Analyzing Their Contribution to Water Demand, Quality, and Groundwater Sustainability of Private Water Wells in Addis Ababa, Ethiopia

Tulu Tola 1✉ Emailtulutollatura@gmail.com

Sisay Demeku Derib 1✉ Emailsisay.demeku@aastu.edu.et

1 Department of civil engineering, collage of Engineering Addis Ababa Science and Technology University P.O. Box 16417 Addis Ababa Ethiopia

2 Construction quality and technology center of excellence Addis Ababa Science and Technology University P.O. Box 16417 Addis Ababa Ethiopia

3 College of Business, Technology and Vocational Kotebe University of Education P.O.Box 31248 Addis Ababa Ethiopia

Tulu Tola¹³, Sisay Demeku Derib¹²

¹Department of civil engineering, collage of Engineering, Addis Ababa Science and Technology University, P.O. Box 16417, Addis Ababa, Ethiopia.

²Construction quality and technology center of excellence, Addis Ababa Science and Technology University, P.O. Box 16417, Addis Ababa, Ethiopia.

³Kotebe University of Education, College of Business, Technology and Vocational, P.O.Box 31248, Addis Ababa, Ethiopia

Corresponding Authors: tulutollatura@gmail.com, sisay.demeku@aastu.edu.et

Data Availability

The datasets used and/or analyzed during the current study are available from the corresponding author, Dr. Tulu Tolla, upon reasonable request. Dr. Tulu can be reached at tulutollatura@gmail.com or via phone at +251-911-907038.

Abstract

This study examines the role of private water wells in meeting the water demand, quality, and sustainability of groundwater resources in Addis Ababa, Ethiopia. As the city faces rapid urbanization and a rising population, private wells have emerged as a crucial supplementary water source, particularly in areas where public water supply is inadequate. However, challenges such as insufficient regulation, groundwater over-extraction, and contamination pose significant risks to the long-term viability of these wells. Data were gathered from 449 private wells, with a detailed water quality analysis conducted on 21 of them, focusing on parameters like turbidity, p^H, nitrate, and fluoride levels. The findings indicate considerable variability in water quality; some wells exceeded safe limits for turbidity and nitrates, while others met acceptable standards for key indicators. Furthermore, groundwater extraction from private wells addresses only a small portion of the city's overall water demand. Compounding issues such as well interference, inefficient water usage, and declining water tables further complicate the situation. The study underscores the urgent need for enhanced regulation, integrated groundwater management, and active community participation to promote sustainable groundwater use. It also recommends strategies for improved well placement, ongoing water quality monitoring, and necessary infrastructural investments to alleviate the adverse effects associated with private well usage. This research offers important insights into urban water management dynamics and highlights the significance of private wells in supporting water supply in rapidly developing cities like Addis Ababa.

Key words –

Groundwater

Sustainability

Private Wells

Water Quality

Urban Water

Management, Addis Ababa

Introduction

Water is a vital resource for human survival, directly impacting public health, economic development, and environmental sustainability. For water to be deemed safe for human consumption, it must meet specific criteria related to quantity, accessibility, and quality, as outlined by the World Health Organization (WHO 2011). In urban areas like Addis Ababa, Ethiopia, where rapid population growth and urbanization have put significant pressure on existing water infrastructure, groundwater has become an increasingly essential resource. Groundwater, accessed through wells, is particularly important in regions that suffer from limited or unreliable surface water sources. As cities grow and the demand for water escalates, private water wells have emerged as a common solution for supplementing municipal water supplies.

Globally, groundwater is a primary source of drinking water, supplying approximately 70% of all drinking water and 43% of irrigation water (UNESCO 2013). In Ethiopia, groundwater serves as the primary freshwater source, meeting more than 90% of the country’s water needs (Upton et al. 2018). The capital city of Addis Ababa, home to over 5 million residents, faces significant challenges in meeting its water demands. The municipal water system has struggled to keep up with the rapid population growth, placing immense pressure on the city's water supply infrastructure (Tadesse & Mesfin 2020). In this context, private water wells, drilled by households, businesses, and other private entities, have become a common alternative to the public supply.

However, the growing dependence on private wells in Addis Ababa has raised several concerns, including the potential for groundwater depletion and contamination (Haile & Abera 2021).The absence of adequate regulations and management systems for private well development has led to issues such as over-extraction, contamination of groundwater, and lack of proper monitoring (Solly et al. 1995; USGS 1998). Groundwater quality, particularly, is vulnerable to contamination from domestic waste, industrial effluents, and improper well construction practices. In the absence of a centralized governance system for private well management, these issues are compounded, making it difficult to ensure the sustainable and equitable use of groundwater resources.

Studies have emphasized the need for a structured approach to groundwater management, one that integrates well development with urban planning and considers both the environmental and health impacts of groundwater extraction (Mekash & Roman 2021). Proper well construction and monitoring of water quality are essential to mitigate risks associated with private wells, ensuring that groundwater remains a safe and sustainable resource for future generations (Upeto & Castelo Branco 2005). Moreover, the development of clear policies and regulations is necessary to prevent the over-exploitation of groundwater, safeguard its quality, and ensure that private well development is in line with the broader goals of sustainable urban water management.

This study explores the development opportunities and challenges associated with private water wells in Addis Ababa, Ethiopia. It seeks to test three key hypotheses: first, that private water wells significantly contribute to meeting the city's water demand; second, that the water quality from private wells does not meet acceptable standards; and third, which the development of private wells negatively impacts the groundwater table. The study's primary objective is to evaluate the feasibility and challenges of private water well development in Addis Ababa, with specific focus on their coverage in meeting water demand, water quality, and their influence on neighboring boreholes. The research questions examine the challenges associated with well development and management, as well as the overall contribution of private wells to the water supply system.

This study is crucial for understanding the role of private wells in supplementing public water systems. However, challenges such as over-extraction, aquifer depletion, and contamination must be addressed. By investigating these issues, the research aims to promote sustainable groundwater management practices and inform policy frameworks to mitigate the risks associated with private well proliferation (Kusumawati et al. 2020; Zhang et al. 2021). This research contributes to broader discussions on urban water management, offering insights into sustainable and equitable water access for a rapidly urbanizing city.

Methods

Addis Ababa, the capital city of Ethiopia, was founded in 1886 and stands as one of the largest and oldest urban centers in the country (Abebe & Tesfaye 2021). It is situated in the central part of Ethiopia, at coordinates of 9°1′48″N latitude and 38°44′24″E longitude (NGA 2012) (Fig. 1). As of recent estimates, the population of Addis Ababa exceeds five million, making it one of the most populous urban centers in Africa (Mekonnen & Tadesse 2022).

Fig. 1

Location Map of Addis Ababa City

Elevation and Geographic Setting

The city is uniquely positioned at a high elevation, approximately 2,355 meters (7,726 feet) above sea level, which is characteristic of many parts of Ethiopia's central plateau. This elevation places Addis Ababa within the Ethiopian Highlands, a region renowned for its rugged topography and mountainous landscapes. The city itself is located on a broad plateau, surrounded by hills and mountains, which provide a dramatic backdrop and influence the city's climate and weather patterns.

The city is at the foot of Mount Entoto, a prominent peak that rises sharply to the north of the urban area. Mount Entoto reaches an elevation of over 3,000 meters (9,800 feet) above sea level. This elevated terrain contributes to the city's cooler temperatures compared to other areas at lower altitudes within Ethiopia. To the south and east of Addis Ababa, the terrain slopes downward, giving way to lower valleys and plains.

Climate

Addis Ababa, located in the central highlands of Ethiopia, experiences a temperate climate influenced by its high altitude and the dynamic interactions between the Inter-Tropical Convergence Zone (ITCZ) and local topography. The ITCZ, a zone of low pressure where the tropical easterlies meet the moist equatorial winds, plays a critical role in the distribution and seasonality of rainfall across the region (Jury 2016). This climatic feature results in a distinct wet-dry seasonal pattern, which is modified by orographic effects, particularly as one move from lower elevations to higher altitudes within the Ethiopian highlands (Conway et al. 2004).

Rainfall and Seasons

The seasonal rainfall distribution in Addis Ababa is primarily governed by the annual migration of the ITCZ. The city experiences two main rainy seasons: the belg (small rainy season) from end of February to mid-May, and the kiremt (main rainy season) from end of June to September. The remaining months (October to February) tend to be drier, although some variability exists depending on local topography and altitude. The orographic effects of the Ethiopian highlands significantly influence the spatial distribution of rainfall, with areas at higher elevations receiving more precipitation than lower-lying regions (Seleshi & Zanke 2004).

Temperature and Humidity

Temperature and humidity in Addis Ababa are inversely related to altitude. The city is situated at approximately 2,355 meters above sea level, and its climate is characterized by moderate temperatures year-round. The mean temperature ranges from 12.4°C in November, when minimum temperatures are recorded in Sululta (altitude: 2,610 m), to a maximum of 20°C in May at Deberzeit (altitude: 1,900 m). During the rainy season, relative humidity remains high (> 50%), while in the dry season, it fluctuates between medium and low levels. Notably, Sululta, due to its higher altitude, experiences consistently high relative humidity throughout the year.

Wind Speed and Sunshine

Wind speeds in the Addis Ababa region are highest during the pre-rainy season months of April and May, reaching more than 1 m/s, and can exceed 2 m/s in Sululta. Wind speeds tend to be lower during the peak rainy season, particularly from July to September, when they fall below 1 m/s. Sunshine duration also exhibits seasonal variation. The wet season, which coincides with the main rainy months of July through September, experiences lower sunshine hours (approximately 4 hours per day). In contrast, the dry season, particularly November, is characterized by longer sunshine durations of up to 9 hours per day. Interestingly, sunshine duration does not vary significantly with altitude across the region.

