Browsing by Author "Shi, Kun"

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    A Landsat-derived annual inland water clarity dataset of China between 1984 and 2018
    (Copernicus, 2022-01-13) Tao, Hui; Song, Kaishan; Liu, Ge; Wang, Qiang; Wen, Zhidan; Jacinthe, Pierre-Andre; Xu, Xiaofeng; Du, Jia; Shang, Yingxin; Li, Sijia; Wang, Zongming; Lyu, Lili; Hou, Junbin; Wang, Xiang; Liu, Dong; Shi, Kun; Zhang, Baohua; Duan, Hongtao; Earth and Environmental Sciences, School of Science
    Water clarity serves as a sensitive tool for understanding the spatial pattern and historical trend in lakes' trophic status. Despite the wide availability of remotely sensed data, this metric has not been fully explored for long-term environmental monitoring. To this end, we utilized Landsat top-of-atmosphere reflectance products within Google Earth Engine in the period 1984–2018 to retrieve the average Secchi disk depth (SDD) for each lake in each year. Three SDD datasets were used for model calibration and validation from different field campaigns mainly conducted during 2004–2018. The red  blue band ratio algorithm was applied to map SDD for lakes (>0.01 km2) based on the first SDD dataset, where R2=0.79 and relative RMSE (rRMSE) =61.9  %. The other two datasets were used to validate the temporal transferability of the SDD estimation model, which confirmed the stable performance of the model. The spatiotemporal dynamics of SDD were analyzed at the five lake regions and individual lake scales, and the average, changing trend, lake number and area, and spatial distribution of lake SDDs across China were presented. In 2018, we found the number of lakes with SDD <2 m accounted for the largest proportion (80.93 %) of the total lakes, but the total areas of lakes with SDD of <0.5 and >4 m were the largest, both accounting for about 24.00 % of the total lakes. During 1984–2018, lakes in the Tibetan–Qinghai Plateau region (TQR) had the clearest water with an average value of 3.32±0.38 m, while that in the northeastern region (NLR) exhibited the lowest SDD (mean 0.60±0.09 m). Among the 10 814 lakes with SDD results for more than 10 years, 55.42 % and 3.49 % of lakes experienced significant increasing and decreasing trends, respectively. At the five lake regions, except for the Inner Mongolia–Xinjiang region (MXR), more than half of the total lakes in every other region exhibited significant increasing trends. In the eastern region (ELR), NLR and Yungui Plateau region (YGR), almost more than 50 % of the lakes that displayed increase or decrease in SDD were mainly distributed in the area range of 0.01–1 km2, whereas those in the TQR and MXR were primarily concentrated in large lakes (>10 km2). Spatially, lakes located in the plateau regions generally exhibited higher SDD than those situated in the flat plain regions. The dataset is freely available at the National Tibetan Plateau Data Center (https://doi.org/10.11888/Hydro.tpdc.271571, Tao et al., 2021).
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    Global divergent trends of algal blooms detected by satellite during 1982–2018
    (Wiley, 2022-04) Fang, Chong; Song, Kaishan; Paerl, Hans W.; Jacinthe, Pierre-Andre; Wen, Zhidan; Liu, Ge; Tao, Hui; Xu, Xiaofeng; Kutser, Tiit; Wang, Zongming; Duan, Hongtao; Shi, Kun; Shang, Yingxin; Lyu, Lili; Li, Sijia; Yang, Qian; Lyu, Dongmei; Mao, Dehua; Zhang, Baohua; Cheng, Shuai; Lyu, Yunfeng; Earth and Environmental Sciences, School of Science
    Algal blooms (ABs) in inland lakes have caused adverse ecological effects, and health impairment of animals and humans. We used archived Landsat images to examine ABs in lakes (>1 km2) around the globe over a 37-year time span (1982–2018). Out of the 176032 lakes with area >1 km2 detected globally, 863 were impacted by ABs, 708 had sufficiently long records to define a trend, and 66% exhibited increasing trends in frequency ratio (FRQR, ratio of the number of ABs events observed in a year in a given lake to the number of available Landsat images for that lake) or area ratio (AR, ratio of annual maximum area covered by ABs observed in a lake to the surface area of that lake), while 34% showed a decreasing trend. Across North America, an intensification of ABs severity was observed for FRQR (p < .01) and AR (p < .01) before 1999, followed by a decrease in ABs FRQR (p < .01) and AR (p < .05) after the 2000s. The strongest intensification of ABs was observed in Asia, followed by South America, Africa, and Europe. No clear trend was detected for the Oceania. Across climatic zones, the contributions of anthropogenic factors to ABs intensification (16.5% for fertilizer, 19.4% for gross domestic product, and 18.7% for population) were slightly stronger than climatic drivers (10.1% for temperature, 11.7% for wind speed, 16.8% for pressure, and for 11.6% for rainfall). Collectively, these divergent trends indicate that consideration of anthropogenic factors as well as climate change should be at the forefront of management policies aimed at reducing the severity and frequency of ABs in inland waters.
