Week 9 Flashcards

1
Q

qr =

A

rainfall

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2
Q

qin =

A

canopy interception

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3
Q

Ea =

A

evapotranspiration

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4
Q

qro =

A

runoff

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5
Q

qi =

A

infiltration

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6
Q

qd =

A

drainage

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7
Q

qvp =

A

groundwater recharge

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8
Q

Soil water balance IGNORES

A

Snow

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9
Q

d(H)/dt =

A

qr - qin - qro - qd - Ea

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10
Q

(H) =

A

depth of water stored in soil

Found by integration of theta (moisture content) with respect to elevation above soil layer (z) between 0-H

H = thickness of soil layer

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11
Q

Infiltration =

A

flux of water passing into soil

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12
Q

Infiltration capacity =

A

maximum flux that can pass into soil at given time

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13
Q

Runoff =

A

excess rainfall that can’t infiltrate

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14
Q

Infiltration rate (y) vs time (x) progression

A
  • add water at constant rate
  • initially all infiltrates
  • ponding
  • decrease infiltration as near-surface pore space used
  • eventually steady state related to soil permeability
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15
Q

Horton’s empirical curve

A

i(t) = ic + (io-ic)exp(-kt)

Shows that following ponding, infiltration capacity declines exponentially with time

i = CURRENT infiltration capacity
ic = FINAL
io = INITIAL
k = decay rate
t = time after infiltration event started
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16
Q

How do we find cumulative infiltration? What does this allow us to find?

A
  1. Measure with an infiltrometer diagram
    - diameter = ~30cm
    - maintain near zero pressure head
    - measure supply rate
    - measure amount of runoff
    - difference = infiltration
  2. F(t) = integration of i(t)dt

THEREFORE CAN FIT 2 TO 1 DATA TO FIND PARAMETERS FROM HORTON’S EQUATION

17
Q

Units of infiltration rate

18
Q

Rainfall>infiltration capacity…

19
Q

If PE = Ea…

Is this the case?

A

Then discharge would = rainfall - PE

BUT PE > Ea

20
Q

Field capacity

A

S = Smax

= amount held after XS drained and rate of movement materially decreased

21
Q

Permanent wilting point

A

S = 0

= state of soil water when plants wilt and don’t recover

22
Q

Soil moisture deficit

A

Smax-S

= extent soil drier than field capacity

23
Q

dS/dt =

A

qi - qd - Ea

24
Q

qd =

A

0 ; S=Smax

qi-Ea ; S>Smax

  • b/c S is higher than the straw, any excess water will just drain
  • dS/dt = 0
25
Ea =
0 ; S=<0 Ep ; S >0
26
qi =
qr - qin - qro
27
Ep =
potential evapotranspiration
28
Using the finite difference method to find S(n+1) =
1. dS/dt \n = (S(n+1) - S(n)) / /\t 2. dS/dt \n = q(i,n) - q(d,n) - E(a,n) S(n+1) = S(n) + /\t(q(i,n) - q(d,n) - E(a,n)) = if we know storage in a bucket at time n we can look into future and predict and therefore qd and Ea too!!!
29
S =
Water level in bucket
30
How to constrain 0 < S < Smax
1. Calculate auxiliary variable F = Sn + /\t(q(i,n) - E(p,n)) i. e. F = everything but qd, and E(a,n)=E(p,n) - if 0 < S < Smax
31
Why do we need to constrain 0 < S < Smax
-ve values not physically possible | Can't go over Smax due to 'straw'/tube
32
Constraining 0 < S < Smax; Sn+1
0 ; F=<0 F ; 0 < F<= Smax Smax ; F>Smax
33
Constraining 0 < S < Smax; q(d,n)
0 ; F=Smax
34
Constraining 0 < S < Smax; E(a,n)
q(i,n) + Sn//\t ; Fs =<0 E(p,n) ; F>0
35
Bob Moore's Probability Distributed Model (PDM) CONCEPT
``` A = area As = waterlogged area c = spatially random variable, storage capacity ``` If largest value of c within waterlogged area of C and F(C) is the probability of c not exceeding C in the catchment, then As=AF(C) qro= F(C)(qr-qin) Local water storage level within waterlogged areas = c Outside = C ``` S = $C/0 (1-F(c))dc F(c) = 1-exp(-c/Smax) ``` qro = (S/Smax)(qr-qin) Allows you to account for extra drainage
36
PDM qin =
canopy interception rate
37
Implementation of the PDM
Difficult to distinguish qro/qd at catchment scale --> lumped as qd Same for canopy interception/evapotranspiration --> lumped as Ea qi therefore = qr dS/dt = qi - qro - Ea qd = (S/Smax)qi ; S=Max Ea = 0 ; S=<0 Ep ; S>0
38
PDM with the finite difference method
1. Auxiliary variable G = (Sn/Smax)qi,n F = Sn +/\t(qi,n - Ep,n - G) Because 0 < S < Smax S(n+1) = 0 ; F=<0 F ; 0 < F =Smax q(d,n) G ; F=Smaç E(a,n) q(i,n)+Sn/\t-G ; F=<0 E(p,n) ; F>0