4.1 Socio-demographic characteristics of respondents
Results showed that majority of them were females (n = 78; 52%) as compared to the males (n = 72; 48%) (Table 3). This is in accordance with the recent census report for Kumasi which revealed that the female population outnumber that of their male counterparts (Kumasi Metropolitan Assembly, 2021). About 56% of the respondents (n = 84) were in the age category of 21–40 years. In terms of education, 68 of the respondents (45%) had attained basic education. Few of the respondents (n = 11; 7.3%) had tertiary form of education. Education is an important socio-economic factor because research has revealed that education tends to improve life circumstances and reduce environmental risk factors (Aikens and Barbarin 2008; Morgan et al. 2009). Most of the respondents (n = 98; 65%) had stayed in the study communities for above 10 years. This implies that most of them had an in-depth knowledge and understanding of flood issues in the communities and this is essential for designing flood interventions policies. Majority of the respondents (n = 95; 63%) had access to weather and climate information. A significant coping step that can improve the ability of vulnerable communities to mitigate climate related disasters is the well timed accessibility and utilization of accurate weather and climate information (Antwi-Agyei et al. 2021a, 2021b; Baffour-Ata et al. 2022). Hence, most of the respondents accessing weather and climate information implied that they had the capacity to manage floods in the study communities.
Table 3
Socio-demographic characteristics of respondents
| Gender | |
Variables | Males (n = 72) | Females (n = 78) | Total (n = 150) |
Age (in years) | | | |
Below 20 | 10 (13.9) | 6 (7.7) | 16 (10.7) |
21–40 | 45 (62.5) | 39 (50.0) | 84 (56.0) |
41–60 | 11 (15.3) | 29 (37.1) | 40 (26.7) |
Above 60 | 6 (8.3) | 4 (5.1) | 10 (6.7) |
Household size | | | |
1–5 | 18 (25.0) | 14 (18.0) | 32 (21.3) |
6–10 | 27 (37.5) | 34 (43.6) | 61 (40.7) |
11–15 | 27 (37.5) | 30 (38.4) | 57 (38.0) |
Educational level | | | |
No formal education | 7 (9.7) | 17 (21.8) | 24 (16.0) |
Basic education | 31 (43.0) | 37 (47.4) | 68 (45.3) |
Secondary education | 26 (36.1) | 21 (26.9) | 47 (31.3) |
Tertiary | 8 (11.1) | 3 (3.8) | 11 (7.3) |
Occupation | | | |
Government worker | 5 (6.9) | 1 (1.3) | 6 (4.0) |
Self- employed | 67 (93.0) | 77 (98.7) | 144 (96.0) |
Period of staying in the community | | | |
Below 5 years | 11 (15.3) | 14 (18.0) | 25 (16.7) |
5–10 years | 18 (25.0) | 9 (11.5) | 27 (18.0) |
Above 10 years | 43 (59.7) | 55(70.5) | 98 (65.3) |
Access to weather information | 47 (65.3) | 48 (61.5) | 95 (63.3) |
Access to household communication gadgets | 64 (88.9) | 69 (88.5) | 133 (88.7) |
Numbers in and out of parentheses indicate percentages and frequencies respectively |
4.2 Study respondents’ perception of changes in rainfall and floods
Table 4 presents the respondents’ perception of changes in rainfall and floods. Perception is relevant in environmental and climate change studies because peoples’ coping mechanisms to weather extremes are closely related to their perception of changing weather conditions (Afriyie et al. 2018; Ge et al. 2021). For instance, Ge et al. (2021) reported that comprehension and enhancing public risk perception have become a key component in flood risk management. Majority of the respondents (n = 81; 54%) reported that the amount of rainfall had increased in the study communities. For instance, one of the respondents stated this:
“Recently, there has been an increase in the amount of rainfall particularly in Kumasi. The rains could start around 4 pm in the evening today and end tomorrow at dawn. The intensity at which it rains these days is also very high so you can imagine the total amount that could be measured when the rain stops” – (Male respondent, Sepe-Buokrom, April, 2021)
About 48% of the respondents (n = 72) reported that the duration of rainy season had also increased. Regarding floods, 81 of the respondents representing 54% reported that flood incidence had increased. Slightly more than half (55%) of the study respondents (n = 82; 55%) indicated that storms had also increased in the study communities. These findings agree with earlier research works (for example: Amoateng et al. 2018; Tazen et al. 2019; Lai et al. 2020; Jamal et al. 2021) suggesting that rainfall amounts have increased recently contributing to increased incidence of floods. The increase in storms and strong winds in the study communities has the potential to increase flood incidence. This is because, studies have shown that increased storms and strong winds are the main drivers of floods (Slingo et al. 2014; Muis et al. 2016). For example, Muis et al. (2016) conducted a global reanalysis of storm surges and extreme sea levels and suggested that extreme sea levels and high tides contribute significantly to increase coastal flooding in many countries across the globe.
