1 Introduction

1.1 Background

Flood, inundation or overflow of water resulting from different overland flow mechanisms is associated with frequent disastrous effects (Barredo 2007; Berz 2000; Yin 2020; Zeleňáková et al. 2020), including causing essential damages to livelihoods, properties, and some cases, deaths. Overland flow mechanisms such as infiltration-excess, saturation-excess and preferential flows become dominant in different soil and vegetation environment; largely impervious or loosely vegetated but dry surfaces, near-stream humid and vegetated surface as well as areas characterized by natural or artificial mole or pipes, respectively (Beven 1986; Hussaini and Khan 2020). Floods generally result from the interaction of physical processes, including certain hydrological preconditions, meteorological or climate factors, runoff generation processes and river routing at different scales (Nied et al. 2014). While floods are initiated by precipitation excess or dam failure (Kunkel et al. 1999; Ologunorisa 2001; Ologunorisa & Tersoo 2006; Adelekan and Fregene 2015; Albright and Crow 2019; Tei et al. 2020), the effects are largely exacerbated by blocked drainage systems and poorly planned settlements, among other urban planning problems (Costa 1985; Brown and Graham 1988; Adelekan 2011; Atufu and Holt 2018; Asiedu 2020; Latrubesse et al. 2020).

Studies have shown that floods are not always disastrous; especially in agricultural communities of sub-Saharan Africa, Asia and South America where deposited alluvial plains in many flood-prone watersheds have accounted for productive farmlands (Fairbairn 2005; Sommer et al. 2020). Floods also inundate wetlands with fresh wastes and nourish lakes and streams with nutrients, among some other positive impacts (Ponnamperuma 1984; Bai et al. 2020; Firth et al. 2020). The impact (destructive or non-destructive) of flood is often dependent on the strength (intensity and stretch) of rainfall and the environmental responses (coping, adaptation or resilience) (Baker et al. 1998; Hu et al. 2019). Floods may also result into direct or indirect fatalities (Janerich et al. 1981; Jonkman and Kelman 2005; Davis et al. 2019; Knighton et al. 2020). The effects include 40–47% of all weather-related disasters, loss of livelihoods of about 2.3 billion people and 242,000 deaths between 1995 and 2015 (United Nations Office for Disaster Reduction, UNISDR 2015). The indirect effects include psychological and mental illness of victims of flood-related losses. Alderman et al. (2012) indicated that flood in many densely and poorly planned settlements may significantly correlate with increased risk of disease outbreaks, increased mortality and prolonged psychological distress.

Di Baldassarre et al (2010) argued that flood-related losses and fatalities have dramatically increased in Africa since about half of the century and that there is a growing global concern on the need to identify the causes for the increased amount of damages. According to the United Nations (2009), over 600,000 people were either displaced or suffered significant economic loss across the West Africa in September 2009, and about over 500 deaths occurred in flood-linked disasters in 2007. In general, fatalities due to flood appear to be an annual occurrence, probably due to poor understanding of the flood disasters alongside poor settlement planning system (Di Baldassarre et al. 2010). In Nigeria, coastal and urban floods have been linked to numerous disasters, such that the National Emergency Management Agency (NEMA) documented that flood events occurrence in four months (June–September) in 2012 directly caused more than 363 human deaths with displacement of at least 1.2 million people. Only in the state (Oyo State)’s capital of Ibadan in the south-western Nigeria, more than a million people were severely affected by the ‘Ogunpa flood’ disasters in 1980 (Smit and Parnell 2012; Nwala 2017). Life and properties worth millions of dollars have also been lost to flood events in different parts of the countries, including the Niger Delta (Ologunorisa 2001, 2004; Ologunorisa and Adeyemo 2005), Lagos (Adelekan 2016a; Olanrewaju et al. 2019), Ibadan (Adelekan 2016b), Akure (Eludoyin et al. 2007), Abuja (Adeleye et al. 2019), Chad basin (Oyebande 1991) and Yobe (Goes 2002).

