Severity-duration-frequency Research Articles

Evaluation of CHIRPS in dry and wet spell assessment utilizing copula-based severity–duration–frequency curves

ABSTRACT In situ rainfall data play a significant role in drought assessment studies. However, they are not available with reliable spatiotemporal coverage. With the advancements in satellite rainfall estimates (SREs), monitoring hydrological events in ungauged basins is possible. Additionally, the evaluation of newly released SREs such as CHIRPS, with a long-term record and comparably high resolution (0.05°), in the assessment of extreme hydrological events (dry/wet spells) has scarcely been carried out, which is the most novel motivation of this study. Moreover, evaluation of CHIRPS in developing copula-based multivariate severity–duration–frequency curves based on the severity and duration of the occurred events in 1988–2019 over the Zayandehroud basin (a critical central basin of Iran), is innovatively appraised. An evaluation of CHIRPS in drought assessment shows its acceptable performance, with slight underestimation, in assessing the severity and duration of dry spells. In contrast, an overestimation is identified for wet spells.

Copula-Based Severity–Duration–Frequency (SDF) Analysis of Streamflow Drought in the Source Area of the Yellow River, China

In classical severity–duration–frequency (SDF) analysis, the dependence between drought characteristics is not effectively considered. The present study aims to propose the SDF relationships of streamflow drought in the source area of the Yellow River (SAYR) using a copula-based approach. Comparison of multiple time-varying threshold levels and the integration and elimination of drought events were considered. Selection of marginal probability distribution and copula-based joint probability distribution was properly conducted with multiple means. Copula-based joint and conditional probabilities were computed. The findings support carrying out integration and elimination processing on the preliminarily identified streamflow droughts through a run analysis with a time-varying threshold level of the 80% quantile of daily streamflow. The Gaussian copula was selected as the optimal model for constructing bivariate joint probability distribution, with generalized extreme value and log-normal as the suitable marginal probability distributions of streamflow drought duration and severity. The proposed copula-based SDF relationships of streamflow drought events can provide more critical information in addition to univariate frequency analysis, benefitting from the joint and conditional probabilities. The multivariate probabilistic analyses can effectively consider the connection and interaction between drought characteristics, while conditional probability distribution allows analyzing the impact of one drought characteristic on another. The results also indicate a relatively high risk of streamflow drought with short duration and low severity in the region, requiring effective drought-mitigation strategies and measures.

Development of drought severity–duration–frequency curves for identifying drought proneness in semi-arid regions

AbstractThe effectual estimation of meteorological drought parameters such as severity, duration and frequency to plan suitable drought mitigation measures is challenging owing to the complex relationship among these parameters. The present study endeavored to assess the drought proneness of various districts of chronic drought prone Saurashtra region of Gujarat state (India). The district wise Drought Severity Duration Frequency (DSDF) curves were developed using Standardized Precipitation Evapotranspiration Index (SPEI) based on 40 years (1980 to 2019) data. The monthly drought severities of SPEI for various return periods ranging from 2 to 100 years were estimated by testing 10 probability distributions. The DSDF curves revealed that severe droughts were more prominent for shorter durations and identical severities were observed for 1 to 4 month drought duration for smaller rerun periods. As drought mitigation measures vary according to drought severity and duration, the study employed a novel approach of ranking the districts based on three criteria as proneness to higher severities for longer drought durations, high severities with short drought duration, and low severities with long drought duration. Rather than relying on rainfall or drought index-based judgement, the present study demonstrated the better alternative for drought risk assessment, resilience planning, and mitigation.

Performance evaluation of Standardized Copula‐based Drought Index with Reconnaissance Drought Index and Standardized Precipitation Temperature Index using severity–duration frequency curves over Balochistan, Pakistan

