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Effective prediction of runoff is a substantial feature for the successful management of hydrological phenomena in arid regions. The present research findings reveal that a rainfall simulator (RS) can be a valuable instrument to estimate runoff as the intensity of rainfall is modifiable in the course of an experimental process, which turns out to be of great advantage. The rainfall-runoff process is a complex physical phenomenon caused by the effect of various parameters. In this research, a new hybrid technique integrating PSR (phase space reconstruction) with FFA (firefly algorithm) and SVM (support vector machine) has gained recognition in various modelling investigations in contrast to the principle of empirical risk minimization through ANN practices. Outcomes of SVM are contrasted against SVM-FFA and PSR-SVM-FFA models. The improvements in NSE (Nash–Sutcliffe efficiency), RMSE (Root Mean Square Error), and WI (Willmott's Index) by PSR-SVM-FFA over SVM models specify that the prediction accuracy of the hybrid model is better. The established PSR-SVM-FFA model generates preeminent WI values that range from 0.97 to 0.98, while the SVM and SVM-FFA models encompass 0.93–0.95 and 0.96–0.97, respectively. The proposed PSR-SVM-FFA model gives more accurate results and error limiting up to 2–3%.

Dripping rainfall simulators are important instruments in soil research. However, a large number of non-standardized simulators have been developed, making it difficult to combine and compare the results of different studies in which they were used. To overcome this problem, it is necessary to become familiar with the design and performances of the current rainfall simulators. A search has been conducted for scientific papers describing dripping rainfall simulators (DRS) and papers that are thematically related to the soil research using DRS. Simulator design analysis was performed integrally, for simulators with more than one dripper (DRS>1) and with one dripper (DRS=1). Descriptive and numerical data were extracted from the papers and sorted by proposed categories, according to which the types and subtypes of used simulators are determined. The six groups of elements that simulators could consist of have been determined, as well their characteristics, representation and statistical analyses of the available numerical parameters. The characteristics of simulators are analyzed and presented, facilitating the selection of simulators for future research. Description of future simulators in accordance to the basic groups of simulator elements should provide all data necessary for their easier replication and provide a step closer to the reduction of design diversification and standardization of rainfall simulators intended for soil research.

The most important properties affecting the soil loss and runoff were investigated, and the effects of land use on the soil properties, together with the erodibility indices in a semiarid zone, central Iran, were evaluated. The locations of 100 positions were acquired by cLHS and 0–5-cm surface soil layer samples were used for laboratory analyses from the Borujen Region, Chaharmahal-Va-Bakhtiari Province, central Iran. To measure in situ runoff and soil erodibility of three different land uses comprising dryland, irrigated farming, and rangeland, a portable rainfall simulator was used. The results showed that the high variations (coefficient of variation, CV) were obtained for electrical conductivity (EC), mean weight diameter (MWD), soil organic carbon (SOC), and soil erodibility indices including runoff volume, soil loss, and sediment concentration (CV ~ 43.6–77.4%). Soil erodibility indices showed positive and significant correlations with bulk density and negative correlations with SOC, MWD, clay content, and soil shear strength in the area under investigation. The values of runoff in the dryland, irrigated farming, and rangeland were found 1.5, 28.9, and 58.7 cm 3 ; soil loss in the dryland, irrigated farming, and rangeland were observed 0.25, 2.96, and 76.8 g; and the amount of sediment concentration in the dryland, irrigated farming, and rangeland were found 0.01, 0.11, and 0.15 g cm −3 . It is suggested that further investigations should be carried out on soil erodibility and the potential of sediment yield in various land uses with varying topography and soil properties in semiarid regions of Iran facing the high risk of soil loss.

Rainfall simulators represent often-used equipment for soil research. Depending on their performance, they could be appropriate for some soil research or not. The aim of this research is to provide insight into the capabilities of existing dripping rainfall simulators (DRS) to mimic natural rainfall and the frequency of simulated rainfalls of certain characteristics, facilitate the selection of rain simulators that would best meet the needs of soil research and to reach a step closer to the standardization of rainfall simulators. DRS performance was analyzed integrally, for simulators with more than one dripper (DRS>1) and with one dripper (DRS=1). A statistical analysis was performed for the performance of the DRS, wetted area, drop size, rainfall intensity, duration and kinetic energy. The analysis showed that DRS can provide rainfall that corresponds to natural rainfall, except in terms of the drop size distribution and wetted area. However, usually there are more factors that do not correspond to natural rainfall, such as the median drop size, volume and kinetic energy. Metal and plastic tubes (MT and PT) as the most present dripper types showed a strong relation between the outer diameter (OD) and drop size, while the inner diameter (ID) relation was moderate-to-weak. However, when increasing the range of MT drippers, for diameter size, the relation significance becomes very strong for bouts ID and OD. With the increase in the ID of PT, the relation deviates from the logarithmic curve that represents all drippers together. The sizes of the drops generated by the drippers are mostly in the range between 2 and 6 mm, while the number of drops smaller than 2 mm is relatively small. The intensity and duration of the simulated rain can be successfully produced to match natural values, with the most frequently simulated short-term rainfall of a high intensity. Most simulations were conducted at a fall height of up to 2 m, and then their number gradually decreases as the height gets closer to 5 m. Most simulations (58.6%) occur in the range between 20-90% KE, then 33.0% in a range of 90-100%, with only 8.4% lower than 20% KE.

