Radar Scaling and Runoff Prediction Models in Arid and Semi Arid Basins
Investigators (most current known information)
The lack of rainfall data, which are crucial for hydrological modeling, is one of the most serious problems that arid hydrological modelers are confronted with. Now, when meteorological radar systems cover arid and semi-arid regions and high-resolution rainfall data are available, new opportunities exist.
Because radar rainfall data are essentially different from the rain-gauge data in their unit area, spatial coverage, and data accuracy, the radar data should be viewed as a new type of rainfall data. New approaches of rainfall-runoff analyses using radar data are needed.
We raise here the question of what is the most appropriate scale to represent radar rainfall for runoff prediction. Although rainfall is highly variable in space and time, outlet runoff, which is the result of rainfall excess integration, is not necessarily sensitive to the small scale variation; some integration of the radar rainfall data may be justified. In addition, original data integration reduces the error, which might be quite large in the local instantaneous radar rainfall data. On the other hand, rainfall integration may cause the loss of valuable information.
The research deals with several aspects of the relationships between radar rainfall, scale, and the catchment hydrological response in the arid and semi-arid environments. In the first part (Section 3), the problem of scale dependency of radar rainfall estimated was investigated. The main finding was that the optimal parameters depend on the scale at which the optimization is conducted. It was shown that observational errors as well as model errors cause scale dependency. In the second part (Section 4), the characteristic time scale of the catchment hydrological response in the transformation of rainfall into runoff was explored. This response time scale (RTS) represents the amount of smoothing conducted in the rainfall-runoff transformation. The technique developed in this research determines the basin RTS based on rainfall and runoff observations. The RTS was found to be stable and an intrinsic characteristic of the basin. In further expanding the idea of a characteristic scale of a basin, the relationships between the rainfall maximum intensity at different time and space scales and the peak discharge at the basin outlet were examined (Section 5). A best fit between the peak rainfall and peak runoff is achieved at a specific scale, which depends on the basin. Finally, in the last part of the research (Section 6), we begin to examine the radar rainfall, not as a pixel of data but as a representation of organization and structure. The structure is of convective rain cells. The methodology to derive the rain cells structure from the radar data is developed. The two last parts (Sections 5 and 6), are still ongoing studies, and the results presented here are partial.
Articles in Journals
Morin E., D.C. Goodrich, R.A. Maddox, H.V. Gupta and S. Sorooshian. 2005. "Rainfall modeling for integrating radar information into hydrological model." Atmospheric Science Letters (in press).
Shamir E., B. Imam, E. Morin, H.V. Gupta and S. Sorooshian. 2005. "Role of hydrograph indices in parameter estimation of rainfall-runoff models." Hydrological Processes (in press).
Morin E., W.F. Krajewski, D.C. Goodrich, X. Gao and S. Sorooshian. 2003. "Rainfall intensities from weather radar data: The scale dependency problem." J. Hydrometeorology 4(5):782-797.
Morin E., D.C. Goodrich, R.A. Maddox, X. Gao, H.V. Gupta and S. Sorooshian. 2004. "Spatial patterns in thunderstorm rainfall events: Conceptual modeling and hydrological insights." Presented, Sixth international symposium on hydrological applications of weather radar, February. Melbourne, Australia.
Morin E., D.C. Goodrich, X. Gao and S. Sorooshian. 2001. "On radar rainfall, catchment runoff and the response scale." Presented, International meeting of the American Geophysical Union, December. San Francisco CA.
Morin E., X. Gao. D.C. Goodrich and S. Sorooshian. 2001. "Estimating rainfall intensities from meteorological radar data: The scale dependency problem." Presented, Seventh international conference on precipitation, observations, estimations and prediction of precipitation variability at all scales, July. Maine.