[1]全科会,郭永刚.高原高寒水利工程数字孪生技术应用综述[J].水利与建筑工程学报,2026,(04):137-146.[doi:10.3969/j.issn.1672-1144.2026.04.018]
点击复制

高原高寒水利工程数字孪生技术应用综述()

《水利与建筑工程学报》[ISSN:1672-1144/CN:61-1404/TV]

卷:
期数:
2026年04期
页码:
137-146
栏目:
出版日期:
2026-08-20

文章信息/Info

作者:
全科会郭永刚
西藏农牧大学 水利土木工程学院,西藏 林芝 860000
关键词:
数字孪生高原寒区水利工程冻融循环边缘计算
分类号:
TV672;TP391
DOI:
10.3969/j.issn.1672-1144.2026.04.018
文献标志码:
A
摘要:
为厘清高原高寒环境下水利数字孪生的研究现状、关键技术需求和未来发展方向,遵循 PRIS-MA规范,以 WebofScience、Scopus和 CNKI(中国知网)为主要检索源,对 2015—2026年发表的相关文献进行了系统检索与筛选,纳入核心文献 52篇,结合背景文献共引用 64篇,以高原高寒环境为独特视角,对数字孪生技术在水利工程领域的研究进展与关键挑战进行了全面梳理。结果表明:该领域自 2020年以来呈爆发式增长,但配水管网与污水处理占据近七成研究,高原寒区案例严重匮乏;实际工程中实现物理-数字双向闭环的系统不足 5%,多数停留在“仅咨询”模式;高原环境对数字孪生提出了多物理场耦合仿真、低功耗边缘计算、冻融智能预警和自适应调度四大关键技术需求,尚未被现有研究体系充分覆盖。在此基础上提出了从近期到远期的分阶段实施路径,并建议以西藏跨流域调水工程为载体建设示范项目。

参考文献/References:

