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Scientific and technical knowledge of sugarcane cover-management USLE/RUSLE factor

ABSTRACT:

Sugarcane covers 10.6 Mha of Brazilian agricultural land (13 % of all cropland), mainly in the south-central region. In tropical climate conditions, the physiological characteristics of sugarcane allow a wide range of management systems with contrasting soil erosion outcomes. Models can assess these differences and the Universal Soil Loss Equation (USLE) based models are the most frequently used. The cover-management factor (C Factor) is the USLE input variable that represents the changes in soil cover and management. We collected, compared, and evaluated sugarcane C Factor values reported in technical and scientific literature to support modelers and soil scientists on the adequate choice of these values. We analyzed references reporting primary C Factor values and sources that applied these values or described them. We found 50 references, showing a wide value variation ranging from 0.0012 to 0.5800. Thirteen references were primary sources. We found seven primary sources for Brazilian sugarcane growing conditions, but only two papers were peer-reviewed. Sugarcane C Factor modelers frequently used C values based on a poor understanding and description of the methodological and geographical origin of these values and out of the context of the specific crop management systems of application. Therefore, the results may not be compatible with the study site conditions. The primary sources lack clarity in the description of the site–specific environmental and management conditions in which the C Factors were obtained, hindering the use of these specificities by the end user.

Keywords:
bibliometric research; modeling; soil loss

Introduction

Sugarcane is a primary crop in Brazil by the extension of cultivated areas (10.6 Mha, occupying 13 % of total cropped area), the high value of its production chain (US$ 22 billion yr−1) (IBGE, 2016Instituto Brasileiro de Geografia e Estatística [IBGE]. 2016. Systematic Survey of Agricultural Production = Levantamento Sistemático da Produção Agrícola. Brasileira. IBGE, Rio de Janeiro, RJ, Brazil. Available at: http://www.ibge.gov.br [Accessed July 26, 2016] (in Portuguese).
http://www.ibge.gov.br...
; FIESP, 2020Federação das Indústrias do Estado de São Paulo [FIESP]. 2020. Outlook Fiesp 2029: Projections for Brazilian Agribusiness. FIESP, São Paulo, SP, Brazil.), and for its importance in energy (ethanol and electricity) and food production. Production is expected to increase by 0.8 Mha and 35 % in volume until 2029 driven by increments in energy and food consumption (FIESP, 2020Federação das Indústrias do Estado de São Paulo [FIESP]. 2020. Outlook Fiesp 2029: Projections for Brazilian Agribusiness. FIESP, São Paulo, SP, Brazil.). This increase is directly related to land-use changes, with pastures located in less suitable and susceptible areas to erosion being replaced by sugarcane cultivation (Sparovek et al., 2009Sparovek, G.; Barretto, A.; Berndes, G.; Martins, S.; Maule, R. 2009. Environmental, land-use and economic implications of brazilian sugarcane expansion 1996-2006. Mitigation and Adaptation Strategies for Global Change 14: 285-298.; Spera et al., 2017Spera, S.; VanWey, L.; Mustard, L. 2017. The drivers of sugarcane expansion in Goiás, Brazil. Land Use Policy 66: 111-119.).

The physiological characteristics of sugarcane cultivation in tropical climates enable the adoption of a wide range of management systems including planting date, soil tillage, variety (influencing soil cover dynamic and harvesting date), planting density and row spacing, type of harvest, among others.

Sugarcane crops are planted close to the mills to reduce harvesting and logistic costs. By having the distance of the mills as the main factor defining land use, sugarcane occupies a wide range of soil and slope conditions occurring near the mills. In many cases, this results in sugarcane cultivated in highly erodible soil and slope conditions. According to Medeiros et al. (2016)Medeiros, G.O.R.; Giarola, A.; Sampaio, G.; Marinho, M.A. 2016. Estimates of annual soil loss rates in the state of São Paulo, Brazil. Revista Brasileira de Ciência do Solo 40: 1-18., sugarcane crops have expanded mainly to highly erodible soils and distinct climatic conditions, due to the wide range of available management options.

