Effect of hillslope aspect on landform characteristics and erosion rates

Analysis of spatiotemporal variations and influencing factors of soil erosion in the Jiangnan Hills red soil zone, China

Soil erosion is an important environmental problem in China. The hilly region of Jiangnan is characterized by severe soil erosion due to its unique climate and intensive human activities. Therefore, assessing soil erosion in this area is of great significance for achieving regional sustainable development. Based on the spatial zoning of natural resources and the spatial differences in precipitation, land cover, topographic features, and soil texture, we estimated soil erosion from 2000 to 2020 using the Revised Universal Soil Loss Equation (RUSLE) model. The study showed that micro-erosion dominates spatially in the subtropical forest subzone of the eastern hills, accounting for more than 60% of the total erosion area. Intense erosion was found in woodlands and grasslands and the erosion intensity tended to be lower in the plains. Erosion occurred mainly in areas with slopes >8°. The areas with significantly lower erosion were mainly distributed at the boundaries between forests, arable land, and artificial land surfaces. The areas where soil erosion significantly increased over the study period were mainly found in farmland areas (31.70%). Soil erosion occurred because of a combination of factors, among which vegetation cover played a prominent role. Elevation and slope were correlated with soil erosion intensity. Severe erosion in different parts of the study area showed two trends of spatial aggregation and discrete distribution. This analysis of soil erosion in the study area by the RUSLE model provides reference data for the eastern subtropical forest subregion including the Jiangnan Hills.

High-resolution, spatially resolved quantification of wind erosion rates based on UAV images (case study: Sistan region, southeastern Iran)

Estimating the quantitative distribution of wind erosion rates is one of the most important requirements for managing affected environments and optimizing locations to control wind erosion. This study develops high-resolution maps for wind erosion with unmanned aerial vehicles or UAV images in the Sistan region-an area in southeastern Iran with severe wind erosion. Aerial imaging by UAV was done during period of erosive winds. Changes in the amount of wind erosion were measured for 7 months. Digital elevation models or DEM with a spatial resolution of 6 mm, orthophoto mosaic images with a resolution of 3 mm, were prepared before and after the erosion event. Three erosive facies consisting of surface, edge, and blowout were identified. The amount of erosion in different geomorphological landscapes or facies was measured according to differences of DEMs (DOD). The effect of physical factors of the geomorphological landscapes on wind erosion was investigated by calculating the correlation between the erosion, roughness, and slope in the geomorphological landscapes. The results showed that the highest and lowest mean of eroded soil were 22 mm and 4 mm in the blowout and surface facies, respectively. The average rate of wind erosion was 201 t/ha during the study period, which indicates the high intensity of wind erosion in the Sistan plain. Overall, UAV-as an aerial imaging technique collecting ground data-can be a helpful tool in the aeolian geomorphology especially for collecting data for measuring the rate of soil erosion by the wind in the aeolian landscapes located in remote regions.

Field testing study on the rainfall thresholds and prone areas of sandstone slope erosion at Mogao Grottoes, Dunhuang

The Dunhuang Mogao Grotto is a famous Buddhist monument and was inscribed in the list of world cultural heritage sites by UNESCO in 1987. Water poses a major threat to the preservation of this heritage even though it is located in an arid region. This study was conducted to investigate the effect of rainfall on rock erosion. Specifically, the formation mechanism of slope runoff and the erosion threshold of rainfall were analyzed, and erosion-prone areas of the site were identified. This was carried out using field artificial rainfall simulation testing, and the results inform methods of preventing rainfall-induced cliff erosion. In addition, the rainfall threshold and erosion-prone areas obtained from the experiment were further validated and optimized using monitoring data for natural rainfall and historic documentation. The threshold value of erosive rainfall obtained by empirical statistical analysis method was found to be similar to that obtained by the runoff generation mechanism. The areas identified as prone to erosion using field tests coincided with areas of historic erosion as recorded in site documentation. Furthermore, the forecast grade of cliff slope erosion and its erosion-prone areas are determined after comprehensive analysis of the results obtained by these two methods. The research results are critical for the monitoring, early warning, and prevention of cliff slope erosion. The research methods can also be used as reference in areas for which rainfall data are missing.