Linking Rainstorm-Driven Sediment Dynamics to the Decadal Evolution of Grain Sizes in Dryland Basins

Abstract:

Efforts to understand the dynamics and evolution of dryland basins are complicated by the episodic nature of rainstorms, which generate discontinuous hillslope and channel flows and heterogeneous supply of sediment from hillslopes. Moreover, rainstorms in drylands tend to be highly spatially variable and often smaller than the basin area. Coupled with low infiltration rates and stony soils, rainstorms erode sediment from hillslopes, the grain size distribution of which varies depending on storm characteristics. Therefore, in these landscapes, the discrete and spatially variable nature of convective rainstorms and other basin characteristics create challenges for deterministic modeling of surface dynamics and evolution. Here we investigate the evolution of grain sizes on the hillslopes and in the channel over decadal timescales using a particle-based hillslope sediment transport model driven by a stochastic rainstorm generator that samples from probability density functions of storm properties (total annual rainfall, location, size, duration, peak rainfall intensity). We investigated sediment dynamics and grain size evolution based on data collected within a 170 km² semi-arid basin in SE Spain. Over decadal timescales, our modeling suggests significant sediment redistribution on steeper hillslopes over multiple storm cycles, whereas low gradient hillslopes do not exhibit dramatic sediment size changes over time. At the reach scale, the cumulative effect of decades of storms is that the median fraction (D₅₀) of sediment supplied by the hillslope is preserved in the coarse fraction of the channel grain size distribution (D₉₀). Therefore, despite large fluctuations in supplied grain size from individual rainstorms, over decadal timescales, the inter-storm variability in coarse grain sizes supplied to the channel from hillslopes tends to converge to a characteristic grain size that reflects the balance between the most frequently occurring runoff event and the hillslope gradient and length. The combination of physics-based modeling with stochastic climate representation generates insights into the storm-driven dynamics and evolution of dryland basins.