– SUPPLEMENTARY MATERIAL

.

Figure A7: Results of the biogeochemical simulations shown for the anaerobic sulfide oxidation of the micro-topography scenario with the mean length 0.5 m. PHREEQC simulations were performed along the flow paths shown in A. Results were interpolated into the 2D cross sections. B shows the age distribution in years of subsurface flow derived from backward particle tracking. Anaerobic sulfide oxidation rates in mol/Ls are shown in C. Sulfide concentrations, iron(III) and iron(II) concentrations in mol/L are shown in D-F respectively.

STUDY 2 – SUPPLEMENTARY MATERIAL

Figure A8: Top view for the micro-topography scenarios and the planar reference. Micro-topography is shown in categories, red for hummock and blue for hollow structures. Additionally, for the planar reference the linear slope is shown. Black areas to the ride sides represent areas of aerobic respiration hot spots relative to their surroundings. Aerobic respiration can only occur if oxygen is present. Below hummocks a variably saturated zone with high oxygen contents is stable where preferential aerobic respiration occurs. Zones below hollows usually are water saturated where no oxygen is available for aerobic respiration.

STUDY 2 – SUPPLEMENTARY MATERIAL

Figure A9: Top view for the micro-topography scenarios and the planar reference. Micro-topography is shown in categories, red for hummock and blue for hollow structures. Additionally, for the planar reference the linear slope is shown. Black areas to the ride sides represent areas of preferential iron(III) reduction (hot spots) relative to their surroundings. The patchy pattern develops because Iroon(III) reduction preferentially occurs below hummock structures because of higher iron(III) abundance. Below hollows upwelling water is rich in reduced iron species (Iron(II)).

STUDY 2 – SUPPLEMENTARY MATERIAL

Figure A10: Top view for the micro-topography scenarios and the planar reference. Micro-topography is shown in categories, red for hummock and blue for hollow structures. Additionally, for the planar reference the linear slope is shown. Black areas to the ride sides represent areas of preferential ammonium oxidation (hot spots) relative to their surroundings.

STUDY 2 – SUPPLEMENTARY MATERIAL

Figure A11: Top view for the micro-topography scenarios and the planar reference. Micro-topography is shown in categories, red for hummock and blue for hollow structures. Additionally, for the planar reference the linear slope is shown. Black areas to the ride sides represent areas of preferential iron(II) oxidation (hot spots) relative to their surroundings.

STUDY 2 – SUPPLEMENTARY MATERIAL

Figure A12: Top view for the micro-topography scenarios and the planar reference. Micro-topography is shown in categories, red for hummock and blue for hollow structures. Additionally, for the planar reference the linear slope is shown. Black areas to the ride sides represent areas of preferential sulfide oxidation (hot spots) relative to their surroundings.

STUDY 2 – SUPPLEMENTARY MATERIAL

Figure A13:. Fence plots showing the zones of preferential sulfate reduction for the whole 3D domain of the mean length 0.25 m model.

STUDY 2 – SUPPLEMENTARY MATERIAL

Figure A14: Fence plots showing the zones of preferential sulfate reduction for the whole 3D domain of the planar reference model

STUDY 3

Study 3

Representing effects of micro-topography on runoff generation and subsurface flow patterns by using superficial rill storage height variations.

By Sven Frei and Jan H. Fleckenstein

Ready for submission to Environmental Modelling & Software

STUDY 3

Ready for submission to Environmental Modelling & Software

Representing effects of micro-topography on runoff generation and subsurface flow patterns by using superficial rill storage height variations.

Frei¹, S. and Fleckenstein². J.H.