Models allow the understanding, prediction, and simulation of soil erosion. The Revised Universal Soil Loss Equation (RUSLE), described by Renard et al. (1997)Renard, K.G.; Foster, G.R.; Weesies, G.A.; McCool, D.K.; Yoder, D.C. 1997. Predicting Soil Erosion by Water: A Guide to Conservation Planning with the Revised Universal Soil Loss Equation (RUSLE). USDA, Washington, DC, USA. (Agricultural Handbook, 703)., is the currently most widely used model for soil loss prediction (Zhuang et al., 2015Zhuang, Y.; Du, C.; Zhang, L.; Du, Y.; Li, S. 2015. Research trends and hotspots in soil erosion from 1932 to 2013: a literature review. Scientometrics 105: 743-758.), due to its operational simplicity.

The RUSLE consists of six factors (R, K, L, S, C, and P). The cover-management factor (C Factor) reports the interaction of phenological (canopy cover, dry matter production, and production cycle) and management (tillage, planting and harvesting dates, and soil cover) conditions with environmental information (precipitation). The RUSLE C Factor and its subfactors are an evolution from the USLE C Factor (original model described by Wishmeier and Smith (1978)Wischmeier, W.H.; Smith, D.D. 1978. Predicting Rainfall Erosion Losses: A Guide to Conservation Planning. USDA, Washngton, DC, USA. (Agricultural Handbook, 537).). The USLE C Factor uses tree variables to determinate the soil loss ratio: i) soil cover, ii) canopy cover, and iii) canopy hight. The RUSLE approach is an evolution of USLE and it has five subfactors: i) previous land use, ii) canopy cover, iii) soil cover, iv) soil roughness, and v) soil moisture (canopy hight was merged with canopy cover subfactor).

For semi-perennial crops and crops with highly variable management systems, such as sugarcane, long-term and laborious experimental studies needed to obtain direct C Factors, as described in the USLE manuals (Wischmeier and Smith, 1978Wischmeier, W.H.; Smith, D.D. 1978. Predicting Rainfall Erosion Losses: A Guide to Conservation Planning. USDA, Washngton, DC, USA. (Agricultural Handbook, 537).), restrict the availability of primary values based on experiments. In addition, the experimental determination of C Factor values for different crop and management systems has focused mainly on temperate climate crops (Wischmeier and Smith, 1978Wischmeier, W.H.; Smith, D.D. 1978. Predicting Rainfall Erosion Losses: A Guide to Conservation Planning. USDA, Washngton, DC, USA. (Agricultural Handbook, 537).; Morgan, 2005Morgan, R.P.C. 2005. Soil Erosion and Conservation. 3ed. Blackwell, Oxford, UK.).

Considering the importance of sugarcane, its large management options variability, and its impacts on soil conservation, we have carried out a broad literature survey on sugarcane C Factors. We compared and analyzed the sources to subsidize modelers and soil scientists on an adequate choice of this variable and reported on the scientific gaps on the topic. We also reported on how wrong references may be propagated by authors who do not take into account all descriptions of the primary sources of this information.

Materials and Methods

The bibliographic research used online databases and national and international technical and academic publications (up to 18 Mar 2020). The databases used were: Web of Science™, Scopus®, the library system at the University of São Paulo (DEDALUS - USP), the library system at the São Paulo State University (P@rthenon - UNESP), agricultural research databases from the Brazilian Agricultural Research Corporation (BSP@ - EMBRAPA), library system of the Agronomic Institute of Campinas (SophiA® - IAC), Google Scholar, and Google.

The terms used in the survey were “sugarcane C Factor” and its variations in Portuguese and English. We traced the citations back in time to find the original reference that generated the current citation. We labeled the references with the following information:

  • value or multiple C values;

  • conditions: environmental and management of the research site;

  • agreement between the C value and the modeling conditions: comparison between the reference value conditions (quoted) and the conditions where the model was applied;

  • methodology to obtain or cite the C value: primary source, indirect C value determination method, or aforementioned citation;

  • author(s) (year): authors and publication year of the reference;

  • study location: the place where the reference was developed;

  • type of reference: i) book; ii) article; iii) dissertation/thesis; or iv) technical/congress paper.

