1 Introduction

Recent extreme weather occurrences, such as droughts and floods brought on by irregular rainfall, have resulted in losses in agricultural production. Hence, mitigation and adaptation measures have been called for. These actions can be implemented with a thorough characterization of the natural phenomenon of hazards. Numerous studies have shown that changes in climate variables, such as an increase in the frequency of heavy rainstorms, a decrease in the number of rainy days, and the occurrence of dry spells during the rainy season, are the foreseeable characteristics of changing rainfall patterns. An investigation in the Brahmaputra and Barak basins revealed that annual and monsoon rainfall has reduced since 2001, which is associated with an increase in the number of deficit years (Deka et al. 2013; Rathore et al. 2013). Contrary to other natural disasters, droughts take a long time to develop and frequently stretch a large area, making it difficult to predict when they will begin and to what degree they will be severe. It is a natural phenomenon caused by a persistent shortage of rainfall, causing hydrological, agricultural, and socio-economic impacts. Since the majority of Indian agriculture is rainfed, the roughly four-month monsoon season, from June to September, has a significant impact on the country’s agricultural industry. This makes the monsoon’s behaviour extremely important for the nation’s agricultural production.

The occurrence of drought conditions is frequently sparked by an increase in the frequency of dry spells, which has detrimental effects on the economy and society. Longer dry spells may impair the availability of surface and groundwater resources, whereas shorter dry spells frequently impact agricultural operations. About 50 million people in India experience drought every year, and 16% of the country’s total land area is drought-prone (Arumugam and Anbazhagan 2017). Drought has traditionally been a frequent occurrence in dry and semi-arid areas. This is no longer the case because many areas with considerable rainfall frequently experience severe water shortages. For instance, Cherrapunji in Meghalaya, which is the second rainiest place on earth and receives over 11,000 mm of rain annually, currently experiences meteorological drought (Ray et al. 2015) for approximately nine months in a year (NDMA 2010). Other instances of drought occurrences in high rainfall regions of North East India are Guwahati city of Assam (Jhajharia et al. 2007), North Lakhimpur district of Assam (Shrivastava et al. 2008), Tura town of Meghalaya (Ray et al. 2013), East Sikkim district (Kusre and Lalringliana 2014), and Nagaland (Nongbri et al. 2016). Parida and Oinam (2015) also reported drought occurrences in northeastern region of India. Thus, drought can occur at any place, irrespective of the climate, and is an issue related to water resource management (NDMA 2010).

Assam is situated in one of the areas with heavy rainfall, where floods occur virtually every year. However, it has recently experienced drought-like situations (Assam State Disaster Management Authority 2022) twice in 2010 and 2014, affecting large areas of Assam. According to a report from the Assam State Disaster Management Authority published in 2022 and also from the report published by the Department of Environment and Forests, Government of Assam in 2015 (Department of Environment and Forests 2015) on Assam State action plan on climate change, the number of drought weeks will increase by 75% from the baseline period of 1971–2000 to the future period of 2021–2050, having an impact on Assamese people’s livelihood due to reduction in production in agriculture and allied sectors. It has also been reported that an increase in the frequency of dry spells has produced extensive damage to paddy cultivation in the North Brahmaputra Plain zone (Neog et al. 2020). In a report published by Assam State Disaster Management Authority (2015), several districts of Assam were severely impacted due to drought-like conditions in 2005 and 2006, which had an impact on more than 1.95 crore people whose livelihood depended on agriculture and allied sectors. A loss of over 100 crore rupees was also reported due to crop failure and other incidentals.

Thus, it becomes crucial to measure and quantify the extent of drought so that timely and effective measures can be made to mitigate its impact. Drought indices are used for quantifying droughts and help decision-makers to get quantitative data on the characteristics of drought (Dogan et al. 2012). Understanding a drought’s features, such as its duration, severity, inter-arrival time, and frequency, is essential for coping with the misery it might cause. With these characteristics known, drought mitigation planning becomes quite simple and easy to implement (Pandey and Ramasastri 2001). The present study attempts to characterize drought occurrences in each district of Assam using the standardized precipitation index (SPI).

