Conventionally, drought analysis has been limited to single drought category. Utilization of models incor- porating multiple drought categories, can relax this limitation. A copula-based model is proposed, which uses meteorological and hydrological drought characteristics to assess drought events for ultimate man- agement of water resources, at small scales, i.e., sub-watersheds. The chosen study area is a sub-basin located at Karkheh watershed (western Iran), with five raingauge stations and one hydrometric station, lo- cated upstream and at the outlet, respectively, which represent 41-year of data. Prior to drought analysis, time series of precipitation and streamflow records are investigated for possible dependency/significant trend. Considering semi-arid nature of the study area, boxplots are utilized to graphically capture the rainy months, which are used to evaluate the degree of correlation between streamflow and precipita- tion records via nonparametric correlations. Time scales of 3- and 12-month are considered, which are used to study vulnerability of early vegetation establishment and long-term ecosystem resilience, respec- tively. Among four common goodness of fit (GOF) tests, Anderson–Darling is found preferable for defining copula distribution functions through GOF measures, i.e., Akaike and Bayesian information criteria and normalized root mean square error. Furthermore, a GOF method is proposed to evaluate the uncertainty associated with different copula models using the concept of entropy. A new bivariate drought modeling approach is proposed through copulas. The proposed index named standardized precipitation-streamflow index (SPSI) unlike common indices which are used in conjunction with station data, can be applied on a regional basis. SPDI is compared with widely applied streamflow drought index (SDI) and standard- ized precipitation index (SPI). To assess the homogeneity of the dependence structure of SPSI regionally, Kendall- τand upper tail coefficient relation is investigated for all stations located within the region. Ac- cording to results, SPSI similar to nonparametric multivariate standardized drought index (NMSDI) was able to detect both onset of droughts dominated by precipitation as is similarly indicated by SPI and persistence of droughts dominated by streamflow as is similarly indicated by SDI. It also captures dis- cordant case of normal period precipitation with dry period streamflow and vice versa. This makes SPSI a powerful tool for estimating a more practical and realistic drought condition. Finally, combination of severity–duration–frequency (SDF) of drought events through copulas resulted in SDF curves that can be used to obtain the recurrence of extreme droughts and assess drought related ecosystem failure or to aid in optimization of water resources allocation. Results indicated that the newly proposed index (SPSI) is able to represent two main characteristics of meteorological and hydrological drought (drought onset and persistency) and also providing an accurate estimation of the recurrence interval of extreme droughts. The procedures can be used to undertake proactive water resource management and planning to assure water security and sustainable agriculture and ecosystem survival for regions experiencing extreme droughts.

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