Fourteen-Year Record (2000–2013) of the Spatial and Temporal Dynamics of Floating Algae Blooms in Lake Chaohu, Observed from Time Series of MODIS Images

Zhang, Yuchao; Ma, Ronghua; Zhang, Min; Duan, Hongtao; Loiselle, Steven; Xu, Jinduo

doi:10.3390/rs70810523

Cited by 106 publications

(48 citation statements)

References 42 publications

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“…Of these, FAI was found to be more tolerant than other indexes to changes in observing conditions (solar/viewing geometry, aerosols, etc. ), thus more appropriate for quantitative analysis and time‐series studies (Hu et al ; Shang et al ; Zhang et al ). Therefore, following the concept of FAI used for MODIS to quantify cyanobacteria blooms in Taihu Lake (Hu et al ), the lack of a shortwave infrared (SWIR) band on GOCI is remedied by an alternative FAI (AFAI) to replace the SWIR band with an NIR band:

AFAI = R_{rc,}_{λ 2} - R_{rc,}_{λ 2^{'}}

R_{rc, λ 2^{'}} = R_{rc,}_{λ 1} + (R_{rc,}_{λ 3} - R_{rc,}_{λ 1}) \times (λ_{2} - λ_{1}) / (λ_{3} - λ_{1}),

…”

Section: Methodsmentioning

confidence: 99%

Diurnal changes of cyanobacteria blooms in Taihu Lake as derived from GOCI observations

Visser

et al. 2018

Limnology & Oceanography

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Using frequent and long‐term measurements (eight times per day, 2011 to present) from a geostationary satellite sensor (Geostationary Ocean Color Imager, GOCI), this study investigates diurnal changes of cyanobacterium Microcystis aeruginosa blooms (near‐surface high concentrations or surface scums) in Taihu Lake, from which vertical migration patterns could be inferred. After proper atmospheric correction, a cyanobacterial index algorithm is used to quantify equivalent surface cyanobacterial density (σ, 0–100%) at both pixel and synoptic scales from each cloud‐free image, followed by analysis of diurnal changing patterns of σ at both scales. Three typical diurnal changing patterns are identified from all images, which show distinctive and different seasonality from the long‐term statistics. Spatial distributions of the “hotspot” regions where diurnal changes are most often observed have also been established. While the seasonality of the three patterns appears to be a result of seasonality in both temperature and light availability, large blooms only occur 1 d after major wind events. Based on several lines of evidence, we hypothesize that the diurnal changes of such observed surface bloom patterns are likely a result of vertical migration rather than horizontal dissipation/aggregation of cyanobacteria. The mean migration speeds inferred from either a simple model or a radiative transfer model (< 0.03 cm s−1 or < 1 m h−1) are consistent with those reported earlier from laboratory measurements for certain cyanobacteria colony sizes. Complete understanding of the three types of diurnal patterns and direct validation of the hypothesis, however, require further investigations from field measurements.

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AFAI = R_{rc,}_{λ 2} - R_{rc,}_{λ 2^{'}}

R_{rc, λ 2^{'}} = R_{rc,}_{λ 1} + (R_{rc,}_{λ 3} - R_{rc,}_{λ 1}) \times (λ_{2} - λ_{1}) / (λ_{3} - λ_{1}),

…”

Section: Methodsmentioning

confidence: 99%

Diurnal changes of cyanobacteria blooms in Taihu Lake as derived from GOCI observations

Visser

et al. 2018

Limnology & Oceanography

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“…The average trophic state index (TSI) during 1984-2003 in Lake Chaohu was 74.6, indicating a eutrophic state in the lake ecosystem (Shang & Shang, 2007). The estimated coverage of the summer blooms of cyanobacteria was approximately 30% of the surface area on average during summer period in 2012 (Zhang et al, 2015b). These records above substantiated the and TP (c) (t yr À1 ) from 1953 to 2012 in Lake Chaohu, along with the fraction of loadings from point and nonpoint sources (%).…”

Section: Study Sitementioning

confidence: 99%

Hydrological regulation drives regime shifts: evidence from paleolimnology and ecosystem modeling of a large shallow Chinese lake

