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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/hessd-4-1-2007
© Author(s) 2007. This work is licensed under
the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.
https://doi.org/10.5194/hessd-4-1-2007
© Author(s) 2007. This work is licensed under
the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.

  10 Jan 2007

10 Jan 2007

Review status
This discussion paper is a preprint. It has been under review for the journal Hydrology and Earth System Sciences (HESS). A final paper in HESS is not foreseen.

A multitemporal remote sensing approach to parsimonious streamflow modeling in a southcentral Texas watershed, USA

B. P. Weissling1,2, H. Xie1, and K. E. Murray1 B. P. Weissling et al.
  • 1Department of Earth and Environmental Sciences, University of Texas San Antonio, 6900 N. Loop 1604 West, San Antonio, Texas, 78249, USA
  • 2SWCA Environmental Consultants, 6200 UTSA Boulevard, Suite 102, San Antonio, Texas, 78249, USA

Abstract. Soil moisture condition plays a vital role in a watershed's hydrologic response to a precipitation event and is thus parameterized in most, if not all, rainfall-runoff models. Yet the soil moisture condition antecedent to an event has proven difficult to quantify both spatially and temporally. This study assesses the potential to parameterize a parsimonious streamflow prediction model solely utilizing precipitation records and multi-temporal remotely sensed biophysical variables (i.e.~from Moderate Resolution Imaging Spectroradiometer (MODIS)/Terra satellite). This study is conducted on a 1420 km2 rural watershed in the Guadalupe River basin of southcentral Texas, a basin prone to catastrophic flooding from convective precipitation events. A multiple regression model, accounting for 78% of the variance of observed streamflow for calendar year 2004, was developed based on gauged precipitation, land surface temperature, and enhanced vegetation Index (EVI), on an 8-day interval. These results compared favorably with streamflow estimations utilizing the Natural Resources Conservation Service (NRCS) curve number method and the 5-day antecedent moisture model. This approach has great potential for developing near real-time predictive models for flood forecasting and can be used as a tool for flood management in any region for which similar remotely sensed data are available.

B. P. Weissling et al.
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Interactive discussion
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
B. P. Weissling et al.
B. P. Weissling et al.
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