1. Presentation to Water Services Forum by Kobie Mare 16 May 2018
Detailed Analysis of Water Use Efficiency per Water Use Component and Category in Rand Water’s Area of Supply
Presentation to Water Services Forum
by Kobie Mare
16 May 2018

2. Contents Background on Water Use Efficiency Model to Bulk Meter level
Inputs
Calculations to date
Outputs
Further development of model to level of Component and Category
Findings
Conclusions

3. Background on Water Use Efficiency Model to Bulk Meter level
Inputs
Geography (SP, Town, Municipality, Discrete metering area (BM_DMA))
Components (Persons, Households, Erfs, Non-res, Real Distribution Loss)
Categories (Level of service re water and sewer, dwelling type, income)
Unit demands per Component and Category(l/c/d, l/hh/d, l/erf/d)
Calculations to date
Normal residential demand per SP, BM_DMA
Actual demand per bulk meter
Water Use Efficiency (WUEI )per BM_DMA
Excess per BM_DMA
Reduceable excess per BM_DMA
Targets per BM_DMA
Outputs
Maps and lists of priority BM_DMAs

4. Further development of model to level of Component and Category
New Calculations
Analysed WUE per Component
Persons
Households
Erfs
Non-residential
Reticulation loss
Analysed WUE per Category (1 to 300; top 20)
Advantages
Enables us to identify and prioritise water use Components and Categories that require the most attention
Appropriate interventions can be developed to address problems causing low efficiency in each Category

5. Findings Findings re WUE per CATEGORY
Most of the water supplied by Rand Water is used by
High level of water and sanitation service
Indigent and low income consumers
High density residential dwelling types (hostels, flats, town houses)
This implies amongst others
Need for interventions that will ensure high efficiency in cases of high level of service (toilet leaks, pressure reduction)
Need to ensure revenue from high income customers to subsidise low income inefficiencies
High density dwelling types need to be addressed

7. Variability per Category
The previous graph shows the values per Category as an average for all suburbs in Rand Water’s area of supply
However, the same values for each individual suburb varies over a wide range per specific Category
This variability assists us to identify those suburbs that perform best or worst per category
The best performers can then be investigated to understand the reasons for their good performances. The best practice lessons learned from these suburbs can then be applied in other suburbs of the same Category
The worst performers can also be investigated to understand the reasons for their bad performances. Appropriate interventions can then be designed to rectify these problems
The graph on the next slide shows the variability in efficiency per suburb of the most populous Category 296 (HouseWater; FlushPipe; HouseStand; Indigent)

9. Findings Findings re ALL COMPONENTS: ACTUAL vs BENCHMARKS
ACTUAL RES = 104% of RES LICENCE (1.25*NORMAL)
This is in line with the overall situation of Rand Water’s total abstraction
However, due to large deviations in efficiency across suburbs, the extreme cases where the Actual exceeds the Normal by more than 50% need to be isolated and assessed
Sum of All Excesses per SP larger than 1.5*NORMAL = 10 Mkl/m; = 12% of ACTUAL RES
Implication:
If all Excess > 1.5 were eliminated, The Actual Residential Demand would bring Rand Water within the Licence limits
Recommendation:
Whole water cycle should focus on staying below a WUEI of 1.5
End User to repair leaks and use water wisely
Municipality should reduce distribution losses (Pressure and Leaks)
Rand Water should improve its own efficiencies and restrict all bulk meters to 1.5*NORMAL

11. Further analysis
The above analysis has also been done for various scales
Municipality
Town
SP (Suburb)
RW Bulk meter DMA
RW System and Sub-system
The respective components have also been analysed separately
Persons use
Household use
External use
The analysis also discerns between various water use categories based on
Level of water and sanitation service
Dwelling type
Income level

12. Conclusion
The further development of the WUE model enables us to identify and prioritise water use Components and Categories that require the most attention on a regional level
Appropriate interventions should be designed to mitigate the risks associated with each water use Category
Where a particular Category shows large differences in efficiency in various localities it should be investigated to determine the root causes
The analysis should assist in the identification of aspects that require further study
The municipalities should do similar detailed investigations based on zonal and end-user meter data

13. THANK YOU