The Analysis of Ground Water Quality Status using Linear Regression Method

Author(s):  
Rahane Prashant Bhausaheb ◽  
M. V Jadhav
2012 ◽  
Vol 9 ◽  
pp. 52-56
Author(s):  
Bishnu Pandey ◽  
Suman Shakya

This study assesses the rural drinking water quality status in Central Development Region of Nepal. With a total of 250 samples collected from 15 districts of the region, drinking water quality of spring water and ground water representing hill and Terai (lowland) regions were tested and compared for their physicochemical parameters and faecal coliform contamination.None of the spring samples as well as ground water samples violated National Drinking Water Standards (NDWS) for electrical conductivity (EC), total dissolved solids (TDS), total suspended solids (TSS), appearance, chloride and nitrate. Similarly none violated the standards for total hardness (TH) indicating soft nature of the water. The spring samples were within the NDWS for manganese (Mn) and iron (Fe) whereas 15.4% and 39.0% of the ground water samples violated the standards for manganese and iron, respectively. Gravity water is found to be more alkaline than ground water. Faecal coliforms were the most problematic in both types of sources followed by Ammonia (NH3) and pH in spring sources and by iron, Mn, pH and ammonia in ground water sources, respectively. Spring sources were more contaminated by bacteria than ground water sources. Correlation and regression analysis revealed highly significant correlations between EC and TDS (r=0.979) and between CaH and TH (r=0.988) in ground water suggesting that aquifer chemistry of ground water to be mainly controlled by EC, TDS, TH, and CaH. Similarly, highly significant correlations were found between the following pairs in gravity water: EC and TDS (r=0.983), TA and TDS(r=0.853), CaH and TDS (r=0.912), TH and TDS (r=0.955), EC and CaH (r=0.898), and between CaH and TH (r=0.951).DOI: http://dx.doi.org/10.3126/hn.v9i0.7074 Hydro Nepal Vol.9 July 2011 52-56


2012 ◽  
Vol 3 (4) ◽  
pp. 75-77
Author(s):  
Prof. A.B. More Prof. A.B. More ◽  
◽  
Prof. C.S. Chavan Prof. C.S. Chavan ◽  
Ajoy Gurung ◽  
Pramod Sarwade ◽  
...  

Author(s):  
Mohammad Shohidul Islam ◽  
Sultana Easmin Siddika ◽  
S M Injamamul Haque Masum

Rainfall forecasting is very challenging task for the meteorologists. Over the last few decades, several models have been utilized, attempting the successful analysing and forecasting of rainfall. Recorded climate data can play an important role in this regard. Long-time duration of recorded data can be able to provide better advancement of rainfall forecasting. This paper presents the utilization of statistical techniques, particularly linear regression method for modelling the rainfall prediction over Bangladesh. The rainfall data for a period of 11 years was obtained from Bangladesh Meteorological department (BMD), Dhaka i.e. that was surface-based rain gauge rainfall which was acquired from 08 weather stations over Bangladesh for the years of 2001-2011. The monthly and yearly rainfall was determined. In order to assess the accuracy of it some statistical parameters such as average, meridian, correlation coefficients and standard deviation were determined for all stations. The model prediction of rainfall was compared with true rainfall which was collected from rain gauge of different stations and it was found that the model rainfall prediction has given good results.


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