Understanding rainfall-driven hydrodynamic variations is critical for elucidating sediment transport patterns and connectivity on sloping farmlands, yet quantifying the distribution mechanisms of sediment fractions modulated by tillage-induced microtopography is still unclear. This study investigated the dynamics of in-situ disturbed sediments (S-D), translocated sediments (S-H), sediment loss (S-L) across flatting cultivation (T-FC), horizontal cultivation (T-HC), artificial digging (T-AD), and hoeing cultivation (T-HE), under six simulated rainfall duration (RD). Sheet flow surface velocity (V-S) stabilized at 0.32, 0.32, 0.30, and 0.24 m/s for T-FC, T-HE, T-AD, and T-HC, respectively, under simulated rainfall. Correspondingly, loss velocity (V-L) plateaued at 0.32, 0.32, 0.31 and 0 m/s. Correction factor alpha transitioned from alpha< 1 to alpha> 1 after runoff initiation. S-L was predominantly generated at 5, 10, and 15 min rainfall for T-FC, T-HE and T-AD. No S-L detected under T-HC. S-D were illustrated by T-HC ([10.6, 43.2] g/min), followed by T-AD ([10.1, 43.3] g/min), T-HE ([8.2, 43.2] g/min), and T-FC ([7.3, 42.9] g/min). S-H demonstrated reductions of 42%, 56%, and 79% under T-HE, T-AD and T-HC, respectively, with increasing rainfall duration. Loss Proportion to Translocated Sediment (R-SL(y)), representing the proportion of sediment loss from slope on translocated sediments, increased and stabilized under T-HE (67%) and T-AD (38%) with the extension of rainfall duration. Loss Proportion to Disturbed Sediment (R-SL), exhibiting proportion of sediment loss on in-situ disturbed sediments from the slope, under T-FC were superior than T-HE (1%), T-AD (2%) and T-HC (3%). Random Forest Analysis confirmed that S-D was significantly controlled by rainfall simulation and sheet flow feature, compared to S-L primarily governed by hydrodynamics. S-H showed significant response to the synergistic effects of microtopographic spatial variation. Structural Equation Model elucidated that tillage-induced microtopography modulated sheet flow hydrodynamics mediated by rainfall, which exerted effects on sediment distribution, verified by RMSEA, CFI, and R-2. This study offers a comprehensive framework for understanding the coupled influence of rainfall-driven hydrodynamics and microtopography on sediment connectivity, providing valuable insights to refine erosion modeling and optimize tillage-based soil conservation strategies on loess sloping farmlands.

While existing studies have explored interactions between microtopography and hydrodynamics, most failed to quantify the continuous dynamic responses of surface fractal heterogeneity along flow transitions triggered by microtopography and prolonged rainfall. This study investigated soil surface microstructure induced by spatial heterogeneity and hydrodynamics, focusing on surface roughness (SR) depicted by flat (TFC), horizontal (THC), artificial digging (TAD), and hoeing cultivation (THE) across variable rainfall duration (RD). The results showed that runoff velocity (V = 0.16–0.32 m/s) initially increased and stabilized with RD, similar to hydraulic shear stress (τ = 1.12–1.68 Pa), while it decreased with SR differently from τ. Reynolds number (Re = 184–480) increased quasi-linearly with RD, similar to Froude number (Fr = 1.3–2.7) inverse of Darcy–Weisbach friction coefficient (f = 0–2). Surface microstructure was dominated by the flow regime shift. Micro-aggregate content and fractal dimension (D) positively correlated with environmental factors (p < 0.05) converse of macro-aggregate. RF analysis and SEM confirmed the positive effects of RD (0.36**) and BD (0.44**) on D, reverse of Fr (−0.15), f (−0.24*), and TN (−0.14), with acceptable model fit (RMSEA, SRMR < 0.08, CFI, TLI > 0.9). The threshold rainfall duration triggered flow regime conversion under the control of microtopography to quantify surface fractal heterogeneity. The established multi-factor causal framework provides targeted theoretical support for optimizing anti-erosion tillage practices on sloping farmlands.

