Seasonal water quality index and suitability of the water body to designated uses at the eastern catchment of Lake Hawassa

2019 ◽  
Vol 27 (1) ◽  
pp. 279-290 ◽  
Author(s):  
Fiseha Bekele Teshome
Keyword(s):  
Water Quality ◽  
Water Body ◽  
Water Quality Index ◽  
Quality Index ◽  
Seasonal Water Quality

scholarly journals Suitability Analysis of Water in an Urban Tropical Lake Using Seasonal Water-Quality Index

2016 ◽  
Vol 02 ◽  
pp. 83
Author(s):  
Madhavi Tiwari ◽  
Anil Kumar Dwivedi ◽  
◽  
Keyword(s):  
Water Quality ◽  
Water Body ◽  
Water Quality Index ◽  
Quality Index ◽  
Winter Season ◽  
Oxygen Demand ◽  
Suitability Analysis ◽  
Public Consumption ◽  
Different Seasons ◽  
Seasonal Water Quality

This study deals with the study of water-quality index (WQI) of a tropical, urban water body in Gorakhpur region (India). Water-quality index was determined on the basis of various physico-chemical parameters like pH, temperature, total solids, total dissolved solids, total suspended solids, dissolved oxygen, biological oxygen demand, hardness, calcium, magnesium, etc. Then, on the basis of calculated WQI, the water was correlated for its use for public consumption, recreation, or any other purpose. A number of parameters directly regulate the utility of water for a particular purpose. The water-quality index obtained for the water body in different seasons of study periods, i.e., rainy season, winter season, and summer season are 78.29, 74.01, and 116.94, respectively; this indicates the water quality of the collected samples to be very poor.

scholarly journals Assessment of Water Quality of Okomu Wetland Using Water Quality Index

2020 ◽  
Vol 4 (2) ◽  
pp. 450-457
Author(s):  
S. I. Ehiorobo ◽  
A. E. Ogbeibu
Keyword(s):  
Water Quality ◽  
Water Body ◽  
Water Quality Index ◽  
Quality Index ◽  
Anthropogenic Activities ◽  
Physicochemical Characteristics ◽  
Poor Quality ◽  
Quality Data ◽  
Water Quality Data

The water quality of the Okomu Wetland was evaluated using the Water Quality Index (WQI) technique which provides a number that expresses overall water quality of a water body or water sample at a particular time. Sampling of physicochemical parameters spanned two years covering the wet and dry seasons and the water quality data were obtained from 10 sampling locations; Ponds 36, 52, 54, 61, 64, 90, 94, Arhakhuan Stream, Okomu River (Agekpukpu) and Okomu River (Iron bridge) all within the Okomu National Park. Parameters such as Total Dissolved Solids (TDS), Turbidity, pH, Electrical conductivity (EC), Chlorine (Cl), Nitrate (NO3), Sulphate (SO4), Sodium (Na), Magnesium (Mg), (Iron) Fe, Chromium (Cr), Zinc (Zn), Copper (Cu), Manganese (Mn), Lead (Pb), and Nikel (Ni) were used to compute WQI and the values obtained for the wetland ranged between 34.36 and 167.28. The Index shows that pond 36, 52 and 54 are unfit for drinking with values between 103.86 and 167.28; ponds 61 and 64 are of the very poor quality category with WQI values of 95.19 and 92.44 respectively, Pond 90, pond 94, Arhakhuan Stream and Okomu River (Agekpukpu) are of poor quality and WQI values between and 53.58 and 73.15. Whereas, the Okomu River (Iron bridge) is within the good water quality (34.36) category. The Okomu River by Iron bridge is of good quality rating while other sampled points were of poor, very poor or unfit for drinking though these water bodies are mostly free from anthropogenic activities because of the conservative status of the study area. A major source of pollution within the wetland is surface runoff. The water quality of the wetland may not be suitable for man’s consumption especially pond water which are majorly impacted by runoff, yet very important for the survival and sustenance of the forest animals and plants. The water quality index (WQI) interprets physicochemical characteristics of water by providing a value which expresses the overall water quality and thus, reveals possible pollution problems of a water body. It turns complex water quality data into information that is easily understandable and usable by scientists, researchers and the general public.

scholarly journals Water Quality Index (WQI) as a Potential Proxy for Remote Sensing Evaluation of Water Quality in Arid Areas

Water ◽  
2021 ◽  
Vol 13 (22) ◽  
pp. 3250
Author(s):  
Fei Zhang ◽  
Ngai Weng Chan ◽  
Changjiang Liu ◽  
Xiaoping Wang ◽  
Jingchao Shi ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Water Body ◽  
Water Quality Index ◽  
Quality Index ◽  
Lake Basin ◽  
Ebinur Lake ◽  
Remote Sensing Techniques ◽  
The Relationship ◽  
Ebinur Lake Basin

