基于ArcGIS的水利大數(shù)據(jù)及應(yīng)用課件

基于ArcGIS的水利大數(shù)據(jù)及應(yīng)用基于ArcGIS的水利大數(shù)據(jù)及應(yīng)用1團(tuán)隊(duì)簡(jiǎn)介水利大數(shù)據(jù)及其面臨的挑戰(zhàn)基于水利大數(shù)據(jù)的多災(zāi)害信息集成與風(fēng)險(xiǎn)預(yù)警案例主要內(nèi)容123團(tuán)隊(duì)簡(jiǎn)介水利大數(shù)據(jù)及其面臨的挑戰(zhàn)基于水利大數(shù)據(jù)的多災(zāi)害信息集2二、水利大數(shù)據(jù)及其面臨的挑戰(zhàn)二、水利大數(shù)據(jù)及其面臨的挑戰(zhàn)3水利工作關(guān)系到國(guó)計(jì)民生，尤其是我國(guó)水資源分布存在嚴(yán)重的時(shí)空分布不均特性，旱災(zāi)洪澇易發(fā)多發(fā)。水利行業(yè)在經(jīng)濟(jì)、生態(tài)、社會(huì)等方面都扮演著重要角色，對(duì)水利大數(shù)據(jù)的研究具有重要的現(xiàn)實(shí)意義和應(yīng)用價(jià)值。水利大數(shù)據(jù)是在大數(shù)據(jù)的理論指導(dǎo)及技術(shù)支撐下的水利科學(xué)和工程的重要實(shí)踐。水利工作及水利大數(shù)據(jù)的重要性水利工作關(guān)系到國(guó)計(jì)民生，尤其是我國(guó)水資源分布存在嚴(yán)重的時(shí)空4水利大數(shù)據(jù)水利大數(shù)據(jù)是指產(chǎn)生于各種水文監(jiān)測(cè)網(wǎng)絡(luò)、水利設(shè)施、用水單位和水利相關(guān)經(jīng)濟(jì)活動(dòng)，并通過現(xiàn)代化信息技術(shù)高效傳輸、分布存儲(chǔ)于各地存儲(chǔ)系統(tǒng)、但又可以快速讀取集中于云端、實(shí)現(xiàn)深度數(shù)據(jù)挖掘并可視化的海量多源數(shù)據(jù)總和。ValueVelocityVolume海量快速價(jià)值Variety多樣Veracity真實(shí)水利大數(shù)據(jù)水利大數(shù)據(jù)ValueVelocityVolume快5交叉性，由于水利和其它領(lǐng)域具有交叉性，因此水利大數(shù)據(jù)和遙感大數(shù)據(jù)、氣象大數(shù)據(jù)、海洋大數(shù)據(jù)等交叉；時(shí)空分布性，需要依賴先進(jìn)大數(shù)據(jù)技術(shù)進(jìn)行處理分析，包括分布式大數(shù)據(jù)存儲(chǔ)框架、機(jī)器學(xué)習(xí)等數(shù)據(jù)挖掘方法；多元循環(huán)性，由水的多元循環(huán)決定的水利大數(shù)據(jù)在經(jīng)濟(jì)、社會(huì)、生態(tài)等領(lǐng)域的價(jià)值循環(huán)。水利大數(shù)據(jù)的外延交叉性，由于水利和其它領(lǐng)域具有交叉性，因此水利大數(shù)據(jù)和遙感6挑戰(zhàn)一：水利大數(shù)據(jù)的收集與集成水利大數(shù)據(jù)來源廣泛，不同的監(jiān)測(cè)平臺(tái)得到的數(shù)據(jù)具有不同的數(shù)據(jù)結(jié)構(gòu)、存儲(chǔ)系統(tǒng)，非結(jié)構(gòu)化數(shù)據(jù)、半結(jié)構(gòu)化數(shù)據(jù)、結(jié)構(gòu)化數(shù)據(jù)并存；由于觀測(cè)條件的差異，數(shù)據(jù)可信度層次不齊，對(duì)數(shù)據(jù)清洗和質(zhì)量的確保提出了很高的要求；大數(shù)據(jù)的存儲(chǔ)與管理需要新型數(shù)據(jù)庫(kù)的支持，水利大數(shù)據(jù)的信息化還未與新型數(shù)據(jù)庫(kù)接軌。水利大數(shù)據(jù)面臨的挑戰(zhàn)挑戰(zhàn)一：水利大數(shù)據(jù)的收集與集成水利大數(shù)據(jù)面臨的挑戰(zhàn)7挑戰(zhàn)二：水利大數(shù)據(jù)的時(shí)空多維度分析水利大數(shù)據(jù)具有明顯的時(shí)空分布特性，時(shí)間、空間雙維度下的數(shù)據(jù)分析具有難度；水利大數(shù)據(jù)在其應(yīng)用領(lǐng)域講究實(shí)時(shí)性，比如洪水預(yù)報(bào)等，這對(duì)大數(shù)據(jù)的處理分析速度提出了高要求；水利大數(shù)據(jù)的深度挖掘有賴于引入先進(jìn)的人工智能算法，兩者的有效結(jié)合至關(guān)重要。水利大數(shù)據(jù)面臨的挑戰(zhàn)挑戰(zhàn)二：水利大數(shù)據(jù)的時(shí)空多維度分析水利大數(shù)據(jù)面臨的挑戰(zhàn)8挑戰(zhàn)三：水利大數(shù)據(jù)的共享與安全眾多水利數(shù)據(jù)掌握在政府機(jī)關(guān)部門，為非公開數(shù)據(jù)，形成數(shù)據(jù)孤島現(xiàn)象；水利數(shù)據(jù)是國(guó)家安全的重要組成部分，水利數(shù)據(jù)的共享與安全是一個(gè)值得探討的問題。水利大數(shù)據(jù)面臨的挑戰(zhàn)挑戰(zhàn)三：水利大數(shù)據(jù)的共享與安全水利大數(shù)據(jù)面臨的挑戰(zhàn)9三、基于水利大數(shù)據(jù)的多災(zāi)害信息集成與風(fēng)險(xiǎn)預(yù)警案例介紹三、基于水利大數(shù)據(jù)的多災(zāi)害信息集成與風(fēng)險(xiǎn)預(yù)警案例介紹10基于水利大數(shù)據(jù)的多災(zāi)害信息集成與風(fēng)險(xiǎn)預(yù)警案例介紹1、天、地、空、海，多基多源降水?dāng)?shù)據(jù)采集2、移動(dòng)眾包信息收集可視化云平臺(tái)mPing3、基于水利大數(shù)據(jù)的全球洪水泥石流災(zāi)害預(yù)測(cè)預(yù)報(bào)4、基于概率洪水風(fēng)險(xiǎn)預(yù)報(bào)EF55、城市洪水模型Urban

