Water is necessary for human health, economic success, and happiness, as well as other developmental goals such as proper diet, gender equality, education, and poverty reduction. Drinking water is a common problem in Ejere Town. The primary goal of this study was to investigate the accessibility of the town's drinking water distribution system. To achieve this research goal, the hydraulic performance of the town's water distribution system and the level of customer satisfaction were assessed. 374 sampled households were randomly chosen from a total of 13,380 to measure the degree of customer satisfaction with the town's water supply services, and the hydraulic performance of the town's water distribution system was analyzed using the WaterGEMS software. Of the 374 customers surveyed for the study, 85 (22.7%) were satisfied and 289 (77.3%) were dissatisfied, implying that the satisfaction levels were below average. The WaterGEMS hydraulic model was calibrated (R2 = 0.94) using measured data from nine randomly chosen nodes. According to the model results, a great amount of the velocity and pressure in the water distribution system was below the minimum recommended limits. These minimum pressures and velocity levels indicate that there is not enough water pressure in the distribution network to reach all parts of Ejere Town. Finally, it was concluded that there was insufficient access to drinking water in the town.

  • The hydraulic performance of the water distribution system was studied.

  • Customer satisfaction of the water users was studied.

  • Measured pressure at selected nodes was used to calibrate the WaterGEMS software before the hydraulic performance analysis.

Graphical Abstract

Graphical Abstract
Graphical Abstract

Water is necessary for human health, economic success, and happiness, as well as other developmental goals such as proper diet, gender equality, education, and poverty reduction (Bereskie et al. 2017; Duan et al. 2020; Tessema 2020). Leaders from 193 nations came together in 2015 to study future prospects and formulated the Sustainable Development Goals (SDGs), which are comprised of 17 goals and 169 targets that must be met and completed by 2030. One of the goals of SDG 6 (6.1) ensures that everyone has access to safe and inexpensive drinking water, and there will be full coverage of safely managed drinking water by 2030 (UN 2018).

Table 1

Projected population numbers until the year (2021)

Year201920202021
Growth rate (%)  4.2 4.0 
Population 61,756 64,405 66,900 
Year201920202021
Growth rate (%)  4.2 4.0 
Population 61,756 64,405 66,900 

The least-developed countries (LDCs), particularly those in Sub-Saharan Africa (SSA), are the most affected, with a disproportionately higher proportion of the population lacking access to safe drinking water. Population growth, changing lifestyles, and rapid urbanization will continue to widen the gap between water demand and available supply, particularly in urban regions, where the majority of SSA's urban population resides (Santos et al. 2017).

Table 2

Total customer satisfaction from all kebeles in terms of time and distance

Households satisfactionFrequencyPercent
Conveyance on-premises 11 2.9 
Medium 74 19.8 
Less conveyance 274 73.3 
No conveyance 15 4.0 
Total 374 100.0 
Households satisfactionFrequencyPercent
Conveyance on-premises 11 2.9 
Medium 74 19.8 
Less conveyance 274 73.3 
No conveyance 15 4.0 
Total 374 100.0 

Since 1990, a global report on drinking water, sanitation, and hygiene has estimated that 844 million people have been left without even basic drinking water services, 263 million people have spent more than 30 min per round trip to collect water from an improved source (constituting a limited drinking water service), and 159 million people have received drinking water from surface water sources, with 58% of them living in SSA (WHO and UNICEF 2017).

In SSA, 42% of people lack access to basic water, and 72% lack access to basic sanitation. Africa, on the other hand, is quickly urbanizing, with a population of 1.3 billion expected by 2050 (Eberhard 2019).

The quantity and quality of water available in households is likely a function of time or distance to collect water from sources that are accessible if located within 30 min of the point of use, but not accessible if located more than 30min from the source (Cassivi et al. 2018). A household is considered to have access to safe drinking water if it has a sufficient amount of water for its use at an affordable price that is readily available to its members without requiring extreme effort (UN-HABITAT 2003).

According to the WHO, access to drinking water is defined based on the quantity of water used (access to drinking water at least 20 l/c/d within 1 km radius for customers) (Kennedy 2006).

