Livestock losses during 2023-24
It was disclosed from Table 1 that during floods in Udalguri and Kalaigaon, cows suffered the highest economic loss (58.07% and 54.90% respectively) due to their high unit value (Rs. 15,000 and Rs. 14,500 respectively). Pigs contributed 18.16% in Udalguri and 30.58% in Kalaigaon, while goats accounted for 22.51% and 13.13%, reflecting their moderate valuation and population density. Despite higher household numbers, poultry had minimal financial impact (1.26% and 1.39%) due to their low unit value (Rs. 100-120). Total losses were Rs. 25,830.20 in Udalguri and Rs. 34,330.00 in Kalaigaon. Similar results were found in the studies of
Borah et al. (2023) and
Saikia et al. (2023).
Problems faced by livestock growers during and after the flood
It was concluded from the above Table 2 that eight important problems were identified by the livestock growers during and after flood situation. Problems like loss of grazing areas as mentioned by 100 per cent of respondents, spreading of diseases (94.5%) and animal treatment (92.5%) were ranked I, II and III respectively. Further, 75.5 per cent of growers faced the problems of alternative feeds (rank IV) followed by the need for fodder storage (rank V) as mentioned by 62.5 per cent of growers. It could be because the floodwaters submerge grazing lands, reducing available pasture for livestock. Floods disrupt infrastructure, hindering access to veterinary services. Inadequate fodder storage facilities often get flooded or washed away, leading to feed shortages and poor animal health.
Again, they faced problems like animal evacuation, damaged forage and animal waste disposal as mentioned by 49.5, 32.5 and 9.5 per cent growers with the rank of VI, VII and VIII respectively. Evacuating animals during floods is challenging due to limited resources and infrastructure. Many animals are estimated to have drowned or been washed away in the floods and their immediate aftermath, highlighting the importance of improved disaster readiness and evacuation plans for livestock. These results align with the observations of
Rasool et al. (2020),
Kumar et al. (2021) and
Prem (2023).
To prioritize the main problems, further analysis was done using Pareto analysis. Fig 1 shows that the cumulative percentage reach 100 per cent around the 7
th bar “Damaged forage”, which mean that all the categories to the left of this bar (included) accounts for all the vital factors.
Strategies adopted by livestock growers in flood-prone areas
The strategies adopted by the livestock growers were arranged into three sections
i.e housing management, feeding management and
health care management. It was identified from Table 3 that in housing management category, majority of livestock growers (94.5%) go for the construction of animal shed in highlands (rank I), construction of pucca sheds for animals adopted by 28.5 per cent growers (rank II) followed by 18 per cent using government buildings for shelter during flood (rank III). The reasons for adopting these management strategies may be that the highlands are less prone to waterlogging and provide a safe refuge for livestock during heavy rains or floods, ensuring their health and reducing losses and the government structures are often well-built and located in flood-resistant areas, providing immediate and reliable protection in emergencies. Similar findings were observed by
Rasool et al. (2020),
Rymes (2022),
Anitha et al. (2023) and
Hirkani et al. (2023).
In feeding management strategies, 100 per cent of the growers go for feeding the locally available crop residues and making hay/ bales (rank I) followed by storage of a sufficient quantity of feed material adopted by 71 per cent of growers (rank II). Growing perennial forage crops in wasteland/highland and silage making were the strategies adopted by 32.5 and 10.5 per cent with rank III and IV respectively. The probable rationale for implementing these strategies could be that during floods, accessing regular feed becomes challenging. Livestock growers rely on locally available crop residues as an immediate and cost-effective source of feed to sustain their animals. Hay and bales are prepared and stored during surplus seasons to ensure a supply of nutritious feed during floods. These are easy to transport and store, providing a reliable food source when fresh forage is unavailable. Perennial forage crops, such as Napier grass, planted in wasteland or highland areas, remain accessible during floods. These crops provide continuous feed even when lowland fields are submerged. These observations align with
Pathak et al. (2006),
Mahajan et al. (2015),
Mishra et al. (2017) and
Patel et al. (2023).