Results and Discussion

In total, we found and analyzed 50 references using sugarcane C Factor. The C Factor values found ranged from 0.0012 to 0.5800 (Table 1). Eleven references are primary sources, with seven developed by experimentation in standard USLE plots and four based on soil cover development data. The C Factors from three references cited were not available in the originals: Wischmieier and Smith (1978)Wischmeier, W.H.; Smith, D.D. 1978. Predicting Rainfall Erosion Losses: A Guide to Conservation Planning. USDA, Washngton, DC, USA. (Agricultural Handbook, 537)., Mitchell and Bubenzer (1980)Mitchell, J.K.; Bubenzer, G.D. 1980. Soil loss estimation. p.17-62. In: Kirkby, M.J.; Morgan, R.P.C., eds. Soil erosion. John Wiley, Chichester, England. and Bertoni and Lombardi Neto (1990Bertoni, J.; Lombardi Neto, F. 1990. Soil Conservation = Conservação do solo. Ícone, São Paulo, SP, Brazil (in Portuguese).). Another four were cited; however, we were unable to access their sources: Soil Conservation Service (1975), Hamer (1981), Arsyad (2010), and SASA (2002). A summary of the results is shown in Figure 1, which presents the publication year (y-axis), factor values, reference type, and citation of the primary sources of the references.

Table 1
Description of the sugarcane C Factor references ordered by publication year.
Figure 1
References of sugarcane C Factors and its connections (arrows): by value range (the shape size is proportional to the values, the continuous lines represent maximum values and internal dotted lines the minimum values), by type of publication (color), year (vertical position in the graph), and primary source or citation (format). The red arrows transpose citations or other arrows, but not a new symbol.

The most frequent C Factor values ranged from 0.1 to 0.2 (40 % of the values), followed by the 0.3-0.4 cluster, with 24 %. The mean value was 0.1872 and the median 0.1308 (Figure 2). This variation is partially explained by the great diversity of sugarcane management systems. From a geographical viewpoint, Brazilian references are concentrated in the southern and southeastern regions, as observed in a bibliographic survey on accelerated erosion by Barretto et al. (2008)Barretto, A.G.O.P.; Barros, M.G.E.; Sparovek, G. 2008. Bibliometrics, history and geography of Brazilian research on accelerated soil erosion. Revista Brasileira de Ciência do Solo 32: 2443-2460 (in Portuguese, with abstract in English).. Although sugarcane is also cropped in the central-western and northeastern regions, most C Factors were also determined for south and southeast Brazil.

Figure 2
Total and relative frequency of the C Factor in the analyzed references by range of values.

Ribeiro and Alves (2007)Ribeiro, L.S.; Alves, M.G. 2007. Quantification of Soil Loss by erosion using geoprocessin tchniques in the municipality of Campos dos Goytacazes / RJ. In: XIII Simpósio Brasileiro de Sensoriamento Remoto. Florianópolis, SC, Brazil (in Portuguese, with abstract in English)., De Maria et al. (1994)De Maria, I.C.; Lombardi Neto, F.; Dechen, S.C.F.; Castro, O.M. 1994. Cover-Management Factor of the Universal Soil Loss Equation (USLE) for the sugarcane = Fator da equação universal de perdas de solo (EUPS) para a cultura da cana-de-açúcar. In: Reunião Brasileira de Manejo e Conservação do Solo e da Água. Florianópolis, SC, Brazil (in Portuguese)., and Donzelli et al. (1992)Donzelli, P.L.; Valério Filho, M.; Pinto, A.S.; Nogueira, F.P.; Rotta, C.L.; Lombardi Neto, F. 1992. Remote Sensing techniques applied to diagnosis for Watershead's planning and monitoring = Técnicas de Sensoriamento Remoto aplicadas ao diagnóstico básico para planejamento e monitoramento de microbacias hidrográficas. p. 91-119. In: Lombardi Neto, F.; Camargo, A.O., eds. São Joaquim Watershed (Pirassununga, SP) = Microbacia do Córrego São Joaquim (Município de Pirassununga, SP). Instituto Agronômico, Campinas, SP, Brazil. (Documentos IAC, 29) (in Portuguese). were the most cited references, each cited by three other authors. Of these, only the work of De Maria et al. (1994)De Maria, I.C.; Lombardi Neto, F.; Dechen, S.C.F.; Castro, O.M. 1994. Cover-Management Factor of the Universal Soil Loss Equation (USLE) for the sugarcane = Fator da equação universal de perdas de solo (EUPS) para a cultura da cana-de-açúcar. In: Reunião Brasileira de Manejo e Conservação do Solo e da Água. Florianópolis, SC, Brazil (in Portuguese). is a primary source.

