Spatial and temporal estimation of the erosivity factor R based on daily rainfall data for the department of Atlántico, Colombia

Soil erosion caused by rain is the detachment and movement of soil particles caused by the impact of raindrops on the surface. Erosivity factor R is a measure of the rain erosive power used for estimating the erosion rate with the RUSLE method (Revised Universal Soil Loss Equation). Estimating R factor requires rainfall intensity records of storms greater than 12.5 mm or greater than 6 mm but longer than 15 min. However, most of the Colombian rainfall stations have daily rainfall records with which it is not possible to estimate the intensity of each storm and, therefore, makes it difficult to estimate the R factor for a specific area. In this paper a methodology for estimating the erosivity factor R for the department of Atlántico, Colombia from daily records of 16 IDEAM stations is presented. The spatial distribution of the erosivity factor R in the department and its temporal distribution throughout the year are also shown. The results showed a minimum erosivity factor R of 6,894 MJ∙mm∙Ha-1∙Hr-1∙yr-1 and a maximum of 10,925 MJ∙mm∙Ha-1∙Hr-1∙yr-1. The average erosivity factor R for the department of Atlántico was 8,697 MJ∙mm∙Ha-1∙Hr-1∙yr-1. This methodology might be used for estimating the erosion factor R in different Colombian regions where high-resolution precipitation data is limited, but seasonal and orographic conditions should be considered for selecting the rain gages and the area of study.

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Prediction of factors affecting activation of soil erosion by mathematical modeling at pedon scale under laboratory conditions

Scientific Reports ◽

10.1038/s41598-020-76926-1 ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Saeed Shojaei ◽

Zahra Kalantari ◽

Jesús Rodrigo-Comino

Keyword(s):

Soil Loss ◽

Rainfall Intensity ◽

Quadratic Function ◽

Interactive Effects ◽

Soil Protection ◽

Single Factor ◽

Rainfall Events ◽

Rainfall Duration ◽

The Impact ◽

Runoff Production

AbstractSoil degradation due to erosion is a significant worldwide problem at different spatial (from pedon to watershed) and temporal scales. All stages and factors in the erosion process must be detected and evaluated to reduce this environmental issue and protect existing fertile soils and natural ecosystems. Laboratory studies using rainfall simulators allow single factors and interactive effects to be investigated under controlled conditions during extreme rainfall events. In this study, three main factors (rainfall intensity, inclination, and rainfall duration) were assessed to obtain empirical data for modeling water erosion during single rainfall events. Each factor was divided into three levels (− 1, 0, + 1), which were applied in different combinations using a rainfall simulator on beds (6 × 1 m) filled with soil from a study plot located in the arid Sistan region, Iran. The rainfall duration levels tested were 3, 5, and 7 min, the rainfall intensity levels were 30, 60, and 90 mm/h, and the inclination levels were 5, 15, and 25%. The results showed that the highest rainfall intensity tested (90 mm/h) for the longest duration (7 min) caused the highest runoff (62 mm3/s) and soil loss (1580 g/m2/h). Based on the empirical results, a quadratic function was the best mathematical model (R2 = 0.90) for predicting runoff (Q) and soil loss. Single-factor analysis revealed that rainfall intensity was more influential for runoff production than changes in time and inclination, while rainfall duration was the most influential single factor for soil loss. Modeling and three-dimensional depictions of the data revealed that sediment production was high and runoff production lower at the beginning of the experiment, but this trend was reversed over time as the soil became saturated. These results indicate that avoiding the initial stage of erosion is critical, so all soil protection measures should be taken to reduce the impact at this stage. The final stages of erosion appeared too complicated to be modeled, because different factors showed differing effects on erosion.

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Estimativa da erosividade da chuva por diferentes métodos e seu impacto na equação universal de perdas de solo, no semiárido pernambucano (Estimation of erosivity by different methods and their impact on the universal soil loss equation in Pernambuco semi-arid)

Revista Brasileira de Geografia Física ◽

10.26848/rbgf.v12.3.p859-875 ◽

2019 ◽

Vol 12 (3) ◽

pp. 859

Author(s):

Joaquim Pedro de Santana Xavier ◽

Alexandre Hugo Cezar Barros ◽

Daniel Chaves Webber ◽

Luciano José de Oliveira Accioly ◽

Flávio Adriano Marques ◽

...