2 Study area and data

Assam is situated in the northeastern part of India and comprises 35 districts. It covers an area of 78,438 km2, including both plains and hills. With an average annual rainfall of 2201 mm between 1951 and 2020, it received more precipitation than most regions in India. The Brahmaputra River, the Barak River, and their tributaries make up Assam’s primary drainage system. The state has a tropical monsoon climate, which is characterized by persistent heavy rainfall and high humidity. Figure 1 shows the state of Assam and its 35 districts.

Figure 1
figure 1

Study area: Assam and its districts.

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Gridded rainfall data with a spatial resolution of approximately 25 km at a daily scale has been obtained from the India Meteorological Department website (Pai et al. 2014) for a period of 70 years from 1951 to 2020. For this study, the daily data is retrieved from the binary raw files, converted to monthly data, and then extracted for each district in Assam through a series of preprocessing in Python and GIS operations. The yearly rainfall in Assam for the past 70 years has been about 2201 mm, with roughly 1438, 150, 56, and 558 mm falling during the monsoon, post-monsoon, winter, and pre-monsoon, respectively. It shows that the monsoon season (June–September) accounts for around 65% of the annual rainfall and that the pre-monsoon and monsoon seasons (from March to September) account for 91% of the total annual rainfall. This implies that any deviation from the normal during these two seasons will have a significant impact on the state’s water resources. The long-term annual rainfall scenario in Assam and its districts is illustrated in figure 2. The data shows that the Hojai district experienced the least amount of rainfall, whereas Kokrajhar experienced the most. The coefficient of variation of rainfall among the districts was determined as 19.5%.

Figure 2
figure 2

Rainfall scenario in Assam and its districts.

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3 Methods

SPI was employed in the current study as an indicator for identifying drought. This index needed data on precipitation. Rainfall is the main indicator of drought and the foundation of most drought monitoring systems, even if it may not encompass the whole range of drought characteristics. SPI has a wide range of acceptability among various researchers on drought as it may be used to monitor droughts in relation to certain water resources at various time scales (Gurrapu et al. 2014). It is regarded as one of the top indicators for determining the severity of a drought (Keyantash and Dracup 2002; Dogan et al. 2012) and was suggested by Morid et al. (2006) for use in drought monitoring in Tehran, Iran, as it performed well in spotting the start of a drought. SPI may serve as a useful indicator for describing various aspects of agricultural drought because of its adaptability in adopting sliding time scales (White and Walcott 2009). If the rainfall deficit persists for a longer period, especially during the growing season of crops, agricultural drought may arise (Faiz et al. 2021) due to a shortage of soil moisture in the crop root zone. A shorter time period, such as 3- or 6-months, would be sufficient to describe a drought that affects agriculture, whereas a longer time scale, such as 12-, 24-, or longer months, would be significant from the perspective of water resources in reservoirs and groundwater. A 1-month time period for a drought analysis would frequently produce inaccurate conclusions in areas with considerable rainfall variability. Since the majority of crops grown in Assam have a growing period of 3–5 months, a timescale of 3 months is employed in this study to reflect the effects of drought on agriculture.

The SPI was developed by McKee et al. (1993) and extensively described by Edwards and McKee (1997). The Gamma probability distribution function is used to calculate the SPI as follows:

$$G\left( x \right) = \frac{1}{{\beta^{\alpha } \varGamma \left( \alpha \right)}}\int_{0}^{x} {x^{\alpha - 1} e^{ - x/\beta } } dx,$$
(1)

where \(\alpha\) and \(\beta\) are the shape and scale parameters, respectively. To determine these parameters, maximum likelihood solutions are used (Thom 1966) as follows:

$$\alpha =\frac{1}{4A}\left[1+\sqrt{\frac{4A}{3}} \right],$$
(2)
$$\beta =\frac{\overline{X}}{\alpha },$$
(3)
$$A={\text{ln}}\left(\overline{x }\right)-\frac{\sum {\text{ln}}\left(x\right)}{n},$$
(4)

where \(n\) is the number of rainfall observations and \(\overline{x }\) is the mean rainfall. When x = 0, the Gamma function is undefined, thus for rainfall = 0, the cumulative probability is:

$$H\left(x\right)=q+\left(1-q\right) \times G\left(x\right),$$
(5)

where q is the probability of zero events. If m is the number of zeros in the series of rainfall, then q becomes m/n (Thom 1966). Further in SPI calculation, the cumulative probability, \(H\left(x\right)\) is normalized to become SPI as follows:

