scholarly journals Rainfall pattern and erosion potential in the physiographic regions of the state of Pernambuco, Brazil

2018 ◽  
Vol 22 (12) ◽  
pp. 849-853
Author(s):  
Antonio G. Pinheiro ◽  
Thais E. M. dos S. Souza ◽  
Suzana M. G. L. Montenegro ◽  
Abelardo A. de A. Montenegro ◽  
Sérgio M. S. Guerra
Keyword(s):  
The State ◽  
Rainfall Data ◽  
Rainfall Pattern ◽  
Annual Rainfall ◽  
Data Series ◽  
Rainfall Erosivity ◽  
Annual Average ◽  
Erosivity Index ◽  
Weather Stations ◽  
Physiographic Regions

ABSTRACT The objective of the present study was to characterize the spatial and temporal (2000-2015) rainfall pattern variability and erosive potential in the different physiographic regions of the state of Pernambuco, Brazil. Rainfall data series (3 to 12 years) from 25 weather stations of the state were analyzed. Erosive rainfall events (more than 10 mm depth) were considered to evaluate the annual erosivity index, monthly erosivity index (EI30), rainfall erosivity factor (R), and rainfall pattern. The inverse distance weighting (IDW) - inverse of the square of the distance - was used to create spatial interpolation and develop maps. The rainfall data from the weather stations showed average annual rainfall of 827 mm and average erosivity of 4,784 MJ mm ha-1 h-1. The Metropolitan region of Pernambuco presented the highest rainfall erosivity index, with annual average of 9,704 MJ mm ha-1 h-1; and the Sertão do São Francisco region had the lowest, with annual average of 4,902 MJ mm ha-1 h-1. The state of Pernambuco presented advanced (42%), intermediate (38%), and delayed (20%) rainfall patterns.

scholarly journals Erosive rainfall in Rio do Peixe Valley in Santa Catarina, Brazil: Part I - Determination of the erosivity index

2017 ◽  
Vol 21 (11) ◽  
pp. 774-779
Author(s):  
Álvaro J. Back ◽  
Augusto C. Pola ◽  
Nilzo I. Ladwig ◽  
Hugo Schwalm
Keyword(s):  
Rain Gauge ◽  
The State ◽  
Rainfall Data ◽  
Data Series ◽  
Rainfall Erosivity ◽  
Santa Catarina ◽  
R Factor ◽  
Erosivity Index ◽  
Erosive Rainfall

ABSTRACT This study aimed to determine the rainfall erosivity index in the Valley of Rio do Peixe, in the state of Santa Catarina, Brazil. The data series of three rain gauge stations in the cities of Campos Novos, Videira, and Caçador were used to determine the rainfall erosivity based on the EI30 index and to adjust the equations in order to estimate the EI30 value from the rainfall coefficient. On average, it was observed that erosive rains represents 81.4-88.5% of the annual precipitation. The adjusted equations can be used to estimate rainfall erosivity in locations with only rainfall data. The regional equation specified for the erosivity estimation is EI30 = 74.23 Rc0.8087. The R factor is 8,704.8; 7,340.8; and 6,387.1 MJ mm ha-1 h-1 year-1 for Campos Novos, Videira, and Caçador, respectively. In Campos Novos and Videira, the erosivity was classified as high, while in Caçador, it was classified as average.

scholarly journals Rainfall erosivity and rainfall return period in the experimental watershed of Aracruz, in the coastal plain of Espirito Santo, Brazil

2010 ◽  
Vol 34 (3) ◽  
pp. 999-1004 ◽  
Author(s):  
Sérgio Gualberto Martins ◽  
Junior Cesar Avanzi ◽  
Marx Leandro Naves Silva ◽  
Nilton Curi ◽  
Lloyd Darrell Norton ◽  
...  
Keyword(s):  
Return Period ◽  
Water Erosion ◽  
Annual Rainfall ◽  
Rainfall Erosivity ◽  
Annual Average ◽  
Espírito Santo ◽  
Average Rainfall ◽  
Weather Stations ◽  
Data Extrapolation ◽  
Espirito Santo

