Research article

Soil Loss Vulnerability in an Agricultural Catchment in the Atlantic Forest Biome in Southern Brazil

  • Received: 14 July 2016 Accepted: 21 November 2016 Published: 24 November 2016
  • This study estimates soil loss vulnerability using field samples and spatial data in a 30 km² area in the Atlantic forest biome in southern Brazil. The anthropogenic part of the landscape consists mainly of small agricultural properties. Soil loss vulnerability was calculated using adaptations of the universal soil loss equation. The results were compared to sediment data collected during field surveys. Spatial analysis was performed using a geographical information system (GIS) and fine resolution data (1 m). Both field and spatial analyses produced similar results, 5.390 tons of soil loss per year using field data and 5.691 tons per year using GIS. Using soil loss and sediment data related to the Concordia River, we estimate that of all the exported sediment 25% of the lost soil reaches the river. These data are an effective source of information for municipal administrators of the region, which consists of small agricultural catchments (dominated by small properties) that comprise the regional economy. A thematic map was used to determine sub-drainage priority as information for public managers.

    Citation: Rafael Gotardo, Gustavo A. Piazza, Edson Torres, Vander Kaufmann, Adilson Pinheiro. Soil Loss Vulnerability in an Agricultural Catchment in the Atlantic Forest Biome in Southern Brazil[J]. AIMS Geosciences, 2016, 2(4): 345-365. doi: 10.3934/geosci.2016.4.345

    Related Papers:

  • This study estimates soil loss vulnerability using field samples and spatial data in a 30 km² area in the Atlantic forest biome in southern Brazil. The anthropogenic part of the landscape consists mainly of small agricultural properties. Soil loss vulnerability was calculated using adaptations of the universal soil loss equation. The results were compared to sediment data collected during field surveys. Spatial analysis was performed using a geographical information system (GIS) and fine resolution data (1 m). Both field and spatial analyses produced similar results, 5.390 tons of soil loss per year using field data and 5.691 tons per year using GIS. Using soil loss and sediment data related to the Concordia River, we estimate that of all the exported sediment 25% of the lost soil reaches the river. These data are an effective source of information for municipal administrators of the region, which consists of small agricultural catchments (dominated by small properties) that comprise the regional economy. A thematic map was used to determine sub-drainage priority as information for public managers.


