Rafael Cavalcanti | Universidade Federal do Rio Grande do Sul (original) (raw)

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Papers by Rafael Cavalcanti

Research paper thumbnail of Definition of water quality variability parameters and dynamics to improve management in a deep canyon type subtropical hydroelectric reservoir

RBRH

Spatial and temporal variability patterns of water quality were evaluated through monthly collect... more Spatial and temporal variability patterns of water quality were evaluated through monthly collection of water samples (surface, sub-surface and bottom) from 2005 to 2012. Principal Component Analysis was used to define the relative importance of each variable and Anova (two way) to analyze the significance of differences in water quality in the longitudinal axis of the reservoir. The variables: turbidity, Secchi transparency, residence time and temperature have greater importance on water quality. It was observed spatial and temporal gradients, related to the circulation, sedimentation and resuspension processes, and the influence of low flow, high residence time and winter mixing of water column on the cycling of solids and nutrients may explain the variation in these processes. The use of multivariate statistical analysis methods provided important information to understand these processes, it helps the interpretation of complex data to improve monitoring, and use of information t...

Research paper thumbnail of Assessing the large-scale variation of heat budget in poorly gauged watershed-shallow lake system using a novel integrated modeling approach

Journal of Hydrology, 2019

Assessment of large-scale temperature dynamics and heat fluxes in shallow lakes requires comprehe... more Assessment of large-scale temperature dynamics and heat fluxes in shallow lakes requires comprehensive modeling capabilities to simulate water interactions, the processes related to the heat budget, and their driving forces. In this study, we investigated the spatial and temporal variations in water-surface temperature (WST) and surface heat fluxes for the period between January 2001 and December 2010 in Lake Mirim, a large (surface area ca. 4,000 km 2) shallow lake on the Brazil-Uruguay border. The aquatic ecosystem was examined using in-situ WST measurements, MODIS land surface temperature (M*D11A1 LST) products, and a coupling between a large-scale hydrologic model (MGB-IPH) and a hydrodynamic/water quality model (IPH-ECO). The WST values estimated by the hydrodynamic model were consistent with measured in-situ data and MODIS-derived WST, using both daytime and nighttime time series (R 2 = 0.88; Bias = 1.45 °C; RMSE = 2.16 °C; ENS = 0.77). Our findings also revealed that the dominant heat fluxes in the lake are the atmospheric longwave radiation (annual mean = 303.38 W m-2), water longwave radiation (annual mean = 336.01 W m-2), and the latent heat flux (annual mean = 51.14 W m-2). Additionally, the heat flux from the river inflows contribute minimally to the overall seasonal heat budget in the lake, being the Cebollati river the main contributor (annual average = 4.63 W m-2). Coupled large-scale hydrological and hydrodynamic models will benefit future modeling efforts by providing an 2 effective management tool to study the effect of case scenarios (e.g., climate change) on temperature dynamics, heat fluxes, and physical and ecological processes in these ecosystems.

Research paper thumbnail of Coupling large-scale hydrological and hydrodynamic modeling: Toward a better comprehension of watershed-shallow lake processes

Journal of Hydrology, 2018

Highlights  Coupling large-scale hydrological and hydrodynamic modeling for full representation.... more Highlights  Coupling large-scale hydrological and hydrodynamic modeling for full representation.  The lake-watershed behavior, basin responses and human activities were evaluated.  External forcing cause strong variations on the hydrodynamic patterns in the lake.  Proposed approach reduces the dependency of observation data for discharge boundaries.  First coupling between MGB-IPH and IPH-ECO models.