CREST介紹6、全球風(fēng)暴數(shù)據(jù)庫(kù)及CI-FLOW7、中國(guó)區(qū)域多尺度洪水模擬及預(yù)警系統(tǒng)的建立8、基于ArcGIS的FFG介紹9、基于ArcGIS平臺(tái)開發(fā)的ArcCREST介紹基于水利大數(shù)據(jù)的多災(zāi)害信息集成與風(fēng)險(xiǎn)預(yù)警案例介紹基于水利大數(shù)據(jù)的多災(zāi)害信息集成與風(fēng)險(xiǎn)預(yù)警案例介紹1、天113小時(shí)臨近預(yù)報(bào)（250米／2.5分鐘）＋36小時(shí)模型預(yù)報(bào)（1公里／小時(shí)）1.天、地、空、海多基多源降水?dāng)?shù)據(jù)采集雙偏振雷達(dá)＋衛(wèi)星＋站點(diǎn)＋模型3小時(shí)臨近預(yù)報(bào)1.天、地、空、海多基多源降水?dāng)?shù)據(jù)采集雙偏振12PERSIANN

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SWANCI-FLOW:HL-RDHM/SWAN/ADCIRCC337.中國(guó)區(qū)域多尺度洪水模擬及預(yù)警系統(tǒng)的建立中國(guó)的山洪預(yù)警系統(tǒng)量融合，驅(qū)動(dòng)CREST模型，模擬徑流分布與氣象局以及國(guó)家氣象中心合作開發(fā)多源降水產(chǎn)品和地面臺(tái)站數(shù)據(jù)進(jìn)行雨地貌水動(dòng)力學(xué)模型模擬洪水淹沒情景的時(shí)空演進(jìn)，實(shí)時(shí)動(dòng)態(tài)提取洪水淹沒范圍、水深分布和淹沒時(shí)間分布，實(shí)現(xiàn)對(duì)洪水的模擬7.中國(guó)區(qū)域多尺度洪水模擬及預(yù)警系統(tǒng)的建立中國(guó)的山洪預(yù)警系統(tǒng)34洪水模擬的時(shí)間：199806280501001502002503000500010000150002000025000Date3/5/19975/8/19977/11/19979/13/199711/16/19971/19/19983/24/19985/27/19987/30/199810/2/199812/5/19982/7/19994/12/19996/15/19998/18/199910/21/199912/24/19992/26/20004/30/20007/3/20009/5/200011/8/20001/11/20013/16/20015/19/20017/22/20019/24/200111/27/20011/30/20024/4/20026/7/20028/10/200210/13/200212/16/20022/18/20034/23/20036/26/20038/29/200311/1/20031/4/20043/8/20045/11/20047/14/20049/16/200411/19/20041/22/20053/27/20055/30/20058/2/200510/5/200512/8/2005R_Obsin