$$\begin{aligned}SPI= & -\left[t-\frac{{c}_{0}+{c}_{1}t+{c}_{2}{t}^{2}}{1+{d}_{1}t+{d}_{2}{t}^{2}+{d}_{3}{t}^{3}}\right]\\& \text{for } 0<H\left(x\right)\le 0.5,\end{aligned}$$
(6)
$$\begin{aligned}SPI= & +\left[t-\frac{{c}_{0}+{c}_{1}t+{c}_{2}{t}^{2}}{1+{d}_{1}t+{d}_{2}{t}^{2}+{d}_{3}{t}^{3}}\right]\\& \text{for } 0.5<H\left(x\right)\le 1,\end{aligned}$$
(7)
$$t=\sqrt{{\text{ln}}\left(\frac{1}{{\left(H\left(x\right)\right)}^{2}}\right) }\quad\text{for }0<H\left(x\right)\le 0.5,$$
(8)
$$t=\sqrt{{\text{ln}}\left(\frac{1}{{\left[1-H(x)\right]}^{2}}\right)}\quad{\text{for}}\ 0.5<H\left(x\right)\le 1,$$
(9)
$${c}_{0}=2515517;\ c_{1}=0.802853;\ {c}_{2}=0.010328;\ {d}_{1}=1.432788;\ {d}_{2}=0.189269;\ {\text{and}}\ {d}_{3}=0.001308.$$
(10)

Ghosh (2010) compared four probability distributions, Weibull, normal, lognormal, and Gamma, to fit the monthly monsoon (June–September) rainfall in AM (Assam and Meghalaya) and NMMT (Nagaland, Manipur, Mizoram and Tripura) regions. The study found that Gamma distribution fits the best in both regions. The study period they chose (1951–2000) is also within the study period in the current research. Therefore, the source code of the SPI generator, which is based on Gamma distribution fitting, was not modified in this study. Because SPI values are normalized, they represent both wet and dry conditions equally. Table 1 shows how McKee et al. (1993) classified drought situations based on SPI values. In this study, a drought event begins when the SPI reaches –1.0 or lower and ends when the SPI becomes positive. In this study, an SPI generator program developed by the National Drought Mitigation Centre has been employed. This program can calculate SPI at multiple time scales and drought durations for multiple drought severity levels.

Table 1 Classification of drought based on SPI range.
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Jain et al. (2015), Merabti et al. (2018), Kumar et al. (2019), Surmaini et al. (2019), Ekwezuo and Ezeh (2020), Oikonomou et al. (2020), Adisa et al. (2021), Mianabadi et al. (2022), Razmi et al. (2022), Saini et al. (2022), and Jafarpour et al. (2023) are some recent applications of SPI in different parts of the world. Applications of drought indices such as the SPI in the northeastern region of India are very limited. Few recent applications can be found in Pai et al. (2010), Guhathakurta et al. (2017), Taggu and Shrivastava (2018), Hangshing and Dabral (2018a, b), Sharma et al. (2022), and Lairenjam and Hangshing (2023). The ability of SPI to characterize drought in a multitude of time scales makes it a perfect tool for monitoring different variations of drought (Zargar et al. 2011; Faiz et al. 2021). World Meteorological Organization also recommended using SPI for hydro-meteorological services at the national level (World Meteorological Organization 2012). A seasonal estimation of precipitation, given by a 3-month SPI (SPI03), represents short- and medium-term moisture conditions and could be more useful in illustrating moisture conditions in agricultural areas (World Meteorological Organization 2012). One of the features of drought is how frequently a drought spell resurfaces. In this study, the average inter-arrival time of drought (IAT), which is the average months between two consecutive onsets of drought, was determined.

4 Results and discussion

SPI03 of all the districts was averaged each month and displayed in figure 3 to depict the general drought state in Assam. In terms of time coverage, the positive SPI03 (shown by blue colour) was found to be slightly more dominant than the negative SPI03 (represented by orange colour). However, the wettest magnitude of SPI = 2.25, reported in February 1993, was less severe than the driest magnitude of SPI = –3.09, which was observed in February 1999. This plot has shown that there have been occasional droughts in addition to occasional floods in Assam.

Figure 3
figure 3

Three-month SPI in Assam.

