Changes in water use efficiency related to climatic factors and land use and occupation in the MATOPIBA region
DOI:
https://doi.org/10.33448/rsd-v10i9.17891Keywords:
Water Use Efficiency; MATOPIBA; Land use and occupation.Abstract
The study aims to: estimate and analyze the spatial-temporal changes of the WUE in MATOPIBA and evaluate the influence of climatic factors and land use and occupation on the variation of the WUE. The study will use the products MOD17A2 (GPP), and MOD16A2 (ET) derived from the MODIS sensor (Moderate Resolution Imaging Spectroradiometer) obtained in the United States Geological Survey (USGS), with spatial resolution 1 km x 1km, for the computation of the annual WUE in the period between 2001 and 2019. Regarding the evaluation of land use based on the MAPBIOMAS maps, with a resolution of 30m x 30m. Precipitation data will come from the Climate Hazard Group InfraRed Precipitation with Station data (CHIRPS) with a spatial resolution of 5.6 km by 5.6 km. The mathematical calculations were developed in R environment software version 3.6-3 and Quantum GIS version 3.4-6. The results show that the highest (lowest) values of WUE occur in agricultural regions and areas of native Amazonian vegetation (non-vegetated surface areas). This WUE pattern is associated with the growing agricultural expansion over the regions (West Bahia and in the Piauí portion), mainly motivated by soy planting. In addition, during dry (wet) years have positive (negative) anomalies of WUE. Concluding that, agricultural areas are prone to higher WUE values due to cultural management helping develop crops. Vegetation responses to dry and rainy events were more sensitive in agricultural areas than in areas of native vegetation.
References
Bastiaanssen, W. G. & Ali, S. (2003). A New Crop Yield Forecasting Model Based On Satellite Measurements Applied Across The Indus Basin, Pakistan. Agriculture, Ecosystems & Environment, 94, 321-340.
Bourque, C. P. A., & Mir, M. A. (2012). Seasonal snow cover in the Qilian Mountains of Northwest China: Its dependence on oasis seasonal evolution and lowland production of water vapour. Journal of Hydrology, 454, 141-151.
Carrão, H., Russo, S., Sepulcre-Canto, G. & Barbosa, P. (2016). An mpirical standardized soil moisture index for agricultural drought assessment from emotely sensed data. International Journal of Applied Earth Observation and Geoinformation, 48, 74-84.
Chapin III, F. S., Matson, P. A., Mooney, H. A. (2002). Principles Of Terrestrial Ecosystem Ecology. Berlin, Germany: Springer-Verlag, 2002. 436 P.
Coelho, E. F., Coelho Filho, M., A., & De Oliveira, S. L. (2005). "Agricultura Irrigada: Eficiência De Irrigação E De Uso De Água. " Bahia Agrícola 7. 1: 57-60.
Colussi, J. (2017). MATOPIBA: Mudanças No Uso Da Terra Na Nova Fronteira.
CONAB - Companhia Nacional de Abastecimento. (2019). Acompanhamento da Safra Brasileira de Grãos, Safra 2018/19 - Oitavo Levantamento, 1-135, https://www. conab. gov. br/info-agro/safras/graos/boletim-da-safra-de-graos.
Correia Filho, W. L. F., Barros Santiago, D., Oliveira-Júnior, J. F., & Silva Junior, C. A. (2019). Impact Of Urban Decadal Advance On Land Use And Land Cover And Surface Temperature In The City Of Maceió, Brazil. Land Use Policy, 87, 104026. Https://Doi. Org/10. 1016/J. Landusepol. 2019. 104026.
Correia Filho, W. L. F., De Oliveira-Júnior, J. F., De Barros Santiago, D., De Bodas Terassi, P. M., Teodoro, P. E., De Gois, G., & Dos Santos, P. J. (2019). Rainfall variability in the Brazilian northeast biomes and their interactions with meteorological systems and ENSO via CHELSA product. Big Earth Data, 3(4), 315-337. Https://Doi. Org/10. 1080/20964471. 2019. 1692298.
Dalastra, G. M., De Moraes Echer, M., Guimarães, V. F., Brito, T. S., & Inagaki, A. M. (2020). Trocas gasosas e produtividade de tomateiro com diferentes hastes por planta. Iheringia. Série Botânica. 75.
De Melo, J. C. (1999). O fenômeno El Niño e as secas no Nordeste do Brasil. Raízes: Revista de Ciências Sociais e Econômicas, (20), 13-21.
Diaz, M. B., Roberti, D. R., Carneiro, J. V., Souza, V. de A., & de Moraes, O. L. L. (2019). Dynamics of the superficial fluxes over a flooded rice paddy in southern Brazil. Agricultural and Forest Meteorology, 276-277, 107650. 10. 1016/j. agrformet. 2019. 107650
Eiten. (1972). The Cerrado Vegetation Of Brazil. York, New Garden, Botanical, 38, 201–341.
Freire, J. L. M., Lima, J. R. A., & Cavalcanti, E. P. (2011). Análise de aspectos meteorológicos sobre o Nordeste do Brasil em anos de El Niño e La Niña. Revista Brasileira de Geografia Física, 3, 429-444.
