Assessment of soil loss vulnerability in data-scarce watersheds in southern Brazil

Steinmetz, Alice Alonzo; Cassalho, Felício; Caldeira, Tamara Leitzke; Oliveira, Vinícius Augusto de; Beskow, Samuel; Timm, Luis Carlos

doi:10.1590/1413-70542018426022818

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Agricultural Sciences • Ciênc. agrotec. 42 (6) • Nov-Dec 2018 • https://doi.org/10.1590/1413-70542018426022818 copy

Assessment of soil loss vulnerability in data-scarce watersheds in southern Brazil

Avaliação da vulnerabilidade à perda de solos em uma bacia hidrográfica com dados escassos no sul do Brasil

Authorship SCIMAGO INSTITUTIONS RANKINGS

ABSTRACT

Soil erosion is currently one of the main concerns in agriculture, water resources, soil management and natural hazards studies, mainly due to its economic, environmental and human impacts. This concern is accentuated in developing countries where the hydrological monitoring and proper soil surveys are scarce. Therefore, the use of indirect estimates of soil loss by means of empirical equations stands out. In this context, the present study proposed the assessment of the Revised Universal Soil Loss Equation (RUSLE) with the aid of Geographical Information Systems (GIS) and remote sensing for two agricultural watersheds in southern Rio Grande do Sul - Brazil. Among all RUSLE factors, LS showed the closest patterns to the local when compared to the total annual soil loss, thus being a good indicator t of risk areas. The total annual soil loss varied from 0 to more than 100 t ha^-1 yr^-1, with the vast majority (about 65% of the total area) classified from slight to moderate rates of soil loss. The results estimated according to RUSLE indicated that over 10% of the study area presented very high to extremely high soil loss rates, thus requiring immediate soil conservation practices. The present study stands out as an important scientific and technical support for practitioners and decision-makers, being probably the first of its nature applied to extreme southern Brazil.

Index terms:
Soil erosion; revised universal soil loss equation; geographical information systems; remote sensing

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[1] ^*Corresponding author: alicesteinmetz@gmail.com

Erosivity (MJ mm ha^-1 h^-1 yr^-)	Erosivity class
0 - 2,452	Low erosivity
2,452 - 4,905	Medium erosivity
4,905 - 7,357	Medium-strong erosivity
7,357 - 9,810	Strong erosivity
>9,810	Very strong erosivity

Soil class	K fator (t h MJ^-1 mm^-1)	Reference
Neosol	0.0569	Marques et al. (1997MARQUES, J. J. et al. Adequação de métodos indiretos para estimativa da erodibilidade de solos com horizonte B textural no Brasil. Revista Brasileira de Ciência do Solo, 21(3):447-456, 1997. )
Planosol	0.0570	Silva, Paiva and Santos (2009SILVA, R. M.; PAIVA, F. M.; SANTOS, C. A. Análise do grau de erodiblidade e perdas de solo na bacia do Rio Capiá baseado em SIG e sensoriamento remoto. Revista Brasileira de Geografia Física, 2(1):26-40, 2009.)
Cambisol	0.0508	Araújo, Salviano and Neto (2011ARAÚJO, F.; SALVIANO, A.; NETO, M. Estimativa da erodibilidade de latossolos do Piauí. Scientia Plena, 7(10):6, 2011.)
Argisol	0.0330	Sá et al. (2004SÁ, M. A. C. et al. Estimativa da erodibilidade pela desagregação por ultra-som e atributos de solos com horizonte B textural. Pesquisa Agropecuária Brasileira , 39(7):691-699, 2004.)

Land use	C factor	Reference
Native forest	0.012	Farinasso et al. (2006FARINASSO, M. et al. Avaliação qualitativa do potencial de erosão laminar em grandes áreas por meio da EUPS utilizando novas metodologias em sig para os cálculos dos seus fatores na região do Alto Parnaíba-Pi-MA. Revista Brasileira de Geomorfologia, 7(2):73-85, 2006.)
Planted forest	0.032	Adapted from Panagos et al. (2015PANAGOS, P. et al. Estimating the soil erosion cover-management factor at the European scale. Land Use Policy, 48:38-50, 2015.)
Annual cropping	0.2	Adapted from Panagos et al. (2015PANAGOS, P. et al. Estimating the soil erosion cover-management factor at the European scale. Land Use Policy, 48:38-50, 2015.)
Cultivated pasture	0.01	Tomazoni et al. (2005TOMAZONI, J. C. et al. A sistematização dos fatores da EUPS em SIG para quantificação da erosão laminar na bacia do rio Anta Gorda (PR). Revista Eletrônica de Geografia, 3(1):01-21, 2005.)
Native grassland	0.01	Tomazoni et al. (2005TOMAZONI, J. C. et al. A sistematização dos fatores da EUPS em SIG para quantificação da erosão laminar na bacia do rio Anta Gorda (PR). Revista Eletrônica de Geografia, 3(1):01-21, 2005.)
Permanent cropping	0.02	Adapted from Panagos et al. (2015PANAGOS, P. et al. Estimating the soil erosion cover-management factor at the European scale. Land Use Policy, 48:38-50, 2015.)

Soil loss (t ha^-1 yr^-1)	Vulnerability	FRW (%)	PRW (%)
0 - 2.5	Slight	34.8	35.3
2.5 - 5	Slight to moderate	11.9	11.8
5 - 10	Moderate	18.0	18.8
10 - 15	Moderate to High	11.4	12.3
15 - 25	High	10.7	11.8
25 - 100	Very high	11.2	8.5
> 100	Extremely high	2	1.5

Vulnerability	Rock outcrop (%)	Neosol (%)	Planosol (%)	Cambisol (%)	Argisol (%)
Slight	100.0	19.7	63.1	28.8	33.4
Slight to moderate	0.0	3.0	9.5	9.5	12.5
Moderate	0.0	8.9	8.0	16.1	19.9
Moderate to High	0.0	10.7	4.3	12.3	12.7
High	0.0	18.0	4.5	15.3	11.7
Very high	0.0	36.5	8.2	14.5	8.4
Extremely high	0.0	3.3	2.4	3.6	1.4