Rainfall Erosivity Research Articles

Analisis Tingkat Erosi Menggunakan Metode USLE di Kapanewon Panggang Kabupaten Gunungkidul Daerah Istimewa Yogyakarta

One of the causes of critical land is erosion; the greater the intensity of erosion, the more critical the land becomes. The distribution of erosion predictions is influenced by variables such as rainfall erosivity, soil erodibility, slope length and steepness, ground cover vegetation, land use, and land conservation. One of the critical lands is located in Kapanewon Panggang, Gunungkidul Regency, Special Region of Yogyakarta, covering an area of 9130.01 hectares, which consists of six villages: Giriharjo, Girisuko, Giriwungu, Girimulyo, Girikarto, and Girisekar. The purpose of this study is to determine the erosion rate in Kapanewon Panggang, to assess the level of erosion hazard in Kapanewon Panggang, and to formulate a land management concept based on actual land use conditions with erosion criticality parameters in Kapanewon Panggang, Gunungkidul Regency, Special Region of Yogyakarta. The method used is the USLE (Universal Soil Loss Equation). USLE is an erosion model designed to predict long-term erosion from sheet or rill erosion under specific conditions. USLE is used on both agricultural and non-agricultural lands. The results show that the erosion hazard levels in Kapanewon Panggang are categorized as very light (1184.28 hectares), light (1074.65 hectares), moderate (1831.70 hectares), severe (2411.01 hectares), and very severe (2628.38 hectares). The factors that most influence the magnitude of erosion are land use, slope length, and steepness. The land management concept to minimize erosion can be implemented based on land cover, namely in residential areas where water infiltration areas are needed, in savanna land use where additional vegetation and ground cover plants are necessary, and based on slope length and steepness, mechanical conservation by constructing bench terraces and stone bunds should be applied.

Soil erosion estimation and risk assessment based on RUSLE in Google Earth Engine (GEE) in Turkiye

ABSTRACT Soil erosion is a critical challenge threatening agricultural productivity and environmental sustainability globally. This study presents the first estimation of water-induced soil loss in Ordu province, Turkey, using the Revised Universal Soil Loss Equation (RUSLE) integrated with Google Earth Engine (GEE) and Geographic Information System (GIS) technologies. Our analysis provides spatial insights into erosion patterns across the region, revealing that soil loss rates range from 0–5 t/ha/yr in stable areas to over 200 t/ha/yr in severely eroded regions. The mean soil loss rate is estimated at 12.58 t/ha/yr. The study identified the LS factor (slope length and steepness) as the most significant contributor to soil erosion, followed by the R factor (rainfall erosivity). These findings offer valuable insights into soil erosion dynamics, supporting sustainable soil management practices and informing erosion control strategies. The results contribute to land use planning and policy development aimed at mitigating soil degradation and enhancing agricultural resilience in Ordu province.

Soil erosion susceptibility maps and raster dataset for the hydrological basins of North Africa

Soil erosion in North Africa modulates agricultural and urban developments as well as the impacts of flash floods. Existing investigations and associated datasets are mainly performed in localized urban areas, often representing a limited part of a watershed. The above compromises the implementation of mitigation measures for this vast area under accentuating extremes and continuous hydroclimatic fluctuations. To address this deficiency, we use the Revised Universal Soil Loss Equation to map surface erosion, providing the first insight into the decadal impacts of land degradation, which are largely unconstrained on North Africa’s continental scale. We generate soil erosion maps for the major hydrological basins of North Africa using Google Earth Engine and multiple hydroclimatic and land use datasets, covering 5.8 million square kilometers. The generated geospatial dataset integrates land use, soil erodibility, slope, vegetation cover, and land practices. The resulting product is an expansive and publicly available Soil erosion susceptibility maps and rasters dataset (SESMAR). This dataset is a crucial step toward understanding the drivers of soil erosion in this vast, poorly characterized area as well as its potential to be used for future soil conservation campaigns for both agricultural and urban planning. We validate SESMAR using the Global Rainfall Erosivity Database (GloREDa) and the European Soil Data Centre (ESDAC) datasets as well as published peer-reviewed reports across 20 watersheds, demonstrating a robust agreement in assessing the average annual soil loss values and soil erosion classes in local areas covered by independent study teams. Our continental maps show commendable accuracy, supporting scientists, practitioners, and policymakers in their efforts for more resilient land management practices across North Africa to mitigate rising hydroclimatic extremes.

