Nutrients loads in aquatic systems are dynamic and highly influenced by changing the land, soil, and atmospheric conditions. This study enhances water quality modeling by providing novel nitrate transport models using remotely-sensed geospatial data, allowing for dynamic predictions of nitrate loads in watersheds. One factor at a time, sensitivity analysis was employed in the classical nitrate transport model to incorporate the impacts of 1) nitrates in the soil moisture profiles 2) wet deposition of nitrates and 3) the synergistic effects of multiple atmospheric and soil effects on nitrate-nitrogen in catchments. The study found that the effects of soil moisture profiles were dominant than the wet deposition in the evaluation of nitrate-nitrogen in catchments. The addition of nitrates from soil moisture profile, wet deposition and both together effectively increased the annual average nitrates in the Fish River catchment from 0.180 kg/ha to 0.187 kg/ha, 0.396 kg/ha and 0.381 kg/ha respectively. Their additions consistently increased the nitrate loads from spring to winter seasons but exhibited different seasonal trends for soils such as silty sand and fine sand. The models developed in this study can be utilized in water quality assessment tools for effective dynamic predictions of nutrients loads into water bodies.

中文翻译：

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利用遥感的土壤水分剖面和湿沉降地理空间数据开发硝态氮运移模型。

水生系统中的养分负荷是动态的，并且受到土地，土壤和大气条件变化的强烈影响。这项研究通过使用遥感的地理空间数据提供新颖的硝酸盐迁移模型来增强水质建模，从而可以动态预测流域中的硝酸盐负荷。一次一个因素是，在经典的硝酸盐迁移模型中采用了敏感性分析，以综合考虑以下因素的影响：1）土壤水分剖面中的硝酸盐2）硝酸盐的湿沉降，以及3）多种大气和土壤对硝酸盐的协同作用-流域中的氮。研究发现，在评价集水区硝酸盐-氮的过程中，土壤水分剖面的影响比湿沉降的影响更大。从土壤水分剖面中添加硝酸盐，湿沉降和二者共同有效地使鱼河流域的年平均硝酸盐从0.180千克/公顷增加到0.187千克/公顷，0.396千克/公顷和0.381千克/公顷。从春季到冬季，它们的添加持续增加了硝酸盐的负荷，但是对于粉质沙和细沙等土壤，它们表现出不同的季节性趋势。这项研究中开发的模型可以用于水质评估工具中，以有效地动态预测水体中营养物的负荷。