧ࡋࡓࡀ㸪ࡇࢀࡣほᆅⅬ C ࡀࡼᅗ  ほ7 ᪥๓࠿ࡽࡢỈ఩ᕪᅗ  ほ7 ᪥๓࠿ࡽࡢἼ㧗ࡾୖὶഃ࡟఩⨨ࡋ࡚࠸ࡿࡇ࡜ࡀཎᅉ࡜⪃࠼ࡽࢀࡿࠋሷỈ㐳ୖࡀ☜ㄆ࡛ࡁࡓሙྜࡣ,࠸ࡎࢀࡶ᫂░࡟ሷỈࡢ㌍ᒙࡀぢࡽࢀࡓࠋࡲ
ࡓ㸪ሷỈࡀἙᗋࢆ㏺࠺ࡼ࠺࡟ศᕸࡋ࡚࠸ࡓ
ࡇ࡜࠿ࡽ㸪ሷỈ㐳ୖࡀ☜ㄆࡉࢀࡿሙྜࡣ㸪ሷỈࡃࡉࡧࡀⓎ⏕ࡍࡿࡢ࡛ࡣ࡞࠸࠿࡜⪃࠼ࡽࢀࡿࠋほ

᪥ 7 ᪥๓࠿ࡽࡢỈ఩ᕪࡢኚ໬ࢆᅗ ࡟♧ࡍࠋỈ఩ᕪ߂ߟࡣ㸪₻఩ߟ௥ ࠾ࡼࡧỈ఩ߟோࡼࡾᘧ(1)ࢆ⏝࠸࡚⟬ฟࡋࡓࠋ࡞࠾㸪ࢹ࣮ࢱࡣᅜ஺┬ࡼࡾ⛅⏣ ࡢࢹ࣮ࢱࢆ౑⏝ࡋࡓࠋ߂ߟ ൌ ߟ௥ െ ߟோ       (1)ሷỈ㐳ୖࡀ☜ㄆࡉࢀࡓ 2019/8/9 ࠾ࡼࡧ 2021/8/4 ࡢỈ఩ᕪࡣ-2.5 m ࡛࠶ࡗࡓࡀ㸪㐳ୖࡀ☜ㄆࡉࢀ࡞࠿ࡗࡓ 2021/6/17 ࡢỈ఩ᕪࡣ-0.37 m ࡛࠶ࡗࡓࠋࡇࡢࡇ࡜࠿ࡽ㸪-0.37 m ࠿ࡽ-0.25 m ࡢ⠊ᅖෆ࡛ሷỈ㐳ୖࡢ᮲௳ࢆ‶ࡓࡍ㜈್ࡀ࠶ࡿ࡜⪃࠼ࡽࢀࡿࡓࡵ㸪௒ᚋࡣࢹ࣮ࢱࢆ⵳✚ࡋࠊሷỈ㐳ୖ࡜Ỉ఩ᕪࡢ㛵ಀࢆヲ⣽࡟᳨ウࡍࡿᚲせࡀ࠶ࡿࠋほ ᪥ 7 ᪥๓࠿ࡽࡢἼ㧗ࡢኚ໬ࢆᅗ  ࡟♧ࡍࠋ2021/8/4 ࠾ࡼࡧ 2021/6/17 ࡟ ᐃࡋࡓ㝿ࡢἼ㧗ࡣ

77

100 m

ᅗ  㞝≀ᕝἙཱྀᖜ
0.2 m ⛬ᗘ࡛࠶ࡗࡓࡀ㸪
2019/8/9 ࡢἼ㧗ࡣ ᐃ᪥ࡢ 10 ᫬㛫⛬ᗘ๓࠿ࡽ࡟ᛴ⃭࡟኱ࡁࡃୖ᪼ࡋ࡚࠸ࡿࠋ
ࡇࡢࡇ࡜࠿ࡽࡣ㸪Ἴ㧗࡟ࡼࡿሷỈ㐳ୖ࡬ࡢᙳ㡪ࡣぢࡽࢀ࡞࠿ࡗࡓࠋ
2021/6/17㸪
2021/8/4 ࠾ࡼࡧ 2021/9/15 ࡟ሷศほ ࢆ⾜ࡗࡓ㝿ࡢ㞝≀ᕝἙཱྀ㒊ࡢᙧ≧ࢆᅗ  ࡟♧ࡍࠋࡇࢀࡽࡢᅗࡣ㞝≀ᕝ⌧ᆅ࡟࡚ UAV(unmanned aerial vehicle)ࢆ⏝࠸࡚✵᧜ࢆᐇ᪋ࡋ㸪SfM(Structurefrom Motion)ฎ⌮ࢆ᪋ࡋࡓࡶࡢ࡛࠶ࡿࠋᅗ  ࡢ࠺ࡕ㸪ሷỈ㐳ୖࡀ☜ㄆࡉࢀࡓࡢࡣ 2021/8/4 ࡢࡳ࡛࠶ࡿࡀ㸪Ἑཱྀᖜࡣ 2021/6/17 ࡢ᪉ࡀ኱ࡁ࡞ᩘ್ࢆ♧ࡋࡓࠋࡇࡢࡇ࡜࠿ࡽ 2021/8/4 ࡟ሷỈ㐳ୖࡀ☜ㄆ࡛ࡁࡓせᅉࡢ୍ࡘࡣᅗ  ࡟♧ࡋࡓỈ఩ᕪ࡛࠶ࡿ࡜⪃࠼ࡽࢀࡿࠋࡲࡓ㸪2021/9/15 ࡟࠾࠸࡚ࡣ㸪Ἑཱྀᖜࡀ㠀ᖖ࡟⊃ࡃ࡞ࡗ࡚࠸ࡓࠋ᪤ ࡢ◊✲⁴⁾࡟ࡼࡿ࡜㸪Ἑཱྀ◁ᕞࡀⓎ㐩ࡋ࡚ᕝᖜࡀ㛢ሰࡋࡓሙྜ㸪Ἑᕝὶ㔞ࢆὶୗࡉࡏࡿࡓࡵ࡟ὶ㏿ࡀ᪩ࡃ࡞ࡾ㸪ᾏỈࡢᾐධࡀᅔ㞴࡟࡞ࡿࡇ࡜ࡀ᫂ࡽ࠿࡜࡞ࡗ࡚࠸ࡿࠋࡑࡢ
ࡓࡵ㸪2021/9/15 ࡶྠᵝࡢ⌮⏤࡛ሷỈ㐳ୖࡀ☜ㄆ࡛ࡁ࡞࠿ࡗࡓ࡜⪃࠼ࡽࢀࡿࠋ௨ୖࡢࡇ࡜࠿ࡽ㸪㞝≀ᕝࡢሷỈ㐳ୖ࡟࠾࠸࡚Ἑཱྀᖜࡣ୍ᐃࡢᙳ㡪ࢆ୚࠼࡚࠸ࡿ࡜⪃࠼ࡽࢀࡿࠋ㸬 ᩘ್ィ⟬
4㸬ᩘ್ィ⟬࡟౑⏝ࡋࡓᇶ♏᪉⛬ᘧࢆᘧ(2)㹼(5)࡟♧ࡍࠋᘧ(2)ࡣ㐃⥆ᘧ㸪ᘧ(3)㹼(5)ࡣ㠀ᅽ⦰࡜ࣈࢩࢿ
ࢫࢡ㏆ఝࢆ౑⏝ࡋࡓ 3 ḟඖ Navier-Stokes ᘧ࡛࠶ࡿࠋࡲࡓ㸪ሷศ⃰ᗘࡢ㍺㏦᪉⛬ᘧࢆᘧ(6)࡟♧ࡍࠋ
ఋ௨
ఋ௫
ఋ௨

൅‫ݑ‬

ఋ௧
ఋ௩
ఋ௧
ఋ௪
ఋ௧

ఋ௨
ఋ௫

൅‫ݑ‬

൅‫ݑ‬

ఋ௩
ఋ௫

ఋ௪
ఋ௫

ఋ௨

൅‫ݒ‬

ఋ௫

൅‫ݒ‬
൅‫ݒ‬
ఋ஼
ఋ௧

൅‫ݓ‬

ఋ௩
ఋ௫

ఋ௪
ఋ௫

൅‫ݑ‬

൅‫ݓ‬
൅‫ݓ‬
ఋ஼
ఋ௫

ఋ௨
ఋ௭
ఋ௩
ఋ௭
ఋ௪
ఋ௭

൅‫ݒ‬

ଵ ఋ௣

െ ݂‫ ݒ‬ൌ െെ ݂‫ ݑ‬ൌ െ
ൌെ
ఋ஼
ఋ௬

ଵ ఋ௣
ఘబ ఋ௭

൅‫ݓ‬

ఋ஼
ఋ௭

൅

ఘబ ఋ௫
ଵ ఋ௣
ఘబ ఋ௫

൅
ൌ

ఋ
ఋ௫
ఋ
ఋ௫

൅

൅

ఋ
ఋ௫
ఋ
ఋ௫

ఋ௩
ఋ௬

൅

ఋ௪
ఋ௭

ൌ Ͳ                  (2)

ఋ௨

ఋ

ఋ௨

ఋ

ఋ௨

ఋ௩

ఋ

ఋ௩

ఋ

ఋ௩

ቀܸு ఋ௫ ቁ ൅ ఋ௬ ቀܸு ఋ௬ቁ ൅ ఋ௭ ቀܸு ఋ௭ ቁ          (3)ቀܸு ఋ௫ቁ ൅ ఋ௬ ቀܸு ఋ௬ቁ ൅ ఋ௭ ቀܸு ఋ௭ ቁ          (4)
ఋ

ఋ௪

ఋ

ఋ௪

ఋ௪

௚

ቀܸு ఋ௫ ቁ ൅ ఋ௬ ቀܸு ఋ௬ ቁ ൅ ఋ௭ ቀܸு ఋ௭ ቁ െ ఘ ሺߩ଴ ൅ ߩሻ      (5)
బ

ఋ஼

ఋ

ఋ஼

ఋ

ఋ஼

‫ ܭ‬ቀ ቁ ൅ ‫ ܭ‬ቀ ቁ ൅ ‫ ܭ‬ቀܸு ቁ            (6)
ఋ௫
ఋ௬
ఋ௬
ఋ௭
ఋ௭

78

⾲  ィ⟬ࣃ࣓࣮ࣛࢱ
ὶ㔞࣭Ἴ㧗࡜
ሷỈ㐳ୖࡢ㛵ಀỈ῝᪉ྥࡢึᮇ⃰ᗘศᕸࡢᙳ㡪ὶ㊰㛗 (m)

1400

ᕝᖜ (m)300

Ỉ῝ (m)

6
1/5000୺ὶ㊰㒊໙㓄
ึᮇ㓄⨨⃰ᗘ (psu)32ィ⟬ࢱ࢖࣒ࢫࢸࢵࣉ(s)0.5ィ⟬᱁Ꮚ (m)20 × 20 × 1

ୗὶ➃࿘ᮇ (s)6ୗὶ➃Ἴ㧗 (m)0.22㸪1㸪2㸪3㸪5

3

ὶ㔞 (m /s)ึᮇ⃰ᗘศᕸ (m)ᣑᩓಀᩘࡢᙳ㡪

1

0㸪100

100

300 × 300 × 6

300 × 300 × n (n=1㸪3㸪5㸪6)

300 × 300 × 3

000㸪0.05㸪1㸪5㸪10㸪100ᣑᩓಀᩘ ࡇࡇ࡛㸪u ࡣ x ᪉ྥࡢὶ㏿㸪v ࡣ y ᪉ྥࡢὶ㏿㸪w ࡣ z ᪉ྥࡢὶ㏿㸪t ࡣ᫬㛫㸪f ࡣࢥࣜ࢜ࣜಀᩘ㸪ܸு ࡣỈᖹ᪉ྥࡢ⢓ᛶಀᩘ㸪ܸ௩ ࡣ㖄┤᪉ྥࡢ ⢓ᛶಀᩘ㸪ߩ଴ࡣཧ↷ᐦᗘ㸪ߩ଴ ൅ ߩࡣᐦᗘ㸪C ࡣሷศ⃰ᗘ㸪K ࡣᣑᩓಀᩘ࡛࠶ࡿࠋࡲࡓ㸪ィ⟬᮲௳ࢆ⾲  ࡟♧ࡍࠋࡇࡢィ⟬᮲௳࠿ࡽྲྀᚓ࡛ࡁࡿィ⟬㡿ᇦࡣ㸪1400 m×300 m×6 m ࡢ▴ᙧỈ㊰࡛࠶ࡿࠋᐇ㝿ࡢ㞝≀ᕝࡣ୧ᓊ࠿ࡽ◁ᕞࡀⓎᅗ  Ἴ㧗࡜ሷỈ㐳ୖ㊥㞳ࡢ㛵ಀ㐩ࡋ㸪Ἑཱྀࡀ⊃✽ࡋ࡚࠸ࡿࠋຍ࠼࡚Ἑᗋ㧗ࡶ୍ᐃ࡛ࡣ࡞࠸ࡀ㸪௒ᅇࡢ᳨ド࡛ࡣᐇἙᕝࡢ෌⌧࡛ࡣ࡞ࡃ㸪ሷỈ㐳ୖ࡟୚࠼ࡿᙳ
㡪ࡢ኱ࡁ࡞せᅉࢆ᫂ࡽ࠿࡟ࡍࡿࡇ࡜ࢆ㔜どࡋࡓࠋᮏ◊✲࡛ࡣࣃ࣓࣮ࣛࢱࡢ୍㒊ࢆᅛᐃࡋ㸪ὶ㔞㸪ୗὶ➃Ἴ㧗㸪ึᮇ⃰ᗘศᕸ㸪ᣑᩓಀᩘࢆኚ᭦ࡋ㸪ࡑࢀࡒࢀࡢ㛵ಀࢆ⪃ᐹࡋࡓࠋᅗ  ሷỈࡢ⤒᫬ኚ໬㸬 ィ⟬⤖ᯝ
5㸬
1  ὶ㔞࣭Ἴ㧗࡜ሷỈ㐳ୖ㊥㞳ࡢ㛵ಀ࿘ᮇࢆᅛᐃࡋ࡚Ἴ㧗 H ࠾ࡼࡧἙᕝὶ㔞 Q ࢆኚ໬ࡉࡏ㸪300 m ᆅⅬ࠿ࡽሷỈࡀ㐳ୖࡍࡿ㊥㞳ࢆィ⟬ࡋࡓࠋἼ㧗࡜ሷỈ㐳ୖ㊥㞳ࡢ㛵ಀࢆᅗ  ࡟♧ࡍࠋὶ㔞࡟㛵ࢃࡽࡎ㸪Ἴ㧗ࡀ኱ࡁ࠸࡯࡝㐳ୖ㊥㞳ࡀ

79

ᅗ  ሷศࡢ㖄┤ศᕸࡢ⤒᫬ኚ໬ᅗ  ᣑᩓಀᩘ࡜ሷศศᕸࡢ⤒᫬ኚ໬ᅗ  ึᮇ⃰ᗘศᕸ࡜㖄┤ࡢሷศศᕸࡢ㛵ಀᅗ  ᣑᩓಀᩘ࡜ሷศࡢ㖄┤ศᕸࡢ㛵ಀ㛗ࡃ࡞ࡗ࡚࠸ࡿࡀ㸪ὶ㔞࡟ࡼࡿᕪࡣ᭱኱ 30 m ⛬ᗘ࡛࠶ࡗࡓࠋࡇࡢࡇ࡜࠿ࡽ㸪ሷỈ㐳ୖ࡟࠾ࡅࡿὶ
㔞ࡢᙳ㡪ࡣἼ㧗࡟ẚ࡭ࡿ࡜ᑠࡉ࠸࡜⪃࠼ࡽࢀࡿࠋ
ሷศ⃰ᗘࡢ⤒᫬ኚ໬ࢆᅗ  ࡟♧ࡍࠋ࡞࠾㸪タᐃࡣὶ㔞 Q=100 ⅿ³/s㸪Ἴ㧗 H=1 m ࡛࠶ࡿࠋィ⟬㛤ጞ┤ᚋࡢ 0 s ᫬Ⅼ࡛ࡣ 300 m ࡲ࡛▴ᙧ≧࡟ሷỈࡀ㓄⨨ࡉࢀ࡚࠸ࡿࡀ㸪᫬㛫ኚ໬࡜࡜ࡶ࡟Ἑᗋ࠾ࡼࡧ
ୖὶഃ࡬ሷỈࡀ㐳ୖࡋ࡚࠸ࡃᵝᏊࢆ☜ㄆ࡛ࡁࡓࠋࡲࡓ㸪950s ᫬ⅬࡢᵝᏊ࠿ࡽሷỈࡃࡉࡧࡀ⏕ࡌ࡚࠸ࡿ࡜⪃࠼ࡽࢀࡿࠋ
2) Ỉ῝᪉ྥࡢึᮇ⃰ᗘศᕸࡢᙳ㡪ὶ㔞࣭Ἴ㧗ࢆᅛᐃࡋ㸪ึᮇ⃰ᗘศᕸࢆỈ῝᪉ྥ࡟ኚ໬ࡉࡏࡓሙྜࡢሷศ⃰ᗘࡢᕪ␗ࢆ᳨ドࡋࡓࠋึᮇ⃰ᗘศᕸࢆ 300 m300 m3 m ࡜ࡋࡓሷศ㖄┤ศᕸࡢ⤒᫬ኚ໬ࢆᅗ  ࡟♧ࡍࠋ࡞࠾㸪㖄┤ศᕸࡣἙཱྀ࠿ࡽ 800 m ᆅⅬࡢ୰ኸ࠿ࡽฟຊࡋࡓࠋィ⟬㛤ጞ࠿ࡽ 1000 s ⛬ᗘ࡛ሷศ⃰ᗘࡀ᭱኱࡜࡞ࡗࡓ
ࡀ㸪ࡑࡢᚋࡣ⦆ࡸ࠿࡟పୗࡋࡓࠋࡲࡓ㸪Ỉ㠃ഃࡼࡾࡶἙᗋഃࡢ᪉ࡀ㸪ሷศ⃰ᗘࡀ኱ࡁࡃୖ᪼࠾ࡼࡧ
పୗࡍࡿഴྥ࡛࠶ࡿࡇ࡜ࡀศ࠿ࡗࡓࠋỈ῝᪉ྥࡢึᮇ⃰ᗘศᕸ࡜ሷศࡢ㖄┤ศᕸࡢ㛵ಀࢆᅗ  ࡟♧ࡍࠋィ⟬㛤ጞ 1000 s ᫬Ⅼࡢ 800 m
ᆅⅬࡢ୰ኸ࠿ࡽฟຊࡋࡓࠋึᮇ⃰ᗘศᕸࢆ㧗ࡃ㓄⨨ࡋࡓሙྜࡸἙᗋഃ࡯࡝ሷศ⃰ᗘࡀ㧗ࡃ࡞ࡿഴྥ

80࡛࠶ࡾ㸪ᅗ  ྠᵝࡢᣲືࢆ♧ࡋࡓࠋ୍᪉㸪ᅗ  ࡟♧ࡋࡓ⌧ᆅほ ࡢ⤖ᯝ࡜ẚ㍑ࡍࡿ࡜㸪⌧ᆅほ ࡛ࡣῐỈ࡜ሷỈࡀ᫂░࡟ศ࠿ࢀ࡚࠸ࡓࡀ㸪ᩘ್ࢩ࣑࣮ࣗࣞࢩࣙࣥࡢ⤖ᯝࡣ␗࡞ࡾ㸪Ỉ㠃ഃ࠿ࡽἙᗋഃ
࡬ᚎࠎ࡟ሷศ⃰ᗘࡢୖ᪼ࡀぢࡽࢀࡓࠋࡲࡓ㸪Ἑᗋ௜㏆ࡢሷศ⃰ᗘࡣ⌧ᆅほ ࡼࡾࡶᑠࡉ࠸್ࢆ♧ࡋࡓࠋ3) ᣑᩓಀᩘ࡜ሷỈ㐳ୖࡢ㛵ಀ ᣑᩓಀᩘࢆᐃࡵࡓ࡜ࡁࡢሷศࡢ㖄┤ศᕸࡢ⤒᫬ኚ໬ࢆᅗ  ࡟♧ࡍࠋ࡞࠾㸪㖄┤ศᕸࡣἙཱྀ࠿ࡽ
800 m ᆅⅬࡢ୰ኸ࠿ࡽฟຊࡋࡓࠋ⤒᫬ኚ໬ࡢᵝᏊࡣᅗ  ྠᵝࡢ⤖ᯝࢆ♧ࡋࡓࡀ㸪ᣑᩓಀᩘ࡟ࡼࡿ㐪࠸ࡣぢࡽࢀ࡞࠿ࡗࡓࠋ
ᣑᩓಀᩘ K ࢆ 0㹼100 ࡲ࡛ኚ໬ࡉࡏࡓ㝿ࡢሷศ㖄┤ศᕸࢆᅗ  ࡟♧ࡍࠋィ⟬㛤ጞ࠿ࡽ 1000 s ᫬Ⅼ࡟࠾࠸࡚㸪Ἑཱྀ࠿ࡽ 800 m ᆅⅬࡢ୰ኸ࠿ࡽฟຊࡋࡓࠋᣑᩓಀᩘࢆ୚࠼࡚ࡶ㸪㖄┤ศᕸࡣ࡯࡜ࢇ࡝
ኚ໬ࡋ࡞࠿ࡗࡓࠋࡇࡢࡇ࡜࠿ࡽ㸪ᣑᩓಀᩘࡣሷỈ㐳ୖ࡟ᙳ㡪ࢆ୚࠼࡞࠸࡜⪃࠼ࡽࢀࡿࠋ
6㸬 ⤊ࢃࡾ࡟ ᮏ◊✲࡛ࡣ㸪㞝≀ᕝἙཱྀᇦ࡟࠾࠸࡚⌧ᆅほ ࠾ࡼࡧᩘ್ࢩ࣑࣮ࣗࣞࢩࣙࣥࢆ⾜࠸㸪ሷỈ㐳ୖࡢせᅉࢆ᳨ウࡋࡓࠋ⌧ᆅほ ࡛ࡣ௚ࡢᙅΰྜἙᕝ 2)4)࡜ྠᵝ࡟ሷỈࡢ㌍ᒙࡀ᫂░࡟ぢࡽࢀ㸪እຊࡢᙳ㡪࡜ࡋ࡚ࡣỈ఩ᕪ࡜Ἑཱྀᖜࡀ୍ᐃࡢᙳ㡪ࢆ୚࠼ࡿ࡜⪃࠼ࡽࢀࡿࠋࡲࡓ㸪ᩘ್ࢩ࣑࣮ࣗࣞࢩࣙࣥ࠿ࡽࡣ
Ἴ㧗ࡀ኱ࡁ࡞せᅉࡢ୍ࡘ࡛࠶ࡿࡇ࡜ࡀࢃ࠿ࡗࡓࠋ୍᪉㸪௒ᅇࡢࢩ࣑࣮ࣗࣞࢩ࡛ࣙࣥࡣỈ㊰ࡢἙཱྀᖜࢆᕝᖜ࡟➼ࡋ࠸タᐃ࡛ィ⟬ࡋࡓࡓࡵ㸪ሷỈࡀᕝᖜ࡟ᑐࡋ୍࡚ᵝ࡟☜ㄆࡉࢀࡓࠋ௒ᚋࡣἙཱྀᖜࢆィ⟬᮲௳࡟⤌ࡳ㎸ࢇࡔࢩ࣑࣮ࣗࣞࢩࣙࣥࢆ⾜࠸㸪ヲ⣽࡞᮲௳ࢆ᫂ࡽ࠿࡟ࡋ࡚࠸ࡃࠋ
ㅰ㎡
 ᮏ◊✲ࡢᐇ᪋࡟࠶ࡓࡾ㸪ᅜᅵ஺㏻┬ࡼࡾࢹ࣮ࢱࡢᥦ౪ࢆཷࡅࡓࠋࡇࡇ࡟グࡋ࡚ㅰពࢆ⾲ࡍࡿࠋ
ཧ⪃ᩥ⊩
1)
2)
3)
4)
5)

6)

⚟ᒸᤩ஧㸪⚟ᔱ♸௓㸪Ᏺᒇ⚈୍㸪᪂ᗉ㧗ஂ㸸Ἑཱྀᐦᗘὶࡢὶືᶵᵓ࡜ሷỈࡃࡉࡧࡢἙཱྀ᮲௳㸪ᅵᮌᏛ఍ㄽᩥሗ࿌㞟➨ 327 ྕ㸪pp. 61-71㸪1982㸬ᑠ಴࿴⣖㸪ᐑᓮಇஅ㸪၈⃝ᆂ㸸▼⊁ᕝୗὶ㒊࡟࠾ࡅࡿሷỈ㐳ୖ࡟ࡼࡿ฼Ỉ࡬ࡢᙳ㡪ண ࡟ࡘ࠸࡚, ᖹᡂ 14 ᖺᗘᢏ⾡◊✲Ⓨ⾲఍㸪Ἑ-22㸪pp. 1-8㸪2003.
⚟ᒸᤩ஧㸪ᕷᮧΎ㸪ຍ⸨ಙኵ㸪㧗ᶫ᫭㸪⸨⏣ග୍㸪ຍ㈡㇂ᆒ㸸㜿㈡㔝ᕝ࡟࠾ࡅࡿሷỈ㐳ୖࡢᐇែ㸪➨ 33 ᅇᾏᓊᕤᏛㅮ₇఍ㄽᩥ㞟㸪pp. 596-600㸪1986.
ྡ಴⳹Ꮚ㸪⏣୰ோ㸪ᱵ⏣ಙ㸸⡿௦ᕝ࡟࠾ࡅࡿ෤Ꮨ wave set-up ࡜ሷỈ㐳ୖ࡟㛵ࡍࡿ◊✲㸪ᅵᮌᏛ఍ㄽᩥ㞟 B2(ᾏᓊᕤᏛ)㸪Vol. 66㸪No. 1㸪pp. 316-320㸪2010.
‫‮‬ἑἙᕝᅜ㐨஦ົᡤ㸪⛅⏣Ἑᕝᅜ㐨஦ົᡤ㸪⋢ᕝࢲ࣒⟶⌮ᡤ㸸㞝≀ᕝỈ⣔ῬỈᑐ⟇ᨭ㒊㸦㆙ᡄయไࢆゎ㝖㸧(グ⪅Ⓨ⾲㈨ᩱ) <https://www.thr.mlit.go.jp/bumon/kisya/kisyah/images/76466_1.pdf>(2021/12/11 ࢔ࢡࢭࢫ)᭷㝈఍♫኱᭤タィ஦ົᡤ㸸㞝≀ᕝୗὶỈᩥほ ➼ᴗົ㸦㞝≀ᕝỈ⣔㸧ሷỈ㐳ୖㄪᰝሗ࿌᭩㸪pp.
1-33㸪2020㸬

東北地域災害科学研究81

第58巻（2022）㞝≀ᕝ࡟࠾ࡅࡿฟỈᚋࡢἙཱྀ◁ᕞᅇ᚟࡜Ἴᾉ࢚ࢿࣝࢠ࣮ࡢᙳ㡪ホ౯ 㸨 ⛅⏣኱Ꮫ኱Ꮫ㝔⌮ᕤᏛ◊✲⛉ ㇂ཱྀ㞙ஓ㸪㰻⸨᠇ᑑ㸪Ώ㎶୍ஓ1㸬 ࡣࡌࡵ࡟
㞝≀ᕝἙཱྀ࡟ࡣ◁ᕞࡀᏑᅾࡋ㸪ᾏὒࡸἙᕝ࠿ࡽࡢᙳ㡪ࢆཷࡅ࡚◁ᕞࡀⓎ㐩࡜⦰ᑠࢆ⧞ࡾ㏉ࡋ
࡚࠸ࡿࠋⓎ㐩ࡋࡓ◁ᕞࡣሷỈࡸἼᾉࡢἙᕝෆ࡬ࡢᾐධࢆጉࡆ㸪⯪⯧ࡢ⯟⾜࡟ᙳ㡪ࢆ୚࠼ࡿ 1)࡜
⪃࠼ࡽࢀࡿࠋࡑࡢࡓࡵ㸪◁ᕞࡢ≉ᛶࢆᢕᥱࡍࡿࡇ࡜ࡣἙᕝ⟶⌮࡟࡜ࡗ࡚㔜せ࡛࠶ࡿࠋࡇࢀࡲ࡛㸪ฟỈ᫬࡟Ἀ࡟ὶฟࡋࡓᅵ◁ࡢᅇᖐ㐣⛬ 2)ࡸ㸪Ꮨ⠇ⓗ࡞ኚ໬ 3)ࡀ᫂ࡽ࠿࡟ࡉࢀ࡚࠸ࡿࠋࡋ࠿ࡋ㸪ฟỈᚋࡢ◁ᕞ㠃✚ࡢᅇ᚟㸪Ἑᕝὶ㔞ࡸἼᾉ࡜ࡢ㛵ಀ࡟ࡘ࠸࡚ࡣヲ⣽࡞᳨ウࡀ⾜ࢃࢀ࡚࠸࡞࠸ࠋ
ࡑࡇ࡛ᮏ◊✲࡛ࡣ㸪㞝≀ᕝἙཱྀ◁ᕞ࡟࠾ࡅࡿฟỈᚋࡢ◁ᕞࡢᅇ᚟㸪Ἑᕝὶ㔞ࡸἼᾉ࡜ࡢ㛵ಀࢆ᳨ウࡍࡿࡓࡵ࡟◁ᕞ㠃✚ࡸἙཱྀᖜ࡟ࡘ࠸࡚ࣔࢽࢱࣜࣥࢢࢆ⾜࠸㸪Ἑᕝὶ㔞㸪Ἴᾉ࢚ࢿࣝࢠ࣮
࡜ࡢẚ㍑ࢆ⾜ࡗࡓࠋ2㸬 ᑐ㇟Ἑᕝ࣭ࢹ࣮ࢱࢭࢵࢺ
ᑐ㇟Ἑᕝࡣ㸪⛅⏣┴ࢆὶࢀࡿ୍⣭Ἑᕝࡢ㞝≀ᕝ࡛࠶ࡿࠋ㞝≀ᕝ࠾ࡼࡧほࢹ࣮ࢱࡢᡤᅾࢆᅗ  ࡟♧ࡍࠋἙᕝὶ㔞 Q ࡣᳺᕝほᡤ࡛ 1 ᫬㛫࠾ࡁ㸪᭷⩏Ἴ㧗 H1/3 ࡸἼྥ➼ࡢἼᾉࢹ࣮ࢱࡣ⛅⏣࡛ 20 ศ࠾ࡁ࡟ほࡉࢀࡓࡶࡢࢆ⏝࠸ࡓࠋ࡞࠾㸪ᾏ࠿ࡽ㝣࡟ྥ࠿࠺Ἴᾉ࡟ὀ┠ࡍࡿࡓࡵ㸪໭࠿ࡽ᫬ィᅇࡾ࡟ 0㹼180rࡢࢹ࣮ࢱࡣ㝖࠸࡚࠸ࡿ 4)ࠋἼᾉࢹ࣮ࢱ࠿ࡽ㸪ᘧ(1)㸪ᘧ(2)ࡢࡼ࠺࡟ᓊἈ
᪉ྥ࠾ࡼࡧἢᓊ᪉ྥࡢἈἼ࢚ࢿࣝࢠ࣮ࣇࣛࢵࢡࢫࢆ⟬ฟࡋࡓ 5)ࠋ
‫ܧ‬௙஼ ൌͳଶߩ݃൫‫ܪ‬ଵΤଷ ൯଴ ‫ܥ‬௚଴ ܿ‫ߠݏ݋‬ሺͳሻͳ͸‫ܧ‬௙௅ ൌͳଶߩ݃൫‫ܪ‬ଵΤଷ ൯଴‫ܥ‬௚଴ ‫ߠ݊݅ݏ‬ሺʹሻͳ͸ᅗ  㞝≀ᕝ࠾ࡼࡧほ
࣮ࢱࡢᡤᅾ

ࢹ

ࡇࡇ࡛㸪EfC ࡣᓊἈ᪉ྥࡢἈἼ࢚ࢿࣝࢠ࣮ࣇࣛࢵࢡࢫ㸪
EfL ࡣἢᓊ᪉ྥࡢἈἼ࢚ࢿࣝࢠ࣮ࣇࣛࢵࢡࢫ㸪U ࡣᾏỈᐦᗘ㸪ց ࡣ㔜ຊຍ㏿ᗘ㸪Cց0 ࡣ⩌㏿ᗘ㸪θ ࡣධᑕゅ࡛࠶ࡿࠋධᑕゅ࡜ἈἼ࢚ࢿࣝࢠ࣮ࣇࣛࢵࢡࢫࡢ᪉ྥࡢᐃ⩏ࢆᅗ ࡟♧ࡍࠋ࡞࠾㸪ἢᓊ᪉ྥࡢἈἼ࢚ࢿࣝࢠ࣮ࣇࣛࢵࢡࢫ࡟
ࡘ࠸࡚㸪ṇ࡛࠶ࡿሙྜࡣ༡࠿ࡽ໭࡬㸪㈇࡛࠶ࡿሙྜࡣ໭
࠿ࡽ༡࡬ࡢἼྥࡁ࡛࠶ࡿࡇ࡜ࢆ♧ࡋ࡚࠸ࡿࠋ
3㸬 ◊✲ᡭἲ
ࡲࡎ᪤ ◊✲ 6)࡟ೌ࠸㸪UAV ࡟ࡼࡾୖ✵ 150 m ࠿ࡽ㖄┤᪉ྥ࡟⦪ᶓ 80 %࣮࢜ࣂ࣮ࣛࢵࣉ࡛෗┿ࢆ᧜ᙳࡋࡓࠋᅗ  ධᑕゅ࡜ἈἼ࢚ࢿࣝࢠ࣮ࣇࣛ
ࢵࢡࢫࡢ᪉ྥࡢᐃ⩏*Evaluation of Wave Energy Influence for Recovery of River Mouth Sandbar at Omono River by Junya
Taniguchi, Noritoshi Saito and Kazuya Watanabe

82ḟ࡟㸪᧜ᙳࡉࢀࡓ෗┿࡟ࡘ࠸࡚ SfM ฎ⌮ࢆ᪋ࡋ㸪Ἑཱྀ◁ᕞࢆ᚟ඖࡋࡓࠋ᚟ඖᚋࡢ◁ᕞࢆᅗ ࡟♧ࡍࠋ᚟ඖࡉࢀࡓ◁ᕞ࠿ࡽἙཱྀᖜ B㸪◁ᕞ㠃✚ A㸪ྑᓊ◁ᕞ㠃✚ AR㸪ᕥᓊ◁ᕞ㠃✚ AL ࢆ⟬ฟࡋࡓࠋ◁ᕞ㠃✚ࡣ㸪Ἑཱྀ㒊࡟࠾࠸࡚ኚືࡀ᭱ࡶ኱ࡁ࠸࡜⪃࠼ࡽࢀࡿ㡿ᇦ࡜ࡋࡓࠋ࡞࠾㸪᪥ᮏᾏഃ࡟࠾ࡅࡿ₻ᕪࡣᑠࡉ࠸ࡇ࡜࠿ࡽ㸪◁ᕞ㠃✚ࢆ⟬ฟࡍࡿ㝿ࡢ₻఩⿵ṇࡣ⾜ࡗ࡚࠸࡞࠸ 7)ࠋ
ࡑࡋ࡚㸪ฟỈᚋࡢ◁ᕞ㠃✚ࡢኚ໬㸪◁ᕞ㠃✚ࡸἙཱྀᖜ࡜Ἑᕝὶ㔞㸪ἈἼ࢚ࢿࣝࢠ࣮ࣇࣛࢵࢡ
ࢫࡢ㛵ಀ࡟ࡘ࠸᳨࡚ウࢆ⾜ࡗࡓࠋ4㸬㸬 ᳨ウ⤖ᯝ
(1) Ἑᕝὶ㔞࣭ἈἼ࢚ࢿࣝࢠ࣮ࣇࣛࢵࢡࢫ
2017 ᖺ࠿ࡽ 2020 ᖺ࡟࠾ࡅࡿἙᕝὶ㔞࣭ᓊἈ᪉ྥࡢἈἼ࢚ࢿࣝࢠ࣮ࣇࣛࢵࢡࢫ࣭ἢᓊ᪉ྥࡢ
ἈἼ࢚ࢿࣝࢠ࣮ࣇࣛࢵࢡࢫࢆᅗ  ࡟♧ࡍࠋἙᕝὶ㔞ࡣ 1 ᫬㛫ẖ㸪ἈἼ࢚ࢿࣝࢠ࣮ࣇࣛࢵࢡࢫࡣ
24 ᫬㛫ᖹᆒࡋ࡚⏝࠸ࡓࠋἙᕝὶ㔞ࡣẖᖺ㸪᫓Ꮨ࡟⼥㞷ฟỈ࡟ࡼࡗ࡚ 700㹼1500
m3/s ⛬ᗘࡲ࡛ቑຍࡋ㸪ኟᏘ࣭⛅Ꮨࡣ㇦㞵ࡸྎ㢼࡟ࡼࡗ୍࡚᫬ⓗ࡟኱ࡁࡃቑຍࡋࡓࠋ୍᪉࡛㸪෤Ꮨࡣ 1 ᖺࡢ୰࡛᭱
ࡶῶᑡࡋࡓࠋ
ἈἼ࢚ࢿࣝࢠ࣮ࣇࣛࢵࢡࢫࡣ㸪Ꮨ⠇࡟㛵ࢃࡽࡎἢᓊ᪉
ྥࡼࡾᓊἈ᪉ྥࡀ༟㉺ࡋ࡚࠾ࡾ㸪ἢᓊ᪉ྥࡢἈἼ࢚ࢿࣝ
ࢠ࣮ࣇࣛࢵࢡࢫࡣ໭㐍᪉ྥࡀ༟㉺ࡋ࡚࠸ࡿࡇ࡜ࡀศ࠿
ࡗࡓࠋ෤Ꮨ࡟ࡣᓊἈ᪉ྥ㸪ἢᓊ᪉ྥ࡜ࡶ࡟᭱ࡶᙉࡃ࡞ࡗᅗ  ᚟ඖࡋࡓ◁ᕞࡓࡀ㸪す㧗ᮾపࡢ෤ᆺࡢẼᅽ㓄⨨࡟ࡼࡾ⏕ࡌࡓᙉ࠸Ꮨ⠇෤Ꮨ

Q(m3/s)

4000
3000
2000
1000

EfC(N/s)

0
80
60
40
20

EfL(N/s)

0
40

໭㐍

20
0
-20
-40

༡㐍
2017

2018

year

2019

ᅗ  Ἑᕝὶ㔞㸪ᓊἈ᪉ྥ࣭ἢᓊ᪉ྥࡢἈἼ࢚ࢿࣝࢠ࣮ࣇࣛࢵࢡࢫ

2020

83

E  2018 ᖺD  2017 ᖺG  2020 ᖺF  2019 ᖺᅗ  Ἑཱྀ◁ᕞࡢᆅᙧኚ໬

㢼࡟ࡼࡗ࡚ἼᾉࡀⓎ㐩ࡋ 8)㸪ἈἼ࢚ࢿࣝࢠ࣮ࣇࣛࢵࢡࢫࡀᙉࡃ࡞ࡗࡓ࡜⪃࠼ࡽࢀࡿࠋࡑࡢᚋ㸪᫓Ꮨ࠿ࡽኟᏘ࡟࠿ࡅ࡚ᙅࡲࡾ㸪⛅Ꮨ࠿ࡽ෤Ꮨ࡟࠿ࡅ࡚ᙉࡃ࡞ࡿഴྥࡀ☜ㄆࡉࢀࡓࠋ
(2) Ἑཱྀ◁ᕞࡢᆅᙧኚ໬
2017 ᖺ࠿ࡽ 2020 ᖺ࡟࠾ࡅࡿἙཱྀ◁ᕞࡢᆅᙧኚ໬ࢆᅗ  ࡟♧ࡍࠋ෤Ꮨ࡟ὀ┠ࡍࡿ࡜㸪୧ᓊࡢ◁ᕞࡀⓎ㐩ࡋ㸪ྑᓊ࠿ࡽ༡࡟ྥࡅ࡚◁ნࡀᙧᡂࡉࢀ࡚࠸ࡿࠋᅗ  ࡼࡾ㸪෤Ꮨ࡟Ἑᕝὶ㔞ࡣ᭱ࡶῶᑡࡋ㸪ἈἼ࢚ࢿࣝࢠ࣮ࣇࣛࢵࢡࢫࡣ᭱ࡶᙉ࠸ࠋࡇࡢࡇ࡜࠿ࡽ㸪Ἑᕝὶ࡜ἼᾉࡀἙཱྀࡢἈഃ࡟
࠾࠸࡚ᆒ⾮ࡋࡓࡇ࡜࡟ࡼࡾ㸪Ἴᾉ࡟ࡼࡗ࡚Ἀ࠿ࡽἙཱྀ࡟㍺㏦ࡉࢀࡓᅵ◁ࡀἙཱྀἈഃ࡟ሁ✚ࡋࡓ࡜⪃࠼ࡽࢀࡿࠋ
᫓Ꮨ࡟ࡣ㸪⼥㞷ฟỈ࡟ࡼࡗ࡚Ἑᕝὶ㔞ࡀቑຍࡋ㸪ἈἼ࢚ࢿࣝࢠ࣮ࣇࣛࢵࢡࢫࡣᙅࡲࡗࡓࠋࡑ
ࡢࡓࡵ㸪෤Ꮨ࡟ྑᓊ࡟ᙧᡂࡉࢀ࡚࠸ࡓ༡ྥࡁࡢ◁ნࡣ⦰ᑠࡲࡓࡣᾘኻࡋ㸪Ἑཱྀᖜࡣᣑ኱ࡋࡓࠋ
ኟᏘ࣭⛅Ꮨ࡟ࡣ㸪Ἑᕝὶ㔞ࡀ୍᫬ⓗ࡟኱ࡁࡃቑຍࡍࡿࡇ࡜ࡀ࠶ࡗࡓࡓࡵ㸪◁ᕞࡣ⦰ᑠࡋ㸪Ἑཱྀᖜࡣࡉࡽ࡟ᣑ኱ࡋࡓࠋ᫓Ꮨ࠿ࡽ⛅Ꮨ࡟࠾ࡅࡿᕥᓊ࡟ὀ┠ࡍࡿ࡜㸪༡࠿ࡽ໭࡟ྥࡅ࡚◁ᕞࡀⓎ㐩㸪ࡲࡓࡣ✺㉳ࡀ⛣ືࡋ࡚࠸ࡿࡇ࡜ࡀศ࠿ࡿࠋἈἼ࢚ࢿࣝࢠ࣮ࣇࣛࢵࢡࢫࡣ໭㐍᪉ྥ࡬ࡢᙳ㡪ࡀᙉ࠸ࡇ࡜࠿ࡽ㸪Ἴᾉ࡟ࡼࡗ࡚༡᪉࠿ࡽᅵ◁ࡀ㍺㏦࣭ሁ✚ࡉࢀ࡚Ⓨ㐩ࡋࡓ࡜⪃࠼ࡽࢀࡿࠋ
ố⥺࡟ࡘ࠸࡚㸪୧ᓊ࡜ࡶ▷ᮇⓗ࡟๓㐍ࡲࡓࡣᚋ㏥ࢆ⧞ࡾ㏉ࡋ࡚࠾ࡾ㸪Ꮨ⠇࡜ࡢ㛵ಀᛶࡣ☜ㄆ࡛ࡁ࡞࠿ࡗࡓࠋ

84

250

80000

200

60000

150

40000
20000

AR, AL(m²)

0
50000
40000
30000

B(m)

A(m²)