CHIRPS contribution data in studying rainfall erosion in Oued Kert Watershed (Eastern Rif, Morocco)

CHIRPS contribution data in studying rainfall erosion in Oued Kert Watershed (Eastern Rif, Morocco)

Development of Simplified Relationship between Rainfall Erosion Indices and Precipitation Indices for Soil Conservation in Hisar, Haryana, India

Soil erosion is the functional ability of rainfall to detach the soil particles and simultaneously the susceptibility of soil to resist against raindrop. In this study, an effort was made to develop a relationship between erosion indices and precipitation indices for the study area. The rainfall data of 16 years for the selected durations of 15-60 minute storms was analyzed to evaluate the erosion potential. A highly significant linear correlation was observed between erosion index (EI) and precipitation index (PI) values computed for the durations of 15, 30, 45 and 60 minutes. The obtained correlation coefficient (r) was varied from 0.97 to 0.99. The precipitation index (PI30) for 30 minutes duration also showed significant linear correlation with precipitation index PI15, PI45 and PI60 minutes duration. The equations so developed could be used for the computation of erosion index (EI) values for Hisar region by substituting the corresponding values of precipitation index (PI) as independent variable and without going through the tedious process of computation of kinetic energy. The results could provide a quick idea on erosion potential for planning the general purpose soil and water conservation measures in the study area.

Quantification of soil losses using RUSLE model in the Boumlal watershed (Central Rif, Morocco)

This contribution estimates soil losses in the Boumlal watershed by applying the Revised Universal Soil Loss Equation (RUSLE) and using GIS and remote sensing. This model incorporates five essential factors in water erosion: rainfall erosivity (R), soil erodibility (K), slope length (LS), cover management (C), and erosion control practice (P). The overlay of these parameters makes it possible to produce the synthetic map of annual soil losses (t/ha/year) and identify the most vulnerable areas to water erosion. The results indicate that Boumlal watershed is characterized by high sediment production. Indeed, more than 40% of the watershed produces a considerable amount of sediment exceeding 50 t/ha/year, with soil losses reaching over 200 t/ha/year in some parts of the study area. However, areas with low erosion rates represent approximately 33% of the total watershed area. The extent of water erosion and the high soil loss values are linked to the study area's vulnerability and inadequate anthropogenic interventions. Water erosion in this watershed directly affects soil quality, agricultural land productivity, arable land area, and the siltation of downstream reservoirs.

Preparation and performance evaluation of an efficient microbial dust suppressant for dust control in disturbed areas of blast piles in open-pit coal mines.

Open-pit coal mining creates large rock piles as a result of removing overlying strata. When disturbed by loading operations and wind, these rock piles release considerable dust, leading to significant environmental pollution. This study aims to develop an environmentally friendly and cost-effective method for dust control in disturbed areas of open-pit coal mines, using Sporosarcina pasteurii as a microbial dust suppressant to explore its potential application and development. Laboratory experiments were conducted to simulate the growth characteristics of Sporosarcina pasteurii in the microenvironment of blast pile dust. The effectiveness of the microbial dust suppressant was evaluated under conditions of impact disturbance and rainfall erosion through wind and rain erosion tests. Results showed that under optimal conditions, the wind erosion resistance of treated samples improved significantly, with an increase of 98.24%, 86.99%, 64.08%, and 40.98% after 1, 2, 3, and 4 impact disturbances, respectively. Additionally, rain erosion resistance improved by 75.55% after 35min of simulated rainfall. The growth conditions of Sporosarcina pasteurii in blast pile dust leachate were similar to those in sterile water, demonstrating robust growth and consistent urease activity of 7.78mmolL⁻1min⁻1 after 24h. The mineralization product was calcite-type CaCO3 with uneven particle sizes. This work confirms the feasibility of microbial dust suppressants for managing dust in disturbed areas of open-pit coal mine blast piles, offering a promising approach for dust control in such environments.

Mechanical properties of soil reinforced by fiber and alkaline-activated rice husk ash, and rainfall erosion model tests.