The proportion of the world's population that uses a piped drinking water connection, other improved drinking water sources, or unimproved sources is as follows: 87% of the world's population uses drinking water from improved sources, 54% uses a piped connection in their dwelling, yard, or plot, and 33% uses other sources without a piped water connection (WHO 2017).

The ability of a water distribution network to deliver a required quantity of water under sufficient pressure and at an acceptable level of quality during various normal and abnormal operational situations and any water utility's performance is measured by the efficiency of the water distribution systems in place; and the assessment of an undertaking's performance is used to measure the quality of service as well as the utility's effectiveness and efficiency (Makaya & Hensel 2014). The hydraulic performance of the water distribution system, which is impacted by the condition of the pumping unit, network design, pipe material, and pipe age, is measured by the ability of the water supply system to satisfy the required demand under sufficient pressure during normal and abnormal operating conditions (pipe failure, leakage, and excess demand) (Hunde & Itefa 2020). The first and most obvious issue to address is to improve the hydraulic performance of a water distribution system, which is driven by the need to supply a specific set of demand points with appropriate flow and pressure while avoiding significant variations in the parameters (Jalal et al. 2008). According to the national standard, the operating pressure in the distribution network should be 15–60 m under normal conditions and 10–70 m under exceptional conditions, and water velocity should be between 0.6 and 2 m/s, although one can find pipelines with zero velocity in the looped system (MoWR 2006).

A majority of developing countries in Africa and Asia are severely impacted by the issue of access to clean and safe potable drinking water. However, most developing countries, like Ethiopia, are still unable to secure adequate potable water and have limited access to potable drinking water, causing inhabitants to suffer from a water crisis (Mekuriaw 2019). The situation in Ejere Town is not different, although there is no basic understanding of distribution system performance and consumer satisfaction. Hence, the goal of this study is to investigate the hydraulic performance and customer satisfaction levels of drinking water supply services in Ejere Town, as it has been found that the town's community faces difficulties in finding adequate drinking water for its households.

Study area

Ejere Town is located 43 km west of Addis Ababa, the country's capital city. The town is accessible via Ambo and Wellaga Road, and is geographically located at 9°2′0″–9°4′ 30″N latitude and 38°23′30″–38°26′ 30″E longitude with an elevation ranging from 2,202 to 2,442 m at an average elevation of 2,323 m above sea level. The mean annual temperature of the research region is between 6.2 and 27.4 °C within the average of 17 °C; the mean annual rainfall is 1,200 mm according to climatic data received from the Ethiopian Meteorological Service Agency. The highest temperatures are recorded between November and May, and the lowest temperatures are recorded between June and October (Figure 1).

Data types and methods of data collection

Both primary and secondary data collection strategies were used to obtain the necessary information for the research.

Sources of primary data

Field measurement and observation: Water pressures were measured at representative nodes using a pressure gauge to calibrate the simulated results. Additional information related to checking the presence of water at any time, pipeline area coverage, connectivity types, and their locations, GPS (Global Positioning System) location of the node and service reservoir, is obtained.

Questionnaire and household survey: This is one of the data collection methods to generate information from sampled households/respondents. The researchers employed close-ended questionnaires to acquire primary data from respondents. The researchers were able to get direct responses from the respondents. The close ended questionnaire has several sections, including respondents’ kebeles, sources of drinking water, customer satisfaction level indicators of urban drinking water accessibility, such as distance to sources, time spent for collecting water from sources (getting to, queuing, filling, and returning home), and water quantity and quality of the town water supply services from respondents to meet the customer satisfaction goal.

Sources of secondary data

Information on the elevation of the existing distribution system, pipe data such as material type, size, and length, tank data, distribution network layout, population number, mode of service, pump operating time, and so on were gathered from relevant organizations. The existing water supply system in Ejere includes three groundwater boreholes located within and outside the town and two masonry service reservoirs, a 100 m3 trapezoidal reservoir and a 100 m3 circular one. Water from each of the three boreholes is pumped to its respective service reservoirs via 80–150 mm diameter galvanized iron (GI) pipes with a total estimated length of 4.6 km. The distribution network consists of high-density polyethylene (HDPE) pipes with diameters ranging from DN 50, 50–80, and above 80 mm covering 12.4%, 20.4%, and 58.4%, respectively. The sources of services for domestic water consumers are as follows: house connections (0.5%), private yard connections (30%), shared yard connections (25%), and public taps (44.5%).