Knowledge on the factors influencing water erosion is fundamental for the choice of the best land use practices. Rainfall, expressed by rainfall erosivity, is one of the most important factors of water erosion. The objective of this study was to determine rainfall erosivity and the return period of rainfall in the Coastal Plains region, near Aracruz, a town in the state of Espírito Santo, Brazil, based on available data. Rainfall erosivity was calculated based on historic rainfall data, collected from January 1998 to July 2004 at 5 min intervals, by automatic weather stations of the Aracruz Cellulose S.A company. A linear regression with individual rainfall and erosivity data was fit to obtain an equation that allowed data extrapolation to calculate individual erosivity for a 30-year period. Based on this data the annual average rainfall erosivity in Aracruz was 8,536 MJ mm ha-1 h-1 yr-1. Of the total annual rainfall erosivity 85 % was observed in the most critical period October to March. Annual erosive rains accounted for 38 % of the events causing erosion, although the runoff volume represented 88 % of the total. The annual average rainfall erosivity return period was estimated to be 3.4 years.

scholarly journals Susceptibility to erosion risks in soils dedicated to the pineapple cultivation in the state of Valle del Cauca, Colombia

2021 ◽  
Vol 25 (2) ◽  
pp. 201-206
Author(s):  
Carolina Martinez López ◽  
Albin Osvaldo Rivera Paja ◽  
Juan Carlos Menjivar Flores
Keyword(s):  
River Basin ◽  
The State ◽  
Rainfall Erosivity ◽  
Topographic Factor ◽  
Erosivity Index ◽  
Weather Stations ◽  
Valle Del Cauca ◽  
High Level ◽  
Very High ◽  
Soil Losses

In Colombia almost half of the soils are prone to erosion, where Valle del Cauca is one of the most affected departments with respect to its severity. In order to identify the susceptibility to erosion risks in terms of the rainfall erosivity and the incidence of the topographic factor in the main pineapple producing municipalities of the department, a study was carried out that contemplated the historical climatological information of more than 50 years, for which all available weather stations in the area were selected. The erosivity index (R–EI30), the modified Fournier index (MFI), and the topographic factor (LS) were estimated. The results indicate that the average MFI values ranged between (91.31 and 582.79) which correspond to the moderate, high and very high categories, the results of R-EI30 presented moderate, high, very high and extremely severe values (5076.91 MJ.mm.ha-1 - 22718.83 MJ.mm.ha-1), while the highest values of the topographic factor (with slopes up to 81°) coincide with the upper part of the river basin Dagua, predominantly in the municipality of Dagua. These values indicate that the soils in the area are susceptible to erosion risks depending on the rainfall erosivity and the topographic factor at a moderate, high and very high level, which can generate significant soil losses, and therefore they should be considered when establishing a pineapple crop.

A Rainfall Erosivity database for Brazil from MSWEP rainfall dataset

2021 ◽  
Author(s):  
Ingrid Petry ◽  
Fernando Mainardi Fan
Keyword(s):  
Temporal Resolution ◽  
Soil Loss ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
Rainfall Erosivity ◽  
Regression Equations ◽  
R Factor ◽  
Thiessen Polygons ◽  
Erosivity Index ◽  
Factor Map

<p>In erosion studies the behavior of rainfall is primordial, since rain is responsible for the first stage of the erosion process: the detachment of soil particles. The erosive potential of rainfall, erosivity, is considered in the universal soil loss equations (R)USLE family through the parameter R, or R factor. This factor is calculated from the rainfall erosivity index, which is the product of kinetic energy of the rain by the maximum intensity of the rain of 30 minutes of duration. As sub-hour rainfall data is not always available, there are in the literature a series of equations obtained from regression, which use monthly and annual rainfall and present a good estimate of erosivity for your study site. In Brazil, in addition to limitations regarding the temporal resolution of rainfall data, there are also spatial limitations. Monitoring stations are concentrated mostly in urbanized areas, usually near the coast. The other regions, such as agricultural and forest areas, are poorly monitored, and these areas are of great interest for monitoring erosion, not only because they are periodically exposed soil areas, but also because of the high rainfall rates that humid forests like Amazon have. MSWEP is a rainfall database that combines observed, satellite and reanalysis data. It has global coverage, temporal resolution of 3 hours, spatial 0.1º and data from 1979 to 2016. Databases like this have great potential to be used in areas such as Brazil, due to its spatial and temporal resolution. In this context, considering the relevance that the soil loss equations still present today, this work developed a rainfall erosivity database entitled REDB-BR (Rainfall Erosivity Database for Brazil). It provides the R factor in a 0.1º resolution grid, developed with 37 years of rainfall data from the MSWEP dataset. The R factor was calculated trough 73 erosivity index regression equations, which mostly uses the Modified Fournier Index (MFI), a relation between monthly precipitation and annual precipitation. Thiessen polygons were used in order to spatialize and define the areas of each equation. Over the Brazilian territory, the R factor ranges from 1.200 to 20.000 MJ mm ha-1 h-1 year-1, with the higher values in the North region, and the lowest values in the Northeast. The spatial patterns of erosivity are very similar to the climatic zones of Brazil. The R factor map takes advantage of MSWEP dataset and presents a spatial resolution very detailed to a country with continental scale such as Brazil. The database includes the equations shapefile and table, Thiessen Polygons shapefile and the R factor map in raster format, which allows more possibilities of application. The database can be accessed at <https://zenodo.org/record/4428308#.X_hxsOhKiUk>. We identified sudden changes in behavior between the delimited areas, which suggests a need for more regression equations in order to better represent the behavior of the erosivity in the Brazilian territory.</p>

