iVOD / 164062

Field Value
IVOD_ID 164062
IVOD_URL https://ivod.ly.gov.tw/Play/Clip/1M/164062
日期 2025-10-13
會議資料.會議代碼 委員會-11-4-15-3
會議資料.會議代碼:str 第11屆第4會期內政委員會第3次全體委員會議
會議資料.屆 11
會議資料.會期 4
會議資料.會次 3
會議資料.種類 委員會
會議資料.委員會代碼[0] 15
會議資料.委員會代碼:str[0] 內政委員會
會議資料.標題 第11屆第4會期內政委員會第3次全體委員會議
影片種類 Clip
開始時間 2025-10-13T12:25:42+08:00
結束時間 2025-10-13T12:37:22+08:00
影片長度 00:11:40
支援功能[0] ai-transcript
video_url https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/5d6d14916e595edcfab02d23b8c36196179f4a20aeac8eafeaa2f1cd0be3abd6b99eda9eaf2fc55b5ea18f28b6918d91.mp4/playlist.m3u8
委員名稱 林德福
委員發言時間 12:25:42 - 12:37:22
會議時間 2025-10-13T09:00:00+08:00
會議名稱 立法院第11屆第4會期內政委員會第3次全體委員會議(事由:邀請內政部部長、原住民族委員會主任委員、農業部部長率所屬單位就「堰塞湖監測、災害預警通報、疏散機制及災後復原重建」進行專題報告,並備質詢,另請經濟部、環境部、衛生福利部、行政院公共工程委員會派員列席備詢。)
transcript.pyannote[0].speaker SPEAKER_01
transcript.pyannote[0].start 0.25034375
transcript.pyannote[0].end 1.00971875
transcript.pyannote[1].speaker SPEAKER_00
transcript.pyannote[1].start 0.46971875
transcript.pyannote[1].end 1.38096875
transcript.pyannote[2].speaker SPEAKER_00
transcript.pyannote[2].start 1.87034375
transcript.pyannote[2].end 2.83221875
transcript.pyannote[3].speaker SPEAKER_00
transcript.pyannote[3].start 3.15284375
transcript.pyannote[3].end 6.71346875
transcript.pyannote[4].speaker SPEAKER_00
transcript.pyannote[4].start 7.67534375
transcript.pyannote[4].end 8.46846875
transcript.pyannote[5].speaker SPEAKER_01
transcript.pyannote[5].start 8.46846875
transcript.pyannote[5].end 9.21096875
transcript.pyannote[6].speaker SPEAKER_00
transcript.pyannote[6].start 8.50221875
transcript.pyannote[6].end 8.53596875
transcript.pyannote[7].speaker SPEAKER_00
transcript.pyannote[7].start 8.58659375
transcript.pyannote[7].end 10.03784375
transcript.pyannote[8].speaker SPEAKER_00
transcript.pyannote[8].start 10.79721875
transcript.pyannote[8].end 12.26534375
transcript.pyannote[9].speaker SPEAKER_01
transcript.pyannote[9].start 13.26096875
transcript.pyannote[9].end 14.66159375
transcript.pyannote[10].speaker SPEAKER_00
transcript.pyannote[10].start 15.21846875
transcript.pyannote[10].end 15.55596875
transcript.pyannote[11].speaker SPEAKER_00
transcript.pyannote[11].start 18.27284375
transcript.pyannote[11].end 20.21346875
transcript.pyannote[12].speaker SPEAKER_00
transcript.pyannote[12].start 21.69846875
transcript.pyannote[12].end 22.13721875
transcript.pyannote[13].speaker SPEAKER_00
transcript.pyannote[13].start 23.11596875
transcript.pyannote[13].end 24.93846875
transcript.pyannote[14].speaker SPEAKER_00
transcript.pyannote[14].start 25.44471875
transcript.pyannote[14].end 25.93409375
transcript.pyannote[15].speaker SPEAKER_00
transcript.pyannote[15].start 26.45721875
transcript.pyannote[15].end 28.85346875
transcript.pyannote[16].speaker SPEAKER_00
transcript.pyannote[16].start 28.97159375
transcript.pyannote[16].end 31.63784375
transcript.pyannote[17].speaker SPEAKER_00
transcript.pyannote[17].start 32.09346875
transcript.pyannote[17].end 35.21534375
transcript.pyannote[18].speaker SPEAKER_00
transcript.pyannote[18].start 35.85659375
transcript.pyannote[18].end 38.18534375
transcript.pyannote[19].speaker SPEAKER_00
transcript.pyannote[19].start 39.13034375
transcript.pyannote[19].end 39.88971875
