Rainfall Anomaly Index Research Articles

Exploring spatial and temporal drought over the semi-arid Sahibi river basin in Rajasthan, India.

Rajasthan state of India is prone to recurrent droughts; hence, exploring drought severities over the semi-arid Sahibi river basin is crucial for drought management. To investigate drought severity, the Rainfall Anomaly Index (RAI) was applied at two time spans, such as annual (January to December) and the monsoon season (June to September), using long-term daily rainfall data (1961-2017) for nine rain gauge stations. Similarly, for the examination of various drought characteristics like magnitude, duration and intensity, run theory analysis was used. Trends in rainfall, drought severity, magnitude, duration and intensity were computed by employing both parametric (simple linear regression) and non-parametric (Mann-Kendall and Sen's slope) tests, while spatial pattern maps of rainfall and drought characteristics were prepared using geographical information system. The analysis of rainfall records revealed a declining trend in eastern and central parts, whereas remaining areas of the basin witnessed an increasing trend during two time spans. During the study period, drought occurrence varied both geographically and temporally. The extreme, severe and moderate drought events were more common during monsoon season. Amongst the stations, Tapukara, Bairath and Mundawar rain gauge stations experienced the largest number of drought events compared to other stations. At both time scales, the most extreme droughts in the Sahibi basin occurred in 1979, 1986, 1987, 1989 and 2002. At the annual time span, the basin had the longest drought duration of 300days, with a drought magnitude of - 758.3mm. Likewise, the Tapukara rain gauge station had the longest dry spell of 310days, followed by Behrod and Kotkasim (306days each), Kotputli and Tijara (305days each) and Mundawar (303days). Finally, the findings of this study are expected to be useful to agricultural scientists, policymakers and water resource managers.

Rainfall Anomaly Index Valuation of Agricultural Production in Jakiri Sub- Division, Northwest Region, Cameroon

Climate variability and change is one of the greatest threats facing humanity, with farreaching and devastating impacts on people, ecosystem services, natural resource-base and the natural environment as a whole

Dinâmica espaço-temporal das anomalias de precipitação em uma região semiárida, Nordeste do Brasil

Extreme weather events assume great socioeconomic relevance, especially in regions climatically sensitive such as semi-arid climate. The analysis of the rainfall regime of a given region can be made by the Rainfall Anomaly Index (RAI), which allows classifying the rainfall regime as to the annual anomalies of precipitation, inferring on the dry and humid cycles. Therefore, the objective was to study the spatial-temporal variability of precipitations of an area inserted in the Semiarid region of Brazil. For this, the RAI was used for the climatological normal 1987-2017 of 11 rainfall stations inserted in the mesoregion of the Sertao of the state of Pernambuco. The annual and interannual precipitations were analyzed, determined the negative and positive anomalies along the climatological normal, and, through the spatial interpolation of precipitation by the Method of inverse of the Square of Distance, elaborated spatial distribution maps of rainfall in different annual anomalies. The results showed that in 90.9% of the stations studied the rainy block occurs between the months of January to April, and that the accumulated of these months corresponds to more than 50% of the precipitated annual volume, thus demonstrating the irregularity in the annual distribution of rainfall. It was found that in 55% of the years there were negative anomalies in the mesoregion of the Sertao of Pernambuco. Moreover, it was spatially verified a greater homogeneity in the spatial distribution of negative anomalies in relation to positive anomalies, that is, drought events, when they occurred, tended to reach the entire studied area.

Revisiting the Rainfall Anomaly Index to serve as a Simplified Standardized Precipitation Index

