The rainfall erosivity factor (R-factor) is an important parameter in the universal soil loss equation (USLE), the revised universal soil loss equation (RUSLE) and several other soil erosion prediction models. It is necessary to choose suitable methods to map the R-factor at the basin and regional scales to effectively apply erosion prediction models and establish precise soil and water conservation measures. When rain gauges are sparsely and unevenly distributed on high and steep terrain, it is often difficult to obtain ideal results from traditional spatial interpolation methods. To optimize the interpolation method for the R-factor in mountainous areas and explore the impact of the number and distribution pattern of rain gauges on the interpolation results, the Longchuan River Basin in the Hengduan Mountain region in Southwest China was selected as the study area. Four methods, namely, inverse distance weighting (IDW), ordinary kriging (OK), global regression kriging (GRK) and geographically weighted regression kriging (GWRK), were selected to conduct a comparative analysis under various scenarios of gauge number and distribution. Compared with traditional univariate methods, GRK and GWRK, which incorporate elevation, yield more accurate and detailed results, with GWRK exhibiting the best performance. The accuracy and value ranges of the interpolation results are influenced by the coupling of the number and distribution of gauges. With fewer gauges, the impact of the distribution pattern is more obvious. This study provides insights into optimizing R-factor mapping under future climate scenarios, enabling precise soil erosion risk assessment and targeted prevention in mountainous regions.

Rainfall functions as the predominant driving force of runoff and sediment yield on watershed scale. However, previous studies chiefly focused on the effects of areal rainfall characteristics at event scale on runoff and sediment yield, yet the impacts of rainfall spatial differentiation at event scale, i.e., the spatial distribution of rainfall variables within the watersheds, remained inadequately explored. In the present study, comprehensive data were meticulously collected. This data encompassed runoff and sediment data from a hydrological station, as well as rainfall hyetographs from multiple rainfall stations within a representative watershed on the Loess Plateau of China from 1982 to 2020. Subsequently, a series of indicators were proposed to characterize the features of rainfall spatial differentiation within the watersheds. Based on these indicators, the erosive rainfall events were categorized into diverse rainfall spatial patterns. The roles of rainfall spatial patterns in influencing runoff and sediment were revealed, and sediment yield regression models integrating rainfall spatial differentiation were developed. The findings indicated that multiple proposed rainfall spatial differentiation indicators were significantly correlated with runoff depth (H) and specific sediment yield (SSY) (p < 0.05). Compared to rainfall patterns with weaker spatial differentiation, those with stronger spatial differentiation resulted in the substantially larger specific sediment yield (SSY), sediment coefficient (SLC) and peak discharge (Q(max)) (p < 0.05) of the watershed. The uneven coefficient of maximum 30-min rainfall intensity (eta-I30), the maximum 30min rainfall intensity of "high-rainfall amount zone" (I30CA-P) and the IC (index of connectivity) of "highmaximum 30-min rainfall intensity zone" (ICCA-I30) controlled SSY. The models considering rainfall spatial differentiation outperformed those considering only areal rainfall characteristics in predicting SSY, with higher R-2 values, lower RMSE values and higher NSE values. These results offer valuable perspectives on the remarkable influence of rainfall spatial differentiation in generating and predicting the sediment yield of watersheds, thereby shedding new light on the exploration of rainfall-sediment relationships on the watershed scale.

Rainfall erosivity (R) is commonly used to measure water and soil loss by representing the degree of rainfallinduced soil erosion. However, methods for calculating rainfall erosivity vary significantly regarding regional climatic and precipitation characteristics. How to quantitatively illustrate rainfall erosivity remains a key issue for soil erosion monitoring. In this paper, we summarize the basic principles in calculating rainfall erosivity, as well as the relationships and differences among mainstream methods. By referring to experiences gained from previous studies, this paper aims to better summarize and analyze the current rainfall erosivity estimation models and space-time distribution, so as to avoid the confused use of each estimation model as well as to proposes future researches. Currently, there is a widespread utilization of simple algorithms for rainfall erosivity estimation, and statistical methods like machine learning are also seen in such applications. Besides, while many have proposed to quantify local-scale rainfall erosivity, significant limitations are recognized for large-scale estimations. Future researches that emerge recently developed technologies such as remote sensing are expected to further improve rainfall erosivity estimation.

