scholarly journals Erosivity of rainfall in Lages, Santa Catarina, Brazil

2014 ◽  
Vol 38 (6) ◽  
pp. 1890-1905 ◽  
Author(s):  
Jefferson Schick ◽  
Ildegardis Bertol ◽  
Neroli Pedro Cogo ◽  
Antonio Paz González
Keyword(s):  
Temporal Distribution ◽  
Daily Rainfall ◽  
Rainfall Erosivity ◽  
Santa Catarina ◽  
Time Period ◽  
Erosivity Index ◽  
Annual Total ◽  
Erosive Rainfall ◽  
Management And Conservation ◽  
Erosive Capacity

The erosive capacity of rainfall can be expressed by an index and knowing it allows recommendation of soil management and conservation practices to reduce water erosion. The objective of this study was to calculate various indices of rainfall erosivity in Lages, Santa Catarina, Brazil, identify the best one, and discover its temporal distribution. The study was conducted at the Center of Agricultural and Veterinary Sciences, Lages, Santa Catarina, using daily rainfall charts from 1989 to 2012. Using the computer program Chuveros , 107 erosivity indices were obtained, which were based on maximum intensity in 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 70, 80, 90, 100, 110, 120, 135, 150, 165, 180, 210, and 240 min of duration and on the combination of these intensities with the kinetic energy obtained by the equations of Brown & Foster, Wagner & Massambani, and Wischmeier & Smith. The indices of the time period from 1993 to 2012 were correlated with the respective soil losses from the standard plot of the Universal Soil Loss Equation (USLE) in order to select the erosivity index for the region. Erosive rainfall accounted for 83 % of the mean annual total volume of 1,533 mm. The erosivity index (R factor) of rainfall recommended for Lages is the EI30, whose mean annual value is 5,033 MJ mm ha-1 h-1, and of this value, 66 % occurs from September to February. Mean annual erosivity has a return period estimated at two years with a 50 % probability of occurrence.

scholarly journals Erosive rainfall in the Rio do Peixe Valley in Santa Catarina, Brazil: Part II - Characteristics and temporal distribution pattern

2017 ◽  
Vol 21 (11) ◽  
pp. 780-784
Author(s):  
Álvaro J. Back ◽  
Augusto C. Pola ◽  
Nilzo I. Ladwig ◽  
Hugo Schwalm
Keyword(s):  
Kinetic Energy ◽  
Distribution Pattern ◽  
Precipitation Amount ◽  
Temporal Distribution ◽  
Maximum Intensity ◽  
Santa Catarina ◽  
Average Precipitation ◽  
Erosivity Index ◽  
Energy Maximum ◽  
Erosive Rainfall

ABSTRACT Exploring the characteristics of erosive rain is an important aspect of studying erosive processes, and it allows researchers to create more natural and realistic hydrological simulations. The objective of this study was to analyse the characteristics of erosive rain and to determine the temporal distribution pattern of erosive rainfall in the Valley of Rio do Peixe in the state of Santa Catarina, Brazil. Daily pluviograms from the meteorological stations located in the cities Campos Novos, Videira, and Caçador in Santa Catarina from 1984 to 2014 were utilized for this study. By studying rainfall that is classified as erosive, the values of kinetic energy, maximum intensity in thirty minutes, and the value of EI30 erosivity index were determined. The rainfall was also classified according to the temporal distribution of rainfall in advanced, intermediate, and delayed patterns. Erosive rainfalls occur at a frequency of 53.3% advanced, 31.1% intermediate, and 15.6% delayed patterns. Erosive rainfall has an average precipitation amount of 25.5 mm, duration of 11.1 h, kinetic energy of 5.6 MJ ha-1, maximum intensity of 30 min of 17.7 mm h-1, and erosivity of 206.4 MJ mm ha-1 h-1. The highest frequency of erosive rainfall occurred in rainfalls lasting from 6 to 12 h (36.1%), followed by rainfalls lasting from 4 to 6 h (22.4%).

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 Spatial distribution of the daily precipitation concentration index in Algeria

2015 ◽  
Vol 15 (3) ◽  
pp. 617-625 ◽  
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.

