کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6345461 | 1621221 | 2016 | 18 صفحه PDF | دانلود رایگان |
- MODIS and satellite altimetry data are used to estimate river discharge.
- A global evaluation was done for 8 continental rivers showing high accuracy.
- Using both river stage and effective width records can improve discharge estimates.
- The new method outperforms previously established multi-variate method.
Rivers act as a source of fresh water for terrestrial life, yet the discharges are poorly documented since the existing direct observations are inadequate and some observation stations have been interrupted or discontinued. Discharge estimates using remote sensing thus have a great potential to supplement ground observations. There are remote sensing methods established to estimate discharge based on single parameter derived relationships; however, they are limited to specific sections due to their empirical nature. In this study, we propose an innovative method to estimate daily discharges for continental rivers (with river channel widths >Â 800Â m (Birkett and Beckley, 2010)) using two satellite derived parameters. Multiple satellite altimetry data and Moderate Resolution Imaging Spectroradiometer (MODIS) data are used to provide a time series of river stages and effective river width. The derived MODIS and altimetry data are then used to optimize unknown parameters in a modified Manning's equation. In situ measurements are used to derive rating curves and to provide assessments of the estimated results. The Nash-Sutcliffe efficiency values for the estimates are between 0.60 and 0.97, indicating the power of the method and accuracy of the estimations. A comparison with a previously developed empirical multivariate equation for estimating river discharge shows that our method produces superior results, especially for large rivers. Furthermore, we found that discharge estimates using both effective river width and stage information consistently outperform those that only use stage data.
Journal: Remote Sensing of Environment - Volume 179, 15 June 2016, Pages 36-53