For evaluating the severity of drought of a certain year and/or month, four indices of cumulative precipitation deficit (CPD), relative cumulative precipitation deficit (RCPD), maximum precipitation deficit (MPD) and relative maximum precipitation deficit (RMPD) are used such that a regional frequency analysis has been carried out by L-moments for CPD and MPD. These measures of drought are strongly related to moisture deficits for the vegetation during the growing season. In this thesis, eleven synoptic stations in Isfahan province, Iran with a semi-arid environment have been used that those have minimum 10 years data and the mentioned drought indices calculated for all of them. WeatherMan tool is used for completing the data series that had missing data. FAO Penman-Monteith (FAO-PM) is used for calculating reference evapotrairation (ET (FAO-PM) ) that according to the previous studies, this method is suitable for this region. Hargreaves method is used for calculating reference evapotrairation (ET (H) ) for the days that only maximum and minimum temperatures are available. An artificial neural network (ANN) is used to convert ET (H) to ET (FAO-PM) . Hosking homogeneity test is applied for identifying a homogeneous region. Hosking goodness of fit test is performed for selecting the best regional distribution. The results show that, Ardestan, Khoor-biabanak and Naeen stations have the most severity drought and the maximum intensity of drought in all of the stations happens in the months 6 to 8 which are in late spring to mid-summer. Also, Generalized Logistic (GL) for the two of the yearly drought indices is selected as the best regional distribution. Therefore, severity of drought with various return periods is estimated for CPD and MPD using GL. Using the outcome of this study, required water volume for agriculture can be determined in this province. For determining dry and wet period in the stations under study, standarded state of 4 indices CPD, MPD, RCPD and RMPD are used and for integrating 4 standarded indices, a mean index is developed. These indices compared to SPI. The Results show that new indeices are more accurate than SPI and in detecting drought period are more sensitive and effective. These indices well detect drought of years 1999 to 2001 whereas SPI does not. According to the results of this study, using of these new indices are recommended in Isfahan province. Keyword: New Drought Index, Regional Frequency Analysis, Lmoment, Isfahan Province