Comparison of satellite-based and reanalysis precipitation products for hydrological modeling over a data-scarce region

Jahanshahi, Afshin; Roshun, Sayed Hussein; Booij, Martijn J.

doi:10.1007/s00382-023-07078-x

Cited by 4 publications

(1 citation statement)

References 90 publications

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“…In accordance with the categorization provided by Moriasi et al (2007) [79], all datasets, except ERA5-Land, fell into the satisfactory category. The results of this study, indicating that ERA5-Land exhibits poorer performance in simulating runoff compared to PERSIANN-CDR, are in contrast to the findings of Jahanshahi et al (2024) [80]. Also, comparing the simulated runoff results of the two precipitation datasets, PERSIANN-CDR and APHRODITE in this study revealed the superiority of PERSIANN-CDR.…”

Section: Daily Results Evaluationcontrasting

confidence: 80%

Evaluation of Climatological Precipitation Datasets and Their Hydrological Application in the Hablehroud Watershed, Iran

Salehi,

Gharechelou,

Golian

et al. 2024

Water

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Hydrological modeling is essential for runoff simulations in line with climate studies, especially in remote areas with data scarcity. Advancements in climatic precipitation datasets have improved the accuracy of hydrological modeling. This research aims to evaluate the APHRODITE, PERSIANN-CDR, and ERA5-Land climatic precipitation datasets for the Hablehroud watershed in Iran. The datasets were compared with interpolated ground station precipitation data using the inverse distance weighted (IDW) method. The variable infiltration capacity (VIC) model was utilized to simulate runoff from 1992 to 1996. The results revealed that the APHRODITE and PERSIANN-CDR datasets demonstrated the highest and lowest accuracy, respectively. The sensitivity of the model was analyzed using each precipitation dataset, and model calibration was performed using the Kling–Gupta efficiency (KGE). The evaluation of daily runoff simulation based on observed precipitation indicated a KGE value of 0.78 and 0.76 during the calibration and validation periods, respectively. The KGE values at the daily time scale were 0.64 and 0.77 for PERSIANN-CDR data, 0.62 and 0.75 for APHRODITE precipitation data, 0.50 and 0.66 for ERA5-Land precipitation data during the calibration and validation periods, respectively. These results indicate that despite varying sensitivity, climatic precipitation datasets present satisfactory performance, particularly in poorly gauged basins with infrequent historical datasets.

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Section: Daily Results Evaluationcontrasting

confidence: 80%

Evaluation of Climatological Precipitation Datasets and Their Hydrological Application in the Hablehroud Watershed, Iran

Salehi,

Gharechelou,

Golian

et al. 2024

Water

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Evaluating hydrological responses of satellite precipitation products over an Indian tropical catchment through a distributed physical model

Kalura,

Pandey,

Chowdary

et al. 2024

Hydrological Processes

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Significant advancements in satellite‐based precipitation retrieval algorithms have led to the development of continuous, quasi‐global precipitation products, offering unique opportunities for hydrometeorological and climate research. In this context, six satellite‐based precipitation products (SPPs), including CHIRPS, CMORPH, GSMaP, IMERG, MSWEP, and PERSIANN, were thoroughly investigated for their application in hydrological simulations over the Wardha River basin in India. The observed gridded precipitation product developed by India Meteorological Department (IMD) has been used as reference data to evaluate the performance of SPPs. Hydrological variables such as runoff, soil moisture (SM) and evapotranspiration (ET) were simulated using the Variable Infiltration Capacity model. The performances of SPPs are critically assessed using various statistical metrics, including Pearson's correlation coefficient (R), Klinga‐Gupta Efficiency (KGE), Percent Bias (PBIAS), root mean square error (RMSE), and the RMSE to standard deviation ratio (RSR). The model‐simulated discharge was compared with streamflow observations at a single gauging site, while a spatially distributed comparison was conducted between simulated SM and ET and satellite‐based SM and ET. The IMD dataset consistently shows superior performance for discharge simulation at both daily and monthly scales, with KGE values of 0.85 and 0.91, respectively. Among SPPs, MSWEP and CHIRPS excel in simulating daily and monthly discharge, respectively. For ET simulation, CHIRPS outperforms IMD and other SPPs, achieving an overall KGE value of 0.37. In contrast, PERSIANN is the most effective for simulating SM compared to other precipitation products.

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Quantile mapping technique for enhancing satellite-derived precipitation data in hydrological modelling: a case study of the Lam River Basin, Vietnam

Nguyen,

Anh,

Nguyen

et al. 2024

Journal of Hydroinformatics

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Accurate precipitation is crucial for hydrological modelling, especially in sparse gauge regions like the Lam River Basin (LRB) in Vietnam. Gridded precipitation data sets derived from satellite and numerical models offer significant advantages in such areas. However, satellite precipitation estimates (SPEs) are subject to uncertainties, especially in high variable of topography and precipitation. This study focuses on enhancing the accuracy of Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG), Climate Prediction Center morphing technique (CMORPH) using the Quantile Mapping (QM) technique, aligning the cumulative distribution functions of the observed precipitation data with those of the SPEs, and assessing the impact on hydrological predictions. The study highlights that the post-correction IMERG precipitation using QM performs better than other data sets, enhancing the hydrological model's performance for the LRB at different temporal scales. Nash–Sutcliffe efficiency values increased from 0.60 to 0.77, surpassing the original IMERG's 0.52 to 0.74, and correlation coefficients improved from 0.79 to 0.89 (compared with the previous 0.75–0.86) for hydrological modelling. Additionally,Per cent Bias (PBIAS) decreased from approximately −1.66 to −2.21% (contrasting with the initial −20.22 and 4.6%) with corrected SPEs. These findings have implications for water resource management and disaster risk reduction initiatives in Vietnam and other countries.

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Comparison of satellite-based and reanalysis precipitation products for hydrological modeling over a data-scarce region

Cited by 4 publications

References 90 publications

Evaluation of Climatological Precipitation Datasets and Their Hydrological Application in the Hablehroud Watershed, Iran

Evaluation of Climatological Precipitation Datasets and Their Hydrological Application in the Hablehroud Watershed, Iran

Evaluating hydrological responses of satellite precipitation products over an Indian tropical catchment through a distributed physical model

Quantile mapping technique for enhancing satellite-derived precipitation data in hydrological modelling: a case study of the Lam River Basin, Vietnam

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