Population forecasting

According to the town's administration, its total population was 61,756 in 2019. However, using the 2007 population and housing census analytical report within the Oromia region growth rate, the current population was forecasted to the research year (2021). The Ethiopian Central Statistics Authority uses equation (1) for population forecasting and this method was used to forecast the population in the study area.
(1)
where Pn is the population at nth year, Po is the base population, r is the population growth rate, n is the number of years, and e is constant.

Analysis of the town's level of connection

The amount of domestic connection per family can be used to assess water supply. The recommended level of domestic water supply connection per family is 1 or 100% (as best practice), which means one connection per family (Abduro & Sreenivasu 2020). In this study, the level of connection was calculated by the number of connections in the town's average family size and divided by the total population within the expression of Equation (2). In the 2021 research year, there were in total 5,753 consumer meters in the entire town, according to data received from the town's water supply administration office.
(2)

Water demand

Water demand in the town fluctuates depending on population size, economic, social, and climatic conditions, as well as the manner of service, and encompasses all combinations of domestic, commercial and institutional, industrial, public, firefighting, and unaccounted for water. It was decided for all of the standard sets to take the percentage of each demand category from domestic demand that was set within national standards, FDRE Ministry of Water Resources urban water supply design criteria (MoWR 2006), to estimate the non-domestic demand for the study.

Assessment of the hydraulic performance of the existing distribution system

The Bentley WaterGEMS software, which aids in the evaluation of water distribution systems, was used to examine the existing Ejere Town's water supply system. WaterGEMS is attractive due to its integration with ArcGIS and AutoCAD software, which allows it to be visualized in a range of graphical tools, including ArcGIS mapping. The layout of the water distribution system was obtained in AutoCAD format from the town's water supply administration office. The network was then imported into Bentley WaterGEMS via the model builder toolbar, converted to software format, and analyzed by entering the most important data via the software data entry dialog box.

Developing the distribution network

The network was developed by using data entry dialog boxes to enter data from field surveys, offices, and other sources, such as nodes (elevation, geometry, and base demand), pipes (pipe diameters, pipe lengths, material types, pipe roughness), tank (base, initial, minimum, and maximum elevation, and diameters of the tank), pumps (elevation, pump head, and yields), and Hazen Williams roughness coefficient values were used in the Water Gems software. The International System (SI) was applied throughout the process under the hydraulic option to define all parameters (lengths, diameters, heads, and elevations) within SI standards. The data analysis was simulated by developing water distribution network scenarios to evaluate the performance of the hydraulic parameters in terms of pressure, velocity, flow, head loss, and others.

Base water demand allocation

While data are available only as population information stored in ArcGIS in terms of the area of given land use, population, and population density, the modeler should use a population-based demand allocation method for the water distribution system's junction (Haestad Press Waterbury 2017). Due to the availability of population data stored in ArcGIS within the kebele shapefile, population-based demand allocation was used for the study for the spatial distribution of water demand throughout the hydraulic network model. To allocate the base demand for the node in the water distribution network, the following steps were followed: the kebele shapefile obtained from the town administration was displayed on ArcGIS and its respective population numbers were filled in the Attribute Table, and the population density in a given area was calculated by dividing the population of the kebeles by their respective area. The Thiessen polygon was used to design the nodal influence area around each demand node on the town water distribution network using the WaterGEMS software, and it could be converted to shapefile format. The Thiessen polygon was used to form a polygon around the junction influenced area on the WaterGEMS software and saved in shapefile format. The kebele shapefile, which had been filled with relevant data in ArcGIS, was loaded into WaterGEMS using the load builder toolbar of the software. The demand for each junction was assigned within the load builder toolbar on WaterGEMS within the load estimation by population density methods: first, the load builder dialog box was opened and load estimation by population methods was selected. The influenced area for each junction that was created within the Thiessen polygon on WaterGEMS and the population shapefile that was created on ArcGIS were loaded. Next, load density demand for each kebele within its proportional population (Figure 2) was filled in the displayed table. The demand for each junction was automatically loaded just after load density demand was entered for each kebele with the help of ArcGIS to prepare attribute tables on town population shapefile and WaterGEMS by creating a polygon for each junction-influenced area.

