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Featured researches published by Chong Fang.


Remote Sensing | 2016

Spatial Distribution of Diffuse Attenuation of Photosynthetic Active Radiation and Its Main Regulating Factors in Inland Waters of Northeast China

Jianhang Ma; Kaishan Song; Zhidan Wen; Ying Zhao; Yingxin Shang; Chong Fang; Jia Du

Light availability in lakes or reservoirs is affected by optically active components (OACs) in the water. Light plays a key role in the distribution of phytoplankton and hydrophytes, thus, is a good indicator of the trophic state of an aquatic system. Diffuse attenuation of photosynthetic active radiation (PAR) (Kd(PAR)) is commonly used to quantitatively assess the light availability. The PAR and the concentration of OACs were measured at 206 sites, which covered 26 lakes and reservoirs in Northeast China. The spatial distribution of Kd(PAR) was depicted and its association with the OACs was assessed by grey incidences(GIs) and linear regression analysis. Kd(PAR) varied from 0.45 to 15.04 m−1. This investigation revealed that reservoirs in the east part of Northeast China were clear with small Kd(PAR) values, while lakes located in plain areas, where the source of total suspended matter (TSM) varied, displayed high Kd(PAR) values. The GIs and linear regression analysis indicated that the TSM was the dominant factor in determining Kd(PAR) values and best correlated with Kd(PAR) (R2 = 0.906, RMSE = 0.709). Most importantly, we have demonstrated that the TSM concentration is a reliable measurement for the estimation of the Kd(PAR) as 74% of the data produced a relative error (RE) of less than 0.4 in a leave-one-out cross validation (LOO-CV) analysis. Spatial transferability assessment of the model also revealed that TSM performed well as a determining factor of the Kd(PAR) for the majority of the lakes. However, a few exceptions were identified where the optically regulating dominant factors were chlorophyll-a (Chl-a) and/or the chromophroic dissolved organic matter (CDOM). These extreme cases represent lakes with exceptionally clear waters.


Aquatic Sciences | 2018

Differences in the distribution and optical properties of DOM between fresh and saline lakes in a semi-arid area of Northern China

Zhidan Wen; Kaishan Song; Yingxin Shang; Ying Zhao; Chong Fang; Lili Lyu

In limnological environments, most organic carbon is present in the dissolved form. Dissolved organic carbon (DOC) is the main source of energy for microbial metabolism and biosynthesis, and also affects photosynthetic radiation level and the attenuation of ultraviolet irradiation to protect aquatic organisms. There are large differences in DOC concentration, source, and characteristics due to regional variations in water quality and basin characteristics. Reliable estimates of DOC and analysis of optical characteristics are crucial to understand the true role of lakes in the global carbon cycle. In this article, the distribution of DOC across 30 lakes in semi-arid areas of Northern China is reported. The data shows that saline lakes exhibited higher DOC concentrations than freshwater lakes, and the positive relationship between salinity and DOC was established (R2 = 0.42, p < 0.01, n = 196). The mean DOC concentration in eutrophic lakes was lower than in mesotrophic and oligotrophic lakes. Analysis of optical characteristics of CDOM indicated that saline lakes in this semi-arid regions contained abundant fulvic acid, and greater levels of autochthonous dissolved organic matter (DOM) with a lower molecular mass than fresh waters. The total suspended matter (TSM) is the main factor influencing on SUVA254 in both freshwater and saline lakes with a negative correlation. SUVA254 was negatively correlated with the salinity only in freshwater lakes, and with pH only in saline lakes. The result suggests that it was doubtful whether CDOM or SUVA254 alone can be a predictor of DOC concentration and other water quality parameters, especially in different types of lakes with different optical and physicochemical characteristics.


