

ORIGINAL ARTICLE 



Year : 2010  Volume
: 64
 Issue : 10  Page : 455467 

Modelling population growth on public water and sanitation facilities using GIS and statistics: A case study of Aboabo, Ghana
Jonathan Arthur QuayeBallard^{1}, Ru An^{2}
^{1} Department of Geographic Information Science, School of Earth Science and Engineering, Hohai University, Nanjing, 210098, China; Department of Geomatic Engineering, College of Engineering, Kwame Nkrumah University of Science and Technology (KNUST), Kumasi, Ghana, ^{2} Department of Geographic Information Science, School of Earth Science and Engineering, Hohai University, Nanjing, 210098, China,
Date of Web Publication  29Sep2012 
Correspondence Address: Jonathan Arthur QuayeBallard Hohai University, International Student Hostel, Room  211, No. 1, Xikang Road, Gulou District, Nanjing 210098, China
DOI: 10.4103/00195359.101807
Background: Effect of population increase on public water and sanitation facilities in densely populated area, Aboabo, Kumasi, Ghana. Materials and Methods: Town sheet maps, layout and population census data of Aboabo. GPS for observing spatial locations existing water and sanitation facilities and field verification exercise in the study. GIS for building geodatabase, digitization and Cartographic Visualization. Questionnaires were used to collect nonspatial information on the sanitation facilities and all public facilities. Results: GIS and a Statistical Approach have been respectively used to develop cartographic and mathematical models to analyse, predict and visualize the effect of population increase on public water and sewage facilities in densely populated area. The developed mathematical models correlates with the population at each instance to the required number of water accessible points or standing pipes as well as the number of required public toilet (sewage) facilities. The cartographic and mathematical models provides an efficient and effective means of mitigating diseases associated with water and sanitation; and informs planners and assembly members of the effects of increasing population on public facilities for proper future planning and geospatial decision making; and to ensure proper infrastructural management at the community levels. Conclusions: Effective decision support systems for analysing, predicting and visualizing public water and sewage facilities in densely populated area. Draws the awareness of the government, concerned groups and nonGovernmental Organizations (NGO's) to the extreme detrimental effect that the increase in population has, especially on public water and sewage facilities and how it can be managed at the community level.
Keywords: GIS, GPS, health, statistical approach, water and sanitation facilities
How to cite this article: QuayeBallard JA, An R. Modelling population growth on public water and sanitation facilities using GIS and statistics: A case study of Aboabo, Ghana. Indian J Med Sci 2010;64:45567 
How to cite this URL: QuayeBallard JA, An R. Modelling population growth on public water and sanitation facilities using GIS and statistics: A case study of Aboabo, Ghana. Indian J Med Sci [serial online] 2010 [cited 2014 Oct 24];64:45567. Available from: http://www.indianjmedsci.org/text.asp?2010/64/10/455/101807 
¤ Introduction   
Almost 1 billion people worldwide lack clean drinking water, 2.4 billion people have no access to hygienic sanitation facilities, and 1.2 billion lacks sanitation facilities. ^{[1]} Ghana as part of the SubSaharan Africa is not exception in this categorization in terms of growing cites and slow pace in developing water and sanitation facilities. The size and composition of a country's population can exert a powerful influence on her public facilities. Water and sanitation facilities are those worst affected in densely populated or fast growing population areas as a result of the fast pace of congestion coupled with increasing birth over deaths at the community levels, making population growth coupled with urbanization outpace development of sanitation infrastructure. Sanitation facilities mentioned in this research are the public toilet facilities solely constructed by the Government of Ghana for densely populated areas where there are no toilet facilities in individual homes. Generally, the population increase has a tremendous effect on infrastructural facilities and if unchecked could put unnecessary pressure on water and sanitation facilities. In developing countries, population growth coupled with urbanization has outpaced the development of sanitation infrastructure, leaving the urban poor, virtually without sanitation facilities in many countries. Global shortage of water and sanitation accounts for children dying due to illnesses related to poor access to water and hygienic sanitation. ^{[2]} Ghana's water and sanitation infrastructure is at a gradual developmental pace. Urbanized areas of Ghana are concentrated with very high population density. The consequences are the extreme pressures exerted on public infrastructures in these regions. Water and sanitation facilities are worst affected in these densely populated or fast growing population areas as a result of the fast pace of congestion coupled with the increasing birth over death rates at the community levels. In Ghana, efforts are being made by the Government, NonGovernmental Organizations (NGO's) and other aiding agencies to alleviate this problem; however, inadequate funds is a major setup back.
