Assessment of Precipitation Mappings Using Distributed Hydrologic Modeling

Distributed hydrologic models provide a way to assess the accuracy of multi sensor-based precipitation mappings; this is in addition to the utility of the hydrological modeling for flow prediction supportive to water management. High resolution gridded precipitation fields generated by Multisensor Precipitation Estimation (MPE) provide an enhanced basis for predicting watershed hydrologic response across a wide range of space and time scales. Distributed hydrologic models take account of the spatial variability of rainfall, as well as the variability of watershed terrain, soils, soil moisture, and land use.

A case study conducted on the Russian River basin in California has involved forcing a distributed hydrologic model with MPE precipitation fields. A companion paper (Cifelli, et al 2012) presents details on how the multisensor-based precipitation fields were developed. In this paper we present results of application of the Research Distributed Hydrologic Model (RDHM) using the rainfall fields generated by Multisensor Precipitation Estimator (MPE). Activities for RDHM setup, parameterization, sensitivity, calibration, and performance assessment are described. The influence of storm movement on watershed responses is also explored. Coupling of the hi-res MSP fields with the distributed hydrologic model is shown to provide significant advantages in comparison to a lumped modeling approach. These advantages are associated with the spatial detail of precipitation and land response fields which yields more precise river flow predictions throughout the basin, as well as providing flow predictions at any location throughout the basin.