Drought Trend Analysis Research Articles

The composite drought index incorporated solar-induced chlorophyll fluorescence enhances the monitoring capability of short-term drought

Understanding the response of vegetation to drought is significant for socio-economic development and biodiversity conservation. However, due to the complexity of drought, relying only on one approach, such as the surrounding physical environmental conditions or specific vegetation characteristics, does not yield precise results. To address this challenge, composite drought indices incorporating Normalized Difference Vegetation Index (NDVI) and other multiple variables, have been developed and shown promising effectiveness in drought detection. Compared to NDVI, solar-induced chlorophyll fluorescence (SIF) decreases due to the increased non-photochemical quenching and reduced photosynthesis during short-term drought stress. This indicates a direct association between SIF and vegetation photosynthesis, offering advantages over NDVI in capturing drought effects. Nevertheless, SIF has not yet been fully integrated into composite drought indices. Therefore, this study focused on assessing the advantages of SIF for short-term drought monitoring by constructing a new composite drought index (CPDI) using the Principal Component Analysis (PCA) method. Subsequently, CPDI was employed to forecast future drought conditions. Overall, CPDI performs exceptionally well as a composite drought index in drought trend analysis and drought event identification, indeed advancing the monitoring capability for short-term drought. Furthermore, the incorporation of SIF in CPDI, obtained from various data sources provides more timely monitoring of drought events, while the CPDI with NDVI reflects the cumulative effect of drought conditions over a longer period. In the future, it is potential to utilize the benefits of SIF in constructing drought indices or combine it with NDVI for comprehensive drought characterization.

Wetting or greening? Probing the global trends in Vegetation Condition Index (VCI)

Vegetation Condition Index (VCI), as a widely used drought index for monitoring vegetation drought stress and estimating drought trends, is constructed by normalizing the long-term satellite-based Normalized Difference Vegetation Index (NDVI) data. However, under global greening, vegetation across different regions has shown an increasing trend in greenness, which may cause VCI to inherit the greening trend in NDVI and further hamper its ability in drought trend analysis. Therefore, this study quantitatively explored the underlying relationship among VCI, global greening, and drought from 2001 to 2021 to examine the utility of VCI in a changing environment. Multi-source indicators were employed as surrogates for vegetation greenness and drought, respectively. Particularly, the Leaf Area Index (LAI) and Net Primary Production (NPP) were used as proxies for vegetation greenness while the Root-Zone Soil Moisture (RZSM), Palmer Drought Severity Index (PDSI), and Standardized Precipitation-Evapotranspiration Index (SPEI) were used for drought indices. Based on Sen’s slope estimator, Mann-Kendall (MK) test, and partial correlation analysis, our results show that the proportion of pixels with an increasing trend in VCI is approximately 38.5%, which is similar to the greenness-related indices (i.e., NPP [26.47%] and LAI [59.14%]), and is significantly higher than the other drought indices (i.e., RZSM [19.83%], PDSI [10.38%], and SPEI [9.32%]). Furthermore, our results demonstrate that the VCI, as a drought index, exhibits a closer correlation with greenness-related indicators (LAI and NPP) than other drought indices (RZSM, PDSI, and SPEI). These results reveal the potential limitations in the practical applications of VCI and could enhance our understanding of vegetation dynamics and drought trends, especially in the current greening globe. Additionally, this study serves as a cautionary note for the scientific community involved in drought monitoring, emphasizing that the VCI may not be a suitable tool for evaluating long-term trends in drought impacts on vegetation.

Change point detection and trend analysis of drought over Algeria from 1901 to 2018

Change point detection and trend analysis of drought over Algeria from 1901 to 2018

Hydrological and Meteorological Drought Monitoring and Trend Analysis in Abbay River Basin, Ethiopia

The definition of drought is very controversial due to its multi-dimensional impact and slow propagation in onset and end. Predicting the accurate occurrence of drought remains a challenging task for researchers. The study focused on hydrological and meteorological drought monitoring and trend analysis in the Abbay river basin, using the streamflow drought index (SDI), standardized precipitation index (SPI), and reconnaissance drought index (RDI), respectively, to fill this research gap. The study also looked into the interrelationships between the two drought indicators. The SDI, SPI, and RDI were calculated using long-term streamflow, precipitation, and temperature data collected from 1973 to 2014. The data were collected from eight streamflow stations and fifteen meteorological gauge stations. DrinC software (Drought Indices Calculator) was used to calculate the SDI, SPI, and RDI values. The result from meteorological drought using SPI12 and RDI12 shows that 1975, 1981, 1984, 1986, 1991, 1994, and 2010 were extreme drought years, whereas 1983, 1984, 2001, and 2010 were the most extreme hydrological drought years based on the SDI12 result. Except for Bahir Dar and Gondar, a severe drought occurs at least once a decade in all stations considered in this study. In general, the SPI, RDI, and SDI results indicated that the study area was exposed to the most prolonged severe and extreme drought from 1981 to 1991. The findings of this study also demonstrated that the occurrence of hydrometeorological droughts in the Abbay river basin has a positive correlation at long time scales of 6 and 12 months. The trend analysis using the Mann–Kendall test implied that there was a significant meteorological drought trend in two stations (Debre Berhan and Fiche) at SPI12 and RDI12 time scale, but for the remaining thirteen stations, there is no trend in all time scales. The hydrological drought trend analysis in the basin on a seasonal (SDI3) and yearly (SDI12) time scale also revealed that three streamflow stations have a positive trend (Kessie, Gummera, and Border). This implies that water resource management is still a vital tool for the sustainable development of the Abbay river basin in the future.

Evaluating the Applicability of PERSIANN-CDR Products in Drought Monitoring: A Case Study of Long-Term Droughts over Huaihe River Basin, China

In this study, Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR) was evaluated for the assessment of long-term drought monitoring in Huaihe River Basin using daily gauge observation data for the period from 1983 to 2017. The evaluation results show that the PERSIANN-CDR algorithm has a good detection ability for small precipitation events over the whole basin, but a poor ability for extreme precipitation events (>50 mm/day). Daily PERSIANN-CDR estimates perform relatively better in areas with abundant precipitation, while the monthly and yearly PERSIANN-CDR estimates are highly consistent with gauge observations both in magnitude and space. The Standardized Precipitation Index (SPI) at various time scales (3, 6, and 12 months) was calculated based on PERSIANN-CDR and gauge observation, respectively. Grid-based values of statistics derived from those SPI values demonstrate that PERSIANN-CDR has a good ability to capture drought events of each time scale across the basin. However, caution should be applied when using PERSIANN-CDR estimates for basin-scale drought trend analysis. Furthermore, three drought events with long duration and large extent were selected to test the applicability of PERSIANN-CDR in drought monitoring. The results show that it has a good ability to capture when and where droughts occur and how far they spread. Due to the overestimation of small precipitation events, PERSIANN-CDR tends to overestimate the number of extreme droughts and their extents. This needs to be considered in future algorithm improvement.

Spatial and Temporal Variation of Droughts in the Mongolian Plateau during 1959–2018 Based on the Gridded Self-Calibrating Palmer Drought Severity Index

Drought monitoring is challenging, but it is required for improving agricultural production, protecting the ecological environment, and reducing economic losses in drought-prone regions such as the Mongolian Plateau (MP). This study is a systematic analysis of the spatiotemporal changes in the characteristics of drought events (drought duration, severity, intensity, frequency, peak, and starting season) at the sub-regional scale between 1959 and 2018 based on the run theory and using the gridded self-calibrating Palmer Drought Severity Index (scPDSI) dataset. Principal component analysis and Varimax rotation and the Mann–Kendall trend and Sen’s slope were used for the sub-regional division and drought trend analysis, respectively. In addition, wavelet analysis was employed to analyze drought periodicity and determine the influence of large-scale climate indices on regional drought variation. The study results indicate clear differences in the spatial patterns of drought characteristics in the MP. The northern part suffered from droughts with longer duration and higher severity, whereas more drought events with shorter duration and less severity occurred in the southern part. Most of the MP experienced a relatively wet trend in 1996–2018 compared to the period of 1959–1995. The frequency of spring drought events showed an increasing trend in 1996–2018, unlike in 1959–1995. Some drought events simultaneously affected two or several sub-regions. The wavelet analysis results indicated that the drought periodicity in the MP was 10–64 months. The Arctic Oscillation (Pacific Decadal Oscillation) was significantly correlated with drought in the southern (northern) part.

Trend analysis of drought in Bundelkhand region of India

Trend analysis of drought in Bundelkhand region of India

Precipitation and Potential Evapotranspiration Temporal Variability and Their Relationship in Two Forest Ecosystems in Greece

The assessment of drought conditions is important in forestry because it affects forest growth and species diversity. In this study, temporal variability and trends of precipitation (P), potential evapotranspiration (PET), and their relationship (P/PET) were examined in two selected forest ecosystems that present different climatic conditions and vegetation types due to their location and hypsometric zone. The study area includes the forests of Pertouli and Taxiarchis, which are managed by the Aristotle University Forest Administration and Management Fund. The Pertouli is a coniferous forest in Central Greece with a maximum elevation of 2073 m a.s.l, and Taxiarchis is a broadleaved forest in Northern Greece with a maximum elevation of 1200 m a.s.l. To accomplish the goals of the current research, long–term (1974–2016) monthly precipitation and air temperature data from two mountainous meteorological were collected and processed. The PET was estimated using a parametric model based on simplified formulation of the Penman–Monteith equation rather than the commonly used Thornthwaite approach. Seasonal and annual precipitation, potential evapotranspiration (PET), and their ratio (P/PET) values were subjected to Mann–Kendall tests to assess the possible upward or downward trends, and Sen’s slope method was used to estimate the trends magnitude. The results indicated that the examined climatic variables vary greatly between seasons. In general, negative trends were detected for the precipitation time series of Pertouli, whereas positive trends were found in Taxiarchis; both were statistically insignificant. In contrast, statistically significant positive trends were reported for PET in both forest ecosystems. These circumstances led to different drought conditions between the two forests due to the differences of their elevation. Regarding Pertouli, drought trend analysis indicated downward trends for annual, winter, spring, and summer values, whereas autumn showed a slight upward trend. In addition, the average magnitude trend per decade was approximately −2.5%, −3.5%, +4.8%, −0.8%, and +3.3% for annual, winter, autumn, spring, and summer seasons, respectively. On the contrary, the drought trend and the associated magnitude per decade for the Taxiarchis forest were found to be as follows: annual (+2.2%), winter (+6.2%), autumn (+9.2%), spring (+1.0%), and summer (−5.0%). The performed statistical test showed that the reported trend was statistically insignificant at a 5% significance level. These results may be a useful tool as a forest management practice and can enhance the adaptation and resilience of forest ecosystems to climate change.

Spatio‐temporal trend analysis of drought in the GAP Region, Turkey

Spatio‐temporal trend analysis of drought in the GAP Region, Turkey

Drought occurrence in Different River Basins of India and blockchain technology based framework for disaster management

Drought assessment is crucial to mitigate its adverse impact, especially in India, where risk is more due to an increase in population and climate change. However, most of the studies deal with one or a couple of droughts and lack the interrelationship between all major drought types. The study investigates the spatio-temporal distribution of multiple drought types, individually and concurrently in India. Further drought trend analysis is performed based on their mean duration, mean spatial extent, and frequency. Moreover, the drought evolution process which explains the evolution of drought type into another type is also examined. Finally, a blockchain-based framework is proposed to improve the current drought risk management system to facilitate the drought fatalities to get their help and aid as soon as possible. Results demonstrate that hydrological and soil moisture droughts are observed to be more influential as compared to the other two drought types in most of the river basins of India. Further, it was found that 82% of concurrent droughts involve soil moisture drought in 16 out of 25 river basins. The present study facilitates a novel method to investigate drought from several perspectives over India, thus helps to provide important information for drought mitigation and adaptation strategies.

Drought trend analysis in a semi-arid area of Iraq based on Normalized Difference Vegetation Index, Normalized Difference Water Index and Standardized Precipitation Index

Drought was a severe recurring phenomenon in Iraq over the past two decades due to climate change despite the fact that Iraq has been one of the most water-rich countries in the Middle East in the past. The Iraqi Kurdistan Region (IKR) is located in the north of Iraq, which has also suffered from extreme drought. In this study, the drought severity status in Sulaimaniyah Province, one of four provinces of the IKR, was investigated for the years from 1998 to 2017. Thus, Landsat time series dataset, including 40 images, were downloaded and used in this study. The Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Water Index (NDWI) were utilized as spectral-based drought indices and the Standardized Precipitation Index (SPI) was employed as a meteorological-based drought index, to assess the drought severity and analyse the changes of vegetative cover and water bodies. The study area experienced precipitation deficiency and severe drought in 1999, 2000, 2008, 2009, and 2012. Study findings also revealed a drop in the vegetative cover by 33.3% in the year 2000. Furthermore, the most significant shrinkage in water bodies was observed in the Lake Darbandikhan (LDK), which lost 40.5% of its total surface area in 2009. The statistical analyses revealed that precipitation was significantly positively correlated with the SPI and the surface area of the LDK (correlation coefficients of 0.92 and 0.72, respectively). The relationship between SPI and NDVI-based vegetation cover was positive but not significant. Low precipitation did not always correspond to vegetative drought; the delay of the effect of precipitation on NDVI was one year.

Low Flow and Drought in a German Low Mountain Range Basin

Rising temperatures and changes in precipitation patterns in the last decades have led to an increased awareness on low flow and droughts even in temperate climate zones. The scientific community often considers low flow as a consequence of drought. However, when observing low flow, catchment processes play an important role alongside precipitation shortages. Therefore, it is crucial to not neglect the role of catchment characteristics. This paper seeks to investigate low flow and drought in an integrative catchment approach by observing the historical development of low flows and drought in a typical German low mountain range basin in the federal state of Hesse for the period 1980 to 2018. A trend analysis of drought and low flow indices was conducted and the results were analyzed with respect to the characteristics of the Gersprenz catchment and its subbasin, the Fischbach. It was shown that catchments comprising characteristics that are likely to evoke low flow are probably more likely to experience short-term, seasonal low flow events, while catchments incorporating characteristics that are more robust towards fluctuations of water availability will show long-term sensitivities towards meteorological trends. This study emphasizes the importance of small-scale effects when dealing with low flow events.

Low Flow and Drought in a German Low Mountain Range Basin

Rising temperatures and changes in precipitation patterns in the last decades have led to an increased awareness on low flow and droughts even in temperate climate zones. The scientific community often considers low flow as a consequence of drought. However, when observing low flow, catchment processes play an important role alongside precipitation shortages. Therefore, it is crucial to not neglect the role of catchment characteristics. This paper seeks to investigate low flow and drought in an integrative catchment approach by observing the historical development of low flows and drought in a typical German low mountain range basin in the federal state of Hesse for the period 1980 to 2018. A trend analysis of drought and low flow indices was conducted and the results were analyzed with respect to the characteristics of the Gersprenz catchment and its subbasin, the Fischbach. It was shown that catchments comprising characteristics that are likely to evoke low flow are probably more likely to experience short-term, seasonal low flow events, while catchments incorporating characteristics that are more robust towards fluctuations of water availability will show long-term sensitivities towards meteorological trends. This study emphasizes the importance of small-scale effects when dealing with low flow events.

Meteorological drought trend analysis by standardized precipitation index (SPI) and reconnaissance drought index (RDI): a case study of Gajapati District

Drought is taken into account as a natural hazard, which might be characterized mainly by its severity, duration, and areal extent. Among the above three dimensions, drought severity is that the main factor through which drought analysis was done. The paper aims at presenting the overall meteorological drought analysis of Gajapati District of Odisha by Reconnaissance Drought Index (RDI)and Standard precipitation Index (SPI), through DrinC software using SPI-3, SPI-6, SPI-9 & SPI-12, and RDI-3, RDI-6, RDI-9 & RDI 12 which were computed at multiple time steps (3, 6,9 and 12-month) for the period 1967-2002. The 12-month SPI and RDI series shows well-defined wet periods and dry periods compared to other months. it has been discussed, for identifying dry/wet periods, SPI 12 and RDI 12 shows greater utility than SPI 3 and RDI 3. The analysis of RDI-12 shows that, there was a Moderate drought was recorded during 1967-68, 1973-74, 1984-85, 1987-88. In the Gajapati region drought index, by SPI & RDI method showed that extremely affected by drought among 35 years was 1972-73 and severe drought occurred in 1979-80. Overall, there was a moderate drought situation within the Gajapati district.

Drought Trend Analysis Based on the Standardized Precipitation–Evapotranspiration Index Using NASA’s Earth Exchange Global Daily Downscaled Projections, High Spatial Resolution Coupled Model Intercomparison Project Phase 5 Projections, and Assessment of Potential Impacts on China’s Crop Yield in the 21st Century

Drought is among the costliest natural disasters on both ecosystems and agroeconomics in China. However, most previous studies have used coarse resolution data or simply stopped short of investigating drought projection and its impact on crop yield. Motivated by the newly released higher-resolution climate projection dataset and the crucial need to assess the impact of climate change on agricultural production, the overarching goal of this study was to systematically and comprehensively predict future droughts at unprecedented resolutions over China as a whole. rather than region-specific projections, and then to further investigate its impact on crop yield by innovatively using a soil water deficit drought index. Methodologically, the drought projections were quantified from very high resolution climate data and further predicted impacts on crop yield over China using the standardized precipitation–evapotranspiration index (SPEI) at a relatively high (25 km) spatial resolution from NASA’s Earth Exchange Global Daily Downscaled Projections (NEX-GDDP). The results showed that (1) overall, China is projected to experience a significant decrease in SPEI (−0.15/decade under RCP (representative concentration pathway) 4.5; −0.14/decade under RCP8.5). Seasonally, the decreasing rate of SPEI is projected to be largest in winter (−0.2/decade and −0.31/decade) and the least in summer (−0.08/decade and −0.10/decade) under respective RCPs. (2) Regionally, winter/spring will get drier, especially at high latitudes/altitudes (North China and Tibetan plateau), and summer/autumn will get wetter in southern China. (3) Both the frequency and duration for medium and severe drought are projected to decrease, while extreme drought, particularly in high latitudes/altitudes, is projected to increase. (4) The percentage of the potential crop production affected by drought would increase to 36% (47%) by 2100 under RCP4.5 (RCP8.5). Especially, the ratio impacted by extreme drought is projected to increase over time and with much worse magnitude under RCP8.5; thus, adaptive crop policies are expected to address such a risk.

A Counting Process Approach for Trend Assessment of Drought Condition

This paper discusses some methodological aspects of the historical analysis of drought, particularly the trend assessment. The Standardized Evapotranspiration Index (SPEI) is widely used as a measure of drought condition. Since different SPEI thresholds allow classifying the risk into moderate, severe, and extreme, the drought occurrence becomes a counting process. In this framework, would a statistical trend test based on a Non-Homogeneous Poisson Process (NHPP) give a similar result of the nonparametric Mann–Kendall (M-K) test? In this paper, we demonstrate that the NHPP approach is able to characterize the information given by the classical M-K approach in term of drought risk classes. Furthermore, we show how it can be used to reinforce the framework of drought trend analysis in combination with a standard non-parametric approach. At a global scale, we find that: (1) areas under increasing risk of drought identified by the NHPP approach are considerably larger in comparison to those identified by M-K; and (2) the results of the two tests are different during crucial periods such as hydrological droughts in winter and spring.

Streamflow and Hydrological Drought Trend Analysis and Forecasting in Cyprus

The persistent water shortage in Cyprus has been alleviated by importing freshwater from neighbouring countries, and severe droughts have been met with financial reimbursement from the EU at least twice. The goal of this research is to investigate and perform short-term forecasting of both streamflow and hydrological drought trends over the island. Eleven hydrometric stations with a 34-year common record length of the mean daily discharge from 10/1979 to 09/2013 are used for this purpose, with the relevant upstream catchments considered to represent pristine conditions. The Streamflow Drought Index (SDI) successfully captures the hydrological drought conditions over the island, and the performance of the index is validated based on both the historic drought archives and results from other drought indices for the island. The Mann–Kendall (M-K) test reveals that the annual and seasonal time series of the discharge volumes always illustrate a decreasing but insignificant trend at a significance level of a = 0.05; additionally, the decrease per decade in the average annual streamflow volume based on Sen’s slope statistic is approximately −9.4%. The M-K test on the SDI reveals that drought conditions intensified with time. Ten autoregressive integrated moving average (ARIMA) models are built and used to forecast the mean monthly streamflow values with moderate accuracy; the best ARIMA forecast model in each catchment is derived by comparing two model-performance statistical measures for the different (p,d,q) model parameters. The predicted discharge values are processed by the SDI-3 index, revealing that non-drought conditions are expected in most catchments in the upcoming three months, although mild-drought conditions are anticipated for catchments 7, 8 and 9.

The performance of SPI and PNPI in analyzing the spatial and temporal trend of dry and wet periods over Iran

Drought monitoring is carried out using various drought indices, including SPI, to generate time series of dry and wet periods. Furthermore, the dispersion of dry and wet periods was embossed with different intensities (high, medium, and low) over the data record years. Although these results were very necessary for planning and predicting future droughts, it appeared that the application of any trend over dry and wet periods could provide more accurate and unbiased or safer predictions in terms of analysis process. Generally, most of the researchers believed that the results of a drought trend analysis have been influenced by short-term persistence or significant autocorrelation with different lags on drought event time series and the mentioned impact should be preferably removed. Accordingly, drought monitoring was accomplished using SPI and PNPI drought indices to extract time series of dry and wet periods in terms of 50-year (1965–2014) annual rainfall data of 40 synoptic stations over Iran. Having used the basic and modified Mann–Kendall nonparametric tests, it was attempted to analyze the trend of dry and wet periods extracted from mentioned indices. The results represent the relative advantage of using the modified Mann–Kendall test in drought trend analysis. Furthermore, it was shown that the trend of dry and wet periods was negative in the majority of selected stations and that this trend was significant at 95% confidence level in northwest of Iran. Also, the results indicated the similar performance of SPI and PNPI indices in trend analysis of dry and wet periods.

Trend Analysis of Drought Events Over Upper Krishna Basin in Maharashtra

Drought is a significant natural disaster which leads to food, fodder and water shortages along with destruction of vital ecological system. Drought is acknowledged as a phenomenon associated with scarcity of water due to reduction in the amount of precipitation over an extended period of time, usually a season, a year or more in length. Droughts are frequently occurring in Upper Krishna basin in Maharashtra where about 80 percent of agriculture land is rain fed. Also this region is witnessing rapid urbanization due to industrial growth where thirst for water for drinking as well as industrial use is demanding. The study of drought trends is extremely important as it is related with food security and management of scarce water resource, which becomes critical in case of drought events. In this work, the drought trend of Standardized precipitation index (SPI) at 1-, 6-, 12-, 24- and 48- month time scales, Percent of Normal Precipitation (PNP) at Annual and Water-Year time scales and Seasonal rainfall (winter, pre-monsoon, monsoon and post monsoon time scales) are computed using long time series (1960-2012) of monthly precipitation data at 59 stations in the study area. The statistical significance at 95% confidence level as per Mann-Kendall and Sen's slope estimator are used for drought trend analysis over the Upper Krishna basin in Maharashtra. The PNP drought trend analysis at both annual and water-year time scale is able to detect significant trend at only 5 stations out of all rain gauge stations, SPI based drought trend analysis is found to be more sensitive to multiple time scales. As the SPI-1 time scale is able to detect significant trend at only 4 stations, number of stations having significant trend increases as the SPI time scale increases up to SPI-48 at 50 stations. Drought trend of Seasonal rainfall time series vary as per the classes. Pre-monsoon time scale detects significant negative trend at 41 stations with no significant positive trend at any of the stations. Monsoon time scale detects only 2 positive and 1 negative significant trends at total stations. Post-monsoon time scale is not able to detect any significant trend at all stations. The results indicate that, there is negative trend of pre-monsoon rainfall at over 63 percent of area. SPI- 48 time scale is able to detect significant trend at over 84 percent of area. This analysis may help to solve problems associated with floods, droughts and allocation of water for agriculture, industry, hydro-power generation, domestic and industrial use.

Trend Analysis of Drought in the Guinea and Sudano-Sahelian Climatic Zones of Northern Nigeria (1907-2006)

A quantitative assessment of drought characteristics and their associated variability in the Northern Nigeria was carried out. Monthly rainfall data for all the selected locations which span a period of 100 years (1907-2006) collected from the Climate Research Unit (CRU) database were used. The resolution of the data is 0.5 × 0.5 degrees in longitude and latitude. The long-term rainfall records were analyzed for drought using standardized precipitation index (SPI). The 100 years of Study was subdivided into 10 decades. Using Ilwis GIS software, the SPI results were presented on a spatial digitized map of northern Nigeria. This was done using the coordinates got from the Nigerian Meteorological Agency, Lagos Nigeria. The results of SPI analysis revealed that there were several drought years in the study period. Analysis further revealed that decade 7 to decade 9 (i.e. 1967-1976, 1977-1986, 1987-1996) witnessed persistent drought in the northern Nigeria. These were classified into mild, moderate, severe and extreme drought conditions. Near normal dry or mild drought was predominant in the 100 years of study. Mild drought has the highest number of occurrence in the northern Nigeria. A closer examination shows that north eastern part of Nigeria is susceptible to moderate drought. SPI analysis for 1, 3, 6 and 12 months was carried out. According to the Nigerian Meteorological Agency Classification, 1 month represents meteorological drought, 3 months represents agricultural drought, 6 months represents hydrological drought and 12 months represents socio-economic drought. The SPI analysis revealed distinct period of negative and positive values in which negative values indicate occurrence of drought and positive values imply there is no drought. This study has provided useful information and pro-active intervention to reduce the impact of drought which will be helpful to effectively plan rain-fed agriculture in northern Nigeria.