Watershed Functions and Runoff Processes

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Watershed Functions and Runoff Processes

• Tom Dunne
• Winter 2008

2
A word on the use of analytical and predictive
models in Watershed Analysis
3
Use and interpretation of analytical models of
watershed behavior.
A
Conceptual model of processes as affected by
landscape characteristics. Based on observations
and physical reasoning.
4
Use and interpretation of analytical models of
watershed behavior.
A
B
Conceptual model of processes as affected by
landscape characteristics. Based on observations
and physical reasoning.
Analytical theory of processes, their controls
and inter-relations, expressed mathematically. Too
complex to parameterize for predictions/explanati
ons.
5
Use and interpretation of analytical models of
watershed behavior.
A
B
Conceptual model of processes as affected by
landscape characteristics. Based on observations
and physical reasoning.
Analytical theory of processes, their controls
and inter-relations, expressed mathematically. Too
complex to parameterize for predictions/explanati
ons.
Parameterize? Whazzat????
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Limitations on what can these models tell us

• They express not only our best understanding but
  also the uncertainties
• (i) in our understanding of processes
• (ii) in our knowledge of critical values (e.g.
  albedo of clouds)
• (iii) in our capacity for computation.
• E.g.
• They require simplifications of system
  descriptions (spatial resolution currently 2-5
  degrees 6-20 vertical levels time steps 30
  min.)
• Necessary to parameterize some processes (e.g.
  cloud formation and effects on radiation balance
  ET runoff).
• Parameterize means to represent processes that
  are complex on small time and spatial scales by
  means of simple equations containing coefficients
  (parameters) that express average behavior over
  some time period and spatial scale. e.g. Kcan
  R1 aP1 Q Q0e-kt

ESM 203 Lecture 19
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Use and interpretation of analytical models of
watershed behavior.
A
B
C
Conceptual model of processes as affected by
landscape characteristics. Based on observations
and physical reasoning.
Analytical theory of processes, their controls
and inter-relations, expressed mathematically. Too
complex to parameterize for predictions/explanati
ons.
Computational model of effects of processes and
controls. Used for planning, design or
decision-making. Heavily parameterized to the
point where representation of observable physical
relationships is unclear, and cause-effect
subject to a range of interpretation.
8
Use and interpretation of analytical models of
watershed behavior.How should we insert values
in (or interpret results of) C in the light of
what we understand in A and express in B?
A
B
C
Conceptual model of processes as affected by
landscape characteristics. Based on observations
and physical reasoning.
Analytical theory of processes, their controls
and inter-relations, expressed mathematically. Too
complex to parameterize for predictions/explanati
ons.
Computational model of effects of processes and
controls. Used for design or decision-making. Heav
ily parameterized to the point where
representation of observable physical
relationships is unclear, and cause-effect
subject to a range of interpretation.
9
Use and interpretation of analytical models of
watershed behavior. How should we insert values
in (or interpret results of) C in the light of
what we understand in A and express in B?
A
B
C
Conceptual model of processes as affected by
landscape characteristics. Based on observations
and physical reasoning.
Analytical theory of processes, their controls
and inter-relations, expressed mathematically. Too
complex to parameterize for predictions/explanati
ons.
Computational model of effects of processes and
controls. Used for design or decision-making. Heav
ily parameterized to the point where
representation of observable physical
relationships is unclear, and cause-effect
subject to a range of interpretation.
Well, you see, judge, heres how the result from
this calculation relates to what is going on here
in the watershed when X changes to Y.
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Watershed functions are driven by runoff
processes, which vary geographicallyIn this
context runoff means the processes by which
water travels to a stream channel
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Watershed functions

• Collection of water and transported materials
• Storage (attenuates response to temporally
  discrete inputs). Floodplain storage of water,
  sediment, pollutants
• Conveyance (attenuates response to spatially
  discrete inputs)
• Discharge 
• Transport
• Assembly of sediments into landforms that are
  exploited as habitat for plants or animals

