Evaluation of the surface water quality using global water quality index (WQI) models: perspective of river water pollution Md. Habibur Rahman Bejoy Khan, Amimul Ahsan, M. Imteaz, Md. Shafiquzzaman & Nadhir Al-Ansari Scientific Reports volume 13, Article number: 20454 (2023) Cite th...
The GEP was able to successfully predict the WQI with high accuracy (R 2 = 0.983 and MAE = 0.295). The statistical parameters indicate that, although the ANNs with R 2 = 0.988 and MAE = 0.013 produced better results compared with GEP, the GEP-based formula is more useful for practical ...
WQI is a widely used parameter for water-quality classification. For water-quality level estimation, Brown et al. [8] proposed an index. The index is computed based on water physiochemical parameters such as pH, the concentration of pollutants, dissolved oxygen, temperature, turbidity, and ...
Commonly, WQI models involve four consecutive stages; these are (1) selection of the water quality parameters, (2) generation of sub-indices for each parameter (3) calculation of the parameter weighting values, and (4) aggregation of sub-indices to compute the overall water quality index. ...
The aim of this paper is to present a new approach to assessing water quality by using a new index: "Total Water Quality Index" ("TWQI"). TWQI Method has advantages over other methods in evaluating water quality and has been applied in Belgium, the United States of America ("WQI") ...
2.4. Water Quality Index (WQI) Water quality index is a useful and effective way to determine the overall quality of water. It is also a very useful average tool used to convert large number of water quality data into a single cumulatively derived number. The WQI model gives information abou...
water quality index in Nfifikh watershed in Morocco. Their RMSE and R2values were 1.88 and 0.5 for KR, and 6 (mmolc l-1) and 0.6 for SAR. Based on Figs.4and5and Table4, which confirm the results from Fig.2, the SW model is superior for prediction of IWQI. SW model reported ...
The water quality index (WQI) has been used to identify threats to water quality and to support better water resource management. This study combines a machine learning algorithm, WQI, and remote sensing spectral indices (difference index, DI; ratio inde
3.3. WQI prediction model This section demonstrated the development of the principal component regression model to predict the water quality index. PCR comes with the idea that performed PCA on the dataset and then performed the regression model on the new PCs. The proposed PCR method for predicti...
using normalized curves. The multiplicative formula to produce a single WQI-NSF value, operates the dimensionless subindex raised to a power, or the weight of importance of each variable. More recently, in 2001, emerged the WQI-CCME23,24, a statistical index to assess the quality of surface ...