University of Tabriz Water and Soil Science 2008-5133 20 4 2011 01 21 Spatial Variability of Pan Evaporation in Iran and its Estimation Using Several Empirical Models Spatial Variability of Pan Evaporation in Iran and its Estimation Using Several Empirical Models 113 129 1382 FA H Zare Abyaneh AR Moghaddamnia M Bayat Varkeshi A Gasemi M Shadmani Journal Article 2014 05 21 Evaporation as a basic data has a special importance in agricultural, hydrological, meteorological and water and soil conservation researches. In this study, annual evaporation was estimated by means of 61 meteorological station information with 9 empirical and theoretical methods. Results were compared with class-A pan data. The results showed that among the tested methods, Ivanov method had the best consistency with class-A pan evaporation data. The highest relative frequency was in Ivanov method with covering about 56% of all stations and the least covering in Marciano method with 1.6 % converage.. Therefore, Ivanov method showed the needed accuracy for the predicting of evaporation at the different parts of Iran. For estimation of the evaporation at the locations without measured data, evaporation zoning as an important principle at large scheduling were considered. For zoning two methods of simple and ordinary kriging with circular, spherical, exponential and Gousian models were used. Statistical criteria as MAE and MBE showed that circular model in ordinary kriging method is better. The values of statistical criteria were 1.54 and 0.01 mmday^-1, respectively. Evaporation zoning in Arcview software, based on the actual value of evaporation and value of Ivanov method at four groups of evaporation were considered that they had good overlapping. Results of evaporation zoning showed that value of evaporation in 99.33% of Iran is higher than 4.04 mmday^-1 and same evaporation at 96.43% based on Ivanov method was obtained. Results showed that evaporation in local variation (Ivanov) in ordinary kriging for large area and use of large number of stations is reliable. Finally, the spatial variation of evaporation is estimation by Ivanov method with zoning to ordinary kriging method is recommended for the Iran. Evaporation as a basic data has a special importance in agricultural, hydrological, meteorological and water and soil conservation researches. In this study, annual evaporation was estimated by means of 61 meteorological station information with 9 empirical and theoretical methods. Results were compared with class-A pan data. The results showed that among the tested methods, Ivanov method had the best consistency with class-A pan evaporation data. The highest relative frequency was in Ivanov method with covering about 56% of all stations and the least covering in Marciano method with 1.6 % converage.. Therefore, Ivanov method showed the needed accuracy for the predicting of evaporation at the different parts of Iran. For estimation of the evaporation at the locations without measured data, evaporation zoning as an important principle at large scheduling were considered. For zoning two methods of simple and ordinary kriging with circular, spherical, exponential and Gousian models were used. Statistical criteria as MAE and MBE showed that circular model in ordinary kriging method is better. The values of statistical criteria were 1.54 and 0.01 mmday^-1, respectively. Evaporation zoning in Arcview software, based on the actual value of evaporation and value of Ivanov method at four groups of evaporation were considered that they had good overlapping. Results of evaporation zoning showed that value of evaporation in 99.33% of Iran is higher than 4.04 mmday^-1 and same evaporation at 96.43% based on Ivanov method was obtained. Results showed that evaporation in local variation (Ivanov) in ordinary kriging for large area and use of large number of stations is reliable. Finally, the spatial variation of evaporation is estimation by Ivanov method with zoning to ordinary kriging method is recommended for the Iran. https://water-soil.tabrizu.ac.ir/article_1382_25397b23928899930e26556c5aae8cc1.pdf