cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.7507058.v1
title: Wind-induced internal seiches in Vossoroca reservoir, PR, Brazil

description: ABSTRACT The vertical movements caused by internal waves in lakes and reservoirs have chemical and biological consequences for these ecosystems. The vast majority of studies that investigate internal waves are conducted on large lakes. There are just few researches that investigate this phenomenon on dendritic reservoirs. The purpose of this research was to identify internal waves (baroclinic mode) in the Vossoroca reservoir by using temperature time series recorded between May to November 2012. A two-layer method was used which considered rigid upper and lower boundaries. Moreover, the potential flow theory was used for both layers since the flow within each layer was considered irrotational. From the dispersion relation, we obtained the theoretical shallow internal wave period. The power spectral density (PSD) of temperature series of thermocline depth, provided by fast Fourier transform, helped in the identification on the frequency peak. Subsequently, the theoretical period was compared with the frequency spectra. Using a careful analysis (excluding the interference of solar radiation and intensity of wind), we observed a clear peak in November due to an internal wave with period around 8 hours, which matched the theoretical calculation from the dispersion relation equation for V1H1 mode. Weak winds from southwest excited a V1H1 baroclinic mode. According to spectral analysis, after the passage of this long-basin internal seiches, we identified the formation of higher vertical internal seiche modes. In addition, we observe indications of V1H1 mode degeneration.
DOI: 10.6084/m9.figshare.7507055
title: Soil variables as auxiliary information in spatial prediction of shallow water table levels for estimating recovered water volume

description: ABSTRACT Spatial data became increasingly utilized in many scientific fields due to the accessibility of monitoring data from different sources. In the case of hydrological mapping, measurements of external environmental conditions, such as soil, climate, vegetation, are often available in addition to the measurements of water characteristics. An integrated modelling approach capable to incorporate multiple input data sets that may have heterogeneous geometries and other error characteristics can be achieved using geostatistical techniques. In this study, different physical hydric properties of soils extensively sampled and topography were used as auxiliary information for making optimal, point-level inferences of water table depths in forest areas. We used data from 48 wells in the Bauru Aquifer System in the Santa Bárbara Ecological Station (EEcSB), in the municipality of Aguas de Santa Bárbara in São Paulo State, Brazil. Using the resistance of soil to penetration and topography as auxiliary variables helped reduce prediction errors. With the generated maps, it was possible to estimate the volumes of water recovered from the water table in two periods during the monitoring period. These values showed that 30% of the recovered volume would be sufficient for a three-month supply of water for a population of 30,000 inhabitants. Therefore, this raises the possibility of using areas such as the EEcSB as strategic supplies in artificial recharging management.
DOI: 10.6084/m9.figshare.7507055.v1
title: Soil variables as auxiliary information in spatial prediction of shallow water table levels for estimating recovered water volume

description: ABSTRACT Spatial data became increasingly utilized in many scientific fields due to the accessibility of monitoring data from different sources. In the case of hydrological mapping, measurements of external environmental conditions, such as soil, climate, vegetation, are often available in addition to the measurements of water characteristics. An integrated modelling approach capable to incorporate multiple input data sets that may have heterogeneous geometries and other error characteristics can be achieved using geostatistical techniques. In this study, different physical hydric properties of soils extensively sampled and topography were used as auxiliary information for making optimal, point-level inferences of water table depths in forest areas. We used data from 48 wells in the Bauru Aquifer System in the Santa Bárbara Ecological Station (EEcSB), in the municipality of Aguas de Santa Bárbara in São Paulo State, Brazil. Using the resistance of soil to penetration and topography as auxiliary variables helped reduce prediction errors. With the generated maps, it was possible to estimate the volumes of water recovered from the water table in two periods during the monitoring period. These values showed that 30% of the recovered volume would be sufficient for a three-month supply of water for a population of 30,000 inhabitants. Therefore, this raises the possibility of using areas such as the EEcSB as strategic supplies in artificial recharging management.
DOI: 10.6084/m9.figshare.7510535
title: Monitoring water quality of the Sergipe River basin: an evaluation using multivariate data analysis

description: ABSTRACT This study evaluated the efficiency of the water quality monitoring network of the Sergipe river basin, using multivariate data analysis, such as principal component analysis (PCA) and hierarchical cluster analysis (HCA). The PCA was applied to a data matrix consisting of 12 sampling stations and mean concentrations of 23 water quality parameters, obtained in four sampling campaigns from June/2013 to November/2015. All 12 sampling stations were considered as main (weight&gt;0.7) and therefore should remain in the monitoring program. The PCA pointed out that of the 23 measured parameters, only 16 are essential for water quality assessment, in the dry period and 17 in the rainy season. The HCA separated the stations of the monitoring network in 4 groups according to the water quality characteristics, considering the natural and anthropogenic impacts. The main impacts were originated from natural sources (mineral constituents) and the anthropogenic contributions were associated with urban input, sewage, industrial dumps and surface runoff from agricultural areas.
DOI: 10.6084/m9.figshare.7511543
title: Physical-based time series model applied on water table depths dynamics characteristics simulation