Hydrogeology Formation of Addis Ababa

Addis Ababa, located in the central Ethiopian Plateau, is shaped by a complex geological structure, influencing its hydrogeological characteristics (Ha et al. 2021). The city's aquifers are primarily formed in volcanic and sedimentary rock layers dating back to the Tertiary and Quaternary periods, mainly basalt and tuff, shaped by volcanic activity, tectonic shifts, and erosion (Fentahun 2007). The Ethiopian Rift System, running through the region, plays a significant role in groundwater dynamics by creating fault systems and volcanic eruptions, resulting in aquifers within fractured basaltic rocks, where water is stored and transmitted (Tefera et al. 2010). These aquifers exhibit both primary porosity from the volcanic rocks and secondary porosity formed through fractures and weathering, enhancing groundwater storage and movement (Kebede et al. 2012). Studies have identified two aquifer systems: the upper aquifer, highly porous and recharged by rainfall, and the lower aquifer, which is less permeable but confined and recharged through lateral flow (Tesfaye et al. 2014; Tufa & Ayele 2011). Groundwater flow is influenced by topography and fault lines, with water moving from higher altitudes to lower areas (Berhanu 2017). However, increased extraction due to urbanization has raised concerns about sustainability and pollution, highlighting the need for better groundwater management to ensure long-term supply and quality (Zewdu et al. 2019; Asfaw et al. 2020).

Data Source

A combination of primary and secondary data sources was applied to achieve the objectives of this study to provide understanding of private water wells in Addis Ababa.

The primary data sources were selected private water wells (21) from existing boreholes across the sub-city in order to collect water sample for quality analysis and indexing and discussion with ground water directorate experts (five experts including director of ground water directorate) of AAWSA. The main secondary data sources of the study was private water wells design document documented at AAWSA (18 design document), private water wells data documented at AAWSA (449 private water wells) and literatures. Furthermore, secondary data collected from working documents, reports, strategic plans, and development frameworks related to private wells and water access in Addis Ababa.

Sampling Techniques

The study employed a stratified random sampling method for quality analysis. This was important because different strata within the city (based on factors such as altitude, and density of private water wells) were likely to have different views. Stratified sampling ensured that each subgroup was proportionally represented.

Primary data were collected using a two-stage sampling method. First, private water wells were grouped into clusters based on their location (upper, middle and lower part of the city), allowing for a stratified representation. After determining the required sample size from each cluster, random sampling techniques were applied. Data collection was carried out through KII supported by GIS and remote sensing methods to map and analyze the distribution and spatial interaction of the wells. Furthermore, water sample was collected from randomly sampled boreholes for quality analysis. Secondary data were collected through reviewing of design document documented, private water wells data documented and literatures relevant to study (publish scientific works, policy documents, and guidelines on private water well development).

Sampling Population and Sample Size

The population for this study comprised private water wells located in Addis Ababa, Ethiopia. To accurately define this population, several key factors were considered. First, the total number of private water wells in the city was determined, which, for the purpose of this study, was assumed to be 449 (Table 1). Second, the geographic distribution of these wells was a crucial factor, as the study accounted for variations between sub-city areas (Fig. 2). Additionally, water quality was considered, which was critical for assessing the health of the water supply from these wells. Finally, locations where water point mapping had been conducted were included, providing a more comprehensive view of well placement and interaction (Fig. 2). Finally, Addis Ababa water and sewerage authority, ground water directorate was considered sampled population for KII. By integrating these factors, the study aimed to gather detailed data on the private water wells in Addis Ababa, ensuring a well-defined sampling population.

Table 1

Private water wells distribution across sub-cities of Addis Ababa
Sub city	Private water wells summery
Addis Ketema	4
Akaki Kaliti	46
Arada	15
Bole	92
Gullele	13
Kirkos	85
Kolfe Keranio	31
Lideta	19
Nefas Silk - Lafto	116
Yeka	28
Grand total	449

Fig. 2

Map of private water wells distribution across sub-city

The sample size determination followed a two-step sampling procedure since as presented in the table1above because the number and distribution of private water wells in the city were not uniform. First, the city clustered in to upper, middle and lower based on location. From clustered sub cities, seven sub-cities were selected based on private water wells density and distribution for water quality analysis sampling. Accordingly, Nefas Silk Lafto, Bole, Kirkos, Akaki Kaliti, Yeka, Kolfe Keranio and Gullele sub-cities were targeted for sampling private water wells (Table 2). From each selected sub-city, three private water wells were randomly select and triple water sample was collect for water quality analysis (Table 2).

Proper water sampling, transportation, and storage are essential for accurate borehole water quality analysis. The sampling process was starts with the preparation of sterilized bottles, to avoid contamination. Sterile bottles with tight-fitting caps were used for microbiological tests. To ensure the sample is fresh from the aquifer, the borehole pump was run for 10–15 minutes, purging stagnant water from the system. To avoid contamination, gloves were worn, and bottles were handled by their sides.

During transportation, maintaining proper temperature control is vital. Samples were transported in a cooler with ice packs; ensuring temperatures remain between 2–6°C to prevent microbial activity or chemical changes. Collected samples were transported to AAWSA laboratory within 24 hours to prevent degradation. For storage, preservatives such as nitric acid was added immediately after sampling to maintain specific conditions, such as pH < 2 for metal analysis. Proper labeling of bottles with details was done (such as date, time, location, and sample identifier) for traceability. Samples were stored in a refrigerator below 6°C (APHA 2017; WHO 2011)..

Table 2

Sample distribution of private water wells in the sub-cities
S/N	Sub City	Number of private water wells point	Number of sampled private water wells
1	Nefas Silk Lafto	116	3
2	Bole	92	3
3	Kirkos	85	3
4	Akaki Kaliti	45	3
5	Yeka	28	3
6	Kolfe Keranio	31	3
7	Gullele	13	3
Total Private water wells sampled			21

By synthesizing these primary and secondary data; demand coverage, quality indexing and radius of influence of private water wells were assessed which associated with the development of private water wells in Addis Ababa.

Laboratory Analysis

The analysis of groundwater quality involves numerous physicochemical and biological parameters. However, a selected set of parameters were typically used for water quality indexing. The laboratory procedures for analyzing these parameters follow the standards outlined in APHA 2020, as adopted by the AAWSSA laboratory. The specific procedures for each parameter are detailed in (Table 3).

Table 3

Summary of Laboratory Procedures for Each Parameter
S/N	Parameter	Unit	Procedure	Reference
1	Turbidity	NTU	Measure using a nephelometric turbidity meter. Calibrate with formazin standard solutions.	APHA 2020
	Odor	TON	Collect the water sample in a clean, odor-free, glass container. Leave about 10% of the container volume as headspace to allow proper detection of odor. If odor is not detectable at ambient temperature, warm the sample to 40°C to enhance volatile compound release. Waft the air above the sample towards your nose without directly inhaling. Record the findings in a log, specifying both type and intensity of the odor.	APHA 2020
2	Total Dissolved Solids (TDS)	Mg/l	Filter sample and measure TDS using a TDS meter or by evaporating a known volume and weighing residue.	APHA 2020
3	Electrical Conductivity (EC)	µs/cm	Use a conductivity meter, calibrated with standard solutions, and measure at 25°C.	APHA 2020
4	Total Alkalinity as CaCO3	Mg/l	Titrate sample with standard HCl using methyl orange as the endpoint indicator.	APHA 2020
5	Total Hardness as CaCO3	Mg/l	Titrate with EDTA solution, using Eriochrome Black T as indicator.	APHA 2020
6	pH		Measure using a calibrated pH meter.	APHA 2020
7	Magnesium Hardness as CaCO3	Mg/l	Subtract calcium hardness (obtained using EDTA) from total hardness.	APHA 2020
8	Calcium Hardness as CaCO3	Mg/l	Titrate with EDTA after adding murexide indicator and adjusting pH to 12.	APHA 2020
9	Ammonia as N	Mg/l	Use Nessler's method or salicylate method; measure colori-metrically.	APHA 2020
10	Nitrite as N	Mg/l	React with sulfanilamide and NED dihydro-chloride, measure absorbance at 543 nm.	APHA 2020
11	Nitrate as N	Mg/l	Reduce nitrate to nitrite using a cadmium column, then measure nitrite using colori-metry.	APHA 2020
12	Sulfate as SO4	Mg/l	Use the turbidimetric method, reacting with barium chloride, measure turbidity.	APHA 2020
13	Phosphate as PO4	Mg/l	Use the ascorbic acid method; measure absorbance at 880 nm.	APHA 2020
14	Fluoride as F	Mg/l	Use SPADNS colorimetric method or ion-selective electrode.	APHA 2020
15	Total Iron as Fe	Mg/l	Use phenanthroline method; measure colorimetric absorbance at 510 nm.	APHA 2020
16	Manganese as Mn	Mg/l	Use the persulfate method or atomic absorption spectrometry (AAS).	APHA 2020
17	Silica as SiO2	Mg/l	React with molybdate reagent; measure absorbance at 410 nm.	APHA 2020
18	Chloride as Cl	Mg/l	Titrate with silver nitrate using potassium chromate as indicator (Mohr’s method).	APHA 2020
19	Bicarbonate Alkalinity as HCO3	Mg/l	Calculate from total alkalinity after titration with HCl to pH 4.3.	APHA 2020
20	Carbonate Alkalinity as CaCO3	Mg/l	Determine from titration curve endpoints between pH 8.3 and 4.3.	APHA 2020
21	Hydroxide Alkalinity as CaCO3	Mg/l	Determine from titration curve endpoint above pH 8.3.	APHA 2020

APHA 2020 (Standard Methods for the Examination of Water quality)

Quality Index Model

Water quality index (WQI) provides a single number that expresses the overall water quality, at a certain location and time, based on several water quality parameters. The objective of WQI is to turn complex water quality data into information that is understandable and usable by the public. A number of indices have been developed to summarize water quality data in an easily expressible and easily understood format. The WQI is basically a mathematical means of calculating a single value from multiple test results. Some of models used for water quality index estimation are weighted arithmetic index method (Brown et al. 1972), the Canadian council of ministers of environment water quality index (CCME WQI), nemerow pollution index (NPI) also called row’s pollution index and national sanitation foundation water quality index (NSF WQI) (Brown et al. 1970) and (Tyagi et al. 2013).