Journal of Environmental Management | 2018

Quantification of dissolved organic carbon (DOC) storage in lakes and reservoirs of mainland China

Kaishan Song; Zhidan Wen; Yingxing Shang; Hong Yang; Lili Lyu; Ge Liu; Chong Fang; Jia Du; Ying Zhao

As a major fraction of carbon in inland waters, dissolved organic carbon (DOC) plays a crucial role in carbon cycling on a global scale. However, the quantity of DOC stored in lakes and reservoirs was not clear to date. In an attempt to examine the factors that determine the DOC storage in lakes and reservoirs across China, we assembled a large database (measured 367 lakes, and meta-analyzed 102 lakes from five limnetic regions; measured 144 reservoirs, and meta-analyzed 272 reservoirs from 31 provincial units) of DOC concentrations and water storages for lakes and reservoirs that are used to determine DOC storage in static inland waters. We found that DOC concentrations in saline waters (Mean/median ± S.D: 50.5/30.0 ± 55.97 mg/L) are much higher than those in fresh waters (8.1/5.9 ± 6.8 mg/L), while lake DOC concentrations (25.9/11.5 ± 42.04 mg/L) are much higher than those in reservoirs (5.0/3.8 ± 4.5 mg/L). In terms of lake water volume and DOC storage, the Tibet-Qinghai lake region has the largest water volume (552.8 km3), 92% of which is saline waters, thus the largest DOC (13.39 Tg) is stored in these alpine lake region; followed by the Mengxin lake region, having a water volume of 99.4 km3 in which 1.75 Tg DOC was stored. Compared to Mengxin lake region, almost the same amount of water was stored in East China lake region (91.9 km3), however, much less DOC was stored in this region (0.43 Tg) due to the lower DOC concentration (Ave: 3.45 ± 2.68 mg/L). According to our investigation, Yungui and Northeast lake regions had water storages of 32.14 km3 and 19.44 km3 respectively, but relatively less DOC was stored in Yungui (0.13 Tg) than in Northeast lake region (0.19 Tg). Due to low DOC concentration in reservoirs, especially these large reservoirs having lower DOC concentration (V > 1.0 km3: 2.31 ± 1.48 mg/L), only 1.54 Tg was stored in a 485.1 km3 volume of water contained in reservoirs across the entire country.


Isprs Journal of Photogrammetry and Remote Sensing | 2017

Remote estimation of Kd (PAR) using MODIS and Landsat imagery for turbid inland waters in Northeast China

Kaishan Song; Jianhang Ma; Zhidan Wen; Chong Fang; Yingxin Shang; Ying Zhao; Ming Wang; Jia Du


Journal of Hydrology | 2017

Evaluation of CDOM sources and their links with water quality in the lakes of Northeast China using fluorescence spectroscopy

Ying Zhao; Kaishan Song; Zhidan Wen; Chong Fang; Yingxin Shang; Lili Lv


Environmental Science and Pollution Research | 2018

Phthalate esters in surface water of Songhua River watershed associated with land use types, Northeast China

Zhidan Wen; Xiaoli Huang; Dawen Gao; Ge Liu; Chong Fang; Yingxin Shang; Jia Du; Ying Zhao; Lili Lv; Kaishan Song


Hydrology and Earth System Sciences Discussions | 2017

A systematic examination of the relationships between CDOM and DOC in inland waters in China

Kaishan Song; Ying Zhao; Zhidan Wen; Chong Fang; Yingxin Shang


Atmospheric Environment | 2017

Carbon dioxide emissions from lakes and reservoirs of China: A regional estimate based on the calculated pCO2

Zhidan Wen; Kaishan Song; Yingxin Shang; Chong Fang; Lin Li; Lili Lv; Xianguo Lv; Lijiang Chen


Journal of Hydrology | 2018

Dissolved carbon in a large variety of lakes across five limnetic regions in China

Kaishan Song; Zhidan Wen; Yijun Xu; Hong Yang; Lili Lyu; Ying Zhao; Chong Fang; Yingxin Shang; Jia Du


Environmental Science and Pollution Research | 2018

Characterization of CDOM absorption of reservoirs with its linkage of regions and ages across China

Yingxin Shang; Kaishan Song; Zhidan Wen; Lili Lyu; Ying Zhao; Chong Fang; Bai Zhang

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Kaishan Song

Chinese Academy of Sciences

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Zhidan Wen

Chinese Academy of Sciences

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Yingxin Shang

Chinese Academy of Sciences

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Ying Zhao

Chinese Academy of Sciences

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Jia Du

Chinese Academy of Sciences

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Ge Liu

Nanjing Normal University

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Lili Lyu

Chinese Academy of Sciences

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Jianhang Ma

Chinese Academy of Sciences

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Lili Lv

Chinese Academy of Sciences

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Bai Zhang

Chinese Academy of Sciences

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