Microtopography regulates soil erosion by shaping surface heterogeneity, but the mechanism of loess slope soil loss remains insufficiently quantified. This study combined laboratory rainfall simulations and machine learning to investigate how tillage-induced microtopography modulates soil loss through surface heterogeneity and hydrodynamic processes. Simulations used loess soil (silty loam) with a 5° slope, 60 mm/h rainfall intensity, and 5–30 min rainfall durations (RD). Results indicated that the mean weight diameter (MWD) and aggregate stability index (ASI) of structural, transition, and depositional crusts under micro-terrain decreased by 36~65% and 41~60%, respectively, while the fractal dimension (D) increased by 10~19%. Negative relationships were observed between ASI/MWD and D (R2 = 0.83~0.98). Horizontal cultivation (THC, surface roughness [SR] = 1.76, average depression storage [ADS] = 2.34 × 10−2 m3) delayed runoff connectivity and reduced cumulative soil loss (LS) by 42–58% compared to hoeing cultivation (THE, SR = 1.47, ADS = 3.23 × 10−4 m3). Abrupt hydrodynamic transitions occurred at 10 min RD (THE) and 15 min RD (artificial digging [TAD]), driven by trench connectivity and depression overflow. LS exhibited a significant positive correlation with D and RD and was inversely correlated with ASI, MWD, and SR. A three-hidden-layer BPNN exhibited high predictive accuracy for LS (mean square error = 0.07), verifying applicability in complex scenarios with significant microtopographic heterogeneity and multi-factor coupling. This study demonstrated that surface roughness and depression storage were the dominant microtopographic controls on loess slope soil loss. BPNN provided a reliable tool for soil loss prediction in heterogeneous microtopographic systems. The findings provide critical insights into optimizing tillage-based soil conservation strategies for sloping loess farmlands.

Study Region: Yellow River Basin, China, a region of critical ecological and economic significance. Study Focus: This research presents a novel integrated framework for regional drought-flood analysis and precipitation forecasting by evaluating CMADS-L and ERA5 reanalysis datasets against ground-based observations in the Yellow River Basin. We implement K-means clustering on Standardized Precipitation Evapotranspiration Index (SPEI) sequences to identify drought- flood regions and validate a CNN-LSTM hybrid model for regional precipitation forecasting, uniquely bridging traditional climate analysis with modern deep learning techniques for enhanced prediction accuracy. New Hydrological Insights for the Region: Our Analysis Reveals: (1) CMADS demonstrates superior performance over ERA5 in precipitation representation (r = 0.93 vs 0.92; MAE: 9.6 mm vs 17.5 mm; RMSE: 15.8 mm vs 25.9 mm), providing the first comprehensive evaluation of these datasets in complex terrain; (2) We identify three distinct hydroclimatic zones: Northeast (31.6 % area, "wet-dry-wet" sequences, quasi-4.5-year oscillations), Southeast (42.5 %, post-2000 drying trends, quasi-2.3-year cycles), and Western (25.9 %, post-2008 drying, quasi-12-year periodicities); (3) Our novel CNN-LSTM hybrid model achieves unprecedented prediction performance (R2: 0.70-0.85), with highest accuracy in the Western zone due to stable precipitation patterns. This integrated approach significantly advances regional hydroclimate understanding and provides a robust, transferable framework for water resource management under changing climate conditions, offering valuable methodological insights for similar river basins globally.