Research paper thumbnail of Process-based modeling of shallow lake metabolism: Spatio-temporal variability and relative importance of individual processes

Ecological Modelling, 2016

A process-based model was used to evaluate distributed estimates of aquatic metabolism and the im... more A process-based model was used to evaluate distributed estimates of aquatic metabolism and the importance of different individual processes related to dissolved-oxygen dynamics in a large shallow subtropical lake, Lake Mangueira, on the southern coast of Brazil. In order to assess spatial differences in metabolism estimates, the lake was divided into three geographical areas (North, Central, and South) and each area was subdivided into two biological zones (littoral and pelagic). A well-marked littoral to pelagic gradient was observed, with significant differences in the metabolism estimates between the biological zones of each compartment. In addition, a significant longitudinal difference in metabolism between the North and other lake areas was also apparent. Temporal dynamics featured continuous switching between net autotrophic and net heterotrophic conditions. Phytoplankton primary production and respiration were the main individual processes controlling gross primary production and ecosystem respiration, respectively, for the entire lake. Our findings indicated that spatially distributed estimates of lake metabolism led to different conclusions than did overall metabolism estimates based on single points. Also, individual processes must be taken into account in order to fully understand their relative importance on different spatial and temporal scales for the overall metabolism of aquatic ecosystems.

Research paper thumbnail of Can chlorophyll-a in meso-oligotrophic shallow waters be estimated using statistical approaches and empirical models from MODIS imagery?

RBRH, 2018

Accurate estimation of chlorophyll-a (Chl-a) concentration in inland waters through remote-sensin... more Accurate estimation of chlorophyll-a (Chl-a) concentration in inland waters through remote-sensing techniques is complicated by local differences in the optical properties of water. In this study, we applied multiple linear regression (MLR), artificial neural network (ANN), nonparametric multiplicative regression (NPMR) and four models (Appel, Kahru, FAI and O14a) to estimate the Chl -a concentration from combinations of spectral bands from the MODIS sensor. The MLR, NPMR and ANN models were calibrated and validated using in-situ Chl -a measurements. The results showed that a simple and efficient model, developed and validated through multiple linear regression analysis, offered advantages (i.e., better performance and fewer input variables) in comparison with ANN, NPMR and four models (Appel, Kahru, FAI and O14a). In addition, we observed that in a large shallow subtropical lake, where the wind and hydrodynamics are essential factors in the spatial heterogeneity (Chl-a distribution...

Research paper thumbnail of Definition of water quality variability parameters and dynamics to improve management in a deep canyon type subtropical hydroelectric reservoir

RBRH

Spatial and temporal variability patterns of water quality were evaluated through monthly collect... more Spatial and temporal variability patterns of water quality were evaluated through monthly collection of water samples (surface, sub-surface and bottom) from 2005 to 2012. Principal Component Analysis was used to define the relative importance of each variable and Anova (two way) to analyze the significance of differences in water quality in the longitudinal axis of the reservoir. The variables: turbidity, Secchi transparency, residence time and temperature have greater importance on water quality. It was observed spatial and temporal gradients, related to the circulation, sedimentation and resuspension processes, and the influence of low flow, high residence time and winter mixing of water column on the cycling of solids and nutrients may explain the variation in these processes. The use of multivariate statistical analysis methods provided important information to understand these processes, it helps the interpretation of complex data to improve monitoring, and use of information t...

Research paper thumbnail of Assessing the large-scale variation of heat budget in poorly gauged watershed-shallow lake system using a novel integrated modeling approach