Of all the references that cited the C Factor values, only nine authors used primary sources (Aragão et al., 2013Aragão, R.; Cruz, M.A.S.; Amorim, J.R.A.; Mendonça, L.C.; Figueiredo, E.E.; Srinivasan, V.S. 2013. Sensitivity analysis of the parameters of the SWAT model and simulation of the hydrosedimentological processes in a watershed in the northeastern region of Brazil. Revista Brasileira de Ciência do Solo 37: 1091-1102 (in Portuguese, with abstract in English).; Andrade et al., 2011Andrade, N.S.F.; Martins Filho, M.V.; Torres J.L.R.; Pereira, G.T.; Marques Júnior, J. 2011. Economic and technical impact in soil and nutrient loss through erosion in the cultivation of sugar cane. Engenharia Agrícola 31: 539-550 (in Portuguese, with abstract in English).; Bacchi et al., 2003Bacchi, O.O.S.; Reichardt, K.; Sparovek, G. 2003. Sediment spatial distribution evaluated by three methods and its relation to some soil properties. Soil and Tillage Research 69: 117-125.; Sparovek et al., 2000Sparovek, G.; Bacchi, O.O.S.; Schung, E.; Ranieri, S.B.L.; De Maria, I.C. 2000. Comparison of three water erosion prediction methods (137Cs, WEPP, USLE) in south-east braszilian sugarcane production. Der Tropenlandwirt 101: 107-118.; Vasquez-Fernádez, 1996Vázquez-Fernández, G.A.; Formaggio, A.R.; Epiphanio, J.C.N.; Gleriani, J.M. 1996. Determination of cropsequences using aerial photography to characterize USLE's C factor C. In: VIII Simpósio Brasileiro de Sensoriamento Remoto. Salvador, BA, Brazil (in Portuguese, with abstract in English).; Ramos-Scharrón, 2015Ramos-Scharrón, C.E.; Torres-Pulliza, D.; Hernánzes-Delagado, E.A. 2015. Watershed- and island wide-scale land cover changes in Puerto Rico (1930s-2004) and their potential effects on coral reef ecosystems. Science of the Total Environment 506: 241-251.; Mata, 2009Mata, C.L. 2009. Multitemporal analysis of erosive susceptibility in the Urucuia River basin (MG) using the universal soil loss equation. Master's Dissertation. Universidade de Brasília, Brasília, DF, Brazil (in Portuguese, with abstract in English).; Vis, 1987Vis, M. 1987. A procedure for The Analysis of Soil Erosion and Related Problems in Water and Land Resources Management Studies. IRC, The Hague, The Netherlands.; Brooks, 1977Brooks, F.L. 1977. Use of the universal soil loss equation in Hawaii. p. 22-30. In: SCSA. Soil erosion: prediction and control. SCSA, West Lafayette, IN, USA.). Personal communications or unpublished data were used by two authors (Donzelli et al., 1992Donzelli, P.L.; Valério Filho, M.; Pinto, A.S.; Nogueira, F.P.; Rotta, C.L.; Lombardi Neto, F. 1992. Remote Sensing techniques applied to diagnosis for Watershead's planning and monitoring = Técnicas de Sensoriamento Remoto aplicadas ao diagnóstico básico para planejamento e monitoramento de microbacias hidrográficas. p. 91-119. In: Lombardi Neto, F.; Camargo, A.O., eds. São Joaquim Watershed (Pirassununga, SP) = Microbacia do Córrego São Joaquim (Município de Pirassununga, SP). Instituto Agronômico, Campinas, SP, Brazil. (Documentos IAC, 29) (in Portuguese).; Cavalieri, 1998Cavalieri, A. 1998. Land Use adequacy in Mogi Mirim (SP) region using different methods. PhD Thesis. Universidade Estadual de Campinas, Campinas, SP, Brazil (in Portuguese, with abstract in English).). Sources that do not include C Factor values for sugarcane occurred in three references (Silva et al., 2007Silva, A.M.; Casatti, L.; Álvares, C.A.; Leite, A.M.; Martinelli, L.A.; Durrant, S.F. 2007. Soil loss risk and habitat quality in streams of a meso-scale river basin. Scientia Agrícola 64: 336-343.; Morgan, 1986Morgan, R.P.C. 1986. Soil Erosion and Conservation. Longman, Oxford, UK.; Costa and Silva, 2012Costa, S.G.F.; Silva, R.M. 2012. Anthropic and natural potencial of erosion in the Garnaíra Basin Experimental. Cadernos do LOGEPA 7: 72-91 (in Portuguese, with abstract in English).), and the remaining studies use non-primary citations. The primary sources were mainly published in unreviewed formats, such as technical reports, theses, or dissertations, and congress papers (Figure 3). Most references used C Factors in studies related to soil loss predictions.