The Relationship of Debris Flow Hazards and Rainfall Erosivity in the Bailong River Basin of Southern Gansu Province, China

2014 ◽  
Vol 1073-1076 ◽  
pp. 1614-1619
Author(s):  
Peng Zhang ◽  
He Ping Shu ◽  
Jin Zhu Ma ◽  
Gang Wang ◽  
Li Ming Tian
Keyword(s):  
Soil Erosion ◽  
River Basin ◽  
Debris Flows ◽  
Temporal Distribution ◽  
Gansu Province ◽  
Annual Precipitation ◽  
Annual Rainfall ◽  
Rainfall Erosivity ◽  
Erosive Rainfall ◽  
Bailong River Basin

Rainfall is one of the main factors that drive soil erosion, leading to environmental problems such as increased frequency and severity of debris flows, and ecosystem damage. Rainfall erosivity represents the potential of rainfall to cause soil erosion, and is determined by a combination of rainfall intensity. The spatial and temporal distribution of rainfall erosivity was analyzed to get its relationship with the debris flows in the Bailong River Basin in China's Gansu Province. The mean annual amount of erosive rainfall accounts for 36.0-47.1% of annual precipitation. The annual mean rainfall erosivity amounts to 798.8 MJ mm ha-1 h-1 yr-1 in the Bailong River Basin. A positive correlation between annual precipitation and annual rainfall erosivity was demonstrated at all 18 rainfall stations. However, further research is required to reveal the key factors that explain soil erosion and debris flows.

scholarly journals Rainfall erosivity estimation based on rainfall data collected over a range of temporal resolutions

2015 ◽  
Vol 12 (5) ◽  
pp. 4965-4996 ◽  
Author(s):  
S. Yin ◽  
Y. Xie ◽  
B. Liu ◽  
M. A. Nearing
Keyword(s):  
Daily Rainfall ◽  
Rainfall Amount ◽  
Rainfall Data ◽  
Data Availability ◽  
Rainfall Erosivity ◽  
Data Prediction ◽  
Yearly Average ◽  
Model Efficiency ◽  
Erosivity Index ◽  
Better Than

Abstract. Rainfall erosivity is the power of rainfall to cause soil erosion by water. The rainfall erosivity index for a rainfall event, EI30, is calculated from the total kinetic energy and maximum 30 min intensity of individual events. However, these data are often unavailable in many areas of the world. The purpose of this study was to develop models that relate more commonly available rainfall data resolutions, such as daily or monthly totals, to rainfall erosivity. Eleven stations with one-minute temporal resolution rainfall data collected from 1961 through 2000 in the eastern water-erosion areas of China were used to develop and calibrate 21 models. Seven independent stations, also with one-minute data, were utilized to validate those models, together with 20 previously published equations. Results showed that models in this study performed better or similar to models from previous research to estimate rainfall erosivity for these data. Prediction capabilities, as determined using symmetric mean absolute percentage errors and Nash–Sutcliffe model efficiency coefficients, were demonstrated for the 41 models including those for estimating erosivity at event, daily, monthly, yearly, average monthly and average annual time scales. Prediction capabilities were generally better using higher resolution rainfall data as inputs. For example, models with rainfall amount and maximum 60 min rainfall amount as inputs performed better than models with rainfall amount and maximum daily rainfall amount, which performed better than those with only rainfall amount. Recommendations are made for choosing the appropriate estimation equation, which depend on objectives and data availability.

Spatiotemporal Distribution of Rainfall Erosivity in the Bailong River Basin, Gansu Province

2014 ◽  
Vol 936 ◽  
pp. 2377-2382 ◽  
Author(s):  
Peng Zhang ◽  
Gang Wang ◽  
Li Ming Tian ◽  
Ya Li Zhang
Keyword(s):  
River Basin ◽  
Temporal Distribution ◽  
Gansu Province ◽  
Annual Rainfall ◽  
Rainfall Erosivity ◽  
Distance Weighting ◽  
Erosive Rainfall ◽  
Annual Amount ◽  
Inverse Distance ◽  
Bailong River Basin

Rainfall erosivity is one of the key parameters that determine soil erosion, sediment yield, and water quality, thus its importance has grown in modeling of the environmental effects of climate change. The spatial and temporal distribution of rainfall erosivity in the Bailong River Basin in China's Gansu Province were analyzed. We derived a rainfall erosivity map based on data from 18 meteorological stations in and around the basin using the inverse distance weighting interpolation approach. The annual mean rainfall erosivity within the Bailong River Basin was 798.8 MJ mm ha-1h-1yr-1. The mean annual amount of erosive rainfall accounts for 36.0 to 47.1% of annual precipitation, depending on the station. Rainfall erosivity was greatest from June to September, and rainfall during this period accounts for 77.7% to 84.8% of the total annual rainfall erosivity.