description: ABSTRACT Time series modelling applied to study water table depths monitoring data is an elegant way to model irregular and continuous data. When successive observations are dependent, future values may be predicted from past observations, and target parameters can be estimated. These may include expected values of groundwater levels, or probabilities that critical levels are exceeded at certain times or during certain periods. These target parameters are estimated with the purpose of obtaining characteristics of the development of a certain domain in time and such characteristics can, for instance, be extrapolated to future situations. In a system identification approach, is it possible to establish the dynamic relationship between water table perturbations and climatological events, vegetation, hydrogeological local conditions, management and groundwater abstraction. The aim of this work was demonstrate the use of a physical-based time series model to stablish the relationship between precipitation and water table depths from hydrogeological monitoring data. The results enabled to infer about water table dynamics even when it is affected by different climatological patterns, simulating mean, maximum and minimum states.
DOI: 10.6084/m9.figshare.7511543.v1
title: Physical-based time series model applied on water table depths dynamics characteristics simulation

description: ABSTRACT Time series modelling applied to study water table depths monitoring data is an elegant way to model irregular and continuous data. When successive observations are dependent, future values may be predicted from past observations, and target parameters can be estimated. These may include expected values of groundwater levels, or probabilities that critical levels are exceeded at certain times or during certain periods. These target parameters are estimated with the purpose of obtaining characteristics of the development of a certain domain in time and such characteristics can, for instance, be extrapolated to future situations. In a system identification approach, is it possible to establish the dynamic relationship between water table perturbations and climatological events, vegetation, hydrogeological local conditions, management and groundwater abstraction. The aim of this work was demonstrate the use of a physical-based time series model to stablish the relationship between precipitation and water table depths from hydrogeological monitoring data. The results enabled to infer about water table dynamics even when it is affected by different climatological patterns, simulating mean, maximum and minimum states.
DOI: 10.6084/m9.figshare.6858152
title: Influence of sewage disposal on the water quality of the Sucuru River alluvial aquifer in the municipality of Sumé-PB, Brazil

description: ABSTRACT The objective of this study was to evaluate the influence of sewage discharge on the quality of the water exploited from the Sucuru River alluvial aquifer, located in the municipality of Sumé, Paraíba state, Brazil. The study was based on physical-chemical and microbiological analyses of the waters from nine wells located along the alluvium. The results of the indicators showed that the alluvial aquifer studied has the capacity to filter and disperse pollutants. It is possible to observe a gradual reduction of chlorides, chemical oxygen demand and total dissolved solids along the alluvial perimeter. Thus, urban sewage becomes a source of water recharge with potential to be reused. We concluded that the utilization of water from this type of aquifer, which has been intensified in recent dry years, can be established in a safe and sustainable way. However, a strict monitoring plan for controlling recharge groundwater levels is highly necessary. Further studies in this direction should lead to a model of adequate use of this system, which can be reproduced in the Brazilian semi-arid region.
DOI: 10.6084/m9.figshare.6858152.v1
title: Influence of sewage disposal on the water quality of the Sucuru River alluvial aquifer in the municipality of Sumé-PB, Brazil

description: ABSTRACT The objective of this study was to evaluate the influence of sewage discharge on the quality of the water exploited from the Sucuru River alluvial aquifer, located in the municipality of Sumé, Paraíba state, Brazil. The study was based on physical-chemical and microbiological analyses of the waters from nine wells located along the alluvium. The results of the indicators showed that the alluvial aquifer studied has the capacity to filter and disperse pollutants. It is possible to observe a gradual reduction of chlorides, chemical oxygen demand and total dissolved solids along the alluvial perimeter. Thus, urban sewage becomes a source of water recharge with potential to be reused. We concluded that the utilization of water from this type of aquifer, which has been intensified in recent dry years, can be established in a safe and sustainable way. However, a strict monitoring plan for controlling recharge groundwater levels is highly necessary. Further studies in this direction should lead to a model of adequate use of this system, which can be reproduced in the Brazilian semi-arid region.
DOI: 10.6084/m9.figshare.6858125
title: Combination of the SCS-CN and the GRADEX models to maximum flow estimation

