RETRACTED ARTICLE: Evaluating applicability of multi-source precipitation datasets for runoff simulation of small watersheds: a case study in the United States

Abstract

Small watersheds are ideal objects for studying the evolution of hydrological and water resources at small scales. Whether precipitation products can meet the runoff simulation of small watersheds is the main purpose of this study. With NOAA-CPC-US precipitation as a reference, in nine small watersheds of the United States, accuracy of the precipitation products such as PERSIANN, PERSIANN-CDR, TRMM-3B42V7, GPM-IMERG, StageIV, and ERA5 is analyzed. By driving the CREST hydrological model using these datasets, the runoff simulation effects were evaluated. Result shows the precipitation products match the NOAA-CPC-US from high to low in the order of StageIV, PERSIANN-CDR, GPM-IMERG, PERSIANN, ERA5, and finally TRMM-3B42 V7. These datasets have relatively low accuracy in the northern high latitude area and the western mountains, while accuracy is better in the central, southern, and eastern parts of the United States. In the runoff simulation effectiveness evaluation, the daily runoff of watersheds is simulated during the same verification period. The results show that: NOAA-CPC-US and StageIV have good simulation effect in small watersheds. In the northern and western United States, the PERSIANN, PERSIANN-CDR, GPM-IMERG, and ERA5 for runoff simulation should be used with caution. TRMM-3B42V7 is not suitable for runoff simulation in small watershed.

Evaluation of IMERG and ERA5 precipitation products over the Mongolian Plateau

“…Tang et al concluded that IMERG generally outperformed ERA5 across China, and can better reproduce precipitation diurnal cycles 55 . Other studies were presented in Central Asia 56 , India 57 , Turkey 47 , Iran 58 , and the United States 59 . Most studies have shown that IMERG outperforms ERA5, but the superiority of each dataset varies by regions, precipitation intensity, and altitude.…”

Spatiotemporal Evaluation and Estimation of Precipitation of Multi-Source Precipitation Products in Arid Areas of Northwest China—A Case Study of Tianshan Mountains

“…The spatial distribution of precipitation and inter-annual variation coefficient in the measured years (Figures 8a and 9a), dry season (Figures 8e and 9e), and wet season (Figures 8i and 9i) in the Tianshan Mountains, as well as the annual (Figure 8b-d), dry season (Figure 8f-h) and wet season (Figure 8j-l) precipitation distributions and corresponding precipitation differentiation patterns (Figure 9b-d,f-h,j-l) of the three products were obtained. From the perspective of the spatial distribution of annual precipitation, the three precipitation products can roughly reflect the spatial distribution characteristics of measured precipitation, that is, the decreasing trend from northwest to southeast, indicating that satellite products can roughly reflect the spatial differences of precipitation in mountainous areas caused by air flow and topographic changes [37,38]. Here, we integrated the quantity classification in the legend of Figure 8 and the precipitation range of different products, compared the spatial distribution map of different products with the interpolation map of measured precipitation, and roughly obtained the order of magnitude range of differences between products and measured precipitation.…”

“…Several studies have shown that the characterization ability of MSWEP to retrieve surface precipitation is often higher than that of TRMM, CMORPH, GPM, and other global precipitation data [34,35]. When precipitation datasets are used as inputs to hydrological simulations [36,37], uncertainties in satellite products may propagate to hydrological variables (such as runoff) [38,39]. Therefore, it is increasingly necessary to evaluate the performance of different source precipitation datasets [40,41] and their impact on hydrological research, selecting suitable precipitation products according to the study area.…”