෤Ꮨ
100000

100

A
B

50
0

AR
AR
AL
AL

20000
10000
0

2017

2018

2019

2020

year

ᅗ  ◁ᕞ㠃✚㸪Ἑཱྀᖜ㸪ྑᓊ◁ᕞ㠃✚㸪ᕥᓊ◁ᕞ㠃✚ࡢኚ໬(3)
 ◁ᕞ㠃✚࡜Ἑཱྀᖜࡢኚ໬

70000
60000

ࡢኚ໬㸪ྑᓊ◁ᕞ㠃✚㸪ᕥᓊ◁ᕞ㠃✚ࡢኚ໬ࢆᅗ

50000

 ࡟♧ࡍࠋ◁ᕞ㠃✚ࡣ෤Ꮨ࡟᭱኱㸪ኟᏘࡲࡓࡣ⛅40000

Ꮨ࡟᭱ᑠ࡜࡞ࡾ㸪Ἑཱྀᖜࡣ෤Ꮨ࡟᭱ᑠ㸪ኟᏘࡲࡓA(m²)

2017 ᖺ࠿ࡽ 2020 ᖺ࡟࠾ࡅࡿ◁ᕞ㠃✚㸪Ἑཱྀᖜ

30000

ࡣ⛅Ꮨ࡟᭱኱࡜࡞ࡗࡓࠋࡇࡢࡇ࡜࠿ࡽ㸪᫓Ꮨ࠿ࡽ

20000⛅Ꮨ࡟࠾ࡅࡿἙᕝὶ㔞ࡢቑຍ࡟క࠸㸪◁ᕞ࠿ࡽ10000ᅵ◁ࡀὶฟࡍࡿࡇ࡜࡛◁ᕞ㠃✚ࡀῶᑡࡋ㸪Ἑཱྀ0ᖜࡀቑຍࡍࡿࠋ୍᪉㸪⛅Ꮨ࠿ࡽ෤Ꮨ࡟࠿ࡅ࡚Ἴᾉ
࡟ࡼࡾᅵ◁ࡀἙཱྀ࡟㍺㏦࣭ሁ✚ࡍࡿࡇ࡜࡛◁ᕞ㠃✚ࡀቑຍࡋ㸪Ἑཱྀᖜࡀῶᑡࡍࡿ࡜⪃࠼ࡽࢀࡿࠋ

2017/7/24(Q=3902m³/s)
2017/8/25(Q=2716m³/s)
2018/5/19(Q=2904m³/s)
2019/10/13(Q=1641m³/s)

0

30

60

90
day

120

150

180

ᅗ  ◁ᕞ㠃✚ࡢᅇ᚟ྑᓊ◁ᕞ㠃✚࡜ᕥᓊ◁ᕞ㠃✚ࢆẚ㍑ࡍࡿ࡜㸪ྑᓊࡣᕥᓊࡼࡾኚ໬ࡀ኱ࡁ࠸ࡇ࡜ࡀศ࠿ࡿࠋࡲ
ࡓ㸪ྑᓊࡣ෤Ꮨ࡟᭱኱࡜࡞ࡾ㸪ኟᏘࡲࡓࡣ⛅Ꮨ࡟᭱ᑠ࡜࡞ࡿࡇ࡜࠿ࡽᏘ⠇ⓗ࡞ഴྥࢆ☜ㄆ࡛ࡁࡓࡀ㸪ᕥᓊ࡛ࡣ࠶ࡲࡾ☜ㄆ࡛ࡁ࡞࠿ࡗࡓࠋࡇࢀࡣ㸪ᕥᓊ◁ᕞࡢἈഃ࡟ேᕤ࣮ࣜࣇ 9)ࡀタ⨨ࡉࢀ࡚㸪ᅵ◁ࡢ⛣ືࡀᢚไࡉࢀ࡚࠸ࡿ࡜⪃࠼ࡽࢀࡿࠋᚑࡗ࡚㸪Ἑཱྀ◁ᕞࡢ⟶⌮࡟ࡣ㸪ྑᓊ◁ᕞࡀ㔜せ࡛࠶ࡿ࡜⪃࠼ࡽࢀࡿࠋ
(4) Ἑཱྀ◁ᕞࡢᅇ᚟
Ἑᕝὶ㔞ࡀ 1500 m3/s ࢆ㉺࠼ࡓሙྜࢆฟỈ࡜ࡳ࡞ࡋ㸪ࡑࡢᚋࡢ◁ᕞ㠃✚ࡢኚ໬࠿ࡽ◁ᕞࡢᅇ᚟࡟ࡘ࠸᳨࡚ウࢆ⾜ࡗࡓࠋฟỈᚋࡢ◁ᕞ㠃✚ࡢኚ໬ࢆᅗ  ࡟♧ࡍࠋฟỈ᫬㸪Ἑᕝὶ㔞ࡀ᭱኱࡜࡞ࡗࡓ᪥ࢆ 0 ᪥㸪ฟỈ┤ᚋࡢほ᪥࡟࠾ࡅࡿ◁ᕞ㠃✚ࢆ 0 m3 ࡜ࡋࡓࠋซ౛࡟ࡣ㸪ฟỈࡀⓎ⏕ࡋࡓ᪥࡜Ἑᕝὶ㔞ࡢ᭱኱್ࢆ♧ࡋ࡚࠸ࡿࠋ◁ᕞ㠃✚ࡣฟỈ┤ᚋ࡟ᛴ⃭࡟ቑຍࡍࡿࡇ࡜ࡣ࡞ࡃ㸪⣙60 ᪥ᚋࡲ࡛⦆ࡸ࠿࡟ቑຍࡍࡿഴྥࡀ࠶ࡗࡓࠋࡋ࠿ࡋ㸪2017/8/25㸪2019/10/13 ࡢฟỈᚋ࡟╔┠ࡍࡿ࡜㸪⣙ 90 ᪥ࢆ㐣ࡂ࡚࠿ࡽ◁ᕞ㠃✚ࡣᛴ⃭࡟ቑຍࡋࡓࠋฟỈࡀⓎ⏕ࡋࡓࡢࡣ㸪8 ᭶ࡲࡓࡣ 10᭶࡛࠶ࡾ㸪3 ࣧ᭶ᚋࡣ෤Ꮨ㡭࡜࡞ࡿࡓࡵ㸪Ἴᾉ࢚ࢿࣝࢠ࣮ࣇࣛࢵࢡࢫࡀᙉࡃ࡞ࡿࠋࡑࡢࡓࡵ㸪

1500

1500

1000

1000
dA/dt(m2/day)dA/dt(m2/day)

85

500
0
-500
᫓Ꮨ
⛅Ꮨ

-1000
-1500
0

2

4

6
8
EfC(N/s)

10

ኟᏘ
෤Ꮨ
12

500
0
-500
-1000
-1500

᫓Ꮨ
⛅Ꮨ

ኟᏘ
෤Ꮨ

-2

-1

-3

14

0
EfL(N/s)

1

2

3

4
3
2
1
0
-1
-2
-3
-4
0

2

4

6
8
EfC(N/s)

᫓Ꮨ
⛅Ꮨ

ኟᏘ
෤Ꮨ

10

12

dB/dt(m/day)dB/dt(m/day)ᅗ  1 ᪥࠶ࡓࡾࡢ◁ᕞ㠃✚ࡢኚ໬㔞࡜ᓊἈ࣭ἢᓊ᪉ྥࡢἈἼ࢚ࢿࣝࢠ࣮ࣇࣛࢵࢡࢫࡢ㛵ಀ

14

4
3
2
1
0
-1
-2
-3
-4
-3

᫓Ꮨ
⛅Ꮨ

ኟᏘ
෤Ꮨ

-2

-1

0
1
EfL(N/s)23ᅗ  1 ᪥࠶ࡓࡾࡢἙཱྀᖜࡢኚ໬㔞࡜ᓊἈ࣭ἢᓊ᪉ྥࡢἈἼ࢚ࢿࣝࢠ࣮ࣇࣛࢵࢡࢫࡢ㛵ಀฟỈ࡟ࡼࡾἈ࡟ὶฟࡋࡓ኱㔞ࡢᅵ◁ࡀ㸪෤Ꮨࡢ㧗Ἴᾉ࡟ࡼࡗ࡚Ἑཱྀ࡟㍺㏦࣭ሁ✚ࡉࢀࡿࡇ࡜࡛㸪◁ᕞ㠃✚ࡀᛴ⃭࡟ቑຍࡋࡓ࡜⪃࠼ࡽࢀࡿࠋ(5)
 ◁ᕞ㠃✚࣭Ἑཱྀᖜ࡜࢚ࢿࣝࢠ࣮ࣇࣛࢵࢡࢫࡢ㛵ಀほ㛫࡟࠾ࡅࡿ 1 ᪥࠶ࡓࡾࡢ◁ᕞ㠃✚ࡢኚ໬㔞࡜ᓊἈ᪉ྥࡢἈἼ࢚ࢿࣝࢠ࣮ࣇࣛࢵࢡࢫࡢᖹ

ᆒ್ EfCAve㸪ἢᓊ᪉ྥࡢἈἼ࢚ࢿࣝࢠ࣮ࣇࣛࢵࢡࢫࡢᖹᆒ್ EfLAve ࡢ㛵ಀࢆᅗ 㸪1 ᪥࠶ࡓࡾࡢ
Ἑཱྀᖜࡢኚ໬㔞࡜ᓊἈ᪉ྥ࣭ἢᓊ᪉ྥࡢἈἼ࢚ࢿࣝࢠ࣮ࣇࣛࢵࢡࢫࡢ㛵ಀࢆᅗ  ࡟♧ࡍࠋ◁ᕞ㠃✚㸪Ἑཱྀᖜ࡟ᑐࡋ࡚㸪ᓊἈ᪉ྥࡢἼᾉࡢᙳ㡪ࡀ༟㉺ࡋ࡚࠸ࡿࡀ㸪ἈἼ࢚ࢿࣝࢠ࣮ࣇࣛ
ࢵࢡࢫࡀᙉࡃ࡞ࡿࡇ࡜࡛◁ᕞ㠃✚ࡀቑຍࡍࡿ㸪ࡲࡓࡣἙཱྀᖜࡀ⦰ᑠࡍࡿ࡜࠸ࡗࡓഴྥࡣ☜ㄆ࡛ࡁ࡞࠿ࡗࡓࠋ୍᪉࡛Ꮨ⠇࡟╔┠ࡍࡿ࡜㸪෤Ꮨ࡟◁ᕞ㠃✚ࡣቑຍ㸪Ἑཱྀᖜࡣ⦰ᑠࡍࡿഴྥࡀ☜ㄆ࡛ࡁࡓࠋࡇࢀࡣ㸪⛅Ꮨ࠿ࡽ෤Ꮨ࡟࠿ࡅ࡚ἈἼ࢚ࢿࣝࢠ࣮ࣇࣛࢵࢡࢫࡀᙉࡃ࡞ࡾ㸪෤Ꮨ࡟ࡣἙᕝ
ὶ㔞ࡀ኱ࡁࡃቑຍࡍࡿࡇ࡜ࡀ࡞ࡃ࡞ࡿࡓࡵ㸪◁ᕞ࠿ࡽᅵ◁ࡀὶฟࡍࡿࡇ࡜࡞ࡃ㸪Ἀ࠿ࡽᅵ◁ࡀሁ✚ࡉࢀ⥆ࡅࡓࡇ࡜ࡀせᅉ࡛࠶ࡿ࡜⪃࠼ࡽࢀࡿࠋ
(6) ᅇᖐศᯒ
◁ᕞ࡜ἈἼ࢚ࢿࣝࢠ࣮ࣇࣛࢵࢡࢫ㸪Ἑᕝὶ㔞ࡢ㛵ಀࢆ᳨ウࡍࡿࡓࡵ࡟㸪◁ᕞ㠃✚㸪ᕥᓊ◁ᕞ㠃✚㸪ྑᓊ◁ᕞ㠃✚㸪Ἑཱྀᖜࢆ┠ⓗኚᩘ㸪ἈἼ࢚ࢿࣝࢠ࣮ࣇࣛࢵࢡࢫ࡜Ἑᕝὶ㔞ࢆㄝ᫂ኚᩘ࡜
ࡋ࡚㔜ᅇᖐศᯒࢆ⾜ࡗࡓࠋ᪤ ◊✲ 10)࡟ೌ࠸㸪ἈἼ࢚ࢿࣝࢠ࣮ࣇࣛࢵࢡࢫࡣほ࡟࠾ࡅࡿᖹᆒ್㸪Ἑᕝὶ㔞ࡣほ᪥๓ 1 ࣧ᭶㛫᪥๓ 1 ࣧ᭶㛫࡟࠾ࡅࡿ᭱኱್ࢆ⏝࠸ࡓࠋ◁ᕞ㠃✚㸪ᕥᓊ◁ᕞ㠃✚㸪ྑᓊ◁ᕞ㠃✚㸪Ἑཱྀᖜ࡜㸪ᓊἈ᪉ྥ࣭ἢᓊ᪉ྥࡢἈἼ࢚ࢿࣝࢠ࣮ࣇࣛࢵࢡࢫ㸪Ἑᕝὶ㔞

86ࡢ㔜┦㛵ಀᩘ R ࢆ⾲  ࡟♧ࡍࠋ⤖ᯝ㸪ᓊἈ᪉ྥ㸪⾲  㔜ᅇᖐศᯒ⤖ᯝἢᓊ᪉ྥ࡟㛵ࢃࡽࡎ㸪ἈἼ࢚ࢿࣝࢠ࣮ࣇࣛࢵࢡࢫ㸪Ἑᕝὶ㔞࡜ࡢ┦㛵ࡀ᭱ࡶᙉ࠸ࢹ࣮ࢱࡣἙཱྀᖜ࡛࠶
ࡾ㸪ᕥᓊ◁ᕞ㠃✚ࡣ᭱ࡶᙅ࠸ࡇ࡜ࡀศ࠿ࡗࡓࠋࡇ
ࡢࡇ࡜࠿ࡽ㸪㞝≀ᕝἙཱྀ◁ᕞ࡟ࡘ࠸᳨࡚ウࢆ⾜࠺ሙྜ㸪◁ᕞ㠃✚ࡼࡾἙཱྀᖜࢆ⏝࠸ࡿࡇ࡜ࡀ㐺ษ࡛࠶ࡿ࡜⪃࠼ࡽࢀࡿࠋࡲࡓ㸪ᕥᓊ◁ᕞ㠃✚ࡣᓊἈ᪉ྥࡢἈἼ࢚ࢿࣝࢠ࣮ࣇࣛࢵࢡࢫࡼࡾἢᓊ᪉ྥࡢἈ
Ἴ࢚ࢿࣝࢠ࣮ࣇࣛࢵࢡࢫ࡜ࡢ᪉ࡀ㸪┦㛵ࡀᙉ࠸ࠋἢᓊ᪉ྥࡢἈἼ࢚ࢿࣝࢠ࣮ࣇࣛࢵࢡࢫࡣ໭㐍᪉ྥࡀ༟㉺ࡋ࡚࠸ࡿࡇ࡜࠿ࡽ㸪Ἴᾉ࡟ࡼࡗ࡚༡᪉࠿ࡽᅵ◁ࡀ㍺㏦ࡉࢀ࡚ᕥᓊ◁ᕞ࡟ሁ✚ࡍࡿࠋࡋ࠿ࡋ㸪ᕥᓊ◁ᕞἈ࡟ࡣேᕤ࣮ࣜࣇࡀタ⨨ࡉࢀ࡚࠾ࡾ㸪ᓊἈ᪉ྥࡢᅵ◁ࡢ⛣ືࡣᢚไࡉࢀ࡚࠸
ࡿࠋࡇࢀࡽࡢ⌮⏤࡟ࡼࡾ㸪ᓊἈ᪉ྥࡢἈἼ࢚ࢿࣝࢠ࣮ࣇࣛࢵࢡࢫࡼࡾ㸪ἢᓊ᪉ྥࡢἈἼ࢚ࢿࣝ
ࢠ࣮ࣇࣛࢵࢡࢫ࡜ࡢ᪉ࡀ㸪┦㛵ࡀᙉࡃ࡞ࡗࡓ࡜⪃࠼ࡽࢀࡿࠋ
5㸬
㸬 ࠾ࢃࡾ࡟
ᮏ◊✲࡛ࡣ㸪㞝≀ᕝࡢἙཱྀ◁ᕞࢆᑐ㇟࡟㸪◁ᕞ㠃✚ࡸἙཱྀᖜ࡟ࡘ࠸࡚ࣔࢽࢱࣜࣥࢢࢆ⾜࠸㸪ฟỈᚋࡢ◁ᕞࡢᅇ᚟ࡸ㸪Ἑᕝὶ㔞࣭Ἴᾉ࢚ࢿࣝࢠ࣮࡜ࡢ㛵ಀ࡟ࡘ࠸᳨࡚ウࢆ⾜ࡗࡓࠋz෤Ꮨ࡟ἈἼ࢚ࢿࣝࢠ࣮ࣇࣛࢵࢡࢫࡀᙉࡲࡿࡇ࡜࡟ࡼࡾ㸪Ἀ࠿ࡽ኱㔞ࡢᅵ◁ࡀ㍺㏦㸪ሁ✚ࡉࢀࡿࡇ࡜࡛Ἑཱྀ◁ᕞࡀᛴ⃭࡟Ⓨ㐩ࡍࡿ࡜⪃࠼ࡽࢀࡿࠋzἙཱྀ◁ᕞࡣ㸪ἢᓊ᪉ྥࡼࡾࡶᓊἈ᪉ྥࡢἼᾉࢆᙉࡃཷࡅ࡚࠸ࡿ࡜⪃࠼ࡽࢀࡿࠋ≉࡟㸪෤Ꮨ࡟◁ᕞ㠃✚ࡣቑຍࡋ㸪Ἑཱྀᖜࡣ⦰ᑠࡍࡿഴྥࡀ☜ㄆࡉࢀࡓࠋz㞝≀ᕝἙཱྀ◁ᕞ࡟ࡘ࠸᳨࡚ウࢆ⾜࠺ሙྜ㸪◁ᕞ㠃✚ࡼࡾἙཱྀᖜࡢࢹ࣮ࢱࢆ⏝࠸ࡿࡇ࡜ࡀ㐺ษ࡛࠶ࡿ࡜⪃࠼ࡽࢀࡿࠋ

ཧ⪃ᩥ⊩
1)

๓ᕝ຾ᮁ㸪௒ ῟㸸㉥ᕝἙཱྀ◁ᕞࡢኚᙧ࡟ࡘ࠸࡚㸪ᒣᙧ኱Ꮫ⣖せ㸦㎰Ꮫ㸧㸪➨ 11 ᕳ㸪➨ 4 ྕ㸪
pp. 891-898, 1993.
2) Ώ㎶୍ஓ㸪Dinh Van Duy㸪㔝ཱྀⰋဢ㸪⏣୰ ோ㸸Ἑཱྀࢸࣛࢫࡢᙧᡂ࡜ሁ✚ᅵ◁ࡢᅇᖐ㐣⛬࡟㛵ࡍࡿ◊✲㸪ᅵᮌᏛ఍ㄽᩥ㞟 B2㸦ᾏᓊᕤᏛ㸧㸪Vol. 74, No. 2, Ⅰ_787-Ⅰ_792, 2018.
3) ㇂ཱྀ㞙ஓ㸪Ώ㎶୍ஓ㸪㰻⸨᠇ᑑ㸸㞝≀ᕝ࡟࠾ࡅࡿἙཱྀ◁ᕞࡢືែ࡜ὶ㔞࣭Ἴᾉ࡜ࡢ㛵ಀ㸪ᅵᮌᏛ఍ㄽᩥ㞟 B2㸦ᾏᓊᕤᏛ㸧, Vol. 77, No. 2, Ⅰ_529-Ⅰ_534, 2021.
4) 㘽୺ె㣕㸪ᯇ෠ⱥኵ㸸⛅⏣┴༡㒊ᾏᓊ࡟࠾ࡅࡿố⥺఩⨨ኚ໬ືྥ࡜ᾏᇦᵓ㐀≀つᶍࡢ㛵ಀ࡟㛵ࡍࡿᐇド◊✲, ᮾ໭ᆅᇦ⅏ᐖ⛉Ꮫ◊✲, ➨ 53 ᕳ㸪pp. 47-52, 2017.
5) 㕥ᮌᓫஅ, ᰩᒣၿ᫛㸸ố⥺఩⨨ࡢ㛗࿘ᮇኚື≉ᛶ࠾ࡼࡧố⥺఩⨨ኚືࡢኚ໬㔞࡟ཬࡰࡍἈἼ࢚
ࢿࣝࢠ࣮ࣇࣛࢵࢡࢫ࡜ἢᓊὶ㏿ࡢᙳ㡪,‴✵ ᢏ⾡◊✲ᡤሗ࿌, ➨ 47 ᕳ, ➨ 3 ྕ, pp. 3-31,
2008.
6) ⸨⃝ᑦ▮, Ώ㎶୍ஓ, 㰻⸨᠇ᑑ, ᳜ᮌὯኴ㶺㸸㤿ሙ┠ᕝࢆᑐ㇟࡜ࡋࡓἙ㐨ෆ◁ᕞࡢᣲື࡟㛵ࡍࡿ᳨ウ㸪ᅵᮌᏛ఍ㄽᩥ㞟 G㸦⎔ቃ㸧, Vol. 75, No. 5, Ⅰ_275-Ⅰ_280, 2019.
7) ᯇ෠ⱥኵ㸪㔠ග⣖௦ኴ㸪ᐩᶔᏹ஧㸸⛅⏣┴༡㒊ᾏᓊ࡟࠾ࡅࡿố⥺఩⨨ኚ໬ࡢᇶ♏ⓗ᳨ウ㸪ᾏᓊᕤᏛㄽᩥ㞟, ➨ 47 ᕳ, pp. 666-670, 2000.
8) ᓥ㇂௵ඞ㸪➲ᮏ ㄔ㸪➟஭ኴᚿ㸪኱ሙᏕྖ㸪ᕸໃὈ἞㸪ሜ ⱱᶞ㸸⡿௦ᕝࡢἙཱྀኚື≉ᛶ㸪ᾏᓊᕤᏛㄽᩥ㞟㸪➨ 44 ᕳ pp. 571-575, 1997.
9) ᅜᅵ஺㏻┬ᮾ໭ᆅ᪉ᩚഛᒁ㸸㞝≀ᕝỈ⣔Ἑᕝᩚഛィ⏬㸦኱⮧⟶⌮༊㛫㸧, ᅜᅵ஺㏻┬, 161p., 2018㸬10) Ώ㎶୍ஓ㸪ᇼ஭ඃ௓㸸⡿௦ᕝἙཱྀ◁ᕞᆅᙧኚື࡟ᑐࡍࡿὶ㔞࣭Ἴᾉࡢᙳ㡪ホ౯㸪ᅵᮌᏛ఍ㄽᩥ
㞟(ᾏᓊᕤᏛ), Vol. 75, No. 2, Ⅰ_193-Ⅰ_198, 2019.

東北地域災害科学研究87

第58巻（2022）ᖹ㠃࣭㖄┤᪉ྥ࡟࠾ࡅࡿἙᗋᮦᩱࡢ⢏ᗘศᕸ࡟㛵ࡍࡿ᳨ウ *⛅⏣኱Ꮫ⌮ᕤᏛ㒊 ⮬ぢᑑᏕ⛅⏣኱Ꮫ኱Ꮫ㝔⌮ᕤᏛ◊✲⛉ ㇂ཱྀ㞙ஓ࣭㰻⸨᠇ᑑ࣭Ώ㎶୍ஓ1㸬 ࡣࡌࡵ࡟
㏆ᖺ㸪඲ᅜ࡛ྎ㢼࡞࡝ࡢ኱㞵࡟క࠺Ἑᕝὶ㔞ࡢቑຍ࡟ࡼࡾὥỈ⿕ᐖࡀከⓎࡋ࡚࠾ࡾ㸪Ἑᕝィ࡟࠾࠸࡚Ἑᗋᮦᩱࡢ⢏ᗘศᕸࡢᢕᥱࡣ㔜せ࡞せ⣲ 1)࡜࡞ࡗ࡚࠸ࡿࠋࡑࡇ࡛㸪⏬ࡸᅵ◁ὶฟண

ⰱ⏣ࡽ 2)ࡣΰྜ◁࠿ࡽ࡞ࡿ⺬⾜ὶ㊰ࡢἙᗋኚືཬࡧ⢏ᗘศᕸࡢண
ᥦ᱌ࡋ㸪Ụ⸨ࡽ 3)ࡣἙᗋኚື࡜ᅵ◁཰ᨭ࡟㛵ࡍࡿண࡟㛵ࡍࡿᩘ್ゎᯒࣔࢹࣝࢆἲࢆ᳨ウࡋࡓࠋࡑࡋ࡚㸪୰ᕝࡽ 4)ࡣᅵ◁ࡢ᥇ྲྀሙᡤࢆ 1 ⟠ᡤ࡟㝈ᐃࡋ㸪῝ࡉ᪉ྥࡢ⢏ᗘศᕸ࡟ࡘ࠸࡚ࡶ᳨ウࢆ⾜ࡗࡓࠋࡋ࠿ࡋ㸪ᩘ್ィ⟬࡞࡝࡛⪃៖ࡉࢀࡿ⢏ᚄࡣ⾲ᒙࡢࡳࢆᑐ㇟࡜ࡋࡓሙྜࡀከࡃ㸪῝ࡉ᪉ྥࡢ᳨ウࡣ࠶ࡲࡾ⾜ࢃࢀ࡚࠸࡞࠸ࠋ ᮏ◊✲࡛ࡣ㸪⛅⏣┴ࡢ஧⣭Ἑᕝ࡛࠶ࡿ㤿ሙ┠ᕝࡢ୰ὶᇦࢆᑐ㇟࡜ࡋ㸪◁ᕞୖࡢ」ᩘࡢ⟠ᡤ࠿ࡽࡢᅵ◁᥇ྲྀࢆ⾜ࡗ࡚⢏ᗘศᯒࢆ⾜ࡗࡓࠋࡑࡋ࡚㸪ศᯒ⤖ᯝࢆࡶ࡜࡟Ἑᗋኚືィ⟬ࢆ⾜ࡗࡓࠋ2㸬 ◊✲ᑐ㇟࠾ࡼࡧ⢏ᗘศᯒ᪉ἲᅗ  ࡟◊✲ᑐ㇟ࢆ♧ࡍࠋ◁ᕞୖࡢ St.1~6 ࠿ࡽᅵ◁ࢆ᥇ྲྀࡋ㸪῝ࡉ 30 cm㸪50 cm㸪70 cm ࡢᅵ◁ࢆ 6,000 g ࡎࡘ᥇ྲྀࡋࡓࠋࡑࡋ࡚㸪JIS A12045) ࡟๎ࡾࡩࡿ࠸ศࡅヨ㦂ࢆ⾜ࡗࡓࠋᮏ◊✲࡛ࡣ⢏ᚄຍ✚᭤⥺㸪༨᭷⋡㸪୰ኸ⢏ᚄ D50 ࢆ⟬ฟࡋ㸪ᶓ᩿᪉ྥ࡜⦪᩿᪉ྥ࡟࠾ࡅࡿᖹ㠃࣭㖄┤᪉ྥ࡛ࡢ᳨ウࡸ 2020 ᖺᗘࡢ⤖ᯝ࡜ẚ㍑ࢆ⾜ࡗࡓࠋᅗ  ◊✲ᑐ㇟㸦㤿ሙ┠ᕝ୰ὶᇦᖹࡢୗᆅ༊㸧3㸬 ⢏ᗘศᯒ⤖ᯝ(1)ᶓ᩿᪉ྥ
 St.1~3 ཬࡧ 2020 ᖺᗘࡢ⢏ᚄຍ✚᭤⥺ࢆᅗ  ࡟♧ࡍࠋྛ㝵ᒙࡢ⢏ᚄຍ✚᭤⥺ࢆẚ㍑ࡍࡿ࡜㸪St.1
ཬࡧ 3 ࡛ࡣ῝ࡉ࡟ࡼࡿഴྥࡣぢࡽࢀ࡞࠿ࡗࡓࠋSt.2 ࡛ࡣ῝ࡉ 30~70 cm ࡢ⢏ᚄຍ✚᭤⥺ࡀᴫࡡ୍*Study on Grain Size Distribution of Riverbed Materials in the Horizontal and Vertical Direction by
Yoshitaka JIKEN, Junya TANIGUCHI, Noritoshi SAITO and Kazuya WATANABE

88

100

100

30੉

80

30੉
50੉
70੉

80

50੉
70੉

60

surfacethrough the percentage(%)

through the percentage(%)

surface

60

40

40

20

20

0
0.1

1

particle(mm)

10

0

100

0.1

1

30cm

10

100

30cm

80

50cm
60

100

surfacethrough the percentage(%)

through the percentage(%)

100

surface

80

10

St.2

St.1
100

particle(mm)

50cm

60

70cm

70cm

40

40

20

20

0

0
0.1

1

particle(mm)

10

100

0.1

1

particle(mm)

2020

St.3
ᅗ  ⢏ᚄຍ✚᭤⥺
surface

30cm

50cm

70cm

particle(mm)2015

center

left

10
5
0
St.1

St.2

St.3

2020

ᅗ  ୰ኸ⢏ᚄ D50⮴ࡋ࡚࠾ࡾ㸪2020 ᖺᗘࡢศᯒ⤖ᯝ࡜ྠᵝࡢഴྥ࡛࠶ࡿࡇ࡜࠿ࡽ㸪஺᥮ᒙࡣ 30 cm ᮍ‶࡛࠶ࡿ࡜⪃࠼ࡽࢀࡿࠋࡇࡇ࡛㸪஺᥮ᒙࡢཌࡉࡣ♟ᗋἙᕝ࡟࠾࠸࡚ D90 ࡢ 3 ಸ⛬ᗘ 6)࡜⪃࠼ࡽࢀ࡚࠸ࡿࡀ㸪
St.2 ࡢ D90 ࡣ⣙ 25 mm ࡛࠶ࡾ஺᥮ᒙࡣ 7.5 cm ࡜࡞ࡿࡓࡵ㸪⢏ᗘศᯒ࠿ࡽ⪃࠼ࡽࢀࡿ᮲௳࡜୍⮴ࡋ࡚࠸ࡓࠋḟ࡟୰ኸ⢏ᚄ D50 ࢆ♧ࡋࡓᅗ  ࢆࡳࡿ࡜⾲ᒙ࡟࠾࠸࡚ St.2 ࡣ᭱ࡶ⢏ᚄࡀ⢒ࡃ㸪St.3
࡛ࡣ᭱ࡶ⢏ᚄࡀ⣽࠿࠸⤖ᯝ࡜࡞ࡗࡓࠋࡲࡓ㸪2020 ᖺᗘࡢ⾲ᒙ࡟࠾ࡅࡿ⢏ᚄࡣ௒ᖺᗘ࡟ẚ࡭᫂ࡽ

89

35

25
20

25

15

20
15

10

10

5

5

0
0.1

1 particle(mm) 10

0

100

0.1

St.1

35

35

surface
30cm
50cm
70cm

share(%)

25
20

25

15

20

St.2

100

15

10

10

5

5

0

1 particle(mm) 10

surface
30cm
50cm
70cm

30

share(%)

30

surface
30cm
50cm
70cm

30

share(%)

30

share(%)

35

surface
30cm
50cm
70cm

0
0.1

1 particle(mm) 10

St.3

100

0.1

1 particle(mm) 10

100

2020

ᅗ  ༨᭷⋡(⢏ᚄ)࠿࡟኱ࡁ࠸ࡇ࡜ࡀศ࠿ࡗࡓࠋ
St.1~3 ཬࡧ 2020 ᖺᗘࡢ⢏ᚄẖࡢ༨᭷⋡ࢆᅗ  ࡟♧ࡍࠋ༨᭷⋡ࡢࣆ࣮ࢡ್ࡣ St.1 ࡛ 9.5 mm㸪
St.2 ࡛ 9.5~19 mm㸪St.3 ࡛ 9.5 mm ࡛࠶ࡾ㸪࡝ࢀࡶ㝵ᒙ࡟ࡼࡿ㐪࠸ࡣぢࡽࢀ࡞࠿ࡗࡓࠋࡲࡓ 2020ᖺᗘࡢศᯒ⤖ᯝࢆẚ㍑ࡍࡿ࡜㸪༨᭷⋡ࡢࣆ࣮ࢡ್ࡣ 9.5~26.5 mm ࡛࠶ࡾ㸪St.1~3 ࡜࡯ࡰྠᵝࡢഴྥ࡛࠶ࡗࡓࠋࡲࡓ㸪St.3 ࡛ࡣ⾲ᒙ࡛ 0.85~9.5 mm ࡢ⣽࠿࠸ᅵ◁ࡀከࡃ༨ࡵࡽࢀ࡚࠾ࡾ㸪᭱ࡶἙ㐨࠿ࡽ㞳ࢀ࡚࠸ࡿࡇ࡜࠿ࡽ㸪ᅵ◁ࡢ஺᥮ࡣ࡯ࡰ⾜ࢃࢀ࡚࠸࡞࠸࡜⪃࠼ࡽࢀࡿࠋࡇࡢࡇ࡜࠿ࡽ
ᶓ᩿᪉ྥ࡛ࡣἙ㐨࠿ࡽ㞳ࢀࡿ࡯࡝⾲ᒙ࡟࠾ࡅࡿᅵ◁ࡀ⣽࠿࠸ࡇ࡜ࡀศ࠿ࡗࡓࠋ
(2)⦪᩿᪉ྥ
St.4~6 ࡢ⢏ᚄຍ✚᭤⥺ࢆᅗ  ࡟♧ࡍࠋSt.4 ཬࡧ 5 ࡛ࡣ 50 cm ௨ୖ㸪St. ࡛ࡣ 30 cm ௨ୖ࡛ྠᵝࡢᴫᙧࢆ♧ࡋࡓࠋ୰ኸ⢏ᚄ D50 ࢆ♧ࡋࡓᅗ  ࢆぢࡿ࡜㸪῝ࡉ 50 cm ௨ୖࡢᅵ◁ࡣ࡝ࡢᆅⅬ࡛ࡶ⣽࠿࠸⢏ᚄࡀぢࡽࢀ㸪⢏ᚄࡀᏳᐃࡋ࡚࠸ࡓࠋࡲࡓ㸪St.2 ཬࡧ St.4~6 ࡢᶆ㧗ࢆẚ㍑ࡍࡿ࡜ St.5 ࡀ᭱ࡶపࡃ St.4 ࡀ᭱ࡶ㧗࠸ࠋࡑࡢࡓࡵ㸪⦪᩿᪉ྥ࡛ࡳࡿ࡜ St.4 ࡸ St.5 ࡞࡝㸪◁ᕞࡢୗὶഃ࡛ࡼࡾ῝ࡃᅵ◁ࡢ஺᥮ࡀ⾜ࢃࢀ࡚࠸ࡿ࡜⪃࠼ࡽࢀࡿࠋ
St.4~6 ࡢ⢏ᚄẖࡢ༨᭷⋡ࢆᅗ  ࡟♧ࡍࠋ༨᭷⋡ࡢࣆ࣮ࢡ್ࡣ࡝ࢀࡶ 0.85~9.5 mm ࡢ㛫࡛࠶ࡗ
ࡓࠋSt.1~6 ࡢ⢏ᚄຍ✚᭤⥺ࢆ᣺ࡾ㏉ࡿ࡜㸪஺᥮ᒙࡸ௦⾲ⓗ࡞⢏ᚄࢆ⟬ฟฟ᮶࡞࠸⟠ᡤࡶ࠶ࡿࠋ

90

100

surface
30cm
50cm
70cm
90cm

60
40
20

80

70cm
60
40
20

0
0.1

1
10
particle(mm)
St.4

50cm

through the percentage(%)

80

100

surfacesurface
30cm
50cm
70cm

30cm
through the percentage(%)

through the percentage(%)

100

60
40
20
0

0

100

80

0.1

0.1

100

1
10
particle(mm)
St.5

100

1
10
particle(mm)St.6ᅗ  ⢏ᚄຍ✚᭤⥺
surfaceparticle(mm)

15

30cm

50cm

70cm

10

5

0

downstream

upstream

St.4

St.2

St.5

St.6

ᅗ  ୰ኸ⢏ᚄ D50

35

surface
30cm
50cm
70cm

30

30
25

share(%)

25

share(%)

20
15

35

surface
30cm
50cm
70cm

25

20
15

20
15

10

10

10

5

5

5

0

0
0.1

1
10
particle(mm)
St.4

100

0.1

1
10
particle(mm)St.5

surface
30cm
50cm
70cm

30

share(%)

35

100

0
0.1

1
10
particle(mm)
St.6

100

ᅗ  ༨᭷⋡(⢏ᚄ)ࡲࡓ㸪ᅗ  ࡢ୰ኸ⢏ᚄ D50 ࡢ⾲ᒙ࡟࠾࠸࡚㸪௚ࡢᆅⅬ࡜ẚ࡭࡚ 2020 ᖺᗘࡢ⢏ᚄ࡜኱ࡁࡃ␗࡞
ࡿࡇ࡜ࡀศ࠿ࡗࡓࠋࡋࡓࡀࡗ࡚㸪ྛ㝵ᒙࡢ⢏ᚄຍ✚᭤⥺ࡣ᥇ྲྀ᫬ᮇࡸ఩⨨࡟ࡼࡗ࡚኱ࡁࡃ␗࡞
ࡿࡓࡵ㸪ᩘ್ィ⟬࡛⪃៖ࡍࡿ⢏ᚄ࡟ࡘ࠸࡚ࡣẚ㍑ⓗᏳᐃࡋࡓ⢏ᚄ್ࡀᚓࡽࢀࡿ༨᭷⋡ࢆ㐺⏝ࡍࡿ࡭ࡁ࡛ࡣ࡞࠸࠿࡜⪃࠼ࡽࢀࡿࠋ

91

4㸬
㸬 ᩘ್ィ⟬ḟ࡟ᮏ◊✲࡛ࡣ㸪᪤ ◊✲ 7)8)ࢆཧ⪃࡜ࡋᖹ㠃஧ḟඖィ⟬ࢆ⾜ࡗࡓࠋᘧ(1)㹼(3)࡟௒ᅇ౑⏝ࡋࡓ㐃⥆ᘧ࡜㐠ື᪉⛬ᘧࢆ♧ࡍࠋ
wh w ( hu ) w (hv)


wt
wx
wy

(1)

0

w(uh) w(hu 2 ) w(huv)


wt
wx
wy

hg

wH τ x  Dχwχ
ρ(2)

w(vh) w(huv) w(hv 2 )


wy
wx
wt

hg

wH τ y  Dyρwy(3)

ࡇࡇ࡛ h ࡣỈ῝㸪t ࡣ᫬㛫, u㸪v ࡣ x㸪y ᪉ྥࡢᖹᆒὶ㏿㸪g ࡣ㔜ຊຍ㏿ᗘ㸪H ࡣỈ఩, ߬௫ 㸪߬௬ ࡣ x㸪y ᪉ྥࡢἙᗋࡏࢇ᩿ຊ㸪‫ ܦ‬௫ 㸪‫ ܦ‬௬ ࡣ x㸪y ᪉ྥࡢᣑᩓ㡯ࢆ♧ࡍࠋ௒ᅇࡣ⾲ᒙࡢࡳࢆ⪃៖ࡋࡓሙྜ࡟ࡘ࠸࡚ 2020 ᖺᗘࡢ⢏ᚄ್࡜ẚ㍑ࡋࡓࠋ౑⏝ࡋࡓ⢏ᚄ್ࡣ୰ኸ⢏ᚄ࡛㸪2020 ᖺᗘࡢ⾲ᒙ 19.0 mm ࡜⢏ᚄຍ✚᭤⥺ࡀ㢮ఝࡋ࡚࠸ࡓ St.2 ࡢ⾲ᒙ 9.1 mm ࡛࠶ࡿࠋ⾲  ࡟ィ⟬᮲௳㸪ᅗ ࡟ ୖ ὶ ➃ ࡢ ቃ ⏺ ᮲ ௳ ࢆ ♧ ࡍ ࠋ ቃ ⏺ ᮲ ௳ ࡣ ㄪ ᰝ ᆅ Ⅼ ࡢ ୗ ὶ ࡟ ࠶ ࡿ ஂ ಖ ほᡤࡢࢹ࣮ࢱ(2018/8/24 18:00㹼2018/8/25 18:00 ࡢ 24 ᫬㛫ὶ㔞)ࢆ౑⏝ࡋࡓࠋ⾲  ィ⟬᮲௳
⪃៖ࡍࡿᒙ

⾲ᒙࡢࡳ



࣐ࢽࣥࢢࡢ
⢒ᗘಀᩘ

Ἑᗋ 0.03ࡑࡢ௚ 0.04᫬㛫ࢫࢸࢵࣉ

0.1 ⛊



ィ⟬᱁Ꮚ

㠀ṇ᪉᱁Ꮚ








discharge(m3/s)

400
300
200
100
0
0

6

12

time(hour)1824ᅗ  ୖὶ➃ࡢቃ⏺᮲௳(ὶ㔞)5㸬 ィ⟬⤖ᯝᅗ  ࡟Ἑᗋࡢᶆ㧗ኚ໬ࢆ♧ࡍࠋᅗࡢ㉥Ⰽࡣሁ✚㸪㟷ⰍࡣὙ᥀ࢆ♧ࡍࠋࡇࢀࢆࡳࡿ࡜ᕥᓊ࡟
࠾ࡅࡿ◁ᕞᆅⅬ࡛ࡣἙᗋኚື㔞࡟㐪࠸ࡣぢࡽࢀ࡞࠿ࡗࡓࠋὙ᥀࡟㛵ࡋ࡚ࡣ 2 ࣃࢱ࣮ࣥ࡟࠾࠸࡚
࡯࡜ࢇ࡝㐪࠸ࡣぢࡽࢀࡎ㸪ୖὶഃ࡛኱ࡁࡃὙ᥀ࡍࡿࡇ࡜ࡀ᫂ࡽ࠿࡟࡞ࡗࡓࠋ



⥺

⥺









St. ⾲ᒙ2020 ᖺ⾲ᒙᅗ  ᶆ㧗ኚ໬

920

ᅗ  ࡟ 2021 ᖺ 8 ᭶ 20 ᪥࡟-1

ᒙ 9.1 mm㸪19.0 mm ࡢሙྜࡢィ⟬-2࡛ᚓࡽࢀࡓᶓ᩿ᅗࢆ♧ࡍࠋィ⟬್ࡣᐇ್࡜ẚ࡭࡚ྑᓊഃ࡛ࡼࡾὙ

᥀ࡋ㸪ᕥᓊഃ࡛ࡼࡾሁ✚ࡍࡿഴྥelevation(m)ᶓ᩿ᅗ࡜⾲㔞ࡋࡓ◁ᕞᆅⅬࡢᐇ

-3-4

࡛࠶ࡗࡓࠋࡑࡢࡓࡵ㸪⾲ᒙࡢࡳࢆ-5⪃៖ࡋࡓሙྜ࡟࠾ࡅࡿィ⟬࡛ࡣ㸪

-6Ἑᗋኚືࡀ㐣኱ホ౯ࡉࢀ࡚࠸ࡿ࡜
⪃࠼ࡽࢀࡿࠋࡲࡓ㸪⢏ᚄ࡟ࡼࡿ㐪࠸ࡣぢࡽࢀ࡞࠿ࡗࡓࠋ


2021/8/20
initial
9.1mm
19.0mm

left

-7
0

10

20

right
30

distance(m)