transcript.pyannote[20].speaker SPEAKER_00
transcript.pyannote[20].start 40.22721875
transcript.pyannote[20].end 49.45784375
transcript.pyannote[21].speaker SPEAKER_00
transcript.pyannote[21].start 49.98096875
transcript.pyannote[21].end 61.59096875
transcript.pyannote[22].speaker SPEAKER_00
transcript.pyannote[22].start 62.09721875
transcript.pyannote[22].end 65.11784375
transcript.pyannote[23].speaker SPEAKER_00
transcript.pyannote[23].start 65.23596875
transcript.pyannote[23].end 68.94846875
transcript.pyannote[24].speaker SPEAKER_00
transcript.pyannote[24].start 69.26909375
transcript.pyannote[24].end 69.80909375
transcript.pyannote[25].speaker SPEAKER_00
transcript.pyannote[25].start 71.20971875
transcript.pyannote[25].end 75.66471875
transcript.pyannote[26].speaker SPEAKER_00
transcript.pyannote[26].start 75.71534375
transcript.pyannote[26].end 77.72346875
transcript.pyannote[27].speaker SPEAKER_00
transcript.pyannote[27].start 77.90909375
transcript.pyannote[27].end 79.00596875
transcript.pyannote[28].speaker SPEAKER_00
transcript.pyannote[28].start 79.44471875
transcript.pyannote[28].end 83.74784375
transcript.pyannote[29].speaker SPEAKER_00
transcript.pyannote[29].start 84.10221875
transcript.pyannote[29].end 86.02596875
transcript.pyannote[30].speaker SPEAKER_00
transcript.pyannote[30].start 86.58284375
transcript.pyannote[30].end 89.21534375
transcript.pyannote[31].speaker SPEAKER_00
transcript.pyannote[31].start 89.67096875
transcript.pyannote[31].end 91.24034375
transcript.pyannote[32].speaker SPEAKER_00
transcript.pyannote[32].start 91.72971875
transcript.pyannote[32].end 93.33284375
transcript.pyannote[33].speaker SPEAKER_03
transcript.pyannote[33].start 98.49659375
transcript.pyannote[33].end 108.23346875
transcript.pyannote[34].speaker SPEAKER_03
transcript.pyannote[34].start 108.25034375
transcript.pyannote[34].end 109.46534375
transcript.pyannote[35].speaker SPEAKER_00
transcript.pyannote[35].start 108.30096875
transcript.pyannote[35].end 113.56596875
transcript.pyannote[36].speaker SPEAKER_03
transcript.pyannote[36].start 113.85284375
transcript.pyannote[36].end 123.10034375
transcript.pyannote[37].speaker SPEAKER_03
transcript.pyannote[37].start 123.21846875
transcript.pyannote[37].end 125.53034375
transcript.pyannote[38].speaker SPEAKER_03
transcript.pyannote[38].start 125.64846875
transcript.pyannote[38].end 128.33159375
transcript.pyannote[39].speaker SPEAKER_03
transcript.pyannote[39].start 128.51721875
transcript.pyannote[39].end 144.41346875
transcript.pyannote[40].speaker SPEAKER_00
transcript.pyannote[40].start 144.83534375
transcript.pyannote[40].end 145.67909375
transcript.pyannote[41].speaker SPEAKER_00
transcript.pyannote[41].start 145.98284375
transcript.pyannote[41].end 147.51846875
transcript.pyannote[42].speaker SPEAKER_00
transcript.pyannote[42].start 147.67034375
transcript.pyannote[42].end 149.72909375
transcript.pyannote[43].speaker SPEAKER_00
transcript.pyannote[43].start 150.38721875
transcript.pyannote[43].end 152.66534375
transcript.pyannote[44].speaker SPEAKER_00
transcript.pyannote[44].start 153.18846875
transcript.pyannote[44].end 154.97721875
transcript.pyannote[45].speaker SPEAKER_00
transcript.pyannote[45].start 155.55096875
transcript.pyannote[45].end 157.55909375
