干旱区生态环境知识资源中心(Arid): Multi-source global wetland maps combining surface water imagery and groundwater constraints

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DOI	10.5194/essd-11-189-2019
	Multi-source global wetland maps combining surface water imagery and groundwater constraints
	Tootchi, Ardalan; Jost, Anne; Ducharne, Agnes
通讯作者	Tootchi, Ardalan
来源期刊	EARTH SYSTEM SCIENCE DATA
ISSN	1866-3508
EISSN	1866-3516
出版年	2019
卷号	11 期号:1 页码:189-220
英文摘要	Many maps of open water and wetlands have been developed based on three main methods: (i) compiling national and regional wetland surveys, (ii) identifying inundated areas via satellite imagery and (iii) delineating wetlands as shallow water table areas based on groundwater modeling. However, the resulting global wetland extents vary from 3% to 21% of the land surface area because of inconsistencies in wetland definitions and limitations in observation or modeling systems. To reconcile these differences, we propose composite wetland (CW) maps, combining two classes of wetlands: (1) regularly flooded wetlands (RFWs) obtained by overlapping selected open-water and inundation datasets; and (2) groundwater-driven wetlands (GDWs) derived from groundwater modeling (either direct or simplified using several variants of the topographic index). Wetlands are statically defined as areas with persistent near-saturated soil surfaces because of regular flooding or shallow groundwater, disregarding most human alterations (potential wetlands). Seven CW maps were generated at 15 arcsec resolution (ca. 500m at the Equator) using geographic information system (GIS) tools and by combining one RFW and different GDW maps. To validate this approach, these CW maps were compared with existing wetland datasets at the global and regional scales. The spatial patterns were decently captured, but the wetland extents were difficult to assess compared to the dispersion of the validation datasets. Compared with the only regional dataset encompassing both GDWs and RFWs, over France, the CW maps performed well and better than all other considered global wetland datasets. Two CW maps, showing the best overall match with the available evaluation datasets, were eventually selected. These maps provided global wetland extents of 27.5 and 29 million km(2), i.e., 21.1% and 21.6% of the global land area, which are among the highest values in the literature and are in line with recent estimates also recognizing the contribution of GDWs. This wetland class covers 15% of the global land area compared with 9.7% for RFW (with an overlap of ca. 3.4 %), including wetlands under canopy and/or cloud cover, leading to high wetland densities in the tropics and small scattered wetlands that cover less than 5% of land but are highly important for hydrological and ecological functioning in temperate to arid areas. By distinguishing the RFWs and GDWs based globally on uniform principles, the proposed dataset might be useful for large-scale land surface modeling (hydrological, ecological and biogeochemical modeling) and environmental planning. The dataset consisting of the two selected CW maps and the contributing GDW and RFW maps is available from PANGAEA at https://doi.org/10.1594/PANGAEA.892657 (Tootchi et al., 2018).
类型	Article
语种	英语
国家	France
开放获取类型	Green Submitted, gold
收录类别	SCI-E
WOS记录号	WOS:000458031000001
WOS关键词	HIGH-RESOLUTION ; INTERANNUAL VARIABILITY ; TOPOGRAPHIC INDEX ; SCALE ; COVER ; CLIMATE ; MODEL ; DYNAMICS ; ATMOSPHERE ; LAKES
WOS类目	Geosciences, Multidisciplinary ; Meteorology & Atmospheric Sciences
WOS研究方向	Geology ; Meteorology & Atmospheric Sciences
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/215101
作者单位	Sorbonne Univ, CNRS, EPHE, Milieux Environm Transferts & Interact Hydrosyst, F-75005 Paris, France
推荐引用方式 GB/T 7714	Tootchi, Ardalan,Jost, Anne,Ducharne, Agnes. Multi-source global wetland maps combining surface water imagery and groundwater constraints[J],2019,11(1):189-220.
APA	Tootchi, Ardalan,Jost, Anne,&Ducharne, Agnes.(2019).Multi-source global wetland maps combining surface water imagery and groundwater constraints.EARTH SYSTEM SCIENCE DATA,11(1),189-220.
MLA	Tootchi, Ardalan,et al."Multi-source global wetland maps combining surface water imagery and groundwater constraints".EARTH SYSTEM SCIENCE DATA 11.1(2019):189-220.