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Fusing Large Datasets and Models to Improve Understanding of Hydrologic and Hydraulic Processes
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Fusing Large Datasets and Models to Improve Understanding of Hydrologic and Hydraulic Processes. |
| 개인저자 | Fries, Kevin. |
| 단체저자명 | University of Michigan. Civil Engineering. |
| 발행사항 | [S.l.]: University of Michigan., 2018. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
| 형태사항 | 252 p. |
| 기본자료 저록 | Dissertation Abstracts International 79-12B(E). Dissertation Abstract International |
| ISBN | 9780438126817 |
| 학위논문주기 | Thesis (Ph.D.)--University of Michigan, 2018. |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
Adviser: Branko Kerkez. |
| 요약 | Global water systems are being stressed by aging infrastructure, climate change, and resource withdrawals. The ability to model large water systems has attempted to keep pace with these challenges, with modern water models now operating effectiv |
| 일반주제명 | Civil engineering. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