    加载中
    [1] Silva AM, Silva MLN, Curi N, et al. (2005) Perdas de solo, água, nutrientes e carbono orgânico em Cambissolo e Latossolo sob chuva natural. Pesq Agrop Bra 40: 1223-1230. doi: 10.1590/S0100-204X2005001200010
    [2] Karydas C, Sekuloska T, Silleos G (2009) Quantification and site-specification of the support practice factor when mapping soil erosion risk associated with olive plantations in the Mediterranean island of Crete. Environ Monit Assess 149: 19-28. doi: 10.1007/s10661-008-0179-8
    [3] Ganasri BP, Ramesh H (2015) Assessment of soil erosion by RUSLE model using remote sensing and GIS—A case study of Nethravathi Basin. Geosc Front: 1-9.
    [4] Lin BS, Thomas K, Chen CK, et al. (2016) Evaluation of soil erosion risk for watershed management in Shenmu watershed, central Taiwan using USLE model parameters. Paddy Water Environ 14: 19-43. doi: 10.1007/s10333-014-0476-5
    [5] Markose VJ, Jayappa KS (2016) Soil loss estimation and prioritization of sub-watersheds of Kali River basin, Karnataka, India, using RUSLE and GIS. Environ Monit Assess: 188-225.
    [6] Rahman MR, Shi ZH, Chong C (2009) Soil erosion hazard evaluation: an integrated use of remote sensing, GIS and statistical approaches with biophysical parameters towards management strategies. Ecol Modell 220: 1724-1734. doi: 10.1016/j.ecolmodel.2009.04.004
    [7] Peter HBC, Chandler JH, Armstrong A (2010) Applying close range digital photogrammetry in soil erosion studies. Photogramm Rec 25: 240-265. doi: 10.1111/j.1477-9730.2010.00584.x
    [8] Wischmeier WH, Smith DD (1965) Predicting Rainfall-Erosion Losses from Gopland East of the Rocky Mountains. Agri Hand 282: 47.
    [9] Strand RI, Pemberton EL (1982) Reservoir sedimentation: Technical guidelines for Bureau of Reclamation. U.S. Bureau of Reclamation, Denver.
    [10] Ananda J, Herath G (2003) Soil erosion in developing countries: a socio-economic appraisal. J Environ Manag 68: 343-353. doi: 10.1016/S0301-4797(03)00082-3
    [11] Humberto BC, Rattan L (2008) Water erosion. In: Principles of soil conservation and management. Springer, New York, 21-53.
    [12] Jinren RN, Yingkui KL (2003) Approach to soil erosion assessment in terms of land-use structure changes. J Soil Water Conserv 58: 158-169.
    [13] Prasannakumar V, Shiny R, Geetha N, et al. (2011) Spatial prediction of soil erosion risk by remote sensing, GIS and RUSLE approach: A case study of Siruvani River watershed in Attapady valley, Kerala, India. Envir Ear Sc 64: 965-972. doi: 10.1007/s12665-011-0913-3
    [14] Chen T, Niu R, Ni P, et al. (2011) Regional soil erosion risk mapping using RUSLE, GIS, and remote sensing: A case study in Miyun Watershed, North China. Envir Ear Sc 63: 533-541. doi: 10.1007/s12665-010-0715-z
    [15] Beskow S, Mello CR, Norton LD, et al. (2009) Soil erosion prediction in the Grande River Basin. Brazil using distributed modeling. Catena 79: 49-59.
    [16] Cohen MJ, Shepherd KD, Walsh MG (2005) Empirical reformulation of the universal soil loss equation for erosion risk assessment in a tropical watershed. Geoderma 124: 235-252. doi: 10.1016/j.geoderma.2004.05.003
    [17] Werneck Lima JEF, Lopes WTA, Aquino FG, et al. (2014) Assessing the use of erosion modeling to support payment for environmental services programs. J of Soils and Sed 14: 1258-1265.
    [18] Mellerowicz KT, Rees HW, Chow TL, et al. (1994) Soil conservation planning at the watershed level using the Universal Soil Loss Equation with GIS and microcomputer technologies: a case study. J Soil Water Conser 49: 194-200.
    [19] Ha NM (2011) Application of USLE and GIS tool to predict soil erosion potential and proposal land cover solutions to reduce soil loss in Tay Nguyen. FIG Conference—Bridging the Gap Between Cultures—Marrakech, Morocco.
    [20] Karydas CG, Sekuloska T, Sarakiotis I (2005) Fine scale mapping of agricultural landscape features to be used in environmental risk assessment in an olive cultivation area. IASME Trans 2: 582-589.
    [21] Mati BM, Veihe A (2001) Application of the USLE in a savannah environment: comparative experiences from East and West Africa. Singap J Trop Geogr 22: 138-155. doi: 10.1111/1467-9493.00099