description: ABSTRACT The absence of hydrometric monitoring of adequate extension, periodicity, temporal resolution and quality is the Brazilian reality in many drainage basins. It’s common the use of rainfall-runoff models of simple application to determine rainfall excess volumes, such as the SCS-CN method. Although the SCS method is broadly accepted, many authors have questioned the results derived from its application to catchments with distinct characteristics than those studied during its original formulation. An alternate method for maximum flow estimation in catchments with scarce monitoring is the GRADEX method, which proposes extrapolation of the flood volumes’ frequency curve from precipitation series. Despite being a consolidated method, it is rarely used in Brazil because of the difficulties found in fulfilling its initial hypotheses. This paper suggests, therefore, the combination of both methods, aiming for a methodology that better describes the uncertainties involved in the determination of the direct flood volumes’ probability distribution. The case study is conducted on the Serra Azul river catchment, Juatuba – MG, which offers 12 years of continuous records. The referred combination occurs on the definition of the lower and upper boundaries of the probability distribution of global water retention in the soil and in the catchment, as embedded in the GRADEX method, from the CNASYMPTOTIC concept. The modelled scenarios bear evidence of the many possibilities that may exist in the extrapolation of the frequency curve of surface runoff volumes suggests a range of results that better underpins the definition of the saturation condition and, consequently, the maximum rainfall excess calculation, as compared to the originally proposed methods.
DOI: 10.6084/m9.figshare.6858125.v1
title: Combination of the SCS-CN and the GRADEX models to maximum flow estimation

description: ABSTRACT The absence of hydrometric monitoring of adequate extension, periodicity, temporal resolution and quality is the Brazilian reality in many drainage basins. It’s common the use of rainfall-runoff models of simple application to determine rainfall excess volumes, such as the SCS-CN method. Although the SCS method is broadly accepted, many authors have questioned the results derived from its application to catchments with distinct characteristics than those studied during its original formulation. An alternate method for maximum flow estimation in catchments with scarce monitoring is the GRADEX method, which proposes extrapolation of the flood volumes’ frequency curve from precipitation series. Despite being a consolidated method, it is rarely used in Brazil because of the difficulties found in fulfilling its initial hypotheses. This paper suggests, therefore, the combination of both methods, aiming for a methodology that better describes the uncertainties involved in the determination of the direct flood volumes’ probability distribution. The case study is conducted on the Serra Azul river catchment, Juatuba – MG, which offers 12 years of continuous records. The referred combination occurs on the definition of the lower and upper boundaries of the probability distribution of global water retention in the soil and in the catchment, as embedded in the GRADEX method, from the CNASYMPTOTIC concept. The modelled scenarios bear evidence of the many possibilities that may exist in the extrapolation of the frequency curve of surface runoff volumes suggests a range of results that better underpins the definition of the saturation condition and, consequently, the maximum rainfall excess calculation, as compared to the originally proposed methods.
DOI: 10.6084/m9.figshare.6858110
title: Alternative methodology to gap filling for generation of monthly rainfall series with GIS approach

description: ABSTRACT As an alternative to Gap filling in monthly average rainfall series, we attempted to present a methodology for the generation of series only with the observed data available in the rainfall stations present in the study area and its surroundings. For this, a computational tool was developed with a GIS approach, using scripts in the Python language, to automate the study steps. Two calculation alternatives for the mean precipitation, variable Thiessen polygons or variable inverse distance weights (IDW), were considered. Random gaps were imposed from a series of data without gaps allowing us to evaluate the presented methodology. The results of the series calculated according to this methodology were compared to two methods of Gap filling. The behavior of the series was evaluated through the analysis of position and dispersion measurements as well as the temporal behavior by the evaluation of the correlograms and periodograms. The results are found to be satisfactory, which demonstrates the equivalence of the proposal with results found with the gap filling methods under the tested conditions. The differences found between the series were small, which was reflected in the Nash-Sutcliffe Indexes. There were no significant differences between the calculation alternatives by Thiessen polygons or IDW weights.
DOI: 10.6084/m9.figshare.6858110.v1
title: Alternative methodology to gap filling for generation of monthly rainfall series with GIS approach

description: ABSTRACT As an alternative to Gap filling in monthly average rainfall series, we attempted to present a methodology for the generation of series only with the observed data available in the rainfall stations present in the study area and its surroundings. For this, a computational tool was developed with a GIS approach, using scripts in the Python language, to automate the study steps. Two calculation alternatives for the mean precipitation, variable Thiessen polygons or variable inverse distance weights (IDW), were considered. Random gaps were imposed from a series of data without gaps allowing us to evaluate the presented methodology. The results of the series calculated according to this methodology were compared to two methods of Gap filling. The behavior of the series was evaluated through the analysis of position and dispersion measurements as well as the temporal behavior by the evaluation of the correlograms and periodograms. The results are found to be satisfactory, which demonstrates the equivalence of the proposal with results found with the gap filling methods under the tested conditions. The differences found between the series were small, which was reflected in the Nash-Sutcliffe Indexes. There were no significant differences between the calculation alternatives by Thiessen polygons or IDW weights.
DOI: 10.6084/m9.figshare.6858128
title: Relationships between pacific and atlantic ocean sea surface temperatures and water levels from satellite altimetry data in the Amazon rivers

