Start Submission Become a Reviewer

Reading: Evaluation of PERSIANN-CCS Satellite Derived Rainfall Product with Raingauge Data over Kelan...

Download

A- A+
Alt. Display

Section I

Evaluation of PERSIANN-CCS Satellite Derived Rainfall Product with Raingauge Data over Kelani River Basin, Sri Lanka

Authors:

B. M. L. A. Basnayake ,

University of Ruhuna, LK
About B. M. L. A.
Senior Lecturer, Department of Civil and Environmental Engineering

AMIE (SL), PhD (NUS, Singapore), B.Sc. Eng. (Hons) (Peradeniya), MIAHR
X close

U. G. C. R. Madushani

RR Construction Pvt. Ltd., Colombo, LK
About U. G. C. R.
AMIE (SL), B.Sc. Eng. (Ruhuna), Site Engineer
X close

Abstract

Satellite rainfall estimates (SREs) are high in spatial and temporal resolution and particularly important for regions with sparse raingauges. However, SREs are required to evaluate with gauged rainfall data before applying for hydrological studies. In this research, the accuracy of Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks Cloud Classification System (PERSIANN-CCS) product was evaluated at daily, monthly, yearly, and seasonal scale upon the raingauge data of the Kelani River basin of Sri Lanka for the period 2004 to 2010. The performance of the SREs was evaluated using both continuous and categorical verification statistics. PERSIANN-CCS rainfall estimates follow the bi-modal rainfall pattern and showed greater underestimation in South West Monsoon (SWM) season (May-Sep.) and overestimation in Inter- Monsoon 1 (IM1) period (March-April). PERSIANN-CCS is more capable of recognizing conventional and depressional rains than monsoonal rains. On the other hand, it produces low false alarms in the high rainy season than in the low rainy season. The daily categorical statistics show above average scores (Accuracy>0.69; POD>0.65; FAR<0.34; 0.76>FBias<1.11), however, estimations were with low CC (<0.53) and high bias (<24 & >-64%). Bias corrected PERSIANN-CCS may be a high-resolution rainfall source for flood forecasting applications in the Kelani River basin.
How to Cite: Basnayake, B.M.L.A. and Madushani, U.G.C.R., 2022. Evaluation of PERSIANN-CCS Satellite Derived Rainfall Product with Raingauge Data over Kelani River Basin, Sri Lanka. Engineer: Journal of the Institution of Engineers, Sri Lanka, 55(1), pp.01–11. DOI: http://doi.org/10.4038/engineer.v55i1.7481
Published on 10 Jun 2022.
Peer Reviewed

Downloads

  • PDF (EN)

    comments powered by Disqus