The variability and distribution of rainfall are uniquely significant for climatic risk prediction. This study aims to assess spatiotemporal rainfall variability and flash flood intensity events in the Sylhet haor region of Bangladesh by analyzing rainfall data from April for the period 1995–2022. For this, we used both Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) data and Bangladesh Meteorological Department (BMD) daily rainfall data. Rainfall patterns were studied using zonal statistics in ArcGIS and graphical illustration. The results revealed that the rainfall pattern was erratic and showed a range of spatiotemporal variability. If the average rainfall exceeds 250 mm in Meghalaya and Assam and 400 mm in Sylhet, severe flash floods may occur in the Sylhet haor region. An increase in pre-monsoon rainfall and its shift from May to April may increase the intensity of flash floods and consequently damage the rice crop. This finding might help flood management agencies to develop flood management strategies, prepare flood contingency plans, provide real-time and advanced warnings to strengthen flood warning and forecasting systems, and schedule seasonal agricultural activities.

  • Comparative analysis of April rainfall trends in the Assam, Meghalaya, and the Sylhet haor region between 1995 and 2022.

  • Correlation between rainfall from Assam and Meghalaya and flash flood probability in the Sylhet haor region.

  • Flash flood severity forecast in the Sylhet haor region.

ArcGIS

Aeronautical Reconnaissance Coverage Geographic Information System

BMD

Bangladesh Meteorological Department

BWDB

Bangladesh Water Development Board

CHIRPS

Climate Hazards Group Infrared Precipitation with Station

DBHWD

Department of Bangladesh Haor and Wetland Development

LPA

Long-Period Average

The variability in rainfall over time and space is one of the most significant features of Bangladesh's climate. The predominant climate characteristic in the northeastern Sylhet haor region of Bangladesh is rainfall (Hasan et al. 2012). The Sylhet haor region has a subtropical monsoon climate, and precipitation increases during the pre-monsoon season (April–May), with rainfall ranging from about 490 mm in the southwest to roughly 1,290 mm in the northeast (Nowreen et al. 2014; DBHWD 2017). The haor area, which is located directly below the hills of the Indian states of Assam, Meghalaya, and Tripura, has some of the worst hydrological conditions, such as extremely high rainfall and subsequent flooding (Kartiki 2011; Hossain & Naser 2014). The flooding in the haor area is associated with the amount of rainfall received in the upstream catchment in India (Meghalaya, Barak, and Tripura Basins in India) and often occurs on short notice (Adnan et al. 2019). This rapid flooding with a high discharge and velocity is called a flash flood. The haor region receives water from the catchment slopes of the Shillong Plateau over the borders in India to the north and the Tripura Hills in India to the southeast (Uddin et al. 2013; Bari et al. 2015).

The sudden flash flood in April is the biggest threat to the agriculture of the haor region (Kamruzzaman & Shaw 2018). Flash flood damages were maximum in 1997, 2000, 2002, 2004, 2007, 2010, 2012, 2015, 2016, 2017, 2019, and 2022, and in these years, the flash flood occurred in the haor area in April and also because the duration of the flash flood was the maximum (Salauddin 2010; Roy et al. 2017; Abedin et al. 2022; Rahman et al. 2022). The rainfall pattern in the upstream catchment has a significant impact since floods in the haor area are greatly influenced by rainfall on the nearby Indian side (Basher et al. 2018). A lot of rain falls in Meghalaya and the adjoining haor region of Sylhet when moisture-rich monsoon air sweeps up the hills and mountains of Meghalaya. Additionally, the local rainfall runoff from the Barak valley, located in southern Assam, with that from nearby mountainous areas, runs down the river Barak and its many tributaries before being discharged into Sylhet, Bangladesh (Dey et al. 2021; Haque et al. 2021).

The Bangladesh Water Development Board (BWDB) has revealed that more floods are occurring in the haor area than ever before. Numerous tracts of land in Sylhet and neighboring haors have been overwhelmed by flash floods brought by torrents of water flowing upstream from Meghalaya and heavy rainfall, trapping hundreds of people there (Jahan 2019). Additionally, there is a high chance of getting more floods because most of the sub-districts close to the Indian border may get flooded by the onslaught of water from upstream (Rashidin et al. 2019). Masood et al. (2015) projected that pre-monsoon rainfall in haor place may be extended by 11.4% in the near future (2015–2039), and the accelerated quantity is 33.6% from 2075 to 2099. The haor region has a greater dominance of rainfall variability than other regions of Bangladesh (Chowdhury et al. 2016). Due to inconsistent rainfall, several studies predicted that the flash flood depth would increase in the haor region in the future (Choi et al. 2021). Additionally, there is a possibility of shifting the flash flood time in the future (Masood & Takeuchi 2016). It inevitably requires a thorough understanding of the local rainfall pattern in this situation.