    [22] Angima SD, Stott DE, O'Neill MK, et al. (2003) Soil erosion prediction using RUSLE for central Kenyan highland conditions. Agric Ecosyst Environ 97: 295-308. doi: 10.1016/S0167-8809(03)00011-2
    [23] Kothyari UC, Tewari AK, Singh R (1994) Prediction of sediment yield. J of Irrig and Drain Eng ASCE 120: 1122-1131. doi: 10.1061/(ASCE)0733-9437(1994)120:6(1122)
    [24] Pandolfo C, Braga HJ, Silva Junior VP, et al. (2002) Atlas climático digital do Estado de Santa Catarina. Florianópolis: Epagri. CD-Rom.
    [25] Pinheiro A, Kaufmann V, Perazzoli M, et al. (2010) Avaliação dos escoamentos em diferentes escalas espaciais na bacia do ribeirão Concórdia [Evaluation of flows in diferentes patialscales in the Concórdia creek basin]. In X Symposium of Water Resources of Nordeste, Fortaleza 1: 1-11. Porto Alegre Brazil: ABRH.
    [26] Klein RM, Rodriguez HB (1978) Mapa Fitogeográfico do Estado de Santa Catarina [Phytogeographic map of the state of Santa Catarina]. In Mapa Fitogeográfico do Estado de Santa Catarina. Imprensa Oficial do Estado de Santa Catarina. IOESC. Florianópolis, SC, Brazil.
    [27] Wischmeier WH, Smith DD (1978) Predicting rainfall erosion losses: a guide to conservation planning. Agric Handb 537, Washington-D.C: USDA. 57 p.
    [28] Renard KG, Freimund JR (1994) Using monthly precipitation data to estimate the R-factor in the reviser USLE. J of Hydr 157: 287-306. doi: 10.1016/0022-1694(94)90110-4
    [29] Kim JB, Saunders P, Finn JT (2005) Rapid Assessment of soil erosion in the rio Lempa Basin, Central America, Using the Universal Soil Loss equation and Geographic Information Systems. Envir Manag 36: 872-885. doi: 10.1007/s00267-002-0065-z
    [30] Bertoni J, Lombardi Neto F (1998) Conservação do solo. 4. ed. São Paulo: Ícone Ed., 392 p.
    [31] Denardin JE (1990) Erodibilidade de solo estimada por meio de parâmetros físicos e químicos. 81p. Thesis (Doctored em Agronomy—Soil and Nutrition of Plants)—Escola Superior de Agricultura Luiz de Queiroz, Univ. de São Paulo, Piracicaba.
    [32] Caputo HP (1988) Mecânica dos Solos e suas aplicações. Fundamentos. 6º edição, Rio de Janeiro: Livros Técnicos e Científicos Editora.
    [33] Galindo ICL, Margolis E (1989) Tolerância de perdas por erosão para solos do Estado de Pernambuco. Rev Bra de Ciê do Solo 13: 95-100.
    [34] Alexakis DD, Hadjimitsis DG, Agapiou A (2013) Integrated use of remote sensing, GIS and precipitation data for the assessment of soil erosion rate in the catchment area of “Yialias” in Cyprus. Atm Resea 131: 108-124.
    [35] Ranzi R, Hung Le T, Rulli MC (2012) A RUSLE approach to model suspended sediment load in the Lo River (Vietnam): effects of reservoirs and land use changes. J of Hydrol: 422-423.
    [36] Paiva EMC, Paiva JBD (2001) Hidrologia aplicada à gestão de pequenas bacias hidrográficas. Porto Alegre: ABRH, 367 p.
    [37] Williams JR, Berndt HD (1977) Determining the universal soil equation`s length-slop factor for watershed. In: Soil Erosion: prediction and control. Ankeny: Soil Conservation Society of America: 217-255.
    [38] Bertol I, Shick J, Batistela O (2002) Razão de perdas de solo e Fator C para milho e aveia em rotação com outras culturas em três tipos de preparo de solo. Rev Bra de Ciê de Solo 26: 545-552. doi: 10.1590/S0100-06832002000200029
    [39] Martins SG, Silva MLN, Avanzi JC, et al. (2010) Fator cobertura e manejo do solo e perdas de solo e água em cultivo de eucalipto e em Mata Atlântica nos Tabuleiros Costeiros do Estado do Espírito Santo. Scien. Forest 38: 517-526.
    [40] Stein DP, Donzelli PL, Gimenez AF, et al. (1987) Potencial de erosão laminar, natural e antrópico, na Bacia do Peixe-Paranapanema. Anais 4º Simpósio Nacional de Controle de Erosão. Marília-SP: ABGE/DAEE: 105-135.
    [41] Tomzani JC, Mantovani LE, Bittencourt AVL, et al. (2005) Sistematização dos fatores da Eups em SIG para quantificação da erosão laminar na bacia do rio Anta Gorda (PR). Est Geog 3: 1-21.
    [42] Morgan RPC (1995) Soil erosion and Conservation. Longman Group Limited, 2 ed.
    [43] Silva AM, Schulz HE, Camargo PB (2007) Erosão e hidrossedimentologia em bacias hidrográficas. 2. Ed. São Carlos-SP: RiMa, 158 p.
