Exploring the effects of seismicity on landslides and catchment sediment yield: An Italian case study

Recent studies showed that contemporary average catchment sediment yields (SY, [t km− 2 y− 1]) at regional and continental scales are often strongly correlated to spatial patterns of seismic activity. Nonetheless, we currently have little insights into the mechanisms that explain these correlations. We investigated how spatial patterns of SY in Italy are linked to patterns of seismic activity. For a dataset of 103 Italian catchments with average SY measured over a period of years to decades, we extracted tectonic and none-tectonic variables that potentially explain observed differences in SY. These include proxies for vertical uplift rates and cumulative seismic moments (CSM) associated with historic earthquakes of different ranges of magnitude. Results showed that also across Italy, SY is significantly correlated to seismicity. However, SY showed much stronger correlations with proxies of seismicity relating to small but frequent earthquakes (2 ≤ Mw < 4) than with proxies relating to tectonic uplift or large, potentially landslide-triggering earthquakes (Mw ≥ 4). Analyses of a dataset of about 500,000 landslides across Italy showed very comparable trends: spatial patterns of landslides within similar lithological units generally show a significant positive correlation with CSM of weak but frequent seismicity and generally not with CSM of large earthquakes. These results suggest that, on a decadal time scale and at a regional/continental spatial scale, frequent but relatively weak seismicity may exert a more important geomorphic impact than large earthquake events or tectonic uplift. © 2016 Elsevier B.V

Determining RUSLE P-factors for stonebunds and trenches in rangeland and cropland, Northern Ethiopia

The implementation of soil and water conservation (SWC) measures in the Ethiopian highlands is a top priority to reduce soil erosion rates and to enhance the sustainability of agroecosystem. Nonetheless, the effectiveness of many of these measures for different hillslope and land use conditions remains currently poorly understood. As a result, the overall effects of these measures at regional or catchment scale remain hard to quantify. This study addresses this knowledge gap by determining the cover-management (C) and support practice (P) factors of the Revised Universal Soil Loss Equation (RUSLE), for commonly used SWC measures in semi-arid environments (i.e. stone bunds, trenches and a combination of both). Calculations were based on soil loss data collected with runoff plots in Tigray, northern Ethiopia (i.e. 21 runoff plots of 600 to 1000 m2 , monitored during 2010, 2011 and 2012). The runoff plots were installed in rangeland and cropland sites corresponding to a gentle (5%), medium (12%) and steep (16%) slope gradients. The C and P factors of the RUSLE were calculated following the recommended standard procedures. Results show that the C-factor for rangeland ranges from 0.31 to 0.98 and from 0.06 to 0.39 for cropland. For rangeland, this large variability is due to variations in vegetation cover caused by grazing. In cropland, C-factors vary with tillage practices and crop types. The calculated P-factors ranged from 0.32 to 0.74 for stone bunds, from 0.07 to 0.65 for trenches and from 0.03 to 0.22 for a combination of both stone bunds and trenches. This variability is partly due to variations in the density of the implemented measures in relation to land use (cropland vs rangeland) and slope angles. However, also annual variations in P factor values are highly significant. Especially trenches showed a very significant decline of effectiveness over time, which is attributable to their reduced static storage capacity as a result of sediment deposition (e.g. for trenches in rangeland: 0.07-0.13 in 2010 to 0.37-0.65 in 2012). Hence, the results of this work may not only help in better modelling and quantifying the average long-term impacts of SWC measures over larger areas, but also show the importance of considering temporal variations of the effectiveness of SWC measures

Landslides, river incision and environmental change : the Ruzizi gorge in the Kivu Rift

The understanding of the interplay between natural and human induced factors in the occurrence of landslides remains poorly constrained in many regions, especially in tropical Africa where data-scarcity is high. In these regions where population growth is significant and causes changes in land use/cover, the need for a sustainable management of the land is on the rise. Here, we aim to unravel the occurrence of landslides in the 40 km-long Ruzizi gorge, a rapidly incising bedrock river in the Kivu Rift in Africa that has seen its landscape disturbed over the last decades by the development of the city of Bukavu (DR Congo). Careful field observations, historical aerial photographs, satellite imagery and archive analysis are combined to produce a multi-temporal inventory of 264 landslides. We show that the lithological context of the gorge and its extremely high incision rate (> 20 mm year-1) during the Holocene explains the presence of a concentration of large landslides (up to 2 km²) of undetermined age (well before the first observations of 1959) whose occurrence is purely natural. They are mostly of the slide type and do not show morphologic patterns of recent activity. The landslides that occurred during the last 60 years are flow-like shallower slope failures of smaller size (up to 0.12 km²) and tend to disappear rather quickly (sometimes within a few years) from the landscape as a result of rapid vegetation growth, land reclamation and (human-induced) soil erosion. They are primarily related to threshold slopes and precipitation plays a frequent role in their onset. However, land use/cover changes also affect their occurrence. This study provides useful information for a more accurate evaluation of the landslide hazard in the area, particularly with respect to the growth of the city of Bukavu that has developed without the consideration of naturally instable slopes. It also stresses the need and added value of building accurate landslide inventories in data-scarce regions