cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.14282077
title: Climate Change, Disaster Increase and Preventive Needs

description: Abstract Natural disasters occurred since the emergence of man on planet Earth, about 350 thousands years ago. Its have been modified ecosystems in a way that can provide the most varied impacts population treatment, quality of life and others activities. Disasters in Brazil have led to significant losses, especially in areas and regions that concentrate the poorest and most vulnerable populations. As a hypothesis, we believe that it is pertinent to disseminate information on prevention and mitigation measures, specific to each identified vulnerability. The insertion of knowledge on integrated disaster risk management in higher education institutions presents itself as an effective option for the dissemination of prevention culture and the strengthening of more resilient communities. The general objective is to find out which natural physical phenomena have contributed to slowing down social and economic development. Given that the study of disasters is incipient in the country, we have opted for an exploratory research whose purpose was to provide us with greater scope with the problem of the research in question. In the contemporary world, it is essential that managers invest in risk and vulnerability management. As a suggestion, I believe that we can take this theme to the undergraduate, graduate and postgraduate courses strictly and broadly so that everyone has an understanding of the subject and can disseminate in a technical scientific way the strategic measures to mitigate the destructive effects of natural physical phenomena that trigger disasters.
DOI: 10.6084/m9.figshare.14282080.v1
title: Determination of the Cardinal Temperatures of Cashew Tree Using a Nonlinear Development Model

description: Abstract The aim of this study was to determine the cardinal temperatures of three cashew tree clones using a nonlinear development model for estimate the phenological stage of ripening of their fruits. Between August 2010 and August 2012, up to ten young fruits per clone were identified weekly, accompanying them until they ripened. Fruit development rate was obtained with the Wang and Engel model, using three approximations of the air temperature of Santo Antônio de Leverger / MT (15° 51’ S and 56°04’ W, 140 m). Fruits marked from May to July required a greater time, nearly 44 days to reach maturity due to lower air temperature values during this period, with a compensated average of 23 °C. However, fruits marked between August and October, the period with the largest average compensated air, of approximately 26.6 °C required a shorter time, 37 days. Cardinal temperatures ranged from 14.0 to 17 °C, 27.5 to 32.5 °C and 33.0 to 41.5 °C for the minimum, optimal and maximum base temperatures, respectively.
DOI: 10.6084/m9.figshare.14282080
title: Determination of the Cardinal Temperatures of Cashew Tree Using a Nonlinear Development Model

description: Abstract The aim of this study was to determine the cardinal temperatures of three cashew tree clones using a nonlinear development model for estimate the phenological stage of ripening of their fruits. Between August 2010 and August 2012, up to ten young fruits per clone were identified weekly, accompanying them until they ripened. Fruit development rate was obtained with the Wang and Engel model, using three approximations of the air temperature of Santo Antônio de Leverger / MT (15° 51’ S and 56°04’ W, 140 m). Fruits marked from May to July required a greater time, nearly 44 days to reach maturity due to lower air temperature values during this period, with a compensated average of 23 °C. However, fruits marked between August and October, the period with the largest average compensated air, of approximately 26.6 °C required a shorter time, 37 days. Cardinal temperatures ranged from 14.0 to 17 °C, 27.5 to 32.5 °C and 33.0 to 41.5 °C for the minimum, optimal and maximum base temperatures, respectively.
DOI: 10.6084/m9.figshare.14282077.v1
title: Climate Change, Disaster Increase and Preventive Needs

description: Abstract Natural disasters occurred since the emergence of man on planet Earth, about 350 thousands years ago. Its have been modified ecosystems in a way that can provide the most varied impacts population treatment, quality of life and others activities. Disasters in Brazil have led to significant losses, especially in areas and regions that concentrate the poorest and most vulnerable populations. As a hypothesis, we believe that it is pertinent to disseminate information on prevention and mitigation measures, specific to each identified vulnerability. The insertion of knowledge on integrated disaster risk management in higher education institutions presents itself as an effective option for the dissemination of prevention culture and the strengthening of more resilient communities. The general objective is to find out which natural physical phenomena have contributed to slowing down social and economic development. Given that the study of disasters is incipient in the country, we have opted for an exploratory research whose purpose was to provide us with greater scope with the problem of the research in question. In the contemporary world, it is essential that managers invest in risk and vulnerability management. As a suggestion, I believe that we can take this theme to the undergraduate, graduate and postgraduate courses strictly and broadly so that everyone has an understanding of the subject and can disseminate in a technical scientific way the strategic measures to mitigate the destructive effects of natural physical phenomena that trigger disasters.
DOI: 10.6084/m9.figshare.14282081
title: Simulating Weather Events with a Linked Atmosphere-Hydrology Model