scholarly journals Erosive rainfall in the Rio do Peixe Valley: Part III - Risk of extreme events

2018 ◽  
Vol 22 (1) ◽  
pp. 63-68
Author(s):  
Álvaro J. Back ◽  
Augusto C. Pola ◽  
Nilzo I. Ladwig ◽  
Hugo Schwalm
Keyword(s):  
Extreme Events ◽  
Annual Rainfall ◽  
Data Series ◽  
Rainfall Erosivity ◽  
Significance Level ◽  
Control Structures ◽  
Kolmogorov Smirnov ◽  
Runoff Control ◽  
The Mean ◽  
Erosive Rainfall

ABSTRACT Understanding the risks of extreme events related to soil erosion is important for adequate dimensioning of erosion and runoff control structures. The objective of this study was to determine the rainfall erosivity with different return periods for the Valley of the Rio do Peixe in Santa Catarina state, Brazil. Daily pluviographic data series from 1984 to 2014 from the Campos Novos, and Videira meteorological stations and from 1986 to 2014 from the Caçador station were used. The data series of maximum annual rainfall intensity in 30 min, maximum annual erosive rainfall, and total annual erosivity were analyzed for each station. The Gumbel-Chow distributions were adjusted and their adhesions were evaluated by the Kolmogorov-Smirnov test at a significance level of 5%. The Gumbel-Chow distribution was adequate for the estimation of all studied variables. The mean annual erosivity corresponds to the return period of 2.25 years. The data series of the annual maximum individual rainfall erosivity coefficients varied from 47 to 50%.

scholarly journals Regiões pluviométricas homogêneas e a erosividade das chuvas na unidade hidrográfica Pirapó, Paranapanema III e IV-Paraná / Homogeneous rainfall regions and rainfall erosivity in the hydrographic unit Pirapó, Paranapanema III and IV hydrographic (...)

2016 ◽  
Vol 26 (46) ◽  
pp. 507 ◽  
Author(s):  
Paulo Miguel De Bodas Terassi ◽  
Hélio Silveira ◽  
Carlos Henrique Da Graça
Keyword(s):  
Euclidean Distance ◽  
Rainfall Erosivity ◽  
Proximity Measure ◽  
Temporal Segmentation ◽  
Rain Gauges ◽  
Monthly Distribution ◽  
Erosivity Index ◽  
Weather Stations ◽  
Annual Scale ◽  
The Relationship

