Analysis of water clarity decrease in Xin’anjiang Reservoir, China, from 30-Year Landsat TM, ETM+, and OLI observations

Li, Yuan; Shi, Kun; Zhang, Yunlin; Zhu, Guangwei; Zhang, Hongjie; Wu, Zhixu; Liu, Mingliang; Guo, Yulong; Li, Na

doi:10.1016/j.jhydrol.2020.125476

Cited by 36 publications

(28 citation statements)

References 58 publications

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“…Similarly, a study in India (Vembanad Kayal, Kerala) also highlighted that how much the supply of suspended particulate matter (SPM Decreased 15.9% during lockdown) was restricted in the lake water during COVID-19 lockdown and the purification level of lake water has been detected applying remote sensing techniques ( Yunus et al, 2020 ). Another work also investigated that the water quality (Dissolved Oxygen and organic pollutants) was detected through the different spectral bands of OLI image analysis and it showed that how remote sensing technique helped to monitor the spatiotemporal data regarding the water quality assessment ( Li et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

Effects of COVID-19 lockdown and unlock on health of Bhutan-India-Bangladesh trans-boundary rivers

Sarkar

Roy

Bhattacharjee

et al. 2021

Journal of Hazardous Materials Advances

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Section: Introductionmentioning

confidence: 99%

Effects of COVID-19 lockdown and unlock on health of Bhutan-India-Bangladesh trans-boundary rivers

Sarkar

Roy

Bhattacharjee

et al. 2021

Journal of Hazardous Materials Advances

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“…More than 2.0 ×10 9 m 3 water per year is transported to Hangzhou and Jiaxing through Lake Qiandaohu Water Diversion Project since 2020. Under the dual pressure of climate change and human activities, Lake Qiandaohu faces nutrient increase, Secchi disc depth decrease, phytoplankton bloom appearance, and water quality deterioration risk, which threaten drinking water supply safety (Li et al 2020 ; Zhang et al 2015 ; Zhang et al 2020 ).…”

Section: Methodsmentioning

confidence: 99%

Long-term trend of heat waves and potential effects on phytoplankton blooms in Lake Qiandaohu, a key drinking water reservoir

Huang

2021

Environ Sci Pollut Res

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Global warming is increasing the frequency and duration of heat waves, which is defined as when air temperature exceeds a threshold for more than specific consecutive days. Ecosystem around the globe will be impaired by heat waves just like the exposures to dangerously high temperatures as a public health threat to human. However, the knowledge of the response of lake and reservoir ecosystem to heat waves is largely unknown although it has been argued that climate warming may increase the incidence of harmful algal blooms. We examined the long-term trend of heat waves and how the variability of phytoplankton biomass responds to lake heat waves on a deep reservoir (Lake Qiandaohu). Long-term (1980Long-term ( -2020 meteorological observation in the lake watershed showed a significant warming trend of 0.36°C per decade for the yearly average of daily average air temperature and the yearly average of daily maximum air temperature of 18.32°C was observed in 2016. Meanwhile, a significant increasing number of heat wave events lasting longer was observed, and Lake Qiandaohu suffered an unusually severe lake heat wave in summer 2016. Significant correlations were found between the yearly average of daily maximum air temperature and heat days, heat wave events, and heat wave days. Nuisance phytoplankton bloom was found in Lake Qiandaohu by high frequency observation and remote sensing monitoring in summer 2016. Remote sensing estimation from two Landsat 8 Operational Land Imager (OLI) images showed that the average chlorophyll a (Chla) was 7.45 ± 4.89 μg/L on July 18 before heat wave and 18.96 ± 0.98 μg/L on August 19 during the heat wave. Two heat wave events lasting from July 20 to August 2 and August 11 to 26 with average surface water temperature of 29.93 and 31.99°C promoted two marked phytoplankton blooms with average Chla concentrations of 11.75 ± 4.08 and 10.53 ± 1.65 μg/L in the central lake region, respectively, as evidenced by highfrequency buoy data. These findings suggest that heat waves are likely to yield an increased threat of harmful algal bloom in freshwater ecosystems. With lake heat waves projected to increase in frequency, duration, and spatial extent with global climate change, more studies are needed to improve our understanding of lake heat waves and their potential effects on the species, communities, frequency of phytoplankton bloom, and also help providing advanced schemes of water quality management.

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“…The first example (Pro.1) is the above‐water remote sensing database of water clarity for Xin'anjiang reservoir in China from 2013 to 2014 from Landsat TM, ETM+, and PLI observations 27 . The value of water clarity has been estimated using NIC with consideration of a collection of input data extracted from each Landsat sensor.…”

Section: Numerical Studymentioning

confidence: 99%

“…Figures 10–12 illustrate the scatter of the inputs against the target for each of the three problems. More information about the considered datasets for the numerical study of this article can be found directly from their References 27–29. The extracted inputs from the references of these examples are defined in Table A1 (see Appendix).…”

Section: Numerical Studymentioning

confidence: 99%

NIC: An innovative supervised machine learning computational framework having network‐based interactional connections

Mirrashid

Shirazi

2021

Computational Intelligence

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Models based on computational intelligence have many applications in various problems. Such systems are generally set up and designed based on a collection of data and information. In some real problems, the implementation of experimental studies or doing tests are costly and time‐consuming. Therefore, a model which requires fewer data than the existing soft computing methods can be useful and applicable. In this article, a network‐based interactional connection system is proposed as a new supervised machine learning computational framework for problems with small data. This model, which is inspired by the connections between neurons of the brain, utilizes the series and parallel structures with interactional connections to determine the best estimation. The proposed approach uses less unknown parameters than existing models and gives a suitable response in a few steps. The learning process starts with one generation and continues until an acceptable prediction is found, and the coefficients are determined. However, it may have more generations in a sequential format for better prediction and providing more accurate answers. To evaluate the performance of the proposed computational system, three engineering problems were investigated as a numerical study. The results also compared with the predicted values of four well‐known techniques.

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Analysis of water clarity decrease in Xin’anjiang Reservoir, China, from 30-Year Landsat TM, ETM+, and OLI observations

Cited by 36 publications

References 58 publications

Effects of COVID-19 lockdown and unlock on health of Bhutan-India-Bangladesh trans-boundary rivers

Effects of COVID-19 lockdown and unlock on health of Bhutan-India-Bangladesh trans-boundary rivers

Long-term trend of heat waves and potential effects on phytoplankton blooms in Lake Qiandaohu, a key drinking water reservoir

NIC: An innovative supervised machine learning computational framework having network‐based interactional connections

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