Tapas Mahesh R, Etheridge Randall, Tran Thanh-Nhan-Duc, Finlay Colin G, Peralta Ariane L, Bell Natasha, Xu Yicheng, Lakshmi Venkataraman
Integrated Coastal Program, East Carolina University, Greenville, NC 27858, USA.
Department of Engineering, Center for Sustainable Energy and Environmental Engineering, East Carolina University, Greenville, NC 27858, USA.
Sci Total Environ. 2024 Nov 15;951:175523. doi: 10.1016/j.scitotenv.2024.175523. Epub 2024 Aug 13.
This study addresses the urgent need to understand the impacts of climate change on coastal ecosystems by demonstrating how to use the SWAT+ model to assess the effects of sea level rise (SLR) on agricultural nitrate export in a coastal watershed. Our framework for incorporating SLR in the SWAT+ model includes: (1) reclassifying current land uses to water for areas with elevations below 0.3 m based on SLR projections for mid-century; (2) creating new SLR-influenced land uses, SLR-influenced crop database, and hydrological response units for areas with elevations below 2.4 m; and (3) adjusting SWAT+ parameters for the SLR-influenced areas to simulate the effects of saltwater intrusion on processes such as plant yield and denitrification. We demonstrate this approach in the Tar-Pamlico River basin, a coastal watershed in eastern North Carolina, USA. We calibrated the model for monthly nitrate load at Washington, NC, achieving a Nash-Sutcliffe Efficiency (NSE) of 0.61. Our findings show that SLR substantially alters nitrate delivery to the estuary, with increased nitrate loads observed in all seasons. Higher load increases were noted in winter and spring due to elevated flows, while higher percentage increases occurred in summer and fall, attributed to reduced plant uptake and disrupted nitrogen cycle transformations. Overall, we observed an increase in mean annual nitrate loads from 155,000 kg NO-N under baseline conditions to 157,000 kg NO-N under SLR scenarios, confirmed by a statistically significant paired t-test (p = 2.16 × 10). This pioneering framework sets the stage for more sophisticated and accurate modeling of SLR impacts in diverse hydrological scenarios, offering a vital tool for hydrological modelers.
本研究通过展示如何使用SWAT+模型评估海平面上升(SLR)对沿海流域农业硝酸盐输出的影响,满足了理解气候变化对沿海生态系统影响的迫切需求。我们将SLR纳入SWAT+模型的框架包括:(1)根据本世纪中叶的SLR预测,将海拔低于0.3米区域的当前土地利用重新分类为水域;(2)为海拔低于2.4米的区域创建受SLR影响的新土地利用、受SLR影响的作物数据库和水文响应单元;(3)调整受SLR影响区域的SWAT+参数,以模拟盐水入侵对植物产量和反硝化等过程的影响。我们在美国北卡罗来纳州东部的一个沿海流域塔尔-帕姆利科河流域演示了这种方法。我们对北卡罗来纳州华盛顿市的月度硝酸盐负荷进行了模型校准,纳什-萨特克利夫效率(NSE)达到了0.61。我们的研究结果表明,SLR显著改变了向河口输送的硝酸盐,所有季节的硝酸盐负荷均有所增加。由于流量增加,冬季和春季的负荷增加幅度更大,而夏季和秋季的百分比增加幅度更高,这归因于植物吸收减少和氮循环转化中断。总体而言,我们观察到年均硝酸盐负荷从基线条件下的155,000千克NO-N增加到SLR情景下的157,000千克NO-N,经统计显著的配对t检验(p = 2.16×10)证实。这一开创性框架为在各种水文情景中更精细、准确地模拟SLR影响奠定了基础,为水文建模人员提供了一个重要工具。