Abstract
This study aimed to statistically and hydrologically assess the performance of the four latest and widely used satellite–gauge combined precipitation estimates (SGPEs), namely CRT (CMORPH CRT), BLD (CMORPH BLD), CDR (PERSIANN CDR), 3B42 (TMPA 3B42 version 7) over the upper yellow river basins (UYRB) in china during 2001–2012 time period. The performances of the SGPEs were compared with the Chinese Meteorological Administration (CMA) datasets using the hydrologic model called Variable Infiltration Capacity (VIC) which is known as a land surface hydrologic model. Results indicated that irrespective of the slight underestimation in the western mountains and overestimation in the southeast, the four SGPEs could generally captured the spatial distribution of precipitation well. Although 3B42 exhibited a better performance in capturing the spatial distribution of daily average precipitation, BLD agreed best with CMA in the time series of watershed average precipitation, which resulted in BLD having a comparable performance to the CMA in the long-term hydrological simulations. Moreover, the potential for disastrous heavy rain mainly occurs in southeastern corner of the basin, and CRT and BLD comparisons showed to be closer to the CMA in the distribution of extreme precipitation events while 3B42 and CDR overestimated the extreme precipitation especially over the southeast of UYRB region. Therefore, CRT and BLD were able to match the high peak discharges very well for the wet seasons, while 3B42 and CDR overrated the high peak discharges. In addition, the four SGPEs performed well for the 2005 flood event but exhibited poorly when tested for the 2012 flood event. Results indicate that the application of the four SGPEs should be used with caution in simulating massive flood events over UYRB region.
Highlights
Floods are among the most frequently occurring and disastrous natural hazards worldwide and have caused tremendous loss of life and property over the past decades [1]
We evaluated the applicability of the four satellite–gauge combined precipitation estimates (SGPEs) based on Chinese Meteorological Administration (CMA) over the study region
A large amount of precipitation concentrated upon the southeastern region of the upper yellow river basins (UYRB) and the spatial vReamroiatebSielnitsy. 20a1n7a, 9ly, 1s1i7s6revealed that the low-altitude regions of the basin are characterized by hi7gohf e19r spatial variability of precipitation in comparison with the high mountainous regions partly due to the tahbeunadbaunntdmanotismtuoreisstuupreplsyubpypltyhebIyndthiaenISnudmiamneSruMmomnseoroMn fornosmoothnefBroamy otfhBeenBgaayl aonf dBtehnegoalroagnrdapthhiec oenrohgarnacpehmicenent ehfafneccteminetnhteewffeesctteirnntphaerwt. estern part
Summary
Floods are among the most frequently occurring and disastrous natural hazards worldwide and have caused tremendous loss of life and property over the past decades [1]. Hydrologic models have become important tools for understanding hydrological processes, for forecasting and monitoring flood hydrograph. In spite of synthetic streamflow generated by distributed hydrologic models being a response to a highly complex and non-linear process, gridded precipitation is a critical input for distributed hydrologic models. The gridded precipitation that drives the hydrological model is mainly generated by interpolating ground observations (rain gauge and weather radar networks). Techniques for making precipitation observations from ground-based measurement networks have limitations in hydrologic modeling because of the large spatial nonuniformity and temporal unavailability in rainfall fields inherently. With the significant increase in spatial coverage with high spatial and temporal resolutions, satellite-based precipitation estimates (SPEs) are critical and valuable resources in acquiring reliable hydrologic data, for the regions without ground observation networks
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