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Existing research on soil erosion primarily focuses on the individual effects of factors such as rainfall intensity, slope gradient, grass cover, and soil characteristics, with limited exploration of the interactions among these factors. This study investigated the mechanisms of soil erosion on overland covered with vegetation in the Loess Plateau region through indoor artificial simulated rainfall experiments. The experiments included six levels of grass coverage (0, 30%, 40%, 50%, 60%, 70%), five grass distribution patterns (DP, CP, VP, SP, HP), five rainfall intensities (60, 80, 90, 100, 120 mm/hr) and three slope gradients (5°, 10°, 15°) to explore the effects of experimental design factors and hydraulic parameters on the overland soil erosion mechanisms. The results show that as the grass coverage increases, the soil erosion rate on the overland decreases. Under different grass distribution patterns, horizontal grass distribution played an important role in inhibiting overland soil erosion rate. The overland soil erosion rate increased following a power function relationship with rising slope steepness and rainfall intensity, with erosion rates being more sensitive to changes in rainfall intensity than slope gradient. Among the six hydraulic parameters, dimensionless stream power was the optimal hydraulic parameters for predicting overland soil erosion rate under grass cover. Furthermore, an overland soil erosion model under the influence of grass cover and rainfall intensity was established based on general dimensionless hydraulic parameters (KGE = 0.931, R2 = 0.912). The model satisfactorily simulates overland soil erosion rate under grass cover and helps to reveal the mechanism of overland soil erosion. Plain Language Summary Grass cover has a complex influence on overland soil erosion. This study quantified the impact of grass cover on overland soil erosion using a dimensionless water flow path index. It systematically analyzed the response mechanism among overland soil erosion, slope gradient, rainfall intensity, and hydrodynamic parameters, aiming to identify the optimal hydrodynamic parameters capable of characterizing overland soil erosion. A predictive model for soil erosion was constructed based on general dimensionless water flow intensity parameters, comprehensively evaluating the mechanism of soil erosion on grass‐covered overland under simulated rainfall conditions. The results indicate that the model constructed using dimensionless parameters exhibits strong adaptability and can be effectively validated in other experiments. Key Points Systematically analyze the response mechanism of overland soil erosion concerning experimental design factors and hydrodynamic variables Dimensionless stream power is the most effective hydrodynamic parameters for predicting overland soil erosion under grass cover Develop an overland soil erosion prediction model using general dimensionless flow strength parameters

Canopy interception represents the initial phase of rainfall redistribution across the land surface and is crucial for hydrological and ecological processes. This study proposes a novel theoretical model of canopy interception based on the microphysical processes of raindrops within the canopy. The model incorporates physical parameters pertinent to canopy characteristics, such as the attachment retention coefficient and the pinning proportion coefficient. Both the basic and simplified model forms of canopy interception during rainfall events have been derived. Further elaborations of the model account for stem flow, the surface evaporation during rainfall, and other conditions. The model parameters are clearly defined, physically meaningful, and can be directly estimated using detailed canopy structure data. This estimation process is now more feasible than ever due to advances in high‐resolution lidar technology. Simulated rainfall experiments were conducted to validate the movement patterns of raindrops in the canopy, establish model parameters, validate the models' accuracy, and compare the applicability of the two model forms. Key Points Investigates raindrop microphysical processes within a canopy and identifies critical model parameters Derives and establishes a novel theoretical canopy interception model grounded in the microphysical processes of raindrops Validates the new models' efficacy, and compare the basic and simplified model forms through simulated rainfall experiments

Soil erosion is a universal phenomenon on the Loess Plateau but it exhibits complex and typical mechanism which makes it difficult to understand soil loss laws on slopes. We design artificial simulated rainfall experiments including six rainfall intensities (45, 60, 75, 90, 105, 120 mm/h) and five slopes (5°, 10°, 15°, 20°, 25°) to reveal the fundamental changing trends of runoff and sediment yield on bare loess soil. Here, we show that the runoff yield within the initial 15 min increased rapidly and its trend gradually became stable. Trends of sediment yield under different rainfall intensities are various. The linear correlation between runoff and rainfall intensity is obvious for different slopes, but the correlations between sediment yield and rainfall intensity are weak. Runoff and sediment yield on the slope surface both presents an increasing trend when the rainfall intensity increases from 45 mm/h to 120 mm/h, but the increasing trend of runoff yield is higher than that of sediment yield. The sediment yield also has an overall increasing trend when the slope changes from 5° to 25°, but the trend of runoff yield is not obvious. Our results may provide data support and underlying insights needed to guide the management of soil conservation planning on the Loess Plateau.

