Download Using response function concepts to model groundwater

Survey
yes no Was this document useful for you?
   Thank you for your participation!

* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project

Document related concepts

Data assimilation wikipedia , lookup

SahysMod wikipedia , lookup

Transcript
The Hydrological Cycle
Overview
• A very brief history of hydrology
• Relevance to training course
– Surface water & groundwater
• a single resource
– Climate
• Variability
• Change
• Oceanic perspective
Typical representation
Not immediately obvious
Rain
E/T?
Flow > Rain?
?
Historical developments.
• Greek philosophers (500 BC)
–
–
–
–
Aware of underground water
Failed to appreciate significance of rain
Relied on reasoning without observation
Hypothesis of “underground condensation”
• Misunderstanding persisted for centuries
Historical developments..
• Leonardo da Vinci (1452-1519)
–
–
–
–
Made hydrological observations
Developed a concept of a hydrological cycle
Included evaporation and precipitation, but
Still underestimated the role of rainfall &
suggested that rivers were fed from the sea via
underground veins
Historical developments…
• Seventeeth century
– French scientists produced evidence that
rainfall could account for observed river flow
– Edmund Halley (1656-1742) measured
evaporation but still retained belief in
underground mechanism
– John Dalton (1760-1844) correctly described
the complete hydrological cycle based on his
quantitative hydrological and meteorological
observations.
The completed cycle
E/T
Rain
Flow
Lessons from the brief history
• Though the hydrological cycle now seems an
obvious and simple concept this was not always
the case
• Development of a complete and rational theory
depended on systematic observations and analysis
• Despite developments of complex computer
models, data collection, data processing and
analysis continue to provide the foundation for the
science of hydrology
Back to the present
Strengths of the cycle concept
• Describes spatial
variability of flow
and storage
• Emphasizes interconnection of
components
• Reinforces that
“Everyone lives
downstream”
Weaknesses
• Implies a smooth and
continuous process
• Suggests a selfcontained system
• Does not portray the
variability which
produces the extremes
of flood & drought
But….
• Implies a smooth and
continuous process
• Suggests a selfcontained system
• Does not portray the
variability which
produces the extremes
of flood & drought
• The process is actually
highly complex
• The hydrological cycle
is driven by climate
• Without variability
hydrologists would by
now have run out of a
job
Climate drivers
Sea-surface temperatures
Nov 1988 (La Nina)
Sept 1997 (El Nino)
El Niño-Southern Oscillation
• Two components
– Tropical ocean
– Atmosphere
• Oceanic part (El Niño) revealed by sea-surface
temperatures
• Atmospheric part (Southern Oscillation) related to
sea-level pressure
• Coupled oscillation is ENSO – a major planetary
influence on the hydrological cycle
ENSO
• Continuing efforts to observe and understand
the ocean-atmosphere system is likely to lead
to improved seasonal climate forecasting in
the future
Multivariate ENSO Index
MEI Index
2
0
100
200
300
400
Feb/Mar
1983
-2
500
Apr/May
1987
Mar/Apr
1992
Southern Oscillation Index
SOI Index
2
0
-2
-4
100
200
300
400
500
Oceanic viewpoint
Oceanic viewpoint
• Tempting to believe that Pacific
people would have been less likely
to underestimate the significance
of rainfall and evaporation
• Pacific Island country water
resources are particularly
vulnerable
– Small size
– In the ENSO “engine room”
Conclusions
• The hydrologic cycle portrays the interconnectedness of water in its various forms
• Hydrologic variability (floods & droughts) show
that the cycle does not behave in a steady and selfcontained way
• Climatic variability drives the variability we
observe in hydrology
• Observation – data collection, analysis and
interpretaion continue to be the foundation of
modern hydrology
An exercise with climate data
• Monthly rainfall from Nadi and Suva (1942
to the present)
• Use Excel to compare the seasonal
variability of rainfall on either sides of Viti
Levu
Mean monthly rainfall
400
Mean monthly rainfall
350
Suva
Nadi
300
250
200
150
100
50
0
Jan
Feb Mar
Apr May Jun
Jul
Aug Sep
Oct Nov Dec
Suva – mean (33 & 67 percentile)
500
450
400
350
300
250
200
150
100
50
0
Jan
Feb
Mar
Apr
May Jun
Jul
Aug Sep
Oct
Nov Dec
Jan-02
Jan-99
Jan-96
Jan-93
Jan-90
Jan-87
Jan-84
Jan-81
Jan-78
Jan-75
Jan-72
Jan-69
Jan-66
Jan-63
Jan-60
Jan-57
Jan-54
Jan-51
Jan-48
Jan-45
Jan-42
Suva – hyetograph
1200
1000
800
600
400
200
0