The Drivers of Hydrologic Behavior in Brazil: Insights From a Catchment Classification

Abstract Despite hosting ∼16% of the global freshwater and almost 50% of water resources in South America, Brazilian catchment‐scale relationships between drivers and streamflow are still poorly understood. Here, we used streamflow signatures and attributes of 735 catchments from the Catchment Attributes for Brazil data set to investigate the dominant hydrological processes for the catchments. We also assess how catchments group based on hydrologic behavior similarities and analyze which climatic/landscape attributes control the streamflow variability. To classify and group the catchments, we used the k ‐means method optimized by the Elbow approach, along with a Principal Component Analysis. Uncertainty on catchment grouping was checked by k ‐fold cross‐validation. Then, we used a recursive feature elimination using the random forest technique to assess the most influential catchment attributes to the hydrological signatures. Our results revealed six similarity groups, which followed mainly an aridity gradient ranging from the wettest to the driest, but also seasonality. The climate is the primary driver of hydrological behavior for the water‐limited groups, highlighting the influence and importance of the atmospheric demand in several Brazilian catchments. High soil storage capacity in energy‐limited catchments associated with high precipitation led to high discharge all year due to the subsurface fluxes' contribution. Our findings may be useful to improve streamflow predictability and hydrological behavior identification by further understanding hydrological similarities and their signatures due to catchment landscape characteristics. Further, by employing an easily reproducible methodology and clear metrics to weigh uncertainty, our study provides a significant step toward establishing a catchment‐scale common classification system.

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Publication Details

Journal
Water Resources Research
Published
2024-08-01
DOI
https://doi.org/10.1029/2024wr037212
Citations
16
Primary Topic
Hydrology and Watershed Management Studies
Type
article
Field-Weighted Citation Impact
3.23

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article

The Drivers of Hydrologic Behavior in Brazil: Insights From a Catchment Classification

Paulo Tarso Sanches de Oliveira, Noemi Vergopolan, André Almagro, Antônio Alves Meira Neto et al.
16 citations
Water Resources Research
Hydrology and Watershed Management Studies
3.23
article

The Drivers of Hydrologic Behavior in Brazil: Insights From a Catchment Classification

Paulo Tarso Sanches de Oliveira, Noemi Vergopolan, André Almagro, Antônio Alves Meira Neto, Tirthankar Roy, P. A. Troch
article en
16 citations

Abstract

Abstract Despite hosting ∼16% of the global freshwater and almost 50% of water resources in South America, Brazilian catchment‐scale relationships between drivers and streamflow are still poorly understood. Here, we used streamflow signatures and attributes of 735 catchments from the Catchment Attributes for Brazil data set to investigate the dominant hydrological processes for the catchments. We also assess how catchments group based on hydrologic behavior similarities and analyze which climatic/landscape attributes control the streamflow variability. To classify and group the catchments, we used the k ‐means method optimized by the Elbow approach, along with a Principal Component Analysis. Uncertainty on catchment grouping was checked by k ‐fold cross‐validation. Then, we used a recursive feature elimination using the random forest technique to assess the most influential catchment attributes to the hydrological signatures. Our results revealed six similarity groups, which followed mainly an aridity gradient ranging from the wettest to the driest, but also seasonality. The climate is the primary driver of hydrological behavior for the water‐limited groups, highlighting the influence and importance of the atmospheric demand in several Brazilian catchments. High soil storage capacity in energy‐limited catchments associated with high precipitation led to high discharge all year due to the subsurface fluxes' contribution. Our findings may be useful to improve streamflow predictability and hydrological behavior identification by further understanding hydrological similarities and their signatures due to catchment landscape characteristics. Further, by employing an easily reproducible methodology and clear metrics to weigh uncertainty, our study provides a significant step toward establishing a catchment‐scale common classification system.

Water Resources ResearchVol. 60(8)
University of Nebraska–Lincoln (US), Universidade Federal de Mato Grosso do Sul (BR), University of Arizona (US), Rice University (US), Colorado State University (US)
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Ministério da Ciência, Tecnologia e Inovação, Conselho Nacional de Desenvolvimento Científico e Tecnológico, Fundação de Apoio ao Desenvolvimento do Ensino, Ciência e Tecnologia do Estado de Mato Grosso do Sul
Clean water and sanitation
Openalex Percentile: Top 8%
Hydrology and Watershed Management Studies
3.23
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