Water Quality Index (

$\:\mathbf{W}\mathbf{Q}\mathbf{I}$

)

Sub-Index for Each Parameter (

$\:\text{S}\text{I}\text{i}$

): The sub-index for parameter

$\:i$

is calculated as:

$\:{SI}_{i}=\:\frac{{V}_{i}-{V}_{min}}{{V}_{max}-{V}_{min}}$

Where:

$\:{V}_{i}$

: Measured value of the parameter

$\:{V}_{min}$

: Minimum permissible value of the parameter

$\:{V}_{max}$

: Maximum permissible value of the parameter

ii.

Weighting the Parameters: Each parameter is assigned a weight (

$\:\text{W}\text{i}$

) based on its relative importance to overall water quality. The weights are predefined and normalized so that:

$\:W={\sum\:}_{i=1}^{n}Wi=1$

iii.

Weighted Sub-Indices: The weighted sub-index for each parameter is calculated by multiplying its sub-index (

$\:SIi$

) by its weight (

$\:Wi$

$\:WSIi=SIi\times\:Wi$

iv.

Calculating the Overall WQI: The overall Water Quality Index is obtained by summing the weighted sub-indices for all n parameters:

$\:WQI={\sum\:}_{i=1}^{n}WSI$

Radius of Influence Estimation

The radius of influence of groundwater is defined as the distance from a pumping well where the groundwater level is significantly affected by pumping activities. This zone delineates the area where measurable drawdown, or the lowering of the water table or potentiometric surface, occurs, influencing groundwater flow. Factors such as the pumping rate, hydraulic conductivity, aquifer transmissivity, and the duration of pumping determine the size of this radius (Ha et al. 2021).

The empirical approach used for estimating radius of influence was (Dragoni 1998; Myette et al. 1987 and Kyrieleis 1930)

$\:R=2\times\:(D-SWL)\times\:\surd\:S/D$

Where:

R = radius of influence (in meters)

D = well depth (in meters)

SWL = static water level (in meters)

s = drawdown (in meters)

Data Analysis

The data analysis wasconducted using statistical tools available on the market according to its applicability. The study applied descriptive statistics to assess the status of demand coverage, water quality and radius of influence. In this regard, the study mainly employed mean and standard deviation to describe the existing scenarios. The statistical package use for data analysis was SPSS Version 16.2.

Result and Discussion

Distribution of Private Water Wells across Sub-Cities

The distribution of private water wells across Addis Ababa's city administration exhibits significant spatial variation, reflecting diverse socio-economic and hydro-geological factors. According to the data, Nefas Silk-Lafto and Bole sub-cities possess the highest number of private water wells, with 116 and 92 wells, respectively (Fig. 3). This concentration aligns with findings that areas with rapid urban expansion and high-income populations often invest in private water supply infrastructure to compensate for inadequacies in public water systems (Mekonnen & Hoekstra 2016). The extensive residential developments and thriving commercial activities in these areas drive higher water demands, while their hydro-geological suitability such as adequate aquifer presence facilitates well construction (Gebrewahid et al. 2021).

In contrast, sub-cities like Addis Ketema (4 wells) and Gullele (13 wells) report notably fewer wells (Fig. 3). This discrepancy could be influenced by higher population densities, limited land availability for private infrastructure, or unfavorable geological conditions restricting groundwater accessibility. Addis Ketema, characterized by its dense urban fabric and older settlements, aligns with studies that associate limited private well installations with constrained space and the predominance of older infrastructure (Mengistu et al. 2019). These factors hinder the feasibility of private wells compared to other water sourcing strategies.

Sub cities such as Kirkos (85 wells) and Akaki Kaliti (46 wells) exhibit moderate well distributions (Fig. 3). Kirkos, with its mixed residential and commercial zones, reflects a balanced demand for private water resources. Akaki Kaliti, known for its industrial zones, relies on private wells to meet the dual demands of residential water needs and industrial operations, as seen in other urban-industrial regions globally (Foster et al. 2020). This pattern underscores the significant role of industrial water demand in shaping groundwater dependency. Overall, this distribution underscores the interplay between urbanization patterns, economic activities, and hydro-geological characteristics in Addis Ababa.

Fig. 3

Private Wells distribution in the sub cities

Water Balance of Addis Ababa Water Supply System

The Addis Ababa Water and Sewerage Authority (AAWSA) reported key metrics related to its water supply system in 2023/2024 (2016 in Ethiopian). The total inlet volume reached 165,014,085m³/day from reservoir source/surface water source, with authorized consumption accounting for 97,057,942m³/day. Unauthorized consumption was recorded at 134,320 m³/day, while accounted-for water amounted to 26,147,299 m³/day. Notably, unaccounted-for water (UFW), representing water lost due to leakage, theft, or inaccuracies in metering, totaled 41,674,524 m³ (AAWSA 2024).

The total water losses were 67,956,143m³ which is approximately 41.2% of the total inlet volume, a significant proportion indicating inefficiencies in the system. The non-revenue water (NRW) includes all water produced but not billed of the total inlet volume, highlights substantial operational inefficiencies. Similarly, sub-Saharan Africa cities also face high NRW levels. For instance, Nairobi, Kenya NRW accounts for approximately 45% of the total water supply (World Bank 2016). Lagos, Nigeria:, NRW levels exceed 55% (WHO & UNICEF 2017).

While Addis Ababa's NRW far exceeds these cities, it reflects the widespread challenges of infrastructure aging, poor maintenance, and unauthorized connections common across the region.

The 2016 fiscal year water balance of Addis Ababa reveals significant inefficiencies, with NRW levels reaching alarming rates. A comparative analysis with other sub-Saharan cities underscores the need for immediate action to address water losses, optimize resource use, and ensure sustainable urban water supply systems.

Potential Coverage of Private Water Wells in the City Water Demand

The analysis of private water wells' contribution to Addis Ababa's water demand reveals a significant gap in the city's water supply infrastructure. Addis Ababa's population exceeds 5 million, with a per capita water demand estimated between 120 and 150 liters per day, translating to a total daily demand of approximately 1.2 million cubic meters. However, the current supply, managed predominantly by the Addis Ababa Water and Sewerage Authority (AAWSA), is limited to 563,000 cubic meters per day, leaving a substantial deficit of 637,000 cubic meters per day.

Private water well is a groundwater source built, owned, and maintained by an individual or a private organization to supply water for personal purposes, including drinking, irrigation, or household activities (Ha et al. 2021). Private water wells have emerged as a supplementary source, yet their contribution remains minimal. Private water wells number, totaling 449 in the city, the sustainable potential, contribute an average output of 47.35 cubic meters per day per well (Table 4). This potential in a combined daily contribution of 21,260.10 cubic meters from private per day wells can cover about 1.77% of the total daily demand. It shows the limited role of private wells as a supplementary water source in addressing Addis Ababa's growing water demands (Table 4).. Similar patterns have been observed globally, with studies from Nairobi, Lagos, and other cities underscoring the limited capacity of private wells to mitigate urban water deficits (Ha et al. 2021; Sinha & Gupta 2022).

The limited contribution stems from factors such as declining groundwater levels, the prohibitive costs of well construction and maintenance, and the absence of effective policies to integrate private wells into the municipal water supply network. Studies in Ethiopia suggest that groundwater depletion exacerbates the city's reliance on limited surface water sources, further straining supply systems (Demlie & Wohnlich 2006).

For instance, research in cities like Nairobi and Lagos, which also face acute water scarcity, shows that private wells often contribute less than 5% of the total water demand, emphasizing their limited capacity to significantly offset shortages in the municipal water supply system (Kariuki & Schwartz 2005; Adekalu et al. 2009). This low contribution is often due to challenges such as insufficient groundwater availability, limited well yields, and inadequate infrastructure for water distribution.

Similarly, Adekalu et al. (2009) report that in Lagos, the reliance on private wells has led to significant groundwater stress and quality concerns, with many wells becoming unviable due to contamination and over-extraction.

In Cape Town, South Africa, the 2018 water crisis underscored the limitations of private wells in urban resilience. During the crisis, private wells temporarily supplemented municipal supplies but were unable to address the broader infrastructure deficits or mitigate the city's overreliance on surface water. This experience emphasized the need for integrated water resource management, combining municipal, private, and alternative sources like desalination and water recycling (Muller 2018).

Urbanization places immense pressure on groundwater resources, particularly in cities like Addis Ababa. Increased impervious surfaces from urban sprawl reduce natural recharge rates, compounding groundwater depletion. Research from New Delhi, India, demonstrates a similar pattern, where heavy dependence on private wells has led to significant declines in water tables, with recharge rates unable to match extraction levels (Kumar et al. 2011). Furthermore, the lack of regulation and enforcement exacerbates challenges, leading to inequitable access and unsustainable use.

Addis Ababa's experience reflects these broader trends. With urban expansion encroaching on recharge zones and the city's reliance on aging infrastructure, the sustainability of groundwater as a supplementary source is increasingly in question. While private wells provide localized relief, their capacity is inherently limited by geological and economic constraints.

Addressing water supply challenges in Addis Ababa and similar cities requires a paradigm shift. Integrated water resource management (IWRM) offers a holistic approach, combining municipal systems with private wells, rainwater harvesting, and wastewater recycling. In Bangkok, Thailand, the integration of private wells into a centralized monitoring system has improved efficiency and reduced over-extraction, serving as a potential model for Addis Ababa (Foster & Garduño 2006).

The limited role of private wells in addressing Addis Ababa’s water deficit mirrors global trends, where such wells serve as supplementary sources rather than comprehensive solutions. Comparative studies from Nairobi, Lagos, and Cape Town underscore the challenges of relying on private wells amidst growing urban water demands. While private wells provide crucial relief, their sustainability depends on effective governance, robust infrastructure, and integrated resource management.

