Factors influencing farming households’ climate change adaptation strategies in Central Vietnam

PLOS One | https://doi.org/10.1371/journal.pone.0328058 July 10, 2025 5 / 22 people rely on the Gianh River for daily life and agricultural production. The river water is also used for irrigation, aqua- culture, and providing domestic water for the community. According to Mai and Truong (2022), with current changes in weather and environment, the Gianh River upstream area is facing challenges regarding water resources. The pro- longed heatwave and increasing seawater intrusion have also caused unwanted impacts on the lives and production of the communities. Reality shows that heatway and saltwater intrusion incidents have increased significantly in recent years compared to the period 2000–2010 and usually occur from April to July every year. These two types of disasters often come together and affect agricultural livelihoods. Firstly, it affects aquaculture: increases the cost of aquaculture activities (if salinity increases, farmers must add sugar to the water or pump more fresh water to neutralize and reduce pond salinity to < 25%). If the phenomenon of saltwater intrusion occurs for a long time, farmers cannot pump water into the pond, causing the shrimp to get sick (because there is not enough oxygen to breathe), so aquaculture output can decrease and cause total loss. Second, it affects farming activities: making the soil saline and acidic, rice plants are unable to grow, productivity decreases by 60–70%, people cannot cultivate and convert to shrimp farming ponds,

brackish water crab or rice fish have higher economic efficiency, most of the land area is in low-lying areas. In addition, drought causes lack of water to irrigate the rice growing area, mainly in the Winter-Spring crop. Planted rice having not enough irrigation water will might reduce productivity. If the drought lasts about 1 month, it can cause crop failure (due to dead rice or flat rice grains) [35,46–48]. 2.2 Empirical model development Adaptation has been widely acknowledged as a critical pillar in the policy response to climate change, particularly in the context of agricultural resilience and rural livelihoods [23,49]. A substantial body of literature has examined the ways in which various regions—especially in developing countries—respond to climate-induced challenges, as well as the key factors shaping these adaptive behaviors [50–52]. Existing studies have demonstrated that farmers’ adaptation strategies are highly context-specific and influenced by a range of factors, including but not limited to farm size, land type, agro- climatic conditions, and broader ecological, institutional, socio-economic, cultural, and political contexts [41,42,50,52]. More recent analyses have identified a complex interplay of determinants that extend beyond structural factors to include institutional accessibility, political frameworks, social networks, cultural norms, behavioral and cognitive dimensions, and gender dynamics [53]. Despite the growing interest in climate change adaptation within the Global South, including parts

of Asia and Africa, there remains a notable research gap concerning the specific barriers and enabling conditions for adopting adaptive strategies in Vietnam, particularly at the household level [44,45,54]. In response to this gap, the present study investigates the factors influencing farming households’ decisions to adopt climate variability adaptation strategies in Vietnam. The analysis encompasses a range of determinants across three broad categories: (i) socio-economic variables such as farm size, income levels, civic organization membership, and farming experience; (ii) demographic characteristics including household size and age of the household head; and (iii) institutional factors such as access to credit, markets, technical training, and climate-related information. These factors are conceptualized in the analytical framework summa- rized in Fig 1, which illustrates the multidimensional nature of adaptation decision-making among rural households. To identify essential variables in farmers’ choice of adaptation strategies, we performed a multinomial logit analysis model (MNL) as previous studies [55–58]. The model allowed determining the relationship between the probability of choosing an adaptation option and a set of explanatory variables, then coming up with the determination of probabilities of different selected adaptive options [59]. In MNL model, let Y be a random dependent variable with values {1 to J} represents the adaptation strategies chosen

by farming households (1 to J) and let Xi be the set of variables described as socio-economic characteristics, institutional factors, and climatic properties. To show how changes in the elements are determined by summing the probabilities of P (Yi) = j Xi . The probability of a dependent variable belonging to the nth category in a multinomial logistic regression model is expressed as below [59,60].