Comparison of Satellite and Ground-Based Precipitation Data for Drought Index Analysis in the Khorasan Razavi Province | ||
| پژوهش های آبخیزداری | ||
| Article 2, Volume 38, Issue 2 - Serial Number 147, July 2025, Pages 1-19 PDF (2.04 M) | ||
| Document Type: Research | ||
| DOI: 10.22092/wmrj.2024.366564.1591 | ||
| Author | ||
| Zahra Shirmohammadi-Aliakbarkhani* | ||
| Department of Water Science and Engineering, University of Torbat-e Jam, Torbat-e Jam, Khorasan Razavi, Iran | ||
| Abstract | ||
| Introduction and Goal Drought is a complex natural hazard that can have significant impacts on socio-economic and environmental. Traditional methods of drought assessment often rely on ground-based precipitation measurements, which can be sparse and unevenly distributed, especially in underdeveloped regions. The Standardized Precipitation Index (SPI) is widely used for its assessing and monitoring drought, especially in arid regions. However, the reliability of SPI calculations heavily depends on the availability and accuracy of precipitation data. Satellite precipitation products (SPPs) offer an alternative by providing comprehensive coverage and consistent data over large areas, which is particularly useful in regions with limited ground-based observations. Materials and Methods Using four monthly SPPs-TRMM 3B43 (TRMM), GPM-IMERG v6 (GPM), PERSIANN-CDR (PERSIANN), and ERA5- available on the Google Earth search engine, the 12-month drought index was calculated. Then, this index was compared with the index calculated using long-term precipitation data from ground-based stations, both individually for each station and collectively at the provincial level in Khorasan Razavi, located in northeastern Iran. The selected stations include Quchan, Gonabad, Kashmar, Mashhad, Neyshabour, Sarakhs, Sabzevar, Golmakan, Torbat-e Jam and Torbat-e Heydarieh. The study period spans from 2000 to 2020, covering various climatic variations and drought events. To assess the performance of the satellite data, several statistical metrics were computed, including the correlation coefficient (CC), root mean square error (RMSE), relative bias (RBIAS), Nash-Sutcliffe efficiency (NSE), and estimation probability (POD). Using these criteria, the accuracy and reliability of satellite products in estimating drought indices can be evaluated within a robust framework. Results and Discussion The performance evaluation of the satellite products revealed varied results across different stations. The performance of the TRMM product was better in Torbat-e Heydarieh, Quchan, Kashmar, Mashhad, and Neyshabour. This product exhibited a high correlation coefficient and low root mean square error values compared to ground-based data, indicating its reliability in these regions. The performance of the PERSIANN and GPM products was better in Golmakan and Sabzevar, respectively, and they showed better agreement with ground-based rainfall data at these stations. The ERA5 product was found to be most effective in Torbat-e Jam, Gonabad, and Sarakhs, demonstrating a high degree of accuracy in these areas. The relative bias and mean error metrics also showed that overall, the satellite products provided accurate rainfall estimates with minimal systematic deviation from ground-based data. The NSE values, which which can be used to assess the predictive accuracy of models, were greater than 0.65 for the top-performing products, indicating their high efficiency in drought monitoring. The results of the point-by-point statistical analysis were better compared to the aggregated data at the provincial level. In the aggregated analysis, the highest correlation coefficient (CC=0.8), the highest Nash-Sutcliffe efficiency (NSC=0.55), the lowest root mean square error (RMSE=0.61), and the highest probability of detection (POD=0.70) were obtained from the TRMM satellite data. It seems that individual stations may provide different data compared to the entire province due to specific local conditions such as the presence of local water sources, specific vegetation cover, or human influences. Therefore, by aggregating the data at the provincial level, the impact of these local anomalies was amplified, and the resulting outcomes, due to reduced accuracy and increased influence of local anomalies, no longer accurately reflected the actual climatic conditions of the province. It can be concluded that the validation of the aforementioned satellite products in determining the 12-month drought index should be carried out locally. Conclusion and Suggestions Based on the accuracy assessment of the 12-month SPI time scale, the performance of satellite-derived precipitation data in the studied areas was satisfactory. The results of separate statistical analyses of the data at each station were more accurate compared to the aggregated analysis of all stations. n particular, the accuracy of TRMM data for Torbat-e Heydarieh, Quchan, Mashhad, Neyshabour, and Kashmar stations; the GPM data for Sabzevar station; the ERA5 data for Torbat-e Jam, Sarakhs, and Gonabad stations; and the PERSIANN data for Golmakan station were suitable and can be used for water resources management and drought monitoring. It is suggested that, given the appropriate accuracy of satellite data, these data can be used as a valuable long-term dataset to investigate droughts in the studied areas of Khorasan Razavi Province. Because satellite data uses different data sources, each of these data may be affected by various environmental, geographical, and climatic factors. Therefore, due to local characteristics and inherent differences in the instructions used in each data, it was expected that performance would not be the same across all stations. Therefore, it is suggested to use large-scale satellite data, data analysis methods, local calibration, and uncertainty modeling in a combined manner to achieve an appropriate confidence factor for these data. | ||
| Keywords | ||
| arid and semiarid regions; drought assessment; google earth engine; satellite-based precipitation products | ||
| References | ||
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