Development of site suitability analysis system for riverbank filtration

Sang-il LEE, Sang-sin LEE*

Department of Civil and Environmental Engineering, Dongguk University, Seoul100-715, Korea

Development of site suitability analysis system for riverbank filtration

Sang-il LEE, Sang-sin LEE*

Department of Civil and Environmental Engineering, Dongguk University, Seoul100-715, Korea

Site selection plays a crucial role in riverbank filtration for sustainable water availability and quality. Choosing the most appropriate from among multiple candidate sites requires a complex procedure, involving many tangibles and intangibles. In this study, the Analytic Hierarchy Process (AHP), which selects the optimal alternative by hierarchically classifying various attributes and then quantifying the importance of each attribute, was used to prioritize candidate locations for riverbank filtration. A GIS-based computer program was developed to automate the assessment process. The developed software was applied to the Han River in Korea. Analysis of four candidate sites reveals that a site that has better water quality and connectivity to the neighboring purification facility is more suitable than other locations.

riverbank filtration; AHP; site suitability; Han River

1 Introduction

In European countries such as Germany and the Netherlands, riverbank filtration (RBF) has been successfully practiced as a way of enhancing the quality of the water supply for over 150 years (Grischek et al. 2002; Tufenkji et al. 2002; Eckert and Irmscher 2006). In Germany, RBF is used for 15%-16% of the total drinking water. RBF has also been used for drinking water in many cities in the United States. RBF relies on the streambed and aquifer matrixes to improve source water quality and to reduce pathogens through induced infiltration. The removal or degradation of contaminants is achieved through a combination of physicochemical and biological processes.

Tap water in Korea mainly comes from surface water. A more advanced water treatment process is needed due to the risk of accidental spills and the deterioration of surface water quality. Because of the high cost of water treatment and public concerns, decision makers are turning to RBF as an alternative to the conventional abstraction of surface water. Changwon City started supplying domestic water treated through RBF in 2001, the first time in Korea (Office of Waterworks Changwon City 2009). The city continues to expand the facility, and thewater supply is now 70 000 m3/d. A neighboring city, Chil-seo Myeon in Ham-an Gun, has also been supplying riverbank-filtered water (20 000 m3/d) since 2003. Seoul, the capital of Korea, is pursuing the introduction of RBF to enhance public trust in tap water. Table 1 shows some examples of riverbank filtration throughout the world.

Table 1 Major examples of riverbank filtration

The Analytic Hierarchy Process (AHP), which allows for the selection of the optimal alternative by hierarchically classifying the various attributes and then measuring the importance of each attribute, was developed by Saaty (1980). The novelty of AHP lies in the stratification of a decision-making problem with many objectives, evaluation criteria, and decision-making variables. Due to its simplicity and versatility, AHP has been used in various settings to make decisions (Saaty 2008). AHP involves dividing a sophisticated problem into sub-elements, organizing them, forming an orderly hierarchical structure, determining the relative importance of the elements through pairwise comparison, and finally synthesizing human judgments to provide a total order (Zhang 2009). There have been some studies related to site suitability analysis using AHP. Wu (1998) developed a prototype of a simulation model based on cellular automata (CA) and multi-criteria evaluation (MCE) and integrated with geographic information system (GIS) using the AHP method. Reza (2005) studied the ways in which AHP frames the site evaluation problem and can aid in making decisions involving multiple criteria, factor diversity, and conditions of uncertainty.

2 Suitability analysis using AHP

Applying the AHP procedure involves four basic steps (Fig. 1): (1) definition of the problem; (2) construction of the decision hierarchy; (3) comparative judgment, or data collection and execution of pairwise comparison for elements in the hierarchical structure; and (4) synthesis of priorities, or evaluation of the overall priority rating.

The decision hierarchy is structured from the top, with the goal of the decision, through the intermediate levels to the lowest level. Once a hierarchy is established, pairwise comparison is made. The pairwise comparison makes the complicated comparison of entire elements easy. The degree of relative importance of elementsiandjis assigned according to a 1-9 scale, as shown in Table 2.

Fig. 1 Organized decision-making in AHP

Table 2 Fundamental scale

When the number of elements is four, the pairwise comparison matrix can be formed as follows

The normalized pairwise comparison matrix (or normalized matrix) is obtained from the following equation:

where

andnis the size of the normalized matrix.

