Reconnaissance Drought Index Research Articles

Monitoring environmental water stress in the Upper Ewaso Ngiro river basin, Kenya

This study provides a new methodology for simulating environmental water stress index (EWSI) that addresses environmental droughts' stochastic nature at regional and local scales. The current research used a case study of the Upper Ewaso Ngiro river basin in Kenya that possesses regional disparities attributed to climatic, biophysical, and anthropogenic variables. A stochastic modelling approach that ensembled 4D Euclidean feature space algorithm, least-squares adjustment, and iterations integrated the four environmental droughts indicators (meteorological, agricultural, socio-economic, and hydrological) into a single multivariate index called EWSI. The correlation between the simulated EWSI and initial reconnaissance drought index (RDIα) produced a correlation coefficient (r) of −0.93 and a p-value < 0.02. The correlation between EWSI and river discharge had a correlation coefficient of −0.89 and a p-value < 0.02. The assessment of severity revealed that 67–100% of the basin exhibited moderate to extreme environmental water stresses conditions between 1986 and 2018.

Linking Drought Intensity with Rice Yield in Nagaland

Background: Rainfall being one of the most important factors of production for rainfed kharif rice, occurrence of drought may have serious implication on rice yield. Hence, this study is an attempt to understand the linkage between drought and yield of rice in Phek and Dimapur district of Nagaland where rice is the primary crop. Methods: Reconnaissance Drought Index was calculated using gridded daily rainfall (0.25o X 0.25o) and temperature (1o X 1o) (o=degree) data for the year of 1975-2013.Result: The annual mean temperature has increased by 0.03oC in Phek and Dimapur district during the study period. The increasing linear trends for annual temperatures are significant whereas, the linear trend for annual rainfall shows decreasing but insignificant trend. About 38.46% and 41.02% of the 39 years under study were ‘Normal condition-dry’ in Phek in Dimapur district, respectively. Moderate and severe drought occurred more frequently in Dimapur than Phek. After 1994, majority of the years were drought years and the frequency of occurrence was higher in Dimapur. The drought occurrences negatively impacted the rice yields and the rice yield may reduce by 13.85% in normal condition dry to 18.45% in extreme drought condition.

Projection of Future Drought Characteristics under Multiple Drought Indices

Drought is a natural phenomenon caused by the variability of climate. This study was conducted in the Songhua River Basin of China. The drought events were estimated by using the Reconnaissance Drought Index (RDI) and Standardized Precipitation Index (SPI) which are based on precipitation (P) and potential evapotranspiration (PET) data. Furthermore, drought characteristics were identified for the assessment of drought trends in the study area. Short term (3 months) and long term (12 months) projected meteorological droughts were identified by using these drought indices. Future climate precipitation and temperature time series data (2021–2099) of various Representative Concentration Pathways (RCPs) were estimated by using outputs of the Global Circulation Model downscaled with a statistical methodology. The results showed that RCP 4.5 have a greater number of moderate drought events as compared to RCP 2.6 and RCP 8.5. Moreover, it was also noted that RCP 8.5 (40 events) and RCP 4.5 (38 events) showed a higher number of severe droughts on 12-month drought analysis in the study area. A severe drought conditions projected between 2073 and 2076 with drought severity (DS-1.66) and drought intensity (DI-0.42) while extreme drying trends were projected between 2097 and 2099 with drought severity (DS-1.85) and drought intensity (DI-0.62). It was also observed that Precipitation Decile predicted a greater number of years under deficit conditions under RCP 2.6. Overall results revealed that more severe droughts are expected to occur during the late phase (2050–2099) by using RDI and SPI. A comparative analysis of 3- and 12-month drying trends showed that RDI is prevailing during the 12-month drought analysis while almost both drought indices (RDI and SPI) indicated same behavior of drought identification at 3-month drought analysis between 2021 and 2099 in the research area. The results of study will help to evaluate the risk of future drought in the study area and be beneficial for the researcher to make an appropriate mitigation strategy.

Changes in climatic patterns and tourism and their concomitant effect on drinking water transfers into the region of South Aegean, Greece.