Table 4

Private water wells potential coverage of city water demand and supply
1	Addis Ababa Population	5 million	Reference
2	Capita water demand	120 to 150 L/day	AAWSA 2024 report
3	Demand	1.2 million m³/day
4	Supply	563,000 m³/day
5	Gap	637,000 m³/day
6	Number of private water wells	429
7	Average each private wells output	47.35 m³/day
8	Average potential water supply from private water wells	21,260.15 m³/days
9	Private water wells demand coverage	1.77%
10	Private water wells supply coverage	3.78%

Water Quality of Private Water Wells

The turbidity levels in the private wells of Addis Ababa ranged from 0.17 to 7.46 NTU, with a mean of 2.52 ± 2.51 NTU (Table 5). These findings reveal that 42.9% of the samples exceeded the WHO guideline of < 1 NTU for safe drinking water, suggesting potential microbial contamination. Elevated turbidity levels often indicate suspended particles or microbial presence due to insufficient filtration or infiltration of surface water. Similar studies in sub-Saharan Africa, including rural regions of Nigeria and Ethiopia, report turbidity values exceeding safe limits, frequently linked to agricultural runoff and poor sanitation practices in proximity to water sources (WHO 2017; Abiye 2018).

The TDS levels in Addis Ababa’s private wells ranged from 109 to 531 mg/L, with a mean of 257 ± 99.68 mg/L, within the WHO limit of 1000 mg/L (Table 5). However, EC values (mean: 486.33 ± 168.84 µS/cm) suggest moderate mineralization, reflecting geological interactions. Comparatively, private wells in India and the United States have demonstrated higher TDS and EC values, often attributed to natural geological formations, industrial effluents, and agricultural practices (Kumar et al. 2020; USGS 2021) (Table 5). While moderate mineralization is not directly hazardous, prolonged exposure to elevated TDS may affect water palatability and health.

The p^H of the well water ranged from 6.20 to 8.13, with a mean of 7.23 ± 0.49, aligning well with the WHO guideline range of 6.5–8.5 (Table 5). The neutral to slightly alkaline nature of the water is attributed to carbonate buffering, a characteristic observed in groundwater systems across Ghana and South Africa (Agyeman 2019; Smith et al. 2020). This balance is crucial for mitigating corrosive effects on pipes and ensuring compatibility with drinking water standards.

The total hardness values ranged from 34 to 406 mg/L as CaCO₃, with a mean of 222.13 ± 101.70 mg/L, classifying the water as moderately hard to very hard. Calcium (mean: 167.08 ± 79.97 mg/L) and magnesium (mean: 53.84 ± 23.89 mg/L) hardness dominated (Table 5). While hard water poses minimal direct health risks, it can cause scaling and reduce the efficiency of domestic appliances. Groundwater in arid regions such as Saudi Arabia and North Africa often exhibits even higher hardness levels due to calcareous aquifers (Al-Mahmoudi 2021).

Ammonia-N concentrations (0.01–0.61 mg/L, mean 0.13 mg/L) fell within the WHO limit of 0.5 mg/L (Table 5). However, nitrate levels were concerning, with nitrite-N reaching 28.50 mg/L (mean: 3.32 ± 6.11), surpassing the WHO threshold of 10 mg/L in 14.3% of samples (Table 5). Elevated nitrate levels are frequently associated with agricultural runoff, as evidenced in Kenya and California’s Central Valley (Harter 2020; Oduor 2018).

Sulfate concentrations (mean: 23.50 ± 51.61 mg/L, max: 240 mg/L) were comparable to levels observed in Europe and Asia, where industrial discharges and the dissolution of gypsum-bearing formations are prevalent sources (Jones et al. 2019). Elevated sulfate levels can contribute to laxative effects and scaling in distribution systems.

Fluoride concentrations ranged from 0.01 to 1.68 mg/L, with a mean of 0.54 ± 0.36 mg/L (Table 5). While most samples were within the WHO guideline of 1.5 mg/L, a few exceeded this limit, posing risks of dental and skeletal fluorosis. Fluoride issues are well-documented in endemic regions of India and Ethiopia’s Rift Valley, emphasizing the need for local interventions (Ramesh & Rao 2019; Tekle-Haimanot 2017). Chloride levels (mean: 19.16 ± 18.25 mg/L) were well within the WHO limit of 250 mg/L, indicating minimal anthropogenic contamination.

Iron concentrations ranged from 0.01 to 0.64 mg/L (mean: 0.12 ± 0.17 mg/L), exceeding the aesthetic limit of 0.3 mg/L in some samples (Table 5). Manganese levels were negligible (mean: 0.002 ± 0.01 mg/L), meeting the WHO guideline. Silica levels (mean: 37.33 ± 17.62 mg/L) were notably higher than typical groundwater values, likely influenced by local geological formations (Table 5). Excess silica can contribute to scaling and operational issues in industrial settings.

The water quality of private wells in Addis Ababa shows considerable variability, with multiple parameters exceeding WHO guidelines, particularly turbidity, nitrate, and fluoride. These results align with global trends, underscoring the influence of local geology, agricultural practices, and anthropogenic activities. Regular monitoring, public awareness, and targeted water treatment interventions are critical to safeguarding public health. Comparatively, these findings resonate with studies in Africa, Asia, and the Americas, highlighting universal challenges in maintaining groundwater quality amidst environmental and anthropogenic pressures.

Table 5

Private water wells psychochemical analysis result
Parameters	Descriptive Statistics
Parameters	N	Min	Max	Mean	Std. Deviation
Turbidity	21	.17	7.46	2.52	2.51
TDS	21	109.00	531.00	257.00	99.68
EC	21	185.00	871.00	486.33	168.84
Total alkalinity as CaCO₃	21	96.00	268.00	186.69	50.97
Total hardiness as CaCO₃	21	34.00	406.00	222.13	101.70
P^H	21	6.20	8.13	7.23	0.49
Magnesium hardiness CaCO₃	21	10.00	116.00	53.84	23.89
Calcium hardiness as CaCO₃	21	24.00	344.00	167.08	79.97
Ammonias N	21	.01	.61	0.13	0.15
Nitrite as N	21	.003	.964	0.09	0.21
Nitrite as N	21	.003	28.50	3.32	6.11
Sulfate as SO₄	21	.10	240.00	23.50	51.61
Phosphate as PO₄	21	.06	1.00	0.36	0.22
Fluoride as F	21	.01	1.68	0.54	0.36
Total iron as Fe	21	.01	.64	0.12	0.17
Manganese as Mn	21	.00	.05	0.00	0.01
Silica as SiO₂	21	.00	83.00	37.33	17.62
Chloride as Cl	21	.00	56.50	19.16	18.25
Bicarbonate alkalinity as HCO₃	21	.00	327.00	172.69	111.69
Carbonates alkalinity as CaCO₃	21	.00	.00	0.00	0.00
Hydroxides alkalinity as CaCO₃	21	.00	.00	0.00	0.00

Water Quality Indexes of Private Water Wells

The study of private water wells in Addis Ababa provides critical insights into the quality of groundwater resources, assessed using a Water Quality Index (WQI) framework. The Water Quality Index (WQI) serves as a vital composite measure that simplifies the evaluation of water quality by integrating diverse physical, chemical, and biological parameters into a singular, comprehensible score. It is particularly instrumental in assessing water suitability for varied uses such as drinking, agriculture, and recreation. The overall WQI value for the wells analyzed is 41.11, indicating a moderate water quality category when considering all parameters considered AAWUAS, although individual parameters reveal significant variations (Table 6). The WQI value presented in table below suggesting the presence of pollutants, which may not pose immediate risks but warrant attention in future. This nuanced measure aggregates individual parameter contributions to provide a comprehensive view of water quality (WHO 2020)

Odor was subjectively assessed as “No observable,” suggesting no significant contamination sources affecting the olfactory quality. Turbidity was measured at 3.04, well below the threshold for potable water standards established by the World Health Organization (WHO) (Table 6). Turbidity levels below 5 NTU are generally acceptable globally, similar to findings in studies from India where low turbidity levels (around 3–4 NTU) were recorded in well-maintained groundwater systems (Gupta et al. 2020).

The Total Dissolved Solids (TDS) value of 1.22 mg/L and Electrical Conductivity (EC) at 2.01 µS/cm indicates low salinity and mineral content, reflecting limited ionic presence in the water (Table 6). These results are consistent with findings in arid regions globally, such as Northern Africa, where TDS levels below 500 mg/L are deemed suitable for human consumption (El-Hattab et al. 2019) and consistent with studies in pristine waters like those in the Scandinavian regions, which report TDS below 2 mg/L for freshwaters (Bui et al. 2019).

Total alkalinity and total hardness, recorded at 2.33 and 3.66 (as CaCO₃), respectively, suggest moderate buffering capacity and mineralization (Table 6). Magnesium hardness (4.77) and calcium hardness (4.68) are within permissible limits for potable water, aligning with data from global studies indicating average hardness values in groundwater between 3–5 (Tripathi et al. 2017) and studies in the United States' Midwestern aquifers have recorded magnesium-dominated hardness in similar ranges, suggesting geochemical congruence (USGS 2021).

The pH value of 2.93 indicates highly acidic water, diverging significantly from the WHO recommended range of 6.5–8.5. Acidic pH levels in groundwater are a concerning trend also observed in industrial zones in Asia, likely influenced by anthropogenic activities (Sharma & Walia 2016).

Nitrite (7.26 as N) exceeds permissible levels, signaling possible contamination from agricultural runoff or sewage. Similarly, ammonia (1.83 as N) is within a tolerable range but highlights the potential influence of organic decomposition. Elevated nitrite concentrations above 3 mg/L have also been reported in studies of urban aquifers in Southeast Asia, emphasizing the need for proper waste management (Nguyen et al. 2018).

Phosphate (0.85 as PO₄) and fluoride (0.24 as F) levels are minimal, suggesting limited agricultural or industrial contamination. Comparatively, studies in East Africa indicate similar low fluoride concentrations in volcanic aquifers (Assefa et al. 2015).

Total iron (0.43) and manganese (-0.54) values show negligible levels, below WHO guidelines. The absence of heavy metal pollution is consistent with other African studies of non-industrial zones where levels remain within acceptable limits (Tadesse et al. 2021).

Chloride (0.23) and bicarbonate alkalinity (4.24 as HCO₃) are also minimal, reflecting limited salinity and effective natural filtration in the aquifer system (Table 6).

Silica levels at 2.22 mg/L align with average concentrations observed in volcanic aquifers globally, where silicate weathering significantly contributes to groundwater composition (Rango et al. 2013).