Efforts have emerged through the Ecological Fund initiative of the federal government of Nigeria. The Ecological Fund was founded in 1985 through the Federation Account Act of 1981 with the prime aim of funding ecological projects to mitigate serious ecological problems that include flooding and soil erosion (www.ecologicalfund.gov.ng). Despite the efforts through the initiatives and other efforts of non-governmental agencies, the menace of flooding and associated soil erosion has become a recurrent problem in almost all parts of the country, suggesting that the initiatives are probably not working. Records of flood-related fatalities (Di Baldassarre et al. 2010) revealed an increase in flood-related deaths in Nigeria and the entire African region since the preceding 50 years. A review of recent studies on possible factors that might link to increased fatalities during flood events revealed poor modelling or use of non-validated models (Bernhofen et al. 2018), changing climatic conditions and anthropogenic factors, such as poor land use management and urbanization that are capable of exacerbating the impact (Ekeu-wei 2018). Eidipour et al. (2016), among others, have argued that generalization of information gathered from gauged basins to ungauged basins calls for thorough analysis of spatial variations and their relationship with relevant hydrological features. Subsequently, studies have involved different but relevant approaches/strategies to decipher or estimate from runoff hydrographs in gauged basins (see Bahrami et al. 2019). In terms of flood effects, studies have recommended assessment of direct (tangible, i.e. material damage to buildings and infrastructure) and indirect (difficult-to-quantify damages, such as stress and inconvenience; Veldhuis Ten 2011). Both flood occurrence and effects, however, required spatial technology that allows remote capturing of information in ungauged basins. The study area is a typical flood vulnerable community in a developing country, where residents have considered annual flooding of their communities as a divine act and consequence of flaws in relevant environmental policies (Adebajo 2018; Buba et al. 2021).

1.2 Research problem

Owing to heavy rain, settlements in the Nigerian Benue trough suffered flooding between August and September, 2017. Within the Niger trough, residents of Lokoja and Makurdi, the administrative capital of Kogi and Makurdi States in the western and eastern flange of the middle belt of Nigeria have suffered severe flooding over the years (Onuigbo et al. 2017; Brooks et al. 2020; Lawal 2020). The flooding events of August–September, 2017 resulted in the displacement of over 10,000 people, and the situation was described as being ‘in dire need of humanitarian intervention’ and ‘desperately pathetic’ (Davies 2017). The disturbing level of the impact of flood on the mid-belt environment of Nigeria in 2017 is not unique; such is representative of the situation in many flood-prone communities in the sub-Saharan Africa, including coastal and urban settlements (Douglas et al. 2008; Hula and Udoh 2015; Kanu and Imatari 2016; Nkwunonwo et al. 2020; Plänitz 2020). According to Nkwunonwo et al. (2020), sub-Saharan African countries, including Nigeria are challenged by poorly understood and under-studied flood hazards. Existing studies on disaster management have equally revealed problems with flood management, preparedness as well as coping strategies (Adeleye et al. 2019); many of the studies have linked the inadequate management of flood hazards to limited development control (designing and implementing sustainable policy for ensuring efficient regulations) of physical development (Ahmed and Dinye 2011; Lekwot et al. 2013). Douglas et al. (2008) posited that residents of low to middle economic settlements bare most burdens of flood hazards because disaster response and mitigating facilities are generally poor.

This study has focused on determining the impact of flood events on affected communities in the Benue trough of Nigeria. It is based on the hypothesis of suggested by Lovett (2000) that the ability to combine data from different sources is adequate for effective environmental management. Consequently, the study is aimed at strengthening the importance of freely available satellite imageries, especially Landsat image data to complement climate and survey data for better decision for flood control development in the region. The hypothesis is supported by the argument by Douglas et al. (2008) that flooding is related to heavy rainfall, extreme climatic events and changes in the built-up areas. The extent to which this hypothesis is true is determined in this study from an integrated perspective of climate analysis, remote sensing, social and field surveys, with geographical information system. Specific objectives are to (i) examine the characteristics of rainfall and discharge at the major river in the study area—Benue trough of Nigeria; (ii) assess the occurrence of extreme rainfall conditions and other flood-triggering/ exacerbating factors in the area; and (iii) determine flood damage extent and available warning system in the area.

