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Assessing the Impacts of Future Urban Development Patterns and Climate Changes on Total Suspended Sediment Loading in Surface Waters Using Geoinformatics

Y. C. Jordan1,A. Ghulam1*,M. L. Chu2

  1. Center for Sustainability at Saint Louis University, St. Louis, Missouri 63108, USA
  2. Agricultural and Biological Engineering, University of Illinois, Urbana-Champaign, Illinois 61820, USA

*Corresponding author. Tel: +1-314-9775156 Fax: Email:


Water pollution is a major global issue that has profound impact on sustainable development of our society. In this paper, land cover change trajectories of the study area over the last three decades are developed using Landsat data. Then historic land-cover and land-use change (LCLUC) patterns are used to estimate, calibrate and validate key drivers of land use change. Future likelihood of land-cover/land-use for 2021 and 2031 are simulated using state-of-art image processing techniques based on the driving factors of land use change integrated with Land Change Modeler. Hypothetical scenarios of LCLUC including a) low density of new urbanization growth and open land with vegetation cover, b) normal urbanization and, c) highly development of commercial/urban land use and impervious surfaces, are constructed during the simulations. The Soil and Water Assessment Tool (SWAT) is employed to generate total suspended sediment with the various combinations of three hypothetical scenarios mentioned above and climate change scenarios projected for 2021 and 2031. The future climate patterns for the periods of 2011-2021 and 2021-2031 are generated from the intergovernmental Panel on Climate Change (IPCC) Spatial Report for scenarios A1B, B1, and A2. A total of 19 SWAT models are generated, one for 2011, nine for 2021 and 2031 respectively. The results are then used to compare and identify the impacts of combined land use and climate change on surface water quality, to answer and confirm the hypothesis that urban sprawl developing patterns in the greater St. Louis region have significant impacts on surface water quality in specific way.

Keywords: land-cover and land-use change, remote sensing, water pollution, St. Louis metropolitan area

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