Phosphorus transfer at a small catchment in southeastern Brazil: distributed modelling in different land use scenarios

Abstract

Identifying and ranking nutrient loss risk areas are important steps towards integrated catchment management. This study aimed to apply the P index model at the Posses catchment, south of the state of Minas Gerais, Brazil. We applied the P index for the current land use at the Posses catchment and for two hypothetical scenarios: scenario 1, in which P fertilizer was applied to all land uses, except for native forests; and scenario 2, which considered the use of P fertilizer as in scenario 1, and that the Environmental Protection Areas referring to the riparian forests and springs were totally restored. Considering current land use, almost the whole catchment area (91.4%) displayed a low P loss risk. The highest P index was associated to croplands and eucalyptus plantations. Regarding scenario 1, areas under pasture fell into the low (15.1%), medium (45.5%), high (27.1%) and very high (12.3%) P index categories. Environmental Protection Areas on scenario 2 decreased the P loss risk from the scenario 1 in 37.6%. Hence, the model outputs indicate that the reforestation of buffer zones can decrease P loss risk in the case increasing use of P fertilizer. The P index model is a potential support tool to promote judicious use of fertilizers and conservation practices at the Posses catchment.Index terms: P index; nutrient loss; water erosion; land use management; environmental services. RESUMOIdentificar e classificar áreas quanto ao risco de perda de nutrientes são passos importantes para o manejo integrado de bacia hidrográfica. O objetivo deste estudo foi aplicar o modelo Índice P na bacia hidrográfica das Posses, Extrema-MG. O Índice P foi empregado sobre as condições atuais de uso da terra na bacia hidrográfica das Posses e na simulação de dois cenários: cenário 1, o fertilizante P foi aplicado para todos os usos, exceto para florestas nativas e, cenário 2, além do fertilizante P ser aplicado da mesma forma que no cenário 1, considerou-se que as Áreas de Proteção Ambiental referentes as matas ciliares e nascentes fossem totalmente restituídas. Considerando o uso atual, quase toda a bacia hidrográfica (91,4%) apresentou baixo risco de perda de P. O maior Índice de P foi associado a lavouras e plantações de eucalipto. No cenário 1, as pastagem apresentaram Índice P baixo (15,1%), médio (45,5%), alto (27,1%) e muito alto (12,3%). No cenário 2, as Áreas de Proteção Ambiental promoveram uma redução de 37,6% no risco de perda de P do cenário 1. Dessa forma, os resultados do modelo indicam que o reflorestamento de matas ciliares pode reduzir o risco de perdas de P no caso do aumento do uso de fertilizantes. O Índice P é uma potencial ferramenta para promoção do uso criterioso de fertilizantes e de práticas conservacionistas na bacia hidrográfica das Posses.Termos para indexação: Índice P; perda de nutrientes; erosão hídrica; gestão do uso da terra; serviços ambientais.

Water erosion modeling by the Erosion Potential Method and the Revised Universal Soil Loss Equation: a comparative analysis

“…The retention coefficient (Ru) of the sub-basin was calculated at 0.995, indicating that 9.95% of the sediments generated in the area reach watercourses (real soil loss), contributing to the silting up and the depreciation of water quality (Bispo et al, 2017).…”

Assessing sediment yield and streamflow with SWAT model in a small sub-basin of the Cantareira System

“…in which conc sed,ch,mx is the maximum concentration of sediment that can be transported by the water (Mg m -3 ), SPCON and SPEXP are the linear and exponent coefficients, and v ch,pk is the peak channel velocity (m s -1 ), which is given by q peak divided by the cross-sectional area of flow in the channel. (Bispo et al, 2017a;Silva et al, 2019).…”

Tracing the origin of reservoir sediments using magnetic properties in Southeastern Brazil

“…Research into soil and sediment losses by erosion have traditionally used standard erosion plots for monitoring water-driven erosion (Wischmeier & Smith, 1978;Anache et al, 2017). Certainly, erosion rate quantification using these methods is an essential part of monitoring agricultural practices in order to determine how soil management systems affect water and sediment runoff (Zhang, Nearing, Garbrecht, & Steiner, 2004;Bispo et al, 2017;Le Gall et al, 2017;Saran, Meneghine, Célico, Pinheiro, & Alves, 2017). However, although capable of providing useful information, such plots have limitations in terms of data representativeness, spatial and temporal resolution, and cost (Armstrong, Quinton, & Maher, 2012;Guzmán, Quinton, Nearing, Mabit, & Gómez, 2013;Deasy, Titman, & Quinton, 2014;Batista, Davies, Silva & Quinton, 2019).…”