AbstractDrought and aridity are good measures to study climate change that are measured using several indices. In this study, the performance of Standardized Copula‐based Drought Index (SCDI) is compared with Standardized Precipitation Temperature Index (SPTI) and Reconnaissance Drought Index (RDI) for measuring drought in Balochistan province of Pakistan. These standardized drought indices combine the outcomes of De‐Martone Aridity Index (DAI) and UNEP Aridity Index (UAI). SCDI is calculated using probability distributions and copula models that combine the outcomes of UAI and DAI utilizing data of precipitation, potential evapotranspiration (PE), and temperature. Climate data from nine including arid and humid metrological stations are used to study drought conditions in Balochistan province. SCDI outcomes are graphically and numerically compared with SPTI and RDI. Selected drought indices are compared based on frequency of drought and wet events occurred in moderate, severe, and extreme drought categories, which indicate that SCDI has maximum number of events in these categories. It gives better results due to the utilization of more climate data as compared to RDI and SPTI. Severity–duration frequency curves are used to find future projections which shows that drought severity and drought duration have increasing trend with the passage of time. The indices have more differences in results of arid stations. The results indicate that there are no significant chances of drought at lower time scales, but the chances increase with the increase in time scale. The SCDI may also be more useful for agricultural and hydrological droughts due to temperature and PE variables. This study's results will be helpful for climate planning in Balochistan province.

Non-parametric severity-duration-frequency analysis of drought based on satellite-based product and model fusion techniques.

Climate change has increased the severity and frequency of droughts over the last decades. To alleviate the adverse impacts of droughts, an effective planning and management framework requires high-resolution spatiotemporal data. TRMM multi-satellite precipitation analysis (TMPA) dataset provides sufficient accuracy with fine spatio-temporal resolution. However, it only covers a short temporal span, which limits its applicability for drought studies. This paper presents a methodology for efficient and accurate temporal extension of TMPA using four artificial intelligence (AI)-based models. To improve AI-based model precipitation estimations, fusion techniques including Orness, Orlike, and genetic algorithm (GA)-based weighting methods were employed. Results show that fusion approaches provide more accurate estimates of precipitation. Different timescales of n-SPI time series and drought spatial maps were prepared to visually evaluate the performance of long-term TMPA (LT-TMPA) alongside statistical error indices. The results confirm that this dataset is effective for meteorological drought monitoring over southern Iran. Finally, drought risk assessment was carried out to determine the spatiotemporal characteristics of droughts through severity-duration-frequency (SDF) contour maps. In contrast to the traditional SDF curves, SDF contour maps provide a superior understanding of drought for policymakers since they preserve spatial information.

Today’s 100 year droughts in Australia may become the norm by the end of the century

Accumulating evidence on the impact of climate change on droughts, highlights the necessity for developing effective adaptation and mitigation strategies. Changes in future drought risk and severity in Australia are quantified by analyzing nine Coupled Model Intercomparison Project Phase 6 climate models. Historic conditions (1981–2014) and projections for mid-century (2015–2050) and end-century (2051–2100) from four shared socioeconomic pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) are examined. Drought events are identified using both the standardized precipitation index and the standardized precipitation evapotranspiration index. The spatial-temporal evolution of droughts is addressed by quantifying the areal extent of regions under moderate, severe and extreme drought from historic to end-century periods. Drought characteristics derived from the models are used to develop severity–duration–frequency curves using an extreme value analysis method based on ordinary events. Under SSP5-8.5, a tenfold increase in the area subject to extreme droughts is projected by the end of the century, while a twofold increase is projected under SSP1-2.6. Increase in extreme droughts frequency is found to be more pronounced in the southern and western regions of Australia. For example, frequency analysis of 12 month duration droughts for the state of South Australia indicates that, under SSP5-8.5, drought severities currently expected to happen on average only once in 100 years could happen as often as once in 3 years by the end of the century, with a 33 times higher risk (from 1% to 33%), while under SSP1-2.6, the increase is fivefold (1%–5%). The significant difference in the increase of drought risk between the two extreme scenarios highlights the urge to reduce greenhouse gases emission in order to avoid extreme drought conditions to become the norm by the end of the century.