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When computing a 3-month SPI (SPI03) for a given month, the sum of that month’s rainfall and the rainfall from the preceding two months are considered. For instance, SPI03 of May 2000 used the total amount of precipitation in March, April, and May 2000. As a result, it will be helpful to first estimate the SPI03 for August and September of each year since these two series will cover the entire four months of the monsoon season. These values will be crucial for Kharif crops. Likewise, with knowledge of the growing period of a crop, it can be studied for any type of crop. In the present study, out of 70 years (1951–2020), 54 years were affected by drought in the month of August in at least one of the 35 total districts in Assam (figure 4a). Similarly, 53 years of the total 70 years were affected by drought in the month of September in minimum one of the 35 total districts in Assam (figure 4b). Again, in the 70 years period, every district had witnessed at least seven or five drought years in the month of August (figure 5a) and September (figure 5b), respectively. August drought ranged between 7 and 14 years, while September drought ranged between 5 and 14 years of the total 70 years. The Charaideo district witnessed the highest number of August droughts (14 years), while Lakhimpur, Bishwanath Chariali, and Bongaigaon districts had the highest number of September droughts with 14 years in total. On average, the percentage of August and September drought for the districts of Assam is approximately 15%.

Figure 4
figure 4

Number of districts affected by (a) August drought and (b) September drought during the 70 years period.

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Figure 5
figure 5

Number of years affected by (a) August drought and (b) September drought across the 35 districts of Assam.

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The years having ten or more drought-affected districts in the month of August are 1961 (15), 1962 (15), 1967 (10), 1971 (11), 1986 (14), 1994 (15), 1996 (17), 2001 (18), 2006 (15), 2009 (10), 2011 (11), 2013 (19), 2016 (19), 2018 (15), and 2019 (11). Similarly, for September drought, they were in the years 1951 (13), 1962 (19), 1967 (11), 1969 (11), 1976 (18), 1994 (22), 2001 (14), 2006 (19), 2011 (10), and 2012 (20). This nature of spatial variability indicates that droughts have been more frequent in the last 35 years of the study period. Also, the periods of 1960s, 2000s, and 2010s have been more affected by drought. In August 2013, 19 districts, viz., Tinsukia, Dhemaji, Hojai, Kamrup Rural, West Karbi Anglong, Dima Hasao, Cachar, Hailakandi, Karimganj, South Salmara Mankachar, Kokrajhar, Chirang, Dhubri, Barpeta, Baksa, Bongaigaon, Bajali, Goalpara, and Nalbari, were affected by at least moderate drought. Similarly, in August 2016, 19 districts, viz., Dhemaji, Dibrugarh, Charaideo, Jorhat, Majuli, Kamrup Metro, Kamrup Rural, D Hasao, Cachar, Hailakandi, Karimganj, Barpeta, Baksa, Bajali, Darrang, Udalguri, Tamulpur, Nalbari, and Sonitpur were affected by drought. For September, the maximum number of drought-affected districts were seen in 1994 with the 22 drought-affected districts were Tinsukia, Dhemaji, Sivasagar, Jorhat, Lakhimpur, Majuli, Bishwanath Chariali, Nagaon, Hojai, Kamrup Rural, West Karbi Anglong, Cachar, South Salmara Mankachar, Kokrajhar, Chirang, Dhubri, Baksa, Bongaigaon, Goalpara, Darrang, Udalguri, and Tamulpur.

In terms of drought severity, for August, Sivasagar witnessed the most severe drought in 1978, with an extreme SPI value of –3.42. The next severe August drought occurred in Lakhimpur in 2001 (SPI = –3.02), followed by Udalguri in 1971 with an extreme SPI value of –2.75. Similarly, for the September drought, the most extreme drought event occurred in the same district – Sivasagar, in the same year (1978) with an extreme SPI value of –3.84. This was followed by the Kamrup Rural district in 2006 (SPI = –3.27) and then by Bishwanath Chariali district in 2012 (SPI = –3.06). In general, drought events have been more severe in the years – 1994, 1996, 2001, and 2006. Other districts such as Majuli, Hojai, Kokrajhar, Bajali and Bongaigaon were more affected than the rest of the districts in terms of drought magnitude spanning the 70 years period.

