The Hydrological Cycle

1
The Hydrological Cycle in the Global Climate
System
Guo-Yue Niu
Prepared for Yangs Physical Climatology Class
(Ch. 5)
2

• Outline
• Global water storages and fluxes
• Tools for prediction
• Precipitation
• Evapotranspiration (ET)
• Surface water, groundwater, and runoff
• Land surface modeling
• International water programs

3
Global Water Storages
Water in biosphere Water vapor in the
atmosphere Only 0.3 fresh water is renewable
4
Global Water Cycle
Precipitation onto land Surface 9
Precipitation on ocean surface 91
Evaporation from land 60
Evaporation from ocean 100
River runoff 40 9
Land PLEL R long-term
?S PLELR short-term
Ocean EoPo R
5
Geographical Distribution
Region P (mm/y) E (mm/y) (P-E)/P (runoff
ratio) Europe 657 375 43 Asia
696 420 40 N. America 645 403 38 S.
America 1564 946 40 Australia
803 534 33 Africa 696 582 16 -
arid Antarctica 169 28 83 -
snow/ice All Land 746 480 36 Arctic
97 53 45 - SINK Atlantic
761 1133 -49 Indian
1043 1294 -24 Pacific
1293 1202 7 -
SINK All Oceans 1066
1176 -10
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Interactions between water and energy
Energy cycle

• Solar radiation drives the water cycle
• Greenhouse gases (CO2, CH4, O3 etc.) affect
  longwave radiation
• Aerosol affects solar radiation

Fluxes and Feedbacks
Water Cycle
1. Water vapor is a greenhouse gas Cloud affects
both solar and longwave Radiation 2. Snow can
reflect more solar radiation Phase changes can
damp and delay seasonal climate variations
Water supply
Water for consumption
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Water cycle has been accelerated in a warming
climate
From Dartmouth
NCDC (National Climate Data Center)
Increased T ? increased moisture ? more
convections ? increased P rates ? accelerated
water cycle
8
More dry land areas in a warming climate
Dai et al. (2004)
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Contemporary population under water stress
Population is dramatically increasing, and the
climate is warming
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Do we need better water cycle prediction?
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• Outline
• Global water storages and fluxes
• Tools for prediction
• Precipitation
• Evapotranspiration (ET)
• Surface water, groundwater, and runoff
• Land surface modeling
• International water programs

12
Global Climate Models Efficient Tools

• 1. Computer program
• Describing atmosphere at gt150,000 grid cells
• 2. Operate in two alternate stages
• Dynamics for whole global array, simultaneously
  solves Conservation of Energy
• Conservation of Momentum
• Conservation of Mass
• Ideal Gas Law
• Physics for each independent column, computes
  mass/energy divergences, surface inputs, buoyant
  exchange, e.g.,
• Radiation Transfer Boundary Layer
• Surface Processes Convection
  (cloud)
• Precipitation
• 3. Components
• Atmosphere, Ocean, Land, Sea Ice etc.

Grid spacing 33 horizontally
meters/km vertically Time step 30 minutes

1. Weather forecasting
2. Understanding climate dynamics
3. Projecting future climate change (IPCC)

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The National Center for Atmospheric Research
(NCAR) Community Land Model (CLM)
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Terrestrial Hydrological Processes
Groundwater recharge and discharge
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• Outline
• Global water storages and fluxes
• Tools for prediction
• Precipitation
• Evapotranspiration (ET)
• Surface water, groundwater, and runoff
• Land surface modeling
• International water programs

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Formation of Cloud and Precipitation

1. The environment T decreases at a lapse rate of
   6.5K/1km
2. Convergence ascending air flow
3. Water vapor
4. Condense at the surface of nuclei release heat
5. Rain droplets collide and combine to increase

Dynamical forcing and orographic lifting
Cold warm front lifting, Orographic
lifting, Radiative cooling, thermal convection
(tropical)
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Formation of Cloud and Precipitation
Cold front Cold air moves towards warm air
Warm front Warm air moves towards cold air
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Zonal Mean Precipitation
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Annual Mean Precipitation (mm/year)
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P E (mm/year)

• Sub-tropical oceans lose water (water sources)
• Tropical land areas gain water (water sinks)
• Mid-latitude and boreal coastal/maritime regions
  gain water

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P E Change in a warming climate
Lu et al. (2007), GRL
Seager et al. (2007), Science
22

• Outline
• Global water storages and fluxes
• Tools for prediction
• Precipitation
• Evapotranspiration (ET)
• Surface water, groundwater, and runoff
• Land surface modeling
• International water programs

23
Evaporation and Transpiration
Evaporation liquid water to water vapor from
water, soil, and leaf surfaces. Transpiration
liquid water to water vapor from leaf
stomata Sublimation ice to water
vapor Evapotranspiration (ET) includes
evaporation, transpiration, and sublimation.
Latent heat of vaporization 2.51x106
J/kg Latent heat of sublimation 0.33x106
2.51x106 2.84x106 J/kg
ice ? liquid ? vapor
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Measuring Evaporation Transpiration