Rainfall is the main driving factor for soil-active herbicides, influencing their incorporation, leaching, and absorption. Studies were conducted to determine the effects of simulated rainfall and hexazinone application rates on giant smutgrass [Sporobolus indicus (L.) R. Br. var. pyramidalis (P. Beauv.) Veldkamp] control and the impacts of application timing and rates on S. indicus var. pyramidalis in the field. Greenhouse experiments were established in Florida between 2017 and 2018, comprising hexazinone application rates of 0.56 and 1.12 kg ai ha−1, and seven simulated rainfall accumulation volumes (0, 6, 12, 25, 50, 100, and 200 mm), distributed in a completely randomized design with four replicates and a non-treated control. Field experiments were conducted in a split-plot arrangement, wherein main plots were application timings at 1-wk intervals, subplots were two hexazinone application rates (0.56 and 1.12 kg ha−1) and a non-treated control, distributed in a randomized complete block design, with four replicates. In the greenhouse experiment, 49 and 92 mm were required to obtain 50% visual control and 35 and 82 mm to reduce biomass by 50% for hexazinone rates of 0.56 and 1.12 kg ai ha−1, respectively. Field experiments showed that hexazinone peak efficacy was from mid-June to mid-August when applications were followed by 10 to 75 mm of rainfall during the first 7 d after treatment. The recommended rate of hexazinone at 1.12 kg ai ha−1 should be applied, as it has an extended window of optimum application timing.

In this study, scale-based runoff plots of concave grasslands were designed and simulated rainfall experiments were conducted to investigate their retention effectiveness for runoff volume and pollutant loads, and to analyze the influences of concave depths on runoff and pollution retention of grasslands. Results showed that mean time to runoff of concave grasslands was 88.5 minutes, which was 5.3 times than that of flat grassland. Average peak flow rate of concave grasslands was reduced by 36.2% compared with flat grassland. Concaved grasslands averagely retained 58.2% of stormwater runoff. Deeper concave depths significantly increased runoff detention and retention performance of grasslands. Total suspended solids (TSS) load reduction rates of concave grasslands were ranged from 50.8% to 97.3%. Total nitrogen (TN) load reduction rate was 49.8% for concave depth of 10 cm. Total phosphorus (TP) load reduction rates were 45.0% and 93.9% for grasslands with 5 cm and 10 cm concave depths, respectively. Pollution load reduction rates of TSS, TN and TP enhanced along with the increase in concave depths. The estimated minimum area ratios of upslope impervious surface to grasslands of 5 cm and 10 cm concave depths were approximately 1:1 under 20 mm rainfall events, and 38:1 under 5 mm rainfalls, respectively.

The canopy water storage capacity of vegetation has great significance for the hydrological cycle. We used the Pereira regression analysis method, scale-up method, and simulated rainfall method to determine canopy water storage capacity from 2014 to 2018. The Pereira regression analysis was affected mainly by the seasonal variation in the leaf area index and the observation method of throughfall. The canopy water storage capacity was 0.68 mm and 0.72 mm for C. korshinskii and H. rhamnoides, respectively. The canopy water storage capacity of C. korshinskii and H. rhamnoides was 0.73 mm and 0.76 mm, respectively, using the scale-up method. The scale-up method showed that water storage capacity per area of the canopy components was in the order of branches (0.31 mm) > leaves (0.27 mm) > trunks (0.15 mm) for C. korshinskii, and trunks (0.33 mm) > branches (0.29 mm) > leaves (0.14 mm) for H. rhamnoides. We used eight simulated rainfall intensities to determine the canopy water storage capacity for C. korshinskii and H. rhamnoides, which was 0.63 mm and 0.59 mm, respectively.

Soil and water losses in purple soil area is becoming an increasingly severe problem, bringing enormous challenges to environmental protection in rural areas. In this study, simulated rainfall experiments were conducted to analyse the effects of rainfall and the slope conditions on the soil and water loss. Purple soil from a typical slope in the Beibei District of Chongqing was selected as the experimental soil. Twenty rainfall scenarios with varying rainfall intensities and slope conditions were created in the simulation. The results indicate that the runoff initiation time shortened with an increased rainfall intensity and slope gradient. There was a logarithmic relationship between the effect of the rainfall amount on both the runoff intensity and sediment yield intensity. Generally, both the runoff and sediment yield showed a positive linear relationship with the rainfall intensity under different slope gradient conditions. In terms of the same rainfall intensity, both the runoff intensity and sediment yield intensity increased with the slope. Furthermore, a critical slope gradient for the soil and water loss was found between 20° and 25°. This study aimed to provide a reference for soil and water conservation research in a purple soil area.

