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[Display omitted] • Distribution of vegetation avoided erosion in China increased by 12.89% in 1990–2020. • Greening of the surface has significantly prevented soil and water loss. • Spatial distribution roughly conforms to the division of the Hu Huanyong line. • Surface greening promotes a increase in vegetation avoided erosion efficiency. Global surface greening is very important to slow down regional warming, promote ecological balance and sustainable development, and China has made a significant contribution to this in the past 30 years, and effectively alleviated environmental problems such as land degradation, water shortage and air pollution by rapidly increasing vegetation coverage. Previous studies have shown that vegetation plays a positive role in alleviating soil erosion, but there is no quantitative description of runoff erosion and sediment transport under vegetation evolution with long time series and high resolution in China area. In this study, we use the RUSLE model and multi-source satellite remote sensing data to simulate overland soil erosion in China from 1990 to 2020 and analyze both the temporal and spatial variation of vegetation avoided erosion (VAE) and its correlation with multiple driving factors, such as Gross Primary Production (GPP). The results show that: 1)The distribution has increased by 12.89 % from 1990 to 2020, which is significant, and indicates that greening of the surface has significantly prevented soil and water loss;2)The spatial correlation strength of VAE-GPP in China is roughly in line with the division of the Hu Huanyong line (Hu-line), which is the result of the combined effect of vegetation distribution and human activities;3)The efficiency of VAE was significantly improved, especially the forest, accounting for about 76.50 % of the total, which was twice the sum of the other types. The research conclusion is of great significance to soil erosion prevention and control, soil ecological improvement, vegetation dynamic planning and regional sustainable development. [ABSTRACT FROM AUTHOR]

Highlights • Two crucial periods for suspended sediment transport were June and November/December. • Analysis of 236 floods highlighted their intermittency and did not show relationships. • Medium-term continuous time series are necessary to assess range of variations of SSF. Abstract In mountainous catchments, soil erosion and sediment transport are highly variable throughout time and their quantification remains a major challenge for the scientific community. Understanding the temporal patterns and the main controls of sediment yields in these environments requires a long term monitoring of rainfall, runoff and sediment flux. This paper analyses this type of data collected during 7 years (2007–2014), at the outlet of the Galabre River, a 20 km2 watershed, in south eastern France, representative of meso-scale Mediterranean mountainous catchments. This study is based on a hybrid approach using continuous turbidity records and automated total suspended solid sampling to quantify the instantaneous suspended sediment concentrations (SSC), sediment fluxes, event loads and yields. The total suspended sediment yield was 4661 Mg km−2 and was observed during flood events. The two crucial periods for suspended sediment transport at the outlet were June and November/December (63% of the total). The analysis of suspended sediment transport dynamics observed during 236 flood events highlighted their intermittency and did not show any clear relationship between rainfall, discharge and SSC. The most efficient floods were characterised by counter-clockwise hysteresis relationships between SSC and discharges. The floods with complex hysteresis were the more productive in the long term, during this measuring period exceeding a decade. Nevertheless, the current research outlines the need to obtain medium-term (five years) continuous time series to assess the range of variations of suspended sediment fluxes and to outline clearly the seasonality of suspended sediment yields. Results suggest the occurrence of a temporal dis-connectivity in meso-scale catchments over short time-scales between the meteorological forcing and the sediment yields estimated at the outlet. These findings have important methodological impacts for modelling and operational implications for watershed management. [ABSTRACT FROM AUTHOR]

• CA models for describing runoff are established based on three water distribution rules which significantly impact on confluence. • Dynamic erosion CA models are built by distinguish inter-rill, rill and gully erosions based on critical water depths. • CA models excellently reproduce the runoff and erosion in both the hillslope with rills and the watershed with gullies. • Remain average multi-flow directions algorithm performs the best in runoff and erosion predictions. Rainfall erosion has been calculated and predicted by various soil loss equations, but the progressions of overland flow and sediment transport are less dynamically described. In this study, cellular automata (CA) models based on single flow direction algorithm (SFD), average value multi-flow direction algorithm (AMFD) and remaining average value multi-flow direction algorithm (RAMFD) were constructed. Simultaneously, erosion model was constructed by dividing soil erosion into inter-rill, rill and gully erosions according to critical water depth. The CA models were validated at three scales: a theoretical slope, an in-situ model slope and the natural basin. The results demonstrated the efficient performance of RAMFD in the runoff ascension and recession stages while SFD and AMFD presented unconcentrated runoff distribution, especially in the in-situ slope and basin simulation. Besides, RAMFD model occurred sediment deposition in the basin upstream while SFD and AMFD presented continuous erosion. Furthermore, the runoff Nash-Sutcliffe efficiency (NSE) of three models were 0.85 ∼ 0.95 and 0.65 ∼ 0.94, and the erosion root mean square error (RMSE) were 0.5 ∼ 1.0 kg/min and 0.3 ∼ 0.45 102kg/min in the theoretical slope and natural basin, respectively. Meanwhile, the NSE and RMSE values of RAMFD exhibited the best performance, indicating that this model effectively balanced water distribution while controlling the flow direction to a greater extent. Overall, it is justified to develop an erosion prediction model based on the classification of erosion types, and the rules governing water flow allocation will inevitably result in qualitative and quantitative differences of runoff and erosion. [ABSTRACT FROM AUTHOR]

