DOI: 10.1002/2017MS001144
Scopus记录号: 2-s2.0-85040717951
论文题名: SWAT-Based Hydrological Data Assimilation System (SWAT-HDAS): Description and Case Application to River Basin-Scale Hydrological Predictions
作者: Zhang Y ; , Hou J ; , Gu J ; , Huang C ; , Li X
刊名: Journal of Advances in Modeling Earth Systems
ISSN: 19422466
出版年: 2017
卷: 9, 期: 8 起始页码: 2863
结束页码: 2882
语种: 英语
英文关键词: Climate change
; Efficiency
; Hydrology
; Moisture
; Rain
; Sensor networks
; Snow melting systems
; Soil moisture
; Soils
; Stream flow
; Watersheds
; Data assimilation
; Development and applications
; Distributed hydrological model
; EnKF
; PDAF
; Soil and Water assessment tools
; SWAT
; Temporal and spatial correlation
; Snow
; algorithm
; data assimilation
; hydrological modeling
; Kalman filter
; leaf area index
; prediction
; river basin
; satellite data
; sensor
; snow water equivalent
; software
; soil and water assessment tool
; soil moisture
; spatiotemporal analysis
; streamflow
; watershed
英文摘要: This paper presents the development and application of a physically based hydrological data assimilation system (HDAS) using the gridded and parallelized Soil and Water Assessment Tool (SWATGP) distributed hydrological model. This SWAT-HDAS software integrates remotely sensed data, including the leaf area index (LAI), snow cover fraction, snow water equivalent, soil moisture, and ground-based observational data (e.g., from discharge and ground sensor networks), with SWATGP and the Parallel Data Assimilation Framework (PDAF) to accurately characterize watershed hydrological states and fluxes. SWAT-HDAS employs high-performance computational technologies to address the computational challenges of high-resolution and/or large-area modeling. Multiple observational system simulation experiments (OSSEs), including soil moisture assimilation experiments, snow water equivalent assimilation experiments, and streamflow assimilation experiments, were designed to validate the assimilation efficiency of various types of observations within SWAT-HDAS using an ensemble Kalman filter (EnKF) algorithm. Both the temporal and spatial correlations in the trend/pattern and the magnitudes of improvement between the simulated and “true” states (i.e., for soil moisture, snow water equivalent, and discharge) were satisfactory using the integrated assimilation, which suggests the reliability of SWAT-HDAS for regional hydrology studies. The streamflow assimilation experiment also showed that the observation location dramatically influences the assimilation efficiency. The quantity and quality of observations have effects of varying degrees on the streamflow predictions. SWAT-HDAS is a promising tool for hydrological studies and applications under climate and environmental change scenarios. © 2017. The Authors. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/75686
Appears in Collections: 影响、适应和脆弱性 气候变化与战略
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作者单位: Key Laboratory of Remote Sensing of Gansu Province, Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China; University of Chinese Academy of Sciences, Beijing, China; Key Laboratory of Western China's Environmental Systems (Ministry of Education), Lanzhou University, Lanzhou, China; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, China; CAS Center for Excellence in Tibetan Plateau Earth Sciences, Chinese Academy of Sciences, Beijing, China
Recommended Citation:
Zhang Y,, Hou J,, Gu J,et al. SWAT-Based Hydrological Data Assimilation System (SWAT-HDAS): Description and Case Application to River Basin-Scale Hydrological Predictions[J]. Journal of Advances in Modeling Earth Systems,2017-01-01,9(8)