Table 4
Perception of rainfall changes and floods by residents in urban Kumasi
| Gender | |
Variables | Males (n = 72) | Females (n = 78) | Total (n = 150) |
Amount of rainfall | | | |
Increased | 34 (47.2) | 47 (60.2) | 81 (54.0) |
Constant | 25 (34.7) | 22 (28.2) | 47 (31.3) |
Decreased | 13 (18.0) | 9 (11.5) | 22(14.7) |
Duration of rainy season | | | |
Increased | 35 (48.6) | 37 (47.4) | 72 (48.0) |
Constant | 12 (16.7) | 7 (9.0) | 19 (12.7) |
Decreased | 25 (34.7) | 34 (43.5) | 59 (39.3) |
Incidence of floods | | | |
Increased | 30 (41.7) | 51 (65.4) | 81 (54.0) |
Constant | 29 (40.2) | 24 (30.7) | 53 (35.3) |
Decreased | 13 (18.0) | 3 (3.8) | 16 (10.7) |
Flood risk | | | |
Increased | 32 (44.4) | 39 (50.0) | 71 (47.3) |
Constant | 26 (36.1) | 25 (32.0) | 51 (34.0) |
Decreased | 14 (19.4) | 14 (18.0) | 28 (18.7) |
Storms | | | |
Increased | 40 (55.5) | 42 (53.8) | 82 (54.6) |
Constant | 20 (27.7) | 18 (23.0) | 38 (25.3) |
Decreased | 12 (16.7) | 18 (23.0) | 30 (20.0) |
Strong winds | | | |
Increased | 39 (54.2) | 40 (51.3) | 79 (52.7) |
Constant | 19 (26.4) | 19 (24.4) | 38 (25.3) |
Decreased | 14 (19.4) | 19 (24.4) | 33 (22.0) |
Numbers in and out of parentheses indicate percentages and frequencies respectively |
4.3 Respondents’ perceived causes and effects of floods in urban Kumasi.
The respondents had varying opinions on the causes of floods. Majority of the respondents mentioned that choked drains (n = 145; 97%) and poor design of drain infrastructure (n = 145; 97%) were the major causes of floods in the communities (Fig. 2; Table 4a). For example, one respondent remarked that:
“The poor design of drains is the primary cause of floods in this community. The drains are not large enough to accommodate large volumes of water and ensure easy flow of water. The result is that when the rains fall heavily, there is an overflow of water, even in areas considered to be dry” – (Female respondent, Atonsu, May, 2021).
Lack of adequate drains was also reported by majority of the respondents (n = 140; 93%) as another major cause of floods in the study communities. However, few of the respondents (n = 17; 11%) attributed the cause of floods to an act of God. For instance, one of them said this:
“I believe the main cause of floods in this community is an act of God. Signs like these have already been predicted in the Bible to happen during the end times so I’m really not surprised” – (Female respondent, Ahinsan, May, 2021).
The results are consistent with earlier studies conducted in other parts of Ghana (e.g. Amoako and Frimpong Boamah 2015; Bempah and Øyhus 2017) and sub-Saharan Africa countries including Kenya (e.g. Okaka and Odhiambo 2019) suggesting that poor environmental attitudes (e.g. bad refusal disposal), poor urban planning and development, inadequate drainage facilities and Act of God are the perceived causes of floods. Floods occur in these communities due to the fact that legislation governing erection of buildings and hygiene are not rigorously implemented by the concerned officials.
Further, the arrangement of structures and layout plan of the study communities were haphazardly scattered without adequate spaces created in between these buildings. Buildings for human settlements, offices and businesses were not properly and orderly arranged. These unplanned settlements associated with lack of adequate drain infrastructure resulted in increased flood occurrences in the study communities. Results further revealed that improper waste disposal practices was a key cause of increased incidence of floods in the study communities. The fewer drains situated in these areas were highly choked with solid waste due to improper waste disposal practices of inhabitants. Commuters, educational institutions as well as households throw their solid wastes into drains, gutters and streets. This prevents easy flow of water when it rains heavily. Low lying nature of reliefs in these communities also seemed to pose threat of floods which indirectly affected them without any direct driving actions from inhabitant or communities. Whenever there are heavy rains, such areas experience floods. Uncontrolled generation of wastes has been a major constraint to many city authorities in Africa. With waste generation of 0.75 kilogram across cities in Ghana, city officials have become very disturbed (Miezah et al. 2015).