Global warming is already having a negative impact on vital sectors on which human development depends, such as water resource availability. In this study, the changes and abrupt change timing of climatic extreme indices, aridity and drought over the Region of South Aegean are captured using the Mann–Kendall and Pettitt tests, while the latter variables are correlated with the water volume transported by ships to the region as well as the relevant costs. The region's climate is shifting to warmer conditions with less precipitation, since significantly positive trends were noted with regard to the number of tropical nights, warm nights, warm days, the warm spell duration index and the diurnal temperature range; significant negative trends were observed in relation to the number of cool nights, cool days and the cold spell duration index, with the change-point year for the latter variables being 2006. Inaddition, 7/11 precipitation related indices exhibited a downward trend, while significantly negative trends were observed with regard to the number of consecutive dry days, with the timing of the abrupt change being 2001. The Aridity Index (AI) reveals that the region’s climate characterization is changing from dry and sub-humid to semi-arid conditions, whilst the Reconnaissance Drought Index standardized (RDIst) and the Standardized Precipitation Index (SPI) indices suggests an amplification of drought phenomena over the Region. The tourism variables illustrated a significant positive trend, with the timing of the abrupt change being registered during 2006–2009, whilst the correlation analysis between tourism variables and water transfers implies that the surge on water transfer by ships to the Region occurred between 1998 and 2008. This can be mainly attributed to the changes in climate patterns. The correlation analysis documents a strong positive correlation between the water transfer dataset and the diurnal temperature range, and a moderately negative association with the precipitation related indices, annual precipitation, drought phenomena and aridity with 7/11.

Accuracy Assessment of the SPEI, RDI and SPI Drought Indices in Regions of Iran with Different Climate Conditions

Considering the impact of drought on agricultural products and human food security, the selection of the appropriate drought index to assess drought conditions is very important. Therefore, in this research, based on the relationship between the percent annual yield loss (AYL) of winter wheat (Triticum sativum) and three commonly used drought indices, i.e. Standardized Precipitation Evapotranspiration Index (SPEI), Reconnaissance Drought Index (RDI) and Standardized Precipitation Index (SPI), the accuracy of these indices was evaluated at 1-, 3-, 6- and 12-month time scales. Results showed that the average AYL at Ahvaz, Babolsar, Esfahan, Gorgan, Kerman, Mashhad, Ramsar, Rasht, Shiraz and Zabol was 66.64, 5.42, 97.52, 10.20, 98.57, 84.99, 2.47, 3.84, 77.03 and 97.07%, respectively. At stations with hyper-arid, semi-arid, Mediterranean, humid and hyper-humid type A climate conditions such as Zabol, Esfahan, Mashhad, Shiraz, Gorgan, Babolsar, Ramsar and Rasht stations, the calculated values of SPEI demonstrated the highest CC with AYL in winter wheat. At Kerman and Ahvaz, with arid climate conditions, the calculated values of the RDI had the greatest CC with AYL in winter wheat. Thus, in general, among the SPI, RDI and SPEI, the use of the SPEI is recommended for the assessment of drought characteristics.

Spatio\u2010temporal characteristics of meteorological drought under changing climate in semi\u2010arid region of northern Ethiopia

BackgroundBelow-normal availability of water for a considerable period of time induces occurrence of drought. This paper investigates the Spatio-temporal characteristics of meteorological drought under changing climate. The climate change was analyzed using delta based statistical downscaling approach of RCP 4.5 and RCP 8.5 in R software packages. The meteorological drought was assessed using the Reconnaissance Drought Index (RDI).ResultsThe result of climate change projections showed that the average annual minimum temperature will be increased by about 0.8–2.9 °C. The mean annual maximum temperature will be also increased by 0.9–3.75 °C. The rainfall projection generally showed an increasing trend, it exhibited an average annual increase of 3.5–13.4 % over the study area. The projected drought events reached its maximum severity indicated extreme drought in the years 2043, 2044, 2073, and 2074. The RDI value shows drought will occurred after 1–6 and 2–7 years under RCP 4.5 and RCP 8.5 emission scenarios respectively over the study area. Almost more than 72 % of the current and future spatial coverage of drought in the study area will be affected by extreme drought, 22.3 % severely and 5.57 % also moderate drought.ConclusionsTherefore, the study helps to provide useful information for policy decision makers to implement different adaptation and mitigation measures of drought in the region.