Figure 1

Description of the study area.

Figure 1

Description of the study area.

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Figure 2

Demand allocation for the junction within the Thiessen polygon.

Figure 2

Demand allocation for the junction within the Thiessen polygon.

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Model calibration and validation

In the current study, the model calibration was achieved by taking 10% of the total nodes’ water pressure measured from nine points at low-demanded and high-demanded water consumption periods which were dependent on the standards of USEPA water distribution system calibration guidelines that the numbers of pressure reading 2–10% of total nodes from low pressures to high pressures by the use of portable pressure gauge and made minor adjustments for the sensitive parameters (pipe roughness and nodal demand) until its simulated results were approached to actual or field results. The study-measured water pressure location was determined using a GPS and organized on Excel. The prepared data were uploaded to Google Earth, stored in kml format, and then transferred to Global Mapper. The Global Mapper exported the data or converted the kml format data to shapefile, which was then displayed on ArcGIS and overlapped within the town water distribution system layout to show the location of the points of field-measured pressure sampling for calibration, as exhibited in Figure 3.

Figure 3

Sampling points of field pressure measurement for calibration.

Figure 3

Sampling points of field pressure measurement for calibration.

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The statistical correlation coefficient (R2) was used for the study to evaluate the accuracy of the model in terms of the results of the model output and field data, because the correlation coefficient measures the strength of a straight line or the linear relationship between two variables, described in the form of Equation (3).
(3)
where X is the observed data, is the average of the observed data, Y is the simulated data, and .

Assessment of customer satisfaction for current water supply service

Sampling technique and sample size

Stratified and systematic random sampling techniques were used for the study. As a result, representative households in four separate centers, Kebele-1, Kebele-2, Kebele-3, and Chiri, were selected randomly. These households were identified systematically using house numbers in all four centers with appropriate allocation. The investigator used the sample size determination (Equation (4)) that was developed by Kothari (1990).
(4)
where n is the sample size, Z is the standard variant at a given confidence level = 1.96, p is the sample proportion, if there is no previous study on the key parameters (p is taken as 50%), N is the number of households, q = 1–p, and e is the precision (significance level = 5%). From the total number of households, n representative samples (households) were taken as samples by using the above formula.

Data types, sources of data, and data collection tools

The researchers employed close-ended questionnaires to acquire primary data from respondents. The questionnaires were divided into sections that included respondents’ kebeles, sources of drinking water, customer satisfaction levels, and indicators of urban drinking water accessibility such as distance to sources, time spent collecting water from sources (getting to the sources, queing, filling, and returning home), and the quantity and quality of town water supply services. Following the data collection, the data were coded, edited, and entered into SPSS (Statistical Package for Social Science) for further analysis. To create a concise picture of the data, the results were presented as tables, ages, and figures.

Population forecasting

According to the town's administration, the total population of the town was 61,756 in 2019. The present population number forecasted for the year 2021 was 66,900 (Table 1).

Analysis of the level of town water connection

The estimated level of town water connection was 0.43 using Equation (3); this implies that the current connection coverage was only 43%, and this clearly shows that the number of water supply connection systems in the town is very low. Similar situations are expected to arise in such small towns of the country.

Current water demand assessment

The current water demand for Ejere Town was estimated based on national standards (MoWR 2006). Depending on Ethiopia's second growth and transformation national plan for the water supply and sanitation sub-sector (2015/2016–2019/2020), Ejere Town was classified under category three within 66,900 population numbers (GTP II 2016). The per capita demand for the modes of service was adopted based on the category of the town, and the domestic water demand was estimated. However, there was no well-organized information indicating the kinds, scale, and water consumption patterns of various sectors found within the town to estimate the non-domestic water demand, and, therefore, the national standard was considered to calculate the percentage of each demand category from the domestic demand. Therefore, based on the above consideration, the estimated current average water demand of the town was calculated to be 923,472.24 m3/year or 29.28 l/s (37.8 l/c/d) for the research year (2021) by using modes of service, current population, and other appropriate standards.