Poor waste management practices may elevate flood hazards in a number of ways. Improper disposal of waste along roads could physically block the drainage system, influencing the flow of runoff in the canal system. This directly causes flash floods in urban areas (Mensah and Ahadzie 2020). This driving factor is worsened by the increased rate of ignorance and poor enforcement of environmental laws in the country (Ahadzie et al. 2016).
With reference to perceived effects of floods, a greater number of the respondents (n = 148; 99%) disclosed that their properties have been damaged as a result of the floods (Fig. 2). This was closely followed by decreased economic productivity (n = 147; 98%). Most of the respondents (n = 128; 85%) also pointed out soil erosion as one of the major effects. Nonetheless, few of the respondents (n = 36; 24%) revealed that lives were lost when there were floods in the communities. Study respondents have often experienced the devastating effects of floods including loss of properties and livelihoods. These findings compare favorably with previous studies (Memon, 2015; Mensah and Ahadzie, 2020) indicating that floods exert significant implications on the lives of people including destruction of properties, crops and lives, decreased economic productivity, erosion of soil and waterlogged lands that eventually leads to outbreak of water-related diseases such as malaria. For example, Memon (2015) reported that heavy rains and floods have been responsible for unparalleled losses to the lives of humans and the environment in Pakistan.
Destruction of properties was the major effect reported by the respondents (Table 4b). Floods poses serious risks to domesticated animals including dogs, pigs and goats. Decreased economic productivity was another major effect mentioned by the respondents. According to the respondents, floods adversely affect the flow of trade and finance that make up both individual and national economies. This, they attributed to the fact that when floods occur, people are unable to go about their various economic activities and this tends to affect their incomes and eventually their standard of living.
Flooding also results in eroding of soil (Table 4a). The fast movement of water is able wash the top soil which accommodates majority of the nutrients needed by plants, eventually depleting the soil (Abayomi, 2014). Soil erosion weakens buildings and creates channels and gullies on streets and roads, making some of them impassable. Loss of lives was another effect perceived by few number of respondents (Table 4b). According to the respondents, lives lost in the communities as a result of flood occurrences were due to drowning incidences which occurred when vehicles were carried away by the flood waters.
Table 4
a: Perceived causes of floods in urban Kumasi
| Gender | |
Perceived causes | Males (n = 72) | Females (n = 78) | Total (n = 150) |
Poor design of drain infrastructure | 69 (95.8) | 76 (97.4) | 145 (96.7) |
Choked drains | 70 (97.2) | 75 (96.2) | 145 (96.7) |
Low lying nature of relief | 68 (94.4) | 76 (97.4) | 144 (96.0) |
Lack of adequate drains | 64 (88.9) | 76 (97.4) | 140 (93.3) |
Improper waste disposal practices | 64 (88.9) | 72 (92.3) | 136 (90.7) |
Building on/close to water resources | 65 (90.3) | 68 (87.2) | 133 (88.7) |
Unplanned settlements | 60 (83.3) | 60 (76.9) | 120 (80.0) |
Act of God | 7 (9.7) | 10 (12.8) | 17 (11.3) |
Numbers in and out of parentheses indicate percentages and frequencies respectively |
Table 4
b: Perceived effects of floods reported by study respondents
| Gender | |
Perceived effects | Males (n = 72) | Females (n = 78) | Total (n = 150) |
Destruction of properties | 71 (98.6) | 77 (98.7) | 148 (98.7) |
Decreased economic productivity | 72 (100.0) | 75 (96.1) | 147 (98.0) |
Soil erosion | 62 (86.1) | 66 (84.6) | 128 (85.3) |
Disease outbreak | 39 (54.2) | 39 (50.0) | 78 (52.0) |
Destruction of water distribution channels and septic systems | 55 (76.4) | 59 (75.6) | 114 (76.0) |
Loss of lives | 19 (26.4) | 17 (21.8) | 36 (24.0) |
Numbers in and out of parentheses indicate percentages and frequencies respectively |
4.4 Coping mechanisms used by households to manage floods
The respondents had various coping mechanisms in response to floods in the study communities (Table 5). The majority of the study respondents (n = 149; 99%) reported using temporary migration as a key coping mechanism to floods in the study communities. Others (n = 146; 97%) also relied on family or friends during flood events. Contrastingly, about 48% of the respondents (n = 72) relied on support from government or non-governmental organizations during floods. For instance, one of the respondents indicated that:
“Government officials like Natural Disaster Management Organization (NADMO) comes to our aid two weeks after flood incidence and provide us with blankets and mattresses which will not be beneficial to our situation at that moment. They do not show up again until there is another flood situation” – (Female respondent, Ahinsan, May, 2021).