The Rainfall Anomaly Index (RAI) is revisited herein as an alternative to the Standardized Precipitation Index (SPI), taking into account different time scales and the probability of zero precipitation as in the SPI procedure. To evaluate the performance of the modified RAI that stands as a Simplified Standardized Precipitation Index (SSPI), both indices were computed for 45 stations distributed across diverse climates of Iran. The resulted time series and frequency distribution of the indices values between different dry/wet classes were statistically compared. The results show a very strong association between the two indices at all stations and time scales, particularly at longer time scales. The spatial distribution of the correlation coefficient (R) computed between the two indices depicts large R values across Iran, particularly over northern and western Iran where precipitation is distributed more regularly throughout the year. The spatial distribution of the Shapiro-Wilks (S-W) normality test computed for all studied stations and time scales show values larger than 0.96 in northern and western Iran and lower values ranging from 0.82 to 0.96 for a few stations scattered in eastern, central, and southern Iran. This indicated that both indices have a closer distribution to the standard normal distribution in northern and western Iran where precipitation is less skewed. However, SSPI shows a lower S-W test than the SPI for some stations scattered over central-eastern Iran, which is an indication of its higher deviation from the normal distribution. The comparison of the frequency distribution of the indices values between different dry/wet classes also reveals a very strong association between the two indices, as indicated by very high values of contingency coefficient and Cramér’s V statistic for all time scales at the studied stations. SSPI is simpler in calculation than the SPI and permits for missing data and large numbers of zero values in the data records, which is very common in arid and hyper-arid climates. Thus, SSPI is preferred over SPI when the length of data records is short or contains a large number of zero values for which SPI is incomputable or unreliable.

Evaluation of the similarity between drought indices by correlation analysis and Cohen's Kappa test in a Mediterranean area

In the literature, numerous papers report comparative analyses of drought indices. In these types of studies, the similarity between drought indices is usually evaluated using the Pearson correlation coefficient, r, calculated between corresponding severity time series. However, it is well known that the correlation does not describe the strength of agreement between two variables. Two drought indices can exhibit a high degree of correlation but can, at the same time, disagree substantially, for example, if one index is consistently higher than the other. From an operational point of view, two indices can be considered in agreement when they indicate the same severity category for a given period (e.g. moderate drought). In this work, we compared six meteorological drought indices based on both correlation analysis and Cohen's Kappa test. This test is typically used in medical or social sciences to obtain a quantitative assessment of the degree of agreement between different methods or analysts. The indices considered are five timescale-dependent indices, i.e. the Percent of Normal Index, the Deciles Index, the Percentile Index, the Rainfall Anomaly Index, and the Standardised Precipitation Index, computed at the 1-, 3-, and 6-month timescales, and the Effective Drought Index, a relatively new index, which has a self-defined timescale. The indices were calculated for 15 stations in the Abruzzo region (central Italy) during 1951–2018. We found that the strength of agreement depends on both the criteria of drought severity classification and the different indices' calculation method. The Cohen's Kappa test indicates a prevailing moderate or fair agreement among the indices considered, despite the generally very high correlation between the corresponding severity times series. The results demonstrate that the Cohen's Kappa test is more effective than the correlation analysis in discriminating the actual strength of agreement/disagreement between drought indices.

Application of Signal Processing in Tracking Meteorological Drought in a Mountainous Region

This study addresses the application of signal processing in the evaluation of meteorological drought associated with monthly precipitation time series. Several drought indices and a Haar wavelet decomposition (WD) with ten components are implemented in the evaluation of the monthly precipitation of a mountainous region called Mount Uludag in Turkey. Monthly precipitation time series in three meteorological stations at the summit and foothills are used. The Standardized Precipitation Index (SPI) is used at monthly, annual, and 12- and 48-month moving average time frames as the benchmark to investigate the drought patterns. The results obtained by the WD and SPI are then confirmed using the Z-score index (ZSI) at monthly and annual scales, together with the modified China Z-index (MCZI) and rainfall anomaly index (RAI) at a monthly scale. Changes in the moments of the distribution, correlation analysis, mutual information, and power spectrum are applied to investigate the nature of the relationship between the sequences of precipitation events in time and space. The temporal correlation analysis, together with the mutual information, showed that the system has a short-term memory with strong seasonality. Similarly, the power spectra depicted major seasonality at 1, 3, 5, 6, 12, 22, and 60 months in the precipitation time series. It is concluded that the recent drought events have an infrequent nature, which altered the sinusoidal patterns of the large-scale events. The SPI-48 and the WD showed that declines are strongly related to the large-scale cycles, but the decline patterns are more related to the station located at the mountain summit.

