Rainfall Conditions Research Articles

Characterization of dam failure flooding in an urban reservoir under different rainfall conditions.

In water conservation projects, reservoirs play a key role in controlling and regulating floods. In recent years, extreme rainfall events have occurred more frequently. Urban reservoirs in danger under extreme rainfall happen occasionally. The breaching of urban reservoirs seriously threatens the lives and property of the population downstream. A lack of clarity regarding the characterization of the flooding response remains owing to urban reservoir overtopping under different rainfall conditions. This study used observed data from the heavy rainfall event in Zhengzhou on July 20, 2021, with Jiangang Reservoir in Zhengzhou as the study site. The study designed a storm-flood process with different rainfall scenarios that combines the long-duration rainstorm formula and Chicago rain pattern method, establishing a response relationship between extreme rainfall and flooding processes. Flood evolution simulation analyses were carried out for different scenarios of rainfall and flooding processes under three working conditions: rainfall only, dam failure only and dam failure coupled with rainfall, to characterize the flood response due to dam failure under different rainfall conditions. The results showed that the peak of the rainfall occurs earlier in the total rainfall calendar time, the faster the dam failure rate of the reservoir. As the rain peak occurs at a time that is later in the total rainfall calendar, and the recurrence period and rainfall duration increase, the flood volume increases and urban inundation becomes more severe. The rainfall type had less of an effect on the difference in the extent of inundation between different working conditions. The extent of flood inundation for the dam failure-coupled rainfall scenario is much greater than that for the dam failure only scenario. The increase in inundation extent in the dam failure coupled rainfall scenario at the higher levels of flood severity is smaller. Study results provide hydraulic element support for flood hazard assessment.

Modeling the Effect of Milk Vetch–Rice Rotation on N Runoff Loss in the Middle and Lower Reaches of the Yangtze River

The winter planting of green manure (GM) is widely used in South China to reduce chemical nitrogen (N) fertilizer use, improve soil fertility, and maintain rice yields, but its effect on N runoff loss in paddy fields remains unclear. This study combines multi-site field experiments with a process model (WHCNS-Rice) to assess how GM with reduced N fertilizer impacts N runoff loss and its forms in the Yangtze River’s middle and lower reaches, considering different rainfall years. The network field experiments included four treatments: conventional fertilization (FR), conventional fertilization plus straw return (FRS), GM with a 40% N reduction (MR), and GM-straw combined return with a 40% N reduction (MRS). Monitoring the results showed that compared to the winter fallow treatment, the GM treatments reduced the peak and average total N (TN) concentrations by 11.1–57.9% (average 26.9%) and 17.1–27.3% (average 22.3%), respectively. The TN runoff loss under the GM treatment decreased by 3.50–10.61 kg N ha−1 (22.5–42.1%). GM primarily reduced the runoff loss of dissolved inorganic N (DIN), with reductions at different sites ranging from 0.22 to 9.66 kg N ha−1 (8.4–43.4%), indicating GM effectively decreases N runoff by reducing DIN. Model simulations of ponding water depth, runoff, TN concentration in surface water, and TN loss in paddy fields produced the consistency indices and simulation efficiencies of 0.738–0.985, 0.737–0.986, 0.912–0.986, and 0.674–0.972, respectively, indicating that the model can be used to evaluate water consumption and N runoff loss in the GM-paddy system. The simulations showed that GM with a 40% N fertilizer significantly reduced N runoff loss under all rainfall conditions, with the greatest reductions in wet years. Under wet, normal, and dry conditions, the GM treatments significantly reduced average TN loss by 0.37–5.53 kg N ha−1 (12.77–29.17%), 0.21–5.32 kg N ha−1 (9.95–24.51%), and 0.02–3.2 kg N ha−1 (1.78–23.19%), respectively, compared to the winter fallow treatment. These results indicate that the combination of GM and a 40% reduction in N fertilizer can significantly reduce N runoff loss from paddy fields, demonstrating good effectiveness under various rainfall conditions, making it a green production model worth promoting.

