# Presentation: 511552

## TRANSITION FROM LUMPED TO DISTRIBUTED SYSTEMS

- Victor Koren, Michael Smith,
- Seann Reed, Ziya Zhang
- NOAA/NWS/OHD/HL, Silver Spring, MD

## Distributed and Lumped Modeling Dynamics

## History Lessons

- There is a similarity in dynamics of lumped and distributed model developments
- There is a large delay between model development and application
- There is no ‘unique best’ model.  Selection for application is rather arbitrary process that depends on an expertise of the user and practical requirements
- Most successful models in an operational use are models which have well developed parameterization tools

## Distinguishing Features of Lumped and Distributed Models

**Physics**
- Does point rainfall-runoff model represent well ‘field’ processes
- Can hillslope/channel routing be represented well on ‘practically reasonable’ space/time scales
- Does statistical approach solve a basin heterogeneity problem

## Distinguishing Features of Lumped and Distributed Models (Continued)

**Physics**
- Does statistical approach solve a basin heterogeneity problem

- Surface runoff simulated with and without use of
- rainfall distribution function at different scales

## Distinguishing Features of Lumped and Distributed Models (Continued)

**Space/Time Variability**
- Does accounting for the space/time variability of input data and parameters guarantee better results
- Does scale effect significantly on the model structure
- Is a lumped model a reasonable candidate in a distributed system

- Effect of noisy rainfall data on the peak volume
-            at different simulation scales.

## Distinguishing Features of Lumped and Distributed Models (Continued)

- Parameterization/Calibration
- Can distributed model parameters be measured on the grid scale
- Are distributed model parameters identifiable enough from hydrograph analyses
- How much does scale effect on model parameters

- Change an ‘effective’ parameter value at different
-         scales as a function of rainfall variability

## HL-Research Modeling System (HL-RMS)

- Modeling framework for testing lumped, semi-distributed, and fully distributed hydrologic modeling approaches

## HL-RMS Structure

- Uses channel connectivity matrix defined on the HRAP grid
- Each computational element consists of a number of uniform hillslopes and ‘conceptual’ channels
- Rainfall-runoff component (Sacramento model in the 1st version) generates ‘fast’ and ‘slow’ runoffs
- Hillslope transforms (kinematic routing) ‘fast’ runoff into lateral channel inflow
- Channel inflow combined with ‘slow’ runoff and upstream cell outflow is routed through a cell ‘conceptual’ channel
- Ingests NEXRAD Stage III data
- Includes features of lumping parameters/input data
- Modular design to test other models

## Slide 10

## HL-RMS Structure

- Conceptualization of a grid cell

## HL-RMS Parameterization

- A priori parameters:
- Rainfall-runoff model parameter grids are estimated using soil/vegetation data
- Hillslope/Channel routing parameter grids, slope, length, area above, are calculated based on DEM
- Uniform channel shape and roughness coefficient is assumed at each grid cell
- Parameter adjustment:
- Scaling/Replacement based on lumped or semi-distributed calibration of rainfall-runoff model
- Spatially variable channel shape and roughness parameters can be generated from discharge measurements at outlets and geomorphological properties at each grid cell

## Slide 13

## Slide 14