Kong

Yang

et al. 2016

Global Change Biology

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Quantitative evidence of sudden shifts in ecological structure and function in large shallow lakes is rare, even though they provide essential benefits to society. Such 'regime shifts' can be driven by human activities which degrade ecological stability including water level control (WLC) and nutrient loading. Interactions between WLC and nutrient loading on the long-term dynamics of shallow lake ecosystems are, however, often overlooked and largely underestimated, which has hampered the effectiveness of lake management. Here, we focus on a large shallow lake (Lake Chaohu) located in one of the most densely populated areas in China, the lower Yangtze River floodplain, which has undergone both WLC and increasing nutrient loading over the last several decades. We applied a novel methodology that combines consistent evidence from both paleolimnological records and ecosystem modeling to overcome the hurdle of data insufficiency and to unravel the drivers and underlying mechanisms in ecosystem dynamics. We identified the occurrence of two regime shifts: one in 1963, characterized by the abrupt disappearance of submerged vegetation, and another around 1980, with strong algal blooms being observed thereafter. Using model scenarios, we further disentangled the roles of WLC and nutrient loading, showing that the 1963 shift was predominantly triggered by WLC, whereas the shift ca. 1980 was attributed to aggravated nutrient loading. Our analysis also shows interactions between these two stressors. Compared to the dynamics driven by nutrient loading alone, WLC reduced the critical P loading and resulted in earlier disappearance of submerged vegetation and emergence of algal blooms by approximately 26 and 10 years, respectively. Overall, our study reveals the significant role of hydrological regulation in driving shallow lake ecosystem dynamics, and it highlights the urgency of using multi-objective management criteria that includes ecological sustainability perspectives when implementing hydrological regulation for aquatic ecosystems around the globe.

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“…Many studies have developed models from both broad band and narrow band multispectral satellite sensors to predict Chl-a concentrations for inland waters, but the models and the corresponding parameters can only be applied to the very few images under study and cannot be used on other images [5][6][7][8]. A few studies have produced historical Chl-a concentration values and bloom maps using Landsat [9][10][11][12], MERIS [13,14], MODIS [15], suggesting satellite remote sensing is promising for the retrieval of historic lake environmental parameters. Among them, Landsat series images provide the longest observation record of the earth surface free of charge with a spatial resolution of 30 meters [16,17].…”

Section: Introductionmentioning

confidence: 99%

A 30-Year Assessment of Phytoplankton Blooms in Erhai Lake Using Landsat Imagery: 1987 to 2016

Tan

Liu

et al. 2017

Remote Sensing

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Long-term information of phytoplankton bloom is critical for assessing the processes driving blooms in lakes. A three-decade survey of the phytoplankton blooms was completed for Erhai Lake from 1987 to 2016 with Landsat imagery. A modified three-band model using Landsat broad bands is developed by comparing reflectance data from Landsat imagery to two field datasets. The model is applied to the archived imagery to predict chlorophyll-a (Chl-a). Predicted ln(Chl-a) and observed ln(Chl-a) measurements are significantly correlated (R 2 = 0.70; RMSE = 0.13 µg/L). Bloom maps are generated by identifying Landsat pixels that have Chl-a concentrations larger than 20 µg/L as bloom area. Bloom extent and magnitude are estimated. Our study reveals that algal blooms first occurred in 1996 with a bloom area of 150 km 2 . Bloom occurred frequently from 2002 to 2016, with extreme blooms in 2003, 2013 and 2016. Algal blooms were mostly distributed in the northern and southern part of the lake. The proposed method uses one model for all Landsat images for Erhai Lake and can predict past blooms and extend the record to early years when field data is not available. The bloom extent and magnitude produced in this study can be used as the basis for the understanding of the processes that control the bloom outbreak.

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Fourteen-Year Record (2000–2013) of the Spatial and Temporal Dynamics of Floating Algae Blooms in Lake Chaohu, Observed from Time Series of MODIS Images

Cited by 106 publications

References 42 publications

Diurnal changes of cyanobacteria blooms in Taihu Lake as derived from GOCI observations

Diurnal changes of cyanobacteria blooms in Taihu Lake as derived from GOCI observations

Hydrological regulation drives regime shifts: evidence from paleolimnology and ecosystem modeling of a large shallow Chinese lake

A 30-Year Assessment of Phytoplankton Blooms in Erhai Lake Using Landsat Imagery: 1987 to 2016

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