干旱区生态环境知识资源中心(Arid): Assessment of CHADFDM satellite-based input dataset for the groundwater recharge estimation in arid and data scarce regions

Arid

DOI	10.1002/hyp.14250
	Assessment of CHADFDM satellite-based input dataset for the groundwater recharge estimation in arid and data scarce regions
	Salehi Siavashani, Nafiseh; Jimenez-Martinez, Joaquin; Vaquero, Guillermo; Elorza, Francisco J.; Sheffield, Justin; Candela, Lucila; Serrat-Capdevila, Aleix
通讯作者	Siavashani, NS (corresponding author), Tech Univ Catalonia, Dept Civil & Environm Engn, Barcelona, Spain.
来源期刊	HYDROLOGICAL PROCESSES
ISSN	0885-6087
EISSN	1099-1085
出版年	2021
卷号	35 期号:6
英文摘要	Aquifer natural recharge estimations are a prerequisite for understanding hydrologic systems and sustainable water resources management. As meteorological data series collection is difficult in arid and semiarid areas, satellite products have recently become an alternative for water resources studies. A daily groundwater recharge estimation in the NW part of the Lake Chad Basin, using a soil-plant-atmosphere model (VisualBALAN), from ground- and satellite-based meteorological input dataset for non-irrigated and irrigated land and for the 2005-2014 period is presented. Average annual values were 284 mm and 30 degrees C for precipitation and temperature in ground-based gauge stations. For the satellite-model-based Lake Chad Basin Flood and Drought Monitor System platform (CHADFDM), average annual precipitation and temperature were 417 mm and 29 degrees C, respectively. Uncertainties derived from satellite data measurement could account for the rainfall difference. The estimated mean annual aquifer recharge was always higher from satellite- than ground-based data, with differences up to 46% for dryland and 23% in irrigated areas. Recharge response to rainfall events was very variable and results were very sensitive to: wilting point, field capacity and curve number for runoff estimation. Obtained results provide plausible recharge values beyond the uncertainty related to data input and modelling approach. This work prevents on the important deviations in recharge estimation from weighted-ensemble satellite-based data, informing in decision making to both stakeholders and policy makers.
英文关键词	CHADFDM data set ground-satellite meteorological data groundwater recharge modelling Lake Chad Basin
类型	Article
语种	英语
开放获取类型	Green Published, hybrid
收录类别	SCI-E
WOS记录号	WOS:000667549500012
WOS关键词	WATER-RESOURCES ; POTENTIAL EVAPOTRANSPIRATION ; GRIDDED PRECIPITATION ; RAINFALL ; BASIN ; IRRIGATION ; GAUGE ; SYSTEM ; SPACE
WOS类目	Water Resources
WOS研究方向	Water Resources
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/368713
作者单位	[Salehi Siavashani, Nafiseh] Tech Univ Catalonia, Dept Civil & Environm Engn, Barcelona, Spain; [Salehi Siavashani, Nafiseh; Vaquero, Guillermo; Candela, Lucila] IMDEA Agua, Alcala De Henares, Spain; [Salehi Siavashani, Nafiseh; Vaquero, Guillermo] Fdn Gomez Pardo, Madrid, Spain; [Jimenez-Martinez, Joaquin] Eawag, Dept Water Resources & Drinking Water, Dubendorf, Switzerland; [Jimenez-Martinez, Joaquin] Swiss Fed Inst Technol, Dept Civil Environm & Geomat Engn, Zurich, Switzerland; [Elorza, Francisco J.] Tech Univ Madrid, Sch Min & Energy Engn, Madrid, Spain; [Sheffield, Justin] Univ Southampton, Dept Geog, Southampton, Hants, England; [Serrat-Capdevila, Aleix] World Bank, Water Global Practice, 1818 H St NW, Washington, DC 20433 USA
推荐引用方式 GB/T 7714	Salehi Siavashani, Nafiseh,Jimenez-Martinez, Joaquin,Vaquero, Guillermo,et al. Assessment of CHADFDM satellite-based input dataset for the groundwater recharge estimation in arid and data scarce regions[J],2021,35(6).
APA	Salehi Siavashani, Nafiseh.,Jimenez-Martinez, Joaquin.,Vaquero, Guillermo.,Elorza, Francisco J..,Sheffield, Justin.,...&Serrat-Capdevila, Aleix.(2021).Assessment of CHADFDM satellite-based input dataset for the groundwater recharge estimation in arid and data scarce regions.HYDROLOGICAL PROCESSES,35(6).
MLA	Salehi Siavashani, Nafiseh,et al."Assessment of CHADFDM satellite-based input dataset for the groundwater recharge estimation in arid and data scarce regions".HYDROLOGICAL PROCESSES 35.6(2021).