Hydro-meteorological drought in Addis Ababa: A characterization study

Drought is one of the most natural hazards that cause damage to ecosystems, agricultural production, and water resources. This study has analyzed seasonal and annual rainfall trends using monthly data series of 33 years (1983–2015) in Addis Ababa city over three stations namely; Sendafa, Bole, and Observation. Here, we examined the occurrence of historical drought trends in the study jurisdiction. The Reconnaissance Drought Index (RDI) and the Standardized Precipitation Index (SPI) were employed to find long-term drought trends as well as to examine the occurrence of drought history at a longer duration. The analysis indicated that severe drought conditions were observed for SPI and RDI indices in the year 2013 for Bole station, while medium droughts were recorded for the years 1991 and 2002 for all stations. Similarly, the RDI indices for 1996 was recorded as severe drought for the Observatory station. On the other hand, higher variability (coefficient of variation) of rainfall during winter seasons were 95.8%, 95.9%, and 77.9% for Sendafa, Bole, and Observatory stations respectively. However, the lower coefficient of variation during annual rainfall was 15.59% for Sendafa, 14.38% for Bole, and 13.98% for the Observatory station. Furthermore, the drought severity classification for the long-term drought analysis of annual precipitation shows that 3% of severe drought, 12% of moderate drought, and 85% of the normal condition were recorded in Bole station. The severe and moderate drought indices due to the reduction of rainfall, temperature change, and other factors can cause a shortage of urban water supply. Thus, the results of this study will help the water sector professionals in forecasting weather variations and for better management of urban water resources.

Spatiotemporal investigation of drought pattern in Iran via statistical analysis and GIS technique

Drought monitoring is very important for water resource planning due to the impact of climate change on the frequency of drought events. The objective of this study was to evaluate the spatiotemporal characteristics of drought in Iran. Spatial and temporal distributions of drought severity were assessed using the well-accepted standardized reconnaissance drought index (RDIst) in seasonal and annual scales in 40 synoptic meteorological stations of Iran during the years 1967–2014. Parametric and nonparametric statistical tests were further used for trend assessments. According to the results of RDIst on an annual time scale, the trends of drought were positive in 87.5% of the stations. The results of seasonal RDIst also indicated that the trends of drought in winter (92.5%), spring (82.5%), summer (37.5%), and fall (67.5%) were upward. In sequence series of all seasons, 90% of all stations had a negative trend in the value of their calculated RDIst over time, which means an upward trend in drought over time. Our findings demonstrated an upward trend in drought over the study period. In 45% of the studied stations, winter had the most significant positive trend at all time scales. The results also showed that a moderate drought covered the highest portion of the study area. Generally, a positive trend was observed in coverage of extreme, severe, and moderate drought. However, a negative trend was evident in the coverage of extreme, severe, and moderate wet conditions during the time. It is suggested that the spatiotemporal distribution of the RDIst trend can be used to identify drought and mitigate its impacts in Iran.

Spatio-temporal analysis of drought variability in central Ethiopia

Abstract Drought is a major problem in Ethiopia and particularly affects the agricultural and water sectors. This paper aims to assess the spatial and temporal drought variability of central Ethiopia. For this purpose, archival rainfall data recorded from 1989 to 2017 and the Gurage zone topographic maps were used. The five stations’ Standardized Precipitation Index (SPI) were combined with the geographical information system (GIS) to analyze the spatial distribution of drought events. The results show that a total number of 41 drought events were recorded in the region. The number of drought events reaches its maximum value in the year 1992, whereas Bui and Koshe contain the most frequent drought events. The spatial analysis of droughts verifies that most of the frequent and extreme events are recorded in the eastern part of the region. The lowland part of Gurage zone is very prone to drought. The grounded spatio-temporal drought risk events analysis has shown a possible threat to the water and rain-fed farming that has a cascading effect on the livelihoods of farmers. Moreover, the drought condition of the region is unpredictable and recurrent. This study recommends further study containing remaining statistical drought indices such as reconnaissance drought and streamflow drought index.

CHARACTERIZATION, FORECASTING AND ASSESSMENT OF AGRICULTURAL DROUGHT IMPACTS IN THE SUDANO-SAHELIAN CLIMATE OF GOURMA PROVINCE IN BURKINA FASO

Natural hazards such as agricultural droughts impact negatively on crop yields and economic activities. Characterization of agricultural droughts provides precise and accurate information for decision making processes during agricultural drought events. Planning and responding to the hazards by government, and non-governmental organizations in the Sudano-Sahelian belt has been limited in the past due to knowledge gap on the nature and impact of the hazard. This study seeks to characterize historical agricultural droughts, assess their impact on crop yields and people’s susceptibility to undernourishment and through forecasting, unravel what the future holds. Annual effective reconnaissance drought index values are computed using mean monthly potential evapotranspiration and effective precipitation data. To assess the impact of agricultural drought, the index’s values are compared to crop yields and prevalence to undernourishment data. Results show that agricultural drought events of 1983 and 2008 are mild and ephemeral while the 1999 – 2006 event is severe and protracted. While there is 26% chance of materialization of an agricultural drought in Gourma, the chance of being ephemeral and of moderate category is the highest (8%). It has been determined that an ephemeral and moderate agricultural drought would trigger below average yields for maize, sorghum and millet. Mild, moderate and severe events increase prevalence to undernourishment by 2.9 %, 4.3 % and 5.8 % respectively. From 2020 to 2030, a continued materialization of agricultural droughts is expected