description: Abstract This study aims at assess the importance of a conceptual representation of hydrological processes when modelling atmospheric circulation. It compares results from a regional atmospheric model that interprets land surface hydrological processes based on parameterizations with results from a two-way coupled atmosphere-hydrological model that has a process-based approach to the land surface hydrological cycle. These numerical models were applied to a region covering the Rio Grande basin, Brazil. The same input data, initial and boundary conditions were used on a 31-day simulation period. Results obtained from these simulations were compared to visible satellite images and gauging rainfall stations for three case studies that included a cold front, deep convective clouds and stable atmospheric conditions. Both models could reproduce regional patterns of air circulation and rainfall influenced by the orography of the basin. However, atmospheric processes driven by spatial gradients of land surface temperature or local surface heating were spatially better represented by the atmospheric-hydrological modelling system rather than the regional atmospheric model. Since areas characterized by spatial gradients of land surface temperature and local surface heating were closely associated with convergent air flows near land surface and strong vertical motion in the mid troposphere, this finding enhanced the role of a good representation of land surface hydrological processes for a better modelling the atmospheric dynamics.
DOI: 10.6084/m9.figshare.14282083
title: Gap Filling and Pluviometrics Spacialization Data: Challenges and perspectives

description: Abstract Precipitation is one of the most important climatic variables for urban and rural planning, to monitor extreme events that may have an impact on society and to assist in urban drainage projects, in order to reduce the risks of floods, or even engineering works, such as dams dimensioning. However, failures in extensive series hamper these studies, and it is necessary to use models to fill them. The present study aims to review the methods of filling in gaps and spatial interpolation of precipitation data. The review of the methods was carried out from the research and reading of bibliographic materials, in order to conceptualize the approaches, identify the advantages and disadvantages of each method and present how recent studies, national and international, have innovated when comparing the performance in different areas of study. Based on this review, the main methods for filling gaps are as follows: i) weighting from Simple or Multiple Linear Regression; ii) mathematical models based on machine learning, such as Artificial Neural Networks; iii) spatial interpolators for filling gaps (Distance Inverse, Natural Neighbor, Krigagem). Finally, there was an evolution in the interpolation and fault filling techniques in the last decades, due to the evolution of computational and technological capacity.
DOI: 10.6084/m9.figshare.14282081.v1
title: Simulating Weather Events with a Linked Atmosphere-Hydrology Model

description: Abstract This study aims at assess the importance of a conceptual representation of hydrological processes when modelling atmospheric circulation. It compares results from a regional atmospheric model that interprets land surface hydrological processes based on parameterizations with results from a two-way coupled atmosphere-hydrological model that has a process-based approach to the land surface hydrological cycle. These numerical models were applied to a region covering the Rio Grande basin, Brazil. The same input data, initial and boundary conditions were used on a 31-day simulation period. Results obtained from these simulations were compared to visible satellite images and gauging rainfall stations for three case studies that included a cold front, deep convective clouds and stable atmospheric conditions. Both models could reproduce regional patterns of air circulation and rainfall influenced by the orography of the basin. However, atmospheric processes driven by spatial gradients of land surface temperature or local surface heating were spatially better represented by the atmospheric-hydrological modelling system rather than the regional atmospheric model. Since areas characterized by spatial gradients of land surface temperature and local surface heating were closely associated with convergent air flows near land surface and strong vertical motion in the mid troposphere, this finding enhanced the role of a good representation of land surface hydrological processes for a better modelling the atmospheric dynamics.
DOI: 10.6084/m9.figshare.14282086
title: Assessments of the Impacts of Land Use and Cover Change and Emission Scenarios (RCP 8.5) on the Water Budget in the Madeira River Basin

description: Abstract In this study, we evaluated the impacts of increased GHGs (RCP 8.5 scenario) and future deforestations on the water cycle in the Madeira River basin by using the Eta Regional Model and MGB-IPH Large-scale Hydrological Model, forced by Brazilian Model of the Terrestrial System (BESM-AO 2.5). In the RCP 8.5 scenario, the model demonstrated sensitivity over the entire Madeira basin, with a temperature increase of 4.0 °C. The increase was intensified with the deforestation scenarios for 2050 (4.8 °C) and 2100 (6.2 °C). In the deforestation scenarios, the Negative Feedback Mechanism (NFM) was predominant because, although there were reductions in precipitation and evapotranspiration, the convergence of humidity presented an increase in all the scenarios. Regarding the hydrological processes, an increase in the discharges in most stations for all future scenarios for RCP8.5 and deforestation was observed. The increase in precipitation in the dry season explains in part the increase in the discharges and in the flood area in the Madeira basin. The increased upstream precipitation and the changes in soil parameters associated with the changes in land use contributed to the increase in the flood area over the Madeira basin. These changes can have negative effects on the environment, on water resources and on the main sectors of the economy, which directly affect the communities that inhabit the river banks, especially the vulnerable populations of the Madeira basin.
DOI: 10.6084/m9.figshare.14282089
title: Upper Tropospheric Cyclonic Vortex and Brazilian Northeast Jet Stream over Alagoas State: Circulation Patterns and Rainfall