• Physically based 2D hydrodynamic and sediment transport model, CCHE2D. • High resolution mesh, topography photogrammetry, experimental landform evolution. • Watershed hydrology, raindrop soil detachment, displacement, erosion and transport. • Distributed solution, tilled watershed, cornfield tillage ridge and furrow morphology. • Simulated runoff, sediment transport, landform evolution; channel network analysis. Soil and gully erosion is a critical threat to sustainable agricultural land management and productivity. Soil erosion by rain splash, sheet runoff, and concentrated flow are complex problems conditioned by the combined interactions of soil physical properties, hydrology, human activity, landscape topography, and climate. Effective management of erosion processes driven by rainfall and surface runoff requires a combined effort of field observation, physical experimentation, and numerical simulation. A physically-based hydrodynamic numerical model, CCHE2D with updated raindrop erosion effects, is applied to simulate landscape evolution processes as a result of raindrop impact and overland flow. The numerical model simulates a thin layer of runoff and concentrated flow over complex terrains, and predicts sediment transport due to raindrop splash detachment, transport and soil surface erosions. Soil erosion and landform evolution simulations due to rainfall are presented for an experimental landscape and a tilled large scale agricultural field. Photogrammetric field data were collected using an unmanned aerial system (UAS) following planting and subsequent rainstorms. Numerical simulation results agreed well with the observed experimental soil surface topography, sediment yield, and drainage network developments. The simulated soil and gully erosion in the tilled field also agreed well with observations. This research successfully demonstrates how high resolution spatial and temporal topographic measurements in experimental and field landscapes can be simulated and interrogated by 2D physically-based hydrodynamic and morphodynamic models. The accurate predictions of tillage field and gully erosion process in agriculture watersheds with complex tillage conditions also indicated the usefulness of the model for studying soil and landscape degradation. [ABSTRACT FROM AUTHOR]

• The proposed sediment connectivity framework integrates the rainfall regime. • Event-based sediment connectivity helps identify the sediment source contribution. • The mismatched area exists for erosion and sediment connectivity. • The overlay between erosion and connectivity is key to explaining sediment yield. Sediment connectivity quantifies the intermediate processes between initial erosion and the corresponding sediment yield. However, fully capturing the variations in sediment connectivity at the event scale and revealing their impact on watershed sediment sources remains challenging. Herein, we established an event-based model to assess sediment connectivity by integrating runoff factors. The spatiotemporal variability of sediment connectivity was evaluated for 58 rainfall events in three heterogeneous watersheds. The degree of sediment connectivity served as an indicator to quantify the proportion of potential sediment transport from units to the watershed outlet, with 1 indicating that the eroded sediment can be fully connected and 0 indicating that it cannot be transported. Moreover, the controls of sediment connectivity on watershed sediment sources and yield were determined. Our results indicated that the watersheds with poor vegetation and dense gullies were characterized by high sediment connectivity during all the rainfall events. The connectivity degree was below 0.5 in approximately 80 % of the watershed area, suggesting that most of the eroded sediment was deposited. Rainfall amount and duration dominated the degree of connectivity of the distal hillslopes, while rainfall intensity exerted a primary control on the transport of sediments from riverbanks to the outlet. In addition, the increase of mismatched area between sediment connectivity and erosion resulted in the decrease of sediment yield. The interaction between sediment connectivity and erosion effectively explained the spatial patterns of sediment sources (p < 0.05). Our work confirmed that the coupled erosion model and sediment connectivity predicted the sediment yield accurately. The predictions for different watersheds portrayed that the Nash-Sutcliffe efficiency and Willmott's agreement index were greater than 0.70 and 0.89, respectively. These findings revealed the role of sediment connectivity and are the critical basis to identify watershed-specific sediment management practices. [ABSTRACT FROM AUTHOR]

• The proposed sediment connectivity framework integrates the rainfall regime. • Event-based sediment connectivity helps identify the sediment source contribution. • The mismatched area exists for erosion and sediment connectivity. • The overlay between erosion and connectivity is key to explaining sediment yield. Sediment connectivity quantifies the intermediate processes between initial erosion and the corresponding sediment yield. However, fully capturing the variations in sediment connectivity at the event scale and revealing their impact on watershed sediment sources remains challenging. Herein, we established an event-based model to assess sediment connectivity by integrating runoff factors. The spatiotemporal variability of sediment connectivity was evaluated for 58 rainfall events in three heterogeneous watersheds. The degree of sediment connectivity served as an indicator to quantify the proportion of potential sediment transport from units to the watershed outlet, with 1 indicating that the eroded sediment can be fully connected and 0 indicating that it cannot be transported. Moreover, the controls of sediment connectivity on watershed sediment sources and yield were determined. Our results indicated that the watersheds with poor vegetation and dense gullies were characterized by high sediment connectivity during all the rainfall events. The connectivity degree was below 0.5 in approximately 80 % of the watershed area, suggesting that most of the eroded sediment was deposited. Rainfall amount and duration dominated the degree of connectivity of the distal hillslopes, while rainfall intensity exerted a primary control on the transport of sediments from riverbanks to the outlet. In addition, the increase of mismatched area between sediment connectivity and erosion resulted in the decrease of sediment yield. The interaction between sediment connectivity and erosion effectively explained the spatial patterns of sediment sources (p < 0.05). Our work confirmed that the coupled erosion model and sediment connectivity predicted the sediment yield accurately. The predictions for different watersheds portrayed that the Nash-Sutcliffe efficiency and Willmott's agreement index were greater than 0.70 and 0.89, respectively. These findings revealed the role of sediment connectivity and are the critical basis to identify watershed-specific sediment management practices. [ABSTRACT FROM AUTHOR]