Model calibration and validation results

The results shown in Figure 4 reveal the pressure measured in distribution networks using a portable pressure gauge at the sampling point and the simulated pressure using the WaterGEMS hydraulic model, which was calibrated using Darwin calibrator components and fine-tuned until agreement within field data was achieved (R2 = 0.94), which indicated a degree of strong correlation.

Figure 4

Schematic diagram of calibrated result with Darwin calibrator in WaterGEMS.

Figure 4

Schematic diagram of calibrated result with Darwin calibrator in WaterGEMS.

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Model validation is a step in the calibration process that ensures that the calibrated model is properly evaluated. The correlation coefficient was used to validate the study model because it is a simple method for measuring the strength of a relationship between two variables. As shown in Figure 5, the correlation coefficients for the maximum periods of water consumption were calculated within Equation (5) to be 0.94. Because there were no major differences, the WaterGEMS hydraulic model was validated.

Figure 5

Plot of the correlation between measured and simulated pressures during the town's maximum water consumption period.

Figure 5

Plot of the correlation between measured and simulated pressures during the town's maximum water consumption period.

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Pressure results of the existing distribution system

Sustainable water supply, which is to meet various human needs for water by neither exhausting the water sources and the local economy nor having a long-term negative impact on the environment, needs resilient water infrastructures. In this research, the hydraulic performance of the water distribution system of Ejere was tested. The output pressure contour map at the maximum is reported below after modeling the current situation prevailing in the town from existing data and survey data using the WaterGEMS software and by calibration. As shown in Figure 6, with 18% (16 nodes) falling below 15 m, and 14% (12 nodes) falling below the exaptational minimum pressure standard, 10, set by MoWR (2006), but which was within the recommended maximum pressure limitation during the peak town water consumption period and at the minimum town water consumption period, it was found that 7% of the pressure was below 10 m, 9% was below 15 m, 2% was above 60 m, and the others were within the standard limit.

Figure 6

Water distribution pressure at maximum consumption.

Figure 6

Water distribution pressure at maximum consumption.

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When there was maximum flow in the town's water supply distribution system, which was expected in the period between evening and early morning to the middle of the day, the pressure of the water distribution system was low. Aside from this comparison, the present water distribution network of Ejere Town is functioning beyond the recommended minimum pressure limitation but within the recommended maximum pressure limitation. The geography of Ejere Town is heterogeneous, with gently descending areas in the town's southern region and somewhat around the town's north-east region, and ascending areas all around the town, that is, in the central, northern, eastern, and most of its western parts. Overall, the town's topography (Figure 7) and the unbalanced existing supply and demand cause a pressure difference in most parts of the town, preventing the distribution system from delivering enough water at adequate pressure to all areas. The low-pressure junctions are concentrated within a limited area based on the pressure contour, and this provides the option to deliver water by properly planning the low pressure areas.

Figure 7

Ejere Town elevation contour map.

Figure 7

Ejere Town elevation contour map.

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Velocity of water in the existing distribution system

The velocity of water in the existing distribution system is shown in Figure 8 by color coding from the model results to analyze the system's performance within the recommended standard limit. The results were as follows: 90% less than (0.4) m/s, 2% (0.4–0.6) m/s, 8% (0.6–1.5) m/s, and 0% above 1.5 m/s, as shown in Figure 8. According to these findings, a great amount of velocity of the water supply network distribution system was less than the minimum recommended value of 0.6 m/s, indicating that the distributed amount of water in the system was minimal as a result of less supplied water and a low flow rate, and an improper design of the pipe diameter. Nevertheless, no amount of velocity was above the maximum recommended ranges (2 m/s). At the minimum and maximum town water consumption rates, the flow velocity was almost less than the minimum recommended value (0.6 m/s).

Figure 8

Velocity of water in distribution system annotation.

Figure 8

Velocity of water in distribution system annotation.

