Assessment of Precipitation Error Propagation in Discharge Simulations over the Contiguous United States

Abstract

This study characterizes precipitation error propagation through a distributed hydrological model based on the river basins across the Contiguous United States (CONUS), to better understand the relationship between errors in precipitation inputs and simulated discharge (i.e., P-Q error relationship). The NLDAS-2 precipitation and its simulated discharge are used as the reference to compare with TMPA-3B42 V7, TMPA-3B42RT V7, StageIV, CPC-U, MERRA-2, and MSWEP-2.2 for 1,548 well gauged river basins. The relative errors in multiple conventional precipitation products and their corresponding discharges are analysed for the period of 2002-2013. The results reveal positive linear P-Q error relationships at annual and monthly timescales, and the stronger linearity for larger temporal accumulations. Precipitation errors can be doubled in simulated annual accumulated discharge. Moreover, precipitation errors are strongly dampened in basins characterized by temperate and continental climate regimes, particularly for peak discharges, showing highly nonlinear relationships. Radar-based precipitation product consistently shows dampening effects on error propagation through discharge simulations at different accumulation timescales compared to the other precipitation products. Although basin size and topography also influence the P-Q error relationship and propagation of precipitation errors, their roles depend largely on precipitation products, seasons and climate regimes.

Evaluation and Applicability Analysis of GPM Satellite Precipitation over Mainland China

“…into the fusion and calibration process can improve the accuracy of precipitation data [41,42]. Based on the accuracy assessment, IMERG precipitation products or IMERG-based correction products can also be applied in hydrological modeling fields, such as flood forecasting and runoff simulation [43].…”

A Coupled River Basin‐Urban Hydrological Model (DRIVE‐Urban) for Real‐Time Urban Flood Modeling

“…With overall good performance in depicting the complexity of river basin processes from runoff generation to river routing, the DRIVE model has been widely applied as an efficient source of flood information from global to regional and finer scales (Grimaldi et al, 2019;Huang et al, 2021;H. Wu et al, 2019;Nanding et al, 2021;Q. Wang et al, 2020;Yan et al, 2020).…”

“…By solving the kinematic wave equations along each river path of the hierarchically organized river network defined by the DRT algorithm, river discharge, river stage, surface water storage and other streamflow variables are derived at each timestep (H. Wu et al., 2014; Yan et al., 2020). With overall good performance in depicting the complexity of river basin processes from runoff generation to river routing, the DRIVE model has been widely applied as an efficient source of flood information from global to regional and finer scales (Grimaldi et al., 2019; Huang et al., 2021; H. Wu et al., 2019; Nanding et al., 2021; Q. Wang et al., 2020; Yan et al., 2020).…”

Hydrological Evaluation of Satellite-Based Precipitation Products in Hunan Province

“…The DRIVE model includes flood inundation modules and is suitable for flood simulation at different spatial and temporal scales. Researchers have also applied the DRIVE model in many other studies [37,[42][43][44][45][46]. The detailed descriptions of the DRIVE model can be found in the literatures [37,45,46].…”

“…Researchers have also applied the DRIVE model in many other studies [37,[42][43][44][45][46]. The detailed descriptions of the DRIVE model can be found in the literatures [37,45,46].…”