Published

2018-07-01

Geospatial assessment of eco-environmental changes in desertification area of the Brazilian semi-arid region

Evaluación geoespacial de los cambios ecoambientales en el área de desertificación de la región semiárida brasileña

Keywords:

Zoning, soil management, erosion, semi-arid zone (en)
Zonificación, manejo del suelo, erosión, zona semiárida (es)

Downloads

Authors

  • Richarde Marques da Silva Federal University of Paraíba https://orcid.org/0000-0001-6601-5174
  • Celso Augusto Guimarães Santos Federal University of Paraíba https://orcid.org/0000-0001-7927-9718
  • Karinna Ugulino de Araújo Maranhão Federal Institute of Education, Science and Technology of Paraíba
  • Alexandro Medeiros Silva Federal University of Paraíba
  • Valéria Raquel Porto de Lima Paraíba State University
Eco-environmental change prediction models are important decision tools for policy makers as they help to quantify environmental sensitivity and understand the relationship between human activities and environmental quality. Thus, this paper aims to analyze eco-environmental changes in Monteiro County, a semi-arid zone within northeastern Brazil. This study used means of satellite images, geographic information system and global position system techniques, topographic map, climatic data and soil maps, as well as field survey data. The result outputs were evaluated on their ability to accurately predict the most sensitive and least sensitive areas. The results showed that land cover changes have modified the environment in general, and two prominent environmental degradation processes were identified: land degradation, and low soil loss. The mean soil loss increased from 0.09 t ha¹ yr¹ in 1987 to 0.18 t ha¹ yr¹ in 2010, as an effect of vegetation gain and particularly the conversion of thousands of square kilometers of Tropophile forest middle slope and barren land into Tropophile forest plain and Tropophile forest high strand. Thus, this study provides insight on territorial ordering and management of environmental services with a regional perspective.

Los modelos de predicción del cambio ecológico ambiental son herramientas de decisión importantes para los responsables de la formulación de políticas, ya que ayudan a cuantificar la sensibilidad ambiental y comprenden la relación entre las actividades humanas y la calidad ambiental. Por lo tanto, este artículo tiene como objetivo analizar los cambios ecológicos en el condado de Monteiro, una zona semiárida en el noreste de Brasil. Este estudio utilizó medios de imágenes satelitales, sistema de información geográfica y técnicas del sistema de posición global, mapas topográficos, datos climáticos y mapas de suelos, así como datos de encuestas de campo. Los resultados fueron evaluados en su capacidad para predecir con precisión las áreas más y menos sensibles. Los resultados mostraron que los cambios en la cobertura terrestre han modificado el medio ambiente en general, y se han identificado dos procesos importantes de degradación ambiental: la degradación de la tierra y la baja pérdida de suelo. La pérdida media de suelo aumentó de 0.09 t ha-¹ año-¹ en 1987 a 0.18 t ha-¹ año-¹ en 2010, como un efecto del aumento de la vegetación y particularmente la conversión de miles de kilómetros cuadrados de bosque Tropophile de pendiente media y tierra estéril en la llanura del bosque Tropophile y el bosque alto Tropophile. Por lo tanto, este estudio proporciona información sobre el ordenamiento territorial y la gestión de los servicios ambientales con una perspectiva regional.

Downloads

Download data is not yet available.

References

Al-Awadhi, J.M., Omar, S.A. & Misak, R.F. (2005). Land degradation indicators in Kuwait. Land Degradation and Development, 16(2):163–176.

Anache, J.A.A., Wendland, E.C., Oliveira, P.T.S., Flanagan, D.C. & Nearing, M.A. (2017). Runoff and soil erosion plot-scale studies under natural rainfall: A meta-analysis of the Brazilian experience. Catena, 152, 29–39. doi: https://doi.org/10.1016/j.catena.2017.01.003

Arnold, J.G., Moriasi, D.N., Gassman, P.W., Abbaspour, K.C., White, M.J., Srinivasan, R., Santhi, C., Harmel, R.D., van Griensven, A., Van Liew, M.W., Kannan, N. & Jha, M.K. (2012). SWAT: model use, calibration, and validation. Transactions of the ASABE, 55(4), 1491–1508.