Satellite-Based Meteorological and Agricultural Drought Monitoring for Agricultural Sustainability in Sri Lanka

For Sri Lanka, as an agricultural country, a methodical drought monitoring mechanism, including spatial and temporal variations, may significantly contribute to its agricultural sustainability. Investigating long-term meteorological and agricultural drought occurrences in Sri Lanka and assessing drought hazard at the district level are the main objectives of the study. Standardized Precipitation Index (SPI), Rainfall Anomaly Index (RAI), and Vegetation Health Index (VHI) were used as drought indicators to investigate the spatial and temporal distribution of agriculture and meteorological droughts. Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) data from 1989 to 2019 was used to calculate SPI and RAI. MOD13A1 and MOD11A2 data from Moderate Resolution Imaging Spectroradiometer (MODIS) from 2001 to 2019, were used to generate the Vegetation Condition Index (VCI) and Temperature Condition Index (TCI). Agricultural drought monitoring was done using VHI and generated using the spatial integration of VCI and TCI. Thus, various spatial data analysis techniques were extensively employed for vector and raster data integration and analysis. A methodology has been developed for the drought declaration of the country using the VHI-derived drought area percentage. Accordingly, for a particular year, if the country-wide annual extreme and severe drought area percentage based on VHI drought classes is ≥30%, it can be declared as a drought year. Moreover, administrative districts of Sri Lanka were classified into four hazard classes, No drought, Low drought, Moderate drought, and High drought, using the natural-beak classification scheme for both agricultural and meteorological droughts. The findings of this study can be used effectively by the relevant decision-makers for drought risk management (DRM), resilience, sustainable agriculture, and policymaking.

An analysis of rainfall variability and drought over Barmer District of Rajasthan, Northwest India

Abstract Climate variability, mainly the annual air temperature and precipitation, have received great attention worldwide. The magnitude of this climate variability changes with variation in location. Rajasthan comes under the arid and semi-arid zone of India in which monsoon is a principal element of water resource. Due to erratic and scanty rainfall in this zone, agriculture is totally dependent on the monsoon. The objective of the present study is to assess the meteorological drought characteristics using Drought Indices Calculator DrinC from the historical rainfall records of the Barmer District of Rajasthan State by employing the criterion of percentage departure (D%), rainfall anomaly index (RAI) and standardized precipitation index (SPI). Trend analysis of seasonal and extreme annual monthly rainfall was carried out for the Barmer District of Rajasthan State using the data period between 1901 and 2002 at the 5% level of significance. Sen's slope estimator was also applied to identify the trend. Temporal analysis is useful to predict and identify the possible drought severity and its duration in the study region. It also helps in understanding its effect on groundwater recharge and increasing the risk of water shortage. Trend analysis of rainfall over 102 years shows an increasing trend in pre-monsoon, post-monsoon, southwest monsoon and annual rainfall and a decreasing trend in winter rainfall. Through this study, policy makers and local administrators will be benefitted, which will help them in taking proactive drought relief decisions in the drought-hit regions.

Temporal analysis of precipitation in Saurashtra, Kutch, and Diu sub-division of Western Indian region

Gujarat is a semi-arid region where the monsoon is the principal element. Temporal analysis of precipitation and drought characteristics for the period of 146 years (1871–1872 to 2015-2016) covering Saurashtra, Kutch, and Diu regions of Gujarat, revealed long-term behavior. In the duration of 146 years, non-parametric trend identification techniques such as Mann-Kendall test and Sen’s slope estimator show an increasing trend in southwest monsoon and annual rainfall. The annual rainfall concentration was computed by the precipitation concentration index (PCI). Its rough concentration in one-third of the year indicates strong irregularity in rainfall distribution, which is because of the monsoon climate. Seasonal analysis of annual rainfall shows extreme rainfall regime over study area which reveals that almost all rainfall occurred within 1 to 2 months. Drought events have been identified by various drought indicators viz. percentage departure (D%), rainfall anomaly index (RAI), and standardized precipitation index (SPI). Rainfall concentration and monthly heterogeneity are also related to each other by drought characteristics. The declining trend of southwest monsoon PCI implies serious impact on the agriculture and water resources over Saurashtra, Kutch, and Diu regions of Gujarat.