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一遇洪水外州站CREST模型率定/模擬效果：氣象臺(tái)站數(shù)據(jù)驅(qū)動(dòng)7.中國(guó)區(qū)域多尺度洪水模擬及預(yù)警系統(tǒng)的建立洪水模擬的時(shí)間：199806280501001502002535114114.5115115.5116116.51172525.52626.52727.52828.529114114.5115115.5116116.511725236iMAP

在嘉陵江流域的應(yīng)用結(jié)果7.中國(guó)區(qū)域多尺度洪水模擬及預(yù)警系統(tǒng)的建立iMAP在嘉陵江流域的應(yīng)用結(jié)果7.中國(guó)區(qū)域多尺度洪水模擬及379.基于ArcGIS平臺(tái)開發(fā)的ArcCREST介紹ArcCREST

UIPrecip

ThiessenEvap

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Data9.基于ArcGIS平臺(tái)開發(fā)的ArcCREST介紹Arc38Usedforrainfallsites(Cell-baseddataneedsome

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(%)-99.999915.25CC0.79630.8382300200100040050011325374961738597109121133145157169181193205217229241253265277289301313325337349361Discharge(m3)Time(24h)Discharge:ArcCRESTvs

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1970toHydrologicFlashFloodGuidance201227-

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Guidance)FlashFloodGuidance:FFGist41DistributedFFG（0.189°）inSouth

China采用ArcGIS插值模塊得到面臨界雨量分布單位：mmDistributedFFG（0.189°）inSout42FlashFloodPotential

Index(FFPI)：DevelopedbyhydrologistGregSmith,CBRFC

(2003).Geographicalfeatures

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productionofbettergriddedFlashFlood

