Silva et al. (2025) Impact of precipitation variability on erosivity, runoff, and soil erosion in a semiarid basin: a case study from Northeast Brazil

Identification

• Journal: Theoretical and Applied Climatology
• Year: 2025
• Date: 2025-10-17
• Authors: Cássio Kaique da Silva, Richarde Marques da Silva, José Yure Gomes dos Santos, A. Pereira, Manoranjan Mishra
• DOI: 10.1007/s00704-025-05748-w

Research Groups

• Postgraduate Programme Civil and Environmental Engineering, Federal University of Paraíba, João Pessoa, Paraíba, Brazil
• Department of Geosciences, Federal University of Paraíba, João Pessoa, Paraíba, Brazil
• Department of Geography, Federal University of Rio Grande do Norte, Caicó, Rio Grande do Norte, Brazil
• Department of Civil and Environmental Engineering, Federal University of Paraíba, João Pessoa, Paraíba, Brazil
• Department of Geography, Fakir Mohan University, Vyasa Vihar, Nuapadhi, Balasore, Odisha, India
• Stokes School of Marine and Environmental Sciences, University of South Alabama, Mobile, Alabama, USA

Short Summary

This study investigated the impacts of precipitation variability on rainfall erosivity, runoff, and soil erosion in the Apodi–Mossoró River basin, Northeast Brazil, using climate indices and the SWAT model. Findings indicate a decline in extreme precipitation events and significant spatiotemporal variability in precipitation, which directly influences erosivity, runoff, and soil erosion patterns across the semiarid region.

Objective

• To evaluate the impacts of precipitation variability on rainfall erosivity, surface runoff, and soil erosion in the Apodi–Mossoró River basin, located in the Brazilian semiarid region.
• To characterize precipitation variability using statistical trend tests (Mann–Kendall, Sen’s slope estimator) and seven precipitation indices.
• To estimate precipitation erosivity using a regionally adapted equation.
• To simulate hydrological responses, including runoff and soil erosion, using the SWAT model.

Study Configuration

• Spatial Scale: Apodi–Mossoró River basin, Northeast Brazil, spanning an area of 15,103 km².
• Temporal Scale: 35 years (1984–2018), with a warm-up period (1984–1986), calibration (1987–2005), and validation (2006–2018).

Methodology and Data

• Models used:
  • Hydrological and sediment transport simulation: Soil and Water Assessment Tool (SWAT).
  • Statistical trend analysis: Mann–Kendall test and Sen’s slope estimator.
  • Precipitation indices: Maximum number of consecutive dry days (CDD), maximum precipitation in a single day (RX1DAY), maximum precipitation over five consecutive days (RX5DAY), number of days with precipitation > 10 mm/day (R10mm), > 50 mm/day (R50mm), > 100 mm/day (R100mm), and total annual precipitation on days exceeding the 95th percentile (R95p).
  • Rainfall erosivity estimation: Equation adapted for the Brazilian semiarid region (Silva, 2004).
  • Model performance evaluation: Coefficient of determination (R²), Nash–Sutcliffe efficiency (NSE), Kling–Gupta efficiency (KGE), and percent bias (Pbias).
• Data sources:
  • Hydro-meteorological data: Daily precipitation records from 15 rainfall gauges, runoff data from two gauging stations (Brazilian National Water Agency - ANA), and meteorological observations from one weather station (National Institute of Meteorology - INMET) for 1984–2018.
  • Digital Elevation Model (DEM): Advanced Spaceborne Thermal Emission and Reflection Radiometer – Global Digital Elevation Model (ASTER-GDEM) with 30 m resolution.
  • Land Use and Cover: MapBiomas Project (Landsat satellite imagery) for the year 2008.
  • Soil Types: Exploratory-reconnaissance soil survey of Rio Grande do Norte (Ministry of Agriculture) and Brazilian Soil Information System (EMBRAPA, 2015).

Main Results

• Extreme precipitation events showed a decline, with negative trends in R95p values and a statistically significant reduction in the annual frequency of daily precipitation events exceeding 100 mm and 50 mm (Z-test values of −0.37 and −0.44, respectively).
• Annual precipitation trend analysis revealed significant decreases at Antônio Martins (−2.90 mm/year), Martins (−2.38 mm/year), and Assu (−12.27 mm/year), while Campo Grande (1.51 mm/year) and Alexandria (1.98 mm/year) exhibited increases.
• The maximum number of consecutive dry days (CDD) ranged from 77% to 93%, indicating a prevalence of dry conditions across the basin.
• Annual average rainfall erosivity varied from 2,761 to 5,032 MJ·mm·ha⁻¹·h⁻¹·year⁻¹, with the highest values concentrated in Upanema, Felipe Guerra, Assu, and Martins.
• Rainfall erosivity showed negative trends at Antônio Martins (Z = −2.90), Martins (−2.38), and Areia Branca (−1.83), and positive trends at Alexandria (1.98), Campo Grande (1.51), and Riacho da Cruz (0.70).
• The SWAT model demonstrated robust performance for runoff simulation (R² = 0.849, NSE = 0.683, KGE = 0.748), though it showed a Pbias of 16.051%, indicating a tendency to overestimate flows.
• Spatial analysis of soil erosion revealed predominantly low rates (0.00 to 0.79 tons·ha⁻¹·year⁻¹) across much of the basin, but localized areas of high susceptibility (exceeding 93 tons·ha⁻¹·year⁻¹) were identified in the south-central and northwestern sectors.
• The observed average soil erosion was 3.64 tons·ha⁻¹·year⁻¹.
• A positive correlation was observed between rainfall erosivity, surface runoff, and soil erosion, with areas experiencing both high erosivity and high runoff also undergoing the greatest soil loss.

Contributions

• This study provides the first specific exploration of precipitation variability, rainfall erosivity, runoff dynamics, and soil erosion in the Apodi–Mossoró River basin.
• It addresses the scarcity of research on the complex interplay between precipitation variability and its effects on soil integrity and nutrient balance in semiarid regions, particularly concerning extreme precipitation events.
• The research offers scientific support for sustainable land and water management and adaptation strategies in semiarid environments under climate variability.

Funding

• Brazilian Federal Agency for the Support and Evaluation of Graduate Education (CAPES) – Finance Code 001
• National Council for Scientific and Technological Development, Brazil – CNPq (Grant Nos. 313358/2021-4, 309330/2021-1, 420031/2021-9, and 409800/2022-8)
• Federal University of Paraíba

Citation

@article{Silva2025Impact,
  author = {Silva, Cássio Kaique da and Silva, Richarde Marques da and Santos, José Yure Gomes dos and Pereira, A. and Mishra, Manoranjan and Santos, Celso Augusto Guimarães},
  title = {Impact of precipitation variability on erosivity, runoff, and soil erosion in a semiarid basin: a case study from Northeast Brazil},
  journal = {Theoretical and Applied Climatology},
  year = {2025},
  doi = {10.1007/s00704-025-05748-w},
  url = {https://doi.org/10.1007/s00704-025-05748-w}
}