40

50

60

ᅗ  ◁ᕞᆅⅬࡢᶓ᩿ᅗ

6㸬
㸬 ࠾ࢃࡾ࡟
ᮏ◊✲࡛ࡣ㤿ሙ┠ᕝ୰ὶᇦࡢ◁ᕞୖࡢ」ᩘࡢ⟠ᡤ࡟ࡘ࠸࡚ᅵ◁ࢆ᥇ྲྀࡋ㸪⢏ᗘศᯒࢆ⾜ࡗࡓࠋࡑࡢ⤖ᯝ㸪St.2 ࡢ⢏ᚄຍ✚᭤⥺࠿ࡽ஺᥮ᒙࡣ 30 cm ᮍ‶࡛࠶ࡿࡇ࡜࠿ࡽ㸪D90 ࡢ 3 ಸ࡜࠸࠺⪃࠼᪉࡜୍⮴ࡋ࡚࠸ࡓࠋࡲࡓ㸪ྛ㝵ᒙࡢ⢏ᚄຍ✚᭤⥺ࡣ᥇ྲྀ᫬ᮇࡸ఩⨨࡟ࡼࡗ࡚኱ࡁࡃ␗࡞ࡿࡓ
ࡵ㸪ᩘ್ィ⟬࡛⪃៖ࡍࡿ⢏ᚄ࡟ࡘ࠸࡚ࡣẚ㍑ⓗᏳᐃࡋࡓ್ࡀᚓࡽࢀࡿ༨᭷⋡ࢆ㐺⏝ࡍࡿ࡭ࡁ࡛
ࡣ࡞࠸࠿࡜⪃࠼ࡽࢀࡿࠋ௒ᚋࡣᩘ್ィ⟬࡟ࡼࡿධຊ್ࡢ㐺ṇ(⢏ᚄຍ✚᭤⥺㸪༨᭷⋡)ࢆ᳨ウࡋ㸪ᐇἙᕝࡢ෌⌧ᛶࢆ᳨ウࡋ࡚࠸ࡁࡓ࠸ࠋ
ㅰ㎡
ᮏ◊✲ࢆ⾜࠺࡟࠶ࡓࡾ⛉Ꮫ◊✲㈝⿵ຓ㔠㸦20H00256㸪௦⾲㸸㢼㛫⪽㸧ࡢຓᡂࢆཷࡅࡓࠋࡇࡇ
࡟グࡋ㸪ㅰពࢆ⾲ࡍࡿࠋཧ⪃ᩥ⊩1)ཎ⏣኱㍜㸪▱ⰼṊⰼ㸪Agus SANTOSO㸸Ἑᗋᮦᩱࡢ⢏ᗘศᕸࡢ≉ᚩ࡜ࡑࡢつᐃせᅉ࡟ࡘ࠸࡚㸪ᅵᮌᏛ఍ㄽᩥ㞟 B1(ỈᕤᏛ)Vol. 73㸪No. 4㸪I_931-I_936㸪2017.
2)ⰱ⏣࿴⏨㸪Ụ㢌㐍἞㸪๽᯶⩏㸸⺬⾜ὶ㊰࡟࠾ࡅࡿὶ◁ࡢศ⣭࠾ࡼࡧἙᗋኚື࡟㛵ࡍࡿᩘ್ゎᯒ㸪ỈᕤᏛㄽᩥ㞟 ➨ 35 ᕳ㸪pp. 383~390㸪1991.
3)Ụ㢌㐍἞㸪㔠ᾏ⏕㸪➉ᯘὒྐ㸪ụ⏣ᬗ㸪Ọ⏣ᚭ㸸ᮌὠᕝୗὶᇦࡢἙᗋኚື࡜ᅵ◁཰ᨭ㸪ỈᕤᏛㄽᩥ㞟㸪➨ 44 ᕳ㸪pp. 777~782㸪2000.
4)୰ᕝ㐶㸪㇂ཱྀ㞙ஓ㸪㰻⸨᠇ᑑ㸪Ώ㎶୍ஓ 㸸㖄┤᪉ྥ⢏ᗘศᕸ࡜Ἑᗋኚື࡟㛵ࡍࡿ᳨ウ㸪௧࿴ඖᖺᗘᅵᮌᏛ఍ᮾ໭ᨭ㒊ᢏ⾡◊✲Ⓨ⾲఍㸪ϩ-41㸪2020.(CD-ROM)5)᪥ᮏ⏘ᴗつ᱁ JISA1204:2020< http://www.kikakurui.com/a1/A1204-2020-01.html>(2021/12/21 ࢔ࢡࢭࢫ)6)㛵᰿ṇே㸸⛣ືᗋὶࢀࡢỈ⌮Ꮫ㸪ඹ❧ฟ∧ᰴᘧ఍♫㸪161 p㸪2005.
7)ụ᳃ಇ௓㸪Ώ㎶୍ஓ㸪ⴗཎ↷㏻㸸㤿ሙ┠ᕝ࡟࠾ࡅࡿ⢏ᚄࢆ⪃៖ࡋࡓኚືィ⟬࡟㛵ࡍࡿ᳨ウ, ᅵᮌᏛ఍ᮾ໭ᨭ㒊ᢏ⾡◊✲Ⓨ⾲఍ᴫせ㸪ϩ-25㸪2017.(CD-ROM㸧8)᳜ᮌὯኴ㑻㸪Ώ㎶୍ஓ㸸㤿ሙ┠ᕝ࡟࠾ࡅࡿᩘ್ィ⟬ࢆ⏝࠸ࡓሐ㜵⿕⅏࡟㛵ࡍࡿ᳨ウ, ᅵᮌᏛ఍ᮾ໭ᨭ㒊ᢏ⾡◊✲Ⓨ⾲఍ᴫせ㸪ϩ-49㸪2018.(CD-ROM)

東北地域災害科学研究

93

第58巻（2022）

ᓥ᰿┴Ụࡢᕝୗὶ㒊࡟࠾ࡅࡿ௧࿴ 3 ᖺ 8 ᭶ࡢỏ℃࡟ࡘ࠸࡚ ᒸᒣ⌮⛉኱Ꮫ⌮Ꮫ㒊  ⏣ୖ┤ᘺ࣭ྂ⏣኱ᬛ࣭ᒸᮏెዉ࣭㙊⁪Ꮥಙ
1㸬ࡣࡌࡵ࡟
2020 ᖺ 7 ᭶ 5 ᪥㹼14 ᪥ࡢ኱㞵࡟ࡼࡾ㸪ᗈᓥ┴ཬࡧᓥ᰿┴ࡢỤࡢᕝὶᇦ࡛኱つᶍ࡞ὥỈࡀⓎ⏕ࡋࡓࠋ2021 ᖺ
8 ᭶ 11 ᪥㹼15 ᪥࡟ࡶ㸪஑ᕞ࠿ࡽ㛵ᮾᆅ᪉ࡢྛᆅ࡛኱㞵ࡀほ ࡉࢀ㸪Ụࡢᕝ࡛෌ࡧỏ℃ࡀ☜ㄆࡉࢀࡓࠋࡇࡢࡼ
࠺࡞㏆ᖺࡢἙᕝỏ℃ࢆཷࡅ㸪ὥỈ᫬ࡢỈ⌮≧ἣࢆ᳨ウࡍࡿ㔜せ࡞ᇶ♏ࢹ࣮ࢱ࡜࡞ࡿᾐỈ⑞㊧㸦ὥỈሁ✚≀ࡢ࣋ࢵࢻࣇ࢛࣮࣒ࡸሁ✚ᵓ㐀➼㸧ࢆㄪᰝࡍࡿࡇ࡜ࡣ㸪Ỉᐖ᝿ᐃࡢ⢭ᗘྥୖ࡟ࡶࡘ࡞ࡀࡿ࡜⪃࠼ࡽࢀࡿࠋᮏ◊✲࡛ࡣ
2 ᖺ㐃⥆࡛ỏ℃ࡀⓎ⏕ࡋ㸪୰ᅜᆅ᪉᭱኱つᶍ࡛࠶ࡿỤࡢᕝࢆᑐ㇟࡟㸪⌧ᆅㄪᰝ⤖ᯝࡸほ ࢹ࣮ࢱ࠿ࡽୗὶ࡛ࡢ
ỏ℃࡟㉳ᅉࡍࡿẼ㇟᮲௳ཬࡧᆅ⌮ⓗ᮲௳ࢆ⪃ᐹࡍࡿࡇ࡜ࢆ┠ⓗ࡜ࡍࡿࠋ

2㸬Ἑᕝᴫせ࠾ࡼࡧ᪤ ὥỈỤࡢᕝࡣጞ※ࢆᗈᓥ┴ᒣ┴㒆໭ᗈᓥ⏫㜿బᒣ࡜ࡋ㸪ᓥ᰿┴Ụὠᕷ࡛᪥ᮏᾏ
࡟ὀࡄ୍⣭Ἑᕝ࡛࠶ࡿࠋὶ㊰ᘏ㛗
194km ࡢỤࡢᕝỈ⣔ࡣ⚄㔝℩ᕝ㸪㤿Ὑᕝ㸪ඵᡞᕝ࡞࡝ィ 293 ᮏࡢᨭᕝࡀྜὶ
ࡋ㸪㜿బᒣ࠿ࡽ୕ḟ┅ᆅࡲ࡛ࢆୖὶ㒊㸪୕ḟ┅ᆅࢆ㯄࡜ࡍࡿᑿ㛵ᒣ࠿ࡽ὾ཎࢲ
࣒ࡲ࡛ࢆ୰ὶ㒊㸪὾ཎࢲ࣒࠿ࡽἙཱྀࡲ
࡛ࢆୗὶ㒊࡜༊ศࡉࢀ࡚࠸ࡿࠋ୰ὶ㒊ࡢἙᗋ໙㓄ࡣୗὶ㒊ࡢ 3㹼20 ಸ࡛㸪ୖὶ㒊ࡢἙᗋ໙㓄ࡀ୰ὶ㒊ࡢ 1.5 ಸ௨ୖ࡜࡞ࡿࡓࡵୖὶ㒊ࡢᛴᓧ໬࡜ୗὶ㒊ࡢᖹᆠ໬ࡀ≉ᚩⓗ࡞Ἑᕝ࡛࠶ࡿ㸦ᅜᅵ஺㏻┬Ἑᕝᒁ㸪2007㸧ࠋᩥ⊩࡟ṧࡿỤࡢᕝࡢ᭱ྂࡢὥỈࡣ჆Ọ 3 ᖺ㸦1850 ᖺ㸧6 ᭶ࡲ࡛㐳ࡾ㸪ᡓᚋ᭱኱ࡢቑỈ࡜࡞ࡗࡓ᫛࿴ 47 ᖺ㸦1972 ᖺ㸧7 ᭶ὥỈ࡛ࡣ㸪ᦆቯᐙᒇࡀ 3,960 ᡞ㸪ᾐỈᐙᒇࡀ 14,063 ᡞ࡟㐩ࡋࡓ㸦୰ᅜᆅ᪉Ἑᕝᒁ㸪2007㸧ࠋ᫛࿴ 20 ᖺ㸦1945 ᖺ㸧9 ᭶ࡢᯖᓮྎ㢼ࡸᖹᡂ 18 ᖺ㸦2006 ᖺ㸧9 ᭶ࡢྎ㢼 13 ྕ࡞࡝ࡢྎ㢼㉳※ࡢࡶࡢࢆྵࡵ㸪ᱵ㞵ࢆྵࡴ๓⥺ᛶ኱㞵ࡀὥỈࡢせᅉ࡜ࡉࢀ㸪ᖹᡂ௨ᚋỤࡢᕝ࡛ỏ℃ࡢ☜ㄆࡉࢀࡿ࿘ᮇࡀ▷ࡃ࡞ࡗ࡚࠸ࡿഴྥࡀ
࠶ࡿ㸦୰ᅜᆅ᪉ᩚഛᒁ㸪2018㸧ࠋ௧࿴ 3 ᖺ㸦2021 ᖺ㸧8 ᭶ࡢὥỈ࡛ࡣ 8 ᭶ 13 ᪥㸪14 ᪥࡟ୖὶ࡛ 2 ᅇ㸪⥆࠸࡚ࠋୗὶ࡛⁄Ỉࡀሗ࿌ࡉࢀ㸪ୗὶ࡛ࡢᾐỈ㠃✚ࡣ 1.93ଶ࡟ཬࢇࡔ㸦୰ᅜᆅ᪉ᩚഛᒁ㸪2021㸧3㸬ㄪᰝ࣭ศᯒࡢ᪉ἲ
௒ᅇࡢ⌧ᆅㄪᰝ࡛ࡣ㸪Ἑཱྀ࠿ࡽࡢ㊥㞳 0㹼55km ࡢ༊㛫ࢆᑐ㇟࡜ࡍࡿࠋ2021 ᖺ 7 ᭶࡟ᐇ᪋ࡋࡓ⡆᫆ⓗ࡞ㄪᰝࡢᚋ 8 ᭶ 11᪥࠿ࡽ୰ᅜᆅ᪉࡛኱㞵࡜࡞ࡾ㸪඲ὶᇦ࡟ཬࡪỏ℃࡜࡞ࡗࡓࠋ
ᅜᅵ஺㏻┬୰ᅜᆅ᪉ᩚഛᒁࡢሗ㐨㈨ᩱ㸦2㸧ࢆཧ⪃࡟㸪እỈ࡟ࡼࡿᾐỈᆅⅬࢆ 9 ⟠ᡤ㑅ᐃࡋࡓ࠺࠼࡛ 8 ᭶ 25㹼27 ᪥ࡢ 3 ᪥㛫࡛ㄪᰝࢆ⾜ࡗࡓࠋࡑࡢ 9 ⟠ᡤࡣᅗ 1 ࡟♧ࡍ㏻ࡾ㸪ୖὶഃ࠿ࡽ㑚ᬛ㒆⨾㒓⏫ᮏ㒓࣭⨾㒓⏫ ࣭ᕝᮏ⏫㇂࣭ỤὠᕷᱜỤ⏫኱㈏࣭ᱜỤ⏫⏣ὠ࣭ᱜỤ⏫ᴮ㇂࣭ᱜỤ⏫ோ୓℩࣭Ụὠᕷᯇᕝ⏫
ୖ㛗Ⰻ࣭Ụὠᕷᕝᖹ⏫⏣㔝࡛࠶ࡿࠋྛᆅⅬࡢ⿕ᐖ≧ἣ࡟ᛂࡌ࡚㸪◁ሁୖ࡟ᙧᡂࡉࢀࡓ࣋ࢵࢻࣇ࢛࣮࣒ࢆヲ⣽࡟ほᐹࡍࡿ࡜*The field survey of inundation in August 2021, from Gounokawa River, Shimane Prefecture by Naoya TAGAMI,
Daichi FURUTA, Kana OKAMOTO and Takanobu KAMATAKI94ඹ࡟㸪ࢹ࣮ࣗࣥ࡞࡝ࡢ㛫㝸ཬࡧἼ㧗ࢆ⡆᫆ⓗ࡟ィ ࡋࡓࠋࡲࡓ㸪⁄Ỉ࡟ࡼࡗ࡚ᙧᡂࡉࢀࡓᘓ㐀≀➼ࡢ⾲㠃ࡢ⑞㊧㸪ሁ✚ᅵ◁ࡢ㐳ୖ㧗ࡉ࡞࡝ࢆཧ⪃࡟ᾐỈつᶍࢆ᥎ᐃࡍࡿ࡯࠿㸪ྛᆅⅬࡢὥỈሁ✚ᒙࡢཌࡉࢆ ᐃࡋࡓࠋẼ㇟≧ἣ࡜Ỉ఩ኚ໬ࡢศᯒ࡛ࡣ㸪➨ 1 ࡟ỏ℃๓ᚋࡢ㝆Ỉ㔞ࡢ≉ᚩࢆ᳨ウࡍࡿࠋỤࡢᕝỈ⣔ࡀ㞟Ỉᇦ࡜࡞ࡾ࠺
ࡿྜィ 13 ⟠ᡤࡢ࢔࣓ࢲࢫほ ᡤ࡜ࡋ࡚㸪ୖὶഃࡢᗈᓥ┴࡛ 7 ⟠ᡤ㸪ୗὶഃࡢᓥ᰿┴࡛ 6 ⟠ᡤࢆ㑅ᐃࡋࡓࠋ➨2 ࡟ኳẼᅗ࡜⾨ᫍ⏬ീࢆ౑⏝ࡋ㸪Ụࡢᕝὶᇦࢆ୰ᚰ࡜ࡍࡿ⥲ほつᶍࡢẼ㇟ࢆ㏣㊧ࡋࡓࠋ㈨ᩱࡣ㸪Ẽ㇟ᗇ࡟ࡼࡿ
༠ᐃୡ⏺᫬ 2021 ᖺ 8 ᭶ 11 ᪥ 18 ᫬㹼15 ᪥ 18 ᫬ࡢ࢔ࢪ࢔ኴᖹὒᇦᆅୖኳẼᅗ㸪ཬࡧ 850hPa࣭700hPa࣭500hPa࣭
300hPa 㧗ᗘࡢ㧗ᒙኳẼᅗࢆ฼⏝ࡋࡓࠋẼ㇟⾨ᫍ⏬ീࡣ㸪᪥ᮏẼ㇟༠఍ࡼࡾ᪥ᮏᶆ‽᫬ 2021 ᖺ 8 ᭶ 12 ᪥ 0 ᫬
㹼16 ᪥ 0 ᫬ࡢ㉥እ⏬ീ࣭Ỉ⵨Ẽ⏬ീࢆཧ↷ࡋࡓࠋ➨ 3 ࡟Ụࡢᕝୗὶ㒊࡛ࡢἙᕝỈ఩ኚ໬ࢆศᯒࡍࡿ࠺࠼࡛㸪
ᅜᅵ஺㏻┬ࡼࡾ 2021 ᖺ 8 ᭶ 13 ᪥ 0 ᫬㹼20 ᪥ 0 ᫬ࡢほ Ỉ఩ࢹ࣮ࢱࢆཧ↷ࡋࡓࠋᆅⅬࡣୖὶഃ࠿ࡽ὾ཎ࣭ᕝ
ᮏ࣭㇂ఫ㒓ࢆ㑅ᐃࡋ㸪ᇶ‽Ỉ఩ࡢ㉸㐣≧ἣ➼ࡶྵࡵ᳨ウࡋࡓࠋ㸬⌧ᆅㄪᰝࡢ⤖ᯝ
4㸬ὥỈ⏤᮶࡜᥎ᐃࡉࢀࡿ࣋ࢵࢻࣇ࢛࣮࣒
࡟ࡘ࠸࡚㸪Ụὠᕷᴮ㇂ࡢሐእ⏿ᆅ࡛ࡣ 10㹼
15cm Ἴ㛗ࡢ࢝ࣞࣥࢺࣜࢵࣉࣝࡀ࠶ࡾ㸪ୗὶഃ࡯࡝Ἴ㛗ࡀ▷ࡃ୙᫂░࡟࡞ࡗ࡚࠸ࡓ
ࡇ࡜࠿ࡽ㸪Ỉ఩ୖ᪼࡟క࠺ἙᕝỈࡢὶ㏿పୗࡀ⪃࠼ࡽࢀࡿࠋỤὠᕷ኱㈏࡛ࡣ෇♟ࡢ࢖ࣥࣈࣜࢣ࣮ࢩࣙࣥࡀ☜ㄆࡉࢀ㸪◁ሁୖ࡟ 60
㹼170cm Ἴ㛗ࡢࢹ࣮ࣗࣥࡀ࠶ࡾ㸪Ἴ㧗ࡀ᭱኱ 18cm ࡟ཬࡪࡇ࡜࠿ࡽ㏿࠸ὶ㏿ࢆ⥔ᣢࡋ࡚࠸ࡓ࡜ࡳࡽࢀࡿࠋᨭᕝࡢྩ㇂ᕝࡀὶධࡍ
ࡿᆅⅬ࡟㏆࠸⨾㒓⏫ ࡛ࡣ㸪◁ሁୖ࡟ 80㹼
90cm Ἴ㛗ࡢ࢔ࣥࢸ࢕ࢹ࣮ࣗࣥࡀ࠶ࡾ㸪ἙᕝỈࡀ㐳ୖࡋ࡚࠸ࡓྍ⬟ᛶࡀ᥎ᐃࡉࢀࡓࠋ࡞
࠾㸪ࢹ࣮ࣗࣥࡢ☜ㄆࡉࢀࡓ኱㈏࡛ࡣ㸪㐣ཤ࡟ᙧᡂࡉࢀࡓὥỈሁ✚≀㸦Ἑᓊ◁࡜Ἶࡢ஫ᒙ㸧ࡀỏ℃ὶ࡟ࡼࡗ࡚๐ࡽࢀ㸪࿘㎶ࡢ➉⸭ࡢಽቯࢆࡶࡓࡽࡋ࡚࠸ࡓࠋἙᓊ◁࡜Ἶࡢ஫ᒙࡢᔂⴠ㒊ศ࡟ࡣࠕᮾὒ㧗ᅽࠖ࡜グ㍕ࡉࢀࡓᒀ⣲⫧ᩱࡢ⿄ࡀΰධࡋ࡚࠾ࡾ㸪௻ᴗἢ㠉ࡸ〇㐀᫬ᮇࢆㄪ࡭ࡓ⤖ᯝ㸪1948 ᖺ௨㝆ࡢὥỈ࡟ࡼࡾࡇࡢὥỈሁ✚≀ࡀᙧᡂࡉࢀࡓࡇ
࡜ࡀุ᫂ࡋ㸪⿄ࡢᇙἐ≧ែ࠿ࡽ᫛࿴ 47 ᖺ㸦1972 ᖺ㸧7 ᭶ὥỈ࡜ࡢ㧗࠸┦㛵ᛶࡀ⪃࠼ࡽࢀࡿࠋ
୍᪉㸪௧࿴ 3 ᖺ 8 ᭶ὥỈ࡟ࡼࡿὥỈሁ✚≀ࡢᒙཌ࡟ࡘ࠸࡚㸪⨾㒓⏫ᮏ㒓ࡸᕝᮏ⏫㇂ࢆ㝖ࡃ 7 ᆅⅬ࡛ࡣᴫࡡ
1mm ௨ୖࡢཌࡉ࡛࠶ࡿࠋỤὠᕷ⏣㔝࡛ࡣ␏㐨࡛ 3mm㸪⏿ᆅࡢᰠࡢᮌ࿘㎶࡛ 10mm㸪⯪ὠᶫ㏆㎶࡛᭱኱ 6mm ࡢࢩࣝࢺࡢሁ✚ࡀ☜ㄆࡉࢀ㸪Ụὠᕷோ୓℩ࡢᮡᯘࡢᶞ㛫࡛ࡣࢩࣝࢺࡀ 10mm ሁ✚ࡋ࡚࠸ࡓࠋࡲࡓỤὠᕷୖ㛗ⰋࡢἙᕝᩜⲡᆅୖ࡛ࡣ⣙ 8mm ࡢ◁ࡢሁ✚ࡀࡳࡽࢀ㸪ࡇࢀࡽࡢㄪᰝ⤖ᯝࢆ⥲ྜⓗ࡟㋃ࡲ࠼ࡿ࡜㸪ୗὶഃࡢἙ㐨࡟㏆࠸ሙᡤ࡯࡝ὥỈሁ✚≀ࡢᒙཌࡀ኱ࡁ࠸ഴྥࡀ♧၀ࡉࢀࡿࠋ
ᾐỈ⑞㊧ࡢㄪᰝ࡟ࡘ࠸࡚㸪࿘㎶㐨㊰࠿ࡽࡢ᭱኱ᾐỈ఩⨨ࢆ≉ᐃࡍࡿ࠺࠼࡛㸪ఫᐙࡢᗞ࡟࠶ࡿ᳜࠼㎸ࡳࡢᅵ◁௜╔఩⨨ࡸᘓ≀ቨ㠃࡟࡛ࡁࡓ⑞㊧ࢆᡭ᥃࠿ࡾ࡜ࡋࡓࠋලయ౛࡜ࡋ࡚㸪Ụὠᕷᴮ㇂࡛ࡣබ⾗㟁ヰ࣎ࢵࢡࢫࡢෆഃ
࢞ࣛࢫ㠃࡟࡛ࡁࡓ⑞㊧࠿ࡽ᭱኱ 1.39m㸪Ụὠᕷ⏣ὠ࡛ࡣ㟁ಙᰕࡸࢣ࣮ࣈࣝࢸࣞࣅ⥺࡟⤡ࡳࡘࡃ࢖ࢿ⛉᳜≀ࡢ఩⨨࠿ࡽ᭱኱ 5.70m ࡢᾐỈ㧗ࡀ᥎ᐃࡉࢀࡓࠋỤὠᕷோ୓℩࡟ࡣ㙾㠃࡟⣙ 2.7m ࡢ㧗ࡉࡲ࡛ᩘᮏࡢᾐỈ⑞㊧ࡀධࡗࡓ࣮࢝ࣈ࣑࣮ࣛࡀ࠶ࡗࡓࡀ㸪7 ᭶ࡢㄪᰝ᫬࡟᧜ᙳࡉࢀࡓྠ୍ࡢ࣮࢝ࣈ࣑࣮ࣛࡢ⏬ീ࡜ẚ㍑ࡋࡓ⤖ᯝ㸪⑞㊧ࡢ఩95⨨࡟┦㐪ࡀ࡞࠿ࡗࡓࡓࡵ㸪௒ᅇࡢὥỈ࡟ࡼࡿࡶࡢ࡛ࡣ࡞࠸࡜ุ᩿ࡋࡓࠋࡲࡓ㸪࣮࢝ࣈ࣑࣮ࣛ⿬㠃ࡢタ⨨᫬ᮇࡢ⾲♧࠿ࡽ㸪ࡇࡢ᭱኱ᾐỈ఩⨨ࡀ௧࿴ 2 ᖺ 7 ᭶ὥỈ࡟㉳ᅉࡍࡿ࡜᥎ᐹࡉࢀࡓࠋࡇࢀࢆ㋃ࡲ࠼㸪➉⸭ࡢ⾲㠃ࢆそ࠺ᅵ◁ࡸ᳜≀∦ࡢ㧗ࡉ㸪ᪧ୕Ụ⥺㝣ᶫࡢ᱆ୗ┳ᯈ࡟ࡳࡽࢀࡿ⑞㊧࠿ࡽ㸪ᮏᖺᗘࡢὥỈ࡛ࡇࡢᆅⅬ࡟࠾ࡅࡿ᭱኱ᾐ
Ỉ఩ࡣ 2.10m ࡜⪃࠼ࡽࢀࡿࠋࡲࡓ㸪⨾㒓⏫ ࡛ࡣᅜᅵ஺㏻┬ࡢタ⨨ࡋࡓ⡆᫆Ỉ఩ィ㸪ᕝᮏ⏫㇂࡛ࡣ㐣ཤࡢᾐỈ㧗ࢆ♧ࡍ⾲♧ᯈࡀ࠶ࡾ㸪௧࿴ 3 ᖺ 8 ᭶ὥỈ࡟࠾ࡅࡿᐇ⦼ᾐỈ῝ࡣࡑࢀࡒࢀ⣙ 2.70m㸪⣙ 0.65m ࡛࠶ࡗࡓࠋ㐣ཤࡢὥỈ࡟࠾ࡅࡿᐇ⦼ᾐỈ῝࡜ẚ㍑ࡍࡿ࡜㸪㏆ᖺⓎ⏕ࡋࡓὥỈ࡯࡝ḟ➨࡟ᾐỈ㧗ࡀపୗࡋ࡚࠸ࡿഴྥࡀ࠶ࡿࠋ
㸬Ẽ㇟≧ἣ࡜Ỉ఩ኚ໬ࡢศᯒ
5㸬ᮏᖺᗘࡢὥỈ࡟࠾࠸࡚㸪8 ᭶ 12 ᪥ 0
᫬㹼13 ᪥ 15 ᫬ࢆᮇ㛫๓༙㸪8 ᭶ 13 ᪥
15 ᫬㹼14 ᪥ 15 ᫬ࢆᮇ㛫ᚋ༙࡜ࡋࡓ✚⟬㝆Ỉ㔞ࢆ᳨ウࡋࡓ࡜ࡇࢁ㸪13 ⟠ᡤ୰
9 ⟠ᡤࡢ࢔࣓ࢲࢫᆅⅬ࡛ᮇ㛫ᚋ༙ࡢ᪉ࡀ኱ࡁ࠸್ࢆ♧ࡋ࡚࠸ࡿࠋ
1 ᫬㛫㝆Ỉ㔞᥮⟬࡛ࡶᕪࡣṔ↛࡛㸪ୖὶ㒊ࡢୡ⨶࡛
3.58mm/h ࠿ࡽ 14.25mm/h㸪ୗὶഃࡢ⍞✑࡛ 2.28mm/h ࠿ࡽ 11.42mm/h ࡟ቑ኱ࡍࡿ࡞࡝㸪Ụࡢᕝ඲ὶᇦ࡛ᖹᆒⓗ࡞㝆Ỉᙉᗘࡢᙉࡲࡾࡀࡳࡽࢀࡿࠋࡲࡓୖὶ
㒊࡛ࡣ㸪1979㹼2020 ᖺࡲ࡛ࡢ⤫ィ࡟࠾
ࡅࡿ 8 ᭶✚⟬㝆Ỉ㔞ᖹᆒ್࡟༉ᩛࡍࡿ
㞵ࡀࢃࡎ࠿ 24 ᫬㛫௨ෆ࡛㝆ࡗࡓᆅⅬࡶ࠶ࡿࠋࡇࡢࡼ࠺࡞Ⳙ኱࡞㝆Ỉ㔞ࢆࡶࡓࡽࡋࡓ⫼ᬒ࡟ࡣᅗ 5 ࡢ࢔ࢪ࢔ᆅୖ
ኳẼᅗ࡟♧ࡍࡼ࠺࡟୰ᅜᆅ᪉ࢆᶓ᩿ࡍࡿᮾす࡟ఙࡧࡓ೵⁫๓⥺ࡢືࡁࡀ኱
ࡁࡃ㛵㐃ࡋ࡚࠸ࡓࠋ
1 ᅇ┠ࡢ኱㞵ࡢࣆ࣮ࢡᚋࡢ13 ᪥9 ᫬ࡲ࡛࡟㸪୍ᗘ໭ୖࡋ࡚࠸ࡓ๓⥺ࡀୖὶ㒊ࡢ༡ഃࡲ࡛⛣ືࡋ㸪ྠ᫬࡟᪥ᮏࡢᮾ
ࡢᾏୖ࡟఩⨨ࡍࡿ࣮࢜࣍ࢶࢡᾏ㧗Ẽᅽ㸪ኴᖹὒ㧗Ẽᅽ㛫ࡢẼᅽࡢ㠡㒊࡟㈏ධࡍࡿᙧ࡛㸪๓⥺ࡢ⠊ᅖࢆᣑ኱ࡉࡏ࡚
࠸ࡿ≧ἣ࡛࠶ࡗࡓࠋࡑࡢ⤖ᯝ㸪13 ᪥ᮍ᫂࠿ࡽᮅࡲ࡛ࡢỈ⵨Ẽ⏬ീ࡟ࡼࡿᑐὶᅪ୰࣭ୖᒙࡢከ‵࡞㡿ᇦࡀ♧ࡍࡼ࠺࡟㸪ᒙཌࡢ኱ࡁ࠸✚஘㞼ࡀ 10mm/h ๓ᚋࡢ㛗㞵ࢆࡶࡓࡽࡋ㸪ࡑࡢᙉ㞵ᇦࡣ๓⥺࡜ඹ࡟༡ᮾ᪉ྥ࡬㏻㐣ࡋ࡚࠸ࡓࠋ2 ᅇ┠ࡢ኱㞵ࡢࣆ࣮ࢡࡀ⌧ࢀࡓ 13 ᪥ 21 ᫬㹼14 ᪥ 15 ᫬๓࡟࠿ࡅ㸪෌ࡧୗὶ㒊࡟๓⥺ࡀ఩⨨ࡋ㸪14 ᪥ 9
᫬ࡢ᫬Ⅼ࡛ 1002hPa ࡢపẼᅽࡀᮾࢩࢼᾏࡢ೵⁫๓⥺ୖ࡟Ⓨ⏕ࡋࡓࠋࢡࣛ࢘ࢻࢡࣛࢫࢱ࣮ࢆక࠺ࡇࡢపẼᅽࡣ
14 ᪥ 21 ᫬㡭ࡲ࡛㐜࠸㏿ᗘ࡛໭ᮾ㐍ࡋ࡚࠸ࡓࡓࡵ㸪ᬮ‵✵Ẽࡢ౪⤥※࡜࡞ࡾάⓎ࡞✚஘㞼ࡀ⥅⥆ⓗ࡟ὶධࡍࡿ
Ẽ㇟≧ἣ࡬࡜Ⓨᒎࡋࡓࠋ
ྠᮇ㛫ࡢ୰ᅜᆅ᪉ࢆ୰ᚰ࡜ࡋࡓẼ㇟≧ἣࢆ㖄┤᪉ྥࡢ㝵ᒙⓗ࡟ᤊ࠼ࡓሙྜ㸪ᅗ 6 ࡢࡼ࠺࡟㸪ୗᒙࡢ 850hPa
㠃࡛ࡣୖὶ㒊ཬࡧᒣ㝧ᆅ᪉࡛ᬮẼ⛣ὶࡢᙉᙅࢆ⧞ࡾ㏉ࡋ㸪▷᫬㛫ᙉ㞵➼࡛㝆Ỉ㔞ࡢቑ኱ࡋࡓ 14 ᪥ 9 ᫬㡭ࢆቃ࡟㸪➼ ⥺ࡢ㞟୰ᖏࡀฟ⌧ࡍࡿࡼ࠺࡟࡞ࡗࡓࠋࡇࡢ㡿ᇦࡣ೵⁫๓⥺ࡢ༡⦕࡟఩⨨ࡋ㸪ୗὶ㒊࠾ࡼࡧᒣ㝜ᆅ᪉࡛ࡣᐮẼࡀὶධࡋጞࡵࡿ᫬ᶵ࡟ࡶ࡞ࡗ࡚࠸ࡓࠋࡲࡓᮇ㛫ࢆ㏻ࡋ㸪700hPa 㠃࠿ࡽᆅୖࡲ࡛‵ᩘ 3℃ᮍ‶ࡢ‵₶ᒙࡀᙧᡂࡉࢀࡿഴྥ࡟࠶ࡾ㸪13 ᪥ 9 ᫬࡟ࡣୖ᪼ὶࡢᴟ኱࡜࡞ࡿ㸫84hPa/h ࢆほ ࡍࡿ࡞࡝✚஘㞼⩌ࡢⓎ㐩ࡀ༑ศண᝿ࡉࢀࡿ≧ἣ࡛࠶ࡗࡓࠋ௒ᅇࡢὥỈࢆⓎ⏕ࡉࡏࡓ኱㞵ࡣẼᅽࡢ㇂ࡢ㏻㐣࡟ࡣࡼࡽࡎ㸪300hPa 㠃࡟࠾࠸࡚ࢪ࢙

96















































97

ࢵࢺẼὶࡀ୰ᅜ኱㝣ᮾᓊ࡛⺬⾜ࡋጞࡵࡓࡢࡣ 14 ᪥ 9 ᫬௨㝆࡛㸪ࢪ࢙ࢵࢺẼὶࡢ༡ୗ࡟ࡼࡾ๓⥺ཬࡧᙉ㞵ᇦࡀỤࡢᕝὶᇦ࠿ࡽ㞳ࢀࡿ≉ᚩࡀ⾲ࢀ࡚࠸ࡓࠋୗᒙ࠿ࡽᬮ‵✵Ẽࡀὶධࡋࡓ㝿࡟క࠺ ᗘୖ᪼ࡣ 500hPa 㠃ࡲ࡛ཬࡧ㸪༡す࠿ࡽすࡢ㢼ྥኚ໬࡟ྜࢃࡏ࡚㢼㏿ࡀቑ኱ࡋࡓࠋ14 ᪥ 9 ᫬ࡢ᫬Ⅼ࡛Ụࡢᕝὶᇦࡣ㈇ ᗘࡢ㧗Ẽᅽᛶᚠ⎔ᇦ࡟୍ᗘධࡗࡓࡀ㸪ఀணℿ௜㏆࡛ 3910-6 /s ࡢṇ ᗘᴟ኱ࡀ⾲ࢀࡿ࡞࡝పẼᅽᛶᚠ⎔ࡢ㡿ᇦࡀ࿘㎶㒊࡟࠶ࡾ㸪୺࡟୰࣭ୗᒙ࡛Ⓨ⏕ࡋࡓ✚஘㞼ࡀỤࡢᕝࡢỈ఩ୖ᪼࡟ࡘ࡞ࡀࡿ኱㞵ࡢㄏᅉ࡟࡞ࡗࡓ࡜⪃࠼ࡽࢀࡿࠋ
ࡇࡇ࡛Ụࡢᕝୗὶ㒊࡟࠾ࡅࡿỈ఩ኚ໬࡟ࡘ࠸࡚ศᯒࡍࡿࠋ㇂ఫ㒓࡛ࡣ㸪13 ᪥ 19 ᫬㡭࡟ 1 ᅇ┠ࡢᴟ኱Ỉ఩
10.48m ࢆグ㘓ࡋࡓࠋ14 ᪥ 8 ᫬㡭࡟ỏ℃ὀពỈ఩ࡲ࡛పୗࡋࡓࡀ㸪ỏ℃Ⓨ⏕ᚋࡢ 14 ᪥ 21 㡭࡟᭦࡞ࡿᴟ኱Ỉ఩
ࡢ 13.98m ࡟㐩ࡋࡓࠋᕝᮏ࡛ࡣ㸪13 ᪥ 17 ᫬㡭࡟ỏ℃༴㝤Ỉ఩ 8.60m ࢆ㉸࠼ࡿ 1 ᅇ┠ࡢᴟ኱Ỉ఩ 9.25m ࢆグ㘓ࡋ㸪14 ᪥ 7 ᫬㡭࡟ 6.33m ࡲ࡛పୗࡋࡓࡀ㸪ỏ℃Ⓨ⏕ᚋࡢ 14 ᪥ 17 ᫬㡭࡟᭦࡞ࡿᴟ኱Ỉ఩ࡢ 11.16m ࡟㐩ࡋࡓࠋᕝᮏ࡛ࡶᮇ㛫ᚋ༙ࡢỈ఩ࡀ㧗࠸ 2 ࡘࡢᒣᆺࡢࣆ࣮ࢡࡀ☜ㄆ࡛ࡁ㸪18㹼20 ᫬㛫࡛ 2 ᅇỏ℃༴㝤Ỉ఩ࢆ㉸㐣ࡍࡿኚືࡢ⃭ࡋ࠸≧ἣ࡛࠶ࡗࡓࠋࡲࡓ὾ཎ࡛ࡣ㸪1 ᅇ┠ࡢᴟ኱Ỉ఩ࡀ 13 ᪥ 15 ᫬㡭ࡢ 10.82m㸪2 ᅇ┠ࡢᴟ኱Ỉ఩ࡀ
14 ᪥ 15 ᫬㡭ࡢ 12.31m ࡛࠶ࡗࡓࡇ࡜࠿ࡽ㸪௒ᅇࡢฟỈࡣᖹᖖ᫬ࡢ⣙ 4 ಸ௨ୖ࡟┦ᙜࡋ࡚࠸ࡓࠋୗὶ㒊࡛ࡢ 3
ᆅⅬ࡛ࡢỈ఩ኚ໬ࢆ⥲ᣓࡍࡿ࡜㸪ୖὶ㒊ࢆ୰ᚰ࡜ࡋࡓⳘ኱࡞㝆Ỉ㔞ཬࡧὶᇦ඲య࡛ࡢᖹᆒⓗ࡞㝆Ỉᙉᗘࡢቑຍࡀ㸪2 ᅇ┠ࡢᴟ኱Ỉ఩ࡢୖ᪼ࡸୗὶ㒊࡛ࡢ⁄Ỉࢆཬࡰࡋࡓ࡜࠸࠼ࡿࠋ

