Excess nitrogen entering rivers, lakes, and groundwater is a major environmental challenge worldwide. Fertilizers, livestock waste, domestic sewage, atmospheric deposition, and other diffuse sources can all contribute to nitrogen pollution, yet determining exactly where the nitrogen comes from and how it moves through a watershed remains difficult.
A new review published in Nitrogen Cycling provides a comprehensive framework for understanding how scientists identify and quantify these sources. The researchers classify existing watershed nitrogen source apportionment approaches into four major categories: qualitative methods, quantitative methods, spatiotemporally refined approaches, and intelligent technologies. They also outline a roadmap toward integrated systems that combine remote sensing, unmanned aerial vehicles, sensors, process models, and artificial intelligence.
"Effective nitrogen pollution control begins with knowing where the pollution originates, how much each source contributes, and how those contributions change across space and time," said corresponding author Yongqiu Xia. "The next generation of source apportionment should move beyond isolated measurements toward integrated, intelligent systems that can support practical watershed management."
The review shows how nitrogen source tracking has progressed over several decades. Earlier approaches relied largely on chemical tracers and microbial indicators, which can help distinguish pollution sources such as sewage, livestock waste, and fertilizer runoff. Stable isotopes of nitrate later provided more powerful tools for identifying sources, while statistical and Bayesian models made it possible to estimate their relative contributions.
However, each approach has limitations. Chemical tracers can be altered by rainfall, hydrological conditions, and biogeochemical reactions. Microbial indicators are sensitive to temperature and other environmental factors. Isotopic signatures may overlap among sources, while statistical models may provide limited information about where pollution originates or how it travels through a watershed.
To address these gaps, researchers increasingly use process-based models such as SWAT and HSPF to simulate nitrogen generation, transport, and transformation. These models can identify critical source areas and reveal how nitrogen moves through surface runoff, subsurface flow, and groundwater over timescales ranging from days to decades.
The review highlights an emerging transition toward intelligent nitrogen source apportionment. Satellite remote sensing can provide large-scale observations, UAVs can capture detailed local information, and in situ sensors can continuously monitor water quality. When these technologies are combined with machine learning and process-based modeling, researchers can obtain higher-resolution and more timely information than is possible through conventional field sampling alone.
Looking ahead, the authors propose three major priorities. First, researchers should build integrated space-air-ground monitoring systems that combine satellite, UAV, and sensor data. Second, statistical models, isotope tracing, and process-based models should be more closely coupled to improve understanding of nitrogen transport under complex conditions and extreme weather events. Third, decision-support platforms should incorporate artificial intelligence and large language models to make sophisticated analyses more accessible to watershed managers.
Such systems could eventually move nitrogen management from periodic diagnosis toward continuous monitoring, early warning, scenario simulation, and targeted intervention.
"Connecting source identification directly with management decisions is the key goal," Xia said. "By integrating monitoring, modeling, and intelligent analysis, we can provide more precise information about where mitigation efforts are most urgently needed."
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Journal Reference: Yan X, Hu W, Xia Y. 2026. Watershed non-point source nitrogen apportionment: from qualitative to intelligence frameworks. Nitrogen Cycling 2: e025 doi: 10.48130/nc-0026-0012
https://www.maxapress.com/article/doi/10.48130/nc-0026-0012
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About Nitrogen Cycling :
Nitrogen Cycling (e-ISSN 3069-8111) is a multidisciplinary platform for communicating advances in fundamental and applied research on the nitrogen cycle. It is dedicated to serving as an innovative, efficient, and professional platform for researchers in the field of nitrogen cycling worldwide to deliver findings from this rapidly expanding field of science.