description: Abstract Interaction between Brazilian Northeast Jet Stream (BNEJS) and Upper Tropospheric Cyclonic Vortexes (UTCV) isn't still well known, as well as its seasonal variability and relation with rainfall pattern. This study's aim is to determine the air circulation patterns in UTCV events with BNEJS in La Niña and El Niño years and its connections with rainfall in the Alagoas State. These connections were analyzed for 9 years between 1988 and 2000 in El Niño, La Niña and Neutral years. NCEP Reanalysis data, rainfall data from 71 meteorological stations and satellite images were used. Fifty-eight percent of 140 observed UTCVs were associated with BNEJS events located in the Brazilian Northeast and 26%, located over the Alagoas State. Three types of BNEJS patterns, denominated as Meridional (M), Zonal (Z) and Transversal (T), have been identified. The M-type BNEJS was the most frequent in Alagoas State, especially in El Niño years. Z and T-types occurred less frequently and were rarely seen in La Niña years. The results showed that in the M-type BNEJS events in 48% of days were not registered precipitation, while Z and T events recorded rainfall in almost 96% of the days.
DOI: 10.6084/m9.figshare.14282086.v1
title: Assessments of the Impacts of Land Use and Cover Change and Emission Scenarios (RCP 8.5) on the Water Budget in the Madeira River Basin

description: Abstract In this study, we evaluated the impacts of increased GHGs (RCP 8.5 scenario) and future deforestations on the water cycle in the Madeira River basin by using the Eta Regional Model and MGB-IPH Large-scale Hydrological Model, forced by Brazilian Model of the Terrestrial System (BESM-AO 2.5). In the RCP 8.5 scenario, the model demonstrated sensitivity over the entire Madeira basin, with a temperature increase of 4.0 °C. The increase was intensified with the deforestation scenarios for 2050 (4.8 °C) and 2100 (6.2 °C). In the deforestation scenarios, the Negative Feedback Mechanism (NFM) was predominant because, although there were reductions in precipitation and evapotranspiration, the convergence of humidity presented an increase in all the scenarios. Regarding the hydrological processes, an increase in the discharges in most stations for all future scenarios for RCP8.5 and deforestation was observed. The increase in precipitation in the dry season explains in part the increase in the discharges and in the flood area in the Madeira basin. The increased upstream precipitation and the changes in soil parameters associated with the changes in land use contributed to the increase in the flood area over the Madeira basin. These changes can have negative effects on the environment, on water resources and on the main sectors of the economy, which directly affect the communities that inhabit the river banks, especially the vulnerable populations of the Madeira basin.
DOI: 10.6084/m9.figshare.14282090.v1
title: CESP Integrated Precipitation Estimation and Forecasting System for its Watersheds

description: Abstract Flow forecasting is one of the most important information to scheduling hydroelectric power generation and short- to long-term planning. Flow prediction is most relevant in water scarcity scenarios, when there is a reduction in hydroelectric power generation and an increase in production by thermoelectric plants to guarantee other uses of water under such conditions. The prediction and prognostic precipitation through stochastic and deterministic models is essential even with the inherent limitations of atmospheric phenomenological complexity. Establishing guidelines upon such models based on hydrometeorological variables (e.g., precipitation time series) and climate phenomena can reduce errors and improve reservoir operations. The National System Operator (ONS) and generation agencies may decide with fewer operational risks in order to optimize energy resources, minimize consumer costs and supply electricity even in times of water scarcity. Thus, this paper describes a rain monitoring and forecasting system in the CESP watersheds to improve the streamflow estimation of CESP reservoirs. We present an objective statistical analysis scheme (ANOBES) that integrates the meteorological satellite precipitation estimation with CESP, DAEE and ANA telemetric network rainfall measurements. Rain forecasting up to five days in advance is performed with the ARPS system. The estimates, measurements and rainfall simulations obtained were used in tributary flow simulations of CESP watersheds with the SMAP model for verification. Rain forecast up to five days in advance was made with the ARPS system. The estimates, measurements and rainfall simulations obtained were used in tributary flow simulations in CESP basins with the SMAP model for verification. The results suggest performance improvement with data integration and precipitation prediction with the ARPS system.
DOI: 10.6084/m9.figshare.14282089.v1
title: Upper Tropospheric Cyclonic Vortex and Brazilian Northeast Jet Stream over Alagoas State: Circulation Patterns and Rainfall