It is crucial to comprehend the characteristics of rainfall variability to reduce damages from the disaster. Now, researchers are concentrating on predicting the rainfall during the pre-monsoon and monsoon seasons (Rana et al. 2007; Terao et al. 2013). The periodicity and trends in the pattern of precipitation are apparent and have been demonstrated in many studies in broader aspects, both spatially and temporally. However, adequate studies are lacking in the regional context. The impacts of dynamic rainfall patterns on northeast India or, comparatively, a smaller state like Assam are less explored and less known till now, making the future scenario more uncertain for flash flood risk management in Bangladesh. However, this study aims to establish a relationship between flash flood probabilities in the Sylhet haor region with rainfall from Assam and Meghalaya and the prediction of flash flood intensity in haor that would provide suggestive information for flood risk managers and climate forecasters.

Description of the study region

A haor is a massive geological depression with a saucer- or bowl-like shape that is submerged during the monsoon but dries out afterward (Irfanullah et al. 2011; Miah 2013). The Sylhet haor region encompasses seven districts: Sylhet, Sunamganj, Habiganj, Maulvibazar, Netrokona, Kishoreganj, and Brahmanbaria. Flash flooding is one of the most recurrent natural disasters in those areas. The Sylhet haor area lies just below the hilly regions of Assam and Meghalaya in India. Meghalaya is the wettest place on Earth, with an average annual rainfall as high as 12,000 mm in some locations (Murata et al. 2007; Das et al. 2014). Assam is most affected in the northeastern region of India due to rainfall-related disasters. However, the average pre-monsoon rainfall has been increasing since the fourth quarter of the 19th century (Kamal et al. 2018). The rainfall pattern of the upstream catchment on the Indian side largely affects flooding in the Sylhet haor region (Tinker & Husain 2020). Due to its geographical location, flood water quickly travels toward the haor areas of Bangladesh along the transboundary rivers (Kartiki 2011; Hossain & Naser 2014). We, therefore, used the District/State shapefile (Figure 1) as our study area, which covers the whole of Meghalaya State, a small portion of Assam State, and the entire Sylhet haor region of Bangladesh.
Figure 1

Location of the study area – Meghalaya, Assam (part), and the Sylhet haor region of Bangladesh.

Figure 1

Location of the study area – Meghalaya, Assam (part), and the Sylhet haor region of Bangladesh.

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Fieldwork and questionnaire survey

A questionnaire survey was administered in several upazilas in the Sunamganj, Sylhet, Maulvibazar, Kishoreganj, and Brahmanbaria districts between November 2021 and April 2022. A total of 298 farmers who were randomly chosen from high and moderate flash flood-prone areas provided information on the timing of the flash flood. Respondents opined that flash floods typically occur during the second and third weeks of April in high-risk areas and between the third and fourth weeks of April in moderately vulnerable areas (Figure 2).
Figure 2

Timing of flash flood occurrence in high and moderately flash flood vulnerable zones.

Figure 2

Timing of flash flood occurrence in high and moderately flash flood vulnerable zones.

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Rainfall data used and analysis

We used the Climate Hazards Group Infrared Precipitation with Station (CHIRPS) data (https://data.chc.ucsb.edu/products/CHIRPS2.0/global_monthly/tifs/) for long-term rainfall analysis. As per requirement, we analyzed CHIRPS global monthly data for April from 1995 to 2022. We produced a year-wise rainfall pattern map with contours. We used Zonal Statistics as a Table, an ArcGIS Spatial Analyst geoprocessing tool, to calculate statistics like the average in defined zones. In ArcGIS, the Zonal Statistics as Table tool generates a summary table based on the specified input value raster, statistical function, and zonal extents.

