The Mekong Delta region has been seriously affected by climate change, with increasing temperatures, sea-level rise, and salinization strongly impacting agricultural activities of the region. Recent studies have shown that groundwater exploitation also contributes significantly to land subsidence throughout the delta. Thus, combating climate change now makes it necessary to design strategies and policies for adapting to and mitigating climate change and subsidence, not only at the individual level (mainly farmers), but also at the institutional level (province and region). This study aims to build an integrated model for the purpose of exploring the socio-economic impact of adaptation strategies provinces choose under various climate and economic scenarios. The LUCAS–GEMMES model (an agent-based model for strategies for adapting to land-use change in the context of climate change) was developed in order to evaluate socio-economic factors, climate, and water use by farmers, as well as the subsidence dynamics and macroeconomic trends in land-use selection strategies. The simulations are carried out according to four main scenarios: (i) lack of provincial adaptation strategies and absence of subsidence dynamics, (ii) lack of adaptation strategies though subsidence and the impact of land-use production benefits, (iii) purely individual adaptation strategies combined with the impact of subsidence, and (iv) provincial and individual-scale adaptation combined with the impact of subsidence. In all the scenarios that consider subsidence, our results show that early response decisions to even low-level subsidence lead to many positive outcomes in water resource management, such as a significant reduction in water-use in the dry season and a reduction in the area vulnerable to subsidence and climate change. However, the same results also indicate a possible decrease in farmers’ income due to reduced agricultural seasons and restricted land-use transformation, which demonstrates the importance of modeling the multi-sectoral aspects of adaptation. Finally, at a more general level, in the fourth scenario, the model clearly shows the benefits when provinces located in the same agro-ecological zone harmonize strategies, thus paving the way for defining integrated land-use policies at the regional level.

Agricultural land-use changes pose challenges for land managers in terms of ensuring the implementation of local land-use plans. This paper aims to build a land-use change model named MEKOLUC (Mekong Delta land-use change) for simulating land-use changes under the impacts of socioeconomic factors (profitability of land-use types, societal impacts on neighborhoods) and environmental factors (soil, salinity, persistence of salinity). The salinity diffusion map was generated using GAMA software and employed Markov cellular automata to depict the spread of salinity under the influence of dike and sluice gate system operations. The land-use decision-making process was based on multi-criteria selection of the main factors, which were land suitability, land convertibility, density of land use in the neighborhood and profitability of land-use patterns. The input data for the case study were historical land-use maps from 2005, 2010 and 2015 of Soc Trang, a coastal province in the Mekong Delta. The model was calibrated using a land-use map from 2010 (with kappa = 0.86) and was verified with land-use maps from 2015 and 2020 with deviations from 0 to 19%. The simulated results showed that shrimp–rice farming areas have been shrinking, even though these are recommended as sustainable farming systems. Inversely, intensive rice crops tended to change to rice–vegetable crops, vegetable crops or perennial fruit trees, which are projected to be well adapted to climate and salinity intrusion by 2030. This case study shows that the developed model is an essential tool for helping land managers and farmers build land-use plans.

Land-use planning plays an important role in agricultural development. However, the tools used to support planners in proposing land-use planning solutions are lacking, especially when considering saltwater intrusion conditions in coastal regions. In this study, optimization is applied by analyzing land use in developing solutions for agricultural land-use planning, wherein a multi-objective optimization model is developed to optimize land-use area, including land-use allocation, and taking into account socioeconomic and environmental factors. The model was applied to three districts of Soc Trang province, Vietnam (Long Phu, My Xuyen, and Tran De), representing three ecological regions of salt water, brackish water, and fresh water in the Mekong Delta of Vietnam. The results are shown for the implementation of two multi-objective optimization scenarios (in terms of profit, labor, environment benefits, and risk reduction) as follows: (i) multi-objective optimization of agricultural land use until 2030 under normal conditions; (ii) optimizing agricultural land use until 2030 under climate change conditions similar to the 2016 drought and saltwater intrusion phenomenon in the Mekong Delta. The results demonstrate that the second scenario is the preferred option for implementing land-use planning thanks to the balance between good profits and minimizing economic and environmental risk. Land allocation was carried out by taking into account the factors of household economics, the influence of adjacent production types, local traffic, and canal systems to allocate areas toward ensuring optimal land use. This process, involving a combination of land-use optimization and spatial allocation, can help planners to improve the quality of agricultural land-use planning.

The rice-shrimp farming system is considered as a sustainable and beneficial model for the environment. However, the area of rice-shrimp was increasingly narrowed due to the trend of converting from rice to aquaculture by economic reasons. This paper aims to propose a medium scale land use change model for understanding the land use decision of farmers in adaptation to the environment and climate change. The model integrates a land-use decision making process based on multi-criteria selection where the main factors are land suitability, land convertibility, land use situation of neighbors, and profitability of land use patterns. Concerning the land use data, we used historical land use map in 2005, 2015 and 2019. Shrimp cultivation regions was completed by Landsat satellite image processing. The model has been calibrated by rice-shrimp map in 2015 and has been verified with the rice – shrimp map in 2019 of the My Xuyen district, Soc Trang province, Vietnam. The simulated results show that the rice-shrimp area was increasingly narrowed and has been converted to aquaculture land. In addition, the model tends to show that in a scenario of sea level rise of 15 cm in 2030, the share of rice-shrimp and shrimp tends to rise sharply, which is an important lesson for developing complex adaptive strategies of farmers.

Background: Climate change, socioeconomic, market demands and labor restructuring have led to the need for agricultural restructuring in coastal areas in Vietnam. This study was conducted to assess the factors affecting agricultural production and analyze land use scenarios to support the agricultural transformation in the coastal area of the Vietnamese Mekong Delta. Methods: The implementation method is based on surveying the necessary dynamic level of socioeconomic and environmental factors affecting land use; the connection between the land area optimization using linear programming and the CLUMondo. Result: The results proposed 3 scenarios to improve the efficiency of state land management for socioeconomic development and agricultural restructuring in the study area. Scenario 1 (the land-allocated results were similar to the land use map) and scenario 2 (extensive shrimp farming areas in the coastal zone will be firmly converted to intensive shrimp farming) are suitable for the district in the short term. However, Scenario 3 (the shrimp-rice area tends to convert to rice land, while agricultural land near the town will be firmly converted to non-agricultural land) is the most appropriate option when funds are available for high technology advancement.