Water quality evaluation of Al-Gharraf river by two water quality indices

Ewaid, Salam Hussein

doi:10.1007/s13201-016-0523-z

Cited by 50 publications

(37 citation statements)

References 19 publications

(29 reference statements)

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“…However, this did not pose major problems because of the plentiful supply of water, albeit dependent on the Euphrates and Tigris Rivers and reasonable rainfall levels. Now, however, with the water scarcity crisis, increased salinity, low rainfall levels and a decrease in the discharge from rivers, there is a need to improve irrigation systems in order to resolve water problems [7][8][9]. These problems are only likely to become more prominent in the future, with the supply 43 billion cubic meters (BCM) in 2015 and anticipated to be 17.6 BCM in 2025, while current demand is somewhere in the range of between 66.8 and 77 BCM [10].…”

Section: Introductionmentioning

confidence: 99%

Water Footprint of Wheat in Iraq

Ewaid

Abed

Al‐Ansari

2019

Water

114

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The water footprint (WF) is an indicator of indirect and direct fresh water use. In respect of facilitating decision-making processes, WF gives an excellent perspective on how and where fresh water is used in the supply chain. More than 39 million people live in Iraq and, with a growing population, there is a water shortage and a rising demand for food that cannot be met in the future. In this study, the WF of wheat production is estimated for the year 2016–2017 for 15 Iraqi provinces. The WF was calculated using the method of Mekonnen and Hoekstra (2011) and the CROPWAT and CLIMWAT softwares’ crop water requirement option. It was found that the WF in m3/ton was 1876 m3/ton. The 15 provinces showed variations in WFs, which can be ascribed to the difference in climate and production values. The highest wheat WF was found in Nineveh province, followed by Muthanna, Anbar, and Basra. The last three provinces produce little and have a high WF so, in these provinces, wheat can be replaced with crops that need less water and provide more economic benefit. There is an opportunity to reduce the green WF by increasing production from the 4 rain-fed provinces, which will reduce the need for production from the irrigated provinces and, therefore, reduce the use of blue water.

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Section: Introductionmentioning

confidence: 99%

Water Footprint of Wheat in Iraq

Ewaid

Abed

Al‐Ansari

2019

Water

114

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“…ere are other important variations, e.g., spatial and temporal variations. For such kinds of variation monitoring, there should be some conceptual and essential estimations of the surface water quality [9], and some standards, e.g., here in this study, such as FAO-29 guidelines and WHO recommendations (given in Table 1) were utilized for assessing the water quality.…”

Section: Introductionmentioning

confidence: 99%

Investigating the Impact of Anthropogenic and Natural Sources of Pollution on Quality of Water in Upper Indus Basin (UIB) by Using Multivariate Statistical Analysis

Baluch

Hashmi

2019

Journal of Chemistry

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Water quality of the Indus River around the upper basin and the main river was evaluated with the help of statistical analysis. In order to analyze the similarities and dissimilarities for identifying the spatial variations in water quality of the Indus River and sources of contamination, multivariate statistical analysis, i.e., principle component analysis (PCA), cluster analysis, and descriptive analysis, was done. Data of 8 physicochemical quality parameters from 64 sampling stations belonging to 6 regions (labeled as M1, M2, M3, M4, M5, and M6) were used for analysis. The parameters used for assessing the water quality were pH, dissolved oxygen (DO), oxygen reducing potential (ORP), electrical conductivity (EC), total dissolved solids (TDS), salinity (%), and concentration of arsenic (As) and lead (Pb), respectively. PCA assisted in extracting and recognizing the responsible variation factors of water quality over the region, and the results showed three underlying factors including anthropogenic source pollution along with runoff due to rain and soil erosion were responsible for explaining the 93.87% of total variance. The parameters which were significantly influenced by anthropogenic impact are DO, EC, TDS (negative), and concentration of Pb (positive), while the concentration of As, % salinity, and ORP are affected by erosion and runoff due to rain. The worst pollution situation for regions M1 and M6 was due to the concentration of As which was approximately 400 μg/l (i.e., 40 times higher than minimum WHO recommendation). Furthermore, the results also indicated that, in the Indus River, three monitoring stations and five quality parameters are sufficient to have a reasonable confidence about the quality of water in this most important reserve of Pakistan.

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“…includes the following nine parameters of quality: TDS (total of dissolved solids), pH, turbidity, phosphates, nitrates, CBO5 (biochemical consumption of oxygen), Coliforms, OD (dissolved oxygen), temperature [14,[16][17][18]. As each parameter presents a different contribution upon the modification of the water quality, a specific weight in the calculation of the NFS-WQI index was attributed to each of these, as presented in Table 1 [16,17,20]. This index is calculated based on formula 1.…”

Section: Nsf-wqi (National Sanitation Foundation-water Quality Index)mentioning

confidence: 99%

Various methods for calculating the water quality index

Calmuc

Călmuc

Topa

et al. 2018

Ann_UGAL_Math_Phys_Mec

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At present, the most commonly used method to evaluate the quality of a water stream is the application of the Water Quality Index, which may be determined by using different methods. The main purpose of this study is to describe four methods for calculating the Water Quality Index with their advantages and disadvantages: NFS-WQI (National Sanitation Foundation-Water Quality Index), OWQI (Oregon Water Quality Index), WAWQI (Weighted Arithmetic Water Quality Index) and CCME-WQI (Canadian Council of Ministers of the Environment-Water Quality Index). Choosing one of the four methods mentioned above should be based on the study purpose and on the nature of the water stream. These indices have already been used to determine the quality of the Danube water in the all the riverine states. Moreover, the present research reveals that two methods are proved to be useful in determining the Danube water quality, namely: WAWQI (Weighted Arithmetic Water Quality Index) and CCME-WQI (Canadian Council of Ministers of the Environment-Water Quality Index).

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Water quality evaluation of Al-Gharraf river by two water quality indices

Cited by 50 publications

References 19 publications

Water Footprint of Wheat in Iraq

Water Footprint of Wheat in Iraq

Investigating the Impact of Anthropogenic and Natural Sources of Pollution on Quality of Water in Upper Indus Basin (UIB) by Using Multivariate Statistical Analysis

Various methods for calculating the water quality index

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