Barbosa, H.A., Huete, A.R. & Baethgen, W.E. (2006). A 20-year study of NDVI variability over the Northeast Region of Brazil. Journal of Arid Environments, 67(2), 288–307. doi: https://doi.org/10.1016/j.jaridenv.2006.02.022

Beskow, S., Mello, C.R., Norton, L.D., Curi, N., Viola, M.R. & Avanzi, J.C. (2009). Soil erosion prediction in the Grande River Basin, Brazil using distributed modelling. Catena 79(1), 49–59. doi: https://doi.org/10.1016/j.catena.2009.05.010

Beuchle, R., Grecchi, R.C., Shimabukuro, Y.E, Seliger, R., Eva, H.D., Sano, E. & Achard, F. (2015). Land cover changes in the Brazilian Cerrado and Caatinga biomes from 1990 to 2010 based on a systematic remote sensing sampling approach. Applied Geography, 58(2), 116127. doi: https://doi.org/10.1016/j.apgeog.2015.01.017

Braga, A.C.F.M., Silva, R.M., Santos, C.A.G., Galvão, C.O. & Nobre, P. (2013). Downscaling of a global climate model for estimation of runoff, sediment yield and dam storage: A case study of Pirapama basin, Brazil. Journal of Hydrology, 498(1), 46–58. doi: https://doi.org/10.1016/j.jhydrol.2013.06.007

Brito Neto, R.T., Santos, C.A.G., Mulligan, K. & Barbato, L. (2016) Spatial and temporal water-level variations in the Texas portion of the Ogallala Aquifer. Natural Hazards, 80(1), 351–365. doi: https://doi.org/10.1007/s11069-015-1971-8

Cerdá, A., Giménez-Morera, A. & Bodí, M.B. (2009). Soil and water losses from new citrus orchards growing on sloped soils in the western Mediterranean basin. Ea Earth Surface Processes and Landforms, 34(13), 1822–1830. doi: https://doi.org/10.1002/esp.1889

Coelho, V.H.R., Montenegro, S.M.G.L., Almeida, C.N., Lima, E.R.V., Ribeiro Neto, A. & Moura, G.S.S. (2014). Dynamic of land use/cover change processes in a Brazilian semiarid watershed. Revista Brasileira de Engenharia Agrícola e Ambiental, 18(1), 64–72. doi: https://doi.org/10.1590/S1415-43662014000100009

Costa, C.A.G., Lopes, J.W.B., Pinheiro, E.A.R., Araújo, J.C. & Gomes Filho, R.R. (2013). Spatial behaviour of soil moisture in the root zone of the Caatinga biome. Revista Ciência Agronômica, v. 44, n. 4, p. 685–694.

Costa, T.C.C., Oliveira, M.A.J., Accioly, L.J.O. & Silva, F.H.B.B. (2009). Analysis of degradation of ‘Caatinga’ in the desertification nucleus of Seridó – Brazil. Revista Brasileira de Engenharia Agrícola e Ambiental, 13, 961–974. doi: https://doi.org/10.1590/S1415-43662009000700020

da Silva, A.M. (2004) Rainfall erosivity map for Brazil. Catena, 57(2), 251–259. doi: https://doi.org/10.1016/j.catena.2003.11.006

de Oliveira, L.B., Fontes, M.P.F., Ribeiro, M.R. & Ker, J.C. (2009). Morphology and classification of luvisols and planosols developed on metamorphic rocks in semiarid northeastern Brazil. Brazilian Journal of Soil Science, 3(5), :1333–1345. doi: https://doi.org/10.1590/S0100-06832009000500026

de Queiroz, J.S. & Norton, B.E. (1992). An assessment of an indigenous soil classification used in the caatinga region of Ceará State, Northeast Brazil. Agricultural Systems, 39(3), 289–305. doi: https://doi.org/10.1016/0308-521X(92)90101-S

de Roo, A.P.J. & Jetten, V. (1999). Calibrating and validating the LISEM model for two data sets from the Netherlands and South Africa. Catena, 37(5), 477–493. doi: https://doi.,org/10.1016/S0341-8162(99)00034-X

dos Santos, J.C.N., Andrade, E.M., Guerreiro, M.J.S., Medeiros, P.H.A., Palácio, H.A.Q. & Araújo Neto, J.R. (2016). Effect of dry spells and soil cracking on runoff generation in a semiarid micro watershed under land use change. Journal of Hydrology, 541, Part B, 1057–1066. doi: https://doi.org/10.1016/j.jhydrol.2016.08.016

