Natural disaster in the mountainous region of Rio de Janeiro state, Brazil: Assessment of the daily rainfall erosivity as an early warning index

International Soil and Water Conservation Research - Tập 10 - Trang 547-556 - 2022
Geovane J. Alves1, Carlos R. Mello1, Li Guo2, Michael S. Thebaldi1
1Water Resources Department, School of Engineering, Federal University of Lavras, Lavras, MG, 37200-900, CP, 3037, Brazil
2State Key Laboratory of Hydraulics and Mountain River Engineering & College of Water Resource and Hydropower, Sichuan University, Chengdu 610065, China

Tài liệu tham khảo

Angulo-Martínez, 2009, Estimating rainfall erosivity from daily precipitation records: A comparison among methods using data from the Ebro basin (NE Spain), Journal of Hydrology, 379, 111, 10.1016/j.jhydrol.2009.09.051 Brito, 2016, Multivariate analysis applied to monthly rainfall over Rio de Janeiro state, Brazil, Meteorology and Atmospheric Physics, 129, 469, 10.1007/s00703-016-0481-x Brooks, 2000, Climatology of heavy rain events in the United States from hourly precipitation observations, Monthly Weather Review, 4, 1194, 10.1175/1520-0493(2000)128<1194:COHREI>2.0.CO;2 Busch, 2011 Calvello, 2015, The Rio de Janeiro early warning system for rainfall-induced landslides: Analysis of performance for the years 2010–2013, Internatinal Journal Disaster Risk Reduction Reduct, 12, 3, 10.1016/j.ijdrr.2014.10.005 Cardozo, 2018, Shallow landslide susceptibility assessment using SINMAP in Nova Friburgo (Rio de Janeiro, Brazil), Revista Brasileira de Cartografia, 4, 1206, 10.14393/rbcv70n4-46139 Cardozo, 2019, Assessing social vulnerability to natural hazards in Nova Friburgo, Vol. 2, 71 2013 Coelho Netto, 2013, January 2011: The extreme landslide disaster in Brazil, 377 De Maria, 1994, Cálculo da erosividade da chuva Dolif, 2012, Improving extreme precipitation forecasts in Rio de Janeiro, Brazil: Are synoptic patterns efficient for distinguishing ordinary from heavy rainfall episodes?, Atmospheric Science Letters, 3, 216, 10.1002/asl.385 Fernandes, 2018, Changes in the patterns of extreme rainfall events in southern Brazil, International Journal of Climatology, 38, 1337, 10.1002/joc.5248 Freitas, 2012, Vulnerabilidade socioambiental, redução de riscos de desastres e construção da resiliência: Lições do terremoto no Haiti e das chuvas fortes na Região Serrana, Brasil, Ciência & Saúde Coletiva, 17, 1577, 10.1590/S1413-81232012000600021 Groisman, 2001, Heavy precipitation and high streamflow in the contiguous United States: Trends in the twentieth century, Bulletin of the American Meteorological Society, 82, 219, 10.1175/1520-0477(2001)082<0219:HPAHSI>2.3.CO;2 Groisman, 2012, Changes in intense precipitation over the central United States, Journal of Hydrometeorology, 1, 47, 10.1175/JHM-D-11-039.1 Guzzetti, 2007, Rainfall thresholds for the initiation of landslides in central and southern Europe, Meteorology and Atmospheric Physics, 98, 239, 10.1007/s00703-007-0262-7 2010 McGregor, 1976, Status of the R-factor in northern Mississippi, 135 Mello, 2020, Daily rainfall erosivity as an indicator for natural disasters: Assessment in mountainous regions of southeastern Brazil, Natural Hazards, 103, 947, 10.1007/s11069-020-04020-w Mello, 2015, Assessing the climate change impacts on the rainfall erosivity throughout the twenty-first century in the Grande River Basin (GRB) headwaters, southeastern Brazil, Environmental Earth Sciences, 73, 8683, 10.1007/s12665-015-4033-3 Mendes, 2018, Understanding shallow landslides in Campos do Jordão municipatily – Brazil: Disentangling the anthropic effects from natural causes in the disaster of 2000, Natural Hazards and Earth System Sciences, 18, 15, 10.5194/nhess-18-15-2018 Nash, 1970, River flow forecasting through conceptual models part I: A discussion of principles, Journal of Hydrology, 10, 282, 10.1016/0022-1694(70)90255-6 Oliveira, 2016, Correlation between rainfall and landslides in Nova Friburgo, Rio de Janeiro—Brazil: A case study, Environmental Earth Sciences, 75, 1358, 10.1007/s12665-016-6171-7 Pinto, 2018, A hydropedological approach to a mountainous Clayey Humic Dystrudept in the Mantiqueira range, Southeastern Brazil. Scientia Agricola, 75, 60, 10.1590/1678-992x-2016-0144 Pristo, 2018, Climatologia de chuvas intensas no município do Rio de Janeiro, Rev. Bras. Meteorol., 4, 615, 10.1590/0102-7786334005 Reboita, 2010, Regimes de precipitação na América do Sul: Uma revisão bibliográfica, Revista Brasileira de Meteorologia, 2, 185, 10.1590/S0102-77862010000200004 Richardson, 1983, Estimation of erosion index from daily rainfall amount, Transactions of the ASABE, 26, 153, 10.13031/2013.33893 Wang, 2017, Estimating rainfall erosivity by incorporating seasonal variations in parameters into the Richardson model, Journal of Geographical Sciences, 27, 275, 10.1007/s11442-017-1376-6 Wischmeier, 1958, Rainfall energy and its relationship to soil loss, Transactions - American Geophysical Union, 39, 285, 10.1029/TR039i002p00285 Wischmeier, 1978 Xie, 2002, Practical thresholds for separating erosive and non-erosive storms, Transactions of the ASAE, 45, 1843 Xie, 2016, Models for estimating daily rainfall erosivity in China, Journal of Hydrology, 535, 547, 10.1016/j.jhydrol.2016.02.020 Xu, 2014, Natural hazard chain research in China: A review, Natural Hazards, 70, 1631, 10.1007/s11069-013-0881-x Yang, 2015, Modelling and mapping rainfall erosivity in new south Wales, Australia, Soil Research, 53, 178, 10.1071/SR14188 Yu, 1996, Rainfall erosivity estimation using daily rainfall amounts for South Australia, Australian Journal of Soil Research, 53, 721, 10.1071/SR9960721