Figure 3
Quantity of each reference class by type of information (primary or citation) of the works analyzed.

C factor values determined in Brazil

Seven out of 13 primary references were developed in Brazil. The first Brazilian efforts are from the 1980s and 1990s and were developed at the Agronomic Institute of Campinas (IAC), as noted in the references by Donzelli et al. (1992)Donzelli, P.L.; Valério Filho, M.; Pinto, A.S.; Nogueira, F.P.; Rotta, C.L.; Lombardi Neto, F. 1992. Remote Sensing techniques applied to diagnosis for Watershead's planning and monitoring = Técnicas de Sensoriamento Remoto aplicadas ao diagnóstico básico para planejamento e monitoramento de microbacias hidrográficas. p. 91-119. In: Lombardi Neto, F.; Camargo, A.O., eds. São Joaquim Watershed (Pirassununga, SP) = Microbacia do Córrego São Joaquim (Município de Pirassununga, SP). Instituto Agronômico, Campinas, SP, Brazil. (Documentos IAC, 29) (in Portuguese). and Cavalieri (1998)Cavalieri, A. 1998. Land Use adequacy in Mogi Mirim (SP) region using different methods. PhD Thesis. Universidade Estadual de Campinas, Campinas, SP, Brazil (in Portuguese, with abstract in English).. These studies cited personal communications from IAC researchers based on ongoing experiments. The first published reference with C Factor calculated in Brazil was prepared by Stein et al. (1987)Stein, D.P.; Donzelli, P.L.; Gimenez, A.F.; Ponçano, W.L.; Lombardi Neto, F. 1987. Laminar, natural, and anthropic potencial erosionin the Paranapanema Peixe Watershead = Potencial de erosão laminar, natural e antrópica, na Bacia do Peixe Paranapanema. p. 105-135. In: IV Simpósio Nacional de Controle de Erosão. Marília, SP, Brazil (in Portuguese)., based on a methodology defined by Bertoni and Lombardi Neto (1985Bertoni, J.; Lombardi Neto, F. 1985. Soil Conservation = Conservação do Solo. Ícone, São Paulo, SP, Brazil (in Portuguese).), and published in the Annals of the IV National Symposium on Erosion Control, 1987. The reference by De Maria et al. (1994)De Maria, I.C.; Lombardi Neto, F.; Dechen, S.C.F.; Castro, O.M. 1994. Cover-Management Factor of the Universal Soil Loss Equation (USLE) for the sugarcane = Fator da equação universal de perdas de solo (EUPS) para a cultura da cana-de-açúcar. In: Reunião Brasileira de Manejo e Conservação do Solo e da Água. Florianópolis, SC, Brazil (in Portuguese). was developed in standard plots in a sugarcane management system of three cuts in two different soils and could be considered a milestone because it was the first publication based on experimental values obtained in field plots. The reference is available in summary form with limited detail in methodology description, printed in the Proceedings of the Brazilian Soil and Water Management and Conservation Meeting (1994), with no peer-review.

