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

Ghimire, Ganesh R.; Krajewski, Witold F.; Ayalew, Tibebu B.; Goska, Radoslaw

doi:10.1016/j.advwatres.2022.104145

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

Journal Article · Sat Jan 29 00:00:00 EST 2022 · Advances in Water Resources

DOI:https://doi.org/10.1016/j.advwatres.2022.104145· OSTI ID:1843668

^[1]; Krajewski, Witold F. ^[2]; Ayalew, Tibebu B. ^[3]; Goska, Radoslaw ^[2]

Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Univ. of Iowa, Iowa City, IA (United States)
Berkshire Hathaway Specialty Insurance, San Ramon, CA (United States)

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.

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Research Organization:: Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 1843668

Journal Information:: Advances in Water Resources, Vol. 161; ISSN 0309-1708

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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

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