<p>O presente trabalho objetiva definir regiões pluviométricas homogêneas e investigar a relação entre o regime pluviométrico e o potencial da erosividade para a unidade hidrográfica Pirapó, Paranapanema III e IV - Paraná. Foram obtidos os dados de pluviosidade de trinta e cinco postos pluviométricos do Instituto das Águas do Paraná e de cinco estações meteorológicas do Instituto Agronômico do Paraná (IAPAR), Instituto Nacional de Meteorologia (INMET) e Sistema Meteorológico do Paraná (SIMEPAR), trabalhados com o segmento temporal de 1976 a 2012. O índice de erosividade da chuva utilizado foi calculado a partir da equação apresentada por Rufino, Biscaia e Merten (1993) para o estado do Paraná. Definiu-se que o método de agrupamento mais adequado é o método aglomerativo de Ward, tendo como medida de proximidade a distância euclidiana. A área de estudo apresenta uma variação espacial da pluviosidade que mostra a influência da orografia principalmente para a distribuição espacial na escala anual, enquanto que a localização dos grupos demonstra uma maior associação à dinâmica atmosférica, conforme consultado pela literatura, para a compreensão da distribuição mensal das chuvas. Sobretudo, a delimitação dos grupos pluviométricos homogêneos permitiu compreender a relação entre o relevo, as alturas pluviométricas e o potencial erosivo das chuvas.</p><p><strong>Palavras-chave</strong>: agrupamento, pluviosidade, potencial erosivo, bacia hidrográfica.</p><p> </p><p>Abstract</p><p>This paper aims to define homogeneous rainfall regions and to investigate the relationship between rainfall and the potential erosivity for Pirapó, Paranapanema III and IV hydrographic unit - Paraná. The rainfall data was collected from thirty five rain gauges at Paraná Water Institute and from five weather stations at Paraná Agronomy Institute (IAPAR), National Weather Institute (INMET) and Paraná Meteorological System (SIMEPAR) and were processed within the temporal segmentation 1976 to 2012. The erosivity index rain used was calculated from the equation presented by Rufino, Biscaia and Merten (1993) for the Paraná State. It was defined that the most appropriate clustering method is the agglomerative method of Ward, with the proximity measure the Euclidean distance. The study area presents a spatial variation of rainfall that shows the orography influence mainly to the spatial distribution in the annual scale, while the location of groups shows a greater association with the atmospheric dynamics, as referred in the literature, for understanding the monthly distribution of rainfall. Above all, the delimitation of homogeneous rainfall groups allowed to understand the relationship between relief, the rain heights and the erosive potential of rainfall.</p><p><strong>Keywords</strong>: clustering, rainfall, erosive potential, watershed.</p>

scholarly journals Precipitation Patterns and Rainfall Erosivity Return Period Under Savanna Conditions in Formosa, Goiás, Brazil

2020 ◽  
Vol 8 (4) ◽  
pp. 554
Author(s):  
Aline Franciel de Andrade ◽  
Roriz Luciano Machado ◽  
Cássia Cristina Rezende ◽  
Elizabete Alves Ferreira ◽  
Daniel Fonseca de Carvalho ◽  
...  
Keyword(s):  
Annual Rainfall ◽  
Rainfall Erosivity ◽  
Return Periods ◽  
Tropical Regions ◽  
Average Annual Rainfall ◽  
Physical Attributes ◽  
Erosivity Index ◽  
Rainfall Patterns ◽  
Agricultural Areas ◽  
Intermediate Pattern

Losses of soil and nutrients affect a large part of agricultural areas in tropical regions, regardless of the level of technology adopted. This study evaluated the physical attributes and erosivity indices associated with rainfall patterns and return periods in the region of Formosa, State of Goiás, Brazil. Using series of pluviographic (2002-2008) and pluviometric (1975-1998) data from a station located at municipality of Formosa, the erosive potential (EI30 and KE>25), rainfall patterns (advanced, intermediate and delayed) and the erosivity associated with the rainfall return periods were determined. The average annual rainfall of the region was 1,391.6 mm with 87.4% of the rains concentrated in October to March. The average annual values of EI30 and KE>25 corresponded to 8,041.6 MJ mm ha-1 h-1 year-1 and 125.7 MJ ha-1 year-1, respectively. The months of the year did not differ based on rainfall pattern. The advanced hydrological pattern had the highest frequency of occurrence, followed by the delayed and intermediate patterns. The highest EI30 and KE>25 indices for individual rainfall seasons occurred under the intermediate and the advanced patterns in February and under the intermediate pattern in October for the index KE>25. The average annual erosivity index (R factor of USLE) (8041.6 MJ mm ha-1 h-1 year-1) is expected to occur at least once every 1.89 years, corresponding to a probability of occurrence of 52.84%. The average annual values of EI30 estimated for the return periods of 2, 5, 10, 25, 50 and 100 years were 8,230, 10,225, 10,889, 11,222, 11,421 and 11,488 MJ mm ha-1 h-1 year-1, respectively.

scholarly journals 50 year rainfall data analysis and future trend in Saharanpur region