An Analysis of Vertical Infiltration Responses in Unsaturated Soil Columns from Permafrost Regions

Rainfall infiltration affects permafrost-related slope stability by changing the pore water pressure in soil. In this study, the infiltration responses under rainfall conditions were elucidated. The instantaneous profile method and filter paper method were used to obtain the soil–water characteristic curve (SWCC) and hydraulic conductivity function (HCF). During the rainfall infiltration test, the vertical patters of volumetric moisture contents, total hydraulic head or suction and wetting front were recorded. Advancing displacement and rate of the wetting front, the cumulative infiltration, the instantaneous infiltration rate, and the average infiltration rate were determined to comprehensively assess the rainfall infiltration process, along with SWCC and HCF. Additionally, the effects of dry density and runoff on the one-dimensional vertical infiltration process of soil columns were evaluated. The results showed that the variation curve of wetting front displacement versus time obeys a power function relationship. In addition, the infiltration rate–time relationship curve and the unsaturated permeability curve could be roughly divided into three stages, and the SWCC and HCF calculated by volumetric moisture content are more sensitive to changes in dry density than to changes in runoff or hydraulic head height.

Development of a Mexican corn landrace, Northern Conical, under temperature and rainfall conditions predicted by the middle of this century: an experimental field approach

Background: Corn is the most important crop in Mexico, but it can be affected by climate change. Small farmers from arid and semiarid ecosystems mainly use rainfed native landraces with short productive cycles (less than 90 days), which are adapted to elevated temperatures and intense drought. Among these landraces we can find the Norther Conical corn. Hypothesis: As Northern Conical seems to be adapted to arid agroecosystems, we hypothesize that this corn landrace can tolerate the mid-century climate change conditions. Studied species: Zea mays subsp. mays (Poaceae), Northern Conical landrace. Study site and dates: An abandoned agricultural field in San Luis Potosí, central Mexico, between August and October 2022. Methods: In a field experiment, corn seeds were sowed under the conditions of higher temperature and lower rainfall predicted by the middle of this century (period 2041-2060), as well as under the current climate. Emergence and survival of plants were regularly monitored, and their functional responses were measured by the end of the experiment. Results: Northern Conical plants performed better (in terms of emergence, survival, growth rates, and photosynthetic performance) under higher temperature and lower rainfall, as compared with those developed under the current climate. Conclusions: Our results suggest that the Northern Conical corn landrace may tolerate the increases in aridity expected in the short term. However, simulations under contrasting environmental and ontogenetical conditions are needed.

RainForests: A Machine Learning Approach to Calibrating NWP Precipitation Forecasts

Abstract Probabilistic forecasts derived from ensemble prediction systems (EPSs) have become the standard basis for many products and services produced by modern operational forecasting centers. However, statistical postprocessing is generally required to ensure forecasts have the desired properties expected for probability-based outputs. Precipitation, a core component of any operational forecast, is particularly challenging to calibrate due to its discontinuous nature and the extreme skew in rainfall amounts. A skillful forecasting system must maintain accuracy for low-to-moderate precipitation amounts, but preserve resolvability for high-to-extreme rainfall amounts, which, though rare, are important to forecast accurately in the interest of public safety. Existing statistical and machine learning approaches to rainfall calibration address this problem, but each has drawbacks in design, training approaches, and/or performance. We describe RainForests, a machine learning approach for calibrating ensemble rainfall forecasts using gradient-boosted decision trees. The model is based on the ecPoint system recently developed at ECMWF by Hewson and Pillosu, but uses machine learning models in place of the semisubjective decision trees of ecPoint, along with some other improvements to the model structure. We evaluate RainForests on the Australian domain against some simple benchmarks and show that it outperforms standard calibration approaches both in overall skill and in accurately forecasting high rainfall conditions, while being computationally efficient enough to be used in an operational forecasting system. Significance Statement Weather forecasting typically uses physical models to simulate the atmosphere and produce a set of scenarios, called an ensemble, for each forecast time. Forecast calibration is a set of statistical techniques for using these ensemble forecasts to obtain probability forecasts of weather variables. For example, on a given day, we may predict that there are a 90% chance of at least 1 mm of rain and a 50% chance of at least 3 mm. We introduce RainForests, a new machine learning method for calibrating ensemble forecasts, which uses ensemble forecasts of rainfall and other related variables to produce more accurate probability forecasts of rainfall amounts in operational forecasting settings.

