Sensitivity analysis of a Penman-Monteith type equation to estimate reference evapotranspiration in southern Spain

• Published in: Hydrological processes Vol. 23; no. 23; pp. 3342 - 3353
• Main Authors: Estévez, Javier, Gavilán, Pedro, Berengena, Joaquín
• Format: Journal Article
• Language: English
• Published: Chichester, UK John Wiley & Sons, Ltd 15.11.2009; Wiley
• Subjects: annual evolution; climatic change; Earth sciences; Earth, ocean, space; Exact sciences and technology; Hydrology. Hydrogeology; reference evapotranspiration; sensitivity coefficients; spatial distribution; Iberian Peninsula; Southern Europe; Guadalquivir; Europe; Spain; Spain, Andalusia; ANE, Spain; landscapes; rainfall; sensitivity analysis; springs; topography; solar radiation; vegetation; climatic change; climate; evapotranspiration; variability; spatial distribution; reference evapotranspiration; winds; standard samples; temperature; humidity; sensitivity coefficients; valleys; errors; climate change; annual evolution
• ISSN: 0885-6087; 1099-1085
• DOI: 10.1002/hyp.7439

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 ET₀ 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 ET₀ values of introduced random errors was larger than that of systematic errors. ET₀ overestimations were produced using positive errors in temperature, solar radiation and wind speed data, while these errors in relative humidity resulted in ET₀ underestimations. The sensitivity of ET₀ 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, ET₀ equation was more sensitive to temperature in stations located along the Guadalquivir Valley. Copyright © 2009 John Wiley & Sons, Ltd.