Science Target Conference Systems, Ajman 4th International Environment Conference 2016

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The Impact of Potential Evapotranspiration Methods at Various Altitudes on the Reconnaissance Drought Index Alpha Form for Arid and Semi-arid Regions
Ruqayah Mohammed, Miklas Scholz

Last modified: 2015-10-10

Abstract


 

The agriculture industry in arid regions depends on irrigation and appropriate water management strategies informed by hydrological indicators. Meteorological drought severity is conventionally evaluated through indices. Several drought indices with different complexity have been utilized in many geographical regions. Recently, a robust meteorological drought index, the Reconnaissance Drought Index (RDI), is acquisitioning acceptance primarily in arid and semi-arid climatic areas. Since RDI is founded on precipitation and potential evapotranspiration (PET), it is vital assessing the impact of the PET estimation method on the drought severity characterization obtained by RDI. The main focus of the current research is to evaluate how the PET methods impact on the results of RDI, in particular, the alpha form of the index for annual reference periods using three of the most popular empirical PET methods with minimum data requirements. These methods are known as Hargreaves, Thornthwaite, and locations Blaney-Criddle, and are applied in addition to the Food and Agriculture Organization Penman-Monteith standard method. The Climate Forecasting System Reanalysis (CFSR) global methodological dataset has been applied for different altitudes and. No significant influences on both the standardized and normalized forms of the RDI were detected by using the selected PET methods at different altitudes for various climatic conditions. However, the alpha form of RDI is directly influenced by various PET methods at different altitudes. Accordingly, attention should be paid to the method of estimation of PET, particularly at high altitude. The application of different methods may lead to flaws in water resources availability predictions.