Studies have shown that preferential flow induced by cracks establishes multiple features such as morphology in different soil profiles. However, there has been little experimental evidence of the contribution of physical crust towards crack features and preferential flow. Essentially, this investigation focused on physical crust (structural and deposition crust) of Lou soil, a loam and silt loam-textured soil, to demarcate the formation of cracks and preferential flow under artificial rainfall. The crack initiation and propagation processes were defined as the formation of primary cracks in the initial phase and narrow cracks around primary cracks, respectively. The cylindrical soil containers and cubical stainless-steel boxes were employed to trace preferential flow in the horizontal and vertical profile, respectively. The cracks in structural and deposition crusts were dominated by initiation and propagation cracks, respectively. The area, length, and width of the cracks in the structural crusts (5.7 cm2, 815, and 1.44 mm) were notably larger than deposition crusts (1.7 cm2, 604, and 0.96 mm). The maximum dyed depths of the structural and deposition crusts reached 35, 45, and 65 mm, and 35, 55, and 75 mm under the infiltration amounts of 10, 30, and 50 mm, respectively. The uniform infiltration depth, length index and PF-fr of structural crusts were in the ranges of 6.7∼25.5 mm, 19∼46%, and 83∼111%, respectively. Corresponding values for deposition crusts were 7.2∼26.2 mm, 10∼46%, and 87∼103%, respectively. The preferential flow in the soil profiles with structural crusts was superior to deposition crust. An assessment of the potential function of the physical crust for preferential flow is a supplement to study the effect of soil surface morphology on hydrological process.

Understanding hydrological nonstationarity under climate change is important for runoff prediction and it enables more robust decisions. Regarding the multiple structural hypotheses, this study aims to identify and interpret hydrological structural nonstationarity using the Bayesian Model Averaging (BMA) method by (i) constructing a nonstationary model through the Bayesian weighted averaging of two lumped conceptual rainfall–runoff (RR) models (the Xinanjiang and GR4J model) with time-varying weights; and (ii) detecting the temporal variation in the optimized Bayesian weights under climate change conditions. By combining the BMA method with period partition and time sliding windows, the efficacy of adopting time-varying model structures is investigated over three basins located in the U.S. and Australia. The results show that (i) the nonstationary ensemble-averaged model with time-varying weights surpasses both individual models and the ensemble-averaged model with time-invariant weights, improving NSE[Q] from 0.04 to 0.15; (ii) the optimized weights of Xinanjiang model increase and that of GR4J declines with larger precipitation, and vice versa; (iii) the change in the optimized weights is proportional to that of precipitation under monotonic climate change, as otherwise the mechanism changes significantly. Overall, it is recommended to adopt nonstationary structures in hydrological modeling.

Comprehensive insights into the aggregate stability of physical crusts enhance the understanding of erosional processes and transport mechanisms. This study evaluated the erosion resistance and aggregate stability in structural and sedimentary crusts of a Lou soil induced by simulated rainfall. A runoff plot (200 cm long x 100 cm wide x 50 cm high) with a slope of 5 degrees was set up to simulate contour tillage (20 cm in ridges, 30 cm in furrows). A single rainfall intensity (60 mm h(-1)) was applied over six durations (5, 10, 15, 20, 25, and 30 min) to obtain structural and sedimentary crusts. With an increase in rainfall duration, bulk density of structural and sedimentary crusts increased from 1.26 g cm(-3) (soil before rainfall) to 1.56 and 1.58 g cm(-3), respectively. Macroaggregate contents in structural crust changed slightly (from 7.5 to 7.4%); however, a marked increase (from 9.0 to 18.6%) was observed in sedimentary crust with increased rainfall duration. The mean weight diameter and geometric mean diameter (i.e., the inverse of erodibility factor) in structural crusts were lower than sedimentary crusts developed from all rainfall conditions. The aggregate stability index of structural and sedimentary crusts initially increased from 2.12 and 2.07 with the increase in rainfall duration, respectively, and then leveled off at 2.42 and 2.48. Soil aggregate stability of sedimentary crust, which conferred greater resistance against external erosive forces, was stronger than that of structural crust.

