JWSS - Journal of Water and Soil Science

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Under different climatic conditions of Iran, the evaluation of evapotranspiration (ETo) models sensitivity to meteorological parameters, prior to introducing the superior performance model, seems quite necessary. Using a 35-year (1971-2005) climatological observations in Hamedan, this study compares the sensitivity of different commonly used evapotranspiration models to different meteorological parameters within the IPCC recommended variability range of 10 to 20% during the growing season (April-October). The radiation and temperature-based ETo models include: Penman-Monteith -FAO56 [PMF56], Jensen-Haise [JH1,2], Humid Turc [TH], Arid (semi) arid Turc [TA], Makkink [MK], Hansen [HN], and Hargreaves-Samani [HS]. Results indicate that all the above-mentioned ETo models show the highest sensitivity to radiation and temperature parameters. This implies that special care is required when we apply model-generated radiation and albedo parameters in such ETo models. It is predicted that by 2050, as a result of global warming, the cold semi-arid climates of Iran will cause an average evapotranspiration rise of about 8.5% in crop reference during the growing season.

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Soil temperature is one of the important variables in hydrology, agriculture, meteorology and climatology studies. Owing to the fact that soil temperature is only measured at synoptic stations, reconstruction of this variable in other places is of great importance for many relevant agricultural surveys. Using 10-year (1996-2005) daily meteorological observations, including: air temperature, global solar radiation, precipitation, relative humidity, vapor pressure, wind speed and air pressure data, different empirical relationships are suggested. At statistically significant level (P<0.05), the suggested regressions are reliable for estimating soil temperature in various depths (5, 10, 20, 30, 50 and 100 cm) and different climate types. Using soil temperature as the dependent variable and the other meteorological parameters as the independent variables, the multivariable relationships are classified accordingly. The results indicate that the impact of meteorological parameters on soil temperature is not the same. At statistically significant level (P<0.05), the mean daily air temperature presented the highest correlation coefficients with soil temperature for all climate types (on average, from R2>0.91 for warm semi-arid, to R2>0.85 for humid climates). Other results highlighted that the correlation coefficients decreased as the soil depth increased. The behavior of statistical validation criteria of the suggested relations are also discussed for all the mentioned climates.

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Quantitative evaluation of evapotranspiration on a regional scale is necessary for water resources management, crop production and environmental assessments in irrigated lands. In this study, in order to estimate ETo and because of few synoptic stations and also little recorded meteorological data in North Khorasan Province, Iran, with arid and semi-arid climate, 7 stations from neighboring provinces were used. Reference evapotranspiration was calculated using 6 different methods which required a small amount of input data, including Class A pan, Hargreaves-Samani, Priestly-Tailor, Turc, Makkink and the method proposed by Allen et al (1998) to estimate ETo with missing climate data. Besides, the standard FAO-Penman-Monteith was used (because there was no Lysimetric data in the region) to evaluate the applied formulas. Since there was no agreement over the appropriate method to calculate ETo in the selected stations, by using significance test of regression lines, a linear regression equation was computed for each month, in order to convert the best calculating method to FAO-Penman-Monteith formula. Evaluations of these equations showed their acceptable accuracy, in comparison with the previous researches, specifically for cold months (MAE values ranged from 0.3 to 1.4 mm/day).