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Title: Modeling surface water dynamics in the Amazon Basin using MOSART-Inundation v1.0: Impacts of geomorphological parameters and river flow representation

Abstract

In the Amazon Basin, floodplain inundation is a key component of surface water dynamics and plays an important role in water, energy and carbon cycles. The Model for Scale Adaptive River Transport (MOSART) was extended with a macroscale inundation scheme for representing floodplain inundation. The extended model, named MOSART-Inundation, was used to simulate surface hydrology of the entire Amazon Basin. Previous hydrologic modeling studies in the Amazon Basin identified and addressed a few challenges in simulating surface hydrology of this basin, including uncertainties of floodplain topography and channel geometry, and the representation of river flow in reaches with mild slopes. This study further addressed four aspects of these challenges. First, the spatial variability of vegetation-caused biases embedded in the HydroSHEDS digital elevation model (DEM) data was explicitly addressed. A vegetation height map of about 1 km resolution and a land cover dataset of about 90 m resolution were used in a DEM correction procedure that resulted in an average elevation reduction of 13.2 m for the entire basin and led to evident changes in the floodplain topography. Second, basin-wide empirical formulae for channel cross-sectional dimensions were refined for various subregions to improve the representation of spatial variability in channel geometry.more » Third, the channel Manning roughness coefficient was allowed to vary with the channel depth, as the effect of riverbed resistance on river flow generally declines with increasing river size. Lastly, backwater effects were accounted for to better represent river flow in mild-slope reaches. The model was evaluated against in situ streamflow records and remotely sensed Envisat altimetry data and Global Inundation Extent from Multi-Satellites (GIEMS) inundation data. In a sensitivity study, seven simulations were compared to evaluate the impacts of the five modeling aspects addressed in this study. The comparisons showed that representing floodplain inundation could significantly improve the simulated streamflow and river stages. Refining floodplain topography, channel geometry and Manning roughness coefficients, as well as accounting for backwater effects had notable impacts on the simulated surface water dynamics in the Amazon Basin. As a result, the understanding obtained in this study could be helpful in improving modeling of surface hydrology in basins with evident inundation, especially at regional to continental scales.« less

Authors:
ORCiD logo [1];  [2];  [1];  [1]; ORCiD logo [3];  [4];  [5]
  1. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  2. Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Montana State Univ., Bozeman, MT (United States)
  3. NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States)
  4. Univ. de Toulouse, Toulouse (France); IISc-NIO-IITM-IRD Joint International Lab., Bangalore (India)
  5. Univ. of California, Santa Barbara, CA (United States)
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1348057
Alternate Identifier(s):
OSTI ID: 1349164
Report Number(s):
PNNL-SA-119428
Journal ID: ISSN 1991-9603; KP1703020
Grant/Contract Number:  
AC05-76RL01830; KP1703020
Resource Type:
Journal Article: Published Article
Journal Name:
Geoscientific Model Development (Online)
Additional Journal Information:
Journal Name: Geoscientific Model Development (Online); Journal Volume: 10; Journal Issue: 3; Journal ID: ISSN 1991-9603
Publisher:
European Geosciences Union
Country of Publication:
United States
Language:
English
Subject:
58 GEOSCIENCES; inundation; modeling; Amazon Basin; geomorphology; DEM; channel cross-sectional geometry; manning roughness coefficient; backwater effects

Citation Formats

Luo, Xiangyu, Li, Hong -Yi, Leung, L. Ruby, Tesfa, Teklu K., Getirana, Augusto, Papa, Fabrice, and Hess, Laura L. Modeling surface water dynamics in the Amazon Basin using MOSART-Inundation v1.0: Impacts of geomorphological parameters and river flow representation. United States: N. p., 2017. Web. doi:10.5194/gmd-10-1233-2017.
Luo, Xiangyu, Li, Hong -Yi, Leung, L. Ruby, Tesfa, Teklu K., Getirana, Augusto, Papa, Fabrice, & Hess, Laura L. Modeling surface water dynamics in the Amazon Basin using MOSART-Inundation v1.0: Impacts of geomorphological parameters and river flow representation. United States. doi:10.5194/gmd-10-1233-2017.
Luo, Xiangyu, Li, Hong -Yi, Leung, L. Ruby, Tesfa, Teklu K., Getirana, Augusto, Papa, Fabrice, and Hess, Laura L. Thu . "Modeling surface water dynamics in the Amazon Basin using MOSART-Inundation v1.0: Impacts of geomorphological parameters and river flow representation". United States. doi:10.5194/gmd-10-1233-2017.
@article{osti_1348057,
title = {Modeling surface water dynamics in the Amazon Basin using MOSART-Inundation v1.0: Impacts of geomorphological parameters and river flow representation},
author = {Luo, Xiangyu and Li, Hong -Yi and Leung, L. Ruby and Tesfa, Teklu K. and Getirana, Augusto and Papa, Fabrice and Hess, Laura L.},
abstractNote = {In the Amazon Basin, floodplain inundation is a key component of surface water dynamics and plays an important role in water, energy and carbon cycles. The Model for Scale Adaptive River Transport (MOSART) was extended with a macroscale inundation scheme for representing floodplain inundation. The extended model, named MOSART-Inundation, was used to simulate surface hydrology of the entire Amazon Basin. Previous hydrologic modeling studies in the Amazon Basin identified and addressed a few challenges in simulating surface hydrology of this basin, including uncertainties of floodplain topography and channel geometry, and the representation of river flow in reaches with mild slopes. This study further addressed four aspects of these challenges. First, the spatial variability of vegetation-caused biases embedded in the HydroSHEDS digital elevation model (DEM) data was explicitly addressed. A vegetation height map of about 1 km resolution and a land cover dataset of about 90 m resolution were used in a DEM correction procedure that resulted in an average elevation reduction of 13.2 m for the entire basin and led to evident changes in the floodplain topography. Second, basin-wide empirical formulae for channel cross-sectional dimensions were refined for various subregions to improve the representation of spatial variability in channel geometry. Third, the channel Manning roughness coefficient was allowed to vary with the channel depth, as the effect of riverbed resistance on river flow generally declines with increasing river size. Lastly, backwater effects were accounted for to better represent river flow in mild-slope reaches. The model was evaluated against in situ streamflow records and remotely sensed Envisat altimetry data and Global Inundation Extent from Multi-Satellites (GIEMS) inundation data. In a sensitivity study, seven simulations were compared to evaluate the impacts of the five modeling aspects addressed in this study. The comparisons showed that representing floodplain inundation could significantly improve the simulated streamflow and river stages. Refining floodplain topography, channel geometry and Manning roughness coefficients, as well as accounting for backwater effects had notable impacts on the simulated surface water dynamics in the Amazon Basin. As a result, the understanding obtained in this study could be helpful in improving modeling of surface hydrology in basins with evident inundation, especially at regional to continental scales.},
doi = {10.5194/gmd-10-1233-2017},
journal = {Geoscientific Model Development (Online)},
number = 3,
volume = 10,
place = {United States},
year = {Thu Mar 23 00:00:00 EDT 2017},
month = {Thu Mar 23 00:00:00 EDT 2017}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record at 10.5194/gmd-10-1233-2017

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Cited by: 3 works
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