Aboabo, the study area located within the Kumasi metropolitan area of Ghana is a classical area of increase in population with a noncorresponding increase in infrastructural facilities such as water and sanitation facility. The area had a population of about 22,634 in 1984 with only five (5) toilet facilities. When the population increased to 34,206 in 2000, only one additional public toilet facility was added. Currently, the situation remains the same. The inadequacy of these facilities coupled with their deplorable state has encouraged sanitation problems in the area and its nearby surrounding leading to outbreak of diseases such as cholera and diarrhoea. The few standing public taps hardly flow. Inhabitants traverse several meters for accessibility to water. This is typical of the assertion made by ^{[3]} that over one billion people currently live in urban slums, 300 million of which do not have access to a clean water supply, while 400 million people do not have access to improved sanitation.
The use of Geographic Information System (GIS) applications can enable water and environmental professionals to manage allocation of the few facilities to populations as well as plan for additional location of facilities that can carry the ever increasing population with great precision. Related works are those by Gopal et al.^{[4]} , Baumann ^{[5]} and Zeilhofer et al.^{[6]} . GIS functions as tool that displays a set of series of layered thematic maps on a computer screen that shows spatial features and their relationships on the earth's surface and allows the integration of Global Position System (GPS) data into its database without difficulty. This added advantage is why the GPS was used to observe the coordinates water and sanitation facilities. GIS allows queries to be done to answer questions on the number of water and sanitation facilities that will be needed in the years come. ^{[4],[7],[8],[9],[10],[11]} GIS can effectively be used in population management and address matching; ^{[1],[12],[13],[14]} and also serve as a platform to equip Assemblymen and District Chief Executive as a tool to help in proper planning of community. Galley studies fell short of estimating the number of facilities that will be required in future years depending on the driving force of population growth. It is also based on this gab that the research was conducted to adopt the statistical, which is basically a process of creating a mathematical representation of the water and sanitation facilities to better gain an insight into the effects of population growth on the public facilities. The paper creates a model with the use of GIS to cartographically showcase the problem on existing public facilities, the current population, and the number of facilities that can carry the population so as to visualize the inadequacy of the existing. It also used mathematical models to predict the number of such facilities that will be needed at any given time in the near future. The paper has further thorough cartographic modelling, other than network analysis, suggesting approximate positions of such facilities. The study area is described, the transformed GPS observations of water and sanitation facilities are provided, the conceptual workflow is highlighted, the mathematical equations for projecting population growth is highlighted, graphs of the statistical analysis are shown, the GIS interface is shown and finally recommendations for future spatial decision making are mentioned.
¤ Materials and Methods   
The study area [Figure 1] is located north of Dichemso and the south of Amakom. It is also to the east of Asawasi and west to Akrom. Aboabo is bounded by a railway line from Kumasi to Tarkwa. Inadequate amount of water and sanitation facilities has led to a lot of problems including school children going round a number of meters before they get water for bathing and even for breakfast before leaving for school.
People must be in these queues for hours in order to use public sanitation facilities before leaving for work or school in the Aboabo community [Figure 2]ac. This is very typical for most densely populated areas of Ghana of which Aboabo is not an exception since people most times have carry water more than 200 m to individual homes.  Figure 2: Ways of accessing water and sanitation facilities at the Aboabo community
Click here to view 
Town sheet map of Kumasi Metropolis for projecting, layout, and population and 1984 and 2000 census data of Aboabo were used. GPS equipment was used to observe existing water and sanitation facilities in the study area in WGS84 systems and was transformed to War Office Datum of Ghana [Table 1]. These results were geocoded in the digital database of Aboabo obtained from digitizing the layout map of study area. GIS was used for building a geodatabase, digitization, and modeling. Field verification exercise was conducted with the GPS to assess accuracy of the digitized map. Questionnaires were used to collect nonspatial information on the sanitation facilities [Table 2] and all public facilities [Table 3] in the Aboabo Township. Data on the population of Aboabo was obtained from the Statistical Service department, Kumasi. Other secondary sources of data were from administered questionnaires in the community. This gave detailed information about the problems associated with using the water and toilet facilities. These data were modeled in the GIS software for display and cartographic visualization. For questionnaires on water facilities, questions were formulated for (1) owners of water facilities to obtain information related to owners of standing pipes and water reservoirs, how much owners pay to the utility service at the end of every month, the number of people who fetch water per day, the charge of water per bucket, and the peak hours when water is fetched; and (2) users of water facilities on how much they pay daily, the number of buckets fetched a day, the distance they travel to fetch water, whether they need direct pipe borne water in their homes and the provision made, the frequency of flow of water in the Aboabo community, the purity of the water and any history of water borne disease. Statistical software was used analyze the data. [Figure 3] illustrates the conceptual framework of the research.  Table 1: GPS coordinates of sewage facilities (SF), standing pipes (SP), public toilet (PT) and well (W) at aboabo
Click here to view 
Projecting population growth through mathematical equations
Since population census data used are only for 1984 and 2000; there is the need to use mathematical equations to project for other years. Equation 1 was used to derive the population growth rate of Aboabo which was input into equation 2 to project the population for subsequent years.