The response of erosion to soil physical crusts (i.e., structural and sedimentary crusts) has been extensively investigated. Yet few studies have quantified the effects of physical crusts on their detachment capacity (Dc). Accordingly, we investigated the variation in Dc of physical crusts as induced by simulated rainfall. The runoff plot (2.0 m long x 1.0 m wide x 0.5 m high) was set to a slope of 5 degrees and filled with Lou soil (Haplic Luvisol) using horizontal tillage with ridges (1.0 m long x 0.2 m wide x 0.1 m high) and cm furrows (1.0 m long x 0.3 m wide x 0.1 m deep). Simulated rainfall was applied at a single intensity (60 mm h(-1)) for seven durations (0, 5, 10, 15, 20, 25, and 30 min) to obtain structural (at ridges) and sedimentary (at furrows) crusts. Crust samples were collected to obtain Dc, by scouring them for 2 min at a constant inflow discharge (0.8 L min(-1)) on a hydraulic flume (15(degrees) slope). For both structural and sedimentary crusts, with increasing rainfall duration, the measured bulk density (BD), crust thickness (Ct), micro-aggregate content (MIA), and disintegration index (DI) increased, whereas the macro-aggregate content (MAA) decreased. Dc of 0 min and structural crust formed within 5 min of rainfall decreased with a longer scouring time. By contrast, Dc of the other crust types initially rose with an extended scouring time but then plateaued after similar to 60 s. Dc of sedimentary crusts were significantly lower than that of structural crusts. Notably, crusts formed by rainfall at 30 min had greatest detachment reduction benefit. Dc was inversely related to BD, Ct, MIA and DI, whereas increased with increasing MAA. This research provides a timely reference for the effect of physical crust on concentrated flow in arid and semi-arid areas.

Fine mesh nets (FMNs) are commonly used as a mulch material to control soil erosion in construction spoil deposits. Here, three rainfall intensities (60–120 mm·h−1) and seven slope gradients (5–35°) were considered in relation to an FMN’s function of reducing soil erosion on spoil deposits. Soil surfaces covered with an FMN (NS) were prepared in 2 m × 0.5 m soil boxes, with a smooth surface (SS) as the control. Runoff and sediment reduction benefits (RRB and SRB, respectively) were used to quantify the role of the FMN in soil erosion reduction. The FMN performed better in controlling the total sediment yield (mean SRB: 35.9%) compared with total runoff (mean RRB: 5.3%). There was a difference in runoff between SS and NS under a low rainfall intensity (60 mm·h−1; p < 0.05). SS and NS on different slopes generated similar runoff, with significantly different sediment yields (p < 0.05). The benefits of the FMN basically decreased with increases in the rainfall intensity and slope, although the RRB fluctuated on different slopes. The results demonstrate that the soil and water conservation benefits of the FMN on spoil deposits were influenced by the rainfall intensity and slope. The effectiveness of FMNs in soil erosion control needs further investigation in the context of local climates.

Disintegration is closely correlated with geological disasters and soil erosion. However, quantitative studies on the disintegration processes of physical crust controlling the soil surface erosion are limited. Therefore, we disintegration process in structural and sedimentary crusts induced by artificial rainfall on a typical cropland soil from the Loess Plateau, China. The physical crusts were immersed for 200 s at different alcohol concentrations applied for delaying disintegration process to obtain disintegration rate (DR). The content of organic matter and the sand percentage in the structural and sedimentary crusts decreased with increasing rainfall duration, while the bulk density, silt and clay percentages increased. The initial DR values ranged from −0.01 to 1.82 in structural crusts and from −0.01 to 1.47 in sedimentary crusts under different alcohol concentrations. DR decreased by [86.5%, 91.3%] in structural crusts and by [86.3%, 88.2%] in sedimentary crusts during the whole disintegration period. For both structural and sedimentary crust, the DR was the lowest when the rainfall lasted for 30 min, and finally stabilized at 0.19 and 0.18, respectively, at the disintegration time of 80 s. Notably, the 50% alcohol concentration slowed the disintegration process most efficiently. The structural crust had a lower erosion resistance than the sedimentary crust due to the lower DR. These results provide a theoretical method for evaluating disintegration process and timely information revealing the erosion resistance mechanism of physical crusts.

