Evaluating the Performance of Precipitation Products Taking into Account the Climatic and Topographic Conditions across Iran

Document Type : Original Article

Authors

1 M.Sc. Student of Water Resources Management and Engineering, Water Resources Engineering Department, Civil, Water and Environmental Engineering Faculty, Shahid Beheshti University, Tehran, Iran.

2 Assistant Professor of Civil Engineering, Environmental Engineering Department, Civil, Water and Environmental Engineering Faculty, Shahid Beheshti University, Tehran, Iran.

3 Ph.D. Graduate in Water Resources Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran.

4 Ph.D. Student, Water Resources Engineering Department, Civil, Water and Engineering Environmental Faculty, Shahid Beheshti University, Tehran, Iran.

Abstract

Precipitation is a major component of the hydrological cycle which has significant changes over space and time. Missing data in precipitation measurements and improper distribution of precipitation measurement sites cause major problems in hydrological studies. Satellite data is a new alternative for estimating precipitation data and the present study aimed at evaluating the performance of P-CDR (Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks- Climate Data Record) and CHIRPS (Climate Hazards Group Infrared Precipitation with Station Data) with spatial separation of 0.25 × 0.25 and on a daily, monthly and yearly scale for the period of 1990 to 2019 in 88 synoptic stations located in Iran. As a result of annual precipitation estimation analysis and according to performance evaluation indices, P-CDR had better performance than CHIRPS in all regions except for the north and northwest of Iran. Precipitation estimation by P-CDR dataset in all basins except Urmia and Sarakhs had less error in estimating monthly precipitation compared to CHIRPS, and it had the highest correlation with observed data. CHIRPS daily rainfall estimation had better performance than P-CDR, especially in the Persian Gulf and Oman Sea basins. As CSI (critical success index) showed, CHIRPS had a better performance in detecting rainy and non-rainy days in almost all stations. According to the results of altitude-rainfall analysis, both datasets in the highlands of the Zagros mountain chain and north of the Alborz mountain chain performed weak in estimating precipitation.

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References

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Iran-Water Resources Research
Volume 17, Issue 2 - Serial Number 57
September 2021
Pages 62-81

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History

  • Receive Date: 27 April 2021
  • Revise Date: 04 July 2021
  • Accept Date: 10 July 2021

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