Drought Monitoring Using Rainfall, Evapotranspiration and Streamflow Data: A Case Study of Kaduna River Catchment Area (Nigeria)

Drought is defined as the lack of adequate precipitation, either rain or snow that causes reduced soil moisture or groundwater, diminished streamflow, crop damage and a general water shortage. The objective of this study focuses on meteorological and hydrological drought monitoring in river Kaduna catchment area. Standardized Precipitation Index (SPI) and Reconnaissance Drought Index (RDI) drought indices were used to characterize meteorological drought while Streamflow Drought Index (SDI) was used for hydrological drought monitoring for a period of 34 years (1967 – 2001). DrinC software, a drought indices calculator, was used for the calculation of SPI, RDI, and SDI respectively. The drought severity classification based on meteorological and hydrological drought indices gave 33% and 37% drought conditions period with the year 1967 – 2001. Based on these indexes, the drought characteristics of the catchment area were investigated by analyzing meteorological data from 1967 to 2001. The results of this analysis show that more non-drought/normal conditions were predominant than drought conditions. During the period under study (34 years), only one-year return period of extreme drought condition.

Drought Risk Analysis for Water Assessment at Gauged and Ungauged Sites in the Low Rainfall Regions of Pakistan

In this study, projection of droughts was performed using monthly precipitation and temperature data in the Balochistan and Sindh provinces of Pakistan. Rainfall is the main source of water in the study area. The Reconnaissance Drought Index was used to explore drought events from the selected sites of the regions. The index-flood procedure was used to perform the drought analysis in the study area. Two statistical methods were used to select Generalized Pareto distribution as the most acceptable distribution for drought risk assessment. The distribution was estimated through the L-moments approach for both regions. Three problems were addressed in this study. Regional analysis was performed for regional quantiles covering a large area and on-site analysis for each site’s drought projections. The Monte Carlo simulations procedure was utilized for reliability assessment of estimated quantiles that proved likeness at lower return periods and uncertainty at higher return periods. Lastly, quadratic regression was performed between drought means and site characteristics for drought quantiles at ungauged sites. According to the results, there are chances of more drought in the future if the recent climatic conditions continue in the study area. The study results will help stakeholders, government, and water resource managers in preparing plans about drought and water availability in the area.

Comparison of meteorological indices for drought monitoring and evaluating: a case study from Euphrates basin, Turkey

Abstract Drought incidents occur due to the fact that precipitation values are below average for many years. Drought causes serious effects in many sectors, such as agriculture, economy, health, and energy. Therefore, the determination of drought and water scarcity, monitoring, management, and planning of drought and taking early measures are important issues. In order to solve these issues, the advantages and disadvantages of five different meteorological drought indices were compared, and the most effective drought index was determined for monitoring drought. Accordingly, in the monthly, 3-month, and 12-month time period, covering the years between 1966 and 2017 (52 years), Standardized Precipitation Index (SPI), Statistical Z-Score Index (ZSI), Rainfall Anomaly Index (RAI), Standardized Precipitation Evapotranspiration Index (SPEI), and Reconnaissance Drought Index (RDI) were used. It was concluded that precipitation-based SPI and ZSI are similar patterns and precipitation, and temperature-based SPEI and RDI are similar patterns. Also, it has been determined that RAI is more effective than other indices in determining the periods of extreme drought or wet. Furthermore, SPEI and RDI have been found to be superior to other indices as they take into account the water consumption and climate effects caused by evapotranspiration.