Assessment of the hydrological drought risk in Calgary, Canada using weekly river flows of the past millennium

Abstract Planning and management of water resource infrastructure requires a depth of knowledge on the characteristics of hydrological extremes, floods and droughts. Infrastructure design is traditionally based upon historically observed extreme events, assuming that they are independent and identically distributed (i.i.d.) and stationary, i.e. they fluctuate within a fixed envelope of variability. Information on historical hydroclimate provides a limited range of hydrological extremes, which rarely includes long-term worst droughts. This study demonstrates the application of a paleo-environmental dataset, 900 years of weekly streamflow stochastically derived from a tree-ring reconstruction of annual streamflow, to assess the hydrological drought risk. The historic and prehistoric hydrological drought characteristics, i.e. severity–duration–frequency (SDF) relationships, are evaluated. The results indicate that the severity and duration of hydrological drought with the same recurrence interval is substantially larger and longer than those observed over the 100-year historical period. Historic and prehistoric drought SDF relationships established in this study demonstrate the implications of non-stationary climate in the analysis of extreme droughts. Therefore, projected droughts of the 21st century may not exceed the drought severity found in the prehistoric record to the same extent that they exceed historical droughts in the instrumental record. This study emphasizes the importance of paleohydrology in comprehending the region's drought.

Development of flow-duration-frequency curves for episodic low streamflow

In water resources management and practices, the time-connected duration and frequency of episodic low streamflow events (and droughts) are often needed for a range of purposes such as water supply planning, low flow management, and drought planning. However, the existing graphical tools commonly used in hydrology such as flow duration curves (FDC), discharge-duration-frequency (QdF), and severity-duration-frequency (SDF) curves, often do not provide this information. In this study, we contribute an approach to develop a flow-duration-frequency (FDF) curve by fitting the exponential function to graphically show the time-connected duration and frequency of episodic low streamflow events. The FDF fitting is comprehensively tested with a bootstrap resampling experiment using long-term continuous streamflow records for 92 USGS gages located in the state of Illinois, U.S.A. The experiment results reveal that the proposed methodology can reasonably develop FDF curves for episodic low streamflow events. The results demonstrate that the FDF fitting is improved by using longer streamflow record though the improvement appears to level off with 30 years or longer streamflow records. The results also confirm that the FDF fitting is more reliable for higher streamflow threshold to define episodic low streamflow events.

Regional analysis of drought severity‐duration‐frequency and severity‐area‐frequency curves in the Godavari River Basin, India

AbstractIndia is one of the most drought‐ravaged countries in the world and faces at least one drought in one region or another in every 3 years. There is no single reliable approach in characterizing future droughts. To understand future drought risk, potential changes of drought properties and characteristics are analysed in this study. Using Fuzzy c‐means clustering approach, homogeneous drought regions are identified in the Godavari river basin and therefore, optimum number of clusters were assigned as four. The 12‐month standardized precipitation index (SPI) using precipitation data from India Meteorological Department (IMD) and Global Climate Model (GCM)—MIROC‐ESM‐CHEM is calculated for the homogeneous regions of the Godavari basin. The best fit copula for observed and simulated severity and duration are: Region 1—Clayton, Regions 2 and 3—Gumbel, Region 4—Frank copula. Severity‐duration‐frequency (SDF) and severity‐area‐frequency (SAF) curves were developed and analysed using the best fit copulas. The research findings conclude that moderate and severe droughts are frequently increasing for future periods (2006–2099) compared to the historic period (1962–2005). Droughts with high severity and high mean interarrival time are observed as expected in the future. For the Godavari basin, the SDF curves were concave upwards indicating an increase in severity with an increase in duration. The rate of increase of severity is small for shorter durations compared to that of longer‐duration drought. Thus, more prolonged drought events in the 21st century are likely to occur. The SAF curves with steeper slopes and high variability in topographical and hydrological characteristics have been observed over the Godavari basin. From these curves, for a specified percentage of area and return period, the drought severity can be calculated and the information can be used for crop management and agricultural water demands. Overall, the findings of this research offer a view of likely scenarios of drought in the Godavari basin.

Future drought analysis using SPI and EDDI to consider climate change in South Korea

Abstract Prediction of drought is important for efficient water management, as the occurrence of droughts affects large areas over a long period. According to various climate change scenarios, it is reported that in the future, Korea's climate is likely to increase in temperature with increasing rainfall. This increase in temperature will have a big impact on evapotranspiration. The occurrence of drought begins mainly with two causes: lack of rainfall or an increase in evapotranspiration. Therefore, in this study, the impact of climate change on future droughts is revealed through the Standardized Precipitation Index (SPI) and the Evaporative Demand Drought Index (EDDI). These two drought indices with different characteristics are used to examine the trend of future drought, and a drought Severity-Duration-Frequency (SDF) curve was derived to quantitatively analyze the depth of future drought. Future droughts are projected by applying future climate data generated from various climate models.