transcript.pyannote[46].speaker SPEAKER_00
transcript.pyannote[46].start 157.57596875
transcript.pyannote[46].end 163.68471875
transcript.pyannote[47].speaker SPEAKER_00
transcript.pyannote[47].start 164.20784375
transcript.pyannote[47].end 167.29596875
transcript.pyannote[48].speaker SPEAKER_00
transcript.pyannote[48].start 168.24096875
transcript.pyannote[48].end 169.97909375
transcript.pyannote[49].speaker SPEAKER_00
transcript.pyannote[49].start 170.31659375
transcript.pyannote[49].end 171.46409375
transcript.pyannote[50].speaker SPEAKER_00
transcript.pyannote[50].start 171.80159375
transcript.pyannote[50].end 172.24034375
transcript.pyannote[51].speaker SPEAKER_00
transcript.pyannote[51].start 172.35846875
transcript.pyannote[51].end 174.73784375
transcript.pyannote[52].speaker SPEAKER_00
transcript.pyannote[52].start 174.95721875
transcript.pyannote[52].end 184.08659375
transcript.pyannote[53].speaker SPEAKER_00
transcript.pyannote[53].start 184.40721875
transcript.pyannote[53].end 185.57159375
transcript.pyannote[54].speaker SPEAKER_00
transcript.pyannote[54].start 186.16221875
transcript.pyannote[54].end 187.44471875
transcript.pyannote[55].speaker SPEAKER_00
transcript.pyannote[55].start 187.81596875
transcript.pyannote[55].end 191.32596875
transcript.pyannote[56].speaker SPEAKER_00
transcript.pyannote[56].start 191.47784375
transcript.pyannote[56].end 193.26659375
transcript.pyannote[57].speaker SPEAKER_00
transcript.pyannote[57].start 193.70534375
transcript.pyannote[57].end 195.32534375
transcript.pyannote[58].speaker SPEAKER_03
transcript.pyannote[58].start 193.90784375
transcript.pyannote[58].end 194.07659375
transcript.pyannote[59].speaker SPEAKER_03
transcript.pyannote[59].start 195.32534375
transcript.pyannote[59].end 199.56096875
transcript.pyannote[60].speaker SPEAKER_03
transcript.pyannote[60].start 199.99971875
transcript.pyannote[60].end 203.49284375
transcript.pyannote[61].speaker SPEAKER_00
transcript.pyannote[61].start 203.49284375
transcript.pyannote[61].end 205.24784375
transcript.pyannote[62].speaker SPEAKER_00
transcript.pyannote[62].start 205.48409375
transcript.pyannote[62].end 206.17596875
transcript.pyannote[63].speaker SPEAKER_03
transcript.pyannote[63].start 205.53471875
transcript.pyannote[63].end 223.62471875
transcript.pyannote[64].speaker SPEAKER_00
transcript.pyannote[64].start 221.16096875
transcript.pyannote[64].end 226.93221875
transcript.pyannote[65].speaker SPEAKER_03
transcript.pyannote[65].start 227.01659375
transcript.pyannote[65].end 233.09159375
transcript.pyannote[66].speaker SPEAKER_03
transcript.pyannote[66].start 233.59784375
transcript.pyannote[66].end 235.20096875
transcript.pyannote[67].speaker SPEAKER_00
transcript.pyannote[67].start 235.15034375
transcript.pyannote[67].end 250.82721875
transcript.pyannote[68].speaker SPEAKER_03
transcript.pyannote[68].start 235.21784375
transcript.pyannote[68].end 235.23471875
transcript.pyannote[69].speaker SPEAKER_00
transcript.pyannote[69].start 251.08034375
transcript.pyannote[69].end 267.11159375
transcript.pyannote[70].speaker SPEAKER_00
transcript.pyannote[70].start 267.43221875
transcript.pyannote[70].end 269.08596875
transcript.pyannote[71].speaker SPEAKER_00
transcript.pyannote[71].start 269.38971875
