Background
Type: Article

Improving the catchment scale wetland modeling using remotely sensed data

Journal: Environmental Modelling and Software (13648152)Year: 2019/12/01Volume: 122Issue:
Lee S.Yeo I.-Y.Lang M.W.McCarty G.W.Sadeghi A.aSharifi, Amirreza
BronzeDOI:10.1016/j.envsoft.2017.11.001Language: English

Abstract

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. © 2017 Elsevier Ltd


Author Keywords

Inundation mapsSoil and Water Assessment Tool (SWAT)Wetland inundationWetland-watershed modeling approach

Other Keywords

Atlantic Coastal PlainUnited StatesCatchmentsDecision makingFloodsForecastingRemote sensingUncertainty analysisWatershedsAgricultural watershedsDistributed informationDistributed watershed modelsIntegrated modeling approachesInundation mapsPrediction uncertaintySoil and water assessment toolWatershed modelingcatchmentenvironmental monitoringgeological mappingsatellite datasubmergencewetlandWetlands