Modeling River Discharge Using Automated River Width Measurements Derived from Sentinel-1 Time Series

David Mengen,Lars Ribbe,Patrick Leinenkugel,Marco Ottinger

doi:10.3390/rs12193236

Abstract

Against the background of a worldwide decrease in the number of gauging stations, the estimation of river discharge using spaceborne data is crucial for hydrological research, river monitoring, and water resource management. Based on the at-many-stations hydraulic geometry (AMHG) concept, a novel approach is introduced for estimating river discharge using Sentinel-1 time series within an automated workflow. By using a novel decile thresholding method, no a priori knowledge of the AMHG function or proxy is used, as proposed in previous literature. With a relative root mean square error (RRMSE) of 19.5% for the whole period and a RRMSE of 15.8% considering only dry seasons, our method is a significant improvement relative to the optimized AMHG method, achieving 38.5% and 34.5%, respectively. As the novel approach is embedded into an automated workflow, it enables a global application for river discharge estimation using solely remote sensing data. Starting with the mapping of river reaches, which have large differences in river width over the year, continuous river width time series are created using high-resolution and weather-independent SAR imaging. It is applied on a 28 km long section of the Mekong River near Vientiane, Laos, for the period from 2015 to 2018.

Highlights

The majority of today’s global population lives in close proximity to a river, as they are a crucial resource for fresh water, agriculture, or industrial development, as well as being the source of religious and cultural values [1,2,3,4]
The method was tested for multiple rivers with up to 20 Landsat-5 TM images with relative root mean square error (RRMSE) ranging between 20% to 30% and they proposed to use a proxy of −0.3 for the slope and −0.3 times the mean of all observed river widths as the intercept for the at-many-stations hydraulic geometry (AMHG) function to estimate the discharge without using any in situ data [18,24]
We present a novel framework for estimating river discharge using river width measurements, Sentinel-1 SAR time series data and a priori knowledge on minimum and maximum discharge

Summary

Introduction

The majority of today’s global population lives in close proximity to a river, as they are a crucial resource for fresh water, agriculture, or industrial development, as well as being the source of religious and cultural values [1,2,3,4]. The number of gauging stations has decreased in the past on a global scale, which is severe in front of hydrological regimes that have changed considerably in recent years or will do so in the future as a result of climate change [6,7] In this regard, new ways and technologies need to be found and applied for measuring hydrological parameters [8]. Using multiple earth-observation data sources, Stisen et al [9] proposed a distributed hydrological model, driven solely by remote sensing data. Another way is to obtain hydraulic river parameters (e.g., river width, slope and stage) from satellite images in order to estimate the discharge [14,15,16,17,18,19,20]. The method was tested for multiple rivers with up to 20 Landsat-5 TM images with RRMSE ranging between 20% to 30% and they proposed to use a proxy of −0.3 for the slope and −0.3 times the mean of all observed river widths as the intercept for the AMHG function to estimate the discharge without using any in situ data [18,24]

Methods

Results

Conclusion