These findings agree with earlier research works (for example: Bola et al. 2014; Musyoki et al. 2016; Danso and Addo 2017; Owusu-Ansah et al. 2019) conducted in other parts of Ghana and Africa suggesting that households have managed floods through the implementation of coping strategies such as reliance on family and friends and temporary migration. Social capital is an important aspect in a community's ability to recover quickly and 'bounce back' after a disaster. Coordination and collaboration for mutual benefit are made easier by these social networks, norms, and social trust (Okayo et al. 2015). The more networks a household head is a member of, the more the family will rely on disaster coping strategies to deal with disaster effects (Nji and Balgah 2019). Temporary migration was the major coping mechanism used by the respondents (Table 5). Temporary migration in this study is defined as migration to another community that is not intended to be permanent, for a specified and limited period of time, and usually undertaken because of the floods (Call et al. 2017). The respondents remarked that after the floods, they return to their communities and clean up their houses hoping to recover some of the properties that were not destroyed by the floods.
Majority of the respondents also relied on family and friends for assistance which have often proven to be very helpful (Armah et al. 2010; Casagrande et al. 2015). This emphasizes the crucial role played by social networks as critical tools for management of floods. For instance, results from a study conducted at Mississippi in the United States of America showed that flood affected people relied mostly on immediate family for support (Casagrande et al., 2015). However, in this study, few of the respondents relied on governmental and non-governmental organizations (Table 5). This could be attributed to the fact that most of these organizations do not have specific policies targeted at flood victims (Armah et al. 2010). This situation subverts the sustainability of the relief programmes initiated by governmental and non-governmental organizations (Armah et al. 2010). The least cited mechanism was climbing on top of wardrobes with reason being that it was risky using that as a coping strategy because the duration and intensity of the rains were mostly uncertain and also, most of the inhabitants found it difficult climbing these structures.
Table 5
Coping mechanisms used by respondents to manage floods
| Gender | |
Coping mechanisms | Males (n = 72) | Females (n = 78) | Total (n = 150) |
Temporary migration | 71 (98.6) | 78 (100.0) | 149 (99.3) |
Rely on family/friends | 70 (97.2) | 76 (97.4) | 146 (97.3) |
Desilting of choked gutters | 37 (51.4) | 41 (52.6) | 78 (52.0) |
Rely on government and non-governmental organisations | 32 (44.4) | 40 (51.3) | 72 (48.0) |
Proper waste disposal | 34 (47.2) | 35 (44.9) | 69 (46.0) |
Demolishing of buildings (unplanned) | 24 (33.3) | 20 (25.6) | 44 (29.3) |
Climb on roof tops | 13 (18.1) | 14 (17.9) | 27 (18.0) |
Climb a tree above the flood level | 4 (5.6) | 0 (0.0) | 4 (2.7) |
Climb on top of wardrobes | 3 (4.2) | 0 (0.0) | 3 (2.0) |
Numbers in and out of parentheses indicate percentages and frequencies respectively |
4.5 Determinants of coping mechanisms used by the respondents
Results showed that the coping mechanisms employed by the respondents to manage floods were significantly influenced by socio-demographic factors including access to weather and climate information (p = 0.000, β = 1.983), access to household communication gadgets (p = 0.001, β = 2.371), period of staying in the community (p = 0.012, β = 0.670) and age of the respondent (p = 0.040, β = 5.350) (Table 6). These factors been reported in prior research including Balgah et al. (2019), Nji et al. (2019) and Navarro et al. (2020) to significantly affect coping mechanisms to floods. For instance, weather and climate information services provide science-based and user-specific information that can be used to manage flood risks and exploit opportunities created by floods (Machingura et al. 2018). The predominant source of dissemination of weather and climate information to respondents is the media. This implies that acquiring of household communication gadgets such as mobile phone, radio and television is very crucial to accessing weather and climate information. Most of the respondents in this study had access to household communication gadgets (Table 3) thereby explaining the reason for it being a significant factor.
Period of staying in the communities also facilitated the implementation of coping mechanisms in the study communities. Results showed that majority of the respondents had lived in the selected communities for above 10 years (Table 3). There is high probability that people who have lived in a flood prone community for a long time will cope better with flood risks as compared to those who have lived there for a shorter period. This is consistent with a prior research indicating that factors including period of staying in a community significantly influenced coping mechanisms to floods in Colombia (Navarro et al. 2019). Age was also a significant determinant in the model and this is in line with a previous study conducted in northern Ghana indicating that age plays a crucial role in the implementation of coping strategies to floods (Lolig et al. 2014). This is because, the residents who are old tend to depend on social support as compared to the younger ones (Berman et al. 2015). The younger ones tend to implement coping strategies including climbing on roof tops, trees and wardrobes by virtue of their energy and strength.
