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

Wellynne Carla de Sousa Barbosa, Antonio José Teixeira Guerra, Iracilde Maria de Moura Fé Lima

Article ID: 9639
Vol 7, Issue 2, 2024

VIEWS - 1756 (Abstract) 1345 (PDF)

Abstract


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 h1ha1year1, with a variation between 7943 and 10,081 MJ mm h1ha1year1, 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 MJ1 mm1. 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.


Keywords


soil erosion; rainfall erosivity; soil erodibility; extreme rainfall events; Brazilian Cerrado

Full Text:

PDF


References


1. Abreu LP, Mutti PR, Lima KC. Spatial and temporal variability of precipitation in the Parnaíba River basin, Northeast Brazil (Portuguese). Revista Brasileira de Meio Ambiente; 2019.

2. Guerra AJT, Fullen MA, Jorg MCO, et al. Slope Processes, Mass Movement and Soil Erosion: A Review. Pedosphere. 2017; 27 (1), 27-41. doi: 10.1016/S1002-0160(17)60294-7

3. Barbosa WCS, Guerra AJT, Valladares GS. Soil Erosion Modeling Using the Revised Universal Soil Loss Equation and a Geographic Information System in a Watershed in the Northeastern Brazilian Cerrado. Geosciences. 2024; 14(3): 78. doi: 10.3390/geosciences14030078

4. Morais RCS, Sales MCL. Estimating the natural soil erosion potential of the Alto Gurguéia watershed, Piauí-Brazil, using a Geographic Information System. (Portuguese). Caderno de Geografia; 2017.

5. Morais RCS, Silva AJO. Estimating the Natural Potential for Soil Erosion in the Longá River Basin, Piauí, Brazil. (Portuguese). Revista Geotemas; 2020.

6. Alves WS, Martins AP, Morais WA, et al. USLE modelling of soil loss in a Brazilian cerrado catchment. Remote Sensing Applications: Society and Environment. 2022; 27: 100788. doi: 10.1016/j.rsase.2022.100788

7. Dang X, Sun Y. Estimation of soil erosion in loess plateau based on geographic information system. Journal of Geography and Cartography. 2021; 5(1): 1. doi: 10.24294/jgc.v5i1.1410

8. Silva AMD, Silva MLN, Curi N, et al. Rainfall erosivity and erodibility of Cambissolo and Latossolo in the Lavras region, southern Minas Gerais. (Portuguese). Revista Brasileira de Ciência do Solo. 2009; 33(6): 1811-1820. doi: 10.1590/s0100-06832009000600029

9. Bonilla CA, Johnson OI. Soil erodibility mapping and its correlation with soil properties in Central Chile. Geoderma. 2012; 189-190: 116-123. doi: 10.1016/j.geoderma.2012.05.005

10. Guerra AJT, Fullen MA, Bezerra JFR, Jorge MCO. Gully Erosion and Land Degradation in Brazil: A Case Study from São Luís Municipality, Maranhão State. Cingapura: Springer Singapore; 2018.

11. Favis-Mortlock D. Erosion by Water: Accelerated. Managing Soils and Terrestrial Systems; 2020.

12. Barbosa WCS, Lima IMMF, Guerra AJT. Study of soil erosion in a gully located in the municipality of Miguel Alves-Piauí/Brazil, based on soil density and porosity parameters. (Portuguese). In: Pereira R, Cachada A, Rodríguez-Seijo A, et al. (editors). Solos e Desenvolvimento Sustentável: Desafios e Soluções, 1st ed. Porto: GreenUPorto-Centro de Investigação em Produção Agroalimentar Sustentável, U.Porto Press; 2021.

13. Delgado D, Sadaoui M, Ludwig W, et al. Depth of the pedological profile as a conditioning factor of soil erodibility (Rusle K-Factor) in Ecuadorian basins. Environmental Earth Sciences. 2023; 82(12). doi: 10.1007/s12665-023-10944-w

14. Freires EV, Silva Neto CÂ, Silva MT, et al. Mapping the erosivity and erodibility of the humid slope of the Uruburetama Massif and its surroundings as a subsidy to environmental planning. (Portuguese). Revista de Geociências do Nordeste. 2023; 9(2): 21-40. doi: 10.21680/2447-3359.2023v9n2id30719

15. Andriyani I, Indarto I, Soekarno S, et al. Analysis of rainfall erosivity factor (R) on prediction of erosion yield using USLE and RUSLE Model’s; A case study in Mayang Watershed, Jember Regency, Indonesia. Sains Tanah-Journal of Soil Science and Agroclimatology. 2024; 21(1): 64. doi: 10.20961/stjssa.v21i1.63641

16. Nur AH, Ahmed AH, Mohamed AA,et al. Geospatial Assessment of Aridity and Erosivity Indices in Northwest Somalia Using The CORINE Model. Journal of Environmental and Science Education. 2024.

