A hydro-optical model for deriving water quality variables from satellite images (HydroSat): A case study of the Nile River demonstrating the future Sentinel-2 capabilities

2012 ◽  
Vol 50-52 ◽  
pp. 224-232 ◽  
Author(s):  
Mhd. Suhyb Salama ◽  
Mona Radwan ◽  
Rogier van der Velde
Keyword(s):  
Water Quality ◽  
Optical Model ◽  
Satellite Images ◽  
Nile River ◽  
Water Quality Variables ◽  
The Future ◽  
Sentinel 2

scholarly journals Evaluating the potential of Sentinel-2 satellite images for water quality characterization of artificial reservoirs: The Bin El Ouidane Reservoir case study (Morocco)

2019 ◽  
Vol 7 (1) ◽  
Author(s):  
Karaoui Ismail ◽  
Abdelghani Boudhar ◽  
Arioua Abdelkrim ◽  
Hssaisoune Mohammed ◽  
Sabri Mouatassime ◽  
...  
Keyword(s):  
Water Quality ◽  
Satellite Images ◽  
Bin El Ouidane ◽  
Artificial Reservoirs ◽  
Sentinel 2

scholarly journals Effect of Solar Canals on Evaporation, Water Quality, and Power Production: An Optimization Study

Water ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 2103 ◽  
Author(s):  
Sherine El Baradei ◽  
Mai Al Sadeq
Keyword(s):  
Water Quality ◽  
Well Being ◽  
Power Production ◽  
Mitigation Measures ◽  
Optimum Conditions ◽  
Water Quality Variables ◽  
Optimization Study ◽  
New Energy ◽  
To Come

Both energy and availability of water with good quality are essential for the well-being of humans. Thus, it is very important to study the parameters that would affect water quality, so as to come up with mitigation measures if water quality would be at risk or negatively affected. Moreover, it is very important to always search for new energy resources, especially if they are renewable. This research study is concerned with studying solar canals and their effect on evaporation and water quality variables of canals covered by solar cells, as well as the effect on power production. Both a mathematical model and an optimization study were done, in order to determine the previously mentioned effects, and thus, to determine the most favorable covering percentage of the case study canal’s area that would lead to minimum evaporation volumes, maximum power, and yet preserving and meeting the standards of the water quality variables of the covered waterway. Water quality variables that were investigated are dissolved oxygen concentration, algae, nutrients, and pH of the water. It was found that, between 33% and 50% covering of the canal, the optimum conditions will be met.

scholarly journals Synoptic Characteristics of Torrential Rains in Southwest and Southeast Iraq: A Case Study

2021 ◽  
Vol 32 (3) ◽  
pp. 1
Author(s):  
Aqeel Ghazi Mutar ◽  
Asraa Khtan ◽  
Loay E. George
Keyword(s):  
Satellite Images ◽  
Research Work ◽  
Heavy Rain ◽  
Moisture Flux ◽  
Relative Vorticity ◽  
Water Index ◽  
Normalized Difference Water Index ◽  
Modern Era ◽  
Sentinel 2

Torrential rains cause many losses in city infrastructure, crops, and deaths in several regions of the world including Iraq as in the case that we will discuss in this work, on January 28 and 29, 2019. Torrential rain caused the flow of torrents in several areas of Iraq and the neighboring areas. This research work aims to identify the synoptic characteristics of torrential rains and the causes of this case. This will be done by analyzing and interpreting the weather maps at different pressure levels with focusing on the troughs and fronts locations, relative vorticity, polar jet stream effect as well as the moisture flux. The Geographic Information System (GIS) was used to analyze the satellite images in order to calculate the Normalized Difference Water Index (NDWI) to confirm the heavy rain case. The weather maps were obtained from the Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2).  As for the satellite images we used the satellite imagery from Sentinel-2 and EMUTSAT.