High-spatiotemporal-resolution rainfall data are vital for investigating local terrestrial water cycles. Although remote-sensing satellite retrieval of precipitation products effectively reproduces spatial patterns of rainfall, it suffers from low spatial resolution. To overcome such limitations, a two-step downscaling approach is proposed here. First, 80 % of the meteorological-station data is utilized to calibrate the original Global Precipitation Measurement (GPM) data, enhancing the correlation between GPM and station data. Subsequently, utilizing elevation, slope, aspect, the normalized difference vegetation index (NDVI), wind direction, water vapor, and land surface temperature, as well as slope and aspect correction factors, as independent variables, multiscale geographically weighted regression (MGWR) and temporal lag MGWR (TL-MGWR) models were constructed. Through the aforementioned steps, downscaled monthly and daily precipitation data for the geographic region under investigation in 2022 at a spatial resolution of 0.01 degrees were obtained. Our findings indicate that selectively employing suitable MGWR or TL-MGWR models on a monthly basis can effectively downscale monthly GPM rainfall data. The downscaled (original) monthly precipitation data exhibited a correlation of 0.94 (0.768), with a mean absolute error (MAE) of 16.233 mm/month, root-mean- square error (RMSE) of 27.106 mm/month, and bias of-0.043. Similar enhancement was likewise noted in daily precipitation, displaying a correlation coefficient of 0.863 (0.318) for downscaled (original) data, and a RMSE of 3.209 mm/day, MAE of 1.082 mm/day, and bias of-0.06. The downscaled results show a correlation increase of 0.172 monthly and 0.545 daily, with MAE reductions of 18.43 mm/month and 1.658 mm/day, RMSE reductions of 26.172 mm/month and 4.183 mm/day, and bias reductions of 82.7% and 56.8%. In summary, the data after downscaling, both for monthly and daily datasets, was markedly improved in accuracy. The proposed downscaling method is applicable for reconstructing high-resolution grid data in the complex terrain of the southwest China highland canyon area.

Soil erosion is an important cause of global land degradation and other ecological and environmental problems. Revealing the influence mechanism of land use/cover change (LUCC) on sediment yield can provide a scientific basis for efficient comprehensive and decision-making management of watersheds. As an important indicator of sediment yield and transport capacity, sediment connectivity has been widely studied in recent years. However, the existing index of sediment connectivity (IC) ignores the influence of upslope land use/cover on confluence and the corresponding changes in downslope sediment transport. Moreover, a formula describing the upslope and downslope components does not establish an effective correlation with existing soil erosion formulas. Therefore, the index is not closely related to the erosion process and does not reflect the physical process of sediment transport and sediment deposition. In addition, there have been few reports concerning the effect of LUCC on sediment connectivity inside (on-site impact) and outside (off-site impact) the changed patches. Consequently, by based on addition of the revised parameters of the effective confluence area (Ar) and the runoff velocity factor (v) of the sediment delivery distributed (SEDD) model, an improved sediment connectivity index (ICZQ) is proposed. The results indicate that ICZQ has a significant linear relationship with annual runoff depth or sediment yield modulus in small watersheds within 100 km2 in the Loess Plateau, except for feature years containing rainstorm events (daily rainfall exceeding 50 mm). Therefore, the runoff and sediment transport capacity of small watersheds can be characterized by ICZQ under the influence of LUCC and rainfall change. In 1982-2020, driven by LUCC with an enhancement in vegetation (forest and grass), the ICZQ decreased in 90% of the area and decreased by a significant or extremely significant level over 48% of the area. To better understand the effects of LUCC on sediment connectivity, we analyzed on-site and off-site impacts with rainfall remaining unchanged to control the variables. The contribution rates of the on-site and off-site impacts caused by LUCC on sediment connectivity in Lvergou were 61% and 39%, 48% and 52%, respectively, over two typical periods (1985-1990 and 2015-2020). Due to the large proportion that off-site impacts occupied in the sediment connectivity change, the impact of LUCC on sediment connectivity cannot be ignored, especially when the associated scale is relatively small. The present study provides a quantitative method for the optimization of land use/cover patterns, such as vegetation restoration in watersheds along with a reference for further revealing the impact mechanism of erosion and sediment yield in watersheds.

