inflow forecasting for hydro catchments...inflow forecasting for hydro catchments ross woods and...
TRANSCRIPT
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Inflow Forecasting forHydro Catchments
Ross Woods and Alistair McKerchar
NIWA Christchurch
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Inflows
• Water flowing into hydro storages
• Usually measured by monitoring thelevels and outflows from hydro storages
Inflow = Outflow + (Rate of increase of storage)
• Variable at many timescales, differentfrom place to place
• Why make forecasts? How?
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Nearly 80 years of levels for Lake Wakatipu
Data courtesy Contact Energy Ltd
309
310
312
313
level m
Jan-1924 Jan-27 Jan-30 Jan-33 Jan-36 Jan-39 Jan-42 Jan-45 Jan-48 Jan-51
309
310
312
313
level m
Jan-57 Jan-60 Jan-63 Jan-66 Jan-69 Jan-72 Jan-75 Jan-78 Jan-81 Jan-84
309
310
312
313
level m
Jan-87 Jan-90 Jan-93 Jan-96 Jan-99 Jan-02site 89135 L Wakatipu at Unadjusted Level
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Main hydropower storagesMain hydropower storagesLake Storage Capacities
0
400
800
1200
1600
2000
Tau
po
Rot
oaira
Moa
wha
ngo
Wai
kare
moa
na
Cob
b
Col
erid
ge
Tek
apo
Puk
aki
Oha
u
Ben
mor
e
Haw
ea
Wan
aka
Wak
atip
u
Te
Ana
u
Man
apou
ri
Mah
iner
angi
Lake
Cap
acit
y (G
Wh
)
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Forecasting for Three Timescales
• Weather systems: 0-3 days from now
• Seasonal forecasting: 1 week to severalmonths
• Interannual variability: Decadal-scale
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Timescale: 0-3 days
• Why? How much electricity can we make?Flushing flows; High flow management
• What we need to know– What water is already in the catchment (river flows,
soil water, groundwater)?– How will weather system affect the rainfall, snowfall
and evaporative demand?
• With this information, we can use a model tocalculate snow melt, runoff from land into rivers,flow along rivers to lakes
• This can be done in more or less detail …
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TOPNET - 1• Snowpack, canopy and root-zone
submodels over a shallow water table
Sat. zone
Rain, Evap
Subsurfaceflow
Recharge
ThroughfallSurfaceflow Sub-basin
outflow RiverNetwork
Othersub-basins:each one is
unique
Root zone
Canopy
Topo. controls
Snowpack
Melt
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TOPNET - 2
• Sub-basin outflows are connected to rivernetwork routing
• Model gives results for every sub-basin andevery river reach, every hour
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Balclutha (20,500 km2)Pomahaka R.
L. Roxburgh
L. L. HaweaHaweaL. Wanaka
L. WakatipuShotover Shotover R.R.
Alexandra
The Clutha River Catchment
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The Catchment Model
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RAMS Rainfall Forecasts overClutha Catchment
Balclutha
Alexandra
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Real Time Forecasts for Alexandra - Nov. 1999using RAMS forecast on 20 km grid
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200
400
600
800
1000
1200
10-Nov-99 12-Nov-99 14-Nov-99 16-Nov-99 18-Nov-99 20-Nov-99
Ale
xand
ra In
flow
(um
/h)
0
200
400
600
800
1000
1200
10-Nov-99 12-Nov-99 14-Nov-99 16-Nov-99 18-Nov-99 20-Nov-99
Ale
xand
ra In
flow
(um
/h)
Diamonds mark forecast time at 0800 each day
0
200
400
600
800
1000
1200
10-Nov-99 12-Nov-99 14-Nov-99 16-Nov-99 18-Nov-99 20-Nov-99
Ale
xand
ra In
flow
(um
/h)
Diamonds mark forecast time at 0800 each day
0
200
400
600
800
1000
1200
10-Nov-99 12-Nov-99 14-Nov-99 16-Nov-99 18-Nov-99 20-Nov-99
Ale
xand
ra In
flow
(um
/h)
Diamonds mark forecast time at 0800 each day
0
200
400
600
800
1000
1200
10-Nov-99 12-Nov-99 14-Nov-99 16-Nov-99 18-Nov-99 20-Nov-99
Ale
xand
ra In
flow
(um
/h)
Diamonds mark forecast time at 0800 each day
0
200
400
600
800
1000
1200
10-Nov-99 12-Nov-99 14-Nov-99 16-Nov-99 18-Nov-99 20-Nov-99
Ale
xand
ra In
flow
(um
/h)
Diamonds mark forecast time at 0800 each day
0
200
400
600
800
1000
1200
10-Nov-99 12-Nov-99 14-Nov-99 16-Nov-99 18-Nov-99 20-Nov-99
Ale
xand
ra In
flow
(um
/h)
Diamonds mark forecast time at 0800 each day
Successfulflood forecast
on a largeevent in a
slowly-respondingcatchment
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Next Generation of Forecasts
• Operational Forecasting for catchments,with linked weather and hydrology models
• Operational Forecasting for Regions, withlinked weather and hydrology models
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Timescale: 1 week – 6 months
• Why? Is there a hydro drought coming? Whendo we need pre-empt with thermal?
• What we need to know for inflow forecasts:– How much rainfall/snowfall?
– What temperatures?