In the previous sections, drought events in various districts of Assam in the month of August and September were discussed. Figure 6(a, b) illustrates the number of droughts (moderate, severe, extreme and total drought) and their percentages in the 70 years period considering all the months. It is found that the total number of drought events ranged between 101 and 143 months, indicating that every district in Assam had been affected by drought at least 12.1% of the entire period. On average, the districts in Assam are affected by drought in 121 months (14.5%) of the total 838 months. It comprises 68 months of moderate drought (8.1%), 31 months of severe drought (3.8%), and 22 months of extreme drought (2.6%). The maximum occurred in Bishwanath Chariali with 143 months out of 838 months, with 81 months of moderate nature, 42 months of severe nature, and 20 months of extreme nature. On the other hand, the minimum number of droughts that occurred in the Karbi Anglong district was 101 months. However, 27 months of this is extreme in nature, which is more than Bishwanath Chariali.

Figure 6
figure 6

(a) Number of droughts and (b) percentage of drought in the various districts of Assam for moderate, severe, and extreme drought conditions.

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The highest number of moderate, severe, and extreme droughts occurred in Bishwanath Chariali (81 months), South Salmara Mankachar (43 months), and Sivasagar (34 months). Tamulpur district was found to be affected by least number of extreme droughts (10 months only). The spatial distribution of the total number of droughts in Assam is shown in figure 7. It shows that droughts are more frequent in the northern (northeastern), western and southern parts of the state. The average number of droughts that occurred in each month of the year is also checked and found that there is little variation, indicating that droughts in Assam occurred in all seasons. Analyzing the time series of SPI values, it is observed that positive SPIs (wet conditions) occurred in the state just a little more than negative SPIs. This shows that there is potential to make up the dry condition, however, the problem arises due to the fact that most of the flood water is not able to enter the soil profile and recharge the groundwater resources of the state. Hence, interventions to increase water entry are required to be taken up as a watershed management practice.

Figure 7
figure 7

Spatial distribution of total number of droughts in Assam.

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Maximum and average durations of drought occurred in each district of Assam were computed and is shown in figure 8. Average duration of drought due to deficit in rainfall in a cumulative 3-months basis ranges between 4 and 7 months with highest average month in the Tamulpur district. Furthermore, the maximum duration of drought occurred in the state ranges between 14 and 41 months. The ranges were observed for districts – West Karbi Anglong (lowest) and Sonitpur (highest). The results showed that the average duration of drought in various districts of Assam is approximately 5.2 months, while the maximum duration is about 20.4 months. Other districts such as Kamrup Metro, Lakhimpur, Sivasagar, and Bishwanath Chariali also had high average duration of droughts.

Figure 8
figure 8

Maximum and average duration of drought in various districts of Assam.

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The SPI generator used in this study can also compute the start and end date of drought spells. For the sake of space in this manuscript, only the onset and end of 3-month droughts for the district with the highest number of droughts (Bishwanath Chariali) is presented in table 2. For all the other districts, it is provided as supplementary material. As seen in the table, there are 41 drought spells in Bishwanath Chariali during the span of 70 years from 1951 to 2020, of which 18 are moderate, 15 are severe, and 8 are extreme drought spells. The most extreme drought spell spans 15 months from July 2012 to October 2013 (peak SPI = –3.83). The drought of August 1959 to July 1960 (peak SPI = –3.43) spanning 11 months and the drought of November 1998 to May 1999 (peak SPI = –2.85) spanning six months are the second and third extreme droughts, respectively, in terms of severity. With respect to duration, the drought of January 2000 to April 2002, spanning more than two years (27 months), was the longest spell, which also happened to be a severe drought. The second and the third longest drought spells occurred in the drought of June 1961 to June 1963 (24 months) and September 2008 to March 2010 (18 months), in which both spells were of the severe drought category. The results indicate that there is no direct relationship between drought severity and its duration. Both of these characteristics are crucial in monitoring drought. A less severe drought with a very long spell would inflict socio-economic damages slowly but would aggregate to huge ones. On the other hand, shorter spell droughts with extreme severity could also cause irreversible damage to crops, thereby affecting the socio-economic conditions. In all the districts, the drought of spells in less than a year comprised more than 80% of all drought spells. In Bishwanath Chariali, of the 41 drought spells, 37 spells had been for less than a year, two spells were between 1 and 2 years, and the other two spells had been for two years and more. The drought spells shown at sl. no. 30–33 given in table 2 are compliant with the report published in Assam State Disaster Management Plan (Assam State Disaster Management Authority 2022).

