Name
Abstract | ||
|---|---|---|
Accurate rainfall estimation from radar reflectivity is crucial in hydrological modeling and quantitative precipitation estimation. Various rainfall intensities exhibited by different rainfall drop size distribution contribute to reflectivity and rain rate relationship (Z-R) variability in radar rainfall estimation. This paper focuses to evaluate the Z-R model during the massive flood in December 2014 for different rainfall intensity. Hourly reflectivity and rain gauge data were used. Linear and non-linear least square regression were applied to compare the accuracy of Z-R coefficients (a and b). This study found that the non-linear least square gives the best evaluation of a and b estimates in high intensity rainfall and Kelantan was experiencing frequent high intensity rainfall during the massive flood in December 2014. Evaluation of empirical model demonstrated in this study can improve the accuracy of radar rainfall estimation. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/IGARSS.2016.7730148 | 2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) |
Keywords | Field | DocType |
Rainfall, Weather radar, Flood, Empirical model, Least square function | Meteorology,Least squares,Radar,Quantitative precipitation estimation,Rain gauge,Weather radar,Computer science,Runoff model,Climatology,Flood myth,Precipitation | Conference |
ISSN | Citations | PageRank |
2153-6996 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| M. N. M. Reba | 1 | 0 | 0.34 |
| N. H. Roslan | 2 | 0 | 0.34 |
| A. Syafiuddin | 3 | 0 | 0.34 |
| Mazlan Hashim | 4 | 42 | 13.59 |