Semi-Arid to Arid Scenario Shift: Is the Cabrobó Desertification Nucleus Becoming Arid?

被引:3
作者
da Silva, Jose Lucas Pereira [1 ]
da Silva Junior, Francisco Bento [1 ]
Santos, Joao Pedro Alves de Souza [1 ]
Almeida, Alexsandro Claudio dos Santos [1 ]
da Silva, Thieres George Freire [1 ,2 ]
de Oliveira-Junior, Jose Francisco [3 ]
Araujo Junior, George do Nascimento [1 ]
Scheibel, Christopher Horvath [1 ]
da Silva, Jhon Lennon Bezerra [4 ]
de Lima, Joao Luis Mendes Pedroso [5 ,6 ]
da Silva, Marcos Vinicius [1 ]
机构
[1] Univ Fed Alagoas, Dept Plant Prod, Engn & Agr Sci Campus,BR 104 SN, BR-57100000 Rio Largo, AL, Brazil
[2] Fed Rural Univ Pernambuco UFRPE, Acad Unit Serra Talhada UAST, Agrometeorol Lab, Av Gregorio Ferraz Nogueira S-N, BR-56909535 Serra Talhada, PE, Brazil
[3] Fed Univ Alagoas UFAL, Inst Atmospher Sci ICAT, BR-57072260 Maceio, AL, Brazil
[4] Goiano Fed Inst Campus Ceres, Cerrado Irrigat Grad Program, GO 154,Km 218 Zona Rural, BR-76300000 Ceres, GO, Brazil
[5] Univ Coimbra, Fac Sci & Technol, Dept Civil Engn, P-3030788 Coimbra, Portugal
[6] Univ Coimbra, MARE Marine & Environm Sci Ctr, P-3000456 Coimbra, Portugal
关键词
land use and land cover; aridity index; standardized precipitation index (SPI); native vegetation suppression; CLIMATE-CHANGE; RAINFALL VARIABILITY; DROUGHT; BRAZIL;
D O I
10.3390/rs16152834
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Monitoring areas susceptible to desertification contributes to the strategic development of regions located in environments of extreme hydric and social vulnerability. Therefore, the objective of this study is to evaluate the process of soil degradation in the Desertification Nucleus of Cabrob & oacute; (DNC) over the past three decades using remote sensing techniques. This study used primary climatic data from TerraClimate, geospatial data of land use and land cover (LULC), and vegetation indices (SAVI and LAI) via Google Earth Engine (GEE) from Landsat 5/TM and 8/OLI satellites, and established the aridity index (AI) from 1992 to 2022. The results indicated 10 predominant LULC classes with native vegetation suppression, particularly in agriculture and urbanization. SAVI ranged from -0.84 to 0.90, with high values influenced by La Ni & ntilde;a episodes and increased rainfall; conversely, El Ni & ntilde;o episodes worsened the rainfall regime in the DNC region. Based on the Standardized Precipitation Index (SPI), it was possible to correlate normal and severe drought events in the DNC with years under the influence of El Ni & ntilde;o and La Ni & ntilde;a phases. In summary, the AI images indicated that the DNC remained semi-arid and that the transition to an arid region is a cyclical and low-frequency phenomenon, occurring in specific periods and directly influenced by El Ni & ntilde;o and La Ni & ntilde;a phenomena. The Mann-Kendall analysis showed no increasing trend in AI, with a Tau of -0.01 and a p-value of 0.97. During the analyzed period, there was an increase in Non-Vegetated Areas, which showed a growing trend with a Tau of 0.42 in the Mann-Kendall analysis, representing exposed soil areas. Annual meteorological conditions remained within the climatic pattern of the region, with annual averages of precipitation and actual evapotranspiration (ETa) close to 450 mm and an average temperature of 24 degrees C, showing changes only during El Ni & ntilde;o and La Ni & ntilde;a events, and did not show significant increasing or decreasing trends in the Mann-Kendall analysis.
引用
收藏
页数:27
相关论文
共 73 条
[61]  
Silva C.O.F., 2021, Rev. Bras. Eng. Biossistemas, V15, P425, DOI [10.18011/bioeng2021v15n3p425-468, DOI 10.18011/BIOENG2021V15N3P425-468]
[62]   Spatial modeling of rainfall patterns and groundwater on the coast of northeastern Brazil [J].
Silva, Marcos Vinicius da ;
Pandorfi, Heliton ;
Jardim, Alexandre Manitoba da Rosa Ferraz ;
Oliveira-Junior, Jose Francisco de ;
Divincula, Jesiele Silva da ;
Giongo, Pedro Rogerio ;
Silva, Thieres George Freire da ;
Almeida, Gledson Luiz Pontes de ;
Moura, Geber Barbosa de Albuquerque ;
Lopes, Pabricio Marcos Oliveira .
URBAN CLIMATE, 2021, 38
[63]  
Singh R., 2022, CLIMATE CHANGE DISAS, P121
[64]  
Soares D.B., 2011, Rev. Bras. Geogr. Fsica, V4, P174, DOI [10.26848/rbgf.v4i1.232699, DOI 10.26848/RBGF.V4I1.232699, 10.26848/RBGF.V4I1.232699]
[65]   Towards identifying areas at climatological risk of desertification using the Koppen-Geiger classification and FAO aridity index [J].
Spinoni, Jonathan ;
Vogt, Juergen ;
Naumann, Gustavo ;
Carrao, Hugo ;
Barbosa, Paulo .
INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2015, 35 (09) :2210-2222
[66]   AN APPROACH TOWARD A RATIONAL CLASSIFICATION OF CLIMATE [J].
Thornthwaite, C. W. .
GEOGRAPHICAL REVIEW, 1948, 38 (01) :55-94
[67]   Climate variability and vulnerability to climate change: a review [J].
Thornton, Philip K. ;
Ericksen, Polly J. ;
Herrero, Mario ;
Challinor, Andrew J. .
GLOBAL CHANGE BIOLOGY, 2014, 20 (11) :3313-3328
[68]   Desertification risk assessment in Northeast Brazil: Current trends and future scenarios [J].
Vieira, Rita Marcia D. S. P. ;
Tomasella, Javier ;
Barbosa, Alexandre A. ;
Martins, Minella A. ;
Rodriguez, Daniel A. ;
Rezende, Fernanda S. D. ;
Carriello, Felix ;
Santana, Marcos D. O. .
LAND DEGRADATION & DEVELOPMENT, 2021, 32 (01) :224-240
[69]  
WANDERLEY HS, 2014, REV BRASILEIRA GEOGR, V7, P662, DOI [10.26848/rbgf.v7.4.p662-667, DOI 10.26848/RBGF.V7.4.P662-667]
[70]   Remote sensing for drought monitoring & impact assessment: Progress, past challenges and future opportunities [J].
West, Harry ;
Quinn, Nevil ;
Horswell, Michael .
REMOTE SENSING OF ENVIRONMENT, 2019, 232