The combined cover of different vegetation types significantly changes hydraulic properties, thereby controlling soil erosion. However, there are still gaps in the research on how sediment transport capacity is affected by combinations of litter and stem cover. Therefore, this study aimed to reveal the hydrodynamic mechanism through which combined litter and stem cover affected the sediment transport capacity and to develop prediction equations of sediment transport capacity under the condition of combined vegetation cover. Locust leaves and wooden cylinders (diameter of 1 cm) were used to simulate litter and shrub stems, with a combination of different coverage levels. The ranges of litter cover and stem cover were 0-70% and 0-30%, respectively. One discharge rate (1 x 10(-3) m(3) s(-1)) and one slope gradient (26.8%) were chosen to perform the flume experiments. The results showed that for the same vegetation coverage, the stems in the combined cover had a greater impact on hydraulic parameters and sediment transport capacity than did the litter. The decay coefficient of stem cover to reduce the normalized flow velocity and normalized sediment transport capacity was 2.0 and 2.5 times that of litter cover, respectively. Under the condition of combined litter and stem cover, stem cover affected the relationships between the sediment transport capacity and hydraulic parameters related to flow velocity. When stream power was used to estimate the sediment transport capacity, the stem and litter cover must be used together as additional parameters to improve the prediction accuracy. Flow velocity and unit stream power were the most practical parameters for predicting the sediment transport capacity under the combined cover of litter and stems, with determination coefficients of 0.95.

Precipitation extremes can pose adverse impacts on local and downstream society, economy, and ecosystems. Accordingly, their characteristics have attracted widespread attention in many regions, such as the world famous Hengduan Mountain Region in Southwest China, where the overall characteristics in precipitation extremes have been widely reported yet. However, the spatial heterogeneity and internal variation of precipitation extremes caused by the complicated topography were rarely reported, moreover, few studies have evaluated the effect of dynamics in precipitation extremes and soil and water conservation measures on changes in flood discharge and sediment yield. In this study, a typical watershed in the Hengduan Mountain Region, the Longchuanjiang watershed, was selected to identify the dynamics in precipitation extremes from 1965 to 2018, and the contributions of soil and water conservation measures on the characteristics in flood discharge and sediment load. The results of this study are as follows. 1) Substantial decreasing trends occurred for both flood discharge and sediment yield from the early period (1965–2008) to the later period (2009–2018) in the Longchuanjiang watershed. 2) The increase in precipitation extremes in the dry-hot valley and decrease in the mountains revealed great internal variation of the characteristics in precipitation extremes in the Longchuanjiang watershed.3) Soil and water conservation measures that were implemented in recent decades, such as terraced farmland, forest and grass plantation, ecological restoration, and small reservoirs, resulted in the significant reduction of both flood discharge and sediment yield under similar extreme precipitation events. This study highlights the discrepancy of dynamics in precipitation extremes in the dry valleys with an entire watershed in the Hengduan Mountain Region, emphasizes the risks of soil erosion in the ecologically fragile dry valley, and assesses the contribution of soil and water conservation measures on changes in characteristics of flood discharge and sediment load in the selected watershed. The study results are of great importance not only for gaining a scientific understanding of changes in precipitation extremes, flood discharge, and sediment yield but also for the objective assessment of the ecological benefits of soil and water conservation projects and deployment of suitable measures in the future.