The lack of cover is one of the main accelerators of soil degradation. Without protection and exposed to rainfall, the soil breaks the particles, causing surface sealing, making infiltration difficult. This study characterizes surface sealing and hydraulic erosion in Ultisols of the Alto Ipanema Basin. Eight erosion plots were established under the treatments: bare soil and soil with Brachiaria decumbens mulch. Three rain events were simulated at 24-hour intervals, with an intensity of 54.63 mmh-1. After each simulation, the surface micromorphology and the amount of soil lost were investigated. The use of mulch reduced runoff by 42% and the loss of soil and the rate of disaggregation was reduced by 70% on average. Infiltration was increased by 242%. Mulch was effective in preserving soil porosity and microstructure for the first simulated rainfall event (0 h), but was not observed in the second (24 h) and third (48 h) rainfall events.

Reliable estimates of extreme rainfall events are necessary for an accurate prediction of floods. Most of the global rainfall products are available at a coarse resolution, rendering them less desirable for extreme rainfall analysis. Therefore, regional mesoscale models such as the advanced research version of the Weather Research and Forecasting (WRF) model are often used to provide rainfall estimates at fine grid spacing. Modelling heavy rainfall events is an enduring challenge, as such events depend on multi-scale interactions, and the model configurations such as grid spacing, physical parameterization and initialization. With this background, the WRF model is implemented in this study to investigate the impact of different processes on extreme rainfall simulation, by considering a representative event that occurred during 15–18 June 2013 over the Ganga Basin in India, which is located at the foothills of the Himalayas. This event is simulated with ensembles involving four different microphysics (MP), two cumulus (CU) parameterizations, two planetary boundary layers (PBLs) and two land surface physics options, as well as different resolutions (grid spacing) within the WRF model. The simulated rainfall is evaluated against the observations from 18 rain gauges and the Tropical Rainfall Measuring Mission Multi-Satellite Precipitation Analysis (TMPA) 3B42RT version 7 data. From the analysis, it should be noted that the choice of MP scheme influences the spatial pattern of rainfall, while the choice of PBL and CU parameterizations influences the magnitude of rainfall in the model simulations. Further, the WRF run with Goddard MP, Mellor–Yamada–Janjic PBL and Betts–Miller–Janjic CU scheme is found to perform best in simulating this heavy rain event. The selected configuration is evaluated for several heavy to extremely heavy rainfall events that occurred across different months of the monsoon season in the region. The model performance improved through incorporation of detailed land surface processes involving prognostic soil moisture evolution in Noah scheme compared to the simple Slab model. To analyse the effect of model grid spacing, two sets of downscaling ratios – (i) 1 : 3, global to regional (G2R) scale and (ii) 1 : 9, global to convection-permitting scale (G2C) – are employed. Results indicate that a higher downscaling ratio (G2C) causes higher variability and consequently large errors in the simulations. Therefore, G2R is adopted as a suitable choice for simulating heavy rainfall event in the present case study. Further, the WRF-simulated rainfall is found to exhibit less bias when compared with the NCEP FiNaL (FNL) reanalysis data.

This study investigates the influences of urban land cover on the extreme rainfall event over the Zhengzhou city in central China on 20 July 2021 using the Weather Research and Forecasting model at a convection-permitting scale [1-km resolution in the innermost domain (d3)]. Two ensembles of simulation (CTRL, NURB), each consisting of 11 members with a multi-layer urban canopy model and various combinations of physics schemes, were conducted using different land cover scenarios: (i) the real urban land cover, (ii) all cities in d3 being replaced with natural land cover. The results suggest that CTRL reasonably reproduces the spatiotemporal evolution of rainstorms and the 24-h rainfall accumulation over the key region, although the maximum hourly rainfall is underestimated and displaced to the west or southwest by most members. The ensemble mean 24-h rainfall accumulation over the key region of heavy rainfall is reduced by 13%, and the maximum hourly rainfall simulated by each member is reduced by 15–70 mm in CTRL relative to NURB. The reduction in the simulated rainfall by urbanization is closely associated with numerous cities/towns to the south, southeast, and east of Zhengzhou. Their heating effects jointly lead to formation of anomalous upward motions in and above the planetary boundary layer (PBL), which exaggerates the PBL drying effect due to reduced evapotranspiration and also enhances the wind stilling effect due to increased surface friction in urban areas. As a result, the lateral inflows of moisture and high- θ e (equivalent potential temperature) air from south and east to Zhengzhou are reduced.