Water sector investment framework and IRR projects

Report
DWA – Water sector investment
framework and IRR projects
Structure of analysis, data and
deliverables v3
PDG 26th January 2012
DIAGRAM SHOWING OVERALL INFRASTRUCTURE FRAMEWORK
Water resource management institutions (DWA & CMAs)
‘National’ water
resource infrastructure
WSA
WUA
‘Local’ water
resource
infrastructure
‘Regional’
bulk
wastewater
infrastructure
Local bulk
wastewater
infrastructure
‘Local’ bulk
water
infrastructure
Sanitation
‘collector’
infrastructure
Water
distribution
infrastructure
Sanitation users
‘Regional’
water resource
infrastructure
‘Regional’ bulk
water
infrastructure
Potable water users
Consumers and ‘dischargers’
‘Local’ water
resource
infrastructure
Non-potable
water bulk and
distribution
infrastructure
Individual
abstractor infra
Non-potable
water users
Return flow
‘dischargers’
Structure for linking demand – bulk – WR infrastructure
Local WR
water infra
% - B loss
Distribution
(retail) water
infra - potable
% - D loss
% - B loss
Local bulk
water infra
To other DM
% - B loss
Demand
zone X (LM)
To other DM
Regional
bulk water
scheme A
Regional
bulk water
scheme B
Regional
WR scheme
C
To other DM
Regional
WR scheme
D
% - D loss
Distribution water infra non-potable
All % - R loss
To other DM
Local WR
water infra
Regional
WR scheme
E
DWA, NWRIA or TCTA
‘National’ water
resource infrastructure
DIAGRAM SHOWING OVERALL INSTITUTIONAL
FRAMEWORK
RWUs, (DWA & WSA options)
‘Regional’
water resource
infrastructure
WSA
‘Local’ water
resource
infrastructure
Local bulk
wastewater
infrastructure
‘Local’ bulk
water
infrastructure
Sanitation
‘collector’
infrastructure
Water
distribution
infrastructure
‘Regional’
bulk
wastewater
infrastructure
‘Regional’ bulk
water provider
WUA
‘Local’ water
resource
infrastructure
Non-potable
water bulk and
distribution
infrastructure
Individual
abstractor infra
Non-potable
return flow
infrastructure
Structure for current water use analysis
Estimated by LM
based on levels of
economic activity
(Gross Value Added
Estimated using
settlement level data
from DWA database
Local municipality or metro
is unit of analysis
Non-residential
Mining, power and
industry (non-potable)
Residential
Irrigation
Estimated from
ISPs and
Reconciliation
Studies
Estimated from
WMA Internal
Strategic
Perspectives (ISPs)
by quaternary
catchment
Data – existing use and existing assets
Non-potable
Potable
Regional WR
infrastructure
Local WR
infrastructure
Regional bulk
infrastructure
Local bulk
infrastructure
Distribution
infrastructure
Water use
DWA WS database;
water boards
DWA WR infrastructure database (via Pula
and P-Systems )
Calculated from unit costs
DWA WS database; water
boards
MIIF – based on unit costs
But also broken down to LM
level.
Test water use against other
sources of information
Grey area; still to be
explored; some data from
WUAs
ISPs; WARMs; Agriculture
and industrial sector info
Current demand for potable water
(a) residential
• Abstract population and household information per
settlement from DWA database.
• Abstract current service levels per settlement (DWA
database).
• Tabulate, by LM, water use per household for each service
level:
– Differentiate between urban and rural.
– Differentiate between 5 local municipality level situations (A to B4).
• Differentiate between three levels of management (poor,
moderate and good).
Current demand for potable water
(b) non-residential
• Non-residential consumers are grouped as follows:
– Institutions.
– Commercial (tertiary economic activity).
– Industrial or manufacturing (potable water only).
• Institutional demand is calculated as a percentage of
residential demand.
• Commercial demand is estimated based on the level of
economic activity in the tertiary sectors in the municipality, as
measured by Gross Value Added.
• Industrial demand: water use per unit of manufacturing GVA
is used, divided between potable water and non-potable
water.
Technical water losses (potable)
• Technical losses are applied to get the bulk water
requirement for the system. This is done based on
typical figures available from benchmarking studies,
with variations provided for:
– urban and rural.
– 5 LM sub-categories.
– 3 levels of management of the system.
Current non-potable water demand
• Water uses are divided as follows:
–
–
–
–
Irrigation.
Mining.
Power stations.
Industry.
Irrigation water use
• Best done by quaternary catchment as data is available at this level and
these catchment boundaries are small enough to allow for sufficiently
accurate alignment with LM boundaries.