    [44] Strand GH, Dramstad W, Engan G (2002) The effect of field experience on the accuracy of identifying land cover types in aerial photographs. Int J Appl Earth Obs Geoinf 4: 137-146. doi: 10.1016/S0303-2434(02)00011-9
    [45] Wanielista MP (1978) Storm water management: quality and quantity, Ann Arbor Science, 383 p.
    [46] Ali SA, Hagos H (2016) Estimation of soil erosion using USLE and GIS in Awassa catchment, Rift valley, Central Ethiopia. Geod Reg 7: 159-166.
    [47] Berberoglu S (2003) Sustainable management for the Eastern Mediterranean coast of Turkey. Env Manag 31: 442-451. doi: 10.1007/s00267-002-2724-5
    [48] Ali SA, Tesgaya D (2010) Landuse and landcover change detection between 1985–2005 in parts of Highland of Eastern Ethiopia using remote sensing and GIS techniques. Int J Geoinf 6: 35-40.
    [49] Meshesha DT, Tsunekawa A, Tsubo M, et al. (2014) Land use change and its socio-environmental impact in Eastern Ethiopia’s Highland. Reg Environ Chang 14: 757-768. doi: 10.1007/s10113-013-0535-2
    [50] Evrendilek F, Doygun H (2000) Assessing major ecosystem types and the challenge of sustainability in Turkey. Env Manag 26: 479-489. doi: 10.1007/s002670010106
    [51] Wali MK, Safaya NM, Evrendilek F (2002) Ecological rehabilitation and restoration in the Americas with special reference to the United States of America. In: Perrow MR, Davy AJ (Eds.) Handbook of Rest Ec 2. Cambridge University Press, Cambridge, 3-31.
    [52] Yang CT (1996) Sediment Transport: Theory and Practice. McGraw-Hill Book Company, Inc, New York.
    [53] EMBRAPA (1997) Manual de métodos de análise de solo. Rio de Janeiro. 2. ed. rev. EMBRAPA: 212 p.
    [54] Yang CT (1973) Incipient motion and sediment transport. J of the Hyd Div 99: 1679-1701.
    [55] Silva CR, Bressiani DA, Bettiol GM S, et al. (2014) Aplicação do Modelo SWAT (Soil and Water Assessment Tool) para estimar produção de sedimento e nutrientes na Microbacia Experimental da EMBRAPA Pecuária Sudeste. Simpósio Nacional de Instrumentação Agropecuária. São Carlos: 609-612.
    [56] Silva CR (2010) Aplicação do Modelo SWAT para estimar produção de sedimentos e transporte de fósforo e nitrogênio na microbacia do Ribeirão Canchim—EMBRAPA Pecuária Sudeste. Dissertação (Mestrado)—Escola de Engenharia de São Carlos, Universidade de São Paulo, São Carlos.
    [57] Vieira VF (2008) Estimativa de perdas de solo por erosão hídrica em uma sub-bacia hidrográfica. Geografia 17: 73-81.
    [58] Oliveira VA, Mello CR, Durões MF, et al. (2014) Vulnerabilidade a erosão do solo na bacia do rio Verde, Minas Gerais do Sul. Ciê Agrotec 38.
    [59] Pradeep GS, Ninu Krishnan MV, Vijith H (2014) Identification of critical soil erosion prone areas and annual average soil loss in an upland agricultural watershed of Western Ghats, using analytical hierarchy process (AHP) and RUSLE techniques. Arab J of Geosc 8: 3697-3711.
    [60] Gilles L, Cogo NP, Bissani CA, et al. (2009) Perdas de água, solo, matéria orgânica e nutriente por erosão hídrica na cultura do milho implantada em área de campo nativo, influenciadas por métodos de preparo do solo e tipos de adubação. Rev Bra de Ciê do Solo 33, p. 1427-1440.
    [61] Adinarayana J (2003) Spatial decision support system for identifying priority sites for watershed management schemes. In First interagency conference on research in the watersheds (ICRW) Arizona: Benson: 405-408.
    [62] Silva RM, Santos CAG, Montenegro SMGL (2012). Integration of GIS and remote sensing for estimation of soil loss and prioritization of critical sub-catchments: a case study of Tapacura catchment. Nat Haz 62: 953-970. doi: 10.1007/s11069-012-0128-2
    [63] Patel DP, Gajjar CA, Srivastava PK (2013) Prioritization of Malesari mini-watersheds through morphometric analysis: a remote sensing and GIS perspective. Env Ear Sc 69: 2643-2656. doi: 10.1007/s12665-012-2086-0
    [64] Khadse GK, Vijay R, Labhasetwar PK (2015) Prioritization of catchments based on soil erosion using remote sensing and GIS. Env Monit and Assess 187: 333. doi: 10.1007/s10661-015-4545-z
  • Reader Comments
  • © 2016 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(4244) PDF downloads(1196) Cited by(4)

Article outline

Figures and Tables

Figures(4)  /  Tables(10)

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog