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Hydrologic investigations of radar-rainfall error propagation to rainfall-runoff model hydrographs
Journal article   Open access   Peer reviewed

Hydrologic investigations of radar-rainfall error propagation to rainfall-runoff model hydrographs

Ganesh R Ghimire, Witold F Krajewski, Tibebu B Ayalew and Radoslaw Goska
Advances in water resources, Vol.161, 104145
03/2022
DOI: 10.1016/j.advwatres.2022.104145
url
https://doi.org/10.1016/j.advwatres.2022.104145View
Published (Version of record) Open Access

Abstract

•Several aspects of the radar-rainfall contributing to streamflow errors are explored.•The basin-wide rainfall volume bias explains most of the streamflow prediction errors from radar-rainfall given a reasonable estimation of its spatial structure.•Radar-rainfall resolutions’ effect on streamflow prediction errors generally shows spatial scale dependence.•Other rainfall characteristics explored do not show a strong signature of streamflow errors at most of the USGS streamflow monitoring gages. Rainfall is arguably the most important yet most variable input for rainfall-runoff hydrologic models. In this study, the authors search for the characteristics of radar-rainfall estimates that are most important for skillful streamflow predictions. They perform comprehensive hydrologic investigations of radar-rainfall characteristics, including spatiotemporal resolution, radar range visibility, statistical characterization of rainfall variability, all vis-a-vis basin characteristics such as size and river network topology. Since the true rainfall fields are unknown, the authors exploit a paradigm of using two independently constructed radar-rainfall products i.e., Multi-Radar Multi-Sensor and IFC-ZR used operationally by the Iowa Flood Center (IFC). Using the distributed hydrologic model called the Hillslope-Link Model for the domain of the state of Iowa, they evaluate streamflow prediction at 140 USGS gauge stations that monitor rivers in Iowa. Through spatial and temporal rainfall aggregation experiments, the authors show that the impact of spatial and temporal resolution of rainfall is significant typically for smaller basins while starts reducing significantly for basins larger than 1,000 km2. Other rainfall characteristics they explored do not reveal a strong signature in the relationship of rainfall differences between the two products and hydrograph errors. However, exploring the product similarities rather than differences reveals that the basin-wide rainfall volume has the most significant effect on streamflow prediction. The results from this study are generalizable for all rainfall observing systems.
Basin-wide rainfall volume error IFC MRMS Radar-rainfall error Resolution Width function

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