Mr. Aliakbar Mirshafie, , ,
Volume 11, Issue 2 (8-2024)
Abstract
Assessment of the measurement statistics of model accuracy and the appropriate
use of them (Case study: Interpolation of Precipitation in Fars province)
Abstract
In many scientific researches, error measurement statistics are often used without taking notices into account
when selecting a model or method for the spatial analysis of environmental hazards. In order to assess the
accuracy of precipitation interpolation methods in Fars province, the performance of widely used error
measurement statistics and some comments were implemented. Spatial interpolation of precipitation was
accomplished using inverse distance weighting, kriging, co-kriging, and radial basis functions methods with 161
weather stations (22 synoptic and 139 rain gauge stations) for 2018 as a rainy year. The results of MBE statistic
evaluation indicated that the researcher may have chosen the incorrect interpolation method in certain cases
where the sum of the positive and negative values became zero. In addition, this statistic is limited to indicating
overestimation or underestimation and should not be used for assessing accuracy or selecting interpolation
techniques. Regarding the coefficient of determination (r 2 ), the results revealed that due to the lack of
compatibility in the magnitude of the range of this coefficient (0 to 1) with error values (100 to 400 mm for the
interpolation of precipitation in Fars province), its use in evaluation of the accuracy of a method is not
recommended. In terms of NRMSE, the results showed that samples with a small number of observations (n=3),
its value increased excessively (NRMSE=0.35) when compared to samples with a bigger number of data (n=20,
NRMSE=0.097). Therefore, it is not advised to use this statistic. In conclusion, since MAE and RMSE statistics
provide a more realistic error value, it is advised to use them for assessing the accuracy of interpolation
methods.
Keywords: Precipitation, Error evaluation statistics, Interpolation methods, Fars province
Dr. Mohammad Hossein Nasserzadeh, Dr. Ali Reza Karbalaee, A Master's Student Maryam Ghaderi Rastaghi,
Volume 11, Issue 4 (2-2025)
Abstract
Precipitation concentration denotes the temporal and spatial distribution of precipitation within a watershed, and has a substantial influence on hydrology and water resource management. This study examines the spatial and temporal patterns of precipitation concentrations in Mazandaran Province. Precipitation data from eight meteorological stations covering the period from 2002 to 2021 were used, and the Precipitation Concentration Index (PCI) was employed for data analysis. The findings revealed that the precipitation concentration in this province exhibited significant spatial and temporal variation. The highest PCI values were recorded in the western regions, particularly in Babolsar and Nowshahr, indicating high concentrations of precipitation during specific seasons. Conversely, the eastern region displayed a more uniform precipitation distribution. Seasonal analyses confirmed that spring was the least rainy season and autumn was the wettest. Additionally, Inter-annual variations in PCI indicated an increasing trend at some stations, suggesting a growing concentration of precipitation in recent years. Spatial analysis of PCI patterns also indicated that the southwestern and eastern regions of the province, influenced by topographic factors and distance from the Caspian Sea, experienced relative precipitation concentration during specific months. In contrast, the northern and northwestern regions, which are affected by Mediterranean weather systems and recent climate change, demonstrate an irregular and seasonal distribution of precipitation. The findings of this study underscore the necessity of considering spatial and temporal variations in precipitation concentrations in the management of water resources and hydrological processes in Mazandaran Province. The observed increasing trend in PCI highlights the need to develop adaptive strategies to address the challenges posed by extreme precipitation events and prolonged dry periods.