Keyword(s):

Soil Loss ◽

Universal Soil Loss Equation ◽

Rainfall Erosivity ◽

R Factor ◽

Semi Arid Region ◽

Erosion Loss ◽

R Factors ◽

Semi Arid ◽

Soil Loss Equation

Dentre os diversos métodos indiretos para estimar as perdas de solo por erosão, a Equação Universal de Perdas de Solo (EUPS) é a mais utilizada devido a sua robustez e por ser constituída de uma simples estrutura fatorial, que integra fatores naturais e antrópicos atuantes na perda de solos. A erosão é um dos fenômenos mais danosos ao solo e às atividades humanas e por isso seu estudo é importante. Para o cálculo das perdas de solo por meio da EUPS, a avaliação da erosividade das chuvas (fator R) é essencial, pois estima o fenômeno produzido pelas chuvas. O objetivo deste trabalho foi avaliar três metodologias disponíveis de obtenção da erosividade das chuvas para a região do semiárido pernambucano, avaliando sua influência nos resultados da EUPS. Os três modelos selecionados para estimar o Fator R foram desenvolvidos por Wischmeier e Smith (mais conhecido e utilizado), por Silva que estimou valores para diversas regiões do País e por Cantalice e outros que trabalharam especificamente para cada região climática do estado de Pernambuco. Os resultados indicam que as metodologias de Wischmeier e Smith e Silva obtiveram resultados de erosividade da chuva semelhantes, tendo Silva alcançado valores maiores. Cantalice e outros obtiveram os resultados mais baixos. Os resultados da EUPS indicam que, quantitativamente, os diferentes fatores R geram grande diferença nas perdas de solo, porém, qualitativamente chegam a resultados semelhantes na classificação de áreas de maior erosão, de acordo com a FAO. Logo, as três metodologias são viáveis na identificação de áreas prioritárias para a mitigação da erosão. A B S T R A C TAmong several indirect methods to estimate soil erosion loss, the Universal Soil Loss Equation (EUPS) is the most used due to its robustness and because it is constituted of a simple factorial structure that integrates natural and anthropic factors which act in the loss of soils. Erosion is one of the most damaging phenomena to the soil and the human activities, evidencing the importance of studying it. The evaluation of rainfall erosivity (R factor) is essential for the calculation of soil loss through the EUPS, since it is possible to estimate how significant rainfall is to the occurrence of this phenomenon. The objective of this work was to evaluate three methodologies to obtain the rainfall erosivity available for the semi - arid region of Pernambuco, evaluating its influence on the results of the EUPS. The three models used to estimate the R-factor were developed by Wischmeier and Smith, the best known and used model, Silva who estimated values for several regions of the country and Cantalice and others who worked specifically for each climatic region of the state of Pernambuco. As a result, very similar results of rainfall erosivity were obtained between Wischmeier and Smith´s and Silva´s methodology, with Silva reaching higher values of energy amplitude, while Cantalice and others obtained the lowest results. The results of EUPS indicate that, quantitatively, the different R factors generate a large difference in soil loss, but qualitatively they reach similar results in the classification of areas where erosion are greater, according to the FAO. Therefore, the three methodologies are feasible in the identification of priority areas for erosion mitigation.Keywords: soil, rainfall erosivity, USLE, GIS

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Spatial and temporal prediction and uncertainty of soil loss using the revised universal soil loss equation: a case study of the rainfall–runoff erosivity R factor

Ecological Modelling ◽

10.1016/s0304-3800(01)00507-5 ◽

2002 ◽

Vol 153 (1-2) ◽

pp. 143-155 ◽

Cited By ~ 60

Author(s):

Guangxing Wang ◽

George Gertner ◽

Vivek Singh ◽

Svetlana Shinkareva ◽

Pablo Parysow ◽

...