transcript.pyannote[71].end 269.82846875
transcript.pyannote[72].speaker SPEAKER_00
transcript.pyannote[72].start 269.99721875
transcript.pyannote[72].end 274.53659375
transcript.pyannote[73].speaker SPEAKER_00
transcript.pyannote[73].start 274.85721875
transcript.pyannote[73].end 281.67471875
transcript.pyannote[74].speaker SPEAKER_00
transcript.pyannote[74].start 281.75909375
transcript.pyannote[74].end 282.65346875
transcript.pyannote[75].speaker SPEAKER_02
transcript.pyannote[75].start 283.39596875
transcript.pyannote[75].end 294.73596875
transcript.pyannote[76].speaker SPEAKER_02
transcript.pyannote[76].start 295.51221875
transcript.pyannote[76].end 297.63846875
transcript.pyannote[77].speaker SPEAKER_00
transcript.pyannote[77].start 295.54596875
transcript.pyannote[77].end 295.90034375
transcript.pyannote[78].speaker SPEAKER_00
transcript.pyannote[78].start 297.58784375
transcript.pyannote[78].end 305.33346875
transcript.pyannote[79].speaker SPEAKER_00
transcript.pyannote[79].start 305.48534375
transcript.pyannote[79].end 306.85221875
transcript.pyannote[80].speaker SPEAKER_00
transcript.pyannote[80].start 307.39221875
transcript.pyannote[80].end 310.15971875
transcript.pyannote[81].speaker SPEAKER_00
transcript.pyannote[81].start 310.54784375
transcript.pyannote[81].end 318.04034375
transcript.pyannote[82].speaker SPEAKER_00
transcript.pyannote[82].start 318.32721875
transcript.pyannote[82].end 319.37346875
transcript.pyannote[83].speaker SPEAKER_00
transcript.pyannote[83].start 319.96409375
transcript.pyannote[83].end 321.16221875
transcript.pyannote[84].speaker SPEAKER_02
transcript.pyannote[84].start 320.28471875
transcript.pyannote[84].end 320.87534375
transcript.pyannote[85].speaker SPEAKER_02
transcript.pyannote[85].start 321.02721875
transcript.pyannote[85].end 334.98284375
transcript.pyannote[86].speaker SPEAKER_00
transcript.pyannote[86].start 334.69596875
transcript.pyannote[86].end 334.71284375
transcript.pyannote[87].speaker SPEAKER_01
transcript.pyannote[87].start 334.71284375
transcript.pyannote[87].end 335.52284375
transcript.pyannote[88].speaker SPEAKER_00
transcript.pyannote[88].start 334.98284375
transcript.pyannote[88].end 335.01659375
transcript.pyannote[89].speaker SPEAKER_01
transcript.pyannote[89].start 337.37909375
transcript.pyannote[89].end 342.37409375
transcript.pyannote[90].speaker SPEAKER_00
transcript.pyannote[90].start 341.81721875
transcript.pyannote[90].end 353.42721875
transcript.pyannote[91].speaker SPEAKER_00
transcript.pyannote[91].start 353.86596875
transcript.pyannote[91].end 357.15659375
transcript.pyannote[92].speaker SPEAKER_03
transcript.pyannote[92].start 357.15659375
transcript.pyannote[92].end 357.44346875
transcript.pyannote[93].speaker SPEAKER_00
transcript.pyannote[93].start 357.44346875
transcript.pyannote[93].end 357.46034375
transcript.pyannote[94].speaker SPEAKER_00
transcript.pyannote[94].start 357.76409375
transcript.pyannote[94].end 366.97784375
transcript.pyannote[95].speaker SPEAKER_00
transcript.pyannote[95].start 367.36596875
transcript.pyannote[95].end 371.63534375
transcript.pyannote[96].speaker SPEAKER_00
transcript.pyannote[96].start 372.17534375
transcript.pyannote[96].end 395.24346875
transcript.pyannote[97].speaker SPEAKER_01