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ofsoil,slope,vegetationandurbanizationcanbevisualized基于ArcGIS平臺(tái)的中國(guó)洪水風(fēng)險(xiǎn)潛在指標(biāo)FFPIFlashFloodPotentialIndex43基于ArcGIS的水利大數(shù)據(jù)及應(yīng)用課件44基于ArcGIS的水利大數(shù)據(jù)及應(yīng)用基于ArcGIS的水利大數(shù)據(jù)及應(yīng)用45團(tuán)隊(duì)簡(jiǎn)介水利大數(shù)據(jù)及其面臨的挑戰(zhàn)基于水利大數(shù)據(jù)的多災(zāi)害信息集成與風(fēng)險(xiǎn)預(yù)警案例主要內(nèi)容123團(tuán)隊(duì)簡(jiǎn)介水利大數(shù)據(jù)及其面臨的挑戰(zhàn)基于水利大數(shù)據(jù)的多災(zāi)害信息集46二、水利大數(shù)據(jù)及其面臨的挑戰(zhàn)二、水利大數(shù)據(jù)及其面臨的挑戰(zhàn)47水利工作關(guān)系到國(guó)計(jì)民生，尤其是我國(guó)水資源分布存在嚴(yán)重的時(shí)空分布不均特性，旱災(zāi)洪澇易發(fā)多發(fā)。水利行業(yè)在經(jīng)濟(jì)、生態(tài)、社會(huì)等方面都扮演著重要角色，對(duì)水利大數(shù)據(jù)的研究具有重要的現(xiàn)實(shí)意義和應(yīng)用價(jià)值。水利大數(shù)據(jù)是在大數(shù)據(jù)的理論指導(dǎo)及技術(shù)支撐下的水利科學(xué)和工程的重要實(shí)踐。水利工作及水利大數(shù)據(jù)的重要性水利工作關(guān)系到國(guó)計(jì)民生，尤其是我國(guó)水資源分布存在嚴(yán)重的時(shí)空48水利大數(shù)據(jù)水利大數(shù)據(jù)是指產(chǎn)生于各種水文監(jiān)測(cè)網(wǎng)絡(luò)、水利設(shè)施、用水單位和水利相關(guān)經(jīng)濟(jì)活動(dòng)，并通過現(xiàn)代化信息技術(shù)高效傳輸、分布存儲(chǔ)于各地存儲(chǔ)系統(tǒng)、但又可以快速讀取集中于云端、實(shí)現(xiàn)深度數(shù)據(jù)挖掘并可視化的海量多源數(shù)據(jù)總和。ValueVelocityVolume海量快速價(jià)值Variety多樣Veracity真實(shí)水利大數(shù)據(jù)水利大數(shù)據(jù)ValueVelocityVolume快49交叉性，由于水利和其它領(lǐng)域具有交叉性，因此水利大數(shù)據(jù)和遙感大數(shù)據(jù)、氣象大數(shù)據(jù)、海洋大數(shù)據(jù)等交叉；時(shí)空分布性，需要依賴先進(jìn)大數(shù)據(jù)技術(shù)進(jìn)行處理分析，包括分布式大數(shù)據(jù)存儲(chǔ)框架、機(jī)器學(xué)習(xí)等數(shù)據(jù)挖掘方法；多元循環(huán)性，由水的多元循環(huán)決定的水利大數(shù)據(jù)在經(jīng)濟(jì)、社會(huì)、生態(tài)等領(lǐng)域的價(jià)值循環(huán)。水利大數(shù)據(jù)的外延交叉性，由于水利和其它領(lǐng)域具有交叉性，因此水利大數(shù)據(jù)和遙感50挑戰(zhàn)一：水利大數(shù)據(jù)的收集與集成水利大數(shù)據(jù)來源廣泛，不同的監(jiān)測(cè)平臺(tái)得到的數(shù)據(jù)具有不同的數(shù)據(jù)結(jié)構(gòu)、存儲(chǔ)系統(tǒng)，非結(jié)構(gòu)化數(shù)據(jù)、半結(jié)構(gòu)化數(shù)據(jù)、結(jié)構(gòu)化數(shù)據(jù)并存；由于觀測(cè)條件的差異，數(shù)據(jù)可信度層次不齊，對(duì)數(shù)據(jù)清洗和質(zhì)量的確保提出了很高的要求；大數(shù)據(jù)的存儲(chǔ)與管理需要新型數(shù)據(jù)庫(kù)的支持，水利大數(shù)據(jù)的信息化還未與新型數(shù)據(jù)庫(kù)接軌。水利大數(shù)據(jù)面臨的挑戰(zhàn)挑戰(zhàn)一：水利大數(shù)據(jù)的收集與集成水利大數(shù)據(jù)面臨的挑戰(zhàn)51挑戰(zhàn)二：水利大數(shù)據(jù)的時(shí)空多維度分析水利大數(shù)據(jù)具有明顯的時(shí)空分布特性，時(shí)間、空間雙維度下的數(shù)據(jù)分析具有難度；水利大數(shù)據(jù)在其應(yīng)用領(lǐng)域講究實(shí)時(shí)性，比如洪水預(yù)報(bào)等，這對(duì)大數(shù)據(jù)的處理分析速度提出了高要求；水利大數(shù)據(jù)的深度挖掘有賴于引入先進(jìn)的人工智能算法，兩者的有效結(jié)合至關(guān)重要。水利大數(shù)據(jù)面臨的挑戰(zhàn)挑戰(zhàn)二：水利大數(shù)據(jù)的時(shí)空多維度分析水利大數(shù)據(jù)面臨的挑戰(zhàn)52挑戰(zhàn)三：水利大數(shù)據(jù)的共享與安全眾多水利數(shù)據(jù)掌握在政府機(jī)關(guān)部門，為非公開數(shù)據(jù)，形成數(shù)據(jù)孤島現(xiàn)象；水利數(shù)據(jù)是國(guó)家安全的重要組成部分，水利數(shù)據(jù)的共享與安全是一個(gè)值得探討的問題。水利大數(shù)據(jù)面臨的挑戰(zhàn)挑戰(zhàn)三：水利大數(shù)據(jù)的共享與安全水利大數(shù)據(jù)面臨的挑戰(zhàn)53三、基于水利大數(shù)據(jù)的多災(zāi)害信息集成與風(fēng)險(xiǎn)預(yù)警案例介紹三、基于水利大數(shù)據(jù)的多災(zāi)害信息集成與風(fēng)險(xiǎn)預(yù)警案例介紹54基于水利大數(shù)據(jù)的多災(zāi)害信息集成與風(fēng)險(xiǎn)預(yù)警案例介紹1、天、地、空、海，多基多源降水?dāng)?shù)據(jù)采集2、移動(dòng)眾包信息收集可視化云平臺(tái)mPing3、基于水利大數(shù)據(jù)的全球洪水泥石流災(zāi)害預(yù)測(cè)預(yù)報(bào)4、基于概率洪水風(fēng)險(xiǎn)預(yù)報(bào)EF55、城市洪水模型Urban