Keyword(s):

Soil Loss ◽

Universal Soil Loss Equation ◽

Rainfall Runoff ◽

Temporal Prediction ◽

R Factor ◽

Soil Loss Equation

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Extreme rainfall events during and following heatwaves

10.5194/egusphere-egu21-8851 ◽

2021 ◽

Author(s):

Christoph Sauter ◽

Christopher White ◽

Hayley Fowler ◽

Seth Westra

Keyword(s):

Natural Hazards ◽

Rainfall Intensity ◽

Daily Rainfall ◽

Extreme Rainfall ◽

Extreme Rainfall Events ◽

Rainfall Events ◽

Rainfall Extremes ◽

Average Rainfall ◽

Time Of Year ◽

The Impact

Heatwaves and extreme rainfall events are natural hazards that can have severe impacts on society. The relationship between temperature and extreme rainfall has received scientific attention with studies focussing on how single daily or sub-daily rainfall extremes are related to day-to-day temperature variability. However, the impact multi-day heatwaves have on sub-daily extreme rainfall events and how extreme rainfall properties change during different stages of a heatwave remains mostly unexplored.In this study, we analyse sub-daily rainfall records across Australia, a country that experiences severe natural hazards on a frequent basis, and determine their extreme rainfall properties, such as rainfall intensity, duration and frequency during SH-summer heatwaves. These properties are then compared to extreme rainfall properties found outside heatwaves, but during the same time of year, to examine to what extent they differ from normal conditions. We also conduct a spatial analysis to investigate any spatial patterns that arise.We find that rainfall breaking heatwaves is often more extreme than average rainfall during the same time of year. This is especially prominent on the eastern and south-eastern Australian coast, where frequency and intensity of sub-daily rainfall extremes show an increase during the last day or the day immediately after a heatwave. We also find that although during heatwaves the average rainfall amount and duration decreases, there is an increase in sub-daily rainfall intensity when compared to conditions outside heatwaves. This implies that even though Australian heatwaves are generally characterised by dry conditions, rainfall occurrences within heatwaves are more intense.Both heatwaves and extreme rainfall events pose great challenges for many sectors such as agriculture, and especially if they occur together. Understanding how and to what degree these events co-occur could help mitigate the impacts caused by them.

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Development Land Erosion Model Using Model Builder GIS (Case Study: Citepus Watershed)

MATEC Web of Conferences ◽

10.1051/matecconf/201814703003 ◽

2018 ◽

Vol 147 ◽

pp. 03003

Author(s):

Dina PA Hidayat ◽

Sih Andajani

Keyword(s):

Soil Loss ◽

Universal Soil Loss Equation ◽

Rainfall Erosivity ◽

Model Builder ◽

Watershed Analysis ◽

Runoff Discharge ◽

The Impact ◽

Impervious Areas ◽

Soil Loss Equation

Land erosion is the impact of increasing runoff discharge and land use conversion to impervious areas. Land erosion usually calculated by formula called USLE (Universal Soil Loss Equation) then modified as MUSLE (Modified Universal Soil Loss Equation). These formula calculate average annual soil loss in tons/areas depends on rainfall erosivity (R), soil erodibility factor (K), topographic factor (LS), cropping and conservation factor (CP). GIS (Geographic Information System) is a system designed to capture, manipulate, and analyze spatial/geographic data. There are some tools related water resources analysis in ArcGIS such as: watershed analysis and also have a tools for user to create their own model called model builder. This research was aim to create a model to calculate land erosion using MUSLE formula by model builder in ArcGIS. The output for this research is the model which can be used to calculate annual soil loss in watershed area based on GIS systems. For the model trial and case study, we use Citepus watershed located on Bandung West Java, that has 5 river branches: Cibogo, Cikakak, Cilimus, Cipedes and Ciroyom. As the result of the model, the value of average annual soil loss in Citepus watershed can be calculated automatically by developed model.

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Spatial distribution of the daily precipitation concentration index in Algeria

Natural Hazards and Earth System Science ◽

10.5194/nhess-15-617-2015 ◽

2015 ◽

Vol 15 (3) ◽

pp. 617-625 ◽

Cited By ~ 30

Author(s):

A. Benhamrouche ◽

D. Boucherf ◽

R. Hamadache ◽

L. Bendahmane ◽

J. Martin-Vide ◽

...

