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Abstract:Sensitivity analysis is crucial in assessing the impact of climatic variables on reference evapotranspiration estimations. The sensitivity of the standardized ASCE-Penman-Monteith evapotranspiration equation for daily estimations to climatic variables has not yet been studied in Spain. Andalusia is located in southern Spain where almost 1 million ha are irrigated under quite different conditions; it has a high inter-annual variability in rainfall. In this study, sensitivity analyses for this equation were carried out for temperature, relative humidity, solar radiation and wind speed data from 87 automatic weather stations, including coastal and inland locations, from 1999 to 2006. Topography and Mediterranean climate characterize the heterogeneous landscape and vegetation of this region. Simulated random and systematic errors have been added to meteorological data to obtain ET 0 deviations and sensitivity coefficients for different time periods. BIAS and SEE (standard error of estimate) have been used to evaluate the effect of both types of errors. The results showed a large degree of daily and seasonal variability, especially for temperature and relative humidity. In general, the effect on ET 0 values of introduced random errors was larger than that of systematic errors. ET 0 overestimations were produced using positive errors in temperature, solar radiation and wind speed data, while these errors in relative humidity resulted in ET 0 underestimations. The sensitivity of ET 0 to the same climatic variables showed significant differences among locations. The geographical distribution of sensitivity coefficients across this region was also studied. As an example, during spring months, ET 0 equation was more sensitive to temperature in stations located along the Guadalquivir Valley.

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In this work, the multifractal properties of hourly rainfall data recorded at a location in Southern Spain have been related to the scale properties of the corresponding intensity–duration–frequency (IDF) curves. Four parametric models for the IDF curves have been fitted to the quantiles of rainfall obtained using the generalized Pareto frequency distribution function with the extreme data series obtained for the same place. The scaling of the rainfall intensity moments has been analysed, and the empirical moments scaling exponent function has been obtained. The corresponding values of q1 and γ1 have been empirical and theoretically calculated and compared with some characteristics of the different IDF models. Thus, the scaling behaviour of IDF curves has been analysed, and the best model has been selected. Copyright © 2012 John Wiley & Sons, Ltd.

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