Semi-analytical prediction of Secchi depth using remote-sensing reflectance for lakes with a wide range of turbidity
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It is crucial to monitor light environments in large lakes using satellite remote-sensing data. Many studies have proposed prediction schemes of transparency information, but most of them were site-specific. Here, we applied semi-analytical retrieval procedures of inherent optical properties from in situ-measured remote-sensing reflectance and then predicted the Secchi depth (SD) using contrast transmittance theory. Two types of water regions (clear or turbid waterbodies) were first classified based on spectral characteristics, and a selection from two retrieval procedures for clear and turbid water bodies was made. The relationship between the SD and the sum of attenuation coefficients (beam and diffuse attenuation coefficients), which arises in contrast transmittance theory, was determined by analyzing the data from the previous research. The predicted SD values were compared with the observed values in 10 Japanese lakes with a wide variety of turbidity (SD 0.4–17 m). Fairly good agreement between the predicted and observed SD values was obtained, indicating the usefulness of this prediction scheme. We then made an accuracy comparison with the results obtained by previous studies, and we discuss the coefficients and the discrepancies between the measured and predicted SD values in addition to the future directions of this approach.
KeywordsSecchi depth Lakes Remote sensing Semi-analytical prediction Hybrid model
This research was supported in part by Grants-in Aid for Scientific Research from the Ministry of Education, Culture, Sport, Science and Technology (MEXT), Japan (Nos. 23404015 and 25420555), the Global Environment Research Fund (S9-4) of the Ministry of Environment, Japan, and the River Fund (27-1271-001) in charge of The River Foundation, Japan. We express our appreciation to two anonymous reviewers for constructive criticisms on an earlier version of the manuscript.
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