poster - International Conference of Agricultural Engineering

y denitrification because of lower air temperature during winter. The NO 3 concentration of
the animal manure origin tended to be always higher in the upper stream, no. 2, than in the
mid stream, no. 9 (Fig. 3A). During flow from the upper stream to the mid stream,
denitrification and/or dilution might attribute to lower NO 3 concentration at no. 9 than that at no.
2.
At no. 9, the NO 3 concentration of the chemical fertilizer origin tended to higher than that of
the animal manure origin whereas at no. 2 that of either origin was similar. During summer,
the NO 3 concentration of the chemical fertilizer origin tended to be similar at no. 2 and 9.
This might be reflected by the fact that a large amount of chemical fertilizer was used from the
upper stream to the mid stream.
NO 3 -N concentration (mg/L)
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
(A)
Animal manure origin
No 2
No 9
NO 3 -N concentration (mg/L)
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
(B)
Chemical fertilizer origin
No 2
No 9
0.1
0.1
0
Dec-03 Jun-04 Dec-04 Jun-05 Dec-05 Jun-06 Dec-06
Measuring date
0
Dec-03 Jun-04 Dec-04 Jun-05 Dec-05 Jun-06 Dec-06
Measuring date
FIGURE 3: Temporal changes in estimated NO 3 concentrations at no. 2 and 9: (A) for
the animal manure origin with Eq. 7, and (B) for the chemical fertilizer origin with Eq. 6
4. Conclusions
The mixing model described by Eqs. 1-3 successfully estimated NO 3 concentration or δ 15 N
values of the main stream based on those values obtained at tributaries only when there was
no major denitrification. Discrepancies between modeled and measured values implied that
N of either the chemical fertilizer or the animal manure origin merged the main stream. We
examined to distinguish the origin of N using the mixing model. Because of large temporal
variations in NO 3 concentrations and δ 15 N values, it was quite difficult to specify the NO 3 of the
animal manure origin along the river.
To monitor NO 3 concentration originated by animal manure or chemical fertilizer, more
monitoring sites and more frequent sampling periods will be needed. It would be possible to
improve the accuracy of the mixing model with the information on the quantities of flow in
each sub-watershed.
Acknowledgments
This research was partly supported by the River Environment Management Foundation
(project #1211). We are grateful to Ms. A. Nakano, and Mr. M. Yoshida of Iwate Agricultural
Research Center for their technical assistance.