Application of Landsat 5 and Landsat 7 images data for water quality mapping in Mosul Dam Lake, Northern Iraq

Khattab, Mohammed F. O.; Merkel, Broder J.

doi:10.1007/s12517-013-1026-y

Cited by 59 publications

(35 citation statements)

References 42 publications

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“…Water turbidity can be caused by the presence of suspended and dissolved matter. Previous studies indicate that turbid waters have high reflectance in bands b4 and b5 (Wu et al, 2009;Khattab & Merkel, 2013), which is consistent with findings in this study.…”

Section: Statistical Models Of Water Quality and Depthsupporting

confidence: 93%

“…The surface of El Guájaro reservoir water was delimited by applying the Normalized Differential Water Index (NDWI), which is an index used to mark off the water from the soil in satellite images (McFeeters, 1996;Khattab & Merkel, 2013). NDWI values range from -1 to 1, where values greater that zero indicate surfaces covered with water and values equal to or less than zero refer to surfaces not covered by water.…”

Section: Delimitation Of the Water Surfacementioning

confidence: 99%

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Use of LANDSAT 8 images for depth and water quality assessment of El Guájaro reservoir, Colombia

González-Márquez

Torres-Bejarano

Torregroza-Espinosa

et al. 2018

Journal of South American Earth Sciences

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The aim of this study was to evaluate the viability of using Landsat 8 spectral images to estimate water quality parameters and depth in El Guájaro Reservoir. On February and March 2015, two samplings were carried out in the reservoir, coinciding with the Landsat 8 images. Turbidity, dissolved oxygen, electrical conductivity, pH and depth were evaluated. Through multiple regression analysis between measured water quality parameters and the reflectance of the pixels corresponding to the sampling stations, statistical models with determination coefficients between 0.6249 and 0.9300 were generated. Results indicate that from a small number of measured parameters we can generate reliable models to estimate the spatial variation of turbidity, dissolved oxygen, pH and depth, as well the temporal variation of electrical conductivity, so models generated from Landsat 8 can be used as a tool to facilitate the environmental, economic and social management of the reservoir.

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Section: Statistical Models Of Water Quality and Depthsupporting

confidence: 93%

Section: Delimitation Of the Water Surfacementioning

confidence: 99%

Use of LANDSAT 8 images for depth and water quality assessment of El Guájaro reservoir, Colombia

González-Márquez

Torres-Bejarano

Torregroza-Espinosa

et al. 2018

Journal of South American Earth Sciences

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“…The repeated construction of dams due to acute water storage in Turkey and Syria which is the major reason for water quality deterioration in the Iraqi marshlands needs further clarification. Besides, the domestic industrial pollution and hydroelectric power generation along the Euphrates and Tigris Rivers also declined the marshland water quality in Iraq (Khattab and Merkel 2014;Abdul Jabbar 2010;Nicholson and Clark 2003;Sun et al 2014;Ustin 2004;Wu et al 2013Wu et al , 2014. Despite the necessity, research is seldom carried out to model the Iraqi marshlands water quality for effective remediation of pollutants.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Water Quality Parameters in Marshes Zone Southern of Iraq Based on Remote Sensing and GIS Techniques

Hasab

Jawad

Dibs

et al. 2020

Water Air Soil Pollut

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Al-Hawizeh Marsh is considered a major marsh in the south of Iraq with a longitude of 47°32″-47°45″ and latitude of 31°30″-31°42″, length of 80 km and width of 30 km, while the depth is from 1.5 to 4 m. It has a significant impact on the ecosystem and provides habitat for several types of living creatures. The surface water and the agricultural lands surrounding this marsh suffered from high level degrees of salinity. In the last decades, radical deterioration of water quality in this marsh happened because of the postwar related events and several human activities. Landsat-8 data was used to predict and evaluate the spatial variation and map distributions of the salinity, SO 4 and CaCO 3 within Al-Hawizeh Marsh during the two seasons in the year 2017 based on the development of salinity and minerals mathematical equations. The evaluated values for salinity, SO 4 and CaCO 3 are found to be minimal in winter and maximum in autumn. The values of correlation coefficient (R 2) between the real data and the equation results for the salinity, SO 4 and CaCO 3 during the two seasons are 0.95, 0.96 and 0.92, respectively.

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“…The researchers developed the remote sensing monitoring of water quality from simple qualitative analysis into quantitative inversion, from an empirical model with spatial and temporal limitations to a widely applicable biological optical model, which continuously broadened the application prospects of remote sensing water quality monitoring [15,16]. In addition, with the emergence of various remote sensing data sources, especially hyperspectral and multispectral remote sensing data, and the deep understanding of the spectra of various water quality parameters, the parameters of remote sensing water quality monitoring continue to increase, and the inversion accuracy also constantly improves [17][18][19]. However, the past remote sensing monitoring was mainly based on satellite remote sensing, and its data source only had a spatial resolution of 10-30 m and a spectral resolution of 10-20 nm, so it isn't suitable for the mapping of inland small and medium inland water, especially the typical aquaculture area in Guangdong Province.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Inversion of Inland Aquaculture Water Quality Based on UAVs-WSN Spectral Analysis

et al. 2020

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The inland aquaculture environment is an artificial ecosystem, where the water quality is a key factor which is closely related to the economic benefits of inland aquaculture and the quality of aquatic products. Compared with marine aquaculture, inland aquaculture is normally smaller and susceptible to pollution, with poor self-purification capacity. Considering its low cost and large-scale monitoring ability, many researches have developed spectrum sensor on-board satellite platforms to allow remote monitoring of inland water surface. However, there remain many problems, such as low image resolution, poor flexible data acquisition, and anti-interference. Apart from that, the conventional forecasting model is of weak generalization ability and low accuracy. In our study, we combine unmanned aerial vehicles system (UAVs) with the wireless sensor network (WSN) to design a new ground water quality parameter and drone spectrum information acquisition approach, and to propose a novel dynamic network surgery-deep neural networks (DNS-DNNs) model based on multi-source feature fusion to forecast the distribution of dissolved oxygen (DO) and turbidity (TUB) in inland aquaculture areas. The result of using fused features, including characteristic spectrum, Gray-level co-occurrence matrix (GLCM) texture feature, and convolutional neural network (CNN) texture feature to build a model is that the characteristic spectrum+ CNN texture fusion features were the best input items for DNS-DNNs when forecasting DO, with the determination coefficient R 2 of the vertical set arriving at 0.8741, while the characteristic spectrum+ GLCM texture+ CNN texture fusion features were the best for TUB, with the R 2 reaching 0.8531. Compared with a variety of conventional models, our model had a better performance in the inversion of DO and TUB, and there was a strong correlation between predicted and real values: R 2 reached 0.8042 and 0.8346, whereas the root mean square error (RMSE) were only 0.1907 and 0.1794, separately. Our study provides a new insight about using remote sensing to rapidly monitor water quality in inland aquaculture regions.

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Application of Landsat 5 and Landsat 7 images data for water quality mapping in Mosul Dam Lake, Northern Iraq

Cited by 59 publications

References 42 publications

Use of LANDSAT 8 images for depth and water quality assessment of El Guájaro reservoir, Colombia

Use of LANDSAT 8 images for depth and water quality assessment of El Guájaro reservoir, Colombia

Evaluation of Water Quality Parameters in Marshes Zone Southern of Iraq Based on Remote Sensing and GIS Techniques

Dynamic Inversion of Inland Aquaculture Water Quality Based on UAVs-WSN Spectral Analysis

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