Rice husk ash is an industrial waste produced by biomass power plant to generate electricity, which contains a lot of silica. The accumulation of rice husk ash not only consumes land resources, but also causes environmental pollution. It is an urgent problem to explore the resource utilization of rice husk ash. In order to reuse rice husk ash, this study focuses on the application of polypropylene fiber and alkaline activated rice husk ash to slope reinforcement. Polypropylene fiber has the advantages of good toughness and corrosion resistance. Reinforced soil can effectively improve soil toughness and mechanical properties of soil engineering. NaOH solution was selected as the alkaline activator, and rice husk ash and polypropylene fiber were used to stabilize and strengthen the clay, which was consistent with the principles of sustainable development and circular economy. Through unconfined compressive strength test, the effects of ash content, polypropylene fiber content, NaOH concentration and curing age of rice husk on soil strength characteristics were studied. In addition, the mechanical properties and curing reinforcement mechanism of alkali-activated rice husk ash fiber-reinforced soil were studied by using dry-wet cycle test, rainfall erosion model test and microstructure analysis. The results show that the curing effect is best when 5 % rice husk ash is used, and the unconfined compressive strength of rice husk ash reinforced soil is the highest when the fiber content is 0.7%. NaOH solution improve soil strength, with maximum strength observed at a concentration of 0.6mol/L. The resistance to dry-wet damage of rice husk ash fiber reinforced soil is better than that of unreinforced soil, but the strength loss after dry-wet cycle by alkali activation is greater. In addition, the surface erosion of fibrous soil slope is the smallest, and the erosion amount is much lower than that of unreinforced soil. Fiber can effectively improve the erosion resistance and slip resistance of slope. The microscopic test analysis confirms the strength test results, and the addition of 5% rice husk ash will produce more hydration products, reduce soil porosity and improve soil strength. NaOH can effectively stimulate the active ingredients in soil particles, and the hydration products produced by the reaction can effectively fill the soil pores and significantly enhance the soil strength. The staggered network structure of polypropylene fibers improves the integrity of the soil, providing significant reinforcement.

Model test study on the rainfall erosion mechanisms and reclamation potential of open-pit coal mine dump soil improved by fly ash and polyacrylamide

Increasing the soil erosion resistance is one of the core issues in slope erosion control and ecological environmental restoration of open-pit coal mine (OPCM) dumps. In this study, fly ash (FA) and polyacrylamide (PAM) were used to improve the soil quality of an OPCM dump, and an indoor physical model was constructed to investigate the water and soil loss characteristics of the improved soil via simulated rainfall experiments. Scanning electron microscopy and Pore and Crack Analysis System software were employed to systematically investigate the erosion resistance mechanisms of the improved soil qualitatively and quantitatively. Finally, the improved technique for order preference by similarity to an ideal solution (TOPSIS) method was adopted to evaluate the reclamation potential of the improved soil. The results revealed that under the action of PAM (PAM and PAM–FA), the average erosion rate of the slope decreased by more than 90 %. Compared with that in the control group, when FA was applied alone, the slope erosion rate first decreased and then increased with increasing FA content. Upon PAM addition, the erosion pattern changed from the splash erosion stage, cave erosion stage, gully erosion stage, and tensile slip stage to the splash erosion stage and cave erosion stage. However, no obvious change in the runoff pattern. Erosion and runoff patterns are generally affected by the amendment type, addition concentration, porosity, pore shape, pore direction and hydrological environment. The erosion resistance mechanism of the improved soil entailed the formation of more stable soil aggregates via filling, cementation, skeleton support generation, and flocculation of FA and PAM. In addition, the optimal soil improvement was achieved when FA and PAM were added at levels of 16 % and 0.01 %, respectively. The obtained research results could be used for erosion control and ecological environmental protection of coarse-grained soil slopes in mining areas, highways and other fields and could be widely applied.

Exploring the relationship between drought-flood abrupt alternation and soil erosion over Guangdong, China through a convection-permitting model

Climate change has caused a more heterogeneous distribution of extreme precipitation, leading to the deterioration of drought-flood abrupt alternation (DFAA) events and soil erosion. The security and sustainable utilization of water and soil resources are severely threatened. Previous studies have focused separately on these two aspects, failing to comprehensively consider their interrelationship. Furthermore, these studies often rely on climate models with convection parameterization, resulting in substantial uncertainties. We use a 4 km convective permitting model (CPM) to generate reliable outputs for extreme precipitation. By incorporating the long-cycle drought-flood abrupt transition index and the Revised Universal Soil Loss Equation model, we analyze the changes in DFAA events and soil erosion, as well as their interconnectedness. The results show that the CPM outperforms coarse-resolution climate models in reproducing erosive rainfall and simulating the heterogeneous distribution of rainfall by capturing convection processes effectively. Projections indicate an escalation in the occurrence of DFAA events and soil erosion due to the more uneven distribution of precipitation. Specifically, the frequency of flood-to-drought (FTD) events within DFAA is projected to rise from 3.8 to 4.7 per decade. Soil loss is projected to increase 61 t·hm−2·a−1, with 73% of the area experiencing more severe soil erosion intensity. A positive correlation between FTD events and soil erosion is found throughout most of Guangdong. This correlation will be further amplified with an increase in the frequency of FTD events. Consequently, existing soil conservation measures are rendered inadequate, presenting substantial challenges for climate change adaptation and ecological protection in the region.