On the rarity of the 2015 drought in India: A country-wide drought atlas using the multivariate standardized drought index and copula-based severity-duration-frequency curves

Study regionThe study is conducted over 30 meteorological sub-divisions of India. Study focusThe Multivariate Standardized Drought Index (MSDI) is employed to analyze the drought conditions caused by simultaneous precipitation and soil moisture deficiencies. The Severity-Duration-Frequency (SDF) relationships for the 30 sub-divisions are derived using copula-based conditional distribution for duration and severity; which are further used to prepare the country-wide drought atlas for different return periods. Subsequently, the developed atlas is used to assess the spatial extent and historical context of the impactful 2015 drought event. New hydrological insights for the regionThis is the first study to present a country-wide drought atlas for India, considering concurrent deficits in precipitation and soil moisture, and using copula-based SDF relationships. In general, drought characteristics such as severity and duration are found to be significantly correlated, highlighting the importance of their joint modeling for probabilistic risk assessment of droughts in India. The drought atlas reveals regions that are severely affected by the drought variability. The drought atlas developed here shows that the impactful 2015 drought event was severely deficient both in terms of precipitation and soil moisture. In particular, West Uttar Pradesh, East Uttar Pradesh, Jharkhand, Marathwada, Telangana and North Interior Karnataka sub-divisions are found to be under a very rare drought (probability of exceedance less than 10 %).

Spatio-temporal analysis of maximum drought severity using Copulas in Northern Algeria

Abstract Drought mitigation and prevention require a broader knowledge of the spatio-temporal characteristics and return periods of droughts over several years. In this research, drought characteristics (severity, duration, frequency and areal extent) have been analysed in northern Algeria by using the Standardized Precipitation Index to identify drought events from 194 precipitation stations. For frequency analysis, three Archimedean copula families were used to find a relationship between drought duration and severity. The severity–duration–frequency (SDF) and the severity–area–frequency (SAF) curves were obtained. The SDF and SAF curves are then used to build three-dimensional surfaces of drought severity, drought duration and cumulated percentage of the affected area (SDA) for each return period. It has been shown that the return periods of maximum drought events severity vary according to their durations. To address the issue of long-term droughts, a new classification of dry events based on drought severities is proposed. The obtained results show that the western part of Algeria is the most sensitive to severe/extreme droughts of short durations and high probabilities of exceedance. For long-term durations, the study area was sensitive to mild droughts with lower probabilities.

Two Ways to Quantify Korean Drought Frequency: Partial Duration Series and Bivariate Exponential Distribution, and Application to Climate Change

Studies using drought index to examine return levels of drought can be classified into two approaches: univariate frequency analysis using annual series extracted from drought index time series and multivariate frequency analysis that simultaneously reflects various characteristics of drought. In the case of drought analysis, it is important to properly consider the duration, so, in this study, univariate frequency analysis is performed using the partial duration series. In addition, a bivariate frequency analysis is performed using a relatively simple bivariate exponential distribution to give a more realistic return level to major drought events in the past while reflecting the correlation between drought severities and durations. The drought severity–duration–frequency curves using each of the two frequency analyses are derived, and these curves are used to examine how the drought phenomenon currently in progress is evolving. From this, the advantages and disadvantages of the two approaches, as well as the points to be aware of in application, are discussed. Finally, using the two approaches to the proposed drought frequency analysis, the behavior of Korea’s future extreme droughts is investigated under the conditions of various future climate change scenarios.

