CABra: a novel large-sample dataset for Brazilian catchments

Almagro, André; Oliveira, Paulo Tarso Sanches de; Neto, Antônio Alves Meira; Roy, Tirthankar; Troch, P. A.

doi:10.5194/hess-2020-521

Cited by 9 publications

(26 citation statements)

References 60 publications

(70 reference statements)

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“…Our ECI results were positively correlated with mean slope and mean elevation corroborating the gaining water condition found in 72% of the catchments located in the Atlantic Forest biome, which presents the highest mean elevation and slope (Almagro et al, 2020). Indeed, low and high slopes were associated with smaller and larger effective areas, respectively (Figure 5b).…”

Section: The Eci Most Influencing Attributessupporting

confidence: 85%

“…The country comprises six biomes with a climate that varies from semiarid to subtropical with annual precipitation ranging from about 400 to 4,000 mm. Elevation ranges from sea level up to 2,900 m. In this study, we used the Catchment Attributes for Brazil dataset (CABra) (Almagro, Oliveira, Meira Neto, Roy, & Troch, 2020) for the analysis detailed throughout the next sections. CABra is a large-scale dataset for catchment attributes, comprising a set of several multi-scale attributes for 735 Brazilian catchments.…”

Section: Study Area and Datamentioning

confidence: 99%

“…We have used P and PET from the climatology of the CABra dataset (calculated over the 1980-2010 period). As described in Almagro et al (2020), P is derived from a reference dataset obtained from˜4,000 rain gauges that cover the Brazilian area. Nonetheless, as there are catchments with area beyond borders of the Brazilian territory, Almagroet al (2020) developed an ensemble dataset (reference + ERA5) that we used in the present study.…”

Section: The Effective Catchment Indexmentioning

confidence: 99%

“…Nonetheless, as there are catchments with area beyond borders of the Brazilian territory, Almagroet al (2020) developed an ensemble dataset (reference + ERA5) that we used in the present study. The PET, in turn, is also a climatology from daily estimation by the Priestley and Taylor method (see Almagro et al, 2020). Finally, the Q is only based on streamflow gauge observations over the Brazilian catchments.…”

Section: The Effective Catchment Indexmentioning

confidence: 99%

“…The precipitation seasonality indicates the timing between the precipitation seasonal cycle and the temperature seasonal cycle. Values of this attribute close to +1 indicate the occurrence of summer precipitation while values close to -1 indicate winter precipitation (Almagro et al, 2020). Additionally, we added the Brazilian biomes -Amazon, Cerrado, Caatinga, Atlantic Forest, Pantanal, and Pampa -and soil texture -clay, clay loam, loam, sandy clay, sandy loam, and sandy clay-loam -as categorical variables to the analysis by using the One-Hot encoding method (Pedregosa et al , 2011).…”

Section: Influence Of Catchment Attributes On Ecimentioning

confidence: 99%

See 4 more Smart Citations

Are Brazilian Catchments Gaining or Losing Water? The Effective Area of Tropical Catchments

Schwamback¹,

Gesualdo²,

Sone³

et al. 2021

Preprint

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Similar to most countries, the Brazilian water resources management considers topographically delineated catchment as a territorial unit for policy implementation. Yet, previous studies have shown that catchments are not hydrologically isolated, and topographic limits often neglect the groundwater boundaries. Thus, studies on effective catchment area are promising for shedding light on inter-catchment groundwater flow. Here, we investigated the deviation between the topographic and effective areas across Brazil. We applied the Effective Catchment Area index (ECI) to 733 Brazilian catchments and identified the most influencing attributes on the ECI by using Principal Component and Random Forest Analyses (PCA and RFA, respectively). Further analysis of consistency was carried out by contrasting the ECI values against the expected range of the Budyko curve considering both topographic and effective catchment areas (classic and adjusted framework). Considering the studied catchments, 15% and 16% of their effective areas were respectively smaller than half (strong losing water condition) and larger than double (strong gaining water condition) of their corresponding topographic areas. The aridity index was the main driving factor and negatively correlated with ECI followed by mean slope, precipitation seasonality, and mean elevation. In general, the more arid biomes in Brazil — the Cerrado and Caatinga — are prone to have smaller effective areas while larger effective areas were mostly found in the Atlantic Forest biome, a humid tropical region with a higher mean elevation. We highlight the potential of adopting a pooling of catchments based on their interconnectivity to minimize management costs while maximizing synergies and lessening trade-offs of water transfer processes. Our results contribute to a better country-scale understanding of hydrological connectivity among catchments and highlight the need to consider the effective catchment area to overcome water-food-energy security challenges on multiple scales.