Ability Assessment of the Stationary and Cyclostationary Time Series Models to Predict Drought Indices

Drought forecasting and monitoring play a significant role in reducing the negative effects of global meteorological droughts caused by different intensities at different temporal and spatial scales in different regions, especially in regions with high dependency on rainwater. The present study tries to compare the accuracy of stationary time series (ST) models including autoregressive moving average (ARMA), moving average (MA) and autoregressive (AR) and cyclostationary time series (CT) models including periodic autoregressive moving average (PARMA), periodic moving average (PMA) and periodic autoregressive (PAR) to predict drought index (i.e. monthly reconnaissance drought index (RDI)) in periodic data series considering that CT models are more powerful and efficient than ST models by using data series of 8 synoptic stations with different climate conditions in Iran from 1967 to 2017. According to the results the monthly RDI was significantly periodic in all selected stations. The PAR (25) model was the best fitted CT model in data series at all stations and on the other hand, the following models were the best-fitted ST models in data series: the AR models at Babolsar and Rasht AR (25) and at Gorgan AR (24) and ARMA models at Tehran ARMA (2, 3), at Zahedan and Shiraz ARMA (2, 4) and at Esfahan and Shahre Kord ARMA (2, 5). Based on the best fitted CT and ST models, the results showed that the correlation coefficients (R) between observed and simulated RDI vary from 0.882 to 0.946 and from 0.693 to 0.874, respectively from January 1967 to December 2017. According to the best fitted CT and ST models, the validation test of the best fitted models indicated that the R between observed and simulated RDI vary from 0.634 to 0.883 and 0.585 to 0.847, respectively from January 2012 to December 2017. In total, it can be concluded that that the accuracy and capability of CT models in predicting the RDI were more than those of the ST models at all stations and the hypothesis of the study was confirmed.

Drought Characterization and Trend Detection Using the Reconnaissance Drought Index for Setsoto Municipality of the Free State Province of South Africa and the Impact on Maize Yield

The reconnaissance drought index (RDI) for the Setsoto municipality of the Free State province in South Africa was calculated for the period between 1985 and 2019 at 3 month (October–December), 6 month (October–March), and 12 month (October–September) intervals. Rainfall and minimum and maximum temperature data from four weather stations (Clocolan, Ficksburg, Marquard, and Senekal) were used for this study to characterize drought using “DrinC” software together with the Mann Kendall test with Sen’s slope to detect drought trends and the rate of change. Extreme, severe, and moderate droughts were recorded for all the stations, with RDIs ranging from −3.6 to −1.0 at different temporal scales. The years 1991, 1994, 2006, 2011, and 2015 were highlighted using the RDI 3, 6, and 12 month calculations. Results showed that the yield decreased either in the year of the drought or in the subsequent year, due to the exact timing of the low-rainfall events in the season and soil moisture storage. Yields were low, on average 2.5 tons ha−1 year−1, with high variability. Optimal growing conditions are essential in the early part of the season, October–December, for maximizing yield; if droughts are experienced at this time then the yield is more greatly impacted than if the droughts occur later in the season. Spatial analysis shows a large variability of drought patterns across the Municipality, over the years, with the 3 month RDI values giving a more detailed picture of this variability than the 6 and 12 month RDI values.

Assessment of drought with a real-time web-based application for drought management in humid tropical Kerala, India.

Geospatial techniques are useful for near real-time monitoring of drought and towards devising local-level effectivedrought management plan. Based on thehistoric and current remote sensing data, one can identify the influence of drought on the vegetation status by analyzing the anomaly/drought condition of a particular area of interest (AOI) through different digital image processing techniques. In this study, an attempt has been made to develop a web-based application for generating drought maps and district-wise drought information at real time in the web server using Hypertext Preprocessor (PHP) and Python scripts. A web-based application was developed and drought conditions existing in the study area were understood both spatially and temporally.The results of the application showed distinct variation of drought prevalence within the administrative boundaries. This web-based application was validated with drought analysis carried out using different drought indices, viz., standard precipitation index and reconnaissance drought index. The results established that this validated approach could be used for developing disaster management plan well in advance to combat the consequences of drought across the globe and to evolve strategic decisions which will have implications in the various sectors of the economy.

Altitudinal pattern of shrub biomass allocation in Southwest China.

Shrubs play an important role in the global carbon cycle and are particularly sensitive to climate change. However, the altitudinal pattern of biomass allocation in mountainous shrubs and its responses to climate change are still unclear. In this study, biomass accumulation and allocation of the shrub community and their relationships with climatic factors were investigated in 331 sampling sites along an extensive altitudinal gradient (311–4911 m) in Southwest China. The results showed that the above-ground biomass (AGB) and the total biomass (TB) of the shrub community decreased quadratically (R2 = 0.107) and linearly (R2 = 0.024) from 9.86 to 0.15 kg·m-2 and 15.61 to 0.26 kg·m-2 with increasing altitude, respectively. However, the below-ground biomass (BGB) and TB of the herb layer increased quadratically with increasing altitudes (R2 = 0.136 and 0.122, respectively. P<0.001). The root/shoot ratio (R/S) of the community and its component synusiae increased gradually with increasing altitudes (P<0.001). The standardized major axis (SMA) indicated an isometric relationship between AGB and BGB for the whole shrub community, but allometric relationships were found for the shrub and herb layer. Redundancy analysis and Pearson correlation analysis showed that the biomass and R/S were significantly correlated with mean annual temperature (MAT), mean annual precipitation (MAP) and reconnaissance drought index (RDI). These findings indicate that shrub biomass allocation is strongly affected by the altitude, MAT and MAP and support the isometric relationship of AGB and BGB partitioning at the community level on mountainous shrub biomes.