Drought hotspot analysis and risk assessment using probabilistic drought monitoring and severity–duration–frequency analysis

AbstractDrought hotspot identification requires continuous drought monitoring and spatial risk assessment. The present study analysed drought events in the agriculture‐dominated mid‐Mahanadi River Basin in Odisha, India, using crop water stress as a drought indicator. This drought index incorporated different factors that affect crop water deficit such as the cropping pattern, soil characteristics, and surface soil moisture. The drought monitoring framework utilized a relevance vector machine model‐based classification that provided the uncertainty associated with drought categorization. Using the proposed framework, drought hotspots are identified in the study region and compared with indices based on precipitation and soil moisture. Further, a bivariate copula is employed to model the agricultural drought characteristics and develop the drought severity–duration–frequency (S–D–F) relationships. The drought hotspot maps and S–D–F curves are developed for different locations in the region. These provided useful information on the site‐specific drought patterns and the characteristics of the devastating droughts of 2002 and 2012, characterized by an average drought duration of 7 months at several locations. The site‐specific risk of short‐ and long‐term agricultural droughts are then investigated using the conditional copula. The results suggest that the conditional return periods and the S–D–F curves are valuable tools to assess the spatial variability of drought risk in the region.

Analysis of streamflow droughts using fixed and variable thresholds

AbstractHydrological drought analysis is very important in the design of hydrotechnical projects and water resources management and planning. In this study, a methodology is proposed for the analysis of streamflow droughts using the threshold level approach. The method has been applied to Yermasoyia semiarid basin in Cyprus based on 30‐year daily discharge data. Severity was defined as the accumulated water deficit volume occurring during a drought event, in respect with a target threshold. Fixed and variable thresholds (seasonal, monthly, and daily) were employed to derive the drought characteristics. The threshold levels were determined based on the Q50 percentiles of flow extracted from the corresponding flow duration curves for each threshold. The aim is to investigate the sensitivity of these thresholds in the estimation of maximum drought severities for various return periods and the derivation of severity–duration–frequency curves. The block maxima and the peaks over threshold approaches were used to perform the extreme value analysis. Three pooling procedures (moving average, interevent time criterion, and interevent time and volume criterion) were employed to remove the dependent and minor droughts. The application showed that the interevent time and volume criterion is the most unbiased pooling method. Therefore, it was selected to estimate the drought characteristics. The results of this study indicate that monthly and daily variable thresholds are able to capture abnormal drought events that occur during the whole hydrological year whereas the other two, only the severe ones. They are also more sensitive in the estimation of maximum drought severities and the derivation of the curves because they incorporate better the effect of drought durations.

The Construction and Comparison of Regional Drought Severity-Duration-Frequency Curves in Two Colombian River Basins—Study of the Sumapaz and Lebrija Basins

Accurate classification of drought-severity is one of the most challenging issues in designing regional monitoring and control plans, especially in developing countries, where resources are scarce and must be carefully optimized to maximize social benefit. Typically, drought assessment is performed using drought indices which enable the interpretation of complex climatic information series for operational purposes. Frequency analyses are also useful for estimating future occurrence probabilities, even on regional scales. This study generated regional Severity-Duration-Frequency (SDF) curves for two Colombian catchments (Sumapaz and Lebrija River Basins), and 7 index-calculation procedures. First, the relationships between the two catchments were analyzed to obtain differences between drought indices. Second, the consistency among the indices that identified the same drought types for each region was evaluated. Finally, historical regional drought occurrences were selected, characterized, and located in local SDF curves to determine their gravity. It was concluded that (i) curves for the same indices displayed similar behavior, when comparing the two case studies; (ii) a certain degree of consistency existed in regional curves, which identify the same drought types (meteorological and agricultural droughts being the most coherent); (iii) meteorological drought regional events, identified through different drought-indices methodologies, were the most common for both case studies, followed by agricultural droughts and hydrological droughts; (iv) when analyzing occurrences with higher return periods, there is coherence when using different methodologies; and (v) identified historical events, which are located on larger return period zones of SDF curves (around 10, 25, and 50 years), had large impacts on regional socio-economic issues. Hence, it was possible to confirm that regional SDF curves could become potentially useful tools for the prioritization of drought-vulnerable zones.