Journal of Hydrology, 2019

Assessment of large-scale temperature dynamics and heat fluxes in shallow lakes requires comprehe... more Assessment of large-scale temperature dynamics and heat fluxes in shallow lakes requires comprehensive modeling capabilities to simulate water interactions, the processes related to the heat budget, and their driving forces. In this study, we investigated the spatial and temporal variations in water-surface temperature (WST) and surface heat fluxes for the period between January 2001 and December 2010 in Lake Mirim, a large (surface area ca. 4,000 km 2) shallow lake on the Brazil-Uruguay border. The aquatic ecosystem was examined using in-situ WST measurements, MODIS land surface temperature (M*D11A1 LST) products, and a coupling between a large-scale hydrologic model (MGB-IPH) and a hydrodynamic/water quality model (IPH-ECO). The WST values estimated by the hydrodynamic model were consistent with measured in-situ data and MODIS-derived WST, using both daytime and nighttime time series (R 2 = 0.88; Bias = 1.45 °C; RMSE = 2.16 °C; ENS = 0.77). Our findings also revealed that the dominant heat fluxes in the lake are the atmospheric longwave radiation (annual mean = 303.38 W m-2), water longwave radiation (annual mean = 336.01 W m-2), and the latent heat flux (annual mean = 51.14 W m-2). Additionally, the heat flux from the river inflows contribute minimally to the overall seasonal heat budget in the lake, being the Cebollati river the main contributor (annual average = 4.63 W m-2). Coupled large-scale hydrological and hydrodynamic models will benefit future modeling efforts by providing an 2 effective management tool to study the effect of case scenarios (e.g., climate change) on temperature dynamics, heat fluxes, and physical and ecological processes in these ecosystems.

Research paper thumbnail of Coupling large-scale hydrological and hydrodynamic modeling: Toward a better comprehension of watershed-shallow lake processes

Journal of Hydrology, 2018

Highlights  Coupling large-scale hydrological and hydrodynamic modeling for full representation.... more Highlights  Coupling large-scale hydrological and hydrodynamic modeling for full representation.  The lake-watershed behavior, basin responses and human activities were evaluated.  External forcing cause strong variations on the hydrodynamic patterns in the lake.  Proposed approach reduces the dependency of observation data for discharge boundaries.  First coupling between MGB-IPH and IPH-ECO models.

Research paper thumbnail of Process-based modeling of shallow lake metabolism: Spatio-temporal variability and relative importance of individual processes

Ecological Modelling, 2016

A process-based model was used to evaluate distributed estimates of aquatic metabolism and the im... more A process-based model was used to evaluate distributed estimates of aquatic metabolism and the importance of different individual processes related to dissolved-oxygen dynamics in a large shallow subtropical lake, Lake Mangueira, on the southern coast of Brazil. In order to assess spatial differences in metabolism estimates, the lake was divided into three geographical areas (North, Central, and South) and each area was subdivided into two biological zones (littoral and pelagic). A well-marked littoral to pelagic gradient was observed, with significant differences in the metabolism estimates between the biological zones of each compartment. In addition, a significant longitudinal difference in metabolism between the North and other lake areas was also apparent. Temporal dynamics featured continuous switching between net autotrophic and net heterotrophic conditions. Phytoplankton primary production and respiration were the main individual processes controlling gross primary production and ecosystem respiration, respectively, for the entire lake. Our findings indicated that spatially distributed estimates of lake metabolism led to different conclusions than did overall metabolism estimates based on single points. Also, individual processes must be taken into account in order to fully understand their relative importance on different spatial and temporal scales for the overall metabolism of aquatic ecosystems.

Research paper thumbnail of Can chlorophyll-a in meso-oligotrophic shallow waters be estimated using statistical approaches and empirical models from MODIS imagery?

RBRH, 2018

Accurate estimation of chlorophyll-a (Chl-a) concentration in inland waters through remote-sensin... more Accurate estimation of chlorophyll-a (Chl-a) concentration in inland waters through remote-sensing techniques is complicated by local differences in the optical properties of water. In this study, we applied multiple linear regression (MLR), artificial neural network (ANN), nonparametric multiplicative regression (NPMR) and four models (Appel, Kahru, FAI and O14a) to estimate the Chl -a concentration from combinations of spectral bands from the MODIS sensor. The MLR, NPMR and ANN models were calibrated and validated using in-situ Chl -a measurements. The results showed that a simple and efficient model, developed and validated through multiple linear regression analysis, offered advantages (i.e., better performance and fewer input variables) in comparison with ANN, NPMR and four models (Appel, Kahru, FAI and O14a). In addition, we observed that in a large shallow subtropical lake, where the wind and hydrodynamics are essential factors in the spatial heterogeneity (Chl-a distribution...