Table 2 Onset, end, duration, severity, and drought category of 3-month drought (SPI03) in Bishwanath Chariali.
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In this study, the average inter-arrival time (IAT) of drought, or the average interval between the onset of consecutive droughts, was also determined. This parameter indicates how quickly and frequently a drought spell will occur at a particular place. The average IATs for the various districts of Assam are shown in figure 9(a) and their spatial variability is shown in figure 9(b). The average IATs of the districts of Assam range between 15 and 25 months. Smaller IATs indicate the tendency of frequent drought spells and vice-versa. Thus, the Dhubri district, with the smallest average IAT of 15 months, is likely to be affected by frequent drought spells, while Lakhimpur, with the highest average IAT of 25 months, was less affected by frequent drought spells. In a drought vulnerability analysis conducted by IIT Mandi and IIT Guwahati (2020), Dhubri was found to be the most vulnerable district. On analysis, it was determined that in most of the districts in Assam, a drought spell (whether it was of only one month or more) occurred every 20 months. A point to be considered is that the above figures are the outcomes of the SPI series computed using 3-month cumulative rainfall. Since SPI03 is effective in monitoring seasonal drought or, to some extent, agricultural drought, in which soil moisture deficit in the last three months is replicated, this study has also suggested that, after every 20 months, at least a month of agricultural/seasonal drought had occurred in most of the districts in Assam. To understand the importance of time scale selection, average IATs for SPI12 and SPI24 were also determined. These two SPIs signify the deficit in rainfall accumulated over 12 and 24 months, respectively. It is found that the average inter-arrival time of drought for deficit rainfall over 12- and 24-month periods is approximately 6 and 10.5 years. The spatial distribution in figure 9(b) shows that drought spells repeated quicker in the western Assam (Dhubri district lies in this region) and also in the southern region of Assam. Central and northern parts of Assam were comparatively less affected by frequent drought spells.

Figure 9
figure 9

Average inter-arrival time of drought in various districts of Assam.

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Sahana et al. (2021) mentioned that Assam is one of the states in India that is affected by moderate to severe drought and is also put in the moderate to severe drought risk category. The Disaster Management Authority of Assam (Assam State Disaster Management Authority 2022) has also reported that the majority of the districts in Assam, except southern districts, would be more vulnerable to drought in the future, with a potential increase in the number of drought weeks. The above drought occurrences do not necessarily translate to the worst conditions. A district well-equipped with irrigation systems and water resources could cope with the drought situation easily. So, a vulnerability analysis would add value to the preparation of a framework for drought mitigation planning in the state, which is currently taking place with consideration of both the physical and socio-economic status of the state. Districts with a greater number of droughts, greater duration of drought spells, and smaller IATs between two consecutive drought spells are recommended to fasten mitigation and adaptation planning. The results of this study, which used the recommended drought indicator – SPI at a 3-month time scale, would benefit the efforts being made by the Disaster Management Authority, Agriculture Department, Irrigation Department, and Water Resources Department of Assam in proper planning, action, and management of several entities with regards to drought in the state.

5 Conclusions

This study found that 91% of the average annual rainfall occurred during pre-monsoon and monsoon seasons, suggesting great dependency on these two seasons for the growth of agriculture sectors. This also led to the suggestion that there is an urgent need to turn to irrigation-based systems from the traditional rainfed ecosystems. The dominant positive SPI series also suggested that there is enough potential for developing an irrigation system and recharging groundwater resources. The percentage of August and September droughts representing monsoonal drought in Assam was approximately 15% in the 70 years (1951–2020) period. Also, the total percentage of drought in Assam was about 14.5% of the entire period, suggesting that irrespective of the season, drought will occur. Based on the number of droughts, Bishwanath Chariali was the most affected district, while Karbi Anglong was the least affected one. In terms of severity, Sivasagar district was found to be affected by the greatest number of droughts of extreme nature. The average duration of drought in Assam was found to be about 5.2 months, in which Sonitpur, Kamrup Metro, Lakhimpur, Sivasagar, and Bishwanath Chariali districts had high drought durations. This study also found that droughts occur faster in the western region of Assam, including Dhubri district, which had the lowest IAT of SPI03 drought. It is concluded that districts with a greater number of droughts, greater duration of drought spells and smaller IATs between two consecutive drought spells are required to set up drought mitigation planning.