㸬⪃ ᐹ
6㸬 ᮏ◊✲࡛ࡣ⌧ᆅㄪᰝ➼࡟ࡼࡾ㸪Ἑᕝࡢὶ㊰ᙧែཬࡧỈὶࡢ౵㣗స⏝࡟⾲ࢀࡿἙᗋ㧗ᶆ㧗ࡀỏ℃つᶍ࡜࡝ࡢࡃࡽ࠸ࡢ┦㛵ࢆࡶࡘ࠿ࢆ᳨ウࡋࡓࠋྛᆅⅬࡢᶆ㧗࡜㸪⌧ᆅㄪᰝᆅⅬ࡟࠾ࡅࡿ᭱኱ᾐỈ㧗ࢆ⾲ 3 ࡜⾲ 4 ࡟♧ࡍࠋὶ㊰ࡀ┤⥺ࡲࡓࡣᒅ᭤࡟ヱᙜࡍࡿᆅⅬ࡛ࢹ࣮ࢱࢆẚ㍑ࡋࡓ⤖ᯝ㸪Ụὠᕷෆࡢᒅ᭤ᆅⅬ࡯࡝᭱኱ᾐỈ㧗ࡀࡸࡸ኱ࡁ࠸ഴྥ࡛࠶ࡿࠋࡓࡔࡋ㸪௒ᅇࡢ⌧ᆅㄪᰝ࡟࠾ࡅࡿィ ࡟ㄗᕪࢆྵࡴศ㸪ὶ㊰ᙧែࡀᚲࡎࡋࡶᾐỈつᶍ࡟┤98⤖ࡍࡿ࡜ࡣ᩿ᐃ࡛ࡁ࡚࠸࡞࠸ࠋࡲࡓ௧࿴ 3 ᖺ 8 ᭶ὥỈ࡟࠾࠸࡚㸪ᅜᅵ஺㏻┬୰ᅜᆅ᪉ᩚഛᒁࡀ☜ㄆࡋࡓྜィ 28 ࡢእỈ࡟ࡼࡿᾐỈᆅⅬࢆᇶ࡟㸪Ἑཱྀ࠿ࡽࡢ㊥㞳࡜ᖹᆒ-᭱῝Ἑᗋ㧗ࡢᶆ㧗ᕪࡢࢹ࣮ࢱࢆࣉࣟࢵࢺࡋࡓ⤖ᯝ㸪ᅗ 8 ࡢࡼ࠺࡟┦㛵ಀᩘࡀ
㸫0.429 ࡜ẚ㍑ⓗ┦㛵ᛶࡣప࠸ࠋᖹᆒ-᭱῝Ἑᗋ㧗ᶆ㧗ᕪࡢᖹᆒ್㸪➨ 3 ᅄศ఩ᩘࡣࡑࢀࡒࢀ 5.11m㸪6.40m ࡜࡞ࡾ㸪ᶆ㧗ᕪ
ࡀ 8.0m ௨ୖ࡟┦ᙜࡍࡿᆅⅬࡶ 4 ⟠ᡤ࠶ࡗࡓࠋἙཱྀ࠿ࡽࡢ㊥㞳ࡀ 25km ࡢᆅⅬࡼࡾୗὶഃ࡛ࡣ౛እࡶ࠶ࡿࡀ㸪0~55km ᆅⅬ㛫ࡢୗὶ㒊ࢆᕧどⓗ࡟ᤊ࠼ࡿ࡜㸪ᖹᆒ-᭱῝Ἑᗋ㧗ᶆ㧗ᕪࡀᴟ➃࡟኱ࡁ࠸ሙᡤ࡛ࡣ⁄Ỉࡢྍ⬟ᛶࡣ┦ᑐⓗ࡟ప࠸࡜࠸࠼
ࡿࠋ௒ᅇࡢỏ℃ࡢẼ㇟せᅉ࡟ࡣ㸪ᑐὶᅪ୰࣭ୗᒙ࡛Ⓨ㐩ࡋࡓ✚஘㞼⩌࡟ࡼࡿୖὶ㒊ࢆ୰ᚰ࡜ࡋࡓ⥅⥆ⓗ࡞኱㞵㸪೵⁫๓⥺ཬࡧࡑࡢ༡⦕࡛ࡢୗᒙࢪ࢙ࢵࢺ㸪೵⁫๓⥺ୖ࡟Ⓨ⏕ࡋࡓపẼᅽ࡟ࡼࡿᬮ‵✵Ẽࡢὶධ㸪㧗Ỉ఩ࡢ≧ἣୗ࡟࠾ࡅࡿ㝆Ỉ㔞ᛴቑ㸪ࡀᣲࡆࡽࢀࡿࠋࡲࡓ㸪࢝ࣞࣥࢺࣜࢵࣉࣝࡸࢹ࣮ࣗࣥཬࡧ
ὥỈሁ✚≀ࡀ☜ㄆࡉࢀࡓࡇ࡜࠿ࡽ㸪ỤὠᕷෆࡢἙ㐨ᒅ᭤ᆅⅬࢆ୰ᚰ࡟⁄Ỉࡢ༴㝤ᛶࡀࡼࡾ㧗ࡲࡾ㸪ỏ℃༴㝤Ỉ఩ࡼࡾࡉࡽ
࡟ 2㹫௨ୖ㧗Ỉ఩ࡀ⥅⥆ࡉࢀࢀࡤ㸪ᗈ⠊ᅖࡢᾐỈ࡟Ⓨᒎࡋ࠺ࡿ࡜࠸࠼ࡿࠋᘬ⏝ᩥ⊩㸦1㸧ᅜᅵ஺㏻┬㸪➨ 74 ᅇἙᕝᩚഛᇶᮏ᪉㔪᳨ウᑠጤဨ఍㸪ཧ⪃㈨ᩱ 4-2 ỤࡢᕝỈ⣔ࡢ≉ᚩ࡜ㄢ㢟㸪2007㸬
㸦2㸧ᅜᅵ஺㏻┬୰ᅜᆅ᪉ᩚഛᒁ㸪௧࿴ 2 ᖺ 7 ᭶㇦㞵࡟ࡼࡿ୰ᅜᆅ᪉ᩚഛᒁ⟶ෆࡢฟỈᴫἣ࠙➨ 3 ሗࠚ㸪2020 ᖺ 8 ᭶
25 ᪥グ⪅Ⓨ⾲㈨ᩱ㸪2020㸬㸦3㸧Ẽ㇟ᗇ㐣ཤࡢ㝆Ỉ㔞ࢹ࣮ࢱ㸦1979㹼2020 ᖺࡢ 8 ᭶㝆Ỉ㔞ࢹ࣮ࢱ㸪2021 ᖺ 8 ᭶ 11 ᪥㹼19 ᪥᪥ẖ✚⟬㝆Ỉ㔞㸪1᫬㛫᭱኱㝆Ỉ㔞㸧㸪2021㸬https://www.data.jma.go.jp/gmd/risk/obsdl/index.php
㸦4㸧Ẽ㇟ᗇ࢔ࢪ࢔ኴᖹὒᇦᆅୖኳẼᅗ ୡ⏺༠ᐃ᫬࡛ 2021 ᖺ 8 ᭶ 11 ᪥ 0 ᫬㹼15 ᪥ 18 ᫬ 㸪2021㸬
https://www.data.jma.go.jp/fcd/yoho/wxchart/quickmonthly.htmlɾ
㸦2021 ᖺ 8 ᭶ 15 ᪥㜀ぴ㸧㸦5㸧᪥ᮏẼ㇟༠఍㐣ཤࡢẼ㇟⾨ᫍほ ࢹ࣮ࢱ ㉥እ⏬ീ㸪ྍど⏬ീ㸪Ỉ⵨Ẽ⏬ീ㸦2021 ᖺ 8 ᭶ 12 ᪥ 0 ᫬㹼
16 ᪥ 0 ᫬㸧㸪2021㸬https://tenki.jp/past/2021/08/12/satellite/japan-near/㸦6㸧Ẽ㇟ᗇ㧗ᒙኳẼᅗ ୡ⏺༠ᐃ᫬࡛ 2021 ᖺ 8 ᭶ 11 ᪥ 0 ᫬㹼15 ᪥ 18 ᫬ 㸪2021㸬
https://www.jma.go.jp/bosai/numericmap/#type=upper㸪㸦2021 ᖺ 8 ᭶ 16 ᪥㜀ぴ㸧㸦7㸧ᅜᅵ஺㏻┬Ἑᕝᒁ㸪ỤࡢᕝỈ⣔ࡢὶᇦཬࡧἙᕝࡢᴫせ ᱌ 㸪2007㸬
㸦8㸧ᕝࡢ㜵⅏᝟ሗᅜᅵ஺㏻┬㐣ཤ 1 㐌㛫ࡢほ Ỉ఩㸦8 ᭶ 13 ᪥ 0 ᫬㹼8 ᭶ 19 ᪥ 24 ᫬㸧㸪2021
https://www.river.go.jp/kawabou/pcfull/tm?itmkndCd=4&ofcCd=22308&obsCd=2&isCurrent=true&fld=0㸪㸦2021 ᖺ 8 ᭶ 20 ᪥㜀ぴ㸧
㸦9㸧ᅜᅵ஺㏻┬୰ᅜᆅ᪉ᩚഛᒁ㸪௧࿴ 3 ᖺ 8 ᭶ 11 ᪥࠿ࡽ 19 ᪥࡟࠿ࡅ࡚ࡢ๓⥺࡟ࡼࡿ኱㞵୰ᅜᆅ᪉ᩚഛ
ᒁ⟶ෆࡢฟỈᴫἣ࠙➨ 3 ሗ ᭱⤊ሗ ࠚ㸪2021 ᖺ 10 ᭶ 1 ᪥グ⪅Ⓨ⾲㈨ᩱ㸪2021㸬㸦10㸧ᅜᅵ஺㏻┬Ἑᕝᒁ㸪ỤࡢᕝỈ⣔Ἑᕝᩚഛᇶᮏ᪉㔪 ᇶᮏ㧗Ỉ➼࡟㛵ࡍࡿ㈨ᩱ ᱌ 㸪2007㸬東北地域災害科学研究

第58巻（2022）

99

Estimation of floodwater depth in Quang Tri province using Sentinel-1 data
Vuong Tai Chi1, Dinh Nhat Quang2,*, Nguyen Xuan Tinh3, Hitoshi Tanaka3

Abstract
Floodwater depth is an essential parameter to assess the flood damages and release the prompt
decisions to mitigate severe consequences. In the context of climate change, water-related disaster becomes
more frequent and severe; therefore, rapid estimation of floodwater depth plays a vital role in disaster
response and damage mitigation. In recent years, the approach of integrating Sentinel-1 data that is
independent of weather conditions and GEE, a cloud-based platform attracts many researchers in flood extent
and floodwater depth assessment. In this paper, the authors apply a Google Earth Engine implementation of
the Floodwater Depth Estimation Tool (FwDET-GEE) algorithm on the Sentinel-1 images to detect the flood
extent extraction and DEM accuracy improvement for floodwater depth estimation. The authors also use GEE
to conduct further analysis about flood damages based on the estimated floodwater level dataset and thecloud-based datasets of population, cropland, and urban area. The results reveal that 0.5m floodwater depth
has covered an area of 19,000 ha, and 3m floodwater depth covered an area of 800 ha in the Hai Lang district.
Furthermore, the 2020 flood event has respectively impacted 9,100 ha of cropland and 360 ha of the urban
area.
1. Introduction
Flood is a phenomenon causing massive catastrophic impacts on humans and nature. In recent years,
extreme floods have been more frequent and severe on the Central Coast of Vietnam. Quang Tri province
has diverse water resources with a dense river network, composed of 3 main river basins with a total
catchment area of more than 4,000 km2 and more than 600,000 residents (Quang Tri Province, n.d.).
Therefore, rapid floodwater depth assessment is crucial for mitigating flood risk on people andinfrastructures.
Recently, satellite-based Remote Sensing Technology has been shown as a valuable dataset for floodrisk and depth assessment (Abrishamchi et al., 2012; Anusha and Bharathi, 2020; Do et al., 2019; Quang etal., 2021; Vuong Tai Chi et al., 2020). Among available satellite data, Sentinel-1 Synthetic Aperture Radar(SAR) data has become a more attractive data resource for flood mapping and damage assessment (Huang
and Jin, 2020). This is because Sentinel-1 SAR provides Level-1 Ground Range Detected products
independent of weather conditions, especially clouds. For this reason, Sentinel-1 data can even be used toanalyze under cloudy conditions during flood events, which is a huge difference compared to the Optical
Satellite data. Moreover, Google Earth Engine (GEE), a cloud-based image processing platform, appears as
a high-performance tool to access numerous satellite images and process a large scale of geospatial data
(Gorelick et al., 2017). This approach helps reduce significant time intervals for data processing compared to
desktop-based tools, which require a considerable duration for data downloading and processing (Tiwari etal., 2020).
The FwDET-GEE tool, developed by Peter et al.(2020), appears to be an effective and reliable tool
for floodwater depth estimation implemented on the GEE platform. It uses flood extent layer and DEM data
1

Former student of Thuyloi University, 175 Tay Son, Dong Da, Hanoi, Vietnam
Thuyloi University, 175 Tay Son, Dong Da, Hanoi, Vietnam
3
Tohoku University, 6-6-06 Aoba, Sendai 980-8579, Japan*
Corresponding author2

100

as its main inputs. Peter et al.(2020) evaluated the results from FwDET-GEE with iRIC-FaSTMETCH
hydrodynamics model. They achieved an RMSE up to 0.7m and sufficient good to apply for floodwater depth
estimation.
This paper aims to integrate FwDET-GEE with Sentinel-1 data for floodwater depth estimation on
the GEE platform. Further assessment about exposed people, affected cropland, and urban areas are also
conducted to obtain an overview of flood damages in Quang Tri province.
2. Case study and data collection
2.1. Case study
Quang Tri province is located on the North
Central coast of Vietnam with a total area of 3,469 km2
and 75km of coastline (Quang Tri Statistics Office,2015). The province has diverse and complex terrain,
comprising wide sand dunes, a deep delta area along thecoast, and an increasingly high elevation towards theWest. The high mountainous area is about 100km awayfrom the sea. Quang Tri province has a dense river
network with 17 primary rivers and 13 secondary ones,
supplying water for more than 4000km2 river basin(NewsTech and SWS Consulting Engineering S.r.l(Italy), 2019). These topography characteristics makethe province vulnerable to storms with very highlandslide risk in the West and heavy floods in the East.
Figure 1. Administrative map of Quang Tri
Quang Tri province is a very attractive tourist
province
destination with many famous historical andrevolutionary sites. Moreover, the province is a part ofthe economic center of the region and the East-West Economic Corridor (EWEC), offering multiple
opportunities for economic development and international economic integration (Vietnam Chamber ofCommerce and Industry (VCCI), 2017). However, these economic potentials are annually being threatenedby tropical storms. For instance, Quang Tri has directly suffered at least 15 tropical storms in the last three
decades and three severe storms in 2020. Especially, the Molave tropical storm, hitting Quang Tri province
from 26 October 2020, has caused extreme floods and landslides and forced thousands of people to excavate
their homes.
2.2. Data collection
Sentinel-1 data provides Level-1 Ground Range Detected (GRD) products, consisting of the SAR
data, with the advantage of operating at wavelengths without being affected by cloud cover or lack of
illumination (European Space Agency, n.d.). Sentinel-1 data provides multiple polarizations, including VH(Vertical transmit – Horizontal receive) and VV (Vertical transmit – Vertical receive) polarizations, which
provide more information on inundated areas than that in single-polarized radar. In this study, two Sentinel1 GRD scenes with a resolution of 10m are used, focusing on the flood event on 28 October 2020 caused by
the tropical storm Molave (Table 1).
Table 1. List of Sentinel-1 images used in the study
Product
Date
Polarization
S1_GRD/S1B_IW_GRDH_1SDV_20201028T224307_20201028T2243
28-Oct-20
VH + VV
32_024019_02DA78_5453
S1_GRD/S1B_IW_GRDH_1SDV_20201028T224332_20201028T2243
28-Oct-20
VH + VV
57_024019_02DA78_486D

101

Digital elevation model (DEM) represents elevation data to represent the Earth’s topographic surface.
In this study, the 30m-resolution SRTM (Shuttle Radar Topography Mission) is used as an important part ofthefloodwater
depth
estimation
process(https://developers.google.com/earthengine/datasets/catalog/USGS_SRTMGL1_003).
In addition, the assessment of flood damages are estimated based on the 100m-resolution dataset of
population statistics, and 500m-resolution dataset of cropland and urban area in Quang Tri province in 2020
from WorldPop (https://www.worldpop.org/) and Moderate Resolution Imaging Spectroradiometer(MODIS) image, respectively.
3. Methodology
The procedure for floodwater depth estimation follows three main steps: i) flood extent extraction;ii) DEM accuracy improvement; iii) floodwater depth estimation (Figure 2).
For flood extent extraction, the authors based on the ratio between pixel values of the during-floodevent image and the before one to produce the temporal water layer. The generated temporary water layer
includes floodwater and the water resulting from radar error on mountainous areas. In GEE, this error is
assigned to low values, corresponding to the values of water. In this context, the areas having a slope ofgreater than 5% are removed based on the DEM layer from the HydroSHEDS data, also available in GEE.
This procedure helps to remove the non-correct pixels and retrieve only the floodwater layer. Within theprocess of floodwater extraction, the removal of permanent water is not conducted since the permanent water
is included in both before and during-flood-event images.

Figure 2. Flowchart of the methodology for floodwater depth estimation
Two filtering processes are used to improve the accuracy of DEM data. The first process is applied
for the entire DEM layer using a low-pass filter with a 3×3 square kernel and the modified z-score. Eachpixel with an outlier value is detected and replaced by the median of the surrounding eight pixels. The second
process is similar but applied for DEM pixels nearest the floodwater surface boundary pixels.
After the DEM improvement, the boundary pixel elevations of flood extent are extracted based oncorresponding pixels of the DEM layer. These values are assigned to the nearest pixels to the flood extent
boundary by the focal statistic method with the condition of choosing the smallest neighborhood value. This
process is conducted until assigned to all pixels within the floodwater surface. For floodwater depth
estimation, the elevation of floodwater surface is subtracted from corresponding pixel elevations of DEM.
After using a low-pass filter to calculate the average value for each pixel based on its 3×3 neighborhood, thefinal floodwater depth layer is retrieved. The estimated floodwater depth is validated using the 2Dhydrodynamic model – MIKE 21.

102

4. Results and discussion
4.1. Flood extent and floodwater depth of the flood event on 28 October 2020
Figure 3 shows the results of flood extent extraction with a total area of more than 19,000 ha of
Quang Tri province during the flood event on 28 October 2020. From Figure 3a, floodwater was mainly inthe low-elevation region along the coast and mountainous area. Hai Lang district has the largest inundated
area with nearly 8,000 ha and accounts for 50% of the whole inundated area. The Quang Tri floodwater depth
results in Figure 3b reveal mainly less than 0.5m and covered around 10,500 ha. A 3m floodwater depth
covered more than 400ha of the Hai Lang district.

a) Flood extent mapb) Inundation map
Figure 3. Flood extent and floodwater depth of the flood event on 28 October 2020 in Quang Tri province
4.2. Flood damage assessment of flood event on 28 October 2020
Based on the flood extent boundary, the layers of the population, cropland, and urban area are
extracted on GEE to assess the flood damages during the target flood event. The estimation reveals that about
54,000 people in Quang Tri province were exposed to floods, in which Vinh Linh and Dong Ha were two
districts with the highest affected population density (Figure 4a). In addition, the region with the deepest
floodwater level in Hai Lang district had the lowest population density exposed to the flood event on 28
October 2020.
The results in Figure 4b highlight that cropland area was impacted by less-than-0.5m floodwater levelwith more than 5,000 ha. In addition, the most affected cropland area focused on Trieu Phong, Hai Lang, andVinh Linh districts with a total area of 3,450 ha, 2,000 ha and 1,881 ha, respectively. On the other hand, theaffected urban area was mainly in Hai Lang district with around 200 ha, in which about 7.3 ha was inundatedby 2m floodwater depth..

103a) Exposed peopleb) Affected Cropland and Urban area
Figure 4. Damage assessment due to the flood event on 28 October 2020 in Quang Tri province
5. Conclusion
In this study, the authors introduce the FwDET-GEE algorithm for rapidly estimating floodwater
depth on GEE with integration with Sentinel-1 data. This approach helps reduce a significant time interval
and requires minimal computer capability. After achieving the floodwater depth result, the authors integratewith the population, cropland, and urban area dataset recorded in 2020 to give the detailed assessment offlood damages to Quang Tri province in the flood event of 28 October 2020. The results reveal that thedominant floodwater depth was less than 0.5m covered about 10,500 ha; in addition, greater-than-3m
floodwater depth covered the area of 800 ha and mainly appeared in the Hai Lang district. Furthermore, theflood event on 28 October 2020 impacted about 54,000 people, 9,100 ha and 360 ha of cropland and urban
area, respectively. In the future, since natural flood disaster becomes more frequent and severe, integrating
Sentinel-1 data and GEE will help achieve reliable assessment rapidly, hence obtaining better disaster
response and management.
6. Reference
Abrishamchi, A., Dashti, M., Alamdari, N., Salavitabar, A., 2012. A GIS-Google Earth Based Approach to
Estimating the Flood Damage Function in Large River Basins 3811–3821.
https://doi.org/10.1061/41173(414)399
Anusha, N., Bharathi, B., 2020. Flood detection and flood mapping using multi-temporal synthetic apertureradar and optical data. Egypt. J. Remote Sens. Space Sci. 23, 207–219.
https://doi.org/10.1016/j.ejrs.2019.01.001
Do, A., Kralli, V., Vries, S., Viet, N., Stive, M., 2019. Morphodynamics of a Seasonal Inlet: A Case Study
Using Remote Sensing and Numerical Modelling for Cua Dai Inlet, Central Vietnam. pp. 417–425.
https://doi.org/10.1007/978-981-15-0291-0_58
European Space Agency, n.d. Sentinel-1 - Overview - Sentinel Online - Sentinel Online [WWWDocument]. Sentin.-1 Overv. URL https://sentinels.copernicus.eu/web/sentinel/missions/sentinel1/overview

104

Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., Moore, R., 2017. Google Earth Engine:
Planetary-scale geospatial analysis for everyone. Remote Sens. Environ., Big Remotely Sensed
Data: tools, applications and experiences 202, 18–27. https://doi.org/10.1016/j.rse.2017.06.031
Huang, M., Jin, S., 2020. Rapid Flood Mapping and Evaluation with a Supervised Classifier and Change
Detection in Shouguang Using Sentinel-1 SAR and Sentinel-2 Optical Data. Remote Sens. 12,2073. https://doi.org/10.3390/rs12132073
NewsTech, SWS Consulting Engineering S.r.l (Italy), 2019. Development of hydrological, hydraulicmodels and supplementary surveying (Package C1- C1: “River basins-wide integrated Disaster
Risk Management Plan (8 river basin 10 province)”).
Peter, B.G., Cohen, S., Lucey, R., Munasinghe, D., Raney, A., Brakenridge, G.R., 2020. Google EarthEngine Implementation of the Floodwater Depth Estimation Tool (FwDET-GEE) for Rapid andLarge Scale Flood Analysis. IEEE Geosci. Remote Sens. Lett. 19, 1–5.
https://doi.org/10.1109/LGRS.2020.3031190
Quang, D.N., Linh, N.K., Tam, H.S., Viet, N.T., 2021. Remote sensing applications for reservoir waterlevel monitoring, sustainable water surface management, and environmental risks in Quang Nam
province, Vietnam. J. Water Clim. Change. https://doi.org/10.2166/wcc.2021.347
Quang Tri Province, D. of F.A., n.d. Overview of Quang Tri [WWW Document]. Dep. Foreign Aff. Quang
Tri Prov. URL http://songoaivu.quangtri.gov.vn/en/about/Overview-of-Quang-Tri.html
Quang Tri Statistics Office, 2015. Quang Tri Statistical Yearbook 2015.
Tiwari, V., Kumar, V., Matin, M.A., Thapa, A., Ellenburg, W.L., Gupta, N., Thapa, S., 2020. Floodinundation mapping- Kerala 2018; Harnessing the power of SAR, automatic threshold detection
method and Google Earth Engine. PLOS ONE 15, e0237324.
https://doi.org/10.1371/journal.pone.0237324
Vietnam Chamber of Commerce and Industry (VCCI), 2017. Going for Gold - The Central Region ofVietnam.
Vuong Tai Chi, Dinh Nhat Quang, Ho Sy Tam, Nguyen Trung Viet, 2020. Rapid assessment of flood
extent and damages in Quang Nam province by using Sentinel-1 data. J. Water Resour. Environ.
Eng. 49–56.

東北地域災害科学研究

第58巻（2022）

105

Shoreline change and impacts of coastal protection structures on Da Rang
River mouth and adjacent coast, south central of Vietnam
Nguyen Trong Hiep1, Hitoshi Tanaka2, Nguyen Xuan Tinh3, Nguyen Trung Viet4
Abstract
Da Rang River mouth, Phu Yen, Vietnam is a representative coastal area of Vietnam where recently
was observed a significant change on the morphology change. The morphology change was resulted byeither natural and human influences. Since 2016, several coastal constructions (jetties, groins,breakwaters) had been implemented to stabilize the mouth area and the morphology of the river mouth isnow very different from it in the last decade. This study, by satellite image analysis, provides the last
decadal shoreline change in the entire Phu Yen coast from Ganh Ba Seacliff to Da Nong River mouth. The
severe erosion can be found in region B where the old sand spits were both eroded in the mouth and pushed
into the river channel after the typhoon in 2017. The morphology of the Da Rang river mouth been recently
stabilized by new coastal structures constructed since 2018.
Keywords: Da Rang River mouth, Phu Yen Coast, coastal constructions, shoreline erosion.
1. INTRODUCTION
River mouths, estuaries or coastal regions in general are considered the centralized regions for socioeconomic development in almost all countries in the globe. The studies regarding coastal processes,
mechanism and potential coastal morphological change have been conducted broadly in the world in favourof coastal management, sustainable development, coastal protection and countermeasures against
catastrophes.
Vietnam is one of a few countries in the world having a long coastline along the country. This brings agreat deal of advantages for the development of many aspects such as economics, tourism, etc. However,
the responsibility of preserving the coastline stability by which affected overwhelmingly natural change
and nowadays mankind is also vital challenge. In recent years, many areas in Vietnam, particularly incentral region, have reported on the erosion occurring severely. Cua Dai and Nha Trang are two coastal
regions have had deep concern about coastal changes for several years lately. Viet et al. (2014) presented
the erosion of sandy beach on the right side of the Cai River mouth, Nha Trang City associated to thedifference of wave conditions in monsoon and non-monsoon periods. The study also discussed theinfluence of protrusive hotel similar to a groin that blocks the alongshore transport drift. Further analyses
on the evolution of Nha Trang Coast utilizing shoreline dataset extracted from time-average images ofvideo-camera monitoring system, were discussed in Thanh et al. (2015). Tanaka et al. (2017) investigatedsevere retreat of shoreline of the sandy beach on the left side of Cua Dai River mouth, Hoi An City, central
Vietnam. In addition, Nagasawa et al. (2016) discussed the reduction of sediment supply from Thu Bon
River basin to Cua Dai River mouth due to construction of dam reservoirs as well as excessive dredge ofsand and gravel along the river channels. Noshi et al. (2015) investigated changes of coastal morphology
associated with the elongation of a sandspit and longshore sediment accumulation at the jetty in Phan Rang
City, south central Vietnam.
(1) Graduate Student, Department of Civil and Environmental Engineering, Tohoku University, 6-606 Aoba, Sendai 980-8579, Japan(2) Professor, Department of Civil and Environmental Engineering, Tohoku University, 6-6-06 Aoba,
Sendai 980-8579, Japan(3) Assistant Professor, Department of Civil and Environmental Engineering, Tohoku University, 6-606 Aoba, Sendai, 980-8579, Japan(4) Professor, Department of Civil Engineering, Thuyloi University, Hanoi, Vietnam
1

106

Similar to the coastal zones mentioned above, Darang River mouth and the adjacent coasts experienced
notable morphology and coastal changes induced by both natural and human effects. Hoang et al. (2015)
claimed the existence of the sand terrace in front of the river mouth created by floods contributing mainly
the sediment on both sides of the entrance. Hiep et al. (2020) explains the migration of the river mouth
before the sand mining in 2015 by mathematical solution of one-line model. In addition, Hiep et al. (2018)
mentioned the severe erosion of the sand spits of Darang River mouth after Typhoon in 2017. Since 2016,
multiple coastal constructions (jetties, groins, breakwaters) had been implemented to stabilize the mouth
area and the morphology of the river mouth is now very different from it in the last decade. This study, byusing shoreline analysis, provides the recent morphology change in the Da Rang River mouth and its
adjacent coast over last decade.
2. STUDY AREA
The region including Da Rang River mouth and adjacent coasts in Phu Yen, Vietnam is one of thebiggest coastal area in the south-central coast of Vietnam. Da Rang River mouth is located in Tuy Hoa City,
Phu Yen Province, south central Vietnam. Figure 1 shows the location of the study area. Da Rang Rivermouth is the estuary of Ba River and known as the longest river in the centre of Vietnam with the length of
374 km, and total basin area of 13,900 km2. The left coast of Da Rang River mouth extends from the mouth
entrance to the Ganh Ba Seacliff, while the right coast is from the mouth to Da Nong River mouth (Figure1). This mouth area is usually affected by typhoons during the rainy season which extends from September
to December. The typhoon causes heavy rainfall resulting in floods which widens the river mouth. Thisriver mouth is deemed to be one of the most important area contributing to the development of Phu Yen
Province. The mouth area is now the shelter and harbour for more than 900 small and big fishing boats andvessels. Da Rang Opening is also an active and dynamic area that the severe deposition or erosion often
occurs in the river mouth. In 2015, The deposition was so severe that hundreds of ships were unable toenter or exit, raising concerns about navigation clearance. As a result, several sand mining events were held
to alleviate the problem. After 2015, consecutive coastal protection constructions were implemented inmouth area. These constructions had the objectives to prevent the erosions on the adjacent local coasts on
both sides of river mouth.

Figure 1. Phu Yen Coast and Da Rang River mouth2

107

Regarding hydrodynamic conditions, the diurnal tide of Tonkin Gulf is the main tidal cycle having aneffect on Da Rang River mouth. During the spring tide, the maximum that tidal range can reach is about
1.7 m and the minimum is nearly 0.5 m during the neap tide. The fresh water river discharge depends
mainly on the rainfall and flood regimes of the entire basin. In flood season, river discharge can increase
up to 2100 m3/s and the annual river discharge is about 275 m3/s. Similar to other coastal regions in central
Vietnam, incident waves are mainly dominant at the northeast direction during monsoon season. Waveheight is smaller dung non-monsoon season as the northeast wind becomes less dominant. The wave rosefrom the offshore wave data from WAVEWATCH III from 2006-2016 shows the dominance of northeast
monsoon drives the wave condition Phu Yen Coast (Figure 1)
3. MATERIALS AND METHODSThe Landsat Imagery retrieved from the U.S Geological Survey (USGS) database from 2013 to 2021 isutilized as the main dataset for this study. The dataset is a combination of images taken from different
satellite missions, Landsat 7 (EMT+), Landsat 8 (OLI), and Sentinel‐2 (MSI). Some images obtained from
Google Earth data base system were also collected for this study
Since Landsat Images are TOA images (Top-of-Atmosphere), all data must be pre-processed in order toextract the best quality of the image. Acquired images are then required to go through a pre‐processing
stage that involves cloud masking, pan sharpening and down-sampling. The pre-processing techniques
followed the same process introduced by Vos et al. (2019). Landsat data from USGS assesses the cloud
cover of each image by computing the percentage of cloud pixels on the image. Some images contain large
parts covered by clouds which are difficult to perform the shoreline detection. The cloud masking stage is
optional but necessary for discarding all images that are unable to analysis. In this study, a threshold is set
for evaluating cloud percentage of each image. The value of cloud cover of any image exceeding thisthreshold is excluded from the data. The resolution of Landsat 7,8 images can be enhanced to be optimalby merging high-resolution panchromatic and lower resolution multispectral imagery due to the availabilityof panchromatic band in these images (Tu et al, 2001). The resolution can be enhanced from 30 m to 15 m
per pixel. On the other hand, the resolution of Sentinal-2 is 10 m.
For shoreline detection, firstly, the separation between water and land zones in the image is implemented
using the modified normalized water index (MNDWI) expressed as follows
SWIR1  G(1)
MNDWI
SWIR1  G
Where: SWIR1 is pixel intensity in short-wave infrared band and G is the green band. The range ofvalue is between -1 and 1. The shoreline is then detected by using K-mean clustering method. In this study,
the effect of tidal level at different capturing is not considered since the local beach slope is quite steep (≈0.1) and the possible error position error is likely smaller than the resolution of the image. The total error
in shoreline is considered to be equal to the resolution of image as 10 m.
The Shoreline change rate is obtained by applying the linear regression rate to all data sets of shoreline
position as follows
yat  b(2)

where a is slope of regression line (shoreline change rate); b is a constant.
4. RESULTS AND DISCUSSIONS
4.1 Overall shoreline change rate in Phu Yen Coast
Due to the different behaviours of shoreline change in different areas, the entire Phu Yen Coast is divided
into 4 sub-zones (A, B, C and D) from north to south. Zone B is the regions representing for the Da Rang
River mouth (Figure 1).

3

108

Figure 2. Shoreline position change in each zone

Figure 33. Sh
Fi
Shoreline
li changehrate (2013~2021)(2013 2021)
4

109

The shoreline change of Phu Yen Coast are shown in Figures 2 and 3. The shoreline changes in Zone
A, B, D shows no significant change since these areas are almost straight sandy beaches. The small
deposition can be found the Ganh Ba Seacliff and Da Nong River mouth. In the Da Nong River mouth,
due to the construction of the jetty in the past, the sand spit of this river mouth is similar to the restricted
spit which it can not elongate. The remarkable changes are found in Zone B where Da Rang River mouth
is located. The severe erosion spot with the change rate approximately 40 m/y was the position of the sandspit. As seen in Figure, the elongated sand spit was gradually eroded until it was disappeared after the
Typhoon in 2017. The deposition on the southern coast of Da Rang River mouth was due to the constructionof breakwaters and groins in this area from 2016. The highest deposition rate is at the position of jetty after
constructed in 2019. The sand accumulation is also detected at the locations of breakwaters and groins. The
deposition was resulted from the formation of tombolo.
4.2 Morphology
gy change
g in Da Rangg River mouth (Zone B)
According to Hiep et al. (2018, 2020), after the constructions of detached breakwaters and groins on
southern coast, and riprap on the northern coast at the river mouth, the sand spits were eroded severely until
they were disappeared caused by the Molave Typhoon in 2017. Figure 4 shows that the sediment from sandspits was actually over-washed and pushed into the river mouth by extremely high waves to form two
sediment strips attached on the embankment inside the river mouth. The natural subsequent recovery of thesand spits at the old locations were not observed after typhoon due to the coastal infrastructures on bothsides of the river mouth preventing the alongshore drift to transport sediment to the mouth (Hiep et al,2018). Due to the intensity of storm waves, the detach breakwaters and groins were also destroyed partly
by the typhoon in 2017. To stabilized the morphology in the river mouth, the local government continued
to constructed 5 more breakwaters beyond the position of the groins and 2 jetties on both sides of the rivermouth. After the completion of the new coastal structures, the formation of tombolo at the new breakwaters
and the deposition at the position of two jetties were observed.

Figure 4. Sand spit in Da Rang River mouh before and after the Molave Typhoon in 2017 (Zone B)
5

110

The current morphology of mouth entrance can improve the flushing behaviour of the river during flood
events. However, the wide opening can result to wave intrusion propagating inside the river mouth. Thiscan trigger erosion inside the river and possible complicated cross-shore sediment transport induced byhigh and storm waves, especially inside the Dong Tac Fishing port where diffracted wave can propagate
inside the port. The formation of subaqueous channel-spit was also discussed in several river mouth after
the construction of jetties caused by the tidal transport current induced by ebb flows (Hein et al., 2019).
Therefore, the detailed sediment transport inside the river must require further monitoring in the rivermouth and thorough analysis in the near future.
5. CONCLUSIONSThe shoreline evolution of Phu Yen Coast and Da Rang River mouth in recent years is investigated by
the satetllite image analysis. Significant change of shoreline from 2013 to 2021 was detected at the locationof Da Rang River mouth where the sand spits was dissapeared at the mouth entrance and pushed inside thechannel after the historic typhoon in 2017. The morphology of the river mouth been recently stabilzed by
new coastal structures constructed since 2018. The opening of the river mouth and new construction ofjetties requires further analyses in the future since wave-induced sediment transport inside the river mouth
can be more complicated when waves can propagate further upstream.
REFERENCES
Hein, C.J, Fallon, A.R., Rosen,P., Hoagland, P., Georgiou, I.Y., FitzGerald, D.M., Morris, M., Baker, S.,
Marino, G.B. and Fitzsimons, G. (2019). “Shoreline Dynamics Along a Developed River Mouth Barrier
Island: Multi-Decadal Cycles of Erosion and Event-Driven Mitigation”. Front Earth Science, 7:103.
Hiep, N. T., Tanaka, H., Tinh, N.T. and Viet, N.T. (2018). “Recent morphology changes at Da Rang Rivermouth, Phu Yen, Vietnam”. Tohoku Journal of Natural Disaster Science, 55, 79-84.
Hiep, N.T., Tanaka, H., Viet, N.T., Tinh, N.X. and Hoa, T.D. (2020). “Modelling river mouth evolution
under migration process”. Journal of Japan Society of Civil Engineers (Applied Mech.), Ser. A2, Vol.
76(2).
Hoang, C.V., Tanaka, H., Viet, T.N. and Binh, H.T.L. (2015). “Analysis of shoreline erosion at the Da Rang
River mouth, south central Vietnam”. Proceeding of Vietnam – Japan Workshop on Estuaries, Coasts
and Rivers, September 2015, Hoian, Vietnam, VJWECR 2015, 60-68.
Nagasawa, T., Thuy, M.T.T, Viet, T.N. and Tanaka, H. (2018). “Analysis of shoreline change in Cua Dai
beach by using Empirical Orthogonal Function”. Coastal Engineering Journal, 60(4), 548-565.
Noshi, Y., Uda, T., Kobayashi, A. and Miyahara, S. (2015). “Beach changes observed in Phan Rang Cityin southeast Vietnam”. Proceedings of the 8th International Conference on Asian and Pacific Coasts.
Tanaka, H., Hoang, V. C., and Viet, N. T. (2017). “Investigation of morphological change at the Cua Dai
River mouth through satellite image analysis”. Proceedings of the 35th International Conference on
Coastal Engineering, 35(1).
Thanh T. M., Tanaka H., Viet N. T., Mitobe Y., and Hoang V. C. (2015). “Evaluation of longshore sedimenttransport on Nha Trang Coast considering influence of northeast monsoon waves”. Journal of Japan
Society of Civil Engineers, Ser. B2 (Coastal Engineering), 71(2), I_1681-I_1686.
Tu, T.M., Su, S., hu, C., Shyu, H. and Huang, P.S. (2001). “A new look at IHS-like image fusion methods”.
Information Fusion, 2, 177–186.
Viet, N, T., Duc, N, V., Hoang, V, C., Tanaka, H., Uu, D.V., Tung, T, T., Lefebvre, J, P. and Almar, R. (2014)
Investigation of erosion mechanism on Nha Trang coast, Vietnam. Proceedings of the 19th Congress of
the Asia and Pacific Division of the International Association of Hydraulic Engineering and Research.
Vos, K., Harley, M. D., Splinter, K. D., Simmons, J. A., and Turner, I. L. (2019). “Sub-annual to multidecadal shoreline variability from publicly available satellite imagery”. Coastal Engineering. 150, 160–
174.
6

東北地域災害科学研究

第58巻（2022）

111

Assessment of river mouth variability after jetty and groyne construction: A
case study of the Volta River mouth, Ghana
Stephan Korblah Lawson1, Hitoshi Tanaka2, Keiko Udo3, Nguyen Trong Hiep4, and Nguyen Xuan
Tinh5
Abstract
The response of the Volta River mouth to the construction of a jetty and groyne system wasstudied using satellite images from Landsat and Sentinel-2. Prior to the construction of these coastal
structures, the river mouth sandspits exhibited a cyclic morphological pattern which included sandspit
elongation, spit breaching and deposition of the breached updrift spit onto the downdrift beach. However,a new morphological regime has been observed at the river mouth. Results from the image analysis has
shown that, intrusion of the sandspit into the estuary, development of offshore shoals, accretion anderosion of the sandspits due to an alteration of the sediment budget are some morphological changes thathave occurred at the river mouth.
Keywords: Coastal structures, river mouth, sandspit, satellite image analysis, Volta River mouth.
1. INTRODUCTION
In many coastal regions, jetties and groyne systems have been utilized in beach stabilization andflood related projects. These coastal structures also facilitate tidal exchange and channel navigation
especially at river mouths or inlets. In the design phase of these projects, several attempts are made to
predict the interactions of these structures with prevailing hydrodynamic conditions. In most cases,
unforeseen alterations are observed at such locations. One of such cases is the construction of the Pranburi
Jetties in Thailand. A study by Phanomphongphaisarn et al. (2020) showed that the post construction
period disagreed with the simulations in the design phase of the project which resulted in the constructionof three detached breakwaters north of the jetty. This was done through the use of satellite images.
Another study by Tanaka & Lee (2003), at the Shiribetsu River mouth in Japan revealed a decrease inwave set-up after a jetty was constructed.
The Volta River mouth was chosen for the study mainly because of the presence of a jetty on thewestern side of the river mouth. Also present on this side of the river mouth is a groyne system which
covers a 16 km stretch with each groyne spaced at 800 m. These structures were constructed as part of
the Ada Sea Defence Project (ASDP) from 2012 – 2016. The project was aimed at controlling the severe
beach erosion, restricting the growth of the updrift sandspit, improve tidal exchange and navigation(Mensah & FitzGibbon, 2013).
2. STUDY AREA AND ENVRIONMENTThe Volta River mouth is situated at Ada-Foah on the eastern coast of Ghana, West Africa (Figure1). The river drainage area is approximately 400,000 km2 which is made up of catchment areas within
Mali, Burkina Faso, Ivory Coast, Ghana, Togo and Benin. Several hydro-electric and irrigation dams
have been constructed on the Volta River network. The Akosombo and Kpong dams are the closest dams
located upstream of the river mouth which have affected the flow rate and fluvial sediment supply to theriver mouth. Prior to dam construction, mean monthly flow rates over 4000 m3/s were recorded and thissubsequently reduced to about 2000 m3/s after dam construction. A study by Amenuvor et al. (2020)
indicates the reduction of the annual fluvial sediment supply from 180×106 to 13×106 m3/year due to dam
operations.

The coastal zone around the river mouth is marked by a micro-tidal environment with tides being
semi-diurnal. The average tidal range is 1m with spring tides at 1.28m and neap tides at 0.64m (Allersma
1,2,4,5
Department of Civil and Environmental Engineering, Tohoku University, 6-6-06 Aoba, Sendai
980-8579, Japan.
3International Research Institute of Disaster Science, Tohoku University, 468-1 Aoba, Sendai 980-8572,
Japan.

112& Tilmans, 1993). The significant wave heights along the river mouth ranges from 0.5 to 3.30 m basedon wave data retrieved from the WaveWatch III model. The dominant wave direction is southwest fromswells generated in the Atlantic Ocean. In addition, the West African Monsoon affects the wave heights,
with the largest wave heights generated from March-October. The induced longshore currents along thiscoast is unidirectional from the west to east and the average longshore sediment transport at the Volta
River mouth is about 1.25 ×106 m3/year as determined by sandspit and wave analysis (Lawson et al.,2021).

Figure 1. Map of the Volta River mouth at Ada-Foah, Ghana.
3. MATERIALS AND METHODS
3.1 Data Collection and Shoreline Extraction
The primary dataset used in this study were satellite images retrieved from the Google EarthEngine repository. These included images from Landsat 5 (TM), Landsat 7 (EMT+), Landsat 8 (OLI) andSentinel-2 (MSI). The image collection period for the study extended from March, 2002 to July, 2021.
This was chosen due to the significant morphological evolutions observed at the river mouth before andafter the completion of the ASDP.
The shorelines for the study area were extracted using the Coastsat toolkit (Vos et al., 2019). The
toolkit uses a supervised image classification and a sub-pixel resolution border segmentation to extract
shorelines with a horizontal accuracy of 10m (Vos et al., 2019). The image classification stage enables
the definition of the sand, water, white-water and other land features whereas the sub-pixel segmentation
stage uses the Modified Normalized Water Index (MNDWI) to categorize the water and land pixels. The
shoreline is then defined using Otsu’s thresholding and the Marching Squares algorithms.
3.2 River Mouth Variability Analysis
To ascertain the river mouth variability before and after the construction of the jetty and groyne
system, the river mouth sandspits were divided into three sectors. These included Sector 1 on the updrift

113

sandspit (red), Sectors 2 (yellow) and 3 (green) on the downdrift sandspit (Figure 2). Furthermore, thesandspit areas for each sector was estimated for the study period to depict accretion and erosion trends at
the river mouth. For this analysis, the areas for Sector 1, 2 and 3 were denoted as A1, A2 and A3,
respectively (Figure 2).

Figure 2. Definition of the three sectors used in the river mouth variability analysis.
4. RESULTS AND DISCUSSIONS
4.1 River Mouth Morphological Change
Within the study period, a number of morphological changes were observed at the Volta Rivermouth from the collected satellite images. The jetty at the river mouth was constructed with the purposeof halting the lateral migration of the updrift sandspit from the west to the east (Figures 3a and 3b). This
resulted in an increase in the width of the river mouth which facilitated an efficient tidal exchange andchannel navigation. In the years following the construction of the jetty, there has been the frequent
formation of offshore shoals which could be attributed to changes in the water depth at the river mouth
and wave breaking. These shoals move landward and attach to the downdrift sandspit which led to a
reduction in the width of the river mouth (Figures 3c to 3e). In addition to this, the landward growth of
the updrift sandspit is observed (Figure 3c to 3e). This phenomenon has manifested in the intrusion ofboth sandspits into the estuary (Figure 4). A more recent development at the river mouth is the multiple
breaching of the sandspits which has led to widening of the river mouth (Figure 3f). These distinct
changes at the river mouth give an indication of the river mouth’s response to alterations in the sedimentbudget at the river mouth by the ASDP.

Figure 3. Satellite images showing the various morphological evolutions at the Volta River mouth(2002 – 2021).

114

Figure 4. Shoreline variation of the Volta River mouth (2016 – 2021).
4.2 Variation of Sandspit Area
By plotting the sandspit area for the three defined sectors of the river mouth, the accretion anderosion trends can be assessed. Figure 5 shows the time variation plot of the sandspit area for Sector 1.
Regression analysis for this sector after the jetty and groyne construction shows a sandspit area change
rate of 1.3×104 m2/year from 2016 to 2020. The increment in sandspit area within this period is as a resultof the intrusion of the updrift spit into the estuary induced by sediment bypassing the jetty and the actionof breaking waves.

Figure 5. Updrift sandspit area variation for Sector 1.
With respect to Sector 2 on the downdrift spit, the regression analysis revealed an area change
rate of 4.1×104 m2/year from 2013 to 2019 (Figure 6). This gain in sandspit area was mainly due to theattachment of the offshore shoals to this section of the downdrift sandspit. Sector 3 on the other handshows the exact opposite of both Sectors 1 and 2. The analysis showed a sandspit area change rate of 6.4×104 m2/year from 2013 to 2021 for Sector 3 (Figure 7). This corresponds to the shoreline retreat
observed in Figure 4 for this sector of the river mouth. Table 1 shows a summary of the sandspit areachange rate for the three sectors of the river mouth.

115

Figure 6. Downdrift sandspit area variation for Sector 2.