Amaral (2003)Amaral, N.S. 2003. Spatial variability of the erosion risk and expectative of soil loss for the Usina São Domingos (Catanduva, SP). Monography. Universidade Estadual Paulista, Jaboticabal, SP, Brazil (in Portuguese, with abstract in English). and Serra (2004)Serra, A.S. 2004. Prediction and risk of erosion in the FCAV/UNESP – Jaboticabal (SP). Completion of Course Work. Universidade Estadual Paulista, Jaboticabal, SP, Brazil (in Portuguese, with abstract in English). developed Sugarcane C Factor values for the Catanduva (SP) and Jaboticabal (SP) regions, respectively. Amaral (2003)Amaral, N.S. 2003. Spatial variability of the erosion risk and expectative of soil loss for the Usina São Domingos (Catanduva, SP). Monography. Universidade Estadual Paulista, Jaboticabal, SP, Brazil (in Portuguese, with abstract in English). used standard plots, with the adoption of artificial rain and collecting gutters, while Serra (2004)Serra, A.S. 2004. Prediction and risk of erosion in the FCAV/UNESP – Jaboticabal (SP). Completion of Course Work. Universidade Estadual Paulista, Jaboticabal, SP, Brazil (in Portuguese, with abstract in English). used previous values of soil loss ratio (SLR) determinated by Pundek (1994)Pundek, M. 1994. Universal Equation of Soil Loss's application for the conditions of Santa Catarina = Utilização prática da equação universal de perdas de solo para as condições de Santa Catarina. p. 99-129. In: EPAGRI. Soil and water conservation handbook: Recovery's projects and Watershead's management = Manual de uso, manejo e conservação do solo e da água: projeto de recuperação, conservação e manejo dos recursos naturais em microbacias hidrográficas. EPAGRI, Florianópolis, SC, Brazil (in Portuguese).. Both are undergraduate course completion studies, with restricted circulation and no peer-review.

Weill and Sparovek (2008)Weill, M.A.M.; Sparovek, G. 2008. Erosion study in the Ceveiro Watershed (Piracicaba, SP). I. Estimation o soil loss rates and sensitivity factor analysis of the USLE model. Revista Brasileira de Ciência do Solo 32: 801-814 (in Portuguese, with abstract in English). developed soil erosion modeling using sugarcane C Factors. In their study, the C Factor value (0.3066) was calculated based on a publication by Machado et al. (1982)Machado, E.C.; Pereira, A.R.; Fahl, J.I.; Arruda, H.V.; Cione, J. 1982. Biometric indices of two sugarcane varieties. Pesquisa Agropecuária Brasileira 17: 1323-1329 (in Portuguese, with abstract in English)., in which biometric indices for sugarcane were determined according to days after planting. The methodology determined is not specified in the study. This was the first Brazilian article submitted to a peer-review in which a new C Factor value for sugarcane was published.

An article (Corrêa et al., 2016Corrêa, E.A.; Moraes, I.C.; Pinto, S.A.F.; Lupinacci, C.M. 2016. Soil losses, soil loss ratio and cover management factor of sugarcane: a first approach. Revista do Departamento de Geografia 32: 72-87 (in Portuguese, with abstract in English).) elaborated from a PhD thesis (Corrêa, 2016Corrêa, E.A. 2016. Soil loss and vegetation indexes: methodological proposal for determining factor C (MEUPS) in pastures and sugarcane. PhD Thesis. Universidade Estadual Paulista, Rio Claro, SP, Brazil (in Portuguese, with abstract in English).) comprehensively explored C Factors and Modified Universal Soil Loss Equation (MUSLE), in which four values were calculated based on standard plots and natural rainfall, with variations in the planting date, number of cuts (ratoon or first harvest), previous use, and straw maintenance on the soil surface, resulting in values from 0.1308 to 0.4100.

