Knowledge Resource Center for Ecological Environment in Arid Area
DOI | 10.1007/s10333-011-0308-9 |
To improve model soil moisture estimation in arid/semi-arid region using in situ and remote sensing information | |
Hsu, Kuolin; Li, Jialun; Sorooshian, Soroosh | |
通讯作者 | Hsu, Kuolin |
来源期刊 | PADDY AND WATER ENVIRONMENT |
ISSN | 1611-2490 |
出版年 | 2012 |
卷号 | 10期号:3页码:165-173 |
英文摘要 | Soil moisture plays a key role in water and energy exchange in the land hydrologic process. Effective soil moisture information can be used for many applications in weather and hydrological forecasting, water resources, and irrigation system management and planning. However, to accurate modeling of soil moisture variation in the soil layer is still very challenging. In this study, in situ and remote sensing information of near-surface soil moisture is assimilated into the Noah land surface model (LSM) to estimate deep-layer soil moisture variation. The sequential Monte Carlo-Particle Filter technique, being well known for capability of modeling high nonlinear and non-Gaussian processes, is applied to assimilate surface soil moisture measurement to the deep layers. The experiments were carried out over several locations over the semi-arid region of the US. Comparing with in situ observations, the assimilation runs show much improved from the control (non-assimilation) runs for estimating both soil moisture and temperature at 5-, 20-, and 50-cm soil depths in the Noah LSM. |
英文关键词 | Soil moisture Land surface model Data assimilation Sequential Monte Carlo |
类型 | Article |
语种 | 英语 |
国家 | USA |
收录类别 | SCI-E |
WOS记录号 | WOS:000307889300002 |
WOS关键词 | LAND-SURFACE MODELS ; MESOSCALE ETA-MODEL ; NEAR-SURFACE ; DATA ASSIMILATION ; PARAMETERIZATION ; IMPLEMENTATION ; PRECIPITATION ; SENSITIVITY ; PREDICTION ; IMPACT |
WOS类目 | Agricultural Engineering ; Agronomy |
WOS研究方向 | Agriculture |
资源类型 | 期刊论文 |
条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/174256 |
作者单位 | Univ Calif Irvine, Dept Civil & Environm Engn, Ctr Hydrometeorol & Remote Sensing, Irvine, CA 92717 USA |
推荐引用方式 GB/T 7714 | Hsu, Kuolin,Li, Jialun,Sorooshian, Soroosh. To improve model soil moisture estimation in arid/semi-arid region using in situ and remote sensing information[J],2012,10(3):165-173. |
APA | Hsu, Kuolin,Li, Jialun,&Sorooshian, Soroosh.(2012).To improve model soil moisture estimation in arid/semi-arid region using in situ and remote sensing information.PADDY AND WATER ENVIRONMENT,10(3),165-173. |
MLA | Hsu, Kuolin,et al."To improve model soil moisture estimation in arid/semi-arid region using in situ and remote sensing information".PADDY AND WATER ENVIRONMENT 10.3(2012):165-173. |
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