ESRI – Arc Map Version 10.2 (2015). User Manual. ESRI, 380 New York Street, Redlands, CA, 92373-8100, USA.

FAO/UNESCO  Food and Agriculture Organization of the United Nations (1988). Soil map of the world, revised legend. World Soil Resources. Rep. 60, FAO, Rome.

Flanagan, D.C., Frankenberger, J.R. & Ascough II, J.C. (2012). WEPP: model use, calibration, and validation. Transactions of the ASABE, 55(4), 1463–1477.

Garcia, A.S. & Ballester, M.V.R. (2016). Land cover and land use changes in a Brazilian Cerrado landscape: drivers, processes, and patterns. Journal of Land Use Science, 11(5), 538–559. doi: https://doi.org/10.1080/1747423X.2016.1182221

Gopinath, T.R. & Lima, A.A. (2011). Modeling and mining of bentonite deposits Boavista region, Paraíba. Available in: www.brasilminingsite.com.br/anexos/artigos/12_0.pdf.

Huhn, S.R.B., Sousa, M.J., Souza Filho, C.R. & Monteiro, L.V.S. (2014). Geology of the Riacho do Pontal iron oxide copper-gold (IOCG) prospect, Bahia, Brazil: hydrothermal alteration approached via hierarchical cluster analysis. Brazilian Journal of Geology, 44(2), 309–324. doi: https://doi.org/10.5327/Z2317-4889201400020010

Lal, R. (1986). Soil surface management in the tropics for intensive land use and high and sustained production. In: Stewart ED. Advances in soil science, Volume 5, 109p.

Lima, V.R.P. (2012). Caracterización biogeográfica del bioma Caatinga en el sector semiárido de la cuenca del Río Paraíba – Noreste de Brasil: propuesta de ordenación y gestión de un medio semiárido tropical. Ph.D. Thesis, Sevilla University, Spain.

Lima, V.R.P. & Artigas, R.C. (2013). Management proposal for the conservation and management of natural resources in Caatinga Biome. Mercator, 12(29), 191–210. doi: https://doi.org/10.4215/RM2013.1229.0013

Lima, V.R.P. & Artigas, R.C. (2014). Caracterización de las formaciones vegetales de la caatinga del Carirí (Paraíba, Brasil). In: Artigas, R.C., Pérez, B.R., Gómez, J.L.M. (Org.). Biogeografia de Sistema Litorales: dinámicas y conservación. Sevilla, 143–152.

Manfré, L.A., da Silva, A.M., Urban, R.C., Rodgers, J. (2013). Environmental fragility evaluation and guidelines for environmental zoning: a study case on Ibiuna (the Southeastern Brazilian region). Environmental Earth Sciences, 69(3), 947–957. doi: https://doi.org/10.1007/s12665-012-1979-2

Mansur, R.R., Nogueira, C. & Barbosa, D.C.A. (2000). Comportamento fisiológico em plantas jovens de quatro espécies lenhosas da caatinga submetidas a dois ciclos de estresse hídrico. Phyton, International Journal of Experimental Botany, 68, 97–106.

Maranhão, K.U.A. (2014). O zoneamento ambiental do município de Monteiro, Paraíba. MSc. Thesis. Universidade Federal da Paraíba, Brazil.