Growth Rate (R) Equation:
Where N is number of years; P_{0} is the Initial Population; and P is the population at a certain period of years.
Estimated Population (EP) Equation: EP = (1 + R) ^{n} Equation 2
Where n is n the difference between the two years and
R is the Growth rate.
The input variables for estimating the population are the current year, current population data, number of years from the current year, number existing facilities, and the growth rate. The population estimation was made up to year 2008 in order not to overestimate or underestimate by the projection formula. By observing the trend in [Figure 4], the change in estimation is similar since constant rate of increase was obtained from Equation 1.
¤ Results and Discussion   
Dependence of Aboabo population on various toilet facility types
In [Table 3] it is shown that less than 40% of the total population at Aboabo have sanitation facilities in their homes [Figure 5]; and approximately 66% depend solely on public toilet facilities. Thus, the dependence of Aboabo population on sanitation facilities is very high.  Figure 5: Chart showing dependency of the population on various sanitation facilities
Click here to view 
Population growth by years in Aboabo
Using Equation 2, there is an increase in trend of Population in Aboabo from 1984 [Figure 4]. This calls for the need for more water and sanitation facilities to meet the population.
A scatter plot of Available Public Toilets (AvPT) against the Population trend in Aboabo from years 1984 to 2008 shows the gap in the available standing pipe in the community [Figure 6].
A scatter plot of Available Standing Pipe (AvSP) against Population [Figure 7] demonstrate spatial distributing of standing pipes and the population; which indicates a positive distribution.
The Cartographic model on the GIS platform, [Figure 8], depicts the site locations of water facilities at Aboabo. The model shows where new water facilities can be built. The Cartographic model shows the spatial locations of the existing standing pipes in different coloration corresponding to the number of the population in the scatter plot. [Figure 9] shows the total number and spatial location of public sewage facilities at Aboabo, and new spatial location for new sewage facilities.  Figure 8: The cartographic model of water facilities with population between 1984 and 2000
Click here to view 
 Figure 9: GIS interface of the number and site location of public toilets at Aboabo
Click here to view 
Regression analysis of available standing pipe with years and estimated population
A line plot made on Available Standing Pipe (AvSP) against Year [Figure 10] shows a positive linear relation implying that as time progresses there has been a corresponding increase in the water facilities provided. A 4 year increase in years results in a corresponding increase of 1.768 (approximately 2) water facilities (i.e. standing pipes) for the Aboabo community. The statistical Rsq and Rsq (adj) values of 98.9% and 98.7% resulted respectively. These indicate that 98.9% of the variation in the available standing pipe data pertains to the year. The statistical Pvalue of 0.000 also indicates that year is statistically significant since it is less than the alevel.