17. Fullen MA, Catt JA. Soil Management: Problems and Solutions. Edward Arnold, Londres; 2004.

18. Moisa MB, Dejene IN, Merga BB, et al. Soil loss estimation and prioritization using geographic information systems and the RUSLE model: a case study of the Anger River sub-basin, Western Ethiopia. Journal of Water and Climate Change. 2022; 13(3): 1170-1184. doi: 10.2166/wcc.2022.433

19. Amraoui M, Bouabidi L, El Amrani M, et al. Land Use Dynamics And Soil Conservation Strategies In The El Kssiba Region, Atlas Mountains Of Morocco. The Journal “Agriculture and Forestry”. 2024; 70(3). doi: 10.17707/agricultforest.70.3.01

20. Ennaji N, Ouakhir H, Abahrour M, et al. Impact of watershed management practices on vegetation, land use changes, and soil erosion in River Basins of the Atlas, Morocco. Notulae Botanicae Horti Agrobotanici Cluj-Napoca. 2024; 52(1): 13567. doi: 10.15835/nbha52113567

21. MMA, Ministério do Meio Ambiente. Parnaíba Hydrographic Region Booklet. (Portuguese). Secretaria de Recursos Hídricos-Brasília: MMA; 2006.

22. Nascimento JRS, Marcuzzo FFN, Pinto EJA. Maps of annual and monthly rainfall distribution and pluviogram of the Parnaíba river basin. (Portuguese). ABRH; 2020.

23. HidroWeb. Historical rainfall series. (Portuguese). Available online: https://www.snirh.gov.br/hidroweb/ (accessed on 12 July 2023).

24. Pinto EJA, Azambuja, AD, Farias JAM, et al. Rainfall atlas of Brazil: monthly isopleths, quarterly isopleths, annual isopleths, driest months, wettest months, driest quarters, wettest quarters. (Portuguese). Brasília: CPRM; 2011.

25. Bertone J, Lombardi Neto F. Soil Conservation (Portuguese). Icone Editora Ltda: São Paulo; 2014.

26. Mannigel AR, E Carvalho MDP, Moreti D, et al. Erodibility factor and soil loss tolerance in the State of São Paulo. (Portuguese). Acta Scientiarum Agronomy. 2008; 24: 1335. doi: 10.4025/actasciagron.v24i0.2374

27. Albuquerque AW, M. Filho G, Santos JR, et al. Determination of universal soil loss equation factors in Sumé, PB. (Portuguese). Revista Brasileira de Engenharia Agrícola e Ambiental. 2005; 9(2): 153-160. doi: 10.1590/s1415-43662005000200001

28. Aquino CMS, Oliveira JGB. Estimating the erodibility factor (k) of soil associations in the state of Piauí described in Jacomine (Portuguese). Revista Geotemas; 2017.

29. Farinasso M, Carvalho Júnior OA, Guimarães RF, et al. Qualitative Evaluation of the Potential for Laminar Erosion in Large Areas by Means of the EUPS Universal Soil Loss Equation Using New GIS Methodologies for Calculating its Factors in the Alto Parnaíba PI-MA Region. (Portuguese). Revista Brasileira de Geomorfologia. 2006; 7(2). doi: 10.20502/rbg.v7i2.80

30. Jacomine PKT, Paulo Klinger Tito Jacomine, C. Exploratory and reconnaissance survey of soils in the state of Piauí. (Portuguese). Embrapa Solos; 1986.

31. Wischmeier WH, Smith DD. Predicting Rainfall Erosion Losses: A Guide to Conservation Planning. Department of Agriculture, Science and Education Administration. 1978.

32. Renard KG, Freimund JR. Using monthly precipitation data to estimate the R-factor in the revised USLE. Journal of Hydrology. 1994.

33. Loureiro HAS, Guerra AJT. Landscapes of Geomorphology: Themes and Concepts of the 21st Century. (Portuguese). Rio de Janeiro: Bertrand Brasil; 2022.

34. Barbosa WCS, Lima IMMF, Guerra AJT. Multivariate analysis of the urban gully located in the southern portion of the Lower Parnaíba River basin. (Portuguese). William Morris Davis- Revista de Geomorfologia; 2021.

35. Tesfaye G, Bekele D, Eshetu M, et al. Gully Erosion Risk Assessment Using a GIS-Based Bivariate Statistical Models and Machine Learning in the Dodota Alem Watershed, Ethiopia. American Journal of Environmental Science and Engineering. 2024; 8(3): 49-64. doi: 10.11648/j.ajese.20240803.11




DOI: https://doi.org/10.24294/jgc9639

Refbacks

  • There are currently no refbacks.


Copyright (c) 2024 Wellynne Carla de Sousa Barbosa, Antonio José Teixeira Guerra, Iracilde Maria de Moura Fé Lima

License URL: https://creativecommons.org/licenses/by/4.0/

This site is licensed under a Creative Commons Attribution 4.0 International License.