J.E.M. Baartman

Runoff and sediment yield of tilled and spontaneous grass-covered olive groves grown on sloping land

Soil erosion in olive groves is a widespread phenomenon in the Mediterranean Basin. Many studies have investigated the effects of tillage and herbaceous ground cover (spontaneous or seeded) in their effectiveness to reduce soil erosion in a wide range of Mediterranean sites under different pedoclimatic and topographic conditions. The present study was performed in Ferrandina, southern Italy: a small drip-type rainfall simulator was used on square microplots (0.25 × 0.25 m) to evaluate the propensity to erosion of a steep rain-fed olive grove (mean slope ~10%) with a sandy loam soil by measuring runoff and sediment load under extreme rain events. Two types of soil management were compared: (1) spontaneous grasses as ground cover (GC) providing a maximum ground cover close to 100%; and (2) tillage (T). In the tillage treatment, a further distinction was made between runoff and sediment produced 1 day (T1) and 10 days (T2) after tillage in order to assess the temporal evolution of tillage effects. The results show that GC reduced surface runoff to approximately one-third and soil losses to zero compared with T1. T2 microplots, tested 10 days after tillage, produced only one-tenth the sediment compared with T1 microplots that were subjected to rainfall simulations 1 day after tillage. Total runoff between the two tilled microplots was similar, although runoff on T1 microplots increased steadily over time whereas runoff on T2 microplots remained stable over the duration of simulations. Such findings may be useful to direct and strengthen the policy towards measures to prevent further soil degradation, as clearly requested by the European Union via the cross-compliance concept. A further economic recognition to the olive growers for the achievable environmental benefits could convince them to a shift towards alternative soil management strategies.

Transport of silver nanoparticles by runoff and erosion – A flume experiment

Silver nanoparticles (AgNPs) are being used in many products as they have unique antimicrobial-biocidal properties. After disposal of these products AgNPs can reach the soil environment possibly affecting soil organisms and disrupting plants. This work aimed to study the transport of AgNPs by water and sediment during overland flow and soil erosion. This was done in a laboratory setting, using a flume and rainfall simulator. A low concentration of AgNPs (50μg·kg-1) was applied to two soil-flumes with slope percentages of 20% and 10%. The rainfall was applied in four events of 15min each with a total amount of rainfall of 15mm during each event. After applying the rainfall, samples of the non-transported background soil (BS) and the transported sediment (Sf) were collected from the flume surface. Runoff sediment (RS) and water (RW) were collected from the outlet. AgNPs were detected in all samples collected. However, concentration varied according to sample type (soil or water), time of collection (for runoff water and sediment) and the slope of the soil flume. Higher concentrations of AgNPs in soil were detected in the BS than in the Sf likely due to the BS having more fine particles (silt and clay). The AgNPs concentration in the runoff sediments increased with subsequent applied rain events. In addition, increasing the slope of the flume from 10% to 20% increased the total AgNPs transported with the runoff sediment by a factor 1.5. The study confirms that AgNPs can be transported by both overland flow and sediment due to erosion.

The effect of landform variation on vegetation patterning and related sediment dynamics

Semi‐arid ecosystems are often spatially self‐organized in typical patterns of vegetation bands with high plant cover interspersed with bare soil areas, also known as ‘tiger bush’. In modelling studies, most often, straight planar slopes were used to analyse vegetation patterning. The effect of slope steepness has been investigated widely, and some studies investigated the effects of microtopography and hillslope orientation. However, at the larger catchment scale, the overall form of the landscape may affect vegetation patterning and these more complex landscapes are much more prevalent than straight slopes. Hence, our objective was to determine the effect of landform variation on vegetation patterning and sediment dynamics. We linked two well‐established models that simulate (a) plant growth, death and dispersal of vegetation, and (b) erosion and sedimentation dynamics. The model was tested on a straight planar hillslope and then applied to (i) a set of simple synthetic topographies with varying curvature and (ii) three more complex, real‐world landscapes of distinct morphology. Results show banded vegetation patterning on all synthetic topographies, always perpendicular to the slope gradient. Interestingly, we also found that movement of bands – a debated phenomenon – seems to be dependent on curvature. Vegetation banding was simulated on the slopes of the alluvial fan and along the valley slopes of the dissected and rolling landscapes. In all landscapes, local valleys developed a full vegetation cover induced by water concentration, which is consistent with observations worldwide. Finally, banded vegetation patterns were found to reduce erosion significantly as compared to other vegetation configurations.

A framework approach for unravelling the impact of multiple factors influencing flooding

To have a better understanding of the influence of topographic, climatic, and, especially, anthropogenic factors on hydrological discharge and flooding, this study proposes a new framework approach using a set of methods to answer the questions why, where, when, and how flooding occurs. Including conditional inference tree (CIT), cross-correlation, and double-mass curves analysis, the approach is demonstrated in an application to the Wei River Basin, China. From the CIT analysis, dam construction period was identified as the most important factor (why), and the sub-catchment farthest upstream contributed the most to the flooding of the downstream floodplain (where). We then analysed the effect of the periods of dam construction on the time lag change (when) and the precipitation-discharge relationship (how) using cross-correlation analysis and double-mass curves analysis, respectively. The results suggested that the dam construction delayed the precipitation for 0.4days on average compared to before the dam construction period, and the discharge at the outlet of the basin was reduced by 44%. This framework approach is promising as it can quantitatively evaluate the importance of multiple factors on multiple years of flooding, while many studies evaluate single flooding events.

An integrated method for calculating DEM-based RUSLE LS

The improvement of resolution of digital elevation models (DEMs) and the increasing application of the Revised Universal Soil Loss Equation (RUSLE) over large areas have created problems for the efficiency of calculating the LS factor for large data sets. The pretreatment for flat areas, flow accumulation, and slope-length calculation have traditionally been the most time-consuming steps. However, obtaining these features are generally usually considered as separate steps, and calculations still tend to be time-consuming. We developed an integrated method to improve the efficiency of calculating the LS factor. The calculation model contains algorithms for calculating flow direction, flow accumulation, slope length, and the LS factor. We used the Deterministic 8 method to develop flow-direction octrees (FDOTs), flat matrices (FMs) and first-in-first-out queues (FIFOQs) tracing the flow path. These data structures were much more time-efficient for calculating the slope length inside the flats, the flow accumulation, and the slope length linearly by traversing the FDOTs from their leaves to their roots, which can reduce the search scope and data swapping. We evaluated the accuracy and effectiveness of this integrated algorithm by calculating the LS factor for three areas of the Loess Plateau in China and SRTM DEM of China. The results indicated that this tool could substantially improve the efficiency of LS-factor calculations over large areas without reducing accuracy.