• Local scale
• Evaporation pan potential evaporation (water
  surface)
• Lysimeter a weighting machine measuring ET
• 3. Eddy correlation system ET
• River basin scale a challenge
• Satellites GRACE (?S)
• ET P R ?S

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Formulating ET
ET fluxes ?p / r (Ohms Law) Eg e(Tg)
eatm/raw rsrf ? cp/? Etr e(Tc)
eatm/raw rs ? cp/? raw (z0,?, d) - the
aerodynamic resistance using M-O similarity
theory rs(s?,?,Tc,?e,co2) - the stomatal
resistance
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• Outline
• Global water storages and fluxes
• Tools for prediction
• Precipitation
• Evapotranspiration (ET)
• Surface water, groundwater, and runoff
• Land surface modeling
• International water programs

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The Processes to Generate Surface Runoff
Urban areaFrozen surfaceSevere storms
Dominantcontributor
zwt
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History of Formulating Runoff in Climate Models
Soil Vegetation Atmosphere Transfer Schemes
(SVATs) 1980s-1990s (BATS and SiB)
Bucket or Leaky Bucket Models 1960s-1970s (Manabe
1969)
Big Leaf
Big Bucket
150mm
100km
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Recent Developments in Modeling Runoff in GCMs
TOPMODEL concepts

• Representing topographic effects on subgrid
  distribution of soil moisture and its impacts on
  runoff generation
• (Famiglietti and Wood, 1994 Stieglitz et
  al. 1997 Koster et al. 2000 Chen and Kumar,
  2002, Niu and Yang, 2003 Niu et al., 2005)
• Representing groundwater and its impacts on
  runoff generation, soil moisture, and ET
• (Liang et al., 2003 Maxwell and Miller,
  2005 Yeh and Eltahir 2005 Niu et al., 2007 Fan
  et al., 2007)

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Relationship Between the Saturated Area and Water
Table Depth
The saturated area showing expansion during a
single rainstorm. Dunne and Leopold, 1978
zwt
fsat F (zwt, ?) Fmax (?) e0.5 f zwt
fsat
? wetness index derived from DEM
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DEM (1km) to Wetness Index (WI)
WI ln(a) ln(S)
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Surface Runoff Formulation
Lowland
upland
zm ?m
?i ?m f zm TOPMODEL (Beven and Kirkby,
1979)
The Maximum Saturated Fraction of the Grid-Cell
Fmax CDF ?i gt ?m
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Surface Runoff Formulation
A 1 x 1 grid-cell in the Amazon River basin
Both Gamma and exponential functions fit for the
lowland part (?i gt ?m) fsat Fmaxe C (?i
?m) ? fsat Fmaxe C f zwt Fmax
0.45 C 0.6
?i ?m f zwt TOPMODEL
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Surface Runoff Formulation
A 1 x 1 grid-cell in Northern Rocky Mountain
Gamma function fails, while exponential function
works. Fmax 0.30 C 0.5
fsat Fmaxe C f zwt
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Fmax derived from Hydro1k data
fsat Fmaxe C f zwt (Niu et al., 2005)

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Runoff Scheme for Climate Models
Runoff Qs Qsb
Surface Runoff Rs P Fmax e C f zwt p
precipitation zwt the depth to water table f
the runoff decay parameter that determines
recession curve Subsurface Runoff Rsb
Rsb,maxe f zwt Rsb,max the maximum subsurface
runoff, which is related to lateral Ksat of an
aquifer and local slopes (e-?) . Parameters
Two calibration parameters Rsb,max (10mm/day)
and f (1.02.0) Two topographic parameters
Fmax (0.37) and C (0.6)
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Prognostic Water Table depth A Simple
Groundwater Model (Niu et al. 2007 JGR)
Water storage in an unconfined aquifer
Recharge Rate
3.4m
Buffer Zone
Gravitational Drainage
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Basins for Model Validation
Torne/Kalix
- river basin
-small or middle watershed, research site
Rhone
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Torne/Kalix Rivers, Sweden and Finland (58,000
km2)

• 20-year (1979-1998) meteorological forcing data
  at hourly time step
• 218 grid-cells at 1/4 degree resolution

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Modeled Runoff in Comparison with Observed
Streamflow
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• Model intercomparison
• 20 models from 11 different countries (Australia,
  Canada, China, France, Germany, Japan,
  Netherlands, Russia, Sweden, U.K., U.S.A.)
• VISA Versatile Integrator of Surface and
  Atmospheric processes