Slope stability analysis of unsaturated colluvial slopes based on case studies of rainfall-induced landslides

Landslides in colluvial soils under rainfall have been identified as a significant problem due to their loose, heterogeneous nature and low shear strength. Evaluation of the stability of colluvial slopes under rainfall conditions is challenging. This study investigated two landslide failure case studies of colluvial soils to understand the failure patterns using finite element (FE) and limit equilibrium (LE) slope stability analysis methods under unsaturated conditions. Transient seepage conditions due to rainfall infiltration and failure were analysed using hydromechanical models. Here, a FE fully coupled hydromechanical model and a sequential coupling of a FE hydrological and LE mechanical model were used to evaluate the failure of variably saturated slopes. Results from the case studies revealed that the failure occurred due to the rise in the groundwater table in both cases. It was evident that there can be significant disparities in the pore water pressure profiles with the fully coupled and sequentially coupled analysis. The dynamic capability of the two models can also affect the interplay between the hydrological and mechanical aspects. When the thickness of the colluvium layer is large, the failure could potentially occur as a deep-seated failure along the boundary of overburden and the bedrock surface due to the large driving force. However, when the thickness is small, failure can occur along the colluvium-weathered rock surface. The outcomes from the study will contribute to mitigate the uncertainty of failure prediction of landslides in colluvial soils.

Evaluation of climate conditions and ecological traits that limit the distribution expansion of alien Lolium rigidum in Japan

Invasive alien plants cause severe global problems; therefore, determining the factors that lead to the success or failure of invasion is a critical question in the field of invasion ecology. In this study, we aimed to determine the factors underlying differences in the distribution range of alien plants in Japan by investigating why Lolium multiflorum thrives in a wide range of habitats while L. rigidum is mainly distributed on sandy beaches. We initially evaluated environmental niche suitability through species distribution modelling and subsequently examined whether species traits influence the differences in range expansion between the two species. We used MaxEnt modelling to identify potential environmental niches for both species. The analysis revealed that L. rigidum was considerably less suited to the Japanese climate compared to L. multiflorum, with high summer precipitation in Japan identified as one of the climatic factors limiting the distribution of L. rigidum. Given that these winter annual plants remain dormant as seeds during summer, in subsequent experiments, we buried seeds in paddy field soil and sandy beach sand during summer and evaluated their survival rate in autumn. The survival rate of L. rigidum seeds was significantly lower than that of L. multiflorum, particularly in paddy soil. Factors contributing to seed mortality may include the decay or early germination of L. rigidum seeds under Japan’s high rainfall conditions. This study emphasises the importance of considering local environmental factors alongside climate niche modelling in the risk assessment of invasive species. Moreover, the integration of species distribution modelling for large-scale evaluations and manipulation experiments for fine-scale assessments proved effective in identifying climatic conditions and species traits influencing the success or failure of alien species invasion.

Multi-Source Monitoring and Numerical Simulation Deformation on Highway Steep Slopes Under Rainfall Effects

Rainfall is one of the most important factors affecting slope stability. This study employed multi-source monitoring devices to observe the slope displacements in real time under rainfall infiltration and performed numerical simulations to investigate the effects of different rainfall conditions and anti-slip pile configurations on slope stability. Specifically, multi-source monitoring operations were conducted on the high and steep slopes along the Yunmao Expressway. Real-time data on slope deformation, rainfall, and displacement at the tops of anti-slip piles were collected and analyzed, and numerical simulations were conducted using Geo Studio finite-element software. The findings indicated that abrupt deformation of slopes occurs once a threshold rainfall amount is surpassed and sustained over a specific duration. Slope displacement decreased with increasing slope depth above the potential slip fracture surface, with a more rapid reduction in deformation rates observed in slopes reinforced with anti-slip piles. For equivalent rainfall amounts, short-duration, intense rainfalls led to a rapid decrease in the slope safety factor, which also recovered rapidly once the rainfall ceased, in contrast to long-duration, mild rainfalls. The presence and location of anti-slip piles significantly influenced slope stability; therefore, project implementation should carefully consider factors such as cost and duration for optimal decision making.

A Case Study for Analysis of Stability and Treatment Measures of a Landslide Under Rainfall with the Changes in Pore Water Pressure

Mining causes damage to the soil and rock mass, while rainfall has a pivotal impact on the mining slope stability, even leading to geological hazards such as landslides. Therefore, the study evaluated the mine landslide stability and determined the effectiveness of the treatment measures under the impact of pore water pressure changes caused by rainfall, taking the Kong Mountain landslide in Nanjing, Jiangsu Province, China, as the research object. The geological conditions and deformation characteristics were clarified, and the failure mechanism and influencing factors were analyzed. Also, the landslide stability was comprehensively evaluated and calculated utilizing the finite element-improved limit equilibrium method and FLAC 3D 6.0, which simulated the distribution of pore water pressure, displacement, etc., to analyze the influence of rainfall conditions and reinforcement effects. The results indicated the following: (1) Rainfall is the key influencing factor of the landslide stability, which caused the pore water pressure changes and the loosening of the soil due to the strong permeability; (2) The distribution of the pore water pressure and plastic zone showed that, during the rainfall process, a large area of transient saturation zone appeared at the leading edge, affecting the stability of the whole landslide and led to the further deformation; (3) After the application of treatment measures (anti-sliding piles and anchor cables), the landslide stability increased under both natural and rainfall conditions (from 1.02 and 0.94 to 1.38 and 1.31, respectively), along with a reduction in displacement, plastic zones, etc. The Kong Mountain landslide, with the implemented treatment measures, is in good stability, which is in line with the evaluation and calculation results. The study provides certain contributions to the stability evaluation and treatment selection of similar engineering under rainfall infiltration.

Dynamic Analysis and Hazard Assessment of Debris Flows in Donghaolitaogao

Utilizing the FLO-2D software, the motion processes of debris flows in Donghaolitaogao under 20-year, 50-year, and 100-year return periods of rainfall are analyzed, revealing that as the rainfall return period increases, the debris flow velocity, accumulation depth, and accumulation area all significantly expand. Specifically, under the 20-year, 50-year, and 100-year rainfall conditions, the maximum debris flow velocities are 1.85 m/s, 1.95 m/s, and 1.99 m/s, respectively, while the maximum accumulation depths are 1.31 m, 1.33 m, and 1.35 m, and the total accumulation areas are 27,267.8 m2, 31,500.6 m2, and 33,901.3 m2, respectively. Using the depth of debris flow and the product of debris flow depth and velocity as evaluation indicators, the debris flow hazard assessment indicates that the Donghaolitaogao debris flow is primarily characterized by low- and medium-risk areas, with high-risk areas scattered sporadically along the central part of the channel. Moreover, as the rainfall return period increases, the area of high-risk zones continues to expand, gradually accounting for a larger proportion of the total hazard zone.

Risk assessment of urban infrastructure vulnerability to meteorological disasters: A case study of Dongguan, China

Effective forecasting and response to meteorological hazards are crucial for safeguarding life, property, and supporting sustainable socioeconomic development. With the rising frequency and severity of meteorological hazards worldwide, this study proposes an enhanced risk assessment framework for urban infrastructure exposed to extreme weather events, with a focus on cascading impacts to critical services such as electricity, communication, and transportation networks (roads and subways). A disaster-loss model is developed to quantify infrastructure vulnerability at various spatial and temporal scales under heavy rainfall conditions, accounting for secondary effects. The model's performance is validated through empirical analysis of a 15-year rainfall event in Dongguan City, China, occurring from September 7–8, 2023. Results indicate the model's ability to predict real-event outcomes with approximately 70% accuracy. This model offers valuable insights for disaster prevention and mitigation strategies, aiding decision-makers in optimizing emergency resource allocation, enhancing disaster response efficiency, and issuing timely public risk warnings to minimize losses.