Nitrite as N exhibits a peak of 7.26, signaling potential nitrate contamination, commonly arising from agricultural runoff or urban waste. Comparatively, global studies in highly urbanized rivers, such as the Ganges in India, report nitrite levels exceeding 5 mg/L in polluted stretches (Kumar et al. 2020). Sulfate levels at -3.62 indicate potential measurement discrepancies or inherent low concentrations, as pristine waters globally often exhibit sulfate levels below 10 mg/L. Phosphate at 0.85 aligns with acceptable limits but suggests the need for ongoing monitoring due to potential eutrophication risks.

Fluoride levels are significantly lower than regions such as the Rift Valley, where natural geochemistry elevates concentrations to over 2 mg/L (WHO 2020) and manganese (-0.54) levels are notably low, underscoring minimal contamination by these ions.

Iron levels at 0.43 suggest borderline acceptability, considering WHO standards advocating a limit of 0.3–0.5 mg/L for aesthetic and health reasons (Table 6). The negative manganese value requires verification, as globally, manganese in natural waters typically ranges between 0.01–1 mg/L (WHO 2017). However, urban areas, particularly in Africa, often exhibit higher levels, surpassing permissible limits due to industrial discharges (Adekunle 2009).

Silica (2.22) and chloride (0.23) concentrations demonstrate minimal variability, comparable to freshwater systems in temperate climates, where chloride levels often remain below 1 mg/L in unpolluted conditions. These findings align with global benchmarks for rural or semi-rural surface waters.

The WQI of 41.11, though indicative of moderate water quality, highlights areas requiring intervention (Table 6). The acidic pH and elevated nitrite levels are the primary concerns, necessitating targeted mitigation strategies. Globally, studies in urban areas report similar WQI trends influenced by industrial discharge and agricultural practices (Barakat et al. 2016). In Addis Ababa, rapid urbanization and inadequate wastewater management likely exacerbate these issues. To ensure water safety, regular monitoring and the implementation of groundwater protection policies are critical.

The study underscores the importance of WQI as a diagnostic tool for water resource management. While Addis Ababa's private wells show moderate overall quality, specific parameters, particularly pH and nitrite, demand immediate attention to safeguard public health. This study’s findings resonate with trends observed in various global freshwater systems, including improved WQI values for protected catchments and higher contamination in anthropogenically impacted zones (Smith et al. 2018).

Globally, WQI studies illustrate diverse outcomes influenced by geographical and anthropogenic factors. Urbanized regions in Nigeria, for instance, report WQI values between 70 and 80 due to significant industrial and domestic waste discharge (Adekunle 2009). Conversely, remote Canadian lakes often exhibit WQI values below 20, indicative of pristine conditions. The moderate WQI of 41.11 for Addis Ababa’s wells aligns with semi-urban areas in Asia, where moderate agricultural and industrial activities prevail (EPA 2021).

The WQI analysis for private wells in Addis Ababa reveals moderate water quality with localized challenges such as pH imbalance and elevated nitrite levels. To improve water quality, targeted interventions are necessary, including monitoring programs such as regular water quality assessments to detect and mitigate emerging pollutants. Effluent Management such as stringent regulations to control industrial and domestic waste discharge, sustainable agriculture such as encouraging practices that minimize fertilizer runoff into water systems and public awareness such as educating the community on water conservation and pollution prevention.

Table 6

Private water quality index considering all AAWUSA Parameters
Parameters	Idia	WHO	Average Measured Parameters	Sub-index for the parameter i	Weight for parameter i	WQI
Odor	No.ob	No.ob	No.ob	No.ob	No.ob	No.ob
Test	No.ob	No.ob	No.ob	No.ob	No.ob	No.ob
Turbidity	1	5	2.52	37.98	0.08	3.04
TDS	100	1000	257	17.44	0.07	1.22
EC	400	700	486.33	28.78	0.07	2.01
Total alkalinity as CaCO3	30	500	186.69	33.34	0.07	2.33
Total hardiness as CaCO3	100	500	222.13	30.53	0.12	3.66
P^H	6.5	9.5	7.23	24.38	0.12	2.93
Magnesium hardiness CaCO3	30	50	53.84	119.19	0.04	4.77
Calcium hardiness as CaCO3	50	150	167.08	117.08	0.04	4.68
Ammonias N	0	0.5	0.13	26.10	0.07	1.83
Nitrite as N	0	0.1	0.09	90.76	0.08	7.26
Nitrite as N	0	10	3.32	33.24	0.1	3.32
Sulfate as SO4	250	500	23.50	-90.60	0.04	-3.62
Phosphate as PO4	0.1	1	0.36	28.36	0.03	0.85
Fluoride as F	0.5	1.5	0.54	4.00	0.06	0.24
Total iron as Fe	0.1	0.3	0.12	8.57	0.05	0.43
Manganese as Mn	0.05	0.4	0.00	-13.61	0.04	-0.54
Silica as Sio2	1	50	37.33	74.15	0.03	2.22
Chloride as Cl	10	250	19.16	3.82	0.06	0.23
Bicarbonate alkalinity as HCO3	20	200	172.69	84.83	0.05	4.24
Sum of quality index						41.11

The quality indexes based on selected WHO parameters is a cornerstone for public health and sustainable urban development.

Odor and General Observations

Odor is a key sensory indicator of water quality. This study found the private wells' odor to be within WHO acceptable range (WHO 2017) (Table 7). Odorless water is preferred universally, and deviations often signal organic or chemical contamination. Comparatively, urban centers such as Mumbai, India, report odor issues linked to inadequate sanitation and industrial effluents (Kumar et al. 2020).

Turbidity

The average turbidity of Addis Ababa's private wells was 2.52 NTU (Table 7), well below the WHO threshold of 5 NTU, yielding a sub-index of 37.98. Elevated turbidity, observed in Dhaka (Bangladesh) and Lagos (Nigeria), often correlates with sediment influx and inadequate urban drainage infrastructure (Rahman et al. 2018; Akintola et al. 2021). Maintaining low turbidity is critical for effective pathogen removal during treatment.

Total Dissolved Solids (TDS)

The mean TDS value of 257 mg/L in Addis Ababa's wells is significantly below the WHO upper limit of 1000 mg/L (Table 7). A sub-index of 17.44 highlights excellent mineral balance. In arid regions such as the Middle East, TDS levels frequently exceed 500 mg/L due to groundwater salinity (Al-Zubari et al. 2020). The relatively low TDS in Addis Ababa signifies minimal salt intrusion and favorable water recharge conditions.

Total Alkalinity and Hardness

Alkalinity (186.69 mg/L as CaCO₃) and hardness (222.13 mg/L as CaCO₃) were within permissible WHO limits, with sub-indices of 33.34 and 30.53, respectively (Table 7). Elevated hardness, often seen in regions like Rajasthan, India, is typically associated with limestone-dominated geology (Sharma et al. 2019). Addis Ababa’s geology appears less conducive to such mineral leaching, resulting in acceptable hardness levels.

p^H Levels

The average pH of 7.23 falls within the WHO guideline range of 6.5–9.5, indicating neutral to slightly alkaline water suitable for drinking (Table 7). Globally, regions with pH deviations, such as parts of Africa and Southeast Asia, often face acidification due to industrial emissions or acid rain (Chowdhury et al. 2017).

Nitrite as Nitrogen

Nitrite concentrations averaged 0.09 mg/L, close to the WHO limit of 0.1 mg/L. The sub-index of 90.76 indicates potential contamination, likely from agricultural runoff or inadequate waste management (Table 7). Similar concerns have been reported in agricultural belts of the USA and Europe, highlighting the need for proactive monitoring (Smith et al. 2019).

Sulfate

Sulfate levels averaged 23.50 mg/L, substantially below the WHO limit of 500 mg/L (Table 7). However, the anomalous sub-index (-90.60) suggests potential inconsistencies in sampling or data recording. Urban studies, such as those conducted in Cairo, Egypt, report elevated sulfate concentrations linked to industrial discharge (Ahmed et al. 2020).

Fluoride

Fluoride levels of 0.54 mg/L were within WHO’s recommended range (0.5–1.5 mg/L), with a sub-index of 4.00 (Table 7). While this supports dental health, higher fluoride levels in Rift Valley regions often lead to fluorosis (Tekle-Haimanot et al. 2006).

Total Iron and Chloride

Iron (0.12 mg/L) and chloride (19.16 mg/L) concentrations were well within WHO limits, with sub-indices of 8.57 and 3.82, respectively (Table 7). In contrast, elevated iron levels are prevalent in Nigerian aquifers due to mineralogical influences (Oyeku & Eludoyin 2010).

The overall WQI of 21.87 for Addis Ababa's private wells indicates good water quality. Comparative studies in urban centers like Lagos and Dhaka often report WQI values exceeding 50, reflecting significant contamination risks (Akintola et al. 2021; Rahman et al. 2018). Addis Ababa's favorable WQI underscores the benefits of limited industrialization and effective natural filtration systems.

Despite favorable overall quality, elevated nitrite levels necessitate immediate interventions, including source tracking and enhanced waste management. Regular monitoring programs, public education, and adoption of advanced treatment technologies, similar to those in Singapore and Germany, could ensure long-term water quality (Cheng et al. 2016).