[1] TaylorJE,OlmstedFL,BennettG,etal.Engineeringsmartercitieswithsmartcitydigitaltwins[J].JournalofManagementinEngineering,2021,37(06):02021001.
[2] BejiH,LadeM.Impactofdigitaltransformationoncar-bonemissionreductionsinthewaterindustry[M].Lec-tureNotesinEnergy.Cham:Springer,2022,86:117-127.
[3] 张绿原,胡露骞,沈启航,等.水利工程数字孪生技术研究与探索[J].中国农村水利水电,2021(11):58-62.
[4] TaoF,SuiF,LiuA,etal.Digitaltwin-drivenproductdesignframework[J].InternationalJournalofProductionResearch,2019,57(12):3935-3953.
[5] SinghM,FuenmayorE,HinchyEP,etal.Digitaltwin:Origintofuture[J].AppliedSystemInnovation,2021,4(02):36.
[6] O′DwyerE,PanI,CharlesworthR,etal.Integrationofanenergymanagementtoolanddigitaltwinforcoordina-tionandcontrolofmulti-vectorsmartenergysystems[J].SustainableCitiesandSociety,2020,62:102412.
[7] SchrotterG,HürzelerC.ThedigitaltwinofthecityofZurichforurbanplanning[J].PFG-JournalofPhoto-grammetry,RemoteSensingandGeoinformationScience,2020,88(01):99-112.
[8] GhorbaniBamP,RezaeiN,RoubanisA,etal.Digitaltwinapplicationsinthewatersector:Areview[J].Wa-ter,2025,17(20):2957.
[9] 刘家宏,梅 超,王 浩,等.数字孪生流域:未来流域治理管理的新基建新范式[J].水科学进展,2022,33(5):683-696.
[10] 马伟强,马耀明,马龙腾飞,等.青藏高原地-气相互作用过程及其天气、气候效应数值模拟研究综述[J].气象学报,2025,83(03):584-638.
[11] 赵 林,胡国杰,邹德富,等.青藏高原土壤冻融过程研究进展[J].地理科学进展,2020,39(11):1950-1962.
[12] 程国栋,赵 林.青藏高原多年冻土变化及其对生态过程的影响 [J].中国科学 (地球科学),2022,52(01):1-17.
[13] 王 羿,王正中,刘铨鸿,等.寒区输水渠道衬砌与冻土相互作用的冻胀破坏试验研究[J].岩土工程学报,2018,40(10):1799-1808.
[14] 夏润亮,李 涛,余 伟,等.流域数字孪生理论及其在黄河防汛中的实践[J].中国水利,2021(20):11-13.
[15] 朱思宇,杨红卫,尹桂平,等.基于数字孪生的智慧水利框架体系研究[J].水利水运工程学报,2023(03):68-74.
[16] GrievesM,VickersJ.Digitaltwin:Mitigatingunpre-dictable,undesirableemergentbehaviorincomplexsys-tems[M].TransdisciplinaryPerspectivesonComplexSystems.Cham:Springer,2016:85-113.
[17] 陶 飞,张 萌,程江峰,等.数字孪生车间———一种未来车间运行新模式[J].计算机集成制造系统,2017,23(01):1-9.
[18] KritzingerW,KarnerM,TraarG,etal.Digitaltwininmanufacturing:Acategoricalliteraturereviewandclas-sification[J].IFAC-PapersOnLine,2018,51(11):1016-1022.
[19] JonesD,SniderC,NassehiA,etal.Characterizingthedigitaltwin:Asystematicliteraturereview[J].CIRPJournalofManufacturing Science and Technology,2020,29(PartA):36-52.
[20] RasheedA,SanO,KvamsdalT.Digitaltwin:Values,challengesandenablersfrom amodelingperspective[J].IEEEAccess,2020,8:21980-22012.
[21] SchneiderMY,QuaghebeurW,BorzooeiS,etal.Hy-bridmodellingofwaterresourcerecoveryfacilities:Sta-tusandopportunities[J].WaterScienceandTechnolo-gy,2022,85(09):2503-2524.
[22] 张建云,刘九夫,金君良,等.关于智慧水利的认识与思考[J].水利水运工程学报,2019(06):1-7.
[23] CavalieriS,GambadoroS.Digitaltwinofawatersupplysystemusingtheassetadministrationshell[J].Sensors,2024,24(5):1360.
[24] 水利部.关于推进水库、水闸、蓄滞洪区运行管理数字孪生的指导意见[EB/OL].中华人民共和国中央人民政府网.(2024-10-14)
[2025-06-30].https://www.gov.cn/gongbao/2024/issue_11726/202411/con-tent_6989758.html.
[25] 詹全忠,陈真玄,张 潮,等.《数字孪生水利工程建设技术导则(试行)》解析[J].水利信息化,2022(04):1-5.
[26] 谢文君,李家欢,李鑫雨,等.《数字孪生流域建设技术大纲(试行)》解析[J].水利信息化,2022(04):6-12.
[27] 李国英.建设数字孪生流域 推动新阶段水利高质量发展[J].中国水利,2022(13):1-3.
