The Analysis of Water Quality Using Canadian Water Quality Index: Green Belt Project/Kerbala-Iraq

During the last five decades, a huge amount of water pollutants has been recorded in all water resources around the world. Therefore, the water quality has become an important indicator affecting the vitality and productivity of plants, which requires an effective technique to monitor all these pollutants. The main objective of this study is to assess the validity of groundwater for wells located within the boundaries of the Green Belt area in Karbala city/Iraq for irrigation of palm and olive trees. Whereas, the use of saline groundwater as an alternative to available fresh water will promote the sustainable development of water resources. The technique of Water Quality Index (WQI) is a reliable and widely used tool for assessing water quality for various sources, including groundwater. In this study, the Canadian water quality index (CWQI) model was applied to provide a database for planning and monitoring the quality of groundwater in wells located in the study area. Groundwater samples were taken from these wells and tested to find seven parameters which were; pH, CL, Mg, HCO3, EC, Na and Ca. The CWQI values of groundwater for the studied wells ranged from 30 to 35. According to the CWQI scale, the groundwater of all wells is classified as poor water. Therefore, the groundwater of all wells in the study area must be treated before it is used for the purpose of irrigation of palm and olive trees. This study concluded that to ensure good irrigation management in the study area, future changes of groundwater in the study area must be monitored.

Assessment of water quality during the floods in may 2014, Serbia

Floods are considered to be the most common natural disaster which causes more destructive effects than other natural disasters including loss of human life, property and infrastructure damage, as well as a negative impact on social and economic development. Besides these consequences, floods also affect water quality. The aim of this paper is to present water quality impairment caused by the floods in Serbia in May 2014. The parameters of water quality were measured 13 times in 2014 (12 ordinary monthly measurements and one extraordinary measurement during the flood) in hydrological stations Ostruznica and Sabac (on the river Sava) and Badovinci (on the river Drina). The Canadian Water Quality Index (CWQI) was used for water quality assessment. This method calculates the overall water quality and the water quality for specific conditions and purposes including: drinking, aquatic habitats, recreation, irrigation, and livestock. Water quality decline was recorded in all the stations in overall water quality as well as for specific uses. Turbidity and heavy metals values were tens of times higher than normal ranges. The most drastic example was Al with the values which were thousand(s) of times higher than the objective.

Assessment of Groundwater Quality in Al’am District using the Canadian Water Quality Index

The study assesses groundwater quality characteristics in Al’am District which is a part of Salah al-Din Governorate, by use of the Canadian Council of Ministers of the Environment Water Quality Index (CCMEWQI). The samples were taken from six groundwater wells for the assessment and sampling was done at six months per year. Based on CCMEWQI calculated values, the six wells from which the samples collected were in poor rank for drinking purpose. The prime causes of deterioration groundwater quality are total dissolved solids (TDS), and total hardness (TH). This study suggested further improvement and continuous monitoring for the groundwater in the study area to provide safe drinking water

Entropy - System Approach to Assess the Ecological Status of Reservoirs in Armenia

In this article, the quality of water in the reservoirs of Lake Arpi, Lake Yerevan, Akhuryan, Azat, Aparan and Kechut was estimated with usage of the Armenian Water Quality Index. It was established that in the waters of reservoirs the the maximum permissible concentration of copper, vanadium, aluminum, chromium, manganese, iron, NH4+ and NO2- regularly increases. The following computational algorithm was used for determination of the Armenian Water Quality Index values: to determine the number of cases of MPC excess of i-substance or indicator of water –n; to estimate the total amount of cases of the maximum permissible concentration (N) – N = ∑n; to computes log2N, nlog2n and ∑nlog2n; to determine geoecological syntropy (I) and entropy (H): I = ∑ nlog2n/N and H = log2N – I. Then, Geo-Ecological Evolving Organized index index was determined: G = H/I. Further, the total amount multiplicity of MAC exceedances was estimated: (M) - M=∑m and log2M was computed. Finally, Armenian Water Quality Index was obtained: AWQI = G + 0.1log2M. It was established that the Armenian Water Qquality Index showed a linear dependence on the Water Contamination Index, the Specific Combinatory Water Quality Index, the Geo-Ecological Evolving Organized index and an inverse dependence on the Canadian Water Quality Index.

Deep-learning based approach for forecast of water quality in intensive shrimp culture ponds

With the enormous development of aquaculture, reducing the impacts of effluent discharge and improving water quality had become a critical global environmental concern. It is important to assess and predict water quality in the environmental management process of shrimp mariculture. Meanwhile, the accurate forecast of water quality is still in the exploration stage at present. In this study, deep belief networks (DBN) model are used to forecast water quality in intensive shrimp culture. This method based on deep learning includes a five-layered structure to extract relationships between the quantitative characteristic of water bodies and water quality variables. The water quality can be forecasted by the Canadian Water Quality Index (WQI) obtained from the output layer of simulated model. The results show that the DBN model has a great potential to predict the water quality and the ability of generalization and accuracy of model are satisfied.