transcript.pyannote[97].start 373.18784375
transcript.pyannote[97].end 373.23846875
transcript.pyannote[98].speaker SPEAKER_00
transcript.pyannote[98].start 395.51346875
transcript.pyannote[98].end 397.30221875
transcript.pyannote[99].speaker SPEAKER_00
transcript.pyannote[99].start 397.45409375
transcript.pyannote[99].end 399.04034375
transcript.pyannote[100].speaker SPEAKER_00
transcript.pyannote[100].start 399.36096875
transcript.pyannote[100].end 399.68159375
transcript.pyannote[101].speaker SPEAKER_00
transcript.pyannote[101].start 399.86721875
transcript.pyannote[101].end 401.21721875
transcript.pyannote[102].speaker SPEAKER_00
transcript.pyannote[102].start 401.62221875
transcript.pyannote[102].end 401.95971875
transcript.pyannote[103].speaker SPEAKER_00
transcript.pyannote[103].start 402.44909375
transcript.pyannote[103].end 403.07346875
transcript.pyannote[104].speaker SPEAKER_00
transcript.pyannote[104].start 403.57971875
transcript.pyannote[104].end 404.57534375
transcript.pyannote[105].speaker SPEAKER_00
transcript.pyannote[105].start 405.04784375
transcript.pyannote[105].end 406.27971875
transcript.pyannote[106].speaker SPEAKER_00
transcript.pyannote[106].start 407.03909375
transcript.pyannote[106].end 408.08534375
transcript.pyannote[107].speaker SPEAKER_00
transcript.pyannote[107].start 408.38909375
transcript.pyannote[107].end 414.02534375
transcript.pyannote[108].speaker SPEAKER_00
transcript.pyannote[108].start 414.27846875
transcript.pyannote[108].end 416.80971875
transcript.pyannote[109].speaker SPEAKER_00
transcript.pyannote[109].start 416.84346875
transcript.pyannote[109].end 423.62721875
transcript.pyannote[110].speaker SPEAKER_00
transcript.pyannote[110].start 424.55534375
transcript.pyannote[110].end 431.18721875
transcript.pyannote[111].speaker SPEAKER_00
transcript.pyannote[111].start 431.76096875
transcript.pyannote[111].end 435.59159375
transcript.pyannote[112].speaker SPEAKER_00
transcript.pyannote[112].start 436.48596875
transcript.pyannote[112].end 437.21159375
transcript.pyannote[113].speaker SPEAKER_00
transcript.pyannote[113].start 437.81909375
transcript.pyannote[113].end 442.15596875
transcript.pyannote[114].speaker SPEAKER_00
transcript.pyannote[114].start 442.61159375
transcript.pyannote[114].end 443.21909375
transcript.pyannote[115].speaker SPEAKER_00
transcript.pyannote[115].start 443.57346875
transcript.pyannote[115].end 448.02846875
transcript.pyannote[116].speaker SPEAKER_00
transcript.pyannote[116].start 451.38659375
transcript.pyannote[116].end 452.77034375
transcript.pyannote[117].speaker SPEAKER_00
transcript.pyannote[117].start 453.10784375
transcript.pyannote[117].end 455.58846875
transcript.pyannote[118].speaker SPEAKER_02
transcript.pyannote[118].start 454.94721875
transcript.pyannote[118].end 466.13534375
transcript.pyannote[119].speaker SPEAKER_02
transcript.pyannote[119].start 466.50659375
transcript.pyannote[119].end 504.47534375
transcript.pyannote[120].speaker SPEAKER_02
transcript.pyannote[120].start 504.62721875
transcript.pyannote[120].end 513.01409375
transcript.pyannote[121].speaker SPEAKER_00
transcript.pyannote[121].start 513.01409375
transcript.pyannote[121].end 516.01784375
transcript.pyannote[122].speaker SPEAKER_00