description: Abstract Interaction between Brazilian Northeast Jet Stream (BNEJS) and Upper Tropospheric Cyclonic Vortexes (UTCV) isn't still well known, as well as its seasonal variability and relation with rainfall pattern. This study's aim is to determine the air circulation patterns in UTCV events with BNEJS in La Niña and El Niño years and its connections with rainfall in the Alagoas State. These connections were analyzed for 9 years between 1988 and 2000 in El Niño, La Niña and Neutral years. NCEP Reanalysis data, rainfall data from 71 meteorological stations and satellite images were used. Fifty-eight percent of 140 observed UTCVs were associated with BNEJS events located in the Brazilian Northeast and 26%, located over the Alagoas State. Three types of BNEJS patterns, denominated as Meridional (M), Zonal (Z) and Transversal (T), have been identified. The M-type BNEJS was the most frequent in Alagoas State, especially in El Niño years. Z and T-types occurred less frequently and were rarely seen in La Niña years. The results showed that in the M-type BNEJS events in 48% of days were not registered precipitation, while Z and T events recorded rainfall in almost 96% of the days.
DOI: 10.6084/m9.figshare.14282090
title: CESP Integrated Precipitation Estimation and Forecasting System for its Watersheds

description: Abstract Flow forecasting is one of the most important information to scheduling hydroelectric power generation and short- to long-term planning. Flow prediction is most relevant in water scarcity scenarios, when there is a reduction in hydroelectric power generation and an increase in production by thermoelectric plants to guarantee other uses of water under such conditions. The prediction and prognostic precipitation through stochastic and deterministic models is essential even with the inherent limitations of atmospheric phenomenological complexity. Establishing guidelines upon such models based on hydrometeorological variables (e.g., precipitation time series) and climate phenomena can reduce errors and improve reservoir operations. The National System Operator (ONS) and generation agencies may decide with fewer operational risks in order to optimize energy resources, minimize consumer costs and supply electricity even in times of water scarcity. Thus, this paper describes a rain monitoring and forecasting system in the CESP watersheds to improve the streamflow estimation of CESP reservoirs. We present an objective statistical analysis scheme (ANOBES) that integrates the meteorological satellite precipitation estimation with CESP, DAEE and ANA telemetric network rainfall measurements. Rain forecasting up to five days in advance is performed with the ARPS system. The estimates, measurements and rainfall simulations obtained were used in tributary flow simulations of CESP watersheds with the SMAP model for verification. Rain forecast up to five days in advance was made with the ARPS system. The estimates, measurements and rainfall simulations obtained were used in tributary flow simulations in CESP basins with the SMAP model for verification. The results suggest performance improvement with data integration and precipitation prediction with the ARPS system.
DOI: 10.6084/m9.figshare.14282092
title: Evaluation of Erosivity Extremes Caused by Precipitation in the Apodi/Mossoró-RN River Basin

description: Abstract Identifying areas with a potential risk of environmental degradation by anthropic or natural processes is important for sustainable management of natural resources, especially in the semiarid regions of northeastern Brazil. Rain erosivity is given by the Universal Soil Loss Equation (EUPS) which relates the erosive capacity of rainfall and its ability to disintegrate by the impact of the particle surface. The present study aimed to evaluate the erosion index (EI30) and to evaluate the EI30 extremes in the Apodi/Mossoró watershed through the theory of extreme values and to associate with the rainfall pattern of the region. For this, precipitation data from the Agência Nacional das águas (ANA) and the Tropical Rainfall Measuring Mission (TRMM) project were used. Among several methodologies for the selection of mathematical models that explain the extremes of erosivity, this research used the Akaike Information Criteria (AIC) and the Schwarz Bayesian Criterion (BIC), together with the correlation assessment at EI30 and the coefficient of rain (Rc). Thus, Felipe Guerra station presented the best results to generate the hydrological effect of the EI30 in the basin with TRMM data. It can be concluded that TRMM data can be of great value for the estimation of the EI30 where observational data is not available. Moreover, the EI30 follows the precipitation seasonality and was classified as moderate whose highest values occur from February to May.
DOI: 10.6084/m9.figshare.14282096.v1
title: A Conceptual Model of Probability for Determining Population Vulnerability to Climate

description: Abstract The population's vulnerability assessment is an analysis of the expected impacts, risk modeling, exposure, sensitivity and lack of adaptability of a specific region or sector to the effects of extreme weather events. The vulnerability encompasses a variety of concepts including sensitivity or susceptibility to harm and a lack of ability to cope and adapt. One way to analyze these very different aspects is through a stochastic process, such as conditional probability. In this article, a conceptual model is presented to assess the population's vulnerability to the climate, taking into account one of the susceptible regions of Brazil, the Northeast. The results show that the proposed indicator IVPopS presents the most vulnerable central semi-arid region, in addition to a detailed assessment in each component of the indicator. Production areas such as Petrolina-PE have high levels of risk (0,604), exposure (0,863), sensitivity (0,910), while the inability to adapt is low (0.002).