Site Suitability for RBF Using Geospatial Technology in Tungabhadra Sub-basin, India

Abstract

As per the 2017 global reports, 63 million Indians are living in rural areas without access to the safe drinking source of water. Access to the safe drinking water was declared as a human right by the United Nations but remains a challenge for India. Due to increase in demand of water, 30% of urban and 90% of rural households completely depend on untreated surface or groundwater, which causes serious health issues. It is estimated that 21% of communicable diseases in India are water related. These problems have raised concern on alternative, sustainable treatment solutions to manage pollution of source of water and to continue the supply of safe drinking water to the community. Many organizations and universities in India have been working to tackle the access to safe water problems with the novel approaches. In this context, a natural filtration technique, river bank filtration (RBF) is one of the alternatives which is proved to be cost-efficient technology for providing safe drinking water The crucial step in the development of River Bank Filtration project is site selection. However, site selection for RBF using conventional methods are costly, time consuming and restricted to small area. This study highlights the use of geospatial technology to develop the site suitability for river bank filtration locations based on a case study in Tungabhadra river stretch between Mudenur and Halavagalu villages. Though several researches have carried out investigation on site selection for RBF, this is the first attempt to use geospatial technology in particular. The crucial parameters which influence site suitability for RBF are hydrology, hydrogeology, water supply, water quality, land use/land cover etc. The spatial maps were prepared using these parameters and weighted overlay analysis was done after assigning weights to the spatial maps in the GIS environment. The developed site suitability map shows the villages namely Halavagalu, Nitturu, Konnatambigi, Somlapur, Nitturubasapuram, Yellapur, Hirebidri and some parts of Udgatti, Airani, Tavaragundi areas were found to be suitable for implementing the RBF.

Methodology for evaluation of potential sites for large-scale riverbank filtration

“…Without this, any abstracted water will consist mostly (or exclusively) of groundwater and not bank filtrate (BF). This condition is indispensable for RBF and should be included in any methodology independently of region or goal, although this is not the case for most of the aforementioned methods, which simply assume connection is always present (Lee and Lee 2010;Srisuk et al 2012;Patil et al 2020). Wang et al (2016) weight it equally with other criteria, which results in the potential for a high mark to be achieved for sites where RBF is not feasible.…”

“…Nonetheless good indicators that a site has low clogging potential are a high river shear stress, high area of infiltration in the river and high quality of infiltrated water (Schubert 2002;Hubbs 2006a, b;Grischek and Bartak 2016). Of the previous methods, only two have considered clogging in their evaluation (Wang et al 2016;Patil et al 2020).…”

“…Previous methods give high weights for surface-water quality parameters (Lee and Lee 2010;Wang et al 2016;Patil et al 2020), which can at times disqualify a potentially suitable site where RBF application would be of great benefit. Furthermore, the choice of chemical parameters for grading has also been in the authors' opinions inadequate.…”

“…Depending on the site selection goals, social aspects can and have been taken into consideration in other studies (Lee and Lee 2010;Srisuk et al 2012;Boving et al 2019;Patil et al 2020). This includes population density, availability of land, insufficient or low-quality water supply from other sources, availability of electricity, and proximity to villages/ cities which may limit pipeline construction.…”

“…To date, there is no consensus on the optimal methodology to evaluate site suitability for RBF. Several works in the past have highlighted the relevant parameters for RBF application (Ray et al 2002;Schubert 2002;Hubbs 2006a, b;Shamrukh 2011), but only a few researchers have offered quantitative methodologies to evaluate RBF sites (Lee and Lee 2010;Srisuk et al 2012;Wang et al 2016;Patil et al 2020). However, in the view of the authors, the current methodologies still have many limitations (further discussed in section 'Method overview and review of previous methods'), including the overweighting of low relevance variables, the arbitrary assignment of parameters weights and the requirements of datasets that are impractical to obtain.…”