Equation 3 depicts the regression:
Av SP = − 3500 + 1.768* Year &nabsp;&nabsp;Equation 3
Where S = 1.78085 RSq = 98.9% RSq (adj) = 98.7%
The analysis of variance is illustrated below:
Source DF SS MS F P
Regression 1 1400.14 1400.14 441.49 0.000
Error 5 15.86 3.17
Total 6 1416.00
A line plot of Available Standing Pipe (AVSP) against Population reveals a positive linear correlation exists [Figure 11]. A unit increase in population results in 0.00219 increases in the available standing pipes. The Rsq and Rsq (adj) values of 99.4% and 99.3% indicate that 99.4% of the variation of the existing standing pipes data pertains to the population data. The Pvalue of 0.000 also indicates that year is statistically significant since it is less than the alevel although the population data show a weaker effect on the water facility increment.  Figure 11: Fitted line plot of the available standing pipe against population
Click here to view 
Equation 4 depicts the regression:
Av SP = −40.1212 + 0.0021973* Population. Equation 4
Where S = 1.28999 RSq = 99.4 % RSq (adj) = 99.3 %
The analysis of variance is illustrated below:
Source DF SS MS F P
Regression 1 1407.68 1407.68 845.920 0.000
Error 5 8.32 1.66
Total 6 1416.00
Regression analysis on required public toilet versus population
The fitted line plot of Required Public Toilet (ReqPT) against Population indicates a positive linear relation [Figure 12]. A unit increases in the population results in 0.0013 increase in the public toilets available in the area. The resulted Rsq and Rsq (adj) values were 94.4% and 93.3%, respectively. These indicate that 94.4% of the variation in the available standing pipe data pertains to the population. The Pvalue of 0.000 indicates that the population data is statistically significant since it less than the alevel.  Figure 12: Fitted line plot of the required public toilet against population
Click here to view 
Equation 5 depicts the regression:
Req PT = −8.557 + 0.001307* Population Equation 5
Where: S = 2.42226 RSq = 94.4% RSq (adj) = 93.3%
The analysis of variance is illustrated below:
Source DF SS MS F P
Regression 1 498.377 498.377 84.94 0.000
Error 5 29.337 5.867
Total 6 527.714
Regression analysis on required standing pipe versus population
The fitted line plot of the Required Standing Pipe (ReqSP) against population indicates of the regression analysis indicates a positive linear correlation [Figure 13]. A unit increase in population results in 0.0025 increases in the available standing pipes. The Rsq and Rsq (adj) values of 99.9% indicates that 99.9% of the variation of the existing standing pipes data pertains to the population data. The Pvalue of 0.000 less than the alevel also indicates that year is statistically significant.  Figure 13: Fitted line plot of the required standing pipe against population
Click here to view 
Equation 6 depicts the regression:
Req SP = 0.014 + 0.002511 Population Equation 6
S = 0.609937 RSq = 99.9% RSq (adj) = 99.9%
The analysis of variance is illustrated below:
Source DF SS MS F P
Regression 1 1838.14 1838.14 4940.93 0.000
Error 5 1.86 0.37
Total 6 1840.00
Statistical research conducted by the Ghana National Development Population Council (NDPC) reveals that a borehole or standing pipe is required to support 400 people. Therefore, a population of 34,206 people needs to have about 86 number of borehole in the Aboabo community as at the year 2000; however, this was not the case. About 105 standing pipe facilities will support a population of 41,939 but as at 2008, the existing situation are 53 standing pipes to a population of 41,939. This implies that the community has a backlog of 52 water facilities in order to meet the population of the community. Therefore, measures need to be put in place to provide the required number of water facilities to meet the water of the needs of the community. In addition, a one pit of toilet facility is required to support 50 people ideally according to NDPC. Therefore, population of 41,739 is to be served by 94 toilet facilities but this is not so. The existing public toilet is 6 with a backlog of 82 which they need additional eightyeight (88) public toilet in order to meet their needs.
Equations 1 and 2 were used compute the population growth rate and estimated population, respectively. The fitted line plots were used to derive equations for available standing pipes (Equation 3), available public toilet (Equation 4), ReqSP (Equation 5), and required public toilet (Equation 6); it can be observed that there is a big backlog of facilities that needs to be provided. From the mathematical models (equations) developed, the number of facilities for any population or at any specific year can be estimated. Also the cartographic model will also help locate the spatial location of the facilities, the number of facilities for a particular plot can be specified, and spatial location for new water and sanitation infrastructure as overplayed with population data. [Figure 14] shows an example of the number of standing pipes and spatial location that will be required for the Aboabo community in 2015 and 2020, along with the nonspatial information of the number of standing pipes.  Figure 14: Locations and attributes for various standing pipes at different years
Click here to view 
¤ Conclusions and Recommendations   
The findings in this study show that population increase has no corresponding increase in the water and public toilet facilities consequently leading to poor quality of life of the citizenry as a whole. The models demonstrate the relationship between facilities and population and hence to estimate the number of public toilet and water facilities that a particular locality needs at a particular time with respect to its growing population. Although the estimated model was based on less population datasets the models proved satisfactory compared with the exiting ground situations. The Cartographic model serves as a spatial decision support tool which can be employed by the local government in densifying the number of toilet facilities required for individual homes as being envisioned by the Government of Ghana. The designed geodatabase and analytical capabilities demonstrated to the officials of water and sanitation at Kumasi Metropolitan Assembly (KMA) saw the potential need for GIS in their day to day activities and decision making. To meet the sanitation and water requirements of rapidly growing populations in order to improve the lives, condition and health of the people of Aboabo, this research provides an efficient, effective, and satisfactory means of making spatial decision on a click of button in the GIS platform. The Geodatabase thus provides an efficient database for government officials in building new toilet and water facilities at public places and encouraging landlords to build their houses to reduce the burden on the public facilities. Quick spatial decision can be made on the GIS interface with the aid of cartographic models (maps) to indicate where there public open spaces for building new public sanitation facilities; and if no space consideration can be made on individual houses.