Mohamed, E.S. (2013). Spatial assessment of desertification in north Sinai using modified MEDLAUS model. Arabian Journal of Geosciences, 6(12), 4647–4659. doi: https://doi.org/10.1007/s12517-012-0723-2

Mohamed, E.S., Schütt, B. & Belal A. (2013). Assessment of environmental hazards in the north western coast-Egypt using RS and GIS. The Egyptian Journal of Remote Sensing and Space Science, 16(2), 219–229. doi: https://doi.org/10.1016/j.ejrs.2013.11.003

Montenegro, A.A.A., Abrantes, J.R.C.B., de Lima, J.L.M.P., Singh, V.P. & Santos, T.E.M. (2013) Impact of mulching on soil and water dynamics under intermittent simulated rainfall. Catena, 109(1),139–149. doi: https://doi.org/10.1016/j.catena.2013.03.018

Moore, I.D. & Burch, G. (1986). Physical basis of the length-slope factor in the Universal Soil Loss Equation. Soil Science Society of America Journal, 50(5), 1294–1298. doi: https://doi.org/10.2136/sssaj1986.03615995005000050042x

Portillo-Quintero, C., Sanchez-Azofeifa, A. & Espirito-Santo, M.M. (2013). Monitoring deforestation with MODIS Active Fires in Neotropical dry forests: An analysis of local-scale assessments in Mexico, Brazil and Bolivia. Journal of Arid Environments, 97(1), 150–159. doi: https://doi.org/10.1016/j.jaridenv.2013.06.002

Puyravaud, J.P. (2003). Standardizing the calculation of the annual rate of deforestation. Forest Ecology and Management, 177(1–3), 593–596. doi: https://doi.org/10.1016/s0378-1127(02)00335-3

Rao, V.B., Franchito, S.H., Santo, C.M. & Gan, M.A. (2016). An update on the rainfall characteristics of Brazil: seasonal variations and trends in 1979-2011. International Journal of Climatology, 36(1), 291–302. doi: https://doi.org/10.1002/joc.4345

Ribeiro, K., de Sousa-Neto, E.R., de Carvalho Junior, J.A., Lima, J.R.S., Menezes, R.S.C., Duarte-Neto, P.J., Guerra, G.S. & Ometto, J.P.H.B. (2016). Land cover changes and greenhouse gas emissions in two different soil covers in the Brazilian Caatinga. Science of the Total Environment. 571, 1048–1057. doi: https://doi.org/10.1016/j.scitotenv.2016.07.095

Salazar, A., Baldi, G., Hirota, M., Syktus, J. & McAlpine, C. (2015). Land use and land cover change impacts on the regional climate of non-Amazonian South America: A review. Global and Planetary Change, 128, 103–119. doi: https://doi.org/10.1016/j.gloplacha.2015.02.009

Santos, C.A.G., da Silva, R.M., Silva, A.M. & Brasil Neto, R.M. (2017). Estimation of evapotranspiration for different land covers in a Brazilian semi-arid region: A case study of the Brígida River basin, Brazil. Journal of South American Earth Sciences, 74, 54–66. doi: https://doi.org/10.1016/j.jsames.2017.01.002

Schucknecht, A., Erasmi, S., Niemeyer, I. & Matschullat, J. (2013). Assessing vegetation variability and trends in north-eastern Brazil using AVHRR and MODIS NDVI time series. European Journal of Remote Sensing, 46(1), 4059. doi: https://doi.org/10.5721/EuJRS20134603

Schulz, C., Koch, R., Cierjacks, A. & Kleinschmit B. (2017). Land change and loss of landscape diversity at the Caatinga phytogeographical domain – Analysis of pattern-process relationships with MODIS land cover products (2001–2012). Journal of Arid Environments, 136, 54–74. doi: https://doi.org/10.1016/j.jaridenv.2016.10.004

Shao, H., Liu, M., Shao, Q., Sun, X., Wu, J., Xiang, Z. & Yang, W. (2014). Research on eco-environmental vulnerability evaluation of the Anning River Basin in the upper reaches of the Yangtze River. Environmental Earth Sciences, 72(5), 1555–1568. doi: https://doi.org/10.1007/s12665-014-3060-9.