Figure 7. Downdrift sandspit area variation for Sector 3.
Table 1. Summary of sandspit area change rates for the three defined sectors.
SectorSandspit area change
rate (m2/year)

Remarks1

1.3×104

Spit intrusion

2

4

Spit intrusion

4

Erosion3

4.1×10-6.4×10

116

4. CONCLUSION
From this study, the variability of the Volta River mouth has been investigated after theconstruction of a jetty and groyne system. The study employed the use of remotely sensed images from2002 to 2021. The results of the study for three sectors of the river mouth showed that while the sandspit
area for two sectors showed a positive trend (spit intrusion), the third sector was characterized by anegative trend (erosion). Furthermore, the findings from the image analysis is unable to determine if thejetty and the groyne system are the main cause of erosion on the third sector since chronic erosion along
this section of the of the river mouth has been an existing predicament. As such, further analysis would
be required to properly understand the variability of the river mouth through the use of advanced
numerical models. The results from the image analysis in this study could serve as a basis for conducting
such future studies.
REFERENCES
Allersma, E., & Tilmans, W. M. K. (1993). Coastal conditions in West Africa-A review. Ocean andCoastal Management, 19(3), 199–240.
Amenuvor, M., Gao, W., Li, D., & Shao, D. (2020). Effects of Dam Regulation on the Hydrological
Alteration and Morphological Evolution of the Volta River Delta. Water, 12(3), 646.
Lawson, S. K., Tanaka, H., Udo, K., Hiep, N. T., & Tinh, N. X. (2021). Morphodynamics andEvolution of Estuarine Sandspits along the Bight of Benin Coast, West Africa. Water, 13(21),2977.
Mensah, K. O., & FitzGibbon, J. (2013). Responsiveness of Ada Sea Defence Project to salt water
intrusion associated with sea level rise. Journal of Coastal Conservation, 17(1), 75–84.
Phanomphongphaisarn, N., Rukvichai, C., & Bidorn, B. (2020). Impacts of long jetties construction on
shoreline change at the western coast of the gulf of Thailand. Engineering Journal, 24(4), 1–17.
Tanaka, H., & Lee, H. S. (2003). Influence of jetty construction on morphology and wave set-up at ariver mouth. Coastal Engineering Journal, 45(4), 659–683.
Vos, K., Splinter, K. D., Harley, M. D., Simmons, J. A., & Turner, I. L. (2019). CoastSat: A Google
Earth Engine-enabled Python toolkit to extract shorelines from publicly available satellite
imagery. Environmental Modelling & Software, 122, 104528.

東北地域災害科学研究

117

第58巻（2022）ᩘ ್ࢩ࣑࣮ࣗࣞࢩࣙࣥ⤖ᯝࢆ⏝࠸ࡓ⅏ᐖࣜࢫࢡホ౯ ඵᡞᕤᴗ኱Ꮫ ୖ㔝 ♩ឿ ඵᡞᕤᴗ኱Ꮫ ୰ᮧ ඃ┿ ඵᡞᕤᴗ኱Ꮫ 㧗℩ ៅ௓ 
1㸬 ࡣࡌࡵ࡟
㟷᳃┴ඵᡞᕷࡢἢᓊ࡟ࡣᆅ㟈࡞࡝ࡢᙳ㡪࡛㢖⦾࡟ὠἼࡀ᮶くࡍࡿࡀ㸪㜵₻ሐ࣭ሐ㜵ࢆ㉺ὶࡍࡿ࡜ᕷ⾤ᆅ࡛⏒኱࡞⿕ᐖࢆࡶࡓࡽࡍࠋᮾ᪥ᮏ኱㟈⅏࡛ࡣ㸪㜵₻ሐࢆ኱ࡁࡃ㉺࠼ࡿ㧗ࡉࡢὠἼࡀ᮶くࡋ࡚࠸ࡿᆅᇦࡶከ࠸ࠋࡑࡢࡼ࠺࡞≧ἣࡢ୰㸪୰ኸ㜵⅏఍㆟࡟࡚᭱኱ࢡࣛࢫࡢὠἼ࡜Ⓨ⏕㢖ᗘࡢ㧗࠸ὠἼ࡜࠸࠺ 2 ࡘࡢὠἼࣞ࣋ࣝࡢタᐃࡢᥦゝࡀ࠶ࡾ㸪ᅜ࡜ࡋ࡚ࡣⓎ⏕㢖ᗘࡢ㧗࠸ὠἼࢆᩚഛࡍࡿ࡜࠸࠺᪉㔪࡛࠶ࡾ㸪௒ᚋ㜵ㆤ᪋タࡢᙺ๭࡜ࡋ࡚᏶඲࡟ᾐỈࢆṆࡵࡿ࡜࠸࠺ࡶࡢ࡛ࡣ࡞
ࡃ࡞ࡗࡓࡇ࡜ࡣ㸪⫼ᚋᆅᇦࡢࡲࡕ࡙ࡃࡾ࡟࠾࠸࡚ࡶ኱ࡁࡃᙳ㡪ࡍࡿ࡜⪃࠼ࡽࢀࡿࠋᏳ඲࡞ࡲࡕ
࡙ࡃࡾ࡟㝿ࡋ࡚ࡣ᭷ຠ࡞㜵⅏ィ⏬ࢆ❧᱌ࡍࡿࡓࡵ㸪஦๓࡟㜵⅏᪋タ(㜵Ἴሐ࣭㜵₻ሐ࣭ሐ㜵➼)࠾ࡼࡧᕷ⾤ᆅࡢᵓ㐀≀ࡀ㐳ୖὠἼ࠾ࡼࡧỏ℃ὶࡢᣲື࡟ཬࡰࡍᙳ㡪ࢆヲ⣽࡟᳨ウࡋ㸪ࡇࢀࡽࡀ⅏ᐖ᫬࡟᭷ຠ࡟ᶵ⬟ࡋ࠿ࡘᏳ඲࡛࠶ࡿ࠿ࢆ༑ศ᳨ウࡍࡿࡇ࡜ࡀ㔜せ࡛࠶ࡿࠋὠἼࡢᩘ್ゎᯒ࡟㛵ࡍࡿ◊✲ࡣ㧗ᗘ࡟Ⓨᒎࡋ࡚࠾ࡾ㸪⢭ᗘࡢ㧗࠸ホ౯ࡸணࡀྍ⬟࡟࡞ࡗ࡚

ࡁࡓࠋࡲࡓ㸪⅏ᐖ᫬࡟࠾࠸࡚ࡣ㸪⿕ᐖࡀ࡝ࡢ⛬ᗘࡲ࡛ཬࡪࡢ࠿࡜࠸ࡗࡓ᝟ሗࢆ࡛ࡁࡿࡔࡅ᪩ࡃ
ྲྀᚓࡍࡿࡇ࡜ࡀ㑊㞴⾜ືࡸ⅏ᐖᑐᛂࢆ⾜࠺ୖ࡛㠀ᖖ࡟㔜せ࡟࡞ࡿࠋ୍᪉࡛㸪୍⯡ⓗ࡟㧗ᗘ࡞ᩘ್ゎᯒ࡟㛵ࡋ࡚ࡣィ⟬ࢥࢫࢺࡀၥ㢟࡜࡞ࡿࡇ࡜࡟ຍ࠼㸪⅏ᐖࡣ୙☜ᐇᛶࢆ㠀ᖖ࡟ከࡃྵࡴ஦㇟
࡛࠶ࡿࡇ࡜࠿ࡽ㸪⅏ᐖࡀ㉳ࡇࡗࡓ┤ᚋ࡟ࡑࡢ୙☜ᐇᛶࡲ࡛ࢆ⪃៖ࡋ࡚⅏ᐖࢩ࣑࣮ࣗࣞࢩࣙࣥࢆ⾜࠸㸪ࡑࡢ᝟ሗࢆࣜ࢔ࣝࢱ࢖࣒࡛⿕ᐖࡢண࡟ά࠿ࡍ࡜࠸࠺ࡢࡣ⌧≧࡛ࡣ㞴ࡋ࠸ࠋࡑࡢࡓࡵィ⟬ࢥࢫࢺࡢ㧗࠸㧗ᗘ࡞ᩘ್ゎᯒ࡜㸪༑ศ࡞ヨ⾜ᅇᩘࢆồࡵࡽࢀࡿ☜⋡ㄽⓗホ౯ࢆຠ⋡ⓗ࡟฼⏝ࡋ࡚㸪ࣜ࢔ࣝࢱ࢖࣒ࡢὠἼࡢ⿕ᐖணࢆ⾜࠺ࡇ࡜ࡢ࡛ࡁࡿᯟ⤌ࡳࡢᵓ⠏ࡀồࡵࡽࢀࡿࠋ

ᮏ◊✲࡛ࡣ㸪୙☜ᐇᛶࢆ⪃៖ࡋࡓ␗࡞ࡿィ⟬᮲௳࠿ࡽᚓࡽࢀࡿᩘ್ゎᯒ⤖ᯝࢆ฼⏝ࡋ࡚㸪ࡑࡢ✵㛫ⓗ࡞ศᕸࡢ┦㛵ࡢ≉ᚩࢆࡘ࠿ࡳ㸪ప࠸ィ⟬ࢥࢫࢺ࡛㏆ఝⓗ࡟ᩘ್ゎᯒ࡜ྠ➼ࡢゎࢆᚓࡿࡇ࡜ࢆྍ⬟࡟ࡍࡿᯟ⤌ࡳࢆᵓ⠏ࡋ㸪ὠἼࣜࢫࢡゎᯒ 1)࡬ࡢ㐺⏝ࢆᥦ᱌ࡍࡿࡇ࡜ࢆ┠ⓗ࡜ࡍࡿࠋ

2㸬 ᅛ᭷┤஺ศゎ࡟ࡼࡿ࣮ࣔࢻศゎ࡜௦⌮ࣔࢹࣝࡢᵓ⠏ ⤫ィⓗᡭἲࡢ 1 ࡘ࡛࠶ࡿᅛ᭷┤஺ศゎ(Proper Orthogonal Decomposition)ࡢ⌮ㄽࢆᩘ್ࢩ࣑ࣗ
࣮ࣞࢩࣙࣥ⤖ᯝ࡟㐺⏝ࡍࡿࡇ࡜࡛㸪ὠἼࡢࣜ࢔ࣝࢱ࢖࣒ࢩ࣑࣮ࣗࣞࢩࣙࣥࢆྍ⬟࡜ࡍࡿᯟ⤌ࡳࡢᵓ⠏ࢆ⾜࠺ࠋࢹ࣮ࢱ࡟ᑐࡋ࡚ᅛ᭷┤஺ศゎࢆ㐺⏝ࡍࡿ࡟࠶ࡓࡾ㸪ࢹ࣮ࢱ⾜ิࢆᐃ⩏ࡍࡿࠋ࠶ࡿࢣ࣮ࢫࡢ i ࡢࢹ࣮ࢱࢆ࣋ࢡࢺࣝ࡜ࡋ࡚ xi(i = 1, …, N)࡜ࡍࡿࠋࡑࡢ࣋ࢡࢺࣝ xi ࡀ n ḟඖ㸪ࡍ࡞ࢃࡕ n ಶࡢࢹ࣮ࢱࢆᣢࡘ࡜ࡁ㸪ࢹ࣮ࢱ⾜ิ X ࡣ௨ୗࡢᵝ࡟ᐃ⩏ࡍࡿࠋ* Disaster risk assessment using numerical simulation results by Reiji Uwano118㹺㸻 ቌ ‫ݔ‬ଵ
㹺

‫ڮ‬

㹺
‫ݔ‬ே ቍ
㹺ิ᪉ྥ࡟ࢣ࣮ࢫ㸪⾜᪉ྥ࡟ࢹ࣮ࢱࡀḟඖᩘࡢᩘࡔࡅ୪ࡪ⾜ิ࡛࠶ࡾ㸪ࡇࡢ⾜ิ࡟ࡘ࠸࡚ᅛ᭷┤஺ศゎࢆ⾜࠺ࠋࡲࡓ㸪ࢹ࣮ࢱ⾜ิ X ࡣࢹ࣮ࢱ࣋ࢡࢺࣝࡢ㞟ྜయࡢࡓࡵ㸪࣋ࢡࢺࣝ࡟⦪⥺ࢆ௜ࡅ࡚⾲⌧ࡍࡿࠋᅛ᭷┤⾜ศゎ࡜ࡣ㸪ࣃ࣓࣮ࣛࢱ✵㛫࡟࠾࠸࡚ศᩓࡀ᭱኱࡜࡞ࡿࡼ࠺࡞ᇶᗏࢆᢳฟ
ࡍࡿᢏ⾡࡛࠶ࡾ㸪ࢹ࣮ࢱࡢ≉ᚩࢆࡘ࠿ࡳ㸪ࡼࡾపḟඖ࡛ࢹ࣮ࢱࢆ⾲⌧ࡍࡿᡭἲ࡛࠶ࡿࠋࡇࢀࡣ
ࢹ࣮ࢱ⾜ิࡢඹศᩓ⾜ิ C ࡟ࡘ࠸࡚ᅛ᭷┤⾜ศゎࢆ⾜࠺ࡇ࡜࡛ồࡵࡿࡇ࡜ࡀ࡛ࡁࡿࠋ‫ ܥ‬ൌ ܺܺ ் ᅛ᭷್ࡣศᩓࢆព࿡ࡋ㸪ศᩓࡀᑠࡉ࠸ᅛ᭷್࡟ᑐᛂࡍࡿᇶᗏࡣ᝟ሗ㔞ࢆ࡯࡜ࢇ࡝ᣢࡓ࡞࠸ࡓ
ࡵ┬␎ࡋ㸪඲యࢆ⦰⣙ࡋ࡚⾲⌧࡛ࡁࡿࠋᇶᗏࢆ┬␎ࡍࡿ㝿࡟ࡣᐤ୚⋡ࢆ⪃៖ࡍࡿࠋᐤ୚⋡ࡣ㸪ᅛ᭷್ࡢ඲య࡟ᑐࡍࡿ๭ྜ࡜ࡋ࡚౑⏝ࡍࡿᇶᗏᩘࢆỴᐃࡍࡿࡢ࡟⏝࠸ࡽࢀࡿᣦᶆ࡛࠶ࡾ㸪ᇶᗏ݆ࡢᐤ୚⋡݀௝ ࡣᅛ᭷್ࢆ⏝࠸࡚௨ୗࡢᘧ࡛୚࠼ࡽࢀࡿࠋ݀௝ ൌ 

ߣ௝σ௡௞ୀଵ ߣ௞ᅛ᭷┤⾜ศゎ࡛ᚓࡽࢀࡓᇶᗏࢆ⏝࠸࡚௦⌮ࣔࢹࣝࢆసᡂࡍࡿࠋࡲࡎ㸪ධຊࣃ࣓࣮ࣛࢱ࡜ᇶᗏ
࡟࠿࠿ࡿಀᩘࢆ㛵㐃௜ࡅࡿࡇ࡜࡛ᛂ⟅᭤㠃ࢆసᡂࡍࡿࠋᇶᗏࡀศᕸࡢ≉ᚩࢆ⾲⌧ࡋ㸪ࡑࡢ≉ᚩࡢ㔜ࡳࡀධຊࣃ࣓࣮ࣛࢱ࡟ࡼࡗ࡚Ỵࡲࡿࠋࡇࡢࡼ࠺࡟ྛᇶᗏ࡟࠿࠿ࡿಀᩘ㒊ศࢆධຊࣃ࣓࣮ࣛ
ࢱࡢ㛵ᩘ࡜ࡋ࡚㏆ఝࡍࡿࡇ࡜࡛㸪௵ពࡢࢣ࣮ࢫ࡟ࡘ࠸࡚ồࡵࡓ࠸㔞ࢆ⟬ฟࡍࡿࡇ࡜ࡀྍ⬟࡜࡞ࡿࠋ3㸬
㸬 ὠἼゎᯒࢹ࣮ࢱ࡬ࡢ㐺⏝ࡇࢀࡲ࡛࡟㏙࡭࡚ࡁࡓᅛ᭷┤஺ศゎࢆὠἼࡢᩘ್ゎᯒࢹ࣮ࢱ࡟㐺⏝ࡍࡿࠋ⡆᫆ⓗ࡞ࣔࢹࣝ࡬
ࡢ㐺⏝ࢆ⾜࠸㸪ࡑࡢ᭷⏝ᛶ࡟ࡘ࠸࡚☜ㄆࡍࡿࠋ
 3.1 ゎᯒᡭἲ࡜ゎᯒ᮲௳  ᨭ㓄᪉⛬ᘧ࡟ࡣ㸪㐠ື㔞ಖᏑ๎࠾ࡼࡧ㐃⥆ᘧࢆ⏝࠸࡚࠸ࡿࠋࡇࢀࡽ࡟ᑐࡋ㸪Ᏻᐃ໬᭷㝈せ⣲ἲࡢࡦ࡜ࡘ࡛࠶ࡿ SUPG/PSPG ἲࢆ㐺⏝ࡋ࡚࠸ࡿࠋߩ൬߲‫ݑ‬൅ ‫ ݑ‬ή ‫ ݑ׏‬െ ݂൰ െ ‫ ׏‬ή ߪ ൌ Ͳ߲‫ݐ‬‫ ׏‬ή ‫ ݑ‬ൌ Ͳࡇࡇ࡛㸪ߩࡣᐦᗘ㸪‫㏿ࡣݑ‬ᗘ࣋ࢡࢺࣝ㸪ߪࡣᛂຊࢸࣥࢯࣝ㸪݂ࡣ≀యຊ࣋ࢡࢺ࡛ࣝ࠶ࡿࠋᵓᡂ๎࡟
ࡣ㸪ḟᘧࡢ Newton ὶయࡢᵓᡂ๎ࢆ⏝࠸࡚࠸ࡿࠋߪ ൌ െ‫ ܫ݌‬൅ ʹߤߝሺ‫ݑ‬ሻࡇࡇ࡛㸪‫ࡣ݌‬ᅽຊ㸪ߤࡣ⢓ᛶಀᩘ࡛࠶ࡾ㸪ߝሺ‫ݑ‬ሻࡣḟᘧ࡛ᐃ⩏ࡉࢀࡿኚᙧ㏿ᗘࢸࣥࢯ࡛ࣝ࠶ࡿࠋ
ͳߝሺ‫ݑ‬ሻ ൌ ሺ‫ ݑ׏‬൅ ሺ‫ݑ׏‬ሻ் ሻʹ ゎᯒࣔࢹࣝࡣᅗ㸫1 ࡟♧ࡍࡶࡢ࡛࠶ࡿࠋゎᯒ᮲௳࡜ࡋ࡚㸪t=0 ࡛ẁἼࢆゎᨺࡋ㸪ᘓ≀࡟ᶍࡋࡓ
4 ಶࡢゅᰕࡢὶయࡢ⾪ᧁຊࢆ⟬ฟࡋ࡚࠸ࡿࠋ⪃៖ࡍࡿ୙☜ᐇᛶ࡜ࡋ࡚㜵₻ሐࡢ㧗ࡉ h1 ࠾ࡼࡧ119ึᮇὠἼ㧗ࡉ h2 ࢆኚ໬ࡉࡏࡓ㸪⾲㸫1 ࡟♧ࡍ 6 ࢣ࣮ࢫࡢ⤖ᯝࢆ⏝࠸ࡿࠋᅗ㸫1 ゎᯒࣔࢹࣝ⾲㸫1 ゎᯒࢣ࣮ࢫ 3.2 ✵㛫ศᕸࢹ࣮ࢱࡢᅛ᭷┤஺ศゎ

FDVH K P ྛࢣ࣮ࢫࡢ᭱኱⾪ᧁຊ ᭱኱ὶయຊ ࡢࢹ࣮ࢱࢆᑐ㇟࡜ࡋ࡚㸪K P✵㛫ⓗ࡞ศᕸࡢࢹ࣮ࢱࢆᑐ㇟࡜ࡋࡓศᯒࢆ⾜࠺ࠋࡑࢀࡒࢀࡢ







ࢣ࣮ࢫ࡟࠾࠸࡚㸪ྛᘓ≀ࡢ᭱኱⾪ᧁຊࢆ᫬⣔ิࢹ࣮ࢱ࠿ࡽᢳ







ฟࡍࡿࠋࡇࢀࡽࢆ୪࡭ࡓࡶࡢࢆࢹ࣮ࢱ⾜ิ࡜ࡋ࡚ᐃ⩏ࡍࡿࠋ







ࡇࡇ࡛㸪ゎᯒࢣ࣮ࢫࡣ 6 ࢣ࣮ࢫ㸪ᘓ≀ࡣ 4 Ჷ࠶ࡿࡓࡵ㸪ࢹ࣮







ࢱ⾜ิࡣ 46 ࡢࢧ࢖ࢬ࡜࡞ࡿࠋࡇࢀ࡟ᑐࡋ࡚ᅛ᭷┤஺ศゎࢆ







⾜࠺ࠋ







 ࡲࡎᐤ୚⋡࡟ࡘ࠸࡚☜ㄆࡍࡿࠋྛࣔ
1.00E+00

ࡇࡢᅗ࠿ࡽ㸪➨ 1 ࣔ̿ࢻࡀࡇࡢࢹ࣮ࢱ

8.00E-01࡟ᑐࡋ࡚ᨭ㓄ⓗ࡛࠶ࡿࡇ࡜ࡀ☜ㄆ࡛ࡁ

6.00E-01‫ر‬༫ི࣮ࢻࡢᐤ୚⋡ࡣᅗ㸫2 ࡢࡼ࠺࡟࡞ࡿࠋ

ࡿࠋ࣮ࣔࢻࡢ㑅ᢥࡣ㸪ᐤ୚⋡ࡀ㔜せ࡞
ᣦᶆࡢ 1 ࡘ࡜࡞ࡿࡀ㸪ᐤ୚⋡ࡔࡅ࡛ࡣ

4.00E-01ᒁᡤⓗ࡞ኚ໬࡞࡝ࢆ㏣࠸ࡁࢀ࡞࠸ྍ⬟2.00E-01ᛶࡀ࠶ࡿࡓࡵ㸪ඖࢹ࣮ࢱࢆ෌ᵓ⠏ࡋࡓ

0.00E+00

㝿࡟⏕ࡌࡿㄗᕪࡶ⪃៖ࡋ࡚๐ῶࡍࡿࣔ

1

2

3

4

5

6

֦Ϡʖχ͹൬ߺ

࣮ࢻࡢᩘࢆỴᐃࡋࡓࠋr ಶࡢ࣮ࣔࢻࢆ
⏝࠸࡚෌ᵓ⠏ࡋࡓࢹ࣮ࢱ࡟ࡘ࠸࡚㸪඲ᅗ㸫2 ྛ࣮ࣔࢻࡢᐤ୚⋡ࢹ࣮ࢱࡢㄗᕪࡢ 2 ஌ࡢᖹᆒ࡟ࡘ࠸࡚ᖹ

᪉ࢆ࡜ࡗࡓ್(ᖹᆒᖹ᪉஧஌ㄗᕪ)࡜ࡋ࡚ḟᘧࡢࡼ࠺࡟ᐃ⩏ࡍࡿࠋ
௡

ே

ͳ
ଶ
݁௥ ൌ ඩ ෍ ෍൫‫ݔ‬௝௜ െ ‫ݔ‬ො௝௜௥ ൯ ݊ܰ௝ୀଵ ௜ୀଵ

ࡇࡇ࡛㸪݊ࡀᘓ≀ᩘ n=4 㸪ܰࡀࢣ࣮ࢫᩘ N=6 ࡛࠶ࡿࠋࡲࡓ㸪‫ݔ‬௝௜ ࡣࢣ࣮ࢫ i ࡢ j ␒┠ࡢᘓ≀ࡢ᭱኱⾪ᧁຊ㸪ࡍ࡞ࢃࡕࢹ࣮ࢱ⾜ิ X ࡢ j ⾜ i ิᡂศࢆ⾲ࡋ࡚࠾ࡾ㸪‫ݔ‬ො௝௜௥ ࡀ r ಶࡢ࣮ࣔࢻࢆ⏝࠸࡚ศᕸࢆ⾲ࡋࡓ᫬ࡢࢣ࣮ࢫ i ࡢ j ␒┠ࡢᘓ≀ࡢ᭱኱⾪ᧁຊ࡛࠶ࡿࠋ⏝࠸ࡿ࣮ࣔࢻࡢᩘ࡜㸪ࡑࡢ࡜ࡁ

120

࡟ィ⟬ࡉࢀࡿㄗᕪࢆࣉࣟࢵࢺࡋࡓࡶࡢࢆ
ᅗ㸫3 ࡟♧ࡍࠋࡇࡢᅗࡼࡾ㸪r=4 ࡲ࡛ࡣㄗ➨ 4 ࣮ࣔࢻ௨㝆࡛ࡣㄗᕪࡢ㏴ῶ⋡ࡀᶓࡤ࠸࡟࡞ࡗ࡚࠸ࡿࡇ࡜࠿ࡽ㸪➨ 4 ࣮ࣔࢻࡲ‫ࠫޣ‬

ᕪࡢ㏴ῶ⋡ࡀ኱ࡁࡃ࡞ࡗ࡚࠸ࡿ୍᪉࡛㸪࡛ࢆ⏝࠸࡚௦⌮ࣔࢹࣝࢆసᡂࡍࡿࡇ࡜࡜
ࡍࡿࠋ

800000700000600000500000400000300000200000100000
0
1

3

4

5

6

֦Ϡʖχ͹൬ߺ

ḟ࡟㸪ᩘ್ゎᯒ⤖ᯝࡢඹศᩓ⾜ิࡢᅛ᭷┤஺ศゎ࡟ࡼࡗ࡚ᚓࡽࢀࡓ✵㛫࣮ࣔࢻ

2ᅗ㸫3 ౑⏝ࡍࡿ࣮ࣔࢻᩘࡈ࡜ࡢㄗᕪ

ࢆᅗ㸫4 ࡟♧ࡍࠋඛ㏙ࡢࡼ࠺࡟ 4 ࡘࡢ࣮ࣔࢻࢆ⏝࠸ࡿࡇ࡜࠿ࡽ㸪➨ 1 ࣮ࣔࢻ࠿ࡽ➨ 4 ࣮ࣔࢻࡲ࡛ࡢศᕸࡢᵝᏊࢆ♧ࡍࠋᅗ࡟♧ࡍᩘᏐࡣ㸪ᅛ᭷࣋ࢡࢺࣝࡢྛᘓ≀࡟ᑐᛂࡍࡿᡂศࡢ್ࢆ♧ࡋ࡚࠸ࡿࠋ✵㛫࣮ࣔࢻࡢ᝟ሗࡣ✵㛫ⓗ࡞┦㛵ࡢ≉ᚩࢆ⾲ࡋ㸪✵㛫ⓗ࡞ศᕸࡢ≉ᚩࢆ⾲⌧ࡍࡿࠋලయⓗ࡟ᚓࡽࢀࡓ✵㛫࣮ࣔࢻ࡟ࡘ࠸࡚☜ㄆࡋ࡚࠸ࡃࠋ➨ 1 ࣮ࣔࢻ࡟ࡘ࠸࡚ࡣ㸪๓ഃࡢᘓ≀࡯࡝ᙉ࠸ᙳ㡪ࢆཷࡅࡿ࡜࠸࠺ഴྥࡀㄞࡳྲྀࢀࡿࠋࡲ
ࡓ㸪➨ 2 ࣮ࣔࢻ࡟ࡘ࠸࡚ࡣ㸪1 ࡘࡢᵓ㐀≀ࡀཷࡅࡿᙳ㡪ࡀ࡯࠿ࡢᵓ㐀≀࡟ẚ࡭࡚኱ࡁࡃ࡞ࡗ࡚
࠸ࡿࡇ࡜ࡀࢃ࠿ࡿࠋࡉࡽ࡟➨ 3 ࣮ࣔࢻ࡟ࡘ࠸࡚ࡣ㸪➨ 2 ࣮ࣔࢻ࡜ྠᵝ࡟ 1 ࡘࡢᵓ㐀≀ࡀཷࡅࡿᙳ㡪ࡀ࡯࠿ࡢᵓ㐀≀࡟ẚ࡭࡚኱ࡁࡃ࡞ࡗ࡚࠸ࡿࡀ㸪ࡑࡢẚ⋡ࡀ➨ 2 ࣮ࣔࢻࡼࡾࡶᑠࡉࡃ࡞ࡗ࡚
࠸ࡿࡇ࡜ࡀࢃ࠿ࡿࠋ➨ 4 ࣮ࣔࢻ࡟ࡘ࠸࡚ࡶ㸪➨ 2 ࣮ࣔࢻ㸪➨ 3 ࣮ࣔࢻ࡜ྠᵝࡢഴྥ࡛㸪ᙳ㡪ࡢẚ⋡ࡀࡇ࡜࡞ࡗ࡚࠸ࡿ࡜࠸࠺ࡇ࡜ࡀㄞࡳྲྀࢀࡿࠋ

ᅗ㸫4 ✵㛫࣮ࣔࢻ

121

 3.3 POD ಀᩘࡢᛂ⟅᭤㠃ࡢసᡂ ධຊࣃ࣓࣮ࣛࢱ࡛࠶ࡿ㜵₻ሐࡢ㧗ࡉ h1 ࡜ึᮇὠἼ㧗ࡉ h2 ࡜㸪ྛ࣮ࣔࢻ࡟࠿࠿ࡿಀᩘࡢ㛵㐃௜ࡅࢆ⾜࠺ࡇ࡜࡛ᛂ⟅᭤㠃ࢆసᡂࡍࡿࠋᑐᛂࡍࡿ࣮ࣔࢻࡈ࡜࡟ධຊࣃ࣓࣮ࣛࢱࡢ㛵ᩘ࡜ࡋ࡚⿵
㛫ࡋ㸪ࡑࢀࢆᅗ♧ࡋࡓࡶࡢࢆᅗ㸫5 ࡟♧ࡍࠋ
➨ 1 ࣮ࣔࢻ࠿ࡽ➨ 4 ࣮ࣔࢻ࡟ᑐᛂࡍࡿ㛵ᩘቀ݂௝ ሺ݄ͳǡ ݄ʹሻሺ݆ ൌ ͳǡʹǡ͵ǡͶሻቁࢆ♧ࡍࠋᅗ㸫5 ྛ࣮ࣔࢻ࡟ᑐᛂࡍࡿᛂ⟅᭤㠃ᡭ๓ࡢྑഃࡢ㍈ࡀ㜵₻ሐࡢ㧗ࡉ㸪ᕥഃࡢ㍈ࡀึᮇὠἼ㧗ࡉ࡟࡞ࡗ࡚࠸ࡿࠋࡇࡢࡼ࠺࡟㸪࣮ࣔࢻ࠿ࡽࢃ࠿ࡿศᕸࡢ≉ᚩ࡜ධຊࣃ࣓࣮ࣛࢱࡢ㛵ಀࢆ⤖ࡧࡘࡅࡿࡇ࡜ࡀ࡛ࡁ㸪ࡇࡢ 2 ࡘࢆྜࢃࡏ࡚
௦⌮ࣔࢹࣝࢆసᡂࡍࡿࡇ࡜ࡀ࡛ࡁࡿࠋ
 3.4 ௦⌮ࣔࢹࣝ࡟ࡼࡿ⤖ᯝ࡜ゎᯒ⤖ᯝࡢẚ㍑
 ๓⠇ࡲ࡛࡛♧ࡋ࡚ࡁࡓ࣮ࣔࢻ࡜ಀᩘࡢ㛵ಀࢆ⏝࠸ࡿࡇ࡜࡛㸪௵ពࡢධຊࣃ࣓࣮ࣛࢱ 㜵₻ሐࡢ㧗ࡉ h1㸪ึᮇὠἼ㧗ࡉ h2 ࡛ࡢ᭱኱⾪ᧁຊࡢ✵㛫ศᕸࡣ௨ୗࡢࡼ࠺࡟ィ⟬࡛ࡁࡿࠋ
௥‫ݔ‬ොሺ݄ͳǡ ݄ʹሻ ൌ ෍ ݂௞ ሺ݄ͳǡ ݄ʹሻ‫ݑ‬௞௞ୀଵ௦⌮ࣔࢹࣝࡢጇᙜᛶࢆ᳨ドࡍࡿࡓࡵ࡟㸪⾲㸫1 ࡟♧ࡍ 6 ࡘࡢࢣ࣮ࢫ௨እࡢࣃ࣓࣮ࣛࢱࡢ⤌ࡳྜࢃࡏ࡛ࡢᩘ್ゎᯒ⤖ᯝ࡜௦⌮ࣔࢹࣝ࠿ࡽᚓࡽࢀࡿ⤖ᯝࡢẚ㍑ࢆ⾜࠺ࠋ122ܿܽ‫݁ݏ‬ሺ݄ͳǡ ݄ʹሻ ൌ ሺ͹ǤͷǡʹͲሻゎᯒ⤖ᯝ࡜௦⌮ࣔࢹࣝ࠿ࡽồࡵࡓ⤖ᯝࢆ୪࡭࡚ࡑࢀࡒࢀᅗ㸫6 ࡟♧ࡍࠋᕥഃ࡟♧ࡋࡓࡶࡢࡀᩘ
್ゎᯒ࠿ࡽᚓࡽࢀࡿ⤖ᯝ࡛࠶ࡾ㸪ྑഃ࡟♧ࡋࡓࡶࡢࡀ௦⌮ࣔࢹࣝ࠿ࡽồࡵࡽࢀࡓ⤖ᯝ࡛࠶ࡿࠋ
ࡇࢀࡽࡢ⤖ᯝ࠿ࡽ㸪ᩘ್ゎᯒ࠿ࡽᚓࡽࢀࡿ⤖ᯝࢆᴫࡡ෌⌧࡛ࡁ࡚࠸ࡿࡇ࡜ࡀศ࠿ࡿࠋලయⓗ࡟ࡑࢀࡒࢀࡢࢣ࣮ࢫ࡟࠾࠸࡚ᖹᆒᖹ᪉஧஌ㄗᕪࢆィ⟬ࡍࡿ࡜㸪129891.6[N]࡜࡞ࡗࡓࠋࡲࡓ㸪4 Ჷࡢᖹᆒ್࡜ࡢẚࢆ࡜ࡗ࡚ㄗᕪ⋡࡜ࡋ࡚⾲ࡍ࡜㸪3.3%࡜࡞ࡿࡇ࡜࠿ࡽ㸪௦⌮ࣔࢹࣝ࡟ࡼࡗ࡚௵ព
ࡢࣃ࣓࣮ࣛࢱࡢ᫬ࡢ᭱኱⾪ᧁຊࡢศᕸࢆᴫࡡ⾲⌧࡛ࡁࡿࡇ࡜ࡀࢃ࠿ࡿࠋ ࡲࡓ㸪ィ⟬ࢥࢫࢺ࡟ࡘ࠸࡚ࡣ㸪㏻ᖖࡢᩘ್ゎᯒ࡛ࡣ 1 ࢣ࣮ࢫ 72 ᫬㛫⛬ᗘ࠿࠿ࡿィ⟬ࢆ㸪௦⌮ࣔࢹ࡛ࣝࡣ࡯࡜ࢇ࡝᫬㛫ࢆせࡍࡿࡇ࡜࡞ࡃ⤖ᯝࢆᚓࡿࡇ࡜ࡀ࡛ࡁࡿࠋࡇࡢィ⟬ࢥࢫࢺࡢ኱ᖜ࡞
పῶࡣ㸪௦⌮ࣔࢹࣝࢆᵓ⠏ࡍࡿ኱ࡁ࡞฼Ⅼ࡛࠶ࡿࠋᅗ㸫6 ᩘ್ゎᯒ⤖ᯝ࡜௦⌮ࣔࢹࣝ࠿ࡽồࡵࡽࢀࡓ⤖ᯝࡢẚ㍑
4㸬
㸬 ⤖ㄽ ᩘ್ゎᯒࡢ⤖ᯝࢆຠ⋡ⓗ࡟฼⏝ࡋ࡚㸪௦⌮ࣔࢹࣝࢆసᡂࡋ㸪ᑡ࡞࠸ィ⟬ࢥࢫࢺ࡛ᩘ್ゎᯒ࡜ྠ➼ࡢ⤖ᯝࢆ⟬ฟࡍࡿᡭ㡰࡟ࡘ࠸࡚ㄝ᫂ࡋࡓࠋᩘ್ゎᯒ࠿ࡽᚓࡽࢀࡿࢹ࣮ࢱ࡟ᑐࡋ࡚ᅛ᭷┤஺ศゎࢆ⾜࠺ࡇ࡜࡛㸪ࡑࡇ࠿ࡽᚓࡽࢀࡿ࣮ࣔࢻࡢ⥺ᙧ⤖ྜ࡜ࡋ࡚ᑐ㇟࡜ࡍࡿศᕸࢆ⾲⌧ࡍࡿࡇ࡜ࡀ࡛ࡁ㸪ࡉࡽ࡟ࡑࡢಀᩘ㒊ศࢆゎᯒࣃ࣓࣮ࣛࢱࡢ㛵ᩘ࡜ࡋ࡚⾲⌧ࡍࡿࡇ࡜࡛㸪௦⌮ࣔࢹࣝ࡜ࡋ
࡚ᩘ್ゎᯒࢆᐇ᪋ࡋ࡚࠸࡞࠸௵ពࡢࢣ࣮ࢫ࡟ࡘ࠸࡚ࡶᴟࡵ࡚ప࠸ィ⟬ࢥࢫࢺ࡛ศᕸࢆ⟬ฟࡍࡿࡇ࡜ࡀྍ⬟࡜࡞ࡿࠋ ࡇࡢᡭἲࡣ㸪⅏ᐖࡢ☜⋡ㄽⓗ࡞ホ౯ࢆ⾜࠺ୖ࡛㔜せ࡞ᙺ๭ࢆᯝࡓࡍ࡜⪃࠼ࡽࢀࡿࠋ☜⋡ㄽⓗ࡞ホ౯ࢆ㐺ษ࡟⾜࠺ࡓࡵ࡟ࡣ㸪༑ศ࡞ヨ⾜ᅇᩘࡀồࡵࡽࢀࡿࠋ௦⌮ࣔࢹࣝࢆ⏝࠸ࡿࡇ࡜࡛㸪㧗ᗘ࡞ᩘ್ゎᯒࢆ฼⏝ࡋ࡞ࡀࡽຠ⋡ⓗ࡟ヨ⾜ᅇᩘࢆ☜ಖࡍࡿࡇ࡜ࡀྍ⬟࡛࠶ࡾ㸪☜⋡ㄽⓗ࡞㆟ㄽ࡟⤖ࡧ௜ࡅࡿࡇ࡜ࡀྍ⬟࡜࡞ࡿࠋ♧ࡋࡓ౛࡛ࡣホ౯Ⅼࡢᩘࡀ 4 ࡜ᑡᩘ࡛࠶ࡗࡓࡀ㸪㒔ᕷ࡟Ꮡᅾࡍࡿከᩘࡢᘓ≀࡟ᑐࡋ࡚ࡶྠᵝࡢホ౯ࡀྍ⬟࡛࠶ࡿࠋ௒ᚋࡣᘓ≀ࡈ࡜࡟኱ࡁࡉࡸᙧ≧ࡀ␗࡞ࡿၥ㢟࡬ࡢ㐺⏝ࡢྍ⬟ᛶ࡟ࡘ࠸᳨࡚ウࡢᚲせࡀ࠶ࡿࠋ5㸬 ཧ⪃ᩥ⊩
1)እ㔛೺ኴ㸪㧗℩ៅ௓㸪᳃ཱྀ࿘஧㸪ᑎ⏣㈼஧㑻㸪኱➉㞝㸪⚟㇂㝧㸪㔝ᓥ࿴ஓ㸪Ḉᗞ㞞᫂㸪ᶓὪᘯṊ㸸ᅛ᭷┤஺ศゎࢆ⏝࠸ࡓࣜ࢔ࣝࢱ࢖࣒ὠἼࢩ࣑࣮ࣗࣞࢩࣙࣥ㸪ィ⟬ᕤᏛㅮ₇఍ㄽᩥ㞟 Vol.25(2020 ᖺ 6 ᭶)

東北地域災害科学研究

123

第58巻（2022）ᅜ ෆ⮬↛⅏ᐖ⿕ᐖࡢ☜⋡ศᕸ࡟㛵ࡍࡿ୍⪃ᐹ 㸨 ᮾ໭኱Ꮫ⅏ᐖ⛉Ꮫᅜ㝿◊✲ᡤ ዟᮧ ㄔ
1㸬 ᮏ◊✲ࡢ┠ⓗ ⮬↛⅏ᐖ࠿ࡽࡢ♫఍ࡢᦆኻࡣ㸪┤᥋⿕ᐖ࡟క࠺♫఍⤒῭άືࡢ୍᫬ⓗ࡞ⴠࡕ㎸ࡳ㸦࢖ࣥࣃࢡࢺ㸧ࢆ㉳Ⅼ࡜ࡋ࡚㸪ᚎࠎ࡟᚟ᪧࡋ࡚⿕⅏๓ࡢỈ‽࡟ᡠࡿࡲ࡛ࢆ᫬㛫✚ศࡋࡓࣞࢪ࢚ࣜࣥࢫࡢ୕
ゅᙧ࡟ࡼࡗ࡚ホ౯࡛ࡁ㸪㏻ᖖࡢ⮬↛⅏ᐖ⤫ィࡀィ㔞ࡋ࡚࠸ࡿࡢࡣᙜึࡢ࢖ࣥࣃࢡࢺ࡟┦ᙜࡋ㸪ࣁࢨ࣮ࢻᙉᗘ᭚㟢⬤ᙅᛶ࡟ࡼࡗ࡚ㄝ࡛᫂ࡁࡿࠋ♫఍ⓗ࡟⮬↛⅏ᐖࡢ࢖ࣥࣃࢡࢺࢆᑠࡉࡃࡍ
ࡿ࡟ࡣ㸪 ȋͳȌ᭚㟢ࢆୗࡆࡿᡓ␎࡜ ȋʹȌ⬤ᙅᛶࢆୗࡆࡿᡓ␎ࡀ࠶ࡾ㸪௒ᚋࡢᑐ⟇❧᱌ࡢࡓࡵ࡟ࡣ㸪ࡇࢀࡲ࡛ࡢᑐ⟇ࡢຠᯝࢆᐃ㔞ⓗ࡟ᢕᥱࡍࡿࡇ࡜ࡀᮃࡲࢀࡿࠋ
ࡋ࠿ࡋ㸪ಶࠎࡢ⮬↛⅏ᐖ࢖࣋ࣥࢺࡣ㸪␗࡞ࡿሙᡤ㸪᫬㛫㸪≧ἣࡢ୰࡛Ⓨ⏕ࡍࡿࡶࡢ࡛࠶ࡾ㸪㐣ཤࡢ୍ࡘࡢ࢖࣋ࣥࢺࡢ⿕ᐖ㔞࡟ᑐࡋ࡚≉ᐃࡢ᪋⟇ࡀ㍍ῶຠᯝࢆⓎ᥹ࡋࡓ࡜ࡋ࡚ࡶ㸪௒ᚋูࡢ᫬
㛫㸪ሙᡤ㸪≧ἣࡢ୰࡛Ⓨ⏕ࡍࡿ⮬↛⅏ᐖ࢖࣋ࣥࢺ࡟ᑐࡋ࡚ྠ➼ࡢ㍍ῶຠᯝࡀᮇᚅ࡛ࡁࡿ࡜ࡣ㝈ࡽ࡞࠸ࠋࡑࢀࡺ࠼㸪ᮏ◊✲࡛ࡣ୍ᐃᮇ㛫࡟࠾ࡅࡿྠ✀ࡢ࢖࣋ࣥࢺ࡟ࡼࡿ⿕ᐖ㔞ࡢศᕸ࡟╔┠ࡋ㸪ྛ✀ࡢᨻ⟇ࡀࡇࡢ⿕ᐖ㔞ࡢศᕸ࡟୚࠼ࡿᙳ㡪ࢆ㸪㡰఩つᶍ᭤⥺ࢆ⏝࠸࡚ᴫᛕⓗ࡟⪃ᐹࡍࡿࠋࡘ
࠸࡛㸪㒔㐨ᗓ┴ู⮬↛⅏ᐖ⿕ᐖ⤫ィࡢ᭱㏆ ͳ͵ ᖺ㛫ࡢࢹ࣮ࢱࢆ㠀㈇್⾜ิᅉᏊศゎȋ Ȍ࡟ࡼࡾᑡᩘࡢᅉᏊᚓⅬ࡟㞟⣙ࡋࡓୖ࡛㡰఩つᶍ᭤⥺ࢆᥥࡁ㸪ྛ✀ࡢ㜵⅏ᑐ⟇ࡢᙳ㡪ࡢ⪃ᐹࢆヨࡳࡿࠋ2㸬 ᨻ⟇せᅉࡀ⿕ᐖ㔞࡟୚࠼ࡿᙳ㡪ࡢ㡰఩つᶍ᭤⥺ࢆ⏝࠸ࡓᴫᛕⓗ᳨ウ ᆅ㟈ࡢᑐᩘつᶍ࡜ᑐᩘⓎ⏕☜⋡ࡢ㛫࡟ぢࡽࢀࡿ┤⥺ⓗ㛵ಀࡣ Gutenberg-Righter ๎࡜࿧ࡤࢀ㸪௚ࡢከࡃࡢ⮬↛⌧㇟ࡸ♫఍⌧㇟࡟ࡶ㸪୧ᑐᩘ⾲♧ࡢ㡰఩つᶍ᭤⥺ࡀ┤⥺࡛♧ࡉࢀࡿ࡜࠸࠺ࠕ࡭
ࡁ஌๎ࠖࡀほᐹࡉࢀ࡚࠸ࡿࠋᮏ◊✲࡛ࡣ⮬↛⅏ᐖࣁࢨ࣮ࢻࡢほᚑ࠺࡜௬ᐃࡋࡓୖ࡛㸪ྛ✀ࡢᨻ⟇ຠᯝ࡟ࡼࡗ
࡚㸪ࡑࡢࣁࢨ࣮ࢻ࡟ἢࡗ࡚Ⓨ⏕ࡍࡿ⿕ᐖ㸦࢖ࣥࣃࢡࢺ㸧ࡢ㡰఩つᶍ᭤⥺ࡢᙧࡀ࡝ࡢࡼ࠺࡟
ኚ໬ࡍࡿ࠿ࢆ⪃ᐹࡍࡿࠋᅗ  ࡣᚋ㏙ࡍࡿ㒔㐨ᗓ┴ู⅏ᐖ⿕ᐖ⤫ࡲࡎᅗィࡢ୺せ࡞ 6 㡯┠࡟㛵ࡍࡿ୧ᑐᩘ⾲♧ࡢ㡰఩つᶍ᭤⥺࡛㸪ྛ᭤⥺ࡢഴࡁࡣ 0.5ࠥ0㸬9 ⛬ᗘ࠿ࡽጞࡲࡾ㸪ྑ᪉࡟ᫎࡿ࡜࡜ࡶ࡟ഴࡁࡀ 1.2
ࠥ2.5 ⛬ᗘ࡟ቑຍࡋ࡚࠸ࡿࠋࡇࡢࡼ࠺࡞ྑୖ
࡟ฝ࡞ᙧ≧ࡀ⌧ࢀࡿཎᅉࢆ⪃࠼ࡿࠋࡲࡎ᭚㟢ࡢᙳ㡪ࢆ⪃࠼ࡿࠋᆅ⾲㠃࡛ࡢ⮬↛ࣁࢨ࣮ࢻࡢⓎ⏕⋡ࡣ୍ᵝ࡛࡞ࡃ೫ᅾࡋ࡚ศ