Spatiotemporal monitoring and change detection of vegetation cover for drought management in the Middle East

The Middle East (ME), as an arid and semi-arid region, is prone to environmental risks and stresses, such as drought are inseparable phenomena of the region. In this study, an approach for identifying sustained vegetation cover (SVC) is suggested to identify the connection between SVC and drought. Normalized difference vegetation index (NDVI) and land surface temperature (LST) were used to filter zones of rich vegetation cover from poorly vegetated or non-vegetated regions of the ME. The change detection of vegetation cover was computed by the NDVI differencing technique, and the vegetation condition index (VCI) and normalized vegetation supply water index (NVSWI) were used to derive drought indices. The standardized precipitation index (SPI) and rainfall anomaly index (RAI) were used to monitor the intensity of meteorological drought events. A comparison of the estimates of vegetation change, remote sensing-based VCI, and meteorological drought indices revealed that the highest SVC is concurrent with the occurrence of drought. Moreover, it was found that the most severe meteorological drought and VCL-based drought condition occurred in 2008 and that the highest percentage of SVC was also obtained for this year. The results suggest the possibility of using the SVC instead of other spectral indices, such as the NDVI, VCI, NVSWI, and NVSWI, for the superior assessment and detection of environmental stresses such as drought.

Influence of rainfall on wind power generation in Northeast Brazil

Wind power has been emerging as one of the main renewable energy sources in Northeast Brazil, which concentrates 87% of the country’s installed wind capacity, especially in recent years, due to water scarcity and its seasonal energy complementarity to hydraulic generation. The objective of this article is to present a method to evaluate the influence of rainfall on the behavior of wind power generation, considering rainfall anomaly index and extreme climatic indices of precipitation. We utilized daily rainfall data from cities located near wind farms CE1 and CE2 in the state of Ceará — Aracati, in the 1974-2016 period, and Trairi, in the 1976-2016 period —, as well as daily wind power generation data for the same period, provided by the Electric System National Operator (ONS). The RClimdex software was used to calculate 11 indices of climatic extremes dependent on rainfall. The capacity factor for wind power generation was calculated for the period from 2011 to 2016 for the CE1 and CE2 wind farms. The application of this method found an inversely proportional relation between rainfall anomaly index (RAI) and the wind power capacity factor, with a decrease in total rainfall and a greater number of consecutive dry days and concentrated rain in the short term. From 2012 to 2016, the rainfall anomaly index was negative. However, wind power factors were higher than in 2011. The developed methodology can be applied to other wind farms, contributing to the medium and long term energy planning of the National Interconnected System.

Rainfall Anomaly Index Valuation of Agricultural Production in Jakiri Sub-Division, Northwest Region, Cameroon

This paper aims to evaluate the impact of rainfall variability on agricultural production in Jakiri Sub-Division of the Northwest Region of Cameroon. Previous studies on the impact of climate on agriculture focused on stakeholder signatures to climate change adaptation to the agrarian sector of the Bui Plateau, which revealed that despites glaring consequences of climate, the Jakiri Council only allocates only 1% of its annual budget for climate action. Data sources for this study included the administration of 211 questionnaires to cover the three agro-ecological zones of Jakiri Sub-Division, rainfall data collected from UNVDA Ndop (lowland zone), National Meteorological Service (mid-altitude zone) and the Oku Wildlife Sanctuary (highland zone). The Rainfall Anomaly Index (RAI) was used in analysing rainfall data. Results revealed that rainfall is reducing as depicted by the increasing trends in RAI. Farmers also perceived that food crop production has been decreasing. Despite these perceptions, some crops like cassava that is drought tolerant has been increasing. Again, rice production at the WahsiBer Plain has been increasing. This calls for the development and production of more drought tolerant food crops to ensure sustainable rural livelihoods.