Water Resource Sustainability Management plays a vitally important role in ensuring sustainable development, especially in water-stressed arid regions throughout the world. In order to achieve sustainable development, it is necessary to study and monitor the water quality in the arid region of Central Asia, an area that is increasingly affected by climate change. In recent decades, the rapid deterioration of water quality in the Ebinur Lake basin in Xinjiang (China) has severely threatened sustainable economic development. This study selected the Ebinur Lake basin as the study target, with the purpose of revealing the response between the water quality index and water body reflectivity, and to describe the relationship between the water quality index and water reflectivity. The methodology employed remote sensing techniques that establish a water quality index monitoring model to monitor water quality. The results of our study include: (1) the Water Quality Index (WQI) that was used to evaluate the water environment in Ebinur Lake indicates a lower water quality of Ebinur Lake, with a WQI value as high as 4000; (2) an introduction of the spectral derivative method that realizes the extraction of spectral information from a water body to better mine the information of spectral data through remote sensing, and the results also prove that the spectral derivative method can improve the relationship between the water body spectral and WQI, whereby R2 is 0.6 at the most sensitive wavelengths; (3) the correlation between the spectral sensitivity index and WQI was greater than 0.6 at the significance level of 0.01 when multi-source spectral data were integrated with the spectral index (DI, RI and NDI) and fluorescence baseline; and (4) the distribution map of WQI in Ebinur Lake was obtained by the optimal model, which was constructed based on the third derivative data of Sentinel 2 data. We concluded that the water quality in the northwest of Ebinur Lake was the lowest in the region. In conclusion, we found that remote sensing techniques were highly effective and laid a foundation for water quality detection in arid areas.

scholarly journals Assessment of Quality Index of Water by Using Different Physico-Chemical Parameters in Rabale Waterbody, Navi-Mumbai, Maharashtra, India

2021 ◽  
Vol 7 (2) ◽  
Author(s):  
Singh Pooja ◽  
Jadhav Anita S
Keyword(s):  
Water Quality ◽  
Chemical Oxygen Demand ◽  
Water Body ◽  
Water Quality Index ◽  
Quality Index ◽  
Oxygen Demand ◽  
Quality Data ◽  
Chemical Parameters ◽  
Rapid Urbanization ◽  
Physico Chemical

Water is a must for all living things. Reservoir and lake water is used for a variety of purposes, including drinking water, agricultural, commercial, recreational, and aquaculture. However, due to rising population pressures, which has resulted in rapid urbanization, industrialization, and modern agricultural practices, water pollution has become a major issue in recent years. The water quality index is a single number that reflects overall water quality at a specific place and time. To compute, water quality index (WQI) we used Temperature, pH, Dissolved Oxygen (DO), Biochemical Oxygen Demand (B.O.D), Chemical Oxygen Demand (C.O.D), Alkalinity, Electrical Conductivity, Turbidity, and Chemical Oxygen Demand (C.O.D), Nitrite-Nitrogen, Nitrate-Nitrogen and Hardness were the physico-chemical parameters investigated in this study. The water quality index is to transform complicated water quality data into information that the general public can use. The Water Quality Index was calculated using the Weighted Arithmetic Water Quality Index (WQI). The measured WQI was then used to assess the water quality in Rabale water body. The water quality index (WQI) of the lake was 49.813, 53.483, and 53.045 during the pre-monsoon, monsoon, and post-monsoon periods, respectively. When comparing seasonal variations, WQI values show that water status is fairly good during the pre-monsoon but is low during the monsoon and postmonsoon seasons, thus water from Rabale water body may be used for a variety of industrial purposes.

Разработка нового метода оценки качества загрязненной воды

2020 ◽  
Author(s):  
F.G.O. Agaev ◽  
B.L.K. Dzhafarova ◽  
A.D.K. Alieva
Keyword(s):  
Water Quality ◽  
Water Body ◽  
Water Quality Index ◽  
Quality Index ◽  
Cumulative Effect ◽  
World Health ◽  
Sampling Point ◽  
Regression Estimate ◽  
Calculated Parameter ◽  
Health Organization

Статья посвящена разработке нового метода оценки качества загрязненной воды водоисточников. В настоящее время наиболее широко используется индекс качества воды, являющийся расчетным параметром, показывающим суммарный эффект всех факторов, характеризующих качество воды. Дан краткий обзор показателей оценки загрязненности водоемов. В качестве базового положения проводимых исследований выбран известный факт о наличии некоторой статистической взаимосвязи между величиной WQIj водного объекта и видом отражательной характеристики. На основе двух известных показателей загрязненности водоемов: индекса качества воды WQI, рекомендованного Всемирной организацией здравоохранения, и многофакторной регрессионной оценки сформирован новый показатель в виде скалярного многочлена, численно равного величине WQI для исследуемой точки отбора проб. Показана возможность использования информации базы данных о загрязненности исследуемого водоема для вычисления предложенной оценки его загрязненности.The article dwells upon the development of a new method of estimating the quality of contaminated water in water sources. At present, the water quality index is most widely used which is a calculated parameter indicating the cumulative effect of all factors characterizing the water quality. A brief review of the indicators for estimating the pollution of water bodies is given. A well-known fact about the presence of some statistical relationship between the value WQIj of a water body and the type of the reflectance profile is selected as the fundamental proposition of the conducted studies. On the basis of two known indicators of the water body pollution: WQIj water quality index recommended by the World Health Organization, and multifaceted regression estimate, a new indicator is developed in the form of a scalar polynomial, numerically equal to WQIj value for the studied sampling point. The possibility of using the database information on the pollution of the studied water body is shown to calculate the proposed estimation of its pollution.

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