transcript.pyannote[122].start 516.40596875
transcript.pyannote[122].end 517.84034375
transcript.pyannote[123].speaker SPEAKER_00
transcript.pyannote[123].start 517.89096875
transcript.pyannote[123].end 519.51096875
transcript.pyannote[124].speaker SPEAKER_00
transcript.pyannote[124].start 520.15221875
transcript.pyannote[124].end 525.43409375
transcript.pyannote[125].speaker SPEAKER_00
transcript.pyannote[125].start 525.90659375
transcript.pyannote[125].end 528.04971875
transcript.pyannote[126].speaker SPEAKER_00
transcript.pyannote[126].start 528.42096875
transcript.pyannote[126].end 528.85971875
transcript.pyannote[127].speaker SPEAKER_00
transcript.pyannote[127].start 529.04534375
transcript.pyannote[127].end 540.77346875
transcript.pyannote[128].speaker SPEAKER_00
transcript.pyannote[128].start 541.21221875
transcript.pyannote[128].end 544.31721875
transcript.pyannote[129].speaker SPEAKER_00
transcript.pyannote[129].start 544.67159375
transcript.pyannote[129].end 548.40096875
transcript.pyannote[130].speaker SPEAKER_00
transcript.pyannote[130].start 548.78909375
transcript.pyannote[130].end 551.03346875
transcript.pyannote[131].speaker SPEAKER_00
transcript.pyannote[131].start 551.21909375
transcript.pyannote[131].end 555.60659375
transcript.pyannote[132].speaker SPEAKER_00
transcript.pyannote[132].start 555.77534375
transcript.pyannote[132].end 575.02971875
transcript.pyannote[133].speaker SPEAKER_00
transcript.pyannote[133].start 575.18159375
transcript.pyannote[133].end 577.57784375
transcript.pyannote[134].speaker SPEAKER_00
transcript.pyannote[134].start 577.94909375
transcript.pyannote[134].end 579.82221875
transcript.pyannote[135].speaker SPEAKER_03
transcript.pyannote[135].start 580.98659375
transcript.pyannote[135].end 586.15034375
transcript.pyannote[136].speaker SPEAKER_00
transcript.pyannote[136].start 585.99846875
transcript.pyannote[136].end 601.30409375
transcript.pyannote[137].speaker SPEAKER_00
transcript.pyannote[137].start 602.21534375
transcript.pyannote[137].end 605.80971875
transcript.pyannote[138].speaker SPEAKER_00
transcript.pyannote[138].start 606.41721875
transcript.pyannote[138].end 607.00784375
transcript.pyannote[139].speaker SPEAKER_00
transcript.pyannote[139].start 607.44659375
transcript.pyannote[139].end 617.43659375
transcript.pyannote[140].speaker SPEAKER_00
transcript.pyannote[140].start 618.43221875
transcript.pyannote[140].end 620.94659375
transcript.pyannote[141].speaker SPEAKER_00
transcript.pyannote[141].start 621.57096875
transcript.pyannote[141].end 622.02659375
transcript.pyannote[142].speaker SPEAKER_02
transcript.pyannote[142].start 622.66784375
transcript.pyannote[142].end 673.98471875
transcript.pyannote[143].speaker SPEAKER_00
transcript.pyannote[143].start 650.25846875
transcript.pyannote[143].end 652.75596875
transcript.pyannote[144].speaker SPEAKER_00
transcript.pyannote[144].start 673.37721875
transcript.pyannote[144].end 681.54471875
transcript.pyannote[145].speaker SPEAKER_00
transcript.pyannote[145].start 681.73034375
transcript.pyannote[145].end 683.02971875
transcript.pyannote[146].speaker SPEAKER_00
transcript.pyannote[146].start 683.16471875
transcript.pyannote[146].end 685.20659375
transcript.pyannote[147].speaker SPEAKER_00