Assessment of five meteorological indices for monitoring the drought condition in Chengalpattu District, Tamilnadu, India

Drought indices are widely used for monitoring the drought condition. The study is aimed to estimate the performance of composite indices for monitoring the severity condition of drought in Chengalpattu District, Tamilnadu, India. Indices such as Standardized Precipitation Index (SPI), Decile Indicator (DI), Effective Drought Index (EDI), Percent of Normal Indicator (PNI) and Rainfall Anomaly Index (RAI) were evaluated for monitoring the condition of drought. These indices were calculated with the help of 30 years’ rainfall data from 1989 to 2018. Rainfall plays a prominent role in the identification and monitoring of drought condition, prevailing in a region. The drought condition was categorized from extremely dry to extremely wet based on the values computed by different indices. Based on the results, the most frequent category of SPI was below normal to moderately dry condition and that of PNI was moderate drought condition. The deciles indicated 1 to 3 which shows a much below normal precipitation, the frequent category of EDI was moderate to severely dry and RAI indicated extreme to severely dry condition. By the evaluation of different meteorological indices, the drought is monitored and it is evident that the selected region is under moderate to severe drought condition.

Drought Identification through Climatic Variables

Temperature and rainfall are among the climatic variables required in determining the availability of water in an environment, especially for agricultural purposes and domestic consumption by man. However, there are concerns that these variables are being affected by global warming which thus necessitates the need to study their impact on the environment such as the identification of drought. The mean monthly temperature and rainfall data utilized in this work were obtained from the Nigerian Meteorological Agency (NIMET), Lagos, Nigeria for the period 1981 to 2010, and analyzed using the descriptive statistical approach including the rainfall anomalies index. After the analysis, the results showed that a non-uniform pattern of changes in temperature was evident across the different stations considered in which the variations in the local temperature trends were not spatially uniform. Twelve of the stations (Calabar, Port-Harcourt, Owerri, Benin, Enugu, Lagos, Ondo, Ibadan, Ilorin, Maiduguri, Sokoto and Katsina) out of the 18 stations considered have their mean monthly temperature increasing, which shows that majority of these stations are experiencing warming. In essence, the rainfall anomaly index thus showed that there is an evidence of drought in some of these stations considered (Warri, Benin, Enugu, Minna, Nguru, Sokoto and Katsina). However, it is important to continually check for both temperature trends and rainfall anomalies for enhanced and good agricultural planning of a nation since it was discovered that each particular area has unique rainfall and temperature patterns which are non-consistent with each other.

Drought vulnerability perceptions and food security status of rural lowland communities: An insight from Southwest Ethiopia

Food security is a common discourse across the globe. Drought affected Gamo rural lowland households are predisposed to food shortfalls. The study, therefore, mainly aimed to investigate the rural households' drought vulnerability perceptions and food security status in the Gamo lowlands. Primary data were obtained from 285 survey respondents, key informants, focus group discussants, agricultural professionals, and field observations. Secondary data were drawn from the published and unpublished relevant materials and complemented the primary data. A multistage sampling technique was used to select the sample respondents. Descriptive statistics, Rainfall Anomaly Index, correlation analysis, the Rasch and Logit models were used for quantitative data analysis. Discussions, narrations, and annotations were conducted to analyze the qualitative data. Multiple measures were employed to assess households' food security status. The findings showed that 53.68% of the households were food insecure in the light of the adapted Household Food Balance Model. The Household Dietary Diversity Score revealed low dietary diversity and poor nutritious quality. Food Insecurity Experience Scale showed only 13% of food security or mild food insecurity wherein 87% of the households were moderately and severely food insecure. The findings also indicated that drought hazard is a threat to communities' food security. To curb food problems, the studied households pursued strategies like selling out small animals, minimizing daily consumption frequency, reducing dietary quantity, and buying food on credit among the others. Importantly, more drought coping and food insecurity relieving strategies are recommended for all stakeholders to alleviate people's vulnerability to droughts and food insecurity.

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.

Trend analysis of long-term rainfall and temperature data for Ethiopia

ABSTRACT Trend analysis for the long-term average temperature and rainfall of Ethiopia during 1901 to 2015 has been performed to understand the pattern of these important meteorological features under climate change. The rainfall characterizations viz., precipitation concentration index (PCI), seasonality index (SI), rainfall anomaly index (RAI) and departure analysis of rainfall (DAR) have been calculated and interpreted. The annual rainfall recorded for the whole period was 816.3 ± 90.82 mm/year. During kiremt (long rainy) season, maximum seasonal rainfall of 453.2 mm were recorded while, its minimum value (39.6 mm) were received in bega (dry) season, respectively. The analysis of probability distribution for the time series data showed slightly positive skewness and kurtosis in monthly, seasonal and annual rainfall from the normal distribution. The results of Modified Mann–Kendall trend analysis for average temperature revealed a significant increasing trend from 1961 to 2015. Conversely, dry season (bega) rainfall, showed an increasing trend while kiremt season rainfall with decreasing trend for the period of 1901–2015. However, annual and other seasonal rainfall did not show any statistically significant trend. Study concludes that there is an increase in the average temperature in Ethiopia but, it constitutes a high degree of stability in rainfall rate and distribution.