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Watershed functions

• Runoff processes supply water and transported
  materials into channels
• The channels and valley floors temporarily store
  these substances as they move downvalley
• This channel and valley-floor storage acts like a
  reservoir to dampen the response making the
  waves or pulses of input later and more diffuse

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Watershed functions at differing basin sizes

• As the size of the watershed increases, the
  storage and damping of the hillslope response by
  the channel/valley floor increases
• In small watersheds, the hillslope processes
  dominate the hydrological response
• Therefore the condition of the watershed surface
  controls hydrological response
• Watershed surface affected by natural and
  anthropogenic processes (i.e. land management)
• In large watersheds, hydrological response is
  dominated by valley-floor storage processes

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TerminologyStreamflow (runoff) storm
runoff baseflowor quickflow delayed
flow(from ESM 203)
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Runoff in the Water Balance ESM 203
Rnet
E
Advection of sensible (H) and latent heat (L)
P

• ?volume fraction of water
• V(t) volume of groundwater storage resulting
  from balance between drainage from soil and
  drainage to rivers
• Ddepth of root zone

Quickflow R
Soil SM(t)D?(t)
Recharge when SM(t)gtSMmax
Ground water V(t)
Delayed flow R
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Vegetation change and water yield

• Thicker, taller, darker vegetation favors canopy
  interception (of rain or snow) and
  evapotranspiration ESM 203 notes
• R P E
• Inadvertent manipulation through clearing, fire,
  or reforestation diminishes E and therefore
  increases R
• Planned rotational clearing for water yield
  management

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Vegetation change and water yield results of
paired watershed experiments
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Tree removal and increases in water yield (?R) in
a Douglas fir forest in Oregon results of paired
watershed experiments Harr, 1983

• ?Rt (mm) 308 0.09Pt (mm) 18t (yr)
• E.g. for Pt annual precipitation of 3000 mm/yr
• 560 mm extra after year 1
• 398 after 10 year 10
• 218 mm after year 20

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Vegetation change and water yield in Eastern
hardwood forests results of paired watershed
experiments Douglas, 1983
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Runoff pathways determine the partitioning of
total R into overland and subsurface flow . and
that makes all the difference to the functioning
of a watershed !
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There is a maximum rate at which a land surface
in a given condition can accept water.

• This maximum rate is called the infiltration
  capacity.
• Infiltration capacity is the maximum rate at
  which a soil can absorb rainfall
• It is the key control on partitioning of water
  into surface and subsurface flow paths
• Infiltration capacity declines exponentially
  through a rainstorm

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Infiltration capacity (f) declines exponentially
through a rainstorm as time or soil moisture
content of soil surface (?) increase
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Horton overland flow is generated when rainfall
intensity exceeds the infiltration capacity of
the soil
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Analytical theory of infiltration rate (f)
Green-Ampt equation

• Darcys Law ESM 203 notes

H elevation head pressure head Infiltration
is driven by gradient of elevation (which is
constant) and gradient of pressure (? p/ ? z)
between the surface and the wetting front (which
is decreasing as wetting front penetrates soil
and therefore ?z increases)
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Green-Ampt derivation
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Green-Ampt derivation
Rainfall intensity, I

?z(t) depth of wetting front at time t F(t)
accumulated amount of infiltration up to time
t Ts porosity (saturated water content) of
soil Ti initial water content of soil
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Green-Ampt derivation
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The infiltration capacity decreases through time
as the wetting front penetrates the soil,
decreasing the pressure gradient between the
surface and the wetting front
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Controls on infiltration capacity(mainly
effective hydraulic conductivity Ksat)

• Population of pore sizes (micro to macro) and
  therefore texture, structure, biotic activity,
  organic content, etc. Blocking of pores by frost
• Vegetation cover/litter/soil macrofauna/macropores
  . Root zone collapse (burning trampling
  traffic)

• Surface crusting (especially in silty soils).
  Lemon groves in Goleta
  Nabatean/Israeli runoff farming by removing
  stones.
• Asphalt
• Antecedent moisture of the soil (previous
  rainfall pattern) affects rate of convergence of
  f on K sat.