Keyword(s):

Concentration Index ◽

Rainfall Intensity ◽

Daily Precipitation ◽

Temporal Distribution ◽

Daily Rainfall ◽

Precipitation Concentration Index ◽

Precipitation Concentration ◽

Northern Country ◽

Torrential Rainfall ◽

Erosive Capacity

Abstract. In this paper, the spatial and temporal distribution of the daily precipitation concentration index (CI) in Algeria (south Mediterranean Sea) has been assessed. CI is an index related to the rainfall intensity and erosive capacity; therefore, this index is of great interest for studies on torrential rainfall and floods. Forty-two daily rainfall series based on high-quality and fairly regular rainfall records for the period from 1970 to 2008 were used. The daily precipitation CI results allowed the identification of three climate zones: the northern country, characterized by coastal regions with CI values between 0.59 and 0.63; the highlands, with values between 0.57 and 0.62, except for the region of Biskra (CI = 0.70); and the southern region of the country, with high rainfall concentrations with values between 0.62 and 0.69.

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Assessment of Rainfall Kinetic-Energy–Intensity Relationships

Water ◽

10.3390/w11101994 ◽

2019 ◽

Vol 11 (10) ◽

pp. 1994 ◽

Cited By ~ 5

Author(s):

Claudio Mineo ◽

Elena Ridolfi ◽

Benedetta Moccia ◽

Fabio Russo ◽

Francesco Napolitano

Keyword(s):

Kinetic Energy ◽

Soil Loss ◽

Energy Intensity ◽

Rainfall Intensity ◽

Central Italy ◽

Direct Evaluation ◽

Hydrological Variable ◽

The Mean ◽

Raindrop Energy ◽

Soil Loss Equation

Raindrop-impact-induced erosion starts when detachment of soil particles from the surface results from an expenditure of raindrop energy. Hence, rain kinetic energy is a widely used indicator of the potential ability of rain to detach soil. Although it is widely recognized that knowledge of rain kinetic energy plays a fundamental role in soil erosion studies, its direct evaluation is not straightforward. Commonly, this issue is overcome through indirect estimation using another widely measured hydrological variable, namely, rainfall intensity. However, it has been challenging to establish the best expression to relate kinetic energy to rainfall intensity. In this study, first, kinetic energy values were determined from measurements of an optical disdrometer. Measured kinetic energy values were then used to assess the applicability of the rainfall intensity relationship proposed for central Italy and those used in the major equations employed to estimate the mean annual soil loss, that is, the Universal Soil Loss Equation (USLE) and its two revised versions (RUSLE and RUSLE2). Then, a new theoretical relationship was developed and its performance was compared with equations found in the literature.

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Socioeconomic modifications of the universal soil loss equation

Solid Earth ◽

10.5194/se-6-1025-2015 ◽

2015 ◽

Vol 6 (3) ◽

pp. 1025-1035 ◽

Cited By ~ 16

Author(s):

A. Erol ◽

Ö. Koşkan ◽

M. A. Başaran

Keyword(s):

Socioeconomic Factors ◽

Soil Loss ◽

Universal Soil Loss Equation ◽

Physical Factors ◽

Simulation Methods ◽

Human Influence ◽

Social Scientists ◽

Socioeconomic And Demographic Factors ◽

The Impact ◽

Soil Loss Equation

Abstract. While social scientists have long focused on socioeconomic and demographic factors, physical modelers typically study soil loss using physical factors. In the current environment, it is becoming increasingly important to consider both approaches simultaneously for the conservation of soil and water, and the improvement of land use conditions. This study uses physical and socioeconomic factors to find a coefficient that evaluates the combination of these factors. It aims to determine the effect of socioeconomic factors on soil loss and, in turn, to modify the universal soil loss equation (USLE). The methodology employed in this study specifies that soil loss can be calculated and predicted by comparing the degree of soil loss in watersheds, with and without human influence, given the same overall conditions. A coefficient for socioeconomic factors, therefore, has been determined based on adjoining watersheds (WS I and II), employing simulation methods. Combinations of C and P factors were used in the USLE to find the impact of their contributions to soil loss. The results revealed that these combinations provided good estimation of soil loss amounts for the second watershed, i.e., WS II, from the adjoining watersheds studied in this work. This study shows that a coefficient of 0.008 modified the USLE to reflect the socioeconomic factors, such as settlement, influencing the amount of soil loss in the studied watersheds.