Assessment of drought and wet projections in the humid climatic regions for Pakistan

Investigation of extreme hydrological events are necessary for planning and designing hydrological structures. In this study, we examine and project two hydrological extremes of drought and wet conditions over the north and eastern regions of the country. A statistical procedure of the Reconnaissance Drought Index at the annual time scale was used to combine the monthly rainfall and temperature data for the assessment of extreme drought and wet events. These hydrological extreme events were combined with Index-Drought Procedure using L-moments to obtain study results. Homogenous regions were satisfied for both the extremes based on statistical measures. Two statistical tools were used to select suitable probability distributions in the form of Generalized Pareto and Pearson Type-III distributions to discuss drought risk and wet conditions in the regions. Secondly, regional projections of drought risk and wet conditions were performed based on regional quantiles at different interarrival periods which show greater chances of the wet condition in region one while drought risk in region two. Lastly, at-site projections were carried out for all the included sites for both extremes at various interarrival periods using the suitable probability distributions. Both at-site and regional projections show greater similarity at lower while uncertainty at higher interarrival periods. As droughts and wets cover, a large area, therefore, regional results are more functional and better for regional planning and development programs. These statistical projections will help planners of water resources management and hydrological extremes in the study area.

Assessment of the potential impacts of climate change on the hydrology at catchment scale: modelling approach including prediction of future drought events using drought indices

In this study, the Distributed Catchment-Scale Model, DiCaSM, was used to study the impact of climate change on the hydrology of the Eden catchment, north east of Scotland. As a first step, the model was successfully calibrated and validated for a 42 years period. The DiCaSM model was then used to study the impact of climate change on the water availability. Data from the UKCP09 Climate change scenarios for the 2010–2039, 2040–2069 and 2070–2099 periods, considering three gas emission scenarios (low, medium and high), were applied. The results indicated that the greatest decrease in streamflow and groundwater recharge was projected to happen under the high emission scenarios towards the end of the century, i.e. between 2070 and 2099. This would mainly be due to the summers becoming drier. Meanwhile, the projected increase in winter precipitation did not contribute much towards groundwater recharge due the projected increases in evapotranspiration and soil moisture deficit.The following drought indices were calculated and were found to be effective in predicting different types of droughts: the Standardized Precipitation Index, SPI, and the Standardized Precipitation Evaporation Index, SPEI, the Reconnaissance Drought Index, RDI, the modified adjusted RDI, the Soil Moisture Deficit, SMD and the Wetness Index, WI. The findings of the study have broader implications in water resources management considering the future changes in climate.

Hydro-Metrological Drought Assessments along the Blue Nile River Basin in East Gojjam Zone

The Upper Blue Nile basin is less-explored in drought studies as compared to other river basins in Ethiopia and a shortage of particular basin drought monitoring system. The area founds in along a Blue Nile basin faced a recurrent drought conditions in several years ago. The main objectives of this study to investigate droughts along a Blue Nile basin in the east Gojjam zone. To evaluate the drought duration, severity, occurrence and risks it was used different indices . The results shows a hydrological drought was occurring in a frequent condition in partial areas of Shebel Berenta, Goncha siso enese and Enarg enawuga woreda. Based on 12-month time-scale, the total number of drought events were identified in the area, using Reconnaissance drought index (RDI) during the period of analysis (1995–1996) and its values 100% drought and its ranges were highly sever. Considering the drought events in the stream flow drought index (SDI) the values indicates drought severity was existed in the year 1984/1985 and 1989/1990. Inaddation standard precipitation index (SPI) also indicates a severe drought in 1984/1985, 1990/1991 and 1991/1992 and its values was -1.5. Generally the hydrological, metrological and agricultural drought where existed in the year (1984-2012) within the study area. Keywords : RDI, Drought, SDI, SPI, NDVI DOI: 10.7176/CER/12-9-04 Publication date: September 30 th 2020