Hydrological modeling using remote sensing precipitation data in a Brazilian savanna basin

Junqueira, Rubens; Viola, Marcelo Ribeiro; Amorim, Jhones da Silva; Camargos, Carla; Mello, Carlos Rogério de

doi:10.1016/j.jsames.2022.103773

Cited by 9 publications

(5 citation statements)

References 37 publications

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“…Ten parameters were used in the SWAT calibration and validation with OP and CRU climatological data, selected based on previous studies in the PRB [56]. The final range and the best parameters obtained in the calibration (Table 3) agree with the result obtained by Junqueira et al [65] in the same basin using OP and observed climatological data from 2004 to 2018.…”

Section: Calibration Validation and Uncertainty Analysissupporting

confidence: 58%

“…In this study, the calibration (2004-2011) was carried out with OP of four rain gauge stations from ANA (station codes 1545006, 1445000, 1545005, and 1544032) and CRU climate data, with the warm-up period from June 2000 to December 2003. The initial parameters were selected based on previous studies in the basin [56]. It used two iterations of 600 simulations each and Nash-Sutcliffe efficiency (NSE) as the objective function.…”

Section: Calibration Validation and Uncertainty Analysismentioning

confidence: 99%

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Hydrological Retrospective and Historical Drought Analysis in a Brazilian Savanna Basin

Junqueira

Viola

Amorim

et al. 2022

Water

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Analyzing historical droughts is essential to improve the assessment of future hydrological risks and to understand the effects of climate variability on streamflow. However, prolonged and consistent hydrological time series are scarce in the Brazilian savanna region. This study aimed to analyze the performance of climate reanalysis products in precipitation estimation, hydrological modeling, and historical drought analysis in a Brazilian savanna basin. For this purpose, precipitation data from the twentieth-century atmospheric model ensemble (ERA-20CM) and the land component of the fifth generation of European ReAnalysis (ERA5-Land) with bias correction were used. The weather variables were obtained from the Climatic Research Unit (CRU) and the hydrological modeling was performed using the Soil and Water Assessment Tool (SWAT). The Standardized Streamflow Index (SSI) was used to calculate hydrological drought in the basin. Overall, ERA5-Land performed satisfactorily in precipitation estimation, mainly on the monthly time scale, hydrological modeling, and drought prediction. Since ERA-20CM showed unsatisfactory values for the performance statistics in all analyses, the hydrologic drought (1950 to 2018) was performed with ERA5-Land. The results showed both an increase in the number of dry months and a decrease in wet months in recent decades.

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Section: Calibration Validation and Uncertainty Analysissupporting

confidence: 58%

Section: Calibration Validation and Uncertainty Analysismentioning

confidence: 99%

Hydrological Retrospective and Historical Drought Analysis in a Brazilian Savanna Basin

Junqueira

Viola

Amorim

et al. 2022

Water

Self Cite

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“…However, there was a considerable underestimation of rainfall estimated by the satellite identified across the Andes and coastal mountain areas lying at 36.5 degrees south, while the performance was better for northern and valley areas [20]. For the severe event that took place from 28-31 January 2021, Junqueira et al [25] showed that a correlation of 0.73 was achieved between the gridded IMERG Final product estimates and the gauge measurements. On the other hand, Soto Alvarez et al [15] analyzed the performance of IMERG Late and Final products for four different macro zones around Chile.…”

Section: Introductionmentioning

confidence: 98%

“…However, they showed a moderate correlation performance in Iran [21]. Other studies evaluated the different IMERG products in Iran [22], Finland [10], Greece [23], South America [24], Brazil [25][26][27], Saudi Arabia [19,28,29], Indonesia [30], Ecuador [31], Pakistan [32] and Chile [15,20,33].…”

Section: Introductionmentioning

confidence: 99%

Assessment of the IMERG Early-Run Precipitation Estimates over South American Country of Chile

et al. 2023

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Accurate rainfall measurement is a challenge, especially in regions with diverse climates and complex topography. Thus, knowledge of precipitation patterns requires observational networks with a very high spatial and temporal resolution, which is very difficult to construct in remote areas with complex geological features such as desert areas and mountains, particularly in countries with high topographical variability such as Chile. This study evaluated the performance of the near-real-time Integrated Multi-satellite Retrievals for GPM (IMERG) Early product throughout Chile, a country located in South America between 16° S–66° S latitude. The accuracy of the IMERG Early was assessed at different special and temporal scales from 2015 to 2020. Relative Bias (PBIAS), Mean Absolute Error (MAE), and Root-Mean-Squared Error (RMSE) were used to quantify the errors in the satellite estimates, while the Probability of Detection (POD), False Alarm Ratio (FAR), and Critical Success Index (CSI) were used to evaluate product detection accuracy. In addition, the consistency between the satellite estimates and the ground observations was assessed using the Correlation Coefficient (CC). The spatial results show that the IMERG Early had the best performance over the central zone, while the best temporal performance was detected for the yearly precipitation dataset. In addition, as latitude increases, so do errors. Also, the satellite product tends to slightly overestimate the precipitation throughout the country. The results of this study could contribute towards the improvement of the IMERG algorithms and open research opportunities in areas with high latitudes, such as Chile.

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“…Recent products that derive rainfall intensity information from meteorological satellite observations complement the in-situ data and are beginning to be used for several purposes, including, for example, the validation and intercomparison of satellite rainfall estimates [18], the analysis of flash floods [19,20], hydrological modeling [21,22,23,24,25], downscaling of rainfall extremes [26], and the estimation of IDF curves [27,28,29,30]. Among these products is the Integrated MultisatellitE Retrievals from GPM-IMERG (or in short IMERG) produced by NASA, a quasi-global dataset (60°N -60°S), calibrated using monthly rain gauge precipitation values, which provides rainfall intensities at 0.5 h intervals, with a spatial resolution of 0.1° (approximately 11 km at the equator).…”

Section: Introductionmentioning

confidence: 99%

Evaluating the IMERG precipitation satellite product to derive intensity-duration-frequency curves in Colombia

Rodríguez

García-Echeverri

González-Ramírez

et al. 2023

Rev.Fac.Ing.Univ.Antioquia

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This article explores the potentialities of the IMERG V06B FINAL product for estimating Intensity-Duration-Frequency curves in Colombia, using the in-situ data available for 110 rain gauges. From observed data for 76 of these stations, we validated the satellite IMERG precipitation data for the period 2001-2019, at daily, monthly, and annual resolutions. For 60 stations, better results were obtained for the monthly time aggregation, followed by the yearly and daily scales, suggesting that seasonality is the main rainfall characteristic captured by the product. Concerning the occurrence of daily precipitation, results indicate that both the probability of detection and the probability of false detection are high. In general terms, the comparison between intensities from existing IDF curves and those derived from IMERG showed underestimations of the rainfall intensities for the short durations studied (0.5 and 1 h), with mean relative errors in the range [-69%,+56%], and overestimations for the large durations of 2 and 6 h, with mean relative errors in the range [-61%,+171%]. Results also suggest that the IMERG product at this moment is not able to capture the daily rainfall distribution in most of the stations. Nevertheless, for almost 20% of the rain gauges, located mainly in the Amazon, Orinoco, and Pacific Regions, the analysis showed that the maximum intensities derived from IMERG are within +/-25% relative error, compared with the ones calculated using the traditional approach.

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Hydrological modeling using remote sensing precipitation data in a Brazilian savanna basin

Cited by 9 publications

References 37 publications

Hydrological Retrospective and Historical Drought Analysis in a Brazilian Savanna Basin

Hydrological Retrospective and Historical Drought Analysis in a Brazilian Savanna Basin

Assessment of the IMERG Early-Run Precipitation Estimates over South American Country of Chile

Evaluating the IMERG precipitation satellite product to derive intensity-duration-frequency curves in Colombia

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