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DOI10.1029/2017WR022040
A New Global Storage-Area-Depth Data Set for Modeling Reservoirs in Land Surface and Earth System Models
Yigzaw, Wondmagegn1,2; Li, Hong-Yi1,2; Demissie, Yonas3; Hejazi, Mohamad I.4; Leung, L. Ruby5; Voisin, Nathalie5; Payn, Rob2
2018-12-01
发表期刊WATER RESOURCES RESEARCH
ISSN0043-1397
EISSN1944-7973
出版年2018
卷号54期号:12页码:10372-10386
文章类型Article
语种英语
国家USA
英文摘要

Reservoir storage-area-depth relationships are the most important factors controlling thermal stratification in reservoirs and, more broadly, the water, energy, and biogeochemical dynamics in the reservoirs and subsequently their impacts on downstream rivers. However, most land surface or Earth system models do not account for the gradual changes of reservoir surface area and storage with the changing depth, inhibiting a consistent and accurate representation of mass, energy, and biogeochemical balances in reservoirs. Here we present a physically coherent parameterization of reservoir storage-area-depth data set at the global scale. For each reservoir, the storage-area-depth relationships were derived from an optimal geometric shape selected iteratively from five possible regular geometric shapes that minimize the error of total storage and surface area estimation. We applied this algorithm to over 6,800 reservoirs included in the Global Reservoir and Dam database. The relative error between the estimated and observed total storage is no more than 5% and 50% for 66% and 99% of all Global Reservoir and Dam reservoirs, respectively. More importantly, the storage-depth profiles derived from the approximated reservoir geometry compared well with remote sensing based estimation at 40 major reservoirs from previous studies and ground-truth measurements for 34 reservoirs in the United States and China. The new global reservoir storage-area-depth data set is critical for advancing future modeling and understanding of reservoir processes and subsequent effects on the terrestrial hydrological, ecological, and biogeochemical cycles at the regional and global scales.


英文关键词global reservoir geometry storage-area-depth profile Earth system models
领域资源环境
收录类别SCI-E
WOS记录号WOS:000456949300021
WOS关键词WATER-QUALITY ; LAKE ; SEDIMENT ; IMPACT ; SCENARIOS ; HABITAT ; BASIN ; FISH
WOS类目Environmental Sciences ; Limnology ; Water Resources
WOS研究方向Environmental Sciences & Ecology ; Marine & Freshwater Biology ; Water Resources
引用统计
文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/21552
专题资源环境科学
作者单位1.Univ Houston, Dept Civil & Environm Engn, Houston, TX 77204 USA;
2.Montana State Univ, Dept Land Resources & Environm Sci, Bozeman, MT 59717 USA;
3.Washington State Univ, Dept Civil & Environm Engn, Pullman, WA 99164 USA;
4.Joint Global Change Res Inst, College Pk, MD USA;
5.Pacific Northwest Natl Lab, Richland, WA USA
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Yigzaw, Wondmagegn,Li, Hong-Yi,Demissie, Yonas,et al. A New Global Storage-Area-Depth Data Set for Modeling Reservoirs in Land Surface and Earth System Models[J]. WATER RESOURCES RESEARCH,2018,54(12):10372-10386.
APA Yigzaw, Wondmagegn.,Li, Hong-Yi.,Demissie, Yonas.,Hejazi, Mohamad I..,Leung, L. Ruby.,...&Payn, Rob.(2018).A New Global Storage-Area-Depth Data Set for Modeling Reservoirs in Land Surface and Earth System Models.WATER RESOURCES RESEARCH,54(12),10372-10386.
MLA Yigzaw, Wondmagegn,et al."A New Global Storage-Area-Depth Data Set for Modeling Reservoirs in Land Surface and Earth System Models".WATER RESOURCES RESEARCH 54.12(2018):10372-10386.
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