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Development of a Hybrid Model for Generating a precipitation map of Iran
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Kazem Saber Chenari   , Kazem Saber Chenari * |
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Abstract: (25 Views) |
| Precipitation is one of the most important components of the hydrological cycle and one of the main factors affecting water resources management, environmental planning, and climate studies. Therefore, the development of accurate and up-to-date national priciptation maps is of great importance. This study aimed to develop an optimal hybrid spatial interpolation model for producing a new national priciptation map of Iran using long-term precipitation records. For this purpose, precipitation data from 1,275 selected rain gauge, evaporation, and synoptic meteorological stations operated by the Iranian Ministry of Energy and the Iran Meteorological Organization during the period 1988–2017 were collected, quality-controlled, and completed using appropriate gap-filling techniques. After testing data normality and applying the Box–Cox transformation, the performance of Inverse Distance Weighting (IDW), Ordinary Kriging (OK), Simple Kriging (SK), Ordinary Co-Kriging (OCK), and Simple Co-Kriging (SCK) with spherical, exponential, and Gaussian variogram models was evaluated. In addition, several hybrid interpolation models were developed by combining the best-performing methods. Model performance was assessed using the correlation coefficient (R), mean absolute error (MAE), mean bias error (MBE), and normalized root mean square error (NRMSE). Among the individual interpolation methods, Ordinary Kriging with the spherical variogram model achieved the highest accuracy, yielding R = 0.951, MAE = 57.2 mm, and NRMSE = 20.4%, while IDW ranked as the second-best individual method. The proposed hybrid models substantially improved interpolation accuracy. In particular, the hybrid model combining Ordinary Kriging (spherical variogram) and IDW with a power parameter of 2.5 produced the best overall performance, with R = 0.999, MAE = 2.98 mm, and NRMSE = 1.23%. Spatial analysis of relative error further demonstrated that 98.9% of Iran's territory exhibited relative errors below 10% using the hybrid model, whereas this proportion was only 15.7% for the best individual interpolation method. These findings demonstrate that the proposed hybrid approach significantly reduces interpolation uncertainty and provides a highly reliable framework for producing a national-scale priciptation map of Iran. |
Article number: 3 |
| Keywords: precipitation map, Geostatistics, Ordinary Kriging, Co-kriging, Hybrid Model, Spatial Interpolation, Iran |
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Type of Study: Research |
Subject:
Special
Received: 2026/07/10 | Revised: 2026/08/3 | Accepted: 2026/09/16 | ePublished ahead of print: 2026/09/17
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