• Three options have been considered:
– WARMs database (registered water use): This has been rejected due
to inaccuracy of data and the fact that it does not specifically relate to
current water use.
– Use per quaternary can be calculated from the WR2005 data set using
the WRSM2000 model. However, the cost and time required to do this
could not be justified.
– Therefore, reliance has been made, in the interim, on data from the
Internal Strategic Perspectives for each WMA. Unfortunately this
information is based on old data and requires conversion from tertiary
to quaternary catchment in some cases
Mining, power generation and non-potable
industrial demand
• These demands will be estimated from ISPs, or where
available, from reconciliation studies. As they are point
sources they can be relatively easily assigned to LMs, noting
that there are many LMs which do not have these uses at all.
Data –future use, new infrastructure and rehabilitation
Potable
Non-potable
Regional WR
infrastructure
DWA WR infrastructure planning data (in DBSA data set?)
Local WR
infrastructure
Calculated from unit costs and asset management principles
Regional bulk
infrastructure
DWA data aggregated by DBSA; checked against
national overview based on reasonable unit costs
Local bulk
infrastructure
Distribution
infrastructure
Water use
MIIF – based on economic,
demographic, LOS, water
conservation and demand
management provisions.
Grey area; still to be explored
Project based on economic
and technology factors
Forward projections- water use and water abstraction
User group
Key variables to get water use at
point of deliver to consumer
Factors influencing volume
of raw water abstracted
Municipal
residential
Population growth
Technical water losses driven
Increases in service level
by water conservation
Economic growth
measures
Demand management effectiveness
Municipal
nonresidential
Economic growth
ditto
Water use efficiency
Demand management effectiveness
Non-potable
agricultural
Expansion of irrigated area
Irrigation efficiency
Economic growth and food market
trends
ditto
Non-potable
industrial
mining &
power
Economic growth
Technology innovation
ditto
-0.2%
BMR (2007)
DBSA (2008)
ASSA (2006)
StatsSA (2011)
-0.4%
IFR (2010 with AIDS)
2040
2039
2038
2037
2036
2035
2034
2033
2032
2031
2030
2029
2028
2027
2026
2025
2024
2023
2022
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
Population growth rate
Population growth projections
1.6%
1.4%
1.2%
1.0%
0.8%
0.6%
0.4%
0.2%
0.0%
BMR (2007)
DBSA (2008)
StatsSA (2011)
BMR extrap
DBSA extrap
StatsSA extrap
2040
2039
2038
2037
2036
2035
2034
2033
2032
2031
2030
2029
2028
2027
2026
2025
2024
2023
2022
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
Household size
Household size
4.5
4.0
3.5
3.0
2.5
2.0
Economic growth
• Individual projections required for:
–
–
–
–
Tertiary sector (commercial, government etc)
Manufacturing,
Mining
Agriculture
• Growth estimates from various sources will be used.
• Likely 4.5% in 3 years time; 6% beyond that but
probably optimistic.
Access to services
• A target is set for everyone to have access to an
adequate level of service in 10 year time, noting that
the model only works at 10 and 20 year time frames.
This ‘adequate’ level of service can be adjusted and
will differ for urban and rural circumstances.
Water conservation and demand
management
• Demand management interventions will be included by:
– Residential: providing for reducing demand per household for
specified service levels.
– Non-residential consumers: providing for demand increased at less
than the rate of economic growth due to technical efficiency gains.
• Water conservation initiatives relating to the way the system
is managed between point of abstraction and point of supply
will be modelled as reduced technical losses.
Data – O&M expenditure and revenue
Potable
Non-potable
Regional WR
infrastructure
DWA WR infrastructure database; DWA scheme tariff data
Local WR
infrastructure
Calculated from unit costs
Regional bulk
infrastructure
Local bulk
infrastructure
Water board data; some from
DWA
MIIF – based on body of case
studies.
Grey area; some info from
WUA business plans?; work
from first principles if
necessary
Distribution
infrastructure
Water tariffs to
users
MIIF – driven by FBW policy
and affordability criteria.
Tariffs to be assessed using
what existing data exists
Costing methodology – local infrastructure
Infrastructure
component
Basis for calculating asset
value
Potable distribution
infrastructure (all
assumed to be ‘local’)
Calculated based on typical costs for Costed based on MIIF
such systems, taken from MIIF
unit costs using
analysis.
number of
connections and
system capacity
Difficult area as good cost data is
Costs taken from WUA
not available. Costing will be
case studies.
undertaken using unit cost
estimates from typical situations.