From Bowling et al. (2003)
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Model Intercomparison
Nijssen et al. (2003)
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• Outline
• Global water storages and fluxes
• Tools for prediction
• Precipitation
• Evapotranspiration (ET)
• Surface water, groundwater, and runoff
• Land surface modeling
• International water programs

44
Inputs outputs

• Spatial-Scales Point, Catchment, Regional, or
  Global
• Time step 30 mins to 3 hours
• Online coupled with atmospheric models
• Offline decoupled forcing data testing model

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Global Off-Line Application (Decoupled from the
Atmospheric Model)
15,238 grid-cells over land at 1 degree spatial
resolution GSWP 2 (Global Soil Wetness
Project)13-year (1983-1995) 3-hour forcing data
(50G)
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Global distribution of annual mean temperature, oC
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Vegetation parameters

• VegClass Vegetation type
• LAI Leaf area index
• VegHeight Vegetation height
• vegFrac Vegetation cover fraction
• classFrac Fraction of each VegClass
• Albedo Snow-free albedo
• RootDepth Root depth
• Rs_min Minimum stomatal resistance

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Global distribution of vegetation Height, m
Estimated by modelers
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Global distribution of the many-year averaged
leaf area index (LAI)
The International Satellite Land-Surface
Climatology Project (ISLSCP) Initiative II data
sets
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Global distribution of the root depth, m
International Satellite Land-Surface Climatology
Project (ISLSCP) Initiative II data sets
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Soil parameter data
Soil texture (IGBP Global Soil Data Task, 2000)
Clay / Sand / Silt / Organic
Wilting point Porosity Saturated
hydraulic conductivity Saturated matric
potential Soil color index (Zeng et al. 2002)
satellite data Visible albedo of soil
Near-infrared albedo
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GRDC (Global Runoff Data Center) Estimated Runoff
http//www.grdc.sr.unh.edu/html/station.html
663 gauging stations with catchment area gt
25,000km2
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Global distribution annual runoff, mm/year
GRDC 295.65 mm/year
Model 328.50 mm/year 42 of P
Our model produces 10 more than GRDC 1) GRDC
did not include smaller basins 2) vegetation
parameters used in this study need to be refined
3) The precipitation used in this study is larger.
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Global River Discharge (kg/year)
Our estimation
GRDC
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• Outline
• Global water storages and fluxes
• Tools for prediction
• Precipitation
• Evapotranspiration (ET)
• Surface water, groundwater, and runoff
• Land surface modeling
• International water programs

56
Agencies Involved in the Water Cycle Program
UNDERSTANDING NSF, NASA, DOE
USDA USGS APPLICATIONS EPA BoR USACE
PREDICTION NOAA, DOE, NASA
OBSERVATIONS NASA, NOAA (DOE, USGS, USDA)
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Water Research Plans

• What are the causes of water cycle variations?
• Are variations in the global and regional water
  cycle predictable?
• How are water and nutrient cycles linked?

Interdisciplinary Research

• Interdisciplinary Linkages
• Aerosols link to precipitation development,
  interaction with energy/radiation cycles
• Carbon link to transpiration and radiation
  absorption
• Weather and Climate water and energy are at the
  heart of weather and climate physics
• Modeling, Assimilation, and Computing essential
  tools for integration and prediction
• Technology development of new observation
  technology
• Applications consequences of change delivered
  through water energy cycle

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Some Examples of Field Programs

• Cabauw
• Type Short Grass
• Cover 16.6
• Precip 776 mm
• Data Jan 87 - Dec 87

• BOREAS (NSA-OJP)
• Type Evergreen Needleleaf
• Cover 6.5
• Precip 242 mm
• Data Jan 94 - Dec 96

• ARM-CART (E13)
• Type Mixed Crop / Farm Land
• Cover 8.1
• Precip 600 mm
• Data Apr 95 - Aug 95

• Tucson
• Type Semi-Desert
• Cover 9.2
• Precip 275 mm
• Data May 93 - Jun 94

• ABRACOS (Reserva Jaru)
• Type Evergreen Broadleaf
• Cover 9.7
• Precip 1600 mm
• Data May 92 - Dec 93

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Terrestrial Water Storage Change
Use GRACE (2002- now) to validate and calibrate
model
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TWS Change
Use model to retrieve historical changes
The Yellow River
The Mississippi
Prediction ?
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• Summary
• Global water storages and fluxes
• Tools for prediction
• Precipitation
• Evapotranspiration (ET)
• Surface water, groundwater, and runoff
• Land surface modeling
• International water programs

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Regional Environmental Model System An
Integrated Framework for modeling and Assessment
Remotely Sensing and GIS
Population growth Agricultural Irrigation
Industrial water use Land use/land cover Climate
change
Global Climate Change and Variability
Air Quality Models
Coupled Ocean-Atmosphere Models
Regional Models
Land Models
Hydrologic/Routing Models
In Situ Data
Water Resources
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• Thank you!
• for your attention and patience