Primary sources generally have a simplified description of the management systems. Important crop management features were not described or were only partially defined, such as tillage date, planting technology, rotation with soil cover crop, number of harvet cycles, and straw management.

Variations regarding the C Factor value

The lowest C Factor value among the references analyzed was 0.0012 by Costa and Silva (2012)Costa, S.G.F.; Silva, R.M. 2012. Anthropic and natural potencial of erosion in the Garnaíra Basin Experimental. Cadernos do LOGEPA 7: 72-91 (in Portuguese, with abstract in English). in a humid tropical climate in the Atlantic Forest biome of Paraíba State. This value has the same magnitude order as natural forests (Martins et al., 2010Martins, S.G.; Silva, M.L.N.; Avanzi, J.C.; Curi, N.; Fonseca, S. 2010. Cover-management factor and soil and water losses from eucalyptus cultivation and Atlantic Forest at the Coastal Plain in the Espírito Santo state, Brazil. Scientia Forestalis 38: 517-526 (in Portuguese, with abstract in English).; Wischmeier and Smith, 1978Wischmeier, W.H.; Smith, D.D. 1978. Predicting Rainfall Erosion Losses: A Guide to Conservation Planning. USDA, Washngton, DC, USA. (Agricultural Handbook, 537).). The highest value was 0.5800 by Evensen et al. (2001)Evensen, C.I.; El-Swaify, S.A.; Smith, C.W. 2001. C-factor development for sugarcane in Hawaii Soil erosion research for the 21st century. In: Proceedings of the International Symposium of ASAE. ASAE, St. Joseph, MO, USA., in a study developed in the state of Hawaii (USA), where the sugar cane cycle lasts 24 months and soil cover develops slower than in the Brazilian growing conditions, resulting in larger C values. Considering the range between the lowest and highest C Factors in the references, soil erosion modelers who choose C values based only on land use may produce results in a range of 480 times in soil loss values. Crop management systems and site conditions are more influential on C Factors than the land use by itself. The range of the sugarcane management systems is an issue for modelers to choose the right C Factor value. Few references describe deeply the management systems (see columns “Conditions” and “Compatibility with the original value” in Table 1).

Another critical point is the discontinuity or adaptations of C values among citations without further explanations. The book of Mitchel and Bubenzer (1980)Mitchell, J.K.; Bubenzer, G.D. 1980. Soil loss estimation. p.17-62. In: Kirkby, M.J.; Morgan, R.P.C., eds. Soil erosion. John Wiley, Chichester, England. does not present C Factor values for sugarcane; nevertheless, it is the reference Silva et al. (2007)Silva, A.M.; Casatti, L.; Álvares, C.A.; Leite, A.M.; Martinelli, L.A.; Durrant, S.F. 2007. Soil loss risk and habitat quality in streams of a meso-scale river basin. Scientia Agrícola 64: 336-343. used as source with a value of 0.1743. The primary source in De Maria et al. (1994)De Maria, I.C.; Lombardi Neto, F.; Dechen, S.C.F.; Castro, O.M. 1994. Cover-Management Factor of the Universal Soil Loss Equation (USLE) for the sugarcane = Fator da equação universal de perdas de solo (EUPS) para a cultura da cana-de-açúcar. In: Reunião Brasileira de Manejo e Conservação do Solo e da Água. Florianópolis, SC, Brazil (in Portuguese). presents a value of 0.11, but Sparovek et al. (2000)Sparovek, G.; Bacchi, O.O.S.; Schung, E.; Ranieri, S.B.L.; De Maria, I.C. 2000. Comparison of three water erosion prediction methods (137Cs, WEPP, USLE) in south-east braszilian sugarcane production. Der Tropenlandwirt 101: 107-118. and Bacchi et al. (2003)Bacchi, O.O.S.; Reichardt, K.; Sparovek, G. 2003. Sediment spatial distribution evaluated by three methods and its relation to some soil properties. Soil and Tillage Research 69: 117-125. present this reference with changed C Factor value of 0.3611.