Risk of rainfall caused leaching from bio-composite material based building façades into the aquatic environment

The increasing focus on sustainability and circularity is driving the global production of environmentally friendly products. The Netherlands started producing new bio-composite materials which are created by reclaiming resources from various sectors of the water industry. These materials can be used for a variety of applications including façade elements in buildings. However, their potential environmental impact, particularly with regard to leaching of potentially harmful substances into surface water, necessitates further evaluation. To address this issue, a systematic environmental risk assessment methodology combined with novel experimental data is presented here. To collect this data, façade panels made of two different bio-composite materials were first subjected to a series of laboratory tests, including analysis in both new and weathered forms, the latter subject to a cyclic UV radiation and high humidity, in order to simulate the effects of aging. Leaching tests were then conducted to determine the potential release of specific chemical substances such as heavy metals and resin compounds, under two different rainfall conditions (every day and more extreme). The data generated this way was used to perform the risk assessment using the existing European ERA framework. The results obtained reveal different leaching behaviour of the new and weathered samples, as well as between the two analysed bio-composite materials, depending on the rain intensity. To overcome the uncertainties caused by the limited input data, a sensitivity analysis was carried out whereby leaching concentrations and rainfall intensities were varied and their influence on the environmental risk was assessed. The results obtained demonstrated that, despite some variability, both materials appear safe to use, i.e., with estimated risks below the established safety threshold. While these findings provide a preliminary indication, they are based on laboratory conditions and assumptions hence further field studies are recommended to obtain more definitive conclusions.

Reinforcement Learning Algorithm for Optimising Durian Irrigation Systems: Maximising Growth and Water Efficiency

This study presents a Reinforcement Learning-based algorithm designed to optimise irrigation for Durio Zibethinus (i.e., durian) trees, aiming to maximise tree growth and reduce water usage. Traditional irrigation methods, as well as current machine learning models, often focus only on soil moisture and weather data, neglecting critical factors like actual tree growth. This study proposed a reinforcement learning irrigation (RL-Irr) algorithm incorporating tree growth stages, soil moisture, and weather conditions to determine precise irrigation needs. The algorithm was developed by calibrating the AQUACROP model using data from actual durian plantations where rain-fed irrigation (rain-fed) was practised. Daily irrigation volumes were calculated based on real-time soil moisture, weather forecasts, and weekly tree growth measurements. The reinforcement learning method was used to optimise irrigation schedules, with rewards based on soil moisture, tree growth, rainfall, and weather conditions. The algorithm was tested using AQUACROP simulations and compared against soil moisture balance irrigation (SMB-Irr) and rain-fed. The results showed that the RL-Irr reduced water use by up to 75 percent while maintaining tree growth. These findings suggest the algorithm could significantly improve water efficiency in durian farming, though real-world applications should consider potential model limitations.

Establishing Climate Change on Rainfall Trend, Variation and Change Point Pattern in Umuahia, Nigeria

This study investigates the prevailing conditions of changing climatic trends and change point dates in Umuahia, Nigeria, using daily annual maximum series (AMS) rainfall data spanning 31 years. The Indian Meteorological Department (IMD) was employed to downscale the time series data into durations ranging from 5 minutes to 24 hours. Mann-Kendall (MK) trend and Sen's Slope Estimator (SSE) tests revealed a statistically significant increasing trend across all durations. The Sen's Slope magnitude ranged from 0.1373 mm/year for 5-minute duration to 0.9045 mm/year for 24-hour duration, corresponding to a variation rate of 9.05 mm/decade for the 24-hour duration. Trend change-point analysis, utilizing Distribution-free CUSUM and Sequential Mann-Kendall tests, identified 2002 as the initial rainfall change-point date. These results provide robust evidence of positive changing climatic conditions for rainfall in Umuahia, indicating that non-stationary Intensity-Duration-Frequency (IDF) modelling may be more appropriate for flood risk management and urban planning in this area.

Spatial Distribution, Leaching Characteristics, and Ecological and Health Risk Assessment of Potential Toxic Elements in a Typical Open-Pit Iron Mine Along the Yangzi River