transcript.pyannote[147].start 685.59471875
transcript.pyannote[147].end 690.23534375
transcript.pyannote[148].speaker SPEAKER_00
transcript.pyannote[148].start 690.53909375
transcript.pyannote[148].end 691.72034375
transcript.pyannote[149].speaker SPEAKER_00
transcript.pyannote[149].start 692.04096875
transcript.pyannote[149].end 692.80034375
transcript.pyannote[150].speaker SPEAKER_00
transcript.pyannote[150].start 693.08721875
transcript.pyannote[150].end 694.62284375
transcript.pyannote[151].speaker SPEAKER_01
transcript.pyannote[151].start 697.71096875
transcript.pyannote[151].end 701.96346875
transcript.whisperx[0].start 0.89
transcript.whisperx[0].end 14.402
transcript.whisperx[0].text 還有這個警政署啊不是那個消防署消署長委員好還有農業部啊這個杜次長請以上三位好那個部長你可以在中間
transcript.whisperx[1].start 24.017
transcript.whisperx[1].end 42.111
transcript.whisperx[1].text 上主席台啊我請問因為根據10月9號行政院災害防救辦公室災害戶員的情形報告花蓮光戶家戶家屋內清一差不多百分之百
transcript.whisperx[2].start 43.243
transcript.whisperx[2].end 51.746
transcript.whisperx[2].text 主要是道路輕於98%學校已經陸陸續續都復課然後根據過往的氣象資料2022、2023以及2024年花蓮10月累計降雨分別為878毫米296.5毫米以及572.5毫米是多雨的季節那
transcript.whisperx[3].start 71.44
transcript.whisperx[3].end 89.976
transcript.whisperx[3].text 馬太安西亞煙澀湖潰壩危機仍然沒有解除還未解除那請問在場你們三位誰可以回答如果再遇到大雨花蓮寬戶鄉累積的雨量這個達到多少毫米就會這個啟動這個撤離的機制
transcript.whisperx[4].start 98.59
transcript.whisperx[4].end 113.353
transcript.whisperx[4].text 是 謝謝報告委員 依現在的狀況我們調整了如果在24小時之內連續雨量達到200毫米的是會啟動紅色警戒那是否有預留一些足夠撤離作業的時間以利民眾能夠疏散
transcript.whisperx[5].start 113.914
transcript.whisperx[5].end 140.041
transcript.whisperx[5].text 我想這也就是為什麼我們現在最優先要在處理的因為紅色警戒有四個要件第一個是法體的部分有沒有穩定第二個是在河道的其餘部分有沒有做深溝第三個是合體有沒有加高這三項都有在做那最重要的最重要的就是現在的撤離計畫因為現在在花蓮當地其實除了當地的居民之外有很多志工有很多中央各部會在進駐在那邊協助的人員
transcript.whisperx[6].start 141.241
transcript.whisperx[6].end 167.029
transcript.whisperx[6].text 所以撤離計畫是我們現階段要盡速來完成的其實這一次整個潰壩這個潰堤這麼嚴重其實主要就是當初你們當然說有一些事前有去做一些測試上面了解那實際上引流工作都沒有做而且這個多久前
transcript.whisperx[7].start 168.288
transcript.whisperx[7].end 185.055
transcript.whisperx[7].text 我們立法院很多委員就擔心這個事務而且那時候你們就是在搞大惡霸所以說根本就沒有心在這個地方你要是當初有引流我相信不會發生這麼嚴重因為你有引流
transcript.whisperx[8].start 186.255
transcript.whisperx[8].end 203.327
transcript.whisperx[8].text 整個水下陷沒有達到那個程度它就不會造成整個淹涉湖的一個潰壩這是很嚴重的問題委員大家也提到了其實這次並不是因為第一個監測的結果當然有很多的預估的模型
transcript.whisperx[9].start 203.527
transcript.whisperx[9].end 226.041
transcript.whisperx[9].text 你們那個部長說沒有問題啊在當下當下的狀況那這次其實是因為畫家沙颱風帶來大量的雨量然後造成特別是堰塞湖區依照中央氣象署的資料會有大量的雨水所以這次下來就不是一般預估的雨量而是有大量的對啊那你平常本來這個就是你要是有引流出去就不會這麼嚴重嗎
transcript.whisperx[10].start 227.082
transcript.whisperx[10].end 244.981
transcript.whisperx[10].text 引流還是有在做提防有在做但是這次因為颱風大量雨水帶下來的狀況確實是天上帶下來的因為齁災後當然政府資源有限民間民力無窮許多民間力量的匯聚支持災民渡過難關對於投入花蓮
transcript.whisperx[11].start 245.962
transcript.whisperx[11].end 266.621
transcript.whisperx[11].text 救災的官兵包括醫護、志工我想本席也是真的非常的感謝跟敬佩然而中央災害應變中心對於花蓮整個災區的管理志工的安排調度保險在災難發生後沒有立刻來啟動導致謠言四起
transcript.whisperx[12].start 270.149
transcript.whisperx[12].end 282.481
transcript.whisperx[12].text 那破壞整個救災團隊讓人感到遺憾希望內政部未來要一併檢討讓這些救災志工有安全的保障 劉部長你的看法呢
transcript.whisperx[13].start 283.564
transcript.whisperx[13].end 306.585
transcript.whisperx[13].text 報告委員其實我們這兩天已經有跟金管會還有財政部已經針對這個志工啊做這個QR Code掃QR Code的時候就有這個平安險的一個保障已經把它列進去這兩天都列進去了其實更令人不捨的是熱心的救災民眾失去了生命挖土機超人林鴻升救災感染
transcript.whisperx[14].start 307.726
transcript.whisperx[14].end 334.762