Selection of flash flood years

Following a search of numerous research papers, a thesis, newsletters, conference proceedings, and reports, flash flood years were selected for this study. The comments of haor farmers on flash flood occurrence years were also taken into consideration. From November 2021 to April 2022, a field survey was conducted for this purpose. However, historical databases indicate that the Sylhet haor region experienced devastating flash floods in 1997, 2000, 2002, 2004, 2007, 2010, 2012, 2015, 2016, 2017, 2019, and 2022. As a result of the prolonged flooding period, considerable crop losses (mostly boro rice) occurred (Salauddin 2010; Rashid & Yasmeen 2017; Roy et al. 2017; Ferdushi et al. 2019; Abedin et al. 2022; Awal 2022). They stated that Sylhet haor was the most often affected area by flash flooding in April.

BMD rainfall data analysis

For the study period of 1995–2022, rainfall data for the Sylhet region were gathered from the Bangladesh Meteorological Department (BMD). Daily rainfall data were collected and grouped into four seasons as suggested by Islam & Uyeda (2007): winter/dry (January and February), pre-monsoon (March–May), monsoon (June–September), and post-monsoon (October–December). The overall methodology of this study is presented in Figure 3.
Figure 3

The data source and stepwise data organization used in the current study.

Figure 3

The data source and stepwise data organization used in the current study.

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Comparison of CHIRPS satellite data and BMD rainfall data

We performed regression analysis (Figure 4) and calculated the correlation coefficient between CHIRPS satellite data and BMD gauge station rainfall data for the month of April. We found a value of the correlation coefficient (r = 0.70), which was statistically significant at the 95% level of significance. This means that the long-term rainfall data obtained from the satellite-based CHIRPS source for April is strongly positively correlated with the BMD data.
Figure 4

Functional relationship between CHIRPS satellite data and BMD rainfall data for April.

Figure 4

Functional relationship between CHIRPS satellite data and BMD rainfall data for April.

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Long-term variability of rainfall trends

The graphic depicts the monthly total precipitation for April from 1995 to 2022 in Meghalaya, Assam (part), and the Sylhet haor region (Figure 5). The rainfall in the three regions is characterized by its irregular distribution in terms of time and place. In all maps, blue represents high rainfall accumulation, while red represents relatively less rainfall. The rainfall raster layers were manually categorized into five groups (<100, 100–200, 201–300, 301–400, and >400 mm). It reveals that heavy rainfall occurred in the foothill region of Meghalaya in the years 1997, 2000, 2002, 2004, 2007, 2010, 2012, 2015, 2016, 2017, 2019, and 2022 (Figure 5). The southwestern region of Assam, adjacent to Sylhet in Bangladesh, and the Jainta Hills of Meghalaya also experienced high rainfall.
Figure 5

Total rainfall patterns map for April month from 1995 to 2022 in Meghalaya, Assam, and the Sylhet haor region of Bangladesh. Contours are climatological precipitation.

Figure 5

Total rainfall patterns map for April month from 1995 to 2022 in Meghalaya, Assam, and the Sylhet haor region of Bangladesh. Contours are climatological precipitation.

Close modal

The contours plotted at 30 mm intervals in the given Figure 5 represent the rainfall gradient. Closely spaced counts are a sign of orographic rainfall, which is the primary cause of flash floods in the Sylhet haor regions. The variation in monthly maximum rainfall over the past three decades was significantly higher than monthly minimum rainfall. Total monthly minimum rainfall varied from 11 mm in 1999 to 228 mm in 2004, while maximum rainfall varied from 161 mm in 1999 to 1,309 mm in 2004.

The average rainfall in each location in April from 1995 to 2022 varied (Figure 6). It demonstrates that the Sylhet district received more rain than the other districts and states over the last 28 years. The highest rainfall encountered was 1,073 mm in 2004 in the Sylhet zone. With three exceptions in 1997, 2013, and 2019, Sunamganj received more rain than Sylhet. In 2004, more than 1,000 mm of rain fell in Sylhet; in 2012, more than 750 mm; and in 2002, 2007, and 2010, more than 600 mm. Meghalaya in 2000, 2001, 2002, 2008, 2010, and 2022 experienced significantly higher rainfall than other haor districts, except Sylhet and Sunamganj. It is noteworthy that Assam recorded higher rainfall than Meghalaya in 1995, 1996, 1998, 2004, 2005, 2007, 2009, 2010, 2012, 2014, 2015, and 2016. However, Brahmanbaria had the lowest rainfall averages throughout all the years, ranging from 18 mm in 1999 to 473 mm in 2004.
Figure 6

Average monthly accumulated rainfall (mm) of April (1995–2022).