Funk, C., Peterson, P., Landsfeld, M., &Michaelsen, J. (2015). The Climate Hazards Infrared Precipitation With Record For Monitoring Extremes. Scientific Data, 2, 10-66.
IBGE. (2002). Mapa De Clima Do Brasil. Http://Www. Visualizador. Inde. Gov. Br/
Kijne, J. W., Barker, R. & Molden, D. J. (2003). Water productivity in agriculture: limits and opportunities for improvement. Cabi.
Koech, R., Langat, P. (2018). Review Improving Irrigation Water Use Efficiency: A Review Of Advances, Challenges, And Opportunities In The Australian.
Lima, J. E. F. W. (2011). "Situação E Perspectivas Sobre As Águas Do Cerrado. " Ciência E Cultura 63. 3: 27-29.
Liu, J., Sun O. J., Jin, H., Zhou, Z. & Han, X. (2011). Application Of Two Remote Sensing GPP Algorithms At A Semiarid Grassland Site Of North China. Journal Of Plant Ecology. 4, 302–312.
Liu, Y., Xiao, J., Ju, W., Zhou, Y., Wang, S., & Wu, X. (2015). Water use efficiency of China’s terrestrial ecosystems and responses to drought. Scientific reports, 5(1), 1-12.
Madugundu R, Al-Gaadi K. A., Tola E. K., Kayad A. G., Jha C. S. (2017). Estimation Of Gross Primary Production Of Irrigated Maize Using Landsat-8 Imagery And Eddy Covariance Data. Saudi J Biol Sci 24:410–20.
Magalhães, L. A., De Miranda, E. E. (2014). MATOPIBA: Quadro Natural. Embrapa Territorial-Outras Publicações Técnicas (INFOTECA-E).
Marengo, J. A., Cunha, A. P., & Alves, L. M. (2016). A seca de 2012-15 no semiárido do Nordeste do Brasil no contexto histórico. Climanálise, 3(1), 1-6.
Mbava, N., Mutema, M., Zengeni, R., Shimelis, H., & Chaplot, V. (2020). Factors affecting crop water use efficiency: A worldwide meta-analysis. Agricultural Water Management, 228, 105878. 10. 1016/j. agwat. 2019. 105878
Miranda, E. E., Magalhães, L. A. & Carvalho, C. A. De. (2014). Proposta De Delimitação Territorial Do MATOPIBA. Embrapa GITE. Https://Www. Embrapa. Br/Gite/Publicacoes/>
Miranda, E. E. (2015). Matopiba Delimitação, Caracterização, Desafios E Oportunidades Para O Desenvolvimento. Embrapa GITE. Https://Www. Embrapa. Br/Gite/Projetos/MATOPIBA/MATOPIBA. Html
Morison, J. I., Baker, N., Mullineaux, P., & Davies, W. (2008). Melhorar O Uso Da Água Na Produção Agrícola. Philosophical Transactions Of The Royal Society B: Biological Sciences, 363 (1491), 639-658. 10. 1098 / Rstb. 2007. 2175
Nascimento, D., Novais, G. (2020). Clima do Cerrado: dinâmica atmosférica e características, variabilidades e tipologias climáticas. Élisée - Revista De Geografia Da UEG, 9(2), e922021. https://www.revista.ueg.br/index.php/elisee/article/view/10854
Nicodemo, M., De Moraes, L. F. D., De Oliveira, R. E., & De Queiroga, J. L. (2021). Tecnologias agroecológicas apropriadas para a transição agroecológica na agricultura familiar. Embrapa Pecuária Sudeste-Documentos (INFOTECA-E).
Ponce-Campos, G. E., Moran, M. S., Huete, A., Zhang, Y., Bresloff, C., Huxman, T. E., & Starks, P. J. (2013). Ecosystem resilience despite large-scale altered hydroclimatic conditions. Nature, 494(7437), 349-352.
PA (Projeções do Agronegócio). (2017). Brasil 2016/17 a 2026/27. Projeções de longo prazo. MAPA (8a ed.), 125 p.
Projeto MapBiomas. (2021) Coleção 5 da Série Anual de Mapas de Cobertura e Uso de Solo do Brasil. Disponível em: https://mapbiomas. org/colecoes-mapbiomas. Acesso em 10 jan. 2021.
QGIS - Quantum Geographic Information System. (2019). Quantum GIS Geographic Information System. V. 3. 4. 6. Open Source Geospatial Foundation Project.
R Development Core Team, (2020). R: A Language And Environment For Statistical Computing. R Foundation For Statistical Computing, Vienna, Austria, Http://Www. R-Project. Org, ISBN 3-900051-07-0.
Sá, H., Morais, L. & Campos, C. (2015). Que Desenvolvimento É Esse? Análise Da Expansão Do Agronegócio Da Soja Na Área Do MATOPIBA A Partir De Uma Perspectiva Furtadiana. In: Anais Do XXI Congresso Brasileiro De Economia.
Schuur, E. A. & Matson, P. A. (2001). Net primary productivity and nutrient cycling across a mesic to wet precipitation gradient in Hawaiian montane forest. Oecologia, v. 128, 431-442.