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ASSESSMENT OF SOIL EROSION BY SIMULATING RAINFALL ON AN EQUATORIAL ORGANIC SOIL

Journal of Civil Engineering Science and Technology ◽

10.33736/jcest.440.2017 ◽

2017 ◽

Vol 8 (2) ◽

pp. 72-81

Author(s):

Johari A.H ◽

Law P.L. ◽

Taib S.N.L. ◽

Yong L.K.

Keyword(s):

Soil Erosion ◽

Soil Loss ◽

Organic Soil ◽

Coarse Sand ◽

Soil Samples ◽

Soil Erodibility ◽

Simulated Rainfall ◽

Construction Sites ◽

The Impact ◽

Soil Loss Equation

Soil erosion occurs on construction sites partly due to site clearing that exposes the land to the erosive power of rainfall. A proposed construction project requires the submission of an Environmental Impact Assessment EIA) to assess the impact of the project on the environment. Assessment of soil erosion is included in the EIA, but the equation to estimate soil erosion known as the Universal Soil Loss Equation (USLE) is only applicable to a soil containing up to four percent organic matter. This limitation of USLE requires an alternative that can predict soil erosion on an organic soil. This study attempts to assess erosion that occurs on an organic soil by simulated rainfall. Field soil samples were reconstructed into three shapes and exposed to simulated rainfall. Results indicate that the amount of organic soil loss decreases with increasing duration of rainfall. Particle size distribution shows that particles with sizes finer than coarse sand (1.7 mm) remained on the slopes. Equations were developed from the graphs of soil loss versus duration of simulated rainfall to estimate soil loss occurring on slopes covered by an organic soil. The outcome of this study can be a precursor to developing an equation to estimate soil erodibility of a slope overlain by an organic soil.

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A Study Case on Estimation of Soil Loss and Sediment Yield in Curtin University, Malaysia

Tropical Aquatic and Soil Pollution ◽

10.53623/tasp.v1i2.17 ◽

2021 ◽

Vol 1 (2) ◽

pp. 62-73

Author(s):

Hui Yee Ngieng ◽

Leong Kong Yong ◽

Striprabu Strimari

Keyword(s):

Sediment Yield ◽

Soil Loss ◽

Rainfall Intensity ◽

Google Earth ◽

Universal Soil Loss Equation ◽

Storm Event ◽

Sieve Analysis ◽

Runoff Depth ◽

Factor C ◽

Soil Loss Equation

Because of human activities, soil erosion has been one of the most concerning issues in Malaysia in the past decades. This study aimed to estimate the amount of soil loss and sediment yield at Curtin University, Malaysia by using the Revised Universal Soil Loss Equation (RUSLE) and the Modified Universal Soil Loss Equation (MUSLE), respectively. The parameters of RUSLE include rainfall erosivity factor (R), soil erodibility factor (K), slope length factor (L), slope steepness factor (S), cover-management factor (C) and support practice factor (P). The rainfall data (10 years) from the Sarawak Meteorological Department was used to determine the R-factor. The K-factor was determined by sieve analysis, hydrometer analysis, the Standard Proctor Test (SPT), and organic content testing. The L-and S-factors were performed by measuring on site and using Google Earth. The C-and P-factors were based on the ground surface cover condition (bare soil in this study). In the MUSLE, the runoff factor comprises V and Qp, while the other parameters are the same as in the RUSLE. The runoff depth, V, is equivalent to the rainfall intensity. Rainfall intensities were recorded by using a rain gauge. The highest rainfall intensity was used for runoff depth. The Rational method has been utilized to calculate Qp. The amount of soil loss estimated was 119.97 tons/ha/year and the sediment yield amount estimated was 0.76 ton/storm event in Curtin University, Malaysia.

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