MAUSAM ◽  
2021 ◽  
Vol 63 (1) ◽  
pp. 55-64
Author(s):  
VARTIKA SINGH ◽  
PRAMENDRA DEV
Keyword(s):  
Ground Water ◽  
Rainwater Harvesting ◽  
Water Reservoir ◽  
Negative Trend ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
Positive Trend ◽  
Environmental Implications ◽  
Annual Average ◽  
Average Rainfall

The environmental implications of rainfall pattern in replenishment of ground water system of Saharanpur region, located in western Uttar Pradesh, have been discussed. The mathematical analysis of rainfall dissimilarity of Saharanpur region for a period of 50 year (1959 to 2008) display a quite good range from 497.70 to 4357.5 mm with an annual average rainfall value of 1209.8 mm. The positive trend of departure from the computer value of average annual rainfall exhibits appropriate periods for recharge of ground water reservoir. The recorded data of annual rainfall during the last 3 year reveal values below the calculated annual average rainfall, pointing out negative trend. The statistical analysis of rainfall data involves computations of various statistical parameters, which also support the negative trend of rainfall. The prediction of expected future rainfall trend for a period up to 2018 has been made, which indicates a negative trend. The proposal have been incorporated to implement a plan for augmentation of ground water resource and also to develop possibilities of rainwater harvesting.

scholarly journals Assessing Inhomogeneities in Extreme Annual Rainfall Data Series by Multifractal Approach

Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 1030 ◽  
Author(s):  
Amanda García-Marín ◽  
Javier Estévez ◽  
Renato Morbidelli ◽  
Carla Saltalippi ◽  
José Ayuso-Muñoz ◽  
...  
Keyword(s):  
Central Italy ◽  
Extreme Rainfall ◽  
Break Point ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
Data Series ◽  
Homogeneity Test ◽  
Umbria Region ◽  
Standard Normal Homogeneity Test ◽  
Break Points

Testing the homogeneity in extreme rainfall data series is an important step to be performed before applying the frequency analysis method to obtain quantile values. In this work, six homogeneity tests were applied in order to check the existence of break points in extreme annual 24-h rainfall data at eight stations located in the Umbria region (Central Italy). Two are parametric tests (the standard normal homogeneity test and Buishand test) whereas the other four are non-parametric (the Pettitt, Sequential Mann–Kendal, Mann–Whitney U, and Cumulative Sum tests). No break points were detected at four of the stations analyzed. Where inhomogeneities were found, the multifractal approach was applied in order to check if they were real or not by comparing the split and whole data series. The generalized fractal dimension functions Dq and the multifractal spectra f(α) were obtained, and their main parameters were used to decide whether or not a break point existed.

scholarly journals Modelling the spatial dependence of the rainfall erosivity index in the Brazilian semiarid region

2017 ◽  
Vol 52 (6) ◽  
pp. 371-379 ◽  
Author(s):  
André Quintão de Almeida ◽  
Rodolfo Marcondes Silva Souza ◽  
Diego Campana Loureiro ◽  
Donizete dos Reis Pereira ◽  
Marcus Aurélio Soares Cruz ◽  
...  
Keyword(s):  
Spatial Dependence ◽  
Semiarid Region ◽  
Data Series ◽  
Rainfall Erosivity ◽  
Semivariogram Model ◽  
Jackknife Test ◽  
Average Value ◽  
Applied Model ◽  
Brazilian Semiarid ◽  
Erosivity Index

Abstract: The objective of this work was to model the spatial dependence and to map the rainfall erosivity index (EI30) in the semiarid region of Brazil. Registers of monthly erosivity from 210 rainfall stations were used, with daily time series equal to or greater than 15 years. Based on the values of the EI30, a spatial dependence model was made by adjusting the semivariogram. From the semivariogram models, erosivity isoline maps were generated with a kriging interpolator. According to the historical data series, the maximum monthly average value of the EI30 was observed in March, and the annual value ranged from 1,439 to 5,864 MJ mm ha-1 per year, classified as low and moderate, respectively. The highest EI30 values were obtained in the northern and southern extremes of the semiarid region. Average spatial dependence was observed for rainfall erosivity, in most months, especially with the spherical semivariogram model. The range of erosivity varied from 62 to 1,508 km for the monthly EI30 and was of approximately 1,046 km for the annual one. The applied model, with the validation of the semivariograms using the jackknife test, allows the spatialization of the EI30 for the semiarid region of Brazil.

Sign in / Sign up

Export Citation Format

Share Document