2 Materials and methods

2.1 Study area

The study area, Makurdi, situated at the narrow end of the River Benue lying on both sides of the riverbanks, is the administrative headquarter of Benue State (Fig. 1). It is situated inside the floodplain of the Lower River Benue valley with a physiographic stretch of about 73–167 m above sea level, and is often drained by River Benue which partitions it into Makurdi North and South banks. Apart from River Benue, tributaries and headwater channels that drain the communities in Makurdi include Kpege, Adaka, Asase, Idye, Urudu and Demekpe streams; the dense drainage system usually makes the area susceptible to inundation in the wet season.

Fig. 1
figure 1

The study area, Makurdi in Benue State, Nigeria

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Dominant climate in the area is the tropical Guinea savanna, classified as Koppen’s Aw climate. The Guinea belt occupies the limits of tropical rainforest climate, and extends to the central part of Nigeria where it forms a boundary with Sudan savanna climate, exhibiting a well-marked single peak rainy season and a dry season. The 1951–2009 average minimum, mean and maximum temperature values are 22.3 ± 2.5 °C, 27.8 ± 1.8 °C and 33.3 ± 2.6 °C, respectively, while mean relative humidity for same period is 69.8 ± 14.2% (Eludoyin et al. 2014). Mean annual rainfall is about 1200 mm, with double peaks and little dry season; the rainy season lasts from April to October, while dry season occurs between November and March. Geological underlain is primarily sedimentary, with micaceous and feldspathic sandstone in some portions of the area, and shale in some low-lying areas (Nyagba 1995). Main soil types are hydromorphic soils that developed on alluvium sediments along River Benue coastline, as well as red ferrosols away from the coastline (Nyagba 1995). Given the influence of good drainage, rich soil and grassland that makes cultivation relatively easier than what obtains in the rainforest belt, over 60% of the indigenous people are small-scale or indigenous farmers, and many of the farmers are also fishermen, depending on their locations. Other residents are either government workers or commercial workers, but a number of the residents combine at least two occupational activities. The population density as at 2016 was estimated at 405,000 and projected to be about 600,000 by 2021, based on the 1991 Nigerian Population Commission’s estimated growth of 3.05% per year, and net migration. Prior to the flood episode of August/September 2017, the study area (Makurdi) has experienced flooding in many years, and significant damages were reported in newsprints in 1996, 1999, 2000, 2002, 2004, 2005, 2007, 2008, 2012 and 2017 (Ologunorisa and Tersoo 2006; Shabu and Tyonum 2013), especially as River Benue overflows its banks, due to either heavy and prolonged rainfall or dam failure, such as the Lagdo dam failure in 2012, which caused displacement of over 500 people and inundation of about 300 buildings (Ocheri and Okele 2012). The 2017 flooding event was next to that of 2012 in magnitude (Davies 2017), hence its selection for this study.

2.2 Data

Data used for this study include remotely sensed imageries of Shuttle Radar Topography Mission, SRTM and Landsat 8 Operational Land Imager (OLI, released on 15th of January, 2017; spatial resolution = 30 m), which were used to derive essential topographical characteristics, such as slope and drainage network (SRTM), as well as the land use/cover over the study area. Both the Landsat and SRTM imageries for the study area were downloaded from the archive of the United States of America’s Geological Survey (USGS). Data also included 57 (1960–2017) daily rainfall and runoff data, as well as daily evaporation data for 36 years (1981–2017) that were obtained from the office of the Nigerian Meteorological Agency (NiMet) and Nigerian Hydrological Service Agency (NiHSA) in Abuja Nigeria, respectively. Furthermore, soil data and geological data were extracted from the Harmonised World Soil Database (HWSD) Nigerian Geological Survey Agency, respectively. In addition, 400 residents of the study area were selected using a systematic sampling procedure for administration of a set of semi-structured questionnaire. Contents of the questionnaire were grouped into personal and socio-economic attributes of respondents, perception on vulnerability to flood disasters and coping strategies.

