1. ASSESSING HILLSLOPE RESPONSE MECHANISMS USING STABLE ISOTOPES C. Freese, SA Lorentz, J van Tol & PAL le Roux 1 Centre for Water Resources Research, University of KwaZulu-Natal, 3201 2 University of Fort Hare 3 Department of Soil Crop and Climate, University of the Free State, Bloemfontein, 9301. *Corresponding author (email carl.freese@gmail.com)carl.freese@gmail.com

2. Introduction Site 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 δ 18 O 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

3. Methodology

4. 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 δO 18 signal t’=integration parameter describing entry time of the tracer into the system t =calendar time δin=input δO 18 signal g(t - t’)=residence time distribution Where: g(t)=response function D p =Dispersion coefficient τ=mean response time. Where: N=number of time steps/samples α i =recharge factor P i =precipitation amount (mm) δ i =precipitation δO 18 value (‰) δ gw =ground water δO 18 value (‰)

5. Methodology

6. Results δ in

7. Results δ(t)

8. Results

9. HillslopeSiteDate Dispersion coefficient (D) Mean response time (τ) R2R2 Lower catchmen t 1LC 04February 20090.002180.81 LC 04March 20120.003120.24 2LC 08February 20090.001512- LC 08March 20120.002120.27 Upper catchmen t 3UC 01February 20090.3010- UC 01March 20120.30100.19 4UC3/4February 20090.099- UC3/4March 20120.0990.41

10. Results (ACRU 2000) R 2 = 0.68

11. ACRU Intermediate zone model

12. Results (ACRU Int)

13. R 2 = 0.71

14. Conclusions Low D p high τ – event pulse responses of the lower catchment. High D p 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

15. 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

16. 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