Vegetation stems and litter cover have different effects on sediment transport capacity under the same experimental conditions, which in essence, may be due to differences in their hydraulic properties, but the availability of comparative studies is limited. This study aimed to compare the hydraulic properties affected by litter and stem cover, compare differences in the drag forces exerted by litter and stems on overland flow, and develop new Manning's n and flow velocity equations for litter cover. Two series of flume experiments were conducted with the same slope gradients (8.8%, 17.6%, 26.8%) and flow discharge rates (0.5, 1.0 x 10(-3) m(3) s(-1)). Artificial Gramineae stems with a 0%-30% cover level and Pinus tabulaeformis litter with a 0%-70% cover level were used in series 1 and series 2, respectively. The flow velocity and depth were measured. The results showed that the Froude number and flow velocity affected by stem cover were much lower than those affected by litter cover, while the opposite trend was observed in the relative magnitude of the Reynolds number, flow depth and shear stress. The form resistance caused by stems was 22-57 times greater than that caused by litter for the same cover level, which suggests that stem cover contributes more than litter cover to increasing the flow resistance and reducing the flow's ability for sediment detachment and transport. Two new equations for calculating Manning's n and flow velocity under the influence of litter cover were developed, with R-2 and NSE values of 0.96. The results of this study contribute to revealing the mechanisms of the differences of the effects of stem and litter cover on soil erosion.

Plant litter cover affects the sediment transport capacity of overland flow, which, in turn, influences the prediction of the soil erosion. In previous studies, researchers focused on the differences in the hydraulic variables and soil erosion for different types of litter incorporated in the soil or present on the surface. The quantitative relationship between the litter morphology and sediment transport capacity on no-till systems with litter covered surfaces has not been examined yet. Therefore, in this study, the effects of different types of litter on the hydraulic variables and sediment transport capacity were examined, along with the quantitative relationships among the three aspects. To this end, one discharge magnitude (2.632 x 10(-3) m(2) s(-1)), two slope gradients (8.8% and 26.8%), and five types of undecomposed surface litter (Populus simonii, Robinia pseudoacacia, 114)pophae rhamnoides, Pinus tabuliformis, and Bothriochloa ischaemum) were considered to conduct experiments in a steel flume bed. The coverage of each type of litter ranged from 0% to 70%. The results showed that the flow regime, hydraulic variables and sediment transport capacity were affected by the types of litter. The length, width-to-length ratio and roundness of the individual litter leaves could suitably reflect the impact of the litter morphology on the sediment transport capacity, as indicated by the high Pearson correlation coefficients (> 0.5). Long and narrow litter with a small roundness more notably reduced the sediment transport capacity than short and wide litter with a large roundness. The litter morphology did not influence the relationships between the sediment transport capacity and hydraulic variables. In particular, the hydraulic variables such as the unit stream power, flow velocity combined with slope gradient, and stream power combined with flow depth could accurately predict the sediment transport capacity (R-2 > 0.94), and the characteristic variables of the litter morphology and cover were not required to be considered in the prediction equation. The presented findings can be used to develop a simple algorithm to predict the sediment transport capacity of litter covered surfaces.

The sediment transport capacity of overland flow is the core input variable of a process-based soil erosion model. Many studies have focused on the sediment transport capacity for overland flow; however, few studies have explored the relationship between sediment transport capacity and soil aggregate characteristics. The objective of this study was to investigate the effects of soil aggregate characteristics on the sediment transport capacity of overland flow. The unit flow discharge ranged from 0.68 x 10(-3) m(2) s(-1) to 5.41 x 10(-3) m(2) s(-1), and the slope gradient varied from 5.24% to 26.80%. Five types of typical Chinese soil were investigated. The results showed that the best correlation was the relationship between the sediment transport capacity and the mass percentage of aggregates greater than 0.25 mm (WSA(0.25)) under the Le Bissonnais method of wetting stirring conditions. Sediment transport capacity was not correlated to the other soil aggregate characteristics, including the mean weight diameter (MWD) under the Le Bissonnais method of fast wetting and slow wetting conditions and the Yoder method, the degree of aggregation (A), and the fractal dimension (D) under the Yoder method. New equations including WSA(0.25) were developed to predict the sediment transport capacity. The equation including flow discharge, slope gradient and WSA(0.25) provided the best accuracy for predicting sediment transport capacity. The sediment transport capacity increased linearly with the mean flow velocity. Between the hydraulic variables of shear stress and stream power, our results showed that stream power was an optimal predictor for calculating sediment transport capacity. These findings offer a new approach for predicting the sediment transport capacity of overland flow.