• No deterministic answers: uncertainty is central.Aim to reduce the uncertainty
• This can be done in more or less detail …
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MaxMin
75%25%
Median
Hermitage monthly rainfall (1931-1996)
Monthly rainfall (m
m)
0
500
1000
1500
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
DEC
MaxMin
75%25%
Median
Lake Wanaka monthly inflows 1931-1995
Monthly inflow
(m3/s)
0
200
400
600
800
JAN
FEB
MAR
APR
MAY
JUNE
JULY
AUG
SEPT
OCT
NOV
DEC
Hermitage monthlyHermitage monthlyrainfallrainfall
Lake WanakaLake Wanakamonthly meanmonthly meaninflowsinflows
SeasonalPatterns
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The Past as a guide to the Future1. It is common to forecast the performance of energy systems
over the next season by starting from the current lakestorage, and then using weekly inflow sequences fromeach of the last 70 years of inflows. This lets us sample thevariability of inflows at this time of year.
BUT, the unspoken assumption is that each of the last 70years is equally likely in the next 3 months. Once we are ina strong El Nino or La Nina, some years are much morelikely than others.
2. Some energy system models use auto-regressive models toforecast streamflows: on average these might be useful, butextreme seasons have a different persistence structure
3. Use “ENSO”-streamflow or rainfall-streamflow forecasting
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Lake Taupo Natural Spring Inflows 1935-1992
Spring SOI
Sp
ring
inflo
w (m
3/s
)
50
100
150
200
250
-30 -20 -10 0 10 20 30
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Non-Outlier MaxNon-Outlier Min
75%25%
Median
Lake Taupo natural spring inflows 1935-1992
Spring SOI
Sp
ring
inflo
w (m
3/s
)
50
100
150
200
250
< -5 (-5,5] > 5
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Clutha lakes summer inflow vs spring SOI
Spring SOI
Su
mm
er in
flow
(m3
/s)
0
200
400
600
800
1000
1200
-30 -20 -10 0 10 20 30
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MaxMin
75%25%
Median
Clutha lake summer inflows vs spring SOI
Spring SOI
Inflo
w (m
3/s
)
0
200
400
600
800
1000
1200
5
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NIWA National Climate Centre andNational Centre for Water Resources• Forecasts each month of the streamflows for the
coming 3 months www.niwa.co.nz/ncc• Based on: climate forecasts, current status of river
flow and soil moisture, expert knowledge andstatistical analysis of past data.
• Forecasts developed as the probability of “Abovenormal”, “Normal” and “Below normal” flows. Inthe long run each of these occurs 33% of the time.So random guesses have 33% hit rate. We havehad 40-45% hit rate over the last 3 years
• www.niwa.co.nz/ncwr - water quality, quantity,lakes, groundwater, …
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Next Steps
• Develop new methods for forecasting climate1. Statistical weather generators2. Regional climate models
• Both of these are ways to generate manysequences of daily rain and temperature for thecoming season (conditioned on the current ocean-atmosphere status – ENSO etc)
• Either way, we need to convert these climateforecasts to inflows: can use the same model as forthe 0-3 day forecasting.
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Topnet• Example of Regional Modelling in Northland
RiverNetwork
Sat. zone
Rain, Evap
Subsurfaceflow
Recharge
ThroughfallSurfaceflow Sub-basin
outflow
Othersub-basins:each one is
unique
Root zone
Canopy
Topo. controls
Snowpack
Melt
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Timescale: Interannual• Why? Investment in new generation; Assessing the
expected performance of existing system• Fact: Inflows can be very different from one decade
to another• Up to 15% changes in South Island• Inflow differences caused mainly by rainfall
variability. This is climate variability (as opposed toclimate change: e.g. rise in temperature & rain inwest and south of South Island by 2050)
• Rainfall differences are caused by slow changes inocean-atmosphere circulation, called InterdecadalPacific Oscillation (IPO, PDO)
• 1945-1977, 1978-1999?, 1999?-
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South Island West Coast Rainfall
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Clutha River at Balclutha 1947/48 to 1998/99Clutha River at Balclutha 1947/48 to 1998/99(data courtesy Contact Energy Ltd)(data courtesy Contact Energy Ltd)
300
500
700
900
1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000
An
nu
al m
ean
flo
w (
m3 /
s)
Mean = 536 m 3/s
Mean = 612 m 3/s
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Lake Te Anau inflow, 1931/32 to 2001/02Lake Te Anau inflow, 1931/32 to 2001/02(data courtesy FRST, Meridian Energy Ltd & The Market Place)
100
200
300
400
500
Jan-30 Jan-40 Jan-50 Jan-60 Jan-70 Jan-80 Jan-90 Jan-00
An
nu
al
me
an
in
flo
w (
m3/s
) 1977/78-1998/99
Mean =305 m3/s
1946/47-1976/77
Mean = 269 m3/s
1931/32-1945/46
Mean = 277 m3/s
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Summary
• 0-3 days: weather system forecasting and a modelof catchment processes
• 1 week – 6 months: Effects such as ENSO can shiftthe distribution of inflows far from the “typical”distribution
• Interdecadal: Differences between decades of order15% - be careful which years of data you use!
• For these inflow forecasts to be useful, we needbetter links with energy system modellers, esp foradvice on how best to communicate inflowforecasts