Developing Short Term Drought Severity-Duration-Frequency Curves for Kerala Meteorological Subdivision, India Using Bivariate Copulas

Severity-duration-frequency (S-D-F) curve is a useful hydrological tool for drought mitigation. This paper presents a bivariate copula approach for developing SDF relationships for Kerala meteorological subdivision, India based on the three month standardized precipitation index (SPI-3). First the univariate models were developed considering Gamma and Weibull distributions to represent the probability of severity and duration of SPI-3 series of the subdivision prepared from the area weighted precipitation data. The joint association of these drought variables is modeled by three Archimedean copulas namely Clayton, Frank and Gumbel- Hougaard (GH). The results showed that the difference between the joint SDF relations with the type of copulas is marginal upto return period 100 (∼) whereas the conditional dependency of drought variables showed distinct differences. The conditional SDF relationships between severity and return period showed larger differences for longer duration and the behaviour is identical in the relationships between duration and return period for conditional severity values. Further, to outline the spatial variability of short term drought, a detailed examination on SDF relations of different districts in Kerala is made by considering representative fine resolution gridded rainfall (0.25° × 0.25°) datasets. SDF relationships of different locations in Kerala showed a shorter duration drought of less severity magnitude is prominent in districts like Wayanad, Kottayam and Pathanamthitta. The highest value of equilibrium severity for longer drought duration for all return periods is noticed for Palakkad while lowest value is observed for the district of Wayanad, which are the two low rainfall regions of the subdivision.

Comparing Threshold Level Methods in Development of Stream Flow Drought Severity-Duration-Frequency Curves

This study compares Severity-Duration-Frequency (SDF) curves (SDFs) of stream flow drought derived from threshold level methods. For this purpose hydrological drought of Roudzard river basin was investigated, based on run theory. Daily runoff data of Mashin hydrometery station (1970–2012) assessed using 70% (Q70), 90% (Q90) of mean daily and 70% of monthly average runoff (monthly) as threshold level methods. Time series of the annual maxima values of duration and volume deficit showed similar trend of increase and decreasing in different thresholds. SDFs were prepared, classifying drought durations to four intervals and fitting statistical distribution to each one. Resulted SDFs showed that, in each period, increasing of duration resulted to increased value of the volume deficit with a non-linear trend while duration and severities from the threshold levels were different. Drought deficit-volume increasing rate was also different in each class of duration-interval. For the additional analysis, the duration-frequency and deficit-frequency curves were also prepared to quantify the extent of drought duration and deficit more. SDFs developed in this study can be used to quantify water deficit for natural stream and reservoir. They could be an effective tool to identify multivariate hydrological drought using severity, duration and frequency.

Integrated meteorological and hydrological drought model: A management tool for proactive water resources planning of semi-arid regions

Conventionally, drought analysis has been limited to single drought category. Utilization of models incorporating 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 management 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, located 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 precipitation 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, respectively. 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 standardized precipitation index (SPI). To assess the homogeneity of the dependence structure of SPSI regionally, Kendall-τ and upper tail coefficient relation is investigated for all stations located within the region. According 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 discordant 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.

Preparing stream flow drought severity–duration–frequency curves using threshold level method

Drought is a natural phenomenon which occurs in different climate regimes. In the present study, hydrological drought of the Roud Zard basin has been investigated based on run theory. Daily runoff data of Mashin hydrometery station during 1970 to 2012 was assessed using 70 % of mean daily runoff as threshold level. Results showed that the maximum drought duration of 309 days occurred in 1998 and 1999 and max drought deficit of 117.217 million cubic meters per second in 1983 with 275 days duration. Time series of the annual maxima values of duration and volume deficit showed similar trend of increase and decreasing. Burr statistical distribution, as the most suitable one fitted to the drought duration data, forecasted 339 days duration for drought event with 20 years return period and generalized extreme value forecasted 37.9 million cubic meters of deficit volume for this return period. Severity-duration-frequency (SDF) curves were prepared, classifying drought durations to four intervals and fitting statistical distribution to each. Resulted SDF curves showed that, in each period, increase of duration resulted in increased value of the volume deficit with a non-linear trend, though predicted drought volume with 20 years return period was 2.1 million cubic meters for 1 to 10 days duration, 6.9 for 11 to 30 days, 34.5 for 31 to 120 days, and 79.1 for more than 120 days duration drought event. Drought deficit volume increasing rate was also different in each class of duration interval. Drought SDF curves derived in this study can be used to quantify water deficit for natural stream and reservoir. SDFs could also be extended to allow for drought regional frequency analysis to be used in ungauged sites.