干旱区生态环境知识资源中心(Arid): Data-Driven Modeling and the Influence of Objective Function Selection on Model Performance in Limited Data Regions

Arid

DOI	10.3390/ijerph17114132
	Data-Driven Modeling and the Influence of Objective Function Selection on Model Performance in Limited Data Regions
	Baddoo, Thelma Dede 1,2; Li, Zhijia 2; Guan, Yiqing 2; Boni, Kenneth Rodolphe Chabi 3; Nooni, Isaac Kwesi 4,5
通讯作者	Baddoo, Thelma Dede
来源期刊	INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
EISSN	1660-4601
出版年	2020
卷号	17 期号:11
英文摘要	The identification of unit hydrographs and component flows from rainfall, evapotranspiration and streamflow data (IHACRES) model has been proven to be an efficient yet basic model to simulate rainfall-runoff processes due to the difficulty in obtaining the comprehensive data required by physical models, especially in data-scarce, semi-arid regions. The success of a calibration process is tremendously dependent on the objective function chosen. However, objective functions have been applied largely in over daily and monthly scales and seldom over sub-daily scales. This study, therefore, implements the IHACRES model using 'hydromad' in R to simulate flood events with data limitations in Zhidan, a semi-arid catchment in China. We apply objective function constraints by time aggregating the commonly used Nash-Sutcliffe efficiency into daily and hourly scales to investigate the influence of objective function constraints on the model performance and the general capability of the IHACRES model to simulate flood events in the study watershed. The results of the study demonstrated the advantage of the finer time-scaled hourly objective function over its daily counterpart in simulating runoff for the selected flood events. The results also indicated that the IHACRES model performed extremely well in the Zhidan watershed, presenting the feasibility of the use of the IHACRES model to simulate flood events in data scarce, semi-arid regions.
英文关键词	data-driven modeling objective function selection Zhidan watershed IHACRES hydromad China
类型	Article
语种	英语
国家	Peoples R China
开放获取类型	Green Published, gold
收录类别	SCI-E ; SSCI
WOS记录号	WOS:000542629600385
WOS关键词	RAINFALL-RUNOFF MODELS ; DATA TIME-STEP ; NEURAL-NETWORK ; GLOBAL OPTIMIZATION ; SENSITIVITY-ANALYSIS ; DATA QUALITY ; CALIBRATION ; PARAMETERS ; IHACRES ; PREDICTIONS
WOS类目	Environmental Sciences ; Public, Environmental & Occupational Health
WOS研究方向	Environmental Sciences & Ecology ; Public, Environmental & Occupational Health
来源机构	南京信息工程大学 ; 河海大学
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/319600
作者单位	1.Hohai Univ, Coll Hydrol & Water Resources, State Key Lab Hydrol Water Resources & Hydraul En, Nanjing 210098, Peoples R China; 2.Hohai Univ, Coll Hydrol & Water Resources, Nanjing 210098, Peoples R China; 3.Hohai Univ, Coll Comp & Informat Engn, Nanjing 211100, Peoples R China; 4.Nanjing Univ Informat Sci & Technol, Sch Geog Sci, Nanjing 210044, Peoples R China; 5.Nanjing Univ Informat Sci & Technol, Binjiang Coll, 333 Xishan Rd, Wuxi 214105, Jiangsu, Peoples R China
推荐引用方式 GB/T 7714	Baddoo, Thelma Dede,Li, Zhijia,Guan, Yiqing,et al. Data-Driven Modeling and the Influence of Objective Function Selection on Model Performance in Limited Data Regions[J]. 南京信息工程大学, 河海大学,2020,17(11).
APA	Baddoo, Thelma Dede,Li, Zhijia,Guan, Yiqing,Boni, Kenneth Rodolphe Chabi,&Nooni, Isaac Kwesi.(2020).Data-Driven Modeling and the Influence of Objective Function Selection on Model Performance in Limited Data Regions.INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH,17(11).
MLA	Baddoo, Thelma Dede,et al."Data-Driven Modeling and the Influence of Objective Function Selection on Model Performance in Limited Data Regions".INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 17.11(2020).