description: ABSTRACT The influence of SST (Sea Surface Temperature) of adjacent oceans on the variability of water levels in the Amazon basin was investigated by using radar altimetry from the ENVISAT and Jason-2 missions. Data from the in situ network was used to compare the correlations of water level and SST anomalies in the sub-basins of the Amazonas-Peru, Solimões, Negro and Madeira Rivers. The analysis was made on the monthly and annual scales between 2003 and 2015. The correlations with anomalies of levels from altimetry presented higher accuracy indices than those from the conventional network. In general, ATN and PAC are better correlated with the entire basin. During the flood months, most of the sub-basins presented negative associations with ATN. In the months of ebb, the response to the indexes varies according to the region. The satellite altimetry data permitted to reach regions non-monitored by the conventional network. We also analyzed the impacts of hydrological extremes in all these sub-regions in the last 13 years. In Western Amazon, the drought of 2010 stands out, associated with the warming of the Tropical Atlantic and the El Niño. In the Negro River, the water level anomalies were the lowest in the basin during the 2005 drought. In the Purus River, the effects of the 2010 drought that affected the entire Amazon, were higher in 2011 due to its strong relationship with the Atlântic and Pacific oceans. In general, hydrological extremes are stronger or highlighted when SST increases simultaneously in both oceans.
DOI: 10.6084/m9.figshare.6858128.v1
title: Relationships between pacific and atlantic ocean sea surface temperatures and water levels from satellite altimetry data in the Amazon rivers

description: ABSTRACT The influence of SST (Sea Surface Temperature) of adjacent oceans on the variability of water levels in the Amazon basin was investigated by using radar altimetry from the ENVISAT and Jason-2 missions. Data from the in situ network was used to compare the correlations of water level and SST anomalies in the sub-basins of the Amazonas-Peru, Solimões, Negro and Madeira Rivers. The analysis was made on the monthly and annual scales between 2003 and 2015. The correlations with anomalies of levels from altimetry presented higher accuracy indices than those from the conventional network. In general, ATN and PAC are better correlated with the entire basin. During the flood months, most of the sub-basins presented negative associations with ATN. In the months of ebb, the response to the indexes varies according to the region. The satellite altimetry data permitted to reach regions non-monitored by the conventional network. We also analyzed the impacts of hydrological extremes in all these sub-regions in the last 13 years. In Western Amazon, the drought of 2010 stands out, associated with the warming of the Tropical Atlantic and the El Niño. In the Negro River, the water level anomalies were the lowest in the basin during the 2005 drought. In the Purus River, the effects of the 2010 drought that affected the entire Amazon, were higher in 2011 due to its strong relationship with the Atlântic and Pacific oceans. In general, hydrological extremes are stronger or highlighted when SST increases simultaneously in both oceans.
DOI: 10.13139/ornlnccs/1772568
title: Neutron Imaging dataset for SMC 2021 data challenge

description: The neutron radiography (nR) dataset provides information of the neutron events as measured for the Siemens star mask using the Timepix3 detector. The recordings consist of the position (x and y axes), the time-stamp, and time-over-threshold (TOT) values of each neutron event.
DOI: 10.13139/olcf/1772569
title: 2021 Smoky Mountains Conference Data Challenge Synthetic-to-Real Domain Adaptation for Autonomous Driving Dataset

description: The dataset is comprised of both real and synthetic images from a vehicleâs forward-facing camera. Each camera image is accompanied by a corresponding pixel-level semantic segmentation image (all files are .png files). In total, the dataset contains 5600 images in the training/validation set and 1400 images in the testing set. The training dataset contains mostly synthetic RGB images collected with a wide range of weather and lighting conditions using the CARLA simulator [1]. In addition, the training data also includes a small pre-selected subset of data from the Cityscapes training dataset â which is comprised of RGB-segmentation image pairs from driving scenarios in various European cities [2]. The testing data is split into three sets. The first set contains synthetic CARLA images with weather/lighting conditions that were not present in the training set. The second set is a subset of the Cityscapes testing dataset. Finally, the third set is an unknown testing set which will not be revealed to the participants until after the submission deadline. [1] Dosovitskiy, A., Ros, G., Codevilla, F., Lopez, A., & Koltun, V. (2017, October). CARLA: An open urban driving simulator. In Conference on robot learning (pp. 1-16). PMLR. [2] Cordts, M., Omran, M., Ramos, S., Rehfeld, T., Enzweiler, M., Benenson, R., ... & Schiele, B. (2016). The cityscapes dataset for semantic urban scene understanding. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 3213-3223).