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This resulted in low velocity in the distribution system, which could further reduce the water quality due to increased water age and deposited contaminants in the water distribution network. This, in turn, resulted in 77.3% of the water users being dissatisfied with the water service, as pointed out in the section ‘Assessment of customer satisfaction over the current water supply service’. Similar reports on the levels of dissatisfaction among the people were seen in the slum areas, with about 71% of the respondents reporting being dissatisfied with the overall water services in an urban ward in India.

Assessment of customer satisfaction over the current water supply service

From a total of 13,380 households, 374 representative samples were taken. Systematic random sampling techniques were employed to represent the households from each kebele, and Figure 9 shows the sample distribution in each kebele.

Figure 9

Sample size for all kebeles.

Figure 9

Sample size for all kebeles.

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Figure 10

Customers' response related to drinking water interruption and water available within the sources.

Figure 10

Customers' response related to drinking water interruption and water available within the sources.

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Total households’ satisfaction levels in terms of time and distance of water sources

Several studies have been conducted to evaluate the public perception of drinking water quality in addition to the traditional scientific metrics (Mahler 2021). Customers’ satisfaction over their water sources in terms of distance and time was determined based on their overall perception of satisfaction of water supply services in the town. From the results, it was revealed that 11 (2.9%), 74 (19.8%), 274 (73.3%), and 15 (4.0%) respondents belonged to the conveyance on-premise, medium, less conveyance, and no conveyance, categories, respectively.

As can be understood, 85 (22.7%) customers were satisfied and 289 (77.3%) customers were dissatisfied with the drinking water services in terms of the distance from, and the time taken from, their residential areas. This implies that the level of satisfaction was below average; the proportion of satisfied customers was below 50%.

Customer response related to drinking water interruptions and water availability within the sources

The town's piped water service was disrupted, and there was less water accessible in customers’ water sources in a week. As can be observed from the results, 99.7% of the respondents confirmed that drinking water was interrupted in their sources, while only 0.3 customers reported that water was not interrupted from their sources. With regard to consumers reporting on water availability through household taps, the highest percentage of customers responding to water unavailability through their sources in the previous week was 85.5% (45.5% within 1–2 days of the week, and 38% less frequent in a week). According to the respondents, no one received water 7 days/week. Ejere Town is served by three boreholes. However, there was no continuous access to water in the town. In addition, there was frequent interruption from customers’ water sources due to water supply by order (shifting) (Table 2; Figure 10).

Customer satisfaction levels on water supply services by kebeles

Customer satisfaction over drinking water sources in terms of time (the time spent to fetch water and come back), distance (distance to be traveled to fetch), and water quality was analyzed to determine the areas with high and low satisfaction levels for the services, and these are presented in Figure 11. Kebele–Chiri area services recorded the highest dissatisfaction levels with regard to the time needed to collect water from their source (round trip) with 100% (>30 min), and Kebele-01 recorded the highest satisfaction levels with 97.6% (5% on-premise, 24.8% within <5 min, 67.8% on 5–30 min), while Kebele-02 recorded 56.85% satisfaction with (5–30 min) and a dissatisfaction of 43.2% (with >30 min). Kebele-03 reported 1.1% (within 5–30 min) satisfaction levels and a dissatisfaction of 98.9% (with >30 min). With regard to the result on customers’ satisfaction in terms of distance to water sources, Kebe-01 responded with the maximum satisfaction of 86.7% with (6.6% on-premise, 70.2% on >250 m, and 9.9% on 250–500 m) and Kebele–Chiri recorded the highest dissatisfaction level, which was 82.2% with (57.3% on 500–1,000 m and 25% on >1,000 m). Kebele-02 services’ satisfaction level was 69.4% with (47.3% on <250 m, 22.1% on 250–500 m), while 30.6% were dissatisfied with (27.4% within 500–100 m and 3.2% on >1,000 m). Kebele-03 recorded an overall satisfaction level of 38.9% with (2.2% on <250 m and 36.7% on 250–500 m) and had an overall dissatisfaction level of 61.1% with (61.1% on >1,000 m). In terms of the outcome of customers’ satisfaction over water quality perception, Kebe-01 recorded the maximum satisfaction levels with 76.1% with (20.7% good and 55.4% medium) and Kebele-03 recorded the maximum dissatisfaction level with 44.4% with (44.4% poor). The Kebele-02 services area had a 66.3% satisfaction with (20% good and 46.3% medium), while 31.6% recorded dissatisfaction with (31.6% poor) and 2.1% neutral. Kebele–Chiri recorded 60.3% satisfaction with (16.2% on good and 44.1% poor on) and had a dissatisfaction level of 39.7% with (39.7% poor). A majority of the existing public taps were non-functional due to a lack of water, and even households with yard connections remained without water for a week due to a lack of water in the system. Thus, the residents of the town were forced to travel long distances in search of any available water sources. From the above results, it is clear that there was no timely access to water for customers in Kebele-02, Kebele-03 and Chiri–Kebeles. For customer satisfaction within distance (distance traveled to water sources), most customers in all town kebeles were not satisfied when compared with the standards (maximum distance) set by Growth and Transformation Plan (GTP)-I, -II (Ethiopian Growth and Transformation Plan) and JMP (WHO and UNICEF), which were 500 m, 250 m, and 1 km, respectively. These results are summarized and presented in Figure 11.