Local, non-potable
distribution
infrastructure.
Basis for O&M
cost
Potable local bulk
infrastructure
Local schemes will be costed based
the assumed capacity, using typical
unit costs from MIIF.
Costed based on MIIF
unit costs using
system capacity as a
basis.
Local water resource
infrastructure
They will be costed based on unit
Operating costs will be
costs from DWA sources, with
estimated from DWA
differentiation between dams,
or WUA data.
boreholes, ‘run-of-river’ sources and
springs.
Costing for regional and national
infrastructure
Potable regional bulk
schemes
Regional water resource
infrastructure
(government water
schemes).
National infrastructure
With regard to asset value an
attempt is made to build up the
value based on the infrastructure
element included in the scheme, as
defined in the DWA database. This
includes abstraction points (including
boreholes), treatment works,
pumping stations, reservoirs and
bulk pipelines. Unit costs for each
element are taken from MIIF cost
curves.
Data is available on each scheme
from the DWA WR infrastructure
database, accessible using ‘P
Systems’ software.
Data for each scheme is available
from DWA WR infra database and
from TCTA.
Operating costs will be
estimated based on
MIIF unit costs.
Also available from
DWA WR infra
database.
As for capital costs.
Linking demand zones to infrastructure
• Potable water
– DWA WS database links settlements to bulk water
schemes.
– Link from bulk water schemes to wate resources schemes
is via abstraction points. Data here is limited and
judgement will be applied, informed by ‘all towns’ and
‘reconciliation’ studies.
• Non-potable water
– Irrigation use to be linked to schemes where these exist,
using ISP reports.
– Mining, power and industrial demand will be linked to
schemes, as far as possible, if they are not served from
own sources.
Projecting future capital costs
• Capital requirements will be grouped as follows:
– New infrastructure for expanded demand.
– New infrastructure for upgrading service levels.
– Rehabilitation of existing infrastructure.
• The default projections will be made in the same way they are
made for MIIF:
– Using unit costs based on component capacity for new infrastructure.
– Using a percentage of asset value in the case of rehabilitation.
• This will provide a smooth curve for each demand zone with
the infrastructure split into distribution, bulk and WR and also
into local, regional and national components.
• Against this the actual projects which have been identified
need to be assessed.
Projecting future O&M costs
• This sill be done based on unit costs which have been
taken from local government case studies used in
MIIF, from water board cost data and from DWA cost
data. Costs will expand as services and the quantity
of water supplied grows.
Capital finance arrangements
• With the data included in the analysis, it will be possible to
divide expenditure into ‘economic’ and ‘social’ components.
This will allow for an assessment of grants and debt finance,
with some provision for the use of internal reserves in some
cases. It is highly likely that there will be a capital financing
gap and the implications of this will need to be addressed.
Revenue projections
• Revenue to cover operating expenditure will be grouped into
tariffs and subsidies.
• The model will allow average tariffs to be estimated at retail,
bulk and water abstraction level and will allow an average
household bill to be calculated.
• This, in turn, can be assessed in relation to an ‘indicative’
affordability level which will determine the extent to which
water supply arrangements are viable within a specific
subsidy framework.
Using the national analysis for individual
RWUs modelling
• The national analysis will include all demand and all
infrastructure, including the information supplied by water
boards themselves for their current supply areas.
• In the RWUs analysis a specific area of the country will be
selected for one of the proposed RWUs. This will allow
aggregate demand to be calculated for that area and identify
the infrastructure in local and regional categories required to
serve that demand.
• All this information will be abstracted into a separate RWU
model which will allow a mix of primary, secondary and
tertiary activity to be tested and will give a capital finance
program and operating budget projections for each proposed
RWU.
The model as a tool to assess division of
responsibility between institutions
• A most important feature of this analysis is it will
allow decisions to be taken on how infrastructure
responsibilities in the country will be shared
between DWA, NWRIA (if instituted), RWUs, WUAs,
LG and other service providers (typically private
sector organisations such as mines, farmers,
industries etc).
Structure of deliverables
National data in spreadsheet form by LM level data on
demand and infrastructure serving the LM area broken
down into categories (note that the accuracy of this will
not be high for this ‘Phase 2’ Framework
Data on regional schemes, current and future, in
spreadsheet form, giving scheme characteristics and
financial info.
Schemes and LM demand zone data linked to GIS so that
information can be shown spatially
National financial model giving aggregate figures for
country
Report on major findings and strategic issues
Link LM
demand zone
to schemes
Link
spreadsheet
detail to GIS
Link detail for demand
zones and schemes to
national model

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