2.3 Data analysis

The remote sensing data were first corrected for geometric and radiometric corrections as required for standard remote sensing imageries for quality enhancement and assessment (Burrough, 1986). The imageries were thereafter georeferenced in ArcGIS software (version 10.5) by merging the coordinates of known points that were obtained from the existing topographical maps of the area, and confirmed with the use of global positioning system (GPS, Germin etrex version) on the physical structure as described by Stopher et al. (2015). Also, the Landsat 8 imagery was classified using supervised classification (based on Maximum likelihood Classification algorithm) into different dominant land use system following Anderson (1976)’s scheme for land use/land cover classification. All the imagery data as well as soil and geological data were analysed following the principles of remote sensing and geographical information system in ArcGIS software as described in previous studies and the software’s manual (Hillier 2007; Crosier 2004). The climate and discharge data were also investigated for non-climatic heterogeneity and instrumentation errors as advised by the World Meteorological Organisation (1989) before analysed. The data were analysed for time series, dispersion using standard extreme rainfall indices, mainly, Standardized Precipitation Index (SPI) and Precipitation Concentration Index (PCI). The PCI was determined based on the recommendation of Oliver (1980) and De Luis et al. (2011) (Eq. 1)

$$\mathrm{PCI}=\frac{{\sum }_{i=1}^{12}{{P}_{i}}^{2}}{{\left({\sum }_{i=1}^{12}{P}_{i}\right)}^{2}}\times 100$$
(1)

where Pi = the rainfall amount of the ith month. PCI less than 10% indicates low precipitation concentration; 11–15% is interpreted as moderate and 16 and above is high.

The SPI is typically determined as probabilities, based on the likelihood of recorded measure of precipitation; zero indicates the median precipitation amount and negative values represent dry spell while positive values indicate wet condition over a period of at least 30 years (McKee et al. 1993; Cheval et al. 2014). SPI was determined using Eq. 2.

$$\mathrm{SPI}=\frac{X-\overline{x}}{\mathrm{SD} }$$
(2)

where \((X-\overline{x }\)) = the rainfall anomaly and SD = standard deviation of the mean of the series.

In this study, monthly SPI was calculated for the period 1980 to 2017, using the rainfall data obtained from the Makurdi station of the Nigerian Meteorological Agency; the body responsibly for obtaining and keeping such records in the country. Also, the Mann–Kendall (MK) trend test, a nonparametric test for determination of monotonic trends in a series of data, was adopted to assess statically significant trend of rainfall over the study period. The MK test is less affected by the outliers than other tends’ procedure (Birsan et al. 2005). The MK test statistic ‘S’ is calculated based as described by Yue et al. (2002) (3)

$$S = \mathop \sum \limits_{i = 1}^{n - 1} \mathop \sum \limits_{j = i + 1}^{n} {\text{sgn}} \left( {x_{j} - x_{i} } \right)$$
(3)

where

$${\text{Sgn}}\left( {x_{j} - x_{i} } \right) = \left\{ {\begin{array}{*{20}l} { + 1,} \hfill & {{\text{if}}\; \left( {x_{j} - x_{i} } \right) > 0} \hfill \\ {0,} \hfill & {{\text{if}} \;\left( {x_{j} - x_{i} } \right) = 0} \hfill \\ { - 1,} \hfill & {{\text{if}}\; \left( {x_{j} - x_{i} } \right) < 0} \hfill \\ \end{array} } \right\}$$

Xi and Xj are the annual values in years i and j (j > i), respectively.

Perceptions of residents were analysed using frequency/percentage distribution analysis. The study area was also visited for visual assessment of flood damage after one of the occurrences in 2017. A summary of the study approach is presented as Fig. 2. Figure (2) in addition to the data source shows the software used for the different approaches used in the study. The approaches were linked by the specific objectives that they addressed. Previous study (Omodanisi et al. 2014) among others argued for multi-perspective approach to environmental analysis because each of the approaches is capable of strengthening the other.