The C Factor is conceptually and originally annual; however, for semi perennial crops such as sugarcane, the entire crop cycle, including ratoons and crop rotations, should be taken into account for C Factor determination (Wischmeier and Smith, 1961Wischmeier, W.H.; Smith, D.D. 1961. A Universal Equation for Predicting Rainfall-Erosion Losses: An Aid to Conservation Farming in Humid Regions. USDA, Washington, DC, USA. (ARS Special Report, 22-66).; Wischmeier and Smith, 1978Wischmeier, W.H.; Smith, D.D. 1978. Predicting Rainfall Erosion Losses: A Guide to Conservation Planning. USDA, Washngton, DC, USA. (Agricultural Handbook, 537).). For sugarcane, it is not possible to determine the C Factor for USLE (Wischmeier and Smith, 1978Wischmeier, W.H.; Smith, D.D. 1978. Predicting Rainfall Erosion Losses: A Guide to Conservation Planning. USDA, Washngton, DC, USA. (Agricultural Handbook, 537).) or RUSLE (Renard et al., 1997Renard, K.G.; Foster, G.R.; Weesies, G.A.; McCool, D.K.; Yoder, D.C. 1997. Predicting Soil Erosion by Water: A Guide to Conservation Planning with the Revised Universal Soil Loss Equation (RUSLE). USDA, Washington, DC, USA. (Agricultural Handbook, 703).) with a single year of data collection. However, it is possible to have a partial C Factor value of the crop for the period in one year. Therefore, multi-annual long-term studies are necessary until the soil cover and management variables become constant. This original concept does not invalidate the generation of partial C Factor values, nor their use, as long as this aspect is consistent with the results reported.

Conclusion

The analyses presented here allow affirming that:

  • There are few references from primary sources (predominance of citations).

  • We found cases of errors in referenced values (misleading citations).

  • As expected, because of the large variation in crop management options, there is a wide range of described C Factor values.

  • By linking the C Factor to land use types rather than to the management system, the considerable variation for C Factors is disregarded and may lead to estimation errors.

  • There are few primary data sources for Brazilian conditions (six) and only one reference with peer-review.

There is a trend towards more significant scientific advances in modeling than in experimental work, as historically reported by Hartemink et al. (2001)Hartemink, A.E.; McBratney, A.B.; Cattle, J.A. 2001. Developments and trends in soil science: 100 volumes of Geoderma 1967-2001. Geoderma 100: 217-268.. The demand for reliable input data for modelers is growing. The use of primary sources as inputs is essential to learn about the reference origin and methodology assessment, reducing the chance of errors or incompatibility of values.

Modelers need to rethink the use of soil erosion models, mainly the data input, otherwise, mistakes may be made and credibility could be lost. All uncertainty must be clearly explained in the sources. If there are gaps in the input database, alternatives soil loss models could be considered.

The search for regional values, analysis of the complete sugarcane crop cycle, and a clear description of the adopted management system are basic premises for generating and using precise C Factor values. The experimental determination of C-factors values for all possible and practically adopted management systems for sugarcane production in Brazil is challenging, if not impossible, due to its diversity and constant improvements.

An alternative way to determine such a wide range of C Factors is the development of sugarcane C Factor modeling tools with an interface sensitive to the most common C Factor parameters, such as harvesting and planting dates, row spacing, soil tillage, and varieties, allowing thus, soil erosion modelers to represent crop management rather than the oversimplified land-use approach for sugarcane soil loss estimation.

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Edited by

Edited by: Silvia del Carmen Imhoff

Publication Dates

  • Publication in this collection
    02 Apr 2021
  • Date of issue
    2021

History

  • Received
    06 Aug 2020
  • Accepted
    15 Nov 2020
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