Water Quality, Reliability and Payment for Services: Household Perspectives II - Water Supply Interruptions and Payment for Water

In this two-part series, Charles Simkins sets out what can be learnt about household perceptions of water services, water quality and interruptions from the 2018 General Household Survey. The second brief considers this information and the extent of household payment for water.

Introduction

The previous brief set out information from the 2018 General Household Survey (GHS) on the sources of drinking water and its quality. This brief will consider information on water supply interruptions, household perceptions on the quality of water services they receive, and the extent of household payment for water. It will also set out general conclusions from both briefs.

Water supply interruptions

In cases where the municipality supplies water, the following questions about water supply interruptions were asked:

  • Whether the supply had been interrupted at any time during the previous 12 months
  • If so, whether any interruption had lasted longer than two days. If it did, what was the alternative source of drinking water used.
  • Whether the supply interruptions occurred for more than 15 days in the last twelve months.

Table 1 sets out the basic information on interruptions.

Table 1 - Interruptions

 

Yes

No

Unspecified

Per cent yes

Water interrupted during last 12 months

5693275

7974743

 

41.7%

Water interrupted lasting for more than 2 days

2762195

2839789

91292

49.3%

Water interrupted for more than 15 days in total

1830418

862075

69702

68.0%

Water interruptions are extensive. 42% of households supplied by municipalities had experienced an interruption in the 12 months prior to the GHS. Of these, half had experienced an interruption lasting for more than two days and just over two-thirds had experienced water interruptions for more than 15 days.

Table 2 reports interruptions by geographical type. They are least severe in urban areas, though nearly a third reported interruption during the past 12 months. Interruptions on farms are worse than in urban areas. They are worst in traditional areas, with nearly 60% of all households reporting interruptions of more than two consecutive days and just under half reporting interruptions for fifteen days or more.

Table 2 - Interruptions by geographical type

 

Last 12 months

More than 2 consecutive days

More than 15 days in total

 

Per cent of total

Per cent of interruptions over last 12 months

Urban

32.8%

34.6%

23.1%

Traditional

80.7%

73.7%

60.4%

Farms

42.4%

46.5%

38.7%

All

41.6%

48.5%

36.5%

When it comes to municipal supply, many more households (5.7 million) have suffered from interruptions in supply than from unsafe or defective water (1.6 million).

Table 3 sets out alternative water sources used by households which experienced water supply interruptions of more than two consecutive days

Table 3 - Alternative water sources used when interruptions have lasted more than two consecutive days

 

Households

Water tanker

735490

None

573974

Water vendor

383834

Other

338372

Rain water tank

179275

River/stream/

174542

Borehole

127706

Unspecified/do not know

91472

Well

72179

Spring

65809

Stagnant water/dam/pool

19541

Total

2762194

Compared against the urban pattern:

  • Households in traditional areas are more likely to use, as alternative sources, water vendors, rain water tanks, rivers and streams, boreholes, wells, springs and stagnant water such as dams and pools.
  • Households on farms are more likely to use rivers and streams, boreholes and springs.

Overall ratings and their determinants

Households were asked whether they regard their municipal water service as good, adequate or poor. Table 4 sets out the distribution of households across the ratings, by geographical type.

Table 4 - Overall rating of municipal service

 

Urban

Traditional

Farms

All

Good

70.2%

29.3%

55.0%

62.6%

Average

22.0%

44.3%

29.7%

26.2%

Poor

7.8%

26.4%

15.3%

11.3%

All

100.0%

100.0%

100.0%

100.0%

Nationally, 63% of households regard their municipally supplied service as good, and 11% as poor. The percentages in the good category drop from 70% in urban areas to 55% on the farms and only 29% in traditional areas. The percentages in the poor category rise from 8% in urban areas to 15% on farms and on farms and 26% in traditional areas.

The determinants of the ratings can be explored using regression analysis[1]. The results show a poorer rating if the water is defective, if there has been an interruption in supply in the last 12 months, if the household is in a traditional area, if there is piped water in yard, a communal tap, a neighbour’s tap, or a water tanker (compared with piped water in dwelling) , and in provinces other than the Western Cape (in increasing size of effect: (1) Gauteng (2) Eastern Cape, KwaZulu-Natal, Mpumalanga, Northern Cape and Limpopo (3) North West and (4) Free State). There is, however, a high level of unexplained variance, in part attributable to differences in criteria for rating between individual households.

The RDP standard, revisited

It was reported in the previous brief that 82%of households had a water supply meeting the RDP standard of piped water in the dwelling, piped water in the yard or a communal tap within 200 metres from the dwelling. Two additional RDP criteria can be added: the water should be safe and there should not be interruptions in supply for more than 15 days in a year. Here ‘safe’ is defined as water which is not defective or water that is defective and not regarded as safe by the household.

Table 5 sets out the results of adding the two criteria. The national percentage of households meeting the RDP standard drops to 69%, varying from 85% in urban areas supplied by municipalities to 17% in traditional areas not supplied by municipalities.

Table 5 - Percentages of households with water supply meeting RDP standards, revised

 

Municipal supply

 

Geographical type

Yes

No

 

Urban

85.5%

37.3%

 

Traditional

38.8%

16.9%

 

Rural

63.2%

46.7%

 

Total

76.7%

26.3%

69.0%

Payment for water

Households which have piped water supplied by municipalities to their dwelling or to their yard were asked whether they pay for water. Table 6 sets out the responses. Just under half of all households who might pay for water do so, with 66% of households having piped water in their dwellings paying, compared with 17% of households having piped water to their yards.

Table 6 - Payment for municipally supplied water

Payment

Piped to dwelling

Piped to yard

Both

Piped to dwelling

Piped to yard

Both

Yes

4838845

708305

5547150

65.8%

17.0%

48.2%

No

2511170

3450181

5961351

34.2%

83.0%

51.8%

Unspecified

57672

21678

79350

     

Total

7407687

4180164

11587851

     

Those not paying for water were asked for reasons why they did not. Possible answers were:

  • The household uses its own source of water
  • The household uses a free water source
  • The household pays the landlord for water directly
  • Water payment is included in a levy
  • The household has permission from the municipality not to pay
  • The household does not have a water meter
  • The household does not receive a water bill
  • The community has decided not to pay for water
  • The household cannot afford to pay for water
  • The water supply is irregular
  • The water supply has been stopped
  • Other
  • Unspecified

Some of the reasons for not paying are better than others. The non-payers are divided into the following categories:

  1. Those with an adequate reason for not paying. These include households paying the landlords in the case of rented accommodation, households paying a levy, households having permission from the municipality not to pay, and households where the water supply has stopped.
  2. Households with no water meters, broken water meters, or not receiving water bills.
  3. Households in communities which have decided not to pay for water or where the household claims not be able to afford payment for water, provided that household per capita income is not more than R 2 000 per month.
  4. The remaining households.

Table 7 sets out the distribution of households across categories. It indicates that 42% of households not paying are doing so for adequate reasons, 16% because their water use is not measured or billed, 13% because households have low incomes. The remaining 29% fall into none of the three categories and they can be regarded as households which ought to pay, but don’t.

Table 7 - Non payers by category

 

Piped to dwelling

Piped to yard

Both

Piped to dwelling

Piped to yard

Both

Adequate reason

1102448

1412140

2514588

43.9%

40.9%

42.2%

No working water meter/no bill

343392

579866

923258

13.7%

16.8%

15.5%

Below income threshold

383015

408047

791062

15.3%

11.8%

13.3%

Other households

682315

1050128

1732443

27.2%

30.4%

29.1%

Total

2511170

3450181

5961351

100.0%

100.0%

100.0%

Summary

Interruptions to the municipal water supply are frequent, and often of long duration. As a source of dissatisfaction, they outweigh poor water quality in the perceptions of households. The interruptions attest to poor operation and maintenance of municipal water infrastructure. While the interruptions last, households are thrown back on using often unsafe sources of water, or they greatly restrict their use of water.

In general, household ratings of water services are rationally related to water quality, water interruptions, geographical type and water sources. Once these factors are controlled for, there remain provincial differences in water service ratings, with Western Cape and Gauteng the most favourable, and North West and Free State the least.

Adding water quality and water interruption criteria to the infrastructural components of the RDP water standard reduces RDP standard compliant households from 82% to 69%.

Just under half of households supplied by municipalities to their dwellings or yards pay the municipalities directly for water. There are good reasons for non-payment in many cases, but about 30% of households which do not pay do not have any of these reasons. Moreover, over 900 000 households do not pay because they have no water meter, or the meter is broken, or they do not receive water bills.

Conclusion

While there is more to be done in linking new communities and households to modern water infrastructure, there are limits to what can be achieved. Reticulating water to remote and low household density parts of the country may become prohibitively expensive.

As the construction of new infrastructure reaches its limits, improved water services requires better operation and maintenance and financial control. The value of infrastructure depreciates sharply if it is not properly looked after, and the picture which emerges from this study is that failure in this regard is widespread. Disorganized, and financially and technically weak municipalities cannot supply adequate water services, so that the water services problem and the local government problem are inextricably linked. At present, it looks as though the local government battle is slowly being lost. The Auditor-General’s 2017-18 Municipal Finance Management Act audit showed an overall decline in municipal audit results, with pervasive control and monitoring failures evident at a significant number of other municipalities across the country. Until this changes, no improvement can be expected in the picture of water services which emerges from the analysis of the 2018 GHS.

Charles Simkins
Head of Research
charles@hsf.org.za

Appendix – Results of ordered probit analysis

Dependent variable

Rating of water service

 

Good =1

 

Average=2

 

Poor=3

Independent variables

 

Not defective

Omitted

Unclear

0.49

Bad taste

0.69

Odour

0.29

No interruption

Omitted

Interruption in last 12 months

0.98

Urban

Omitted

Traditional

0.32

Piped water in dwelling

Omitted

Piped water in yard

0.16

Neighbour's tap

0.53

Communal tap

0.34

Water tanker

0.94

Western Cape

Omitted

Eastern Cape

0.52

Northern Cape

0.60

Free State

1.09

KwaZulu-Natal

0.53

North West

0.82

Gauteng

0.31

Mpumalanga

0.56

Limpopo

0.69

Cutpoint 1

1.51

Cutpoint 2

2.72

Pseudo R squared

0.215


[1] The technique used is backward stepwise ordered probit regression, the numerical results of which are displayed in the Appendix.