Volatile oil in Ramat () was extracted by the method of water vapor distillation and its chemical components was identified by gas-chromatography coupled with mass spectrometry (GC-MS). The volatile oil are evaluated for antibacterial activity against , and . Effects of surfactant, temperature, pH and ultraviolet light on antibacterial activity stability of volatile oil were analyzed too. Total 56 compounds were identified in volatile oil. The main constituents in volatile oil were monoterpenes and sesquiterpenes compounds, including hydrocarbons, esters, aldehydes, ketones, phenols and organic acids.-curcumene was the most abundant volatile component (12.55%). The volatile oil showed promising antibacterial activity against 5 selected strains. The inhibitory effect on exhibited maximum inhibition zone diameter 20.43 mm, and showed 12.29 mm. The volatile oil treated with surfactant Tween 20 showed the strongest antibacterial activity, followed by Tween 80 and the SDS lowest, which showed the lowest. pH also had different effect on antibacterial activity stability of the volatile oil. No significant difference effect on antibacterial activity stability of volatile oil was observed with temperature and UV treatment.

The Loess Plateau has been experiencing large‐scale land use and cover changes (LUCCs) over the past 50 years. It is well known about the significant decreasing trend of annual streamflow and sediment load in the catchments in this area. However, how surface run‐off and sediment load behaved in response to LUCC at flood events remained a research question. We investigated 371 flood events from 1963 to 2011 in a typical medium‐sized catchment within the Plateau in order to understand how LUCC affected the surface run‐off generation and sediment load and their behaviours based on the analysis of return periods. The results showed that the mean annual surface run‐off and sediment load from flood events accounted for 49.6% and 91.8% of their mean annual totals. The reduction of surface run‐off and associated sediment yield in floods explained about 85.0% and 89.2% of declines in the total annual streamflow and sediment load, respectively. The occurrences of flood events and peak sediment concentrations greater than 500 kg/m3 showed a significantly downward trend, yet the counterclockwise loop events still dominated the flood event processes in the catchment. The results suggest that LUCC over the past 50 years resulted in significant changes in the water balance components and associated soil erosion and sediment transportation in the catchment. This was achieved mainly by reducing surface run‐off and sediment yield during floods with return period of less than 5 years. Run‐off–sediment load behaviour during the extreme events with greater than 10‐year return periods has not changed. Outcomes from this study are useful in understanding the eco‐hydrological processes and assisting the sustainable catchment management and land use planning on the Loess Plateau, and the methodologies are general and applicable to similar areas worldwide.

The cover‐management factor (C‐factor) is used in the revised universal soil loss equation to represent the effect of vegetation cover and its management practices on hillslope erosion. Remote sensing has been widely used to estimate vegetation cover and the C‐factor, but most previous studies only used the photosynthetic vegetation (PV) or green vegetation indices (VI, e.g., normalized difference VI) for estimating the C‐factor and the important non‐PV (NPV) component was often ignored. In this study, we developed a new technique to estimate monthly time‐series C‐factor using the fractional vegetation cover (FVC) including both PV and NPV, and weighted by monthly rainfall erosivity ratio. The monthly FVC was derived from the moderate resolution imaging spectroradiometer and LANDSAT data with field validation. We conducted the case‐study over China's Loess Plateau and analysed the spatiotemporal variations of FVC and the C‐factor and their impacts on erosion over the Plateau. Our study reveals a significant increase in total vegetation cover (TC) from 56 to 76.8%, with a mean of 71.2%, resulting in about 20% decrease in the C‐factor and erosion risk during the 17‐year period. Our method has an advantage in estimating the C‐factor from TC at a monthly scale providing a basis for continuously and consistently monitoring of vegetation cover, erosion risk and climate impacts.