Summary: Three small catchments (<2.5km2 in size) were monitored in the Central Spanish Pyrenees to analyse the hydrological and geomorphological consequences of different land covers under the same climate scenario: (i) the San Salvador catchment represents a dense, undisturbed forest environment; (ii) the Arnás catchment corresponds to an old, abandoned cultivated area subjected to colonisation by plants; and (iii) the Araguás catchment consists in part of active badlands. The obtained results demonstrate that plant cover is a key factor, influencing (i) the seasonality and intensity of floods, (ii) the annual volume of discharge, and (iii) the suspended sediment concentration, total sediment yield and proportions of different types of sediment. The forested catchment tends to generate floods in late winter and spring, when the water table is close to the surface, and flood hydrographs are generally gentle, with solutes largely prevailing over suspended sediment. The old agricultural catchment produces in average twice the number of floods as that recorded in the forested catchment, with the highest floods recorded in autumn and spring; this catchment behaves as a complex mosaic, with a large spatial and temporal variability in terms of both sediment- and runoff-contributing areas; in addition, suspended sediment is equal to solutes, and bedload reaches a relatively high importance. Finally, the badland catchment reacts to all rainstorm events throughout the year, with a high suspended-sediment load. Sediment outputs from the Araguás catchment are two orders of magnitude higher than in the Arnás and San Salvador catchments. Suspended sediment concentrations exceed 300gl−1 in the Araguás catchment, whereas they rarely exceed 20gl−1 in the Arnás and rarely 1.5gl−1 in the San Salvador catchment. [Copyright &y& Elsevier]

Summary: A stochastic model of sediment transport by rainfall-runoff was tested with a simple laboratory experiment. Although the conceptual basis of the model has been previously published [Lisle, I.G., Rose, C.W., Hogarth, W.L., Hairsine, P.B., Sander, G.C., Parlange, J.-Y., 1998. Stochastic sediment transport in soil erosion. Journal of Hydrology 204, 217–230] and its mechanistic underpinnings were convincingly theorized, it had not been corroborated with measurements. Small-scale flume experiments, ∼0.8m long, with simulated rainfall were used to imitate “wash-off” of sediment (0.225mm silica sand) from an impervious surface. Fitting two parameters (ejection and deposition rates) to minimize least squares error resulted in good agreement between stochastic model and measurements, R 2 ∼0.9. However, the fitted parameter values differed from values that would be expected following Lisle et al.’s (1998) physical explanation of the ejection and deposition rates. While some of the discrepancy may be attributable to particle interactions, the conceptualization of deposition as a quiescent settling process in mechanistic erosion models may need to be reevaluated. [Copyright &y& Elsevier]

Summary: This work presents three empirical models (MMFI, Morais Modification of Fournier Index; GJRM, Grimm–Jones–Rusco–Montanarella; REMDB, Diodato–Bellocchi Rainfall–Erosivity Model) where monthly-based climate data are used to estimate long-term (R)USLE (Universal Soil Loss Equation and its Revisions) rainfall erosivity factor (R m, MJmmh−1 ha−1 month−1). The objective was to evaluate two known models (MMFI and GJRM), and compare the results with the novel model REMDB meant for complex terrains. MMFI and GJRM are both based on the precipitation amount, whilst REMDB takes site latitude, elevation and precipitation seasonality also into account. The test area was the Italian region, where 30 stations (altitudes from about sea level up to 1270m, over the latitudinal range 36–46°North) with sufficient data to calculate R m according to USLE were available. The three models were evaluated against USLE rainfall erosivity over a validation data set of 14 stations, using a range of performance statistics. The REMDB estimates generally compared well with the USLE estimates according to different statistics. For REMDB, the relative root mean square error was, in average, 48.58% against 71.49% for MMFI and 66.55% for GJRM. The average modelling efficiency of REMDB was 0.51 against −0.02 (MMFI) and 0.13 (GJRM). REMDB was also superior in preventing biased errors in time, as quantified by the average pattern index versus months: 17.65MJmmh−1 ha−1 month−1, against 58.54MJmmh−1 ha−1 month−1 (MMFI) and 57.76MJmm h−1 ha−1 month−1 (GJRM). Of the two simplified models, the MMFI was the worst performer while the GJRM model performed similarly to the REMDB at two mid-altitude sites of Central Italy. [Copyright &y& Elsevier]