Emergent aquatic vegetation (EAV) is an important part of wetland ecosystems that provide multiple ecological services. However, human activities and natural changes often influence wetland hydrological regimes such as water levels, salinity, and other factors, which greatly influence the survival and growth of wetland plants. Based on field measurements and control experiments, we developed an EAV model to simulate biomass dynamics under changing conditions of water levels and salinity. This model successfully reproduced the seasonal biomass variation of three typical emergent plants, Phragmites australis, Typha angustifolia and Scirpus mariqueter, and simulated the response of EVA biomass under multiple scenarios of water levels and salinity in the Chongming Dongtan Nature Reserve (CDNR), Shanghai, China. Results suggest that there is a negative correlation between salinity and biomass. An optimal range of water levels are suitable for EAV, and biomass will decrease when the water levels are below or above their optimal range. Applying this dynamic EAV model is a cost-effective approach to find a sustainable and nature-based solution to managing and predicting wetland vegetation changes. The model and approach used in this study may provide a sustainable and nature-based solution for management and protection of wetland ecosystems, and may be transferrable to other wetland systems as well.

紧急水生植被（EAV）是提供多种生态服务的湿地生态系统的重要组成部分。但是，人类活动和自然变化通常会影响湿地水文状况，例如水位，盐度和其他因素，从而极大地影响湿地植物的生存和生长。基于现场测量和控制实验，我们开发了一个EAV模型来模拟水位和盐度变化条件下的生物量动态。该模型成功地再现了三种典型的新兴植物（芦苇，香蒲和尖吻鲈）的季节性生物量变化。，并模拟了上海崇明东滩自然保护区（CDNR）在多种水位和盐度情景下EVA生物量的响应。结果表明盐度和生物量之间存在负相关。最佳水位范围适用于EAV，当水位低于或高于其最佳范围时，生物量会减少。应用此动态EAV模型是一种经济有效的方法，旨在找到一种可持续的，基于自然的解决方案来管理和预测湿地植被变化。本研究中使用的模型和方法可以为湿地生态系统的管理和保护提供一种基于自然的可持续解决方案，并且也可以转移到其他湿地系统。