Silva, A.B., Resende, M., Sousa, A.R. & Margolis, E. (1999). Soil mobilization, erosion and corn and bean yields in a regosol on the Pernambuco state dry area. Pesquisa Agropecuária Brasileira, 34(2), 299–307. doi: https://doi.org/10.1590/S0100-204X1999000200018

Silva, G.L., Lima, H.V., Campanha, M.M., Gilkes, R.J. & Oliveira, T.S. (2011). Soil physical quality of Luvisols under agroforestry, natural vegetation and conventional crop management systems in the Brazilian semi-arid region. Geoderma, 167168, 61–70. doi: https://doi.org/10.1016/j.geoderma.2011.09.009

Silva, R.M., Montenegro, S.M.G.L. & Santos, C.A.G. (2012). Integration of GIS and remote sensing for estimation of soil loss and prioritization of critical sub-catchments: a case study of Tapacurá catchment. Natural Hazards, 62(3), 953–970. doi: https://doi.org/10.1007/s11069-012-0128-2

Silva, R.M., Santos, C.A.G., Moreira, M., Corte-Real, J., Silva, V.C.L. & Medeiros, I.C. (2015). Rainfall and river flow trends using Mann-Kendall and Sen’s slope estimator statistical tests in the Cobres River basin. Natural Hazards, 77(2), 1205–1221. doi: https://doi.org/10.1007/s11069-015-1644-7

Silva, V.P.R., (2004). On climate variability in Northeast of Brazil. Journal of Arid Environments, 58(4), 575–596. doi: https://doi.org/10.1016/j.jaridenv.2003.12.002

Sousa, F.P., Ferreira, T.O., Mendonça, E.S.¸ Romero, R.E. & Oliveira, J.G.B. (2012). Carbon and nitrogen in degraded Brazilian semi-arid soils undergoing Desertification. Agriculture, Ecosystems and Environment, 148(1), 11– 21. doi: https://doi.org/10.1016/j.agee.2011.11.009

Souza, Z.S., Nascimento, M.A.L., Barbosa, R.V.N. & Dias, L.G.S. (2005). Geology and tectonics of the Boa Vista Basin (Paraíba, northeastern Brazil) and geochemistry of associated Cenozoic tholeiitic magmatism. Journal of South American Earth Sciences, 18(3–4), 391–405. doi: https://doi.org/10.1016/j.jsames.2004.11.007

Srinivasan, V.S. & Galvão, C.O. (1995). Evaluation of runoff and erosion loss in micro-basins utilizing the hydrodynamic model WESP. Advances in Engineering Software, 22(2), 79–85. doi: https://doi.org/10.1016/0965-9978(95)00014-N

Srinivasan, V.S. & Paiva, F.M.L. (2009). Regional validity of the parameters of a distributed runoff-erosion model in the semi-arid region of Brazil. Science in China Series E: Technological Sciences, 52(11), 3348–3356. doi: https://doi.org/10.1007/s11431-009-0345-4

Williams, J.R. (1995). The EPIC Model. In: Singh V. (Ed.) Computer models of watershed hydrology. Chapter 25. Water Resources Publications, Highlands Ranch, 909–1000.

Wischmeier, W.H. & Smith, D.D. (1965). Predicting rainfall erosion losses. Admin. U.S. Department of Agriculture. Washington, Agriculture Handbook Science and Education 357, 58p.

Woolhiser, D.A., Smith, R.E. & Goodrich, D.C. (1990). KINEROS, a Kinematic Runoff and Erosion Model: Documentation and User Manual. U.S. Department of Agriculture, Agricultural Research Service, ARS-77, 130p.

Zhang, R., Santos, C.A.G., Moreira, M., Freire, P.K.M.M. & Corte-Real, J. (2013). Automatic calibration of the SHETRAN hydrological modelling system using MSCE. Water Resources Management, 27(11), 4053–4068. doi: https://doi.org/10.1007/s11269-013-0395-z

Zhang, Y., Degroote, J., Wolter, C. & Sugumaran, R. (2009). Integration of Modified Universal Soil Loss Equation (MUSLE) into a GIS framework to assess soil erosion risk. Land Degradation and Development, 20(1), 84–91. doi: https://doi.org/10.1002/ldr.893