4.7 Article

Leveraging River Network Topology and Regionalization to Expand SWOT-Derived River Discharge Time Series in the Mississippi River Basin

Journal

REMOTE SENSING
Volume 13, Issue 8, Pages -

Publisher

MDPI
DOI: 10.3390/rs13081590

Keywords

discharge; drainage area ratio; regionalization; urbanization; hydrology; remote sensing; surface water and ocean topography

Funding

  1. National Science Foundation Graduate Research Fellowship Program [1451070]
  2. Division Of Graduate Education
  3. Direct For Education and Human Resources [1451070] Funding Source: National Science Foundation

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The SWOT mission will measure river discharges but lacks temporal and spatial uniformity. The drainage area ratio method is not applicable for the observable river network in the Mississippi River basin, with limitations such as cumulative urban area and number of dams affecting its efficiency.
The upcoming Surface Water and Ocean Topography (SWOT) mission will measure rivers wider than 50-100 m using a 21-day orbit, providing river reach derived discharges that can inform applications like flood forecasting and large-scale hydrologic modelling. However, these discharges will not be uniform in time or coincident with those of neighboring reaches. It is often assumed discharge upstream and downstream of a river location are highly correlated in natural conditions and can be transferred using a scaling factor like the drainage area ratio between locations. Here, the applicability of the drainage area ratio method to integrate, in space and time, SWOT-derived discharges throughout the observable river network of the Mississippi River basin is assessed. In some cases, area ratios ranging from 0.01 to 100 can be used, but cumulative urban area and/or the number of dams/reservoirs between locations decrease the method's applicability. Though the mean number of SWOT observations for a given reach increases by 83% and the number of peak events captured increases by 100%, expanded SWOT sampled time series distributions often underperform compared to the original SWOT sampled time series for significance tests and quantile results. Alternate expansion methods may be more viable for future work.

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