Rainfall erosivity and erosivity density through rainfall synthetic series for São Paulo State, Brazil: Assessment, regionalization and modeling
Rainfall is the main cause of erosion of Brazilian soils, which makes assessing the rainfall erosivity factor (RE) and the erosivity density (ED) fundamental for soil and water conservation. Therefore, the objectives of this study were: i) to estimate the RE and ED for São Paulo State, Brazil, using...
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KeAi Communications Co., Ltd.
2022-09-01
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| Series: | International Soil and Water Conservation Research |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2095633921000952 |
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| author | David Bruno de Sousa Teixeira Roberto Avelino Cecílio João Paulo Bestete de Oliveira Laura Thebit de Almeida Gabrielle Ferreira Pires |
| author_facet | David Bruno de Sousa Teixeira Roberto Avelino Cecílio João Paulo Bestete de Oliveira Laura Thebit de Almeida Gabrielle Ferreira Pires |
| author_sort | David Bruno de Sousa Teixeira |
| collection | DOAJ |
| description | Rainfall is the main cause of erosion of Brazilian soils, which makes assessing the rainfall erosivity factor (RE) and the erosivity density (ED) fundamental for soil and water conservation. Therefore, the objectives of this study were: i) to estimate the RE and ED for São Paulo State, Brazil, using synthetic series of pluviographic data; ii) to define homogeneous regions regarding rainfall erosivity; and iii) to generate regression models for rainfall erosivity estimates in each of the homogeneous regions. Synthetic series of pluviographic data were initially obtained on a sub-daily scale from the daily rainfall records of 696 rainfall gauges. The RE values were then estimated from the synthetic rainfall data, and ED was calculated from the relationship between erosivity and rainfall amounts. Monthly and annual maps for RE and ED were obtained. Hierarchical clustering analysis was used to define homogeneous regions in terms of rainfall erosivity, and regionalized regression models for estimating RE were generated. The results demonstrate high spatial variability of RE in São Paulo, where the highest annual values were observed in the coastal region. December to March concentrate approximately 60% of the intra-annual erosivity. The highest values of annual ED were observed in regions with intense agricultural activity. The definition of five homogeneous regions concerning the rainfall erosive potential evidenced distinct seasonal patterns of the spatial distribution of erosivity. Finally, the high predictive accuracy of the regionalized models obtained characterizes them as essential tools for reliable estimates of rainfall erosivity, and contribute to better soil conservation planning. |
| first_indexed | 2024-03-07T17:21:19Z |
| format | Article |
| id | doaj.art-9a84ad7a425e43309002732e31cd933d |
| institution | Directory Open Access Journal |
| issn | 2095-6339 |
| language | English |
| last_indexed | 2024-03-07T17:21:19Z |
| publishDate | 2022-09-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | International Soil and Water Conservation Research |
| spelling | doaj.art-9a84ad7a425e43309002732e31cd933d2024-03-02T20:04:08ZengKeAi Communications Co., Ltd.International Soil and Water Conservation Research2095-63392022-09-01103355370Rainfall erosivity and erosivity density through rainfall synthetic series for São Paulo State, Brazil: Assessment, regionalization and modelingDavid Bruno de Sousa Teixeira0Roberto Avelino Cecílio1João Paulo Bestete de Oliveira2Laura Thebit de Almeida3Gabrielle Ferreira Pires4Department of Agricultural Engineering, Federal University of Viçosa, Viçosa, MG, 36570-900, Brazil; Corresponding author.Department of Forest and Wood Sciences, Federal University of Espírito Santo, Jerônimo Monteiro, ES, 29550-000, BrazilFederal Institute of Espírito Santo, Campus Alegre, Alegre, ES, 29520-000, BrazilDepartment of Agricultural Engineering, Federal University of Viçosa, Viçosa, MG, 36570-900, BrazilDepartment of Agricultural Engineering, Federal University of Viçosa, Viçosa, MG, 36570-900, BrazilRainfall is the main cause of erosion of Brazilian soils, which makes assessing the rainfall erosivity factor (RE) and the erosivity density (ED) fundamental for soil and water conservation. Therefore, the objectives of this study were: i) to estimate the RE and ED for São Paulo State, Brazil, using synthetic series of pluviographic data; ii) to define homogeneous regions regarding rainfall erosivity; and iii) to generate regression models for rainfall erosivity estimates in each of the homogeneous regions. Synthetic series of pluviographic data were initially obtained on a sub-daily scale from the daily rainfall records of 696 rainfall gauges. The RE values were then estimated from the synthetic rainfall data, and ED was calculated from the relationship between erosivity and rainfall amounts. Monthly and annual maps for RE and ED were obtained. Hierarchical clustering analysis was used to define homogeneous regions in terms of rainfall erosivity, and regionalized regression models for estimating RE were generated. The results demonstrate high spatial variability of RE in São Paulo, where the highest annual values were observed in the coastal region. December to March concentrate approximately 60% of the intra-annual erosivity. The highest values of annual ED were observed in regions with intense agricultural activity. The definition of five homogeneous regions concerning the rainfall erosive potential evidenced distinct seasonal patterns of the spatial distribution of erosivity. Finally, the high predictive accuracy of the regionalized models obtained characterizes them as essential tools for reliable estimates of rainfall erosivity, and contribute to better soil conservation planning.http://www.sciencedirect.com/science/article/pii/S2095633921000952Soil erosionStochastic weather generatorHomogeneous regionsModified Fournier indexRegression models |
| spellingShingle | David Bruno de Sousa Teixeira Roberto Avelino Cecílio João Paulo Bestete de Oliveira Laura Thebit de Almeida Gabrielle Ferreira Pires Rainfall erosivity and erosivity density through rainfall synthetic series for São Paulo State, Brazil: Assessment, regionalization and modeling International Soil and Water Conservation Research Soil erosion Stochastic weather generator Homogeneous regions Modified Fournier index Regression models |
| title | Rainfall erosivity and erosivity density through rainfall synthetic series for São Paulo State, Brazil: Assessment, regionalization and modeling |
| title_full | Rainfall erosivity and erosivity density through rainfall synthetic series for São Paulo State, Brazil: Assessment, regionalization and modeling |
| title_fullStr | Rainfall erosivity and erosivity density through rainfall synthetic series for São Paulo State, Brazil: Assessment, regionalization and modeling |
| title_full_unstemmed | Rainfall erosivity and erosivity density through rainfall synthetic series for São Paulo State, Brazil: Assessment, regionalization and modeling |
| title_short | Rainfall erosivity and erosivity density through rainfall synthetic series for São Paulo State, Brazil: Assessment, regionalization and modeling |
| title_sort | rainfall erosivity and erosivity density through rainfall synthetic series for sao paulo state brazil assessment regionalization and modeling |
| topic | Soil erosion Stochastic weather generator Homogeneous regions Modified Fournier index Regression models |
| url | http://www.sciencedirect.com/science/article/pii/S2095633921000952 |
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