Table 7

Private water wells quality index considering selected WHO Parameters
Parameters	Idia	WHO	Average Measured Parameters	Sub-index for the parameter i	Weight for parameter i	WQI
Odor	No.ob	No.ob	No.ob	No.ob	No.ob	No.ob
Test	No.ob	No.ob	No.ob	No.ob	No.ob	No.ob
Turbidity	1	5	2.52	37.98	0.12	4.56
TDS	100	1000	257	17.44	0.12	2.09
Total alkalinity as CaCO3	30	500	186.69	33.34	0.09	3.00
Total hardiness as CaCO3	100	500	222.13	30.53	0.09	2.75
PH	6.5	9.5	7.23	24.38	0.15	3.66
Nitrite as N	0	0.1	0.09	90.76	0.12	10.89
Sulfate as SO4	250	500	23.50	-90.60	0.07	-6.34
Fluoride as F	0.5	1.5	0.54	4.00	0.09	0.36
Total iron as Fe	0.1	0.3	0.12	8.57	0.07	0.60
Chloride as Cl	10	250	19.16	3.82	0.08	0.31
Sum of quality index						21.87

Private Water Wells Radius of Influence on Neighboring Boreholes

Wells Radius of Influence Based on Geospatial

The theoretical radius of influence of a borehole on the neighboring area is often estimated to be 500 meters, based on hydrological principles governing groundwater flow and extraction (Ha et al. 2021). This radius represents the distance over which pumping from a borehole can significantly impact the local water table or groundwater flow dynamics. Within this radius, drawdown (the lowering of the water table due to pumping) is typically noticeable, and there may be interactions between the borehole and nearby wells or natural water bodies (Sinha & Gupta 2021). However, while the 500 meter radius is commonly used in groundwater management and modeling, the actual radius of influence can vary depending on factors such as aquifer properties, pumping rates, and geological settings (Gupta et al. 2021).

The radius of influence (ROI) of private water wells is a critical parameter in groundwater resource management. It determines the extent to which the operation of one well affects neighboring boreholes, especially in areas with dense well distribution. Using Geographic Information System (GIS)-based techniques, the spatial interaction between boreholes can be quantified, allowing for a better understanding of groundwater sustainability and management practices.

The theoretical approach radius influence of borehole on the neighboring one was analyzed at 500m, 400m, 300m, 200m, 100m and 50m radius using GIS and remote sensing (Table 8). The GIS and remote sensing generated data in Table 8 indicates that as the radius between boreholes decreases, the number of overlapping boreholes increases. The trend aligns with expected hydraulic principles, where smaller distances between wells lead to more significant interactions.

Table 8

GIS based spatial interaction between boreholes
Radius between two boreholes (m)	Number of Overlapping Boreholes	Number of Non-Overlapping Boreholes	Total
500	422	27	449
400	410	39	449
300	376	73	449
200	305	144	449
100	138	311	449
50	55	394	449

Overlapping Boreholes

The data reveals a progressive increase in overlapping boreholes as the radius expands. At 500 meters, 94% (422 out of 449) of boreholes have overlapping influence zones (Table 8). Conversely, at 50 meters, only 12% (55 out of 449) exhibit overlaps (Table 8). This inverse relationship demonstrates that larger radii result in broader influence zones, encompassing more neighboring wells. This pattern highlights the critical role of borehole spacing in resource sustainability.

Non-Overlapping Boreholes

The trend for non-overlapping boreholes shows an expected rise as the radius decreases. At 50 meters, 394 boreholes remain independent; a stark contrast to the 27 boreholes at 500 meters (Fig. 4). This demonstrates the spatial independence that can be achieved by reducing the ROI. These findings are essential for delineating buffer zones in well placement policies.

Studies from Arid Regions

In arid regions, such as the Middle East and North Africa (MENA), studies have reported similar patterns of ROI interactions. For example, a study conducted in Saudi Arabia found that a 400-meter radius yielded a 90% overlap rate, closely aligning with the 91% reported in this study. This suggests that aquifer types and groundwater extraction practices significantly influence ROI dynamics (Al-Ghamdi et al. 2021).

Sub-Saharan Africa

In Sub-Saharan Africa, where groundwater resources are heavily relied upon, the ROI of private wells is found to be smaller due to limited recharge and higher drawdown rates. A study in Nigeria found that at a 300-meter radius, 70% of wells overlapped, compared to 83% in this study (Oni et al. 2020). This discrepancy could be attributed to differences in aquifer properties and well yields.

Developed Nations

In developed countries with stringent groundwater regulations, such as the United States, well spacing is designed to minimize ROI overlap. A study in California reported that at a 200 meter radius, only 60% of wells overlapped, significantly lower than the 68% in this study (Smith et al. 2019).

Fig. 4

Spatial based overlapping and non overlapping private water wells in 500, 400, 300,200, 100 and 50 m radius

Implications for Groundwater Management

The findings have significant implications for groundwater management in regions with dense private well distribution such as:

Optimizing Well Placement- The high overlap rates at larger radii emphasize the need for strategic well spacing to minimize interference and ensure sustainable water use.

ii.

Groundwater Regulation-The comparison with global studies underscores the role of regulatory frameworks in mitigating over-extraction and preserving aquifer health.

iii.

Recharge Area Protection - Ensuring that non-overlapping wells are strategically placed in recharge zones could help maintain aquifer recharge capacity and prevent long-term depletion.

This GIS-based analysis provides a comprehensive understanding of the ROI of private wells, demonstrating significant overlap at larger radii. Comparing these findings with global studies illustrates the influence of regional aquifer characteristics and regulatory practices. Effective management strategies, guided by data-driven approaches, are crucial for ensuring sustainable groundwater use.

This study highlights the critical need for integrating GIS-based analysis into well placement and groundwater management strategies. Incorporating temporal data to assess how seasonal variations affect ROI interactions. Investigating how geological and hydrological differences influence ROI dynamics. Establishing guidelines for minimum well spacing based on ROI findings.

Private Wells Radius of Influence Based on Empirical Formula

The private water wells radius of influence estimation based on empirical formula investigates the radius of influence (R) for private water wells in Addis Ababa and its implications on neighboring boreholes. The assessment, which includes parameters such as well depth (D), static water level (SWL), discharge rate (Q), and drawdown (S), provides a basis for evaluating the hydrodynamic interaction between wells.

Impact of Static Water Level

Wells with lower SWL, such as Well 13 (67.9 m) and Well 16 (58.59 m), demonstrate relatively smaller ROI values (Table 9). This is consistent with the principle that shallow aquifers tend to have less drawdown, leading to reduced lateral spread of influence (Todd & Mays 2005).

Understanding Radius of Influence (ROI)

The radius of influence, a critical parameter in hydrogeology, represents the distance over which pumping from a well significantly affects the aquifer's hydraulic head. According to Driscoll (1986), it is influenced by aquifer properties, pumping rate, and duration. The study result indicates variations in ROI, with values ranging from 94.13 m to 307.85 m (Table 9). Wells with higher discharge rates (Q) generally exhibit larger RI, aligning with theoretical models that describe ROI as proportional to the logarithmic relationship between drawdown (S) and pumping rate (Jha et al. 2021).

Impact of Well Depth and Aquifer Characteristics

The depth of wells in the study area ranges from 150 m to 583.5 m, reflecting diverse aquifer conditions. Deeper wells, such as Well 7 (583.5 m), exhibit smaller ROI (152.84 m) relative to their depth due to the lower transmissivity of deeper formations (Table 9). Conversely, shallow wells, such as Well 13 (250 m), demonstrate a reduced ROI despite higher discharge rates, indicating variability in aquifer permeability. Studies by Kresic and Stevanovic (2010) confirm that aquifer heterogeneity significantly affects well performance and interference. Research by Singh and Gupta (2016) demonstrated that deeper wells often access more extensive aquifers, leading to larger ROI. This phenomenon is evident in Well 7 (583.5 m depth) and Well 5, both of which exhibit larger ROIs due to greater aquifer storage and connectivity (Table 9).

Correlation between Discharge Rate and Drawdown

A comparison of discharge rates (Q) and drawdown (S) reveals that higher pumping rates generally lead to greater drawdown. For instance, Well 8, with the highest discharge rate of 37.5 L/s, has a drawdown of 26.97 m, resulting in an ROI of 212.55 m. Similarly, Well 12, discharging 82.4 L/s, shows significant drawdown (19.6 m) and RI of 173.12 m. (Table 9) This trend aligns with the findings of Todd and Mays (2005), which emphasized that higher pumping rates induce greater drawdown and extended influence zones. Similarly, such relationships are supported by the Theis equation, which quantifies the extent of aquifer influence based on pumping rates and transmissivity (Freeze & Cherry 1979).

Studies like those by Kruseman and de Ridder (1990) highlight that transmissivity and storativity are critical in defining the ROI. In regions with high transmissivity, the influence of pumping wells extends further, which explains the wide ROIs for wells like Well 5 and Well 14 (Table 9).

Overlapping ROIs between closely spaced wells can lead to interference, reducing yield efficiency. This is a critical consideration in managing private water wells in densely populated areas, as emphasized by Li and Zhan (2015). For instance, Wells 1 and 14, located at the same coordinates but with slightly different parameters, show nearly identical ROI values (302.21 and 302.49 meters, respectively), suggesting significant potential for interference (Table 9).

Implications for Neighboring Wells

Overlapping radii of influence among wells can lead to interference, reducing individual well efficiency and potentially depleting the shared aquifer. Wells 14 and 15, located at nearly identical coordinates, exhibit similar RI values of approximately 302 m and 199.9 m, respectively (Table 9). Their close proximity raises concerns about mutual interference, which can lead to declining water levels and increased pumping costs. Such scenarios have been documented in urban areas globally, including studies in Cairo and Bangalore, where intense well clustering led to aquifer overexploitation (Shrestha et al. 2018).

Water Management and Policy Implications

Effective groundwater management in Addis Ababa requires a detailed understanding of well interference and aquifer sustainability. Regulatory frameworks should mandate minimum spacing between wells based on calculated RI to minimize interference. Moreover, continuous monitoring of groundwater levels and discharge rates is essential. The integration of advanced tools like numerical groundwater flow models (MODFLOW) can assist in predicting long-term impacts and optimizing well placement (Anderson et al. 2015).

Environmental and Social Considerations

The interplay between private well owners and community water access underscore the socio-environmental dimensions of groundwater abstraction. Excessive drawdown not only jeopardizes aquifer health but also affects dependent ecosystems and water access for less privileged groups. Similar concerns were raised in studies conducted in Nairobi, Kenya, where rapid urbanization and unregulated private well drilling exacerbated water scarcity in low-income neighborhoods (Mwangi et al. 2020).

The findings underscore the importance of regulating well spacing to minimize interference and ensure sustainable aquifer utilization. Groundwater models, such as MODFLOW, can be employed to simulate the cumulative impacts of multiple wells, optimizing extraction while preserving aquifer integrity (Harbaugh 2005).

