Hydrological Drought Assessment Research Articles

Hydrological drought assessment in Aksu River basin

Based on the monthly stream flow date of three representative hydrological stations, in the Aksu River basin during the period of 1957-2010, i.e., ShaliGuilanke station, XieHela station and XiDaqiao station, this paper calculates river inflow anomaly index and stream flow drought index (SDI). The simulation results of these two indexes were compared and the results showed that the SDI could reflect the drought situation better. Runs theory was used to analyse the SDI, getting the drought duration and droughts intensity in Aksu River basin. The results indicate that drought in Aksu River basin occurs mainly in spring (March-May). During 1957-2010, drought occurred 50 times, approximately once per year, with an average interval time of eight to nine months. After the 1990s, drought duration became shorter and intensity decreased in ShaliGuilanke station and Xi Daqiao station, but drought risk frequency and drought intensity became larger. Drought situation is increasingly grim in XiDaqiao station of China.

Comparison of two hydrological drought indices

Summary Drought is a naturally occurring periodical event associated with significant decrease of water availability over a region. Drought, being a complex in nature it is difficult to define, quantify and monitor. Drought is mainly classified into meteorological drought, hydrological drought and agricultural drought. Among these classifications, assessment of hydrological drought has more importance in the water resources management perspective. Objective of this study is to analyse multi-time step hydrological drought by Stream flow Drought Index (SDI) and Standardized Runoff Index (SRI). To obtain these indices, 36 years (1972–2007) of daily discharge data, measured in Ghataprabha river basin (a sub basin of Krishna river) is considered. Results of both indices indicate moderate drought between 1986–1988 and 2001–2005 continuously. While comparing both indices, there is a good correlation between 9-month SRI and SDI is observed and it increases for 12-month SRI and SDI. This study may help to choose the appropriate drought indices among SRI and SDI for different lengths of drought studies.

Uncertainties in assessing hydrological drought using streamflow drought index for the upper Yangtze River basin

Drought is an environmental disaster which is frequently and world-widely occurred in recent years. Precisely assessment and prediction of drought is important for water resources planning and management. Sampling uncertainty commonly exists in frequency analysis-based hydrological drought assessment due to the limited length of observed data series. Based on the daily streamflow data of the Yichang hydrological station from 1882 to 2009, the streamflow drought index (SDI) series with 12-month time scale was calculated and the hydrological drought of the upper Yangtze River was assessed. By employing the bootstrap method, the impact of sample size on the sampling uncertainty of the SDI was analyzed. The longer record is used to derive the SDI, the narrower the shifting ranges of the parameters of the streamflow volume probability distribution functions and corresponding interval estimators of SDI are. The upper Yangtze River basin has experienced successive alternation of wet and dry years, and the spring seems to be the driest season within a year. The current difficulty in fighting against increasing droughts in upper Yangtze River basin is upgrading. Considering the possible misjudgment of drought degree results from the sampling uncertainty, attention should be paid to the preparation of drought relief strategies in order to reduce the potential losses.

Assessment of the Impact of Climate Change on Hydrological Drought in Lake Tana Catchment, Blue Nile Basin, Ethiopia

Droughts are common natural phenomenon in Ethiopia which has been affecting food insecurity and imposing other complex problems. Severe droughts happened once every 10 years in the north and north east Ethiopia, now becoming more frequent and covering areas that never experience drought before, in the southern parts of the country. According to IPCC droughts will become more intense, frequent and severe in the future due to the impact of climate change. This thesis presents the assessment of projected impact of climate change on hydrological drought in the Lake Tana basin in Ethiopia, which is the headwater for the Blue Nile River. The rainfall-runoff HBV model was calibrated and validated against historical data to obtain a reference situation to the possible impact of climate change on hydrological drought in four sub-basins and the Lake Tana basin. Datasets obtained from the EU- ATCH project for three General Circulation Models (CNCM3, IPSL and ECHAM) were used as an input to the HBV model, which was recalibrated for the same historic period to obtain an assessment to what local downscaled, bias-corrected GCM can be used as a forcing data for hydrological drought assessment. Next the GCM outputs with the recalibrated HBV model were used to simulate future streamflow for two future time windows (2021-2050 and 2071-2100) and for one future emission scenario A2. The variable threshold level method combined with a 10-day moving average streamflow was used to detect hydrological drought characteristics.

Hydrological Drought Assessment in Northwestern Iran Based on Streamflow Drought Index (SDI)

Drought is a natural and worldwide phenomenon that occurs when water availability is significantly below normal levels during a significant period of time and cannot meet demand. This work focused on the hydrologic drought defined by the streamflow drought index (SDI) for overlapping periods of 3, 6, 9 and 12 months at 14 hydrometric stations in the northwest of Iran over the period 1975–2009. It was found that some of the streamflow volume series did not follow the normal distribution. The ability of the log-normal, exponential and uniform probability distributions was examined in order to choose the most suitable distribution, and the log-normal distribution was used to fit the long-term streamflow data. The results of the hydrological drought analysis based on the SDI showed that almost all the stations suffered from extreme droughts during the study period. Additionally, extreme droughts occurred most frequently in the last 12 years from 1997–1998 to 2008–2009.

A Water Balance Derived Drought Index for Pinios River Basin, Greece

This study estimates hydrological drought characteristics using a water balance derived drought index in Pinios river basin, Thessaly, Greece. The concept of hydrological management at subwatershed scale has been adopted because it encompasses the areal extent of a drought event. Fourteen (14) sub-watersheds of Pinios river basin were delineated according to the major tributaries of Pinios river using GIS. For the assessment of hydrological drought, because none of the sub-watersheds have flow gauge stations at their outlets, a six-parameter monthly conceptual water balance model (UTHBAL model), has been applied regionally to simulate runoff for the period October 1960–September 2002. The synthetic runoff was normalized through Box-Cox transformation and standardized to the mean runoff to produce the water balance derived drought index for hydrological drought assessment. The standardized precipitation index (SPI) at multiple time scales and four indices of the Palmer method (i.e. PDSI, WPLM, PHDI and the Palmer moisture anomaly Z-index) were also calculated to assess hydrological droughts. The results showed that the water balance derived drought index is a good indicator of hydrological drought in all sub-watersheds, since is capable to quantify drought severity and duration. Furthermore, the drought index provides guidance on the selection of an appropriate meteorological drought index for operational hydrological drought monitoring. Hence, SPI at 3- and 6-month timescales and the WPLM could be used along with the water balance derived drought index in risk and decision analyses at the study area.

Assessment of Hydrological Drought Revisited

A variety of indices for characterising hydrological drought have been devised which, in general, are data demanding and computationally intensive. On the contrary, for meteorological droughts very simple and effective indices such as the Standardised Precipitation Index (SPI) have been used. A methodology for characterising the severity of hydrological droughts is proposed which uses an index analogous to SPI, the Streamflow Drought Index (SDI). Cumulative streamflow is used for overlapping periods of 3, 6, 9 and 12 months within each hydrological year. Drought states are defined which form a non-stationary Markov chain. Prediction of hydrological drought based on precipitation is also investigated. The methodology is validated using reliable data from the Evinos river basin (Greece). It can be easily applied within a Drought Watch System in river basins with significant storage works and can cope with the lack of streamflow data.