Fig. 2
figure 2

Detail of activities involved in this study. 1–3 refer to the objectives

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3 Results

3.1 Rainfall and discharge characteristics

Some mean monthly characteristics of daily rainfall within the selected period are provided in Table 1. Rainfall averagely increased from March and peaked in August before it rescinded in September and October. The generally low rainfall from November to March characterizes the months as dry period. Coefficients of variation were higher in the dry period than in the other months (wet or rainy season). The results of the M–K test and Sen’s slope that were used to examine monotonic trend and its magnitude indicate that while there is no monotonic trend in rainfall pattern between November and February, the period between April and July showed negative trend.

Table 1 Summary statistics and trend of monthly rainfall
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In general, mean monthly rainfall pattern reveals a continuously increasing pattern and probable soil water surplus in the wet season (due to reduced evaporation) that is capable of generating high proportion of overland flow, either as infiltration excess or saturation excess (Fig. 3a) in the area. The assumption of dominant influence of infiltration-excess flow becomes evident with the pattern of measured discharge at the Makurdi station of River Benue, which correspondingly increased with rainfall (Fig. 3b). Whereas rainfall has relatively increased over the studied years (y = 2968 + 4.876x, R2 = 0.01), mean annual discharge has relatively declined (y = 109.9 − 0.329x, R2 = 0.08). Increased rainfall has been depicted as hazardous as more communities become vulnerable to flood, and more communities in the study area have become notoriously vulnerable to flooding while there seems to be no solution or control for years (Ologunorisa and Tersoo 2006; Ajon et al. 2017). Reduced discharge may be linked to land use and land cover change (Eludoyin et al. 2017). The importance of land use/cover change was also strengthened by the fact that the relationship between rainfall and runoff does not indicate a strong (R2 ≤ 0.2) coefficient of determination when compared with both simple linear regression and logarithmic regression (Fig. 3c). The results therefore suggest no strong direct link between the two variables. Previous study on hydrological pathways reveals that antecedent soil moisture, slope, land use and land cover and soil type/geology are factors that may reduce the strength of rainfall–runoff relationship (see Eludoyin et al. 2017).

Fig. 3
figure 3

Monthly mean rainfall, evaporation, corresponding discharge of River Benue at Makurdi, Nigeria (1981–2017) and rainfall–runoff relationship for 1960–2017

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Analysis of the return period for flood incidence reveals that peak discharge in 24 out of the 46 years investigated occurred in September while 20 peaks were recorded in October, and at only one time did discharge peak in November. Furthermore, the observed low and statistically insignificant correlation that occurred in annual total rainfall between 1980 and 2017 (Fig. 4a), and the wavelet transform result (Fig. 4b) reveal low level of similarity in spectral signals (rainfall occurrences) in the area. The low similarity level in the signal reveals the presence of extreme rainfall cases in the wet season. Existing studies showed that the study area experiences wet season whose prevalence is associated with the movement of south westerlies over the Atlantic Ocean (Odekunle and Eludoyin 2008). Also, studies (Hula and Udoh 2015; Agada and Nirupama 2015) documented that area in the Guinea savanna of Nigeria, including the present study area, experiences floods more in the wet period. Such documentation will easily associate flood with rainwater overflow due to infiltration excess. Infiltration-excess flow occurs when the soil infiltration capacity or where when flood is generated due to low infiltration capacity [the maximum rate at which a given soil can absorb precipitation as it falls; Beston (1964)] or where soil storage capacity is extremely low, including poorly vegetated, rocky, paved and concrete surfaces, cultivated and heavily grazed areas (Ziegler et al. 2012; Bilotta et al. 2007; Kechavarzi et al. 2010). Saturation-excess flow, on the other hands, prevails at near-stream areas and expansion of small, locally variable water table, during storm condition (Chappell et al. 2006; see Eludoyin 2013).