Schuur, E. A., Chadwick, O. A. & Matson, P. A. (2001). Carbon cycling and soil carbon storage in mesic to wet Hawaiian montane forests. Ecology, 82, 3182-3196.
Tang X., Li H., Desai A. R., & Ammann C. (2015a). How Is Water-Use Efficiency Of Terrestrial Ecosystems Distributed And Changing On Earth? Science Reports 4:7483.
Tang, X., Ding, Z., Li, H., Li, X., Luo, J., Xie, J., & Chen, D. (2015b). Characterizing Ecosystem Water-Use Efficiency Of Croplands With Eddy Covariance Measurements And MODIS Products. Ecological Engineering, 85, 212–217. 10. 1016/J. Ecoleng. 2015. 09. 078.
Taub, D. (2010). Effects of rising atmospheric concentrations of carbon dioxide on plants. Nature Education Knowledge, v. 1.
Tilahun, H., Teklu, E., Michael, M., Fitsum, H., & Awulachew, S. B., (2011). Comparative Performance Of Irrigated And Rainfed Agriculture In Ethiopia. World Appl. Science. J. 14 (2), 235–244.
Tong, X. -J., Li, J., Yu, Q., & Qin, Z. (2009). Ecosystem water use efficiency in an irrigated cropland in the North China Plain. Journal of Hydrology, 374(3-4), 329–337. 10. 1016/j. jhydrol. 2009. 06. 030
USGS. United States Geological Survey. Earth Explorer. (2021). https://earthexplorer. usgs. gov>.
Vetrita, Y., Chaoyang, W., Zheng, N. & Hirano, T. (2011). Evaluation Of Light Use Efficiency Model Using Modis In Tropical Peat Swamp Forest, Indonesia. In: Second Cresos International Symposium On South East Asia Environmental Problems And Satellite. Remote Sensing, Indonesia, 127-134.
Wang Z., Xiao X., & Yan X. (2010). Modeling Gross Primary Production Of Maize Cropland And Degraded Grassland In Northeastern China. Agricultura Forest Meteorology 150:1160–7.
Wang, Y., Ma, Y., Li, H., & Yuan, L. (2020). Carbon and water fluxes and their coupling in an alpine meadow ecosystem on the northeastern Tibetan Plateau. Theoretical and Applied Climatology, 142(1), 1-18.
Weber, E., Hasenack, H. & Ferreira, C. J. S. (2004). Adaptação do modelo digital de elevação do SRTM para o sistema de referência oficial brasileiro e recorte por unidade da federação. Porto Alegre. UFRGS Centro de Ecologia. https://www.ufrgs. br/labgeo/index.php/dados-espaciais/260-modelos-digitais-de-elevacao-do-srtm-no-formato-geotiff >.
Xiangyang, S., Genxu, W., Mei, H., Ruiying, C., Zhaoyong, H., Chunlin, S., & Juying, S. (2019). The asynchronous response of carbon gain and water loss generate spatio-temporal pattern of WUE along elevation gradient in southwest China. Journal of Hydrology, 124389. 10. 1016/j. jhydrol. 2019. 124389
Xiao, G., Zheng, F., Qiu, Z., & Yao, Y. (2013). Impact of climate change on water use efficiency by wheat, potato and corn in semiarid areas of China. Agriculture, Ecosystems & Environment, 181, 108–114. 10. 1016/j. agee. 2013. 09. 019
Xiao, X., Braswell, B., Zhang, Q., Boles, S., Frolking, S., & Moore, B. (2003) Sensitivity Of Vegetation Indices To Atmospheric Aerosols: Continental- Scale Observations In Northern Asia. Remote Sensing Of Environment. 84, 385–392.
Xiao, X., Zhang, Q., Braswell, B., Urbanski, S., Boles, S., Wofsy, S., Moore Iii, B. & Ojima, D. (2004c). Modeling Gross Primary Production Of Temperate Deciduous Broadleaf Forest Using Satellite Images And Climate Data. Remote Sensing Of Environment. 91, 256–270.
Xiao, X., Zhang, Q., Hollinger, D., Aber, J., & Moore Iii, B. (2004b). Modeling Seasonal Dynamics Of Gross Primary Production Of An Evergreen Needleleaf Forest Using MODIS Images And Climate Data. Ecological Applications. 15, 954-969.
Yamori, W. (2020). Photosynthesis and respiration. Plant Factory, 197–206. 10. 1016/b978-0-12-816691-8. 00012-1
Yan H, Fu Y, Xiao X, Huang HQ, He H, & Ediger L. (2009). Modeling Gross Primary Productivity For Winter Wheat-Maize Double Cropping System Using MODIS Time Series And CO2 Eddy Flux Tower Data. Agric Ecosyst Environ 129:391–400.
Zwart, S. J., & Bastiaanssen, W. G. M. (2004). Review of measured crop water productivity values for irrigated wheat, rice, cotton and maize. Agricultural Water Management, 69(2), 115–133. 10. 1016/j. agwat. 2004. 04. 007
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