The particle size distribution (PSD) of the soil physical crust is a key index of soil properties. This study analysed the multifractal characteristics of physical crust (structural and depositional crust) PSD under artificial rainfall conditions with a single intensity (60 mm h−1) and three durations (5, 15, and 30 min), summarised the differences in erodibility. A runoff plot (200 cm long × 100 cm wide × 50 cm high) with a slope of 5° was used to simulate hoeing tillage (30 cm long × 15 cm wide × 5 cm deep). We defined the crust formed in the ridges as structural crust (Cst), that formed by infiltration of sediments collected in ditches as sediment-containing depositional crust (Cscd), and that formed by the extraction of sediments as sediment-free depositional crust (Csfd). Nine multifractal parameters (capacity dimension D0, information dimension D1, capacity dimension ratio D1/D0, correlation dimension D2, negative variance amplitude Dv, positive variance amplitude Ds, local average singularity α0, multifractal spectrum width Av, multifractal spectrum symmetry Fv) and an erodibility index (KEPIC) were calculated. The sand content of Cst, Cscd, and Csfd decreased, whereas clay and silt contents increased after rainfall. The range of D0 was 0.60–1.00. D1 decreased in the following order: Cscd > Cst > Csfd. D2 values for Cst, Cscd, and Csfd were 0.82–0.95, 0.87–0.95, and 0.87–0.95, respectively. The α0 value of Cst and Cscd increased with rainfall duration, whereas that of Csfd decreased. The Av was largest in the first layer of the crust when rainfall lasted for a short time, then gradually became largest in the second layer of the crust with prolonged rainfall. All crust types exhibited Fv > 0. KEPIC was largest for Cst, followed by Csfd then Cscd. Tillage and rainfall lead to finer soil particles and more heterogeneous particle distributions and erodibility.

Grasslands cover a large portion of the terrestrial ecosystems, and are vital for biodiversity conservation, environmental protection and livestock husbandry. However, climate change scenarios (e.g., drought) could pose grasslands under threat seriously affecting their ecosystem services role. Ponds, an indispensable part of water storage on the grassland, could exert a key role in water supply during extreme water scarcity scenarios, controlling the cycle of water, nutrients, and sediments, supporting livestock and agricultural land production and maintaining the ecologic functions of pastures. Ponds could indeed be seen as a sustainable solution for more resilient grassland landscapes. The climate change forcing will have an impact on grassland extension and spatial distribution of ponds. On the other hand, in literature small ponds have not been satisfactorily investigated in the study of ecosystem service due to the inconformity of geographic location. In this context, we considered the pastures located in Lessinia Regional Park (Veneto, Italy) with elevation ranging from 800 up to 1600 m asl. The climate is classified as cold with no dry season and warm summer with annual rainfall greater than 1500 mm. The area was recently listed (September 2020) in the Italian national register of historic rural landscapes by Italian Ministry of Agricultural, Food and Forestry Policies. The area is characterized by a dense distribution of ponds, supporting livestock activities. We investigated the ecosystem service role of these ponds, and their spatial patterns and fragmentation (also considering remote sensing, e.g., Sentinel-2) under different weather condition: wet and drought in Lessinia Regional Park. Our work is significant for estimating the ecosystem service value by the integration ponds benefit (e.g., visual ponds and walking ponds) with cultural service. This study will provide scientific basis for rational allocation of environmental resources, formulation of regional protection and management planning, and promotion of sustainable development of man-land relationship.