[28] LiShuangping,ZhangBin,TongGuangqin,etal.On-lineintelligentmonitoringsystem andkeytechnologiesfordam operationsafety[J].AdvancesinCivilEngi-neering,2025,2025:9983255.
[29] PereiraRCC,ResendePN,PiresJRC,etal.BIM-enabledstrategiesfordamsandhydroelectricstructures:acomprehensiveanalysisofapplicationsfromdesigntooperation[J].ArchitecturalEngineeringandDesignManagement,2025,21(03):491-512.
[30] DairiA,ChengT,HarrouF,etal.Deeplearningap-proachforsustainableWWTPoperation:Acasestudyondata-driveninfluentconditionsmonitoring[J].Sus-tainableCitiesandSociety,2019,50:101670.
[31] VerhaegheL,VerwaerenJ,Kirim G,etal.Towardsgoodmodellingpracticeforparallelhybridmodelsforwastewatertreatmentprocesses[J].WaterScienceandTechnology,2024,89(12):2971-2990.
[32] HeoSK,OhT,WooTY,etal.Real-scaledemonstra-tionofdigitaltwins-basedaerationcontrolpolicyoptimi-zation[J].Desalination,2025,593:118235.
[33] BolorinosJ,MauterMS,RajagopalR.Integratedener-gy-flexibilitymanagementatwastewater-treatmentfacili-ties[J].EnvironmentalScienceandTechnology,2023,57(45):18362-18371.
[34] CodyRA,TolsonBA,OrchardJ.Detectingleaksinwaterdistributionpipesusingadeepautoencoderandhydroacousticspectrograms[J].JournalofComputinginCivilEngineering,2020,34(02):04020001.
[35] DegelerV,HadadianM,KarabulutE,etal.Ditec:Digitaltwinforevolutionarychangesinwaterdistributionnetworks[C]//Internationalsymposium onleveragingapplicationsofformalmethods.Cham:SpringerNatureSwitzerland,2024:62-82.
[36] OstfeldA,AbhijithGR.Digitaltwinforwaterdistribu-tionsystem management———Towardsaparadigm shift[J].JournalofPipelineSystemsEngineeringandPrac-tice,2023,14(04):02523001.
[37] InoueJ,YamagataY,ChenYuqi,etal.Anomalyde-tectionforawatertreatmentsystem usingunsupervisedmachinelearning[C]//Proceedingsofthe2017IEEEInternationalConference on Data Mining Workshops(ICDMW).New Orleans,USA,November18-21,2017.Piscataway:IEEE,2017:1058-1065.
[38] WangHai,GuoYesshuang,LiLong,etal.DevelopmentofAI-basedprocesscontrollerusingdeepreinforcementlearning[J].JournaloftheTaiwanInstituteofChemicalEngineers,2024,157:105407.
[39] SerraoM,JauzeinV,JuranI,etal.Hybridmodellingofnitrogenremovalbybiofiltration[J].WaterScienceandTechnology,2024,90(6):1416-1432.
[40] vanRooijF,ScarfP,DoP.PlanningtherestorationofmembranesinROdesalinationusingadigitaltwin[J].Desalination,2022,519:115214.
[41] BartosM,KerkezB.Pipedream:Aninteractivedigitaltwinmodelfornaturalandurbandrainagesystems[J].EnvironmentalModelling & Software, 2021,144:105120.
[42] 江浩源,王正中,刘铨鸿,等.考虑太阳辐射的寒区衬砌渠道水-热-力耦合冻胀模型与应用[J].水利学报,2021,52(05):589-602.
[43] 年作斌,王正中,李中煜,等.基于水-热-汽-力耦合的寒区河渠湖库护岸冻融破坏机理[J/OL].水利学报.
[2025-04-26].https://doi.org/10.13243/j.cnki.slxb.20250426.
[44] AmanatidisP,LyratzisE,AngelopoulosV,etal.Intel-ligentwatermanagementthroughedge-enabledIoT,AI,andbigdatatechnologies[J].IoT,2025,7(01):5.
[45] MolinH,WrffC,LindblomE,etal.Automateddatatransferfordigitaltwinapplications:Twocasestudies[J].WaterEnvironmentResearch,2024,96(08):e11074.
[46] TravaV,GalE,LucˇinI,etal.Digitaltwinforreal-timeleakagedetectionandlocalizationinpressurizedpipingsystems[J].JournalofHydroinformatics,2025,27(4):755-770.