᭱኱್࡛ᇶ‽໬ᚋࡢつᶍ࣮ᛶ㸧ࢆ⪃៖ࡋ࡚ಀᩘࡀ 1 ࡢ㡰఩つᶍ┤⥺࡟1༢఩୙ኚᛶ㸦ࢫࢣ࣮࣭ࣝࣇࣜ
10

㡰఩ 100

1000

1
0.1

0.01
0.001
0.00010.00001
0.000001

0.0000001
ᅗṚஸ୙᫂⪅ᩘ
㈇യ⪅ᩘ
඲ቯᐙᒇᩘ
ࡾ⅏ୡᖏᩘ
ࡾ⅏ேᩘ
⿕ᐖ㢠

୺࡞⿕ᐖ㡯┠್ࡢ㡰఩つᶍ᭤⥺* Discussion on the probabilistic distribution of Japanese disaster damage statistics by Makoto Okumura

124ࡼ࠺࡟㸪ࣁࢨ࣮ࢻࡀ㧗࠸ᆅᇦ࡯࡝᭚㟢㔞ࡢᏑᅾᐦᗘࡀపࡅࢀࡤ㸪⿕ᐖࡢ㡰఩つᶍ᭤⥺ࡣࣁ ࢨ࣮ ࢻࡢ ᭤⥺ ࡟ẚ ࡭࡚ ഴࡁ ࡀ⦆ ࡃ ࡞
ࡿࠋ㏫࡟㸪኱Ἑᕝࡢỏ℃ཎୖ࡟ከࡃࡢ㒔ᕷࡀᙧᡂࡉࢀ࡚ࡁࡓࡇ࡜࠿ࡽ㸪Ỉᐖ⿕ᐖࡢ㡰఩つᶍ᭤⥺ࡣࣁࢨ࣮ࢻࡢ᭤⥺࡟ẚ࡭࡚ᛴ࡞ഴࡁ࡜࡞ࡿྍ⬟ᛶࡀ࠶ࡿࠋ
⬤ᙅᛶࡣ㸪ࣁࢨ࣮ࢻ࡟ᑐࡍࡿ᢬ᢠຊ࡟┦ᙜࡍࡿࠋ㧗㢖ᗘ࡛㉳ࡇࡿ㍍ᚤ࡞እຊ࡟ࡣ༑ศ
࡞᢬ᢠຊࢆᣢࡕ⿕ᐖࡣⓎ⏕ࡋ࡞࠸ࡀ㸪つᶍࡀ኱ࡁ࠸እຊ࡛ࡣ⿕ᐖ࡟⤖ࡧࡘࡃྍ⬟ᛶࡀ㧗ࡃ࡞ࡿࠋࡇࡢᶵ⬟ⓗࣇࣛࢪࣜࢸ࢕ࡣ㸪S Ꮠ᭱኱್࡟ࡼࡾᇶ‽໬ࡋࡓつᶍᕸࡍࡿࠋⅆᒣᆅᇦ࡟㒔ᕷࢆసࡽ࡞࠸࡜࠸࠺

1
0
-2
-4
-6
-8
-10
-12
-14
-16
-18

10㡰఩

100

1000

ࣁࢨ࣮ࢻࡢ㡰఩つᶍ᭤⥺

᭚㟢㔞ࡀ
༴㝤ഃ࡟
೫ᅾࡍࡿሙྜ

᭚㟢㔞ࡀᏳ඲ഃ࡟೫ᅾࡍࡿሙྜ

⬤ᙅᛶࢆࣟࢪࢫࢸ࢕ࢵࢡ
㛵ᩘ࡟ࡼࡾ⪃៖ࡋࡓ㸪⿕ᐖࡢ㡰఩つᶍ᭤⥺ᅗ ௬᝿ⓗ࡞⿕ᐖࡢ㡰఩つᶍ᭤⥺≧ࡢࣟࢪࢫࢸ࢕ࢵࢡ᭤⥺࡛⾲⌧ࡉࢀࡿࡇ࡜ࡀከ࠸ࠋࡇࡢຠᯝ࡟ࡼࡾ㸪ᑠつᶍ࡞ࣁࢨ࣮ࢻ࡟ᑐࡍ
ࡿ⿕ᐖࡣᑠࡉࡃ࡞ࡿ࠿ࡽ㸪㡰఩つᶍ᭤⥺ࡢഴࡁࡣྑ᪉࡟࠾࠸࡚ᛴ࡟࡞ࡿࠋࡉࡽ࡟እຊつᶍࡀ᪥ᖖⓗ࡞ኚືᖜ௨ୗ࡟࡞ࢀࡤ⿕ᐖࡣほࡉࢀ࡞ࡃ࡞ࡾ㸪᭤⥺ࡀ࠶ࡿ㡰఩࡛㏵ษࢀࡿࠋ㏫࡟㸪ᴟ➃࡟኱ࡁ࡞ࣁࢨ࣮ࢻࡣᗈᇦ࡟ᙳ㡪ࢆཬࡰࡍࡀ㸪⿕ᐖࡣᆅᇦ༢఩ࡈ࡜࡟ィࡉࢀࡿࡓࡵ㸪ᕥ᪉࡟࠾ࡅࡿ᭤⥺ࡢഴࡁࡣᑠࡉࡃ࡞ࡿྍ⬟ᛶࡀ࠶ࡿࠋ
௨ୖࡢࡇ࡜ࢆ☜ㄆࡍࡿࡓࡵ㸪┤⥺ⓗ࡞ࣁࢨ࣮ࢻࡢ㡰఩つᶍ᭤⥺ࢆ௬ᐃࡋ㸪⬤ᙅᛶࢆࣟࢪࢫࢸ࢕
ᅗ࡟ࢵࢡᆺࡢᶵ⬟ⓗࣇࣛࢪࣜࢸ࢕㛵ᩘ࡛୚࠼࡚⿕ᐖࡢ㡰఩つᶍ᭤⥺ࡢᙧ≧ࢆィ⟬ࡋࡓࡶࡢࢆᅗ
♧ࡍࠋᶵ⬟ⓗࣇࣛࢪࣜࢸ࢕᭤⥺ࡢࣃ࣓࣮ࣛࢱ್࡟౫Ꮡࡍࡿࡀ㸪⿕ᐖࡢ㡰఩つᶍ᭤⥺ࡢഴࡁࡣࣁ
ࢨ࣮ࢻࡼࡾࡶᛴ࡟࡞ࡾྑୖ࡟ฝ࡞ᙧ≧࡜࡞ࡿࡇ࡜ࡀ☜ㄆ࡛ࡁࡓࠋࡇࡢᅗ࡛ࡣࡉࡽ࡟㸪᭚㟢㔞ࡀ୍ᵝ࡞✵㛫ศᕸ࡟ẚ࡭࡚㸪Ᏻ඲ഃ࡟೫ᅾࡍࡿሙྜ࡜༴㝤ഃ࡟೫ᅾࡍࡿሙྜࡶ⾲♧ࡋ࡚࠾ࡾ㸪ࣁࢨ࣮ࢻ࢚ࣜ࢔ࡢᅵᆅ฼⏝ᙉᗘࢆୗࡆࡿ᪋⟇ࢆᡴࡘ࡜㸪኱つᶍ⿕ᐖࡢ㢖ᗘࡀῶᑡࡋ㡰఩つᶍ᭤⥺ࡢᕥഃࡀୗࡀࡗ࡚ഴࡁࡀ⦆ࡃ࡞ࡿ࡜࠸࠺ᙳ㡪ࡀ᝿ᐃ࡛ࡁࡿࠋ௚᪉㸪᢬ᢠຊࡢᙉ໬࡟ࡼࡾ⬤ᙅᛶࢆୗࡆࡿᨻ⟇ࡣᑠつᶍ⿕ᐖࡢ㍍ῶ࡟ຠᯝࡀ኱ࡁ࠸ࡓࡵ࡟㸪㡰఩つᶍ᭤⥺ࡢྑഃࢆୗࡆ࡚໙㓄ࢆ⌫࡟ࡍࡿ࡜࠸࠺ᙳ㡪ࡀ᝿ᐃ࡛ࡁࡿࠋ

3㸬 㒔㐨ᗓ┴ู⿕ᐖ⤫ィࡢ㠀㈇್⾜ิᅉᏊศゎ 10) ᡭἲ࡟ࡼࡿ㞟⣙᪥ᮏ࡟࠾ࡅࡿ⅏ᐖ⿕ᐖศᕸࡢ⤒ᖺኚ໬ࢆศᯒࡍࡿࠋࡇࡇ࡛ࡣ㸪ᾘ㜵ᗇࡀ㞟⣙ࡋᾘ㜵ⓑ᭩ࡢ௜⾲࡟ᥖ㍕ࡉࢀࡓ㒔㐨ᗓ┴ูᖺ㛫⿕ᐖ⤫ィࡢ 2007 ᖺ࠿ࡽ 2019 ᖺࡲ࡛ࡢ 13 ᖺ㛫ࡢࢹ࣮ࢱࢆ⏝࠸ࡿࠋ⿕ᐖ࡟㛵ࡍࡿ㡯┠࠿ࡽ⤒ᖺⓗ࡞㔠㖹౯್ࡢኚ໬ࢆཷࡅࡿ⥲⿕ᐖ㢠ࢆ㝖ࡁ㸪௨ୗ࡟♧ࡍ 21 㡯┠ࡢᩘ್ࢆᩚ⌮ࡋࡓࠋࡍ࡞ࢃࡕ㸪a)Ṛஸ࣭୙᫂⪅ᩘ㸪b)㈇യ⪅ᩘ㸪c)඲ቯ࣭ὶኻᐙᒇᩘ㸪d)༙ቯᐙ
ᒇᩘ㸪e)୍㒊◚ᦆᐙᒇᩘ㸪f)ᗋୖᾐỈᐙᒇᩘ㸪g)ᗋୗᾐỈᐙᒇᩘ㸪h)㠀ఫᐙᘓ≀⿕ᐖ௳ᩘ㸪i)Ỉ⏣ࡢὶኻ࣭ᇙἐ㠃✚㸪j)Ỉ⏣ࡢෙỈ㠃✚㸪k)⏿ࡢὶኻ࣭ᇙἐ㠃✚㸪l)⏿ࡢෙỈ㠃✚㸪m)㐨㊰ᦆቯ௳ᩘ㸪n)ᶫᱱ◚ᦆᩘ㸪o)Ἑᕝᦆቯ௳ᩘ㸪p)ᒣ㸦ᓴ㸧ࡃࡎࢀ௳ᩘ㸪q)㕲㌶㐨⿕ᐖ௳ᩘ㸪r)㏻ಙ᪋タ⿕ᐖ௳ᩘ㸪s)⯪⯧⿕ᐖ௳ᩘ㸪t)⨯⅏ୡᖏᩘ㸪u)⨯⅏⪅ᩘ࡛࠶ࡿࠋሗ࿌᫬ᮇࡲ࡛࡟ㄪᰝࡀ⤊஢ࡋ࡞࠿

125

Missed People
Partly Collap. Houses
Rice Field Destroyed
Road damaged
Railway damaged
Affected People
100%

Injured People
Flood over floor
Rice Field Flooded
Bridge damaged
Telecom damaged

Fully Collap. Houses
Flood under floor
Agric.Field Destroyed
River damaged
Ships damaged

Affected People
River damaged
Affected Households

90%

Affected People

80%
Slope Collupsed
Railway damagedFlood under floor
Agric.Field Flooded

Buildings Dameged
Telecom damaged
Bridge damaged

50%

Bridge damaged

Buildings Dameged
River damaged

Injured People
Road damaged
Partly Collap. Houses
Agric.Field Destroyed

40%
Flood over floor

30%Road damaged

20% Rice Field Destroyed
Rice Field Flooded
10%

Ships damaged

River damaged
Affected Households

70%
60%

Harf Collap. Houses
Buildings Dameged
Agric.Field Flooded
Slope Collupsed
Affected Households

Missed People
Missed People0%
Railway

CityFlood

AgriFlood

Harf Collap. Houses

Rice Field Destroyed
Flood over floor

Missed People

StormDamage

Infra Damage

Missed People

Fully Collap. Houses
Life Damage

Human Damageᅗ  㠀㈇್⾜ิᅉᏊศゎ࡟ࡼࡿ  ࡘࡢᅉᏊࡢᅉᏊ㈇Ⲵ㔞ࡢᵓᡂࡗࡓ⿕ᐖศࡀィୖࡉࢀ࡞࠸ࡓࡵ㸪 2011 ᖺ࡜ 12 ᖺࡢᒾᡭ࣭ᐑᇛ࣭⚟ᓥ㸪2016 ᖺࡢᒾᡭ࣭⇃ᮏ㸪
2019 ᖺࡢᐑᇛ࣭⚟ᓥࡢࢹ࣮ࢱࢆྲྀࡾ㝖ࡁ㸪47ͳ͵ѸͳͲ㸻ͳͺͺ ࢧࣥࣉࣝࢆᑐ㇟࡜ࡋࡓࠋඛ࡟♧ࡋᅗ  ࡟ࡣ㸪ࡇࢀࡽࡢ୰ࡢ a)Ṛஸ࣭୙᫂⪅ᩘ㸪b)㈇യ⪅ᩘ㸪c)඲ቯ࣭ὶኻᐙᒇᩘ㸪t)⨯⅏ୡᖏᩘ㸪ࡓᅗu)⨯⅏⪅ᩘࡢ㡰఩つᶍ᭤⥺ࢆ♧ࡋ࡚࠸ࡿ㸬ࡇࢀࡽࡢᩘ್ࡣ㸪ᬺᖺࡈ࡜࡟Ⓨ⏕ࡋࡓ」ᩘࡢ⮬↛⅏ᐖ࢖࣋ࣥࢺ࡟ࡼࡿ⿕ᐖ㔞ࢆ㒔㐨ᗓ┴ࡈ࡜࡟㞟ィࡋࡓᩘ್࡛࠶ࡿࠋࡲࡓ㸪」ᩘࡢ㡯┠ࡢ⿕ᐖࡀྠ୍ࡢ⮬↛⅏ᐖ࢖࣋ࣥࢺ࡟ࡼࡾྠ᫬࡟ᘬࡁ
㉳ࡇࡉࢀࡓሙྜࢆከࡃྵࢇ࡛࠸ࡿࡓࡵ㸪㡯┠ࡈ࡜ࡢᩘ್ࢆ┦஫࡟⊂❧࡞ࡶࡢ࡜ࡋ࡚ᢅ࠺ࡢ࡛ࡣ
࡞ࡃ㸪ᅉᏊศᯒ࡟ࡼࡿ᝟ሗ㞟⣙ࢆ⾜ࡗࡓࠋࡇࡢ࡜ࡁ㸪ࡇࢀࡽࡢ⿕ᐖ㡯┠ࡢᩘ್ࡣᇶᮏⓗ࡟ṇࡢ್ࡋ࠿࡜ࡾᚓ࡞࠸ࡇ࡜࡟╔┠ࡋ㸪☜⋡ศᕸࡢᙧ≧ࢆṍࡵ࡞࠸㠀㈇್⾜ิᅉᏊศゎ㸦NMF; Nonnegative Matrix Factorization㸧ἲࢆ⏝࠸㸪࣋࢖ࢬ⤫ィ࡟ᇶ♏ࢆ⨨ࡃᩘ್ⓗ᥎ᐃἲࢆ㐺⏝ࡋࡓࠋィ⟬᫬㛫࡜ AIC ࢆཧ⪃࡟ᅉᏊᩘࢆ 7 ಶ࡜ᐃࡵࡓࠋᅗ  ࡟♧ࡍᅉᏊ㈇Ⲵ㔞࠿ࡽ 7 ࡘࡢᅉᏊࡢෆᐜࢆ☜ㄆࡍࡿ࡜㸪(1)㕲㐨⿕ᐖࡢ࡯࠿Ṛஸ࣭୙᫂⪅ࡸỈ⏣ࡢὶኻࢆᘬࡁ㉳ࡇࡍᅉᏊ(Railway),(2) Ἑᕝࡢᦆቯ㸪ఫᏯࡢᗋୖ㸪ᗋୗᾐỈࡀேⓗ⿕ᐖ࡜⨯⅏ୡᖏࡸ⨯⅏⪅ࢆⓎ⏕ࡉࡏࡿ㒔ᕷᇦỈᐖࡢᅉᏊ(City Flood)㸪(3) Ἑᕝࡢᦆቯࡀ⏿ࡸỈ⏣ࡢෙỈࢆࡶࡓࡽࡍ㎰ᆅỈᐖࡢᅉᏊ(Agri Flood)㸪(4)ᅵ◁ᔂࢀ࡟ࡼࡿ㐨㊰㸪Ἑᕝࡢᦆቯ࡜ఫᏯࡢᗋୖ
ᾐỈࢆ㉳ࡇࡍỈᐖᅉᏊ(Storm Damage)㸪(5)Ἑᕝ࣭㐨㊰࣭ᶫᱱ࠾ࡼࡧ㎰⏝ᆅࡢᦆቯ࡜Ṛஸ࣭୙᫂⪅࡟ࡘ࡞ࡀࡿ≀⌮ⓗ◚ቯࡢᅉᏊ(Infra Damage)㸪(6)ᐙᒇ㸪㠀ఫᒃᘓ≀㸪㏻ಙ᪋タ㸪ᶫᱱࡢ◚ቯ࡜⨯⅏ୡᖏ㸪⨯⅏⪅ࢆⓎ⏕ࢆࡶࡓࡽࡍ⏕άᇶ┙ࡢᶵ⬟ᦆኻᅉᏊ(Life Damage)㸪࠾ࡼࡧ(7)㠀ఫᒃᘓ≀ࡸ⯪⯧ࡢ◚ቯ࡜ከᩘࡢṚയ⪅ࢆ⏕ࡳฟࡍேⓗ⿕ᐖࡢᅉᏊ(Human Damage)࡛࠶ࡿ㸬
4㸬 㞟⣙ࡉࢀࡓ⿕ᐖᅉᏊᚓⅬࡢ㡰఩つᶍ᭤⥺࡜ࡑࡢ⤒ᖺẚ㍑
13 ᖺࢆ 1 ᖺࡎࡘ㔜」ࡍࡿ 3 ᮇ㛫㸦2007-2011 ᖺ㸪2011-2015 ᖺ㸪2025-2019 ᖺ㸧࡟ศࡅ㸪㒔㐨ᗓ

126┴ูࡢ 7 ࡘࡢᅉᏊᚓⅬࡢ㡰఩つᶍ᭤⥺ࢆసᡂࡋࡓ㸬ᅗ 4 ࡣ 2 ࡘࡢᅉᏊᚓⅬẖ࡟㡰఩つᶍ᭤⥺ࢆࣉࣟࢵࢺࡋࡓ㸬ࡇࢀࡼࡾ㸪࡝ࡢᅉᏊᚓⅬࡶྑୖ࡟ฝ࡞ᙧ≧ࡢ᭤⥺ࢆᣢࡕ㸪⤒ᖺⓗ࡞ኚ໬ࡣᑠࡉ
࠸㸬ᕥୖ᪉ࡢഴࡁࡣ 0.5 ⛬ᗘ࡛࠶ࡾ㸪኱つᶍࡢ⅏ᐖࡢ⿕ᐖࡀ㒔㐨ᗓ┴ࡢ⠊ᅖ࡟཰ࡲࡽ࡞࠸ࡇ࡜
ࡀᙳ㡪ࡋ࡚࠸ࡿ㸬୍᪉㸪୰఩࡛ࡢഴࡁࡣ 1.5 ࠿ࡽ 2.5 ⛬ᗘ࡜ᛴ࡛࠶ࡾ㸪⬤ᙅᛶࢆୗࡆࡿᨻ⟇ࡢᙳ㡪ࡀ♧၀ࡉࢀࡿ㸬࡞࠿࡛ࡶ (6)Life Damage ࡢ᭤⥺ࡣᕥഃ࠿ࡽᛴ࡞ഴࡁࢆᣢࡘࡢ࡜ᑐ㇟ⓗ࡟㸪(7)Human Damage ࡢ᭤⥺ࡣഴࡁࡢኚ໬ࡀ⦆ࡸ࠿࡛㸪ຠᯝⓗ࡞㜵⅏ᑐ⟇ࡢᅔ㞴ࡉࡀᠱᛕࡉࢀࡿ㸬ྠ୍ࡢᅉᏊᚓⅬࡢ᫬ᮇ࡟ࡼࡿ㐪࠸ࢆ☜ㄆࡍࡿ࡜㸪᭤⥺ࡢᕥୗ᪉࡬ࡢࢩࣇࢺࡀ᫂░࡞ᅉᏊࡣぢᙜࡓࡽࡎ㸪㜵⅏᪋⟇ࡢຠᯝࡀ╔ᐇ࡟⌧ࢀ࡚࠸ࡿ࡜ࡣゝ࠼࡞࠸ࡇ࡜ࡀࢃ࠿ࡗࡓ㸬

A: (1) Railway Damage, (5) Infra Damage

C: (2) City Flood, (4) Storm Damage

B: (2) City Flood, (3) Agri Flood

D: (6) Life Damage, (7) Human Damageᅗ   ࡘࡢᅉᏊᚓⅬࡢ  ᮇ㛫ูࡢ㡰఩つᶍ᭤⥺

1)
2)
3)





டᒸᘯ࿴㸸㠀㈇್⾜ิᅉᏊศゎ㸪ィ ࡜ไᚚ㸪➨ 51 ᕳ➨ 9 ྕ㸪pp.835-844㸪2012㸬ඖ஭ึ㡢࣭ዟᮧㄔ࣭Ỉ㇂኱஧㑻㸸ᖺ㱋ᵓᡂࡢඹ㏻ᛶ࡟╔┠ࡋࡓᆅᇦ♫఍ࡢẚ㍑ศᯒἲ㸪ᅵᮌィ⏬Ꮫ◊✲࣭ㅮ₇
㞟㸪Vol.57㸪No.17-09㸪2018㸬
Mikkel N. Schmidt, Ole Winther, and Lars Kai Hansen: Bayesian Non-negative Matrix Factorization, ICA 2009, LNCS
5441, pp.540-547, 2009.

東北地域災害科学研究

127

第58巻（2022）ᆅᙧ࠿ࡽࡳࡓᒣ㛫㒊㞟ⴠ࡟࠾ࡅࡿ㇦㞵᫬ࡢ㐺ษ࡞㑊㞴ሙᡤ࡟ࡘ࠸࡚
ᮾ໭⚟♴኱Ꮫ ೺ᗣ⛉Ꮫ㒊 ་⒪⤒Ⴀ⟶⌮Ꮫ⛉Ỉᮏ ໷㉳

1㸬 ࡣࡌࡵ࡟
໭ୖᒣᆅࢆࡣࡌࡵ࡜ࡍࡿᮾ໭ᆅ᪉ᒣ㛫㒊ࡢ㞟ⴠࡣ㸪⌧Ἑᗋἢ࠸ࡢ⣽ࡃ⊃࠸పᆅ࡟❧ᆅࡋ࡚࠸ࡿ
ࡓࡵ࡟㸪㇦㞵᫬ࡢὥỈࡸᅵ◁⅏ᐖ࡟ࡼࡿ༴㝤ᗘࡀ┦ᑐⓗ࡟㧗࠸ࠋ஦ᐇ㸪໭ୖᒣᆅ໭㒊࡟఩⨨ࡍࡿᒾᡭ┴ᒾἨ⏫ࡣ㸪2016 ᖺࡢྎ㢼࡟ࡼࡿ㇦㞵࡟ࡼࡗ࡚⏫඲యࡀ⿕⅏ࡋࡓࠋࡑࡋ࡚≉࡟㸪⌧Ἑᗋἢ࠸ࡢ㧗㱋⪅⚟♴᪋タࡣ⏒኱࡞ὥỈ⿕ᐖࢆཷࡅࡓ㸦ᅵᒇ࡯࠿㸪2018㸧ࠋ1947 ᖺ⡿㌷᧜ᙳࡢ✵୰෗┿ࢆ⏝࠸࡚ᚤᆅᙧุㄞࢆ⾜࠺࡜㸪ୖグࡢ㧗㱋⪅⚟♴᪋タࡣ㸪Ἑᕝὶ㔞ቑ኱᫬࡟ᙧᡂࡉࢀࡓᪧἙ㐨ࡀከᩘㄆࡵࡽࢀࡿỏ℃ཎୖ࡟❧ᆅࡋ࡚࠾ࡾ㸪ὥỈࡢ༴㝤ᗘࡀᴟࡵ࡚㧗࠸ሙᡤ࡟࠶ࡗࡓࡇ࡜ࡀࢃ࠿ࡿࠋ
ࡼࡗ࡚㸪ࡇࢀࡽࡢᒣ㛫㒊ࡢ㞟ⴠ࡟࠾࠸࡚㸪㇦㞵⅏ᐖࡀ㉳ࡇࡿ๓࡟ࡼࡾᏳ඲࡞ሙᡤ࡬㐺ษ࡟㑊㞴ࡍࡿࡓࡵ࡟ࡣ㸪ᆅᇦࡢఫẸ㛫࡛㌟㏆࡞ᆅᙧ⎔ቃ࡟㛵ࡍࡿ▱㆑ࢆ஦๓࡟ඹ᭷ࡋ࡚࠾ࡃࡇ࡜㸦Ỉᮏ㸪2022㸧ࡀఱࡼࡾࡶ㔜せ࡜࡞ࡿࠋ࡜ࡇࢁ࡛㸪ᒣ㛫㒊ࢆὶୗࡍࡿἙᕝἢ࠸࡟ࡣ㸪⊃㝼࡞ࡀࡽࡶᙧᡂ᫬௦ࢆ␗࡟ࡍࡿ」ᩘࡢẁୣ㠃ࡀⓎ㐩ࡋ࡚࠸ࡿሙᡤࡀㄆࡵࡽࢀࡿࠋࡑࡋ࡚ࡇࢀࡽࡢẁୣ㠃ࡢ୰࡟ࡣ㸪⌧Ἑᗋ࠿ࡽࡢẚ㧗ࡀᩘ༑㹫௨ୖ࠶ࡾ㸪࠿ࡘ㸪᏶඲࡟㞳Ỉࡋ࡚࠸ࡿ࡜ุ᩿ࡉࢀࡿẁୣ㠃ࡶ࠶ࡿࠋࡋࡓࡀࡗ࡚㸪⫼ᚋࡢᩳ㠃⅏ᐖࡢ༴㝤ᛶࡀ↓࠸㝈ࡾ㸪ࡇࡢࡼ࠺࡞ẁୣ㠃ୖࡢᅵᆅࡣ㸪ᒣ㛫㒊࡟࠾࠸࡚ࡶ㇦㞵᫬ࡢ㑊㞴ሙᡤࡢ㐺ᆅ࡟࡞ࡾᚓࡿ࡜
⪃࠼ࡽࢀࡿࠋ
ᮏ✏ࡣ㸪㇦㞵᫬࡟࠾ࡅࡿᒣ㛫㒊㞟ⴠࡢ㑊㞴ሙᡤ࡟ࡘ࠸࡚⪃ᐹࢆ⾜࠺ࡓࡵ࡟㸪㞟ⴠ࿘㎶࡟」ᩘࡢẁୣ㠃ࡀⓎ㐩ࡍࡿᒾᡭ┴ᒾἨ⏫ࡢᒾἨᆅ༊࡜ྠ┴ᐑྂᕷࡢⱱᕷᆅ༊ࢆ◊✲ᑐ㇟ᆅᇦ࡜ࡍࡿࠋᒾἨᆅ༊ࡣᙺሙ
ࢆ୰ᚰ࡜ࡋࡓẚ㍑ⓗ኱ࡁ࡞㞟ⴠ࡛࠶ࡾ㸪ⱱᕷᆅ༊ࡣ
໭ୖᒣᆅෆ࡛඾ᆺⓗ࡟ࡳࡽࢀࡿᑠつᶍ㞟ⴠ࡛࠶ࡿࠋ
ࡇࢀࡽࡢ 2 ᆅ༊࡟࠾࠸࡚ࡑࢀࡒࢀࡢᆅᙧ⎔ቃࢆㄪᰝࡋ㸪⌧⾜ࡢࣁࢨ࣮ࢻ࣐ࢵࣉ࡟ࡼࡿ᝟ሗࡶ㋃ࡲ࠼࡞
ࡀࡽ㸪㇦㞵᫬࡟࠾ࡅࡿᒣ㛫㒊㞟ⴠࡢලయⓗ࡞㑊㞴ሙᡤࡢ㐺ᆅࢆぢฟࡍࡇ࡜ࢆ┠ⓗ࡜ࡍࡿࠋ2㸬 ᪉ἲ1947 ᖺ⡿㌷࠾ࡼࡧ 1968 ᖺᅜᅵᆅ⌮㝔᧜ᙳࡢ✵୰෗┿ࢆ⏝࠸࡚ᆅᙧศ㢮ᅗࢆసᡂࡋ㸪⌧⾜ࣁࢨ࣮ࢻ࣐ࢵࣉ࡜ࡢẚ㍑᳨ウࢆ⾜ࡗࡓࠋࡲࡓ㸪⌧ᆅ࡟࠾➨ 㻝 ᅗ㻌㻌 ㄪᰝᆅᇦ఩⨨ᅗ㻌㻌ᅜᅵᆅ⌮㝔䛾 㻰㻱㻹 䝕䞊䝍䜢⏝䛔䛶సᡂ䛧䛯䜰䝘䜾䝸䝣⏬ീ䚹㻌㉥㟷䝯䜺䝛䜢⏝䛔䛶ᆅᙧ䜢❧యⓗ䛻ぢ䜛䛣䛸䛜ྍ⬟䚹 㻌*Appropriate evacuation sites during heavy rainfall in mountainous areas based on landform analysis by
Tadaki MIZUMOTO

128

࠸࡚ࡣ㸪ᆅᙧㄪᰝ࠾ࡼࡧᅵᆅ฼⏝≧ἣㄪᰝࢆ⾜ࡗࡓࠋ㸬 㸦㸯㸧ᒾἨ⏫ᒾἨᆅ༊3㸬
ᒾἨ⏫㸦2021㸧࡟ࡼࡿ࡜㸪ᆅᇦ㜵⅏ィ⏬⟇ᐃ࡟㝿ࡋ࡚኱ูࡉࢀࡓ඲ 6 ᆅ༊ࡢ࠺ࡕ㸪⏫Ẹࡢ⣙༙ᩘ࡟࠶ࡓࡿ 4152 ே㸪2067 ୡᖏࡀᒾἨᆅ༊࡟ᒃఫࡋ࡚࠸ࡿࠋᒾἨᆅ༊࡟ࡣᙺሙࢆ୰ᚰ࡜ࡋࡓ⾜ᨻᶵ㛵ࡸᩍ⫱ᶵ㛵ࡶ❧ᆅࡋ࡚࠾ࡾ㸪ࡲࡉ࡟⏫ࡢ୰ᚰᆅ༊࡛ࡶ࠶ࡿࠋ
ࡇࡢࡼ࠺࡟㸪⏫ࡢ༙ᩘ㏆ࡃࡢఫẸࡀᒾἨᆅ༊࡟ᒃఫࡋ࡚࠸ࡿ⌮⏤ࡢ୍ࡘࡣ㸪ᒣ㛫ᆅ࡛࠶ࡿ࡟ࡶ
㛵ࢃࡽࡎ㸪ẚ㍑ⓗᗈ࠸㠃✚ࢆ᭷ࡍࡿ」ᩘࡢẁୣ㠃ࡀⓎ㐩ࡋ࡚࠸ࡿࡇ࡜࡟࠶ࡿࠋ➨㸰ᅗࡣ㸪ᒾἨᆅ༊ࡢᆅᙧศ㢮ᅗ࡛࠶ࡿࠋ໭ୖᒣᆅෆࢆ⺬⾜ࡋ࡞ࡀࡽᮾὶࡍࡿ඲㛗 60 km ࡢᑠᮏᕝ࡟㸪ᨭὶࡢΎỈᕝࡀ༡࠿ࡽす࡬࡜᪉ྥࢆኚ࠼࡞ࡀࡽᑠᮏᕝ࡬ྜὶࡋ࡚࠸ࡿࠋࡇࢀࡽ 2 ࡘࡢἙᕝࡀᙧᡂࡋࡓᆅᙧ㠃ࡣ㸪ୖ఩ࡼࡾᒾἨⅠ㠃㹼Ⅴ㠃࡜⌧Ἑᗋ࠾ࡼࡧỏ℃ཎ࡟༊ศࡉࢀࡿࠋ
ᒾἨⅠ㠃ࡣ㸪ᮏᆅ༊࡛᭱ࡶ㧗఩ࡢἙᡂẁୣ㠃࡛࠶ࡿࠋᒾἨⅠ㠃࡜ᑠᮏᕝࡢ⌧Ἑᗋ࡜ࡢẚ㧗ࡣ⣙ 25➨䠎䠎ᅗ㻌㻌 ᒾἨ⏫ᒾἨᆅ༊䛾ᆅᙧศ㢮ᅗ㻌㻌 㻌ᇶᅗ䛾෗┿䛿ᅜᅵᆅ⌮㝔᧜ᙳ✵୰෗┿ 㼀㻻㻙㻢㻤㻙㻝㻝㼅㻙㻯㻞㻜㻘㻝㻟㻘㻝㻠 䜢⏝䛔䛶సᡂ䛧䛯䜰䝘䜾䝸䝣䠏㻰 ⏬ീ䚹㻌㉥㟷䝯䜺䝛䜢㏻䛧䛶ᆅᙧ䜢❧యⓗ䛻ぢ䜛䛣䛸䛜ྍ⬟䚹㻌

129

㹼30 㹫㸪ΎỈᕝ࡜ࡢẚ㧗ࡣ⣙ 20㹼25 m ࡛࠶ࡿࠋᒾἨⅠ㠃ୖ࡟ࡣ㸪⏫ᙺሙࡸ⏫Ẹ఍㤋ࡀ❧ᆅࡋ࡚࠸
ࡿࠋᒾἨⅡ㠃ࡣ㸪ᮏᆅ༊࡛᭱ࡶᗈࡃⓎ㐩ࡍࡿἙᡂẁୣ㠃࡛࠶ࡿࠋᑠᮏᕝ࠾ࡼࡧΎỈᕝࡢ⌧Ἑᗋ࡜ࡢẚ㧗ࡣ㸪ࡑࢀࡒࢀ 15㹼20 m㸪10㹼15 m ࡛࠶ࡿࠋΎỈᕝࡀᙧᡂࡋࡓᒾἨⅡ㠃ୖ࡟ࡣ㸪୙᫂░࡞ࡀࡽࡶΎỈᕝࡢᪧἙ㐨ࡀㄆࡵࡽࢀࡿࠋᒾἨⅢ㠃ࡣ㸪⌧Ἑᗋ࡟ἢࡗ࡚᩿⥆ⓗ࡟ศᕸࡋ࡚࠸ࡿࠋ⌧Ἑᗋ࡜ࡢẚ㧗ࡣ㸪ᑠᮏᕝ࡛ 10㹼12 㹫㸪ΎỈᕝ࡛ 8㹼10 㹫࡛࠶ࡿࠋᒾἨⅣ㠃ࡣ㸪୧Ἑᕝἢ࠸࡟㐃⥆ⓗ࡟ศᕸࡋ࡚࠸ࡿࠋᑠᮏᕝ࡜ΎỈᕝࡢྜὶⅬ௜㏆࡟ㄆࡵࡽࢀࡿᒾἨⅣ㠃ࡣ㸪ᒾἨᆅ༊ࡢᪧ㞟ⴠࢆࡢࡏࡿᆅᙧ㠃࡛࠶ࡿࠋ⌧Ἑᗋ࠿ࡽࡢẚ㧗ࡣ㸪ᑠᮏᕝ࡜ΎỈᕝ࡜ࡶ࡟ 5 m ๓ᚋ࡛࠶ࡿࠋᒾἨⅤ㠃ࡣ᭱ప఩ࡢἙᡂẁୣ㠃࡛࠶ࡾ㸪⌧Ἑᗋ࠿ࡽࡢẚ㧗ࡣ୧Ἑᕝ࡜ࡶ࡟ᩘ m ࡛࠶ࡿࠋΎỈᕝࡀᑠᮏᕝ࡟ྜὶࡍ
ࡿ௜㏆ࡸ㸪ᪧᒾἨ㥐௜㏆࡟ᗈࡃⓎ㐩ࡋ࡚࠸ࡿࠋ
➨ 3 ᅗ㸦a㸧ࡣ㸪ᒾἨ⏫ࣁࢨ࣮ࢻ࣐ࢵࣉ㸦➨ 3 ᅗ㸦b㸧㸧࡟➨ 2 ᅗࡢᆅᙧศ㢮ᅗࢆ㔜ࡡࡓࡶࡢ࡛࠶
ࡿࠋ➨ 3 ᅗ㸦b㸧ࡣ㸪➨ 2 ᅗ࠾ࡼࡧ➨ 3 ᅗ㸦a㸧࡜ྠࡌ⠊ᅖࡢᒾἨ⏫ࣁࢨ࣮ࢻ࣐ࢵࣉ࡛࠶ࡿࠋὥỈ᫬ࡢ᝿ᐃᾐỈ῝ࡀ 4 ẁ㝵࡛♧ࡉࢀ࡚࠾ࡾ㸪ᅵ◁⅏ᐖ᝿ᐃ༊ᇦࡸ㑊㞴ሙᡤ➼ࡶ♧ࡉࢀ࡚࠸ࡿࠋὥỈᾐỈ᝿ᐃࡣ㸪ィ⏬つᶍࡢ኱㞵࡟ࡼࡿ᝿ᐃ࡛࠶ࡿࠋࡲࡓ㸪2016 ᖺࡢྎ㢼 10 ྕ࡟ࡼࡿ኱㞵࡟ࡼࡗ࡚㸪ᐇ㝿࡟ᾐỈ⿕ᐖࢆཷࡅࡓ⠊ᅖࡶᅗ♧ࡉࢀ࡚࠸ࡿࠋࡑࡋ࡚➨ 3 ᅗ㸦c㸧ࡣ㸪᝿ᐃࡋᚓࡿ᭱኱つᶍࡢ኱㞵࡟ࡼࡿὥỈࡢᾐỈ᝿ᐃࡀᅗ♧ࡉࢀࡓᒾἨ⏫ࣁࢨ࣮ࢻ࣐ࢵࣉ࡛࠶ࡿࠋ➨ 3 ᅗ㸦a㸧ࡢᆅᙧศ㢮ᅗ࡜➨䠏ᅗ㻌㻌 ᒾἨᆅ༊䛻䛚䛡䜛ᆅᙧศ㢮ᅗ䛸㻌㻌䝝䝄䞊䝗䝬䝑䝥䛾ẚ㍑㻌
㻌䠄㼍䠅ᒾἨ⏫䝝䝄䞊䝗䝬䝑䝥䠄㼎䠅䛻ᆅᙧศ㢮ᅗ䜢㔜䛽䛯䜒䛾㻌
㻌䠄㼎䠅ᒾἨ⏫䝝䝄䞊䝗䝬䝑䝥䠄ὥỈ䛻䜘䜛ᾐỈ῝䛿㻡㻜 ᖺ䛻୍ᗘ⛬ᗘ䛾ィ⏬つᶍ䛾኱㞵䜢᝿ᐃ䠅 㻌㻌䠄䠿䠅ᒾἨ⏫䝝䝄䞊䝗䝬䝑䝥䠄ὥỈ䛻䜘䜛ᾐỈ῝䛿༓ᖺ䛻୍ᗘ⛬ᗘ䛾᭱኱つᶍ䛾኱㞵䜢᝿ᐃ䠅㻌