scholarly journals Spatial distribution of the daily precipitation concentration index in Algeria

2014 ◽  
Vol 2 (4) ◽  
pp. 2709-2729 ◽  
Author(s):  
D. Boucherf ◽  
A. Benhamrouche ◽  
R. Hamadache ◽  
L. Bendahmane ◽  
J. Martin-Vide ◽  
...  
Keyword(s):  
Concentration Index ◽  
Daily Precipitation ◽  
Temporal Distribution ◽  
Daily Rainfall ◽  
Climatic Zones ◽  
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. 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 concentration index results allowed identifying three climatic 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 (average of 0.61), except for the area of Biskra (CI = 0.70), and the southern region of the country, with high rainfall concentrations, with values between 0.62 and 0.69. CI is an index related to the rainfall intensity and erosive capacity; therefore, this index has great interest for studies on torrential rainfall and floods.

scholarly journals Database of rainfall erosivity factor for 141 locations in Brazil.

2021 ◽  
Vol 1 (3) ◽  
pp. 95-101
Author(s):  
Roberto Avelino Cecílio ◽  
João Paulo Bestete de Oliveira ◽  
David Bruno de Sousa Teixeira ◽  
Fernando Falco Pruski ◽  
Sidney Sara Zanetti
Keyword(s):  
Soil Erosion ◽  
Best Practices ◽  
Regression Models ◽  
Environmental Problem ◽  
Daily Rainfall ◽  
Annual Rainfall ◽  
Rainfall Erosivity ◽  
R Factor ◽  
Lack Of Information ◽  
Erosivity Index

Soil erosion is a serious agricultural and environmental problem considered as a threat to sustainable development around the world. Rainfall is the primary cause of soil erosion, what leads the knowledge of its potential to cause soil erosion (rainfall erosivity – R-factor) to be a valuable tool for the design of land conservation best practices. As Brazil has a lack of information about rainfall erosivity, the present paper has determined the R-factor of 141 pluviographic stations distributed over Brazilian territory. Initially, erosive rainfalls were identified, and then the EI30 erosivity index was used to obtain the rainfall erosivity values. Regression models for the estimation of rainfall erosivity using daily rainfall data were established based on the correlation between the monthly average values of erosivity and the modified Fournier index. Results showed that the annual rainfall erosivity in the Brazilian stations analyzed ranged from 368.7 to 16,850.6 MJ mm ha-1 h-1 year-1. The results presented help to expand information about the spatial distribution of rainfall erosivity in Brazil, contributing to better conservation planning of land use.

scholarly journals Intensity and distribution in the space-time of the rain erosivity in Goias and Federal District states

2020 ◽  
Vol 13 (10) ◽  
pp. 1
Author(s):  
J. C. R. Anjos ◽  
F. P. Almeida ◽  
K. Ferreira ◽  
D. C. Silva ◽  
A. W. P. Evangelista ◽  
...  
Keyword(s):  
Food Production ◽  
Management Practices ◽  
Descriptive Analysis ◽  
Temporal Distribution ◽  
Federal District ◽  
Rainfall Erosivity ◽  
Annual Average ◽  
Study Region ◽  
Historical Series ◽  
Erosive Capacity

The ability of rainfall to promote soil disaggregation and transport depends on its intensity and distribution over time, allowing proper soil and water management practices in order to minimize their effects in and outside food production fields. The objective of this study was to verify the intensity of the spatial and temporal distribution of rainfall erosivity in Goias and Federal District states using historical series of rainfall data available at the National Institute of Meteorology (Inmet) from 1986 to 2017. Rainfall erosivity (EI) for Goias and Federal District were estimated using the modified Fournier index. Annual average for factor R were obtained by the sum of the EI in the 12 months of the year. Data were placed to descriptive analysis and classification according to their erosive capacity. The annual mean of the factor R for the study region was 8,834±5.2 MJ mm ha-1 h-1 ano-1, being classified as a strong erosive potential. However, considering the territory, its intensity in Goiás and DF varied from very strong to moderate throughout the year, indicating the need to adopt a conservationist practice that protects the soil from the kinetic energy of rainfall. It is concluded, therefore, that the intensity and distribution of the rainfall erosivity fluctuate both between the municipalities of Goiás (from 4.514±2.5 to 11.215±1.8 MJ mm ha-1 h-1 year-1), and throughout the year (from 180±1.5 to 1.519±4.4 MJ mm ha-1 h-1 month-1).

Sign in / Sign up

Export Citation Format

Share Document