Soil and water conservation effects of different types of vegetation cover on runoff and erosion driven by climate and underlying surface conditions

Abstract

Quantitative analyses of runoff and erosion under specific climatic (precipitation characteristics) and underlying surface conditions (slope, antecedent soil moisture) with different types of vegetation cover (or plant measures hereafter) remains a challenging research topic in semi-arid regions. The research site located in the Anjiagou watershed of Gansu Province, China, and used for this study has long-term monitoring data (1987 to 2019) of precipitation conditions, antecedent soil moisture, and runoff and erosion rates from a set of modified standard erosion plots characterized by different vegetation covers or plant measures (arbor forest land, shrub forest land, artificial grassland, natural grassland, and agricultural land) at three slopes (10°, 15°, 20°). Collected data was subjected to path analysis and stepwise regression to determine the main driving factors of runoff and soil erosion, as well as proper input variables for modeling. The results showed that models could be constructed with different variables for different types of vegetation cover (P < 0.05, ra2 > 0.55). The analyses also showed that moderate rain (10 – 25 mm) accounted for >60% of the variation in runoff and plant effects on runoff and soil erosion varied with the measures. Among plant measures, shrub forest had the best performance in reducing runoff and erosion for short-term precipitation events (shorter than 24 hrs), but under the long-durations (72 hrs) precipitation, natural grassland performed the best to prevent the occurrence of runoff and soil erosion. Compared with agricultural land, the rest of the plant measures had an average erosion reduction rate of 73%, which was about twice the runoff reduction rate (37%). Slope was found to play some role in controlling runoff and erosion variation. Compared to slopes of 10° and 20°, runoff and erosion reduction rates at 15° plots were lower. The key variables determining runoff rates under different plant measures included precipitation and maximum 30-minute precipitation intensity, followed by types of vegetation cover. In contrast, erosion rates mostly depended upon runoff and maximum 30-min precipitation intensity. We also found that coupling precipitation characteristics with antecedent soil moisture in the modelling could help produce a more accurate assessment of runoff and soil and water conservation as part of ecological restoration efforts involving typical plant measures under different topographical conditions in semi-arid areas.