130➨ 3 ᅗ㸦b㸧ࢆẚ㍑ࡍࡿ࡜㸪ᒾἨⅤ㠃࠾ࡼࡧỏ℃ཎࡢศᕸᇦࡣ㸪ᾐỈ᝿ᐃ⠊ᅖ࠾ࡼࡧ 2016 ᖺࡢྎ㢼 10 ྕ࡟ࡼࡿὥỈ⿕ᐖ⠊ᅖ࡜࡯ࡰ୍⮴ࡍࡿࠋࡲࡓ㸪➨ 3 ᅗ㸦a㸧࡜㸦c㸧ࢆẚ㍑ࡍࡿ࡜㸪᝿ᐃ᭱኱つᶍࡢᾐỈ᝿ᐃ༊ᇦࡣ㸪ᒾἨⅣ㠃㸪Ⅴ㠃࠾ࡼࡧỏ℃ཎࡢศᕸᇦ࡜࡯ࡰ୍⮴ࡍࡿࠋࡉࡽ࡟ᅗࡢすഃ࡟ᙜࡓࡿᑠᮏᕝᕥᓊ࡛ࡣ㸪ᒾἨⅢ㠃ࡢ୍㒊࡟ࡲ࡛᝿ᐃᾐỈᇦࡀཬࢇ࡛࠸ࡿࡇ࡜ࡀࢃ࠿ࡿࠋ
ᆅᙧศ㢮ᅗ࡟࠾࠸࡚㸪ྠ୍ࡢᆅᙧ㠃࡟ᑐẚࡉࢀࡿẁୣ㠃ࡣ㸪࡯ࡰྠ᫬ᮇ࡟ྠᵝࡢࣉࣟࢭࢫ࡛ᙧ
ᡂࡉࢀࡓẁୣ㠃࡛࠶ࡿࠋࡘࡲࡾ㸪ࣁࢨ࣮ࢻ࣐ࢵࣉ࡛ࡣ᝿ᐃࡉࢀ࡚࠸࡞ࡃ࡚ࡶ㸪ᆅᙧⓗ࡟ࡳࡿ࡜ィ⏬つᶍࡢ 50 ᖺ࡟୍ᗘࡢᾐỈ⿕ᐖࡣᒾἨⅤ㠃࡟ࡲ࡛㸪᝿ᐃ᭱኱つᶍࡢ༓ᖺ࡟୍ᗘࡢᾐỈ⿕ᐖࡣⅢ㠃࡟ࡲ࡛㸪ࡑࢀࡒࢀཬࡪྍ⬟ᛶࡀ㧗࠸ࡇ࡜ࡀ♧ࡉࢀࡿࠋࡑࡋ࡚㸪⤖ᯝ࡜ࡋ࡚ᒾἨⅠ㠃࡜Ⅱ㠃ࡣ㸪᝿ᐃࡉࢀࡿ᭱኱つᶍࡢ㇦㞵᫬࡟ࡶ㸪ẚ㍑ⓗᏳ඲࡞ᅵᆅ࡛࠶ࡿࡇ࡜ࡀᑟ࠿ࢀࡿࠋࡓࡔࡋ㸪ΎỈᕝᕥᓊࡢ
ᒾἨⅡ㠃ୖ࡟ࡣ㸪᳃ࡢ㉺௜㏆࠿ࡽ୕ᮏᯇࢆ⤒࡚ᒾἨ㧗ᰯ௜㏆ࡲ࡛⥆ࡃᪧἙ㐨ࡀㄆࡵࡽࢀࡿ㸦➨ 2ᅗ㸧ࠋࡼࡗ࡚㸪᭱኱つᶍࡢ᝿ᐃࢆࡉࡽ࡟㉸࠼ࡿࡼ࠺࡞㇦㞵ࡢሙྜ࡟ࡣ㸪᳃ࡢ㉺௜㏆࡛⺬⾜ࡍࡿΎỈᕝࡢ⁄ὶࡀ㸪ᒾἨⅡ㠃ୖࢆὶୗࡍࡿྍ⬟ᛶࡶྰᐃ࡛ࡁ࡞࠸ࠋࡑࡶࡑࡶᪧἙ㐨ࡣ࿘ࡾࡼࡾࡶప࠸ሙ
ᡤ࡛࠶ࡿࡓࡵ࡟㸪㇦㞵᫬࡟ࡣᾐỈࡋࡸࡍ࠸ᅵᆅ࡛ࡶ࠶ࡿࠋ௨ୖࡢࡇ࡜࠿ࡽ㸪ᒾἨᆅ༊࡟࠾ࡅࡿ㇦
㞵᫬ࡢ㑊㞴ሙᡤࡢ㐺ᆅࡣࠕᅵ◁⅏ᐖࡢ༴㝤ᛶࡀ↓࠸㸪ΎỈᕝᕥᓊࡢᒾἨⅠ㠃࡜Ⅱ㠃ୖࠖ࡜⤖ㄽࡉࢀࡿࡀ㸪᝿ᐃ᭱኱つᶍࡶ㉸࠼ࡿࡼ࠺࡞㇦㞵ࡢሙྜ࡟ࡣ㸪ࠕᒾἨⅠ㠃ୖ࡟఩⨨ࡍࡿ⏫ᙺሙࡸᅗ᭩㤋㸪⏫
Ẹ఍㤋➼ࠖࡀ᭱ࡶᏳ඲࡞ሙᡤ࡛࠶ࡿࡇ࡜ࡀ♧ࡉࢀࡿࠋ㸦㸰㸧ᐑྂᕷⱱᕷᆅ༊
ᐑྂᕷ᪂㔛ࡢⱱᕷᆅ༊ࡣ㸪໭ୖᒣᆅࢆᮾὶࡍࡿ㛢ఀᕝ࡟㸪㛢ఀᕝᨭὶࡢส㇂ᕝࡀྜὶࡍࡿ௜㏆➨䠐䠐ᅗ㻌㻌 ᐑྂᕷⱱᕷᆅ༊䛾ᆅᙧศ㢮ᅗ㻌㻌 㻌ᇶᅗ䛾෗┿䛿⡿㌷᧜ᙳ䛾✵୰෗┿䠄㻹㻝㻜㻣㻞㻙㻟㻥䠈㻠㻜䠅䜢⏝䛔䛶సᡂ䛧䛯䜰䝘䜾䝸䝣䠏㻰 ⏬ീ䚹㻌㉥㟷䝯䜺䝛䜢㏻䛧䛶ᆅᙧ䜢❧యⓗ䛻ぢ䜛䛣䛸䛜ྍ⬟䚹㻌

131࡟఩⨨ࡍࡿ㸦➨㸰ᅗ㸧ࠋ151 ୡᖏ㸪333 ே㸦ⱱᕷ 3, 4, 5 ᆅ๭ࡢྜィ㸧ࡢẚ㍑ⓗᑠࡉ࡞㞟ⴠ࡛࠶ࡿࠋ
㛢ఀᕝࡢ୧ᓊ࡟ࡣ」ᩘࡢἙᡂẁୣ㠃ࡀⓎ㐩ࡋ࡚࠾ࡾ㸪ୖ఩ࡼࡾⱱᕷⅠ㹼Ⅶ㠃࡟ศ㢮ࡉࢀࡿ㸦➨ 4ᅗ㸧ࠋⱱᕷⅠ㹼Ⅲ㠃ࡣ㸪⌧Ἑᗋ࡜ࡢẚ㧗ࡀ 25 m ௨ୖࡢẁୣ㠃࡛࠶ࡿࠋⱱᕷⅣ㠃࡜Ⅴ㠃ࡣ㸪⌧Ἑᗋࡼࡾࡑࢀࡒࢀ⣙ 20 㹫࡜⣙ 15 m ࡢẚ㧗ࢆ᭷ࡍࡿࠋⱱᕷⅥ㠃ࡣ⌧Ἑᗋ࡜ࡢẚ㧗ࡀ 5㹼8㹫㸪᭱ప఩ࡢ
ⱱᕷⅦ㠃ࡣ 5m ௨ୗ࡛࠶ࡿࠋ㛢ఀᕝᕥᓊࡢ㞟ⴠࡣ㸪࡯ࡰⱱᕷⅥ㠃ࡼࡾୖ఩ࡢẁୣ㠃ୖ࡟❧ᆅࡋ࡚࠸ࡿࠋ୍᪉㸪ⱱᕷ㥐ࢆྵࡴส㇂ᕝྑᓊࡢ㞟ⴠࡣ㸪ⱱᕷⅦ㠃ୖ࡟఩⨨ࡋ࡚࠸ࡿࠋ
ᆅᙧศ㢮ᅗ㸦➨ 5 ᅗ㸦a㸧㸧࡜㛢ఀᕝ࡟ࡼࡿ᭱኱つᶍࡢὥỈࢆ᝿ᐃࡋࡓᾐỈ᝿ᐃᅗ㸦➨ 5 ᅗ㸦b㸧㸹ᒾᡭ┴㸪2021㸧࡜ࢆẚ㍑ࡍࡿ࡜㸪ⱱᕷⅦ㠃࡜ỏ℃ཎࡣᾐỈࡢ༴㝤ᛶࡀ㧗࠸ሙᡤ࡛࠶ࡿࡇ࡜ࡀࢃ࠿
ࡿࠋࡼࡗ࡚㸪ὥỈ⿕ᐖࢆ㑊ࡅࡿࡓࡵࡢ㑊㞴ሙᡤࡣ㸪ⱱᕷⅥ㠃ࡼࡾୖ఩ࡢẁୣ㠃ୖ࡟タ⨨ࡍࡿᚲせࡀ࠶ࡿࠋࡓࡔࡋ㸪➨ 4 ᅗ㸪➨ 5 ᅗ㸦a㸧ࡼࡾ㸪㛢ఀᕝᕥᓊ࡟Ⓨ㐩ࡍࡿẁୣ㠃⩌ࡢ኱㒊ศࡣ㸪⫼ᚋࡢᩳ㠃ࡀᔂቯࡋࡓ㝿ࡢሁ✚≀࡟そࢃࢀ࡚࠸ࡿࡇ࡜࠿ࡽ㸪ྠ⠊ᅖ࡛ࡣ௒ᚋࡶᅵ◁⅏ᐖࡀ㉳ࡁࡿྍ⬟ᛶࡀ࠶ࡿࠋࡼࡗ࡚㸪➨ 5 ᅗ㸦c㸧࡛ᐑྂᕷࡀᣦᐃࡋ࡚࠸ࡿ㑊㞴ᡤࡣ㸪ྠᕷࡢࣁࢨ࣮ࢻ࣐ࢵࣉ࡟ࡶᅗ♧ࡉࢀ࡚࠸ࡿࡼ࠺࡟㸪㇦㞵᫬࡟ࡣᩳ㠃⅏ᐖ࡟ᑐࡍࡿ༴㝤ᗘࡀ㧗ࡲࡿሙᡤ࡟࠶ࡿࡇ࡜ࡀᣦ᦬ࡉࢀࡿࠋ
୍᪉㸪➨ 4 ᅗ㸪➨ 5 ᅗ㸦a㸧࡟♧ࡋࡓᆅⅬ A ࡣ㸪ᩳ㠃⅏ᐖࡢ༴㝤ᗘࡶపࡃ㸪࠿ࡘ⌧Ἑᗋ࠿ࡽࡢ
ẚ㧗ࡀ 25 㹫ࡢⱱᕷⅣ㠃ୖ࡟఩⨨ࡍࡿࠋᆅⅬ A ࡣ⌧ᅾ࣮࢜ࢺ࢟ࣕࣥࣉሙ࡜ࡋ࡚฼⏝ࡉࢀ࡚࠾ࡾ㸦➨
5 ᅗ(d)㸧㸪㑊㞴ሙᡤࡢ㐺ᆅ࡜⪃࠼ࡽࢀࡿࠋࡓࡔࡋ㸪ᆅⅬ A ࡢ༡ᮾ࡟㞄᥋ࡍࡿ᪥ᖐࡾධᾎ᪋タࡣ㸪➨䠑ᅗ㻌㻌 ᐑྂᕷⱱᕷᆅ༊䛾ᆅᙧศ㢮ᅗ䛸䝝䝄䞊䝗䝬䝑䝥䛸䛾ẚ㍑䛚䜘䜃⌧ᆅ෗┿㻌㻌 㻌䠄㼍䠅䠖ᆅᙧศ㢮ᅗ䠄ᇶᅗ䛿ᅜᅵᆅ⌮㝔 㻝㻛㻞㻚㻡 ୓ᆅᙧᅗ㻌 䠄㼎䠅䠖௧࿴ 㻟 ᖺᒾᡭ┴సᡂ㻌 㛢ఀᕝὥỈᾐỈ᝿ᐃ༊ᇦᅗ䠄᝿ᐃ᭱኱つᶍ䠅㻌 䠄㼏䠅䠖ᐑྂᕷ䝝䝄䞊䝗䝬䝑䝥㻌 䠄㼐䠅䠖ᆅⅬ 㻭 䛾⌧ἣ䜢♧䛩෗┿㻌 䠄㼑䠅䠖ᆅⅬ 㻮 䛾⌧ἣ䜢♧䛩෗┿㻌 䠄ᆅⅬ 㻭䠈㻮 䛾ሙᡤ䛿䠈➨ 㻠 ᅗ䛚䜘䜃➨ 㻡 ᅗ䠄㼍䠅䛻ᅗ♧䠅㻌

132➨ 4 ᅗ㸪➨ 5 ᅗ㸦a㸧ࡢᆅᙧศ㢮ᅗࡀ♧ࡍࡼ࠺࡟ᅵ◁⅏ᐖࡢ༴㝤ᛶࡀ࠶ࡿࡓࡵ㸪㇦㞵᫬ࡢ㑊㞴ሙᡤ࡟ࡣ㐺ࡋ࡚࠸࡞࠸ࠋ
ྠᵝ࡟㸪ᆅⅬ B ࡣ㸪ᩳ㠃⅏ᐖࡢ༴㝤ᗘࡀప࠸ሙᡤ࡟఩⨨ࡋ㸪࠿ࡘ⌧Ἑᗋ࠿ࡽࡢẚ㧗ࡀ 20㹫ࡢⱱᕷⅣ㠃ୖ࡟఩⨨ࡍࡿࠋᆅⅬ B ࡣ⌧ᅾ㸪ᕷࡢᡤ᭷ᆅ࡜ࡋ࡚࢔ࢫࣇ࢓ࣝࢺࡀᩜ࠿ࢀࡓᗈ࠸ᩜᆅ࡜࡞ࡗ
࡚࠾ࡾ㸪ᆅⅬ A ࡜ྠᵝ࡟ᮏᆅ༊ࡢ㑊㞴ሙᡤࡢ㐺ᆅ࡜⪃࠼ࡽࢀࡿࠋ
4㸬
㸬 ࡲ࡜ࡵ࡜௒ᚋࡢㄢ㢟໭ୖᒣᆅ࡟఩⨨ࡍࡿᒾἨ⏫ᒾἨᆅ༊࠾ࡼࡧᐑྂᕷⱱᕷᆅ༊ࢆ஦౛࡜ࡋ㸪㇦㞵᫬࡟࠾ࡅࡿᒣ㛫㒊㞟ⴠࡢ㐺ษ࡞㑊㞴ሙᡤ࡟ࡘ࠸࡚㸪ᆅᙧศ㢮ᅗ࡟ᇶ࡙ࡃ⪃ᐹࢆ⾜ࡗࡓࠋᒾἨᆅ༊࡛ࡣ㸪⏫ᙺሙ➼ࡀ❧ᆅࡍࡿᒾἨⅠ㠃࡜㸪ᒾἨ୰Ꮫᰯ௜㏆࠿ࡽす᪉࡬ᗈࡀࡿᒾἨⅡ㠃ࡀ㸪㇦㞵᫬࡟ࡶ┦ᑐⓗ࡟Ᏻ඲࡞ሙ
ᡤ࡜ࡋ࡚ㄆᐃࡉࢀࡿࠋࡓࡔࡋ㸪ᒾἨⅡ㠃ୖ࡟ࡣẚ㍑ⓗ᪂ࡋ࠸᫬௦࡟ᙧᡂࡉࢀࡓᪧἙ㐨ࡀㄆࡵࡽࢀ
ࡿࡇ࡜࠿ࡽ㸪᝿ᐃࢆ㉸࠼ࡿࡼ࠺࡞㇦㞵ࡢሙྜ࡟ࡣ㸪ᒾἨⅠ㠃ୖ࡟㝈ᐃࡋ࡚㑊㞴ሙᡤࢆタ⨨ࡍ࡭ࡁ࡛࠶ࡿࡇ࡜ࡶྠ᫬࡟ᣦ᦬ࡉࢀࡿࠋ
ᐑྂᕷⱱᕷᆅ༊࡛ࡣ㸪ẁୣ㠃ࡢ఩⨨࡜⌧Ἑᗋ࠿ࡽࡢẚ㧗࡟ຍ࠼࡚㸪⫼ᚋࡢᩳ㠃⅏ᐖࣜࢫࢡࡸ⌧ᅾࡢᅵᆅ฼⏝ࢆ⪃៖ࡍࡿ࡜㸪㑊㞴ሙᡤ࡟㐺ᙜ࡞㸰ࣨᡤࢆᣲࡆࡿࡇ࡜ࡀ࡛ࡁࡿࠋࡓࡔࡋ㸪ࡇࢀࡽ㸰ࣨᡤࡢ࠺ࡕ㸪⌧ᅾ࣮࢜ࢺ࢟ࣕࣥࣉሙ࡜ࡋ࡚฼⏝ࡉࢀ࡚࠸ࡿሙᡤ࡬⛣ືࡍࡿ㝿࡟ࡣ㸪㛢ఀᕝ࡟࠿࠿
ࡿᶫࢆΏࡿᚲせࡀ࠶ࡿࠋࡼࡗ࡚㸪࣮࢜ࢺ࢟ࣕࣥࣉሙࢆ㑊㞴ሙᡤ࡜ࡋ࡚᭷ຠά⏝ࡍࡿࡓࡵ࡟ࡣ㸪ࡼࡾ᪩ࡵࡢ㑊㞴ࡀᴟࡵ࡚㔜せ࡜࡞ࡿࠋᴫࡋ࡚୧ᆅ༊࡜ࡶ࡟㸪⌧Ἑᗋ࠿ࡽࡢẚ㧗ࡀ 5 m ௨ୗࡢప఩ẁୣ㠃ࡸỏ℃ཎࡣ㸪ὥỈ⿕ᐖࡢྍ⬟ᛶࡀ㧗࠸ሙᡤ࡛࠶ࡿࡇ࡜ࡀ♧ࡉࢀࡓࠋྂࡃ࠿ࡽᒣ㛫㒊࡟ᬽࡽࡍேࠎࡣ㸪ᅵ◁⅏ᐖࡼࡾࡶⓎ⏕㢖ᗘࡢ㧗࠸ὥỈ⅏ᐖ࠿ࡽ㌟ࢆᏲࡿࡇ࡜ࢆ
➨୍࡟⪃࠼㸪ྍ⬟࡞㝈ࡾᕝ࠿ࡽ㞳ࢀࡓሙᡤ࡟ᒃࢆᵓ࠼࡚࠸ࡿࠋࡘࡲࡾ㸪ẚ㍑ⓗ㛗࠸⧞ࡾ㏉ࡋ㛫㝸࡛㉳ࡁࡿᅵ◁⅏ᐖࡣ㸪ᒣ㛫㒊ࡢேࠎ࡟࡜ࡗ࡚ࡶ㸪ࡑࡢ༴㝤ᛶࡀㄆ▱ࡉࢀ࡟ࡃ࠸⮬↛⅏ᐖ࡜࡞ࡗ࡚
࠸ࡿࠋࡓࡔࡋ㸪㐣ཤ࡟ᅵ◁⅏ᐖࡀ㉳ࡁࡓሙᡤ࡛ࡣ㸪௒ᚋࡶྠᵝࡢ⅏ᐖࡀ༑ศ࡟㉳ࡇࡾᚓࡿࠋࡼࡗ
࡚㸪㇦㞵᫬࡟ࡣὥỈ⅏ᐖ࡜ྠᵝ࡟㸪ᅵ◁⅏ᐖ࡟ᑐࡋ࡚ࡶᖖ࡟㧗࠸㆙ᡄព㆑ࢆᣢࡘᚲせࡀ࠶ࡿࠋ⌧Ἑᗋἢ࠸ࡢ⣽ࡃ⊃࠸పᆅ࡟❧ᆅࡋ࡚࠸ࡿᒣ㛫㒊ࡢ㞟ⴠ࡛ࡣ㸪㇦㞵᫬࡟㑊㞴ሙᡤ࡜࡞ࡾᚓࡿሙ
ᡤࡀᑡ࡞࠸ࠋࡋ࠿ࡋ㸪ᮏ✏ࡀ♧ࡋࡓࡼ࠺࡟ᆅᙧࢆ୎ᑀ࡟ศᯒࡍࡿࡇ࡜࡟ࡼࡗ࡚㸪ࡓ࡜࠼ᒣ㛫㒊࡟࠾࠸࡚ࡶࠊὥỈ⅏ᐖ࡟ຍ࠼࡚ᅵ◁⅏ᐖ࠿ࡽࡶ㌟ࢆᏲࡿࡇ࡜ࡢ࡛ࡁࡿ㑊㞴ሙᡤࡢ㐺ᆅࢆㄆᐃࡍࡿࡇ
࡜ࡣ༑ศ࡟ྍ⬟࡛࠶ࡿࠋ௒ᅇࡣ㇦㞵᫬࡟࠾ࡅࡿࠕ㑊㞴ሙᡤࠖ࡟ࡘ࠸࡚ࡢ⪃ᐹࢆ⾜ࡗࡓࡀ㸪⌧⾜ࡢࣁࢨ࣮ࢻ࣐ࢵࣉࢆぢࡿ㝈ࡾ࡛ࡣࠕ㑊㞴ᡤࠖ࡟ࡘ࠸࡚ࡶྠᵝ࡟㸪ᆅᙧ⎔ቃࢆ⪃៖ࡋࡓࡼࡾᏳ඲࡞タ⨨ሙᡤࢆྛᆅ࡛෌᳨ウࡍࡿᚲせࡀ࠶ࡿࠋᒣ㛫㒊ࡢ㞟ⴠ࡟ఫࡴேࡓࡕࡀ㸪௒ᚋ㸪㇦㞵⅏ᐖ࠿ࡽ㌟ࢆ
Ᏺࡿࡓࡵ࡟ࡣ㸪㌟㏆࡞ᆅᙧࡢᡂࡾ❧ࡕࢆ㏻ࡋ࡚ᑗ᮶㉳ࡇࡾᚓࡿ⮬↛⅏ᐖࢆ༑ศ࡟ㄆ▱ࡋ㸪⅏ᐖࡀ㉳ࡇࡿ๓࡟࠸ࡕ᪩ࡃᏳ඲࡞ሙᡤ࡬㑊㞴ࡍࡿࡇ࡜ࡀ᭱ࡶ㔜せ࡜⪃࠼ࡽࢀࡿࠋ
ཧ⪃ᩥ⊩ᒾἨ⏫㸦2021㸧ᒾἨ⏫ᆅᇦ㜵⅏ィ⏬࣭௧࿴㸰ᖺᗘಟṇ∧㸬ᒾᡭ┴㸦2021㸧㛢ఀᕝỈ⣔㛢ఀᕝ ὥỈᾐỈ᝿ᐃ༊ᇦᅗ㸦᝿ᐃ᭱኱つᶍ㸧2/3㸦୰ὶ㒊㸧㸬ᅵᒇ༑ᅞ࣭ᑠᒣ┤⣖࣭኱▼⿱Ὀ࣭బ఑༤ே㸦2018㸧2016 ᖺ 8 ᭶ࡢྎ㢼 10 ྕ࡟ࡼࡿᒾᡭ┴໭㒊Ỉᐖㄪᰝሗ࿌㸬⮬↛⅏ᐖ⛉Ꮫ㸪36-4㸪409-427㸬Ỉᮏ໷㉳㸦2022㸧ὥỈࣁࢨ࣮ࢻ࣐ࢵࣉ࡟࠾ࡅࡿᆅᙧศ㢮ᅗࡢព⩏㹼௝ྎᕷᅜぢ࣭Ⲩᕳᮏἑᆅᇦࡢ
ᆅᙧࢆ஦౛࡜ࡋ࡚㹼㸬ᮾ໭⚟♴኱Ꮫ◊✲⣖せ㸪➨ 46 ᕳ㸬東北地域災害科学研究133

第58巻（2022）ឤᰁ⑕ᣑ኱ୗ࡛ࡢᏳྰ☜ㄆ࡟≉໬ࡋࡓ㑊㞴カ⦎ࡢྲྀࡾ⤌ࡳ ᒾᡭ┴❧኱Ꮫ⥲ྜᨻ⟇Ꮫ㒊 ᮡᏳ ࿴ஓ
1㸬 ࡣࡌࡵ࡟ ᪂ᆺࢥࣟࢼ࢘࢖ࣝࢫࡢឤᰁᣑ኱ୗ࡟࠾࠸࡚㸪⅏ᐖⓎ⏕᫬㸪࡜ࡃ࡟Ỉᐖ᫬ࡢ㑊㞴᪉㔪ࡣ኱ࡁࡃ㌿᥮ࡀᅗࡽࢀࡿࡇ࡜࡜࡞ࡗࡓࠋࡇࡢ᪉㔪ࢆ♧ࡋࡓෆ㛶ᗓ࣭ᾘ㜵ᗇࡀ௧࿴㸰ᖺᗘ࡟බᕸࡋࡓࠕ᪂
ᆺࢥࣟࢼ࢘࢖ࣝࢫឤᰁ⑕ࡀ཰᮰ࡋ࡞࠸୰࡟࠾ࡅࡿ⅏ᐖ᫬ࡢ㑊㞴࡟ࡘ࠸࡚࡛ࠖࡣࠊ㑊㞴ᡤ࡟ྥ࠿࠺௨እࡢ㑅ᢥ⫥ࢆ࡜ࡿࡇ࡜ࠊࡍ࡞ࢃࡕࠕศᩓ㑊㞴ࠖ࡟ྥࡅࡓ⾜ືࡢ࿘▱ࡀ⾜ࢃࢀ࡚࠸ࡿ 1)ࠋ
ࡇࡢࡼ࠺࡞≧ἣୗ࡟࠾࠸࡚㸪ᆅ༊ࢥ࣑ࣗࢽࢸ࢕㸦࠸ࢃࡺࡿ⮬἞఍࣭⮬୺㜵⅏఍ࡢ࢝ࣂ࣮ࡍࡿඹ
ྠయࡢ⠊ᅖ㸧࡜ࡋ࡚ࡣ㸪ᆅ༊ෆࡢ㑊㞴ᡤ࡛ࡢឤᰁ⑕ᑐ⟇ࢆ㐍ࡵࡿࡇ࡜ࡣࡶࡕࢁࢇ࡛࠶ࡿࡀ㸪୪⾜ࡋ࡚ศᩓ㑊㞴ࢆ⾜࠺ᆅ༊ఫẸࡢᏳྰ☜ㄆࢆዴఱ࡟ࡋ࡚⾜࠺࠿ࡀㄢ㢟࡜࡞ࡗ࡚࠸ࡿࠋࡑࡇ࡛➹⪅ࡣ㸪ࡇࡢࡼ࠺࡞ឤᰁ⑕ᣑ኱ୗ࡟࠾࠸࡚㸪ᆅ༊࡛ࣞ࣋ࣝࡶ㐠⏝ྍ⬟࡞Ᏻྰ☜ㄆࢩࢫࢸ࣒ࢆヨసࡋ㸪ࡇࢀࢆྲྀࡾ⤌ࢇࡔ㑊㞴カ⦎㸦ᆅ㟈࣭ὠἼ᝿ᐃ㸧ࢆ 2021 ᖺ 11 ᭶࡟⚟ᓥ┴࠸ࢃࡁᕷᖹⷧ☾ᆅ༊࡟࠾࠸࡚ᐇ᪋ࡋࡓࠋᮏ✏࡛ࡣ㸪ࡇࡢྲྀࡾ⤌ࡳ࡟ࡘ࠸࡚ሗ࿌ࡍࡿࠋ

2㸬 Ᏻྰ☜ㄆࢆࡵࡄࡿ⌧≧ ౛࠼ࡤᐑᓮ(2020)ࡣ㸪⇃ᮏᆅ㟈ࡢ㝿࡟㸪せ㓄៖⪅ࡢᏳྰ☜ㄆ࡟㝿ࡋ࡚㸪SNS ࡜ࡋ࡚ LINE࣭࣓࣮ࣝ➼ࢆά⏝ࡋ㸪᪩ᛴ࡟Ᏻྰ☜ㄆࡀᐇ᪋࡛ࡁࡓ஦౛ࢆ⤂௓ࡋ࡚࠸ࡿ 2)ࠋ⩏ົᩍ⫱ㄢ⛬࡛ࡢಖㆤ⪅㐃⤡⥙࡛ SNS ࢧ࣮ࣅࢫࢆά⏝ࡋ࡚࠸ࡿሙྜࡸ㸪࢜ࣥࣛ࢖ࣥᅇぴᯈ࡜࠸ࡗࡓ IT ࢧ࣮ࣅࢫࢆࡍ
࡛࡟ά⏝ࡋ࡚࠸ࡿ⮬἞఍࡛࠶ࢀࡤ㸪᪤Ꮡࡢ᝟ሗࢿࢵࢺ࣮࣡ࢡࢆ฼ά⏝ࡍࡿࡇ࡜࡛㸪Ᏻྰ☜ㄆ㐃⤡࡟㌿⏝ࡍࡿࡇ࡜ࡶྍ⬟࡜࠸࠼ࡿࠋࡋ࠿ࡋ㸪≉ᐃࡢ SNS ࢧ࣮ࣅࢫ࡟ᇶ࡙ࡃᏳྰ☜ㄆࡣ㸪ヱᙜࢧ࣮ࣅࢫࢆ฼⏝ࡋ࡚࠸࡞࠸࣮ࣘࢨ࣮ࢆ⥾ࡵฟࡋ࡚ࡋࡲ࠺ㄢ㢟ࡀ࠶ࡿࠋຍ࠼࡚Ꮫᰯࡸ௻ᴗࡢࡼ࠺࡟㸪ࡑࡢᵓᡂဨࡀ᫂☜࡛࠶ࡾࠊᵓᡂဨྡ⡙ࡢ᭦᪂ࡶᴗົࡢ୍⎔࡜ࡋ࡚ᐃᮇⓗ࡟⾜ࢃࢀ࡚࠸ࡿ⤌⧊࡛࠶ࢀࡤ㸪Ᏻྰ☜ㄆࢧ࣮ࣅࢫ࡬ࡢ஦๓Ⓩ㘓࣭ᑓ⏝࢔ࣉࣜࢣ࣮ࢩࣙࣥࡢࣉࣜ࢖ࣥࢫࢺ࣮ࣝ➼ࡶẚ㍑ⓗᐜ᫆࡜࠸࠼ࡿࠋࡋ࠿ࡋ㸪ᵝࠎ࡞せᅉ࠿ࡽேဨࡢኚືࡀ⏕ࡌ㸪ఫẸ࣭ᙺဨ཮᪉ࡢ㧗㱋⪅ẚ⋡ࡀ㧗ࡃ㸪ᵓᡂဨྡ⡙ࡢ᭦᪂సᴗࡶᆅ༊ᙺဨࡢ࣎ࣛࣥࢱ࣮ࣜ࡞άື࡜࡞ࡿᆅ༊ࢥ࣑ࣗࢽࢸ࢕࡟࠾࠸
࡚ࡣ㸪ࡑࡶࡑࡶᆅ༊ఫẸ㸦ᵓᡂဨ㸧ࡢᢕᥱ࡜㸪IT ࣜࢸࣛࢩ࣮ࡢྥୖ⮬య࡟኱ࡁ࡞ປຊࡀᚲせ࡜࡞ࡾ㸪Ꮫᰯ࣭௻ᴗᆺࡢᏳྰ☜ㄆࢩࢫࢸ࣒ࡢᑟධ࡟஧ࡢ㊊ࢆ㋃ࡴሙྜࡀከ࠸ࠋ࠶ࢃࡏ࡚ࠊᖺࠎᆅ
༊ఫẸࡢῶᑡ㸪ࡍ࡞ࢃࡕ⮬἞఍཰ධࡢῶᑡࡀ⏕ࡌ࡚࠸ࡿᆅ༊࡛ࡣࠊ⊂⮬࡟Ᏻྰ☜ㄆࢧ࣮ࣅࢫࢆ
ᑟධࡋࡓ࡜ࡋ࡚ࡶ㸪ࡑࡢ⥔ᣢ⟶⌮㈝⏝ࢆ࠸ࡘࡲ࡛᤬ฟ࡛ࡁࡿࡢ࠿ࡶ୙Ᏻᮦᩱࡢ୍ࡘ࡜࠸࠼ࡿࠋ

3㸬 ᆅ༊࡛ࣞ࣋ࣝࡶ㐠⏝ྍ⬟࡞Ᏻྰ☜ㄆࢩࢫࢸ࣒ࡢヨస ୖグࡢほⅬ࠿ࡽ㸪ᆅ༊ࣞ࣋ࣝ㸦⮬἞఍㸧࡛Ᏻྰ☜ㄆࢩࢫࢸ࣒ࢆᑟධࡋ࡚࠸ࡃ࡟ࡣ㸪ࡲࡎࠕᵓᡂဨྡ⡙ࡀ୙᏶඲ࠖ㸪ࠕ஦๓ࡢⓏ㘓࣭࢔ࣉࣜ࢖ࣥࢫࢺ࣮ࣝࡀᅔ㞴ࠖ㸪ࠕ⥔ᣢ⟶⌮㈝ࡢ᤬ฟࡀᅔ㞴ࠖ
*The action of evacuation drills specializing in confirming safety under the spread of infectious diseases
by Kazuya SUGIYASU

134࡜࠸࠺ㄢ㢟ࢆ㋃ࡲ࠼ࡓୖ࡛㸪ࡇࢀࡽࡢㄢ㢟ࢆᴟຊゎỴࡋࡓᡭẁ࡟ࡼࡿᏳྰ☜ㄆࢩࢫࢸ࣒࡟ゐࢀ㸪ࡑࡢᚋ㸪ᆅ༊඲యࡢ IT ࣜࢸࣛࢩ࣮ࡀྥୖࡋࡓẁ㝵࡛㸪ࡼࡾ㧗௜ຍ౯್ࡢ࠶ࡿẸ㛫ࢧ࣮ࣅࢫ࡟⛣⾜ࡋ࡚࠸ࡃࡇ࡜ࡶ㸪ᡭẁࡢ୍ࡘ࡛ࡣ࡞࠸࠿࡜⪃࠼ࡿࠋࡇࢀࢆ㋃ࡲ࠼㸪➹⪅ࡣᏳྰ᝟ሗࢆⓏ㘓ࡍࡿ❧ሙ࡜࡞ࡿᆅ༊ఫẸࡢ㈇ᢸ㍍ῶ࡟㔜どࡋ㸪ࠕ஦๓ࡢ࢔ࣉࣜ࢖ࣥࢫࢺ࣮࣭ࣝⓏ㘓సᴗ࡞ࡋ࡛ࡶ฼
⏝࡛ࡁࠊ⥔ᣢ⟶⌮࡟㈝⏝ࢥࢫࢺࡀ⏕ࡌ࡞࠸ࢩࢫࢸ࣒ࠖࢆ┠ᣦࡋ㸪࢔ࣥࢣ࣮ࢺ㞟ィ࣭ཧຍ⪅Ⓩ㘓
ࢧ࣮ࣅࢫ࡛࠶ࡿ Google Form ࢆ౑⏝ࡋࡓᏳྰ☜ㄆࢩࢫࢸ࣒ࢆヨసࡋࡓࠋࡇࡢᏳྰ☜ㄆࢩࢫࢸ࣒ࢆᵓ⠏ࡍࡿ Google Form ࡬ࡢ࢔ࢡࢭࢫ URL ࢆ㸪஦๓࡟㸰ḟඖࣂ࣮ࢥ࣮
ࢻ໬ࡋ㸪࣏ࢫࢱ࣮ࡸࣅࣛ࡜ࡋ࡚ᆅ༊ෆ࡟஦๓࡟ᥖ♧࣭㓄ᕸࡋ࡚࠾ࡅࡤ㸪࣓࢝ࣛ௜ࡁࢫ࣐࣮ࢺࣇ
࢛ࣥࡢ኱༙ࡢᡤ᭷⪅࡛࠶ࢀࡤ㸪࣓࢝ࣛࢆ㉳ືࡋࠊ㸰ḟඖࣂ࣮ࢥ࣮ࢻ࡟࠿ࡊࡍࡔࡅ࡛㸪Ᏻྰ☜ㄆࢩࢫࢸ࣒ࡢ࢔ࢡࢭࢫ URL ࡟ࡓ࡝ࡾ╔ࡃࡇ࡜ࡀྍ⬟࡜࡞ࡗ࡚࠸ࡿࠋ
Ᏻྰ᝟ሗⓏ㘓⪅㸦୍⯡ࡢᆅ༊ఫẸ㸧ഃ࠿ࡽぢ࠼ࡿࢩࢫࢸ࣒ࡢᣲື࡜ࡋ࡚ࡣ㸪௒ࠊࠕᏳ඲ࠖ࠿ࠕ༴
㝤ࠖ࠿࡛㸪ධຊࡍࡿ࡭ࡁ᝟ሗࡀศᒱࡍࡿࡼ࠺࡟ࡋ࡚࠸ࡿࠋ Ᏻྰ᝟ሗⓏ㘓⪅㸦୍⯡ࡢᆅ༊ఫẸ㸧ࡢ⌧ᅾ఩⨨ࡀࠕᏳ඲࡞ሙᡤ࡛࠶ࡾ㸪㸦௚⪅࠿ࡽࡢ㸧ᡭຓࡅ㸦ᩆຓ㸧ࡀ୙せ࡛ࠖ࠶ࢀࡤ㸪ࡢࡕ࡟ᚲせ࡜࡞ࡿᩆ᥼≀㈨㔞☜ᐃࡢࡓࡵ᝟ሗ࡛࠶ࡿࠊࡑࡢሙ࡟࠸
ࡿᐙ᪘ࡢࠕ⏨ᛶᩘ࣭ዪᛶᩘ࣭せ㓄៖⪅ᩘ㸦㧗㱋⪅࣭ஙᗂඣ࣭ዷ፬➼㸧ࠖ➼ࡢᩘ್ࢆධຊࡍࡿࡼ࠺
࡟ࡋࡓࠋ୍᪉࡛㸪Ᏻྰ᝟ሗⓏ㘓⪅ࡀࠕ༴㝤࡞ሙᡤ࡛࠶ࡾࠊᡭຓࡅ㸦ᩆຓ㸧ࡀᚲせ࡛ࠖ࠶ࢀࡤ㸪
119 ␒㏻ሗࡀᅔ㞴࡛࠶ࡿሙྜ࡟ࡣ㸪⌧ᅾ఩⨨࣭⥭ᛴ㐃⤡ඛࢆධຊࡋ࡚࠸ࡓࡔࡃࡇ࡜࡛㸪ࡑࡢ᝟ሗࢆཧ⪃࡟㸪ᆅ༊ᙺဨࡸᾘ㜵ᅋࡀᩆ᥼άືࢆ⾜࠺㸪࡜࠸࠺ࡼ࠺࡟཰㞟ࡍࡿ᝟ሗࡢෆᐜ࡟㸰ࡘࡢศᒱࢆタᐃࡋࡓ㸦ᅗ㸯㸧ࠋ࡞࠾㸪Google Form ࡟Ⓩ㘓ࡉࢀࡓ᝟ሗࡣ㸪Google ࢫࣉࣞࢵࢺࢩ࣮ࢺ࡜
࠸࠺⾲ィ⟬࢔ࣉࣜࢣ࣮ࢩࣙࣥ࡟ࢹ࣮ࢱࡀฟຊࡉࢀࡿࡓࡵ㸪ࡇࡢࢩ࣮ࢺࢆຍᕤࡍࡿࡇ࡜࡛㸪ࠕ⏨ᛶᩘ࣭ዪᛶᩘ࣭せ㓄៖⪅ᩘࠖ࡜࠸ࡗࡓேᩘࡢ㞟ィࡶྍ⬟࡛࠶ࡿࠋຍ࠼࡚㸪ࡇࡢ㞟ィ⏝ Google ࢫࣉࣞࢵࢺࢩ࣮ࢺ࡬ࡢ࢔ࢡࢭࢫ URL ⮬యࡶ㸰ḟඖࣂ࣮ࢥ࣮ࢻ໬ࡍࡿࡇ࡜࡛㸪㑊㞴ᡤ㛤タࠊ࠶ࡿ࠸ࡣ
ᩆຓάືࢆ⾜࠺ᆅ༊ᙺဨ࣭ᾘ㜵ᅋ➼ࡢேဨࡀ㸪ࢫ࣐࣮ࢺࣇ࢛ࣥ࠿ࡽධຊࡉࢀࡓ᭱᪂ࡢᏳྰ᝟ሗ
ࢆ㝶᫬☜ㄆࡍࡿࡇ࡜ࡶྍ⬟࡛࠶ࡿ㸦ᅗ㸰㸧ࠋᅗ㸯 Ᏻྰ☜ㄆࢩࢫࢸ࣒࢖࣓࣮ࢪ


135

ᅗ㸰 ධຊࡉࢀࡓᏳྰ☜ㄆ᝟ሗ㸦ࢫ࣐࣮ࢺࣇ࢛࡛ࣥ⾲♧ࠊᕥ㸸⦪ྥࡁࠊྑ㸸ᶓྥࡁ㜀ぴ᫬㸧೘ྙυʖνනࣖϠωνᅗ㸱 㑊㞴カ⦎ᙜ᪥ࡢᏳྰ☜ㄆࡢᵝᏊ㸦ᕥ㸸༊ᙺဨ࡟ࡼࡿᏳྰ☜ㄆࠊྑ㸸㑊㞴カ⦎ᙜ᪥࡟タ⨨ࡋࡓᏳྰ☜ㄆࢩࢫࢸ࣒య㦂ࢥ࣮ࢼ࣮ࡢ࢖࣓࣮ࢪᅗ㸧
4㸬 㑊㞴カ⦎ᙜ᪥࡛ࡢヨ㦂≧ἣ 㑊㞴カ⦎ᙜ᪥ࡣ㸪࠾࠾ࡼࡑ 50 ྡ࡯࡝ࡀカ⦎࡟ཧຍࡉࢀ࡚࠾ࡾࠊࡑࡢ୰࠿ࡽ 8 ྡࡢఫẸࡀᏳྰ☜ㄆࢩࢫࢸ࣒ࡢヨ㦂࡟ࡈ༠ຊ࠸ࡓࡔ࠸ࡓࠋ࡞࠾㸪ᆅ༊࡜ࡋ࡚ࡣᆅ༊ఫẸЍ⌜㛗Ѝ༊㛗࡟Ᏻྰ☜ㄆᚋࡢሗ࿌ࢆ⾜࠺㐃⤡ࣇ࣮ࣟࡀࡍ࡛࡟ᵓ⠏῭ࡳ࡛࠶ࡾ㸪ࡑࡢయไࢆ☜ㄆࡍࡿ㏻ᖖࡢカ⦎ᑐᛂࡶ⾜ࡗ࡚࠸ࡿࠋカ⦎ᙜ᪥࡟㸰ḟඖࣂ࣮ࢥ࣮ࢻࡢㄞࡳ㎸ࡳ࡟ࡼࡿࢺࣛࣈࣝࡣ⏕ࡌ࡞࠿ࡗࡓࡶࡢ
ࡢ㸪ㄪᰝ༠ຊ⪅ᩘࡣఙࡧᝎࢇࡔࠋࡓࡔࡋ㸪ㄪᰝ࡟༠ຊ࠸ࡓࡔ࠸ࡓ᪉࠿ࡽࡢឤ᝿࡜ࡋ࡚ࡣዲពⓗ࡞཯ᛂࡀከ࠿ࡗࡓࠋ㑊㞴カ⦎ᙜ᪥ࡢᏳྰ☜ㄆࡢᵝᏊࢆᅗ㸱࡟♧ࡍࠋ136


