Evaluating land use under climate change by system dynamics in Kohgiluyeh and Boyer Ahmad provinces

Introduction: Land use change represents a dynamic and multidimensional phenomenon shaped by a complex interplay of socio-economic, political, and climatic drivers. These transformations exert profound influences on the integrity of natural resources, the stability of food systems, the quality of the environment, and the broader trajectory of sustainable development. Land use systems are inherently complex, featuring numerous interdependent components and intricate feedback mechanisms—both reinforcing and balancing—that govern their evolution over time. Traditional analytical methods often fall short in capturing such systemic complexity and temporal dynamics. In this context, System Dynamics (SD) has emerged as a robust and effective methodology for modeling and analyzing complex adaptive systems characterized by feedback loops, delays, and nonlinear relationships. Its capacity to simulate long-term behavior makes SD particularly well-suited for investigating land use change dynamics and anticipating future trajectories under varying scenarios.
Materials and Methods: This research applied the System Dynamics approach to explore land use behavior in Kohgiluyeh and Boyer-Ahmad Province, located in southwestern Iran. A comprehensive causal-loop and stock-and-flow model was constructed based on a synthesis of multi-source data, including official statistical records, satellite-derived remote sensing imagery, and supplementary field observations. The model incorporated key state variables such as total population, agricultural land area, rangeland coverage, forested zones, surface water bodies, total water demand, and critical climatic indicators—specifically annual precipitation and average temperature. To ensure model credibility, a dual validation strategy was implemented: behavioral validation, which involved comparing simulated outputs against empirical data from the 2010–2020 period, and structural validation, which examined the internal consistency, logical coherence, and plausibility of the causal relationships embedded within the model architecture.
Results and Discussion: The validation process confirmed a strong alignment between observed historical trends and model-generated simulations, thereby supporting the model’s reliability. Simulation results indicated a clear and direct linkage among population growth, escalating water demand, and the expansion of agricultural activities. Under a medium climate change scenario—reflecting moderate shifts in temperature and precipitation patterns—the model projected a continued increase in both forested and cultivated areas. Conversely, rangelands are anticipated to undergo significant contraction due to the combined pressures of human-induced land conversion and adverse climatic conditions. The expansion of agriculture intensifies reliance on water resources, resulting in heightened extraction from both surface and groundwater systems and a consequent notable decline in the area of lakes, rivers, and other water bodies. Critically, the convergence of declining vegetation cover, reduced rainfall, rising temperatures, accelerated urban sprawl, and population growth may initiate a self-reinforcing cycle of environmental degradation. This negative feedback loop could amplify land degradation and exacerbate water scarcity in the coming decades. Given these projections, the necessity of adopting scientifically informed, adaptive, and integrated land and water management strategies becomes evident.
Conclusion: The findings highlight an urgent imperative for intelligent, forward-looking natural resource management and meticulous spatial planning at the provincial level. Unregulated transformation of ecologically sensitive lands—especially rangelands and forests—into agricultural, industrial, or residential zones, without due consideration of hydroclimatic limits and water sustainability, poses a serious threat of triggering irreversible environmental crises. Consequently, future policy frameworks must be firmly rooted in principles of ecological sustainability, prioritizing the conservation of natural ecosystems and the efficient, equitable use of water resources. This study reaffirms the value of System Dynamics as an integrative modeling tool capable of supporting evidence-based decision-making in land use planning and climate resilience strategies