estimation of radar-rainfall error spatial correlation Big Bar California

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estimation of radar-rainfall error spatial correlation Big Bar, California

The rate at which uncertainty changes depends on the error structure of the input rainfall fields. This is not always the case with calibrated models that adjust their parameter values to compensate for uncertainties in the input.[9]In this study we use a fully distributed, physically based, and Early methods of simulating synthetic radar-rainfall fields, i.e., rainfall fields that are corrupted by radar-like systematic and random errors, were based on a conceptual understanding of the uncertainties involved [Krajewski and The effect of coefficient a on simulated hydrographs is trivial because it is just a multiplicative factor.

Mandapaka,MeteoSwiss,SwitzerlandSearch for more papers by this authorWitold F. On the other hand, there is plenty of evidence documented in the literature that rainfall variability, resolution, and accuracy play crucial roles in the model's development and performance. Your cache administrator is webmaster. The following are state variables: hw is the water table level and ai is the hillslope impermeable area.[30]We adopt a simplified conceptualization of the hillslope subsurface geometry to estimate impermeable area

The fact that the generator is conditional on actual radar-rainfall fields ensures relevance to practical applications and allows analysis of real events.[6]Once realistic radar-rainfall ensembles are generated, they are used as This is expected since the river network filters out small-scale variability and uncertainties [e.g., Mandapaka et al., 2009a]. While a number of direct and indirect methods are available to estimate rainfall rate and accumulation, weather radars remain the only operational instruments capable of providing rainfall quantities over large domains The system returned: (22) Invalid argument The remote host or network may be down.

We discuss the main features of these two components below.[5]Uncertainties in radar rainfall estimates have been studied for more than 30 years [Grayman and Eagleson, 1971; Wilson and Brandes, 1979; Cluckie The aggregated discharge is attenuated by the selected water velocity model. In this study we avoid calibration by adopting a different modeling approach, and instead of calibrating parameters to achieve better results, we systematically improved the model's structure. We calculated the mean annual flood as a function of drainage area using USGS historical data for the Cedar and Iowa Rivers.

The basin decomposition method used in this study provides flow simulation for every link in the basin, which allows us to investigate error scale dependency using a large number of locations Ciacha, Gabriele Villarinia, James A. In this study we also neglected temporal correlations in the random field generator. In addition, the authors used the radar- and gauge-rainfall data to estimate the spatial and temporal correlation of random errors.

Please enable JavaScript to use all the features on this page. The model has a power law functional form with the velocity dependent on the magnitude of the discharge and the upstream drainage area. Note that from here on we use the term dispersion as a synonym for the spread of the ensemble. More details about the generator are provided by Villarini et al. [2009].[38]The generation of ensemble radar-rainfall fields can be summarized as follows: (1) the reference rainfall field was corrected for conditional

In Iowa City, 16 buildings on The University of Iowa campus were reported flooded and the total cost of recovery from the flood reached $750M. Your cache administrator is webmaster. We then repeated the above ensemble simulation for a different scenario of the radar-rainfall model.[25]In the following sections we will focus on the description of the two main components of this Section 4 includes the main results of this study, including: (1) the validation of the hydrological model across multiple scales, (2) the rainfall error scenarios and statistics for the generated rainfall

Evapotranspiration strongly affects soil moisture content, especially between rainfall events in the summer and spring seasons, and consequently plays an important role in runoff generation. Hillslope-link models provide a more accurate representation of the river basins and have lower computational requirements than grid-based models [e.g., Yang et al., 2002]. Smaller values of C3 result in a faster decrease in the correlation close to the origin. This is, in fact, the main motivation behind our study.

The estimation of the RRE model parameters for Iowa would require data from a dense network of rain gauges and is outside of the scope of this study. The generator uses a conditional simulation framework: Given the estimates provided by a specific radar-rainfall estimation algorithm, the method returns rainfall fields that have the same error structure as that observed This slight difference is mainly due to the stochastic nature of the error fields. Once rainfall reaches the surface, it is transformed into surface ponding.

Skip to main content AboutWelcomeMissionPeopleLeadershipDirectorManagement TeamGoverning BoardScientific Advisory BoardFacultyResearch FellowsPhD StudentsStaffPeople by GroupTectonicsVolcanoClimateApplied ProjectsCommunity EngagementArt+MediaTechnicalCorporate ServicesSupportSupport EOSImpactMake a DifferenceMake a GiftBenefactorsCollaboratorsAwardsAnnual ReportsResearchTectonicsVolcanoClimateHazards and SocietyArt+MediaProjects MapEngagementCommunity EngagementCommunicationDocumentary Photography & VideoEducationApplied Projects GroupTechnical We address these questions herein.[7]Previous studies have demonstrated, albeit indirectly, that a fair investigation of how rainfall errors affect flood simulation requires a calibration-free hydrological model since calibration camouflages uncertainties related To reduce the effect of the deterministic distortion function on the spread of the ensemble, we calculated statistics for the time series of spatial averages (without temporal accumulation). As our goal is to have the capability to predict potential flooding conditions anywhere within a large region (basin), we have been developing a distributed, data-intensive rainfall-runoff model.

Therefore, a similar approach is not computationally feasible for large basins using fine decomposition of the terrain (at the hillslope level). The flux from the saturated layer to the channel is also simulated by Darcy's equation, using saturated hydraulic conductivity and terrain slope.[32]Part of the water is removed from the surface, and We did this by evaluating the model's performance using observed streamflow data for 24 sites in Iowa and by comparing the simulated streamflow with that generated by a semidistributed version of PET is used to estimate the actual evaporation from the surface and from the unsaturated and saturated layers of the soil.

Hereafter, we refer to these overall bias corrected fields as reference rainfall. In our case, the algorithm is the precipitation processing system [Fulton et al., 1998] that converts the reflectivity data from the WSR-88D weather radars to the hourly accumulation with approximately 4 We used NEXRAD's stage IV products as a reference in this study to compare how different rainfall error sources and scenarios affect hydrological prediction across scales.Table1.Data Set Used for the Simulations The generated rainfall fields will allow us to map rainfall uncertainty to the response of the hydrological system.4.2.Validation of Hydrological Simulations[50]Before we used our hydrologic rainfall-runoff model to study the effects

We remap the radar rainfall grid to the hillslope-link structure adopted in the model. Calibration is avoided through the use of parameters that are directly or indirectly linked to the physical properties of the watershed (e.g., soil water storage capacity, hillslope shape, and channel flow Dingman [2002] defines PE as “the rate at which evapotranspiration would occur from a large area completely and uniformly covered with growing vegetation which has access to an unlimited supply of or its licensors or contributors.