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Section: The Eci Most Influencing Attributessupporting

confidence: 85%

Section: Study Area and Datamentioning

confidence: 99%

Section: The Effective Catchment Indexmentioning

confidence: 99%

Section: The Effective Catchment Indexmentioning

confidence: 99%

Section: Influence Of Catchment Attributes On Ecimentioning

confidence: 99%

See 3 more Smart Citations

Are Brazilian Catchments Gaining or Losing Water? The Effective Area of Tropical Catchments

Schwamback¹,

Gesualdo²,

Sone³

et al. 2021

Preprint

Self Cite

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Dynamic quantile regression for trend analysis of streamflow time series

Lima

Cribari‐Neto

Lima-Júnior

2022

River Research & Apps

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Water availability is an essential factor in maintaining the integrity of ecological processes and is a source of socio-economic development. However, socio-economic development increases the pressure on water resources. Thus, understanding the flow regime in a watershed is essential to correct water resource management. In this study, we propose using dynamic quantile regression (DQR) to analyse trends in streamflow time series. DQR is a subset of the general class of semi-parametric quantile regression models, which is tailored for time series modelling. It allows for autoregressive dynamics and modelling of trending behaviour and seasonal fluctuations.With a single model, it is possible to estimate the impacts of predictor variables on any given quantile of the response distribution instead of simply evaluating such effects on the mean response, as is typically done in other statistical approaches. In other words, it is possible to gain knowledge on how predictors impact the magnitude of streamflow in wet (upper quantiles) and dry seasons (lower quantiles) separately. We used DQR to model a streamflow time series of 27 gauges, distributed in the Araguaia watershed in central Brazil. The results show that, except for a single gauge (Alto Araguaia), there are downward streamflow trends, thus non-stationary behaviour. The model yielded excellent data fits (pseudo-R 2 above 0.80), and it was possible to obtain a confidence interval for each slope. In our analysis, the usefulness of DQR modelling for assessing trends in streamflow time series is shown and, consequently, for achieving efficient water resource management.

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Assessment of water availability vulnerability in the Cerrado

Althoff

Silva

2021

Appl Water Sci

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Many basins in the Cerrado biome already face increases in water disputes caused by agricultural expansion without long-term planning and monitoring of natural resources. The amount and timing of water availability are crucial for the socioeconomic development of agricultural activities and climate change resilience enhancement in the Cerrado. This study relied on a dataset developed for the Cerrado to characterize its climate and current water availability status. Different climate indices and hydrological signatures were adopted to describe the energy and water budget, climate seasonality, flow magnitude, flow dynamics, and average duration of low-flow events. Risk analysis was carried out to classify the monthly risk severity and identify periods and regions under a higher pressure regarding water availability in the Cerrado. Overall, the water availability is higher in the western and southern regions and lower in the eastern and northern regions, which experience a transition to a humid and semiarid climate, respectively. The water resources in the Cerrado occur under the highest pressure in September and October. We also identified regions with the potential to increase sustainable water use. These regions exhibit a low ratio between the flow equal to or exceeded 95% of the time and the mean flow (Q95/Q), which indicates that sustainable water use may be improved with techniques related to flow regularization and rainwater/runoff harvesting.

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CABra: a novel large-sample dataset for Brazilian catchments

Cited by 9 publications

References 60 publications

Are Brazilian Catchments Gaining or Losing Water? The Effective Area of Tropical Catchments

Are Brazilian Catchments Gaining or Losing Water? The Effective Area of Tropical Catchments

Dynamic quantile regression for trend analysis of streamflow time series

Assessment of water availability vulnerability in the Cerrado

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