Fig. 4
figure 4

Time-rainfall relationship and variability

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3.2 Physical characteristics influencing flood recurrence

The remote sensing-based analysis of relevant physical characteristics of the study area indicated that the communities in Makurdi are within River Benue basin, and are characterized by varying slope; relatively higher in the built-up area than other areas (Fig. 5a–b). The northern part of the study area is largely occupied by Plinthic Luvisols and Fluvisols, while the southern part is dominated by Ferric Acrisols (Fig. 5c). Both Fluvisols and Plinthic luvisols are young, weak and poorly drained soils (Batjes 1997). The soils have derived from the largely sedimentary geology of the crystalline basement rocks (Ofoegbu 1985). Ofoegbu (1985) noted that part of Makurdi is geologically underlain by three categories of geological composition, namely; alluvium, basalts, trachyte and ryolite as well as shale and limestone. The satellite imagery used in the study also revealed the dominance of alluvium and sandstone in the area (Fig. 5d). Alluvium and associated alluvial soil are very productive (Boettinger 2005), and are therefore vulnerable to pressure for tillage as population increases. In addition, analysis of land cover reveals that significant portions of the built-up area are concentrated around the River Benue (Fig. 5e).

Fig. 5
figure 5

a–e Some characteristics of Benue Basin around Makurdi, the study area

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Studies (including O’Connell et al. 2007, Konrad and Dettinger 2017) have established causative links between agriculture intensification, urbanization activities and flooding. In the study area, Acha and Aishetu (2018) reported construction and livelihood activities within the Benue floodplain and along waterways. Consequently, the flood vulnerability analysis of the area classified about 37.3% (representing 307.5 sq. km or 34.1% of the entire built-up area) of the entire land area as medium to high hazard zone (Fig. 6).

Fig. 6
figure 6

Vulnerability of the study area to flood hazards

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3.3 Extreme rainfall events

Results of the SPI showed that the study area received high rainfall as 13.5% of the evaluated years (1980–2017) were considered extremely wet and 54.1% as wet (near normal to very wet); only 32.4% of the entire period were classified as dry. Values of PCI varied from 13 units to 19.8 units, suggesting that the study area witnessed moderate-to-high rainfall concentration (Fig. 7). Iskander et al. (2014) described areas that are characterized by 13–19 units of PCI as that which possesses high flood potential and consequentially high erosion-potential. The PCI during the 2017 flood event in Makurdi was 18.9 unit. The tendency for flooding is relatively higher in well-drained soil of hydromorphic nature as obtained in the study area, especially in period of high rainfall (Olaniran 1983).

Fig. 7
figure 7

Results of SPI and PCI derived from the rainfall analysis in the study area

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Also, the number of consecutive rain days peaked between August and September, when the hazardous flood events occurred. Existing studies on Niger–Benue trough and few others settlements in the country confirmed that most hazardous floods occurred in the wet season (Ologunorisa and Tersoo 2006; Taiwo 2008), and are likely to have been triggered by spontaneous response after the soil was fully saturated due to prolonged rainfall—a condition that may have been worsened by removal of the riparian vegetation during built-up and agricultural processes.

3.4 Flood damage: case study of the 2017 event

Analysis of some socio-economic variables across randomly selected responses from the study area indicates that the residents of the most affected (flooded) communities in the flood event were relatively poor people (Table 2). Majority of the affected people were working class (aged 25–45 years), who’s income was at most NGN 600,000 (US $1520) per annum; about 74.8% of the respondents have lived for at least 4 years before the flood event and 95% have experienced flooding events in the study area before the 2017 event. Residential houses with concrete frame and unreinforced masonry were less damaged (damage percentage = 1.8%) than residential unreinforced masonry buildings (22.4%). The unreinforced masonry structure therefore incurred more damages than concrete frame with unreinforced masonry wall structures (Table 3).

Table 2 Some socio-economic characteristics of residents of flood-prone areas in Makurdi, Nigeria
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Table 3 Some indices of flood damage estimates
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The two indices of flood damage reveal that the unreinforced building and commercial building types were more damaged than the concrete frame buildings. Furthermore, the results of flood vulnerability or depth–damage curves are presented as Fig. 8. Figure 8 is generated for dominant building uses (residential and commercial) and type or make-up (Unreinforced Masonry Building or UMB and Concrete Frame with Unreinforced Masonry Building (CFUMB) types). Values of R2 (Coefficient of Determination, Wheeler et al. 2013) were low, generally less than 50%, suggesting that water or flood depth is not a significant predictor of damage to the building and residential contents. Escarameia et al. (2012) argued that other flood characteristics such as duration, velocity as well as variations in building structure and material and responses of affected communities are other factors. Also, damage whereas became obvious at UMB at 20 cm flood depth, it was at 40 cm with CFUMB and 23 cm with the commercial buildings. This is probably because since the floor elevation is first vulnerable (submerged by flood), buildings with higher floors such as the CFUMB were not as damaged as those with lower floor elevation structure.