ESTIMATION OF SURFACE SOIL EROSION IN GRASSLANDS OF THE POIANA RUSCĂ MOUNTAINS. A CASE STUDY

Soil erosion, a natural phenomenon intensified by human activities, represents a significant threat to the environment, agriculture and economic sustainability, affecting the fertility and stability of land, including grasslands, in different regions of the globe and in Romania. To analyze this phenomenon, the study applies the USLE model integrated into GIS environments, using geospatial and remote sensing data to estimate the average erosion rate in the Poiana Rusca Mountains area, with a focus on grassland areas. Factors analysed include rainfall erosion, soil erodibility, topography, land use and the impact of erosion control measures. The results show that most grassland areas have a low average erosion rate (0-3 t/ha/year), due to the protection offered by the vegetation cover, but areas with steep slopes and sparse vegetation record moderate or severe losses (over 21 t/ha/year). The conclusions of the research emphasize the importance of implementing conservation measures, such as the restoration of the vegetation carpet in degraded grasslands and the sustainable management of grasslands, along with the use of geomatic technologies to monitor erosion phenomena, to reduce risks, contributing to the protection of these valuable ecosystems from an economic and biodiversity point of view.

Assessing seasonal rainfall erosivity variability in East Malaysia: a trend analysis approach

Assessing seasonal rainfall erosivity variability in East Malaysia: a trend analysis approach

Rainfall Erosivity Projection in South‐East Australia Using the Improved Regional Climate Simulations

ABSTRACTRainfall erosivity is one of the most dynamic factors in the soil erosion process. The increase in soil erosion caused by high rainfall erosivity, and the subsequent loss of soil nutrients, can lead to reduced food production and ecosystem services. This research program under the New South Wales (NSW) Climate Change Adaptation Strategy, assesses rainfall pattern change, rainfall erosivity and erosion risk across NSW under future climate conditions. Daily rainfall erosivity and erosion risk were modelled by Revised Soil Loss Universal Equation (RUSLE) approach and compared with that driven by observed rainfall data. Future rainfall erosivity and soil erosion risk change were investigated from daily precipitation projection of the updated NSW and Australian Regional Climate Modelling (NARCliM1.5) for two future scenarios, RCP4.5 and RCP8.5, from the historical (1986–2005) to far future (2060–2079) periods. The annual average rainfall erosivity is projected to increase about 8% under RCP 4.5 and further decrease 5% under RCP 8.5 in NSW due to the predicted temperature rises. More frequent heavy rainfall events are projected to occur during summer (December–January–February), and the rainfall from these extreme rainfall events is expected to account for 51% of the total annual rainfall in the far future. NARCliM‐derived results underestimate annual rainfall erosivity compared with observation‐derived erosivity. There are greater instability (root mean squared error [RMSE]: 803.2) and erosivity uncertainty (Bias: 16%~48%) in high rainfall zones. At a monthly scale, dry months (June–July–August) are becoming drier, while wet months (December–January–February) are becoming wetter and more erosive. 67% of NSW is predicted to experience increased rainfall erosivity under RCP4.5, whereas most of NSW will shift to drought and its consequent effects under the high‐end emission scenario (RCP 8.5). To address the dual challenges of excessive wetness in coastal and north‐east NSW and increasing aridity in Western NSW, it is necessary to develop climate change adaptation management strategies based on high‐risk areas and monthly or seasonal conditions. With the emerging launch of NARCliM2.0, we anticipate further improvements of these predictions will be achieved by more accurate models and data at higher spatial and temporal resolutions.

Incorporating return period in the assessment of rainfall erosivity of India using high temporal resolution satellite precipitation product

Incorporating return period in the assessment of rainfall erosivity of India using high temporal resolution satellite precipitation product

Impact of extreme rainfall events on soil erosion in downstream Parnaíba River Basin, Brazilian Cerrado

This study investigates the impact of extreme rainfall events on soil erosion in the downstream Parnaíba River Basin, located in the Brazilian Cerrado. The analysis focused on rainfall erosivity (R factor) and soil erodibility (K factor) as key indicators. The average erosivity in the region was 9051 MJ mm h−1ha−1year−1, with a variation between 7943 and 10,081 MJ mm h−1ha−1year−1, suggesting a high erosive potential, mainly in the rainiest months, from December to April. The soils of the studied area, mainly Ultisols and Chernosols, present high to very high erodibility, with K factor values ranging from 0.025 to 0.050 t h MJ−1 mm−1. Furthermore, fieldwork revealed areas, near highways, with apparently fragile soils, as well as rills and gullies, identified through photographs taken during fieldwork. These locations, due to the combination of high erosivity and susceptible soils, were considered prone to the occurrence of erosion processes, representing an additional risk to local infrastructure. The spatialization of R and K factors, along with field observations, showed that much of the area is at high risk of erosion and landslides, particularly in regions with greater topographic variability and proximity to water bodies. These results provide a basis for the development of mitigation strategies, being important for the effective prevention of landslides.