[47] JiYukun,WangHaihang,LiXianzhao,etal.Effectofanionicpolyacrylamidepolymeronfrostheavemitigationanditsimplicationforfrost-susceptiblesoil[J].Poly-mers,2023,15(09):2096.
[48] LiJiuling,MohamadNNN,SharmaK,etal.Establis-hingboundaryconditionsinsewerpipe/soilheattransfermodellingusingphysics-informedlearning[J].WaterResearch,2023,244:120441.
[49] 李景刚,陈晓楠,卢明龙,等.南水北调中线干线冰期输水动态调度初探[J].中国水利,2023(02):30-33.
[50] 潘佳佳,郭新蕾,付 辉,等.南水北调中线工程冰期输水水温 -冰情耦合模拟[J].水利学报,2023,54(3):296-306.
[51] TorfsE,NicolaN,DaneshgarS,etal.ThetransitionofWRRFmodelstodigitaltwinapplications[J].WaterScienceandTechnology,2022,85(10):2840-2853.
[52] ZhouShengwen,GuoShunsheng,XuWenxiang,etal.Digitaltwin-basedpumpstationdynamicschedulingforenergy-savingoptimization[J].WaterResourcesMan-agement,2024,38:2773-2789.
[53] DaneshgarS,PoleselF,BorzooeiS,etal.Afull-scaleoperationaldigitaltwinforawater-resource-recoveryfa-cility[J]. WaterEnvironmentResearch,2024,96(05):e11016.
[54] 中国水利水电科学研究院.中国数字孪生水利建设成果亮相第十五届国际水信息学大会[EB/OL].中国水利水电科学研究院网站.(2024-06-25).http://www.iwhr.com/zgskywwnew/mtzs/webinfo/2024/06/1713251117838388.htm.
[55] 潘志权,闫 飞,贾东远,等.长距离输水工程数字孪生模型数据融合及编码技术研究[J].水利与建筑工程学报,2024,22(2):12-18.
[56] 管光华,刘王嘉仪,陈晓楠,等.输水渠系水动力数字孪生模型糙率估计方法[J].水科学进展,2023,34(06):901-912.
[57] DingShaolin,PanJiajun,WangYanli,etal.Develo-pingadigitaltwinfordamsafetymanagement[J].Com-putersandGeotechnics,2025,180:107120.
[58] LiHelin,ZhangRui,ZhengShufeng,etal.Digitaltwin-drivenintelligentoperationandmaintenanceplat-formforlarge-scalehydro-steelstructures[J].AdvancedEngineeringInformatics,2024,62:102661.
[59] SavicD.Digitalwaterdevelopmentsandlessonslearnedfromautomationinthecarandaircraftindustries[J].Engineering,2022,9(02):35-41.
[60] T/CI257—2023 数字孪生水利工程质量评价[S].北京:中国水利水电出版社,2023.
[61] ZhaoChi,ZhangFeifei,LouWenqiang,etal.Acom-prehensivereviewofadvancesinphysics-informedneuralnetworksandtheirapplicationsincomplexfluiddynam-ics[J].PhysicsofFluids,2024,36(10):101301.
[62] DiBellaA,RaissiM,SantoroD,etal.Physics-in-formedneuralnetworksinwaterandwastewatersystems:acriticalreview[J].WaterResearch,2026:125449.
[63] FuGuangtao,JinYiwei,SunSiao,etal.Theroleofdeeplearninginurbanwatermanagement:Acriticalre-view[J].WaterResearch,2022,223:118973.
[64] SaddiqiM M,ZhaoWanqing,CotterillS,etal.Smartmanagementofcombined seweroverflows: From anancienttechnologytoartificialintelligence[J].WIREsWater,2023,10(04):e1635.

相似文献/References:

[1]潘志权,闫飞,贾东远,等.长距离输水工程数字孪生模型数据融合及编码技术研究[J].水利与建筑工程学报,2024,(02):12.[doi:10.3969/j.issn.1672-1144.2024.02.003]
[2]邱志章,胡琳琳,张 扬,等.数字孪生小流域山洪灾害“四预”平台建设与应用[J].水利与建筑工程学报,2024,(04):99.[doi:10.3969/j.issn.1672-1144.2024.04.015]

备注/Memo

备注/Memo:
收稿日期:2026-02-25 修稿日期:2026-03-31
基金项目:西藏自治区重点研发计划项目(XZ202201ZY0034G);西藏农牧大学研究生创新计划项目(SGYC2026006)
作者简介:全科会(2001—),男,硕士研究生,研究方向为高原高寒水利工程数字孪生、人工智能技术与水利信息化。E-mail:2226330355@qq.com
通讯作者:郭永刚(1966—),男,博士,教授,主要从事基于 BIM技术、大数据技术和人工智能技术的智慧河湖系统研发工作。E-mail:1960373107@qq.com
更新日期/Last Update: 1900-01-01