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Riparian vegetation plays a vital role in inhibiting soil and water loss, but few studies have quantified the relationships between vegetation spatial pattern and the hydraulic characteristics of upslope runoff. This study investigated how hydraulic characteristics (e.g., runoff coefficient, flow regime, flow resistance, and flow shear stress of overland flow) responded to differences in vegetation cover (15% and 30%), slope gradient (5°, 10°, 15°, and 20°), and vegetation pattern in the riparian zone along the lower Yellow River, China, based on landscape pattern analysis and a runoff scouring experiment with flow rates of 9 and 15 L/min and an experimental plot size of 1 m × 3 m. We found that runoff generation on shallow slopes was moderated by increasing vegetation cover, but that this moderating effect decreased on steeper slopes. The regime of overland flow switched from laminar and subcritical on the 5° slope (Fr = 0.56–0.87) to laminar and critical on the 10°, 15°, and 20° slopes (Fr = 1.02–2.18). Flow resistance increased with vegetation cover and flow rate and decreased with slope gradients, and it was larger on shallow slopes with high vegetation cover. Flow shear stress had a range of 1.42–3.55 N m−2, and it increased with increasing slope gradient, vegetation cover, and flow rate. The hydraulic characteristics of upslope runoff, especially flow resistance, were significantly related to vegetation pattern at both the landscape and class levels. Flow resistance was negatively related to patch density, and positively related to perimeter–area fractal dimension and connectance index. The influencing mechanism of landscape patterns on soil erosion processes is dependent on the landscape scale, since the relationships between flow resistance and some landscape pattern indices (aggregation index, effective mesh size, and splitting index) were opposite at the landscape level compared to the class level. We conclude that fragmented vegetation distributions reduce flow resistance, and that riparian vegetation could be managed to inhibit slope erosion by increasing flow resistance.

The expansion of agriculture is posited as one of the main dynamics of forest landscape change globally, and the robust modeling of these processes is important for policy as well as academic concern. This paper concerns a relatively small area of Yiluo River catchment where considerable attention has been paid to slow down the process of the expansion of agriculture into the remaining natural forests. In the present study, we reconstructed the former forest landscape structure and elucidated the landscape change during a period of about 15 years. Three sets (1987, 1996 and 2002) of maps derived from Landsat-5 images were used for analyses. The result showed that there was a decrease in the area of the forest landscape from 995.60 km 2 in 1987 to 650.50 km 2 in 2002. Then we examined the degree to which forest landscape conversion could be attributed to a set of factors identified as significant at broader scales, namely topography, distribution of the village clusters (centroids), distance from villages (centroids), and distance from forest edge (1987). By using "spatial analysis" in Arc/gis 8.3, the correlation between forest landscape change and driving factors was constructed. This study found that forest landscape conversion in this region was largely explained by elevation, slope and proximity to village.

Human activities are increasingly recognized as having a critical influence on hydrological processes under the warming of the climate, particularly for dam-regulated rivers. To ensure the sustainable management of water resources, it is important to evaluate how dam construction may affect surface runoff. In this study, using Mann–Kendall tests, the double mass curve method, and the Budyko-based elasticity method, the effects of climate change and human activities on annual and seasonal runoff were quantified for the Yellow River basin from 1961–2018; additionally, effects on runoff were assessed after the construction of the Xiaolangdi Dam (XLD, started operation in 2001) on the Yellow River. Both annual and seasonal runoff decreased over time (p < 0.01), due to the combined effects of climate change and human activities. Abrupt changes in annual, flood season, and non-flood season runoff occurred in 1986, 1989, and 1986, respectively. However, no abrupt changes were seen after the construction of the XLD. Human activities accounted for much of the reduction in runoff, approximately 75–72% annually, 81–86% for the flood season, and 86–90% for the non-flood season. Climate change approximately accounted for the remainder: 18–25% (annually), 14–19% (flood season), and 10–14% (non-flood season). The XLD construction mitigated runoff increases induced by heightened precipitation and reduced potential evapotranspiration during the post-dam period; the XLD accounted for approximately 52% of the runoff reduction both annually and in the non-flood season, and accounted for approximately −32% of the runoff increase in the flood season. In conclusion, this study provides a basic understanding of how dam construction contributes to runoff changes in the context of climate change; this information will be beneficial for the sustainable management of water resources in regulated rivers.

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Climate variation and land use changes have been widely recognized as two major factors that impact hydrological processes. However, it is difficult to distinguish their contributions to changes in streamflow. Quantifying their contributions to alteration of streamflow is especially important for the sustainable management of water resources. In this study, the changes in streamflow for the period of 1960–2008 at two stations (Dongwan and Luhun) were analyzed in the Yihe watershed in China based on hydrological data series and climate parameters. Using a non-parametric Mann–Kendall (MK) and Pettitt’s test, as well as Budyko analysis, we first examined the trends of hydroclimatic variables and the breakpoint of annual streamflow over the past 50 years. Subsequently, we evaluated the contributions of annual precipitation (P), potential evapotranspiration (PET), and land use condition (represented by w), respectively, to streamflow variation. We observed a decreasing trend for P, as well as increasing trends for PET and w. Annual streamflow showed a significant downward trend with an abrupt change occurring in 1985 during the period of 1960–2008. Accordingly, we divided the studied period into two sub-periods: period I (1960–1985) and period II (1986–2008). The sensitivity of the streamflow to the different environmental factors concerned in this study differed. Streamflow was more sensitive to P than to PET and w. The decrease in P was the greatest contributor to the decline in streamflow, which accounted for 50.01% for Dongwan and 55.36% for Luhun, followed by PET, which accounted for 24.25% for Dongwan and 24.45% for Luhun, and land use change was responsible for 25.25% for Dongwan and 20.19% for Luhun. Although land use change plays a smaller role in streamflow reduction, land use optimization and adjustment still have great significance for future water resource management, since climate variation is difficult to control; however, the pattern optimization of land use can be achieved subjectively.