@article{GadelhaCoelhoXavieretal.2018,
  author    = {Gad{\^e}lha, Andr{\´e} N. and Coelho, Victor Hugo R. and Xavier, Alexandre C. and Barbosa, Lu{\´i}s Romero and Melo, Davi C. D. and Xuan, Yunqing and Huffman, George J. and Petersen, Walt A. and Almeida, Cristiano das Neves},
  title     = {Grid box-level evaluation of IMERG over Brazil at various space and time scales},
  series = {Atmospheric Research},
  volume    = {218},
  journal   = {Atmospheric Research},
  publisher = {Elsevier},
  address   = {New York},
  issn      = {0169-8095},
  doi       = {10.1016/j.atmosres.2018.12.001},
  pages     = {231 -- 244},
  year      = {2018},
  abstract  = {Rainfall data from the Global Precipitation Measurement (GPM) mission provide a new source of information with high spatiotemporal resolution that overcomes the limitations of ground-based rainfall information worldwide. This study evaluates the performance of the Integrated multi-satellitE Retrievals for GPM (IMERG) Final Run product over Brazil by means of multi-temporal and -spatial analyses. The assessment of the IMERG Final Run product is based on six statistics obtained for the period between January-December 2016 (daily, monthly, and annual basis). The analysis consisted of comparing the satellite-based estimates against a ground-based gridded rainfall product created using daily records from 4911 rain gauges distributed throughout Brazil. Overall, the results show that the IMERG product can effectively capture the spatial patterns of rainfall across Brazil. However, the IMERG product presents a slight tendency in overestimating the ground-based rainfall at all timescales. Furthermore, the performance of the satellite product varies throughout the region. The higher errors and biases are found in the North and Central-West regions, but the low density of rain gauges in those regions can be a source of large deviations between IMERG estimates and observations. A large underestimation of the IMERG data is evident along the coastal zone of the North-east region, probably due to the inability of the passive microwave and infrared sensors to detect warm-rain processes over land. This study shows that the IMERG product can be a good source of rainfall data to complement the ground precipitation measurements in most of Brazil, although some uncertainties are found and need to be further studied},
  language  = {en}
}
@article{BarbosaCoelhoGusmaoetal.2022,
  author    = {Barbosa, Luis Romero A. and Coelho, Victor Hugo R. and Gusmao, Ana Claudia V. L. F. and Fernandes, Lucila A. E. and da Silva, Bernardo B. and Galvao, Carlos de O. and Caicedo, Nelson O. L. and da Paz, Adriano R. and Xuan, Yunqing and Bertrand, Guillaume F. and Melo, Davi de C. D. and Montenegro, Suzana M. G. L. and Oswald, Sascha and Almeida, Cristiano das N.},
  title     = {A satellite-based approach to estimating spatially distributed groundwater recharge rates in a tropical wet sedimentary region despite cloudy conditions},
  series = {Journal of hydrology},
  volume    = {607},
  journal   = {Journal of hydrology},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0022-1694},
  doi       = {10.1016/j.jhydrol.2022.127503},
  pages     = {15},
  year      = {2022},
  abstract  = {Groundwater recharge (GWR) is one of the most challenging water fluxes to estimate, as it relies on observed data that are often limited in many developing countries. This study developed an innovative water budget method using satellite products for estimating the spatially distributed GWR at monthly and annual scales in tropical wet sedimentary regions despite cloudy conditions. The distinctive features proposed in this study include the capacity to address 1) evapotranspiration estimations in tropical wet regions frequently overlaid by substantial cloud cover; and 2) seasonal root-zone water storage estimations in sedimentary regions prone to monthly variations. The method also utilises satellite-based information of the precipitation and surface runoff. The GWR was estimated and validated for the hydrologically contrasting years 2016 and 2017 over a tropical wet sedimentary region located in North-eastern Brazil, which has substantial potential for groundwater abstraction. This study showed that applying a cloud-cleaning procedure based on monthly compositions of biophysical data enables the production of a reasonable proxy for evapotranspiration able to estimate groundwater by the water budget method. The resulting GWR rates were 219 (2016) and 302 (2017) mm yr(-1), showing good correlations (CC = 0.68 to 0.83) and slight underestimations (PBIAS =-13 to-9\%) when compared with the referenced estimates obtained by the water table fluctuation method for 23 monitoring wells. Sensitivity analysis shows that water storage changes account for +19\% to-22\% of our monthly evaluation. The satellite-based approach consistently demonstrated that the consideration of cloud-cleaned evapotranspiration and root-zone soil water storage changes are essential for a proper estimation of spatially distributed GWR in tropical wet sedimentary regions because of their weather seasonality and cloudy conditions.},
  language  = {en}
}