The priority is obtained from Eq. (4):

wherePjis also called the relative preference or the relative importance weight of elementj. In other words, priorities are obtained by adding each row of the normalized matrix anddividing by the size of the matrix. The consistency ratio (CR) needs to be calculated to check the logical consistency of the pairwise comparison. According to Saaty (1980),CRcan be calculated by dividing the consistency index (CI) by the random index (RI):

whereCIis defined as

whereλmaxis the largest eigenvalue of the pairwise comparison matrix, andRIis given in Table 3. IfCRis less than 0.1, the pairwise comparison can be regarded as reliable.

Table 3RIforn×npairwise comparison matrix

Finally, the suitability index can be calculated by accumulating the multiplication of priorities obtained from the top to the bottom level for theith element.

3 System development

3.1 Analysis frame

To construct a hierarchy and to make pairwise comparisons for the AHP analysis of riverbank filtration, influential elements and their corresponding degrees of importance must be deduced. Comprehensive investigation of previous development projects provided the initial setting (Table 4). Of the 28 elements involved in the development of riverbank filtration in previous projects, we selected the 21 most influential elements for analysis (Fig. 2). Data availability and specialists’ judgments were taken into consideration.

Table 4 Influential elements considered for riverbank filtration projects

Fig. 2 Elements of analysis of site suitability for riverbank filtration

Verification of deduced importance values from previous cases was conducted with an expert survey. Twenty-five experts currently working in the field of water resources participated in the survey. There were eighteen respondents. Three of them, who declared themselves non-specialists in riverbank filtration and site suitability analysis, were excluded. In the final analysis, the scores for the included experts’ knowledge of riverbank filtration and site suitability analysis were 6.73 and 7.73 out of 10, respectively.

Table 5 shows the list of influential elements along with their degree of importance. The scales derived from previous projects are similar to those derived from the expert survey. This feature confirms the justification of the values used in the analysis.

Table 5 Influential elements and scales of importance from previous cases and expert survey

Table 5 Influential elements and scales of importance from previous cases and expert survey (Continued)

The pairwise comparison matrix down to the second level is shown along with priorities and consistency in Table 6. The same method can be applied to the lower levels.

Table 6 Pairwise comparison matrix down to level 2

3.2 System configuration

An AHP-based computer program analyzing the optimal site for riverbank filtration was devised (Fig. 3). Originally, the system was developed for a site suitability analysis system for conjunctive use (SASCU) of surface water and groundwater. It was developed using Avenue (a script language for the GIS software ArcView) and Visual Basic, based on the Microsoft Windows environment (Fig. 4). The system accesses the spatial and attribute database, queries information, and computes the suitability. It integrates the information-searching unit and the AHP-modeling unit. With the aid of the information-searching capability, the task of accessing the database and obtaining the appropriate values for each attribute appearing in the analysis becomes simple and almost automatic. Meanwhile, the AHP-modeling unit analyzes the suitability based on the hierarchy and the relative importance of attributes (Lee and Lee 2008).

Fig. 3 SASCU sample screen

Fig. 4 SASCU system configuration

4 Application

The Han River Basin is the largest basin in the central part of the Korean Peninsula, and constitutes about 23% of its total area (Fig. 5). The basin has an area of 26 356 km2and a length of 481.7 km. In some regions of Kyung-gi Province, including Seoul, gneiss complexesfrom the pre-Cambria Archeozoic Era are widely distributed. Granites that have intruded on these complexes in later periods constitute about 36% of the Seoul region. The granite-filled regions are quite water-permeable because their component particles are relatively large, in contrast to the gneiss- and schist-filled regions, where particles are so small that it is hard for the groundwater to remain in the alluvial layer. This study mainly deals with the Seoul area.

Fig. 5 Han River Basin and candidate locations for riverbank filtration

The Seoul area of the Han River Basin is highly urbanized, which makes it hard to find candidate locations for riverbank filtration. However, eleven terrace areas turned out to be acceptable for initial consideration according to various previously conducted field investigations. Preliminary analysis ruled out seven of them, leaving four for further analysis (Table 7 and Fig. 5).