transcript.whisperx[14].text 他應該是敗血症來身亡那本席是希望內政部積極來研究啟動入中獵池的這個程序以告慰家屬報告委員因為林鴻升先生我們當然非常不捨但是中獵池有中獵池現在的一個入室的部分那我們請衛福部那能不能列入表揚那因為志工服務法是衛福部是不是請次長跟您回應一下
transcript.whisperx[15].start 337.681
transcript.whisperx[15].end 356.678
transcript.whisperx[15].text 有關這部分我會再跟行政院這邊來申請看看我認為這個應該全國的人民都不會反對這麼熱心的一個志工發生這種狀況政府沒有拿出同理心你說叫這些來做志工的人親和一看
transcript.whisperx[16].start 358.44
transcript.whisperx[16].end 370.115
transcript.whisperx[16].text 我認為該做則做你不要說這個一定要怎麼樣規定沒有那個百分之百的規定啦對不對我們這是民意啊你去問10個有9個9都贊成
transcript.whisperx[17].start 372.23
transcript.whisperx[17].end 400.969
transcript.whisperx[17].text 好不好要好好做那個花蓮馬太安溪顏色湖潰壩造成嚴重的災情內政部前部長李鴻元指出台灣當前面臨的都是複合式的災害那已經非單一部會能夠處理呼籲政府要修改災害防救法來設置專責的單位來成立這個防災總署因為這次我看到
transcript.whisperx[18].start 402.49
transcript.whisperx[18].end 430.876
transcript.whisperx[18].text 等於是好幾個單位而且沒有統籌講實在話啦你像那個公兵他們有那麼多的機具那麼多的這個人員沒有發揮到充分來運用他們災害發生的時候能夠做的應該全力都做那是我要成立這個防災總署統一救災的權責此一概念過去在立法院其實也
transcript.whisperx[19].start 431.806
transcript.whisperx[19].end 446.831
transcript.whisperx[19].text 也有討論過啦那花蓮光復鄉災情預警應變及這個救災未來的檢討救責本席請問劉部長你以消防署的看法是不是支持這個防災總署
transcript.whisperx[20].start 451.608
transcript.whisperx[20].end 465.919
transcript.whisperx[20].text 來取代整個中央這個災害應變中心我認為要審慎評估報告委員我剛在回覆其他委員是有提到第一個我們現在消防的這個災害防救體系它是一個因災因而起的那這樣子的
transcript.whisperx[21].start 466.719
transcript.whisperx[21].end 472.763
transcript.whisperx[21].text 前面的有些預警必須要很多專業來幫忙譬如說氣象署他在發布地震或是發布颱風的部分那沒辦法由災防總署來幫忙還有譬如說艷澀湖的監測農業部在幫忙或者是說其他的大型災害或者是生物園的災害必須要衛福部來處理那如果你成立災防總署的部分的話呢他是在
transcript.whisperx[22].start 490.114
transcript.whisperx[22].end 514.973
transcript.whisperx[22].text 應變的時候能不能快速整合所有這方面的資訊然後做出判斷然後減少生命財產的損失那這一部分呢其實在歷次的災害應變從以前的這個921開始他就一直在演變當中那我們也一直在精進那這一部分呢包括中央跟地方都有精進討論的空間我想我們都不排除任何可能因為你不要像這一次一樣
transcript.whisperx[23].start 516.814
transcript.whisperx[23].end 543.986
transcript.whisperx[23].text 這多頭馬車其實外界都有這樣的看法對不對那些志工到底要去給哪一個單位來報到他們要做哪裡對不對你等於是沒有一個統籌嘛那你災害發生的時候就是第一時間最重要因為像台灣地小人籌容易受到一些極端氣候的影響那這個山坡地的災害類型
transcript.whisperx[24].start 546.359
transcript.whisperx[24].end 560.371
transcript.whisperx[24].text 這個將轉變為多元而且災害的規模將遠超過過去歷史的事件面對未來未知的災害可能本席是希望農業部要結合AI大數據的計算以大數據的分析
transcript.whisperx[25].start 561.472
transcript.whisperx[25].end 576.089
transcript.whisperx[25].text 來建立整個災害潛勢圖以疏散避難場所規劃之研究未來會如何與內政部國土署經濟部地礦中心合作以避免類似花蓮關乎這種慘劇再次發生那個次長你有什麼看法
transcript.whisperx[26].start 581.078
transcript.whisperx[26].end 606.624
transcript.whisperx[26].text 是謝謝委員指教應該就是要這樣把所有的資源統合起來一起來就防災救災的事剛剛其實部長講的我意思就是說你要是這個防災總署就是要統籌嘛你災難發生的時候你沒有統籌各司其職每一個單位想法看法都不一樣然後變成多頭馬車所以說變成這種狀況全國人民都看在眼裡啊對不對
transcript.whisperx[27].start 608.144
transcript.whisperx[27].end 621.736
transcript.whisperx[27].text 那其實這個應該本來政府我是希望說那個部長你提出這些看法意見你給立法院一份資料每個委員都都一份資料認為未來應該要怎麼做游部長
transcript.whisperx[28].start 623.091
transcript.whisperx[28].end 649.071
transcript.whisperx[28].text 報告委員我想我不是天才啦但是我會把各方的意見把它收整起來那提供給那個我們的立委來參考那包括如果有修法精進的方案的話我們也必須要研議因為它確實牽涉到不只是各部會恐怕公立公私立協商因為很多人都提到這次的志工的加入以前志工的部分大致上都沒有像這次這麼多人的狀況之下比較不容易處理
transcript.whisperx[29].start 652.173
transcript.whisperx[29].end 674.545
transcript.whisperx[29].text 然後再來就是中央跟地方上面的分工是不是需要再明確那我覺得比較重要就是說我們還是要在各種不同的場合裡面繼續提供給大家危機意識是非常重要你如果沒有準備的話他的危機沒有危機意識的話那當然造成了人命傷亡損失就是比較不是我們能夠預估的範圍之內我希望好好的檢討啦
transcript.whisperx[30].start 675.825
transcript.whisperx[30].end 694.414
transcript.whisperx[30].text 針對未來不要讓災害像這一次變成多頭馬車那其實這些志工真的他們很有愛心那站在政府的角度你應該就是好好的怎麼來檢討以後該怎麼做以最好的方式來做是人民期待的啦謝謝好謝謝林德福委員那我們現在來出