ASSESSING HILLSLOPE RESPONSE MECHANISMS USING STABLE ISOTOPES

C. Freese, SA Lorentz, J van Tol & PAL le Roux

1Centre for Water Resources Research, University of KwaZulu-Natal, 32012University of Fort Hare

3Department of Soil Crop and Climate, University of the Free State, Bloemfontein, 9301.*Corresponding author (email carl.freese@gmail.com)

IntroductionSite specific nature of previous studies makes transfer to ungauged sites difficult due to:

• 1: Spatial and temporal complexity• 2: Current lack of tools

Residence time distribution equations • generalized descriptors of catchment hydrology• Spatially transferrable• Potentially low data intensity

Develop generalized descriptors of subsurface for use in a catchment scale model• δ18O isotope data• two-step algorithm ( derive Dp and τ)• parameterize hillslope sub catchments in the ACRU Intermediate zone model• comparative ACRU simulations to assess the ability of Dp and τ

Methodology

Methodology

•

Convolution integral relates the output isotope time series to the input isotope time series• simulating the probability distribution for a conservative tracer molecules

Where:δ(t) = output δO18 signalt’ = integration parameter describing entry time of the tracer into the systemt = calendar timeδin = input δO18 signalg(t - t’) = residence time distribution

Where:g(t) = response functionDp = Dispersion coefficientτ = mean response time.

Where:N = number of time steps/samplesαi = recharge factorPi = precipitation amount (mm)δi = precipitation δO18 value (‰)δgw = ground water δO18 value (‰)

Methodology

Results δin

04-Oct-09 13-Nov-09 23-Dec-09 01-Feb-10 13-Mar-10-10

-8

-6

-4

-2

0

2

4

input rfl hillslope 1 hillslope 2 hillslope 3 hillslope 4

δO18

Results δ(t)

01-Feb-09 08-Feb-09 15-Feb-09 22-Feb-09 01-Mar-09 08-Mar-09-6

-5

-4

-3

-2

-1

0

1

2

3simulated

lc04 seep

4L

δO18

1-Feb-10 16-Feb-10 3-Mar-10 18-Mar-10 2-Apr-10-6

-5

-4

-3

-2

-1

0

1

2

3simulatedlc04 seep4L

δO18

Results

1-Feb-10 16-Feb-10 3-Mar-10 18-Mar-10 2-Apr-10-6

-5

-4

-3

-2

-1

0

1

2

3simulated

uc 2A

uc 2B

uc 01δO

18

1-Feb-10 16-Feb-10 3-Mar-10 18-Mar-10 2-Apr-10-6

-5

-4

-3

-2

-1

0

1

2

3

simulated

uc 3/4

δO18

Results

Hillslope Site Date Dispersion coefficient (D)

Mean response time (τ)

R2

Lower catchmen

t

1 LC 04 February 2009 0.002 18 0.81

LC 04 March 2012 0.003 12 0.24

2 LC 08 February 2009 0.0015 12 -

LC 08 March 2012 0.002 12 0.27

Upper catchmen

t

3 UC 01 February 2009 0.30 10 -

UC 01 March 2012 0.30 10 0.19

4 UC3/4 February 2009 0.09 9 -

UC3/4 March 2012 0.09 9 0.41

Results (ACRU 2000)

2000/01/0

1

2000/01/1

5

2000/01/2

9

2000/02/1

2

2000/02/2

6

2000/03/1

1

2000/03/2

5

2000/04/0

8

2000/04/2

2

2000/05/0

6

2000/05/2

0

2000/06/0

3

2000/06/1

7

2000/07/0

10

5

10

15

20

25

30 0

10

20

30

40

50

60

70

rainfall simulated observed

Dis

cha

rge

(m

m)

Ra

infa

ll (m

m)

R2= 0.68

ACRU Intermediate zone model

Results (ACRU Int)

Results (ACRU Int)

2000/01/0

1

2000/01/1

5

2000/01/2

9

2000/02/1

2

2000/02/2

6

2000/03/1

1

2000/03/2

5

2000/04/0

8

2000/04/2

2

2000/05/0

6

2000/05/2

0

2000/06/0

3

2000/06/1

7

2000/07/0

10

5

10

15

20

25

30 0

10

20

30

40

50

60

70

rainfall simulated observed

Dis

cha

rge

(m

m)

Ra

infa

ll (m

m)

R2= 0.71

Conclusions

• Low Dp high τ – event pulse responses of the lower catchment.

• High Dp low τ – sustained drainage of upper catchment.

• ACRU Int improvement on baseline simulations.– Peak flows (ACRU 2000 & Int)– Low flows (ACRU Int)– Improved simulation of soil water discharge to stream

Proposal• Initial field setup/ maintainence

– December 2014-February 2015

• Improved data sets– Analyse for a range of tracers (EC, silica, N etc.)– Temporal sampling density (tracers)

• Rainfall• Streamflow• Soil water

• Monitor Mooi hillslopes – Hillslopes across different geologies– Identify similar/typical hillslopes

Proposal

• Further ACRU Int testing– Refine input data set (tracers)– Increase detail of Weatherley simulations (more landsegments)– Define typical hillslopes within certain parts of the Mooi– Parameterise & model Mooi hillslopes

• Further insight into transferability of Dp and τ – Capability to represent hydrological process across scales– Linked to existing classification systems