US EPA

6710228 

Journal Article 

Modelling inter- and intra-annual variation of riverine nitrogen/nitrate losses from snowmelt-affected basins under agricultural and mixed land use captured with high-frequency monitoring 

Kamari, M; Huttunen, I; Valkama, P; Huttunen, Qiang; Korppoo, TQi; Tattari, Kun; Lotsari, E 

2019 

Yes 

Catena
ISSN: 0341-8162
EISSN: 1872-6887 

176 

227-244 

10.1016/j.catena.2019.01.019 

WOS:000462107000019 

We applied a process-based nutrient loading model (VEMALA v.3) into two cold region watersheds and evaluated the simulations against daily observations of nitrate-nitrogen (NO3-N) concentrations and fluxes over a five-year period. The high-frequency NO3 center dot N and water level data revealed fine temporal changes of NO3 center dot N losses from agricultural and mixed land-use catchments and enabled the detection of processes to be further developed in the model. The NO3-N loads were simulated satisfactorily in the agricultural headwater catchment, as the percent bias (PBIAS) was annually within +/- 27%.The results showed that the annual NO3-N loads were better simulated (PBIAS <= +/- 16%) at the larger scale catchment despite the input data for the model being less detailed. Intra-annually, the simulated NO3-N concentrations and loads during snowmelt and autumn were mainly underestimated in both sites. By contrast, the summer baseflow concentrations and fluxes were overestimated by the model. The seasonal biases in the simulation of snowmelt, excess nitrogen flushing events, autumn rain related fluxes and baseflow periods partly compensate each other at the annual scale. Thus, the net result for a 5-year simulation was that simulated NO3-N loads were only - 11% lower than observed. The results suggest that processes influencing autumnal and snowmelt-initiated NO3 center dot N flushing as well as the summertime in-stream mineral nitrogen uptake are potential key issues to be developed in the future. In addition, we highlight temporal similarities and differences in the observed NO3-N losses from the agricultural and mixed land-use catchments. 

Diffuse source; Point source; In-situ monitoring; Solute transport; Clay soil; Process-based modelling