Fig. 8
figure 8

Flood vulnerability or depth–damage curves for different building types in the study area

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In general, only 3.6% of the total damages occurred with the CFURMB, while the UMB and Commercial Building type experienced 40% and 34% damage ratios, respectively (refer to Table 3). Observations from the 2017 flood occurrence reveal that the commercial building type comprises a general set of old or abandoned residential buildings as well as wooden structures that were converted to economic uses. Such wooden and unorganized structures are normally expected to incur high damage ratio at any flood event (Komolafe et al. 2018). Also, 81.9% of the respondents noted that the depth of flood water that displaced the study area between August and September, 2017, was in excess of about one metre above the ground level, and the heavy rainfall lasted roughly four days. An average of eight hundred and eleven thousand (NGN 811,814.97 or US$ 2, 127.96) was lost by residents whose income (of 86.7%) was at most NGN 600,000 or US$ 1572.74 per annum.

3.5 Impact of flood warning system

At least 64.3% of the respondents claimed to be forewarned about the likelihood of a flood event by the Nigerian Meteorological Agency and the Nigerian Association of Hydrological Science but were not sure of the magnitude. Duru (2017) noted that the Benue State Commissioner for Water Resources and Environment noted that they ‘were actually aware that there would be flooding but it was the magnitude we did not know’. With such warning, a youth organization typically embarked on campaign to sensitise the vulnerable communities on cleaning of many blocked drainage channels (Fig. 1) that have been implicated for preventing free runoffs, and consequently aggravating flooding. The Fig. 9, which shows efforts of residents in the study area to prevent flooding, suggest that such effort could not have offered significant impact at reducing the level of the hazard at the period of study. The information on the picture also reveals further the problem with refuse disposal along drainage channels that can further exacerbate the flood occurrence.

Fig. 9
figure a

Sample of drainage channel clearing up activity and typical drainage condition prior the cleaning

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73.1% of respondents argued that construction of more drainage channels could prevent the flooding problem but only 59% claimed to have received any assistance from the State Government while 12.3% noted that relatives have provided some aid. However, 81% of the affected people argued that the responsibility to manage flood disaster in the area is governments’ and not residents. In all, there is no evidence to suggest that the urban growth in trough, at the study area, was properly or sustainably monitored.

4 Discussion and conclusion

The study area is typical of communities that are vulnerable to flood in the wet season or during any course of extreme rainfall event, due to their closeness to water bodies. Findings from the analysis of rainfall and discharge indicate that the flood of the study area may have been influenced by both infiltration-excess and saturation-excess flows. First, given the sedimentary geological undelay that produced well-drained soil and in poorly vegetated areas of the basin (due to land cover alterations), infiltration excess may dominate areas away from the river channel. Also, rainwater would easily permeate the soil and by-and-large runs laterally as interflow on top of the strike-slip fault of the West and Central Africa Rift system, where Benue trough lies (Obaje 2009). In other words, the antecedent moisture would trigger flood more rapidly than would obtain in deep profile soils. The entire Niger–Benue region, Niger Delta and coastline of the Atlantic Ocean are vulnerable to flood in Nigeria as many near-stream communities in the world (Ologunorisa and Adeyemo 2005; Lindersson et al. 2020). Consequently, flood-related hazards have been referred to as ‘natural hazard’ even when studies across urban areas in the country (e.g. Omiunu 1981; Oguntala and Oguntoyinbo 1982; Olaniran 1983; Oriola 1994; Rashid et al. 2007; Adelekan 2016a, b) and many others in other parts of the world (Wens et al. 2019; Lindersson et al. 2020) have argued that flood is fundamentally an anthropogenic disaster with strong societal links involving drivers, impacts and feedback mechanisms.

