Kim JungJin, Her Younggu, Bhattarai Rabin, Jeong Hanseok
Institute of Environmental Technology, Seoul National University of Science and Technology, Seoul, Republic of Korea.
Department of Agricultural and Biological Engineering/Tropical Research and Education Center, Institute of Food and Agricultural Sciences, University of Florida, Homestead, FL, United States.
Sci Total Environ. 2023 Dec 15;904:166331. doi: 10.1016/j.scitotenv.2023.166331. Epub 2023 Aug 16.
Subsurface drainage systems are effective management practices employed to remove excess soil water, thereby improving soil aeration and crop productivity. However, these systems can also contribute to water quality issues by enhancing nitrate leaching and loads from agricultural fields. The Soil and Water Assessment Tool (SWAT) is commonly used to assess nitrate loads and long-term water quality impacts from agricultural watersheds. However, the current SWAT model oversimplifies nitrate transport processes by assuming a linear relationship between nitrate concentrations in tile flow and soil nitrate content. It also neglects the time lag between nitrate loading and transport with the flow. This study aimed to enhance the accuracy of nitrate load prediction by revising the subsurface drainage routine in the SWAT model. The revised routine was tested using flow and nitrate load measurements from a typical tile-drained watershed in east-central Illinois, U.S. The results demonstrated that the revised SWAT nitrate routine outperformed the current one in simulating nitrate transport at field and watershed scales. The revised routine improved the nitrate load prediction from an "unacceptable" to a "satisfactory" or "good" rating on the field scale. A sensitivity analysis conducted using the revised nitrate module showed the parameters directly associated with transpiration, groundwater discharge to the reach, the lag time of tile flow, and channel flow hydraulics were the most sensitive in nitrate load simulation. In addition, different tile depth scenarios were modeled to evaluate variation in the amount of surface runoff, tile flow, and nitrate loads by the surface flow and tile flow. The results of tile configuration scenarios agreed with understanding the tile flow process. The test results demonstrated the potential of the revised SWAT nitrate module as a tool to accurately evaluate the effects of tile drainage systems on water quality.
地下排水系统是用于排除土壤中多余水分的有效管理措施，从而改善土壤通气性并提高作物产量。然而，这些系统也可能因加剧农田硝酸盐淋失和负荷而导致水质问题。土壤和水资源评估工具（SWAT）通常用于评估农业流域的硝酸盐负荷和长期水质影响。然而，当前的SWAT模型通过假设瓦管流中的硝酸盐浓度与土壤硝酸盐含量之间存在线性关系，过度简化了硝酸盐运移过程。它还忽略了硝酸盐负荷与水流运移之间的时间滞后。本研究旨在通过修订SWAT模型中的地下排水程序来提高硝酸盐负荷预测的准确性。使用美国伊利诺伊州中东部一个典型的瓦管排水流域的流量和硝酸盐负荷测量数据对修订后的程序进行了测试。结果表明，修订后的SWAT硝酸盐程序在模拟田间和流域尺度的硝酸盐运移方面优于当前程序。修订后的程序在田间尺度上把硝酸盐负荷预测从“不可接受”提升到了“满意”或“良好”等级。使用修订后的硝酸盐模块进行的敏感性分析表明，与蒸腾作用、到达河段的地下水排放、瓦管流的滞后时间以及河道流水力学直接相关的参数在硝酸盐负荷模拟中最为敏感。此外，还对不同的瓦管深度情景进行了建模，以评估地表径流、瓦管流以及地表径流和瓦管流造成的硝酸盐负荷量的变化。瓦管配置情景的结果与对瓦管流过程的理解一致。测试结果证明了修订后的SWAT硝酸盐模块作为准确评估瓦管排水系统对水质影响的工具的潜力。