The continental lower crust is an important composition- and strength-jump layer in the lithosphere. Laboratory studies show its strength varies greatly due to a wide variety of composition. How the lower crust rheology influences the collisional orogeny remains poorly understood. Here I investigate the role of the lower crust rheology in the evolution of an orogen subject to horizontal shortening using 2D numerical models. A range of lower crustal flow laws from laboratory studies are tested to examine their effects on the styles of the accommodation of convergence. Three distinct styles are observed: 1) downwelling and subsequent delamination of orogen lithosphere mantle as a coherent slab; 2) localized thickening of orogen lithosphere; and 3) underthrusting of peripheral strong lithospheres below the orogen. Delamination occurs only if the orogen lower crust rheology is represented by the weak end-member of flow laws. The delamination is followed by partial melting of the lower crust and punctuated surface uplift confined to the orogen central region. For a moderately or extremely strong orogen lower crust, topography highs only develop on both sides of the orogen. In the Tibetan plateau, the crust has been doubly thickened but the underlying mantle lithosphere is highly heterogeneous. I suggest that the subvertical high-velocity mantle structures, as observed in southern and western Tibet, may exemplify localized delamination of the mantle lithosphere due to rheological weakening of the Tibetan lower crust.

[目的]探讨降雨打击下产生的不同坡面结皮土壤水稳性团聚体分布.[方法]采用人工模拟降雨,研究在降雨打击作用下,地表结皮土壤水稳性团聚体的变化情况.受微地形影响,地表结皮性质呈现差异,以坡面不同位置的地表结皮土壤水稳性团聚体为研究对象,以底部无结皮土壤样品为对照,采用Yoder湿筛法探究不同类型结皮土壤团聚体的变化.[结果]在降雨打击作用下,以降雨时间5 min为例:①土壤水稳性团聚体都呈现大团聚体比例较大的特点,表现为结构性结皮大团聚体占比最大,其次为过渡带、原状土,沉积性结皮最小.原状土、结构性结皮、过渡带、沉积性结皮土壤大团聚体所占比例分别为37.69％、41.95％、37.05％、28.93％.随降雨延续,结构性结皮和过渡带土壤大团聚体明显增加,沉积性结皮土壤大团聚体略有减少.②土壤水稳性团聚体的平均当量直径和几何平均直径差异很大.原状土、结构性结皮、过渡带、沉积性结皮的平均当量直径分别为:0.15、0.19、0.17、0.12 mm;几何平均直径分别为0.16、0.21、0.19、0.14 mm.结构性结皮土壤水稳性团聚体的平均当量直径和几何平均直径最大,其次为过渡带、原状土,沉积性结皮最小.③土壤水稳性团聚体分形维数D不同但差异不显著.原状土、结构性结皮、过渡带、沉积性结皮土壤水稳性团聚体分形维数D的大小分别为:2.725、2.705、2.725、2.737.沉积性结皮水稳性团聚体分形维数最大,其次为过渡带、原状土,结构性结皮最小.[结论]降雨打击作用使得土壤表层大团聚体被分散,小团聚体富集;大团聚体量越高,土壤结构越稳定,抗蚀能力越强;反之,抗蚀能力越弱.

为了探析微地形下土壤受雨滴打击后产生的结皮类型及团聚体组成差异.通过人工模拟降雨,研究坡面不同位置的结皮土壤水稳性团聚体分布特征、稳定性以及土壤可蚀性的变化情况.结果 表明:(1)土壤水稳性团聚体以大团聚体(粒径＞0.25 mm)含量为指标,原状土、结构结皮、沉积结皮、过渡带结皮＞0.25 mm粒级的水稳性团聚体分别占37.28％、43.58％、36.69％、40.34％;(2)以降雨历时5 min为例,原状土、结构结皮、沉积结皮、过渡带结皮的水稳性团聚体的破坏率分别为:51.49％、46.00％、62.76％、51.02％;(3)原状土、结构结皮、沉积结皮、过渡带结皮的水稳性团聚体的平均重量直径分别为:0.15、0.20、0.14、0.17 mm;(4)原状土、结构结皮、沉积结皮、过渡带结皮土壤可蚀性K值的大小分别为:0.223、0.200、0.229、0.205.微地形下产生结皮差异使得水稳性团聚体分布有所区别,因此土壤水稳性团聚体稳定性和可蚀性存在差异.