Guangwei Zhu

Nanjing Institute of Geography and Limnology

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Yunlin Zhang

Nanjing Institute of Geography and Limnology

Boqiang Qin

Nanjing Institute of Geography and Limnology

Kun� Shi

Nanjing Institute of Geography and Limnology

Wei Zou

Chinese Academy of Sciences

Mengyuan Zhu

Northeast Institute of Geography and Agroecology

Hai Xu

Chinese Academy of Sciences

Guang Gao

Nanjing Institute of Geography and Limnology

Huiyun Li

Shenzhen Institutes of Advanced Technology

Yongqiang Zhou

Nanjing Institute of Geography and Limnology

Yibo Zhang

Nanjing Institute of Geography and Limnology

Cooperative Institutions

Chinese Academy of Sciences

Nanjing Institute of Geography and Limnology

University of Chinese Academy of Sciences

Nanjing University

Hohai University

Aarhus University

University of Wisconsin–Madison

State Key Laboratory of Lake Science and Environment

Oregon State University

State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering

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Hypoxia and its environmental influences in large, shallow, and eutrophic Lake Taihu, China

SIL Proceedings 1922-2010 (2008)

Guangwei Zhu F. Wang Y. Zhang Guang Gao Bo Qin

(2008). Hypoxia and its environmental influences in large, shallow, and eutrophic Lake Taihu, China. SIL Proceedings, 1922-2010: Vol. 30, No. 3, pp. 361-365.

Hypoxia

10.1080/03680770.2008.11902144

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Citations (16)

Catastrophic effects of sand mining on macroinvertebrates in a large shallow lake with implications for management

The Science of The Total Environment (2019)

Wei Zou Kimmo Tolonen Guangwei Zhu Boqiang Qin Yunling Zhang

Dredging

Turbidity

Sand mining

Silt

10.1016/j.scitotenv.2019.133706

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Citations (45)

Long-term remote monitoring of total suspended matter concentration in Lake Taihu using 250m MODIS-Aqua data

Remote Sensing of Environment (2015)

Kun� Shi Yunlin Zhang Guangwei Zhu Xiaohan Liu Yongqiang Zhou

Moderate-resolution imaging spectroradiometer

Spectroradiometer

10.1016/j.rse.2015.02.029

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Citations (230)

CO₂ limited conditions favor cyanobacteria in a hypereutrophic lake: An empirical and theoretical stable isotope study

Limnology and Oceanography (2018)

Bryce Van Dam Craig Tobias Andreas Holbach Hans W. Paerl Guangwei Zhu

Abstract Harmful algal blooms (HABs) are a global problem, exacerbated by rising temperatures, cultural eutrophication, urbanization, and agricultural development. During these HABs, phytoplankton consumption of CO 2 may result in conditions of C limitation, where algal taxa best adapted for these conditions will be at a competitive advantage. Many cyanobacteria are capable of alleviating CO 2 limitation by a variety of strategies, including the active assimilation of . In this study, we utilized a high‐resolution, month‐long time series of stable C isotopes and high‐performance liquid chromatograph‐based algal taxonomy in the hypereutrophic Lake Taihu, China, to investigate whether cyanobacteria are indeed advantaged by CO 2 limiting conditions. We employed a model of phytoplankton C acquisition to support the inferences derived from direct measurements. Diurnal cycles of production and respiration caused δ 13 C DIC to vary between −4‰ and −9‰, while δ 13 C POC varied between −29.6‰ and −19.6‰. Measured and modeled phytoplankton fractionation of DIC were positively correlated with pCO 2 and negatively correlated with cyanobacterial abundance, suggesting that CO 2 limitation preferentially favored increased cyanobacterial biomass, relative to other taxa. We propose that the ability of many cyanobacteria to access otherwise limiting pools of inorganic C is intrinsically linked with their capacity to cope with CO 2 limiting conditions, and may be a key factor in their dominance during HABs.

Dominance (genetics)

Limiting

10.1002/lno.10798

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Citations (35)

Estimation of Water Quality Parameters with High-Frequency Sensors Data in a Large and Deep Reservoir

Water (2020)

Cunli Li Cuiling Jiang Guangwei Zhu Wei Zou Mengyuan Zhu

High-frequency sensors can monitor water quality with high temporal resolution and without environmental influence. However, sensors for detecting key water quality parameters, such as total nitrogen(TN), total phosphorus(TP), and other water environmental parameters, are either not yet available or have attracted limited usage. By using a large number of high-frequency sensor and manual monitoring data, this study establishes regression equations that measure high-frequency sensor and key water quality parameters through multiple regression analysis. Results show that a high-frequency sensor can quickly and accurately estimate dynamic key water quality parameters by evaluating seven water quality parameters. An evaluation of the flux of four chemical parameters further proves that the multi-parameter sensor can efficiently estimate the key water quality parameters. However, due to the different optical properties and ecological bases of these parameters, the high-frequency sensor shows a better prediction performance for chemical parameters than for physical and biological parameters. Nevertheless, these results indicate that combining high-frequency sensor monitoring with regression equations can provide real-time and accurate water quality information that can meet the needs in water environment management and realize early warning functions.

