Affiliation:
1. Chinese Academy of Sciences
2. University of Chinese Academy of Sciences
3. Liaocheng University
Abstract
The Trophic state index (TSI) is a vital parameter for aquatic
ecosystem assessment. Estimating TSI by remote sensing is still a
challenge due to the multivariate complexity of the eutrophication
process. A comprehensive in situ
spectral-biogeochemical dataset for 7 lakes in Northeast China was
collected in October 2020. The dataset covers trophic states from
oligotrophic to eutrophic, with a wide range of total phosphorus (TP,
0.07–0.2 mg L−1), Secchi disk depth (SDD, 0.1–0.78 m), and
chlorophyll a (Chla, 0.11–20.41 μg L−1). Here, we propose
an empirical method to estimate TSI from remote sensing data. First,
TP, SDD, and Chla were estimated by band ratio/band combination
models. Then TSI was estimated using the Carlson model with a high
R2 (0.88), a low RMSE (3.87), and a low MRE (6.83%).
Synergistic effects between TP, SDD, and Chla dominated the trophic
state, changed the distribution of light in the water column, affected
the spectral characteristics. Furthermore, the contribution of each
parameter for eutrophication were different among the studied lakes
from ternary plot. High Chla concentration was the main reason for
eutrophication in HMT Lake with 45.4% of contribution more than the
other two parameters, However, in XXK Lake, high TP concentrations
were the main reason for eutrophication with 66.8% of contribution
rather than Chla and SDD. Overall, the trophic state was dominated by
TP, and SDD accounted for 85.6% of contribution in all sampled lakes.
Additionally, we found using one-parameter index to evaluate the lake
trophic state will lead to a great deviation, even with two levels of
difference. Therefore, multi-parameter TSI is strongly recommended for
the lake trophic state assessment. Summarily, our findings provide a
theoretical and methodological basis for future large-scale
estimations of lake TSI using satellite image data, help with water
quality monitoring and management.
Funder
National Key Research and Development
Program of China
National Natural Science Foundation of
China
Science and Technology Development
Project in Jilin, China
the Special Research Assistant Project of
Chinese Academy of Sciences granted to Dr. Yingxin
Shang
Heilongjiang Provincial Natural Science
Foundation of China
Subject
Atomic and Molecular Physics, and Optics
Cited by
7 articles.
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