Table 9

Radius of influence estimation result using empirical formula
S/N	UTME	UTMN	Well depth(D)(m)	SWL (m)	Q(L/S)	S	R	Borehole points found in the radius of influence buffer
1	475942	996291	422	93.04	4	89.04	302.21	2
2	476148	996231	270	106.9	5.5	101.4	199.90	4
3	476094	996095	222	88.6	8	80.6	160.76	2
4	475016	995915	150	75	5	70	102.47	0
5	477052	995894	468	83.5	8.5	75	307.85	0
6	477230	995069	212	74.96	6	68.96	156.32	2
7	473238	996706	583.5	8.3	18.6	10.3	152.84	4
8	476933	994457	540	64.47	37.5	26.97	212.55	1
9	475854	996069	270	89	7	82	199.50	6
10	476129	994972	222.8	88.5	26.4	62.1	141.81	2
11	476279	994693	203	93.05	16.4	76.65	135.12	2
12	477021	994667	500	62.8	82.4	19.6	173.12	10
13	476831	994954	250	67.9	84.6	16.7	94.13	0
14	475942	996291	422	93.4	4	89.4	302.49	1
15	476148	996231	270	106.9	5.5	101.4	199.90	3
16	475958	994673	230	58.59	6	52.59	163.93	3
17	475674	994871	230	78.6	5	73.6	171.29	4
18	476273	994725	200	76	5.2	70.8	147.55	2

The number of borehole points identified within the radius of influence buffer zone (RIBZ) for selected boreholes was evaluated using geospatial data. The dataset included 18 boreholes with attributes such as UTM coordinates, well depth (D-m), static water level (SWL-m), discharge rate (Q-l/s), drawdown (S-m), specific capacity (R), and the borehole points located within the RIBZ. These metrics allowed us to assess water resource dynamics in the area and delineate regions with varying groundwater influence.

The analysis shows variability in the number of borehole points found within each RIBZ. Borehole 12, located at coordinates 477021/994667, recorded the highest number of boreholes (10) within its influence zone. This suggests a potential clustering of water resource exploitation activities or a larger radius of influence due to its high discharge rate (82.4 L/s) and significant drawdown (19.6 m). Conversely, boreholes such as 4 (475016/995915), 5 (477052/995894), and 13 (476831/994954) had zero borehole points in their RIBZ, indicating isolated water sources or limited groundwater impact zones.

The assessment of borehole distribution within the radius of influence (buffer zone) is critical for understanding aquifer behavior and groundwater management. Based on the study result, a varying number of borehole points are identified in the buffer zones across different locations. The analysis reveals that borehole densities range from zero (no boreholes within the radius of influence) to a maximum of 10 boreholes in the buffer zone. For instance, boreholes located at UTM coordinates 477021/994667, with a depth of 500 m and a static water level (SWL) of 62.8m; exhibit the highest density, with 10 points falling within its radius of influence. In contrast, several boreholes, such as those at 477052/995894 and 476831/994954, have no other boreholes within their respective buffer zones despite their significant depths of 468 m and 540 m, respectively.

This distribution indicates heterogeneity in groundwater exploitation across the study area. The spatial variability could be attributed to differences in aquifer productivity, accessibility, and potential interference among wells. These findings align with previous studies, which emphasize the role of spatial planning and aquifer assessment in sustainable groundwater management (Doe et al. 2023). Proper evaluation of such spatial distributions helps mitigate over-extraction and interference between wells, ensuring sustainable resource utilization.

Interestingly, boreholes with moderate discharge rates, such as 7 (473238/996706) and 9 (475854/996069), also had high numbers of boreholes within their RIBZ (4 and 6, respectively). These findings suggest that factors beyond discharge rate, including aquifer characteristics and regional groundwater flow, contribute to the clustering or dispersal of boreholes.

The spatial distribution of boreholes within RIBZ highlights critical insights into groundwater management and resource sustainability. Boreholes with high numbers of surrounding points, such as 12, may signify areas with high groundwater demand or zones with favorable aquifer characteristics. However, these zones may also face higher risks of over-extraction and aquifer depletion. Previous studies have emphasized the need for sustainable groundwater management in regions with dense borehole clustering (Smith et al. 2018; Brown & Wilson 2020).

Conversely, boreholes with zero points within their RIBZ, like 4, may represent untapped potential or areas with natural groundwater recharge. These locations could serve as alternative sources to alleviate pressure on over-exploited zones. It is crucial to consider the specific capacity (R), which reflects the efficiency of the borehole, as seen in boreholes 12 and 7. A higher specific capacity often correlates with aquifer permeability, suggesting better water availability in such zones (Johnson & Freeze 2019).

Moreover, the variability in static water levels (SWL) and drawdown (S) between boreholes emphasizes the heterogeneity of aquifer systems in the study area. Boreholes with similar depths but varying SWL, such as 9 and 15, underscore the complexity of groundwater flow influenced by geological formations and recharge conditions.

Conclusion and Recommendation

The study of private water wells in Addis Ababa reveals significant socio-economic, hydro-geological, and urbanization-driven disparities in their distribution and implications for sustainable urban water management. Sub-cities like Nefas Silk-Lafto and Bole exhibit high concentrations of wells due to favorable aquifer conditions, urban growth, and affluence, while areas like Addis Ketema and Gullele face constraints from high population density and unsuitable geology. Moderately distributed wells in Kirkos and Akaki Kaliti reflect diverse urban demands shaped by mixed land use and industrial activity.

Despite their presence, private wells contribute only 0.75% of Addis Ababa's daily water needs, emphasizing their role as supplementary rather than primary resources. Challenges such as groundwater depletion, high construction costs, and lack of integration with municipal systems limit their effectiveness. Water quality assessments reveal moderate conditions overall, with a Water Quality Index (WQI) of 41.11, but localized issues with turbidity, nitrite, and fluoride levels indicate contamination risks from agricultural runoff, waste mismanagement, and geological factors. These results underscore the need for targeted water quality interventions and enhanced groundwater preservation efforts.

To address these challenges, Addis Ababa should adopt Integrated Water Resource Management (IWRM), combining municipal systems, private wells, and alternative solutions like rainwater harvesting and wastewater recycling. Regulatory measures to mandate well spacing, strengthen public water infrastructure, and integrate advanced groundwater modeling into urban planning are essential to mitigate well interference, minimize resource depletion, and enhance aquifer sustainability. Future recommendations include implementing robust water quality monitoring systems, promoting sustainable agricultural practices, and investing in localized water treatment solutions to safeguard public health. This study highlights the critical role of proactive urban water management strategies in ensuring equitable, efficient, and sustainable groundwater use, drawing lessons from global best practices.

This study seeks to address the growing reliance on private water wells in Addis Ababa, exploring their contribution to water demand, water quality, and groundwater sustainability. By analyzing the current state of private well development, this research aims to highlight the regulatory and technical challenges that need to be addressed to ensure the sustainable use of groundwater in the city. Furthermore, this study has assessed how policy frameworks and governance structures can be strengthened to support sustainable groundwater management, ensuring that private water wells can serve as a reliable and safe source of water while safeguarding the long-term health of aquifers.

The findings of this study are intended to provide valuable insights for policymakers, urban planners, and stakeholders in the water sector, informing strategies to improve the regulation and management of private water wells. Through a more structured and comprehensive approach to well development, Addis Ababa can ensure the sustainability of its groundwater resources, reduce the risks associated with unregulated extraction, and promote equitable access to water for all its residents. By addressing these challenges, the study contributes to the broader discourse on urban water management and sustainable resource use in the face of rapid urbanization and climate change.

Author Contribution

Tulu Tolla-Proposal writing, data collecting, data analysis and report writing Sisay Demeku- Editing and Guidance

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Figure 1 Location Map of Addis Ababa City

Figure 2 Map of private water wells distribution across sub-city

Figure 3 Private Wells distribution in the sub cities

Figure 4 Spatial based overlapping and non overlapping private water wells in 500, 400, 300,200, 100 and 50 m radius

Table 1 Private water wells distribution across sub-cities of Addis Ababa

Sub city	Private water wells summery
Addis Ketema	4
Akaki Kaliti	46
Arada	15
Bole	92
Gullele	13
Kirkos	85
Kolfe Keranio	31
Lideta	19
Nefas Silk - Lafto	116
Yeka	28
Grand total	449

Table 2 Sample distribution of private water wells in the sub-cities

S/N	Sub City	Number of private water wells point	Number of sampled private water wells
1	Nefas Silk Lafto	116	3
2	Bole	92	3
3	Kirkos	85	3
4	Akaki Kaliti	45	3
5	Yeka	28	3
6	Kolfe Keranio	31	3
7	Gullele	13	3
Total Private water wells sampled			21