Table 7 Candidate sites and their characteristics

The site suitability analysis, for selecting the optimal site, was conducted using SASCU. Spatial and attribute databases were established using an online database in the Water Management Information System (http://www.wamis.go.kr), reports from the Office of Waterworks Seoul Metropolitan Government (2006), and numerical maps. Table 8 shows each influential element and suitability index for four candidate locations based on the performance of SASCU. The Kwangnaru district, which has advantages over other sites in terms of good water quality and a close connection to an existing water purification facility, was selected as the optimal site.

Table 8 Suitability index of candidate sites

5 Conclusions

In order to determine the optimal site for riverbank filtration, various hydrogeologic, water quality, and socioeconomic factors should be considered. As for existing riverbank filtration sites, there has been a focus on the assessment of available water and the well design or construction. Selecting the appropriate site has been treated as a minor problem and the process has been carried out in a conventional way, relying on the subjective experience of experts. A systemic approach to the selection of the most suitable site of several candidates would increase the objectivity of the decision-making process and make complex decision-making procedures efficient. This paper developed a site suitability analysis system based on AHP.

Twenty-one elements believed to influence the performance of riverbank filtration were selected and constituted a hierarchy. To enhance the credibility of the AHP analysis, especially the pairwise comparison, experts’ opinions were sought out through a survey. A GIS-based decision support system (SASCU) incorporating both spatial and attribute data was developed. To verify the applicability, we applied SASCU to four candidate locations along the Han River in Korea.

The Kwangnaru district was selected from the candidate locations as the optimal site. The analysis indicated that a site having high water quality and better connectivity to the neighboring purification facility is more advantageous than other locations.

AHP turned out to be a useful tool for assessing a region’s suitability for riverbankfiltration. We believe that the developed system can assist decision makers in finding an appropriate location for riverbank filtration among many candidates, which involves an immense amount of spatial and attribute data. In addition, the impact of including or omitting a certain factor in the analysis can be easily estimated using the system.

Eckert, P., and Irmscher, R. 2006. Over 130 years of experience with riverbank filtration in Düsseldorf, Germany.Journal of Water Supply:Research and Technology-AQUA, 55(4), 283-291. [doi:10.2166/ aqua.2006.040]

Grischek, T., Schoenheinz, D., Worch, E., and Hiscock, K. M. 2002. Bank filtration in Europe - An overview of aquifer conditions and hydraulic controls. Dillon, P., ed.,Management of Aquifer Recharge for Sustainability, 485-488. Rotterdam: Balkema.

Lee, S. I., and Lee, S. 2008. Site suitability analysis for riverbank filtration in the Han River, Korea.Proceedings of the IAHR-APD Congress, 236-239. Beijing: Tsinghua University Press.

Office of Waterworks Changwon City. 2009.Introduction of Riverbank Filtration. Changwon City: Changwon City Hall. http://sudo.changwon.go.kr/05/05_05_05.jsp. (in Korean) [Retrieved March 9, 2010].

Office of Waterworks Seoul Metropolitan Government. 2006.Interim Report: Feasibility Study for the Introduction of Induced Water Abstraction. Seoul: Seoul Metropolitan Government. (in Korean)

Reza, B. K. 2005. A new method for site suitability analysis: The analytic hierarchy process.Environmental Management, 13(6), 685-693. [doi:10.1007/BF01868308]

Saaty, T. L. 1980.The Analytic Hierarchy Process. New York: McGraw-Hill.

Saaty, T. L. 2008. Decision making with the analytic hierarchy process.International Journal of Services Sciences, 1(1), 83-98. [doi:10.1504/IJSSCI.2008.017590]

Tufenkji, N., Ryan, J. N., and Elimelech, M. 2002. The promise of bank filtration.Environmental Science Technology, 36(21), 423-428. [doi:10.1021/es022441j]

Wu, F. 1998. SimLand: A prototype to simulate land conversion through the integrated GIS and CA with AHP-derived transition rules.International Journal of Geographical Information Science, 12(1), 63-82. [doi:10.1080/136588198242012]

Zhang, H. 2009. The analysis of the reasonable structure of water conservancy investment of capital construction in China by AHP method.Water Resources Management, 16, 1-18. [doi:10.1007/ s11269-008-9261-9]

This work was supported by a grant (3-4-3) from the Sustainable Water Resources Research Center of the 21st Century Frontier Research Program.

*Corresponding author (e-mail:sinslee@nate.com)

Received Sep. 28, 2009; accepted Nov. 25, 2009