Figure 6

Average monthly accumulated rainfall (mm) of April (1995–2022).

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Spatiotemporal functional relationship of rainfall

We draw a relationship by calculating the average accumulated rainfall for April between 1995 and 2022 (Figure 7). There are strong correlations between monthly Meghalaya rainfall and Sylhet rainfall (r = 0.93*) and Sunamganj rainfall (r = 0.94*), indicating higher rainfall in Meghalaya and higher rainfall in the Sylhet haor regions. Assam rainfall had stronger relations (r = 0.96*) with Sylhet rainfall compared to Sunamganj rainfall (r = 0.84*). According to our historical observations, the influence of the monsoon climate causes a tendency for high rainfall in the Sylhet and Sunamganj regions if rainfall in nearby Assam and Meghalaya State increases.
Figure 7

Functional relationship between average monthly accumulated rainfall of (a) Meghalaya and Sylhet, (b) Meghalaya and Sunamganj, (c) Assam and Sylhet, and (d) Assam and Sunamganj between 1995 and 2022.

Figure 7

Functional relationship between average monthly accumulated rainfall of (a) Meghalaya and Sylhet, (b) Meghalaya and Sunamganj, (c) Assam and Sylhet, and (d) Assam and Sunamganj between 1995 and 2022.

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Prediction of flash flood occurrence in the Sylhet haor region

Rainfall in the highlands of Meghalaya and catastrophic flooding in the Sylhet wetlands are linked. Figure 8 plots the average annual rainfall in Meghalaya for April from 1995 to 2022, including years with high-intensity flash floods. From Figure 8, the higher rainfall in Meghalaya has a stimulating effect on flash flood occurrence in Sylhet (indicated by an asterisk*). We observed from rainfall patterns that the Sylhet haor region of Bangladesh experienced high-intensity flash floods, with an average rainfall in April ranging from 216 to 519 mm in Meghalaya. Based on the long-period average (LPA) rainfall data from 1995 to 2022, we can predict from Figure 8 that there is a chance that high-intensity flash floods will occur in the Sylhet haor region of Bangladesh if the average rainfall in Meghalaya during April surpasses 255 mm. From Figure 8, we can also see that flash floods have become more frequent than before in the haor region.
Figure 8

Relationship between intensive rainfalls of Meghalaya with flash flood incidence in the Sylhet haor region, Bangladesh. * indicates high-intensity flash flood years during April month.

Figure 8

Relationship between intensive rainfalls of Meghalaya with flash flood incidence in the Sylhet haor region, Bangladesh. * indicates high-intensity flash flood years during April month.

Close modal
Figure 9 compares the long-term (1995–2022) average monthly (April month) accumulated rainfall in Assam with the number of years when high-intensity flash floods occurred in the Sylhet haor region of Bangladesh. The flash flood scenario in the Sylhet region was made worse by long-lasting heavy rains that fell in Assam within a short period of time. We may infer from rainfall patterns that the Sylhet haor region of Bangladesh experienced flash floods, with an average rainfall in April ranging from 176 to 708 mm in Assam (Figure 9). After a thorough analysis of high-intensity flash flood years against the average monthly accumulated rainfall in April (Figure 9), we can predict from LPA rainfall data that if the average rainfall in Assam during April surpasses 259 mm, there is a chance that devastating flash floods would occur in the Sylhet haor region.
Figure 9

Relationship between intensive rainfalls of Assam with flash flood incidence in the Sylhet haor region, Bangladesh. * indicates high-intensity flash flood years during April.

Figure 9

Relationship between intensive rainfalls of Assam with flash flood incidence in the Sylhet haor region, Bangladesh. * indicates high-intensity flash flood years during April.

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Seasonal rainfall trend

Figure 10 shows the seasonal trend of rainfall for the Sylhet district for the period 1995–2022. Monsoon season in Sylhet brings more rain, while winter brings the least. Monsoon, pre- and post-monsoon seasons in the Sylhet region seem to experience a rise in rainfall, indicating a positive tendency of increasing rainfall in those seasons. Contrarily, it appears that rainfall in the Sylhet region is decreasing throughout the winter which has been trending poorly throughout the study period.
Figure 10

Observed total seasonal rainfall trend for Sylhet (1995–2022).