CREST介紹6、全球風(fēng)暴數(shù)據(jù)庫(kù)及CI-FLOW7、中國(guó)區(qū)域多尺度洪水模擬及預(yù)警系統(tǒng)的建立8、基于ArcGIS的FFG介紹9、基于ArcGIS平臺(tái)開發(fā)的ArcCREST介紹基于水利大數(shù)據(jù)的多災(zāi)害信息集成與風(fēng)險(xiǎn)預(yù)警案例介紹基于水利大數(shù)據(jù)的多災(zāi)害信息集成與風(fēng)險(xiǎn)預(yù)警案例介紹1、天553小時(shí)臨近預(yù)報(bào)（250米／2.5分鐘）＋36小時(shí)模型預(yù)報(bào)（1公里／小時(shí)）1.天、地、空、海多基多源降水?dāng)?shù)據(jù)采集雙偏振雷達(dá)＋衛(wèi)星＋站點(diǎn)＋模型3小時(shí)臨近預(yù)報(bào)1.天、地、空、海多基多源降水?dāng)?shù)據(jù)采集雙偏振56PERSIANN

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SystemForUrbanandBuilt-up

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94(32),2776.全球風(fēng)暴數(shù)據(jù)庫(kù)及CI-FLOWGlobalStor73Nov2011

BAMSTheCI-FLOWProject:ASystemforTotalWaterLevelPredictionFromTheSummitToThe

SeaCI-FLOWsummarypaperwithHurricaneIsabel,HurricaneEarl,&TropicalStormNicole

resultsVolume##Number#November

2011BAMSAmericanMeteorological

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Theci-flowproject:asystemfortotalwaterlevelpredictionfromthesummittothesea.Bull.

Amer.Meteor.Soc.,92,1427–1442.已應(yīng)用到美國(guó)北卡羅來納州、墨西哥灣等易受颶風(fēng)和風(fēng)暴潮影響的海岸帶地區(qū)海洋風(fēng)暴潮與內(nèi)陸洪水監(jiān)測(cè)預(yù)警系統(tǒng)(CI-FLOW)SuzanneVanCooten,…,YangHo75CI-FLOWCoastalandInlandFloodingObservationand

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BCsWave

ForcingHydrodynamicModel

(ADCIRC)HydrologicModelAtmosphericModelWave

ModelPrecipitationSource:QPE/QPFAtmosphericModel:NAMorNHC

trackHydrologicModel:HL-RDHM,Vfloor

CRESTWaveModel:unstructured

SWANCI-FLOW:HL-RDHM/SWAN/ADCIRCC777.中國(guó)區(qū)域多尺度洪水模擬及預(yù)警系統(tǒng)的建立中國(guó)的山洪預(yù)警系統(tǒng)量融合，驅(qū)動(dòng)CREST模型，模擬徑流分布與氣象局以及國(guó)家氣象中心合作開發(fā)多源降水產(chǎn)品和地面臺(tái)站數(shù)據(jù)進(jìn)行雨地貌水動(dòng)力學(xué)模型模擬洪水淹沒情景的時(shí)空演進(jìn)，實(shí)時(shí)動(dòng)態(tài)提取洪水淹沒范圍、水深分布和淹沒時(shí)間分布，實(shí)現(xiàn)對(duì)洪水的模擬7.中國(guó)區(qū)域多尺度洪水模擬及預(yù)警系統(tǒng)的建立中國(guó)的山洪預(yù)警系統(tǒng)78洪水模擬的時(shí)間：199806280501001502002503000500010000150002000025000Date3/5/19975/8/19977/11/19979/13/199711/16/19971/19/19983/24/19985/27/19987/30/199810/2/199812/5/19982/7/19994/12/19996/15/19998/18/199910/21/199912/24/19992/26/20004/30/20007/3/20009/5/200011/8/20001/11/20013/16/20015/19/20017/22/20019/24/200111/27/20011/30/20024/4/20026/7/20028/10/200210/13/200212/16/20022/18/20034/23/20036/26/20038/29/200311/1/20031/4/20043/8/20045/11/20047/14/20049/16/200411/19/20041/22/20053/2