Water quality assessment in a wetland complex using Sentinel 2 satellite images

2020 ◽  
Author(s):  
F. Torres-Bejarano ◽  
F. Arteaga-Hernández ◽  
D. Rodríguez-Ibarra ◽  
D. Mejía-Ávila ◽  
L. C. González-Márquez
Keyword(s):  
Water Quality ◽  
Quality Assessment ◽  
Satellite Images ◽  
Water Quality Assessment ◽  
Wetland Complex ◽  
Sentinel 2

scholarly journals Space-time monitoring of water quality in an eutrophic reservoir using SENTINEL-2 data - A case study of San Roque, Argentina

2021 ◽  
pp. 100614
Author(s):  
Alba Germán ◽  
Michal Shimoni ◽  
Giuliana Beltramone ◽  
Maria Ines Rodriguez ◽  
Jonathan Munchiut ◽  
...  
Keyword(s):  
Water Quality ◽  
Space Time ◽  
Eutrophic Reservoir ◽  
Sentinel 2

scholarly journals Seasonal variation and correlation between the physical, chemical and microbiological parameters of Nile water in selected area in Egypt (Case study)

2020 ◽  
Vol 17 (4) ◽  
pp. 1160
Author(s):  
Ghadir El-Chaghaby ◽  
Sayed Rashad ◽  
Muhammad Abdul Moneem
Keyword(s):  
Water Quality ◽  
Seasonal Variation ◽  
Chemical Oxygen Demand ◽  
Water Samples ◽  
Oxygen Demand ◽  
Total Dissolved Solids ◽  
Total Hardness ◽  
Nile River ◽  
Physical Chemical

Fresh water resources in terms of water quality is a crucial issue worldwide. In Egypt, the Nile River is the main source of fresh water in the country and monitoring its water quality is a major task on governments and research levels. In the present case study, the physical, chemical and algal distribution in Nile River was monitored over two seasons (winter and summer) in 2019. The aims of the study were to check the seasonal variation among the different water parameters and also to check the correlations between those parameters. Water samples were collected from the Nile in Cairo governorate in EGYPT. The different physiochemical and microbiological properties in water samples were assessed. The studied parameters were included: temperature, turbidity, dissolved oxygen, chemical oxygen demand, pH, electric conductivity, total dissolved solids, total hardness, anions and cations. Also, the total algae count, blue-green algae, green algae, diatoms, unicellular and filamentous algae were monitored. The results revealed that during winter season the values recorded for (turbidity, total dissolved solids, pH, total alkalinity, total hardness, dissolved oxygen, chemical oxygen demand as well as nitrate, sulfate, chloride, fluoride ions, calcium and magnesium) were higher than during summer. While other parameters including ammonia, nitrite, silicate, carbon dioxide, phosphate, manganese, iron and residual aluminium were higher in summer compared to winter. The data showed a variation total algal count of 4600 to 6500 unit/ml in winter and varied from 3100 to 4500 unit/ml during summer season with predominance of diatoms. The recorded Pearson’s correlations indicated several significant correlations between tested parameters. In conclusion, although there were several variations in tested water quality parameters though all results were within the permissible limits set by the World Health Organization for drinking water.

scholarly journals A comprehensive transferability evaluation of U-Net and ResU-Net for landslide detection from Sentinel-2 data (case study areas from Taiwan, China, and Japan)

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Omid Ghorbanzadeh ◽  
Alessandro Crivellari ◽  
Pedram Ghamisi ◽  
Hejar Shahabi ◽  
Thomas Blaschke
Keyword(s):  
Satellite Images ◽  
Patch Size ◽  
Window Size ◽  
Convolutional Network ◽  
Digital Elevation ◽  
High Resolution Satellite Images ◽  
Elevation Model ◽  
Very High ◽  
Sentinel 2

AbstractEarthquakes and heavy rainfalls are the two leading causes of landslides around the world. Since they often occur across large areas, landslide detection requires rapid and reliable automatic detection approaches. Currently, deep learning (DL) approaches, especially different convolutional neural network and fully convolutional network (FCN) algorithms, are reliably achieving cutting-edge accuracies in automatic landslide detection. However, these successful applications of various DL approaches have thus far been based on very high resolution satellite images (e.g., GeoEye and WorldView), making it easier to achieve such high detection performances. In this study, we use freely available Sentinel-2 data and ALOS digital elevation model to investigate the application of two well-known FCN algorithms, namely the U-Net and residual U-Net (or so-called ResU-Net), for landslide detection. To our knowledge, this is the first application of FCN for landslide detection only from freely available data. We adapt the algorithms to the specific aim of landslide detection, then train and test with data from three different case study areas located in Western Taitung County (Taiwan), Shuzheng Valley (China), and Eastern Iburi (Japan). We characterize three different window size sample patches to train the algorithms. Our results also contain a comprehensive transferability assessment achieved through different training and testing scenarios in the three case studies. The highest f1-score value of 73.32% was obtained by ResU-Net, trained with a dataset from Japan, and tested on China’s holdout testing area using the sample patch size of 64 × 64 pixels.

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