Rainfall frequency and intensity are expected to increase in the Arctic, with potential detrimental impacts on permafrost, leading to enhanced thawing and carbon release to the atmosphere. However, there have been very few studies on the effect of discrete rain events on permafrost in the Arctic and sub-Arctic. Conducting controlled rainfall experiments within permafrost landscapes can provide an improved understanding of the effect of changing intensity, duration, and timing of rain events on permafrost tundra ecosystems. Here, we describe the design and implementation of the Next-Generation Ecosystem Experiment Arctic Rainfall Simulator (NARS), a variable intensity (4–82 mm/h) rainfall simulator that can be used to study the effects of rainfall on permafrost stability. The NARS design includes a 3D-printed 4 cm H-flume and uses an eTape resistivity sensor that was calibrated (R2 = 0.9–0.96) to measure discharge from the system. NARS is designed to be lightweight, simple to construct, and can be easily deployed in remote locations. As a field validation of updated rainfall simulator design and modernized controls, NARS was tested on the Seward Peninsula, AK. Because of its portability, versatility in deployment, dimensions, and rainfall intensity, NARS represents a methodological innovation for researching the impacts of rainfall on permafrost environments.

Rainfall simulators are essential tools in soil research, providing a controlled and repeatable approach to studying rainfall-induced erosion. However, the development of high-fidelity rainfall simulators remains a challenge. This study aimed to design, construct, and calibrate a spraying-type rainfall simulator and validate assessment criteria optimized for soil erosion research. The simulator’s design is based on a modified simulator model previously described in the literature and following the defined criteria. The calibration of the simulator was conducted in two phases, on slopes of 0° and 15°, measuring rainfall intensity, drop size, and its spatial distribution, and calculating drop falling velocity, kinetic energy, and momentum. The simulator consists of structural support, a water tank, a water-moving mechanism, a flow regulation system, and sprayers, contributing to its simplicity, cost-effectiveness, durability, rigidity, and stability, ensuring smooth simulator operation. The calibration of the rainfall simulator demonstrated that rainfall intensity increased from 1.4 mm·min−1 to 4.6 mm·min−1 with higher pressure in the hydraulic system (1.0 to 2.0 bar), while spatial uniformity remained within 79–91% across different nozzle configurations. The selected Rain Bird HE-VAN series nozzles proved highly effective in simulating rainfall, achieving drop diameters ranging from 0.8 mm to 1.9 mm, depending on pressure and nozzle type. The rainfall simulator successfully replicates natural rainfall characteristics, offering a controlled environment for investigating soil erosion processes. Drop velocity values varied between 2.5 and 2.9 m·s−1, influencing kinetic energy, which ranged from 0.6 J·min−1·m−2 to 2.9 J·min−1·m−2, and impact momentum, which was measured between 0.005 N·s and 0.032 N·s. The simulator design suggests that it is suitable for future applications in both field and laboratory soil erosion research, ensuring repeatability and adaptability for various experimental conditions. Calibration results emphasized the significance of nozzle selection and water pressure adjustments. These factors significantly affect rainfall intensity, drop size, kinetic energy, and momentum, parameters that are critical for accurate erosion modeling.