Figure 10

Observed total seasonal rainfall trend for Sylhet (1995–2022).

Close modal

Flash flood intensity prediction in the Sylhet haor region

Based on the deviation from the LPA rainfall, the rainfall in Sylhet between 1995 and 2022 is categorized as excess (E). It is known as an excess rainfall year when the amount of rainfall received in a given year exceeds the LPA. The frequency of years with excess rainfall is shown in Figure 11. It is evident that, out of the 28 years, 11 have had excessive rainfall. As per historical databases, the haor area saw devastating flash floods in 1997, 2000, 2002, 2004, 2007, 2010, 2012, 2015, 2016, 2017, 2019, and 2022. Except for the years 1997, 2019, and 2022, the Sylhet haor region saw flash floods nine times out of 12 years with excessive rainfall. We can predict from LPA rainfall data that if the total rainfall in Sylhet during April exceeds 386 mm, there is a chance that the extent of flash flood effects will be more severe in the Sylhet haor region (Figure 11).
Figure 11

Frequency of excess rainfall years in April during 1995–2022, Sylhet and its relationship with flash flood intensification in the Sylhet haor region. * indicates high-intensity flash flood years during April; LPA indicates long-period average rainfall; E indicates excess rainfall.

Figure 11

Frequency of excess rainfall years in April during 1995–2022, Sylhet and its relationship with flash flood intensification in the Sylhet haor region. * indicates high-intensity flash flood years during April; LPA indicates long-period average rainfall; E indicates excess rainfall.

Close modal

Significant upstream rainfall results in flash floods, which rapidly raise river water levels and overbank discharges. Rainfall is an important meteorological component, and its intensity is taken into account when assessing flash floods. Understanding the characteristics of rainfall variability is essential to reducing damage from flash floods (Bagchi et al. 2020). In this study, we have tried to establish a correlation between rainfall in Assam and Meghalaya and the probability of flash floods in the Sylhet haor region by analyzing rainfall trends in Assam, Meghalaya, and the Sylhet haor region from 1995 to 2022 for April. We observed high-intensity flash floods in the Sylhet haor region during heavy rainfall years. The southern and western foothills of Assam and Meghalaya and the south and southwest of Assam receive heavy rainfall, with an average annual rainfall of more than 12,000 mm (BWDB 2016). Bangladesh receives extraordinarily high flows in northeastern rivers such as Surma, Kushiyara, Manu, Khowai, and Someswari due to the high rainfall in the Indian regions during the pre-monsoon (Adnan et al. 2019).

Based on time-series CHIRPS data from 1995 to 2022, the Sylhet haor region, Assam, and Meghalaya experienced unusually high rainfall levels, even more than 1,000 mm in April. There is also a spatial variability in rainfall in the three regions. Such variability may be due to complex interactions between dynamic systems operating at different spatial and temporal scales (Dey et al. 2021). Assam mainly consists of the Brahmaputra and Barak plain valleys, surrounded by numerous hills, and the Meghalaya mountainous province receives the highest average monsoon rainfall (Goyal & Gupta 2014). With the alignment of these two mountains, warm and moist air from the Bay of Bengal during the monsoon season is the main reason for Meghalaya's high rainfall (Prokop & Walanus 2015). In general, Sylhet and Sunamganj districts received more rainfall than Assam and Meghalaya. This can be attributed to the additional effect of the Meghalaya layer (Bhattacharya & Suman 2012; Rahman et al. 2018). Intense cloud activity over the Meghalaya Plateau creates a cool air mass covering the lower Sylhet layer (Kataoka & Satomura 2005). Murata et al. (2011) reported the existence of cool air masses, which are responsible for pre-monsoon rains.