Environmental Monitoring

10.3390/w12092632

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Citations (7)

Extreme Flood Event Enhances Sewage Nitrogen Input Along a River to Reservoir Continuum, Southeastern China: Evidence from Dual Stable Isotope Analysis

Xingchen Zhao Hai Xu Guangwei Zhu Hans W. Paerl Lijuan Kang

Nitrate (NO3−) pollution in aquatic systems is a worldwide environmental problem, and key nutrient stimulating eutrophication. Accurate source identification is an important first step toward improving water quality. Extreme weather events like floods have recently increased in frequency, intensity, and duration due to global climate change. However, during flooding events when a majority of nitrogen loading occurs, the effects rainstorms haves on nitrogen fate and transport processes in river–reservoir systems are poorly known. We used stable isotopes of nitrate (δ18O-NO3− and δ15N-NO3−) along with δ18O and hydrogen (δD) of water (H2O) to understand the sources and transformations of nitrate in Lake Qiandao, China and its largest inflow river – the Xin’an River during flooding and baseflow periods. The contributions of various sources were quantified and compared using Bayesian isotope mixing model. The results showed that significant differences in nitrate sources existed between flooding and base flow periods temporally, and between the upstream river and the downstream reservoir spatially. During flooding, nitrification of soil nitrogen and chemical fertilizer-based nitrogen contributed 78% of nitrate to Xin’an River water which largely affected the northwestern part of Lake Qiandao, while sewage effluents and denitrification mainly controlled the nitrate distribution in other regions, contributing 53% of nitrate in the southwestern lake. As for the baseflow periods, sewage-derived nitrate became the dominant nitrogen source in the upper river (41%), and remained to be the largest contributor (36%) to the downstream reservoir. Overall, this study points to the impact of extreme flooding on nonpoint nitrogen inputs from upstream rivers and sewage treatment plants in a mountainous river–reservoir system, and provide a perspective of nitrogen nutrient for the transborder river management.

10.2139/ssrn.4394285

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Validating and Mapping Surface Water Temperatures in Lake Taihu: Results From MODIS Land Surface Temperature Products

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2015)

Gang Liu Weixin Ou Yunlin Zhang Tingfeng Wu Guangwei Zhu

Data from four in situ high-frequency monitoring sites in Lake Taihu, China were used to 1) assess the accuracy of MODIS land surface temperature (LST) products; 2) characterize the spatial and temporal variability in lake surface water temperature (LSWT) with Aqua MODIS thermal-infrared imagery; and 3) explore the causes of these variations. The validation showed that MODIS-derived LSWTs and in situ water temperatures were significantly correlated, with a coefficient of determination higher than 0.96 and a root mean square error between 1.2°C and 1.8°C. These results indicate MODIS LST products can be used to assess the spatial and temporal thermal behavior of Lake Taihu. A spatial analysis of daytime LSWT showed different thermal zones along the lake due to the differential heat storage capacity between the deep and shallow regions of the lake, such as the littoral and East Lake Taihu. In contrast, the nighttime LSWT showed little variation, and there was a uniform surface water temperature. Following a change in solar radiation, the annual cycle of the average LSWT (with a nearly 24°C range) started to increase in January and peaked in July. In Lake Taihu, the mean nighttime LSWT from July to September rapidly warmed over the period of 2002-2013 at an average rate of 0.059 ± 0.053°C/year. Our study promotes the use of MODIS LST products in limnology through a validation using a large amount of real-time synchronous water temperature data based on high-frequency observations, which were seldom used in previous studies.

Temporal scales

10.1109/jstars.2014.2386333

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Citations (46)

A comprehensive time-series dataset linked to cyanobacterial blooms in Lake Taihu

Scientific Data (2024)

Kun Xue Ronghua Ma Guangwei Zhu Minqi Hu Zhigang Cao

Lake Taihu has a history of recurrent harmful cyanobacterial blooms. There is a need to better understand the aquatic ecosystem of Lake Taihu in order to improve methods for controlling the cyanobacterial blooms. Based on the field measurement and satellite remote sensing, we produced and collected a time-series dataset, including the water quality, bio-optics, climate, and anthropogenic data of Lake Taihu (THQBCA), which could provide comprehensive information regarding cyanobacterial blooms. The THQBCA dataset contains 26 variables organized into four categories: water quality, bio-optics, climate, and anthropogenic data. The water quality and climate data are field measured data with sampling frequency from daily to quarterly, and bio-optics and anthropogenic data are satellite-derived annual data. The dataset spans more than 15 years (8 of which cover approximately 35 years, 4 of which cover 20 years), and the spatial resolutions of the satellite-derived data range from 30 m to 500 m. This dataset is expected to advance research on evaluating and predicting cyanobacterial blooms, and support science-based management decisions for sustainable ecological development.

Bloom

10.1038/s41597-024-04224-w

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Extraction and characterization of bound extracellular polymeric substances from cultured pure cyanobacterium (Microcystis wesenbergii)

Journal of Environmental Sciences (2014)

Lizhen Liu Boqiang Qin Yunlin Zhang Guangwei Zhu Guang Gao

Microcystis

Characterization

Extracellular polymeric substance

10.1016/j.jes.2014.06.013

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