Sediment transport capacity (Tc) plays a pivotal role in process-based soil erosion models. Surface cover is an important factor that affects Tc; investigation into the potential effect of litter cover on Tc is limited. The objectives of this study were to quantify the effects of Pinus tabulaeformis litter cover on Tc; to explore various relationships between hydraulic variables, litter cover, and Tc; and to compare the similarities and differences of the effect of litter and stem cover on Tc. Experiments were conducted in a 5 x 0.38 m flume. The unit flow discharge varied from 1.316 x 10(-3) to 3.947 x 10(-3) m(2) s(-1), and the slope gradient varied from 8.8 to 26.8 %. Pine needles of Pinus tabulaeformis were selected to simulate litter cover. Seven levels of litter cover were considered: 0%, 5%, 10 %, 20 %, 30 %, 50 %, and 70 %. The median diameter of the test sediment was 0.35 mm. The results showed that Tc decreased exponentially as litter cover increased. Measured Tc could be predicted adequately (R-2 = 0.96) by unit flow discharge, slope gradient and litter cover, or the stream power and litter cover. Flow velocity or unit stream power could predict the Tc equally well (R-2 = 0.95) without including the cover term because the effect of litter cover on the Tc manifests itself in the increased resistance and reduced flow velocity. Tc is most sensitive to the slope gradient when the level of cover is low. The effect of litter cover on Tc could be greater than the unit flow discharge and slope gradient in relative terms when the level of cover exceeded 38 % and 81 %, respectively. The effect of stem cover on Tc is greater than that of litter cover, other variables being the same.

Cross-sectional morphology is an effective approach for calculating rill volume and revealing the mechanism for rill development. In this study, the law governing the temporal–spatial variation in rill cross-section (RCS) under interbedded clay and gravel conditions was investigated by a scouring experiment. A high-flow scouring experiment was conducted in a field plot under heterogeneous soil conditions in the Yuanmou Dry-Hot Valley using 3D laser scanning and ArcGIS techniques. Morphological index system including the size and derived proportional parameters was established to accurately reveal the dynamic process of the rill erosion–sediment sections based on temporal–spatial scale. The study indicated that the RCS size under gravel and soil aggregates showed an irregular variation over different periods, and the variation of RCS morphology tends to be nonlinear. The area of rill cross-section at the middle of the rill was much larger than that of the rill head and the rill mouth, and the fluctuations in RCS along the rill depended heavily on the soil texture heterogeneity. In addition, there were extreme variations in rill erosion direction for different rill parts, i.e., rill head, body, and mouth, and the highly significant asymmetry in RCS distributed along the rill under increasing scouring duration in the Yuanmou Dry-Hot valley. Temporal variations in RCS morphology were opposite to spatial variations by comparing the same morphology parameter. Nonlinear fluctuation trends and asymmetric shapes were observed in the variation of RCS on slopes with soils and gravels.

The morphology of the gully longitudinal profile (GLP) is an important topographic index of the gully bottom associated with the evolution of the gullies. This index can be used to predict the development trend and evaluate the eroded volumes and soil losses by gullying. To depict the morphology of GLP and understand its controlling factors, the Global Positioning System Real-time Kinematic (GPS RTK) and the total station were used to measure the detail points along the gully bottom of 122 gullies at six sites of the Yuanmou dry-hot Valley. Then, nine parameters including length (Lt), horizontal distance (Dh), height (H), vertical erosional area (A), vertical curvature (Cv), concavity (Ca), average gradient (Ga), gully length-gradient index (GL), normalized gully length-gradient index (Ngl), were calculated and mapped using CASS, Excel and SPSS. The results showed that this study area is dominated by slightly concave and medium gradient GLPs, and the lithology of most gullies is sandstone and siltstone. Although different types of GLPs appear at different sites, all parameters present a positively skewed distribution. There are relatively strong correlations between several parameters: namely Lt and H, Dh and H, Lt and A, Dh and A, H and GL. Most GLPs, except three, have a best fit of exponential functions with quasistraight shapes. Soil properties, vegetation coverage, piping erosion and topography are important factors to affect the GLP morphology. This study provides useful insight into the knowledge of GLP morphology and its influential factors that are of critical importance to prevent and control gully erosion.