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    Radiation dimming and decreasing water clarity fuel underwater darkening in lakes
    (Elsevier, 2020-10) Zhang, Yunlin; Qin, Boqiang; Shi, Kun; Zhang, Yibo; Deng, Jianming; Wild, Martin; Li, Lin; Zhou, Yongqiang; Yao, Xiaolong; Liu, Miao; Zhu, Guangwei; Zhang, Lu; Gu, Binhe; Brookes, Justin D.; Earth Sciences, School of Science
    Long-term decreases in the incident total radiation and water clarity might substantially affect the underwater light environment in aquatic ecosystems. However, the underlying mechanism and relative contributions of radiation dimming and decreasing water clarity to the underwater light environment on a national or global scale remains largely unknown. Here, we present a comprehensive dataset of unprecedented scale in China’s lakes to address the combined effects of radiation dimming and decreasing water clarity on underwater darkening. Long-term total radiation and sunshine duration showed 5.8% and 7.9% decreases, respectively, after 2000 compared to 1961–1970, resulting in net radiation dimming. An in situ Secchi disk depth (SDD) dataset in 170 lakes showed that the mean SDD significantly decreased from 1.80 ± 2.19 m before 1995 to 1.28 ± 1.82 m after 2005. SDD remote sensing estimations for 641 lakes with areas ≥ 10 km2 showed that SDD markedly decreased from 1.26 ± 0.62 m during 1985–1990 to 1.14 ± 0.66 m during 2005–2010. Radiation dimming and decreasing water clarity jointly caused an approximately 10% decrease in the average available photosynthetically active radiation (PAR) in the euphotic layer. Our results revealed a more important role of decreasing water clarity in underwater darkening than radiation dimming. A meta-analysis of long-term SDD observation data from 61 various waters further elucidated a global extensive underwater darkening. Underwater darkening implies a decrease in water quality for potable water supplies, recession in macrophytes and benthic algae, and decreases in benthic primary production, fishery production, and biodiversity.
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    A semi-analytical model for estimating total suspended matter in highly turbid waters
    (Optical Society of America, 2018-12-24) Zhang, Yibo; Shi, Kun; Zhang, Yunlin; Moreno-Madrinan, Max J.; Li, Yuan; Li, Na; Environmental Health Science, School of Public Health
    Total suspended matter (TSM) is related to water quality. High TSM concentrations limit underwater light availability, thus affecting the primary productivity of aquatic ecosystems. Accurate estimation of TSM concentrations in various waters with remote sensing technology is particularly challenging, as the concentrations and optical properties vary greatly among different waters. In this research, a semi-analytical model was established for Hangzhou Bay and Lake Taihu for estimating TSM concentration. The model construction proceeded in two steps. 1) Two indices of the model were calculated by deriving absorption and backscattering coefficients of suspended matter (ap(λ) and bbp(λ)) from the reflectance signal using a semi-analytical method. 2) The two indices were then weighted to derive TSM. The performance of the proposed model was tested using in situ reflectance and Geostationary Ocean Color Imager (GOCI) data. The derived TSM based on in situ reflectance and GOCI images both corresponded well with the in situ TSM with low mean relative error (32%, 41%), root mean square error (20.1 mg/L, 43.1 mg/L), and normalized root mean square error (33%, 55%). The model was further used for the slightly turbid Xin’anjiang Reservoir to demonstrate its applicability to derive ap(λ) and bbp(λ) in other water types. The results indicated that the form Rrs −1(λ1) − Rrs −1(λ2) could minimize the effect of CDOM absorption in deriving ap(λ) from the total absorption. The model exploited the different relationships between TSM concentration and multiband reflectance, thus improving the performance and application range in deriving TSM.
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    Water clarity response to climate warming and wetting of the Inner Mongolia-Xinjiang Plateau: A remote sensing approach
    (Elsevier, 2021-11) Zhang, Yibo; Shi, Kun; Zhang, Yunlin; Moreno-Madriñán, Max Jacobo; Xu, Xuan; Zhou, Yongqiang; Qin, Boqiang; Zhu, Guangwei; Jeppesen, Erik; Environmental Health Science, School of Public Health
    Water clarity (generally quantified as the Secchi disk depth: SDD) is a key variable for assessing environmental changes in lakes. Using remote sensing we calculated and elucidated the SDD dynamics in lakes in the Inner Mongolia-Xinjiang Lake Zone (IMXL) from 1986 to 2018 in response to variations in temperature, rainfall, lake area, normalized difference vegetation index (NDVI) and Palmer's drought severity index (PDSI). The results showed that the lakes with high SDD values are primarily located in the Xinjiang region at longitudes of 75°–93° E. In contrast, the lakes in Inner Mongolia at longitudes of 93°–118° E generally have low SDD values. In total, 205 lakes show significant increasing SDD trends (P < 0.05), with a mean rate of 0.15 m per decade. In contrast, 75 lakes, most of which are located in Inner Mongolia, exhibited significant decreasing trends with a mean rate of 0.08 m per decade (P < 0.05). Pooled together, an overall increase is found with a mean rate of 0.14 m per decade. Multiple linear regression reveals that among the five variables selected to explain the variations in SDD, lake area accounts for the highest proportion of variance (25%), while temperature and rainfall account for 12% and 10%, respectively. In addition, rainfall accounts for 52% of the variation in humidity, 8% of the variation in lake area and 7% of the variation in NDVI. Temperature accounts for 27% of the variation in NDVI, 39% of the variation in lake area and 22% of the variation in PDSI. Warming and wetting conditions in IMXL thus promote the growth of vegetation and cause melting of glaciers and expansion of lake area, which eventually leads to improved water quality in the lakes in terms of higher SDD. In contrast, lakes facing more severe drought conditions, became more turbid.