Coupling Benefit of Land Use, Land Cover Change and Soil Erosion Under Algorithmic Optimization Model

Technology realizes the quantitative and positioning acquisition of soil erosion and land use information, grasps the relationship between the two from space, and provides theoretical reference and scientific basis for local ecological environment construction and soil and water conservation work. This paper uses remote sensing images in my country in 2020 and 2021 as the data source and obtains land use data in four periods respectively. The experimental results show that the land use structure in my country has undergone great changes in 2020, and the land use type has gradually changed from a structure dominated by cultivated land, grassland, and unused land to grassland, forest land, and cultivated land. The other four types of land use area have increased to varying degrees, the unused land has decreased significantly, and the grassland and forest land have increased significantly; there are differences in the changes in the degree of land use in each study period, and the overall level of land use has developed phase by phase toward higher levels. In addition, this paper also studies the clustering algorithm in machine learning and proposes an improved interpolation algorithm for the completion of the original rainfall data. This algorithm can also be applied to the calculation process of rainfall erosion factors, which realizes the automatic calculation system of soil erosion model factors, realizes the real-time calculation and monitoring of soil erosion in the form of calculation tasks, and solves the problem that manual calculation consumes manpower and material resources.

Monthly and annual rainfall erosivity in Poland: An empirical model including winter snowfall effect

Study regionPoland Study focusThis study proposes an empirical model to assess rainfall erosivity in Poland, with a particular focus on incorporating the influence of winter snowfall on soil erosivity. Utilizing a dataset collected from 225 meteorological stations across Poland, the research aims to refine both monthly and annual rainfall erosivity assessments. An important feature of this model is the integration of daily minimum temperatures to adjust erosivity calculations during the winter months, a period typically characterized by lower erosivity due to snowfall, which is less erosive compared to rainfall. New hydrological insights for the regionDuring the calibration phase of annual rainfall erosivity, the model achieved a high coefficient of determination (R²) of 0.77. Validation results were similar, with an R² of 0.72. Further, the model was assessed for its seasonal performance, revealing significant variations in effectiveness across the year. For example, during the spring and autumn months, the model showed good predictive capabilities with R² values of 0.77 and 0.68, respectively. For winter and summer the R² value were slightly lower, reaching 0.64 and 0.61, respectively. Overall, the model offers a useful tool for predicting erosivity with improved accuracy by accounting for snowfall effects, which can aid in enhancing soil erosion assessments and supporting more informed soil conservation strategies.

Characteristics and Discrepant Responses of Rainfall Erosivity to El Niño-Southern Oscillation under Varied Rainfall Intensity in a Karst Hilly Region, China

Study regionsThe Guizhou Province (GZP) in southwestern China, where mainly comprises Karst regions. Study focusThe rainfall records were collected from 45 rain gauges within GZP during 1960~2019 to calculate the Rainfall Erosivity (RE). In addition, the spatio-temporal characteristics of RE were analyzed using statistical analysis methods, and the effect of El Niño-Southern Oscillation (ENSO) on RE under different rainfall intensities was also explored for the first time. New hydrological insights for the regionThe annual average RE was 4774 MJ·mm·hm-2·h-1, exhibiting a persistent increasing trend. RE demonstrated an increasing trend in most months, except for April and May, and the trend would continue in the future. The southern region of the GZP exhibited higher RE values, while the northern region displayed lower values. The spatial distribution varied across different seasons and months. On an annual scale, RE was significantly (P < 0.01) negatively correlated with elevation, indicating a decrease in erosive precipitation with increasing elevation. On a monthly scale, except for June to September, RE showed a significant (P < 0.001) negative correlation with elevation. Additionally, the study revealed a significant positive correlation (P < 0.05) with a lag time of 1 year between the total RE and RE under rainfall intensities exceeding 40mm/day and the Multivariate ENSO Index (MEI). This finding provides a possibility for predicting high-intensity RE with one year ahead.

Towards the development of bias-corrected rainfall erosivity time series for Europe

Towards the development of bias-corrected rainfall erosivity time series for Europe

Geochemical composition of suspended sediments generated after erosive rainfall events in nested agroforestry catchments with Mediterranean climate

Geochemical composition of suspended sediments generated after erosive rainfall events in nested agroforestry catchments with Mediterranean climate