Abstract

Quantifying river discharge is a critical component for hydrological studies, floodplain ecological conservation research, and water resources management. In recent years, a series of remote sensing-based discharge estimation methods have been developed. An example is the use of the near infrared (NIR) band of optical satellite images, with the principle of calculating the ratio between a stable land pixel for calibration (C) and a pixel within the river for measurement (M), applying a linear regression between C/M series and observed discharge series. This study trialed the C/M method, utilizing the Harmonized Landsat and Sentinel-2 (HLS) surface reflectance product on relatively small rivers with 30~100 m widths. Two study sites with different river characteristics and geographic settings in the Murray-Darling Basin (MDB) of Australia were selected as case studies. Two independent sets of HLS data and gauged discharge data for the 2017 and 2018 water years were acquired for modeling and validation, respectively. Results reveal high consistency between the HLS-derived discharge and gauged discharge at both sites. The Relative Root Mean Square Errors are 53% and 19%, and the Nash-Sutcliffe Efficiency coefficients are 0.24 and 0.69 for the two sites. This study supports the effectiveness of applying the fine-resolution HLS for modeling discharge on small rivers based on the C/M methodology, which also provides evidence of using multisource synthesized datasets as the input for discharge estimation.

Highlights

  • Quantifying river discharge is essential for both scientific and operational applications for water resources management [1]

  • The results based on the use of a Harmonized Landsat and Sentinel-2 product in this study suggest that blending multisource near infrared (NIR) bands from different sensors is feasible for discharge estimation by the C/M method

  • This study has demonstrated the feasibility of utilizing high spatial resolution and a high temporal resolution Harmonized Landsat and Sentinel-2 surface reflectance product to estimate river discharge for relatively small rivers with 30~100 m widths based on the C/M method

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Summary

Introduction

Quantifying river discharge is essential for both scientific and operational applications for water resources management [1]. River discharge estimation has relied on having a network of in situ gauge stations to measure river levels. Establishment of networks is expensive and requires maintenance, and there are many rivers in the world which are not gauged. This shortage in global discharge data can be partially compensated for by the use of remote sensing [2]. Relevant research both in theory and practice is continually promoting methods and applications of discharge estimation regionally and globally [3,4,5]

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