㸬 ㄢ㢟Ⅼ
5㸬
 ᪤Ꮡࡢ Web ࢧ࣮ࣅࢫࣉࣛࢵࢺࣇ࢛࣮࣒࡛࠶ࡿ Google Form ࢆά⏝ࡍࡿࡇ࡜࡛㸪ࠕ஦๓ࡢ࢔ࣉ
ࣜ࢖ࣥࢫࢺ࣮࣭ࣝⓏ㘓సᴗ࡞ࡋ࡛ࡶ฼⏝࡛ࡁࡿᏳྰ☜ㄆࢩࢫࢸ࣒ࠖࡢࡦ࡞ᙧᵓ⠏ࡣẚ㍑ⓗᐜ᫆࡟ྍ⬟࡛࠶ࡗࡓࡀ㸪ࡑࡢ㐠⏝࡟࠶ࡓࡗ࡚ࡣ࠸ࡃࡘ࠿ㄢ㢟࣭␃ពⅬࡀ࠶ࡿࠋձ Ⓩ㘓ࡉࢀࡓಶே᝟ሗࢆ Web ࢧ࣮ࣅࢫୖ࡟Ⓩ㘓ࡋ㸪ᩆ᥼άືࡢࡓࡵ࡟➨୕⪅࡟ᥦ౪ࡍࡿྍ⬟ᛶࡀ࠶ࡿࡇ࡜࡬ࡢ஦๓ㄝ᫂࡜஢ᢎࡀᚲせ࡛࠶ࡿࠋࡓࡔࡋࡇࢀࡣ㸪ධຊ᫬ࡢෑ㢌ㄝ᫂ᩥෆ࡟㸪➨୕⪅ᥦ౪ࡢ᪨ࢆ♧ࡍᩥ❶ࢆ୍ᩥグ㍕ࡍࡿࡇ࡜࡛㸪ἲⓗ࡟ࡣゎỴ࡛ࡁࡿྍ⬟ᛶࡀ㧗࠸ࡀ㸪฼⏝⋡ࢆୖࡆࡿࡓࡵ࡟ࡶ㸪ᆅ༊ఫẸ࡬ࡢ஦๓ㄝ᫂ࢆ⾜࠺ࡇ࡜ࡀᮃࡲࡋ࠸ࠋղ ᩆຓࢆᐜ᫆࡟ࡍࡿࡓࡵ࡟㸪Ᏻྰ᝟ሗࢆⓏ㘓ࡍࡿ㝿࡟㸪⏬ീ㸦⌧ሙ෗┿ࡢ㏦௜㸧Ⓩ㘓ࢆ᭷ຠ࡟ࡍࡿ㸪࡜࠸࠺ᡭẁࡶྲྀࡾ࠺ࡿࠋᮏࢩࢫࢸ࣒࡛ࡶ㸪ᙜึ㸪⏬ീⓏ㘓ࢆ᭷ຠ࡜ࡋ࡚࠸ࡓࡀ㸪2021
ᖺ 11 ᭶᫬Ⅼ࡛ࡢ Google Form ࡢ௙ᵝ࡛ࡣ㸪⏬ീࢆྵࡵࡓࣇ࢓࢖ࣝⓏ㘓ᶵ⬟ࢆ᭷ຠ࡟ࡋ࡚࠸
ࡿ࡜ࠊࢩࢫࢸ࣒࢔ࢡࢭࢫ᫬࡟ Google ࢔࢝࢘ࣥࢺ࡛ࣟࢢ࢖ࣥࡋ࡚࠸ࡿࡇ࡜ࡀᚲ㡲᮲௳࡜࡞ࡗ
࡚࠸ࡿࠋࡇࡢࡓࡵ㸪ᮏࢩࢫࢸ࣒࡛ࡣ஦๓ࣟࢢ࢖ࣥ୙せ࡛࠶ࡿࡇ࡜ࢆඃඛࡍࡿࡓࡵ㸪⏬ീⓏ㘓
ᶵ⬟ࡣ᤼㝖ࡍࡿࡇ࡜࡜ࡋࡓࠋࡇࢀࡣ௒ᚋࡢ௙ᵝኚ᭦ࢆᮇᚅࡍࡿ࡜ࡇࢁ࡛࠶ࡿࠋճ ே࿨࡟㛵ࡍࡿ᝟ሗࢆྲྀࡾᢅ࠺ࡇ࡜ࡶ࠶ࡾ㸪Ⓩ㘓ࡉࢀࡓᏳྰ᝟ሗࢆ㸪ࡔࢀࡀ㝶᫬☜ㄆࡍࡿࡢ࠿㸦࠸ࢃࡺࡿ⟶⌮⪅㸧ࡣ࠶ࡽ࠿ࡌࡵ᫂☜࡟ࡋ࡚࠾ࡃᚲせࡀ࠶ࡿ࡜࠸࠼ࡿࠋմ ࡇࡢࡼ࠺࡞Ᏻྰ☜ㄆࢩࢫࢸ࣒ࡣࠊᆅ༊ෆ࡛ᐇ᪋ࡉࢀ࠺ࡿᏳྰ☜ㄆᡭἲࡢࡦ࡜ࡘ࡛࠶ࡾࠊᏳ
ྰ☜ㄆᴗົࡢຠ⋡໬ࡢ୍ຓ࡜࡞ࡿࡇ࡜ࡀᮃࡲࡋ࠸ࡀࠊ୍᪉࡛ࠊ⌧≧ࡢᑐ㠃ゼၥᘧࠊ࠶ࡿ࠸ࡣ
㑊㞴ᡤ࡛ࡢཷ௜ᘧࡢᏳྰ☜ㄆࢆ᤼ࡋ୍࡚ᮏ໬ࢆᅗࡿ࡭ࡁ࡛࠶ࡿ࡜ࡣ➹⪅ࡣ⪃࠼࡚࠸࡞࠸ࠋ
ᑐ㠃ゼၥᘧࠊཷ௜ᘧᏳྰ☜ㄆ࡛࠶ࡿ࠿ࡽࡇࡑࡢ฼Ⅼࡶ࠶ࡾࠊ௒ᅇᥦ᱌ࡍࡿᏳྰ☜ㄆࢩࢫࢸ࣒ࡣࠊศᩓ㑊㞴࡟ࡼࡗ࡚᪤ᏑࡢᏳྰ☜ㄆࢫ࣮࣒࢟࠿ࡽ₃ࢀ࡚ࡋࡲ࠺ྍ⬟ᛶࡢ࠶ࡿ㑊㞴⪅ࡢᏳྰ☜ㄆࡢ୍ຓ࡜࡞ࡿࡇ࡜ࡀ┠ⓗ࡛࠶ࡿࡇ࡜ࢆࠊࡇࡇ࡟ᨵࡵ࡚♧ࡋ࡚࠾ࡁࡓ࠸ࠋ
᭱ᚋ࡟ࠊᮏࢩࢫࢸ࣒ࡢࢹࣔయ㦂ࢆ 2021 ᖺ 11 ᭶ 6-7 ᪥࡟ᒾᡭ┴㔩▼ᕷ࡛㛤ദࡉࢀࡓࠕࡰ࠺ࡉ
࠸ࡇࡃࡓ࠸ 2021࡛ࠖᐇ᪋ࡋࡓ࡜ࡇࢁ㸪⮬୺㜵⅏఍ࡸ⏫ෆ఍㛵ಀ⪅ࡢ௚㸪௻ᴗ࡜ࡋ࡚㸪ࡇࡢࡼ࠺࡞ࢩࢫࢸ࣒ࢆᑟධࡋࡓ࠸㸪࡜࠸࠺ពぢࢆከᩘ㡬࠸ࡓࠋࡇࢀࡣᏳྰ☜ㄆࡢྲྀࡾ⤌ࡳ࡟ㄢ㢟ࢆᢪ࠼࡚࠸ࡿࡢࡣ㸪ఫẸ⤌⧊࡛࠶ࡿ⮬἞఍ࡔࡅ࡛࡞ࡃࠊᆅᇦ࡟᰿ࡊࡋࡓᆅሙ⏘ᴗࡢ୰ᑠ௻ᴗ࡟࠾࠸࡚
ࡶྠᵝ࡛࠶ࡿࡇ࡜ࢆ♧ࡋ࡚࠸ࡿࠋ௒ᚋࡶ⅏ᐖ⌧ሙࡢពぢࡸᐇ᝟ࢆ㋃ࡲ࠼ࡓࢩࢫࢸ࣒ࡢᨵⰋ࡟ྲྀ
ࡾ⤌ࢇ࡛࠸ࡃḟ➨࡛࠶ࡿࠋཧ⪃ᩥ⊩1) ෆ㛶ᗓ࣭ᾘ㜵ᗇ(2020), ᪂ᆺࢥࣟࢼ࢘࢖ࣝࢫឤᰁ⑕ࡀ཰᮰ࡋ࡞࠸୰࡟࠾ࡅࡿ⅏ᐖ᫬ࡢ㑊㞴࡟ࡘ࠸࡚㸪 http://www.bousai.go.jp/pdf/colonapoint.pdf (2021 ᖺ 11 ᭶ 11 ᪥㜀ぴ)2) ᐑᓮࡦࡉࡳ(2020), ⇃ᮏᆅ㟈࡟࠾ࡅࡿከ⫋✀㐃ᦠ࡟ࡼࡿᨭ᥼㸸Line ά⏝࡟ࡼࡿ᝟ሗඹ᭷㸪┳ㆤ⸆⌮Ꮫ࢝ࣥࣇ࢓ࣞࣥࢫ㸪2020.1(0), S1-2, බ┈♫ᅋἲே ᪥ᮏ⸆⌮Ꮫ఍ㅰ㎡ᮏ◊✲ࡣ㸪2021 ᖺᗘᮾ໭኱Ꮫ⅏ᐖ⛉Ꮫᅜ㝿◊✲ᡤ࡟࠾ࡅࡿඹྠ◊✲ຓᡂࠕ௧࿴ඖᖺᮾ᪥ᮏྎ㢼࣭ࢥࣟࢼ⚝➼ࡢ㏆ᖺࡢ⅏ᐖ▱ぢ࡟ᇶ࡙ࡃ㑊㞴カ⦎஦౛࢔࣮࢝࢖ࣈᵓ⠏࡟㛵ࡍࡿ◊✲㸦௦⾲㸸ᮡᏳ࿴ஓ㸧ࠖ࡟ࡼࡿᡂᯝ࡛࠶ࡿࠋࡇࡇ࡟ឤㅰࡢពࢆ⾲ࡍࡿࠋ

東北地域災害科学研究

137

第58巻（2022）⮬ ↛⅏ᐖࢹࢪࢱࣝ࢔࣮࢝࢖ࣈࡢㄒᙡ࡟㛵ࡍࡿ◊✲ 㸨ᮾ໭኱Ꮫ⅏ᐖ⛉Ꮫᅜ㝿◊✲ᡤ ᰘᒣ᫂ᐶ
ᮾ໭኱Ꮫ⅏ᐖ⛉Ꮫᅜ㝿◊✲ᡤ -XOLD*HUVWHU1㸬 ࡣࡌࡵ࡟
 2011 ᖺ 3 ᭶ 11 ᪥࡟Ⓨ⏕ࡋࡓᮾ໭ᆅ᪉ኴᖹὒἈᆅ㟈௨㝆㸪඲ᅜⓗ࡟㢼Ỉᐖࡸᆅ㟈⅏ᐖ࡞࡝ࡢ⮬↛⅏ᐖࢹࢪࢱࣝ࢔࣮࢝࢖ࣈࡀᵓ⠏ࡉࢀࡘࡘ࠶ࡿ㸬⮬↛⅏ᐖࢹࢪࢱࣝ࢔࣮࢝࢖ࣈࡣ㸪㐣ཤࡢ⅏ᐖグ㘓ࢆ㜀ぴࡍࡿࡇ࡜ࡔࡅ࡛࡞ࡃ㸪ࡑࢀࡽࡢ⅏ᐖグ㘓ࢆ⏝࠸࡚Ꮫᰯࡸ⮬୺㜵⅏⤌⧊࡞࡝ࡢ㜵⅏ᩍ⫱➼࡟฼ά⏝ࡀ࡞ࡉࢀ࡚࠸ࡿ㸬ࡋ࠿ࡋ㸪⮬↛⅏ᐖࢹࢪࢱࣝ࢔࣮࢝࢖ࣈࡢ඲⯡࡟ゝ࠼ࡿࡇ࡜ࡣ㸪㟈⅏グ㘓ࡢ฼ά⏝஦౛ࡣᑡ࡞ࡃ㸪ࡲࡓᆅᇦ࡛ࡢά⏝ࡢࡳ࡛㝈ᐃⓗ࡛࠶ࡿ㸬ᮾ᪥ᮏ኱㟈⅏ࡢ㟈⅏ࢹࢪࢱࣝ࢔࣮࢝࢖ࣈࡢ฼ά⏝౛࡜ࡋ࡚ࡣ㸪ᑠ୰Ꮫᰯ➼࡛ࡢ㜵⅏ᩍ⫱ࡸ᚟⯆ᩍ⫱ࡢࡓࡵࡢᩍᮦ฼
⏝ࡸ㟈⅏ఏᢎ㤋➼࡛ࡢᒎ♧฼⏝㸪グ㘓ㄅ࡞࡝ࡢ෉Ꮚ፹య࡛ࡢά⏝㸪ࢽ࣮ࣗࢫ࡞࡝ࡢሗ㐨฼⏝࡞࡝ࡀ࠶ࡿ㸬ᮾ᪥ᮏ࡛ࡢά⏝ࡣ㸪╔ᐇ࡟㐍ࢇ࡛࠸ࡿࡶࡢࡢ㸪඲ᅜⓗ࡞ά⏝ࡲ࡛ࡣ࠶ࡲࡾ࡛ࡁ࡚࠸
࡞࠸㸬ࡉࡽ࡟㸪㟈⅏グ㘓ࡢά⏝ࡀ㐍ࢇ࡛࠸࡞࠸࡞࡝ࡢ⌮⏤࡟ࡼࡾ㸪ᮾ᪥ᮏ኱㟈⅏㛵㐃ࡢ㟈⅏ࢹࢪࢱࣝ࢔࣮࢝࢖ࣈࡢࢧ࢖ࢺ㛢㙐ࡀ⥆ࡁ㸪2021 ᖺ⌧ᅾ࡛ 4 ࡘࡢ࢙࢘ࣈࢧ࢖ࢺࡀ㛢㙐ࡋ࡚࠸ࡿ㸬⮬↛⅏ᐖࢹࢪࢱࣝ࢔࣮࢝࢖ࣈࢆά⏝ࡀ㐍ࢇ࡛࠸࡞࠸せᅉࡢ୍ࡘ࡜ࡋ࡚ࡣ㸪⭾኱࡞グ㘓࠿ࡽ┠ⓗࡢࡶࡢࢆぢࡘࡅฟࡍࡇ࡜ࡀ࡛ࡁ࡞࠸ㄢ㢟ࡀ࠶ࡿ࡜⪃࠼ࡿ㸬ࡑࡇ࡛㸪ᮏ✏࡛ࡣ㸪ᮾ᪥ᮏ኱㟈⅏ࢹࢪࢱࣝ࢔࣮࢝࢖ࣈࡢ⌧≧࡜ㄢ㢟࡟ࡘ࠸࡚㏙࡭ࡿ࡜࡜ࡶ࡟㸪᳨⣴࡟ᚲせ࡞ㄒᙡ࡟㛵ࡍࡿㄢ㢟࡟ࡘ࠸
࡚㏙࡭ࡿ㸬2㸬 ᮾ᪥ᮏ኱㟈⅏ࡢ㟈⅏グ㘓ࡢ⌧≧࡜ㄢ㢟ᅜ❧ᅜ఍ᅗ᭩㤋ࡢᮾ᪥ᮏ኱㟈⅏࢔࣮࢝࢖ࣈࠕឡ⛠㸸ࡦ࡞ࡂࡃࠖ1 㸧࡟ࡣ㸪49 ᶵ㛵㸪55 ࢹ࣮ࢱ࣮࣋ࢫࡢ⣙ 496 ୓Ⅼ㸦2021 ᖺ 10 ᭶⌧ᅾ㸧ࡢ㟈⅏グ㘓ࡀබ㛤ࡉࢀ࡚࠸ࡿ㸬⣙ 496 ୓Ⅼ௨እࡢ㟈⅏グ㘓࡟ࡶ㸪ࡦ࡞ࡂࡃ࡜ࢹ࣮ࢱ࣮࣋ࢫ㐃ᦠࡀ࡞ࡉࢀ࡚࠸࡞࠸බⓗᶵ㛵ࡸᅋయ࡞࡝ከᩘ࠶ࡿ㸬ࡉࡽ࡟㸪㟈⅏グ㘓ࡣᩘከࡃಖ᭷ࡋ࡚࠸ࡿࡶࡢࡢ㸪ࢹ࣮ࢱ࣮࣋ࢫ໬ࡸࢹࢪࢱࣝ࢔࣮࢝࢖ࣈ໬ࡀ࡞ࡉࢀ
࡚࠸࡞࠸ᶵ㛵ࡸᅋయࡶከᩘᏑᅾࡍࡿ㸬≉࡟㸪ෆ㛶ᗓࡸ᚟⯆ᗇ㸪ᅜᅵ஺㏻┬㸪⥲ົ┬࡞࡝ࡢྛ┬ᗇ࡜ᆅ᪉⮬἞య➼ࡣ㸪බᩥ᭩ࡸබᩥ᭩࡟ࡣヱᙜࡋ࡞࠸෗┿࡞࡝ࡢ㟈⅏グ㘓ࡀࢹࢪࢱࣝ࢔࣮࢝࢖
ࣈ໬ࡉࢀ࡚࠾ࡽࡎ㸪୍㒊ࡢ㟈⅏グ㘓ࡀ࢙࢘ࣈࢧ࢖ࢺୖࡸグ㘓⣬➼࡟බ㛤ࡉࢀ࡚࠸ࡿࡢࡳ࡛࠶ࡿ㸬ᮾ᪥ᮏ኱㟈⅏ࡢ㟈⅏グ㘓ࡣ㸪ୖグࡢ௚࡟࢖ࣥࢱ࣮ࢿࢵࢺୖ࡟ࡶᩘከࡃᏑᅾࡍࡿ㸬࢖ࣥࢱ࣮ࢿ
ࢵࢺୖ࡟࠾ࡅࡿ㟈⅏グ㘓ࡢṇ☜࡞ᩘࡣ୙࡛᫂ࡣ࠶ࡿࡀ㸪Google ࡸ Yahoo! Japan ࡞࡝ࡢ኱ᡭ᳨⣴ࢧ࢖ࢺ࡛ࠕᮾ᪥ᮏ኱㟈⅏ࠖ࡜᳨⣴ࡋࡓሙྜ㸪2021 ᖺ 10 ᭶᫬Ⅼ࡛⣙ 5,290 ୓Ⅼࡢ࢙࢘ࣈࢧ࢖ࢺࡀ
ぢࡘ࠿ࡿ㸬ࡓࡔࡋ㸪㟈⅏ࢹࢪࢱࣝ࢔࣮࢝࢖ࣈࡣ㸪᳨⣴ࢧ࢖ࢺ࡟㟈⅏グ㘓ࡢ୍Ⅼ୍Ⅼࢆ⮬ື཰㞟ࡀࡉࢀ࡞࠸ࡼ࠺࡟ᑐ⟇ࡀ࡞ࡉࢀ࡚࠸ࡿࡓࡵ㸪ୖグࡢ᳨⣴⤖ᯝ࡟ࡣྵࡲࢀ࡞࠸㸬࢖ࣥࢱ࣮ࢿࢵࢺ
ୖ࠾ࡼࡧ㟈⅏ࢹࢪࢱࣝ࢔࣮࢝࢖ࣈࢆ༢⣧࡟ྜ⟬ࡍࡿ࡜⣙ 5,700 ୓ⅬࡀᏑᅾࡍࡿࡇ࡜࡜࡞ࡿ㸬ࡇࢀࡔࡅࡢከࡃࡢ㟈⅏グ㘓࠿ࡽ┠ⓗࡢグ㘓ࡸ᪂ࡓ࡞Ⓨぢ࡟⧅ࡀࡿグ㘓ࢆぢࡘࡅࡿࡇ࡜ࡣᅔ
*The Vocabulary of Natural Disaster Digital Archives by Akihiro Shibayama and Julia Gerster

138㞴࡛࠶ࡿ࡜ࡶゝ࠼ࡿ㸬ࡉࡽ࡟㸪ᚲせ࡜ࡍࡿ㟈⅏グ㘓ࢆ᳨⣴ࡍࡿࡓࡵ࡟ࡣ㸪ᮾ᪥ᮏ኱㟈⅏ࡢ᚟ᪧ࠿ࡽ᚟⯆ࡲ࡛ࡢ▱㆑ࡸ⿕⅏ᆅᇦࡢᆅྡ㸪㜵⅏㛵㐃▱㆑࡞࡝ࢆ῝ࡃ⌮ゎࡋ࡚࠸ࡿᚲせᛶࡀ࠶ࡾ㸪࠶ࡿ⛬ᗘࡢᑓ㛛▱㆑ࡀᚲせ࡜࡞ࡿ㸬3㸬
㸬 㟈⅏ࢹࢪࢱࣝ࢔࣮࢝࢖ࣈࡢㄒᙡ࡟㛵ࡍࡿㄢ㢟
๓㏙࡛♧ࡋࡓ㏻ࡾ㸪ᑓ㛛ⓗ࡞▱㆑ࡀ࡞ࡅࢀࡤ㸪⭾኱࡞グ㘓࠿ࡽ┠ⓗࡢࡶࡢࢆぢࡘࡅࡿࡇ࡜ࡀ
ᅔ㞴࡛࠶ࡿ㸬ࡉࡽ࡟㸪⮬἞యࡢ㜵⅏ᢸᙜ⫋ဨ࡞࡝⌧ᅾࡢ㜵⅏㛵㐃⏝ㄒࡢ▱㆑ࡀ༑ศ࠶ࡗࡓ࡜ࡋ
࡚ࡶ㸪 ᖺᙜ᫬ࡢ㜵⅏㛵㐃⏝ㄒࡢ▱㆑ࡀ࡞ࡅࢀࡤ᳨⣴⏝ㄒࢆᑟࡁฟࡍࡇ࡜ࡀ㞴ࡋ࠸࡜⪃࠼ࡿ㸬౛࠼ࡤ㸪 ᖺᙜ᫬ࡢὠἼ㆙ሗ࡟ࡘ࠸࡚ࡣ㸪ࠕὠἼ㆙ሗ㸦኱ὠἼ㸧ࠖࡀ⏝࠸ࡽࢀ࡚࠸ࡓࡀ㸪ᖺ  ᭶࠿ࡽࠕ኱ὠἼ㆙ሗࠖ࡜ྡ⛠ࡀኚ᭦࡟࡞ࡗ࡚࠸ࡿ㸬ࡉࡽ࡟㸪 ᖺᙜ᫬ࡣ㸪ࠕ㑊㞴ሙᡤࠖࡸࠕ㑊㞴ᡤࠖࡢྡ⛠ࢆ⏝࠸ࡽࢀ࡚࠸ࡓࡀ㸪 ᖺ  ᭶࡟⅏ᐖᑐ⟇ᇶᮏἲ➼ࡢ୍㒊ࢆᨵṇࡍࡿἲᚊ㸦ᖹᡂ  ᖺἲᚊ➨  ྕ㸧࡟ࡼࡾ㸪ࠕᣦᐃ⥭ᛴ㑊㞴ሙᡤࠖ࡜ࠕᣦᐃ㑊㞴ᡤࠖ࡜ྡ⛠ࡸࡑࡢෆᐜ
ࡀኚ᭦ࡉࢀ࡚࠸ࡿ㸬ࡲࡓ㸪ྡ⛠➼ࡢኚ᭦࡛ࡣ࡞࠸ࡀ㸪㜵⅏㛵㐃⏝ㄒࡢ୰࡟ࡣ㸪ᮾ᪥ᮏ኱㟈⅏ࡢ᚟⯆㛵ಀࡢࡳ࡛⏝࠸ࡽࢀࡿࠕ᚟⯆஺௜㔠ࠖ࡞࡝ࡢ⏝ㄒࡶᏑᅾࡍࡿ㸬ᮾ᪥ᮏ኱㟈⅏ࡢᙜ᫬ࢆ▱ࡿ⮬἞యࡢ㜵⅏ᢸᙜ⫋ဨࡶᑡ࡞࠿ࡽࡎᒃࡿ࡜ࡣᛮࢃࢀࡿࡀ㸪⮬἞యࡢ㜵⅏ᢸᙜ⫋ဨࡣ㸪ᩘᖺ࡛ே஦␗ືࡍࡿࡇ࡜ࡶከࡃ㸪᪂௵ࡢ㜵⅏ᢸᙜ⫋ဨ࡛ࡣ㸪㜵⅏࡟ᚲせ࡞஦౛ࢆᮾ᪥ᮏ኱㟈⅏ࡢ࢔࣮࢝࢖ࣈ࠿ࡽ㟈⅏グ㘓ࢆぢࡘࡅฟࡍࡇ࡜ࡣᅔ㞴࡜⪃࠼ࡿ㸬௨ୗࡢ⾲  ࡟㸪ᅜ❧ᅜ఍ᅗ᭩㤋ࡢᮾ᪥ᮏ኱㟈⅏࢔࣮࢝࢖ࣈࠕឡ⛠㸸ࡦ࡞ࡂࡃࠖ
㸦௨ୗ㸪ࡦ࡞ࡂ
ࡃ㸧1㸧࡜ᐑᇛ┴ᅗ᭩㤋ࡢࠕᮾ᪥ᮏ኱㟈⅏࢔࣮࢝࢖ࣈᐑᇛ㸦௨ୗ㸪ᐑᇛ࢔࣮࢝࢖ࣈ㸧ࠖ2 㸧㸪ᒾᡭ┴ࡢࠕ࠸ࢃ࡚㟈⅏ὠἼ࢔࣮࢝࢖ࣈࠥᕼᮃࠥ㸦௨ୗ㸪ᒾᡭ࢔࣮࢝࢖ࣈ㸧ࠖ3 㸧ࡢ  ࡘࡢ㟈⅏ࢹࢪࢱࣝ࢔
࣮࢝࢖ࣈࢆ⏝࠸࡚⅏ᐖ㛵㐃ἲ௧ࡢྡ⛠ࡸ㜵⅏㛵㐃⏝ㄒࢆ᳨⣴ࡋࡓ⤖ᯝࢆ♧ࡍ㸬ࡦ࡞ࡂࡃࡢ᳨⣴⤖ᯝࡢᩘ࡟ࡘ࠸࡚ࡣ㸪ᐑᇛ࡜ᒾᡭ࢔࣮࢝࢖ࣈࡢ࣓ࢱࢹ࣮ࢱࡢ㐃ᦠࡀ࡞ࡉࢀ࡚࠸ࡿࡓࡵ㸪ᐑᇛ࡜ᒾᡭ࢔࣮࢝࢖ࣈ᳨࡛⣴ࡉࢀࡓⅬᩘࡶྵࡲࢀࡿࡇ࡜ࢆὀグࡋ࡚࠾ࡃ㸬㟈⅏ࢹࢪࢱࣝ࢔࣮࢝࢖ࣈ࡛⅏ᐖ㛵㐃ἲ௧➼ࡢྡ⛠ࢆ᳨⣴ࡋࡓ⤖ᯝ㸪ࡦ࡞ࡂࡃ࡛ࡣ㟈⅏グ㘓ࡀᩘከࡃぢࡘ࠿ࡗࡓ୍᪉㸪ᐑᇛࡸᒾᡭ࢔࣮࢝࢖ࣈ࡛ࡣ㸪㟈⅏グ㘓ࡀ࡯࡜ࢇ࡝ぢࡘ࠿ࡽ࡞࠿ࡗࡓ㸬ࡇࢀࡣ㸪ࡦ࡞ࡂࡃ࡟࠾࠸࡚ᅜ఍㛵㐃㈨ᩱࡀ࢔࣮࢝࢖ࣈ໬ࡉࢀ࡚࠸ࡿࡓࡵ㸪⅏ᐖ㛵㐃ἲ௧ࡢ㛵㐃㈨ᩱࡀᩘከࡃぢࡘ࠿ࡗࡓ㸬ᐑᇛࡸᒾᡭ࢔࣮࢝࢖ࣈ࡟㛵ࡋ࡚ࡣ㸪⅏ᐖ㛵㐃ἲ௧࡟㛵㐃ࡋࡓ㈨ᩱ࡟
᳨⣴ࡢ࣮࣮࢟࣡ࢻࡀ௜ࡅࡽࢀ࡚࠸࡞࠸ࡓࡵ࡛࠶ࡿ㸬౛࠼ࡤ㸪ᛂᛴ௬タఫᏯࡣ㸪⅏ᐖᩆຓἲࡢᑐ
㇟࡜࡞ࡿࡀ㸪
ࠕᛂᛴ௬タఫᏯࠖࡢ෗┿ࡸ㈨ᩱ࡞࡝グ㘓࡟ᑐࡋ࡚ࠕ⅏ᐖᩆຓἲࠖࡢ࣮࣮࢟࣡ࢻࡀ௜
ࡅࡽࢀ࡚࠸࡞࠸࡞࡝࡛࠶ࡿ㸬ᒾᡭ࢔࣮࢝࢖ࣈ࡛ࠕᛂᛴ௬タఫᏯࠖ࡜᳨⣴ࡋࡓሙྜ࡛ࡣ㸪⣙  ୓Ⅼࡢ㟈⅏グ㘓ࡀ᳨⣴࡛ࡁࡿࡶࡢࡢ㸪ࠕ⅏ᐖᩆຓἲࠖ࡜᳨⣴ࡋࡓሙྜ࡛ࡣ㸪 Ⅼ࡜᫂ࡽ࠿࡟ᑡ࡞
ࡃ㸪ࠕ⅏ᐖᩆຓἲࠖ࡜ࠕᛂᛴ௬タఫᏯࠖࡀ࣮࣮࢟࣡ࢻ࡜ࡋ࡚⧅ࡀࡗ࡚࠸࡞࠸ࡇ࡜ࡀゝ࠼ࡿ㸬ḟ࡟ࠕ㜵⅏㞟ᅋ⛣㌿ಁ㐍஦ᴗࠖࡢ஦ᴗྡ⛠᳨࡛⣴ࡋࡓ⤖ᯝ㸪ࠕ㞟ᅋ⛣㌿ࠖࡢ᳨⣴⤖ᯝࡼࡾࡔ࠸
ࡪᑡ࡞࠸⤖ᯝ࡜࡞ࡗࡓ㸬ᒾᡭ࢔࣮࢝࢖ࣈࡢሙྜ㸪࣮࣮࢟࣡ࢻࡀṇ☜࡞஦ᴗྡ⛠࡛ࡣ࡞ࡃࠕ㞟ᅋ⛣㌿ಁ㐍஦ᴗࠖ࡜ࡋ࡚࣮࣮࢟࣡ࢻ௜ࡅࡉࢀࡓࡇ࡜ࡸ⊂⮬ࡢศ㢮ྡ⛠࡟ࠕ㞟ᅋ⛣㌿࣭༊⏬ᩚ⌮ࠖࢆタࡅ࡚࠸ࡓࡓࡵ㸪ṇᘧ࡞஦ᴗྡ⛠᳨࡛⣴࡛ࡁ࡞࠿ࡗࡓࡇ࡜ࡀ⪃࠼ࡽࢀࡿ㸬ㄒᙡ࡟ࡣ㛵ಀࡋ࡞࠸ࡀ㸪㜵⅏㞟ᅋ⛣㌿ಁ㐍஦ᴗ࡟ࡼࡿᏯᆅᩚഛࡣ㸪ᐇែ࡜ࡋ࡚ᐑᇛ┴ࡀ㞟ᅋ⛣㌿ᆅ༊࡜ᡞᩘࡀ᭱
ࡶከࡃ㸪⥆࠸࡚ᒾᡭ┴࡜࡞ࡗ࡚࠸ࡿࡀ㸪᳨⣴⤖ᯝ࡛ࡣᐑᇛ┴ࡼࡾᒾᡭ┴ࡢ᪉ࡀከ࠸⤖ᯝ࡜࡞ࡗ

139

ࡓ㸬ᐑᇛ┴ࡀᑡ࡞࠸⌮⏤ࡣ㸪࠸ࡃࡘ࠿⪃࠼ࡽࢀࡿࡀ㸪ᵓ⠏᫬ᮇࡀᒾᡭ┴࡜ẚ㍑ࡋ࡚  ᖺ௨ୖ๓࡟సࡽࢀࡇ࡜ࡸከࡃࡢᆅ༊ࡀ㐀ᡂ୰ࡔࡗࡓࡇ࡜㸪㠀බ㛤グ㘓ࡶᩘከࡃᏑᅾࡍࡿࡇ࡜࡞࡝ࡶ㛵ಀࡍࡿ࡜ᛮࢃࢀࡿ㸬ࠕᣦᐃ⥭ᛴ㑊㞴ሙᡤࠖ࡜ࠕᣦᐃ㑊㞴ᡤࠖ࡟ࡘ࠸࡚ࡣ㸪ࡍ࡭࡚ࡢ࢔࣮࢝࢖ࣈ࡛ᑡ࡞࠸᳨⣴⤖ᯝ࡜࡞ࡗࡓ㸬ࡓࡔࡋ㸪࢔࣮࢝࢖ࣈࡢ㈨ᩱ୰࡟ࡣᣦᐃ㑊㞴ᡤ࡜グ㍕ࡋ࡚࠸ࡿ࡟ࡶ㛵ࢃࡽࡎ㸪㑊㞴ᡤ࡜࣮࣮࢟࣡ࢻ௜ࡅࡀ࡞ࡉࢀ࡚࠸ࡿࡶࡢࡶぢࡽࢀࡿࡇ࡜࠿ࡽ㸪࣮࣮࢟࣡ࢻ௜ࡅࡢ㝿࡟ព㆑ࡉࢀ࡚࠸
࡞࠿ࡗࡓྍ⬟ᛶࡀ࠶ࡿ㸬ࡲࡓ㸪㐪࠺ㄢ㢟࡜ࡋ࡚㸪ᒾᡭ┴ࡢ୍㒊ࡢᆅᇦ࡛ࡣ㸪 ᖺᙜ᫬ࠕ㑊㞴ᡤࠖࢆࠕ㑊㞴ሙᡤࠖ࡜࠸࠺ྡ⛠࡛⏝࠸࡚࠸ࡓ⮬἞యࡶ࠶ࡗࡓ㸬⿕⅏⪅ྥࡅ࡟౪⤥ࡉࢀࡿබႠఫᏯ࡟ࡘ࠸࡚ࡣ㸪ࠕ⅏ᐖබႠఫᏯࠖࡸࠕ᚟⯆බႠఫᏯࠖ㸪ࠕ⅏ᐖ᚟⯆ఫᏯࠖ㸪ࠕ㟈⅏᚟⯆ఫᏯࠖ࡞࡝㸪⮬἞య࡟ࡼࡗ࡚␗࡞ࡿྡ⛠ࢆ⏝࠸ࡽࢀ࡚࠾ࡾ㸪⤫୍ࡋ᳨࡚⣴࡛ࡁ࡞࠸ㄢ㢟ࡶ࠶ࡗࡓ㸬⾲  㟈⅏ࢹࢪࢱࣝ࢔࣮࢝࢖ࣈ࡛㜵⅏㛵㐃⏝ㄒࢆ᳨⣴ࡋࡓ⤖ᯝ㸦Ⅼᩘ㸧⏝ㄒ⅏ᐖᑐ⟇ᇶᮏἲ
⅏ᐖᩆຓἲ
⿕⅏⪅⏕ά෌ᘓᨭ᥼ἲ
ཎᏊຊ⅏ᐖᑐ⟇≉ูᥐ⨨ἲ⿕⅏ᕷ⾤ᆅ᚟⯆≉ูᥐ⨨ἲᮾ᪥ᮏ኱㟈⅏᚟⯆ᇶᮏἲᮾ᪥ᮏ኱㟈⅏᚟⯆≉ู༊ᇦἲ ᚟⯆஺௜㔠⚟ᓥ᚟⯆෌⏕≉ูᥐ⨨ἲ㜵⅏㞟ᅋ⛣㌿ಁ㐍஦ᴗ㞟ᅋ⛣㌿
ὠἼ᚟⯆ᣐⅬᩚഛ஦ᴗ
㑊㞴ᡤᣦᐃ㑊㞴ᡤ
㑊㞴ሙᡤᣦᐃ⥭ᛴ㑊㞴ሙᡤᛂᛴ௬タఫᏯ
බႠఫᏯ⅏ᐖබႠఫᏯ
᚟⯆බႠఫᏯ
⅏ᐖ᚟⯆ఫᏯ
㟈⅏᚟⯆ఫᏯ

ࡦ࡞ࡂࡃ
















ᐑᇛ























ᒾᡭ


















4㸬
㸬 㟈⅏ࢹࢪࢱࣝ࢔࣮࢝࢖ࣈࡢㄒᙡ࡟㛵ࡍࡿㄢ㢟ゎỴ᪉ἲ࡟ࡘ࠸࡚ ❶࡛♧ࡋࡓ㏻ࡾ㸪ᖺ௦࡟ࡼࡗ࡚㜵⅏㛵㐃⏝ㄒࡀ␗࡞ࡿࡇ࡜㸪㟈⅏グ㘓ࡢ࣓ࢱࢹ࣮ࢱࡢ௜୚
᝟ሗࡀ୙㊊ࡋ࡚࠸ࡿࡇ࡜࡞࡝ࡢㄢ㢟ࡀ᫂ࡽ࠿࡟࡞ࡗࡓ㸬ࡇࢀࡽࡢゎỴ᪉ἲ࡜ࡋ࡚㸪㟈⅏グ㘓ࡢ࣓ࢱࢹ࣮ࢱࡢぢ┤ࡋࡀ⪃࠼ࡽࢀࡿࡀ㸪⭾኱࡞㟈⅏グ㘓ࢆࡍ࡭࡚෌ᩚഛࡍࡿࡇ࡜ࡣᅔ㞴࡛࠶ࡿ㸬ࡑࡢࡓࡵ㸪ࢩࢯ࣮ࣛࢫ㎡᭩㸦ྠ⩏ㄒ࣭㢮ㄒ㎡᭩㸧ࡢసᡂࡀᚲせ࡜⪃࠼ࡽࢀࡿ㸬ࡓࡔࡋ㸪㑊㞴ᡤ㸪

140㑊㞴ሙᡤ࡛♧ࡋࡓ㏻ࡾ㸪㑊㞴ᡤࢆ㑊㞴ሙᡤࡢྡ⛠࡛౑⏝ࡉࢀ࡚࠸ࡓ࡞࡝ࡣ㸪ࢩࢯ࣮ࣛࢫ㎡᭩࡛ࡣゎỴࡍࡿࡇ࡜ࡀ࡛ࡁ࡞࠸㸬ࡲࡓ㸪⅏ᐖᩆຓἲࡢෆᐜ࡟ྵࡲࢀࡿࡶࡢ࡜ࡋ࡚㸪ᛂᛴ௬タఫᏯࡸ
⅕ࡁฟࡋ➼ࡀ࠶ࡿࡀ㸪⅏ᐖ㛵ಀἲ௧࡟࡝ࡇࡲ࡛㟈⅏グ㘓ࢆ⣣௜ࡅࡿ࠿ࡶㄢ㢟ࡀ࠶ࡿ࡜ゝ࠼ࡿ㸬⅏ᐖᑐ⟇ᇶᮏἲࡣ㸪ண㜵㸪ᛂᛴ㸪᚟ᪧ࣭᚟⯆ࡢ⅏ᐖ㛵ಀἲ௧ࢆࡍ࡭࡚⤫ᣓࡍࡿἲᚊ࡛࠶ࡾ㸪⮬἞యࡢ㟈⅏グ㘓ࡢ࡯࡜ࢇ࡝࡟⅏ᐖᑐ⟇ᇶᮏἲࢆ࣮࣮࢟࣡ࢻ௜ࡅࡋ࡞࠸࡜࠸ࡅ࡞ࡃ࡞ࡿ㸬⅏ᐖ㛵ಀἲ௧࡜㟈⅏グ㘓ࡢྲྀࡾᢅ࠸࡟ࡘ࠸࡚ࡶ⪃࠼ࡿᚲせᛶࡀ࠶ࡿ㸬
5㸬
㸬 ࡲ࡜ࡵ
ᮏ✏࡛ࡣ㸪ᮾ᪥ᮏ኱㟈⅏ࢹࢪࢱࣝ࢔࣮࢝࢖ࣈࡢ⌧≧࡜ㄢ㢟㸪᳨⣴࡟ᚲせ࡞ㄒᙡ࡟㛵ࡍࡿㄢ㢟࡟ࡘ࠸࡚ゎㄝࡋࡓ㸬ㄒᙡ࡟ࡘ࠸࡚ࡢゎỴ⟇࡜ࡋ࡚ࢩࢯ࣮ࣛࢫ㎡᭩ࡢసᡂࡀᛴົ࡛࠶ࡿࡀ㸪ㄢ㢟ࡶከࡃ࠶ࡿࡇ࡜ࡀࢃ࠿ࡗࡓ㸬௒ᚋࡣ㸪ࡉࡽ࡟⮬↛⅏ᐖࢹࢪࢱࣝ࢔࣮࢝࢖ࣈ࡛⏝࠸ࡽࢀ࡚࠸ࡿㄒ
ᙡࡢศᯒࢆ㐍ࡵࡿ࡜࡜ࡶ࡟㸪ࢩࢯ࣮ࣛࢫ㎡᭩ࡢసᡂࢆ⾜࠺ணᐃ࡛࠶ࡿ㸬ㅰ㎡
 ᮏ◊✲ࡣ㸪⛉◊㈝㸦+㸧ࡢຓᡂࢆཷࡅࡓࡶࡢ࡛࠶ࡿࠋཧ⪃ᩥ⊩㸧 ᅜ❧ᅜ఍ᅗ᭩㤋㸸ᮾ᪥ᮏ኱㟈⅏࢔࣮࢝࢖ࣈࠕឡ⛠㸸ࡦ࡞ࡂࡃࠖ㸪KWWSVNQQGOJRMS㸦ཧ↷㸸 ᖺ  ᭶  ᪥㸧㸧 ᐑᇛ┴ᅗ᭩㤋㸸ᮾ᪥ᮏ኱㟈⅏࢔࣮࢝࢖ࣈᐑᇛ㸪KWWSVNLRNXOLEUDU\SUHIPL\DJLMS㸦ཧ↷㸸 ᖺ  ᭶  ᪥㸧㸧 ᒾᡭ┴㸸ࠕ࠸ࢃ࡚㟈⅏ὠἼ࢔࣮࢝࢖ࣈࠥᕼᮃࠥࠖ㸪KWWSLZDWHDUFKLYHSUHILZDWHMS㸦ཧ↷㸸 ᖺ  ᭶  ᪥㸧日本自然災害学会東北支部役員（令和 3 年度）
支

部

長

三

浦

幹

事

長

岡

田

知

己（東北大学・理）

評

議

員

片

岡

俊

一（弘前大学・理工）

渡

辺

一

也（秋田大学・理工）

村

山

良

之（山形大学・教育）

山

本

英

和（岩手大学・理工）則男（東北工業大学・工）紀明（日本大学・工）

堀

会計監査員

仙

頭

佐

藤

飯

藤

哲（東北大学・理）健（東北大学・災害研）
將之（仙台高等専門学校）

令和４年３月１日

発行

東北地域災害科学研究 第 58 巻
（令和３年度）編

集者

自然災害研究協議会東北地区部会
部

会

長

三

浦

哲

日本自然災害学会東北支部
支
発

行

者

部

長

三

浦

哲

東北大学災害科学国際研究所
東北地区自然災害資料センター
センター長

今

村

文

彦

〒 980-8572 仙台市青葉区荒巻字青葉 468-1
TEL 022（752）2099
印

刷

所

有限会社

明

〒 983-0842
TEL

倫

社

仙台市宮城野区五輪二丁目９－５022（295）8211