A Amazônia vem sofrendo o aumento de intensidade e de ocorrência de eventos climáticos extremos. A ocorrência de secas nesta região aumenta a susceptibilidade das florestas a incêndios florestais, com diversas consequências para o meio ambiente, economia e saúde da população. O objetivo deste estudo foi fornecer uma análise espaço-temporal do uso do fogo no Estado do Acre, e assim auxiliar a Sala de Situação do Estado na tomada de decisão para priorizar o monitoramento de áreas com risco de incêndios. Para isso, foram utilizados dados de focos de calor oriundos de múltiplos satélites, dados de unidades fundiárias e análises estatísticas para gerar um ordenamento de áreas prioritárias para monitoramento de incêndios. O satélite AQUA, desde o início de sua operação em 2002, foi responsável por 40% a 75% dos totais de detecção de focos. Com o lançamento do satélite S-NPP em 2013, este vem sendo responsável pela maioria das detecções de focos de calor devido melhores em suas resoluções espaciais e radiométricas. Trinta e nove por cento do total de focos de calor detectados, foram localizados em projetos de assentamentos, 26% em áreas particulares, 10% em unidades de conservação e menos de 2% em terras indígenas. Um mapa de risco de incêndios baseado em análises de tendência e número de ocorrências de focos de calor foi proposto para auxiliar a definição de áreas prioritárias para monitoramento e fiscalização. Conclui-se que as informações geradas com base nos dados históricos de focos de calor podem ser incorporadas aos modelos de risco de incêndios que operam com dados puramente climáticos de forma a melhorar a espacialização do risco e assim apoiar o planejamento e a tomada de decisão.

Abstract:Remote sensing allows for the continuous and repetitive measurement of rainfall values. Satellite rainfall products such as Tropical Rainfall Measurement Mission (TRMM) 3B42 and the Hydroestimator (Hydroe) can be potential sources of data for hydrologic applications, mainly in areas with irregular and sparse spatial distributions of traditional rain gauge stations. However, the accuracy of these satellite rainfall products over different spatial and temporal scales is unknown. In this study, we examined the potential of the TRMM 3B42 and Hydroe rainfall products to provide reliable rainfall estimates for a mountainous watershed in a humid subtropical climate region of Brazil. The purpose was to develop useful guidelines for future hydrologic studies on the potential and uncertainties of the rainfall products at different spatial and temporal resolutions. We compared the satellite products to reference rainfall data collected at 11 rain gauge stations irregularly distributed in the area. The results showed different levels of accuracy for each temporal scale evaluated. TRMM 3B42 performed better at the daily, monthly, and seasonal scales than Hydroe, while Hydroe presented a better correlation at the annual scale. In general, TRMM 3B42 overestimated the rainfall over the watershed at all evaluated temporal scales, whereas Hydroe underestimated it except for June-August at the seasonal scale. An evaluation based on contingency tables indicated that TRM 3B42 was better able to represent the local rainfall than Hydroe. The findings of this study indicate that satellite rainfall products are better suited for applications at the monthly and annual scales rather than the daily scale.

Accurate daily rainfall estimation is required in several applications such as in hydrology, hydrometeorology, water resources management, geomorphology, civil protection, and agriculture, among others. CMORPH daily rainfall estimations were integrated with rain gauge measurements in Brazil between 2000 and 2015, in order to reduce daily rainfall estimation errors by means of the statistical objective analysis scheme (SOAS). Early comparisons indicated high discrepancies between daily rain gauge rainfall measurements and respective CMORPH areal rainfall accumulation estimates that tended to be reduced with accumulation time span (e.g., yearly accumulation). Current results show CMORPH systematically underestimates daily rainfall accumulation along the coastal areas. The normalized error variance (NEXERVA) is higher in sparsely gauged areas at Brazilian North and Central-West regions. Monthly areal rainfall averages and standard deviation were obtained for eleven Brazilian watersheds. While an overall negative tendency (3 mm·h−1) was estimated, the Amazon watershed presented a long-term positive tendency. Monthly areal mean precipitation and respective spatial standard deviation closely follow a power-law relationship for data-rich watersheds, i.e., with denser rain gauge networks. Daily SOAS rainfall accumulation was also used to calculate the spatial distribution of frequencies of 3-day rainfall episodes greater than 100 mm. Frequencies greater than 3% were identified downwind of the Peruvian Andes, the Bolivian Amazon Basin, and the La Plata Basin, as well as along the Brazilian coast, where landslides are recurrently triggered by precipitation.