Further, in healthcare management strategies as shown in Table 3, vaccination of animals before or after flood was ranked I as 48 per cent of livestock growers go for it followed by stocking of emergency medicine during flood period adopted by 41 per cent (rank II) and keeping and maintaining emergency contact with veterinary officers/ doctors ranked III as only 12.5 per cent of them adopted it. The rationale behind these strategies may be to safeguard them against diseases that are likely to spread during or after floods, such as foot-and-mouth disease, leptospirosis and to keep a supply of common medicines, such as antibiotics, antipyretics, dewormers and antiseptics to address immediate health issues during floods
(Pyne et al., 2009, Vijay et al., 2024, Tiwari et al., 2025 and
Vismaya et al., 2024). In recent times, Artificial Intelligence (AI) has played a vital role in detecting animal diseases through its ability to analyse data, recognize patterns and make informed decisions (
AlZubi, 2023).
Association between different strategies adopted by livestock growers in flood-prone areas
To check the association between different strategies, Pearson correlation coefficient (r) was calculated between the strategies. The results of the correlations were grouped into 3 sections
i.e strong, moderate and weakest correlation. For the foremost category, it was disclosed from Table 4 that a significant relationship was found between feeding of locally available crop residues and making hay/bales (r=1.00), construction of animal sheds in highlands with feeding of locally available crop residues and making hay/bales (r=0.80) and storage of sufficient amount of feeding material with feeding of locally available crop residues and making hay/bales (r=0.80). Again, vaccination of animals before or after flood and stocking of emergency medicine for flood period (r=0.78). Farmers who opt for highland sheds are more likely to ensure feed security. Using locally available crop residues and producing hay are cost-effective strategies. They minimize the need for purchasing external feed resources, which can be expensive and scarce during flood times. This economic efficiency is crucial for farmers in flood-prone regions, where financial resources may be limited. Disease outbreaks during floods can lead to significant economic losses due to increased treatment costs and livestock mortality. By vaccinating animals and stocking emergency medicines, farmers can prevent or mitigate these losses, ensuring the sustainability of their livelihoods. Similar findings were found in the study of
Sen et al. (2003) and
Kumar et al. (2021).
For the second category, there was a moderate correlation between vaccination of animals before or after flood with the construction of animal sheds in highland (r=0.72), feeding of locally available crop residues (r=0.72), making hay/ bales (r=0.72) and storage of sufficient quantity of feed material (r=0.70). Stocking of emergency common medicine for flood period by establishing animal shed in highland (r=0.65), feeding of locally available crop residues (r=0.68) and making hay/ bales (0.68). Again, storage of proper quantity of feed material with construction of animal shed in highland (r=0.75), stocking of emergency common medicine in flood (r=0.66) and growing perennial forage crop in wasteland/highland (r=0.65). Consolidating livestock and feed storage in highland sheds allows for centralized management, making it easier for farmers to monitor feed consumption and animal health during floods. These results correlate with the findings of
Rasool et al. (2021) and
Borah et al. (2022).
Silage making showed weak correlation with pucca shed construction (r=0.32) and using government buildings for shelter (r=0.29). High costs and labor demands for pucca sheds may shift farmers’ focus to immediate shelter over feed preservation.
Factors influencing farmers’ strategies and actions for managing livestock during floods
The findings from Table 5 indicate that age (-0.091) with farmers’ adaptive strategies for managing livestock during floods. Older farmers are less likely to adopt new technologies and strategies due to reduced flexibility, innovation and risk tolerance. A comparable result has been observed in the work done by
Maddison, (2007),
Acquah (2011),
Quayum et al. (2012) and
Tambo et al. (2013). Larger farms (-9.214) are less likely to adopt flood management strategies due to implementation challenges and complex management structures. Similar findings were given by
Bradshaw et al. (2004) and
Gebrehiwot et al. (2013).
Again, education (1.354), family income (0.0021) and training received (1.235) were found positive and member of farmers organization (6.214) was positive. Higher education increases the likelihood of adopting flood management strategies due to better awareness, access to information and decision-making skills. This finding was supported by
Deressa et al. (2009) and
Asfaw et al. (2004). This finding goes the same with the findings of
Seo et al. (2008) and
Deressa et al., (2011). Training improves farmers’ awareness and ability to adopt flood management strategies. Farmers who participate in groups have a higher tendency to choose adaptation measures. These findings were endorsed by the findings of
Knowler et al. (2007),
Kassie et al. (2011),
Tazeze et al. (2012) and
Bryan et al. (2013). Family size (3.554) and market access (0.021) showing minimal impact on farmers’ flood management decisions
(Below et al., 2012, Ndambiri et al., 2012 and
Khanal et al., 2018).