Figure 11

Customer satisfaction by strata.

Figure 11

Customer satisfaction by strata.

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Figure 12

Customers' responses on the quantity of water collected per day.

Figure 12

Customers' responses on the quantity of water collected per day.

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Customers' responses on the quantity of water collected per day

According to Figure 12, of the total 274 valid households asked for their responses to water quantity collected per day from their sources, 55 customers collected 6–10 l water, 119 customers collected 11–25 l of water, 91 households collected 26–50 l of water, and 9 customers collected 51–75 l of water. This study has seen that most (34 households) collected water (11–25 l) on an average 18 l twice/day, which was equivalent to 36 l/day. Within an average household family size of five, which was obtained from the customer interview, the per capita water consumption was 72.1 l/c/day. The WHO defines access to drinking water based on the quantity of water used (access to drinking water to at least 20 l/c/d for customers) (Kennedy 2006).

The aim of GTP-I was to provide access to water supply for rural and urban areas separately to achieve 100% water supply coverage (15 l/c/d rural and 20 l/c/d urban), and the aim of the second GTP was to provide access to drinking water at 25 l/c/day for the rural population and 40–100 l/c/d for the urban population. The above statistics show that there was no real access to drinking water in the town.

The study examined customer satisfaction levels in Ejere town's existing water supply services, and the results showed that a majority of customers were dissatisfied with their access to improved drinking water at a reasonable distance and time. Of the 374 customers sampled for the study, 85 (22.7%) customers were satisfied, and 289 (77.3%) customers were dissatisfied with the drinking water service in terms of distance and time from their residential area. With regard to customers’ responses in terms of the quantity of water collected per day, most households collected water (11–25 l) on an average 18 l twice/day, which was equivalent to 36 l/day. Within the average household family size (five) that was obtained from customer interviews, the per capita water consumption was 7.2 l/c/d, which was far from national and international standards. The hydraulic performance of the water distribution system was evaluated using WaterGEMS. This software was calibrated using Darwin calibrator components and fine-tuned until a good agreement within the field data was achieved (R2 = 0.94), indicating a degree of strong correlation, and it was verified by using the statistical correlation coefficient. According to the model results, the current town water distribution network was operating above the recommended minimum pressure limitation, with 18% (16 nodes) falling below 15 m, and 14% (12 nodes) falling below the expectational minimum pressure standard of 10 m set by MoWR (2006). But within the recommended maximum pressure limitation during peak town water consumption and at minimum town water consumption period, 7% of the pressure was below 10 m, 9% was below 15 m, 2% above 60 m, and the rest was found within the standard limit. The flow velocity was almost less than the minimum recommended value (0.6 m/s) at the minimum and maximum town water consumption rates due to a shortage of water and a low flow rate, as well as an inappropriate pipe diameter (increasing the size of the pipes), resulting in a lower flow velocity throughout the circuit or system.

This research work has been funded by the Ministry of Education, Ethiopia.

The authors declare no known conflict of interest with any organization.

All relevant data are included in the paper or its Supplementary Information.

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