Hydrological Evaluation of Satellite-Based Precipitation Products in Hunan Province

Yan, Yan; Wang, Guihua; Nanding, Nergui; Chen, Weitian

doi:10.3390/rs14133127

Cited by 3 publications

(1 citation statement)

References 57 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Such evaluation studies can provide important knowledge for the subsequent development of next-generation satellite precipitation products for better hydrometeorological applications. GPM IMERG products have been widely evaluated by various researchers with different evaluation indicators and statistical methods [19][20][21][22]. However, previous studies are mostly reported for different geographical regions.…”

Section: Introductionmentioning

confidence: 99%

Evaluation and Applicability Analysis of GPM Satellite Precipitation over Mainland China

Pan

Chen³

et al. 2023

Remote Sensing

Self Cite

View full text Add to dashboard Cite

This study aims to systematically evaluate the accuracy and applicability of GPM satellite precipitation products (IMERG-E, IMERG-L, and IMERG-F) with varying time lags at different spatial and temporal scales over mainland China. We use quantitative statistical indicators, including correlation coefficient (CC), root mean square error (RMSE), mean absolute error (MAE), mean daily precipitation, probability of detection (POD), false alarm rate (FAR), bias, and equitable threat score (ETS), based on observations from 2419 national gauge sites. The results show that GPM satellite precipitation products perform well in eastern and southern humid regions of China, with relatively poorer performance in western and northern regions in terms of spatial distribution. It reflects the sensitivity of GPM precipitation retrieval algorithm to climate and precipitation type, topography, density, and quality of ground observation across different latitudes. Despite the design of GPM for different forms of precipitation, IMERG products perform the best in summer and the worst in winter, indicating that estimating snowfalls via satellite is still challenging. In terms of precipitation intensity, IMERG products significantly improve performance for light and no rain (POD ≥ 0.7), but errors gradually increase for moderate, heavy, and torrential rain, due to the saturation tendency of satellite echoes. Overall, we comprehensively evaluate the IMERG products, revealing the distinct characteristics at various spatial–temporal scales focusing on rainfall accumulations over mainland China. This study provides an important reference for other similar satellite-based precipitation products. It also helps the parameter optimization of hydrological modelling, especially under extreme precipitation conditions, to enhance the accuracy of flood simulation.

show abstract

Section: Introductionmentioning

confidence: 99%

Evaluation and Applicability Analysis of GPM Satellite Precipitation over Mainland China

Pan

Chen³

et al. 2023

Remote Sensing

Self Cite

View full text Add to dashboard Cite

show abstract

Remote Sensing Data and Indices to Support Water Management: A Holistic Post-mining Approach for Lignite Mining in Greece

Louloudis,

Roumpos,

Mertiri

et al. 2023

Mine Water Environ

View full text Add to dashboard Cite

Product- and Hydro-Validation of Satellite-Based Precipitation Data Sets for a Poorly Gauged Snow-Fed Basin in Turkey

Uysal

2022

Water

View full text Add to dashboard Cite

Satellite-based Precipitation (SBP) products are receiving growing attention, and their utilization in hydrological applications is essential for better water resource management. However, their assessment is still lacking for data-sparse mountainous regions. This study reveals the performances of four available PERSIANN family products of low resolution near real-time (PERSIANN), low resolution bias-corrected (PERSIANN-CDR), and high resolution real-time (PERSIANN-CCS and PERSIANN-PDIR-Now). The study aims to apply Product-Validation Experiments (PVEs) and Hydro-Validation Experiments (HVEs) in a mountainous test catchment of the upper Euphrates Basin. The PVEs are conducted on different temporal scales (annual, monthly, and daily) within four seasonal time periods from 2003 to 2015. HVEs are accomplished via a multi-layer perceptron (MLP)-based rainfall-runoff model. The Gauge-based Precipitation (GBP) and SBP are trained and tested to simulate daily streamflows for the periods of 2003–2008 and 2009–2011 water years, respectively. PVEs indicate that PERSIANN-PDIR-Now comprises the least mean annual bias, and PERSIANN-CDR gives the highest monthly correlation with the GBP data. According to daily HVEs, MLP provides a compromising alternative for biased data sets; all SBP models show reasonably high Nash–Sutcliffe Efficiency for the training (above 0.80) and testing (0.62) periods, while the PERSIANN-CDR-based MLP (0.88 and 0.79) gives the highest performance.

show abstract

Hydrological Evaluation of Satellite-Based Precipitation Products in Hunan Province

Cited by 3 publications

References 57 publications

Evaluation and Applicability Analysis of GPM Satellite Precipitation over Mainland China

Evaluation and Applicability Analysis of GPM Satellite Precipitation over Mainland China

Remote Sensing Data and Indices to Support Water Management: A Holistic Post-mining Approach for Lignite Mining in Greece

Product- and Hydro-Validation of Satellite-Based Precipitation Data Sets for a Poorly Gauged Snow-Fed Basin in Turkey

Contact Info

Product

Resources

About