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Horton overland flow
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Horton overland flow
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Augmentation of irregular sheet of overland flow
r
f
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Sprinkling infiltrometer, Sedgwick
ReserveInfiltration capacity rainfall
intensity runoff rate
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Sprinkling infiltrometer in Western Amazon
rainforest infiltration capacity 180 mm/hr
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Sprinkling infiltrometer in 10-yr old pasture,
Central Amazonia
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Infiltration capacity of soil (mm/hr)
Forest Pasture

• Central Amazon
• (Soils on Tertiary sedimentary rocks)
• W. Amazon, Rondonia
• (Soils on Precambrian rocks)

• 143 98
• 156 105
• 181 30
• 146 41
• 13
• 25

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Measurement or estimation of infiltration
capacity

• Monitoring of runoff and rainfall rates on plots
• Cylinder infiltrometer
• Sprinkling infiltrometer
• Visual observations of water accumulation under
  measured rainfall intensity

• Soil-based estimates from handbooks and soil
  survey reports, later calibrated against computed
  and measured runoff.
• Storm-averaged value or ? index (Total storm
  rainfall minus total storm runoff divided by
  duration of rainfall for small basins)

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Storm-averaged inf. Cap. (? index) is the volume
(depth) of rainfall the volume (depth) of
runoff divided by duration of shaded area
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Low-infiltration landscape sparse vegetation,
clay-rich soil
Horton overland flow environments
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Sparsely vegetated, low-infiltration landscape
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Infiltration capacity lowered from gt100 mm/hr
(forest floor) to 1 mm/hr by eruption of silty
volcanic ash, Mt St Helens 1980
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Clearing of olive tree woodland and heavy
grazing, following population concentration in
civil war in N. Kenya reduces infiltration
capacity and hillslope roughness
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Reducing vegetation cover reduces infiltration
capacity and hillslope roughness
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Bush clearing for agriculture, E. Kenya
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Toxic, unvegetated mine spoils have low
infiltration capacities
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Logging road, W. Washington Olympic Mts.
infiltration capacity 1 mm/hr
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Construction sites have low infiltration
capacities, and short, steep slopes
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Impervious, urban surfaces replacing forested
soils, Rio
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Changes to infiltration capacity, surface
roughness and slope length increase and
accelerate overland flow in urban areas
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Impervious cover is inversely proportional to lot
size
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Runoff pathways
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Steep, shallow, forested soil over volcanic
rocks, Japanese Alps generates shallow subsurface
flow (throughflow/interflow)
Island arc environment in wet climate
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Buildup of saturation and pore pressure in Oregon
Coast Range
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Deep, permeable volcanic ash, Aberdare Mts.,
eastern flank of Rift Valley, Kenya
Volcanic deposits on margins of a graben at humid
divergent plate margin
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Deeply permeable, fractured sandstone, Mesa
Verde, Colorado
Sedimentary platform on a craton in subhumid
environment
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Groundwater emerging from fractures in bedrock
produce channels by seepage erosion during
snowmelt, Vermont
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Emerging groundwater in late melt season, Vermont
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Ground water emerging in deep gullies in a
landscape with deep, permeable soils, S.E. Brazil
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Interflow
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Interflow, exfiltration and direct precipitation
generate saturation overland flow on parts of
landscapes
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Saturation overland flow, Vermont
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Seasonal variation of saturation overland flow on
low-permeability glacial till, Vermont
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Saturation overland flow from spring snowmelt,
near Wenatchee, E. Washington
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Macropore flowSubsurface flow through fractures
in swelling-clay soil, central California coast
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Vertical fissures in soil on volcanic ash, N.
Tanzania
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Gully produced by tunnel erosion after removal of
woodland and onset of heavy grazing, N. Tanzania
(approx 1960-1982)
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Schematic summary of controls on runoff pathways
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Significance of runoff processes (pathways) for
flooding, erosion and particulate transport

• For understanding flood runoff (see later on
  modeling of watershed runoff).
• For understanding erosion and contaminant sources
  and transport Therefore need for a spatially
  registered, field-based appreciation.

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Significance of runoff processes for erosion and
transport
Broad Run, Pa