Potential toxic elements (PTEs) pollution in the soil of abandoned open-pit mines can lead to great ecological risk to the areas around the mining districts. This study selected a typical abandoned open-pit iron mine along the Yangzi River in southeast China to investigate the spatial distribution, leaching characteristics, and ecological and health risk of the soil PTEs (As, Pb, Cd, Ni, Cr, Cu, and Zn). Leaching tests and sequential extraction were applied to study the migration of PTEs under the condition of rainfall. Different risk assessment methods were used to analyze the pollution and ecological risk of PTEs. The contents of As and Cu exceeded the background value of the Chinese soil guideline, with average contents of 50.71 ± 1.59 and 197.47 ± 16.09, respectively. The leaching test and sequential extraction indicated that sites 8 and 9 posed the greatest risk of PTE migration. According to the map of the Nemerow integrated pollution index (NIPI), the pollution level of the middle bare area of the study area was the highest, and Cu possessed the highest pollution index (PI) of 3.92. The average geo-accumulation index (Igeo) of As and Cu was between 1 and 2, reaching the pollution level of moderately contaminated. The average potential ecological risk coefficient (Ei) of As was the highest, and the contributions of As, Cu, and Cd to the potential ecological risk of the whole study area were 46.7%, 29.7%, and 14.3%, respectively. The range of the hazard index (HI) and the range of the As carcinogenic risk (CRAs) of all the sampling sites for children were 1.30–3.94 and 2.19 × 10−4–7.20 × 10−4, and As accounted for more than 85% of the total noncarcinogenic risk, indicating that the comprehensive pollution of PTEs in the study area posed great carcinogenic and noncarcinogenic risks to children. This study can be a proper reference for the subsequent recovery methods and environmental management of the whole mining area.

Evaluation of the Antecedent Saturation and Rainfall Conditions on the Slope Failure Mechanism Triggered by Rainfalls

The stability analysis of rainfall-induced slope failures considers a number of factors including the characteristics of the rainfall, vegetation, geometry of the slope, unsaturated soil characteristics, infiltration capacity, and saturation degree variations. Amongst all these factors, this study aims to investigate the effects of the antecedent rainfall and saturation conditions. A numerical modeling study was conducted using finite difference code software on a representative slope geometry with two different soil types. Two scenarios were followed: The first involved the application of three different rainfall intensities for varying initial saturation levels between 40% and 60%, representing the antecedent saturation conditions. The second scenario involved modeling successive rainfalls for a typical initial saturation degree of 50%. The impact of antecedent rainfall was assessed by determining the time required for failure during the application of a main extreme rainfall after a preceding rainfall of varying durations. Consequently, a zone of susceptible time for failure was suggested for use as a criterion in hazard management, allowing for the tracking of rainfall and its duration through the proposed chart for potential failures. Once the anticipated critical rainfall intensities have been determined through a meteorological analysis, a risk assessment for a specific slope can be conducted using the proposed practical procedure. Accordingly, a control mechanism may be established to detect the potential for a natural hazard. Furthermore, the proposed procedure was applied to a case study, whose modeling insights were in harmony with the real conditions of the slope failure. Thus, this demonstrated the significance of the antecedent conditions in modeling landslides triggered by rainfalls.

Hydromechanical behaviour of a slope reinforced by grass roots under rainfall conditions

Soil bioengineering using vegetation has been considered an environmentally friendly solution to improve slope stability. Although several studies have demonstrated the contribution of vegetation to slope stability, a gap in understanding the mechanisms of grass root–soil interactions under rainfall conditions remains. This study investigates the effects of the roots of vetiver grass (Chrysopogon zizanioides) on the hydromechanical behaviour of an unsaturated soil slope using the centrifuge modelling technique. The changes in pore water pressure and slope deformation were monitored during the test. The monitored data were subsequently back-analysed and interpreted using seepage–stability analyses. In addition, this study focused on evaluating the effect of roots on slope stability, considering safety and pore water pressure during rainfall. Results revealed that the vetiver roots remarkably affected the initial suction of the slope by increasing the soil's air-entry value. The increased suction and the additional cohesion provided by the roots enhanced slope stability under rainfall conditions.

Spatio-temporal characteristics of rainfall and drought conditions are using the different drought indices with geospatial approaches in Karnataka state

Karnataka state drought conditions are assessed via drought indices. Over the past several decades, several indices of drought (DI) have been developed and presented, although some of them are region-specific and have problems regarding their applicability to other climatic circumstances. Additionally, choosing the best DI time step to illustrate the drought condition is difficult because of the DIs' various time steps. The study compares the Standardized Precipitation Index (SPI), Statistical Z-Score, China Z-Index (CZI), Rainfall Anomaly Index (RAI), and Rainfall Departure (RD) to determine which one is most appropriate for the districts of the Karnataka state that are prone to both dry and rainy conditions. This study has pointed out that the best drought indices are SPI and RD, and the least accountable drought indice is China Z index. Droughts were most common in 22 districts in 2009, which represent around 70.97% of the state's landmass. In comparison with the rest of the districts, the Ramanagara district noticed the worst drought conditions in 2003, with rainfall reaching 92.47 mm and SPI -3.68, RAI-6.04, MCZI -2.39, and Z score −2.62. Overall, the results of the study will aid in the organization and improvement of drought, flood, agriculture, and water resource management approaches in the state.

