Improving the catchment scale wetland modeling using remotely sensed data

被引:23
|
作者
Lee, S. [1 ,2 ]
Yeo, I-Y [3 ,4 ]
Lang, M. W. [4 ,5 ]
McCarty, G. W. [2 ]
Sadeghi, A. M. [2 ]
Sharifi, A. [6 ]
Jin, H. [4 ]
Liu, Y. [7 ]
机构
[1] Univ Maryland, Dept Environm Sci & Technol, College Pk, MD 20742 USA
[2] USDA ARS, Hydrol & Remote Sensing Lab, Beltsville, MD 20705 USA
[3] Univ Newcastle, Sch Engn, Callaghan, NSW 2308, Australia
[4] Univ Maryland, Dept Geog Sci, College Pk, MD 20742 USA
[5] US Fish & Wildlife Serv, Natl Wetland Inventory, Falls Church, VA 22041 USA
[6] Govt Dist Columbia, Dept Energy & Environm, Washington, DC 20002 USA
[7] Univ Guelph, Dept Geog, Guelph, ON N1G 2W1, Canada
基金
美国国家航空航天局;
关键词
Wetland-watershed modeling approach; Inundation maps; Wetland inundation; Soil and Water Assessment Tool (SWAT); GEOGRAPHICALLY ISOLATED WETLANDS; MID-ATLANTIC REGION; WATER-QUALITY; SWAT MODEL; RIPARIAN ZONE; RIVER-BASIN; SIMULATION; RESTORATION; LIDAR; CONNECTIVITY;
D O I
10.1016/j.envsoft.2017.11.001
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This study presents an integrated wetland-watershed modeling approach that capitalizes on inundation maps and geospatial data to improve spatial prediction of wetland inundation and assess its prediction uncertainty. We outline problems commonly arising from data preparation and parameterization used to simulate wetlands within a (semi-) distributed watershed model. We demonstrate how wetland inundation can be better captured by the wetland parameters developed from remotely sensed data. We then emphasize assessing model prediction using inundation maps derived from remotely sensed data. This integrated modeling approach is tested using the Soil and Water Assessment Tool (SWAT) with an improved riparian wetlands (RWs) extension, for an agricultural watershed in the Mid-Atlantic Coastal Plain, US. This study illustrates how spatially distributed information is necessary to predict inundation of wetlands and hydrologic function at the local landscape scale, where monitoring and conservation decision making take place. (c) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页数:19
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