Changes in the Characteristics of Dry and Wet Periods in Europe (1851–2015)

This study spanning the period 1851–2015 explores the spatial and temporal characteristics of dry and wet periods in Europe as well as their variability and changes. It is based on up to 220 stations with monthly precipitation time series that have a varying data availability within the study period. The stations are classified into eight regions with similar climate characteristics. Dry and wet periods are analyzed using the decile method as well as the modified Rainfall Anomaly Index mRAI at the 3-month timescale. Spatial extent, duration, and frequency of dry and wet periods show a large multi-decadal variability resulting in comparatively small long-term trends over the entirety of Europe for the study periods 1901–2015 and 1951–2015. Nonetheless, several sub-regions show distinct changes—with opposite signals for northern and southern Europe. Spatial extent and duration of dry periods generally decreased, while wet periods show increases throughout the 20th century—particularly in Scandinavia. A simultaneous increase in the frequency of severely dry and wet years, respectively, is observed since the 1980s. This indicates that temperature increases across Europe may be connected with an increasing frequency of extremes at both sides of the probability density function of precipitation.

Integrated assessment of extreme events and hydrological responses of Indo-Nepal Gandak River Basin

Changes in climate cause significant alterations in morphometric parameters and may lead to hydro-meteorological hazards. In this study, an attempt has been made to identify drainage morphometric characteristics through topographic, geologic and hydrological information to assess the extreme weather events (flood) over the Gandak River Basin (GRB). The standardized precipitation index (SPI) and rainfall anomaly index (RAI) were used for deducing extreme rainfall incidences derived from the Tropical Rainfall Measuring Mission precipitation datasets. An assembled frequency distribution as well as trends in RAI and SPI was calculated to understand the hydro-climatological behaviour of the basin. During the monsoon season, the years 1998, 2007, 2011, 2013 and 2017 witnessed the extreme flood events. The variations in heavy and intense rainfall in short time can be linked to extreme flood events, which leads to channel shifting and modifications, can be deduced from provided asymmetric factors and sinuosity index. The results illustrated that both the monsoonal rainfall and the frequency of extreme rainfall over the basin are increasing, which could be a reason for a high severity and frequency of flood events in the GRB.

Comparative study of meteorological and hydrological drought characteristics in the Pekalen River basin, East Java, Indonesia

Drought is known as a normal part of climate and including in a slow-onset natural hazard which may have several im-pacts on hydrology, agriculture, and socioeconomic. Drought monitoring, including its severity, spatial and duration is re-quired and becomes an essential input for establishing drought risk management and mitigation plan. Many drought indices have been introduced and applied in regions with different climate characteristics in the last decades. This paper aims to compare standardized precipitation index (SPI) and rainfall anomaly index (RAI) along with standardized streamflow index (SSI) in Pekalen River Basin, East Java, Indonesia. The statistical association analyses, included the Pearson correlation (r), Kendal tau (τ), and Spearman rho (rs) were performed to examine the degree of consistency between monthly and annual drought index of SPI and RAI. Additionally, the comparative analysis was performed by overlapping both monthly and an-nual drought index from the SPI and RAI with the SSI at hydrological years. The study revealed that the characteristic of the annual drought index between the SPI and RAI exhibits pattern similarity which indicated by the high correlation coeffi-cient between them. Further, the comparative analysis on each hydrological year showed that the SPI and RAI were very well correlated and exhibited a similar pattern with the SSI. Overall, the SPI shows better performance than the RAI for es-timating drought characteristic either monthly or annual basis. Hence, the SPI is considered as a reliable and effective tool for analyzing drought characteristic in the study area.