Flash floods in the Sylhet haor region are usually worsened by incessant heavy rains in a large marshy area during April. This is in agreement with the findings of several researchers (Rozalis et al. 2010; Haque et al. 2021; Shuvo et al. 2021). Flash floods inundate low-lying floodplains, destroying crops and infrastructure and often taking lives and property. Significant losses of boro rice due to devastating flash floods are not uncommon (Islam et al. 2012; Sikder 2013; Kamal et al. 2018). We have determined the amount of rainfall in April that usually results in flash floods and especially damage to boro rice. For this, we estimated the occurrence and severity of flash floods in the Sylhet haor region from time-series rainfall data, which are often used to predict flash floods (Islam et al. 2019; Deka et al. 2022). We carefully observed and found strong correlations between the rainfall in Assam and Meghalaya and the haor region of Sylhet, with the aim of improving flash flood forecasting. We found a strong correlation between torrential rains in Meghalaya and severe flash floods in the Sylhet haor area. We also found a similar correlation between accumulated rainfall in Assam and the rise in water levels in haor. Mahtab et al. (2018) found that Meghalaya rainfall intensity is a reliable indicator of flash flood frequency and intensity in Tahirpur, Sunamganj. When it rains heavily in Cherrapunji, it takes 6–8 h to reach Tahirpur, and the rainwater does not drain quickly, spreading and creating flooding (Rashid & Yasmeen 2017; Basher et al. 2018).

We observed heavy rainfall for a short time in the Sylhet region during most of the historical flash flood years. Locally intense to extremely continuous and intense rainfalls increase the water level of the Surma River and exacerbate the flash flood situation (Jakariya & Islam 2017). The flow of upstream water almost inundates most of the sub-district near the Indian border and worsens the flash flood situation in Sylhet (Suman et al. 2014). We observed a decreasing trend in rainfall during the monsoon and an increasing trend during the pre-monsoon. The increasing trend of rainfall in the pre-monsoon season shows that Sylhet's flash flood is getting worse day by day. PRECIS (Providing REgional Climates for Impact assessments), a high-resolution regional climate model, is commonly used to produce climate change projections for impact assessments and adaptations. The PRECIS ensemble model predicts a shift to peak rainfall in May with a decrease in rainfall in August (Mondal et al. 2020). As a result, there will be frequent, brief, and intense rainfall episodes in the haor area, particularly during the pre-monsoon season (i.e., the months of March, April, and May). In their investigation, they compared the recorded rainfall over Bangladesh for a base period of 1986–2005 to the simulations of yearly, monthly, and severe rainfall produced by the PRECIS regional climate model. The measured rainfall was gathered from the 28 BMD gauge stations, and the model rainfall was simulated using the standard, unaltered parameter settings. Early flash floods in the haor region are now a new normal (Rumana et al. 2018). Mondal et al. (2020) reported that between 1901 and 1957, May received noticeably more rain than April, and between 1958 and 2017, the difference in total rainfall between May and April decreased while the total rainfall of April increased. Also, seasonal rainfall trend analysis of the Sylhet region indicated that rainfall is increasing during the pre-monsoon season showing a positive trend throughout the study period (1995–2022). Because of this, it is expected that the April rainfall will increase in the future, resulting in sudden, short, and intense flooding in the haor area. This circumstance is concerning since more precipitation in early April increases the risk of flash floods and destroys boro rice (Rumana et al. 2018). Using the PRECIS model, a significant increase in two extreme weather indices, such as ‘maximum rainfall in one day’ and ‘maximum rainfall in five consecutive days’ is projected during the 2080's pre-monsoon season near Sunamganj by Nowreen et al. (2014). Their estimate indicates the potential for frequent occurrence of massive flash floods. This will have a significant impact on the possibility of an earlier than normal flash flood and the loss of standing crops in haor.

A satellite-based approach to estimating precipitation, CHIRPS global monthly data combines in-situ station data with 0.05° resolution satellite images over a 50°S–50°N (and all longitudes) region. In contrast, the BMD gauge station data of Sylhet only offers point data. Both types of data are highly positively correlated, according to regression and correlation analyses. Bangladesh needs more site-specific meteorological stations to analyze the monthly rainfall pattern more carefully and to accurately predict flash floods in the Sylhet haor region.

The Sylhet haor region often experiences high-intensity flash floods when rainfall is high, especially in the foothills of Meghalaya, the southern and southwest parts of Assam, and the Jainta Hills of Meghalaya. Based on the historical rainfall data, there is a possibility of high-intensity flash floods in the Sylhet haor region if the average rainfall exceeds >250 mm in Meghalaya and Assam, and about 400 mm in Sylhet during the month of April. Flash floods are becoming more frequent and intense in the Sylhet haor region. Heavy rains in early April increase the probability of flash floods and the scenario would get worse as pre-monsoonal rains increase and shift from May to April. This requires early warning systems, farmer advisories, and public awareness of flash floods.

This research was supported by the Ministry of National Science and Technology (NST), Government of the People's Republic of Bangladesh.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.

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