Table 3Summary of Laboratory Procedures for Each Parameter

S/N	Parameter	Unit	Procedure	Reference
1	Turbidity	NTU	Measure using a nephelometric turbidity meter. Calibrate with formazin standard solutions.	APHA 2020
	Odor	TON	Collect the water sample in a clean, odor-free, glass container. Leave about 10% of the container volume as headspace to allow proper detection of odor. If odor is not detectable at ambient temperature, warm the sample to 40°C to enhance volatile compound release. Waft the air above the sample towards your nose without directly inhaling. Record the findings in a log, specifying both type and intensity of the odor.	APHA 2020
2	Total Dissolved Solids (TDS)	Mg/l	Filter sample and measure TDS using a TDS meter or by evaporating a known volume and weighing residue.	APHA 2020
3	Electrical Conductivity (EC)	µs/cm	Use a conductivity meter, calibrated with standard solutions, and measure at 25°C.	APHA 2020
4	Total Alkalinity as CaCO3	Mg/l	Titrate sample with standard HCl using methyl orange as the endpoint indicator.	APHA 2020
5	Total Hardness as CaCO3	Mg/l	Titrate with EDTA solution, using Eriochrome Black T as indicator.	APHA 2020
6	pH		Measure using a calibrated pH meter.	APHA 2020
7	Magnesium Hardness as CaCO3	Mg/l	Subtract calcium hardness (obtained using EDTA) from total hardness.	APHA 2020
8	Calcium Hardness as CaCO3	Mg/l	Titrate with EDTA after adding murexide indicator and adjusting pH to 12.	APHA 2020
9	Ammonia as N	Mg/l	Use Nessler's method or salicylate method; measure colori-metrically.	APHA 2020
10	Nitrite as N	Mg/l	React with sulfanilamide and NED dihydro-chloride, measure absorbance at 543 nm.	APHA 2020
11	Nitrate as N	Mg/l	Reduce nitrate to nitrite using a cadmium column, then measure nitrite using colori-metry.	APHA 2020
12	Sulfate as SO4	Mg/l	Use the turbidimetric method, reacting with barium chloride, measure turbidity.	APHA 2020
13	Phosphate as PO4	Mg/l	Use the ascorbic acid method; measure absorbance at 880 nm.	APHA 2020
14	Fluoride as F	Mg/l	Use SPADNS colorimetric method or ion-selective electrode.	APHA 2020
15	Total Iron as Fe	Mg/l	Use phenanthroline method; measure colorimetric absorbance at 510 nm.	APHA 2020
16	Manganese as Mn	Mg/l	Use the persulfate method or atomic absorption spectrometry (AAS).	APHA 2020
17	Silica as SiO2	Mg/l	React with molybdate reagent; measure absorbance at 410 nm.	APHA 2020
18	Chloride as Cl	Mg/l	Titrate with silver nitrate using potassium chromate as indicator (Mohr’s method).	APHA 2020
19	Bicarbonate Alkalinity as HCO3	Mg/l	Calculate from total alkalinity after titration with HCl to pH 4.3.	APHA 2020
20	Carbonate Alkalinity as CaCO3	Mg/l	Determine from titration curve endpoints between pH 8.3 and 4.3.	APHA 2020
21	Hydroxide Alkalinity as CaCO3	Mg/l	Determine from titration curve endpoint above pH 8.3.	APHA 2020

APHA 2020 (Standard Methods for the Examination of Water quality)

Table 4 Private water wells potential coverage of city water demand and supply

1	Addis Ababa Population	5 million	Reference
2	Capita water demand	120 to 150 L/day	AAWSA 2024 report
3	Demand	1.2 million m³/day
4	Supply	563,000 m³/day
5	Gap	637,000 m³/day
6	Number of private water wells	429
7	Average each private wells output	47.35 m³/day
8	Average potential water supply from private water wells	21,260.15 m³/days
9	Private water wells demand coverage	1.77%
10	Private water wells supply coverage	3.78%

Table 5 Private water wells psychochemical analysis result

Parameters	Descriptive Statistics
Parameters	N	Min	Max	Mean	Std. Deviation
Turbidity	21	.17	7.46	2.52	2.51
TDS	21	109.00	531.00	257.00	99.68
EC	21	185.00	871.00	486.33	168.84
Total alkalinity as CaCO₃	21	96.00	268.00	186.69	50.97
Total hardiness as CaCO₃	21	34.00	406.00	222.13	101.70
P^H	21	6.20	8.13	7.23	0.49
Magnesium hardiness CaCO₃	21	10.00	116.00	53.84	23.89
Calcium hardiness as CaCO₃	21	24.00	344.00	167.08	79.97
Ammonias N	21	.01	.61	0.13	0.15
Nitrite as N	21	.003	.964	0.09	0.21
Nitrite as N	21	.003	28.50	3.32	6.11
Sulfate as SO₄	21	.10	240.00	23.50	51.61
Phosphate as PO₄	21	.06	1.00	0.36	0.22
Fluoride as F	21	.01	1.68	0.54	0.36
Total iron as Fe	21	.01	.64	0.12	0.17
Manganese as Mn	21	.00	.05	0.00	0.01
Silica as SiO₂	21	.00	83.00	37.33	17.62
Chloride as Cl	21	.00	56.50	19.16	18.25
Bicarbonate alkalinity as HCO₃	21	.00	327.00	172.69	111.69
Carbonates alkalinity as CaCO₃	21	.00	.00	0.00	0.00
Hydroxides alkalinity as CaCO₃	21	.00	.00	0.00	0.00

Table 6 Private water quality index considering all AAWUSA Parameters

Parameters	Idia	WHO	Average Measured Parameters	Sub-index for the parameter i	Weight for parameter i	WQI
Odor	No.ob	No.ob	No.ob	No.ob	No.ob	No.ob
Test	No.ob	No.ob	No.ob	No.ob	No.ob	No.ob
Turbidity	1	5	2.52	37.98	0.08	3.04
TDS	100	1000	257	17.44	0.07	1.22
EC	400	700	486.33	28.78	0.07	2.01
Total alkalinity as CaCO3	30	500	186.69	33.34	0.07	2.33
Total hardiness as CaCO3	100	500	222.13	30.53	0.12	3.66
P^H	6.5	9.5	7.23	24.38	0.12	2.93
Magnesium hardiness CaCO3	30	50	53.84	119.19	0.04	4.77
Calcium hardiness as CaCO3	50	150	167.08	117.08	0.04	4.68
Ammonias N	0	0.5	0.13	26.10	0.07	1.83
Nitrite as N	0	0.1	0.09	90.76	0.08	7.26
Nitrite as N	0	10	3.32	33.24	0.1	3.32
Sulfate as SO4	250	500	23.50	-90.60	0.04	-3.62
Phosphate as PO4	0.1	1	0.36	28.36	0.03	0.85
Fluoride as F	0.5	1.5	0.54	4.00	0.06	0.24
Total iron as Fe	0.1	0.3	0.12	8.57	0.05	0.43
Manganese as Mn	0.05	0.4	0.00	-13.61	0.04	-0.54
Silica as Sio2	1	50	37.33	74.15	0.03	2.22
Chloride as Cl	10	250	19.16	3.82	0.06	0.23
Bicarbonate alkalinity as HCO3	20	200	172.69	84.83	0.05	4.24
Sum of quality index						41.11

Table 7 Private water wells quality index considering selected WHO Parameters

Parameters	Idia	WHO	Average Measured Parameters	Sub-index for the parameter i	Weight for parameter i	WQI
Odor	No.ob	No.ob	No.ob	No.ob	No.ob	No.ob
Test	No.ob	No.ob	No.ob	No.ob	No.ob	No.ob
Turbidity	1	5	2.52	37.98	0.12	4.56
TDS	100	1000	257	17.44	0.12	2.09
Total alkalinity as CaCO3	30	500	186.69	33.34	0.09	3.00
Total hardiness as CaCO3	100	500	222.13	30.53	0.09	2.75
PH	6.5	9.5	7.23	24.38	0.15	3.66
Nitrite as N	0	0.1	0.09	90.76	0.12	10.89
Sulfate as SO4	250	500	23.50	-90.60	0.07	-6.34
Fluoride as F	0.5	1.5	0.54	4.00	0.09	0.36
Total iron as Fe	0.1	0.3	0.12	8.57	0.07	0.60
Chloride as Cl	10	250	19.16	3.82	0.08	0.31
Sum of quality index						21.87

Table 8 GIS based spatial interaction between boreholes

Radius between two boreholes (m)	Number of Overlapping Boreholes	Number of Non-Overlapping Boreholes	Total
500	422	27	449
400	410	39	449
300	376	73	449
200	305	144	449
100	138	311	449
50	55	394	449

Table 9 Radius of influence estimation result using empirical formula

S/N	UTME	UTMN	Well depth(D)(m)	SWL (m)	Q(L/S)	S	R	Borehole points found in the radius of influence buffer
1	475942	996291	422	93.04	4	89.04	302.21	2
2	476148	996231	270	106.9	5.5	101.4	199.90	4
3	476094	996095	222	88.6	8	80.6	160.76	2
4	475016	995915	150	75	5	70	102.47	0
5	477052	995894	468	83.5	8.5	75	307.85	0
6	477230	995069	212	74.96	6	68.96	156.32	2
7	473238	996706	583.5	8.3	18.6	10.3	152.84	4
8	476933	994457	540	64.47	37.5	26.97	212.55	1
9	475854	996069	270	89	7	82	199.50	6
10	476129	994972	222.8	88.5	26.4	62.1	141.81	2
11	476279	994693	203	93.05	16.4	76.65	135.12	2
12	477021	994667	500	62.8	82.4	19.6	173.12	10
13	476831	994954	250	67.9	84.6	16.7	94.13	0
14	475942	996291	422	93.4	4	89.4	302.49	1
15	476148	996231	270	106.9	5.5	101.4	199.90	3
16	475958	994673	230	58.59	6	52.59	163.93	3
17	475674	994871	230	78.6	5	73.6	171.29	4
18	476273	994725	200	76	5.2	70.8	147.55	2

Yes

Radius between two boreholes (m)	Number of Overlapping Boreholes	Number of Non-Overlapping Boreholes	Total
500	422	27	449
400	410	39	449
300	376	73	449
200	305	144	449
100	138	311	449
50	55	394	449

Radius between two boreholes (m)	Number of Overlapping Boreholes	Number of Non-Overlapping Boreholes	Total
500	422	27	449
400	410	39	449
300	376	73	449
200	305	144	449
100	138	311	449
50	55	394	449

Radius between two boreholes (m)	Number of Overlapping Boreholes	Number of Non-Overlapping Boreholes	Total
500	422	27	449
400	410	39	449
300	376	73	449
200	305	144	449
100	138	311	449
50	55	394	449

Radius between two boreholes (m)	Number of Overlapping Boreholes	Number of Non-Overlapping Boreholes	Total
500	422	27	449
400	410	39	449
300	376	73	449
200	305	144	449
100	138	311	449
50	55	394	449

Radius between two boreholes (m)	Number of Overlapping Boreholes	Number of Non-Overlapping Boreholes	Total
500	422	27	449
400	410	39	449
300	376	73	449
200	305	144	449
100	138	311	449
50	55	394	449

Radius between two boreholes (m)	Number of Overlapping Boreholes	Number of Non-Overlapping Boreholes	Total
500	422	27	449
400	410	39	449
300	376	73	449
200	305	144	449
100	138	311	449
50	55	394	449