Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2018WR022669 |
Estimating Basin-Scale Water Budgets With SMAP Soil Moisture Data | |
Koster, Randal D.1; Crow, Wade T.2; Reichle, Rolf H.1; Mahanama, Sarith P.1,3 | |
2018-07-01 | |
发表期刊 | WATER RESOURCES RESEARCH |
ISSN | 0043-1397 |
EISSN | 1944-7973 |
出版年 | 2018 |
卷号 | 54期号:7页码:4228-4244 |
文章类型 | Article |
语种 | 英语 |
国家 | USA |
英文摘要 | Soil Moisture Active Passive (SMAP) Level-2 soil moisture retrievals collected during 2015-2017 are used in isolation to estimate 10-day warm season precipitation and streamflow totals within 145 medium-sized (2,000-10,000 km(2)) unregulated watersheds in the conterminous United States. The precipitation estimation algorithm, derived from a well-documented approach, includes a locally calibrated loss function component that significantly improves its performance. For the basin-scale water budget analysis, the precipitation and streamflow algorithms are calibrated with 2 years of SMAP retrievals in conjunction with observed precipitation and streamflow data and are then applied to SMAP retrievals alone during a third year. While estimation accuracy (as measured by the square of the correlation coefficient, r(2), between estimates and observations) varies by basin, the average r(2) for the basins is 0.53 for precipitation and 0.22 for streamflow. For the subset of 22 basins that calibrate particularly well, the r(2) increases to 0.63 for precipitation and to 0.51 for streamflow. The magnitudes of the estimated variables are also accurate, with sample pairs generally clustered about the 1:1 line. The chief limitation to the estimation involves large biases induced during periods of high rainfall; the accuracy of the estimates (in terms of r(2) and root-mean-square error) increases significantly when periods of higher rainfall are not considered. The potential for transferability is also demonstrated by calibrating the streamflow estimation equation in one basin and then applying the equation in another. Overall, the study demonstrates that SMAP retrievals contain, all by themselves, information that can be used to estimate large-scale water budgets. |
领域 | 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000442502100002 |
WOS关键词 | L-BAND ; PRECIPITATION ESTIMATION ; RAINFALL ; SURFACE ; ASSIMILATION ; VALIDATION ; PRODUCTS ; IMPROVE ; SENSORS ; DEPTH |
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/19945 |
专题 | 资源环境科学 |
作者单位 | 1.NASA, Global Modeling & Assimilat Off, GSFC, Greenbelt, MD 20771 USA; 2.ARS, Hydrol & Remote Sensing Lab, USDA, Beltsville, MD USA; 3.Sci Syst & Appl Inc, Lanham, MD USA |
推荐引用方式 GB/T 7714 | Koster, Randal D.,Crow, Wade T.,Reichle, Rolf H.,et al. Estimating Basin-Scale Water Budgets With SMAP Soil Moisture Data[J]. WATER RESOURCES RESEARCH,2018,54(7):4228-4244. |
APA | Koster, Randal D.,Crow, Wade T.,Reichle, Rolf H.,&Mahanama, Sarith P..(2018).Estimating Basin-Scale Water Budgets With SMAP Soil Moisture Data.WATER RESOURCES RESEARCH,54(7),4228-4244. |
MLA | Koster, Randal D.,et al."Estimating Basin-Scale Water Budgets With SMAP Soil Moisture Data".WATER RESOURCES RESEARCH 54.7(2018):4228-4244. |
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