GIS and statistics can provide an efficient and effective mean of managing steady supply of clean water, appropriate technology, behaviour change, and environmentfriendly wastewater management strategies. The GIS can play a role in the coordination and cooperation for the mobilization of both water and sanitation facilities and the wise use of such resources as well as allocation of budgets for water resource management, sanitation and human settlements. The GIS can help regulate haphazard building in and around properties allocated for water and sanitation facilities. The designed geodatabase and analytical capabilities demonstrated to the officials of water and sanitation at Kumasi Metropolitan Assembly saw the potential need for GIS in their day to day activities and decision making.
¤ References   
1.  Drummond WJ. Address matching: GIS technology for mapping human activity patterns. J Am Plann Assoc 1995;61:24051. 
2.  UNDP. Water Supply and Sanitation. Electronic Archive. Available from: http://www.undp org/content/undp/en/home/ourwork/environmentandenergy/focus_areas/water_and_ocean_governance/watersupplyandsanitation.html. [Last accessed on 2012 Mar 14]. 
3.  World Bank. 2010 World Development Indicators. International Bank for Reconstruction and Development/The World Bank, Washington, D.C., USA. Electronic Archive. Available from: http:// data.worldbank.org/sites/default/files/wdifinal.pdf. [Last accessed on 2012 Mar 29]. 
4.  Gopal S, Sarkar R, Banda K, Govindarajan J, Harijan BB, Jeyakumar MB, et al. Study of water supply & sanitation practices in India using geographic information systems: Some design & other considerations in a village setting. Indian J Med Res 2009;129;23341. 
5.  Baumann J. System integration key to Hamburg's Waste Management Future. GISUSER.COM: Taking You Beyond The Map. Electronic Archive. Available from: http://www.gisuser com/content/view/1305/28/ [Last accessed on 2012 Mar 14]. 
6.  Zeilhofer, P, Zeilhofer LV, Hardoim EL, Lima ZM, Oliveira CS. GIS applications for mapping and spatial modeling of urbanuse water quality: A case study in District of Cuiabá, Mato Grosso, Brazil. Cad Saude Publica 2007;23:87584. 
7.  Aronoff S. Geographic Information Systems: A Management Perspective. WDL Publications, Ottawa Canada. 1989; 294. 
8.  Yuan M. Representing Geographic Information with both object and field like properties. Cartogr Geogr Inf Sci 2001;28:8396. 
9.  Xiao N, Bennett DA, Armstrong MP. Interactive evolutionary approaches to multiobjective spatial decision making: A synthetic review. Computers, Environment and Urban Systems 2007;31:23252. 
10.  Peuquet DJ. Representation of geographic space: Toward a conceptual synthesis. Ann Assoc Am Geogr 1988;78;37594. 
11.  Peuquet DJ, Duan N. An eventbased spatiotemporal data model (ESTDM) for temporal analysis of geographical data. Int J Geogr Inf Syst 1995;9:724. 
12.  Galley EW. Application of GIS for population management in Ghana, Accra Metropolis. Cape CoastGhana: BSc. Project, Department of Geography, University of Cape Coast; 2007. 
13.  Dueker KJ. Urban geocoding. Ann Assoc Am Geogr 1974;64;31825. 
14.  Rushton G, Armstrong MP, Gittler J, Greene BR, Pavlik CE, West MM, et al. Geocoding Health Data. Boca Raton, FL: CRC Press; 2007. 
[Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6], [Figure 7], [Figure 8], [Figure 9], [Figure 10], [Figure 11], [Figure 12], [Figure 13], [Figure 14]
[Table 1], [Table 2], [Table 3]
