faeze Ghasem Nezhad; Fazeli Mehdi; Omolbanin Bazrafshan; Mohammad Parvinnia
Abstract
Drought monitoring by the Standardized Runoff Index (SRI) presents some uncertainties, mainly dependent on the choice of the probability distribution used to describe the cumulative precipitation and on the characteristics of the dataset. In this study, uncertainty analysis for estimation of the hydrologic ...
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Drought monitoring by the Standardized Runoff Index (SRI) presents some uncertainties, mainly dependent on the choice of the probability distribution used to describe the cumulative precipitation and on the characteristics of the dataset. In this study, uncertainty analysis for estimation of the hydrologic drought characteristics (intensity, duration and frequency) was performed. Four distribution functions, two time period (30 and 49 years), six time scales (3, 6, 9, 12, 24 and 48 months) and Latin hyper cube sampling (LHS) method ware used. For each event at per year and month, was generated 50000 random sampling.Then, lower and upper bands of certainty was calculated for confidence level of 95% . In addition to the drought characteristics (intensity, duration and frequency) were calculated for six time scales, four distribution functions and two length of time series . Investigation of the longest duration and highest intensities showed that an increase time scale led to decrease the frequencies of drought classes and as a result increase drought intensity and duration . Further, no significant difference in the assessment of intensity and duration was between various distribution functions, meanwhile significant difference was between normal compared to weibull and gamma for the estimation of drought frequency in short time scales (3 and 6 months). Results of this study emphasized that considering drought intensity and duration, the normal distribution function, 24-month time scale and 30-years’ time series had the largest uncertainty for hydrologic drought estimation.
محمد قبایی سوق; Abolfazl Mosaedi
Abstract
Reconnaissance Drought Index (RDI) is based on fitting a Log-normal distribution to the ratio of precipitation to evapotranspiration (ETo) values in selected periods. In this index value of ETo were calculated based on mean temperature by Thorenth-Waite (Th) method. Th method, may underestimated ETo ...
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Reconnaissance Drought Index (RDI) is based on fitting a Log-normal distribution to the ratio of precipitation to evapotranspiration (ETo) values in selected periods. In this index value of ETo were calculated based on mean temperature by Thorenth-Waite (Th) method. Th method, may underestimated ETo values comparing to the actual in arid and semi arid regions. The log-normal distribution may not be fitted to the ratio of precipitation to ETo values of some regions. In order to investigate the effects of these two limitations on drought situations' changes, meteorological parameters have been used during 50 years period at 8 Synoptic Stations of Iran. In the first step, the values of RDI(Th) for any stations during the mentioned time were calculated. Then, ETo values were calculated from best fitted empirical equation in any situation of lack of parameters. Subsequently RDI(select) index were established. The Kolmogorov–Smirnov (KS) test is used to assess the goodness of fitting most appropriate distribution function to the ratio of precipitation to ETo values. Then, according to equi-probability transformation the values of RDI(Th) were modified to *RDI(Th). The occurrence of different classes of drought according to RDI(select) and/or *RDI(Th) comparing to RDI(Th) showed the elimination of any mentioned limitations may leads to changing the amount of occurrence of any drought classes in RDI(Th). Hence, The RDI(Th) modified to *RDI(select) by estimating ETo values from selected method and applying appropriate distribution function to the ratio of precipitation to ETo values.