In the Czech Republic, the Universal Soil Loss Equation provides the basis for defining the soil protection strategy. Field rainfall simulators were used to define the actual cover-management factor values of the most extensively seeded crops in the Czech Republic. The second purpose was to assess rainfall-runoff ratio for different crops and management to contribute to the debate of water retention effectiveness during approaching climate change. The methodology focused on multi-seasonal measurements to cover the most important phenological phases. The rainfall intensity was 60 mm·h−1 for 30 min and a plot size of 16 m2. More than 380 rainfall simulation experiments provided data. Soil conservation techniques proved to have a significant effect on runoff reduction. Conventionally seeded maize can reduce the runoff ratio to around 50%. However, cover crops combined with reduced tillage or direct seeding can reduce the runoff ratio to 10–20% for ‘dry’ conditions and to 12–40% for ‘saturated’ conditions. Conventionally seeded maize on average loses 4.3 Mg·ha−1 per 30 min experiment. However, reduced tillage and direct seeding reduce soil loss to 0.6 and 0.16 Mg·ha−1, respectively. A comparison with the original USDA values for maize showed that it is desirable to redefine the crop cover factor.

Mitigating soil erosion‘s effects have been prioritized since the early 20th century. Rainfall simulators and analytical prediction models are used to determine soil erosion susceptibility. This study used different methodologies to measure soil erodibility in two hydrographic sub-basins, the Renato and Caiabi, in the Middle and Upper Teles Pires River in Mato Grosso state, Brazil. The rainfall simulator showed a higher range of K-factor values for the Renato sub-basin of 0.0009 to 0.0086 Mg × h × (MJ × mm)−1 and a lower range of K-factor values for the Caiabi sub-basin of 0.0014 to 0.0031 Mg × h × (MJ × mm)−1. Soil loss equations similarly estimated a higher range of K-factor values for the Renato of 0.0008 to 0.0990 Mg × h × (MJ × mm)−1 and a lower range of K-factor values for the Caiabi of 0.0014 to 0.0846 Mg × h × (MJ × mm)−1. There was no significant difference at the 5% level for the K factor determined by the rainfall simulator for both sub-basins. Equations specified in Bouyoucos (1935) and Lombardi Neto and Bertoni (1975) showed significant correlation (5%) for farming systems in the Caiabi sub-basin. Indirect methodologies that performed well for correlation were equations 2 and 3 from Roloff and Denardin (1994), which use iron and aluminum as parameters. Soil erosion was most influenced by physical texture parameters of the region’s soil.

Rainfall simulators are important pieces of equipment to investigate hydrological processes and soil erosion. Here, we investigated the operational characteristics, the rainfall characteristics, and the soil erosion process under collecting plots and rainfall patterns using the InfiAsper simulator. We evaluated the standard plot of the simulator in a rectangular shape (1.0 × 0.7 m), as well as a circular plot (0.8 m diameter), and four precipitation patterns, characterized as advanced (AV), intermediate (IN), delayed (DL), and constant (CT). In the laboratory, uniformity and water consumption tests were carried out for shutter-disk rotations from 138 to 804 rpm, and in the field, simulated rains were applied on a Dystric Acrisol. Rains with different patterns were simulated and presented a uniformity coefficient above 83% for the circular plot and 78.2% for the rectangular plot. The soil erosion varied as a function of the precipitation patterns and, to a lesser extent, according to the shape of the experimental plot. However, runoff and soil loss in AV were 2.1 and 3.5 times greater when using a circular plot. Concerning IN and DL, the length of the rectangular plot may have influenced the formation of small furrows throughout most of the simulated rainfall event, providing greater runoff (13.1 mm) and soil loss (13.6 g m−2). The results obtained are promising, but plots with different shapes associated with rainfall patterns simulated by InfiAsper must be evaluated in other classes and soil use and cover conditions.

This study derives an empirical equation to determine the rainfall threshold that triggers landslides and subsequent debris flows. In this research, the contribution of different factors, especially various sediment layer thicknesses, was assessed on the landslide leading to debris flows. Bed slope, sediment thickness, sediment mean diameter, sediment layer length, rainfall intensity, and time of landslide occurrence were selected as the effective factors. Rainfall simulator device was used to create rainfall on the sediment sample. The effect of these factors on the landslide which leads to debris flow occurrence was investigated using dimensional analysis of experimental data. Then, linear and power regression models were tested by 30% of the total experimental data to estimate the rainfall-induced landslide. Determination coefficient (R2), mean absolute relative error (MARE), and Akaike information criterion (AIC) were applied to determine the best equation. Results revealed that landslide often occurs at a rapid rate in the thicker deposits than the thinner one. The evaluation of linear and power equations demonstrated that two-variable power model was the best empirical equation for estimation of rainfall threshold in initiation of landslide and debris flows. The evaluation criteria including MARE, R2, and AIC were estimated 0.044, 0.984, and − 25.93, respectively. In this equation, bed slope and the ratio of the time of landslide occurrence to the sediment layer length were used as the effective factors. This study can be used for assessment of the threshold of rainfall-induced landslide which finally leads to debris flow hazard.