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

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

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

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

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

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)

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

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

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

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