Simulation of Vegetation Cover Based on the Theory of Ecohydrological Optimality in the Yongding River Watershed, China

During ecological restoration, it is necessary to comprehensively consider the state of vegetation in climate-soil-vegetation systems. The theory of ecohydrological optimality assumes that this state tends to reach long-term dynamic equilibrium between the available water supply of the system and the water demand of vegetation, which is driven by the maximization of productivity. This study aimed to understand the factors that affect the spatial distribution of vegetation and simulate the ideal vegetation coverage (M-0) that a specific climate and soil can maintain under an equilibrium state. The ecohydrological optimality model was applied based on meteorological, soil, and vegetation data during the 2000-2018 growing seasons, and the sensitivity of the simulated results to input data under distinct vegetation and soil conditions was also considered in the Yongding River watershed, China. The results revealed that the average observed vegetation coverage (M) was affected by precipitation characteristic factors, followed by wind speed and relative humidity. The M, as a whole, exhibited horizontal zonal changes from a spatial perspective, with an average value of 0.502, whereas the average M-0 was 0.475. The ecohydrological optimality theory ignores the drought resistance measures evolved by vegetation in high vegetation coverage areas and is applicable to simulate the long-term average vegetation coverage that minimizes water stress and maximizes productivity. The differences between M and M-0 increased from the northwest to the southeast of this area, with a maximum value exceeding 0.3. Meteorological factors were the most sensitive factors of this model, and the M-0 of the steppe was most sensitive to the stem fraction, mean storm depth, and air temperature. Whether soil factors are sensitive depends on soil texture. Overall, the study of the carrying capacity of vegetation in the natural environment contributes to providing new insights into vegetation restoration and the conservation of water resources.