1Department of Hydrology, University of Bayreuth, Germany

2Department Hydrogeology, Helmholtz-Center for Environmental Research – UFZ, Germany

Abstract

An adequate representation of micro-topography in spatially-explicit, physically-based models can be crucial in modeling runoff generation, surface/subsurface flow interactions or subsurface flow patterns in hydrological systems with pronounced micro-topography. However, representation of micro-topography in numerical models usually requires high grid resolutions to capture relevant small scale variations in topography at the range of centimeters to meters. High grid resolutions usually result in longer simulation times, especially if fully integrated model approaches are being used, where the governing partial differential equations for surface and subsurface flow are solved simultaneously. This often restricts the implementation of micro-topography to plot scale models where the overall model domain is small to minimize computational cost resulting from a high grid resolution. In this study an approach is presented where a highly resolved digital elevation model (DEM) for a hummocky topography in a plot scale wetland model (10m x 21m x 2m), is represented by spatially distributed rill storage zones in a numerical model with a planar surface. By replacing the topographic DEM with spatially distributed rill storage zones, important effects of micro-topography on surface flow generation and subsurface transport characteristics (e.g. residence time distributions) are being preserved, while at the same time the number of computational nodes is reduced significantly. Results indicate that the rill storage concept may be an appropriate tool to represent micro-topography in plot scale models more efficiently because model runtimes drop significantly. Because important aspects of micro-topography induced surface and subsurface flow processes, principally can be mimicked by applying the rill storage concept on a coarser grid, it may also be a useful tool to represent micro-topography in numerical flow models beyond the plot scale.

STUDY 3

1 Introduction

Surface topography significantly controls surface and subsurface flow processes at various scales.

Topography was identified to influence residence times and transport processes in catchments (Kirchner et al., 2001, Haggerty et al., 2002, McGuire et al., 2005, Wörman et al., 2006, Cardenas and Wilson, 2007), which in turn are important controls for retention and degradation of contaminants in groundwater. A strong topographic relationship between the mean residence times and topographic flow path gradients was described by McGuire et al. (2005), where residence times in general decrease with increasing topographic gradients. On the very small scale, surface properties with the dimensions of centimeters to meters like for example in-channel bedforms such as ripples or dunes were identified to be important controls for hyporehic exchange in stream ecosystems (Salehin et al., 2004, Cardenas, 2008). Experimental, as well as modeling studies, which investigated how system specific properties like the extend of the vadose zone (Kollet and Maxwell, 2008b), subsurface heterogeneity (Haggerty et al., 2000) or topography (Wörman et al., 2006, Kollet and Maxwell, 2008b, Kirchner et al., 2001) influence subsurface flow patterns, residence times and transport processes at different scales, describe a common characteristic in the behavior of the system that is independent of the scale of observations. This characteristic, which was described by Kirchner et al.

(2000), is called fractal behavior or fractal scaling and is related to the long term memory of hydrologic systems due to extremely slow groundwater transport mechanisms. Hydrologic systems, showing fractal behavior, usually show typical power law distributed subsurface residence times (Kirchner et al., 2001, Cardenas, 2008, Kollet and Maxwell, 2008b). Across the different spatial scales, time scales of subsurface transport of course do vary, however the statistical distribution of subsurface residence times in systems showing fractal behavior, does not. Power law distributed residence times were reported for hyporehic exchange processes, induced by small scale (10 cm) in-channel bed forms (Cardenas, 2008), for transport through in-channel bend deposits (10m) (Cardenas, 2008) as well as for transport processes at the watershed-scale (Cardenas, 2008, Kollet and Maxwell, 2008b). Cardenas and Wilson (2007) and Kollet and Maxwell (2008b) have shown that surface topography has the potential to induce groundwater flow with fractal behavior and power law distributed subsurface residence times, even if the subsurface is homogenous. Cardenas and Wilson (2007) explained the fractal behavior by the presence of persistent stagnation points in the subsurface flow field where flow velocities are extremely low or even zero. Such stagnation points can be induced by surface topography and are responsible for subsurface velocity distributions that span a wide range of time scales, which will finally lead to fractal scaling and power law distributed residence times (Cardenas and Wilson, 2007).

The impact of small scale, topographical structures with dimensions of centimeters to meters (commonly referred to as micro-topography or micro-relief) on surface/subsurface flow processes and

STUDY 3