Debris flows represent great hazard to humans due to their high destructive power. Understanding their hydrogeomorphic dynamics is fundamental in hazard assessment studies, especially in subtropical and tropical regions where debris flows have scarcely been studied when compared to other mass-wasting processes. Thus, this study aims at systematically analyzing the meteorological and geomorphological factors that characterize a landslide-triggered debris flow at the Pedra Branca catchment (Serra do Mar, Brazil), to quantify the debris flow’s magnitude, peak discharge and velocity. A magnitude comparison with empirical equations (Italian Alps, Taiwan, Serra do Mar) is also conducted. The meteorological analysis is based on satellite data and rain gauge measurements, while the geomorphological characterization is based on terrestrial and aerial investigations, with high spatial resolution. The results indicate that it was a large-sized stony debris flow, with a total magnitude of 120,195 m3, a peak discharge of 2146.7 m3 s−1 and a peak velocity of 26.5 m s−1. The debris flow was triggered by a 188-mm rainfall in 3 h (maximum intensity of 128 mm h−1), with an estimated return period of 15 to 20 years, which, combined with the intense accumulation of on-channel debris (ca. 37,000 m3), indicates that new high-magnitude debris flows in the catchment and the region are likely to occur within the next two decades. The knowledge of the potential frequency and magnitude (F–M) can support the creation of F–M relationships for Serra do Mar, a prerequisite for reliable hazard management and monitoring programs.

Landslides cause enormous economic damage and fatalities worldwide. The "Mega disaster" in the mountainous region of Rio de Janeiro took place on 11 th and 12 th January 2011 and impacted seven municipalities. These landslide events are considered the worst disasters in Brazilian history. Landslide susceptibility zonation is one of the most important tasks in landslide risk assessment. The different approaches for landslide susceptibility modelling include: 1) Heuristics; 2) Statistical and; 3) Deterministic modelling (slope stability factor). This paper presents the comparison of different scenarios based on SINMAP (Stability INdex MAPping) to determine the shallow landslide susceptibility in Nova Friburgo. Taking into consideration the landslide locations occurring on January 2011, the accuracy of the different analyses is evaluated and significant results are highlighted.

A ocorrência de escorregamentos translacionais rasos no litoral paulista é parte integrante da evolução natural das encostas, que se intensifica sob condições de clima tropical em uma morfologia de serras com desníveis em torno de 700m. Sob precipitações intensas, mesmo sem a interferência direta do homem, os movimentos de massa ocorrem de forma isolada ou generalizada. Devido à presença de um grande histórico de movimentos de massa, tomou-se como área de estudo parte da Serra do Mar Paulista localizada no município de Cubatão-SP. Esse trabalho teve como objetivo avaliar a técnica de análise multicriterial ponderada em SIG - Sistema de Informação Geográfica para elaboração de mapas de suscetibilidades aos escorregamentos translacionais. Buscou-se investigar como a qualidade dos dados e os pesos a eles atribuídos influenciam os resultados. Foram elaborados mapas de suscetibilidade, com diferentes pesos para os diferentes fatores, que são os condicionantes do processo: declividade, forma de vertente e litologias. Da mesma forma, foram também testados mapas de vertente com diferentes formas de obtenção. A utilização de dados de formas de vertente mais detalhados, produzidos a partir do modelo digital de elevação (MDE), produziram mapas de suscetibilidade aos escorregamentos mais adequados para estudos pontuais. Os mapas produzidos com os pesos 70% para declividade, 20% para forma de vertente e 10% para a geologia, no processo de validação, apresentaram o maior número de cicatrizes onde era esperado, na classe de muito alta suscetibilidade.

The objective of the present study, developed in a mountainous region in Brazil where many landslides occur, is to present a method for detecting landslide scars that couples image processing techniques with spatial analysis tools. An IKONOS image was initially segmented, and then classified through a Batthacharrya classifier, with an acceptance limit of 99%, resulting in 216 polygons identified with a spectral response similar to landslide scars. After making use of some spatial analysis tools that took into account a susceptibility map, a map of local drainage channels and highways, and the maximum expected size of scars in the study area, some features misinterpreted as scars were excluded. The 43 resulting features were then compared with visually interpreted landslide scars and field observations. The proposed method can be reproduced and enhanced by adding filtering criteria and was able to find new scars on the image, with a final error rate of 2.3%.

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