A report of the UNISDR (2015) referred to population growth and socio-economic development in flood-prone areas as the main driver of past decades’ flood damages. It is obvious in the study area that the communities are flood prone due to their near-river (River Benue) location and seasonal heavy rainfall. The seasonal heavy rainfall between June and October of most years may suggest that the recurring flood disasters are predictable. The period, June–October, is wet season in the country, and the slight difference in some years may be attributed to shift in Inter Tropical Convergence Zone (ITCZ) (the front between the two dominant climate influencing air masses in Nigeria-dust bearing tropical continental air mass from the northeast and rain bearing tropical maritime, from the southwest) (Barry and Chorley 2010). Consequently, warnings of heavy rainfall were announced over the national radio and television stations in events that were mostly sponsored by the Nigerian Meteorological Agency prior the rainy season. Despite the warnings, the 2017 and subsequent flood disasters in the study area resulted in loss of life and properties. It is, however, not certain if the warning was helpful for majority of the residents in the study area. Visit to the study area also revealed as well as the result of the buffer analysis (Fig. 6) revealed a huge amount of human activities within the river basin. Studies from better managed flood-prone areas, however, mandated that construction activities within river basins ought to be sustainably managed (e.g.  Seo et al. 2008; Wang et al. 2020; Hou et al. 2021). In Nigeria, many planning and environmental rules are poorly or partially implemented (Okorodudu-Fubara 1998). For example, while construction of major projects requires Environmental Impact Assessment (EIA) and buildings, permission from planning, the process leading to the procurement of acceptable EIA and permission may be fraught with corruption (Okorodudu-Fubara 1998). In general, flooding of near-stream communities is expected when the river bank is appropriately protected and when land use activities are indiscriminate. Ologunorisa and Adeyemo (2005) recounted that persistent victims of flood in the Niger Delta are quite aware of the causes of flood hazards to include heavy, prolonged rainfall and river overflow would not leave the vulnerable zones because it would mean leaving their source of means of livelihoods.

One striking attribute of the victims of flood and other disasters in the sub-Saharan Africa is that they are poor and their properties are largely uninsured (NEST 1991; Odemerho 1993; Omodanisi et al. 2014) unlike what ensures in many developed countries (Martínez-Gomariz et al. 2020). Like Ologunorisa and Adeyemo (2005) observed for victims of flood in the Niger Delta, most of the flood victims in the study area were not compensated or given any relief. Also, many of the affected buildings were actually within the floodplain of River Benue or its tributary; analysis of the land use/cover suggests that about 34% of the built-up in Makurdi are within the floodplain of the river. These places easily become submerged with increase in the volume of the river.

Furthermore, properties damaged in the 2017 flood hazard were relatively (to the income of the residents) high, and given unreliable/poor insurance policy in the country, poor planning policies and increased rate of land exposure due to urban growth, more records of hazards are predicted. Coping or/and adaptive responses are largely are largely individualistic, and as such, the poor (86.8% who earn at most US $ 4.3; NGN 600,000 by 360 days; Table 2) will be unlikely able to cope, except with government intervention. The huge impact of the 2017 flood disaster after many blocked drainage channels have been cleared in the affected communities suggests that the response was inadequate. In general, the study concluded on the need for an extensive flood control policy for the affected area and similar flood-prone communities. The policy will be strengthened by inclusion of plan for structural control, including channelization, canalization, dredging, building of flood walls and embankments, as well as monitoring and enforcement of the set-back rules to water bodies. The basin-scale analysis the runoff–rainfall relationship of the study area across different settlements and land uses within the entire Benue trough in West Africa is recommended for further study. A study by Abbas et al. (2018) on rural Pakistan suggested that measures such as distance from river and elevating houses can alleviate flood damages, and that flood control issues can be a critical election discussion, at grassroots level. As observed in this study, the authors also considered early warning, location-specific flood intensity information and proper streamlining of planning process and compensation system important for flood control. Knowledge of the rainfall–runoff condition will further improve the understanding of hydrological conditions, and enhance capacity for sustainable mitigation measures for flood vulnerable areas in the trough.