Assessment of standardized precipitation and standardized precipitation-evapotranspiration indices for wet period detection

Background and Objectives: Flood is one of the deadliest natural disasters in the world, which causes enormous sufferings to human societies and changes in environment. In recent years, flooding has become a growing concern for both communities and governments across several parts of the world. This problem, has made the needs for the experienced managers and flood engineers to reduce the flood impact on the society and environment. Flood forecasting is one of the non-structural flood risk management method which gives valuable information for flood alert services and people and various organizations will have enough time to prepare flood control measures in emergency situations.
Materials and Methods: In this study standardized precipitation index (SPI) and standardized precipitation-evapotranspiration index (SPEI) in Darzikala and Sangadeh weather stations located in Kasilian basin, Mazandaran province were calculated using R codes to determine the wet period. In order to explore the efficiency of SPI and SPEI in flood detection, the results were compared with river discharge time series in Valikbon gage station. To compare the results of SPI and SPEI indices, probability of detection (POD), false alarm ratio (FAR), and critical success index (CSI) were applied.
Results: The results showed that maximum and minimum POD for SPI and SPEI were 0.89 and 0.68 respectively. These values for CSI were 0.71 and 0.61 and for FAR parameter were 0.32 and 0.11 respectively. The trend analysis of mentioned indices showed that the SPEI index was relatively better than SPI due to the use of temperature data and hence the calculation of evapotranspiration, especially at the end of spring and summer in the Kasilian basin which has rainfall–snow regime
Conclusion: Based on the POD, FAR, and CSI statistics, it is suggested that the application of SPEI index is more suitable for flood forecasting in rainfall-snow regime due to the use of temperature data for snow melt, especially in spring and summer. The SPI index is also an important indicator because of its ability in providing desirable results in flood forecasting with only one parameter and also due to this fact that the rainfall is the only accurate data with appropriate historical period in all watersheds, and at least two organs in the country are collecting information about it.
Conclusion: Based on the POD, FAR, and CSI statistics, it is suggested that the application of SPEI index is more suitable for flood forecasting in rainfall-snow regime due to the use of temperature data for snow melt, especially in spring and summer. The SPI index is also an important indicator because of its ability in providing desirable results in flood forecasting with only one parameter and also due to this fact that the rainfall is the only accurate data with appropriate historical period in all watersheds, and at least two organs in the country are collecting information about it.