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With fast population growth and economic development in the US-Mexico Borderland, water diversion and usages has reduced the flow substantially in the Low Rio Grande River (LRGR). Tidal portion of the LRGR has posed an environmental drought issue since 1993 and the channel clogged with the invasion of non-native plants also causes environmental problems. As a result of the intensity of these natural and manmade factors, the Rio Grande stopped flowing to the sea in February 2001. The flows were reduced to a point that they were unable to push out the sand deposited at the mouth. Geomorphologic evolution in association with the fluvial process of the LRGR has received wide attention. The purpose of this study is to investigate the necessary flow to maintain the river mouth open to the Gulf of Mexico using integrated approach of remote sensing and numerical analysis. It also sheds lights on possible solutions in decision-making. The analysis starts with a geomorphologic analysis using satellite remote sensing imagery and historic flow rate assessment, followed by a two-dimensional, depth averaged, finite element numerical modeling analysis to simulate the hydrodynamics of the tidal portion of the LRGR. While Landsat 7 Enhanced Thematic Mapper Plus (ETM+) satellite imagery and Digital Orthophoto Quadrangles (DOQs) were used for the geomorphologic investigation, Research Management Associates (RMA-2) software and Surface Water Modeling System (SMS 8.0) were used for minimum stream flow rate analysis. Alternative geomorphic conditions were modeled and compared to the original case, where two simulation runs were established. The first one was designed in dealing with a more refined mesh; and the second was prepared for handling an increased discharge at the inflow boundary along with the investigation of shear stress. The study concludes that the peak shear stress increased with increasing discharge towards the mouth of the river and a 1.27 m3/s discharge is necessary to maintain the opening of the river mouth.


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Journal of Environmental Informatics





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