Factors including household size, educational level and occupation were not significant determinants. This compares favourably with a study conducted in the past where the authors found some of those factors to be non-significant (Wang et al. 2018). For instance, Wang et al. (2018) argued that in discussion of flood risk management strategies, occupation is not a significant factor. With regard to educational level, the possible reason could be that there were no so many highly educated people in the study communities (Table 3) as an earlier study has argued that very well educated people are likely to better appreciate information on flood and hence may feel a greater sense of coping or managing it (Wang et al. 2018). Household size can significantly or insignificantly influence urban residents’ coping mechanisms to floods. Very large household size could contribute to the conversation, conformation and sharing of flood related issues thereby enhancing the management of floods significantly. However, in this study, household sizes were not too huge (Refer to Table 3).
Table 6
Factors influencing coping mechanisms in urban Kumasi
Determinant | Coefficient (β) | p -value |
Access to weather and climate information | 1.983 | 0.000 |
Access to household communication gadgets | 2.371 | 0.001 |
Period of staying in the community | 0.670 | 0.012 |
Age of the respondent | 5.350 | 0.040 |
NB: p < 0.05 = significant whilst p > 0.05 = not significant |
4.6 Barriers to coping mechanisms by respondents in urban Kumasi
The respondents reported several barriers to the use of coping mechanisms to manage floods in the study communities (Table 6). The key barrier reported by the respondents was financial constraints (n = 145; 97%). This was followed by lack or inadequate support from government and non-governmental institutions (n = 142; 95%) and inadequate logistics to respond to floods (n = 142; 95%). For example, one key informant spoke on this:
“Government support flood victims in the municipality with emergency relief items including mattresses, bundles of clothes, sugar and rice, boxes of cooking oil, soap, blankets, plastic buckets, bowls, cups and mats, bags of sachet water, as well as boxes of mosquito coils and treated mosquito nets. However, the flood victims tend to want cash donations and I think that is why they report that we do not support them” – (Key informant, May, 2021)
Lack of weather and climate information was mentioned as the least barrier (n = 55; 37%). These findings are consistent with previous studies (e.g. Biesbroek et al. 2013; Halkos and Skouloudis 2020) suggesting that barriers to coping mechanisms of floods are often related to financial, informational, cognitive, institutional and social. For example, with regards to financial barrier, key informant interviews revealed that insufficient funds are usually disbursed to medium and small-sized organizations such as local governments, to spend and those are usually prioritized to urgent matters. Organisations often have competing needs with inadequate human, financial and technical resources to address issues pertaining to floods. The organisations are then left with inadequate resources to embark on a detailed programme of coping from devising through to execution. Nevertheless, it highlights the importance of institutions for facilitating a successful coping mechanism.
The respondents also disclosed that they do not have enough funds to relocate to communities that are less prone to floods. Furthermore, while there is a huge agreement of climate change, there is unpredictability about the extent of the changes. Although scientific knowledge will keep growing, however, for numerous forms of climate risks including flood risks, it will be difficult to have accurate predictions of the timing as well as the magnitude of floods. People with low comprehension of the changes in climate and weather extremes will also not prepare adequately for its effects or even welcome the idea that other people should arranged to cope. They normally suggest that there is the need to be more confident about the science before taking actions or that the threats are small-scaled and measures could be delayed.
Table 6
Barriers to flood coping mechanisms in urban Kumasi
| Gender | |
Barriers | Males (n = 72) | Females (n = 78) | Total (n = 150) |
Financial constraints | 69 (95.8) | 76 (97.4) | 145 (96.7) |
Lack or inadequate support from government and non-governmental institutions | 70 (97.2) | 72 (92.3) | 142 (94.7) |
Inadequate logistics to respond to floods | 67 (93.0) | 75 (96.2) | 142 (94.7) |
Lack of understanding on early warning systems | 57 (79.2) | 69 (88.5) | 126 (84.0) |
Cognitive barrier (e.g., Uncertainty about impact) | 53 (73.6) | 60 (76.9) | 113 (75.3) |
Lack of information on weather and climate | 26 (36.1) | 29 (37.2) | 55 (36.7) |
Numbers in and out of parentheses indicate percentages and frequencies respectively |