Effects of Different Land Uses and Slope on Runoff and Soil Loss on the Loess Plateau of China

ABSTRACTThe Loess Plateau has one of the most serious areas of soil erosion in China; therefore, studying the effect of soil and water conservation measures on the erosion of loess soil slopes is important for land management and agricultural development. This study is based on 5 years of field runoff observations and rainfall data from 2015 to 2019. Correlation and regression analyses were used to study the runoff and sediment production of loess soil and its relationship with rainfall, slope and land use. The results show that > 80% of the erosive rainfall occurs mainly in July to August in the area. Runoff and soil loss from the plots differed substantially, depending on land use, soil conservation measures and slope degree. Bare plots experienced the highest soil loss rate of over 27 t/ha with higher runoff depth, followed by cultivated plots (4.55 t/ha), grass plots (0.43 t/ha), shrub plots (0.35 t/ha) and forest plots (0.13 t/ha). Among the four soil and water conservation measures, the runoff and sediment reduction benefits of forest and shrub plots were the highest. The runoff reduction benefit fluctuated at approximately 0.8, and the benefit of sediment reduction was ≈1. The overall performance was forest > shrubland > grassland > cultivated land > bare land, and the benefits of sediment reduction were greater than those of runoff reduction. Forests had the highest soil retention capacity on slopes from 5° to 25°, and forests on gentle slopes had the best water storage capacity. Shrub plots had the best water storage capacity when they were on steep slopes. Rainfall erosion forces were significantly and positively correlated (p < 0.01) with runoff depth and soil loss, making it the most significant rainfall indicator of sediment production. Under the same rainfall conditions, soil and water conservation measures are still required on bare slopes, land use is the main control factor for slope sediment production, and appropriate land use can greatly reduce the threat of slopes in terms of soil erosion. This study shows that soil and water conservation measures are imperative to prevent runoff and soil loss, especially for bare land without any measures; on steep slopes, a vegetation combination primarily featuring shrubs is expected to achieve greater benefits in reducing runoff and sediment. This study can provide a scientific basis for the management of vegetation measures and the implementation of soil and water conservation measures on loess soil slopes.

Laboratory Model Tests on the Deformation and Failure of Terraced Loess Slopes Induced by Extreme Rainfall

Heavy rainfall is the main factor inducing the failure of loess slopes. However, the failure mechanism and mode of terraced loess slopes under heavy rainfall have not been well investigated and understood. This paper presents the experimental study on the deformation and failure of terraced loess slopes with different gradients under extreme rainfall conditions. The deformation and failure processes of the slope and the migration of the wetting front within the slope during rainfall were captured by the digital cameras installed on the top and side of the test box. In addition, the mechanical and hydrological responses of the slope, including earth pressure, water content, pore water pressure, and matric suction, were monitored and analyzed under rainfall infiltration and erosion. The experimental study shows that the deformation and failure of terraced loess slopes under heavy rainfall conditions exhibit the characteristic of progressive erosion damage. In general, the steeper the slope, the more severe the deformation and failure, and the shorter the time required for erosion failure. The data obtained from sensors embedded in the slope can reflect the mechanical and hydraulic characteristics of the slope in response to rainfall. The earth pressure and pore water pressure in the slope exhibit a fluctuating pattern with continued rainfall. The failure mode of terraced loess slopes under extreme rainfall can be summarized into five stages: erosion of slope surface and formation of small gullies and cracks, expansion of gullies and cracks along the slope surface, widening and deepening of gullies, local collapse and flow-slip of the slope, and large-scale collapse of the slope. The findings can provide preliminary data references for researchers to better understand the failure characteristics of terraced loess slopes under extreme rainfall and to further validate the results of numerical simulations and analytical solutions.