GLM and joint GLM techniques in hydrogeology: an illustration Online publication date: Sat, 16-Aug-2014
by Rabindra Nath Das; Jinseog Kim
International Journal of Hydrology Science and Technology (IJHST), Vol. 2, No. 2, 2012
Abstract: In regression models with positive observations, estimation is often based on either the log-normal or the gamma model. Generalised linear models and joint generalised linear models are appropriate for analysing positive data with constant and non-constant variance, respectively. This article focuses on the use of these two techniques in hydrogeology. As an illustration, groundwater quality factors are analysed. Softness, non-alkalinity, content dissolved oxygen, chemical oxygen demand, chloride content and electrical conductivity are all the basic positive characteristics (i.e., values are positive in nature) for good drinking water. This article identifies the causal factors of these basic quality characteristics of groundwater at Muzaffarpur Town, Bihar, India, using the above techniques. Many statistical significant factors for these six basic quality characteristics of groundwater are detected. In the process, probabilistic model for each characteristic is developed. Effects of different factors on each characteristic are examined.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Hydrology Science and Technology (IJHST):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook