Performance evaluation of satellite-based rainfall products on hydrological modeling for a transboundary catchment in northwest Africa

Guermazi, Emna; Milano, Marianne; Reynard, Emmanuel

doi:10.1007/s00704-019-02928-3

Cited by 10 publications

(3 citation statements)

References 63 publications

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“…Better correlation of SREs with observed rainfall was observed at monthly than at annual timescales for all products. This is consistent with studies that reported the performance of SREs improved with increased time aggregation that peaks at monthly timescale (Dembélé and Zwart, 2016;Katsanos et al, 2016;Zhao et al, 2017;Ayehu et al, 2018;Li et al, 2018;Guermazi et al, 2019). The weak agreement of SREs with observed data at annual timescale shows that the SREs considered in this study generally did not capture the interannual rainfall variability.…”

Section: Discussionsupporting

confidence: 89%

Performance evaluation of multiple satellite rainfall products for Dhidhessa River Basin (DRB), Ethiopia

Wedajo¹,

Muleta²,

Gessesse³

2020

Preprint

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Abstract. Precipitation is a crucial driver of hydrological processes. Ironically, reliable characterization of its spatiotemporal variability is challenging. Ground-based rainfall measurements using rain gauges can be more accurate. However, installing a dense gauging network to capture rainfall variability can be impractical. Satellite-based rainfall estimates (SREs) can be good alternatives, especially for data-scarce basins like in Ethiopia. However, SREs rainfall is plagued with uncertainties arising from many sources. The objective of this study was to evaluate the performance of the latest versions of several SREs products (i.e., CHIRPS2, IMERG6, TAMSAT3, and 3B42/3) for the Dhidhessa River Basin (DRB). Both statistical and hydrologic modelling approaches were used for performance evaluation. The Soil and Water Analysis Tool (SWAT) was used for hydrological simulations. The results showed that whereas all four SREs products are promising to estimate and detect rainfall for the DRB, the CHIRPS2 dataset performed the best at annual, seasonal, and monthly timescales. The hydrologic simulation-based evaluation showed that SWAT's calibration results are sensitive to the rainfall dataset. The hydrologic response of the basin is found to be dominated by the subsurface processes, primarily by the groundwater flux. Overall, the study showed that both CHIRPS2 and IMERG6 products can be reliable rainfall data sources for hydrologic analysis of the Dhidhessa River Basin.

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Section: Discussionsupporting

confidence: 89%

Performance evaluation of multiple satellite rainfall products for Dhidhessa River Basin (DRB), Ethiopia

Wedajo¹,

Muleta²,

Gessesse³

2020

Preprint

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“…The SWAT model is a catchment scale model, which is developed by the United States Department of Agriculture-Agricultural Research Services (USDA-ARS) to predict the water, sediment, and pollutant loads in large catchments. The SWAT model finds extensive application in hydrological modeling in transboundary, ungauged, small, and large basins (Gitau & Chaubey 2010;Zhang et al 2012;Sisay et al 2017;Guermazi et al 2019). The SWAT model divides the subbasins into several hydrologic response units (HRUs) based on the unique combination of soil, land use, and topographies.…”

Section: Swat Model Setup and Simulationmentioning

confidence: 99%

Comparison of flow simulations with sub-daily and daily GPM IMERG products over a transboundary Chenab River catchment

Ahmed

Janabi

Yang

et al. 2022

Journal of Water and Climate Change

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This study proposes the assessment of SWAT model simulations, with the provision of satellite precipitation products (SPPs), in a transboundary/large catchment. Three latest sub-daily/half-hourly (HH) and daily (D) SPPs, i.e., ‘IMERG-E’, ‘IMERG-L’, and ‘IMERG-F’, were evaluated for daily and monthly flow simulations. The study revealed that monthly flow simulation performance is better than daily flow simulation in all sub-daily and daily SPPs-based models. Results depict that IMERG-HHF and IMERG-DF yield the best performance among the other latency levels of SPPs. The IMERG-HHF model has a reasonably higher daily correlation coefficient (R) and lower daily root-mean-square error (RMSE) than IMERG-DF. IMERG-HHF displays the lowest percent bias (PBIAS) values of 15.4 and 2.4 for daily and monthly flow validation, respectively. It also represents relatively higher values of coefficient of determination (R2) and Nash–Sutcliffe Efficiency (NSE) than any other model, i.e., R2=0.66 and NSE=0.63 for daily model validation and R2=0.84 and NSE=0.82 for monthly model validation. Moreover, the sub-daily IMERG model outperformed the daily IMERG model for all calibration and validation scenarios. The IMERG-DL model demonstrates poor performance in all of the SPPs, in daily and monthly validation, with low R2 (0.63 (dval) and 0.81 (mval)), low NSE (0.50 (dval) and 0.67 (mval)), and high PBIAS (31 (dval) and 26.6 (mval)). Additionally, the IMERG-HHE model outperformed IMERG-HHL.

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“…Spatiotemporal rainfall information is critical in understanding the complex interactions and processes among hydrologic systems, ranging from catchment to a global scale (Gottschalck et al , 2005). The ongoing increase in water demand because of socio-economic activities, as well as global climate change, are expected to have a significant impact on water resource availability (Dakhlaoui et al , 2017; Nauditt et al , 2017; Guermazi et al , 2019).…”

Section: Introductionmentioning

confidence: 99%

Performance evaluation of satellite-based rainfall estimates for hydrological modeling over Bilate river basin, Ethiopia

Ibrahim

Molla

Lohani

2022

WJE

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Purpose The purpose of this study is to address a highly heterogeneous rift margin environment and exhibit considerable spatiotemporal hydro-climatic variations. In spite of limited, random and inaccurate data retrieved from rainfall gauging stations, the recent advancement of satellite rainfall estimate (SRE) has provided promising alternatives over such remote areas. The aim of this research is to take advantage of the technologies through performance evaluation of the SREs against ground-based-gauge rainfall data sets by incorporating its applicability in calibrating hydrological models. Design/methodology/approach Selected multi satellite-based rainfall estimates were primarily compared statistically with rain gauge observations using a point-to-pixel approach at different time scales (daily and seasonal). The continuous and categorical indices are used to evaluate the performance of SRE. The simple scaling time-variant bias correction method was further applied to remove the systematic error in satellite rainfall estimates before being used as input for a semi-distributed hydrologic engineering center's hydraulic modeling system (HEC-HMS). Runoff calibration and validation were conducted for consecutive periods ranging from 1999–2010 to 2011–2015, respectively. Findings The spatial patterns retrieved from climate hazards group infrared precipitation with stations (CHIRPS), multi-source weighted-ensemble precipitation (MSWEP) and tropical rainfall measuring mission (TRMM) rainfall estimates are more or less comparably underestimate the ground-based gauge observation at daily and seasonal scales. In comparison to the others, MSWEP has the best probability of detection followed by TRMM at all observation stations whereas CHIRPS performs the least in the study area. Accordingly, the relative calibration performance of the hydrological model (HEC-HMS) using ground-based gauge observation (Nash and Sutcliffe efficiency criteria [NSE] = 0.71; R2 = 0.72) is better as compared to MSWEP (NSE = 0.69; R2 = 0.7), TRMM (NSE = 0.67, R2 = 0.68) and CHIRPS (NSE = 0.58 and R2 = 0.62). Practical implications Calibration of hydrological model using the satellite rainfall estimate products have promising results. The results also suggest that products can be a potential alternative source of data sparse complex rift margin having heterogeneous characteristics for various water resource related applications in the study area. Originality/value This research is an original work that focuses on all three satellite rainfall estimates forced simulations displaying substantially improved performance after bias correction and recalibration.

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Performance evaluation of satellite-based rainfall products on hydrological modeling for a transboundary catchment in northwest Africa

Cited by 10 publications

References 63 publications

Performance evaluation of multiple satellite rainfall products for Dhidhessa River Basin (DRB), Ethiopia

Performance evaluation of multiple satellite rainfall products for Dhidhessa River Basin (DRB), Ethiopia

Comparison of flow simulations with sub-daily and daily GPM IMERG products over a transboundary Chenab River catchment

Performance evaluation of satellite-based rainfall estimates for hydrological modeling over Bilate river basin, Ethiopia

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